paulo037/starcoder · Datasets at Hugging Face

max_stars_repo_path stringlengths 4 237	max_stars_repo_name stringlengths 6 117	max_stars_count int64 0 95.2k	id stringlengths 1 7	content stringlengths 12 593k	input_ids sequencelengths 7 549k
trainer/train_debug.py	naivelogic/dotatron	0	1610322	<reponame>naivelogic/dotatron #!/usr/bin/python import os import torch import warnings warnings.filterwarnings("ignore", category=FutureWarning) from detectron2.config import * from detectron2 import model_zoo from detectron2.data import DatasetCatalog, MetadataCatalog from detectron2.engine import launch from rotated_trainer import RotatedTrainer from dota2kit_data_tools import dotatron_loader from detectron2.engine import default_setup import logging logger = logging.getLogger("detectron2") torch.cuda.set_device(0) # multi from cfg_lib import base_dota_cfg from dota_project import DOTA2CLASSES def main(args): #DATA_FOLDER = "/mnt/omreast_users/phhale/open_ds/DOTA_aerial_images/" OUTPUT_PATHS="/home/redne/LUIA_challenge_dev/tron_dota/prod_v2/output/x3/x1" TRAIN_PATH = '/home/redne/LUIA_challenge_dev/repos/DOTA_devkit_YOLO/examplesplit' DatasetCatalog.clear() MetadataCatalog.clear() DatasetCatalog.register("Train", lambda: dotatron_loader(dataset_dir=TRAIN_PATH, load_dataset=False, classlist=DOTA2CLASSES, dataset_load_name='train_dota2kit_prodv2')) MetadataCatalog.get("Train").set(thing_classes=DOTA2CLASSES) cfg = base_dota_cfg() cfg.DATASETS.TRAIN = (["Train"]) cfg.DATASETS.TEST = () cfg.MODEL.ROI_HEADS.NUM_CLASSES = len(DOTA2CLASSES) cfg.VIS_PERIOD = 10 #50 cfg.OUTPUT_DIR= OUTPUT_PATHS os.makedirs(cfg.OUTPUT_DIR, exist_ok=True) #lets just check our output dir exists cfg.freeze() # make the configuration unchangeable during the training process default_setup(cfg, args) cfg.dump() trainer = RotatedTrainer(cfg) #trainer.resume_or_load(resume=True) trainer.resume_or_load(resume=False) return trainer.train() if __name__ == '__main__': torch.cuda.empty_cache() from custom_arg_parsers import custom_default_argument_parser args = custom_default_argument_parser().parse_args() print("Command Line Args:", args) torch.backends.cudnn.benchmark = True launch( main, args.num_gpus, num_machines=args.num_machines, 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pyskyqremote/classes/device.py	RogerSelwyn/pyskyqremote	0	119010	"""Methods for retrieving device information.""" import json import logging from dataclasses import dataclass, field from ..const import (CURRENT_SPEED, CURRENT_TRANSPORT_STATE, CURRENT_TRANSPORT_STATUS, DEFAULT_TRANSPORT_SPEED, DEFAULT_TRANSPORT_STATE, KNOWN_COUNTRIES, REST_PATH_DEVICEINFO, REST_PATH_SYSTEMINFO, SKY_STATE_NOMEDIA, SKY_STATE_OFF, SKY_STATE_PAUSED, SKY_STATE_PLAYING, SKY_STATE_STANDBY, SKY_STATE_STOPPED, SKY_STATE_TRANSITIONING, SKY_STATE_UNSUPPORTED, UPNP_GET_TRANSPORT_INFO) _LOGGER = logging.getLogger(__name__) class DeviceInformation: """Sky Q device information retrieval methods.""" def __init__(self, remote_config): """Initialise the device information class.""" self._remote_config = remote_config self._device_access = remote_config.device_access self._port = remote_config.port def get_transport_information(self): """Get the transport information from the SkyQ box.""" response = self._device_access.call_sky_soap_service(UPNP_GET_TRANSPORT_INFO) if response is not None: return TransportInfo( response[CURRENT_TRANSPORT_STATE], response[CURRENT_TRANSPORT_STATUS], response[CURRENT_SPEED], ) return TransportInfo( SKY_STATE_OFF, DEFAULT_TRANSPORT_STATE, DEFAULT_TRANSPORT_SPEED ) def get_system_information(self): """Get the system information from the SkyQ box.""" return self._device_access.retrieve_information(REST_PATH_SYSTEMINFO) def get_device_information(self, override_country): """Get the device information from the SkyQ box.""" device_info = self._device_access.retrieve_information(REST_PATH_DEVICEINFO) if not device_info: return None system_info = self.get_system_information() as_version = device_info["ASVersion"] ip_address = device_info["IPAddress"] country_code = device_info["countryCode"] gateway = device_info["gateway"] hardware_model = system_info["hardwareModel"] device_type = system_info["deviceType"] hardware_name = device_info["hardwareName"] manufacturer = system_info["manufacturer"] model_number = device_info["modelNumber"] serial_number = device_info["serialNumber"] version_number = device_info["versionNumber"] bouquet = device_info["bouquet"] subbouquet = device_info["subbouquet"] wake_reason = system_info["wakeReason"] system_uptime = system_info["systemUptime"] hdr_capable = system_info["hdrCapable"] uhd_capable = system_info["uhdCapable"] used_country_code = override_country or country_code.upper() if not used_country_code: _LOGGER.error("E0010 - No country identified: %s", self._remote_config.host) return None if used_country_code in KNOWN_COUNTRIES: used_country_code = KNOWN_COUNTRIES[used_country_code] return Device( as_version, ip_address, country_code, used_country_code, hardware_model, hardware_name, device_type, gateway, manufacturer, model_number, serial_number, version_number, bouquet, subbouquet, wake_reason, system_uptime, hdr_capable, uhd_capable, ) @dataclass class Device: """SkyQ Device Class.""" ASVersion: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) IPAddress: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) countryCode: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) used_country_code: str = field( init=True, repr=True, compare=False, ) hardwareModel: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) hardwareName: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) deviceType: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) gateway: str = field( init=True, repr=True, compare=False, ) manufacturer: str = field( init=True, repr=True, compare=False, ) modelNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) serialNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) versionNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) bouquet: str = field( init=True, repr=True, compare=False, ) subbouquet: str = field( init=True, repr=True, compare=False, ) wakeReason: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) systemUptime: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) hdrCapable: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) uhdCapable: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) def as_json(self) -> str: """Return a JSON string representing this device info.""" return json.dumps(self, cls=_DeviceJSONEncoder) def device_decoder(obj): """Decode programme object from json.""" device = json.loads(obj) if "__type__" in device and device["__type__"] == "__device__": return Device(device["attributes"]) return device class _DeviceJSONEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, Device): attributes = dict(vars(o)) return { "__type__": "__device__", "attributes": attributes, } @dataclass class TransportInfo: """SkyQ TransportInfo Class.""" CurrentTransportState: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) CurrentTransportStatus: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) CurrentSpeed: float = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) state: str = None def __post_init__(self): """Post process the transport setup.""" self.state = self.CurrentTransportState if self.CurrentTransportState in [SKY_STATE_NOMEDIA, SKY_STATE_STOPPED]: self.state = SKY_STATE_STANDBY if self.CurrentTransportState in [SKY_STATE_PLAYING, SKY_STATE_TRANSITIONING]: self.state = SKY_STATE_PLAYING if self.CurrentTransportState == SKY_STATE_PAUSED: self.state = SKY_STATE_PAUSED if self.CurrentTransportState == SKY_STATE_UNSUPPORTED: self.CurrentTransportState = None def as_json(self) -> str: """Return a JSON string representing this app info.""" return json.dumps(self, cls=_TransportInfoJSONEncoder) def transportinfo_decoder(obj): """Decode 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school/migrations/0001_initial.py	muzamilqadir786/smartchild	0	1605010	<reponame>muzamilqadir786/smartchild # -- coding: utf-8 -- # Generated by Django 1.10.4 on 2016-12-13 07:18 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Fee', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fee_paid', models.DecimalField(decimal_places=2, default=0, max_digits=6)), ('date_of_payment', models.DateField(auto_now_add=True)), ], ), migrations.CreateModel( name='FeeCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fee_category', models.CharField(blank=True, choices=[('M', 'Monthly_Fee'), ('A', 'Admission_Fee')], default='M', max_length=30, null=True)), ('amount', models.DecimalField(decimal_places=2, max_digits=6)), ('description', models.TextField()), ], options={ 'ordering': ('id',), 'verbose_name': 'Fee Categories', }, ), migrations.CreateModel( name='Level', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('level', models.CharField(choices=[('Playgroup', 'Playgroup'), ('Nursery', 'Nursery'), ('PREP', 'PREP'), ('1st Grade', '1st Grade'), ('2nd Grade', '2nd Grade'), ('3rd Grade', '3rd Grade'), ('4th Grade', '4th Grade')], max_length=30)), ], ), migrations.CreateModel( name='Student', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(blank=True, max_length=30, null=True)), ('last_name', models.CharField(blank=True, max_length=30, null=True)), ('father_name', models.CharField(blank=True, max_length=30, null=True)), ('mother_name', models.CharField(blank=True, max_length=30, null=True)), ('gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], default='M', max_length=1)), ('mobile_code', models.CharField(choices=[(b'0300', b'0300'), (b'0301', b'0301'), (b'0302', b'0302'), (b'0303', b'0303'), (b'0304', b'0304'), (b'0305', b'0305'), (b'0306', b'0306'), (b'0307', b'0307'), (b'0308', b'0308'), (b'0309', b'0309'), (b'0310', b'0310'), (b'0311', b'0311'), (b'0312', b'0312'), (b'0313', b'0313'), (b'0314', b'0314'), (b'0315', b'0315'), (b'0320', b'0320'), (b'0321', b'0321'), (b'0322', b'0322'), (b'0323', b'0323'), (b'0324', b'0324'), (b'0331', b'0331'), (b'0332', b'0332'), (b'0333', b'0333'), (b'0334', b'0334'), (b'0335', b'0335'), (b'0336', b'0336'), (b'0337', b'0337'), (b'0340', b'0340'), (b'0341', b'0341'), (b'0342', b'0342'), (b'0343', b'0343'), (b'0344', b'0344'), (b'0345', b'0345'), (b'0346', b'0346'), (b'0347', b'0347'), (b'0348', b'0348'), (b'0349', b'0349')], default='0300', max_length=4)), ('seven_digit_phone', models.CharField(blank=True, max_length=7, null=True)), 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archieve/2020/day3b.py	jabra98/aoc	0	107429	<reponame>jabra98/aoc<gh_stars>0 def main(): grid = open("data.txt").readlines() for i in range(0, len(grid)): grid[i] = grid[i][:-1] x_width = len(grid[i]) y_length = len(grid) ctr = 0 y_pos = 0 x_pos = 0 product = 1 for i in [[1,1], [3,1], [5,1], [7,1], [1,2]]: while y_pos < y_length: if grid[y_pos][x_pos % x_width] == '#': ctr += 1 x_pos += i[0] y_pos += i[1] print(ctr) product *= ctr x_pos=0 y_pos=0 ctr=0 print(product) main()	[ 1, 529, 276, 1112, 420, 29958, 29926, 370, 336, 29929, 29947, 29914, 29874, 542, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 1753, 1667, 7295, 13, 1678, 6856, 353, 1722, 703, 1272, 29889, 3945, 2564, 949, 9012, 580, 13, 13, 1678, 363, 474, 297, 3464, 29898, 29900, 29892, 7431, 29898, 7720, 22164, 13, 4706, 6856, 29961, 29875, 29962, 353, 6856, 29961, 29875, 3816, 13018, 29896, 29962, 13, 13, 1678, 921, 29918, 2103, 353, 7431, 29898, 7720, 29961, 29875, 2314, 13, 1678, 343, 29918, 2848, 353, 7431, 29898, 7720, 29897, 13, 13, 1678, 274, 509, 353, 29871, 29900, 13, 1678, 343, 29918, 1066, 353, 29871, 29900, 13, 1678, 921, 29918, 1066, 353, 29871, 29900, 13, 1678, 3234, 353, 29871, 29896, 13, 13, 1678, 363, 474, 297, 5519, 29896, 29892, 29896, 1402, 518, 29941, 29892, 29896, 1402, 518, 29945, 29892, 29896, 1402, 518, 29955, 29892, 29896, 1402, 518, 29896, 29892, 29906, 5262, 29901, 13, 4706, 1550, 343, 29918, 1066, 529, 343, 29918, 2848, 29901, 13, 9651, 565, 6856, 29961, 29891, 29918, 1066, 3816, 29916, 29918, 1066, 1273, 921, 29918, 2103, 29962, 1275, 16321, 2396, 13, 18884, 274, 509, 4619, 29871, 29896, 13, 13, 9651, 921, 29918, 1066, 4619, 474, 29961, 29900, 29962, 13, 9651, 343, 29918, 1066, 4619, 474, 29961, 29896, 29962, 13, 13, 4706, 1596, 29898, 9988, 29897, 13, 4706, 3234, 334, 29922, 274, 509, 13, 308, 13, 4706, 921, 29918, 1066, 29922, 29900, 13, 4706, 343, 29918, 1066, 29922, 29900, 13, 4706, 274, 509, 29922, 29900, 13, 13, 1678, 1596, 29898, 4704, 29897, 13, 13, 3396, 580, 13, 2 ]
daisy/convenience.py	rhoadesScholar/daisy	0	1612953	from .cl_monitor import CLMonitor from .server import Server from .tcp import IOLooper from multiprocessing.pool import ThreadPool from multiprocessing import Event def run_blockwise(tasks): '''Schedule and run the given tasks. Args: list_of_tasks: The tasks to schedule over. Return: bool: `True` if all blocks in the given `tasks` were successfully run, else `False` ''' stop_event = Event() IOLooper.clear() pool = ThreadPool(processes=1) result = pool.apply_async(_run_blockwise, args=(tasks, stop_event)) try: return result.get() except KeyboardInterrupt: stop_event.set() return result.get() def _run_blockwise(tasks, stop_event): server = Server(stop_event=stop_event) cl_monitor = CLMonitor(server) # noqa return server.run_blockwise(tasks)	[ 1, 515, 869, 695, 29918, 3712, 2105, 1053, 17332, 7185, 2105, 13, 3166, 869, 2974, 1053, 5656, 13, 3166, 869, 23981, 1053, 10663, 3410, 3372, 13, 3166, 6674, 307, 985, 292, 29889, 10109, 1053, 10480, 11426, 13, 3166, 6674, 307, 985, 292, 1053, 6864, 13, 13, 13, 1753, 1065, 29918, 1271, 3538, 29898, 20673, 1125, 13, 1678, 14550, 4504, 11272, 322, 1065, 278, 2183, 9595, 29889, 13, 13, 4706, 826, 3174, 29901, 13, 9651, 1051, 29918, 974, 29918, 20673, 29901, 13, 18884, 450, 9595, 304, 20410, 975, 29889, 13, 13, 4706, 7106, 29901, 13, 9651, 6120, 29901, 13, 18884, 421, 5574, 29952, 565, 599, 10930, 297, 278, 2183, 421, 20673, 29952, 892, 8472, 13, 18884, 1065, 29892, 1683, 421, 8824, 29952, 13, 1678, 14550, 13, 13, 1678, 5040, 29918, 3696, 353, 6864, 580, 13, 13, 1678, 10663, 3410, 3372, 29889, 8551, 580, 13, 1678, 11565, 353, 10480, 11426, 29898, 5014, 267, 29922, 29896, 29897, 13, 1678, 1121, 353, 11565, 29889, 7302, 29918, 12674, 7373, 3389, 29918, 1271, 3538, 29892, 6389, 7607, 20673, 29892, 5040, 29918, 3696, 876, 13, 1678, 1018, 29901, 13, 4706, 736, 1121, 29889, 657, 580, 13, 1678, 5174, 7670, 3377, 4074, 6685, 29901, 13, 4706, 5040, 29918, 3696, 29889, 842, 580, 13, 4706, 736, 1121, 29889, 657, 580, 13, 13, 13, 1753, 903, 3389, 29918, 1271, 3538, 29898, 20673, 29892, 5040, 29918, 3696, 1125, 13, 1678, 1923, 353, 5656, 29898, 9847, 29918, 3696, 29922, 9847, 29918, 3696, 29897, 13, 1678, 1067, 29918, 3712, 2105, 353, 17332, 7185, 2105, 29898, 2974, 29897, 29871, 396, 694, 25621, 13, 1678, 736, 1923, 29889, 3389, 29918, 1271, 3538, 29898, 20673, 29897, 13, 2 ]
Tools/decrypt_ulog.py	lgarciaos/Firmware	4,224	33612	#!/usr/bin/env python3 from Crypto.PublicKey import RSA from Crypto.Cipher import PKCS1_OAEP from Crypto.Cipher import ChaCha20 from Crypto.Hash import SHA256 import binascii import argparse #from pathlib import Path import sys if __name__ == "__main__": parser = argparse.ArgumentParser(description="""CLI tool to decrypt an ulog file\n""") parser.add_argument("ulog_file", help=".ulog file", nargs='?', default=None) parser.add_argument("ulog_key", help=".ulogk, encrypted key", nargs='?', default=None) parser.add_argument("rsa_key", help=".pem format key for decrypting the ulog key", nargs='?', default=None) args = parser.parse_args() # Only generate a key pair, don't sign if not args.ulog_file or not args.ulog_key or not args.rsa_key: print('Need all arguments, the encrypted ulog file, the key and the key decryption key') sys.exit(1); # Read the private RSA key to decrypt the cahcha key with open(args.rsa_key, 'rb') as f: r = RSA.importKey(f.read(), passphrase='') # Read the encrypted xchacha key and the nonce with open(args.ulog_key, 'rb') as f: ulog_key_header = f.read(22) # Parse the header try: # magic if not ulog_key_header.startswith(bytearray("ULogKey".encode())): raise Exception() # version if ulog_key_header[7] != 1: raise Exception() # expected key exchange algorithm (RSA_OAEP) if ulog_key_header[16] != 4: raise Exception() key_size = ulog_key_header[19] << 8 \| ulog_key_header[18]; nonce_size = ulog_key_header[21] << 8 \| ulog_key_header[20]; ulog_key_cipher = f.read(key_size) nonce = f.read(nonce_size) except: print("Keyfile format error") sys.exit(1); # Decrypt the xchacha key cipher_rsa = PKCS1_OAEP.new(r,SHA256) ulog_key = cipher_rsa.decrypt(ulog_key_cipher) #print(binascii.hexlify(ulog_key)) # Read and decrypt the .ulgc cipher = ChaCha20.new(key=ulog_key, nonce=nonce) with open(args.ulog_file, 'rb') as f: with open(args.ulog_file.rstrip(args.ulog_file[-1]), 'wb') as out: 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packages/core/minos-microservice-common/minos/common/protocol/avro/base.py	minos-framework/minos-python	247	162959	<gh_stars>100-1000 import io from typing import ( Any, Union, ) from fastavro import ( parse_schema, reader, writer, ) from ...exceptions import ( MinosProtocolException, ) from ..abc import ( MinosBinaryProtocol, ) class MinosAvroProtocol(MinosBinaryProtocol): """Minos Avro Protocol class.""" @classmethod def encode(cls, value: Any, schema: Any, args, batch_mode: bool = False, kwargs) -> bytes: """Encoder in avro for database Values all the headers are converted in fields with double underscore name the body is a set fields coming from the data type. :param value: The data to be stored. :param schema: The schema relative to the data. :param args: Additional positional arguments. :param batch_mode: If ``True`` the data is processed as a list of models, otherwise the data is processed as a single model. :param kwargs: Additional named arguments. :return: A bytes object. """ if not batch_mode: value = [value] if not isinstance(schema, list): schema = [schema] try: raw_schema = cls._parse_schema(schema) return cls._write_data(value, raw_schema) except Exception as exc: raise MinosProtocolException(f"Error encoding data: {exc!r}") @staticmethod def _parse_schema(schema: list[dict[str, Any]]) -> dict[str, Any]: named_schemas = {} for item in schema[1::-1]: parse_schema(item, named_schemas) return parse_schema(schema[0], named_schemas, expand=True) @staticmethod def _write_data(value: list[dict[str, Any]], schema: dict[str, Any]): with io.BytesIO() as file: writer(file, schema, value) file.seek(0) content = file.getvalue() return content @classmethod def decode(cls, data: bytes, args, batch_mode: bool = False, *kwargs) -> Any: """Decode the given bytes of data into a single dictionary or a sequence of dictionaries. :param data: A bytes object. :param args: Additional positional arguments. :param batch_mode: If ``True`` the data is processed as a list of models, otherwise the data is processed as a single model. :param kwargs: Additional named arguments. :return: A dictionary or a list of dictionaries. """ try: with io.BytesIO(data) as file: ans = list(reader(file)) except Exception as exc: raise MinosProtocolException(f"Error decoding the avro bytes: {exc}") if not batch_mode: if len(ans) > 1: raise MinosProtocolException( f"The 'batch_mode' argument was set to {False!r} but data contains multiple values: {ans!r}" ) ans = ans[0] return ans # noinspection PyUnusedLocal @classmethod def decode_schema(cls, data: bytes, args, **kwargs) -> Union[dict[str, Any], list[dict[str, Any]]]: """Decode the given bytes of data into a single dictionary or a sequence of dictionaries. :param data: A bytes object. :param args: Additional positional arguments. :param kwargs: Additional named arguments. :return: A tuple or a list of tuples. """ try: with io.BytesIO(data) as file: r = reader(file) schema = r.writer_schema except Exception as exc: raise MinosProtocolException(f"Error getting avro schema: {exc}") return schema	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29900, 29899, 29896, 29900, 29900, 29900, 13, 5215, 12013, 13, 3166, 19229, 1053, 313, 13, 1678, 3139, 29892, 13, 1678, 7761, 29892, 13, 29897, 13, 13, 3166, 5172, 485, 307, 1053, 313, 13, 1678, 6088, 29918, 11010, 29892, 13, 1678, 9591, 29892, 13, 1678, 9227, 29892, 13, 29897, 13, 13, 3166, 2023, 11739, 29879, 1053, 313, 13, 1678, 3080, 359, 17830, 2451, 29892, 13, 29897, 13, 3166, 6317, 10736, 1053, 313, 13, 1678, 3080, 359, 25196, 17830, 29892, 13, 29897, 13, 13, 13, 1990, 3080, 359, 12810, 307, 17830, 29898, 8140, 359, 25196, 17830, 1125, 13, 1678, 9995, 8140, 359, 7740, 307, 1019, 5770, 770, 1213, 15945, 13, 13, 1678, 732, 1990, 5696, 13, 1678, 822, 19750, 29898, 25932, 29892, 995, 29901, 3139, 29892, 10938, 29901, 3139, 29892, 334, 5085, 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src/LASER/utils/__init__.py	BigBird01/LASER	7	93894	from .logger_util import * from .argument_types import *	[ 1, 515, 869, 21707, 29918, 4422, 1053, 334, 13, 3166, 869, 23516, 29918, 8768, 1053, 334, 13, 2 ]
rain_atten/powerlaw.py	bzohidov/TomoRain	0	156301	#------------------------------------------------------------------------------- # Name: powerlaw.py # Purpose: This is a set of power law coefficients(a,b) for the calculation of # empirical rain attenuation model A = a*R^b. #------------------------------------------------------------------------------- def get_coef_ab(freq, mod_type = 'MP'): ''' Returns power law coefficients according to model type (mod_type) at a given frequency[Hz]. Input: freq - frequency, [Hz]. Optional: mod_type - model type for power law. This can be 'ITU_R2005', 'MP','GAMMA'. By default, mode_type = 'ITU_R2005'. Output: a,b - power law coefficients. ''' if mod_type == 'ITU_R2005': a = {'18': 0.07393, '23': 0.1285, '38': 0.39225} b = {'18':1.0404605978, '23': 0.99222272,'38':0.8686641682} elif mod_type == 'MP': a = {'18': 0.05911087, '23': 0.1080751, '38': 0.37898495} b = {'18': 1.08693514, '23': 1.05342886, '38': 0.92876888} elif mod_type=='GAMMA': a = {'18': 0.04570854, '23': 0.08174184, '38': 0.28520923} b = {'18': 1.09211488, '23': 1.08105214, '38': 1.01426258} freq = int(freq/1e9) return a[str(freq)], b[str(freq)]	[ 1, 396, 2683, 2683, 2683, 2683, 9072, 5634, 13, 29937, 4408, 29901, 3081, 10653, 29889, 2272, 13, 29937, 15247, 4220, 29901, 910, 338, 263, 731, 310, 3081, 4307, 16127, 29898, 29874, 29892, 29890, 29897, 363, 278, 13944, 310, 13, 29937, 3986, 29190, 936, 17251, 472, 841, 29884, 362, 1904, 319, 353, 263, 29930, 29934, 29985, 29890, 29889, 13, 29937, 2683, 2683, 2683, 2683, 9072, 5634, 13, 13, 13, 13, 13, 1753, 679, 29918, 1111, 1389, 29918, 370, 29898, 29888, 7971, 29892, 878, 29918, 1853, 353, 525, 3580, 29374, 13, 1678, 14550, 13, 1678, 16969, 3081, 4307, 16127, 5034, 304, 1904, 1134, 313, 1545, 29918, 1853, 29897, 13, 1678, 472, 263, 2183, 10868, 29961, 12661, 1822, 13, 1678, 10567, 29901, 13, 4706, 3005, 29939, 448, 10868, 29892, 518, 12661, 1822, 13, 1678, 28379, 29901, 13, 4706, 878, 29918, 1853, 448, 1904, 1134, 363, 3081, 4307, 29889, 910, 508, 367, 525, 1806, 29965, 29918, 29934, 29906, 29900, 29900, 29945, 742, 13, 462, 259, 525, 3580, 3788, 29954, 5194, 1529, 4286, 2648, 2322, 29892, 4464, 29918, 1853, 353, 525, 1806, 29965, 29918, 29934, 29906, 29900, 29900, 29945, 4286, 13, 1678, 10604, 29901, 13, 4706, 263, 29892, 29890, 448, 3081, 4307, 16127, 29889, 13, 1678, 14550, 13, 1678, 565, 878, 29918, 1853, 1275, 525, 1806, 29965, 29918, 29934, 29906, 29900, 29900, 29945, 2396, 13, 4706, 263, 353, 11117, 29896, 29947, 2396, 29871, 29900, 29889, 29900, 29955, 29941, 29929, 29941, 29892, 525, 29906, 29941, 2396, 29871, 29900, 29889, 29896, 29906, 29947, 29945, 29892, 525, 29941, 29947, 2396, 29871, 29900, 29889, 29941, 29929, 29906, 29906, 29945, 29913, 13, 4706, 289, 353, 11117, 29896, 29947, 2396, 29896, 29889, 29900, 29946, 29900, 29946, 29953, 29900, 29945, 29929, 29955, 29947, 29892, 525, 29906, 29941, 2396, 29871, 29900, 29889, 29929, 29929, 29906, 29906, 29906, 29906, 29955, 29906, 5501, 29941, 29947, 2396, 29900, 29889, 29947, 29953, 29947, 29953, 29953, 29946, 29896, 29953, 29947, 29906, 29913, 13, 1678, 25342, 878, 29918, 1853, 1275, 525, 3580, 2396, 13, 4706, 263, 353, 11117, 29896, 29947, 2396, 29871, 29900, 29889, 29900, 29945, 29929, 29896, 29896, 29900, 29947, 29955, 29892, 525, 29906, 29941, 2396, 29871, 29900, 29889, 29896, 29900, 29947, 29900, 29955, 29945, 29896, 29892, 525, 29941, 29947, 2396, 29871, 29900, 29889, 29941, 29955, 29947, 29929, 29947, 29946, 29929, 29945, 29913, 13, 4706, 289, 353, 11117, 29896, 29947, 2396, 29871, 29896, 29889, 29900, 29947, 29953, 29929, 29941, 29945, 29896, 29946, 29892, 525, 29906, 29941, 2396, 29871, 29896, 29889, 29900, 29945, 29941, 29946, 29906, 29947, 29947, 29953, 29892, 525, 29941, 29947, 2396, 29871, 29900, 29889, 29929, 29906, 29947, 29955, 29953, 29947, 29947, 29947, 29913, 13, 1678, 25342, 878, 29918, 1853, 1360, 29915, 29954, 5194, 1529, 2396, 13, 4706, 263, 353, 11117, 29896, 29947, 2396, 29871, 29900, 29889, 29900, 29946, 29945, 29955, 29900, 29947, 29945, 29946, 29892, 525, 29906, 29941, 2396, 29871, 29900, 29889, 29900, 29947, 29896, 29955, 29946, 29896, 29947, 29946, 29892, 525, 29941, 29947, 2396, 29871, 29900, 29889, 29906, 29947, 29945, 29906, 29900, 29929, 29906, 29941, 29913, 13, 4706, 289, 353, 11117, 29896, 29947, 2396, 29871, 29896, 29889, 29900, 29929, 29906, 29896, 29896, 29946, 29947, 29947, 29892, 525, 29906, 29941, 2396, 29871, 29896, 29889, 29900, 29947, 29896, 29900, 29945, 29906, 29896, 29946, 29892, 525, 29941, 29947, 2396, 29871, 29896, 29889, 29900, 29896, 29946, 29906, 29953, 29906, 29945, 29947, 29913, 13, 1678, 3005, 29939, 353, 938, 29898, 29888, 7971, 29914, 29896, 29872, 29929, 29897, 13, 1678, 736, 263, 29961, 710, 29898, 29888, 7971, 29897, 1402, 289, 29961, 710, 29898, 29888, 7971, 4638, 2 ]
curriculum/07_game_02_circle_clash_2_DAYS/07_game_02_circle_clash_day_1/07_02_02_circle_clash_advanced.py	google/teknowledge	31	52030	from tkinter import * # the game data for the initial game state def init(): data.playerX = 250 data.playerY = 550 data.circleX = 250 data.circleY = 0 data.gameOver = False # events updating the game data def keyPressed(event): if event.keysym == "Right" and data.playerX < 550: data.playerX += 5 elif event.keysym == "Left" and data.playerX > 0: data.playerX -= 5 def moveCircle(): if not data.gameOver: data.circleY += 10 # the game data updating the game state def timerFired(): moveCircle() if checkCollision(data.playerX, data.playerY, data.circleX, data.circleY, 10, 50): data.gameOver = True if data.circleY > 600: data.gameOver = True def checkCollision(x1, y1, x2, y2, r1, r2): distance = ((x2 - x1) 2 + (y2 - y1) 2) 0.5 return distance <= r1 + r2 # the game state updating what is drawn def redrawAll(canvas): canvas.create_oval(data.playerX - 10, data.playerY - 10, data.playerX + 10, data.playerY + 10, fill="red") canvas.create_oval(data.circleX - 50, data.circleY - 50, data.circleX + 50, data.circleY + 50, \ fill="yellow") if data.gameOver: canvas.create_text(300, 250, text="Game Over", font=" Arial 20") # Challenge 2.1 - Make it so that at the top of the screen it says "Score: __" # where the __ is a number that increases every time timerFired() happens. # Challenge 2.2 - Make it so that every third time timerFired() happens a new # circle is added to the top of the screen with random x position, color, # and size. # Suggested way to do this: # 1. Make a data.timer variable that starts at 0 and increases by 1 every # timerFired() and a data.circles variable that starts as []. # 2. When data.timer gets to 3, reset it to 0 and call a new function # createNewCircle(). # 3. Write createNewCircle() to append a tuple to data.circles of the # format: # (xCoordinate, yCoordinate, radiusSize, colorString) # 4. In redrawAll(), loop over the data.circles list and draw each circle. # 5. In timerFired(), every second, move each circle's yPosition down by # 10 pixels. # BONUS Challenge 2.3 - Make the game better with your own ideas! # The coding world is now yours for the exploring :) # * DO NOT MODIFY BELOW HERE *** # # animation setup code class Struct(object): pass data = Struct() def run(width=600, height=600): def redrawAllWrapper(canvas): canvas.delete(ALL) redrawAll(canvas) canvas.update() def keyPressedWrapper(event, canvas): keyPressed(event) redrawAllWrapper(canvas) def timerFiredWrapper(canvas): timerFired() redrawAllWrapper(canvas) # pause, then call timerFired again canvas.after(data.timerDelay, timerFiredWrapper, canvas) # Set up data and call init data.width = width data.height = height data.timerDelay = 200 # milliseconds init() # create the root and the canvas root = Tk() canvas = Canvas(root, width=data.width, height=data.height) canvas.pack() # set up events root.bind("<Key>", lambda event: keyPressedWrapper(event, canvas)) timerFiredWrapper(canvas) # and launch the app root.mainloop() # blocks until window is closed print("bye!") run()	[ 1, 515, 18883, 1639, 1053, 334, 30004, 13, 30004, 13, 30004, 13, 29937, 278, 3748, 848, 363, 278, 2847, 3748, 2106, 30004, 13, 1753, 2069, 7295, 30004, 13, 1678, 848, 29889, 9106, 29990, 353, 29871, 29906, 29945, 29900, 30004, 13, 1678, 848, 29889, 9106, 29979, 353, 29871, 29945, 29945, 29900, 30004, 13, 1678, 848, 29889, 16622, 29990, 353, 29871, 29906, 29945, 29900, 30004, 13, 1678, 848, 29889, 16622, 29979, 353, 29871, 29900, 30004, 13, 1678, 848, 29889, 11802, 3563, 353, 7700, 30004, 13, 30004, 13, 30004, 13, 29937, 4959, 13271, 278, 3748, 848, 30004, 13, 1753, 1820, 24104, 29898, 3696, 1125, 30004, 13, 1678, 565, 1741, 29889, 8149, 962, 1275, 376, 7341, 29908, 322, 848, 29889, 9106, 29990, 529, 29871, 29945, 29945, 29900, 29901, 30004, 13, 4706, 848, 29889, 9106, 29990, 4619, 29871, 29945, 30004, 13, 1678, 25342, 1741, 29889, 8149, 962, 1275, 376, 8091, 29908, 322, 848, 29889, 9106, 29990, 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activecampaign/admin/__init__.py	pmiguelima/django-activecampaign	1	142539	<filename>activecampaign/admin/__init__.py from .list import List from .message import Message from .campaign import Campaign	[ 1, 529, 9507, 29958, 4925, 24821, 8729, 29914, 6406, 29914, 1649, 2344, 26914, 2272, 13, 3166, 869, 1761, 1053, 2391, 13, 3166, 869, 4906, 1053, 7777, 13, 3166, 869, 24821, 8729, 1053, 7259, 8729, 13, 2 ]
python/practice/rules.py	icefoxen/lang	0	180169	# Heh, found this on a Usenet sig. reduce(lambda x,y:x+y,map(lambda x:chr(ord(x)^42),tuple('zS^BED\nX_FOY\x0b')))	[ 1, 396, 940, 29882, 29892, 1476, 445, 373, 263, 501, 4881, 300, 4365, 22993, 13, 30004, 13, 17469, 29898, 2892, 921, 29892, 29891, 29901, 29916, 29974, 29891, 29892, 1958, 29898, 2892, 921, 29901, 22495, 29898, 536, 29898, 29916, 4887, 29946, 29906, 511, 23583, 877, 29920, 29903, 29985, 29933, 3352, 29905, 29876, 29990, 29918, 5800, 29979, 29905, 29916, 29900, 29890, 29915, 4961, 2 ]
Leetcode/week_6/multi_threaded_merge_sort.py	SamSamhuns/wallbreakers_projekts	1	16463	import threading def merge_sort(arr): def _merge(arr1, arr2): i, j = 0, 0 l1, l2 = len(arr1), len(arr2) arr_sorted = [0] * (l1 + l2) idx = 0 while i < l1 and j < l2: if arr1[i] < arr2[j]: arr_sorted[idx] = arr1[i] i += 1 else: arr_sorted[idx] = arr2[j] j += 1 idx += 1 while i < l1: arr_sorted[idx] = arr1[i] i += 1 idx += 1 while j < l2: arr_sorted[idx] = arr2[j] j += 1 idx += 1 return arr_sorted def _recursive_sort(arr): if len(arr) == 1: return arr mid = len(arr) // 2 left_arr = _recursive_sort(arr[:mid]) right_arr = _recursive_sort(arr[mid:]) return _merge(left_arr, right_arr) return _recursive_sort(arr) def merge_sort_inplace(arr): def _merge(arr, start, mid, end): start2 = mid + 1 while start <= mid and start2 <= end: if arr[start] <= arr[start2]: # elem in right place start += 1 else: orig_start2 = arr[start2] idx = start2 # shift all elements between start and start2 # to the right by one place while idx != start: arr[idx] = arr[idx - 1] idx -= 1 arr[start] = orig_start2 start += 1 mid += 1 start2 += 1 def _recursive_sort(arr, left, right): if left < right: mid = left + ((right - left) // 2) _recursive_sort(arr, left, mid) _recursive_sort(arr, mid + 1, right) _merge(arr, left, mid, right) _recursive_sort(arr, 0, len(arr) - 1) def _merge(arr, start, mid, end): start2 = mid + 1 while start <= mid and start2 <= end: if arr[start] <= arr[start2]: # elem in right place start += 1 else: orig_start2 = arr[start2] idx = start2 # shift all elements to the right by one place while idx != start: arr[idx] = arr[idx - 1] idx -= 1 arr[start] = orig_start2 start += 1 mid += 1 start2 += 1 def _recursive_sort(arr, left, right): if left < right: mid = left + ((right - left) // 2) _recursive_sort(arr, left, mid) _recursive_sort(arr, mid + 1, right) _merge(arr, left, mid, right) # _recursive_sort(arr, 0, len(arr) - 1) if __name__ == "__main__": ar = [2, 4, 1, 2, 4, 5, 8, 2, 351, 2, 0] thread1 = threading.Thread( target=_recursive_sort, args=(ar, 0, len(ar) // 2),) thread2 = threading.Thread( target=_recursive_sort, args=(ar, (len(ar) // 2) + 1, len(ar) - 1,)) thread1.start() thread2.start() thread1.join() thread2.join() _merge(ar, 0, len(ar) // 2, len(ar) - 1) print(ar)	[ 1, 1053, 3244, 292, 13, 13, 13, 1753, 10366, 29918, 6605, 29898, 2749, 1125, 13, 13, 1678, 822, 903, 14634, 29898, 2749, 29896, 29892, 3948, 29906, 1125, 13, 4706, 474, 29892, 432, 353, 29871, 29900, 29892, 29871, 29900, 13, 4706, 301, 29896, 29892, 301, 29906, 353, 7431, 29898, 2749, 29896, 511, 7431, 29898, 2749, 29906, 29897, 13, 4706, 3948, 29918, 24582, 353, 518, 29900, 29962, 334, 313, 29880, 29896, 718, 301, 29906, 29897, 13, 4706, 22645, 353, 29871, 29900, 13, 4706, 1550, 474, 529, 301, 29896, 322, 432, 529, 301, 29906, 29901, 13, 9651, 565, 3948, 29896, 29961, 29875, 29962, 529, 3948, 29906, 29961, 29926, 5387, 13, 18884, 3948, 29918, 24582, 29961, 13140, 29962, 353, 3948, 29896, 29961, 29875, 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565, 2175, 529, 1492, 29901, 13, 4706, 7145, 353, 2175, 718, 5135, 1266, 448, 2175, 29897, 849, 29871, 29906, 29897, 13, 4706, 903, 3757, 25397, 29918, 6605, 29898, 2749, 29892, 2175, 29892, 7145, 29897, 13, 4706, 903, 3757, 25397, 29918, 6605, 29898, 2749, 29892, 7145, 718, 29871, 29896, 29892, 1492, 29897, 13, 4706, 903, 14634, 29898, 2749, 29892, 2175, 29892, 7145, 29892, 1492, 29897, 13, 13, 29937, 903, 3757, 25397, 29918, 6605, 29898, 2749, 29892, 29871, 29900, 29892, 7431, 29898, 2749, 29897, 448, 29871, 29896, 29897, 13, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 13, 1678, 564, 353, 518, 29906, 29892, 29871, 29946, 29892, 29871, 29896, 29892, 29871, 29906, 29892, 29871, 29946, 29892, 29871, 29945, 29892, 29871, 29947, 29892, 29871, 29906, 29892, 29871, 29941, 29945, 29896, 29892, 29871, 29906, 29892, 29871, 29900, 29962, 13, 13, 1678, 3244, 29896, 353, 3244, 292, 29889, 4899, 29898, 13, 4706, 3646, 29922, 29918, 3757, 25397, 29918, 6605, 29892, 6389, 7607, 279, 29892, 29871, 29900, 29892, 7431, 29898, 279, 29897, 849, 29871, 29906, 511, 29897, 13, 1678, 3244, 29906, 353, 3244, 292, 29889, 4899, 29898, 13, 4706, 3646, 29922, 29918, 3757, 25397, 29918, 6605, 29892, 6389, 7607, 279, 29892, 313, 2435, 29898, 279, 29897, 849, 29871, 29906, 29897, 718, 29871, 29896, 29892, 7431, 29898, 279, 29897, 448, 29871, 29896, 29892, 876, 13, 1678, 3244, 29896, 29889, 2962, 580, 13, 1678, 3244, 29906, 29889, 2962, 580, 13, 1678, 3244, 29896, 29889, 7122, 580, 13, 1678, 3244, 29906, 29889, 7122, 580, 13, 1678, 903, 14634, 29898, 279, 29892, 29871, 29900, 29892, 7431, 29898, 279, 29897, 849, 29871, 29906, 29892, 7431, 29898, 279, 29897, 448, 29871, 29896, 29897, 13, 1678, 1596, 29898, 279, 29897, 13, 2 ]
main.py	impressive8/Practice	197	44090	# =================================== # Import the libraries # =================================== import numpy as np from matplotlib import pylab as plt import imaging import utility import os,sys # =================================== # Which stages to run # =================================== do_add_noise = False do_black_level_correction = True do_lens_shading_correction = True do_bad_pixel_correction = True do_channel_gain_white_balance = True do_bayer_denoise = False do_demosaic = True do_demosaic_artifact_reduction = True do_color_correction = True do_gamma = True do_chromatic_aberration_correction = True do_tone_mapping = True do_memory_color_enhancement = True do_noise_reduction = True do_sharpening = True do_distortion_correction = False # =================================== # Remove all the .png files os.system("rm images/.png") # =================================== # =================================== # raw image and set up the metadata # =================================== # uncomment the image_name to run it via pipeline image_name = "DSC_1339_768x512_rggb" # image content: Rose rggb # image_name = "DSC_1339_768x512_gbrg" # image content: Rose gbrg # image_name = "DSC_1339_768x512_grbg" # image content: Rose grbg # image_name = "DSC_1339_768x512_bggr" # image content: Rose bggr # image_name = "DSC_1320_2048x2048_rggb" # image content: Potrait # image_name = "DSC_1372_6032x4032_rggb" # image content: Downtown San Jose # image_name = "DSC_1372_12096x6032_rgb_out_demosaic" # image content: Downtown San Jose after demosaic # read the raw image temp = np.fromfile("images/" + image_name + ".raw", dtype="uint16", sep="") if (image_name == "DSC_1339_768x512_rggb"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_gbrg"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_gbrg", temp) raw.set_color_space("raw") raw.set_bayer_pattern("gbrg") raw.set_channel_gain((1.0, 1.34375, 1.94921875, 1.0)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_grbg"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_grbg", temp) raw.set_color_space("raw") raw.set_bayer_pattern("grbg") raw.set_channel_gain((1.0, 1.94921875, 1.34375, 1.0)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_bggr"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_bggr", temp) raw.set_color_space("raw") raw.set_bayer_pattern("bggr") raw.set_channel_gain((1.34375, 1.0, 1.0, 1.94921875,)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1320_2048x2048_rggb"): temp = temp.reshape([2048, 2048]) raw = imaging.ImageInfo("1320_2048x2048_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1372_6032x4032_rggb"): temp = temp.reshape([4032, 6032]) raw = imaging.ImageInfo("DSC_1372_6032x4032_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1372_12096x6032_rgb_out_demosaic"): temp = temp.reshape([12096, 6032]) temp = np.float32(temp) data = np.empty((4032, 6032, 3), dtype=np.float32) data[:, :, 0] = temp[0:4032, :] data[:, :, 1] = temp[4032 : 24032, :] data[:, :, 2] = temp[24032 : 34032, :] raw = imaging.ImageInfo("DSC_1372_12096x6032_rgb_out_demosaic", data) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) else: print("Warning! image_name not recognized.") # =================================== # Add noise # =================================== if do_add_noise: noise_mean = 0 noise_standard_deviation = 100 seed = 100 clip_range = [600, 65535] data = utility.synthetic_image_generate(\ raw.get_width(), raw.get_height()).create_noisy_image(\ data, noise_mean, noise_standard_deviation, seed, clip_range) else: pass # =================================== # Black level correction # =================================== if do_black_level_correction: data = imaging.black_level_correction(data, \ raw.get_black_level(),\ raw.get_white_level(),\ [0, 2*raw.get_bit_depth() - 1]) utility.imsave(data, "images/" + image_name + "_out_black_level_correction.png", "uint16") else: pass # =================================== # Lens shading correction # =================================== if do_lens_shading_correction: # normally dark_current_image and flat_field_image are # captured in the image quality lab using flat field chart # here we are synthetically generating thouse two images dark_current_image, flat_field_image = utility.synthetic_image_generate(\ raw.get_width(), raw.get_height()).create_lens_shading_correction_images(\ 0, 65535, 40000) # save the dark_current_image and flat_field_image for viewing utility.imsave(dark_current_image, "images/" + image_name + "_dark_current_image.png", "uint16") utility.imsave(flat_field_image, "images/" + image_name + "_flat_field_image.png", "uint16") data = imaging.lens_shading_correction(data).flat_field_compensation(\ dark_current_image, flat_field_image) # data = lsc.approximate_mathematical_compensation([0.01759, -28.37, -13.36]) utility.imsave(data, "images/" + image_name + "_out_lens_shading_correction.png", "uint16") else: pass # =================================== # Bad pixel correction # =================================== if do_bad_pixel_correction: neighborhood_size = 3 data = imaging.bad_pixel_correction(data, neighborhood_size) utility.imsave(data, "images/" + image_name + "_out_bad_pixel_correction.png", "uint16") else: pass # =================================== # Channel gain for white balance # =================================== if do_channel_gain_white_balance: data = imaging.channel_gain_white_balance(data,\ raw.get_channel_gain()) utility.imsave(data, "images/" + image_name + "_out_channel_gain_white_balance.png", "uint16") else: pass # =================================== # Bayer denoising # =================================== if do_bayer_denoise: # bayer denoising parameters neighborhood_size = 5 initial_noise_level = 65535 10 / 100 hvs_min = 1000 hvs_max = 2000 clip_range = [0, 65535] threshold_red_blue = 1300 # data is the denoised output, ignoring the second output data, _ = imaging.bayer_denoising(data).utilize_hvs_behavior(\ raw.get_bayer_pattern(), initial_noise_level, hvs_min, hvs_max, threshold_red_blue, clip_range) utility.imsave(data, "images/" + image_name + "_out_bayer_denoising.png", "uint16") # utility.imsave(np.clip(texture_degree_debug65535, 0, 65535), "images/" + image_name + "_out_texture_degree_debug.png", "uint16") else: pass # =================================== # Demosacing # =================================== if do_demosaic: #data = imaging.demosaic(data, raw.get_bayer_pattern()).mhc(False) data = imaging.demosaic(data, raw.get_bayer_pattern()).directionally_weighted_gradient_based_interpolation() utility.imsave(data, "images/" + image_name + "_out_demosaic.png", "uint16") else: pass # =================================== # Demosaic artifact reduction # =================================== if do_demosaic_artifact_reduction: data = imaging.demosaic(data).post_process_local_color_ratio(0.80 65535) utility.imsave(data, "images/" + image_name + "_out_local_color_ratio.png", "uint16") edge_detection_kernel_size = 5 edge_threshold = 0.05 # first output is main output, second output is edge_location is a debug output data, _ = imaging.demosaic(data).post_process_median_filter(edge_detection_kernel_size, edge_threshold) utility.imsave(data, "images/" + image_name + "_out_median_filter.png", "uint16") # utility.imsave(edge_location*65535, "images/" + image_name + "_edge_location.png", "uint16") else: pass # =================================== # Color correction # =================================== if do_color_correction: data = imaging.color_correction(data, raw.get_color_matrix()).apply_cmatrix() utility.imsave(data, "images/" + image_name + "_out_color_correction.png", "uint16") else: pass # =================================== # Gamma # =================================== if do_gamma: # brightening data = imaging.nonlinearity(data, "brightening").luma_adjustment(80.) # gamma by value #data = imaging.nonlinearity(data, "gamma").by_value(1/2.2, [0, 65535]) # gamma by table # data = imaging.nonlinearity(data, "gamma").by_table("tables/gamma_2.4.txt", "gamma", [0, 65535]) # gamma by value data = imaging.nonlinearity(data, "gamma").by_equation(-0.9, -8.0, [0, 65535]) utility.imsave(data, "images/" + image_name + "_out_gamma.png", "uint16") else: pass # =================================== # Chromatic aberration correction # =================================== if do_chromatic_aberration_correction: nsr_threshold = 90. cr_threshold = 6425./2 data = imaging.chromatic_aberration_correction(data).purple_fringe_removal(nsr_threshold, cr_threshold) utility.imsave(data, "images/" + image_name + "_out_purple_fringe_removal.png", "uint16") else: pass # =================================== # Tone mapping # =================================== if do_tone_mapping: data = imaging.tone_mapping(data).nonlinear_masking(1.0) utility.imsave(data, "images/" + image_name + "_out_tone_mapping_nl_masking.png", "uint16") # data = imaging.tone_mapping(data).dynamic_range_compression("normal", [-25., 260.], [0, 65535]) # utility.imsave(data, "images/" + image_name + "_out_tone_mapping_drc.png", "uint16") else: pass # =================================== # Memory color enhancement # =================================== if do_memory_color_enhancement: # target_hue = [30., -115., 100.] # hue_preference = [45., -90., 130.] # hue_sigma = [20., 10., 5.] # is_both_side = [True, False, False] # multiplier = [0.6, 0.6, 0.6] # chroma_preference = [25., 17., 30.] # chroma_sigma = [10., 10., 5.] target_hue = [30., -125., 100.] hue_preference = [20., -118., 130.] hue_sigma = [20., 10., 5.] is_both_side = [True, False, False] multiplier = [0.6, 0.6, 0.6] chroma_preference = [25., 14., 30.] chroma_sigma = [10., 10., 5.] data = imaging.memory_color_enhancement(data).by_hue_squeeze(target_hue,\ hue_preference,\ hue_sigma,\ is_both_side,\ multiplier,\ chroma_preference,\ chroma_sigma) utility.imsave(data, "images/" + image_name + "_out_memory_color_enhancement.png", "uint16") else: pass # =================================== # Noise reduction # =================================== if do_noise_reduction: # sigma filter parameters neighborhood_size = 7 sigma = [1000, 500, 500] data = imaging.noise_reduction(data).sigma_filter(neighborhood_size, sigma) utility.imsave(data, "images/" + image_name + "_out_noise_reduction.png", "uint16") else: pass # =================================== # Sharpening # =================================== if do_sharpening: data = imaging.sharpening(data).unsharp_masking() utility.imsave(data, "images/" + image_name + "_out_sharpening.png", "uint16") else: pass # =================================== # Distortion correction # =================================== if do_distortion_correction: correction_type="barrel-1" strength=0.5 zoom_type="fit" clip_range=[0, 65535] data = imaging.distortion_correction(data).empirical_correction(correction_type, strength, zoom_type, clip_range) utility.imsave(data, "images/" + image_name + "_out_distortion_correction.png", "uint16") else: pass	[ 1, 396, 1275, 9166, 9166, 29922, 13, 29937, 16032, 278, 9562, 13, 29937, 1275, 9166, 9166, 29922, 13, 5215, 12655, 408, 7442, 13, 3166, 22889, 1053, 282, 2904, 370, 408, 14770, 13, 5215, 6382, 292, 13, 5215, 19725, 13, 5215, 2897, 29892, 9675, 13, 13, 13, 29937, 1275, 9166, 9166, 29922, 13, 29937, 8449, 22950, 304, 1065, 13, 29937, 1275, 9166, 9166, 29922, 13, 1867, 29918, 1202, 29918, 1217, 895, 353, 7700, 13, 1867, 29918, 8517, 29918, 5563, 29918, 2616, 276, 428, 353, 5852, 13, 1867, 29918, 29880, 575, 29918, 845, 9382, 29918, 2616, 276, 428, 353, 5852, 13, 1867, 29918, 12313, 29918, 29886, 15711, 29918, 2616, 276, 428, 353, 5852, 13, 1867, 29918, 12719, 29918, 29887, 475, 29918, 10921, 29918, 5521, 749, 353, 5852, 13, 1867, 29918, 29890, 2747, 29918, 1145, 29877, 895, 353, 7700, 13, 1867, 29918, 2310, 3628, 293, 353, 5852, 13, 1867, 29918, 2310, 3628, 293, 29918, 8813, 29918, 9313, 428, 353, 5852, 13, 1867, 29918, 2780, 29918, 2616, 276, 428, 353, 5852, 13, 1867, 29918, 4283, 353, 5852, 13, 1867, 29918, 27433, 2454, 29918, 370, 3127, 362, 29918, 2616, 276, 428, 353, 5852, 13, 1867, 29918, 29873, 650, 29918, 20698, 353, 5852, 13, 1867, 29918, 14834, 29918, 2780, 29918, 264, 29882, 27967, 353, 5852, 13, 1867, 29918, 1217, 895, 29918, 9313, 428, 353, 5852, 13, 1867, 29918, 845, 279, 2238, 292, 353, 5852, 13, 1867, 29918, 5721, 441, 291, 29918, 2616, 276, 428, 353, 7700, 13, 13, 13, 29937, 1275, 9166, 9166, 29922, 13, 29937, 15154, 599, 278, 869, 2732, 2066, 13, 359, 29889, 5205, 703, 1758, 4558, 5515, 29889, 2732, 1159, 13, 29937, 1275, 9166, 9166, 29922, 13, 13, 13, 13, 29937, 1275, 9166, 9166, 29922, 13, 29937, 10650, 1967, 322, 731, 701, 278, 15562, 13, 29937, 1275, 9166, 9166, 29922, 13, 29937, 443, 9342, 278, 1967, 29918, 978, 304, 1065, 372, 3025, 16439, 13, 3027, 29918, 978, 353, 376, 29928, 7187, 29918, 29896, 29941, 29941, 29929, 29918, 29955, 29953, 29947, 29916, 29945, 29896, 29906, 29918, 29878, 1505, 29890, 29908, 9651, 396, 1967, 2793, 29901, 14008, 364, 1505, 29890, 13, 29937, 1967, 29918, 978, 353, 376, 29928, 7187, 29918, 29896, 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291, 29918, 2616, 276, 428, 29898, 1272, 467, 3451, 381, 936, 29918, 2616, 276, 428, 29898, 2616, 276, 428, 29918, 1853, 29892, 9324, 29892, 19342, 29918, 1853, 29892, 20102, 29918, 3881, 29897, 13, 1678, 19725, 29889, 326, 7620, 29898, 1272, 29892, 376, 8346, 12975, 718, 1967, 29918, 978, 718, 11119, 449, 29918, 5721, 441, 291, 29918, 2616, 276, 428, 29889, 2732, 613, 376, 13470, 29896, 29953, 1159, 13, 13, 2870, 29901, 13, 1678, 1209, 13, 2 ]
src/pywriter/csv/csv_file.py	peter88213/PyWriter	1	169947	<reponame>peter88213/PyWriter """Provide a generic class for csv file import. Other csv file representations inherit from this class. Copyright (c) 2021 <NAME> For further information see https://github.com/peter88213/PyWriter Published under the MIT License (https://opensource.org/licenses/mit-license.php) """ import os import csv from pywriter.model.novel import Novel class CsvFile(Novel): """csv file representation. - Records are separated by line breaks. - Data fields are delimited by the _SEPARATOR character. """ EXTENSION = '.csv' # overwrites Novel.EXTENSION _SEPARATOR = ',' # delimits data fields within a record. rowTitles = [] def read(self): """Parse the csv file located at filePath, fetching the rows. Check the number of fields in each row. Return a message beginning with SUCCESS or ERROR. Override the superclass method. """ self.rows = [] cellsPerRow = len(self.rowTitles) try: with open(self.filePath, newline='', encoding='utf-8') as f: reader = csv.reader(f, delimiter=self._SEPARATOR) for row in reader: # Each row read from the csv file is returned # as a list of strings if len(row) != cellsPerRow: return 'ERROR: Wrong csv structure.' self.rows.append(row) except(FileNotFoundError): return 'ERROR: "' + os.path.normpath(self.filePath) + '" not found.' except: return 'ERROR: Can not parse "' + os.path.normpath(self.filePath) + '".' return 'SUCCESS' def get_list(self, text): """Split a sequence of comma separated strings into a list of strings. Remove leading and trailing spaces, if any. """ elements = [] tempList = text.split(',') for element in tempList: elements.append(element.lstrip().rstrip()) return elements	[ 1, 529, 276, 1112, 420, 29958, 29886, 1308, 29947, 29947, 29906, 29896, 29941, 29914, 19737, 10507, 13, 15945, 29908, 1184, 29894, 680, 263, 10035, 770, 363, 11799, 934, 1053, 22993, 13, 30004, 13, 16107, 11799, 934, 22540, 13125, 515, 445, 770, 22993, 13, 30004, 13, 11882, 1266, 313, 29883, 29897, 29871, 29906, 29900, 29906, 29896, 529, 5813, 3238, 13, 2831, 4340, 2472, 1074, 2045, 597, 3292, 29889, 510, 29914, 29886, 1308, 29947, 29947, 29906, 29896, 29941, 29914, 19737, 10507, 30004, 13, 21076, 3726, 1090, 278, 341, 1806, 19245, 313, 991, 597, 22156, 1167, 29889, 990, 29914, 506, 11259, 29914, 2415, 29899, 506, 1947, 29889, 1961, 8443, 13, 15945, 19451, 13, 5215, 2897, 30004, 13, 5215, 11799, 30004, 13, 30004, 13, 3166, 282, 5693, 5385, 29889, 4299, 29889, 13715, 295, 1053, 2864, 295, 30004, 13, 30004, 13, 30004, 13, 1990, 315, 4501, 2283, 29898, 25363, 295, 1125, 30004, 13, 1678, 9995, 7638, 934, 8954, 22993, 13, 30004, 13, 1678, 448, 7983, 526, 13055, 491, 1196, 16706, 22993, 13, 1678, 448, 3630, 4235, 526, 628, 326, 1573, 491, 278, 903, 1660, 16320, 1299, 1955, 2931, 22993, 13, 1678, 9995, 30004, 13, 30004, 13, 1678, 8528, 29911, 1430, 13381, 353, 15300, 7638, 29915, 30004, 13, 1678, 396, 975, 8231, 267, 2864, 295, 29889, 12194, 1430, 13381, 30004, 13, 30004, 13, 1678, 903, 1660, 16320, 1299, 1955, 353, 525, 5501, 30004, 13, 1678, 396, 628, 326, 1169, 848, 4235, 2629, 263, 2407, 22993, 13, 30004, 13, 1678, 1948, 29911, 277, 793, 353, 5159, 30004, 13, 30004, 13, 1678, 822, 1303, 29898, 1311, 1125, 30004, 13, 4706, 9995, 12914, 278, 11799, 934, 5982, 472, 934, 2605, 29892, 6699, 292, 278, 4206, 22993, 13, 4706, 5399, 278, 1353, 310, 4235, 297, 1269, 1948, 22993, 13, 4706, 7106, 263, 2643, 6763, 411, 20134, 26925, 470, 14431, 22993, 13, 4706, 6811, 2426, 278, 2428, 1990, 1158, 22993, 13, 4706, 9995, 30004, 13, 4706, 1583, 29889, 5727, 353, 5159, 30004, 13, 4706, 9101, 5894, 4301, 353, 7431, 29898, 1311, 29889, 798, 29911, 277, 793, 8443, 13, 30004, 13, 4706, 1018, 29901, 30004, 13, 9651, 411, 1722, 29898, 1311, 29889, 1445, 2605, 29892, 25899, 2433, 742, 8025, 2433, 9420, 29899, 29947, 1495, 408, 285, 29901, 30004, 13, 18884, 9591, 353, 11799, 29889, 16950, 29898, 29888, 29892, 28552, 29922, 1311, 3032, 1660, 16320, 1299, 1955, 8443, 13, 30004, 13, 18884, 363, 1948, 297, 9591, 29901, 30004, 13, 462, 1678, 396, 7806, 1948, 1303, 515, 278, 11799, 934, 338, 4133, 30004, 13, 462, 1678, 396, 408, 263, 1051, 310, 6031, 30004, 13, 30004, 13, 462, 1678, 565, 7431, 29898, 798, 29897, 2804, 9101, 5894, 4301, 29901, 30004, 13, 462, 4706, 736, 525, 11432, 29901, 399, 29373, 11799, 3829, 6169, 30004, 13, 30004, 13, 462, 1678, 1583, 29889, 5727, 29889, 4397, 29898, 798, 8443, 13, 30004, 13, 4706, 5174, 29898, 2283, 17413, 2392, 1125, 30004, 13, 9651, 736, 525, 11432, 29901, 13577, 718, 2897, 29889, 2084, 29889, 12324, 2084, 29898, 1311, 29889, 1445, 2605, 29897, 718, 18793, 451, 1476, 6169, 30004, 13, 30004, 13, 4706, 5174, 29901, 30004, 13, 9651, 736, 525, 11432, 29901, 1815, 451, 6088, 13577, 718, 2897, 29889, 2084, 29889, 12324, 2084, 29898, 1311, 29889, 1445, 2605, 29897, 718, 525, 1642, 29915, 30004, 13, 30004, 13, 4706, 736, 525, 14605, 26925, 29915, 30004, 13, 30004, 13, 1678, 822, 679, 29918, 1761, 29898, 1311, 29892, 1426, 1125, 30004, 13, 4706, 9995, 18772, 263, 5665, 310, 16694, 13055, 6031, 964, 263, 1051, 310, 6031, 22993, 13, 4706, 15154, 8236, 322, 25053, 8162, 29892, 565, 738, 22993, 13, 4706, 9995, 30004, 13, 4706, 3161, 353, 5159, 30004, 13, 4706, 5694, 1293, 353, 1426, 29889, 5451, 29317, 1495, 30004, 13, 30004, 13, 4706, 363, 1543, 297, 5694, 1293, 29901, 30004, 13, 9651, 3161, 29889, 4397, 29898, 5029, 29889, 29880, 17010, 2141, 29878, 17010, 3101, 30004, 13, 30004, 13, 4706, 736, 3161, 30004, 13, 2 ]
lib/src/align/aligner/basic/BasicAlignerStrategy.py	thormeier-fhnw-repos/ip619bb-i4ds02-audio-text-alignment	0	169960	<reponame>thormeier-fhnw-repos/ip619bb-i4ds02-audio-text-alignment<filename>lib/src/align/aligner/basic/BasicAlignerStrategy.py from typing import List from lib.src.align.aligner.AbstractAlignerStrategy import AbstractAlignerStrategy from lib.src.align.utils.transcript_to_sentences import transcript_to_sentences from lib.src.model.Sentence import Sentence from pydub import AudioSegment import time from bin._bin import bin_print class BasicAlignerStrategy(AbstractAlignerStrategy): """ Basic alignment based on sentence length. """ @staticmethod def perform_alignment(transcript: str, wav_path: str, verbosity: int) -> List["Sentence"]: """ Performs a basic alignment :param transcript: Path to transcript :param wav_path: Path to wav file :param verbosity: Verbosity level :return: Aligned sentences """ start_time = time.time() audio_segment = AudioSegment.from_wav(wav_path) duration = audio_segment.duration_seconds with open(transcript, encoding="utf-8") as f: transcript = f.read() transcript = transcript.replace("\n", " ") sentences = transcript_to_sentences(transcript) number_of_chars_total = sum([len(sentence.sentence) for sentence in sentences]) start = 0.0 for sentence in sentences: end = start + len(sentence.sentence) / number_of_chars_total * duration sentence.interval.start = start sentence.interval.end = end start = end end_time = time.time() bin_print(verbosity, 2, "Time elapsed for", wav_path, ":", (end_time - start_time)) return sentences	[ 1, 529, 276, 1112, 420, 29958, 386, 555, 29872, 631, 29899, 29888, 3123, 29893, 29899, 276, 1066, 29914, 666, 29953, 29896, 29929, 1327, 29899, 29875, 29946, 6289, 29900, 29906, 29899, 18494, 29899, 726, 29899, 2520, 358, 29966, 9507, 29958, 1982, 29914, 4351, 29914, 2520, 29914, 2520, 261, 29914, 16121, 29914, 16616, 2499, 21216, 26910, 29889, 2272, 13, 3166, 19229, 1053, 2391, 13, 3166, 4303, 29889, 4351, 29889, 2520, 29889, 2520, 261, 29889, 9118, 2499, 21216, 26910, 1053, 25513, 2499, 21216, 26910, 13, 3166, 4303, 29889, 4351, 29889, 2520, 29889, 13239, 29889, 3286, 924, 29918, 517, 29918, 18616, 2063, 1053, 1301, 924, 29918, 517, 29918, 18616, 2063, 13, 3166, 4303, 29889, 4351, 29889, 4299, 29889, 29903, 296, 663, 1053, 28048, 663, 13, 3166, 282, 2941, 431, 1053, 21764, 17669, 358, 13, 5215, 931, 13, 3166, 9016, 3032, 2109, 1053, 9016, 29918, 2158, 13, 13, 13, 1990, 19219, 2499, 21216, 26910, 29898, 9118, 2499, 21216, 26910, 1125, 13, 1678, 9995, 13, 1678, 19219, 22239, 2729, 373, 10541, 3309, 29889, 13, 1678, 9995, 13, 13, 1678, 732, 7959, 5696, 13, 1678, 822, 2189, 29918, 2520, 358, 29898, 3286, 924, 29901, 851, 29892, 281, 485, 29918, 2084, 29901, 851, 29892, 9750, 359, 537, 29901, 938, 29897, 1599, 2391, 3366, 29903, 296, 663, 3108, 29901, 13, 4706, 9995, 13, 4706, 2431, 9514, 263, 6996, 22239, 13, 13, 4706, 584, 3207, 1301, 924, 29901, 10802, 304, 1301, 924, 13, 4706, 584, 3207, 281, 485, 29918, 2084, 29901, 259, 10802, 304, 281, 485, 934, 13, 4706, 584, 3207, 9750, 359, 537, 29901, 29871, 26646, 359, 537, 3233, 13, 13, 4706, 584, 2457, 29901, 838, 12961, 25260, 13, 4706, 9995, 13, 4706, 1369, 29918, 2230, 353, 931, 29889, 2230, 580, 13, 13, 4706, 10348, 29918, 28192, 353, 21764, 17669, 358, 29889, 3166, 29918, 29893, 485, 29898, 29893, 485, 29918, 2084, 29897, 13, 4706, 14385, 353, 10348, 29918, 28192, 29889, 19708, 29918, 23128, 13, 13, 4706, 411, 1722, 29898, 3286, 924, 29892, 8025, 543, 9420, 29899, 29947, 1159, 408, 285, 29901, 13, 9651, 1301, 924, 353, 285, 29889, 949, 580, 13, 4706, 1301, 924, 353, 1301, 924, 29889, 6506, 14182, 29876, 613, 376, 16521, 13, 13, 4706, 25260, 353, 1301, 924, 29918, 517, 29918, 18616, 2063, 29898, 3286, 924, 29897, 13, 13, 4706, 1353, 29918, 974, 29918, 305, 1503, 29918, 7827, 353, 2533, 4197, 2435, 29898, 18616, 663, 29889, 18616, 663, 29897, 363, 10541, 297, 25260, 2314, 13, 13, 4706, 1369, 353, 29871, 29900, 29889, 29900, 13, 4706, 363, 10541, 297, 25260, 29901, 13, 9651, 1095, 353, 1369, 718, 7431, 29898, 18616, 663, 29889, 18616, 663, 29897, 847, 1353, 29918, 974, 29918, 305, 1503, 29918, 7827, 334, 14385, 13, 9651, 10541, 29889, 19207, 29889, 2962, 353, 1369, 13, 9651, 10541, 29889, 19207, 29889, 355, 353, 1095, 13, 9651, 1369, 353, 1095, 13, 4706, 1095, 29918, 2230, 353, 931, 29889, 2230, 580, 13, 13, 4706, 9016, 29918, 2158, 29898, 18248, 359, 537, 29892, 29871, 29906, 29892, 376, 2481, 560, 28170, 363, 613, 281, 485, 29918, 2084, 29892, 29242, 613, 313, 355, 29918, 2230, 448, 1369, 29918, 2230, 876, 13, 13, 4706, 736, 25260, 13, 2 ]
imgaug/augmenters/flip.py	pAoenix/image-Augmented	1	3912	<reponame>pAoenix/image-Augmented """ Augmenters that apply mirroring/flipping operations to images. Do not import directly from this file, as the categorization is not final. Use instead :: from imgaug import augmenters as iaa and then e.g. :: seq = iaa.Sequential([ iaa.Fliplr((0.0, 1.0)), iaa.Flipud((0.0, 1.0)) ]) List of augmenters: * Fliplr * Flipud """ from __future__ import print_function, division, absolute_import from .. import parameters as iap import numpy as np import six.moves as sm from .meta import Augmenter class Fliplr(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long """ Flip/mirror input images horizontally. Parameters ---------- p : number or StochasticParameter, optional(default=0) Probability of each image to get flipped. name : string, optional(default=None) See `Augmenter.__init__()` deterministic : bool, optional(default=False) See `Augmenter.__init__()` random_state : int or np.random.RandomState or None, optional(default=None) See `Augmenter.__init__()` Examples -------- >>> aug = iaa.Fliplr(0.5) would horizontally flip/mirror 50 percent of all input images. >>> aug = iaa.Fliplr(1.0) would horizontally flip/mirror all input images. """ def __init__(self, p=0, name=None, deterministic=False, random_state=None): super(Fliplr, self).__init__(name=name, deterministic=deterministic, random_state=random_state) self.p = iap.handle_probability_param(p, "p") def _augment_images(self, images, random_state, parents, hooks): nb_images = len(images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i in sm.xrange(nb_images): if samples[i] == 1: images[i] = np.fliplr(images[i]) return images def _augment_heatmaps(self, heatmaps, random_state, parents, hooks): arrs_flipped = self._augment_images( [heatmaps_i.arr_0to1 for heatmaps_i in heatmaps], random_state=random_state, parents=parents, hooks=hooks ) for heatmaps_i, arr_flipped in zip(heatmaps, arrs_flipped): heatmaps_i.arr_0to1 = arr_flipped return heatmaps def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks): nb_images = len(keypoints_on_images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i, keypoints_on_image in enumerate(keypoints_on_images): if samples[i] == 1: width = keypoints_on_image.shape[1] for keypoint in keypoints_on_image.keypoints: keypoint.x = (width - 1) - keypoint.x return keypoints_on_images def get_parameters(self): return [self.p] class Flipud(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long """ Flip/mirror input images vertically. Parameters ---------- p : number or StochasticParameter, optional(default=0) Probability of each image to get flipped. name : string, optional(default=None) See `Augmenter.__init__()` deterministic : bool, optional(default=False) See `Augmenter.__init__()` random_state : int or np.random.RandomState or None, optional(default=None) See `Augmenter.__init__()` Examples -------- >>> aug = iaa.Flipud(0.5) would vertically flip/mirror 50 percent of all input images. >>> aug = iaa.Flipud(1.0) would vertically flip/mirror all input images. """ def __init__(self, p=0, name=None, deterministic=False, random_state=None): super(Flipud, self).__init__(name=name, deterministic=deterministic, random_state=random_state) self.p = iap.handle_probability_param(p, "p") def _augment_images(self, images, random_state, parents, hooks): nb_images = len(images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i in sm.xrange(nb_images): if samples[i] == 1: images[i] = np.flipud(images[i]) return images def _augment_heatmaps(self, heatmaps, random_state, parents, hooks): arrs_flipped = self._augment_images( [heatmaps_i.arr_0to1 for heatmaps_i in heatmaps], random_state=random_state, parents=parents, hooks=hooks ) for heatmaps_i, arr_flipped in zip(heatmaps, arrs_flipped): heatmaps_i.arr_0to1 = arr_flipped return heatmaps def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks): nb_images = len(keypoints_on_images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i, keypoints_on_image in enumerate(keypoints_on_images): if samples[i] == 1: height = keypoints_on_image.shape[0] for keypoint in keypoints_on_image.keypoints: keypoint.y = (height - 1) - keypoint.y return keypoints_on_images def get_parameters(self): return [self.p]	[ 1, 529, 276, 1112, 420, 29958, 29886, 29909, 29877, 23534, 29914, 3027, 29899, 29909, 688, 358, 287, 13, 15945, 29908, 13, 29909, 688, 358, 414, 393, 3394, 19571, 292, 29914, 20157, 3262, 6931, 304, 4558, 29889, 13, 13, 6132, 451, 1053, 4153, 515, 445, 934, 29892, 408, 278, 11608, 2133, 338, 451, 2186, 29889, 13, 11403, 2012, 4761, 13, 13, 1678, 515, 10153, 2987, 1053, 18765, 414, 408, 29871, 423, 29874, 13, 13, 392, 769, 321, 29889, 29887, 29889, 4761, 13, 13, 1678, 19359, 353, 29871, 423, 29874, 29889, 16941, 2556, 4197, 13, 308, 423, 29874, 29889, 29943, 492, 572, 29878, 3552, 29900, 29889, 29900, 29892, 29871, 29896, 29889, 29900, 8243, 13, 308, 423, 29874, 29889, 29943, 3466, 566, 3552, 29900, 29889, 29900, 29892, 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13, 1678, 1024, 584, 1347, 29892, 13136, 29898, 4381, 29922, 8516, 29897, 13, 4706, 2823, 421, 29909, 688, 358, 261, 17255, 2344, 1649, 2555, 13, 13, 1678, 11806, 4695, 584, 6120, 29892, 13136, 29898, 4381, 29922, 8824, 29897, 13, 4706, 2823, 421, 29909, 688, 358, 261, 17255, 2344, 1649, 2555, 13, 13, 1678, 4036, 29918, 3859, 584, 938, 470, 7442, 29889, 8172, 29889, 17875, 2792, 470, 6213, 29892, 13136, 29898, 4381, 29922, 8516, 29897, 13, 4706, 2823, 421, 29909, 688, 358, 261, 17255, 2344, 1649, 2555, 13, 13, 1678, 1222, 9422, 13, 1678, 448, 26589, 13, 1678, 8653, 11307, 353, 29871, 423, 29874, 29889, 29943, 492, 572, 29878, 29898, 29900, 29889, 29945, 29897, 13, 13, 1678, 723, 4029, 6753, 635, 285, 3466, 29914, 11038, 729, 29871, 29945, 29900, 10151, 310, 599, 1881, 4558, 29889, 13, 13, 13, 1678, 8653, 11307, 353, 29871, 423, 29874, 29889, 29943, 492, 572, 29878, 29898, 29896, 29889, 29900, 29897, 13, 13, 1678, 723, 4029, 6753, 635, 285, 3466, 29914, 11038, 729, 599, 1881, 4558, 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reid_main.py	yujheli/ARN	26	61077	<reponame>yujheli/ARN<filename>reid_main.py from __future__ import print_function, division import os import numpy as np import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets from torch.utils.data import DataLoader from torchvision.utils import make_grid from torchvision import transforms as trans from tensorboardX import SummaryWriter from argparse import ArgumentParser from reid_network import AdaptReID_model from reid_dataset import AdaptReID_Dataset from reid_evaluate import evaluate from reid_loss import * import config parser = ArgumentParser() parser.add_argument("--use_gpu", default=2, type=int) parser.add_argument("--source_dataset", choices=['CUHK03', 'Duke', 'Market', 'MSMT17_V1'], type=str) parser.add_argument("--target_dataset", choices=['CUHK03', 'Duke', 'Market', 'MSMT17_V1'], type=str) parser.add_argument("--batch_size", default=8, type=int) parser.add_argument("--learning_rate", default=1e-4, type=float) parser.add_argument("--total_epochs", default=1000, type=int) parser.add_argument("--w_loss_rec", default=0.1, type=float) parser.add_argument("--w_loss_dif", default=0.1, type=float) parser.add_argument("--w_loss_mmd", default=0.1, type=float) parser.add_argument("--w_loss_ctr", default=1.0, type=float) parser.add_argument("--dist_metric", choices=['L1', 'L2', 'cosine', 'correlation'], type=str) parser.add_argument("--rank", default=1, type=int) parser.add_argument("--model_dir", default='model', type=str) parser.add_argument("--model_name", default='basic_10cls', type=str) parser.add_argument("--pretrain_model_name", default=None, type=str) args = parser.parse_args() total_batch = 4272 transform_list = [trans.RandomHorizontalFlip(p=0.5), trans.Resize(size=(config.IMAGE_HEIGHT, config.IMAGE_WIDTH)),\ trans.ToTensor(), trans.Normalize(mean=config.MEAN, std=config.STD)] def setup_gpu(): assert torch.cuda.is_available() torch.backends.cudnn.benchmark = True print('Using GPU: {}'.format(args.use_gpu)) def tb_visualize(image): return (image+1.0)0.5 def get_batch(data_iter, data_loader): try: _, batch = next(data_iter) except: data_iter = enumerate(data_loader) _, batch = next(data_iter) if batch['image'].size(0) < args.batch_size: batch, data_iter = get_batch(data_iter, data_loader) return batch, data_iter def save_model(model, step): model_path = '{}/{}/{}_{}.pth.tar'.format(args.model_dir ,args.model_name ,args.model_name, step) torch.save(model.state_dict(), model_path) def train(): print('Model name: {}'.format(args.model_name)) classifier_output_dim = config.get_dataoutput(args.source_dataset) model = AdaptReID_model(backbone='resnet-50', classifier_output_dim=classifier_output_dim).cuda() # print(model.state_dict()) print("Loading pre-trained model...") checkpoint = torch.load('{}/{}.pth.tar'.format(args.model_dir, args.pretrain_model_name)) for name, param in model.state_dict().items(): print(name) if name not in ['classifier.linear.weight','classifier.linear.bias']: model.state_dict()[name].copy_(checkpoint[name]) # if args.pretrain_model_name is not None: # model.load_state_dict(torch.load('{}/{}.pth.tar'.format(args.model_dir, args.pretrain_model_name))) sourceData = AdaptReID_Dataset(dataset_name=args.source_dataset, mode='source', transform=trans.Compose(transform_list)) targetData = AdaptReID_Dataset(dataset_name=args.target_dataset, mode='train', transform=trans.Compose(transform_list)) sourceDataloader = DataLoader(sourceData, batch_size=args.batch_size, shuffle=True) targetDataloader = DataLoader(targetData, batch_size=args.batch_size, shuffle=True) source_iter = enumerate(sourceDataloader) target_iter = enumerate(targetDataloader) model_opt = optim.SGD(filter(lambda p: p.requires_grad, model.parameters()), lr=args.learning_rate, momentum=0.9, weight_decay=0.0005) writer = SummaryWriter('log/{}'.format(args.model_name)) match, junk = None, None for epoch in range(args.total_epochs): for batch_idx in range(total_batch): model.train() step = epochtotal_batch + batch_idx print('{}: epoch: {}/{} step: {}/{} ({:.2f}%)'.format(args.model_name, epoch+1, args.total_epochs, step+1, total_batch, float(batch_idx+1)100.0/total_batch)) source_batch, source_iter = get_batch(source_iter, sourceDataloader) target_batch, target_iter = get_batch(target_iter, targetDataloader) source_image, source_label, _ = split_datapack(source_batch) target_image, _, _ = split_datapack(target_batch) feature_t_et_avg, feature_t_ec_avg, image_t_, pred_t, feature_s_es_avg, feature_s_ec_avg, image_s_, pred_s\ = model(image_t=target_image, image_s=source_image) #calculate loss loss_rec = loss_rec_func(image_s_, source_image) + loss_rec_func(image_t_, target_image) loss_cls = loss_cls_func(pred_s, source_label) loss_dif = loss_dif_func(feature_t_et_avg, feature_t_ec_avg) + loss_dif_func(feature_s_es_avg, feature_s_ec_avg) loss_mmd = loss_mmd_func(feature_t_ec_avg, feature_s_ec_avg) loss_ctr = loss_ctr_func(feature_s_ec_avg, source_label) loss = loss_cls + loss_recargs.w_loss_rec + loss_difargs.w_loss_dif + loss_ctrargs.w_loss_ctr + loss_mmd*args.w_loss_mmd #update model model_opt.zero_grad() loss.backward() model_opt.step() #write to tenserboardX if (step+1)%100==0: writer.add_image('source image', tb_visualize(source_image), step) writer.add_image('target image', tb_visualize(target_image), step) writer.add_image('source image_rec', tb_visualize(image_s_), step) writer.add_image('target image_rec', tb_visualize(image_t_), step) writer.add_scalar('loss_rec', loss_rec, step) writer.add_scalar('loss_cls', loss_cls, step) writer.add_scalar('loss_dif', loss_dif, step) writer.add_scalar('loss_ctr', loss_ctr, step) writer.add_scalar('loss_mmd', loss_ctr, step) writer.add_scalar('loss', loss, step) #evaluate if (step+1)%2000==0: rank_score, match, junk = evaluate(args, model, transform_list, match, junk) writer.add_scalar('rank1_score', rank_score, step) save_model(model, step) writer.close() setup_gpu() train()	[ 1, 529, 276, 1112, 420, 29958, 29891, 8016, 3952, 29875, 29914, 15249, 29966, 9507, 29958, 276, 333, 29918, 3396, 29889, 2272, 13, 3166, 4770, 29888, 9130, 1649, 1053, 1596, 29918, 2220, 29892, 8542, 13, 5215, 2897, 13, 5215, 12655, 408, 7442, 13, 5215, 4842, 305, 13, 5215, 4842, 305, 29889, 15755, 408, 302, 29876, 13, 5215, 4842, 305, 29889, 20640, 408, 5994, 13, 3166, 4842, 305, 4924, 1053, 20035, 13, 3166, 4842, 305, 29889, 13239, 29889, 1272, 1053, 3630, 10036, 13, 3166, 4842, 305, 4924, 29889, 13239, 1053, 1207, 29918, 7720, 13, 3166, 4842, 305, 4924, 1053, 4327, 29879, 408, 1301, 13, 3166, 12489, 3377, 29990, 1053, 6991, 5219, 10507, 13, 3166, 1852, 5510, 1053, 23125, 11726, 13, 3166, 337, 333, 29918, 11618, 1053, 23255, 415, 1123, 1367, 29918, 4299, 13, 3166, 337, 333, 29918, 24713, 1053, 23255, 415, 1123, 1367, 29918, 16390, 24541, 13, 3166, 337, 333, 29918, 24219, 403, 1053, 14707, 13, 3166, 337, 333, 29918, 6758, 1053, 334, 13, 5215, 2295, 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scripts/libfranka_gui_gripper_run.py	nbfigueroa/franka_interactive_controllers	6	8052	#!/usr/bin/env python3 import shlex from tkinter import * from tkinter import messagebox from psutil import Popen top = Tk() top.title("Franka Gripper Control") top.geometry("300x75") def open(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 1')) messagebox.showinfo("Open Gripper", "Gripper Opened") node_process.terminate() def close(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 0')) messagebox.showinfo("Close Gripper", "Gripper Closed") node_process.terminate() B1 = Button(top, text = "Open Gripper", command = open) B1.place(x = 30,y = 20) B2 = Button(top, text = "Close Gripper", command = close) B2.place(x = 160,y = 20) top.mainloop()	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 29941, 13, 5215, 528, 2506, 13, 3166, 18883, 1639, 1053, 334, 13, 3166, 18883, 1639, 1053, 2643, 1884, 13, 3166, 6529, 4422, 1053, 349, 3150, 13, 13, 13, 3332, 353, 323, 29895, 580, 13, 3332, 29889, 3257, 703, 7675, 1335, 402, 374, 2496, 11264, 1159, 13, 3332, 29889, 19156, 703, 29941, 29900, 29900, 29916, 29955, 29945, 1159, 13, 13, 1753, 1722, 7295, 29871, 13, 12, 3177, 29918, 5014, 353, 349, 3150, 29898, 845, 2506, 29889, 5451, 877, 1883, 3389, 2524, 1335, 29918, 1639, 4925, 29918, 1285, 11897, 619, 1635, 661, 1335, 29918, 29887, 374, 2496, 29918, 3389, 29871, 29896, 8785, 13, 12, 4906, 1884, 29889, 4294, 3888, 703, 6585, 402, 374, 2496, 613, 376, 29954, 374, 2496, 4673, 287, 1159, 13, 12, 3177, 29918, 5014, 29889, 18821, 403, 580, 13, 13, 1753, 3802, 7295, 1678, 13, 12, 3177, 29918, 5014, 353, 349, 3150, 29898, 845, 2506, 29889, 5451, 877, 1883, 3389, 2524, 1335, 29918, 1639, 4925, 29918, 1285, 11897, 619, 1635, 661, 1335, 29918, 29887, 374, 2496, 29918, 3389, 29871, 29900, 8785, 13, 12, 4906, 1884, 29889, 4294, 3888, 703, 11123, 402, 374, 2496, 613, 376, 29954, 374, 2496, 2233, 2662, 1159, 13, 12, 3177, 29918, 5014, 29889, 18821, 403, 580, 13, 13, 29933, 29896, 353, 11025, 29898, 3332, 29892, 1426, 353, 376, 6585, 402, 374, 2496, 613, 1899, 353, 1722, 29897, 13, 29933, 29896, 29889, 6689, 29898, 29916, 353, 29871, 29941, 29900, 29892, 29891, 353, 29871, 29906, 29900, 29897, 13, 13, 29933, 29906, 353, 11025, 29898, 3332, 29892, 1426, 353, 376, 11123, 402, 374, 2496, 613, 1899, 353, 3802, 29897, 13, 29933, 29906, 29889, 6689, 29898, 29916, 353, 29871, 29896, 29953, 29900, 29892, 29891, 353, 29871, 29906, 29900, 29897, 13, 13, 13, 3332, 29889, 3396, 7888, 580, 13, 2 ]
Numpy-project/code.py	nish700/ga-learner-dsmp-repo	0	133963	# -------------- # Importing header files import numpy as np # Path of the file has been stored in variable called 'path' #New record new_record=[[50, 9, 4, 1, 0, 0, 40, 0]] #Code starts here data = np.genfromtxt(path, delimiter=',' ,skip_header=1) census = np.concatenate((data,np.asarray(new_record))) print(census, type(census)) # -------------- #Code starts here import numpy as np age = census[:,0] # indexing an array, all rows and only the first column max_age = max(age) min_age = min(age) age_mean = np.mean(age) age_std = np.std(age) print(age) print(max_age) print(min_age) print(age_mean) print(age_std) # -------------- #Code starts here race_0 = census[census[:,2] == 0] race_1 = census[census[:,2] == 1] race_2 = census[census[:,2] == 2] race_3 = census[census[:,2] == 3] race_4 = census[census[:,2] == 4] len_0 = len(race_0) len_1 = len(race_1) len_2 = len(race_2) len_3 = len(race_3) len_4 = len(race_4) len_race = [len_0,len_1,len_2,len_3,len_4] minority_race = len_race.index(min(len_race)) print(minority_race) # -------------- #Code starts here senior_citizens = census[census[:,0]>60] working_hours_sum = sum(senior_citizens[:,6]) senior_citizens_len = len(senior_citizens) avg_working_hours = working_hours_sum/senior_citizens_len # print(working_hours_sum) print(avg_working_hours) # -------------- #Code starts here import numpy as np high = census[census[:,1]>10] low = census[census[:,1]<=10] avg_pay_high = np.mean(high[:,7]) avg_pay_low = np.mean(low[:,7]) print(avg_pay_high) print(avg_pay_low)	[ 1, 396, 448, 9072, 29899, 13, 29937, 16032, 292, 4839, 2066, 30004, 13, 5215, 12655, 408, 7442, 30004, 13, 30004, 13, 29937, 10802, 310, 278, 934, 756, 1063, 6087, 297, 2286, 2000, 525, 2084, 29915, 30004, 13, 30004, 13, 29937, 4373, 2407, 30004, 13, 1482, 29918, 11651, 29922, 8999, 29945, 29900, 29892, 259, 29929, 29892, 259, 29946, 29892, 259, 29896, 29892, 259, 29900, 29892, 259, 29900, 29892, 29871, 29946, 29900, 29892, 259, 29900, 5262, 30004, 13, 30004, 13, 29937, 3399, 8665, 1244, 30004, 13, 1272, 353, 7442, 29889, 1885, 3166, 3945, 29898, 2084, 29892, 28552, 29922, 3788, 1919, 11014, 29918, 6672, 29922, 29896, 8443, 13, 30004, 13, 29883, 8841, 353, 7442, 29889, 535, 29883, 2579, 403, 3552, 1272, 29892, 9302, 29889, 294, 2378, 29898, 1482, 29918, 11651, 4961, 30004, 13, 2158, 29898, 29883, 8841, 29892, 1134, 29898, 29883, 8841, 876, 13, 13, 13, 29937, 448, 9072, 29899, 13, 29937, 3399, 8665, 1244, 30004, 13, 5215, 12655, 408, 7442, 30004, 13, 30004, 13, 482, 353, 16411, 7503, 29892, 29900, 29962, 396, 26190, 385, 1409, 29892, 599, 4206, 322, 871, 278, 937, 1897, 30004, 13, 3317, 29918, 482, 353, 4236, 29898, 482, 8443, 13, 1195, 29918, 482, 353, 1375, 29898, 482, 8443, 13, 482, 29918, 12676, 353, 7442, 29889, 12676, 29898, 482, 8443, 13, 482, 29918, 4172, 353, 7442, 29889, 4172, 29898, 482, 8443, 13, 30004, 13, 2158, 29898, 482, 8443, 13, 2158, 29898, 3317, 29918, 482, 8443, 13, 2158, 29898, 1195, 29918, 482, 8443, 13, 2158, 29898, 482, 29918, 12676, 8443, 13, 2158, 29898, 482, 29918, 4172, 29897, 13, 13, 13, 29937, 448, 9072, 29899, 13, 29937, 3399, 8665, 1244, 30004, 13, 25525, 29918, 29900, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29906, 29962, 1275, 29871, 29900, 29962, 30004, 13, 25525, 29918, 29896, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29906, 29962, 1275, 29871, 29896, 29962, 30004, 13, 25525, 29918, 29906, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29906, 29962, 1275, 29871, 29906, 29962, 30004, 13, 25525, 29918, 29941, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29906, 29962, 1275, 29871, 29941, 29962, 30004, 13, 25525, 29918, 29946, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29906, 29962, 1275, 29871, 29946, 29962, 30004, 13, 30004, 13, 2435, 29918, 29900, 353, 7431, 29898, 25525, 29918, 29900, 8443, 13, 2435, 29918, 29896, 353, 7431, 29898, 25525, 29918, 29896, 8443, 13, 2435, 29918, 29906, 353, 7431, 29898, 25525, 29918, 29906, 8443, 13, 2435, 29918, 29941, 353, 7431, 29898, 25525, 29918, 29941, 8443, 13, 2435, 29918, 29946, 353, 7431, 29898, 25525, 29918, 29946, 8443, 13, 30004, 13, 2435, 29918, 25525, 353, 518, 2435, 29918, 29900, 29892, 2435, 29918, 29896, 29892, 2435, 29918, 29906, 29892, 2435, 29918, 29941, 29892, 2435, 29918, 29946, 29962, 30004, 13, 1195, 272, 537, 29918, 25525, 353, 7431, 29918, 25525, 29889, 2248, 29898, 1195, 29898, 2435, 29918, 25525, 876, 30004, 13, 2158, 29898, 1195, 272, 537, 29918, 25525, 29897, 13, 13, 13, 29937, 448, 9072, 29899, 13, 29937, 3399, 8665, 1244, 30004, 13, 4881, 1611, 29918, 20752, 466, 575, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29900, 29962, 29958, 29953, 29900, 29962, 30004, 13, 30004, 13, 22899, 29918, 29882, 2470, 29918, 2083, 353, 2533, 29898, 4881, 1611, 29918, 20752, 466, 575, 7503, 29892, 29953, 2314, 30004, 13, 30004, 13, 4881, 1611, 29918, 20752, 466, 575, 29918, 2435, 353, 7431, 29898, 4881, 1611, 29918, 20752, 466, 575, 8443, 13, 30004, 13, 485, 29887, 29918, 22899, 29918, 29882, 2470, 353, 1985, 29918, 29882, 2470, 29918, 2083, 29914, 4881, 1611, 29918, 20752, 466, 575, 29918, 2435, 30004, 13, 30004, 13, 29937, 1596, 29898, 22899, 29918, 29882, 2470, 29918, 2083, 8443, 13, 2158, 29898, 485, 29887, 29918, 22899, 29918, 29882, 2470, 29897, 13, 13, 13, 29937, 448, 9072, 29899, 13, 29937, 3399, 8665, 1244, 30004, 13, 5215, 12655, 408, 7442, 30004, 13, 30004, 13, 9812, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29896, 29962, 29958, 29896, 29900, 29962, 30004, 13, 677, 353, 16411, 29961, 29883, 8841, 7503, 29892, 29896, 29962, 14065, 29896, 29900, 29962, 30004, 13, 30004, 13, 485, 29887, 29918, 10472, 29918, 9812, 353, 7442, 29889, 12676, 29898, 9812, 7503, 29892, 29955, 2314, 30004, 13, 485, 29887, 29918, 10472, 29918, 677, 353, 7442, 29889, 12676, 29898, 677, 7503, 29892, 29955, 2314, 30004, 13, 30004, 13, 2158, 29898, 485, 29887, 29918, 10472, 29918, 9812, 8443, 13, 2158, 29898, 485, 29887, 29918, 10472, 29918, 677, 29897, 13, 13, 13, 2 ]
usernamerules/simple.py	74wny0wl/entusergenerator	1	60751	<filename>usernamerules/simple.py def simple(user_data, with_separator=''): return [with_separator.join(user_data)]	[ 1, 529, 9507, 29958, 375, 824, 4183, 2540, 29914, 12857, 29889, 2272, 13, 1753, 2560, 29898, 1792, 29918, 1272, 29892, 411, 29918, 344, 17954, 2433, 29374, 13, 1678, 736, 518, 2541, 29918, 344, 17954, 29889, 7122, 29898, 1792, 29918, 1272, 4638, 13, 2 ]
pylinex/basis/GramSchmidtBasis.py	CU-NESS/pylinex	0	159564	<gh_stars>0 """ File: pylinex/basis/GramSchmidtBasis.py Author: <NAME> Date: 3 Sep 2017 Description: File containing subclass of Basis which implements a set of basis vectors created through a Gram-Schmidt orthogonalization procedure. """ from __future__ import division import numpy as np from ..expander import NullExpander from .Basis import Basis def orthonormal_basis(seed_vectors, error=None): """ Creates an orthonormal basis from the given seed vectors using a Gram-Schmidt orthogonalization procedure. seed_vectors: vectors with which to generate new modes using the Gram-Schmidt orthogonalization procedure error: 1D numpy.ndarray containing error values with which to define 'orthogonal' returns: a set of basis vectors. a numpy.ndarray of the same shape as the seed vectors """ if type(error) is type(None): error = np.ones_like(seed_vectors[0]) inverse_error = 1 / error covariance = np.diag(error 2) inverse_covariance = np.diag(inverse_error 2) correction_matrix = inverse_covariance.copy() def dot_product(u, v): return np.dot(u * inverse_error, v * inverse_error) basis = [] for degree in range(len(seed_vectors)): pbv = seed_vectors[degree] cpbv = np.dot(pbv, correction_matrix) basis.append(np.dot(covariance, cpbv) / np.sqrt(np.dot(pbv, cpbv))) CinvF = np.reshape(np.dot(inverse_covariance, basis[-1]), (-1, 1)) correction_matrix -= np.dot(CinvF, CinvF.T) return np.array(basis) def orthonormal_polynomial_basis(num_points, max_degree, error=None): """ Creates a new Legendre polynomial-like basis with the given number of points and basis vectors. num_points: number of points to include in the basis vectors max_degree: one less than the number of basis vectors desired error: 1D numpy.ndarray with which to define 'orthogonal' returns: 2D numpy.ndarray of shape (md+1,np) where md is the max_degree given and np is the num_points given """ xs = np.linspace(-1, 1, num_points) seed_vectors = [(xs ** degree) for degree in range(max_degree + 1)] return orthonormal_basis(seed_vectors, error=error) def orthonormal_harmonic_basis(num_points, max_degree, error=None): """ Creates a new Fourier series-like basis with the given number of points and basis vectors. num_points: number of points to include in the basis vectors max_degree: determines number of basis vectors returned error: 1D numpy.ndarray with which to define 'orthogonal' returns: 2D numpy.ndarray of shape (2md+1,np) where md is the max_degree given and np is the num_points given """ xs = np.linspace(-np.pi, np.pi, num_points) num_basis = (2 max_degree) + 1 def vector(index): scaled_xs = (((index + 1) // 2) * xs) is_sin = bool(index % 2) if is_sin: return np.sin(scaled_xs) else: return np.cos(scaled_xs) seed_vectors = np.array([vector(i) for i in range(num_basis)]) return orthonormal_basis(seed_vectors, error=error) class GramSchmidtBasis(Basis): """ Class representing a Basis object whose vectors are calculated through a Gram-Schmidt orthogonalization procedure. """ def __init__(self, seed_vectors, error=None, expander=None,\ translation=None): """ Initializes the new GramSchmidtBasis object. seed_vectors: the vectors with which to generate further modes through the Gram-Schmidt orthogonalization procedure error: the error with which to define 'orthogonal' expander: if None, no expansion is applied otherwise, expander must be an Expander object. translation: if None, no constant additive is included in the results of calling this Basis. otherwise: should be a 1D numpy.ndarray of the same length as the seed vectors. 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daemon/lib/traceroute.py	shawnduong/CyberTrace	2	40371	<reponame>shawnduong/CyberTrace import subprocess def traceroute(dest: str) -> dict: """ Trace the route to some destination IP and return a dict of intermediates. In order to prevent the daemon itself from needing to run with elevated privileges, this is primarily handled by the system's traceroute utility. """ # Sanitize input. for char in dest: if char not in "ABCDEFabcdef12345567890.:": return -1 # Run system traceroute. p = subprocess.Popen(["traceroute", "-q 1", dest], stdout=subprocess.PIPE) d = p.stdout.read().decode("utf-8") hops = {} # Parse the output. for line in d.split("\n"): try: tokens = line.split() n = int(tokens[0]) if tokens[1] == "*": ip = "?" else: ip = tokens[2].strip("(").strip(")") hops[n] = ip except: pass return hops	[ 1, 529, 276, 1112, 420, 29958, 845, 1450, 299, 29884, 549, 29914, 29733, 495, 11591, 13, 5215, 1014, 5014, 13, 13, 1753, 16703, 261, 2663, 29898, 7854, 29901, 851, 29897, 1599, 9657, 29901, 13, 12, 15945, 29908, 13, 12, 11591, 278, 5782, 304, 777, 12551, 5641, 322, 736, 263, 9657, 310, 1006, 4210, 1078, 29889, 13, 12, 797, 1797, 304, 5557, 278, 1146, 9857, 3528, 515, 817, 292, 304, 1065, 411, 11858, 630, 13, 12, 22534, 488, 2710, 29892, 445, 338, 19434, 16459, 491, 278, 1788, 29915, 29879, 16703, 261, 2663, 19725, 29889, 13, 12, 15945, 29908, 13, 13, 12, 29937, 3087, 277, 675, 1881, 29889, 13, 12, 1454, 1373, 297, 2731, 29901, 13, 12, 12, 361, 1373, 451, 297, 376, 19658, 24405, 10736, 1753, 29896, 29906, 29941, 29946, 29945, 29945, 29953, 29955, 29947, 29929, 29900, 4898, 1115, 13, 12, 12, 12, 2457, 448, 29896, 13, 13, 12, 29937, 7525, 1788, 16703, 261, 2663, 29889, 13, 12, 29886, 353, 1014, 5014, 29889, 29925, 3150, 29898, 3366, 29873, 945, 261, 2663, 613, 11663, 29939, 29871, 29896, 613, 2731, 1402, 27591, 29922, 1491, 5014, 29889, 2227, 4162, 29897, 13, 12, 29881, 353, 282, 29889, 25393, 29889, 949, 2141, 13808, 703, 9420, 29899, 29947, 1159, 13, 13, 12, 29882, 3554, 353, 6571, 13, 13, 12, 29937, 20969, 278, 1962, 29889, 13, 12, 1454, 1196, 297, 270, 29889, 5451, 14182, 29876, 29908, 1125, 13, 13, 12, 12, 2202, 29901, 13, 12, 12, 12, 517, 12360, 353, 1196, 29889, 5451, 580, 13, 12, 12, 12, 29876, 353, 938, 29898, 517, 12360, 29961, 29900, 2314, 13, 13, 12, 12, 12, 361, 18897, 29961, 29896, 29962, 1275, 26345, 1115, 13, 12, 12, 12, 12, 666, 353, 376, 3026, 13, 12, 12, 12, 2870, 29901, 13, 12, 12, 12, 12, 666, 353, 18897, 29961, 29906, 1822, 17010, 703, 703, 467, 17010, 703, 25760, 13, 13, 12, 12, 12, 29882, 3554, 29961, 29876, 29962, 353, 10377, 13, 12, 12, 19499, 29901, 13, 12, 12, 12, 3364, 13, 13, 12, 2457, 298, 3554, 13, 13, 2 ]
test_api.py	atifar/mini-key-value	0	26779	def test_check_sanity(client): resp = client.get('/sanity') assert resp.status_code == 200 assert 'Sanity check passed.' == resp.data.decode() # 'list collections' tests def test_get_api_root(client): resp = client.get('/', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert 'keys_url' in resp_data assert len(resp_data) == 1 assert resp_data['keys_url'][-5:] == '/keys' def test_delete_api_root_not_allowed(client): resp = client.delete('/', content_type='application/json') assert resp.status_code == 405 # 'list keys' tests def test_get_empty_keys_list(client): resp = client.get('/keys', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert len(resp_data) == 0 def test_get_nonempty_keys_list(client, keys, add_to_keys): add_to_keys({'key': 'babboon', 'value': 'Larry'}) add_to_keys({'key': 'bees', 'value': ['Ann', 'Joe', 'Dee']}) resp = client.get('/keys', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert isinstance(resp_data, list) assert len(resp_data) == 2 for doc_idx in (0, 1): for k in ('key', 'http_url'): assert k in resp_data[doc_idx] if resp_data[doc_idx]['key'] == 'babboon': assert resp_data[doc_idx]['http_url'][-13:] == '/keys/babboon' else: assert resp_data[doc_idx]['http_url'][-10:] == '/keys/bees' def test_delete_on_keys_not_allowed(client): resp = client.delete('/keys', content_type='application/json') assert resp.status_code == 405 # 'get a key' tests def test_get_existing_key(client, keys, add_to_keys): add_to_keys({'key': 'babboon', 'value': 'Larry'}) add_to_keys({'key': 'bees', 'value': ['Ann', 'Joe', 'Dee']}) resp = client.get('/keys/bees', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert isinstance(resp_data, dict) for k in ('key', 'http_url', 'value'): assert k in resp_data assert resp_data['key'] == 'bees' assert resp_data['http_url'][-10:] == '/keys/bees' assert resp_data['value'] == ['Ann', 'Joe', 'Dee'] def test_get_nonexisting_key(client, keys): resp = client.get('/keys/bees', content_type='application/json') assert resp.status_code == 404 def test_post_on_a_key_not_allowed(client): resp = client.post('/keys/bees', content_type='application/json') assert resp.status_code == 405 # 'create a key' tests def test_create_new_key(client, keys): new_doc = {'key': 'oscillator', 'value': 'Colpitts'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 201 resp_data = resp.get_json() assert isinstance(resp_data, dict) for k in ('key', 'http_url', 'value'): assert k in resp_data assert resp_data['key'] == new_doc['key'] assert resp_data['value'] == new_doc['value'] assert resp_data['http_url'][-16:] == '/keys/oscillator' def test_create_duplicate_key(client, keys, add_to_keys): new_doc = {'key': 'oscillator', 'value': 'Colpitts'} add_to_keys(new_doc.copy()) resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == "Can't create duplicate key (oscillator)." def test_create_new_key_missing_key(client, keys): new_doc = {'value': 'Colpitts'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Please provide the missing "key" parameter!' def test_create_new_key_missing_value(client, keys): new_doc = {'key': 'oscillator'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Please provide the missing "value" ' \ 'parameter!' # 'update a key' tests def test_update_a_key_existing(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) update_value = {'value': ['Pierce', 'Hartley']} resp = client.put( '/keys/oscillator', json=update_value, content_type='application/json' ) assert resp.status_code == 204 def test_update_a_key_nonexisting(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) update_value = {'value': ['Pierce', 'Hartley']} resp = client.put( '/keys/gadget', json=update_value, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Update failed.' # 'delete a key' tests def test_delete_a_key_existing(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) resp = client.delete( '/keys/oscillator', content_type='application/json' ) assert resp.status_code == 204 def test_delete_a_key_nonexisting(client, keys): resp = client.delete( '/keys/oscillator', content_type='application/json' ) assert 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TSNE/clustering.py	KatherLab/Pathology_Adversarial	0	114995	<reponame>KatherLab/Pathology_Adversarial # -- coding: utf-8 -- """ Created on Tue Jul 13 2021 @author: dcifci """ import numpy as np import seaborn as sns import pandas as pd import matplotlib.pyplot as plt import matplotlib as mpl from sklearn.manifold import TSNE from dataclasses import dataclass from sklearn.decomposition import PCA @dataclass class DataClustering(): """A class for holding clustering objects""" name_project: str npy_feature_vectors: str npy_labels: str ss_im_names: str def load_data(self): self.df = pd.read_csv(self.ss_im_names) self.X = np.load(self.npy_feature_vectors) self.y = np.load(self.npy_labels) def cluster_tSNE(self): self.load_data() tsne = TSNE(n_components=2) X_2d = tsne.fit_transform(self.X) self.df["labels"] = self.y.T.reshape(-1) self.df["comp-1"] = X_2d[:,0] self.df["comp-2"] = X_2d[:,1] def cluster_PCA_tSNE(self): self.load_data() pca = PCA(n_components=50) pca_result = pca.fit_transform(self.X) tsne = TSNE(n_components=2, perplexity=5) X_2d = tsne.fit_transform(pca_result) self.df["labels"] = self.y.T.reshape(-1) self.df["comp-1"] = X_2d[:,0] self.df["comp-2"] = X_2d[:,1] def plot_scatter(self): plt.figure(figsize=(16,10)) n_classes = len(self.df["labels"].unique()) sns.scatterplot(x="comp-1", y="comp-2", hue=self.df.labels.tolist(), palette=sns.color_palette("hls", n_classes), data=self.df).set(title="T-SNE projection") #plt.show() plt.savefig("./out_visuals/out_scatter_dots_" + self.name_project + ".png") def plot_imgs(self): fig, ax = plt.subplots() plt.figure(figsize=(16,10)) x_min = int(self.df["comp-1"].min()) x_max = int(self.df["comp-1"].max()) y_min = int(self.df["comp-2"].min()) y_max = int(self.df["comp-2"].max()) for im in self.df["im_names"]: with mpl.cbook.get_sample_data(im) as file: arr_image = plt.imread(file) ax.set_xlim([x_min-30, x_max+30]) ax.set_ylim([y_min-30, y_max+30]) ax.set_title("t-SNE projection with images") 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src/citycode.py	masaminh/weatherapi	0	170616	"""市町村コード関係の関数群.""" from collections import namedtuple Urls = namedtuple('Urls', 'hourly') def get_cityname(code): """市町村名を取得する. Arguments: code {str} -- 市町村コード Returns: str -- 市町村名 """ if code != '01101': return None return "札幌市中央区" def get_tenkijp_urls(code): """tenki.jpのurlを取得する. Arguments: code {str} -- 市町村コード Returns: Urls -- tenki.jpのURL情報 """ if code != '01101': return None urls = Urls( hourly='https://tenki.jp/forecast/1/2/1400/1101/1hour.html') return urls def get_weathernews_urls(code): """weathernewsのurlを取得する. Arguments: code {str} -- 市町村コード Returns: Urls -- weathernewsのURL情報 """ if code != '01101': return None urls = Urls( hourly='https://weathernews.jp/onebox/tenki/hokkaido/01101/') return urls	[ 1, 9995, 30461, 30829, 30402, 30459, 30185, 30335, 31606, 231, 194, 133, 30199, 31606, 30354, 31829, 1213, 15945, 13, 13, 3166, 16250, 1053, 4257, 23583, 13, 13, 5983, 29879, 353, 4257, 23583, 877, 5983, 29879, 742, 525, 18721, 368, 1495, 13, 13, 13, 1753, 679, 29918, 12690, 978, 29898, 401, 1125, 13, 1678, 9995, 30461, 30829, 30402, 30548, 30396, 30683, 31050, 30427, 30332, 29889, 13, 13, 1678, 11842, 9331, 29901, 13, 4706, 775, 426, 710, 29913, 1192, 29871, 30461, 30829, 30402, 30459, 30185, 30335, 13, 13, 1678, 16969, 29901, 13, 4706, 851, 1192, 29871, 30461, 30829, 30402, 30548, 13, 13, 1678, 9995, 13, 1678, 565, 775, 2804, 525, 29900, 29896, 29896, 29900, 29896, 2396, 13, 4706, 736, 6213, 13, 13, 1678, 736, 376, 233, 159, 176, 232, 188, 143, 30461, 30275, 232, 167, 177, 30467, 29908, 13, 13, 13, 1753, 679, 29918, 841, 29895, 823, 29886, 29918, 26045, 29898, 401, 1125, 13, 1678, 9995, 841, 1984, 29889, 16865, 30199, 2271, 30396, 30683, 31050, 30427, 30332, 29889, 13, 13, 1678, 11842, 9331, 29901, 13, 4706, 775, 426, 710, 29913, 1192, 29871, 30461, 30829, 30402, 30459, 30185, 30335, 13, 13, 1678, 16969, 29901, 13, 4706, 501, 2096, 29879, 1192, 3006, 1984, 29889, 16865, 30199, 4219, 30993, 31519, 13, 13, 1678, 9995, 13, 1678, 565, 775, 2804, 525, 29900, 29896, 29896, 29900, 29896, 2396, 13, 4706, 736, 6213, 13, 13, 1678, 23942, 353, 501, 2096, 29879, 29898, 13, 4706, 7234, 368, 2433, 991, 597, 841, 1984, 29889, 16865, 29914, 1079, 4384, 29914, 29896, 29914, 29906, 29914, 29896, 29946, 29900, 29900, 29914, 29896, 29896, 29900, 29896, 29914, 29896, 18721, 29889, 1420, 1495, 13, 1678, 736, 23942, 13, 13, 13, 1753, 679, 29918, 705, 1624, 15753, 29918, 26045, 29898, 401, 1125, 13, 1678, 9995, 705, 1624, 15753, 30199, 2271, 30396, 30683, 31050, 30427, 30332, 29889, 13, 13, 1678, 11842, 9331, 29901, 13, 4706, 775, 426, 710, 29913, 1192, 29871, 30461, 30829, 30402, 30459, 30185, 30335, 13, 13, 1678, 16969, 29901, 13, 4706, 501, 2096, 29879, 1192, 14826, 15753, 30199, 4219, 30993, 31519, 13, 13, 1678, 9995, 13, 1678, 565, 775, 2804, 525, 29900, 29896, 29896, 29900, 29896, 2396, 13, 4706, 736, 6213, 13, 13, 1678, 23942, 353, 501, 2096, 29879, 29898, 13, 4706, 7234, 368, 2433, 991, 597, 705, 1624, 15753, 29889, 16865, 29914, 650, 1884, 29914, 841, 1984, 29914, 29882, 554, 1335, 1941, 29914, 29900, 29896, 29896, 29900, 29896, 29914, 1495, 13, 1678, 736, 23942, 13, 2 ]
main.py	chillum1718/EffcientNetV2	0	3054	<filename>main.py import argparse import csv import os import torch import tqdm from torch import distributed from torch.utils import data from torchvision import datasets from torchvision import transforms from nets import nn from utils import util data_dir = os.path.join('..', 'Dataset', 'IMAGENET') def batch(images, target, model, criterion=None): images = images.cuda() target = target.cuda() if criterion: with torch.cuda.amp.autocast(): loss = criterion(model(images), target) return loss else: return util.accuracy(model(images), target, top_k=(1, 5)) def train(args): epochs = 350 batch_size = 288 util.set_seeds(args.rank) model = nn.EfficientNet().cuda() lr = batch_size * torch.cuda.device_count() * 0.256 / 4096 optimizer = nn.RMSprop(util.add_weight_decay(model), lr, 0.9, 1e-3, momentum=0.9) ema = nn.EMA(model) if args.distributed: model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank]) else: model = torch.nn.DataParallel(model) criterion = nn.CrossEntropyLoss().cuda() normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) dataset = datasets.ImageFolder(os.path.join(data_dir, 'train'), transforms.Compose([util.RandomResize(), transforms.ColorJitter(0.4, 0.4, 0.4), transforms.RandomHorizontalFlip(), util.RandomAugment(), transforms.ToTensor(), normalize])) if args.distributed: sampler = torch.utils.data.distributed.DistributedSampler(dataset) else: sampler = None loader = data.DataLoader(dataset, batch_size, sampler=sampler, num_workers=8, pin_memory=True) scheduler = nn.StepLR(optimizer) amp_scale = torch.cuda.amp.GradScaler() with open(f'weights/{scheduler.__str__()}.csv', 'w') as f: if args.local_rank == 0: writer = csv.DictWriter(f, fieldnames=['epoch', 'acc@1', 'acc@5']) writer.writeheader() best_acc1 = 0 for epoch in range(0, epochs): if args.distributed: sampler.set_epoch(epoch) if args.local_rank == 0: print(('\n' + '%10s' * 2) % ('epoch', 'loss')) bar = tqdm.tqdm(loader, total=len(loader)) else: bar = loader model.train() for images, target in bar: loss = batch(images, target, model, criterion) optimizer.zero_grad() amp_scale.scale(loss).backward() amp_scale.step(optimizer) amp_scale.update() ema.update(model) torch.cuda.synchronize() if args.local_rank == 0: bar.set_description(('%10s' + '%10.4g') % ('%g/%g' % (epoch + 1, epochs), loss)) scheduler.step(epoch + 1) if args.local_rank == 0: acc1, acc5 = test(ema.model.eval()) writer.writerow({'acc@1': str(f'{acc1:.3f}'), 'acc@5': str(f'{acc5:.3f}'), 'epoch': str(epoch + 1).zfill(3)}) util.save_checkpoint({'state_dict': ema.model.state_dict()}, acc1 > best_acc1) best_acc1 = max(acc1, best_acc1) if args.distributed: torch.distributed.destroy_process_group() torch.cuda.empty_cache() def test(model=None): if model is None: model = nn.EfficientNet() model.load_state_dict(torch.load('weights/best.pt', 'cpu')['state_dict']) model = model.cuda() model.eval() normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) dataset = datasets.ImageFolder(os.path.join(data_dir, 'val'), transforms.Compose([transforms.Resize(416), transforms.CenterCrop(384), transforms.ToTensor(), normalize])) loader = data.DataLoader(dataset, 48, num_workers=os.cpu_count(), pin_memory=True) top1 = util.AverageMeter() top5 = util.AverageMeter() with torch.no_grad(): for images, target in tqdm.tqdm(loader, ('%10s' * 2) % ('acc@1', 'acc@5')): acc1, acc5 = batch(images, target, model) torch.cuda.synchronize() top1.update(acc1.item(), images.size(0)) top5.update(acc5.item(), images.size(0)) acc1, acc5 = top1.avg, top5.avg print('%10.3g' * 2 % (acc1, acc5)) if model is None: torch.cuda.empty_cache() else: return acc1, acc5 def print_parameters(): model = nn.EfficientNet().eval() _ = model(torch.zeros(1, 3, 224, 224)) params = sum(p.numel() for p in model.parameters()) print(f'Number of parameters: {int(params)}') def benchmark(): shape = (1, 3, 384, 384) util.torch2onnx(nn.EfficientNet().export().eval(), shape) util.onnx2caffe() util.print_benchmark(shape) def main(): # python -m torch.distributed.launch --nproc_per_node=3 main.py --train parser = argparse.ArgumentParser() parser.add_argument("--local_rank", default=0, type=int) parser.add_argument('--benchmark', action='store_true') parser.add_argument('--train', action='store_true') parser.add_argument('--test', action='store_true') args = parser.parse_args() args.distributed = False args.rank = 0 if 'WORLD_SIZE' in os.environ: args.distributed = int(os.environ['WORLD_SIZE']) > 1 if args.distributed: torch.cuda.set_device(args.local_rank) torch.distributed.init_process_group(backend='nccl', init_method='env://') args.rank = torch.distributed.get_rank() if args.local_rank == 0: if not os.path.exists('weights'): os.makedirs('weights') if args.local_rank == 0: print_parameters() if args.benchmark: benchmark() if args.train: train(args) if args.test: test() if __name__ == '__main__': 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test/functional/test-framework/storage_devices/disk.py	josehu07/open-cas-linux-mf	2	85835	<filename>test/functional/test-framework/storage_devices/disk.py # # Copyright(c) 2019-2020 Intel Corporation # SPDX-License-Identifier: BSD-3-Clause-Clear # import itertools from enum import IntEnum from test_utils import disk_finder from test_utils.output import CmdException from test_utils.size import Unit from test_tools import disk_utils, fs_utils from storage_devices.device import Device from datetime import timedelta from test_utils.os_utils import wait from core.test_run import TestRun import json import re class DiskType(IntEnum): hdd = 0 hdd4k = 1 sata = 2 nand = 3 optane = 4 class DiskTypeSetBase: def resolved(self): raise NotImplementedError() def types(self): raise NotImplementedError() def json(self): return json.dumps({ "type": "set", "values": [t.name for t in self.types()] }) def __lt__(self, other): return min(self.types()) < min(other.types()) def __le__(self, other): return min(self.types()) <= min(other.types()) def __eq__(self, other): return min(self.types()) == min(other.types()) def __ne__(self, other): return min(self.types()) != min(other.types()) def __gt__(self, other): return min(self.types()) > min(other.types()) def __ge__(self, other): return min(self.types()) >= min(other.types()) class DiskTypeSet(DiskTypeSetBase): def __init__(self, args): self.__types = set(args) def resolved(self): return True def types(self): return self.__types class DiskTypeLowerThan(DiskTypeSetBase): def __init__(self, disk_name): self.__disk_name = disk_name def resolved(self): return self.__disk_name in TestRun.disks def types(self): if not self.resolved(): raise LookupError("Disk type not resolved!") disk_type = TestRun.disks[self.__disk_name].disk_type return set(filter(lambda d: d < disk_type, [DiskType])) def json(self): return json.dumps({ "type": "operator", "name": "lt", "args": [self.__disk_name] }) class Disk(Device): def __init__( self, path, disk_type: DiskType, serial_number, block_size, ): Device.__init__(self, path) self.device_name = path.split('/')[-1] self.serial_number = serial_number self.block_size = Unit(block_size) self.disk_type = disk_type self.partitions = [] def create_partitions( self, sizes: [], partition_table_type=disk_utils.PartitionTable.gpt): disk_utils.create_partitions(self, sizes, partition_table_type) def umount_all_partitions(self): TestRun.LOGGER.info( f"Umounting all partitions from: {self.system_path}") cmd = f'umount -l {self.system_path}?' TestRun.executor.run(cmd) def remove_partitions(self): for part in self.partitions: if part.is_mounted(): part.unmount() if disk_utils.remove_partitions(self): self.partitions.clear() def is_detected(self): if self.serial_number: serial_numbers = disk_finder.get_all_serial_numbers() if self.serial_number not in serial_numbers: return False else: self.device_name = serial_numbers[self.serial_number] self.system_path = f"/dev/{self.device_name}" for part in self.partitions: part.system_path = disk_utils.get_partition_path( part.parent_device.system_path, part.number) return True elif self.system_path: output = fs_utils.ls_item(f"{self.system_path}") return fs_utils.parse_ls_output(output)[0] is not None raise Exception("Couldn't check if device is detected by the system") def wait_for_plug_status(self, should_be_visible): if not wait(lambda: should_be_visible == self.is_detected(), timedelta(minutes=1), timedelta(seconds=1)): raise Exception(f"Timeout occurred while tying to " f"{'plug' if should_be_visible else 'unplug'} disk.") def plug(self): if self.is_detected(): return self.execute_plug_command() self.wait_for_plug_status(True) def unplug(self): if not self.is_detected(): return if not self.device_name: raise Exception("Couldn't unplug disk without disk id in /dev/.") self.execute_unplug_command() self.wait_for_plug_status(False) if self.serial_number: self.device_name = None @staticmethod def plug_all_disks(): TestRun.executor.run_expect_success(NvmeDisk.plug_all_command) TestRun.executor.run_expect_success(SataDisk.plug_all_command) def __str__(self): disk_str = f'system path: {self.system_path}, type: {self.disk_type}, ' \ f'serial: {self.serial_number}, size: {self.size}, ' \ f'block size: {self.block_size}, partitions:\n' for part in self.partitions: disk_str += f'\t{part}' return disk_str @staticmethod def create_disk(path, disk_type: DiskType, serial_number, block_size): if disk_type is DiskType.nand or disk_type is DiskType.optane: return NvmeDisk(path, disk_type, serial_number, block_size) else: return SataDisk(path, disk_type, serial_number, block_size) class NvmeDisk(Disk): plug_all_command = "echo 1 > /sys/bus/pci/rescan" def __init__(self, path, disk_type, serial_number, block_size): Disk.__init__(self, path, disk_type, serial_number, block_size) def execute_plug_command(self): TestRun.executor.run_expect_success(NvmeDisk.plug_all_command) def execute_unplug_command(self): if TestRun.executor.run( f"echo 1 > /sys/block/{self.device_name}/device/remove").exit_code != 0: output = TestRun.executor.run( f"echo 1 > /sys/block/{self.device_name}/device/device/remove") if output.exit_code != 0: raise CmdException(f"Failed to unplug PCI disk using sysfs.", output) class SataDisk(Disk): plug_all_command = "for i in $(find -H /sys/devices/ -path '/scsi_host//scan' -type f); " \ "do echo '- - -' > $i; done;" def __init__(self, path, disk_type, serial_number, block_size): self.plug_command = SataDisk.plug_all_command Disk.__init__(self, path, disk_type, serial_number, block_size) def execute_plug_command(self): TestRun.executor.run_expect_success(self.plug_command) def execute_unplug_command(self): TestRun.executor.run_expect_success( f"echo 1 > {self.get_sysfs_properties(self.device_name).full_path}/device/delete") def get_sysfs_properties(self, device_name): ls_command = f"$(find -H /sys/devices/ -name {device_name} -type d)" output = fs_utils.ls_item(f"{ls_command}") sysfs_addr = fs_utils.parse_ls_output(output)[0] if not sysfs_addr: raise Exception(f"Failed to find sysfs address: ls -l {ls_command}") dirs = sysfs_addr.full_path.split('/') scsi_address = dirs[-3] matches = re.search( r"^(?P<controller>\d+)[-:](?P<port>\d+)[-:](?P<target>\d+)[-:](?P<lun>\d+)$", scsi_address) controller_id = matches["controller"] port_id = matches["port"] target_id = matches["target"] lun = matches["lun"] host_path = "/".join(itertools.takewhile(lambda x: not x.startswith("host"), dirs)) self.plug_command = f"echo '{port_id} 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Python3/0947-Most-Stones-Removed-with-Same-Row-or-Column/soln.py	wyaadarsh/LeetCode-Solutions	5	1608142	class Solution: def removeStones(self, stones): """ :type stones: List[List[int]] :rtype: int """ parent = {} def find(x): if x != parent[x]: parent[x] = find(parent[x]) return parent[x] def union(x, y): parent.setdefault(x, x) parent.setdefault(y, y) parent[find(x)] = find(y) for x, y in stones: union(x, ~y) return len(stones) - len({find(x) for x in parent})	[ 1, 770, 24380, 29901, 13, 1678, 822, 3349, 855, 2873, 29898, 1311, 29892, 25702, 1125, 13, 4706, 9995, 13, 4706, 584, 1853, 25702, 29901, 2391, 29961, 1293, 29961, 524, 5262, 13, 4706, 584, 29878, 1853, 29901, 938, 13, 4706, 9995, 13, 4706, 3847, 353, 6571, 13, 4706, 822, 1284, 29898, 29916, 1125, 13, 9651, 565, 921, 2804, 3847, 29961, 29916, 5387, 13, 18884, 3847, 29961, 29916, 29962, 353, 1284, 29898, 3560, 29961, 29916, 2314, 13, 9651, 736, 3847, 29961, 29916, 29962, 13, 4706, 822, 9833, 29898, 29916, 29892, 343, 1125, 13, 9651, 3847, 29889, 842, 4381, 29898, 29916, 29892, 921, 29897, 13, 9651, 3847, 29889, 842, 4381, 29898, 29891, 29892, 343, 29897, 13, 9651, 3847, 29961, 2886, 29898, 29916, 4638, 353, 1284, 29898, 29891, 29897, 13, 4706, 363, 921, 29892, 343, 297, 25702, 29901, 13, 9651, 9833, 29898, 29916, 29892, 3695, 29891, 29897, 13, 4706, 736, 7431, 29898, 303, 2873, 29897, 448, 7431, 3319, 2886, 29898, 29916, 29897, 363, 921, 297, 3847, 1800, 2 ]
clearfile.py	redcapattitide/Python	0	134225	f = open('C:/Users/Tom/Documents/Python/Bot/Receptura/Recept/Recept/bin/Release/moves_info.txt','w',encoding='UTF-8') f.close()	[ 1, 29871, 13, 29888, 353, 1722, 877, 29907, 8419, 5959, 29914, 21599, 29914, 20128, 29914, 11980, 29914, 29933, 327, 29914, 1123, 1547, 2002, 29914, 1123, 1547, 29914, 1123, 1547, 29914, 2109, 29914, 19729, 29914, 13529, 267, 29918, 3888, 29889, 3945, 3788, 29893, 742, 22331, 2433, 10496, 29899, 29947, 1495, 13, 29888, 29889, 5358, 580, 13, 2 ]
pgmpy/factors/base.py	Stoffle/pgmpy	0	135871	from abc import abstractmethod from pgmpy.extern.six.moves import reduce class BaseFactor(object): """ Base class for Factors. Any Factor implementation should inherit this class. """ def __init__(self, args, kwargs): pass @abstractmethod def is_valid_cpd(self): pass def factor_product(args): """ Returns factor product over `args`. Parameters ---------- args: `BaseFactor` instances. factors to be multiplied Returns ------- BaseFactor: `BaseFactor` representing factor product over all the `BaseFactor` instances in args. Examples -------- >>> from pgmpy.factors.discrete import DiscreteFactor >>> from pgmpy.factors import factor_product >>> phi1 = DiscreteFactor(['x1', 'x2', 'x3'], [2, 3, 2], range(12)) >>> phi2 = DiscreteFactor(['x3', 'x4', 'x1'], [2, 2, 2], range(8)) >>> phi = factor_product(phi1, phi2) >>> phi.variables ['x1', 'x2', 'x3', 'x4'] >>> phi.cardinality array([2, 3, 2, 2]) >>> phi.values array([[[[ 0, 0], [ 4, 6]], [[ 0, 4], [12, 18]], [[ 0, 8], [20, 30]]], [[[ 6, 18], [35, 49]], [[ 8, 24], [45, 63]], [[10, 30], [55, 77]]]]) """ if not all(isinstance(phi, BaseFactor) for phi in args): raise TypeError("Arguments must be factors") # Check if all of the arguments are of the same type elif len(set(map(type, args))) != 1: raise NotImplementedError( "All the args are expected to ", "be instances of the same factor class." ) return reduce(lambda phi1, phi2: phi1 * phi2, args) def factor_divide(phi1, phi2): """ Returns `DiscreteFactor` representing `phi1 / phi2`. Parameters ---------- phi1: Factor The Dividend. phi2: Factor The Divisor. Returns ------- DiscreteFactor: `DiscreteFactor` representing factor division `phi1 / phi2`. Examples -------- >>> from pgmpy.factors.discrete import DiscreteFactor >>> from pgmpy.factors import factor_product >>> phi1 = DiscreteFactor(['x1', 'x2', 'x3'], [2, 3, 2], range(12)) >>> phi2 = DiscreteFactor(['x3', 'x1'], [2, 2], range(1, 5)) >>> phi = factor_divide(phi1, phi2) >>> phi.variables ['x1', 'x2', 'x3'] >>> phi.cardinality array([2, 3, 2]) >>> phi.values array([[[ 0. , 0.33333333], [ 2. , 1. ], [ 4. , 1.66666667]], [[ 3. , 1.75 ], [ 4. , 2.25 ], [ 5. , 2.75 ]]]) """ if not isinstance(phi1, BaseFactor) or not isinstance(phi2, BaseFactor): raise TypeError("phi1 and phi2 should be factors instances") # Check if all of the arguments are of the same type elif type(phi1) != type(phi2): raise NotImplementedError( "All the args are expected to be instances", "of the same factor class." ) return phi1.divide(phi2, inplace=False)	[ 1, 515, 25638, 1053, 9846, 5696, 13, 13, 3166, 23822, 1526, 29891, 29889, 735, 725, 29889, 28319, 29889, 13529, 267, 1053, 10032, 13, 13, 13, 1990, 7399, 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src/utils.py	headout/dagen-airflow	2	147251	<filename>src/utils.py __loader = None def get_template_loader(): from dagen.loader import TemplateLoader # Avoid circular imports global __loader if __loader is None: __loader = TemplateLoader() return __loader def get_managed_dags(): loader = get_template_loader() if not loader.template_classes: loader.load_templates() return loader.get_managed_dags() def refresh_dagen_templates(): loader = get_template_loader() loader.load_templates(only_if_updated=False)	[ 1, 529, 9507, 29958, 4351, 29914, 13239, 29889, 2272, 13, 1649, 12657, 353, 6213, 13, 13, 13, 1753, 679, 29918, 6886, 29918, 12657, 7295, 13, 1678, 515, 270, 5370, 29889, 12657, 1053, 25663, 10036, 29871, 396, 319, 5405, 19308, 24802, 13, 13, 1678, 5534, 4770, 12657, 13, 1678, 565, 4770, 12657, 338, 6213, 29901, 13, 4706, 4770, 12657, 353, 25663, 10036, 580, 13, 1678, 736, 4770, 12657, 13, 13, 13, 1753, 679, 29918, 25240, 29918, 29881, 810, 7295, 13, 1678, 23466, 353, 679, 29918, 6886, 29918, 12657, 580, 13, 1678, 565, 451, 23466, 29889, 6886, 29918, 13203, 29901, 13, 4706, 23466, 29889, 1359, 29918, 20943, 580, 13, 1678, 736, 23466, 29889, 657, 29918, 25240, 29918, 29881, 810, 580, 13, 13, 13, 1753, 11086, 29918, 29881, 5370, 29918, 20943, 7295, 13, 1678, 23466, 353, 679, 29918, 6886, 29918, 12657, 580, 13, 1678, 23466, 29889, 1359, 29918, 20943, 29898, 6194, 29918, 361, 29918, 21402, 29922, 8824, 29897, 13, 2 ]
tess_exoplanet_search/jobs.py	jbcurtin/bert-etl-tess-exoplanet-search	0	68329	from bert import binding, utils, constants @binding.follow('noop') def create_data(): work_queue, done_queue, ologger = utils.comm_binders(create_data) for idx in range(0, 100): done_queue.put({ 'idx': idx }) @binding.follow(create_data, pipeline_type=constants.PipelineType.CONCURRENT) def calculate_data(): import math work_queue, done_queue, ologger = utils.comm_binders(calculate_data) for details in work_queue: details['calculated-result'] = math.pow(details['idx'], 2) done_queue.put(details) @binding.follow(calculate_data, pipeline_type=constants.PipelineType.CONCURRENT) def variation(): work_queue, done_queue, ologger = utils.comm_binders(variation) for details in work_queue: for key, value in details.items(): ologger.info(f'Key[{key}], Value[{value}], Alteration[{value % 5}]')	[ 1, 515, 289, 814, 1053, 9956, 29892, 3667, 29879, 29892, 17727, 13, 13, 29992, 19672, 29889, 23031, 877, 1217, 459, 1495, 13, 1753, 1653, 29918, 1272, 7295, 13, 1678, 664, 29918, 9990, 29892, 2309, 29918, 9990, 29892, 288, 21707, 353, 3667, 29879, 29889, 2055, 29918, 5355, 414, 29898, 3258, 29918, 1272, 29897, 13, 13, 1678, 363, 22645, 297, 3464, 29898, 29900, 29892, 29871, 29896, 29900, 29900, 1125, 13, 4706, 2309, 29918, 9990, 29889, 649, 3319, 13, 9651, 525, 13140, 2396, 22645, 13, 4706, 5615, 13, 13, 29992, 19672, 29889, 23031, 29898, 3258, 29918, 1272, 29892, 16439, 29918, 1853, 29922, 3075, 1934, 29889, 29925, 23828, 1542, 29889, 6007, 22484, 29450, 29897, 13, 1753, 8147, 29918, 1272, 7295, 13, 1678, 1053, 5844, 13, 13, 1678, 664, 29918, 9990, 29892, 2309, 29918, 9990, 29892, 288, 21707, 353, 3667, 29879, 29889, 2055, 29918, 5355, 414, 29898, 15807, 403, 29918, 1272, 29897, 13, 13, 1678, 363, 4902, 297, 664, 29918, 9990, 29901, 13, 4706, 4902, 1839, 15807, 630, 29899, 2914, 2033, 353, 5844, 29889, 12248, 29898, 14144, 1839, 13140, 7464, 29871, 29906, 29897, 13, 4706, 2309, 29918, 9990, 29889, 649, 29898, 14144, 29897, 13, 13, 29992, 19672, 29889, 23031, 29898, 15807, 403, 29918, 1272, 29892, 16439, 29918, 1853, 29922, 3075, 1934, 29889, 29925, 23828, 1542, 29889, 6007, 22484, 29450, 29897, 13, 1753, 19262, 7295, 13, 1678, 664, 29918, 9990, 29892, 2309, 29918, 9990, 29892, 288, 21707, 353, 3667, 29879, 29889, 2055, 29918, 5355, 414, 29898, 5927, 362, 29897, 13, 13, 1678, 363, 4902, 297, 664, 29918, 9990, 29901, 13, 4706, 363, 1820, 29892, 995, 297, 4902, 29889, 7076, 7295, 13, 9651, 288, 21707, 29889, 3888, 29898, 29888, 29915, 2558, 19660, 1989, 29913, 1402, 7865, 19660, 1767, 29913, 1402, 20561, 362, 19660, 1767, 1273, 29871, 29945, 6525, 1495, 13, 13, 2 ]
api/beers/migrations/0031_matchfilter.py	haavardnk/Vinmonopolet-x-Untappd	0	178631	<filename>api/beers/migrations/0031_matchfilter.py<gh_stars>0 # Generated by Django 3.1.4 on 2020-12-11 07:30 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('beers', '0030_beer_match_manually'), ] operations = [ migrations.CreateModel( name='MatchFilter', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ], ), ]	[ 1, 529, 9507, 29958, 2754, 29914, 915, 414, 29914, 26983, 800, 29914, 29900, 29900, 29941, 29896, 29918, 4352, 4572, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 3251, 630, 491, 15337, 29871, 29941, 29889, 29896, 29889, 29946, 373, 29871, 29906, 29900, 29906, 29900, 29899, 29896, 29906, 29899, 29896, 29896, 29871, 29900, 29955, 29901, 29941, 29900, 30004, 13, 30004, 13, 3166, 9557, 29889, 2585, 1053, 9725, 800, 29892, 4733, 30004, 13, 30004, 13, 30004, 13, 1990, 341, 16783, 29898, 26983, 800, 29889, 29924, 16783, 1125, 30004, 13, 30004, 13, 1678, 9962, 353, 518, 30004, 13, 4706, 6702, 915, 414, 742, 525, 29900, 29900, 29941, 29900, 29918, 915, 261, 29918, 4352, 29918, 1171, 1474, 5477, 30004, 13, 1678, 4514, 30004, 13, 30004, 13, 1678, 6931, 353, 518, 30004, 13, 4706, 9725, 800, 29889, 4391, 3195, 29898, 30004, 13, 9651, 1024, 2433, 9652, 5072, 23592, 13, 9651, 4235, 11759, 30004, 13, 18884, 6702, 333, 742, 4733, 29889, 12300, 3073, 29898, 6921, 29918, 11600, 29922, 5574, 29892, 7601, 29918, 1989, 29922, 5574, 29892, 28755, 29922, 8824, 29892, 26952, 29918, 978, 2433, 1367, 1495, 511, 30004, 13, 18884, 6702, 978, 742, 4733, 29889, 27890, 29898, 3317, 29918, 2848, 29922, 29945, 29900, 8243, 30004, 13, 9651, 21251, 30004, 13, 4706, 10353, 30004, 13, 1678, 4514, 30004, 13, 2 ]
migrations/versions/e1c435b9e9dc_.py	vipshae/todo-lister	0	20381	<reponame>vipshae/todo-lister """empty message Revision ID: e1c435b9e9dc Revises: <PASSWORD> Create Date: 2020-06-11 14:22:00.453626 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'e1c435b9e9dc' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.alter_column('todolists', 'completed', existing_type=sa.BOOLEAN(), nullable=False) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.alter_column('todolists', 'completed', existing_type=sa.BOOLEAN(), nullable=True) # ### end Alembic commands ###	[ 1, 529, 276, 1112, 420, 29958, 1403, 567, 2350, 29872, 29914, 29873, 8144, 29899, 29880, 1531, 13, 15945, 29908, 6310, 2643, 13, 13, 1123, 4924, 3553, 29901, 321, 29896, 29883, 29946, 29941, 29945, 29890, 29929, 29872, 29929, 13891, 13, 1123, 1730, 267, 29901, 529, 25711, 17013, 29958, 13, 4391, 4712, 29901, 29871, 29906, 29900, 29906, 29900, 29899, 29900, 29953, 29899, 29896, 29896, 29871, 29896, 29946, 29901, 29906, 29906, 29901, 29900, 29900, 29889, 29946, 29945, 29941, 29953, 29906, 29953, 13, 13, 15945, 29908, 13, 3166, 20712, 29890, 293, 1053, 1015, 13, 5215, 4576, 284, 305, 6764, 408, 872, 13, 13, 13, 29937, 26554, 2893, 14903, 29892, 1304, 491, 319, 2409, 29890, 293, 29889, 13, 276, 4924, 353, 525, 29872, 29896, 29883, 29946, 29941, 29945, 29890, 29929, 29872, 29929, 13891, 29915, 13, 3204, 29918, 276, 4924, 353, 12801, 25711, 17013, 16299, 13, 17519, 29918, 21134, 353, 6213, 13, 2716, 1975, 29918, 265, 353, 6213, 13, 13, 13, 1753, 14955, 7295, 13, 1678, 396, 835, 8260, 4469, 5759, 491, 319, 2409, 29890, 293, 448, 3113, 10365, 29991, 835, 13, 1678, 1015, 29889, 13794, 29918, 4914, 877, 20034, 324, 2879, 742, 525, 5729, 9446, 742, 13, 1669, 5923, 29918, 1853, 29922, 4977, 29889, 8456, 29949, 1307, 2190, 3285, 13, 1669, 1870, 519, 29922, 8824, 29897, 13, 1678, 396, 835, 1095, 319, 2409, 29890, 293, 8260, 835, 13, 13, 13, 1753, 1623, 8228, 7295, 13, 1678, 396, 835, 8260, 4469, 5759, 491, 319, 2409, 29890, 293, 448, 3113, 10365, 29991, 835, 13, 1678, 1015, 29889, 13794, 29918, 4914, 877, 20034, 324, 2879, 742, 525, 5729, 9446, 742, 13, 1669, 5923, 29918, 1853, 29922, 4977, 29889, 8456, 29949, 1307, 2190, 3285, 13, 1669, 1870, 519, 29922, 5574, 29897, 13, 1678, 396, 835, 1095, 319, 2409, 29890, 293, 8260, 835, 13, 2 ]
starbursts/plots/mpl.sr_fe_5Gyr_burst.py	rcooke-ast/VICE	22	124896	import visuals import matplotlib.pyplot as plt import vice import sys def plot_sr_fe_tracks(ax): plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun", "sr", "crimson", '-') plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun", "fe", "black", ':') plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun_riaexp", "fe", "black", '--') plot_legend(ax) def plot_track(ax, name, ref, color, linestyle): """ Plots [O/X]-[X/H] tracks on a matplotlib subplot Args: ===== ax: The name of the subplot name: The name of the VICE output ref: The symbol for the reference element color: The color of the line linestyle: The linestyle to use """ out = vice.output(name) ax.plot(out.history["[%s/h]" % (ref)], out.history["[o/%s]" % (ref)], c = visuals.colors()[color], linestyle = linestyle) def plot_legend(ax): lines = 3 * [None] linestyles = ['-', ':', '--'] colors = ["red", "black", "black"] labels = ["Sr", r"Fe; $R_\text{Ia}\propto t^{-1.1}$", r"Fe; $R_\text{Ia}\propto e^{-t/\tau_\text{Ia}}$"] for i in range(3): lines[i] = ax.plot([1, 2], [1, 2], c = visuals.colors()[colors[i]], linestyle = linestyles[i], label = labels[i])[0] leg = ax.legend(loc = visuals.mpl_loc()["lower left"], ncol = 1, bbox_to_anchor = (0.01, 0.01), frameon = False) for i in range(3): lines[i].remove() if __name__ == "__main__": ax = visuals.subplots(1, 1) ax.set_xlabel("[X/H]") ax.set_ylabel("[O/X]") plot_sr_fe_tracks(ax) ax.set_xlim([-1.7, 0.1]) ax.set_ylim([0., 0.6]) plt.tight_layout() plt.savefig(sys.argv[1]) plt.clf()	[ 1, 29871, 13, 5215, 7604, 29879, 13, 5215, 22889, 29889, 2272, 5317, 408, 14770, 13, 5215, 11289, 13, 5215, 10876, 13, 13, 1753, 6492, 29918, 21935, 29918, 1725, 29918, 3018, 4684, 29898, 1165, 1125, 13, 12, 5317, 29918, 11294, 29898, 1165, 29892, 376, 21546, 3601, 8250, 29914, 29879, 566, 1145, 29918, 29945, 29954, 4316, 29918, 29945, 29872, 29929, 29924, 11445, 613, 376, 21935, 613, 376, 29883, 5632, 1100, 613, 17411, 1495, 13, 12, 5317, 29918, 11294, 29898, 1165, 29892, 376, 21546, 3601, 8250, 29914, 29879, 566, 1145, 29918, 29945, 29954, 4316, 29918, 29945, 29872, 29929, 29924, 11445, 613, 376, 1725, 613, 376, 8517, 613, 525, 29901, 1495, 13, 12, 5317, 29918, 11294, 29898, 1165, 29892, 376, 21546, 3601, 8250, 29914, 29879, 566, 1145, 29918, 29945, 29954, 4316, 29918, 29945, 29872, 29929, 29924, 11445, 29918, 2849, 4548, 613, 376, 1725, 613, 13, 12, 12, 29908, 8517, 613, 525, 489, 1495, 13, 12, 5317, 29918, 26172, 29898, 1165, 29897, 13, 13, 1753, 6492, 29918, 11294, 29898, 1165, 29892, 1024, 29892, 2143, 29892, 2927, 29892, 6276, 342, 1508, 1125, 13, 12, 15945, 29908, 13, 12, 3247, 1862, 518, 29949, 29914, 29990, 29962, 29899, 29961, 29990, 29914, 29950, 29962, 16257, 373, 263, 22889, 1014, 5317, 13, 13, 12, 7883, 29901, 13, 12, 2751, 29922, 13, 12, 1165, 29901, 12, 12, 12, 12, 1576, 1024, 310, 278, 1014, 5317, 13, 12, 978, 29901, 29871, 12, 12, 12, 1576, 1024, 310, 278, 478, 12107, 1962, 13, 12, 999, 29901, 29871, 12, 12, 12, 1576, 5829, 363, 278, 3407, 1543, 13, 12, 2780, 29901, 29871, 12, 12, 12, 1576, 2927, 310, 278, 1196, 13, 12, 1915, 342, 1508, 29901, 29871, 12, 12, 1576, 6276, 342, 1508, 304, 671, 13, 12, 15945, 29908, 13, 12, 449, 353, 11289, 29889, 4905, 29898, 978, 29897, 13, 12, 1165, 29889, 5317, 29898, 449, 29889, 18434, 3366, 29961, 29995, 29879, 29914, 29882, 18017, 1273, 313, 999, 29897, 1402, 714, 29889, 18434, 3366, 29961, 29877, 22584, 29879, 18017, 1273, 313, 999, 29897, 1402, 13, 12, 12, 29883, 353, 7604, 29879, 29889, 27703, 580, 29961, 2780, 1402, 6276, 342, 1508, 353, 6276, 342, 1508, 29897, 13, 13, 1753, 6492, 29918, 26172, 29898, 1165, 1125, 13, 12, 9012, 353, 29871, 29941, 334, 518, 8516, 29962, 13, 12, 1915, 342, 5577, 353, 6024, 29899, 742, 525, 29901, 742, 525, 489, 2033, 13, 12, 27703, 353, 6796, 1127, 613, 376, 8517, 613, 376, 8517, 3108, 13, 12, 21134, 353, 6796, 29903, 29878, 613, 364, 29908, 8263, 29936, 395, 29934, 3187, 726, 29912, 29902, 29874, 1012, 771, 24070, 260, 3426, 29896, 29889, 29896, 1042, 613, 13, 12, 12, 29878, 29908, 8263, 29936, 395, 29934, 3187, 726, 29912, 29902, 29874, 1012, 771, 24070, 321, 3426, 29873, 7998, 4722, 3187, 726, 29912, 29902, 29874, 7920, 3108, 13, 12, 1454, 474, 297, 3464, 29898, 29941, 1125, 13, 12, 12, 9012, 29961, 29875, 29962, 353, 4853, 29889, 5317, 4197, 29896, 29892, 29871, 29906, 1402, 518, 29896, 29892, 29871, 29906, 1402, 274, 353, 7604, 29879, 29889, 27703, 580, 29961, 27703, 29961, 29875, 20526, 13, 12, 12, 12, 1915, 342, 1508, 353, 6276, 342, 5577, 29961, 29875, 1402, 3858, 353, 11073, 29961, 29875, 2314, 29961, 29900, 29962, 13, 12, 1397, 353, 4853, 29889, 26172, 29898, 2029, 353, 7604, 29879, 29889, 29885, 572, 29918, 2029, 580, 3366, 13609, 2175, 12436, 302, 1054, 353, 29871, 29896, 29892, 13, 12, 12, 29890, 1884, 29918, 517, 29918, 25367, 353, 313, 29900, 29889, 29900, 29896, 29892, 29871, 29900, 29889, 29900, 29896, 511, 3515, 265, 353, 7700, 29897, 13, 12, 1454, 474, 297, 3464, 29898, 29941, 1125, 13, 12, 12, 9012, 29961, 29875, 1822, 5992, 580, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 12, 1165, 353, 7604, 29879, 29889, 1491, 26762, 29898, 29896, 29892, 29871, 29896, 29897, 13, 12, 1165, 29889, 842, 29918, 29916, 1643, 703, 29961, 29990, 29914, 29950, 29962, 1159, 13, 12, 1165, 29889, 842, 29918, 29891, 1643, 703, 29961, 29949, 29914, 29990, 29962, 1159, 13, 12, 5317, 29918, 21935, 29918, 1725, 29918, 3018, 4684, 29898, 1165, 29897, 13, 12, 1165, 29889, 842, 29918, 29916, 2576, 4197, 29899, 29896, 29889, 29955, 29892, 29871, 29900, 29889, 29896, 2314, 13, 12, 1165, 29889, 842, 29918, 29891, 2576, 4197, 29900, 1696, 29871, 29900, 29889, 29953, 2314, 13, 12, 572, 29873, 29889, 29873, 523, 29918, 2680, 580, 13, 12, 572, 29873, 29889, 7620, 1003, 29898, 9675, 29889, 19218, 29961, 29896, 2314, 13, 12, 572, 29873, 29889, 695, 29888, 580, 13, 13, 13, 2 ]
treebuilder/spinn_cnn/model.py	NLP-Discourse-SoochowU/cdtb_dp2018	6	134603	<reponame>NLP-Discourse-SoochowU/cdtb_dp2018 # -- coding: utf-8 -- """ @Author: oisc <<EMAIL>> @Date: 2018/5/4 @Description: SPINN shift reduce model Ref: <NAME>, <NAME>, <NAME>, et al. A fast unified model for parsing and sentence understanding[J]. 2016. """ from collections import deque import torch import torch.nn as nn import torch.nn.functional as nnfunc import numpy as np UNK = "<UNK>" PAD = "<PAD>" class SPINNState: def __init__(self, stack, buffer, tracking): self.stack = stack self.buffer = buffer self.tracking = tracking def __copy__(self): stack = [(hs.clone(), cs.clone()) for hs, cs in self.stack] buffer = deque([(hb.clone(), cb.clone()) for hb, cb in self.buffer]) h, c = self.tracking tracking = h.clone(), c.clone() return SPINNState(stack, buffer, tracking) class Reducer(nn.Module): def __init__(self, hidden_size): nn.Module.__init__(self) self.hidden_size = hidden_size self.comp = nn.Linear(self.hidden_size * 3, self.hidden_size * 5) def forward(self, state): (h1, c1), (h2, c2) = state.stack[-2], state.stack[-1] tracking = state.tracking[0].view(-1) a, i, f1, f2, o = self.comp(torch.cat([h1, h2, tracking])).chunk(5) c = a.tanh() * i.sigmoid() + f1.sigmoid() * c1 + f2.sigmoid() * c2 h = o.sigmoid() * c.tanh() return h, c class Tracker(nn.Module): def __init__(self, hidden_size): nn.Module.__init__(self) self.hidden_size = hidden_size self.rnn = nn.LSTMCell(3 * self.hidden_size, hidden_size) def init_state(self): return tuple(torch.zeros(self.hidden_size).view(1, -1) for _ in range(2)) def forward(self, state): stack, buffer, tracking = state.stack, state.buffer, state.tracking (s2h, _), (s1h, _) = stack[-2], stack[-1] b1h, _ = buffer[0] cell_input = torch.cat([s2h, s1h, b1h]).view(1, -1) tracking = self.rnn(cell_input, tracking) return tracking class MLP(nn.Module): def __init__(self, hidden_size, num_layers, dropout_p, num_classes): nn.Module.__init__(self) self.linears = nn.ModuleList([nn.Linear(hidden_size, hidden_size) for _ in range(num_layers-1)]) self.activations = nn.ModuleList([nn.ReLU() for _ in range(num_layers - 1)]) self.dropouts = nn.ModuleList([nn.Dropout(p=dropout_p) for _ in range(num_layers - 1)]) self.logits = nn.Linear(hidden_size, num_classes) def forward(self, hidden): for linear, dropout, activation in zip(self.linears, self.dropouts, self.activations): hidden = linear(hidden) hidden = activation(hidden) hidden = dropout(hidden) return self.logits(hidden) class SPINN(nn.Module): def __init__(self, hidden_size, proj_dropout, mlp_layers, mlp_dropout, edu_cutoff, position_embedding_size, unigram_filter_num, bigram_filter_num, trigram_filter_num, pos_vocab, pos_embedding_size, word_vocab, word_embedding, labels): nn.Module.__init__(self) self.hidden_size = hidden_size # build word vocab and initialize embedding word2idx = {UNK: 0, PAD: 1} for word in word_vocab: word2idx[word] = len(word2idx) self.word2idx = word2idx self.wordemb_size = word_embedding.shape[1] word_embedding = np.vstack([ np.random.normal(word_embedding.std(), word_embedding.var(), (2, self.wordemb_size)), word_embedding]) self.wordemb = nn.Embedding.from_pretrained(torch.FloatTensor(word_embedding), freeze=False) # build pos vocab and initialize embedding pos2idx = {UNK: 0, PAD: 1} for pos in pos_vocab: pos2idx[pos] = len(pos2idx) self.pos2idx = pos2idx self.posemb = nn.Embedding(len(self.pos2idx), pos_embedding_size) # word position embedding self.edu_cutoff = edu_cutoff self.position_embedding_size = position_embedding_size self.positionemb = nn.Embedding(edu_cutoff + 1, position_embedding_size) # convolution layer cnn_input_width = self.wordemb_size + pos_embedding_size + position_embedding_size self.edu_unigram_cnn = nn.Conv2d(1, unigram_filter_num, (1, cnn_input_width), padding=(0, 0)) self.edu_bigram_cnn = nn.Conv2d(1, bigram_filter_num, (2, cnn_input_width), padding=(1, 0)) self.edu_trigram_cnn = nn.Conv2d(1, trigram_filter_num, (3, cnn_input_width), padding=(2, 0)) # build label index self.label_size = len(labels) self.labels = list(labels) self.label2idx = {label: i for i, label in enumerate(self.labels)} self.dumb = nn.Parameter(torch.randn(self.hidden_size * 2)) self.dumb.requires_grad = True self.tracker = Tracker(self.hidden_size) self.reducer = Reducer(self.hidden_size) self.proj = nn.Linear(self.wordemb_size * 2 + pos_embedding_size + unigram_filter_num + bigram_filter_num + trigram_filter_num, self.hidden_size * 2) self.proj_dropout = nn.Dropout(proj_dropout) self.mlp = MLP(hidden_size, mlp_layers, mlp_dropout, self.label_size) def new_state(self, conf): stack = [self.dumb.chunk(2), self.dumb.chunk(2)] buffer = deque() for idx in conf.buffer: buffer.append(self.node_encode(conf.discourse, idx)) buffer.append(self.dumb.chunk(2)) tracker_init_state = self.tracker.init_state() state = SPINNState(stack, buffer, tracker_init_state) state = self.update_tracking(state) return state def forward(self, state): tracking_h = state.tracking[0].view(-1) return self.mlp(tracking_h) def score(self, state): label_score = nnfunc.softmax(self(state), dim=0).tolist() return dict(zip(self.labels, label_score)) def shift(self, state): state.stack.append(state.buffer.popleft()) return self.update_tracking(state) def reduce(self, state): reduced = self.reducer(state) state.stack.pop() state.stack.pop() state.stack.append(reduced) return self.update_tracking(state) def update_tracking(self, state): tracking = self.tracker(state) state.tracking = tracking return state def edu_cnn_encode(self, word_emb, tags_emb, position_emb): cnn_input = torch.cat([word_emb, tags_emb, position_emb], dim=1) # convolution input size (batch, in_chanel, seq_len, features_size) cnn_input = cnn_input.view(1, 1, cnn_input.size(0), cnn_input.size(1)) # convolution output size (batch, filter_num, seq_strip_times) unigram_output = nnfunc.relu(self.edu_unigram_cnn(cnn_input)).squeeze(-1) bigram_output = nnfunc.relu(self.edu_bigram_cnn(cnn_input)).squeeze(-1) trigram_output = nnfunc.relu(self.edu_trigram_cnn(cnn_input)).squeeze(-1) # max pooling unigram_feats = nnfunc.max_pool1d(unigram_output, kernel_size=unigram_output.size(2)).view(-1) bigram_feats = nnfunc.max_pool1d(bigram_output, kernel_size=bigram_output.size(2)).view(-1) trigram_feats = nnfunc.max_pool1d(trigram_output, kernel_size=trigram_output.size(2)).view(-1) return torch.cat([unigram_feats, bigram_feats, trigram_feats], dim=0) def node_encode(self, discourse, node_index): node = discourse[node_index] words = [word if word in self.word2idx else UNK for tag, word in discourse.tags(node.span)] or [PAD] tags = [tag if tag in self.pos2idx else UNK for tag, word in discourse.tags(node.span)] or [PAD] positions = [i + 1 if i < self.edu_cutoff else self.edu_cutoff for i, word in enumerate(discourse.words(node.span))] or [0] word_emb = self.wordemb(torch.Tensor([self.word2idx[word] for word in words]).long()) tags_emb = self.posemb(torch.Tensor([self.pos2idx[tag] for tag in tags]).long()) position_emb = self.positionemb(torch.Tensor(positions).long()) w1 = word_emb[0] w2 = word_emb[-1] t1 = tags_emb[0] cnn_emb = self.edu_cnn_encode(word_emb, tags_emb, position_emb) edu_emb = torch.cat([w1, w2, t1, cnn_emb]) proj = self.proj(edu_emb) proj_dropout = self.proj_dropout(proj) 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hug/__init__.py	zhwei820/aio_hug	3	71893	<filename>hug/__init__.py """hug/__init__.py Everyone needs a hug every once in a while. Even API developers. Hug aims to make developing Python driven APIs as simple as possible, but no simpler. Hug's Design Objectives: - Make developing a Python driven API as succint as a written definition. - The framework should encourage code that self-documents. - It should be fast. Never should a developer feel the need to look somewhere else for performance reasons. - Writing tests for APIs written on-top of Hug should be easy and intuitive. - Magic done once, in an API, is better then pushing the problem set to the user of the API. - Be the basis for next generation Python APIs, embracing the latest technology. Copyright (C) 2016 <NAME> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from __future__ import absolute_import from hug import (authentication, directives, exceptions, format, input_format, introspect, middleware, output_format, redirect, route, transform, types, use, validate) from hug._version import current from hug.api import API from hug.decorators import (default_input_format, default_output_format, directive, extend_api, middleware_class, request_middleware, response_middleware, startup, wraps) from hug.route import (call, connect, delete, exception, get, get_post, head, http, not_found, object, options, patch, post, put, sink, static, trace) from hug.types import create as type from hug import development_runner # isort:skip from hug import defaults # isort:skip - must be imported last for defaults to have access to all modules try: # pragma: no cover - defaulting to uvloop if it is installed import uvloop import asyncio asyncio.set_event_loop_policy(uvloop.EventLoopPolicy()) except (ImportError, AttributeError): pass __version__ = current	[ 1, 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utils/hpelm/tests/unittest_elm.py	mohyunho/ENAS_ELM	187	196435	<gh_stars>100-1000 # -- coding: utf-8 -- """ Created on Tue Mar 15 22:04:41 2016 @author: akusok """ import os import tempfile from unittest import TestCase import numpy as np import sys from hpelm import ELM class TestCorrectness(TestCase): def test_AddNeurons_WorksWithLongType(self): if sys.version_info[0] == 2: ltype = long else: ltype = int model = ELM(3, 2) L = ltype(10) model.add_neurons(L, 'tanh') def test_CrossValidation_ReturnsError(self): model = ELM(5, 2) model.add_neurons(10, 'tanh') X = np.random.rand(100, 5) T = np.random.rand(100, 2) err = model.train(X, T, 'CV', k=3) self.assertIsNotNone(err) def test_ClassificationError_CorrectWithMultipleClasses(self): T = np.zeros((100, 5)) T[:, 0] = 1 Y = np.zeros((100, 5)) Y[:, 1] = 1 model = ELM(1, 5, classification='c') self.assertEqual(1, model.error(T, Y)) def test_MultilabelError_CorrectWithMultipleClasses(self): T = np.zeros((100, 5)) T[:, 0] = 1 Y = np.zeros((100, 5)) Y[:, 1] = 1 model = ELM(1, 5, classification='ml') self.assertEqual(0.4, model.error(T, Y)) def test_LOO_CanSelectMoreThanOneNeuron(self): X = np.random.rand(100, 5) T = np.random.rand(100, 2) for _ in range(10): model = ELM(5, 2) model.add_neurons(5, 'lin') model.train(X, T, 'LOO') max1 = model.nnet.L if max1 > 1: break self.assertGreater(max1, 1) def test_LOOandOP_CanSelectMoreThanOneNeuron(self): X = np.random.rand(100, 5) T = np.random.rand(100, 2) for _ in range(10): model = ELM(5, 2) model.add_neurons(5, 'lin') model.train(X, T, 'LOO', 'OP') max2 = model.nnet.L if max2 > 1: break self.assertGreater(max2, 1)	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29900, 29899, 29896, 29900, 29900, 29900, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 15945, 29908, 13, 20399, 373, 323, 434, 1085, 29871, 29896, 29945, 29871, 29906, 29906, 29901, 29900, 29946, 29901, 29946, 29896, 29871, 29906, 29900, 29896, 29953, 13, 13, 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dsmlbc5/eda/eda.py	tahayasindemir/dsmlbc5	13	140379	<filename>dsmlbc5/eda/eda.py<gh_stars>10-100 """EDA Modülüne hoş geldiniz. Bedava bööörek var.""" import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt def check_df(dataframe, head=5): """Hello boyöööööz""" print("##################### Shape #####################") print(dataframe.shape) print("##################### Types #####################") print(dataframe.dtypes) print("##################### Head #####################") print(dataframe.head(head)) print("##################### Tail #####################") print(dataframe.tail(head)) print("##################### NA #####################") print(dataframe.isnull().sum()) print("##################### Quantiles #####################") print(dataframe.quantile([0, 0.05, 0.50, 0.95, 0.99, 1]).T) def cat_summary(dataframe, col_name, plot=False): """Gocuk.com""" print(pd.DataFrame({col_name: dataframe[col_name].value_counts(), "Ratio": 100 * dataframe[col_name].value_counts() / len(dataframe)})) print("##########################################") if plot: sns.countplot(x=dataframe[col_name], data=dataframe) plt.show() def num_summary(dataframe, numerical_col, plot=False): quantiles = [0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 0.95, 0.99] print(dataframe[numerical_col].describe(quantiles).T) if plot: dataframe[numerical_col].hist(bins=20) plt.xlabel(numerical_col) plt.title(numerical_col) plt.show() def grab_col_names(dataframe, cat_th=10, car_th=20): """ Veri setindeki kategorik, numerik ve kategorik fakat kardinal değişkenlerin isimlerini verir. Not: Kategorik değişkenlerin içerisine numerik görünümlü kategorik değişkenler de dahildir. Parameters ------ dataframe: dataframe Değişken isimleri alınmak istenilen dataframe cat_th: int, optional numerik fakat kategorik olan değişkenler için sınıf eşik değeri car_th: int, optinal kategorik fakat kardinal değişkenler için sınıf eşik değeri Returns ------ cat_cols: list Kategorik değişken listesi num_cols: list Numerik değişken listesi cat_but_car: list Kategorik görünümlü kardinal değişken listesi Examples ------ import seaborn as sns df = sns.load_dataset("iris") print(grab_col_names(df)) Notes ------ cat_cols + num_cols + cat_but_car = toplam değişken sayısı num_but_cat cat_cols'un içerisinde. Return olan 3 liste toplamı toplam değişken sayısına eşittir: cat_cols + num_cols + cat_but_car = değişken sayısı """ # cat_cols, cat_but_car cat_cols = [col for col in dataframe.columns if dataframe[col].dtypes == "O"] num_but_cat = [col for col in dataframe.columns if dataframe[col].nunique() < cat_th and dataframe[col].dtypes != "O"] cat_but_car = [col for col in dataframe.columns if dataframe[col].nunique() > car_th and dataframe[col].dtypes == "O"] cat_cols = cat_cols + num_but_cat cat_cols = [col for col in cat_cols if col not in cat_but_car] # num_cols num_cols = [col for col in dataframe.columns if dataframe[col].dtypes != "O"] num_cols = [col for col in num_cols if col not in num_but_cat] # print(f"Observations: {dataframe.shape[0]}") # print(f"Variables: {dataframe.shape[1]}") # print(f'cat_cols: {len(cat_cols)}') # print(f'num_cols: {len(num_cols)}') # print(f'cat_but_car: {len(cat_but_car)}') # print(f'num_but_cat: {len(num_but_cat)}') return cat_cols, num_cols, cat_but_car def target_summary_with_cat(dataframe, target, categorical_col): print(pd.DataFrame({"TARGET_MEAN": dataframe.groupby(categorical_col)[target].mean()}), end="\n\n\n") def target_summary_with_cat_extended(dataframe, target, categorical_col): """ Veri setindeki Target colonunu, girilen kategorik colona gore gruplayip - mean - count - ratio sonuclarini ekrana yazdirir. Parameters ------ dataframe: dataframe Target ve Kategorik kolonlarin bulundugu dataframe target: str Sonucun getirilecegi hedef degisken categorical_col: str Gruplanmak istenen kategorik kolon Returns ------ None Examples ------ import pandas as pd in: df = pd.DataFrame({'Animal': ['Falcon', 'Falcon', 'Falcon', 'Parrot', 'Parrot'], 'Max Speed': [310, 330, 340, 24, 28]}) in: df out: Animal Max Speed 0 Falcon 310 1 Falcon 330 2 Falcon 340 3 Parrot 24 4 Parrot 28 in: target_summary_with_cat_extended(df, 'Max Speed', 'Animal') out: TARGET_MEAN TARGET_CCOUNT RATIO Animal Falcon 326.6667 3 60.0000 Parrot 26.0000 2 40.0000 Notes ------ None """ print(pd.DataFrame({"TARGET_MEAN": dataframe.groupby(categorical_col)[target].mean(), "TARGET_CCOUNT": dataframe.groupby(categorical_col)[target].count(), "RATIO": 100 * dataframe[categorical_col].value_counts() / len(dataframe)}), end="\n\n\n") def target_summary_with_num(dataframe, target, numerical_col): print(dataframe.groupby(target).agg({numerical_col: "mean"}), end="\n\n\n") def high_correlated_cols(dataframe, plot=False, corr_th=0.90): corr = dataframe.corr() cor_matrix = corr.abs() upper_triangle_matrix = cor_matrix.where(np.triu(np.ones(cor_matrix.shape), k=1).astype(np.bool)) drop_list = [col for col in upper_triangle_matrix.columns if any(upper_triangle_matrix[col] > corr_th)] if plot: import seaborn as sns import matplotlib.pyplot as plt sns.set(rc={'figure.figsize': (15, 15)}) sns.heatmap(corr, cmap="RdBu") plt.show() return drop_list	[ 1, 529, 9507, 29958, 6289, 828, 12328, 29945, 29914, 8710, 29914, 8710, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29900, 29899, 29896, 29900, 29900, 13, 15945, 29908, 3352, 29909, 3382, 6001, 29993, 484, 5089, 30169, 10559, 262, 466, 29889, 14195, 879, 289, 29997, 29997, 29997, 22218, 722, 1213, 15945, 13, 13, 5215, 12655, 408, 7442, 13, 5215, 11701, 408, 10518, 13, 5215, 409, 370, 1398, 408, 269, 1983, 13, 5215, 22889, 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pyfibre/gui/pyfibre_plugin.py	franklongford/ImageCol	2	1609715	<reponame>franklongford/ImageCol<filename>pyfibre/gui/pyfibre_plugin.py from envisage.api import Plugin from envisage.ui.tasks.api import TaskFactory from traits.api import List from pyfibre.ids import TASKS, MULTI_IMAGE_FACTORIES from pyfibre.gui.pyfibre_main_task import PyFibreMainTask class PyFibreGUIPlugin(Plugin): """ The Plugin containing the PyFibre UI. This contains the factories which create the Tasks (currently Main)""" id = 'pyfibre.core.pyfibre_gui_plugin' name = 'PyFibre GUI' tasks = List(contributes_to=TASKS) def _tasks_default(self): return [TaskFactory(id='pyfibre.pyfibre_main_task', name='PyFibre GUI (Main)', factory=self._create_main_task) ] def _create_main_task(self): factories = self.application.get_extensions( MULTI_IMAGE_FACTORIES) pyfibre_main_task = PyFibreMainTask( multi_image_factories=factories, ) return pyfibre_main_task	[ 1, 529, 276, 1112, 420, 29958, 29888, 10003, 5426, 4006, 29914, 2940, 1625, 29966, 9507, 29958, 2272, 29888, 747, 276, 29914, 23569, 29914, 2272, 29888, 747, 276, 29918, 8582, 29889, 2272, 13, 3166, 427, 1730, 482, 29889, 2754, 1053, 1858, 3851, 13, 3166, 427, 1730, 482, 29889, 1481, 29889, 20673, 29889, 2754, 1053, 9330, 5126, 13, 3166, 1020, 1169, 29889, 2754, 1053, 2391, 13, 13, 3166, 11451, 29888, 747, 276, 29889, 4841, 1053, 323, 3289, 17557, 29892, 341, 8647, 29902, 29918, 2382, 29918, 4519, 1783, 1955, 29059, 13, 3166, 11451, 29888, 747, 276, 29889, 23569, 29889, 2272, 29888, 747, 276, 29918, 3396, 29918, 7662, 1053, 10772, 29943, 747, 276, 6330, 5398, 13, 13, 13, 1990, 10772, 29943, 747, 276, 29954, 3120, 16288, 29898, 16288, 1125, 13, 1678, 9995, 450, 1858, 3851, 6943, 278, 10772, 29943, 747, 276, 3740, 29889, 910, 3743, 278, 13, 1678, 2114, 3842, 607, 1653, 278, 9330, 29879, 313, 3784, 368, 4241, 5513, 15945, 13, 13, 1678, 1178, 353, 525, 2272, 29888, 747, 276, 29889, 3221, 29889, 2272, 29888, 747, 276, 29918, 23569, 29918, 8582, 29915, 13, 13, 1678, 1024, 353, 525, 19737, 29943, 747, 276, 14839, 29915, 13, 13, 1678, 9595, 353, 2391, 29898, 1285, 5026, 29918, 517, 29922, 29911, 3289, 17557, 29897, 13, 13, 1678, 822, 903, 20673, 29918, 4381, 29898, 1311, 1125, 13, 4706, 736, 518, 5398, 5126, 29898, 333, 2433, 2272, 29888, 747, 276, 29889, 2272, 29888, 747, 276, 29918, 3396, 29918, 7662, 742, 13, 462, 9651, 1024, 2433, 19737, 29943, 747, 276, 14839, 313, 6330, 29897, 742, 13, 462, 9651, 12529, 29922, 1311, 3032, 3258, 29918, 3396, 29918, 7662, 29897, 13, 18884, 4514, 13, 13, 1678, 822, 903, 3258, 29918, 3396, 29918, 7662, 29898, 1311, 1125, 13, 13, 4706, 2114, 3842, 353, 1583, 29889, 6214, 29889, 657, 29918, 24299, 29898, 13, 9651, 341, 8647, 29902, 29918, 2382, 29918, 4519, 1783, 1955, 29059, 29897, 13, 13, 4706, 11451, 29888, 747, 276, 29918, 3396, 29918, 7662, 353, 10772, 29943, 747, 276, 6330, 5398, 29898, 13, 9651, 2473, 29918, 3027, 29918, 17028, 3842, 29922, 17028, 3842, 29892, 13, 4706, 1723, 13, 13, 4706, 736, 11451, 29888, 747, 276, 29918, 3396, 29918, 7662, 13, 2 ]
deprecated/code_manager/javascript_parser/pre_process_constant.py	utarsuno/quasar_source	7	188638	<filename>deprecated/code_manager/javascript_parser/pre_process_constant.py<gh_stars>1-10 # coding=utf-8 """This module, pre_process_constant.py, provides an abstraction for JS constants to pre-process.""" class PreProcessConstant(object): """Represents a constant to pre-process.""" def __init__(self, raw_line): self._raw = raw_line self._variable = None self._value = None self._initialize() def _initialize(self): """Gets the constant name.""" r = self._raw.lstrip().rstrip() r = r[r.index('const ') + len('const '):] r = r[:r.index(';')] self._variable = r[:r.index('=')].lstrip().rstrip() self._value = r[r.index('=') + 1:].lstrip().rstrip() @property def variable(self) -> str: """Returns the name of this constant/variable.""" return self._variable @property def value(self) -> str: """Returns the value of this constant/variable.""" return self._value def parse_out_constants(lines_to_parse): """Returns the lines with certain constants parsed out.""" constants = [] first_pass = [] final_pass = [] for line in lines_to_parse: if 'const' in line and '#pre-process_global_constant' in line: constants.append(PreProcessConstant(line)) else: first_pass.append(line) for l in first_pass: line = l for c in constants: if c.variable in line: line = line.replace(c.variable, c.value) final_pass.append(line) return final_pass	[ 1, 529, 9507, 29958, 311, 17990, 630, 29914, 401, 29918, 12847, 29914, 7729, 29918, 16680, 29914, 1457, 29918, 5014, 29918, 23362, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 29937, 14137, 29922, 9420, 29899, 29947, 13, 13, 15945, 29908, 4013, 3883, 29892, 758, 29918, 5014, 29918, 23362, 29889, 2272, 29892, 8128, 385, 27086, 428, 363, 7649, 17727, 304, 758, 29899, 5014, 1213, 15945, 13, 13, 13, 1990, 4721, 7032, 12075, 424, 29898, 3318, 1125, 13, 12, 15945, 29908, 1123, 4569, 1237, 263, 4868, 304, 758, 29899, 5014, 1213, 15945, 13, 13, 12, 1753, 4770, 2344, 12035, 1311, 29892, 10650, 29918, 1220, 1125, 13, 12, 12, 1311, 3032, 1610, 418, 353, 10650, 29918, 1220, 13, 12, 12, 1311, 3032, 11918, 353, 6213, 13, 12, 12, 1311, 3032, 1767, 1678, 353, 6213, 13, 12, 12, 1311, 3032, 24926, 580, 13, 13, 12, 1753, 903, 24926, 29898, 1311, 1125, 13, 12, 12, 15945, 29908, 29954, 1691, 278, 4868, 1024, 1213, 15945, 13, 12, 12, 29878, 353, 1583, 3032, 1610, 29889, 29880, 17010, 2141, 29878, 17010, 580, 13, 12, 12, 29878, 353, 364, 29961, 29878, 29889, 2248, 877, 3075, 25710, 718, 7431, 877, 3075, 525, 1125, 29962, 13, 12, 12, 29878, 353, 364, 7503, 29878, 29889, 2248, 877, 29936, 1495, 29962, 13, 13, 12, 12, 1311, 3032, 11918, 353, 364, 7503, 29878, 29889, 2248, 877, 29922, 1495, 1822, 29880, 17010, 2141, 29878, 17010, 580, 13, 12, 12, 1311, 3032, 1767, 1678, 353, 364, 29961, 29878, 29889, 2248, 877, 29922, 1495, 718, 29871, 29896, 29901, 1822, 29880, 17010, 2141, 29878, 17010, 580, 13, 13, 12, 29992, 6799, 13, 12, 1753, 2286, 29898, 1311, 29897, 1599, 851, 29901, 13, 12, 12, 15945, 29908, 11609, 29879, 278, 1024, 310, 445, 4868, 29914, 11918, 1213, 15945, 13, 12, 12, 2457, 1583, 3032, 11918, 13, 13, 12, 29992, 6799, 13, 12, 1753, 995, 29898, 1311, 29897, 1599, 851, 29901, 13, 12, 12, 15945, 29908, 11609, 29879, 278, 995, 310, 445, 4868, 29914, 11918, 1213, 15945, 13, 12, 12, 2457, 1583, 3032, 1767, 13, 13, 13, 1753, 6088, 29918, 449, 29918, 3075, 1934, 29898, 9012, 29918, 517, 29918, 5510, 1125, 13, 12, 15945, 29908, 11609, 29879, 278, 3454, 411, 3058, 17727, 21213, 714, 1213, 15945, 13, 12, 3075, 1934, 29871, 353, 5159, 13, 12, 4102, 29918, 3364, 353, 5159, 13, 12, 8394, 29918, 3364, 353, 5159, 13, 13, 12, 1454, 1196, 297, 3454, 29918, 517, 29918, 5510, 29901, 13, 12, 12, 361, 525, 3075, 29915, 297, 1196, 322, 16321, 1457, 29899, 5014, 29918, 10945, 29918, 23362, 29915, 297, 1196, 29901, 13, 12, 12, 12, 3075, 1934, 29889, 4397, 29898, 6572, 7032, 12075, 424, 29898, 1220, 876, 13, 12, 12, 2870, 29901, 13, 12, 12, 12, 4102, 29918, 3364, 29889, 4397, 29898, 1220, 29897, 13, 13, 12, 1454, 301, 297, 937, 29918, 3364, 29901, 13, 12, 12, 1220, 353, 301, 13, 12, 12, 1454, 274, 297, 17727, 29901, 13, 12, 12, 12, 361, 274, 29889, 11918, 297, 1196, 29901, 13, 12, 12, 12, 12, 1220, 353, 1196, 29889, 6506, 29898, 29883, 29889, 11918, 29892, 274, 29889, 1767, 29897, 13, 13, 12, 12, 8394, 29918, 3364, 29889, 4397, 29898, 1220, 29897, 13, 13, 12, 2457, 2186, 29918, 3364, 13, 13, 2 ]
missingdata/tests/test_missingdata.py	jubyraju1979/new	13	189659	#!/usr/bin/env python # -- coding: utf-8 -- """Tests for `missingdata` package.""" from os import makedirs from os.path import join as pjoin import numpy as np import pandas as pd from missingdata.base import blackholes # from quilt.data.ResidentMario import missingno_data # collisions = missingno_data.nyc_collision_factors() # collisions = collisions.replace("nan", np.nan) in_dir = '/Volumes/data/work/rotman/CANBIND/data/Tier1_v1' proc_dir = pjoin(in_dir, 'processing') miss_vis_dir = pjoin(proc_dir, 'missingdata_vis') makedirs(miss_vis_dir, exist_ok=True) path_tier1 = pjoin(in_dir, 'Canbind.Primary.Variables.20190114.xlsx') tier1_full = pd.read_excel(path_tier1) np.random.seed(342) rows = np.random.randint(0, 180, 150) cols = np.append([0, 1], np.random.randint(2, 120, 100)) # keeping cols 0 and 1 tier1 = tier1_full.iloc[rows, cols] path_dict_tier1 = pjoin(in_dir, 'Canbind.Tier.1.variables.DICT.0002.xlsx') dict_tier1 = pd.read_excel(path_dict_tier1) col_groups = dict_tier1['Category'].values.astype('str') var_catg = np.genfromtxt(pjoin(proc_dir, 'variable_to_category.txt'), dtype='str', delimiter=',') subjlabel_dx = np.genfromtxt(pjoin(proc_dir, 'subjlabel_to_diagnosis.txt'), dtype='str', delimiter=',') catg = {var: catg for var, catg in var_catg} diag = {lbl: dx for lbl, dx in subjlabel_dx} row_groups = [diag[slbl] if slbl in diag else 'Unknown' for slbl in tier1['SUBJLABEL']] col_groups = [catg[varb] if varb in catg else 'Unknown' for varb in tier1.columns] # making them short row_groups = [r[:4] for r in row_groups] col_groups = [c[:4] for c in col_groups] min_missing = 0.00 freq_thresh_show_labels = .01 out_path = pjoin(miss_vis_dir, 'missing_data_trial_minmiss{}perc_freqmissthresh{}.pdf' ''.format(100 * min_missing, 100 * freq_thresh_show_labels)) # # missing data viz # fig, ax_frame, \ # ax_freq_over_row, ax_freq_over_col, \ # ax_row_groups, ax_col_groups = blackholes(tier1, # label_rows_with='SUBJLABEL', # freq_thresh_show_labels=freq_thresh_show_labels, # out_path=out_path, # show_fig=True) # fig, ax_frame, ax_freq_over_row, ax_freq_over_col, ax_row_groups, ax_col_groups \ # = blackholes(tier1, # filter_spec_samples=(min_missing, 1.0), # filter_spec_variables=(min_missing, 1.0), # label_rows_with='SUBJLABEL', # freq_thresh_show_labels=freq_thresh_show_labels, # out_path=out_path, # show_fig=True) fig, ax_frame, ax_freq_over_row, ax_freq_over_col, ax_row_groups, ax_col_groups = \ blackholes(tier1, label_rows_with='SUBJLABEL', group_rows_by=row_groups, group_cols_by=col_groups, freq_thresh_show_labels=freq_thresh_show_labels, out_path=out_path, show_fig=True) print()	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 13, 15945, 29908, 24376, 363, 421, 27259, 1272, 29952, 3577, 1213, 15945, 13, 13, 3166, 2897, 1053, 2136, 287, 12935, 13, 3166, 2897, 29889, 2084, 1053, 5988, 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src/artists/migrations/0003_auto_20191025_0454.py	slee981/sos-music-project	0	176428	<filename>src/artists/migrations/0003_auto_20191025_0454.py # Generated by Django 2.2.1 on 2019-10-25 04:54 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('artists', '0002_auto_20191025_0444'), ] operations = [ migrations.AlterModelTable( name='artist', table='artists', ), ]	[ 1, 529, 9507, 29958, 4351, 29914, 442, 2879, 29914, 26983, 800, 29914, 29900, 29900, 29900, 29941, 29918, 6921, 29918, 29906, 29900, 29896, 29929, 29896, 29900, 29906, 29945, 29918, 29900, 29946, 29945, 29946, 29889, 2272, 13, 29937, 3251, 630, 491, 15337, 29871, 29906, 29889, 29906, 29889, 29896, 373, 29871, 29906, 29900, 29896, 29929, 29899, 29896, 29900, 29899, 29906, 29945, 29871, 29900, 29946, 29901, 29945, 29946, 13, 13, 3166, 9557, 29889, 2585, 1053, 9725, 800, 13, 13, 13, 1990, 341, 16783, 29898, 26983, 800, 29889, 29924, 16783, 1125, 13, 13, 1678, 9962, 353, 518, 13, 4706, 6702, 442, 2879, 742, 525, 29900, 29900, 29900, 29906, 29918, 6921, 29918, 29906, 29900, 29896, 29929, 29896, 29900, 29906, 29945, 29918, 29900, 29946, 29946, 29946, 5477, 13, 1678, 4514, 13, 13, 1678, 6931, 353, 518, 13, 4706, 9725, 800, 29889, 2499, 357, 3195, 3562, 29898, 13, 9651, 1024, 2433, 442, 391, 742, 13, 9651, 1591, 2433, 442, 2879, 742, 13, 4706, 10353, 13, 1678, 4514, 13, 2 ]
game.py	Rafael705/pong-game	0	1617430	<gh_stars>0 import pygame, sys, random # ------- # CLASSES # ------- class Paddle: def __init__(self, screen, color, posX, posY, width, height): self.screen = screen self.color = color self.posX = posX self.posY = posY self.width = width self.height = height self.state = 'stopped' self.draw() def draw(self): pygame.draw.rect( self.screen, self.color, (self.posX, self.posY, self.width, self.height) ) def move(self): if self.state == 'up': self.posY -= 0.8 elif self.state == 'down': self.posY += 0.8 def clamp(self): if self.posY <= 0: self.posY = 0 if self.posY + self.height >= HEIGHT: self.posY = HEIGHT - self.height def restart_pos(self): self.posY = HEIGHT//2 - self.height//2 self.state = 'stopped' self.draw() class Ball: def __init__(self, screen, color, posX, posY, radius): self.screen = screen self.color = color self.posX = posX self.posY = posY self.dx = 0 self.dy = 0 self.radius = radius self.draw() def draw(self): pygame.draw.circle( self.screen, self.color, (self.posX, self.posY), self.radius ) def start(self): self.dx = 1 self.dy = 1 def move(self): self.posX += self.dx self.posY += self.dy def increase_speed(self, velX): self.dx += velX def wall_collision(self): self.dy = -self.dy def paddle_collision(self): self.dx = -self.dx def restart_pos(self): self.posX = WIDTH//2 self.posY = HEIGHT//2 self.dx = 0 self.dy = 0 self.draw() class PlayerScore: def __init__(self, screen, points, posX, posY): self.screen = screen self.points = points self.posX = posX self.posY = posY self.font = pygame.font.SysFont("monospace", 80, bold=True) self.label = self.font.render(self.points, 0, WHITE) self.show() def show(self): self.screen.blit(self.label, (self.posX - self.label.get_rect().width // 2, self.posY)) def increase(self): points = int(self.points) + 1 self.points = str(points) self.label = self.font.render(self.points, 0, WHITE) def restart(self): self.points = '0' self.label = self.font.render(self.points, 0, WHITE) class CollisionManager: def between_ball_and_paddle1(self, ball, paddle): ballX = ball.posX ballY = ball.posY paddleX = paddle.posX paddleY = paddle.posY if ballY + ball.radius > paddleY and ballY - ball.radius < paddleY + paddle.height: if ballX - ball.radius <= paddleX + paddle.width: return True return False def between_ball_and_paddle2(self, ball, paddle): ballX = ball.posX ballY = ball.posY paddleX = paddle.posX paddleY = paddle.posY if ballY + ball.radius > paddleY and ballY - ball.radius < paddleY + paddle.height: if ballX + ball.radius >= paddleX: return True return False def between_ball_and_walls(self, ball): ballY = ball.posY if ballY - ball.radius <= 0: return True if ballY + ball.radius >= HEIGHT: return True return False def between_ball_and_goal1(self, ball): return ball.posX + ball.radius <= 0 def between_ball_and_goal2(self, ball): return ball.posX - ball.radius >= WIDTH # --------- # CONSTANTS # --------- WIDTH, HEIGHT = 900, 500 BLACK = (0, 0, 0) WHITE = (255, 255, 255) RED = (255, 0, 0) # SCREEN pygame.init() screen = pygame.display.set_mode( (WIDTH, HEIGHT) ) pygame.display.set_caption('PONG') # --------- # FUNCTIONS # --------- def draw_board(): screen.fill( BLACK ) pygame.draw.line( screen, WHITE, (WIDTH//2, 0), (WIDTH//2, HEIGHT), 5 ) def restart(): draw_board() score1.restart() score2.restart() ball.restart_pos() paddle1.restart_pos() paddle2.restart_pos() draw_board() # ------- # OBJECTS # ------- paddle1 = Paddle( screen, WHITE, 15, HEIGHT//2 - 60, 20, 120 ) paddle2 = Paddle( screen, WHITE, WIDTH - 20 - 15, HEIGHT//2 - 60, 20, 120 ) ball = Ball( screen, WHITE, WIDTH//2, HEIGHT//2, 10 ) ball = Ball( screen, WHITE, WIDTH//2, HEIGHT//2, 10) collision = CollisionManager() score1 = PlayerScore( screen, '0', WIDTH//4, 15 ) score2 = PlayerScore( screen, '0', WIDTH - WIDTH//4, 15 ) # --------- # VARIABLES # --------- playing = False # -------- # MAINLOOP # -------- while True: for event in pygame.event.get(): if event.type == pygame.QUIT: sys.exit() if event.type == pygame.KEYDOWN: if event.key == pygame.K_p and not playing: ball.start() playing = True if event.key == pygame.K_r and playing: restart() playing = False if event.key == pygame.K_w: paddle1.state = 'up' if event.key == pygame.K_s: paddle1.state = 'down' if event.key == pygame.K_UP: paddle2.state = 'up' if event.key == pygame.K_DOWN: paddle2.state = 'down' # if event.type == pygame.KEYUP: # paddle1.state = 'stopped' # paddle2.state = 'stopped' if playing: draw_board() # ball ball.move() ball.draw() # paddle 1 paddle1.move() paddle1.clamp() paddle1.draw() # paddle 2 paddle2.move() paddle2.clamp() paddle2.draw() # wall collision if collision.between_ball_and_walls(ball): print('Point') ball.wall_collision() # paddle1 collision if collision.between_ball_and_paddle1(ball, paddle1): ball.paddle_collision() # paddle2 collision if collision.between_ball_and_paddle2(ball, paddle2): ball.paddle_collision() # GOAL OF PLAYER 1 ! if collision.between_ball_and_goal2(ball): 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paraments.py	JoenHune/DQN-Meets-Atari	0	56730	<gh_stars>0 import sys import tensorflow as tf2 DEFAULT_GPU_LIST = [0, 1, 2] SCALE = 2 MEMORY_LENGTH = 1000000 STACK_LENGTH = 4 BATCH_SIZE = 64 LEARNING_RATE = 0.00025 GAMMA = 0.9 EPSILON = 1.0 EPSILON_MIN = 0.01 EPSILON_DECAY = 0.00003 GIVEN_GPU = [eval(sys.argv[1])] if len(sys.argv) > 1 else DEFAULT_GPU_LIST def get_strategy(gpu_visible=None): gpu_total = tf2.config.experimental.list_physical_devices(device_type="GPU") gpu_candidates = [] if gpu_visible is None: gpu_visible = GIVEN_GPU for gpu_id in gpu_visible: if 0 <= gpu_id < len(gpu_total): gpu_candidates.append(gpu_total[gpu_id]) tf2.config.experimental.set_visible_devices(devices=gpu_candidates, device_type="GPU") print("gpu_total :", gpu_total, "\| gpu_candidates :", gpu_candidates) strategy = tf2.distribute.OneDeviceStrategy(device="/cpu:0") if len(gpu_candidates) == 1: strategy = tf2.distribute.OneDeviceStrategy(device="/gpu:0") elif len(gpu_candidates) > 1: strategy = tf2.distribute.MirroredStrategy() return strategy	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 13, 5215, 10876, 13, 5215, 26110, 408, 15886, 29906, 13, 13, 23397, 29918, 29954, 7056, 29918, 24360, 353, 518, 29900, 29892, 29871, 29896, 29892, 29871, 29906, 29962, 13, 13, 29903, 5454, 1307, 353, 29871, 29906, 13, 13, 2303, 29924, 18929, 29918, 19433, 353, 29871, 29896, 29900, 29900, 29900, 29900, 29900, 29900, 13, 1254, 11375, 29918, 19433, 353, 29871, 29946, 13, 13, 29933, 14789, 29918, 14226, 353, 29871, 29953, 29946, 13, 1307, 25614, 29918, 29934, 3040, 353, 29871, 29900, 29889, 29900, 29900, 29900, 29906, 29945, 13, 13, 29954, 5194, 1529, 353, 29871, 29900, 29889, 29929, 13, 15488, 5425, 29931, 1164, 353, 29871, 29896, 29889, 29900, 13, 15488, 5425, 29931, 1164, 29918, 16173, 353, 29871, 29900, 29889, 29900, 29896, 13, 15488, 5425, 29931, 1164, 29918, 2287, 5454, 29979, 353, 29871, 29900, 29889, 29900, 29900, 29900, 29900, 29941, 13, 13, 29954, 5667, 1430, 29918, 29954, 7056, 353, 518, 14513, 29898, 9675, 29889, 19218, 29961, 29896, 2314, 29962, 565, 7431, 29898, 9675, 29889, 19218, 29897, 1405, 29871, 29896, 1683, 22236, 29918, 29954, 7056, 29918, 24360, 13, 13, 13, 1753, 679, 29918, 710, 8963, 29898, 29887, 3746, 29918, 12872, 29922, 8516, 1125, 13, 1678, 330, 3746, 29918, 7827, 353, 15886, 29906, 29889, 2917, 29889, 735, 27910, 29889, 1761, 29918, 14017, 936, 29918, 3359, 1575, 29898, 10141, 29918, 1853, 543, 29954, 7056, 1159, 13, 1678, 330, 3746, 29918, 29883, 5380, 1078, 353, 5159, 13, 13, 1678, 565, 330, 3746, 29918, 12872, 338, 6213, 29901, 13, 4706, 330, 3746, 29918, 12872, 353, 402, 5667, 1430, 29918, 29954, 7056, 13, 13, 1678, 363, 330, 3746, 29918, 333, 297, 330, 3746, 29918, 12872, 29901, 13, 4706, 565, 29871, 29900, 5277, 330, 3746, 29918, 333, 529, 7431, 29898, 29887, 3746, 29918, 7827, 1125, 13, 9651, 330, 3746, 29918, 29883, 5380, 1078, 29889, 4397, 29898, 29887, 3746, 29918, 7827, 29961, 29887, 3746, 29918, 333, 2314, 13, 13, 1678, 15886, 29906, 29889, 2917, 29889, 735, 27910, 29889, 842, 29918, 12872, 29918, 3359, 1575, 29898, 3359, 1575, 29922, 29887, 3746, 29918, 29883, 5380, 1078, 29892, 4742, 29918, 1853, 543, 29954, 7056, 1159, 13, 1678, 1596, 703, 29887, 3746, 29918, 7827, 584, 613, 330, 3746, 29918, 7827, 29892, 376, 29989, 330, 3746, 29918, 29883, 5380, 1078, 584, 613, 330, 3746, 29918, 29883, 5380, 1078, 29897, 13, 13, 1678, 13705, 353, 15886, 29906, 29889, 5721, 2666, 29889, 6716, 11501, 26910, 29898, 10141, 13802, 21970, 29901, 29900, 1159, 13, 1678, 565, 7431, 29898, 29887, 3746, 29918, 29883, 5380, 1078, 29897, 1275, 29871, 29896, 29901, 13, 4706, 13705, 353, 15886, 29906, 29889, 5721, 2666, 29889, 6716, 11501, 26910, 29898, 10141, 13802, 29887, 3746, 29901, 29900, 1159, 13, 1678, 25342, 7431, 29898, 29887, 3746, 29918, 29883, 5380, 1078, 29897, 1405, 29871, 29896, 29901, 13, 4706, 13705, 353, 15886, 29906, 29889, 5721, 2666, 29889, 29924, 381, 729, 287, 26910, 580, 13, 13, 1678, 736, 13705, 13, 13, 2 ]
aulaDjango/py3.5/bin/django-admin.py	tmenegaz/django	0	85931	<reponame>tmenegaz/django<gh_stars>0 #!/home/tmenegaz/Documentos/cimatec/2016.2/escolaTecnica/mundoSenai/django/aula/aulaDjango/py3.5/bin/python3.5 from django.core import management if __name__ == "__main__": management.execute_from_command_line()	[ 1, 529, 276, 1112, 420, 29958, 29873, 1527, 387, 834, 29914, 14095, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 29937, 14708, 5184, 29914, 29873, 1527, 387, 834, 29914, 6268, 359, 29914, 29883, 6490, 29883, 29914, 29906, 29900, 29896, 29953, 29889, 29906, 29914, 267, 15519, 29911, 687, 8902, 29914, 29885, 6201, 29903, 264, 1794, 29914, 14095, 29914, 29874, 2497, 29914, 29874, 2497, 29928, 5364, 29914, 2272, 29941, 29889, 29945, 29914, 2109, 29914, 4691, 29941, 29889, 29945, 13, 3166, 9557, 29889, 3221, 1053, 10643, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 1678, 10643, 29889, 7978, 29918, 3166, 29918, 6519, 29918, 1220, 580, 13, 2 ]
Dataset/2DGS_FD_Solver[RK4].py	paulpuren/PhySR	6	177463	import torch import torch.nn as nn import numpy as np import scipy.io as scio import os import matplotlib.pyplot as plt os.environ['CUDA_VISIBLE_DEVICES'] = '0' torch.manual_seed(1) np.random.seed(1) lapl_op = [[[[ 0, 0, -1/12, 0, 0], [ 0, 0, 4/3, 0, 0], [-1/12, 4/3, -5, 4/3, -1/12], [ 0, 0, 4/3, 0, 0], [ 0, 0, -1/12, 0, 0]]]] # ============ define relevant functions ============= # https://github.com/benmaier/reaction-diffusion/blob/master/gray_scott.ipynb def apply_laplacian(mat, dx = 0.01): # dx is inversely proportional to N """This function applies a discretized Laplacian in periodic boundary conditions to a matrix For more information see https://en.wikipedia.org/wiki/Discrete_Laplace_operator#Implementation_via_operator_discretization """ # the cell appears 4 times in the formula to compute # the total difference neigh_mat = -5mat.copy() # Each direct neighbor on the lattice is counted in # the discrete difference formula neighbors = [ ( 4/3, (-1, 0) ), ( 4/3, ( 0,-1) ), ( 4/3, ( 0, 1) ), ( 4/3, ( 1, 0) ), (-1/12, (-2, 0)), (-1/12, (0, -2)), (-1/12, (0, 2)), (-1/12, (2, 0)), ] # shift matrix according to demanded neighbors # and add to this cell with corresponding weight for weight, neigh in neighbors: neigh_mat += weight np.roll(mat, neigh, (0,1)) return neigh_mat/dx*2 # Define the update formula for chemicals A and B def update(A, B, DA, DB, f, k, delta_t): """Apply the Gray-Scott update formula""" # compute the diffusion part of the update diff_A = DA apply_laplacian(A) diff_B = DB * apply_laplacian(B) # Apply chemical reaction reaction = AB2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f (1-A) diff_B -= (k+f) * B A += diff_A * delta_t B += diff_B * delta_t return A, B def GetEachTerm(A, B, DA, DB, f, k, delta_t, dx): lap_A = DA * apply_laplacian(A,dx) lap_B = DB * apply_laplacian(B,dx) # Apply chemical reaction reaction = A * B ** 2 # Apply birth/death, linear term lin_A = f * (1 - A) lin_B = (k + f) * B return lap_A, lap_B, reaction, lin_A, lin_B def update_rk4(A0, B0, DA, DB, f, k, delta_t, dx): """Update with Runge-kutta-4 method See https://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods """ ############# Stage 1 ############## # compute the diffusion part of the update diff_A = DA * apply_laplacian(A0, dx) diff_B = DB * apply_laplacian(B0, dx) # Apply chemical reaction reaction = A0 * B0 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A0) diff_B -= (k + f) * B0 K1_a = diff_A K1_b = diff_B ############# Stage 1 ############## A1 = A0 + K1_a * delta_t/2.0 B1 = B0 + K1_b * delta_t/2.0 diff_A = DA * apply_laplacian(A1, dx) diff_B = DB * apply_laplacian(B1, dx) # Apply chemical reaction reaction = A1 * B1 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A1) diff_B -= (k + f) * B1 K2_a = diff_A K2_b = diff_B ############# Stage 2 ############## A2 = A0 + K2_a * delta_t/2.0 B2 = B0 + K2_b * delta_t/2.0 diff_A = DA * apply_laplacian(A2, dx) diff_B = DB * apply_laplacian(B2, dx) # Apply chemical reaction reaction = A2 * B2 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A2) diff_B -= (k + f) * B2 K3_a = diff_A K3_b = diff_B ############# Stage 3 ############## A3 = A0 + K3_a * delta_t B3 = B0 + K3_b * delta_t diff_A = DA * apply_laplacian(A3, dx) diff_B = DB * apply_laplacian(B3, dx) # Apply chemical reaction reaction = A3 * B3 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A3) diff_B -= (k + f) * B3 K4_a = diff_A K4_b = diff_B # Final solution A = A0 + delta_t(K1_a+2K2_a+2K3_a+K4_a)/6.0 B = B0 + delta_t(K1_b+2K2_b+2K3_b+K4_b)/6.0 return A, B def get_initial_A_and_B(N, random_influence = 0.2): """get the initial chemical concentrations""" # get initial homogeneous concentrations A = (1-random_influence) * np.ones((N,N)) B = np.zeros((N,N)) # put some noise on there A += random_influence * np.random.random((N,N)) B += random_influence * np.random.random((N,N)) # initial disturbance N1, N2, N3 = N//4-4, N//2, 3N//4 r = int(N/10.0) # initial disturbance 1 A[N1-r:N1+r, N1-r:N1+r] = 0.50 B[N1-r:N1+r, N1-r:N1+r] = 0.25 # # initial disturbance 2 # A[N1-r:N1+r, N3-r:N3+r] = 0.50 # B[N1-r:N1+r, N3-r:N3+r] = 0.25 # # # initial disturbance 3 # A[N3-r:N3+r, N3-r:N3+r] = 0.50 # B[N3-r:N3+r, N3-r:N3+r] = 0.25 # # # initial disturbance 4 # A[N3-r:N3+r, N1-r:N1+r] = 0.50 # B[N3-r:N3+r, N1-r:N1+r] = 0.25 # initial disturbance 5 A[N2-r:N2+r, N2-r:N2+r] = 0.50 B[N2-r:N2+r, N2-r:N2+r] = 0.25 # # # initial disturbance 6 # A[N2-r:N2+r, N3-r:N3+r] = 0.50 # B[N2-r:N2+r, N3-r:N3+r] = 0.25 return A, B def postProcess(output, N, xmin, xmax, ymin, ymax, num, batch, save_path): ''' num: Number of time step ''' x = np.linspace(xmin, xmax, N+1)[:-1] y = np.linspace(ymin, ymax, N+1)[:-1] x_star, y_star = np.meshgrid(x, y) u_pred = output[num, 0, :, :] # v_star = true[num+25, 1, 1:-1, 1:-1] v_pred = output[num, 1, :, :] fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) fig.subplots_adjust(hspace=0.3, wspace=0.3) cf = ax[0].scatter(x_star, y_star, c=u_pred, alpha=0.95, edgecolors='none', cmap='hot', marker='s', s=2) ax[0].axis('square') ax[0].set_xlim([xmin, xmax]) ax[0].set_ylim([ymin, ymax]) cf.cmap.set_under('black') cf.cmap.set_over('white') ax[0].set_title('u-FDM') fig.colorbar(cf, ax=ax[0], extend='both') cf = ax[1].scatter(x_star, y_star, c=v_pred, alpha=0.95, edgecolors='none', cmap='hot', marker='s', s=2) # ax[1].axis('square') ax[1].set_xlim([xmin, xmax]) ax[1].set_ylim([ymin, ymax]) cf.cmap.set_under('black') cf.cmap.set_over('white') ax[1].set_title('v-FDM') fig.colorbar(cf, ax=ax[1], extend='both') # plt.draw() plt.savefig(save_path + '/uv_[b=%d][t=%d].png'%(batch, num)) plt.close('all') if __name__ == '__main__': #################### generate data ##################### # =========== define model parameters ========== # dt should be 1/2 of dx # Diffusion coefficients DA = 0.16 #210*-5 DB = 0.08 #DA/4 # define birth/death rates f = 0.06 #1/25 k = 0.062 #3/50 # grid size N = 256 # 128 # update in time delta_t = 1.0 #1.0/2 # spatial step dx = 1.0 #1.0 / N # intialize the chemical concentrations, random_incluence=0 A, B = get_initial_A_and_B(N, random_influence = 0.0) A_record = A.copy()[None,...] B_record = B.copy()[None,...] N_simulation_steps = 15000 for step in range(N_simulation_steps): # Runge-kutta scheme #A, B = update(A, B, DA, DB, f, k, delta_t) A, B = update_rk4(A, B, DA, DB, f, k, delta_t, dx) if step%5 ==0: print(step) A_record = np.concatenate((A_record, A[None,...]), axis=0) B_record = np.concatenate((B_record, B[None,...]), axis=0) UV = np.concatenate((A_record[None,...], B_record[None,...]), axis=0) save_path = './2DGS_IC1_2x3001x256x256.mat' scio.savemat(save_path, {'uv': UV}) # Plot the result output = np.transpose(UV, [1, 0, 2, 3]) fig_save_path = './2DGS/' for i in range(21): postProcess(output, N, 0, Ndx, 0, Ndx, 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vagrant/tournament/tournament.py	sxw031/fullstack-nanodegree-vm	0	1611187	#!/usr/bin/env python # # tournament.py -- implementation of a Swiss-system tournament # # A Swiss-System tournament is a kind of game or sports tournament in which players # are not eliminated when they are lose a match, but are paired in each round with opponents # having approximately the same win-loss record. import psycopg2 def connect(database_name="tournament"): """Connect to the PostgreSQL database. Returns a database connection.""" try: db = psycopg2.connect("dbname={}".format(database_name)) cursor = db.cursor() return db,cursor except: print ("<error message>") def deleteMatches(): """Remove all the match records from the database.""" db, db_cursor = connect() query = "DELETE FROM matches" db_cursor.execute(query) db.commit() db.close() def deletePlayers(): """Remove all the player records from the database.""" db, db_cursor = connect() query = "TRUNCATE players" db_cursor.execute(query) db.commit() db.close() def countPlayers(): """Returns the number of players currently registered.""" db, db_cursor = connect() query = "SELECT COUNT(id) AS num FROM players" db_cursor.execute(query) results = db_cursor.fetchone() db.close() if results: return results[0]; else: return '0' def registerPlayer(name): """Adds a player to the tournament database. The database assigns a unique serial id number for the player. (This should be handled by your SQL database schema, not in your Python code.) Args: name: the player's full name (need not be unique). """ db, db_cursor = connect() query = "INSERT INTO players (name) VALUES (%s)" parameter = (name,) db_cursor.execute(query, parameter) db.commit() db.close() def playerStandings(): """Returns a list of the players and their win records, sorted by wins. The first entry in the list should be the player in first place, or a player tied for first place if there is currently a tie. Returns: A list of tuples, each of which contains (id, name, wins, matches): id: the player's unique id (assigned by the database) name: the player's full name (as registered) wins: the number of matches the player has won matches: the number of matches the player has played """ db, db_cursor = connect() query = "SELECT * FROM total_wins;" db_cursor.execute(query) results = db_cursor.fetchall() db.close() return results def reportMatch(winner, loser): """Records the outcome of a single match between two players. Args: winner: the id number of the player who won loser: the id number of the player who lost """ db, db_cursor = connect() query = "INSERT INTO matches (winner, loser) VALUES (%s, %s)" parameter = (winner, loser,) db_cursor.execute(query, parameter) db.commit() db.close() def swissPairings(): """Returns a list of pairs of players for the next round of a match. Assuming that there are an even number of players registered, each player appears exactly once in the pairings. Each player is paired with another player with an equal or nearly-equal win record, that is, a player adjacent to him or her in the standings. Returns: A list of tuples, each of which contains (id1, name1, id2, name2) id1: the first player's unique id name1: the first player's name id2: the second player's unique id name2: the second player's name """ db, db_cursor = connect() results = playerStandings() pairings = [] count = len(results) for x in range (0, count-1, 2): paired_list = (results[x][0], results[x][1], results[x+1][0],results[x+1][1]) pairings.append(paired_list) db.close() return pairings	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 13, 29937, 29871, 13, 29937, 14743, 29889, 2272, 1192, 5314, 310, 263, 26182, 29899, 5205, 14743, 13, 29937, 13, 29937, 319, 26182, 29899, 3924, 14743, 338, 263, 2924, 310, 3748, 470, 14717, 14743, 297, 607, 10769, 29871, 13, 29937, 526, 451, 10397, 630, 746, 896, 526, 14074, 263, 1993, 29892, 541, 526, 3300, 2859, 297, 1269, 4513, 411, 23995, 1237, 13, 29937, 2534, 14235, 278, 1021, 5401, 29899, 6758, 2407, 29889, 13, 13, 5215, 6529, 29891, 9708, 29887, 29906, 13, 13, 1753, 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pepys_import/file/highlighter/support/export.py	debrief/pepys-import	4	30001	import html from tqdm import tqdm from .color_picker import color_for, html_color_for, mean_color_for def export_report(filename, chars, dict_colors, include_key=False): """ Export a HTML report showing all the extraction usages for the file. :param filename: Output filename :param chars: Characters array (should be HighlightedFile.chars) :param dict_colors: Dictionary specifying colors to use (should be HighlightedFile.dict_colors) :param include_key: Whether to include a key at the bottom defining the usages of the colors This basically loops through all of the characters in the characters array, and then creates the relevant <span> tags for each character based on the usages stored for that character. """ output_strings = [] html_header = """<html> <head> </head> <body style="font-family: Courier"> """ output_strings.append(html_header) last_hash = "" for char in tqdm(chars): letter = char.letter this_hash = "" this_message = "" colors = [] multi_usages = len(char.usages) > 1 for usage in char.usages: this_hash += usage.tool_field needs_new_line = this_message != "" colors.append(color_for(usage.tool_field, dict_colors)) if needs_new_line: this_message += " " if multi_usages: this_message += "-" this_message += usage.tool_field + ", " + usage.message # do we have anything to shade? if this_hash != "": # generate/retrieve a color for this hash new_color = mean_color_for(colors) hex_color = html_color_for(new_color) # are we already in hash? if last_hash != "": # is it the different to this one? if last_hash != this_hash: # ok, close the span output_strings.append("</span>") # start a new span output_strings.append( f"<span title='{this_message}' style=\"background-color:{hex_color}\">" ) else: output_strings.append( f"<span title='{this_message}' style=\"background-color:{hex_color}\">" ) elif last_hash != "": output_strings.append("</span>") # just check if it's newline if letter == "\n": output_strings.append("<br>") else: # Escape the letter as otherwise the XML from XML files gets # interpreted by browsers as (invalid) HTML output_strings.append(html.escape(letter)) last_hash = this_hash if last_hash != "": output_strings.append("</span>") # also provide a key if include_key: output_strings.append("<hr/><h3>Color Key</h3><ul>") for key in dict_colors: color = dict_colors[key] hex_color = html_color_for(color) output_strings.append( f'<li><span style="background-color:{hex_color}">{key}</span></li>' ) output_strings.append("</ul>") html_footer = """</body> </html>""" output_strings.append(html_footer) with open(filename, "w") as f: f.write("".join(output_strings))	[ 1, 1053, 3472, 13, 13, 3166, 260, 29939, 18933, 1053, 260, 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app/routers/openstack/sizes.py	skyworkflows/swm-cloud-gate	3	46341	<reponame>skyworkflows/swm-cloud-gate import typing from fastapi import APIRouter, Header from .connector import OpenStackConnector from .models import convert_to_flavor CONNECTOR = OpenStackConnector() ROUTER = APIRouter() @ROUTER.get("/openstack/flavors") async def list_flavors(username: str = Header(None), password: str = Header(None)): CONNECTOR.reinitialize(username, password, "compute") flavor_list: typing.List[ImageInfo] = [] for item in CONNECTOR.list_sizes(): flavor_list.append(convert_to_flavor(item)) return {"flavors": flavor_list}	[ 1, 529, 276, 1112, 420, 29958, 7912, 1287, 1731, 29879, 29914, 2774, 29885, 29899, 9274, 29899, 17062, 13, 5215, 19229, 13, 13, 3166, 5172, 2754, 1053, 3450, 23971, 29892, 19345, 13, 13, 3166, 869, 11958, 2801, 1053, 4673, 7264, 20971, 2801, 13, 3166, 869, 9794, 1053, 3588, 29918, 517, 29918, 29888, 4112, 272, 13, 13, 6007, 8186, 1783, 1955, 353, 4673, 7264, 20971, 2801, 580, 13, 1672, 2692, 1001, 353, 3450, 23971, 580, 13, 13, 13, 29992, 1672, 2692, 1001, 29889, 657, 11974, 3150, 1429, 29914, 29888, 4112, 943, 1159, 13, 12674, 822, 1051, 29918, 29888, 4112, 943, 29898, 6786, 29901, 851, 353, 19345, 29898, 8516, 511, 4800, 29901, 851, 353, 19345, 29898, 8516, 22164, 13, 1678, 8707, 8186, 1783, 1955, 29889, 276, 24926, 29898, 6786, 29892, 4800, 29892, 376, 26017, 1159, 13, 1678, 21054, 272, 29918, 1761, 29901, 19229, 29889, 1293, 29961, 2940, 3401, 29962, 353, 5159, 13, 1678, 363, 2944, 297, 8707, 8186, 1783, 1955, 29889, 1761, 29918, 29879, 7093, 7295, 13, 4706, 21054, 272, 29918, 1761, 29889, 4397, 29898, 13441, 29918, 517, 29918, 29888, 4112, 272, 29898, 667, 876, 13, 1678, 736, 8853, 29888, 4112, 943, 1115, 21054, 272, 29918, 1761, 29913, 13, 2 ]
state/state_example_01.py	brandaoplaster/learning-design-patterns-in-python	0	1601781	from __future__ import annotations from abc import ABC, abstractmethod class Order: """ Context """ def __init__(self) -> None: self.state: OrderState = PaymentPending(self) def pending(self) -> None: print("Trying to pending()") self.state.pending() print("Current state ~>", self.state) print() def approve(self) -> None: print("Trying to run approve()") self.state.approve() print("Current state ~>", self.state) print() def reject(self) -> None: print("Trying to reject()") self.state.reject() print("Current state ~>", self.state) print() class OrderState(ABC): def __init__(self, order: Order) -> None: self.order = order @abstractmethod def pending(self) -> None: pass @abstractmethod def approve(self) -> None: pass @abstractmethod def reject(self) -> None: pass def __str__(self): return self.__class__.__name__ class PaymentPending(OrderState): def pending(self) -> None: print("payment declined") def approve(self) -> None: self.order.state = PaymentApproved(self.order) print("payment declined") def reject(self) -> None: self.order.state = PaymentRejected(self.order) print() class PaymentApproved(OrderState): def pending(self) -> None: self.order.state = PaymentPending(self.order) print("pending payment") def approve(self) -> None: print("Payment already approved") def reject(self) -> None: self.order.state = PaymentRejected(self.order) print("payment declined") class PaymentRejected(OrderState): def pending(self) -> None: print("Payment declined. I will not move to pending.") def approve(self) -> None: print("payment declined") def reject(self) -> None: print("payment declined") if __name__ == "__main__": order = Order() order.pending() order.approve() order.pending() order.reject() order.pending() order.approve()	[ 1, 515, 4770, 29888, 9130, 1649, 1053, 25495, 13, 3166, 25638, 1053, 16417, 29892, 9846, 5696, 13, 13, 1990, 8170, 29901, 13, 29871, 9995, 15228, 9995, 13, 13, 29871, 822, 4770, 2344, 12035, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 3859, 29901, 8170, 2792, 353, 14617, 358, 29925, 2548, 29898, 1311, 29897, 13, 13, 29871, 822, 28235, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 15870, 292, 304, 28235, 580, 1159, 13, 1678, 1583, 29889, 3859, 29889, 29886, 2548, 580, 13, 1678, 1596, 703, 7583, 2106, 3695, 28341, 1583, 29889, 3859, 29897, 13, 1678, 1596, 580, 13, 13, 29871, 822, 2134, 345, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 15870, 292, 304, 1065, 2134, 345, 580, 1159, 13, 1678, 1583, 29889, 3859, 29889, 9961, 345, 580, 13, 1678, 1596, 703, 7583, 2106, 3695, 28341, 1583, 29889, 3859, 29897, 13, 1678, 1596, 580, 13, 13, 29871, 822, 12560, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 15870, 292, 304, 12560, 580, 1159, 13, 1678, 1583, 29889, 3859, 29889, 276, 622, 580, 13, 1678, 1596, 703, 7583, 2106, 3695, 28341, 1583, 29889, 3859, 29897, 13, 1678, 1596, 580, 13, 13, 1990, 8170, 2792, 29898, 19658, 1125, 13, 13, 29871, 822, 4770, 2344, 12035, 1311, 29892, 1797, 29901, 8170, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 2098, 353, 1797, 13, 13, 29871, 732, 16595, 5696, 13, 29871, 822, 28235, 29898, 1311, 29897, 1599, 6213, 29901, 1209, 13, 13, 29871, 732, 16595, 5696, 13, 29871, 822, 2134, 345, 29898, 1311, 29897, 1599, 6213, 29901, 1209, 13, 13, 29871, 732, 16595, 5696, 13, 29871, 822, 12560, 29898, 1311, 29897, 1599, 6213, 29901, 1209, 13, 13, 29871, 822, 4770, 710, 12035, 1311, 1125, 13, 1678, 736, 1583, 17255, 1990, 1649, 17255, 978, 1649, 13, 13, 259, 13, 1990, 14617, 358, 29925, 2548, 29898, 7514, 2792, 1125, 13, 13, 29871, 822, 28235, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 27825, 4845, 1312, 1159, 13, 13, 29871, 822, 2134, 345, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 2098, 29889, 3859, 353, 14617, 358, 2052, 307, 1490, 29898, 1311, 29889, 2098, 29897, 13, 1678, 1596, 703, 27825, 4845, 1312, 1159, 13, 13, 29871, 822, 12560, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 2098, 29889, 3859, 353, 14617, 358, 1123, 622, 287, 29898, 1311, 29889, 2098, 29897, 13, 1678, 1596, 580, 13, 13, 13, 1990, 14617, 358, 2052, 307, 1490, 29898, 7514, 2792, 1125, 13, 29871, 822, 28235, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 2098, 29889, 3859, 353, 14617, 358, 29925, 2548, 29898, 1311, 29889, 2098, 29897, 13, 1678, 1596, 703, 29886, 2548, 19179, 1159, 13, 13, 29871, 822, 2134, 345, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 15467, 358, 2307, 23454, 1159, 13, 13, 29871, 822, 12560, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1583, 29889, 2098, 29889, 3859, 353, 14617, 358, 1123, 622, 287, 29898, 1311, 29889, 2098, 29897, 13, 1678, 1596, 703, 27825, 4845, 1312, 1159, 13, 13, 13, 1990, 14617, 358, 1123, 622, 287, 29898, 7514, 2792, 1125, 13, 29871, 822, 28235, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 15467, 358, 4845, 1312, 29889, 306, 674, 451, 4337, 304, 28235, 23157, 13, 13, 29871, 822, 2134, 345, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 27825, 4845, 1312, 1159, 13, 13, 29871, 822, 12560, 29898, 1311, 29897, 1599, 6213, 29901, 13, 1678, 1596, 703, 27825, 4845, 1312, 1159, 13, 13, 13, 361, 4770, 978, 1649, 1275, 376, 1649, 3396, 1649, 1115, 13, 29871, 1797, 353, 8170, 580, 13, 29871, 1797, 29889, 29886, 2548, 580, 13, 29871, 1797, 29889, 9961, 345, 580, 13, 29871, 1797, 29889, 29886, 2548, 580, 13, 29871, 1797, 29889, 276, 622, 580, 13, 29871, 1797, 29889, 29886, 2548, 580, 13, 29871, 1797, 29889, 9961, 345, 580, 2 ]
data_structures/stacks_and_queues/stack/node.py	michaelsklepowich/data_structures_and_algorithms	0	125455	class Node: def __init__(self, value, _next=None): self._value = value self._next = _next def __str__(self): return f'{self._value}' def __repr__(self): return f'<Node \| Val: {self._value} \| Next: {self._next}>'	[ 1, 770, 9071, 29901, 13, 1678, 822, 4770, 2344, 12035, 1311, 29892, 995, 29892, 903, 4622, 29922, 8516, 1125, 13, 4706, 1583, 3032, 1767, 353, 995, 13, 4706, 1583, 3032, 4622, 353, 903, 4622, 13, 13, 1678, 822, 4770, 710, 12035, 1311, 1125, 13, 4706, 736, 285, 29915, 29912, 1311, 3032, 1767, 10162, 13, 13, 1678, 822, 4770, 276, 558, 12035, 1311, 1125, 13, 4706, 736, 285, 29915, 29966, 4247, 891, 2630, 29901, 426, 1311, 3032, 1767, 29913, 891, 8084, 29901, 426, 1311, 3032, 4622, 29913, 16299, 13, 2 ]
01_Diag_Dispersion_Bicis.py	JosefinaMedina/Deep-Learning-2021-P1	0	91804	<gh_stars>0 import matplotlib.pyplot as plt import pandas as pd import seaborn as sns import os import chardet os.chdir('../Datos//') nomArch = 'SeoulBikeData.csv' with open(nomArch, 'rb') as f: result = chardet.detect(f.read()) df= pd.read_csv(nomArch, encoding=result['encoding']) print(df.dtypes) sns.heatmap(df[['Temperature(°C)','Rented Bike Count','Humidity(%)','Visibility (10m)']].corr(), square=True, annot=True) plt.figure() plt.scatter(df['Temperature(°C)'],df['Rented Bike Count'], marker='o') plt.xlabel('Temperature(°C)') plt.ylabel('Rented Bike Count') plt.figure() plt.scatter(df['Humidity(%)'],df['Visibility (10m)'], marker='o') plt.xlabel('Humidity(%)') plt.ylabel('Visibility (10m)')	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 5215, 22889, 29889, 2272, 5317, 408, 14770, 30004, 13, 5215, 11701, 408, 10518, 30004, 13, 5215, 409, 370, 1398, 408, 269, 1983, 30004, 13, 5215, 2897, 30004, 13, 5215, 521, 538, 300, 30004, 13, 30004, 13, 359, 29889, 305, 3972, 877, 6995, 6086, 458, 1495, 30004, 13, 11522, 13197, 353, 525, 2008, 5059, 29933, 9345, 1469, 29889, 7638, 29915, 30004, 13, 2541, 1722, 29898, 11522, 13197, 29892, 525, 6050, 1495, 408, 285, 29901, 30004, 13, 1678, 1121, 353, 521, 538, 300, 29889, 4801, 522, 29898, 29888, 29889, 949, 3101, 29871, 6756, 13, 30004, 13, 2176, 29922, 10518, 29889, 949, 29918, 7638, 29898, 11522, 13197, 29892, 8025, 29922, 2914, 1839, 22331, 2033, 8443, 13, 30004, 13, 2158, 29898, 2176, 29889, 29881, 8768, 8443, 13, 30004, 13, 29879, 1983, 29889, 354, 271, 1958, 29898, 2176, 29961, 1839, 5776, 546, 1535, 29898, 30073, 29907, 29897, 3788, 29934, 14927, 3457, 446, 3917, 3788, 29950, 398, 333, 537, 29898, 10997, 3788, 23318, 313, 29896, 29900, 29885, 29897, 2033, 1822, 29725, 3285, 6862, 29922, 5574, 29892, 9732, 29922, 5574, 8443, 13, 30004, 13, 572, 29873, 29889, 4532, 26471, 13, 572, 29873, 29889, 1557, 2620, 29898, 2176, 1839, 5776, 546, 1535, 29898, 30073, 29907, 29897, 7464, 2176, 1839, 29934, 14927, 3457, 446, 3917, 7464, 17456, 2433, 29877, 1495, 30004, 13, 572, 29873, 29889, 29916, 1643, 877, 5776, 546, 1535, 29898, 30073, 29907, 29897, 1495, 30004, 13, 572, 29873, 29889, 29891, 1643, 877, 29934, 14927, 3457, 446, 3917, 1495, 30004, 13, 30004, 13, 572, 29873, 29889, 4532, 26471, 13, 572, 29873, 29889, 1557, 2620, 29898, 2176, 1839, 29950, 398, 333, 537, 29898, 10997, 7464, 2176, 1839, 23318, 313, 29896, 29900, 29885, 29897, 7464, 17456, 2433, 29877, 1495, 30004, 13, 572, 29873, 29889, 29916, 1643, 877, 29950, 398, 333, 537, 29898, 10997, 1495, 30004, 13, 572, 29873, 29889, 29891, 1643, 877, 23318, 313, 29896, 29900, 29885, 29897, 1495, 30004, 13, 30004, 13, 2 ]
IoT/presentation/plots/step_plot.py	Mohitsharma44/CUSP-GX-6004-C	5	53208	import matplotlib.pyplot as plt import numpy as np plt.style.use('seaborn-darkgrid') x = range(8) y = np.linspace(1.1, 5.0, 8) ylabel = map(lambda num: bin(num)[2:], x) xlabel = map(lambda num: "{0:.2f}".format(num), y) plt.step(x, y) plt.yticks(y, ylabel) plt.xticks(x, xlabel, rotation=45) plt.ylabel("Binary Output") plt.xlabel("Analog Input") plt.savefig("adc.png", transparent=True)	[ 1, 1053, 22889, 29889, 2272, 5317, 408, 14770, 13, 5215, 12655, 408, 7442, 13, 572, 29873, 29889, 3293, 29889, 1509, 877, 344, 370, 1398, 29899, 26031, 7720, 1495, 13, 13, 29916, 353, 3464, 29898, 29947, 29897, 13, 29891, 353, 7442, 29889, 1915, 3493, 29898, 29896, 29889, 29896, 29892, 29871, 29945, 29889, 29900, 29892, 29871, 29947, 29897, 13, 13, 29891, 1643, 353, 2910, 29898, 2892, 954, 29901, 9016, 29898, 1949, 9601, 29906, 29901, 1402, 921, 29897, 13, 29916, 1643, 353, 2910, 29898, 2892, 954, 29901, 29850, 29900, 29901, 29889, 29906, 29888, 29913, 1642, 4830, 29898, 1949, 511, 343, 29897, 13, 13, 572, 29873, 29889, 10568, 29898, 29916, 29892, 343, 29897, 13, 572, 29873, 29889, 3637, 7358, 29898, 29891, 29892, 343, 1643, 29897, 13, 572, 29873, 29889, 486, 7358, 29898, 29916, 29892, 921, 1643, 29892, 13733, 29922, 29946, 29945, 29897, 13, 572, 29873, 29889, 29891, 1643, 703, 25196, 10604, 1159, 13, 572, 29873, 29889, 29916, 1643, 703, 21067, 468, 10567, 1159, 13, 572, 29873, 29889, 7620, 1003, 703, 328, 29883, 29889, 2732, 613, 17772, 29922, 5574, 29897, 13, 2 ]
robot-server/tests/service/json_api/test_response.py	mrod0101/opentrons	0	2129	<filename>robot-server/tests/service/json_api/test_response.py from pytest import raises from pydantic import ValidationError from robot_server.service.json_api.response import ( ResponseDataModel, ResponseModel, MultiResponseModel, ) from tests.service.helpers import ItemResponseModel def test_attributes_as_dict() -> None: MyResponse = ResponseModel[ResponseDataModel, None] obj_to_validate = { "data": {"id": "123"}, "links": None, } my_response_object = MyResponse(obj_to_validate) assert my_response_object.dict() == { "links": None, "data": { "id": "123", }, } def test_attributes_as_item_model() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": {"id": "123", "name": "apple", "quantity": 10, "price": 1.20}, } my_response_obj = ItemResponse(obj_to_validate) assert my_response_obj.dict() == { "links": None, "data": { "id": "123", "name": "apple", "quantity": 10, "price": 1.20, }, } def test_list_item_model() -> None: ItemResponse = MultiResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": [ {"id": "123", "name": "apple", "quantity": 10, "price": 1.20}, {"id": "321", "name": "banana", "quantity": 20, "price": 2.34}, ], } my_response_obj = ItemResponse(obj_to_validate) assert my_response_obj.dict() == { "links": None, "data": [ { "id": "123", "name": "apple", "quantity": 10, "price": 1.20, }, { "id": "321", "name": "banana", "quantity": 20, "price": 2.34, }, ], } def test_attributes_as_item_model_empty_dict() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": { "id": "123", }, } with raises(ValidationError) as e: ItemResponse(obj_to_validate) assert e.value.errors() == [ { "loc": ("data", "name"), "msg": "field required", "type": "value_error.missing", }, { "loc": ("data", "quantity"), "msg": "field required", "type": "value_error.missing", }, { "loc": ("data", "price"), "msg": "field required", "type": "value_error.missing", }, ] def test_response_constructed_with_resource_object() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] item = ItemResponseModel(id="abc123", name="pear", price=1.2, quantity=10) data = item.dict() assert ItemResponse(data=data, links=None).dict() == { "links": None, "data": { "id": "abc123", "name": "pear", "price": 1.2, "quantity": 10, }, } def test_response_constructed_with_resource_object_list() -> None: ItemResponse = MultiResponseModel[ItemResponseModel, None] items = [ ItemResponseModel(id="1", name="apple", price=1.5, quantity=3), ItemResponseModel(id="2", name="pear", price=1.2, quantity=10), ItemResponseModel(id="3", name="orange", price=2.2, quantity=5), ] response = ItemResponse(data=items, links=None) assert response.dict() == { "links": None, "data": [ { "id": "1", "name": "apple", "price": 1.5, "quantity": 3, }, { "id": "2", "name": "pear", "price": 1.2, "quantity": 10, }, 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WorkingExamples/MNIST_Worker.py	iansee/FYP	0	1617385	import tensorflow as tf import h5py import collections import six from syft.workers.websocket_server import WebsocketServerWorker import torch import sys import syft import sys import argparse from torchvision import datasets from torchvision import transforms import numpy as np import tensorflow_federated as tff import os.path from tensorflow_federated.python.simulation.hdf5_client_data import HDF5ClientData fractionToUse = 5 class TrainDataset: def __init__(self,transform=None, id="h2"): fileprefix = "fed_emnist_digitsonly" dir_path = os.path.dirname("/home/mininet/") train = HDF5ClientData(os.path.join(dir_path, fileprefix + '_train.h5')) trainFile = h5py.File(os.path.join(dir_path, fileprefix + '_train.h5'), "r") _EXAMPLES_GROUP = "examples" numberofclients = len(train.client_ids) data = np.empty((0,28,28), np.float32) target = np.empty((0), np.int_) if id == "h2": offset = 0 elif id == "h3": offset = 1 elif id == "h4": offset = 2 for i in range(int(numberofclients/(3fractionToUse))): clientdataset = collections.OrderedDict((name, ds[()]) for name, ds in sorted( six.iteritems(trainFile[HDF5ClientData._EXAMPLES_GROUP][train.client_ids[i3*fractionToUse+offset]]))) data = np.concatenate((data, clientdataset['pixels'])) target = np.concatenate((target, clientdataset['label']), axis=0) self.target = list(target) self.data = list(data) self.transform = transform def __getitem__(self, index): x=self.data[index] y=self.target[index] if self.transform: x = self.transform(x) return x,y def __len__(self): return len(self.target) def main(_id,ip): mnist_dataset = TrainDataset(transform=transforms.Compose([ transforms.ToTensor(), transforms.Normalize( (0.1307,), (0.3081,)) ]), id=_id) hook = syft.TorchHook(torch) server = WebsocketServerWorker(id = _id,host =ip, port = 8778,hook=hook,verbose=True) print ("Worker:{}, Dataset contains {}".format(_id,str(len(mnist_dataset.data)))) dataset = syft.BaseDataset( data=mnist_dataset.data, targets=mnist_dataset.target, transform=mnist_dataset.transform ) key = "targeted" server.add_dataset(dataset, key=key) server.start() main (sys.argv[1], sys.argv[2])	[ 1, 29871, 13, 5215, 26110, 408, 15886, 13, 5215, 298, 29945, 2272, 13, 5215, 16250, 13, 5215, 4832, 13, 13, 3166, 9878, 615, 29889, 1287, 414, 29889, 2676, 11514, 29918, 2974, 1053, 2563, 11514, 6004, 16164, 13, 5215, 4842, 305, 13, 5215, 10876, 13, 5215, 9878, 615, 13, 5215, 10876, 13, 5215, 1852, 5510, 13, 3166, 4842, 305, 4924, 1053, 20035, 13, 3166, 4842, 305, 4924, 1053, 4327, 29879, 13, 5215, 12655, 408, 7442, 13, 13, 5215, 26110, 29918, 29888, 2447, 630, 408, 260, 600, 13, 5215, 2897, 29889, 2084, 13, 3166, 26110, 29918, 29888, 2447, 630, 29889, 4691, 29889, 3601, 2785, 29889, 29882, 2176, 29945, 29918, 4645, 29918, 1272, 1053, 379, 4037, 29945, 4032, 1469, 13, 13, 29888, 13857, 1762, 11403, 353, 29871, 29945, 13, 13, 1990, 28186, 16390, 24541, 29901, 13, 1678, 822, 4770, 2344, 12035, 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ui/controller/user_handler.py	ctwardy/sitehound	0	65811	from ui import app, Singleton import json from dao.JsonDatetimeEncoder import MyEncoder from ui import app from flask import Response, request, jsonify from utils.json_encoder import JSONEncoder from flask_login import login_required from flask_security import roles_required, utils from mongoengine import NotUniqueError from controller.InvalidException import InvalidUsage from service.user_service import get_all, delete, updateUser, get_all_roles __author__ = 'tomas' @app.route("/api/role", methods=['GET']) @login_required @roles_required('admin') def get_all_roles_api(): in_doc = get_all_roles() out_doc = MyEncoder(JSONEncoder()).encode(in_doc) return Response(json.dumps(out_doc, cls = MyEncoder), mimetype="application/json") @app.route("/api/user", methods=['GET']) @login_required @roles_required('admin') def get_all_api(): in_doc = get_all() out_doc = MyEncoder(JSONEncoder()).encode(in_doc) return Response(json.dumps(out_doc, cls = MyEncoder), mimetype="application/json") @app.route("/api/user/<id>", methods=['PUT']) @app.errorhandler(InvalidUsage) @login_required @roles_required('admin') def activate_api(id): roles = None isActive = None if 'roles' in request.json: roles = request.json['roles'] if 'isActive' in request.json: isActive = bool(request.json['isActive']) if isActive is None and roles is None: raise InvalidUsage("no update provided", status_code=409) updateUser(id, isActive, roles) return Response("{}", mimetype="application/json") @app.route("/api/user/<id>", methods=['DELETE']) @login_required @roles_required('admin') def delete_api(id): delete(id) return Response("{}", mimetype="application/json") @login_required @roles_required('admin') @app.errorhandler(InvalidUsage) @app.route('/api/user/<username>', methods=['POST']) def create_account(username): password = request.json['password'] encrypted_password = utils.encrypt_password(password) try: Singleton.getInstance().user_datastore.create_user( email=username, password=<PASSWORD>, roles=[], active=True, login_count=0) except NotUniqueError as ex: raise InvalidUsage('An username with that email already exists', status_code=409) return Response("{}", mimetype="application/json")	[ 1, 29871, 13, 3166, 14313, 1053, 623, 29892, 6106, 11285, 13, 13, 13, 5215, 4390, 13, 13, 3166, 1146, 29877, 29889, 8148, 16390, 5410, 8566, 6119, 1053, 1619, 8566, 6119, 13, 3166, 14313, 1053, 623, 13, 3166, 29784, 1053, 13291, 29892, 2009, 29892, 4390, 1598, 13, 3166, 3667, 29879, 29889, 3126, 29918, 3977, 6119, 1053, 4663, 8566, 6119, 13, 3166, 29784, 29918, 7507, 1053, 6464, 29918, 12403, 13, 3166, 29784, 29918, 8926, 1053, 16178, 29918, 12403, 29892, 3667, 29879, 13, 3166, 19476, 10599, 1053, 2216, 8110, 802, 2392, 13, 13, 3166, 4701, 29889, 13919, 2451, 1053, 21403, 27573, 13, 3166, 2669, 29889, 1792, 29918, 5509, 1053, 679, 29918, 497, 29892, 5217, 29892, 2767, 2659, 29892, 679, 29918, 497, 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scripts/python/lib/bmc.py	purushammi/power-up	0	75435	<filename>scripts/python/lib/bmc.py #!/usr/bin/env python3 # Copyright 2019 IBM Corp. # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import argparse import time import requests.exceptions import lib.logger as logger import lib.open_bmc as open_bmc import lib.ipmi as ipmi class Bmc(object): """ Creates a 'bmc' class instance. The created class establishes a connection to a BMC. The connection can be openBMC rest API or IPMI. Args: host (str): ip address or resolvable hostname. user (str): <NAME> pw (str): <PASSWORD> bmc_type (str): Indicates the type of BMC ('ipmi' or 'openbmc') """ def __init__(self, host, user, pw, bmc_type='ipmi', timeout=10): self.log = logger.getlogger() self.host = host self.user = user self.pw = pw self.bmc_type = bmc_type self.timeout = timeout self.connected = False if bmc_type == 'openbmc': self.bmc = open_bmc.login(host, user, pw) if isinstance(self.bmc, requests.sessions.Session): self.connected = True elif bmc_type == 'ipmi': self.bmc = ipmi.login(host, user, pw) if isinstance(self.bmc, ipmi.command.Command): self.connected = True else: self.log.error(f'Unsupported BMC type: {bmc_type}') def is_connected(self): return self.connected def get_host(self): return self.host def logout(self): if self.bmc_type == 'openbmc': return open_bmc.logout(self.host, self.user, self.pw, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.logout(self.host, self.user, self.pw, self.bmc) def chassis_power(self, op, timeout=5): if self.bmc_type == 'openbmc': return open_bmc.chassisPower(self.host, op, self.bmc) if self.bmc_type == 'ipmi': return ipmi.chassisPower(self.host, op, self.bmc) def host_boot_source(self, source='', timeout=5): if self.bmc_type == 'openbmc': return open_bmc.hostBootSource(self.host, source, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.hostBootSource(self.host, source, self.bmc) def host_boot_mode(self, mode='', timeout=5): if self.bmc_type == 'openbmc': return open_bmc.hostBootMode(self.host, mode, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.hostBootMode(self.host, mode, self.bmc) def bmc_reset(self, op): if self.bmc_type == 'openbmc': return open_bmc.bmcReset(self.host, op, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.bmcReset(self.host, op, self.bmc) def bmc_status(self, timeout=5): if self.bmc_type == 'openbmc': return open_bmc.bmcPowerState(self.host, self.bmc, timeout) elif self.bmc_type == 'ipmi': return 'Ready' if __name__ == '__main__': """Show status of the Cluster Genesis environment Args: INV_FILE (string): Inventory file. LOG_LEVEL (string): Log level. Raises: Exception: If parameter count is invalid. """ logger.create('debug', 'debug') log = logger.getlogger() parser = argparse.ArgumentParser() parser.add_argument('host', nargs='?', help='bmc ip address', default='') parser.add_argument('user', nargs='?', help='bmc user', default='ADMIN') parser.add_argument('pw', nargs='?', help='bmc password', default='<PASSWORD>') # parser.add_argument('user', nargs='?', # help='bmc user', # default='root') # # parser.add_argument('pw', nargs='?', # help='bmc password', # default='<PASSWORD>') parser.add_argument('bmc_type', nargs='?', choices=['open', 'ipmi'], help='bmc type (open, ipmi)', default='ipmi') parser.add_argument('--print', '-p', dest='log_lvl_print', help='print log level', default='info') parser.add_argument('--file', '-f', dest='log_lvl_file', help='file log level', default='info') args = parser.parse_args() if not args.host: args.host = input('Enter bmc ip address: ') bmc = Bmc(args.host, args.user, args.pw, args.bmc_type) if bmc.is_connected(): print(f'logged into BMC {bmc}') if args.bmc_type in ('open', 'ipmi'): bmc_status = bmc.bmc_status() print(f'BMC status: {bmc_status}') # print('Rebooting bmc') # r = bmc.bmc_reset('cold') # print(f'BMC response: {r}') # if not r: # log.error(f'Failed reboot of bmc {args.host}.') # else: # print('Attempting BMC logout...') # if bmc.logout(): # print(f'Logged out of BMC {args.host}') # else: # log.debug(f'Failed to log out of BMC {args.host}') # del bmc # print('Setting host boot mode') # r = bmc.host_boot_mode('regular') # get boot source # r = bmc.host_boot_source() # print(f'host boot source: {r}') # source = 'network' # source = 'default' # print(f'Setting host boot source to {source}') # r = bmc.host_boot_source(source) # print('clossing BMC connection') # bmc.logout() print('Attempting to log back into BMC') while True: bmc = Bmc(args.host, args.user, args.pw, args.bmc_type) if bmc.is_connected(): print(f'\nsuccessfully logged back into {args.host}') break else: print('Failed login attempt') time.sleep(3) else: log.error('Failed to instantiate the bmc class') print('done')	[ 1, 529, 9507, 29958, 16713, 29914, 4691, 29914, 1982, 29914, 5838, 29883, 29889, 2272, 13, 29937, 14708, 4855, 29914, 2109, 29914, 6272, 3017, 29941, 13, 29937, 14187, 1266, 29871, 29906, 29900, 29896, 29929, 27955, 2994, 29886, 29889, 13, 29937, 13, 29937, 2178, 26863, 2538, 9841, 29889, 13, 29937, 13, 29937, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 13, 29937, 366, 1122, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 13, 29937, 887, 1122, 4017, 263, 3509, 310, 278, 19245, 472, 13, 29937, 13, 29937, 268, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 13, 29937, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 13, 29937, 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5838, 29883, 29889, 1188, 449, 29898, 1311, 29889, 3069, 29892, 1583, 29889, 1792, 29892, 1583, 29889, 29886, 29893, 29892, 1583, 29889, 5838, 29883, 29897, 13, 4706, 25342, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 666, 2460, 2396, 13, 9651, 736, 10377, 2460, 29889, 1188, 449, 29898, 1311, 29889, 3069, 29892, 1583, 29889, 1792, 29892, 1583, 29889, 29886, 29893, 29892, 1583, 29889, 5838, 29883, 29897, 13, 13, 1678, 822, 521, 465, 275, 29918, 13519, 29898, 1311, 29892, 1015, 29892, 11815, 29922, 29945, 1125, 13, 4706, 565, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 3150, 5838, 29883, 2396, 13, 9651, 736, 1722, 29918, 5838, 29883, 29889, 305, 465, 275, 21472, 29898, 1311, 29889, 3069, 29892, 1015, 29892, 1583, 29889, 5838, 29883, 29897, 13, 4706, 565, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 666, 2460, 2396, 13, 9651, 736, 10377, 2460, 29889, 305, 465, 275, 21472, 29898, 1311, 29889, 3069, 29892, 1015, 29892, 1583, 29889, 5838, 29883, 29897, 13, 13, 1678, 822, 3495, 29918, 4777, 29918, 4993, 29898, 1311, 29892, 2752, 2433, 742, 11815, 29922, 29945, 1125, 13, 4706, 565, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 3150, 5838, 29883, 2396, 13, 9651, 736, 1722, 29918, 5838, 29883, 29889, 3069, 20967, 4435, 29898, 1311, 29889, 3069, 29892, 2752, 29892, 1583, 29889, 5838, 29883, 29897, 13, 4706, 25342, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 666, 2460, 2396, 13, 9651, 736, 10377, 2460, 29889, 3069, 20967, 4435, 29898, 1311, 29889, 3069, 29892, 2752, 29892, 1583, 29889, 5838, 29883, 29897, 13, 13, 1678, 822, 3495, 29918, 4777, 29918, 8513, 29898, 1311, 29892, 4464, 2433, 742, 11815, 29922, 29945, 1125, 13, 4706, 565, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 3150, 5838, 29883, 2396, 13, 9651, 736, 1722, 29918, 5838, 29883, 29889, 3069, 20967, 6818, 29898, 1311, 29889, 3069, 29892, 4464, 29892, 1583, 29889, 5838, 29883, 29897, 13, 4706, 25342, 1583, 29889, 5838, 29883, 29918, 1853, 1275, 525, 666, 2460, 2396, 13, 9651, 736, 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backend/base/urls/order_urls.py	danylott/sale-rent-real-estate-platform	0	155565	from django.urls import path from base.views import order_views as views urlpatterns = [ path("", views.get_orders, name="orders"), path("add/", views.add_order_items, name="orders-add"), path("myorders/", views.get_my_orders, name="myorders"), path("<str:pk>/", views.get_order_by_id, name="user-order"), path("<str:pk>/deliver/", views.update_order_to_delivered, name="order-delivered"), path("<str:pk>/pay/", views.update_order_to_paid, name="pay"), ]	[ 1, 515, 9557, 29889, 26045, 1053, 2224, 13, 13, 3166, 2967, 29889, 7406, 1053, 1797, 29918, 7406, 408, 8386, 13, 13, 2271, 11037, 29879, 353, 518, 13, 1678, 2224, 703, 613, 8386, 29889, 657, 29918, 20488, 29892, 1024, 543, 20488, 4968, 13, 1678, 2224, 703, 1202, 29914, 613, 8386, 29889, 1202, 29918, 2098, 29918, 7076, 29892, 1024, 543, 20488, 29899, 1202, 4968, 13, 1678, 2224, 703, 1357, 20488, 29914, 613, 8386, 29889, 657, 29918, 1357, 29918, 20488, 29892, 1024, 543, 1357, 20488, 4968, 13, 1678, 2224, 28945, 710, 29901, 20571, 20690, 613, 8386, 29889, 657, 29918, 2098, 29918, 1609, 29918, 333, 29892, 1024, 543, 1792, 29899, 2098, 4968, 13, 1678, 2224, 28945, 710, 29901, 20571, 20690, 6144, 2147, 29914, 613, 8386, 29889, 5504, 29918, 2098, 29918, 517, 29918, 6144, 2147, 287, 29892, 1024, 543, 2098, 29899, 6144, 2147, 287, 4968, 13, 1678, 2224, 28945, 710, 29901, 20571, 20690, 10472, 29914, 613, 8386, 29889, 5504, 29918, 2098, 29918, 517, 29918, 3274, 333, 29892, 1024, 543, 10472, 4968, 13, 29962, 13, 2 ]
value_based_1.py	frankfangy/gridlab	0	32200	<reponame>frankfangy/gridlab # -- coding: utf-8 -- ''' 这个来源于 udacity 的讲座验证基础的概念和算法 ''' from grid_world import * import sys #from PyQt5.QtCore import QPoint, QRect, QSize, Qt #from PyQt5.QtGui import (QBrush, QPainter, QColor, QPen ) #from PyQt5.QtWidgets import (QApplication, QPushButton, QCheckBox, QGridLayout,QLabel, QWidget, QInputDialog) from PyQt5.QtWidgets import ( QLabel , QTextEdit , QPlainTextEdit , QLineEdit ) import numpy as np from random import randint import time from math import fabs class value_based(grid_world): ''' 用来实验各种算法，并图形展示，基于方块地图 ''' def __init__(self): super(value_based, self).__init__() def config_map(self): # 地图大小 , 初始map , 供子类再定义 self.map_mask = ''' 1113 1214 1111 ''' # map mask must be plus i8 (0 ~ 127 ) def config_gui(self): super(value_based, self).config_gui() self.add_ctrl( QLabel , '移动奖励' ) self.edit_moving_reward = self.add_ctrl( QLineEdit , '-0.04' , 15 ) self.add_ctrl( QLabel , '绿位奖励' ) self.edit_green_reward = self.add_ctrl( QLineEdit , '+1' , 15 ) self.add_ctrl( QLabel , '红位奖励' ) self.edit_red_reward = self.add_ctrl( QLineEdit , '-1' , 15 ) self.add_ctrl( QLabel , '运动稳定度' ) self.edit_moving_stability = self.add_ctrl( QLineEdit , '0.8' , 15 ) self.block_size = 60 # using a bigger block def reset(self): ''' 初始化地图，以及计算条件，可能会反复运算 ''' self.moving_reward = float( self.edit_moving_reward.text() ) self.green_reward = float( self.edit_green_reward.text() ) self.red_reward = float( self.edit_red_reward.text() ) self.moving_stability = float( self.edit_moving_stability.text() ) print('get config :',self.moving_reward , self.green_reward , self.red_reward , self.moving_stability ) # init value self.value_init = -100 self.value = np.zeros( ( self.map_width , self.map_height ) , float ) for x in range(self.map_width): for y in range(self.map_height): mpv = self.map[x][y] self.value[x][y] = {1:self.value_init , 2:self.value_init , 3: self.green_reward , 4:self.red_reward }.get(mpv,0) self.show_direction = False self.update() def avaliable_for_value(self,x,y): if x < 0 or x >= self.map_width or y < 0 or y >= self.map_height: return False return self.map[x][y] != 2 def calc_direction(self): self.direction = np.ndarray( ( self.map_width , self.map_height ) , dtype=np.int8 ) for x in range(self.map_width): for y in range(self.map_height): maxv = self.value_init ii = 4 # stay there if self.avaliable_for_value(x,y): v0 = self.value[x][y] for i in range(5): d = ((0,-1),(1,0),(0,1),(-1,0),(0,0))[i] nx = x + d[0] ny = y + d[1] if self.avaliable_for_value(nx,ny): if maxv < self.value[nx][ny] : ii = i maxv = self.value[nx][ny] self.direction[x][y] = ii self.show_direction = True def run_proc(self): ''' 此处是一个示范代码，子类应沿袭相同结构 ''' # setup flag self.running = True self.set_log('运算中') while self.running: updated = 0 self.value_old = self.value.copy() for x in range(self.map_width): for y in range(self.map_height): if self.map[x][y] == 1: v0 = self.value_old[x][y] maxv = self.value_init for i in range(4): d =((0,-1),(1,0),(0,1),(-1,0))[i] d1 =((-1,0),(0,-1),(1,0),(0,1))[i] d2 =((1,0),(0,1),(-1,0),(0,-1))[i] nx = x + d[0] ny = y + d[1] nx1 = x + d1[0] ny1 = y + d1[1] nx2 = x + d2[0] ny2 = y + d2[1] if self.avaliable_for_value(nx,ny): # this nx,ny is avaliable for value # 计算，如果向 nx ny 点移动，本地的value值可能是多少 v = self.value_old[nx][ny] * self.moving_stability if self.avaliable_for_value(nx1,ny1): v += (1.0-self.moving_stability )0.5 self.value_old[nx1][ny1] else: # 留在原地 v += (1-self.moving_stability )0.5 v0 if self.avaliable_for_value(nx2,ny2): v += (1-self.moving_stability )0.5 self.value_old[nx2][ny2] else: # 留在原地 v += (1-self.moving_stability )0.5 v0 if v > maxv: maxv = v # here we got the maxv if v0 - self.moving_reward < maxv: updated += fabs( v0 - maxv - self.moving_reward ) self.value[x][y] = maxv + self.moving_reward if updated < 1e-5 : break self.update() time.sleep(0.3) self.set_log('价值网络计算完成') self.calc_direction() self.running = False self.update() def draw_block(self, painter,x,y , block_map_value = None ): painter.save() if block_map_value is None: block_map_value = self.map[x][y] block_value = self.value[x][y] bkcolor = {0:(55,55,55) , 1:(222,255,222) , 2 :(111,111,111) , 3:(111,255,111) , 4:(255,0,0) }.get( block_map_value , (0,0,0) ) self.draw_background( painter, x,y , bkcolor ) if block_map_value == 1: # path block self.draw_text( painter , x,y , '%g'%(block_value) , (0,0,0) , 'd' ) if self.show_direction: self.draw_arrow(painter,x,y, 'urdlo'[ self.direction[x][y] ] , (255,0,0) , 'u' ) elif block_map_value != 2: # other self.draw_text( painter , x,y , str(block_value) , (0,0,0) , 'd' ) painter.restore() if __name__ == '__main__': run_gui( value_based )	[ 1, 529, 276, 1112, 420, 29958, 29888, 10003, 11363, 29891, 29914, 7720, 8205, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 6756, 13, 12008, 30004, 13, 30810, 30502, 30805, 31193, 30909, 11430, 5946, 29871, 30210, 235, 177, 181, 31780, 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29896, 29896, 29896, 29897, 1919, 29871, 29946, 5919, 29906, 29945, 29945, 29892, 29900, 29892, 29900, 29897, 500, 29889, 657, 29898, 2908, 29918, 1958, 29918, 1767, 1919, 313, 29900, 29892, 29900, 29892, 29900, 29897, 1723, 29871, 6756, 13, 4706, 1583, 29889, 4012, 29918, 7042, 29898, 23187, 29892, 921, 29892, 29891, 1919, 289, 29895, 2780, 29871, 1723, 30004, 13, 4706, 565, 2908, 29918, 1958, 29918, 1767, 1275, 29871, 29896, 29901, 396, 2224, 2908, 30004, 13, 9651, 1583, 29889, 4012, 29918, 726, 29898, 23187, 1919, 921, 29892, 29891, 1919, 29871, 14210, 29887, 29915, 29995, 29898, 1271, 29918, 1767, 29897, 1919, 313, 29900, 29892, 29900, 29892, 29900, 29897, 1919, 525, 29881, 29915, 29871, 1723, 30004, 13, 9651, 565, 1583, 29889, 4294, 29918, 20845, 29901, 30004, 13, 18884, 1583, 29889, 4012, 29918, 2936, 29898, 29886, 475, 357, 29892, 29916, 29892, 29891, 29892, 525, 18245, 417, 29915, 29961, 1583, 29889, 20845, 29961, 29916, 3816, 29891, 29962, 4514, 1919, 313, 29906, 29945, 29945, 29892, 29900, 29892, 29900, 29897, 1919, 29871, 525, 29884, 29915, 29871, 1723, 29871, 6756, 13, 4706, 25342, 2908, 29918, 1958, 29918, 1767, 2804, 29871, 29906, 29901, 396, 916, 30004, 13, 9651, 1583, 29889, 4012, 29918, 726, 29898, 23187, 1919, 921, 29892, 29891, 1919, 29871, 851, 29898, 1271, 29918, 1767, 29897, 1919, 313, 29900, 29892, 29900, 29892, 29900, 29897, 1919, 525, 29881, 29915, 29871, 1723, 30004, 13, 30004, 13, 4706, 23187, 29889, 5060, 487, 26471, 13, 30004, 13, 30004, 13, 30004, 13, 30004, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 29871, 6756, 13, 1678, 1065, 29918, 23569, 29898, 995, 29918, 6707, 1723, 6756, 13, 2 ]
BasicConcepts/SyntaxErrors/Volume1_Chapter6_SyntaxErrors_Fixed.py	jpike/PythonProgrammingForKids	0	37565	# Commenting syntax errors. print("Printing out a message!") # This is a comment. floating_point_number = 1.5 * 2.7	[ 1, 396, 461, 292, 5877, 4436, 29889, 13, 2158, 703, 11816, 292, 714, 263, 2643, 29991, 1159, 29871, 396, 910, 338, 263, 3440, 29889, 13, 29888, 417, 1218, 29918, 3149, 29918, 4537, 353, 29871, 29896, 29889, 29945, 334, 29871, 29906, 29889, 29955, 13, 2 ]
knox/serializers.py	liradb2000/django-rest-knox	0	177945	from django.contrib.auth import get_user_model from rest_framework import serializers from knox.models import AuthToken User = get_user_model() username_field = User.USERNAME_FIELD if hasattr(User, 'USERNAME_FIELD') else 'username' class UserSerializer(serializers.ModelSerializer): class Meta: model = User fields = (username_field,) class AuthTokenSerializer(serializers.ModelSerializer): class Meta: model = AuthToken fields = ('created', 'token_key')	[ 1, 515, 9557, 29889, 21570, 29889, 5150, 1053, 679, 29918, 1792, 29918, 4299, 13, 3166, 1791, 29918, 4468, 1053, 7797, 19427, 13, 3166, 889, 2251, 29889, 9794, 1053, 13189, 6066, 13, 2659, 353, 679, 29918, 1792, 29918, 4299, 580, 13, 13, 6786, 29918, 2671, 353, 4911, 29889, 11889, 5813, 29918, 3738, 27286, 565, 756, 5552, 29898, 2659, 29892, 525, 11889, 5813, 29918, 3738, 27286, 1495, 1683, 525, 6786, 29915, 13, 13, 13, 1990, 4911, 17679, 29898, 15550, 19427, 29889, 3195, 17679, 1125, 13, 1678, 770, 20553, 29901, 13, 4706, 1904, 353, 4911, 13, 4706, 4235, 353, 313, 6786, 29918, 2671, 29892, 29897, 13, 13, 1990, 13189, 6066, 17679, 29898, 15550, 19427, 29889, 3195, 17679, 1125, 13, 1678, 770, 20553, 29901, 13, 4706, 1904, 353, 13189, 6066, 13, 4706, 4235, 353, 6702, 11600, 742, 525, 6979, 29918, 1989, 1495, 2 ]
src/rgw/setup/rgw.py	Seagate/cortx-rgw-integration	2	91089	#!/usr/bin/python3 # Copyright (c) 2022 Seagate Technology LLC and/or its Affiliates # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <https://www.gnu.org/licenses/>. # For any questions about this software or licensing, # please email <EMAIL> or <EMAIL>. import os import shutil import time import errno import json from urllib.parse import urlparse from cortx.utils.security.certificate import Certificate from cortx.utils.errors import SSLCertificateError from cortx.utils.validator.v_pkg import PkgV from cortx.utils.conf_store import Conf, MappedConf from cortx.utils.conf_store.error import ConfError from cortx.utils.process import SimpleProcess from cortx.utils.schema.release import Release from cortx.utils.log import Log from cortx.rgw.setup.error import SetupError from cortx.rgw.setup.rgw_service import RgwService from cortx.utils.security.cipher import Cipher, CipherInvalidToken from cortx.rgw import const from cortx.utils.common import ExponentialBackoff class Rgw: """Represents RGW and Performs setup related actions.""" _machine_id = Conf.machine_id _conf_idx = f'{const.COMPONENT_NAME}_config' # e.g. rgw_config @staticmethod def validate(phase: str): """Perform validations.""" Log.info(f'validations started for {phase} phase.') if phase == 'post_install': # Perform RPM validations for rpms in [const.REQUIRED_RPMS]: PkgV().validate('rpms', rpms) Log.info(f'All RGW required RPMs are installed on {Rgw._machine_id} node.') elif phase == 'prepare': Rgw._file_exist(const.CONF_TMPL) Log.info(f'validations completed for {phase} phase.') return 0 @staticmethod def post_install(conf: MappedConf): """Performs post install operations.""" Log.info('PostInstall phase completed.') return 0 @staticmethod def prepare(conf: MappedConf): """Prepare for operations required before RGW can be configured.""" Log.info('Prepare phase started.') try: config_path = Rgw._get_rgw_config_path(conf) tmpl_idx = f'{const.COMPONENT_NAME}_conf_tmpl' # e.g. rgw_conf_tmpl tmpl_url = const.CONFSTORE_FILE_HANDLER + const.CONF_TMPL Rgw._load_rgw_config(tmpl_idx, tmpl_url) confstore_url = const.CONFSTORE_FILE_HANDLER + config_path Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Conf.copy(tmpl_idx, Rgw._conf_idx) Conf.save(Rgw._conf_idx) Log.info(f'{const.CONF_TMPL} config copied to {config_path}') except Exception as e: raise SetupError(errno.EINVAL, f'Error ocurred while fetching node ip, {e}') Log.info('Prepare phase completed.') return 0 @staticmethod def config(conf: MappedConf): """Performs configurations.""" Log.info('Config phase started.') Rgw._check_consul_connection(conf) config_file = Rgw._get_rgw_config_path(conf) if not os.path.exists(config_file): raise SetupError(errno.EINVAL, f'"{config_file}" config file is not present.') # Create ssl certificate Rgw._generate_ssl_cert(conf) # Create svc config Rgw._create_svc_config(conf) # Create motr trace directory for collecting m0trace files # in case admin user creation issue during mini-provisioner execution. Log.info('Creating motr trace directory for collecting m0trace files..') log_path = Rgw._get_log_dir_path(conf) motr_trace_dir = os.path.join(log_path, 'motr_trace_files') os.makedirs(motr_trace_dir, exist_ok=True) os.environ['M0_TRACE_DIR'] = motr_trace_dir Log.info('Created motr trace directory : %s' % os.environ.get('M0_TRACE_DIR')) # Read Motr HA(HAX) endpoint from data pod using hctl fetch-fids and update in config file # Use remote hax endpoint running on data pod which will be available during rgw # config phase since data pod starts before server pod. # Try HAX endpoint from data pod of same node first & if it doesnt work, # from other data pods in cluster Rgw._update_hax_endpoint_and_create_admin(conf) Log.info('Config phase completed.') return 0 @staticmethod def start(conf: MappedConf, index: str): """Create rgw admin user and start rgw service.""" Log.info(f'Configure logrotate for {const.COMPONENT_NAME} at path: {const.LOGROTATE_CONF}') Rgw._logrotate_generic(conf) # Before starting service,Verify backend store value=motr in rgw config file. Rgw._verify_backend_store_value(conf) # Create motr trace & addb stob dirctory. # Collect fid value of motr to create addb value. config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) motr_fid_key = const.MOTR_MY_FID % index motr_fid_value = Conf.get(Rgw._conf_idx, motr_fid_key) log_path = Rgw._get_log_dir_path(conf) motr_trace_dir = os.path.join(log_path, 'motr_trace_files') addb_dir = os.path.join(log_path, f'addb_files-{motr_fid_value}') os.makedirs(motr_trace_dir, exist_ok=True) os.makedirs(addb_dir, exist_ok=True) # Create rgw crash file directory rgw_core_dir = os.path.join(log_path, 'rgw_debug') os.makedirs(rgw_core_dir, exist_ok=True) Log.info('Starting radosgw service.') log_file = os.path.join(log_path, f'{const.COMPONENT_NAME}_startup.log') RgwService.start(conf, config_file, log_file, motr_trace_dir, rgw_core_dir, index) Log.info("Started radosgw service.") return 0 @staticmethod def init(conf: MappedConf): """Perform initialization.""" Log.info('Init phase completed.') return 0 @staticmethod def test(conf: MappedConf, plan: str): """Perform configuration testing.""" Log.info('Test phase completed.') return 0 @staticmethod def reset(conf: MappedConf): """Remove/Delete all the data/logs that was created by user/testing.""" Log.info('Reset phase completed.') return 0 @staticmethod def cleanup(conf: MappedConf, pre_factory: bool = False): """Remove/Delete all the data that was created after post install.""" config_path = Rgw._get_rgw_config_path(conf) if os.path.exists(config_path): os.remove(config_path) Log.info('Cleanup phase completed.') return 0 @staticmethod def _update_rgw_config(conf: MappedConf, config_index:str, config_key: str, config_val: str): """Update RGW Config based on changed Gconf values.""" for rgw_config_key, confstore_key in const.SVC_CONFIG_DICT.items(): if confstore_key == config_key: Conf.set(config_index, f'{const.CLIENT_SECTION}>{rgw_config_key}', config_val) Conf.save(config_index) @staticmethod def _remove_rgw_config(conf: MappedConf, config_index:str, config_key: str): """Remove specific key from rgw config file.""" for rgw_config_key, confstore_key in const.SVC_CONFIG_DICT.items(): if confstore_key == config_key: Conf.delete(config_index, f'{const.CLIENT_SECTION}>{rgw_config_key}') Conf.save(config_index) @staticmethod def upgrade(conf: MappedConf, changeset_path: str): """Perform upgrade steps.""" Log.info('Upgrade phase started.') conf_dir = Rgw._get_rgw_config_dir(conf) svc_conf_file = Rgw._get_rgw_config_path(conf) # Load changeset file changeset_index="rgw_changeset_index" Rgw._load_rgw_config(changeset_index, changeset_path) # Get all changed keys from changeset file. changeset_all_keys=Conf.get_keys(changeset_index) # Load deployed rgw config and take a backup. Rgw._load_rgw_config(Rgw._conf_idx, const.CONFSTORE_FILE_HANDLER + svc_conf_file) deployed_version = conf.get(const.VERSION_KEY) conf_bkp_file = os.path.join(conf_dir, const.RGW_CONF_FILE + f'.{deployed_version}') try: # Cleaning up failure config of previous upgrade. if os.path.exists(conf_bkp_file): os.remove(conf_bkp_file) # create backup of existing config file shutil.copy(svc_conf_file, conf_bkp_file) # Handle svc key & Gconf key mapping for key in changeset_all_keys: if key.startswith('new') : # Handle addition of new key # This will work if corresponding rgw config mapping is preset in const.py for this new key. new_val = Conf.get(changeset_index, key) key =key.split('new>')[1] Rgw._update_rgw_config(conf, Rgw._conf_idx, key, new_val) elif key.startswith('changed'): # Handle updation of existing key value = Conf.get(changeset_index, key) key =key.split('changed>')[1] new_val = value.split('\|')[1] Rgw._update_rgw_config(conf, Rgw._conf_idx, key, new_val) elif key.startswith('deleted'): # Handle deletion of existing key key =key.split('deleted>')[1] Rgw._remove_rgw_config(conf, Rgw._conf_idx, key) # Update upgraded release version. updated_version = Release(const.RELEASE_INFO_URL).get_release_version() Conf.set(Rgw._conf_idx, 'release>version', updated_version) # Save updated config file. Conf.save(Rgw._conf_idx) # delete backup file after upgrade. os.remove(conf_bkp_file) except Exception as e: raise SetupError(errno.EINVAL, f'Upgrade failed with error: {e}') Log.info('Upgrade phase completed.') return 0 @staticmethod def _create_svc_config(conf: MappedConf): """Create svc config""" svc_name = Rgw._get_svc_name(conf) client_instance_count = Rgw._get_num_client_instances(conf, svc_name) Log.info('fetching endpoint values from hctl fetch-fids cmd.') # For running rgw service and radosgw-admin tool, # we are using same endpoints fetched from hctl fetch-fids cmd as default endpoints, # given radosgw-admin tool & rgw service not expected to run simultaneously. # Update motr fid,endpoint config in cortx_rgw.conf. instance = 1 while instance <= client_instance_count: service_endpoints = Rgw._parse_endpoint_values( conf, instance, client_instance_count, svc_name) Log.debug('Validating endpoint entries provided by fetch-fids cmd') Rgw._validate_endpoint_paramters(service_endpoints) Log.info('Validated endpoint entries provided by fetch-fids cmd successfully.') Log.info('Updating endpoint values in rgw config file.') Rgw._update_rgw_config_with_endpoints(conf, service_endpoints, instance) instance = instance + 1 # Add additional parameters of SVC & Motr to config file. Rgw._update_svc_config(conf, 'client', const.SVC_CONFIG_DICT) Rgw._update_svc_data_path_value(conf, 'client') # Before user creation,Verify backend store value=motr in rgw config file. Rgw._verify_backend_store_value(conf) Log.info(f'Configure logrotate for {const.COMPONENT_NAME} at path: {const.LOGROTATE_CONF}') Rgw._logrotate_generic(conf) @staticmethod def _get_consul_url(conf: MappedConf, seq: int = 0): """Return consul url.""" http_endpoints = Rgw._fetch_endpoint_url(conf, const.CONSUL_ENDPOINT_KEY, 'http') consul_fqdn = http_endpoints[seq].split(':')[1] consul_url = 'consul:' + consul_fqdn + ':8500' return consul_url @staticmethod @ExponentialBackoff(exception=Exception, tries=4) def _check_consul_connection(conf: MappedConf): import socket sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.settimeout(2) consul_url = Rgw._get_consul_url(conf).split('//')[-1] host, port = consul_url.split(':') result = sock.connect_ex((host, int(port))) if result != 0: raise SetupError(errno.EINVAL, f"Consul server {host:port} not reachable") @staticmethod def _fetch_endpoint_url(conf: MappedConf, confstore_endpoint_key: str, endpoint_type: str): """Fetch endpoint url based on endpoint type from cortx config.""" endpoints = Rgw._get_cortx_conf(conf, confstore_endpoint_key) endpoints_values = list(filter(lambda x: urlparse(x).scheme == endpoint_type, endpoints)) if len(endpoints_values) == 0: raise SetupError(errno.EINVAL, f'{endpoint_type} endpoint is not specified in the conf.' f' Listed endpoints: {endpoints_values}') return endpoints_values @staticmethod def _file_exist(file_path: str): """Check if a file is exists.""" if not os.path.exists(file_path): raise SetupError(errno.EINVAL, f'{file_path} file not exists.') @staticmethod def _load_rgw_config(conf_idx: str, conf_url: str): """Add/Updated key-values in given config.""" try: if conf_url is None: raise SetupError(errno.EINVAL, 'Conf url is None.') Conf.load(conf_idx, conf_url, fail_reload=False) except (AssertionError, ConfError) as e: raise SetupError(errno.EINVAL, f'Error occurred while adding the key in {conf_url} config. {e}') @staticmethod def _get_rgw_config_path(conf: MappedConf): """Return RGW config file path.""" rgw_config_dir = Rgw._get_rgw_config_dir(conf) os.makedirs(rgw_config_dir, exist_ok=True) rgw_conf_file_path = os.path.join(rgw_config_dir, const.RGW_CONF_FILE) return rgw_conf_file_path @staticmethod def _get_rgw_config_dir(conf: MappedConf): """Return RGW config directory path.""" config_path = Rgw._get_cortx_conf(conf, const.CONFIG_PATH_KEY) rgw_config_dir = os.path.join(config_path, const.COMPONENT_NAME, Rgw._machine_id) return rgw_config_dir @staticmethod def _get_log_dir_path(conf: MappedConf): """Return log dir path.""" log_path = Rgw._get_cortx_conf(conf, const.LOG_PATH_KEY) log_dir_path = os.path.join(log_path, const.COMPONENT_NAME, Rgw._machine_id) os.makedirs(log_dir_path, exist_ok=True) return log_dir_path @staticmethod def _create_rgw_user(conf: MappedConf): """Create RGW admin user.""" user_name = Rgw._get_cortx_conf(conf, const.AUTH_USER_KEY) access_key = Rgw._get_cortx_conf(conf, const.AUTH_ADMIN_KEY) auth_secret = Rgw._get_cortx_conf(conf, const.AUTH_SECRET_KEY) err_str = f'user: {user_name} exists' timeout_str = f'timed out after {const.ADMIN_CREATION_TIMEOUT} seconds' # decrypt secret key. try: cluster_id = Rgw._get_cortx_conf(conf, const.CLUSTER_ID_KEY) cipher_key = Cipher.gen_key(cluster_id, const.DECRYPTION_KEY) password = Cipher.decrypt(cipher_key, auth_secret.encode(const.UTF_ENCODING)) password = password.decode(const.UTF_ENCODING) except CipherInvalidToken as e: raise SetupError(errno.EINVAL, f'auth_secret decryption failed. {e}') rgw_config = Rgw._get_rgw_config_path(conf) create_usr_cmd = f'radosgw-admin user create --uid={user_name} --access-key \ {access_key} --secret {password} --display-name="{user_name}" \ --caps="users=;metadata=;usage=;zone=;info=;user=;roles=;user-policy=;buckets=" \ -c {rgw_config} -n client.radosgw-admin --no-mon-config' _, err, rc, = SimpleProcess(create_usr_cmd).run(timeout=const.ADMIN_CREATION_TIMEOUT) if rc == 0: Log.info(f'RGW admin user {user_name} is created.') return 0 elif rc != 0: err = err.decode(const.UTF_ENCODING) if isinstance(err, bytes) else err if err_str in err: Log.info(f'RGW admin user {user_name} is already created,' ' Skipping user creation.') return 0 elif timeout_str in err: Log.info('RGW user creation process exceeding timeout value - ' f'{const.ADMIN_CREATION_TIMEOUT} seconds. Skipping user creation on this node.') return rc else: Log.error(f'"{create_usr_cmd}" failed with error {err}.') return rc @staticmethod def _parse_endpoint_values(conf: MappedConf, instance: int, client_instance_count: int, svc_name: str): """Fetch endpoint values from hctl fetch-fids.""" hare_config_dir = Rgw._get_hare_config_path(conf) fetch_fids_cmd = f'hctl fetch-fids -c {hare_config_dir}' decoded_out = Rgw._run_fetch_fid_cmd(fetch_fids_cmd) Rgw._validate_hctl_cmd_response(decoded_out, svc_name) endpoints = [comp for comp in decoded_out if comp['name'] == svc_name] # RGW client_instance_count should be equal/less than the # no of rgw config elements present in hctl fetch-fids output. if len(endpoints) < client_instance_count: raise SetupError(errno.EINVAL, f'The count of {svc_name} elements in hctl-fetch-fids o/p ' f'does not match with the {svc_name} client instance count.') # Fetch endpoints based on instance, # for eg. for instance=1 read 0th index rgw config list from output and so on. index = instance - 1 endpoints = endpoints[index] for ep_key, ep_value in const.RgwEndpoint.__members__.items(): if list(ep_value.value.keys())[0] in endpoints: endpoints[ep_key] = endpoints.pop(list(ep_value.value.keys())[0]) return endpoints @staticmethod def _update_rgw_config_with_endpoints(conf: MappedConf, endpoints: dict, instance: int): """Update endpoints,port and log path values to rgw config file.""" config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) log_path = Rgw._get_log_dir_path(conf) service_instance_log_file = os.path.join(log_path, f'{const.COMPONENT_NAME}-{instance}.log') radosgw_admin_log_file = os.path.join(log_path, 'radosgw-admin.log') # Update version in conf file. version = Rgw._get_cortx_conf(conf, const.VERSION_KEY) Conf.set(Rgw._conf_idx, 'release>version', version) # Update client.radosgw-admin section only once, # Update this with same config that is define for 1st instance. if instance == 1: for key, ep_value in const.RgwEndpoint.__members__.items(): value = list(ep_value.value.values())[0] Conf.set(Rgw._conf_idx, f'{const.ADMIN_SECTION}>{value}', endpoints[key]) Conf.set(Rgw._conf_idx, const.MOTR_ADMIN_FID_KEY, endpoints[const.RgwEndpoint.MOTR_PROCESS_FID.name]) Conf.set(Rgw._conf_idx, const.MOTR_ADMIN_ENDPOINT_KEY, endpoints[const.RgwEndpoint.MOTR_CLIENT_EP.name]) Conf.set(Rgw._conf_idx, const.RADOS_ADMIN_LOG_FILE_KEY, radosgw_admin_log_file) # Create separate section for each service instance in cortx_rgw.conf file. for key, ep_value in const.RgwEndpoint.__members__.items(): value = list(ep_value.value.values())[0] Conf.set(Rgw._conf_idx, f'{const.SVC_SECTION % instance}>{value}', endpoints[key]) Conf.set(Rgw._conf_idx, const.SVC_LOG_FILE % instance, service_instance_log_file) # Removed port increment support for service multiple instances. # (in case of multiple instances port value needs to be incremented.) http_port = Rgw._get_service_port(conf, 'http') https_port = Rgw._get_service_port(conf, 'https') ssl_cert_path = Rgw._get_cortx_conf(conf, const.SSL_CERT_PATH_KEY) Conf.set(Rgw._conf_idx, const.RGW_FRONTEND_KEY % instance, f'beast port={http_port} ssl_port={https_port} ssl_certificate={ssl_cert_path} ssl_private_key={ssl_cert_path}') Conf.save(Rgw._conf_idx) @staticmethod def _get_service_port(conf: MappedConf, protocol: str): """Return rgw service port value.""" port = None endpoints = conf.get(const.SVC_ENDPOINT_KEY) if endpoints: svc_endpoints = list(filter(lambda x: urlparse(x).scheme == protocol, endpoints)) port = urlparse(svc_endpoints[0]).port Log.info(f'{protocol} port value - {port}') else: # If endpoint is not present, use default port value. if protocol == 'http': port = const.DEFAULT_HTTP_PORT elif protocol == 'https': port = const.DEFAULT_HTTPS_PORT Log.info(f'{const.SVC_ENDPOINT_KEY} is not available in cluster.conf,' f' using the default value. {protocol} - {port}') return port @staticmethod def _validate_endpoint_paramters(endpoints: dict): """Validate endpoint values fetched from hctl fetch-fids cmd.""" for key, _ in const.RgwEndpoint.__members__.items(): if key not in endpoints: raise SetupError(errno.EINVAL, f'Failed to validate hare endpoint values.' f'endpoint {key} is not present.') for ept_key, ept_value in endpoints.items(): if ept_value == '': raise SetupError(errno.EINVAL, f'Invalid values for {ept_key}: {ept_value}') @staticmethod def _validate_hctl_cmd_response(decoded_out: list, svc_name: str): """Validate hctl command response.""" try: next(endpoint for endpoint in decoded_out if endpoint['name'] == svc_name) except StopIteration: raise SetupError(errno.EINVAL, 'Invalid %s endpoint values', svc_name) @staticmethod def _get_hare_config_path(conf: MappedConf): """Return config path of hare component.""" base_config_path = Rgw._get_cortx_conf(conf, const.CONFIG_PATH_KEY) hare_config_path = os.path.join(base_config_path, 'hare', 'config', Rgw._machine_id) return hare_config_path @staticmethod def _get_num_client_instances(conf: MappedConf, svc_name: str): """Read number of client instances.""" client_idx = 0 num_instances = 1 while conf.get(const.CLIENT_INSTANCE_NAME_KEY % client_idx) is not None: name = Rgw._get_cortx_conf(conf, const.CLIENT_INSTANCE_NAME_KEY % client_idx) if name == svc_name: num_instances = int(Rgw._get_cortx_conf(conf, const.CLIENT_INSTANCE_NUMBER_KEY % client_idx)) break client_idx = client_idx + 1 return num_instances @staticmethod def _get_cortx_conf(conf: MappedConf, key: str, default_value = None): """Read value from cluster config for given key""" val = conf.get(key) if val is None: if default_value is None: raise SetupError(errno.EINVAL, f'Value for {key} key is None.') else: val = default_value return val @staticmethod def _get_svc_name(conf: MappedConf): """Read service name from cluster.conf""" svc_name = None num_component = Rgw._get_cortx_conf(conf, const.NUM_COMPONENTS_KEY % Rgw._machine_id) for idx in range(0, num_component): if (Rgw._get_cortx_conf(conf, const.COMPONENT_NAME_KEY % (Rgw._machine_id, idx)) == const.COMPONENT_NAME): svc_name = Rgw._get_cortx_conf(conf, const.SVC_NAME_KEY % (Rgw._machine_id, idx), const.COMPONENT_NAME) break Log.info(f'Service name for {const.COMPONENT_NAME} is {svc_name}') return svc_name @staticmethod def _generate_ssl_cert(conf: MappedConf): """Generate SSL certificate.""" ssl_cert_path = Rgw._get_cortx_conf(conf, const.SSL_CERT_PATH_KEY) if not os.path.exists(ssl_cert_path): # Generate SSL cert. Log.info(f'"https" is enabled and SSL certificate is not present at {ssl_cert_path}.') Log.info('Generating SSL certificate.') try: ssl_cert_configs = const.SSL_CERT_CONFIGS ssl_cert_obj = Certificate.init('ssl') ssl_cert_obj.generate( cert_path=ssl_cert_path, dns_list=const.SSL_DNS_LIST, ssl_cert_configs) except SSLCertificateError as e: raise SetupError(errno.EINVAL, f'Failed to generate self signed ssl certificate: {e}') @staticmethod def _update_hax_endpoint(conf: MappedConf, data_pod_hostname: str): """Update hax endpoint values in rgw config file.""" Log.info('Reading motr_ha_endpoint from data pod') if not data_pod_hostname: raise SetupError(errno.EINVAL, 'Invalid data pod hostname: %s', data_pod_hostname) hare_config_dir = Rgw._get_hare_config_path(conf) fetch_fids_cmd = f'hctl fetch-fids -c {hare_config_dir} --node {data_pod_hostname}' decoded_out = Rgw._run_fetch_fid_cmd(fetch_fids_cmd, data_pod_hostname) Rgw._validate_hctl_cmd_response(decoded_out, 'hax') motr_ha_endpoint = [endpoints['ep'] for endpoints in decoded_out \ if 'hax' in endpoints.values()][0] Log.info(f'Fetched motr_ha_endpoint from data pod. Endpoint: {motr_ha_endpoint}') config_path = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_path Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) ha_ep_key = list(const.RgwEndpoint.MOTR_HA_EP.value.values())[0] Conf.set(Rgw._conf_idx, f'client.radosgw-admin>{ha_ep_key}', motr_ha_endpoint) Conf.save(Rgw._conf_idx) Log.info(f'Updated motr_ha_endpoint in config file {config_path}') @staticmethod def _run_fetch_fid_cmd(fetch_fids_cmd: str, data_pod_hostname: str = None): """Run hctl fetch-fids command through SimpleProcess.""" out, err, rc = SimpleProcess(fetch_fids_cmd).run() if rc != 0: if data_pod_hostname: Log.error(f'Unable to read fid information for hostname: ' f'{data_pod_hostname}. {err}') raise SetupError(rc, 'Unable to read fid information for hostname: ' '%s. %s', data_pod_hostname, err) else: Log.error(f'Unable to read fid information. {err}') raise SetupError(rc, 'Unable to read fid information. %s', err) decoded_out = json.loads(out.decode(const.UTF_ENCODING)) return decoded_out @staticmethod def _create_admin_on_current_node(conf: MappedConf, current_data_node: str): try: Rgw._update_hax_endpoint(conf, current_data_node) Log.info('Creating admin user.') # Before creating user check if user is already created. user_status = Rgw._create_rgw_user(conf) return user_status except Exception: return -1 @staticmethod def _update_hax_endpoint_and_create_admin(conf: MappedConf): """Update motr_ha(hax) endpoint values to rgw config file and create admin.""" # admin user should be created only on one node. # 1. While creating admin user, global lock created in consul kv store. # (rgw_consul_index, cortx>rgw>volatile>rgw_lock, machine_id) # 2. Before creating admin user. # a. Check for rgw_lock in consul kv store # b. Create user only if lock value is equal to self* machine_id # 3. If user creation attempt failed from this node, delete the lock # so other node can acquire the lock and try user creation. # 4. If user creation is successful, update lock value to 'user_created'. rgw_consul_idx = f'{const.COMPONENT_NAME}_consul_idx' # Get consul url from cortx config. consul_url = Rgw._get_consul_url(conf) # Check for rgw_lock in consul kv store. Log.info('Checking for rgw lock in consul kv store.') Rgw._load_rgw_config(rgw_consul_idx, consul_url) rgw_lock = Rgw._get_lock(rgw_consul_idx) if rgw_lock is True: # TODO: Find a way to get current data pod hostname on server node. # current_data_node = socket.gethostname().replace('server', 'data') # user_status = Rgw._create_admin_on_current_node(conf, current_data_node) # if user_status == 0: # Log.info(f'User creation is successful on "{Rgw._machine_id}" node.') # Rgw._set_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY, const.ADMIN_USER_CREATED) # else: data_pod_hostnames = Rgw._get_data_nodes(conf) # if len(data_pod_hostnames) == 1 and current_data_node == data_pod_hostnames[0]: # Log.error('Admin user creation failed') # Rgw._delete_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY) # raise SetupError(user_status, 'Admin user creation failed on' # f' "{Rgw._machine_id}" node, with all data pods - {data_pod_hostnames}') # data_pod_hostnames.remove(current_data_node) for data_pod_hostname in data_pod_hostnames: try: Rgw._update_hax_endpoint(conf, data_pod_hostname) except SetupError as e: Log.debug(f'Error occured while updating hax endpoints. {e}') continue status = Rgw._create_rgw_user(conf) if status == 0: Log.info(f'User creation is successful on "{Rgw._machine_id}" node.') Rgw._set_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY, const.ADMIN_USER_CREATED) break else: if data_pod_hostname == data_pod_hostnames[-1]: Log.error(f'Admin user creation failed with error code - {status}') Rgw._delete_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY) raise SetupError(status, 'Admin user creation failed on' f' "{Rgw._machine_id}" node, with all data pods - {data_pod_hostnames}') @staticmethod def _get_data_nodes(conf: MappedConf): """Return all data nodes hostname""" storage_set = Rgw._get_cortx_conf(conf, const.STORAGE_SET % Rgw._machine_id) storage_set_count = Rgw._get_cortx_conf(conf, const.STORAGE_SET_COUNT) machine_ids = [] for storage_set_index in range(0, storage_set_count): if Rgw._get_cortx_conf(conf, const.STORAGE_SET_NAME % storage_set_index) == storage_set: machine_ids = Rgw._get_cortx_conf( conf, const.STORAGE_SET_NODE % storage_set_index) data_pod_hostnames = [Rgw._get_cortx_conf(conf, const.NODE_HOSTNAME % machine_id) for machine_id in machine_ids if Rgw._get_cortx_conf(conf, const.NODE_TYPE % machine_id) == const.DATA_NODE] return data_pod_hostnames @staticmethod def _get_lock(consul_idx: str): """Get lock from consul kv.""" # if in case try-catch block code executed at the same time on all the nodes, # then all nodes will try to update rgw lock-key in consul, after updating key # it will wait for sometime(time.sleep(3)) and in next iteration all nodes will # get lock value as node-id of node who has updated the lock key at last. # and then only that node will perform the user creation operation. rgw_lock = False while True: try: rgw_lock_val = Conf.get(consul_idx, const.CONSUL_LOCK_KEY) Log.info(f'{const.CONSUL_LOCK_KEY} value - {rgw_lock_val}') if rgw_lock_val is None: Log.info(f'Setting consul kv store value for key :{const.CONSUL_LOCK_KEY}' f' and value as :{Rgw._machine_id}') Rgw._set_consul_kv(consul_idx, const.CONSUL_LOCK_KEY, Rgw._machine_id) continue elif rgw_lock_val == Rgw._machine_id: Log.info('Required lock already possessed, proceeding with RGW ' f'admin user creation on node {rgw_lock_val}') rgw_lock = True break elif rgw_lock_val != Rgw._machine_id: if rgw_lock_val == const.ADMIN_USER_CREATED: Log.info('User is already created.') break Log.info(f'RGW lock is acquired by "{rgw_lock_val}" node.') Log.info(f'Waiting for user creation to complete on "{rgw_lock_val}" node') time.sleep(3) continue except Exception as e: Log.error('Exception occured while connecting to consul service' f' endpoint {e}') break return rgw_lock @staticmethod def _set_consul_kv(consul_idx: str, key: str, value: str): """Update key value pair in consul kv store.""" Conf.set(consul_idx, key, value) Conf.save(consul_idx) time.sleep(3) Log.info(f'Updated consul kv store - {key} - {value}.') @staticmethod def _delete_consul_kv(consul_idx: str, key: str): """Delete key value pair from consul kv store.""" Log.debug(f'Deleting rgw_lock key {key}.') Conf.delete(consul_idx, key) Log.info(f'{key} key is deleted') @staticmethod def _logrotate_generic(conf: MappedConf): """ Configure logrotate utility for rgw logs.""" log_file_path = Rgw._get_log_dir_path(conf) # Configure the cron job on hourly frequency for RGW log files. try: with open(const.CRON_LOGROTATE_TMPL, 'r') as f: content = f.read() with open(const.CRON_LOGROTATE, 'w') as f: f.write(content) except Exception as e: Log.error(f"Failed to configure cron job for logrotate at {const.FREQUENCY} basis." f"ERROR:{e}") # create radosgw logrotate file. # For eg: # filepath='/etc/logrotate.d/radosgw' old_file = os.path.join(const.LOGROTATE_DIR, 'ceph') if os.path.exists(old_file): os.remove(old_file) try: with open(const.LOGROTATE_TMPL, 'r') as f: content = f.read() content = content.replace('TMP_LOG_PATH', log_file_path) with open(const.LOGROTATE_CONF, 'w') as f: f.write(content) Log.info(f'{const.LOGROTATE_TMPL} file copied to {const.LOGROTATE_CONF}') except Exception as e: Log.error(f"Failed to configure logrotate for {const.COMPONENT_NAME}. ERROR:{e}") # start cron.d service try: os.system(f"chmod +x {const.CRON_LOGROTATE}") os.system("/usr/sbin/crond start") except Exception as e: Log.error(f"Failed to start the crond service for {const.COMPONENT_NAME}. ERROR:{e}") @staticmethod def _verify_backend_store_value(conf: MappedConf): """Verify backed store value as motr.""" config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) backend_store = Conf.get(Rgw._conf_idx, const.RGW_BACKEND_STORE_KEY) if not backend_store in const.SUPPORTED_BACKEND_STORES: raise SetupError(errno.EINVAL, f'Supported rgw backend store are {const.SUPPORTED_BACKEND_STORES},' f' currently configured one is {backend_store}') @staticmethod def _update_svc_config(conf: MappedConf, client_section: str, config_key_mapping: dict): """Update config properties from confstore to rgw config file.""" svc_config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + svc_config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Log.info(f'updating parameters to {client_section} in {svc_config_file}') for config_key, confstore_key in config_key_mapping.items(): default_value = Conf.get(Rgw._conf_idx, f'{client_section}>{config_key}') if confstore_key is None: Log.info(f'config key:{config_key} not found in rgw key mapping.\ hence using default value as {default_value} specified in config file.') continue else: # fetch actual value of parameter from confstore. # if config key/value is missing in confstore then use default value mentioned in config file. config_value = conf.get(confstore_key) if config_value is not None: Log.info(f'Setting config key :{config_key} with value:{config_value} at {client_section} section') Conf.set(Rgw._conf_idx, f'{client_section}>{config_key}', str(config_value)) else : Log.info(f'GConfig entry is missing for config key :{config_key}.\ hence using default value as {default_value} specified in config file.') continue Conf.save(Rgw._conf_idx) Log.info(f'added paramters to {client_section} successfully..') @staticmethod def _update_svc_data_path_value(conf: MappedConf, client_section: str): "Update svc config file with data path key which needs pre-processing values incase of default values." # Fetch cluster-id cluster_id = Rgw._get_cortx_conf(conf, const.CLUSTER_ID_KEY) svc_config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + svc_config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Log.info(f'updating data_path paramter to {client_section} in {svc_config_file}') # Create data path's default value e.g. /var/lib/ceph/radosgw/<cluster-id> data_path_default_value = const.SVC_DATA_PATH_DEFAULT_VALUE + cluster_id confstore_data_path_value = conf.get(const.SVC_DATA_PATH_CONFSTORE_KEY) if confstore_data_path_value is not None: Log.info(f'Setting config key :{const.SVC_DATA_PATH_KEY} with value:{confstore_data_path_value}\ at {client_section} section') Conf.set(Rgw._conf_idx, f'{client_section}>{const.SVC_DATA_PATH_KEY}', str(confstore_data_path_value)) else: Log.info(f'GConfig entry is missing for config key :{const.SVC_DATA_PATH_KEY}.\ hence using default value as {data_path_default_value} specified in config file.') Conf.set(Rgw._conf_idx, f'{client_section}>{const.SVC_DATA_PATH_KEY}', str(data_path_default_value)) Conf.save(Rgw._conf_idx) Log.info(f'added config parameters to {client_section} successfully..')	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appiumbase/fixtures/page_utils.py	Pawan7593/AppiumBase	0	177243	<reponame>Pawan7593/AppiumBase<gh_stars>0 def is_xpath_selector(selector): """ A basic method to determine if a selector is an xpath selector. """ if ( selector.startswith("/") or selector.startswith("./") or selector.startswith("(") ): return True return False def is_link_text_selector(selector): """ A basic method to determine if a selector is a link text selector. """ if ( selector.startswith("link=") or selector.startswith("link_text=") or selector.startswith("text=") ): return True return False def is_partial_link_text_selector(selector): """ A basic method to determine if a selector is a partial link text selector. """ if ( selector.startswith("partial_link=") or selector.startswith("partial_link_text=") or selector.startswith("partial_text=") or selector.startswith("p_link=") or selector.startswith("p_link_text=") or selector.startswith("p_text=") ): return True return False def is_name_selector(selector): """ A basic method to determine if a selector is a name selector. """ if selector.startswith("name=") or selector.startswith("&"): return True return False def get_link_text_from_selector(selector): """ A basic method to get the link text from a link text selector. """ if selector.startswith("link="): return selector[len("link="):] elif selector.startswith("link_text="): return selector[len("link_text="):] elif selector.startswith("text="): return selector[len("text="):] return selector def get_partial_link_text_from_selector(selector): """ A basic method to get the partial link text from a partial link selector. 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tests/587/test_interface.py	CSUN-COMP587-F18/keras	0	79783	<reponame>CSUN-COMP587-F18/keras<gh_stars>0 from __future__ import print_function import pytest from keras.preprocessing import sequence from keras.models import Sequential from keras.layers import Dense, Dropout, Activation from keras.layers import Embedding from keras.layers import Conv1D, GlobalMaxPooling1D from keras.datasets import imdb def test_interface(): maxFeat = 5000 maxLength = 400 batchSize = 32 embed = 50 fils = 250 kernSize = 3 hidDimensions = 250 epochs = 2 (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=maxFeat) x_train = sequence.pad_sequences(x_train, maxlen=maxLength) x_test = sequence.pad_sequences(x_test, maxlen=maxLength) model = Sequential() model.add(Embedding(maxFeat, embed, input_length=maxLength)) model.add(Dropout(0.2)) model.add(Conv1D(fils, kernSize, padding='valid', activation='relu', strides=1)) model.add(GlobalMaxPooling1D()) model.add(Dense(hidDimensions)) model.add(Dropout(0.2)) model.add(Activation('relu')) model.add(Dense(1)) model.add(Activation('sigmoid')) model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) model.fit(x_train, y_train, batch_size=batchSize, epochs=epochs, validation_data=(x_test, y_test)) score, acc = model.evaluate(x_test, y_test, batch_size=batchSize) assert(acc > .8) if __name__ == '__main__': pytest.main([__file__])	[ 1, 529, 276, 1112, 420, 29958, 9295, 3904, 29899, 21514, 29945, 29947, 29955, 29899, 29943, 29896, 29947, 29914, 3946, 294, 29966, 12443, 29918, 303, 1503, 29958, 29900, 13, 3166, 4770, 29888, 9130, 1649, 1053, 1596, 29918, 2220, 13, 13, 5215, 11451, 1688, 13, 13, 3166, 13023, 294, 29889, 1457, 19170, 1053, 5665, 13, 3166, 13023, 294, 29889, 9794, 1053, 922, 339, 2556, 13, 3166, 13023, 294, 29889, 29277, 1053, 360, 1947, 29892, 20724, 449, 29892, 21775, 362, 13, 3166, 13023, 294, 29889, 29277, 1053, 2812, 2580, 8497, 13, 3166, 13023, 294, 29889, 29277, 1053, 1281, 29894, 29896, 29928, 29892, 12002, 7976, 11426, 292, 29896, 29928, 13, 3166, 13023, 294, 29889, 14538, 1691, 1053, 527, 2585, 13, 13, 13, 1753, 1243, 29918, 13248, 7295, 13, 1678, 4236, 8263, 271, 353, 29871, 29945, 29900, 29900, 29900, 13, 1678, 4236, 6513, 353, 29871, 29946, 29900, 29900, 13, 1678, 9853, 3505, 353, 29871, 29941, 29906, 13, 1678, 8297, 353, 29871, 29945, 29900, 13, 1678, 14560, 353, 29871, 29906, 29945, 29900, 13, 1678, 413, 824, 3505, 353, 29871, 29941, 13, 1678, 20552, 16142, 5580, 353, 29871, 29906, 29945, 29900, 13, 1678, 21502, 12168, 353, 29871, 29906, 13, 13, 1678, 313, 29916, 29918, 14968, 29892, 343, 29918, 14968, 511, 313, 29916, 29918, 1688, 29892, 343, 29918, 1688, 29897, 353, 527, 2585, 29889, 1359, 29918, 1272, 29898, 1949, 29918, 9303, 29922, 3317, 8263, 271, 29897, 13, 13, 1678, 921, 29918, 14968, 353, 5665, 29889, 8305, 29918, 6831, 2063, 29898, 29916, 29918, 14968, 29892, 4236, 2435, 29922, 3317, 6513, 29897, 13, 1678, 921, 29918, 1688, 353, 5665, 29889, 8305, 29918, 6831, 2063, 29898, 29916, 29918, 1688, 29892, 4236, 2435, 29922, 3317, 6513, 29897, 13, 13, 1678, 1904, 353, 922, 339, 2556, 580, 13, 13, 1678, 1904, 29889, 1202, 29898, 6026, 2580, 8497, 29898, 3317, 8263, 271, 29892, 13, 462, 4706, 8297, 29892, 13, 462, 4706, 1881, 29918, 2848, 29922, 3317, 6513, 876, 13, 1678, 1904, 29889, 1202, 29898, 15063, 449, 29898, 29900, 29889, 29906, 876, 13, 13, 1678, 1904, 29889, 1202, 29898, 1168, 29894, 29896, 29928, 29898, 1777, 29879, 29892, 13, 462, 268, 413, 824, 3505, 29892, 13, 462, 268, 7164, 2433, 3084, 742, 13, 462, 268, 26229, 2433, 2674, 29884, 742, 13, 462, 268, 851, 2247, 29922, 29896, 876, 13, 1678, 1904, 29889, 1202, 29898, 12756, 7976, 11426, 292, 29896, 29928, 3101, 13, 13, 1678, 1904, 29889, 1202, 29898, 29928, 1947, 29898, 29882, 333, 16142, 5580, 876, 13, 1678, 1904, 29889, 1202, 29898, 15063, 449, 29898, 29900, 29889, 29906, 876, 13, 1678, 1904, 29889, 1202, 29898, 21786, 362, 877, 2674, 29884, 8785, 13, 13, 1678, 1904, 29889, 1202, 29898, 29928, 1947, 29898, 29896, 876, 13, 1678, 1904, 29889, 1202, 29898, 21786, 362, 877, 18816, 29885, 3398, 8785, 13, 13, 1678, 1904, 29889, 12198, 29898, 6758, 2433, 19541, 29918, 19128, 296, 14441, 742, 13, 462, 29871, 5994, 3950, 2433, 328, 314, 742, 13, 462, 29871, 21556, 29922, 1839, 562, 2764, 4135, 11287, 13, 1678, 1904, 29889, 9202, 29898, 29916, 29918, 14968, 29892, 343, 29918, 14968, 29892, 13, 795, 9853, 29918, 2311, 29922, 16175, 3505, 29892, 13, 795, 21502, 12168, 29922, 1022, 2878, 29879, 29892, 13, 795, 8845, 29918, 1272, 7607, 29916, 29918, 1688, 29892, 343, 29918, 1688, 876, 13, 13, 1678, 8158, 29892, 1035, 353, 1904, 29889, 24219, 403, 29898, 29916, 29918, 1688, 29892, 343, 29918, 1688, 29892, 9853, 29918, 2311, 29922, 16175, 3505, 29897, 13, 13, 1678, 4974, 29898, 5753, 1405, 869, 29947, 29897, 13, 13, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 13, 1678, 11451, 1688, 29889, 3396, 4197, 1649, 1445, 1649, 2314, 13, 2 ]
mall_spider/utils/session_id_generator.py	524243642/taobao_spider	12	116616	# coding: utf-8 from abc import ABCMeta, abstractmethod class SessionIdGenerator(object): __metaclass__ = ABCMeta @abstractmethod def generate_id(self, session): pass	[ 1, 396, 14137, 29901, 23616, 29899, 29947, 13, 3166, 25638, 1053, 16417, 19346, 29892, 9846, 5696, 13, 13, 13, 1990, 16441, 1204, 21575, 29898, 3318, 1125, 13, 1678, 4770, 2527, 562, 605, 1649, 353, 16417, 19346, 13, 13, 1678, 732, 16595, 5696, 13, 1678, 822, 5706, 29918, 333, 29898, 1311, 29892, 4867, 1125, 13, 4706, 1209, 13, 2 ]
conduit/transforms/fixmatch.py	wearepal/conduit	0	199000	from dataclasses import dataclass from typing import Callable, Generic, List, Optional, TypeVar, Union from PIL import Image import numpy as np from ranzen.decorators import implements from ranzen.misc import gcopy from torch import Tensor from typing_extensions import Self from conduit.data.datasets.utils import ImageTform, apply_image_transform from conduit.data.structures import InputContainer, RawImage, concatenate_inputs __all__ = [ "FixMatchPair", "FixMatchTransform", ] X = TypeVar("X", bound=Union[Tensor, RawImage, List[Image.Image]]) @dataclass class FixMatchPair(InputContainer[X]): strong: X weak: X @implements(InputContainer) def __len__(self) -> int: if isinstance(self.strong, Image.Image): return 1 return len(self.strong) @implements(InputContainer) def __add__(self, other: Self) -> Self: copy = gcopy(self, deep=False) is_batched = isinstance(self.strong, (Tensor, np.ndarray)) and (self.strong.ndim == 4) copy.strong = concatenate_inputs(copy.strong, other.strong, is_batched=is_batched) copy.weak = concatenate_inputs(copy.weak, other.weak, is_batched=is_batched) return copy A = TypeVar("A", bound=ImageTform) class FixMatchTransform(Generic[A]): def __init__( self, strong_transform: A, *, weak_transform: A, shared_transform_start: Optional[Callable[[Union[RawImage, Tensor]], RawImage]] = None, shared_transform_end: Optional[ Callable[[Union[RawImage, Tensor]], Union[RawImage, Tensor]] ] = None, ) -> None: self.strong_transform = strong_transform self.weak_transform = weak_transform self.shared_transform_start = shared_transform_start self.shared_transform_end = shared_transform_end def __call__(self, image: RawImage) -> FixMatchPair: if self.shared_transform_start is not None: image = self.shared_transform_start(image) strongly_augmented_image = apply_image_transform( image=image, transform=self.strong_transform ) weakly_augmented_image = apply_image_transform(image=image, transform=self.weak_transform) if self.shared_transform_end is not None: strongly_augmented_image = self.shared_transform_end(strongly_augmented_image) weakly_augmented_image = self.shared_transform_end(weakly_augmented_image) return FixMatchPair(strong=strongly_augmented_image, weak=weakly_augmented_image)	[ 1, 515, 848, 13203, 1053, 848, 1990, 13, 3166, 19229, 1053, 8251, 519, 29892, 3251, 293, 29892, 2391, 29892, 28379, 29892, 5167, 9037, 29892, 7761, 13, 13, 3166, 349, 6227, 1053, 7084, 13, 5215, 12655, 408, 7442, 13, 3166, 6350, 2256, 29889, 19557, 4097, 1053, 10703, 13, 3166, 6350, 2256, 29889, 29885, 10669, 1053, 330, 8552, 13, 3166, 4842, 305, 1053, 323, 6073, 13, 3166, 19229, 29918, 24299, 1053, 21782, 13, 13, 3166, 13417, 277, 29889, 1272, 29889, 14538, 1691, 29889, 13239, 1053, 7084, 29911, 689, 29892, 3394, 29918, 3027, 29918, 9067, 13, 3166, 13417, 277, 29889, 1272, 29889, 4984, 1973, 1053, 10567, 7895, 29892, 22038, 2940, 29892, 16125, 403, 29918, 2080, 29879, 13, 13, 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scripts/SV_modules/BioNanoDuplications.py	wongkarenhy/Full-Genome-Analysis-Pipeline	2	159776	<gh_stars>1-10 #!/usr/bin/env python3.6 import pandas as pd import os import pyranges as pr from pyranges import PyRanges from io import StringIO import numpy as np import argparse from .BioNanoDeletions import reciprocal_overlap, checkRefOverlap, checkParentsOverlap, exonOverlap, overlap_length def readsmapDup(input): colnames = ['SmapEntryID', 'QryContigID', 'RefcontigID1', 'RefcontigID2', 'QryStartPos', 'QryEndPos', 'RefStartPos', 'RefEndPos', 'Confidence', 'Type', 'XmapID1', 'XmapID2', 'LinkID', 'QryStartIdx', 'QryEndIdx', 'RefStartIdx', 'RefEndIdx', 'Zygosity', 'Genotype', 'GenotypeGroup', 'RawConfidence', 'RawConfidenceLeft', 'RawConfidenceRight', 'RawConfidenceCenter', 'SVsize'] raw_df = pd.read_csv(input, sep='\t', comment='#', names=colnames, header=None, skiprows=lambda x: x in [0]) raw_df = raw_df[['SmapEntryID', 'RefcontigID1', 'RefcontigID2', 'RefStartPos','RefEndPos', 'QryStartPos', 'QryEndPos', 'Confidence', 'Type', 'Zygosity', 'Genotype']] #confident_df = raw_df.loc[raw_df['Confidence'] > 0.5] #modulate confidence threshold here confident_df = raw_df[raw_df['Type'].str.contains('duplication')] confident_df['RefcontigID1'] = confident_df['RefcontigID1'].astype(str).str.replace("23", "X") confident_df['RefcontigID2'] = confident_df['RefcontigID2'].astype(str).str.replace("24", "Y") # calculate SV size confident_df['SV_size'] = confident_df['RefEndPos'] - confident_df['RefStartPos'] confident_df['SV_size'] = confident_df['SV_size'].abs().round(0) confident_df = confident_df.loc[confident_df['SV_size'] >= 1000] return(confident_df) def BN_duplication(args): # Load Sample sample_frame = readsmapDup(args.samplepath) # Some old BN pipeline doesn't call duplication if sample_frame.empty: return None, None # Load parent data if args.type == 'trio' or args.father_duo: father_frame = readsmapDup(args.fpath) else: father_frame = pd.DataFrame(columns=['RefStartPos', 'RefEndPos', 'RefcontigID1']) if args.type == 'trio' or args.mother_duo: mother_frame = readsmapDup(args.mpath) else: mother_frame = pd.DataFrame(columns=['RefStartPos', 'RefEndPos', 'RefcontigID1']) # Load reference ref_frame = readsmapDup(args.referencepath) # Actual fun sample_copy, mother_copy, father_copy, ref_copy = sample_frame.copy(), mother_frame.copy(), father_frame.copy(), ref_frame.copy() for df in [sample_copy, mother_copy, father_copy, ref_copy]: df['Start'], df['End'], df['Chromosome'] = df.RefStartPos, df.RefEndPos, df['RefcontigID1'] # Remove anything that overlaps with the reference filtered_sample_frame = checkRefOverlap(sample_copy, ref_copy, sample_frame) # Add column based on overlap with parents filtered_sample_frame = checkParentsOverlap(sample_copy, father_copy, filtered_sample_frame, args, 'Found_in_Father') filtered_sample_frame = checkParentsOverlap(sample_copy, mother_copy, filtered_sample_frame, args, 'Found_in_Mother') filtered_sample_frame.to_csv(args.outputdirectory + '/' + args.sampleID + '_BioNano_duplications_raw.txt', sep='\t', index = False) # Describe exon overlap filtered_sample_frame['Start'], filtered_sample_frame['End'], filtered_sample_frame['Chromosome'] = filtered_sample_frame.RefStartPos, filtered_sample_frame.RefEndPos, filtered_sample_frame['RefcontigID1'] exon_calls = exonOverlap(args, filtered_sample_frame) exon_calls.to_csv(args.outputdirectory + '/' + args.sampleID + '_Bionano_duplications_exons.txt', sep='\t', index = False) return filtered_sample_frame, exon_calls def main(): parser = argparse.ArgumentParser(description='Sample and Path arguments.') parser.add_argument("-i", "--sampleID", help="Give the sample ID", dest="sampleID", type=str, required=True) parser.add_argument("-s", "--samplepath", help="Give the full path to the sample file", dest="samplepath", type=str, required=True) parser.add_argument("-f", "--fpath", help="Give the full path to the father's file", dest="fpath", type=str, required=True) parser.add_argument("-m", "--mpath", help="Give the full path to the mother's file", dest="mpath", type=str, required=True) parser.add_argument("-r", "--referencepath", help="Give the full path to the reference file", dest="referencepath", type=str, required=True) parser.add_argument("-o", "--outputdirectory", help="Give the directory path for the output file", dest="outputdirectory", type=str, required=True) parser.add_argument("-c", "--confidence", help="Give the confidence level cutoff for the sample here", dest="confidence", type=str, default=0.5) parser.add_argument("-e", "--exons", help="Give the file with exons intervals, names, and phenotypes here", dest="exons", type=str, required=True) parser.add_argument("-g", "--genelist", help="Primary genelist with scores", dest="genelist", type=str) parser.add_argument("-t", "--type", help="Specify whether this is a trio, duo, or singleton case", dest="type", type=str) parser.add_argument("-F", 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tests/integration/Containers.py	adnrs96/runtime	0	10448	# -- coding: utf-8 -- from storyruntime.Containers import Containers from storyruntime.constants.ServiceConstants import ServiceConstants import storyscript def test_containers_format_command(story): """ Ensures a simple resolve can be performed """ story_text = 'alpine echo msg:"foo"\n' story.context = {} story.app.services = { 'alpine': { ServiceConstants.config: { 'actions': { 'echo': { 'arguments': {'msg': {'type': 'string'}} } } } } } story.tree = storyscript.Api.loads(story_text).result()['tree'] assert Containers.format_command( story, story.line('1'), 'alpine', 'echo' ) == ['echo', '{"msg":"foo"}'] def test_containers_format_command_no_arguments(story): story_text = 'alpine echo\n' story.context = {} story.app.services = { 'alpine': { ServiceConstants.config: { 'actions': { 'echo': {} } } } } story.tree = storyscript.Api.loads(story_text).result()['tree'] assert Containers.format_command( story, story.line('1'), 'alpine', 'echo' ) == ['echo']	[ 1, 396, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 3166, 5828, 15634, 29889, 1323, 475, 414, 1053, 2866, 475, 414, 13, 3166, 5828, 15634, 29889, 3075, 1934, 29889, 3170, 26570, 1053, 6692, 26570, 13, 13, 5215, 5828, 2154, 13, 13, 13, 1753, 1243, 29918, 1285, 475, 414, 29918, 4830, 29918, 6519, 29898, 24098, 1125, 13, 1678, 9995, 13, 1678, 22521, 1973, 263, 2560, 8814, 508, 367, 8560, 13, 1678, 9995, 13, 1678, 5828, 29918, 726, 353, 525, 284, 26215, 2916, 10191, 6160, 5431, 26732, 29876, 29915, 13, 1678, 5828, 29889, 4703, 353, 6571, 13, 1678, 5828, 29889, 932, 29889, 9916, 353, 426, 13, 4706, 525, 284, 26215, 2396, 426, 13, 9651, 6692, 26570, 29889, 2917, 29901, 426, 13, 18884, 525, 7387, 2396, 426, 13, 462, 1678, 525, 8057, 2396, 426, 13, 462, 4706, 525, 25699, 2396, 11117, 7645, 2396, 11117, 1853, 2396, 525, 1807, 29915, 930, 13, 462, 1678, 500, 13, 18884, 500, 13, 9651, 500, 13, 4706, 500, 13, 1678, 500, 13, 13, 1678, 5828, 29889, 8336, 353, 5828, 2154, 29889, 11713, 29889, 18132, 29898, 24098, 29918, 726, 467, 2914, 580, 1839, 8336, 2033, 13, 1678, 4974, 2866, 475, 414, 29889, 4830, 29918, 6519, 29898, 13, 4706, 5828, 29892, 5828, 29889, 1220, 877, 29896, 5477, 525, 284, 26215, 742, 525, 8057, 29915, 13, 1678, 1723, 1275, 6024, 8057, 742, 525, 6377, 7645, 4710, 5431, 9092, 2033, 13, 13, 13, 1753, 1243, 29918, 1285, 475, 414, 29918, 4830, 29918, 6519, 29918, 1217, 29918, 25699, 29898, 24098, 1125, 13, 1678, 5828, 29918, 726, 353, 525, 284, 26215, 2916, 29905, 29876, 29915, 13, 1678, 5828, 29889, 4703, 353, 6571, 13, 1678, 5828, 29889, 932, 29889, 9916, 353, 426, 13, 4706, 525, 284, 26215, 2396, 426, 13, 9651, 6692, 26570, 29889, 2917, 29901, 426, 13, 18884, 525, 7387, 2396, 426, 13, 462, 1678, 525, 8057, 2396, 6571, 13, 18884, 500, 13, 9651, 500, 13, 4706, 500, 13, 1678, 500, 13, 1678, 5828, 29889, 8336, 353, 5828, 2154, 29889, 11713, 29889, 18132, 29898, 24098, 29918, 726, 467, 2914, 580, 1839, 8336, 2033, 13, 1678, 4974, 2866, 475, 414, 29889, 4830, 29918, 6519, 29898, 13, 4706, 5828, 29892, 5828, 29889, 1220, 877, 29896, 5477, 525, 284, 26215, 742, 525, 8057, 29915, 13, 1678, 1723, 1275, 6024, 8057, 2033, 13, 2 ]
photos/models.py	eude313/vault	0	2801	from django.db import models from cloudinary.models import CloudinaryField # Create your models here. class Category(models.Model): name = models.CharField( max_length=200, null=False, blank=False ) def __str__(self): return self.name class Photo(models.Model): category = models.ForeignKey( Category, on_delete=models.SET_NULL, null=True, blank=True ) image = CloudinaryField('image', default='') description = models.TextField() def __str__(self): return self.description	[ 1, 515, 9557, 29889, 2585, 1053, 4733, 13, 3166, 9570, 3821, 29889, 9794, 1053, 14293, 3821, 3073, 13, 13, 29937, 6204, 596, 4733, 1244, 29889, 13, 13, 1990, 17943, 29898, 9794, 29889, 3195, 1125, 13, 1678, 1024, 353, 4733, 29889, 27890, 29898, 4236, 29918, 2848, 29922, 29906, 29900, 29900, 29892, 1870, 29922, 8824, 29892, 9654, 29922, 8824, 1723, 29871, 13, 13, 1678, 822, 4770, 710, 12035, 1311, 1125, 13, 4706, 736, 1583, 29889, 978, 13, 268, 13, 1990, 1963, 3747, 29898, 9794, 29889, 3195, 1125, 13, 1678, 7663, 353, 4733, 29889, 27755, 2558, 29898, 17943, 29892, 373, 29918, 8143, 29922, 9794, 29889, 10490, 29918, 10074, 29892, 1870, 29922, 5574, 29892, 9654, 29922, 5574, 1723, 13, 1678, 1967, 353, 14293, 3821, 3073, 877, 3027, 742, 2322, 2433, 1495, 13, 1678, 6139, 353, 4733, 29889, 15778, 580, 29871, 13, 13, 1678, 822, 4770, 710, 12035, 1311, 1125, 13, 4706, 736, 1583, 29889, 8216, 2 ]
core/tests/test_polyflow/test_workflows/test_hyperband.py	erexer/polyaxon	0	8286	<reponame>erexer/polyaxon #!/usr/bin/python # # Copyright 2018-2020 Polyaxon, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pytest from marshmallow.exceptions import ValidationError from tests.utils import BaseTestCase, assert_equal_dict from polyaxon.polyflow.matrix import V1Hyperband from polyaxon.polyflow.optimization import V1Optimization, V1OptimizationMetric @pytest.mark.workflow_mark class TestWorkflowV1Hyperbands(BaseTestCase): def test_hyperband_config(self): config_dict = { "kind": "hyperband", "maxIterations": 10, "eta": 3, "resource": {"name": "steps", "type": "int"}, "resume": False, "metric": V1OptimizationMetric( name="loss", optimization=V1Optimization.MINIMIZE ).to_dict(), "params": {"lr": {"kind": "choice", "value": [[0.1], [0.9]]}}, } config = V1Hyperband.from_dict(config_dict) assert_equal_dict(config.to_dict(), config_dict) # Raises for negative values config_dict["maxIterations"] = 0 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["maxIterations"] = -0.5 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["maxIterations"] = 3 # Add numRuns percent config_dict["eta"] = -0.5 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["eta"] = 2.9 config = V1Hyperband.from_dict(config_dict) assert_equal_dict(config.to_dict(), config_dict)	[ 1, 529, 276, 1112, 420, 29958, 406, 29916, 261, 29914, 22678, 1165, 265, 13, 29937, 14708, 4855, 29914, 2109, 29914, 4691, 13, 29937, 13, 29937, 14187, 1266, 29871, 29906, 29900, 29896, 29947, 29899, 29906, 29900, 29906, 29900, 21755, 1165, 265, 29892, 9266, 29889, 13, 29937, 13, 29937, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 13, 29937, 366, 1122, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 13, 29937, 887, 1122, 4017, 263, 3509, 310, 278, 19245, 472, 13, 29937, 13, 29937, 418, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 13, 29937, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 13, 29937, 399, 1806, 8187, 2692, 399, 1718, 29934, 13566, 29059, 6323, 8707, 29928, 22122, 29903, 8079, 13764, 29979, 476, 22255, 29892, 2845, 4653, 470, 2411, 2957, 29889, 13, 29937, 2823, 278, 19245, 363, 278, 2702, 4086, 14765, 1076, 11239, 322, 13, 29937, 27028, 1090, 278, 19245, 29889, 13, 13, 5215, 11451, 1688, 13, 13, 3166, 1766, 845, 29885, 9536, 29889, 11739, 29879, 1053, 15758, 362, 2392, 13, 3166, 6987, 29889, 13239, 1053, 7399, 3057, 8259, 29892, 4974, 29918, 11745, 29918, 8977, 13, 13, 3166, 15680, 1165, 265, 29889, 22678, 1731, 29889, 5344, 1053, 478, 29896, 26322, 546, 4980, 13, 3166, 15680, 1165, 265, 29889, 22678, 1731, 29889, 20640, 2133, 1053, 478, 29896, 20624, 326, 2133, 29892, 478, 29896, 20624, 326, 2133, 10095, 2200, 13, 13, 13, 29992, 2272, 1688, 29889, 3502, 29889, 1287, 1731, 29918, 3502, 13, 1990, 4321, 5531, 1731, 29963, 29896, 26322, 546, 29890, 4167, 29898, 5160, 3057, 8259, 1125, 13, 1678, 822, 1243, 29918, 24947, 4980, 29918, 2917, 29898, 1311, 1125, 13, 4706, 2295, 29918, 8977, 353, 426, 13, 9651, 376, 14380, 1115, 376, 24947, 4980, 613, 13, 9651, 376, 3317, 13463, 800, 1115, 29871, 29896, 29900, 29892, 13, 9651, 376, 1187, 1115, 29871, 29941, 29892, 13, 9651, 376, 10314, 1115, 8853, 978, 1115, 376, 24530, 613, 376, 1853, 1115, 376, 524, 10758, 13, 9651, 376, 690, 2017, 1115, 7700, 29892, 13, 9651, 376, 16414, 1115, 478, 29896, 20624, 326, 2133, 10095, 2200, 29898, 13, 18884, 1024, 543, 6758, 613, 13883, 29922, 29963, 29896, 20624, 326, 2133, 29889, 16173, 7833, 29902, 10721, 13, 9651, 13742, 517, 29918, 8977, 3285, 13, 9651, 376, 7529, 1115, 8853, 29212, 1115, 8853, 14380, 1115, 376, 16957, 613, 376, 1767, 1115, 5519, 29900, 29889, 29896, 1402, 518, 29900, 29889, 29929, 5262, 11656, 13, 4706, 500, 13, 4706, 2295, 353, 478, 29896, 26322, 546, 4980, 29889, 3166, 29918, 8977, 29898, 2917, 29918, 8977, 29897, 13, 4706, 4974, 29918, 11745, 29918, 8977, 29898, 2917, 29889, 517, 29918, 8977, 3285, 2295, 29918, 8977, 29897, 13, 13, 4706, 396, 390, 1759, 267, 363, 8178, 1819, 13, 4706, 2295, 29918, 8977, 3366, 3317, 13463, 800, 3108, 353, 29871, 29900, 13, 4706, 411, 1583, 29889, 9294, 29934, 1759, 267, 29898, 19448, 2392, 1125, 13, 9651, 478, 29896, 26322, 546, 4980, 29889, 3166, 29918, 8977, 29898, 2917, 29918, 8977, 29897, 13, 13, 4706, 2295, 29918, 8977, 3366, 3317, 13463, 800, 3108, 353, 448, 29900, 29889, 29945, 13, 4706, 411, 1583, 29889, 9294, 29934, 1759, 267, 29898, 19448, 2392, 1125, 13, 9651, 478, 29896, 26322, 546, 4980, 29889, 3166, 29918, 8977, 29898, 2917, 29918, 8977, 29897, 13, 13, 4706, 2295, 29918, 8977, 3366, 3317, 13463, 800, 3108, 353, 29871, 29941, 13, 4706, 396, 3462, 954, 6558, 29879, 10151, 13, 4706, 2295, 29918, 8977, 3366, 1187, 3108, 353, 448, 29900, 29889, 29945, 13, 4706, 411, 1583, 29889, 9294, 29934, 1759, 267, 29898, 19448, 2392, 1125, 13, 9651, 478, 29896, 26322, 546, 4980, 29889, 3166, 29918, 8977, 29898, 2917, 29918, 8977, 29897, 13, 13, 4706, 2295, 29918, 8977, 3366, 1187, 3108, 353, 29871, 29906, 29889, 29929, 13, 4706, 2295, 353, 478, 29896, 26322, 546, 4980, 29889, 3166, 29918, 8977, 29898, 2917, 29918, 8977, 29897, 13, 4706, 4974, 29918, 11745, 29918, 8977, 29898, 2917, 29889, 517, 29918, 8977, 3285, 2295, 29918, 8977, 29897, 13, 2 ]
Day 4/D4.py	avidiotic/advent-of-code	0	186805	<reponame>avidiotic/advent-of-code import re from collections import defaultdict input_file = open('Puzzle4_input.txt','r') data = input_file.read().split('\n') data.sort() entry = [(list(map(int,re.findall(r'\d+',line))), re.findall(r'[a-zA-Z].+',line)) for line in data] log_gt = defaultdict(int) log_g = defaultdict(int) log_t = defaultdict(int) for timecode, text in entry: date = str(timecode[1])+"-"+str(timecode[2]) time_end_index = timecode[4] if 'begins shift' in text[0]: guard = timecode[5] asleep = None elif 'falls asleep' in text[0]: asleep = timecode[4] elif 'wakes up' in text[0]: for t in range(asleep, timecode[4]): log_gt[(guard,t)] += 1 log_g[guard] += 1 def max_g(d): best = None for k,v in d.items(): if(best is None or v > d[best]): best = k return(best) def max_t(d): best = None for (guard, time) in d: if(guard == best_guard): if(best is None or d[(guard,time)] > d[best]): best = (guard, time) return(best[1]) best_guard = max_g(log_g) best_time = max_t(log_gt) print(best_guard * best_time) def max_gt(d): best = None for (guard,time) in d: if(best is None or d[(guard,time)] > d[best]): best = (guard,time) return(best) (best_guard, best_time) = max_gt(log_gt) print(best_guard*best_time)	[ 1, 529, 276, 1112, 420, 29958, 485, 8819, 13574, 29914, 328, 794, 29899, 974, 29899, 401, 13, 5215, 337, 13, 3166, 16250, 1053, 2322, 8977, 13, 13, 2080, 29918, 1445, 353, 1722, 877, 29925, 18813, 280, 29946, 29918, 2080, 29889, 3945, 3788, 29878, 1495, 13, 1272, 353, 1881, 29918, 1445, 29889, 949, 2141, 5451, 28909, 29876, 1495, 13, 1272, 29889, 6605, 580, 13, 13, 13, 8269, 353, 17288, 1761, 29898, 1958, 29898, 524, 29892, 276, 29889, 2886, 497, 29898, 29878, 12764, 29881, 29974, 742, 1220, 876, 511, 337, 29889, 2886, 497, 29898, 29878, 29915, 29961, 29874, 29899, 25265, 29899, 29999, 1822, 29974, 742, 1220, 876, 363, 1196, 297, 848, 29962, 13, 1188, 29918, 4141, 353, 2322, 8977, 29898, 524, 29897, 13, 1188, 29918, 29887, 353, 2322, 8977, 29898, 524, 29897, 13, 1188, 29918, 29873, 353, 2322, 8977, 29898, 524, 29897, 13, 13, 1454, 931, 401, 29892, 1426, 297, 6251, 29901, 13, 1678, 2635, 353, 851, 29898, 2230, 401, 29961, 29896, 2314, 13578, 29899, 17969, 710, 29898, 2230, 401, 29961, 29906, 2314, 13, 1678, 931, 29918, 355, 29918, 2248, 353, 931, 401, 29961, 29946, 29962, 13, 1678, 565, 525, 463, 29879, 9500, 29915, 297, 1426, 29961, 29900, 5387, 13, 4706, 8372, 353, 931, 401, 29961, 29945, 29962, 13, 4706, 408, 5436, 353, 6213, 13, 1678, 25342, 525, 12559, 408, 5436, 29915, 297, 1426, 29961, 29900, 5387, 13, 4706, 408, 5436, 353, 931, 401, 29961, 29946, 29962, 13, 1678, 25342, 525, 29893, 6926, 701, 29915, 297, 1426, 29961, 29900, 5387, 13, 4706, 363, 260, 297, 3464, 29898, 294, 5436, 29892, 931, 401, 29961, 29946, 29962, 1125, 13, 9651, 1480, 29918, 4141, 15625, 17728, 29892, 29873, 4638, 4619, 29871, 29896, 13, 9651, 1480, 29918, 29887, 29961, 17728, 29962, 4619, 29871, 29896, 13, 13, 1753, 4236, 29918, 29887, 29898, 29881, 1125, 13, 1678, 1900, 353, 6213, 13, 1678, 363, 413, 29892, 29894, 297, 270, 29889, 7076, 7295, 13, 4706, 565, 29898, 13318, 338, 6213, 470, 325, 1405, 270, 29961, 13318, 29962, 1125, 13, 9651, 1900, 353, 413, 13, 1678, 736, 29898, 13318, 29897, 13, 13, 13, 13, 1753, 4236, 29918, 29873, 29898, 29881, 1125, 13, 1678, 1900, 353, 6213, 13, 1678, 363, 313, 17728, 29892, 931, 29897, 297, 270, 29901, 13, 4706, 565, 29898, 17728, 1275, 1900, 29918, 17728, 1125, 13, 9651, 565, 29898, 13318, 338, 6213, 470, 270, 15625, 17728, 29892, 2230, 4638, 1405, 270, 29961, 13318, 29962, 1125, 13, 18884, 1900, 353, 313, 17728, 29892, 931, 29897, 13, 1678, 736, 29898, 13318, 29961, 29896, 2314, 13, 13, 13318, 29918, 17728, 353, 4236, 29918, 29887, 29898, 1188, 29918, 29887, 29897, 13, 13318, 29918, 2230, 353, 4236, 29918, 29873, 29898, 1188, 29918, 4141, 29897, 13, 2158, 29898, 13318, 29918, 17728, 334, 1900, 29918, 2230, 29897, 13, 13, 1753, 4236, 29918, 4141, 29898, 29881, 1125, 13, 1678, 1900, 353, 6213, 13, 1678, 363, 313, 17728, 29892, 2230, 29897, 297, 270, 29901, 13, 4706, 565, 29898, 13318, 338, 6213, 470, 270, 15625, 17728, 29892, 2230, 4638, 1405, 270, 29961, 13318, 29962, 1125, 13, 9651, 1900, 353, 313, 17728, 29892, 2230, 29897, 13, 1678, 736, 29898, 13318, 29897, 13, 29898, 13318, 29918, 17728, 29892, 1900, 29918, 2230, 29897, 353, 4236, 29918, 4141, 29898, 1188, 29918, 4141, 29897, 13, 2158, 29898, 13318, 29918, 17728, 29930, 13318, 29918, 2230, 29897, 4706, 2 ]
src/fresnel/f_ratio.py	JonNRb/physics506	0	52192	<gh_stars>0 txt = None with open('f_data.txt') as f: txt = f.read() lines = [i for i in txt.split('\n') if i] data = [[int(i.strip()) for i in j.split('\t')] for j in lines] import math d2r = lambda ang: ang * math.pi / 180 ratio = lambda ang_2, ang_1: math.sin(d2r(ang_1)) / math.sin(d2r(ang_2)) for point in data: print(ratio(point)) print('avg:', sum(ratio(point) for point in data) / len(lines))	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 3945, 353, 6213, 13, 2541, 1722, 877, 29888, 29918, 1272, 29889, 3945, 1495, 408, 285, 29901, 13, 29871, 13872, 353, 285, 29889, 949, 580, 13, 13, 9012, 353, 518, 29875, 363, 474, 297, 13872, 29889, 5451, 28909, 29876, 1495, 565, 474, 29962, 13, 13, 1272, 353, 5519, 524, 29898, 29875, 29889, 17010, 3101, 363, 474, 297, 432, 29889, 5451, 28909, 29873, 1495, 29962, 363, 432, 297, 3454, 29962, 13, 13, 5215, 5844, 13, 13, 29881, 29906, 29878, 353, 14013, 2614, 29901, 2614, 334, 5844, 29889, 1631, 847, 29871, 29896, 29947, 29900, 13, 13, 3605, 601, 353, 14013, 2614, 29918, 29906, 29892, 2614, 29918, 29896, 29901, 5844, 29889, 5223, 29898, 29881, 29906, 29878, 29898, 574, 29918, 29896, 876, 847, 5844, 29889, 5223, 29898, 29881, 29906, 29878, 29898, 574, 29918, 29906, 876, 13, 13, 1454, 1298, 297, 848, 29901, 13, 29871, 1596, 29898, 3605, 601, 10456, 3149, 876, 13, 13, 2158, 877, 485, 29887, 29901, 742, 2533, 29898, 3605, 601, 10456, 3149, 29897, 363, 1298, 297, 848, 29897, 847, 7431, 29898, 9012, 876, 13, 2 ]
ofspy/interSatelliteLink.py	ehsanfar/ofspy_v2	0	138010	""" Copyright 2015 <NAME>, Massachusetts Institute of Technology Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ """ InterSatelliteLink class. """ from .transceiver import Transceiver class InterSatelliteLink(Transceiver): def __init__(self, name=None, cost=0, size=1, capacity=1, protocol=None, maxTransmitted=1, maxReceived=1): """ @param name: the name of this transceiver @type name: L{str} @param cost: the cost of this inter-satellite link @type cost: L{float} @param size: the size of this inter-satellite link @type size: L{float} @param capacity: the data capacity of this inter-satellite link @type capacity: L{int} @param protocol: the protocol of this inter-satellite link @type protocol: L{str} @param maxTransmitted: the max data transmitted by this inter-satellite link each turn @type maxTransmitted: L{int} @param maxReceived: the max data received by this inter-satellite link each turn @type maxReceived: L{int} """ Transceiver.__init__(self, name=name, cost=cost, size=size, capacity=capacity, protocol=protocol, maxTransmitted=maxTransmitted, maxReceived=maxReceived) def couldTransmit(self, data, receiver, txLocation, rxLocation, context): """ Checks if this inter-satellite link could transmit data (state-independent). @param data: the data to transmit @type data: L{Data} @param receiver: the receiver receiving the data @type receiver: L{Transceiver} @param txLocation: the transmitter location @type txLocation: L{Location} @param rxLocation: the receiver location @type rxLocation: L{Location} @param context: the context @type context: L{Context} @return: L{bool} """ return super(InterSatelliteLink, self).couldTransmit(data, receiver) \ and txLocation.isOrbit() \ and rxLocation.isOrbit() \ and (abs(txLocation.sector - rxLocation.sector) <= 1 or abs(txLocation.sector - rxLocation.sector) >= context.getNumSectors() - 1) def couldReceive(self, data, transmitter, txLocation, rxLocation, context): """ Checks if this inter-satellite link could receive data (state-independent). @param data: the data to transmit @type data: L{Data} @param transmitter: the transmitter transmitting the data @type transmitter: L{Transceiver} @param txLocation: the transmitter location @type txLocation: L{Location} @param rxLocation: the receiver location @type rxLocation: L{Location} @param context: the context @type context: L{Context} @return: L{bool} """ return super(InterSatelliteLink, self).couldReceive(data, transmitter) \ and txLocation.isOrbit() \ and rxLocation.isOrbit() \ and (abs(txLocation.sector - rxLocation.sector) <= 1 or abs(txLocation.sector - rxLocation.sector) >= context.getNumSectors() - 1) def isISL(self): """ Checks if this is an inter-satellite link. @return: L{bool} """ return True	[ 1, 9995, 13, 11882, 1266, 29871, 29906, 29900, 29896, 29945, 529, 5813, 10202, 16167, 8907, 310, 17968, 13, 13, 29931, 293, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 13, 6293, 1122, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 13, 3492, 1122, 4017, 263, 3509, 310, 278, 19245, 472, 13, 13, 1678, 1732, 597, 1636, 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pytils/clock.py	d33jiang/pytils	0	28441	import functools import heapq import logging from collections import deque from threading import Condition, RLock from typing import Any, Callable, List, NamedTuple, Optional from pytils.mixins import DaemonHandler from ._config.time import DEFAULT_TIME_SUPPLIER, TimeSupplier, TimeType, ZERO_DURATION __all__ = [ 'Action', 'Clock', 'Handler', 'Schedule', 'ScheduleKey', 'SchedulingQueue', 'TimeSupplier', 'TimeType', ] _DEFAULT_MAX_TASK_QUEUE_SIZE = 4096 _MAX_SLEEP_DURATION = 12. # # Convenience Function wrap_action = functools.partial # # Data Definitions class ScheduleKey(NamedTuple): period: Optional[float] action: 'Action' class ScheduleEntry(NamedTuple): next_run: float key: 'ScheduleKey' Action = Callable[[], Any] Handler = Callable[[Action], Any] # # Clock LOGGER = logging.getLogger('pytils.clock') class Clock: def __init__( self, max_queue_size: int = _DEFAULT_MAX_TASK_QUEUE_SIZE, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self._scheduling_queue = SchedulingQueue(max_queue_size, s_time) @property def schedule(self): return self._scheduling_queue.schedule def run_scheduler(self): self.schedule.run() def start_scheduler(self): self.schedule.start() def run_handler(self): self._scheduling_queue.run() def start_handler(self): self._scheduling_queue.start() class SchedulingQueue(DaemonHandler): def __init__( self, max_queue_size: int = _DEFAULT_MAX_TASK_QUEUE_SIZE, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self._cv = Condition() self._task_queue = deque(maxlen=max_queue_size) self._schedule = Schedule(self._enqueue, s_time) @property def schedule(self): return self._schedule def handle_one(self): with self._cv: self._cv.wait_for(self._task_queue.__len__) action = self._task_queue.popleft() self._cv.notify() action() def _enqueue(self, action: Action): with self._cv: self._task_queue.append(action) self._cv.notify() class Schedule(DaemonHandler): def __init__(self, handler: Handler, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self.s_time = s_time self._lock = RLock() self._cv = Condition(self._lock) self._schedule = [] # type: List[ScheduleEntry] self._handler = handler def register( self, action: Action, period: Optional[TimeType], delay: Optional[TimeType] = None) -> ScheduleKey: if period <= ZERO_DURATION: raise ValueError('period must be positive or None') if delay < ZERO_DURATION: raise ValueError('delay must be non-negative or None') if not delay: delay = ZERO_DURATION key = ScheduleKey(period, action) entry = ScheduleEntry(self.s_time() + delay, key) with self._cv: self._enqueue(entry) return key def handle_one(self): with self._cv: while not self._cv.wait_for(self.has_expired, self._get_next_sleep_duration()): pass self._handle_entry(self._dequeue()) def _handle_entry(self, entry: ScheduleEntry): self._handler(self._create_readmittence_action_from_key(entry.key)) def _create_readmittence_action_from_key(self, key: ScheduleKey) -> Action: if key.period is None: return key.action def perform_action_and_readmit(): next_run = self.s_time() + key.period key.action() current_time = self.s_time() if next_run < current_time: LOGGER.warning('Scheduled task took longer than its period length to complete') self._enqueue(ScheduleEntry(max(current_time, next_run), key)) return perform_action_and_readmit def has_expired(self) -> bool: with self._lock: return bool(self._schedule) and self._schedule[0].next_run - self.s_time() <= 0 def _get_next_sleep_duration(self) -> TimeType: if self._schedule: return min(_MAX_SLEEP_DURATION, max(ZERO_DURATION, self._schedule[0].next_run - self.s_time())) else: return _MAX_SLEEP_DURATION def _enqueue(self, entry: ScheduleEntry): self._cv.notify() heapq.heappush(self._schedule, entry) def _dequeue(self) -> Optional[ScheduleEntry]: self._cv.notify() return heapq.heappop(self._schedule) if self._schedule else None	[ 1, 1053, 2090, 312, 8789, 13, 5215, 16947, 29939, 13, 5215, 12183, 13, 3166, 16250, 1053, 316, 802, 13, 3166, 3244, 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pyjq/__init__.py	spraakbanken/pyjq	0	192198	<gh_stars>0 from .cli import cli	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 13, 3166, 869, 11303, 1053, 9335, 13, 2 ]
splicing_annotations/countSupportingReads.py	stevenxchen/splicing-modulators	0	154382	<filename>splicing_annotations/countSupportingReads.py #Junction counter adapted from rMATS "process unique sam" ### import necessary libraries import re,os,sys,logging,time,datetime,commands,argparse; import scipy,math,pickle,pysam; from scipy import stats; def listToString(x): rVal = ''; for a in x: rVal += a+' '; return rVal; ######### basic functions ############# # #Input: #insertsize_inclusion: a numerical variable for the paired-end read inclusion form insert size #insertsize_skipping: a numerical variable for the paired-end read skipping form insert size #insertsize_mean: a numerical variable for the mean of the insert size #insertsize_var: a numerical variable for the variance of the insert size #Output: #A 2-element vector for the [fraction of the inclusion form, fraction of the skipping form] def PE_fraction(insertsize_inclusion, insertsize_skipping, insertsize_mean, insertsize_var): p1=stats.norm.cdf(insertsize_inclusion+0.5,insertsize_mean,math.sqrt(insertsize_var)); p1=p1-stats.norm.cdf(insertsize_inclusion-0.5,insertsize_mean,math.sqrt(insertsize_var)); p2=stats.norm.cdf(insertsize_skipping+0.5,insertsize_mean,math.sqrt(insertsize_var)); p2=p2-stats.norm.cdf(insertsize_skipping-0.5,insertsize_mean,math.sqrt(insertsize_var)); return([p1/(p1+p2),p2/(p1+p2)]); def getInitialCounts(): ## getting initial counts for each AS event #rValue = [[[[],[]]],[[[],[]]],[[[],[]]]]; ## count type 1, 2, and 3, Include or Skip rValue = [[[],[]],[[],[]],[[],[]]]; rValue[CT1][I]=0; rValue[CT1][S]=0; rValue[CT2][I]=0; rValue[CT2][S]=0; rValue[CT3][I]=0; rValue[CT3][S]=0; return rValue; #### end of getInitialCounts() ############################### ## SAMPLE COUNTING FUNCTIONS ## ############################### def is_unique(r): # check if read is uniquely mapped for tag in r.tags: if tag[0]=='NH': # NH is tag for number of hits if int(tag[1])==1: # uniquely mapped if NH=1 if dataType=='single': ## single end, sufficient return True; elif r.is_proper_pair: return True; return False # def processSample(sample): ## call it with processSample(sample_1, S1) something like this global anchorLength; readCount=0; ### process the given sample ### #for s1 in sample: ## for each sam file # rep = sample.index(s1); # if len(s1.strip())<1: ## incorrect split. a user might accidently put comma at the end of input sam file list # continue; ### just skip this entry, probably the last one though s1=sample; sFile = pysam.Samfile(s1.strip(),'rb'); ## open bam file e1 = {}; ## edge count here for read in sFile.fetch(): readCount=readCount+1; if (readCount % 1000000) == 0: print(str(readCount)+" reads processed..."); if not is_unique(read): continue; rL = readLength; chr = sFile.getrname(read.tid) if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; mc = read.pos+1 mString = read.cigarstring #rID = read.qname group = mc/chunk; ## group does not change, it's okay to check only one group for a junction read ## if showMe: print 'mc:'+ str(group); if 'D' in mString or 'I' in mString or 'S' in mString or 'H' in mString or 'P' in mString or 'X' in mString or '=' in mString: ## skip continue; ## go to next line ### check to see if the line is either exonic read or junction read split_mString = mString.split('M'); tor = 0; ## type of read, 0 nothing, 1 exonic read, 2 junction read if len(split_mString)==2: tor = 1; ############ exonic read ###### rL = int(split_mString[0]); ## read length specified in this mapping string mec = mc+rL-1; ## mapping end coord egroup = mec/chunk; ## group for the mapping end coord of genomic reads if rL != readLength: continue ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group if (mc>se[chr][group][c][0] and mec<=se[chr][group][c][1]): ## read on the target c_se[c][CT2][I]+=1; ### end of SE ### ### MXE #### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group if (mc>mxe[chr][group][c][0] and mec<=mxe[chr][group][c][1]): ## read on the target exon c_mxe[c][CT2][I]+=1; elif (mc>mxe[chr][group][c][2] and mec<=mxe[chr][group][c][3]): ## read on the second exon c_mxe[c][CT2][S]+=1; ## end of MXE ### ## A5SS ## if chr in a5ss: ## this chromosome has a5ss event(s) if egroup in a5ss[chr]: ## this egroup has a5ss event(s), this group is valid for positive strand only for c in a5ss[chr][egroup]: ## for each a5ss event in this group if a5ss[chr][egroup][c][4]>a5ss[chr][egroup][c][1]: ## positive strand if (mc<=(a5ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a5ss[chr][egroup][c][1] and mec>=(a5ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][egroup][c][3] and mec<=a5ss[chr][egroup][c][1]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; if group in a5ss[chr]: ## this group has a5ss event(s), this group is valid for negative strand only for c in a5ss[chr][group]: ## for each a5ss event in this group if a5ss[chr][group][c][4]<a5ss[chr][group][c][1]: ## negative strand if (mc>a5ss[chr][group][c][0] and mc<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][group][c][0] and mec<=a5ss[chr][group][c][2]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; ## end of A5SS ### ## A3SS ## if chr in a3ss: ## this chromosome has a3ss event(s) if egroup in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][egroup]: ## for each a3ss event in this group if a3ss[chr][egroup][c][4]>a3ss[chr][egroup][c][1]: ## negative strand if (mc<=(a3ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a3ss[chr][egroup][c][1] and mec>=(a3ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][egroup][c][3] and mec<=a3ss[chr][egroup][c][1]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group if a3ss[chr][group][c][4]<a3ss[chr][group][c][1]: ## positive strand if (mc>a3ss[chr][group][c][0] and mc<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][group][c][0] and mec<=a3ss[chr][group][c][2]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; ## end of A3SS ### ## RI ## if chr in ri: ## this chromosome has ri event(s) groupsToExamine = list(set([group,egroup])); ## to examine multiple groups tempProcessedRI_id={}; ## to examine multiple groups for ggg in groupsToExamine: ## for each group if ggg in ri[chr]: ## this group has ri event(s) for c in ri[chr][ggg]: ## for each ri event in this group, strand does not matter for ri events if c in tempProcessedRI_id: ## already processed this event, skip it continue; ## next c please else: ## new c here tempProcessedRI_id[c]='1'; if (mc<=(ri[chr][ggg][c][3]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][3]+(rL-junctionLength/2))) or (mc<=(ri[chr][ggg][c][4]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][4]+(rL-junctionLength/2))): ## multi-exon read supporting target c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; if (mc>ri[chr][ggg][c][3] and mec<=ri[chr][ggg][c][4]): ## exon read supporting target c_ri[c][CT2][I]+=1; ## end of RI ### ####### now take care of junction counts from junction reads ###### elif len(split_mString)>=3: ###### junction read ########### beginning=int(split_mString[0].split('N')[-1]); ending = int(split_mString[-2].split('N')[-1]); jS=mc; jE=mc-1; usedE={};## to avoid using the same read more than one time for the same event #usedG={}; ## used group, to avoid examining the same group more than once prevN=-1; nextN=-1; ## for previous junction and next junction for ec in range(0,len(split_mString)-2): ## for each coordinate secondNumber = int(split_mString[ec].split('N')[-1]); jumpNumber = int(split_mString[ec+1].split('N')[0]); lastNumber = int(split_mString[ec+1].split('N')[-1]); if ec>0: ## there is prevN prevN = int(split_mString[ec].split('N')[0]); if (ec>=0 and ec<len(split_mString)-3): ## there is nextN nextN = int(split_mString[ec+2].split('N')[0]); if (ec>=0 and ec<len(split_mString)-2): ## there iS nextN if (ec==len(split_mString)-3): nextN=-1; else: nextN = int(split_mString[ec+2].split('N')[0]); jS = jE+secondNumber; ## 1-base jE = jS+jumpNumber; ## 0-base key = chr+'_'+str(jS)+'_'+str(jE); cStart=jS-secondNumber+1; cEnd=jS; cStart_last=cStart; cEnd_last=cEnd; minAnchor = min(int(split_mString[0]), int(split_mString[-2].split('N')[1])); ## min nts going across junction if minAnchor<anchorLength: ## not a valid junction read, do not count it continue; if ec==0: ## first junction, check the first number if beginning<anchorLength: ## not a valid junction read, do not count it continue; ## next junction if ec==(len(split_mString)-3): ## check the last segment length if ending<anchorLength: ## not a valid junction read, do not count it continue; ## edge counts if key in e1: ## exist! e1[key] = e1[key]+1; else: ## new junction e1[key] = 1; group = jS/chunk; ## changing group here #if group in usedG: ## already visited this group # continue; ## next junction coord #else: ## update usedG dictioanry # usedG[group]='1'; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group, examine if the given junction is part of it seLength=se[chr][group][c][1]-se[chr][group][c][0]; upjLength=se[chr][group][c][0]-se[chr][group][c][3]; dnjLength=se[chr][group][c][4]-se[chr][group][c][1]; if (jS==se[chr][group][c][3] and jE==se[chr][group][c][0] and ((lastNumber<=seLength and nextN==-1) or (lastNumber==seLength and nextN==dnjLength))) or (jS==se[chr][group][c][1] and jE==se[chr][group][c][4] and ((secondNumber<=seLength and prevN==-1) or (secondNumber==seLength and prevN==upjLength))): ## IJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][I]+=1; c_se[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif jS==se[chr][group][c][3] and jE==se[chr][group][c][4]: ## SJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][S]+=1; c_se[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of SE ### ## MXE ### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group, examine if the given junction is part of it mxeLen1=mxe[chr][group][c][1]-mxe[chr][group][c][0]; mxeLen2=mxe[chr][group][c][3]-mxe[chr][group][c][2]; upj1Len=mxe[chr][group][c][0]-mxe[chr][group][c][5]; dnj1Len=mxe[chr][group][c][6]-mxe[chr][group][c][1]; upj2Len=mxe[chr][group][c][2]-mxe[chr][group][c][5]; dnj2Len=mxe[chr][group][c][6]-mxe[chr][group][c][3]; if (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][0] and ((lastNumber<=mxeLen1 and nextN==-1) or (lastNumber==mxeLen1 and nextN==dnj1Len))) or (jS==mxe[chr][group][c][1] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen1 and prevN==-1) or (secondNumber==mxeLen1 and prevN==upj1Len))): ## IJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][I]+=1; c_mxe[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][2] and ((lastNumber<=mxeLen2 and nextN==-1) or (lastNumber==mxeLen2 and nextN==dnj2Len))) or (jS==mxe[chr][group][c][3] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen2 and prevN==-1) or (secondNumber==mxeLen2 and prevN==upj2Len))): ## SJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][S]+=1; c_mxe[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of MXE ### ## A5SS ### if chr in a5ss: ## this chromosome has a5ss event(s) if group in a5ss[chr]: ## this group has a5ss event(s) for c in a5ss[chr][group]: ## for each a5ss event in this group, examine if the given junction is part of it if a5ss[chr][group][c][4]>a5ss[chr][group][c][1]: ## positive strand if ( jS==a5ss[chr][group][c][1] and jE==a5ss[chr][group][c][4] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][3] and jE==a5ss[chr][group][c][4] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; if (cStart_last<=(a5ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last<=a5ss[chr][group][c][1] and cEnd_last>=(a5ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## negative strand if ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][0] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][2] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: if (cStart>a5ss[chr][group][c][0] and cStart<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A5SS ### ## A3SS ### if chr in a3ss: ## this chromosome has a3ss event(s) if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group, examine if the given junction is part of it if a3ss[chr][group][c][4]>a3ss[chr][group][c][1]: ## negative strand if ( jS==a3ss[chr][group][c][1] and jE==a3ss[chr][group][c][4] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][3] and jE==a3ss[chr][group][c][4] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; if (cStart_last<=(a3ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last<=a3ss[chr][group][c][1] and cEnd_last>=(a3ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A3SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## positive strand if ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][0] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][2] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: if (cStart>a3ss[chr][group][c][0] and cStart<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A3SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A3SS ### ## RI ### if chr in ri: ## this chromosome has ri event(s) if group in ri[chr]: ## this group has ri event(s) for c in ri[chr][group]: ## for each ri event in this group, examine if the given junction is part of it if jS==ri[chr][group][c][3] and jE==ri[chr][group][c][4] : ## SJC key=':'.join(["RI",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_ri[c][CT1][S]+=1; c_ri[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite if prevN == -1: if cStart<=(ri[chr][group][c][4]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][4]+(rL-junctionLength/2)): ## multi-exon read supporting target key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite if nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; ## just change cStart and cEnd then do the same process if cStart_last<=(ri[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last>=(ri[chr][group][c][3]+(rL-junctionLength/2)): key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of RI ### #### end of for ec ##### else: ## it is not exonic nor junction read. proceed to the next line continue; sFile.close(); #edgeFile = open(s1.strip()+'.edgeCount', 'w'); #for k in e1: # edgeFile.write(k+'\t'+str(e1[k])+'\n'); #edgeFile.close(); ##### end of processSample ###### def processSample_stranded(sample,dt,lt): ## call it with processSample_firststrand(sample_1, S1,dataType,libraryType) something like this global anchorLength; ### process the given sample ### #for s1 in sample: ## for each sam file # rep = sample.index(s1); # if len(s1.strip())<1: ## incorrect split. a user might accidently put comma at the end of input sam file list # continue; ### just skip this entry, probably the last one though s1=sample; sFile = pysam.Samfile(s1.strip(),'rb'); ## open bam file e1 = {}; ## edge count here for read in sFile.fetch(): if not is_unique(read): continue; rL = readLength; chr = sFile.getrname(read.tid) if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; mc = read.pos+1 mString = read.cigarstring #rID = read.qname group = mc/chunk; ## group does not change, it's okay to check only one group for a junction read if 'D' in mString or 'I' in mString or 'S' in mString or 'H' in mString or 'P' in mString or 'X' in mString or '=' in mString: ## skip continue; ## go to next line ### check to see if the line is either exonic read or junction read split_mString = mString.split('M'); tor = 0; ## type of read, 0 nothing, 1 exonic read, 2 junction read if len(split_mString)==2: tor = 1; ############ exonic read ###### rL = int(split_mString[0]); ## read length specified in this mapping string mec = mc+rL-1; ## mapping end coord egroup = mec/chunk; myStrand=''; sFlag=read.flag; if dt=='paired' and lt=='first': ## paired-read, firststrand if (sFlag&16 and sFlag&64) or (sFlag&32 and sFlag&128): ##'+' strand myStrand='+'; elif (sFlag&32 and sFlag&64) or (sFlag&16 and sFlag&128): ##'-' strand myStrand='-'; elif dt=='paired' and lt=='second': ## paired-read, secondstrand if (sFlag&32 and sFlag&64) or (sFlag&16 and sFlag&128): ##'+' strand myStrand='+'; elif (sFlag&16 and sFlag&64) or (sFlag&32 and sFlag&128): ##'-' strand myStrand='-'; elif dt=='single' and lt=='first': ##single-end, firststrand if sFlag&16 : ##'+' strand myStrand='+'; elif sFlag&32: ##'-' strand myStrand='-'; elif dt=='single' and lt=='second': ##single-end, secondstrand if sFlag&32 : ##'+' strand myStrand='+'; elif sFlag&16: ##'-' strand myStrand='-'; if len(myStrand)==0 or rL != readLength: ## skip this read, cannot determine the strand continue; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group if se[chr][group][c][-1]==myStrand: ## same strand if (mc>se[chr][group][c][0] and mec<=se[chr][group][c][1]): ## read on the target c_se[c][CT2][I]+=1; ### end of SE ### ### MXE #### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group if mxe[chr][group][c][-1]==myStrand: ## same strand if (mc>mxe[chr][group][c][0] and mec<=mxe[chr][group][c][1]): ## read on the target exon c_mxe[c][CT2][I]+=1; elif (mc>mxe[chr][group][c][2] and mec<=mxe[chr][group][c][3]): ## read on the second exon c_mxe[c][CT2][S]+=1; ## end of MXE ### ## A5SS ## if chr in a5ss: ## this chromosome has a5ss event(s) if egroup in a5ss[chr]: ## this egroup has a5ss event(s), valid only for positive strand only for c in a5ss[chr][egroup]: ## for each a5ss event in this group if a5ss[chr][egroup][c][-1]==myStrand: ## same strand if a5ss[chr][egroup][c][4]>a5ss[chr][egroup][c][1]: ## positive strand if (mc<=(a5ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a5ss[chr][egroup][c][1] and mec>=(a5ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][egroup][c][3] and mec<=a5ss[chr][egroup][c][1]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; if group in a5ss[chr]: ## this group has a5ss event(s), for negative strand ones only for c in a5ss[chr][group]: ## for each a5ss event in this group if a5ss[chr][group][c][-1]==myStrand: ## same strand if a5ss[chr][group][c][4]<a5ss[chr][group][c][1]: ## negative strand if (mc>a5ss[chr][group][c][0] and mc<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][group][c][0] and mec<=a5ss[chr][group][c][2]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; ## end of A5SS ### ## A3SS ## if chr in a3ss: ## this chromosome has a3ss event(s) if egroup in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][egroup]: ## for each a3ss event in this group if a3ss[chr][egroup][c][-1]==myStrand: ## same strand if a3ss[chr][egroup][c][4]>a3ss[chr][egroup][c][1]: ## negative strand if (mc<=(a3ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a3ss[chr][egroup][c][1] and mec>=(a3ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][egroup][c][3] and mec<=a3ss[chr][egroup][c][1]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group if a3ss[chr][group][c][-1]==myStrand: ## same strand if a3ss[chr][group][c][4]<a3ss[chr][group][c][1]: ## positive strand if (mc>a3ss[chr][group][c][0] and mc<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][group][c][0] and mec<=a3ss[chr][group][c][2]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; ## end of A3SS ### ## RI ## if chr in ri: ## this chromosome has ri event(s) groupsToExamine = list(set([group,egroup])); ## to examine multiple groups tempProcessedRI_id={}; ## to examine multiple groups for ggg in groupsToExamine: ## for each group if ggg in ri[chr]: ## this group has ri event(s) for c in ri[chr][ggg]: ## for each ri event in this group, strand does not matter for ri events if c in tempProcessedRI_id: ## already processed this event, skip it continue; ## next c please else: ## new c here if ri[chr][ggg][c][-1]==myStrand: ## same strand if (mc<=(ri[chr][ggg][c][3]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][3]+(rL-junctionLength/2))) or (mc<=(ri[chr][ggg][c][4]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][4]+(rL-junctionLength/2))): ## multi-exon read supporting target c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; if (mc>ri[chr][ggg][c][3] and mec<=ri[chr][ggg][c][4]): ## exon read supporting target c_ri[c][CT2][I]+=1; ## end of RI ### ####### now take care of junction counts from junction reads ###### elif len(split_mString)>=3: ###### junction read ########### beginning=int(split_mString[0].split('N')[-1]); ending = int(split_mString[-2].split('N')[-1]); jS=mc; jE=mc-1; usedE={};## to avoid using the same read more than one time for the same event #usedG={}; ## used group, to avoid examining the same group more than once prevN=-1; nextN=-1; ## for previous junction and next junction for ec in range(0,len(split_mString)-2): ## for each coordinate secondNumber = int(split_mString[ec].split('N')[-1]); jumpNumber = int(split_mString[ec+1].split('N')[0]); lastNumber = int(split_mString[ec+1].split('N')[-1]); if ec>0: ## there is prevN prevN = int(split_mString[ec].split('N')[0]); if (ec>=0 and ec<len(split_mString)-3): ## there is nextN nextN = int(split_mString[ec+2].split('N')[0]); if (ec>=0 and ec<len(split_mString)-2): ## there iS nextN if (ec==len(split_mString)-3): nextN=-1; else: nextN = int(split_mString[ec+2].split('N')[0]); jS = jE+secondNumber; ## 1-base jE = jS+jumpNumber; ## 0-base key = chr+'_'+str(jS)+'_'+str(jE); cStart=jS-secondNumber+1; cEnd=jS; minAnchor = min(int(split_mString[0]), int(split_mString[-2].split('N')[1])); ## min nts going across junction if minAnchor<anchorLength: ## not a valid junction read, do not count it continue; if ec==0: ## first junction, check the first number if beginning<anchorLength: ## not a valid junction read, do not count it continue; ## next junction if ec==(len(split_mString)-3): ## check the last segment length if ending<anchorLength: ## not a valid junction read, do not count it continue; ## edge counts if key in e1: ## exist! e1[key] = e1[key]+1; else: ## new junction e1[key] = 1; group = jS/chunk; ## changing group here #if group in usedG: ## already visited this group # continue; ## next junction coord #else: ## update usedG dictioanry # usedG[group]='1'; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group, examine if the given junction is part of it seLength=se[chr][group][c][1]-se[chr][group][c][0]; upjLength=se[chr][group][c][0]-se[chr][group][c][3]; dnjLength=se[chr][group][c][4]-se[chr][group][c][1]; if (jS==se[chr][group][c][3] and jE==se[chr][group][c][0] and ((lastNumber<=seLength and nextN==-1) or (lastNumber==seLength and nextN==dnjLength))) or (jS==se[chr][group][c][1] and jE==se[chr][group][c][4] and ((secondNumber<=seLength and prevN==-1) or (secondNumber==seLength and prevN==upjLength))): ## IJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][I]+=1; c_se[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif jS==se[chr][group][c][3] and jE==se[chr][group][c][4]: ## SJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][S]+=1; c_se[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of SE ### ## MXE ### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group, examine if the given junction is part of it mxeLen1=mxe[chr][group][c][1]-mxe[chr][group][c][0]; mxeLen2=mxe[chr][group][c][3]-mxe[chr][group][c][2]; upj1Len=mxe[chr][group][c][0]-mxe[chr][group][c][5]; dnj1Len=mxe[chr][group][c][6]-mxe[chr][group][c][1]; upj2Len=mxe[chr][group][c][2]-mxe[chr][group][c][5]; dnj2Len=mxe[chr][group][c][6]-mxe[chr][group][c][3]; if (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][0] and ((lastNumber<=mxeLen1 and nextN==-1) or (lastNumber==mxeLen1 and nextN==dnj1Len))) or (jS==mxe[chr][group][c][1] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen1 and prevN==-1) or (secondNumber==mxeLen1 and prevN==upj1Len))): ## IJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][I]+=1; c_mxe[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][2] and ((lastNumber<=mxeLen2 and nextN==-1) or (lastNumber==mxeLen2 and nextN==dnj2Len))) or (jS==mxe[chr][group][c][3] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen2 and prevN==-1) or (secondNumber==mxeLen2 and prevN==upj2Len))): ## SJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][S]+=1; c_mxe[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of MXE ### ## A5SS ### if chr in a5ss: ## this chromosome has a5ss event(s) if group in a5ss[chr]: ## this group has a5ss event(s) for c in a5ss[chr][group]: ## for each a5ss event in this group, examine if the given junction is part of it if a5ss[chr][group][c][4]>a5ss[chr][group][c][1]: ## positive strand if ( jS==a5ss[chr][group][c][1] and jE==a5ss[chr][group][c][4] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][3] and jE==a5ss[chr][group][c][4] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart<=(a5ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd<=a5ss[chr][group][c][1] and cEnd>=(a5ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## negative strand if ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][0] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][2] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart>a5ss[chr][group][c][0] and cStart<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A5SS ### ## A3SS ### if chr in a3ss: ## this chromosome has a3ss event(s) if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group, examine if the given junction is part of it if a3ss[chr][group][c][4]>a3ss[chr][group][c][1]: ## negative strand if ( jS==a3ss[chr][group][c][1] and jE==a3ss[chr][group][c][4] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][3] and jE==a3ss[chr][group][c][4] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart<=(a3ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd<=a3ss[chr][group][c][1] and cEnd>=(a3ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## positive strand if ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][0] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][2] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart>a3ss[chr][group][c][0] and cStart<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A3SS ### ## RI ### if chr in ri: ## this chromosome has ri event(s) if group in ri[chr]: ## this group has ri event(s) for c in ri[chr][group]: ## for each ri event in this group, examine if the given junction is part of it if jS==ri[chr][group][c][3] and jE==ri[chr][group][c][4] : ## SJC key=':'.join(["RI",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_ri[c][CT1][S]+=1; c_ri[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite if prevN == -1: if cStart<=(ri[chr][group][c][4]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][4]+(rL-junctionLength/2)): ## multi-exon read supporting target key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite if nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; ## just change cStart and cEnd then do the same process if cStart<=(ri[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][3]+(rL-junctionLength/2)): key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of RI ### #### end of for ec ##### else: ## it is not exonic nor junction read. proceed to the next line continue; sFile.close(); #edgeFile = open(s1.strip()+'.edgeCount', 'w'); #for k in e1: # edgeFile.write(k+'\t'+str(e1[k])+'\n'); #edgeFile.close(); ##### end of processSample_stranded ###### #def getId(ids,key): # for chr in ids: ## this chromosome has se event(s) # for group in ids[chr]: ## this group has skipped exon event(s) # if key in ids[chr][group]: # event_location=ids[chr][group][key]; #[tS,tE,uS,uE,dS,dE,strand] # return [chr,event_location[-1],":".join(map(str,event_location[:-1]))]; def writeInputFile2(h1,f1,id_index,cnt,sup): ## header 1,2,3, file 1,2,3, count dict, supple dict) ## print header first f1.write(h1+'\n'); for k in sorted(sup.keys()): f1.write(str(id_index[k])+'\t'+str(cnt[k][CT1][I])+'\t'+str(cnt[k][CT1][S])+'\t'+str(sup[k][CT1][0])+'\t'+str(sup[k][CT1][1])+'\n'); #f1.write(':'.join(map(str,getId(id_index,k)))+'\t'+str(cnt[k][CT1][I])+'\t'+str(cnt[k][CT1][S])+'\t'+str(sup[k][CT1][0])+'\t'+str(sup[k][CT1][1])+'\n'); ##### end of writeInputFile function ####### def main(): parser = argparse.ArgumentParser(description=''' Given a BAM file and rMATS event files, count the reads supporting the events.''') parser.add_argument('SE', help='skipped event file, generated by rMATS') parser.add_argument('MXE', help='mutually exclusive event file, generated by rMATS') parser.add_argument('A5SS', help='alternative 5 prime event file, generated by rMATS') parser.add_argument('A3SS', help='alternative 3 prime event file, generated by rMATS') parser.add_argument('RI', help='retianed intron event file, generated by rMATS') parser.add_argument('input_file', help='BAM file, previously aligned') parser.add_argument('outDir', help='output directory.') parser.add_argument('-rl', '--read_length', type=int, default=50, help='read length. Default: 50.') parser.add_argument('-jl', '--junction_length', type=int, default=84, help='junction length. Default: 84.') #parser.add_argument('-p', '--processor', type=int, default=1, # help='number of processors to use. Default: 1.') print("initializing variables...") #### global variables ################ #### default configuration values ##### #readLength=50; #junctionLength=84; global SE global MXE global A5SS global A3SS #AFE='AFE'; #ALE='ALE'; global RI global experiment experiment = 'custom'; global base base ='base'; global dataType dataType = 'paired'; ## either single or paired global samDir samDir = '.'; #input_file='.'; #outDir = 'myOutput'; email = '<EMAIL>'; libType='fr-unstranded'; ####################################### #import readLength,junctionLength,outDir,input_file args = parser.parse_args(); #events = parse_events(args.efname, args.column) #sys.stderr.write('Total number of events: {}.\n'.format(len(events))) #sample_info = parse_sample(args.sfname) #sys.stderr.write('Total number of samples: {}.\n'.format(len(sample_info['sample']))) #psi_diff(events, sample_info, args.ofname, args.iteration, args.seed, args.group_size, args.processor) global readLength; readLength = args.read_length; global junctionLength; junctionLength = args.junction_length; global input_file; input_file = args.input_file; global outDir; outDir = args.outDir; SE=args.SE; MXE=args.MXE; A5SS=args.A5SS; A3SS=args.A3SS; RI=args.RI; # print("Input File: "+input_file) print("Output Folder: "+outDir) print("Read Length: "+str(readLength)) print("Junction Length: "+str(junctionLength)) # commands.getstatusoutput('mkdir '+outDir); # ejLength = junctionLength-readLength+1; ## effective junction length global anchorLength; anchorLength = readLength-junctionLength/2; ## anchor length global CT1,CT2,CT3; CT1,CT2,CT3=0,1,2; ### count type 1,2, or 3 #S1,S2=0,1; ## sample 1 or sample 2 global I,S; I,S=0,1; ## inclusion isoform or skipping form # #pPath = outDir+'/junctions.per.sample.pickle'; #junctions = pickle.load(open(pPath)); ## junctions per sample # prefix = experiment; # ### open AS event files.. # seFile = open(SE); ## skipped exon event file mxeFile = open(MXE); ## mxe event file a5ssFile = open(A5SS); ## a5ss event file a3ssFile = open(A3SS); ## a3ss event file riFile = open(RI); ## ri event file # ### open output files here... # JC_seFile = open(outDir+'/JC.'+prefix+'.SE.MATS.input.txt', 'w'); JC_mxeFile = open(outDir+'/JC.'+prefix+'.MXE.MATS.input.txt', 'w'); JC_a5ssFile = open(outDir+'/JC.'+prefix+'.A5SS.MATS.input.txt', 'w'); JC_a3ssFile = open(outDir+'/JC.'+prefix+'.A3SS.MATS.input.txt', 'w'); JC_riFile = open(outDir+'/JC.'+prefix+'.RI.MATS.input.txt', 'w'); global chunk; chunk=1000; ## to speed up the sam file processing ############################## ## BUILD EVENT DICTIONARIES ## ############################## print("Building event dictionaries from annotation...") global se,mxe,a5ss,a3ss,afe,ale,ri se={};mxe={};a5ss={};a3ss={};afe={};ale={};ri={}; ## 7 dictionaries global id_se,id_mxe,id_a5ss,id_a3ss,id_afe,id_ale,id_ri id_se={};id_mxe={};id_a5ss={};id_a3ss={};id_afe={};id_ale={};id_ri={}; global e_se,e_mxe,e_a5ss,e_a3ss,e_afe,e_ale,e_ri e_se={};e_mxe={};e_a5ss={};e_a3ss={};e_afe={};e_ale={};e_ri={}; ## exons dictionaries global c_se,c_mxe,c_a5ss,c_a3ss,c_afe,c_ale,c_ri c_se={};c_mxe={};c_a5ss={};c_a3ss={};c_afe={};c_ale={};c_ri={}; ## count dictionaries global s_se,s_mxe,s_a5ss,s_a3ss,s_afe,s_ale,s_ri s_se={};s_mxe={};s_a5ss={};s_a3ss={};s_afe={};s_ale={};s_ri={}; ## supple dict. effective length of inclusion or skipping form for CT1,CT2,CT3 # #### SE ###### c=0; ## count numSE=0; ## number of SE numSEDup=0; ## duplicate SE id line=seFile.readline(); ## skipping header for line in seFile: ## process skipped exon events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; tS = int(ele[5]); tE = int(ele[6]); ## target exon coord uS = int(ele[7]); uE = int(ele[8]); ## upstream exon coord dS = int(ele[9]); dE = int(ele[10]); ## downstream exon coord tLen=tE-tS; ## target exon length uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length id_se[id]=":".join(map(str,[chr,strand,tS,tE,uS,uE,dS,dE])); e_se[id] = [tS,tE,uS,uE,dS,dE]; c_se[id] = getInitialCounts(); I_0= min(tLen,readLength)+readLength-4anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2anchorLength+1; ## effective skipping form length for JC I_1= readLength-2anchorLength+tLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_se[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(uS/chunk, uE/chunk+1) + range(tS/chunk, tE/chunk+1) + range(dS/chunk, dE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in se: ## already processed this chromosome for i in group: ## for each possible group if i in se[chr]: ## this group is already there if id in se[chr][i]: ## not likely but this group already has the id numSEDup+=1; else: ## new SE ID se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; else: ## new group to this chromosome se[chr][i]={}; se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; else: ## first time accesing this chromosome se[chr]={}; for i in group: ## for each possible group se[chr][i]={}; se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; # #### MXE #### c=0; ## count numMXE=0; ## number of MXE numMXEDup=0; ## duplicate MXE id line=mxeFile.readline(); ## mxe header for line in mxeFile: ## process mxe events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; ## '+' or '-' tS = int(ele[5]); tE = int(ele[6]); ## target exon coord sS = int(ele[7]); sE = int(ele[8]); ## second exon coord if strand=='-': ## negative strand, switch target exon and second exon tS = int(ele[7]); tE = int(ele[8]); ## target exon coord sS = int(ele[5]); sE = int(ele[6]); ## second exon coord uS = int(ele[9]); uE = int(ele[10]); ## upstream exon coord (samller coord) dS = int(ele[11]); dE = int(ele[12]); ## downstream exon coord (bigger coord) tLen=tE-tS; ## target exon length sLen=sE-sS; ## second exon length uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length id_mxe[id]=":".join(map(str,[chr,strand,tS,tE,sS,sE,uS,uE,dS,dE])); e_mxe[id] = [tS,tE,sS,sE,uS,uE,dS,dE]; ## target, second, up, down (This is different from the input file) c_mxe[id] = getInitialCounts(); I_0= min(tLen,readLength)+readLength-4anchorLength+2; ## effective inclusion form length for JC S_0= min(sLen,readLength)+readLength-4anchorLength+2; ## effective skipping form length for JC I_1= readLength-2anchorLength+tLen+1; ## effective inclusion form length for JC+reads on target S_1= readLength-2anchorLength+sLen+1; ## effective inclusion form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_mxe[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(uS/chunk,uE/chunk+1)+range(tS/chunk,tE/chunk+1); group = group + range(sS/chunk,sE/chunk+1)+range(dS/chunk,dE/chunk+1);## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in mxe: ## already processed this chromosome for i in group: ## for each possible group if i in mxe[chr]: ## this group is already there if id in mxe[chr][i]: ## not likely but this group already has the id numMXEDup+=1; else: ## new MXE ID mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE += 1; else: ## new group to this chromosome mxe[chr][i]={}; mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE += 1; else: ## first time accesing this chromosome mxe[chr]={}; for i in group: ## for each possible group mxe[chr][i]={}; mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE+=1; # #### A5SS #### c=0; ## count numA5SS=0; ## number of A5SS numA5SSDup=0; ## duplicate A5SS id line=a5ssFile.readline(); ## skipping header for line in a5ssFile: ## process a5ss events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; lS = int(ele[5]); lE = int(ele[6]); ## long exon coord sS = int(ele[7]); sE = int(ele[8]); ## short exon coord fS = int(ele[9]); fE = int(ele[10]); ## flanking exon coord lLen=min(lE-lS,junctionLength/2); ## long exon length sLen=min(sE-sS,junctionLength/2); ## short exon length fLen=min(fE-fS,junctionLength/2); ## flanking exon length aLen=lE-lS-(sE-sS); ## alternative SS region length id_a5ss[id]=":".join(map(str,[chr,strand,lS,lE,sS,sE,fS,fE])); e_a5ss[id] = [lS,lE,sS,sE,fS,fE]; c_a5ss[id] = getInitialCounts(); I_0= min(aLen,readLength)+readLength-4anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2anchorLength+1; ## effective skipping form length for JC I_1= readLength-2anchorLength+aLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_a5ss[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(lS/chunk, lE/chunk+1) + range(fS/chunk, fE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in a5ss: ## already processed this chromosome for i in group: ## for each possible group if i in a5ss[chr]: ## this group is already there if id in a5ss[chr][i]: ## not likely but this group already has the id numA5SSDup+=1; else: ## new A5SS ID a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; else: ## new group to this chromosome a5ss[chr][i]={}; a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; else: ## first time accesing this chromosome a5ss[chr]={}; for i in group: ## for each possible group a5ss[chr][i]={}; a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; # ### A3SS #### c=0; ## count numA3SS=0; ## number of A3SS numA3SSDup=0; ## duplicate A3SS id line=a3ssFile.readline(); ## skipping header for line in a3ssFile: ## process a3ss events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; lS = int(ele[5]); lE = int(ele[6]); ## long exon coord sS = int(ele[7]); sE = int(ele[8]); ## short exon coord fS = int(ele[9]); fE = int(ele[10]); ## flanking exon coord lLen=min(lE-lS,junctionLength/2); ## long exon length sLen=min(sE-sS,junctionLength/2); ## short exon length fLen=min(fE-fS,junctionLength/2); ## flanking exon length aLen=lE-lS-(sE-sS); ## alternative SS region length id_a3ss[id]=":".join(map(str,[chr,strand,lS,lE,sS,sE,fS,fE])); e_a3ss[id] = [lS,lE,sS,sE,fS,fE]; c_a3ss[id] = getInitialCounts(); I_0= min(aLen,readLength)+readLength-4anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2anchorLength+1; ## effective skipping form length for JC I_1= readLength-2anchorLength+aLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_a3ss[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(lS/chunk, lE/chunk+1) + range(fS/chunk, fE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in a3ss: ## already processed this chromosome for i in group: ## for each possible group if i in a3ss[chr]: ## this group is already there if id in a3ss[chr][i]: ## not likely but this group already has the id numA3SSDup+=1; else: ## new A3SS ID a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; else: ## new group to this chromosome a3ss[chr][i]={}; a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; else: ## first time accesing this chromosome a3ss[chr]={}; for i in group: ## for each possible group a3ss[chr][i]={}; a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; # #### RI #### c=0; ## count numRI=0; ## number of RI numRIDup=0; ## duplicate RI id line=riFile.readline(); ## skipping header for line in riFile: ## process ri events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; rS = int(ele[5]); rE = int(ele[6]); ## ri exon coord (including up- and down-stream exons) uS = int(ele[7]); uE = int(ele[8]); ## upstream exon coord dS = int(ele[9]); dE = int(ele[10]); ## downstream exon coord uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length riLen=rE-rS-(uE-uS)-(dE-dS); ## retained exon length id_ri[id]=":".join(map(str,[chr,strand,rS,rE,uS,uE,dS,dE])); e_ri[id] = [rS,rE,uS,uE,dS,dE]; ## ri event with coord c_ri[id] = getInitialCounts(); I_0= min(riLen,readLength)+readLength-4anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2anchorLength+1; ## effective skipping form length for JC I_1= readLength-2anchorLength+riLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_ri[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(rS/chunk, rE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in ri: ## already processed this chromosome for i in group: ## for each possible group if i in ri[chr]: ## this group is already there if id in ri[chr][i]: ## not likely but this group already has the id numRIDup+=1; else: ## new RI ID ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; else: ## new group to this chromosome ri[chr][i]={}; ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; else: ## first time accesing this chromosome ri[chr]={}; for i in group: ## for each possible group ri[chr][i]={}; ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; print("Counting Reads...") #################################### ## Running the counting functions ## #################################### #if dataType=="skipThisForNow": ## call paired.. #logging.debug("Start processing sample_1: %s" % base_1); #processSample_PE(input_file, 72, 60); if libType=='fr-unstranded': ## unstranded.. processSample(input_file); elif libType=='fr-firststrand': ## first strand.. processSample_stranded(input_file,dataType,'first') elif libType=='fr-secondstrand': ## second strand.. processSample_stranded(input_file,dataType,'second') ### print("Writing Output...") ###################################### ## Writing out the rMATS input file ## ###################################### header = 'ID(chr:strand:SE_s:SE_e:UP_s:UP_e:DN_s:DN_e)\tIC_'+base+'\tSC_'+base+'\tIncFormLen\tSkipFormLen'; # ## SE ## writeInputFile2(header,JC_seFile,id_se,c_se,s_se); ## MXE ## writeInputFile2(header,JC_mxeFile,id_mxe,c_mxe,s_mxe); ## A5SS ##... writeInputFile2(header,JC_a5ssFile,id_a5ss,c_a5ss,s_a5ss); ## A3SS ##... writeInputFile2(header,JC_a3ssFile,id_a3ss,c_a3ss,s_a3ss); ## RI ## writeInputFile2(header,JC_riFile,id_ri,c_ri,s_ri); # print("Done!") #### close all files here ########## seFile.close() mxeFile.close() a5ssFile.close() a3ssFile.close() riFile.close() # JC_seFile.close() JC_mxeFile.close() JC_a5ssFile.close() JC_a3ssFile.close() JC_riFile.close() # sys.exit(0); # if __name__ == '__main__': main()	[ 1, 529, 9507, 29958, 1028, 506, 292, 29918, 6735, 800, 29914, 2798, 14039, 292, 6359, 29879, 29889, 2272, 13, 29937, 29967, 651, 6795, 23430, 515, 364, 29924, 1299, 29903, 376, 5014, 5412, 3514, 19451, 13, 30004, 13, 2277, 29937, 1053, 5181, 9562, 30004, 13, 5215, 337, 29892, 359, 29892, 9675, 29892, 21027, 29892, 2230, 29892, 12673, 29892, 26381, 29892, 1191, 5510, 2104, 13, 5215, 4560, 2272, 29892, 755, 29892, 23945, 280, 29892, 29886, 952, 314, 2104, 13, 3166, 4560, 2272, 1053, 22663, 2104, 13, 30004, 13, 1753, 1051, 8246, 29898, 29916, 1125, 30004, 13, 29871, 364, 1440, 353, 6629, 2104, 13, 29871, 363, 263, 297, 921, 29901, 30004, 13, 1678, 364, 1440, 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util.py	asahi417/VAE	9	74889	import logging import os import numpy as np import tensorflow as tf import sys def create_log(name): """Logging.""" if os.path.exists(name): os.remove(name) logger = logging.getLogger(name) logger.setLevel(logging.DEBUG) # handler for logger file handler1 = logging.FileHandler(name) handler1.setFormatter(logging.Formatter("H1, %(asctime)s %(levelname)8s %(message)s")) # handler for standard output handler2 = logging.StreamHandler() handler2.setFormatter(logging.Formatter("H1, %(asctime)s %(levelname)8s %(message)s")) logger.addHandler(handler1) logger.addHandler(handler2) return logger def mnist_loader(): from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets mnist = read_data_sets('MNIST_data', one_hot=True) n_sample = mnist.train.num_examples return mnist, n_sample def shape_2d(_x, batch_size): _x = _x.reshape(batch_size, 28, 28) return np.expand_dims(_x, 3) def mnist_train(model, epoch, save_path="./", mode="supervised", input_image=True): """ Train model based on mini-batch of input data. :param model: :param epoch: :param save_path: :param mode: conditional, supervised, unsupervised :param input_image: True if use CNN for top of the model :return: """ # load mnist data, n = mnist_loader() n_iter = int(n / model.batch_size) # logger if not os.path.exists(save_path): os.mkdir(save_path) logger = create_log(save_path+"log") logger.info("train: data size(%i), batch num(%i), batch size(%i)" % (n, n_iter, model.batch_size)) result = [] # Initializing the tensor flow variables model.sess.run(tf.global_variables_initializer()) for _e in range(epoch): _result = [] for _b in range(n_iter): # train _x, _y = data.train.next_batch(model.batch_size) _x = shape_2d(_x, model.batch_size) if input_image else _x if mode in ["conditional", "unsupervised"]: # conditional unsupervised model feed_val = [model.summary, model.loss, model.re_loss, model.latent_loss, model.train] feed_dict = {model.x: _x, model.y: _y} if mode == "conditional" else {model.x: _x} summary, loss, re_loss, latent_loss, _ = model.sess.run(feed_val, feed_dict=feed_dict) __result = [loss, re_loss, latent_loss] elif mode == "supervised": # supervised model feed_val = [model.summary, model.loss, model.accuracy, model.train] feed_dict = {model.x: _x, model.y: _y, model.is_training: True} summary, loss, acc, _ = model.sess.run(feed_val, feed_dict=feed_dict) __result = [loss, acc] else: sys.exit("unknown mode !") _result.append(__result) model.writer.add_summary(summary, int(_b + _e * model.batch_size)) # validation if mode == "supervised": # supervised model _x = shape_2d(data.test.images, data.test.num_examples) if input_image else data.test.image _y = data.test.labels feed_dict = {model.x: _x, model.y: _y, model.is_training: False} loss, acc = model.sess.run([model.loss, model.accuracy], feed_dict=feed_dict) _result = np.append(np.mean(_result, 0), [loss, acc]) logger.info("epoch %i: acc %0.3f, loss %0.3f, train acc %0.3f, train loss 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data/pandas.py	sean-liang/crypto-quant-toolkit	0	1600481	<gh_stars>0 def with_dataframe(df, method, kwargs): """ 包装pandas的dataframe方法为pipeline形式 """ func = getattr(df, method) new_df = func(kwargs) return df if new_df is None or ('inplace' in kwargs and kwargs['inplace']) else new_df	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29900, 13, 1753, 411, 29918, 1272, 2557, 29898, 2176, 29892, 1158, 29892, 3579, 19290, 1125, 13, 1678, 9995, 13, 268, 31473, 31905, 15112, 30210, 1272, 2557, 30525, 30545, 30573, 13096, 5570, 31305, 30607, 13, 1678, 9995, 13, 1678, 3653, 353, 679, 5552, 29898, 2176, 29892, 1158, 29897, 13, 1678, 716, 29918, 2176, 353, 3653, 29898, 1068, 19290, 29897, 13, 1678, 736, 4489, 565, 716, 29918, 2176, 338, 6213, 470, 6702, 262, 6689, 29915, 297, 9049, 5085, 322, 9049, 5085, 1839, 262, 6689, 11287, 1683, 716, 29918, 2176, 13, 2 ]
lib/googlecloudsdk/command_lib/compute/os_config/declarative.py	google-cloud-sdk-unofficial/google-cloud-sdk	2	187558	<filename>lib/googlecloudsdk/command_lib/compute/os_config/declarative.py # -- coding: utf-8 -- # # Copyright 2021 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Hooks for declarative commands.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals def SetDefaultPageSizeRequestHook(default_page_size): """Create a modify_request_hook that applies default_page_size to args. Args: default_page_size: The page size to use when not specified by the user. Returns: A modify_request_hook that updates `args.page_size` when not set by user. """ def Hook(unused_ref, args, request): if not args.page_size: args.page_size = int(default_page_size) return request return Hook	[ 1, 529, 9507, 29958, 1982, 29914, 3608, 9274, 15348, 29914, 6519, 29918, 1982, 29914, 26017, 29914, 359, 29918, 2917, 29914, 311, 16544, 1230, 29889, 2272, 13, 29937, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 396, 13, 29937, 14187, 1266, 29871, 29906, 29900, 29906, 29896, 5087, 365, 12182, 29889, 2178, 26863, 2538, 9841, 29889, 13, 29937, 13, 29937, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 13, 29937, 366, 1122, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 13, 29937, 887, 1122, 4017, 263, 3509, 310, 278, 19245, 472, 13, 29937, 13, 29937, 1678, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 13, 29937, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 13, 29937, 399, 1806, 8187, 2692, 399, 1718, 29934, 13566, 29059, 6323, 8707, 29928, 22122, 29903, 8079, 13764, 29979, 476, 22255, 29892, 2845, 4653, 470, 2411, 2957, 29889, 13, 29937, 2823, 278, 19245, 363, 278, 2702, 4086, 14765, 1076, 11239, 322, 13, 29937, 27028, 1090, 278, 19245, 29889, 13, 15945, 29908, 29950, 2550, 29879, 363, 7669, 1230, 8260, 1213, 15945, 13, 13, 3166, 4770, 29888, 9130, 1649, 1053, 8380, 29918, 5215, 13, 3166, 4770, 29888, 9130, 1649, 1053, 8542, 13, 3166, 4770, 29888, 9130, 1649, 1053, 29104, 29918, 20889, 1338, 13, 13, 13, 1753, 3789, 4592, 5074, 3505, 3089, 29950, 2550, 29898, 4381, 29918, 3488, 29918, 2311, 1125, 13, 29871, 9995, 4391, 263, 6623, 29918, 3827, 29918, 20849, 393, 16058, 2322, 29918, 3488, 29918, 2311, 304, 6389, 29889, 13, 13, 29871, 826, 3174, 29901, 13, 1678, 2322, 29918, 3488, 29918, 2311, 29901, 450, 1813, 2159, 304, 671, 746, 451, 6790, 491, 278, 1404, 29889, 13, 13, 29871, 16969, 29901, 13, 1678, 319, 6623, 29918, 3827, 29918, 20849, 393, 11217, 421, 5085, 29889, 3488, 29918, 2311, 29952, 746, 451, 731, 491, 1404, 29889, 13, 29871, 9995, 13, 29871, 822, 29612, 29898, 348, 3880, 29918, 999, 29892, 6389, 29892, 2009, 1125, 13, 1678, 565, 451, 6389, 29889, 3488, 29918, 2311, 29901, 13, 418, 6389, 29889, 3488, 29918, 2311, 353, 938, 29898, 4381, 29918, 3488, 29918, 2311, 29897, 13, 1678, 736, 2009, 13, 29871, 736, 29612, 13, 2 ]
augment.py	MohamedHeshamMustafa/Brain-Tumor-Automatic-Detection-and-Segmentation-	0	121498	from __future__ import absolute_import, print_function import numpy as np import sys import tensorflow as tf from util.data_loader import * from util.data_aug import * from util.parse_config import parse_config def test(config_file): # 1, load configure file config = parse_config(config_file) config_data = config['data'] # 2, Augmentation dataaug = DataAug(config_data) dataaug.aug_data() if __name__ == '__main__': if(len(sys.argv) != 2): print('Number of arguments should be 2. e.g.') print(' python test.py config17/test_all_class.txt') exit() config_file = str(sys.argv[1]) assert(os.path.isfile(config_file)) test(config_file)	[ 1, 515, 4770, 29888, 9130, 1649, 1053, 8380, 29918, 5215, 29892, 1596, 29918, 2220, 13, 5215, 12655, 408, 7442, 13, 5215, 10876, 13, 5215, 26110, 408, 15886, 13, 3166, 3667, 29889, 1272, 29918, 12657, 1053, 334, 13, 3166, 3667, 29889, 1272, 29918, 2987, 1053, 334, 13, 3166, 3667, 29889, 5510, 29918, 2917, 1053, 6088, 29918, 2917, 13, 13, 1753, 1243, 29898, 2917, 29918, 1445, 1125, 13, 12, 29937, 29871, 29896, 29892, 2254, 10822, 934, 13, 12, 2917, 353, 6088, 29918, 2917, 29898, 2917, 29918, 1445, 29897, 13, 12, 2917, 29918, 1272, 353, 2295, 1839, 1272, 2033, 13, 13, 12, 29937, 29871, 29906, 29892, 22333, 358, 362, 29871, 13, 12, 1272, 2987, 353, 3630, 29909, 688, 29898, 2917, 29918, 1272, 29897, 13, 12, 1272, 2987, 29889, 2987, 29918, 1272, 580, 13, 1678, 13, 361, 4770, 978, 1649, 1275, 525, 1649, 3396, 1649, 2396, 13, 565, 29898, 2435, 29898, 9675, 29889, 19218, 29897, 2804, 29871, 29906, 1125, 13, 268, 1596, 877, 4557, 310, 6273, 881, 367, 29871, 29906, 29889, 321, 29889, 29887, 29889, 1495, 13, 268, 1596, 877, 1678, 3017, 1243, 29889, 2272, 2295, 29896, 29955, 29914, 1688, 29918, 497, 29918, 1990, 29889, 3945, 1495, 13, 268, 6876, 580, 13, 2295, 29918, 1445, 353, 851, 29898, 9675, 29889, 19218, 29961, 29896, 2314, 13, 4974, 29898, 359, 29889, 2084, 29889, 275, 1445, 29898, 2917, 29918, 1445, 876, 13, 1243, 29898, 2917, 29918, 1445, 29897, 2 ]
cio/plugins/txt.py	beshrkayali/content-io	6	4298	<reponame>beshrkayali/content-io # coding=utf-8 from __future__ import unicode_literals from .base import BasePlugin class TextPlugin(BasePlugin): ext = 'txt'	[ 1, 529, 276, 1112, 420, 29958, 5707, 1092, 29895, 388, 2606, 29914, 3051, 29899, 601, 13, 29937, 14137, 29922, 9420, 29899, 29947, 13, 3166, 4770, 29888, 9130, 1649, 1053, 29104, 29918, 20889, 1338, 13, 13, 3166, 869, 3188, 1053, 7399, 16288, 13, 13, 13, 1990, 3992, 16288, 29898, 5160, 16288, 1125, 13, 13, 1678, 1294, 353, 525, 3945, 29915, 13, 2 ]
HMQ/datasets/auto_augmentation_transform.py	UniSerj/ai-research	46	167742	import random from PIL import ImageOps, ImageEnhance, ImageFilter, Image import torchvision.transforms as transforms PARAMETER_MAX = 10 # What is the max 'level' a transform could be predicted def int_parameter(level, maxval) -> int: """ A function to scale between zero to max val with casting to int :param level: The level of augmentation an integer between 0 to 9 :param maxval: The maximal output value :return: A int value """ return int(level * maxval / PARAMETER_MAX) def float_parameter(level, maxval): """ A function to scale between zero to max val :param level: The level of augmentation an integer between 0 to 9 :param maxval: The maximal output value :return: A int value """ return float(level) * maxval / PARAMETER_MAX class BaseAugmentation(object): def __init__(self, p, level): """ Base Augmentation class which performed data augmentation with probability p and severity level :param p: The probability that the augmentation is performed :param level: The severity of data augmentation """ self.p = p self.level = level def __call__(self, img): if random.random() < self.p: img = self._augment(img) return img def _augment(self, img): raise NotImplemented def __repr__(self): return self.__class__.__name__ + '(p={}, level={})'.format(self.p, self.level) class AutoContrast(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform auto contrast. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.autocontrast(img) class Equalize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Equalization. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.equalize(img) class Invert(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Invert. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.invert(img) class Blur(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Image Blur. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return img.filter(ImageFilter.BLUR) class Smooth(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Smoothing. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return img.filter(ImageFilter.SMOOTH) class Rotate(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform rotation. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ degrees = int_parameter(self.level, 30) if random.random() > 0.5: degrees = -degrees return img.rotate(degrees) class Posterize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Posterize. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 4) return ImageOps.posterize(img, 4 - level) class ShearX(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform ShearX. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = float_parameter(self.level, 0.3) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, level, 0, 0, 1, 0)) class ShearY(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform ShearY. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = float_parameter(self.level, 0.3) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, 0, level, 1, 0)) class TranslateX(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform TranslateX. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 10) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, level, 0, 1, 0)) class TranslateY(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform TranslateY. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 10) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, 0, 0, 1, level)) class Solarize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Solarize. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 256) return ImageOps.solarize(img, 256 - level) class Color(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Color. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Color(img).enhance(v) class Contrast(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Contrast change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Contrast(img).enhance(v) class Brightness(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Brightness change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Brightness(img).enhance(v) class Sharpness(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Sharpness change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Sharpness(img).enhance(v) CIFAR10_AUGMENT_POLICY = transforms.RandomChoice([transforms.Compose([Invert(0.1, 7), Contrast(0.2, 6)]), transforms.Compose([Rotate(0.7, 2), TranslateX(0.3, 9)]), transforms.Compose([Sharpness(0.8, 1), Sharpness(0.9, 3)]), transforms.Compose([ShearY(0.5, 8), TranslateY(0.7, 9)]), transforms.Compose([AutoContrast(0.5, 8), Equalize(0.9, 2)]), transforms.Compose([ShearY(0.2, 7), Posterize(0.3, 7)]), transforms.Compose([Color(0.4, 3), Brightness(0.6, 7)]), transforms.Compose([Sharpness(0.3, 9), Brightness(0.7, 9)]), transforms.Compose([Equalize(0.6, 5), Equalize(0.5, 1)]), transforms.Compose([Contrast(0.6, 7), Sharpness(0.6, 5)]), transforms.Compose([Color(0.7, 7), TranslateY(0.5, 8)]), transforms.Compose([Equalize(0.3, 7), AutoContrast(0.4, 8)]), transforms.Compose([TranslateY(0.4, 3), Sharpness(0.2, 6)]), transforms.Compose([Brightness(0.9, 6), Color(0.2, 8)]), transforms.Compose([Solarize(0.5, 2), Invert(0.0, 3)]), transforms.Compose([Equalize(0.2, 0), AutoContrast(0.6, 0)]), transforms.Compose([Equalize(0.2, 8), Equalize(0.6, 4)]), transforms.Compose([Color(0.9, 9), Equalize(0.6, 6)]), transforms.Compose([AutoContrast(0.8, 4), Solarize(0.2, 8)]), transforms.Compose([Brightness(0.1, 3), Color(0.7, 0)]), transforms.Compose([Solarize(0.4, 5), AutoContrast(0.9, 3)]), transforms.Compose([TranslateY(0.9, 9), TranslateY(0.7, 9)]), transforms.Compose([AutoContrast(0.9, 2), Solarize(0.8, 3)]), transforms.Compose([Equalize(0.8, 8), Invert(0.1, 3)]), transforms.Compose([TranslateY(0.7, 9), AutoContrast(0.9, 1)])]) IMAGENET_AUGMENT_POLICY = transforms.RandomChoice([transforms.Compose([Posterize(0.4, 8), Rotate(0.6, 9)]), transforms.Compose([Solarize(0.6, 5), AutoContrast(0.6, 5)]), transforms.Compose([Equalize(0.8, 18), Equalize(0.6, 3)]), transforms.Compose([Posterize(0.6, 7), Posterize(0.6, 6)]), transforms.Compose([Equalize(0.4, 7), Solarize(0.2, 4)]), transforms.Compose([Equalize(0.4, 4), Rotate(0.8, 8)]), transforms.Compose([Solarize(0.6, 3), Equalize(0.6, 7)]), transforms.Compose([Posterize(0.8, 5), Equalize(1.0, 2)]), transforms.Compose([Rotate(0.2, 3), Solarize(0.6, 8)]), transforms.Compose([Equalize(0.6, 8), Posterize(0.4, 6)]), transforms.Compose([Rotate(0.8, 8), Color(0.4, 0)]), transforms.Compose([Rotate(0.4, 9), Equalize(0.6, 2)]), transforms.Compose([Equalize(0.0, 7), Equalize(0.8, 8)]), transforms.Compose([Invert(0.6, 4), Equalize(1.0, 8)]), transforms.Compose([Color(0.6, 4), Color(1.0, 8)]), transforms.Compose([Rotate(0.8, 8), Color(1.0, 2)]), transforms.Compose([Color(0.8, 8), Solarize(0.8, 7)]), transforms.Compose([Sharpness(0.4, 7), Invert(0.6, 8)]), transforms.Compose([ShearX(0.6, 5), Equalize(1.0, 9)]), transforms.Compose([Color(0.4, 0), Equalize(0.6, 3)]), transforms.Compose([Equalize(0.4, 7), Solarize(0.2, 4)]), transforms.Compose([Solarize(0.6, 5), AutoContrast(0.6, 5)]), transforms.Compose([Invert(0.6, 4), Equalize(1.0, 8)]), transforms.Compose([Color(0.6, 4), Contrast(1.0, 8)]), transforms.Compose([Equalize(0.8, 8), 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backend/course/views.py	thangplum/nova-cs322	0	116790	<filename>backend/course/views.py from rest_framework import viewsets, status from rest_framework.response import Response from django.shortcuts import get_object_or_404 from .serializers import courseSerializer, courseSerializer2 from .models import course class CourseViewSet(viewsets.ViewSet): def list(self, request): courses = course.objects.all() serializer = courseSerializer2(courses, many=True) return Response(serializer.data) def retrieve(self, request, pk=None): queryset = course.objects.all() form = get_object_or_404(queryset, pk=pk) serializer = courseSerializer(form) if ((request.user.is_instructor and form.user == request.user) or request.user.is_researcher) : return Response(serializer.data) return Response(status=status.HTTP_403_FORBIDDEN) def create(self, request): serializer = courseSerializer(data=request.data) if serializer.is_valid() and request.user.is_instructor: serializer.validated_data["user"] = request.user serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(status=status.HTTP_403_FORBIDDEN) def destroy(self, request, pk=None): instance = course.objects.get(pk=pk) if request.user.is_instructor and instance.user == request.user: instance.delete() return Response(status=status.HTTP_200_OK) return Response(status=status.HTTP_401_UNAUTHORIZED) def partial_update(self, request, pk=None): queryset = course.objects.all() form = get_object_or_404(queryset, pk=pk) serializer = courseSerializer(form, data=request.data, partial=True) if serializer.is_valid() and ((request.user.is_instructor and form.user == request.user) or request.user.is_researcher) : serializer.validated_data["user"] = request.user serializer.save() return Response(serializer.data, status=status.HTTP_200_OK) return Response(status=status.HTTP_401_UNAUTHORIZED)	[ 1, 529, 9507, 29958, 27852, 29914, 15775, 29914, 7406, 29889, 2272, 13, 3166, 1791, 29918, 4468, 1053, 1776, 7224, 29892, 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wxPython/wxGlade-0.9.1/tests/testsupport_new.py	DarkShadow4/python	0	44240	""" @copyright: 2012-2016 <NAME> (as file __init__.py) @copyright: 2016-2018 <NAME> @license: MIT (see LICENSE.txt) - THIS PROGRAM COMES WITH NO WARRANTY """ import os, sys sys.path.insert(1, os.path.dirname(sys.path[0])) import errno, fnmatch, glob, shutil, re import unittest, difflib, logging, imp import gettext t = gettext.translation(domain="wxglade", localedir="locale", fallback=True) t.install("wxglade") import common common.init_paths(None) import config config.testing = True import wxglade, codegen, compat, log if compat.PYTHON2: from StringIO import StringIO else: from io import StringIO class WXGladeBaseTest(unittest.TestCase): "Provide basic functions for all tests" longMessage = True caseDirectory = 'casefiles' # Directory with input files and (expected) result files outDirectory = 'generated' # Directory with generated result files # Language specific constants for file names: language, file prefix, file extensions language_constants = [("python","Py", ".py", ".py"),("perl","Pl", ".pl", ".pm"), ("C++","CPP", ".cpp", ".cpp"),("lisp","Lisp", ".lisp",".lisp"), ("XRC","xrc", ".xrc",".xrc")] @classmethod def setUpClass(cls): "Initialise parts of wxGlade before individual tests starts" # set icon path back to the default default #config.icons_path = 'icons' # initialise wxGlade preferences and set some useful values common.init_preferences() config.preferences.autosave = False config.preferences.write_timestamp = False config.preferences.show_progress = False config.version = '"faked test version"' # make e.g. the preview raise Exceptions config.testing = True # Determinate case and output directory cls.caseDirectory = os.path.join( os.path.dirname(__file__), cls.caseDirectory ) cls.outDirectory = os.path.join( os.path.dirname(__file__), cls.outDirectory ) if not os.path.exists(cls.outDirectory): os.mkdir(cls.outDirectory) # disable bug dialogs sys._called_from_test = True @classmethod def tearDownClass(cls): "Cleanup after all individual tests are done" # de-register own logging log.deinit() def setUp(self): "Initialise" codegen.BaseLangCodeWriter._show_warnings = False def tearDown(self): "Cleanup" pass def _read_file_lines(self, filename): "read a file, split into lines and drop 'generated by ...'" with open(filename, "rb") as f: ret = f.read() ret = ret.split( b"\r\n" if b"\r\n" in ret else b"\n" ) # drop empty lines and 'generated by...' while ret and not ret[-1]: del ret[-1] for i, line in enumerate(ret[:10]): if b'generated by wxGlade' in line: del ret[i] break return ret def _compare_files(self, expected_filename, generated_filename, check_mtime=False): self.assertTrue( os.path.isfile(generated_filename), "File %s was not generated"%generated_filename ) if check_mtime: self.assertGreater( os.stat(generated_filename).st_mtime, os.stat(expected_filename).st_mtime, "File was not overwritten" ) # open files, split into lines and convert to str/unicode expected = self._read_file_lines(expected_filename) generated = self._read_file_lines(generated_filename) if expected == generated: return False expected = [s.decode('ascii', 'replace') for s in expected] generated = [s.decode('ascii', 'replace') for s in generated] if wx.Platform == '__WXGTK__': # on gtk, the frames get resized after creation if len(expected)==len(generated): expected_ = [l for l in expected if not l.strip().startswith("<size>") and not "SetSize" in l] generated_ = [l for l in generated if not l.strip().startswith("<size>") and not "SetSize" in l] if expected_ == generated_: return False diff = difflib.unified_diff(expected, generated, fromfile=expected_filename, tofile=generated_filename, lineterm='') diff = list(diff) print( '\n'.join(diff[:40]) ) if len(diff)>40: print("...") #if compat.PYTHON3: self.assertFalse( diff, "Generated file and expected result differs:\n%s" % "\n".join(diff) ) return True def _get_inputfile_path(self, filename): "return the absolute path of a .wxg input file" basename, extension = os.path.splitext(filename) fn = os.path.join(self.caseDirectory, filename) if os.path.exists(fn): return fn return None def _get_casefile_path(self, filename): "return the absolute path of an input file or directory; for .py files, this might include _Phoenix/_Classic" basename, extension = os.path.splitext(filename) if extension.lower() == ".py": # search for version specific files if compat.IS_CLASSIC: fn = "%s_Classic%s"%(basename, extension) elif compat.IS_PHOENIX: fn = "%s_Phoenix%s"%(basename, extension) fn = os.path.join(self.caseDirectory, fn) if os.path.exists(fn): return fn # this could be a directory as well if extension.lower() == ".wxg": # search for "_Saved" version fn = "%s_Saved%s"%(basename, extension) fn = os.path.join(self.caseDirectory, fn) if os.path.exists(fn): return fn # this could be a directory as well fn = os.path.join(self.caseDirectory, filename) if os.path.exists(fn): return fn return None def _get_outputfile_path(self, filename): """return the name for an output file filename can be - a full path, where only the part relative to caseDirectory will be used - an absolute path, where only the leafname will be used - a relative path""" commonpath = os.path.commonprefix( (self.caseDirectory, filename) ) if commonpath==self.caseDirectory: leaf = filename[len(commonpath)+1:] elif os.path.isabs(filename): leaf = os.path.basename(filename) else: leaf = filename return os.path.join(self.outDirectory, leaf) class WXGladeCLITest(WXGladeBaseTest): @classmethod def setUpClass(cls): logging.disable(logging.WARNING) wxglade.init_stage1() wxglade.init_localization() wxglade.init_stage2(False) import xrc2wxg import wx import config, common, compat, main class WXGladeGUITest(WXGladeBaseTest): # as Python created an own instance for each test, we use class variables for persistent storing 'app' and 'frame': app = None # Reference to a wx.App object. The object is persistent after the creation in setUp(). frame = None # Reference to main.wxGladeFrame. The object is persistent after the creation in setUp(). nolog = None # nolog: wxWidgets Null logger to suppress error messages orig_stdout = None # original fd for stdout def mockMessageBox(self, message, caption, args, *kwargs): "Mock object for wx.MessageBox" self._messageBox = [message, caption] def _assert_message(self, substring, caption ): self.assertTrue( self._messageBox, "No %s message generated"%caption ) generated_message, generated_caption = self._messageBox self.assertTrue( generated_caption==caption, "Expected %s message, got %s"%(caption, generated_caption) ) fmt='%s message does not match: Expected message containing "%s" \ngot wxMessageBox(message="%s", caption="%s")' msg = fmt%(caption, substring, self._messageBox[0], self._messageBox[1] ) self.assertTrue( substring in generated_message, msg ) self._messageBox = None def _assert_error_message(self, substring ): self._assert_message(substring, u"Error") def _assert_warning_message(self, substring ): self._assert_message(substring, u"Warning") def _assert_info_message(self, substring ): self._assert_message(substring, u"Information") @classmethod def setUpClass(cls): WXGladeBaseTest.setUpClass() xrc2wxg._write_timestamp = False # create an simply application cls.app = wx.App() cls.locale = wx.Locale(wx.LANGUAGE_DEFAULT) compat.wx_ArtProviderPush(main.wxGladeArtProvider()) cls.frame = main.wxGladeFrame() # suppress wx error messages cls.nolog = wx.LogNull() #cls.app.SetAssertMode(0) # avoid triggering of wx assertions; sometimes needed for debugging # hide all windows #cls.frame.Hide() #cls.frame.hide_all() @classmethod def tearDownClass(cls): cls.nolog = None def setUp(self): # redirect stdout self.orig_stdout = sys.stdout sys.stdout = StringIO() # initialise base class WXGladeBaseTest.setUp(self) # inject mock object for wxMessageBox wx.MessageBox = self.mockMessageBox self._messageBox = [] # show dialog "Code generation completed successfully" config.preferences.show_completion = True def tearDown(self): # restore original stdout if self.orig_stdout: sys.stdout = self.orig_stdout # initialise base class WXGladeBaseTest.tearDown(self) def _process_wx_events(self): "Process wx events, because we don't start the main loop" for i in range(3): wx.SafeYield() self.app.ProcessPendingEvents() def load_and_generate(self, basename, excluded=None, included=None, test_GUI=True, preview=True): "Load a wxGlade document 'basename' and generate code for all languages except the ones in list 'excluded'" if included is None: languages = set( [l[0] for l in self.language_constants] + ["wxg"] ) else: languages = set(included) if excluded is not None: languages -= set(excluded) # open file infilename = self._get_inputfile_path('%s.wxg' % basename) common.main._open_app(infilename, use_progress_dialog=False, add_to_history=False) # some shortcuts tree = common.app_tree app = tree.app if test_GUI or preview: # expand tree and show edit window first_window_node = app.node.children[0] first_window = first_window_node.widget first_window_item = first_window_node.item if test_GUI: if first_window_item.IsOk(): tree.expand() self._process_wx_events() tree.SelectItem(first_window_item) self._process_wx_events() tree.show_toplevel(first_window_node) self._process_wx_events() if preview: first_window.properties["preview"]() self._process_wx_events() if compat.PYTHON2: # the languages that failed due to differences to expected files diff_fails = [] else: # with Python 3, we use subTests subtest = 0 if "wxg" in languages: # save file again and check generated_filename = self._get_outputfile_path(infilename) compare_filename = self._get_casefile_path(infilename) # some properties may have changed on loading common.main._save_app(generated_filename) if compat.PYTHON2: if self._compare_files(compare_filename, generated_filename): diff_fails.append("wxg") else: with self.subTest(subtest): self._compare_files(compare_filename, generated_filename) subtest += 1 # try to generate code with empty output path -> will fail app.properties["output_path"].set("") app.generate_code() # first test should fail because no output file is given self._assert_error_message( u'You must specify an output file' ) # now test full code generation for language, dummy, ext, dummy in self.language_constants: if not language in languages: continue if language=="C++" and app.multiple_files: app_basename = os.path.splitext(config.default_cpp_app_name)[0] app_basename = "%s_%s"%(first_window.klass.split("_")[0], app_basename) app.app_filename = app_basename expected_filename = self._get_casefile_path( "%s.%s"%(app_basename, app.source_extension) ) # first_window.klass # 'Bug179_Frame' else: expected_filename = self._get_casefile_path( '%s%s' % (basename, ext) ) if not expected_filename: continue generated_filename = self._get_outputfile_path(expected_filename) # check for language first self.assertTrue( language in common.code_writers, "No codewriter loaded for %s" % language ) # set absolute "Output path", language and generate code if language=="C++" and app.multiple_files: app.properties["output_path"].set( os.path.dirname(generated_filename) ) else: app.properties["output_path"].set(generated_filename) app.properties["language"].set(language) self._process_wx_events() app.generate_code() self._assert_info_message(u'Code generation completed successfully') compare_files = [(expected_filename, generated_filename)] if language == 'C++': if not app.multiple_files: # compare header file as well expected_filename_h = '%s.%s' % ( os.path.splitext(expected_filename )[0], app.header_extension ) generated_filename_h = '%s.%s' % ( os.path.splitext(generated_filename)[0], app.header_extension ) compare_files.append( (expected_filename, generated_filename) ) compare_files.append( (expected_filename_h, generated_filename_h) ) else: for toplevel in app.node.children: classname = toplevel.widget.klass # class C++ file expected_filename = self._get_casefile_path( "%s.%s"%(classname, app.source_extension) ) if expected_filename: compare_files.append( (expected_filename, self._get_outputfile_path(expected_filename) ) ) # class header file expected_filename = self._get_casefile_path( "%s.%s"%(classname, app.header_extension) ) if expected_filename: compare_files.append( (expected_filename, self._get_outputfile_path(expected_filename) ) ) for expected_filename, generated_filename in compare_files: if compat.PYTHON2: # no subtests if self._compare_files(expected_filename, generated_filename): diff_fails.append(language) else: with self.subTest(subtest): self._compare_files(expected_filename, generated_filename) subtest += 1 if compat.PYTHON2: self.assertFalse(diff_fails, "Expected and generated files do not match for %s"%",".join(diff_fails)) def _copy_and_modify(self, source, target, original=None, replacement=None): if original is None: shutil.copy2( source, target ) return with open(source,"rb") as infile: content = 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src/tools/rut5_finetuning.py	JetBrains-Research/relevant-tasks-search	1	168760	<filename>src/tools/rut5_finetuning.py<gh_stars>1-10 import os from argparse import ArgumentParser import numpy as np import pandas as pd from transformers import ( AutoTokenizer, AutoModelForSeq2SeqLM, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer, ) from datasets import DatasetDict, load_metric import nltk def read_data(input_path: str, load_courses=False): """ Used for reading data from input path and returning pd.DataFrames :param input_path: path to dir with train/test/val .csv files :param load_courses: if True, loading data about courses and sections too :return: """ if not isinstance(input_path, str): raise Exception(f"You passed {type(input_path)} instead of str type") if not os.path.exists(input_path): raise FileNotFoundError(f"{input_path} doesn't exist") data_train = pd.read_csv(os.path.join(input_path, "train.csv")) data_val = pd.read_csv(os.path.join(input_path, "val.csv")) data_test = pd.read_csv(os.path.join(input_path, "test.csv")) data_train = data_train.dropna().reset_index(drop=True) data_val = data_val.dropna().reset_index(drop=True) data_test = data_test.dropna().reset_index(drop=True) if load_courses: data_courses = pd.read_csv(os.path.join(input_path, "popular_courses.csv")) data_sections = pd.read_csv(os.path.join(input_path, "popular_courses_sections.csv")) return data_train, data_val, data_test, data_courses, data_sections else: return data_train, data_val, data_test def create_dataset(input_path: str, output_path: str): """ Used for dataset's creation. You should provide input path with train/test/val .csv files and sections & courses data :param input_path: path to load train/test/val .csv files and sections & courses data :param output_path: path to save datasets :return: """ if not os.path.isdir(output_path): os.mkdir(output_path) data_train, data_val, data_test, data_courses, data_sections = read_data(input_path, load_courses=True) dataset_train = pd.DataFrame({"text": data_train.preprocessed_text, "id": data_train.id}) dataset_test = pd.DataFrame({"text": data_test.preprocessed_text, "id": data_test.id}) dataset_val = pd.DataFrame({"text": data_val.preprocessed_text, "id": data_val.id}) course2title = {} for index in data_courses.index: course2title[data_courses.at[index, "id"]] = data_courses.at[index, "title"] section2title = {} for index in data_sections.index: section2title[data_sections.at[index, "id"]] = data_sections.at[index, "title"] # Adding key word "summarize" which T5 is needed dataset_train.text = "summarize: " + dataset_train.text + " </s>" dataset_test.text = "summarize: " + dataset_test.text + " </s>" dataset_val.text = "summarize: " + dataset_val.text + " </s>" # Adding some king of summary - section_name + delimiter + course_name dataset_train["summary"] = "" dataset_test["summary"] = "" dataset_val["summary"] = "" for index in data_train.index: course_id = data_train.at[index, "course_id"] section_id = data_train.at[index, "section_id"] dataset_train.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] for index in data_test.index: course_id = data_test.at[index, "course_id"] section_id = data_test.at[index, "section_id"] dataset_test.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] for index in data_val.index: course_id = data_val.at[index, "course_id"] section_id = data_val.at[index, "section_id"] dataset_val.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] # Saving datasets to the output dir dataset_train.to_csv(os.path.join(output_path, "dataset_train.csv"), index=False, header=True) dataset_test.to_csv(os.path.join(output_path, "dataset_test.csv"), index=False, header=True) dataset_val.to_csv(os.path.join(output_path, "dataset_val.csv"), index=False, header=True) def preprocess_function(examples, tokenizer, max_length=512): """ This function is used to tokenized text in datasets Adopt by me almost without changes from https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb :param examples: dataset :param tokenizer: tokenizer to use :param max_length: max length of sequence in tokens :return: """ inputs = [doc for doc in examples["text"]] model_inputs = tokenizer(inputs, max_length=max_length, truncation=True, padding="max_length") # Setup the tokenizer for targets with tokenizer.as_target_tokenizer(): labels = tokenizer(examples["summary"], max_length=max_length, truncation=True, padding="max_length") model_inputs["labels"] = labels["input_ids"] return model_inputs def compute_metrics(eval_pred, tokenizer, metric): """ This function is used to compute ROUGE metric. Adopt by me almost without changes from https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb :param eval_pred: :param tokenizer: :param metric: :return: """ predictions, labels = eval_pred decoded_preds = tokenizer.batch_decode(predictions, skip_special_tokens=True) # Replace -100 in the labels as we can't decode them. labels = np.where(labels != -100, labels, tokenizer.pad_token_id) decoded_labels = tokenizer.batch_decode(labels, skip_special_tokens=True) # Rouge expects a newline after each sentence decoded_preds = ["\n".join(nltk.sent_tokenize(pred.strip())) for pred in decoded_preds] decoded_labels = ["\n".join(nltk.sent_tokenize(label.strip())) for label in decoded_labels] result = metric.compute(predictions=decoded_preds, references=decoded_labels, use_stemmer=True) # Extract a few results result = {key: value.mid.fmeasure * 100 for key, value in result.items()} # Add mean generated length prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in predictions] result["gen_len"] = np.mean(prediction_lens) return {k: round(v, 4) for k, v in result.items()} def train( input_path: str, output_path: str, metric_name: str = "rouge", model_checkpoint: str = "cointegrated/rut5-small" ): """ Used for training. You should provide input path with already computed datasets :param input_path: path to directory with datasets :param output_path: where to save trained model :param metric_name: metric to compute while training :param model_checkpoint: checkpoint to start finetuning :return: """ if not os.path.exists(input_path): raise FileNotFoundError(f"{input_path} doesn't exist") if not os.path.isdir(output_path): os.mkdir(output_path) raw_datasets = DatasetDict.from_csv( { "train": os.path.join(input_path, "dataset_train.csv"), "test": os.path.join(input_path, "dataset_test.csv"), "validation": os.path.join(input_path, "dataset_val.csv"), } ) metric = load_metric(metric_name) tokenizer = AutoTokenizer.from_pretrained(model_checkpoint) model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint) tokenized_datasets = raw_datasets.map(lambda x: preprocess_function(x, tokenizer), batched=True) batch_size = 4 args = Seq2SeqTrainingArguments( os.path.join(output_path, "rut5_finetuned"), evaluation_strategy="steps", eval_steps=200, learning_rate=2e-5, per_device_train_batch_size=batch_size, per_device_eval_batch_size=batch_size, weight_decay=1e-5, save_total_limit=1, save_strategy="steps", save_steps=1000, num_train_epochs=2, predict_with_generate=True, logging_steps=200, logging_first_step=True, logging_dir=os.path.join(output_path, "logs"), push_to_hub=False, ) try: nltk.data.find("tokenizers/punkt") except LookupError: nltk.download("punkt") data_collator = DataCollatorForSeq2Seq(tokenizer, model=model) trainer = Seq2SeqTrainer( model, args, train_dataset=tokenized_datasets["train"], eval_dataset=tokenized_datasets["test"], data_collator=data_collator, tokenizer=tokenizer, compute_metrics=lambda x: compute_metrics(x, tokenizer, metric), ) trainer.train() model.save_pretrained(os.path.join(output_path, "rut5_finetuned")) def configure_arg_parser() -> ArgumentParser: arg_parser = ArgumentParser() arg_parser.add_argument("-t", "--task", choices=["create_dataset", 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Two pointers/26. Remove Duplicates from Sorted Array.py	ParisMineur/LeetCode-note	0	40410	class Solution: def removeDuplicates(self, nums: List[int]) -> int: l = len(nums) if l == 1: return 1 index = 1 num = nums[0] for i in range(1, l): if nums[i] == num: continue num = nums[i] nums[index] = nums[i] index += 1 return index	[ 1, 770, 24380, 29901, 13, 1678, 822, 3349, 29928, 786, 15815, 29898, 1311, 29892, 954, 29879, 29901, 2391, 29961, 524, 2314, 1599, 938, 29901, 13, 4706, 301, 353, 7431, 29898, 1949, 29879, 29897, 13, 4706, 565, 301, 1275, 29871, 29896, 29901, 13, 9651, 736, 29871, 29896, 13, 308, 13, 4706, 2380, 353, 29871, 29896, 13, 4706, 954, 353, 954, 29879, 29961, 29900, 29962, 13, 308, 13, 4706, 363, 474, 297, 3464, 29898, 29896, 29892, 301, 1125, 13, 9651, 565, 954, 29879, 29961, 29875, 29962, 1275, 954, 29901, 13, 18884, 6773, 13, 462, 13, 9651, 954, 353, 954, 29879, 29961, 29875, 29962, 13, 9651, 954, 29879, 29961, 2248, 29962, 353, 954, 29879, 29961, 29875, 29962, 13, 9651, 2380, 4619, 29871, 29896, 13, 13, 4706, 736, 2380, 13, 2 ]
Lesson2_Functions/8-return.py	StyvenSoft/degree-python	0	30229	<filename>Lesson2_Functions/8-return.py def divide_by_four(input_number): return input_number/4 result = divide_by_four(16) # result now holds 4 print("16 divided by 4 is " + str(result) + "!") result2 = divide_by_four(result) print(str(result) + " divided by 4 is " + str(result2) + "!") def calculate_age(current_year, birth_year): age = current_year - birth_year return age my_age = calculate_age(2049, 1993) dads_age = calculate_age(2049, 1953) print("I am "+str(my_age)+" years old and my dad is "+str(dads_age)+" years old")	[ 1, 529, 9507, 29958, 29931, 404, 265, 29906, 29918, 6678, 29879, 29914, 29947, 29899, 2457, 29889, 2272, 13, 1753, 16429, 29918, 1609, 29918, 17823, 29898, 2080, 29918, 4537, 1125, 13, 29871, 736, 1881, 29918, 4537, 29914, 29946, 13, 259, 13, 2914, 353, 16429, 29918, 1609, 29918, 17823, 29898, 29896, 29953, 29897, 13, 29937, 1121, 1286, 8640, 29871, 29946, 13, 2158, 703, 29896, 29953, 13931, 491, 29871, 29946, 338, 376, 718, 851, 29898, 2914, 29897, 718, 376, 29991, 1159, 13, 2914, 29906, 353, 16429, 29918, 1609, 29918, 17823, 29898, 2914, 29897, 13, 2158, 29898, 710, 29898, 2914, 29897, 718, 376, 13931, 491, 29871, 29946, 338, 376, 718, 851, 29898, 2914, 29906, 29897, 718, 376, 29991, 1159, 13, 13, 13, 1753, 8147, 29918, 482, 29898, 3784, 29918, 6360, 29892, 12060, 29918, 6360, 1125, 13, 29871, 5046, 353, 1857, 29918, 6360, 448, 12060, 29918, 6360, 13, 29871, 736, 5046, 13, 259, 13, 1357, 29918, 482, 353, 8147, 29918, 482, 29898, 29906, 29900, 29946, 29929, 29892, 29871, 29896, 29929, 29929, 29941, 29897, 13, 29881, 7925, 29918, 482, 353, 8147, 29918, 482, 29898, 29906, 29900, 29946, 29929, 29892, 29871, 29896, 29929, 29945, 29941, 29897, 13, 13, 13, 2158, 703, 29902, 626, 15691, 710, 29898, 1357, 29918, 482, 7240, 29908, 2440, 2030, 322, 590, 270, 328, 338, 15691, 710, 29898, 29881, 7925, 29918, 482, 7240, 29908, 2440, 2030, 1159, 2 ]
bauble/routes/auth.py	Bauble/bauble.api	0	120367	<reponame>Bauble/bauble.api<filename>bauble/routes/auth.py """ All routes in Bauble use HTTP basic auth. """ from datetime import datetime, timedelta import os import smtplib import bottle from bottle import request import sqlalchemy as sa import bauble import bauble.config as config import bauble.db as db import bauble.email as email from bauble import app, API_ROOT from bauble.middleware import basic_auth from bauble.model import User from bauble.utils import create_unique_token def create_access_token(): return create_unique_token(), datetime.now() + timedelta(weeks=2) def create_password_reset_token(): return create_unique_token(), datetime.now() + timedelta(days=1) @app.get(API_ROOT + "/login") def login(): auth = request.auth if not auth: bottle.abort(401, "No Authorization header.") username, password = auth session = db.Session() try: user = session.query(User).filter(sa.func.lower(User.email) == username.lower()).first() if not user or not user.password == password: bottle.abort(401) # not authorized user.access_token, user.access_token_expiration = create_access_token() user.last_accessed = datetime.now() session.commit() user_json = user.json() finally: session.close() return user_json @app.get(API_ROOT + "/logout") @basic_auth def logout(): request.user.access_token = None request.user.access_token_expiration = None request.session.commit() @app.post(API_ROOT + "/forgot-password") def forgot_password(): user_email = request.params.get('email', None) if not user_email and not user_email.contains('@'): bottle.abort("Valid email address required") session = None try: session = db.Session() user = session.query(User)\ .filter(sa.func.lower(User.email) == user_email.lower())\ .first() if not user: bottle.abort(422, "Could not get a user with the requested email address") token, expiration = create_password_reset_token() user.password_reset_token = token user.password_reset_token_expiration = expiration session.commit() finally: if session: session.close() app_url = config.get("BAUBLE_APP_URL") mappings = {'token': token, 'email': user_email, 'app_url': app_url} try: email.send_template('reset_password.txt', mappings, **{ 'to': user_email, 'from': '<EMAIL>', 'subject': 'Bauble Password Reset'}) except smtplib.SMTPException as exc: print(exc) bottle.abort(500, 'Could not send reset password email.') @app.post(API_ROOT + "/reset-password") def reset_password(): session = None user_email = request.json['email'] try: session = db.Session() user = session.query(User).filter(sa.func.lower(User.email) == user_email.lower()).first() if user is None: print('use is None') # TODO: is this the correct status code? bottle.abort(422, 'A user could be be found with the provided email') if request.json['token'] != user.password_reset_token or \ (request.json['token'] == user.password_reset_token and user.password_reset_token_expiration < datetime.now()): # TODO: is this the correct status code? bottle.abort(422, 'Invalid password reset token') # TODO: need to set the expiration user.password_reset_token = None user.password_reset_token_expiration = None user.password = request.json['password'] user.access_token, user.access_token_expiration = create_access_token() user.last_accesseed = datetime.now() session.commit() user_json = user.json() # except Exception as exc: # print('type(exc): ', type(exc)) # print(exc) # bottle.abort(400, "Could not get a user with the requested email address") finally: if session: session.close() return user_json	[ 1, 529, 276, 1112, 420, 29958, 29933, 29874, 431, 280, 29914, 2291, 431, 280, 29889, 2754, 29966, 9507, 29958, 2291, 431, 280, 29914, 27894, 29914, 5150, 29889, 2272, 13, 15945, 29908, 13, 3596, 12049, 297, 6000, 431, 280, 671, 7331, 6996, 4817, 29889, 13, 15945, 29908, 13, 13, 3166, 12865, 1053, 12865, 29892, 5335, 287, 2554, 13, 5215, 2897, 13, 5215, 1560, 9392, 1982, 13, 13, 5215, 18046, 280, 13, 3166, 18046, 280, 1053, 2009, 13, 5215, 4576, 284, 305, 6764, 408, 872, 13, 13, 5215, 9922, 431, 280, 13, 5215, 9922, 431, 280, 29889, 2917, 408, 2295, 13, 5215, 9922, 431, 280, 29889, 2585, 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bin/make_expmap.py	sjtuzyk/chandra-acis-analysis	3	110917	<filename>bin/make_expmap.py<gh_stars>1-10 #!/usr/bin/env python3 # # Copyright (c) 2017 <NAME> <<EMAIL>> # MIT license """ Create the spectral-weighted exposure map, which will be used to produce the exposure-corrected images and to extract the surface brightness profiles. NOTE ---- We do not use the CIAO tool ``fluximage`` to create the exposure map, because it requires an event file (other than an image) as input file. However, we want to create the exposure map directly based on the (previously created) image file. (But an event file is required to create the aspect histograms for each chip.) NOTE/CAVEAT ----------- To compute an image which gives the integrated flux over the full energy range, it may be best to first compute flux-corrected images in several narrow energy bands (where the ARF is nearly flat) and then sum those fluxed images together. Weighted exposure maps work well for an energy band where the ARF variation isn't very large, but for a full-band 0.5-10 keV image, it may not be a good idea to compute the flux by dividing the counts image by a single number. This is especially true for cases where the source spectrum varies significantly within the image; in that case, there is no general way to compute a single set of weights which will be sensible for every part of the image. References ---------- * <NAME>: An Introduction to Exposure Map http://cxc.harvard.edu/ciao/download/doc/expmap_intro.ps * CIAO: Single Chip ACIS Exposure Map and Exposure-corrected Image http://cxc.harvard.edu/ciao/threads/expmap_acis_single/ * CIAO: Multiple Chip ACIS Exposure Map and Exposure-corrected Image http://cxc.harvard.edu/ciao/threads/expmap_acis_multi/ * CIAO: Calculating Spectral Weights for mkinstmap http://cxc.harvard.edu/ciao/threads/spectral_weights/ """ import os import argparse import subprocess import logging from _context import acispy from acispy.manifest import get_manifest from acispy.ciao import setup_pfiles from acispy.acis import ACIS from acispy.header import write_keyword, copy_keyword from acispy.image import get_xygrid logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def make_aspect_histogram(outfile, asol, evtfile, chip, clobber=False): """ Create the aspect histogram for each chip, detailing the aspect history of the observation. """ clobber = "yes" if clobber else "no" logger.info("Make aspect histogram for chip: %s" % chip) subprocess.check_call(["punlearn", "asphist"]) subprocess.check_call([ "asphist", "infile=%s" % asol, "outfile=%s" % outfile, "evtfile=%s[ccd_id=%s]" % (evtfile, chip), "clobber=%s" % clobber ]) def make_instrument_map(outfile, spectrumfile, chip, obsfile, maskfile, badpixfile, clobber=False): """ Make the spectral-weighted instrument map (effective area vs. detector position). NOTE ---- The ``obsfile`` should be a FITS file containing keywords which specify the mission, detector, SIM offsets, observation date, etc. This should be an event file; can also be a binned image file (tested OK). """ logger.info("Set bad pixel file: %s" % badpixfile) subprocess.check_call(["punlearn", "ardlib"]) subprocess.check_call(["punlearn", "acis_set_ardlib"]) subprocess.check_call([ "acis_set_ardlib", "badpixfile=%s" % badpixfile, "verbose=0" ]) clobber = "yes" if clobber else "no" pixelgrid = "1:1024:#1024,1:1024:#1024" logger.info("Make spectral-weighted instrument map for chip: %s" % chip) subprocess.check_call(["punlearn", "mkinstmap"]) subprocess.check_call([ "mkinstmap", "outfile=%s" % outfile, "spectrumfile=%s" % spectrumfile, "pixelgrid=%s" % pixelgrid, "detsubsys=ACIS-%s" % chip, "obsfile=%s" % obsfile, "maskfile=%s" % maskfile, "clobber=%s" % clobber, "mode=h" ]) def make_exposure_map(outfile, asphistfile, instmapfile, xygrid, clobber=False): """ Create the spectral-weighted exposure map by projecting the instrument map onto the sky with the aspect information. """ clobber = "yes" if clobber else "no" logger.info("Make exposure map by projecting instrument map ...") subprocess.check_call(["punlearn", "mkexpmap"]) subprocess.check_call([ "mkexpmap", "outfile=%s" % outfile, "asphistfile=%s" % asphistfile, "instmapfile=%s" % instmapfile, "xygrid=%s" % xygrid, "normalize=no", "useavgaspect=no", "clobber=%s" % clobber, "mode=h" ]) # Copy several keywords from instrument map (as ``fluximage`` does) logger.info("Copy several keywords from instrument map ...") copy_keyword(instmapfile, outfile, keyword=["SPECTRUM", "WGTFILE", "ENERG_LO", "ENERG_HI", "GRATING"]) def combine_expmaps(outfile, expmaps, clobber=False): """ Combine multiple exposure maps of each chip into a single one for ACIS-I (i.e., chips 0123). """ if len(expmaps) > 1: logger.info("Combine exposure maps: {0}".format(", ".join(expmaps))) operation = "imgout=%s" % "+".join([ "img%d" % (i+1) for i in range(len(expmaps)) ]) clobber = "yes" if clobber else "no" subprocess.check_call(["punlearn", "dmimgcalc"]) subprocess.check_call([ "dmimgcalc", "infile=%s" % ",".join(expmaps), "infile2=none", "outfile=%s[EXPMAP]" % outfile, "operation=%s" % operation, "clobber=%s" % clobber ]) # Add the lost "BUNIT" keyword during ``dmimgcalc`` write_keyword(outfile, keyword="BUNIT", value="cm*2 s") # Remove original exposure maps for single chip for f in expmaps: os.remove(f) else: logger.info("No need to combine exposure maps.") if os.path.exists(outfile) and (not clobber): raise OSError("File already exists: %s" % outfile) os.rename(expmaps[0], outfile) def threshold_expmap(expmap, cut="1.5%", clobber=False): """ The strongly variable exposure near the edge of a dithered field may produce "hot" pixels when divided into an image. Therefore, apply a threshold to the exposure map pixels that cuts the pixels with value of exposure less than this threshold. NOTE ---- The original/input exposure map is replaced* by the threshold-cut exposure map. """ logger.info("Apply threshold to cut the exposure map: cut=%s" % cut) clobber = "yes" if clobber else "no" expmap_thresh = os.path.splitext(expmap)[0] + "_thresh.fits" subprocess.check_call(["punlearn", "dmimgthresh"]) subprocess.check_call([ "dmimgthresh", "infile=%s" % expmap, "outfile=%s" % expmap_thresh, "cut=%s" % cut, "clobber=%s" % clobber ]) os.rename(expmap_thresh, expmap) def main(): parser = argparse.ArgumentParser( description="Make spectral-weighted exposure map") parser.add_argument("-C", "--clobber", dest="clobber", action="store_true", help="overwrite existing file") parser.add_argument("-w", "--weights", dest="weights", help="spectral weights file (default: " + "'spec_weights' from manifest)") parser.add_argument("-e", "--evtfile", dest="evtfile", help="event file for aspect histogram creation " + "(default: 'evt2_clean' from manifest)") parser.add_argument("-i", "--infile", dest="infile", required=True, help="input image file") parser.add_argument("-o", "--outfile", dest="outfile", required=True, help="filename of output exposure map") args = parser.parse_args() setup_pfiles(["get_sky_limits", "asphist", "mkinstmap", "mkexpmap", "ardlib", "acis_set_ardlib", "dmimgcalc", "dmimgthresh"]) manifest = get_manifest() if args.weights: weights = args.weights else: weights = manifest.getpath("spec_weights", relative=True) if args.evtfile: evtfile = args.evtfile else: evtfile = manifest.getpath("evt2_clean", relative=True) asol = manifest.getpath("asol", relative=True, sep=",") bpix = manifest.getpath("bpix", relative=True) msk = manifest.getpath("msk", relative=True) chips = ACIS.get_chips_str(args.infile) logger.info("infile: %s" % args.infile) logger.info("output expmap: %s" % args.outfile) logger.info("weights: %s" % weights) logger.info("evtfile: %s" % evtfile) logger.info("chips: %s" % chips) logger.info("bpix: %s" % bpix) logger.info("asol: %s" % asol) logger.info("msk: %s" % msk) xygrid = get_xygrid(args.infile) logger.info("%s:xygrid: %s" % (args.infile, xygrid)) expmaps = [] for c in chips: logger.info("Processing chip %s ..." % c) asphist = "asphist_c{chip}.fits".format(chip=c) instmap = "instmap_c{chip}.fits".format(chip=c) expmap = "expmap_c{chip}.fits".format(chip=c) make_aspect_histogram(outfile=asphist, asol=asol, evtfile=evtfile, chip=c, clobber=args.clobber) make_instrument_map(outfile=instmap, spectrumfile=weights, chip=c, obsfile=args.infile, maskfile=msk, badpixfile=bpix, clobber=args.clobber) make_exposure_map(outfile=expmap, asphistfile=asphist, instmapfile=instmap, xygrid=xygrid, clobber=args.clobber) expmaps.append(expmap) # Remove intermediate files os.remove(asphist) os.remove(instmap) combine_expmaps(outfile=args.outfile, expmaps=expmaps, clobber=args.clobber) detnam = "ACIS-{0}".format(chips) logger.info("Update keyword 'DETNAM' to %s" % detnam) write_keyword(args.outfile, keyword="DETNAM", value=detnam) threshold_expmap(args.outfile, clobber=args.clobber) logger.info("Add created exposure map to manifest ...") key = "expmap" manifest.setpath(key, args.outfile) logger.info("Added '%s' to manifest: %s" % (key, manifest.get(key))) if __name__ == "__main__": main()	[ 1, 529, 9507, 29958, 2109, 29914, 5675, 29918, 4548, 1958, 29889, 2272, 29966, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 29937, 14708, 4855, 29914, 2109, 29914, 6272, 3017, 29941, 13, 29937, 13, 29937, 14187, 1266, 313, 29883, 29897, 29871, 29906, 29900, 29896, 29955, 529, 5813, 29958, 3532, 26862, 6227, 6778, 13, 29937, 341, 1806, 19405, 13, 13, 15945, 29908, 13, 4391, 278, 23161, 29899, 7915, 287, 14060, 545, 2910, 29892, 607, 674, 367, 1304, 304, 7738, 13, 1552, 14060, 545, 29899, 15728, 287, 4558, 322, 304, 6597, 278, 7101, 11785, 2264, 28723, 29889, 13, 13, 12256, 29923, 13, 807, 13, 4806, 437, 451, 671, 278, 315, 10764, 29949, 5780, 4954, 1579, 1314, 3027, 16159, 304, 1653, 278, 14060, 545, 2910, 29892, 13, 18103, 372, 6858, 385, 1741, 934, 313, 1228, 1135, 385, 1967, 29897, 408, 1881, 934, 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protos/control_pb2_grpc.py	uni-tue-kn/p4-ipsec	13	169849	# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc import control_pb2 as control__pb2 class ControlStub(object): # missing associated documentation comment in .proto file pass def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.addMACsecProtectRule = channel.unary_unary( '/Control/addMACsecProtectRule', request_serializer=control__pb2.MACsecProtectRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.addMACsecValidateRule = channel.unary_unary( '/Control/addMACsecValidateRule', request_serializer=control__pb2.MACsecValidateRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.deleteMACsecProtectRule = channel.unary_unary( '/Control/deleteMACsecProtectRule', request_serializer=control__pb2.MACsecProtectRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.deleteMACsecValidateRule = channel.unary_unary( '/Control/deleteMACsecValidateRule', request_serializer=control__pb2.MACsecValidateRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) class ControlServicer(object): # missing associated documentation comment in .proto file pass def addMACsecProtectRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def addMACsecValidateRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def deleteMACsecProtectRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def deleteMACsecValidateRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_ControlServicer_to_server(servicer, server): rpc_method_handlers = { 'addMACsecProtectRule': grpc.unary_unary_rpc_method_handler( servicer.addMACsecProtectRule, request_deserializer=control__pb2.MACsecProtectRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'addMACsecValidateRule': grpc.unary_unary_rpc_method_handler( servicer.addMACsecValidateRule, request_deserializer=control__pb2.MACsecValidateRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'deleteMACsecProtectRule': grpc.unary_unary_rpc_method_handler( servicer.deleteMACsecProtectRule, request_deserializer=control__pb2.MACsecProtectRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'deleteMACsecValidateRule': grpc.unary_unary_rpc_method_handler( servicer.deleteMACsecValidateRule, request_deserializer=control__pb2.MACsecValidateRule.FromString, 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v7/mediawiki/mediawiki.py	hardening/nikola-plugins	0	139157	# -- coding: utf-8 -- # Copyright © 2015 <NAME> and others. # Permission is hereby granted, free of charge, to any # person obtaining a copy of this software and associated # documentation files (the "Software"), to deal in the # Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the # Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice # shall be included in all copies or substantial portions of # the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY # KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE # WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR # PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS # OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR # OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """Implementation of compile_html based on smc.mw. You will need, of course, to install smc.mw """ from __future__ import unicode_literals import io import os import re from lxml import etree try: import smc.mw as mw except: mw = None from nikola.plugin_categories import PageCompiler from nikola.utils import makedirs, req_missing, write_metadata try: from collections import OrderedDict except ImportError: OrderedDict = dict # NOQA class CompileMediaWiki(PageCompiler): """Compile mediawiki into HTML.""" name = "mediawiki" demote_headers = True def compile_html(self, source, dest, is_two_file=True): makedirs(os.path.dirname(dest)) if mw is None: req_missing(['smc.mw'], 'build this site (compile with MediaWiki)', python=True) with io.open(dest, "w+", encoding="utf8") as out_file: with io.open(source, "r", encoding="utf8") as in_file: data = in_file.read() if not is_two_file: data = re.split('(\n\n\|\r\n\r\n)', data, maxsplit=1)[-1] parser = mw.Parser(parseinfo=False, whitespace='', nameguard=False) ast = parser.parse(data, 'document', semantics=mw.Semantics(parser)) output = etree.tostring(ast, encoding='utf8').decode('utf8') out_file.write(output) def create_post(self, path, **kw): content = kw.pop('content', None) onefile = kw.pop('onefile', False) # is_page is not used by create_post as of now. kw.pop('is_page', False) metadata = {} metadata.update(self.default_metadata) metadata.update(kw) makedirs(os.path.dirname(path)) if not content.endswith('\n'): content += '\n' with io.open(path, "w+", encoding="utf8") as fd: if onefile: fd.write(write_metadata(metadata)) fd.write('\n\n') fd.write(content)	[ 1, 396, 448, 29930, 29899, 14137, 29901, 23616, 29899, 29947, 448, 29930, 29899, 13, 13, 29937, 14187, 1266, 29871, 30211, 29871, 29906, 29900, 29896, 29945, 529, 5813, 29958, 322, 4045, 29889, 13, 13, 29937, 20894, 2333, 338, 1244, 1609, 16896, 29892, 3889, 310, 8323, 29892, 304, 738, 13, 29937, 2022, 4017, 292, 263, 3509, 310, 445, 7047, 322, 6942, 13, 29937, 5106, 2066, 313, 1552, 376, 6295, 14093, 4968, 304, 5376, 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src/mobu/autostart.py	lsst-sqre/sciencemonkey	0	176381	<reponame>lsst-sqre/sciencemonkey """Support for automatically starting flocks.""" from __future__ import annotations import yaml from .config import config from .dependencies.manager import monkey_business_manager from .models.flock import FlockConfig async def autostart() -> None: """Automatically start configured flocks. This function should be called from the startup hook of the FastAPI application. """ if not config.autostart: return with open(config.autostart, "r") as f: autostart = yaml.safe_load(f) flock_configs = [FlockConfig.parse_obj(flock) for flock in autostart] for flock_config in flock_configs: await monkey_business_manager.start_flock(flock_config)	[ 1, 529, 276, 1112, 420, 29958, 3137, 303, 29899, 3044, 276, 29914, 26167, 3977, 9857, 1989, 13, 15945, 29908, 14039, 363, 6336, 6257, 285, 908, 29879, 1213, 15945, 13, 13, 3166, 4770, 29888, 9130, 1649, 1053, 25495, 13, 13, 5215, 343, 8807, 13, 13, 3166, 869, 2917, 1053, 2295, 13, 3166, 869, 22594, 29889, 12847, 1053, 1601, 1989, 29918, 8262, 3335, 29918, 12847, 13, 3166, 869, 9794, 29889, 29888, 908, 1053, 383, 908, 3991, 13, 13, 13, 12674, 822, 1120, 520, 442, 580, 1599, 6213, 29901, 13, 1678, 9995, 28451, 19574, 1369, 13252, 285, 908, 29879, 29889, 13, 13, 1678, 910, 740, 881, 367, 2000, 515, 278, 20234, 12422, 310, 278, 23786, 8787, 13, 1678, 2280, 29889, 13, 1678, 9995, 13, 1678, 565, 451, 2295, 29889, 1300, 520, 442, 29901, 13, 4706, 736, 13, 13, 1678, 411, 1722, 29898, 2917, 29889, 1300, 520, 442, 29892, 376, 29878, 1159, 408, 285, 29901, 13, 4706, 1120, 520, 442, 353, 343, 8807, 29889, 11177, 29918, 1359, 29898, 29888, 29897, 13, 1678, 285, 908, 29918, 2917, 29879, 353, 518, 29943, 908, 3991, 29889, 5510, 29918, 5415, 29898, 29888, 908, 29897, 363, 285, 908, 297, 1120, 520, 442, 29962, 13, 13, 1678, 363, 285, 908, 29918, 2917, 297, 285, 908, 29918, 2917, 29879, 29901, 13, 4706, 7272, 1601, 1989, 29918, 8262, 3335, 29918, 12847, 29889, 2962, 29918, 29888, 908, 29898, 29888, 908, 29918, 2917, 29897, 13, 2 ]
edx/config/lms/docker_run.py	openfun/learning-analytics-playground	1	16741	""" This is the default template for our main set of servers. This does NOT cover the content machines, which use content.py Common traits: * Use memcached, and cache-backed sessions * Use a MySQL 5.1 database """ # We intentionally define lots of variables that aren't used, and # want to import all variables from base settings files # pylint: disable=wildcard-import, unused-wildcard-import # Pylint gets confused by path.py instances, which report themselves as class # objects. As a result, pylint applies the wrong regex in validating names, # and throws spurious errors. Therefore, we disable invalid-name checking. # pylint: disable=invalid-name import datetime import dateutil from glob import glob import json import os from path import Path as path import pkgutil import platform from django.utils.translation import ugettext_lazy from django.conf import global_settings from celery_redis_sentinel import register from openedx.core.lib.logsettings import get_logger_config from path import Path as path from xmodule.modulestore.modulestore_settings import ( convert_module_store_setting_if_needed, update_module_store_settings, ) from ..common import * from .utils import Configuration, prefer_fun_video # Load custom configuration parameters from yaml files config = Configuration(os.path.dirname(__file__)) # edX has now started using "settings.ENV_TOKENS" and "settings.AUTH_TOKENS" everywhere in the # project, not just in the settings. Let's make sure our settings still work in this case ENV_TOKENS = config AUTH_TOKENS = config # SERVICE_VARIANT specifies name of the variant used, which decides what JSON # configuration files are read during startup. SERVICE_VARIANT = config("SERVICE_VARIANT", default=None) # CONFIG_ROOT specifies the directory where the JSON configuration # files are expected to be found. If not specified, use the project # directory. CONFIG_ROOT = path(config("CONFIG_ROOT", default=ENV_ROOT)) # CONFIG_PREFIX specifies the prefix of the JSON configuration files, # based on the service variant. If no variant is use, don't use a # prefix. CONFIG_PREFIX = SERVICE_VARIANT + "." if SERVICE_VARIANT else "" ################################ ALWAYS THE SAME ############################## RELEASE = config("RELEASE", default=None) DEBUG = False DEFAULT_TEMPLATE_ENGINE["OPTIONS"]["debug"] = False # IMPORTANT: With this enabled, the server must always be behind a proxy that # strips the header HTTP_X_FORWARDED_PROTO from client requests. Otherwise, # a user can fool our server into thinking it was an https connection. # See # https://docs.djangoproject.com/en/dev/ref/settings/#secure-proxy-ssl-header # for other warnings. SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") ###################################### CELERY ################################ CELERY_ALWAYS_EAGER = config("CELERY_ALWAYS_EAGER", default=False, formatter=bool) # Don't use a connection pool, since connections are dropped by ELB. BROKER_POOL_LIMIT = 0 BROKER_CONNECTION_TIMEOUT = 1 # For the Result Store, use the django cache named 'celery' CELERY_RESULT_BACKEND = config( "CELERY_RESULT_BACKEND", default="djcelery.backends.cache:CacheBackend" ) # When the broker is behind an ELB, use a heartbeat to refresh the # connection and to detect if it has been dropped. BROKER_HEARTBEAT = 60.0 BROKER_HEARTBEAT_CHECKRATE = 2 # Each worker should only fetch one message at a time CELERYD_PREFETCH_MULTIPLIER = 1 # Celery queues DEFAULT_PRIORITY_QUEUE = config( "DEFAULT_PRIORITY_QUEUE", default="edx.lms.core.default" ) HIGH_PRIORITY_QUEUE = config("HIGH_PRIORITY_QUEUE", default="edx.lms.core.high") LOW_PRIORITY_QUEUE = config("LOW_PRIORITY_QUEUE", default="edx.lms.core.low") HIGH_MEM_QUEUE = config("HIGH_MEM_QUEUE", default="edx.lms.core.high_mem") CELERY_DEFAULT_QUEUE = DEFAULT_PRIORITY_QUEUE CELERY_DEFAULT_ROUTING_KEY = DEFAULT_PRIORITY_QUEUE CELERY_QUEUES = config( "CELERY_QUEUES", default={ DEFAULT_PRIORITY_QUEUE: {}, HIGH_PRIORITY_QUEUE: {}, LOW_PRIORITY_QUEUE: {}, HIGH_MEM_QUEUE: {}, }, formatter=json.loads, ) CELERY_ROUTES = "lms.celery.Router" # Force accepted content to "json" only. If we also accept pickle-serialized # messages, the worker will crash when it's running with a privileged user (even # if it's not the root user but a user belonging to the root group, which is our # case with OpenShift). CELERY_ACCEPT_CONTENT = ["json"] CELERYBEAT_SCHEDULE = {} # For scheduling tasks, entries can be added to this dict ########################## NON-SECURE ENV CONFIG ############################## # Things like server locations, ports, etc. STATIC_ROOT_BASE = path("/edx/app/edxapp/staticfiles") STATIC_ROOT = STATIC_ROOT_BASE STATIC_URL = "/static/" STATICFILES_STORAGE = config( "STATICFILES_STORAGE", default="lms.envs.fun.storage.CDNProductionStorage" ) CDN_BASE_URL = config("CDN_BASE_URL", default=None) MEDIA_ROOT = path("/edx/var/edxapp/media/") MEDIA_URL = "/media/" # DEFAULT_COURSE_ABOUT_IMAGE_URL specifies the default image to show for courses that don't provide one DEFAULT_COURSE_ABOUT_IMAGE_URL = config( "DEFAULT_COURSE_ABOUT_IMAGE_URL", default=DEFAULT_COURSE_ABOUT_IMAGE_URL ) PLATFORM_NAME = config("PLATFORM_NAME", default=PLATFORM_NAME) # For displaying on the receipt. At Stanford PLATFORM_NAME != MERCHANT_NAME, but PLATFORM_NAME is a fine default PLATFORM_TWITTER_ACCOUNT = config( "PLATFORM_TWITTER_ACCOUNT", default=PLATFORM_TWITTER_ACCOUNT ) PLATFORM_FACEBOOK_ACCOUNT = config( "PLATFORM_FACEBOOK_ACCOUNT", default=PLATFORM_FACEBOOK_ACCOUNT ) SOCIAL_SHARING_SETTINGS = config( "SOCIAL_SHARING_SETTINGS", default=SOCIAL_SHARING_SETTINGS, formatter=json.loads ) # Social media links for the page footer SOCIAL_MEDIA_FOOTER_URLS = config( "SOCIAL_MEDIA_FOOTER_URLS", default=SOCIAL_MEDIA_FOOTER_URLS, formatter=json.loads ) CC_MERCHANT_NAME = config("CC_MERCHANT_NAME", default=PLATFORM_NAME) EMAIL_BACKEND = config( "EMAIL_BACKEND", default="django.core.mail.backends.smtp.EmailBackend" ) EMAIL_FILE_PATH = config("EMAIL_FILE_PATH", default=None) EMAIL_HOST = config("EMAIL_HOST", default="localhost") EMAIL_PORT = config("EMAIL_PORT", default=25) # django default is 25 EMAIL_USE_TLS = config("EMAIL_USE_TLS", default=False) # django default is False HTTPS = config("HTTPS", default=HTTPS) SESSION_COOKIE_DOMAIN = config("SESSION_COOKIE_DOMAIN", default=None) SESSION_COOKIE_HTTPONLY = config( "SESSION_COOKIE_HTTPONLY", default=True, formatter=bool ) SESSION_COOKIE_SECURE = config( "SESSION_COOKIE_SECURE", default=SESSION_COOKIE_SECURE, formatter=bool ) SESSION_ENGINE = config("SESSION_ENGINE", default="redis_sessions.session") SESSION_SAVE_EVERY_REQUEST = config( "SESSION_SAVE_EVERY_REQUEST", default=SESSION_SAVE_EVERY_REQUEST, formatter=bool ) # Configuration to use session with redis # To use redis, change SESSION_ENGINE to "redis_sessions.session" SESSION_REDIS_HOST = config("SESSION_REDIS_HOST", default="redis") SESSION_REDIS_PORT = config("SESSION_REDIS_PORT", default=6379, formatter=int) SESSION_REDIS_DB = config("SESSION_REDIS_DB", default=1, formatter=int) SESSION_REDIS_PASSWORD = config("SESSION_REDIS_PASSWORD", default=None) SESSION_REDIS_PREFIX = config("SESSION_REDIS_PREFIX", default="session") SESSION_REDIS_SOCKET_TIMEOUT = config( "SESSION_REDIS_SOCKET_TIMEOUT", default=1, formatter=int ) SESSION_REDIS_RETRY_ON_TIMEOUT = config( "SESSION_REDIS_RETRY_ON_TIMEOUT", default=False, formatter=bool ) SESSION_REDIS = config( "SESSION_REDIS", default={ "host": SESSION_REDIS_HOST, "port": SESSION_REDIS_PORT, "db": SESSION_REDIS_DB, # db 0 is used for Celery Broker "password": SESSION_REDIS_PASSWORD, "prefix": SESSION_REDIS_PREFIX, "socket_timeout": SESSION_REDIS_SOCKET_TIMEOUT, "retry_on_timeout": SESSION_REDIS_RETRY_ON_TIMEOUT, }, formatter=json.loads, ) SESSION_REDIS_SENTINEL_LIST = config( "SESSION_REDIS_SENTINEL_LIST", default=None, formatter=json.loads ) SESSION_REDIS_SENTINEL_MASTER_ALIAS = config( "SESSION_REDIS_SENTINEL_MASTER_ALIAS", default=None ) REGISTRATION_EXTRA_FIELDS = config( "REGISTRATION_EXTRA_FIELDS", default=REGISTRATION_EXTRA_FIELDS, formatter=json.loads ) # Set the names of cookies shared with the marketing site # These have the same cookie domain as the session, which in production # usually includes subdomains. EDXMKTG_LOGGED_IN_COOKIE_NAME = config( "EDXMKTG_LOGGED_IN_COOKIE_NAME", default=EDXMKTG_LOGGED_IN_COOKIE_NAME ) EDXMKTG_USER_INFO_COOKIE_NAME = config( "EDXMKTG_USER_INFO_COOKIE_NAME", default=EDXMKTG_USER_INFO_COOKIE_NAME ) # Override feature by feature by whatever is being redefined in the settings.yaml file CONFIG_FEATURES = config("FEATURES", default={}, formatter=json.loads) FEATURES.update(CONFIG_FEATURES) LMS_BASE = config("LMS_BASE", default="localhost:8072") CMS_BASE = config("CMS_BASE", default="localhost:8082") LMS_ROOT_URL = config("LMS_ROOT_URL", default="http://{:s}".format(LMS_BASE)) LMS_INTERNAL_ROOT_URL = config("LMS_INTERNAL_ROOT_URL", default=LMS_ROOT_URL) SITE_NAME = config("SITE_NAME", default=LMS_BASE) ALLOWED_HOSTS = config( "ALLOWED_HOSTS", default=[LMS_BASE.split(":")[0]], formatter=json.loads ) if FEATURES.get("PREVIEW_LMS_BASE"): ALLOWED_HOSTS.append(FEATURES["PREVIEW_LMS_BASE"]) # allow for environments to specify what cookie name our login subsystem should use # this is to fix a bug regarding simultaneous logins between edx.org and edge.edx.org which can # happen with some browsers (e.g. Firefox) if config("SESSION_COOKIE_NAME", default=None): # NOTE, there's a bug in Django (http://bugs.python.org/issue18012) which necessitates this # being a str() SESSION_COOKIE_NAME = str(config("SESSION_COOKIE_NAME")) CACHE_REDIS_HOST = config("CACHE_REDIS_HOST", default="redis") CACHE_REDIS_PORT = config("CACHE_REDIS_PORT", default=6379, formatter=int) CACHE_REDIS_DB = config("CACHE_REDIS_DB", default=1, formatter=int) CACHE_REDIS_BACKEND = config( "CACHE_REDIS_BACKEND", default="django_redis.cache.RedisCache" ) CACHE_REDIS_URI = "redis://{}:{}/{}".format( CACHE_REDIS_HOST, CACHE_REDIS_PORT, CACHE_REDIS_DB ) CACHE_REDIS_CLIENT = config( "CACHE_REDIS_CLIENT", default="django_redis.client.DefaultClient" ) CACHES_DEFAULT_CONFIG = { "BACKEND": CACHE_REDIS_BACKEND, "LOCATION": CACHE_REDIS_URI, "OPTIONS": {"CLIENT_CLASS": CACHE_REDIS_CLIENT}, } if "Sentinel" in CACHE_REDIS_BACKEND: CACHES_DEFAULT_CONFIG["LOCATION"] = [(CACHE_REDIS_HOST, CACHE_REDIS_PORT)] CACHES_DEFAULT_CONFIG["OPTIONS"]["SENTINEL_SERVICE_NAME"] = config( "CACHE_REDIS_SENTINEL_SERVICE_NAME", default="mymaster" ) CACHES_DEFAULT_CONFIG["OPTIONS"]["REDIS_CLIENT_KWARGS"] = {"db": CACHE_REDIS_DB} CACHES = config( "CACHES", default={ "default": dict(CACHES_DEFAULT_CONFIG, {"KEY_PREFIX": "default"}), "general": dict(CACHES_DEFAULT_CONFIG, {"KEY_PREFIX": "general"}), "celery": dict(CACHES_DEFAULT_CONFIG, {"KEY_PREFIX": "celery"}), "mongo_metadata_inheritance": dict( CACHES_DEFAULT_CONFIG, {"KEY_PREFIX": "mongo_metadata_inheritance"} ), "openassessment_submissions": dict( CACHES_DEFAULT_CONFIG, *{"KEY_PREFIX": "openassessment_submissions"} ), "loc_cache": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "edx_location_mem_cache", }, # Cache backend used by Django 1.8 storage backend while processing static files "staticfiles": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "edx_location_mem_cache", }, }, formatter=json.loads, ) # Email overrides DEFAULT_FROM_EMAIL = config("DEFAULT_FROM_EMAIL", default=DEFAULT_FROM_EMAIL) DEFAULT_FEEDBACK_EMAIL = config( "DEFAULT_FEEDBACK_EMAIL", default=DEFAULT_FEEDBACK_EMAIL ) ADMINS = config("ADMINS", default=ADMINS, formatter=json.loads) SERVER_EMAIL = config("SERVER_EMAIL", default=SERVER_EMAIL) TECH_SUPPORT_EMAIL = config("TECH_SUPPORT_EMAIL", default=TECH_SUPPORT_EMAIL) CONTACT_EMAIL = config("CONTACT_EMAIL", default=CONTACT_EMAIL) BUGS_EMAIL = config("BUGS_EMAIL", default=BUGS_EMAIL) PAYMENT_SUPPORT_EMAIL = config("PAYMENT_SUPPORT_EMAIL", default=PAYMENT_SUPPORT_EMAIL) FINANCE_EMAIL = config("FINANCE_EMAIL", default=FINANCE_EMAIL) UNIVERSITY_EMAIL = config("UNIVERSITY_EMAIL", default=UNIVERSITY_EMAIL) PRESS_EMAIL = config("PRESS_EMAIL", default=PRESS_EMAIL) # Currency PAID_COURSE_REGISTRATION_CURRENCY = config( "PAID_COURSE_REGISTRATION_CURRENCY", default=["EUR", u"\N{euro sign}"] ) # Payment Report Settings PAYMENT_REPORT_GENERATOR_GROUP = config( "PAYMENT_REPORT_GENERATOR_GROUP", default=PAYMENT_REPORT_GENERATOR_GROUP ) # Bulk Email overrides BULK_EMAIL_DEFAULT_FROM_EMAIL = config( "BULK_EMAIL_DEFAULT_FROM_EMAIL", default=BULK_EMAIL_DEFAULT_FROM_EMAIL ) BULK_EMAIL_EMAILS_PER_TASK = config( "BULK_EMAIL_EMAILS_PER_TASK", default=BULK_EMAIL_EMAILS_PER_TASK, formatter=int ) BULK_EMAIL_DEFAULT_RETRY_DELAY = config( "BULK_EMAIL_DEFAULT_RETRY_DELAY", default=BULK_EMAIL_DEFAULT_RETRY_DELAY, formatter=int, ) BULK_EMAIL_MAX_RETRIES = config( "BULK_EMAIL_MAX_RETRIES", default=BULK_EMAIL_MAX_RETRIES, formatter=int ) BULK_EMAIL_INFINITE_RETRY_CAP = config( "BULK_EMAIL_INFINITE_RETRY_CAP", default=BULK_EMAIL_INFINITE_RETRY_CAP, formatter=int, ) BULK_EMAIL_LOG_SENT_EMAILS = config( "BULK_EMAIL_LOG_SENT_EMAILS", default=BULK_EMAIL_LOG_SENT_EMAILS, formatter=bool ) BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS = config( "BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS", default=BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS, formatter=int, ) # We want Bulk Email running on the high-priority queue, so we define the # routing key that points to it. At the moment, the name is the same. # We have to reset the value here, since we have changed the value of the queue name. BULK_EMAIL_ROUTING_KEY = config("BULK_EMAIL_ROUTING_KEY", default=HIGH_PRIORITY_QUEUE) # We can run smaller jobs on the low priority queue. See note above for why # we have to reset the value here. BULK_EMAIL_ROUTING_KEY_SMALL_JOBS = LOW_PRIORITY_QUEUE # Theme overrides THEME_NAME = config("THEME_NAME", default=None) COMPREHENSIVE_THEME_DIR = path( config("COMPREHENSIVE_THEME_DIR", default=COMPREHENSIVE_THEME_DIR) ) # Marketing link overrides MKTG_URL_LINK_MAP = config("MKTG_URL_LINK_MAP", default={}, formatter=json.loads) SUPPORT_SITE_LINK = config("SUPPORT_SITE_LINK", default=SUPPORT_SITE_LINK) # Mobile store URL overrides MOBILE_STORE_URLS = config("MOBILE_STORE_URLS", default=MOBILE_STORE_URLS) # Timezone overrides TIME_ZONE = config("TIME_ZONE", default=TIME_ZONE) # Translation overrides LANGUAGES = config("LANGUAGES", default=LANGUAGES, formatter=json.loads) LANGUAGE_DICT = dict(LANGUAGES) LANGUAGE_CODE = config("LANGUAGE_CODE", default=LANGUAGE_CODE) USE_I18N = config("USE_I18N", default=USE_I18N) # Additional installed apps for app in config("ADDL_INSTALLED_APPS", default=[], formatter=json.loads): INSTALLED_APPS.append(app) WIKI_ENABLED = config("WIKI_ENABLED", default=WIKI_ENABLED, formatter=bool) local_loglevel = config("LOCAL_LOGLEVEL", default="INFO") # Configure Logging LOG_DIR = config("LOG_DIR", default=path("/edx/var/logs/edx"), formatter=path) DATA_DIR = config("DATA_DIR", default=path("/edx/app/edxapp/data"), formatter=path) # Default format for syslog logging standard_format = "%(asctime)s %(levelname)s %(process)d [%(name)s] %(filename)s:%(lineno)d - %(message)s" syslog_format = ( "[variant:lms][%(name)s][env:sandbox] %(levelname)s " "[{hostname} %(process)d] [%(filename)s:%(lineno)d] - %(message)s" ).format(hostname=platform.node().split(".")[0]) LOGGING = { "version": 1, "disable_existing_loggers": False, "handlers": { "local": { "formatter": "syslog_format", "class": "logging.StreamHandler", "level": "INFO", }, "tracking": { "formatter": "raw", "class": "logging.StreamHandler", "level": "DEBUG", }, "console": { "formatter": "standard", "class": "logging.StreamHandler", "level": "INFO", }, }, "formatters": { "raw": {"format": "%(message)s"}, "syslog_format": {"format": syslog_format}, "standard": {"format": standard_format}, }, "filters": {"require_debug_false": {"()": "django.utils.log.RequireDebugFalse"}}, "loggers": { "": {"level": "INFO", "propagate": False, "handlers": ["console", "local"]}, "tracking": {"level": "DEBUG", "propagate": False, "handlers": ["tracking"]}, }, } SENTRY_DSN = config("SENTRY_DSN", default=None) if SENTRY_DSN: LOGGING["loggers"][""]["handlers"].append("sentry") LOGGING["handlers"]["sentry"] = { "class": "raven.handlers.logging.SentryHandler", "dsn": SENTRY_DSN, "level": "ERROR", "environment": "production", "release": RELEASE, } COURSE_LISTINGS = config("COURSE_LISTINGS", default={}, formatter=json.loads) SUBDOMAIN_BRANDING = config("SUBDOMAIN_BRANDING", default={}, formatter=json.loads) VIRTUAL_UNIVERSITIES = config("VIRTUAL_UNIVERSITIES", default=[]) META_UNIVERSITIES = config("META_UNIVERSITIES", default={}, formatter=json.loads) COMMENTS_SERVICE_URL = config("COMMENTS_SERVICE_URL", default="") COMMENTS_SERVICE_KEY = config("COMMENTS_SERVICE_KEY", default="") CERT_NAME_SHORT = config("CERT_NAME_SHORT", default=CERT_NAME_SHORT) CERT_NAME_LONG = config("CERT_NAME_LONG", default=CERT_NAME_LONG) CERT_QUEUE = config("CERT_QUEUE", default="test-pull") ZENDESK_URL = config("ZENDESK_URL", default=None) FEEDBACK_SUBMISSION_EMAIL = config("FEEDBACK_SUBMISSION_EMAIL", default=None) MKTG_URLS = config("MKTG_URLS", default=MKTG_URLS, formatter=json.loads) # Badgr API BADGR_API_TOKEN = config("BADGR_API_TOKEN", default=BADGR_API_TOKEN) BADGR_BASE_URL = config("BADGR_BASE_URL", default=BADGR_BASE_URL) BADGR_ISSUER_SLUG = config("BADGR_ISSUER_SLUG", default=BADGR_ISSUER_SLUG) # git repo loading environment GIT_REPO_DIR = config( "GIT_REPO_DIR", default=path("/edx/var/edxapp/course_repos"), formatter=path ) GIT_IMPORT_STATIC = config("GIT_IMPORT_STATIC", default=True) for name, value in config("CODE_JAIL", default={}, formatter=json.loads).items(): oldvalue = CODE_JAIL.get(name) if isinstance(oldvalue, dict): for subname, subvalue in value.items(): oldvalue[subname] = subvalue else: CODE_JAIL[name] = value COURSES_WITH_UNSAFE_CODE = config( "COURSES_WITH_UNSAFE_CODE", default=[], formatter=json.loads ) ASSET_IGNORE_REGEX = config("ASSET_IGNORE_REGEX", default=ASSET_IGNORE_REGEX) # Event Tracking TRACKING_IGNORE_URL_PATTERNS = config( "TRACKING_IGNORE_URL_PATTERNS", default=TRACKING_IGNORE_URL_PATTERNS, formatter=json.loads, ) # SSL external authentication settings SSL_AUTH_EMAIL_DOMAIN = config("SSL_AUTH_EMAIL_DOMAIN", default="MIT.EDU") SSL_AUTH_DN_FORMAT_STRING = config("SSL_AUTH_DN_FORMAT_STRING", default=None) # Django CAS external authentication settings CAS_EXTRA_LOGIN_PARAMS = config( "CAS_EXTRA_LOGIN_PARAMS", default=None, formatter=json.loads ) if FEATURES.get("AUTH_USE_CAS"): CAS_SERVER_URL = config("CAS_SERVER_URL", default=None) INSTALLED_APPS.append("django_cas") MIDDLEWARE_CLASSES.append("django_cas.middleware.CASMiddleware") CAS_ATTRIBUTE_CALLBACK = config( "CAS_ATTRIBUTE_CALLBACK", default=None, formatter=json.loads ) if CAS_ATTRIBUTE_CALLBACK: import importlib CAS_USER_DETAILS_RESOLVER = getattr( importlib.import_module(CAS_ATTRIBUTE_CALLBACK["module"]), CAS_ATTRIBUTE_CALLBACK["function"], ) # Video Caching. Pairing country codes with CDN URLs. # Example: {'CN': 'http://api.xuetangx.com/edx/video?s3_url='} VIDEO_CDN_URL = config("VIDEO_CDN_URL", default={}, formatter=json.loads) # Branded footer FOOTER_OPENEDX_URL = config("FOOTER_OPENEDX_URL", default=FOOTER_OPENEDX_URL) FOOTER_OPENEDX_LOGO_IMAGE = config( "FOOTER_OPENEDX_LOGO_IMAGE", default=FOOTER_OPENEDX_LOGO_IMAGE ) FOOTER_ORGANIZATION_IMAGE = config( "FOOTER_ORGANIZATION_IMAGE", default=FOOTER_ORGANIZATION_IMAGE ) FOOTER_CACHE_TIMEOUT = config( "FOOTER_CACHE_TIMEOUT", default=FOOTER_CACHE_TIMEOUT, formatter=int ) FOOTER_BROWSER_CACHE_MAX_AGE = config( "FOOTER_BROWSER_CACHE_MAX_AGE", default=FOOTER_BROWSER_CACHE_MAX_AGE, formatter=int ) # Credit notifications settings NOTIFICATION_EMAIL_CSS = config( "NOTIFICATION_EMAIL_CSS", default=NOTIFICATION_EMAIL_CSS ) NOTIFICATION_EMAIL_EDX_LOGO = config( "NOTIFICATION_EMAIL_EDX_LOGO", default=NOTIFICATION_EMAIL_EDX_LOGO ) ############# CORS headers for cross-domain requests ################# if FEATURES.get("ENABLE_CORS_HEADERS") or FEATURES.get( "ENABLE_CROSS_DOMAIN_CSRF_COOKIE" ): CORS_ALLOW_CREDENTIALS = True CORS_ORIGIN_WHITELIST = config( "CORS_ORIGIN_WHITELIST", default=(), formatter=json.loads ) CORS_ORIGIN_ALLOW_ALL = config( "CORS_ORIGIN_ALLOW_ALL", default=False, formatter=bool ) CORS_ALLOW_INSECURE = config("CORS_ALLOW_INSECURE", default=False, formatter=bool) # If setting a cross-domain cookie, it's really important to choose # a name for the cookie that is DIFFERENT than the cookies used # by each subdomain. For example, suppose the applications # at these subdomains are configured to use the following cookie names: # # 1) foo.example.com --> "csrftoken" # 2) baz.example.com --> "csrftoken" # 3) bar.example.com --> "csrftoken" # # For the cross-domain version of the CSRF cookie, you need to choose # a name DIFFERENT than "csrftoken"; otherwise, the new token configured # for ".example.com" could conflict with the other cookies, # non-deterministically causing 403 responses. # # Because of the way Django stores cookies, the cookie name MUST # be a `str`, not unicode. Otherwise there will `TypeError`s will be raised # when Django tries to call the unicode `translate()` method with the wrong # number of parameters. CROSS_DOMAIN_CSRF_COOKIE_NAME = str(config("CROSS_DOMAIN_CSRF_COOKIE_NAME")) # When setting the domain for the "cross-domain" version of the CSRF # cookie, you should choose something like: ".example.com" # (note the leading dot), where both the referer and the host # are subdomains of "example.com". # # Browser security rules require that # the cookie domain matches the domain of the server; otherwise # the cookie won't get set. And once the cookie gets set, the client # needs to be on a domain that matches the cookie domain, otherwise # the client won't be able to read the cookie. CROSS_DOMAIN_CSRF_COOKIE_DOMAIN = config("CROSS_DOMAIN_CSRF_COOKIE_DOMAIN") # Field overrides. To use the IDDE feature, add # 'courseware.student_field_overrides.IndividualStudentOverrideProvider'. FIELD_OVERRIDE_PROVIDERS = tuple( config("FIELD_OVERRIDE_PROVIDERS", default=[], formatter=json.loads) ) ############################## SECURE AUTH ITEMS ############### # Secret things: passwords, access keys, etc. ############### XBlock filesystem field config ########## DJFS = config( "DJFS", default={ "directory_root": "/edx/var/edxapp/django-pyfs/static/django-pyfs", "type": "osfs", "url_root": "/static/django-pyfs", }, formatter=json.loads, ) ############### Module Store Items ########## HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS = config( "HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS", default={}, formatter=json.loads ) # PREVIEW DOMAIN must be present in HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS for the preview to show draft changes if "PREVIEW_LMS_BASE" in FEATURES and FEATURES["PREVIEW_LMS_BASE"] != "": PREVIEW_DOMAIN = FEATURES["PREVIEW_LMS_BASE"].split(":")[0] # update dictionary with preview domain regex HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS.update({PREVIEW_DOMAIN: "draft-preferred"}) ############### Mixed Related(Secure/Not-Secure) Items ########## LMS_SEGMENT_KEY = config("LMS_SEGMENT_KEY", default=None) CC_PROCESSOR_NAME = config("CC_PROCESSOR_NAME", default=CC_PROCESSOR_NAME) CC_PROCESSOR = config("CC_PROCESSOR", default=CC_PROCESSOR) SECRET_KEY = config("SECRET_KEY", default="ThisisAnExampleKeyForDevPurposeOnly") # Authentication backends # - behind a proxy, use: "lms.envs.fun.backends.ProxyRateLimitModelBackend" # - for LTI provider, add: "lti_provider.users.LtiBackend" # - for CAS, add: "django_cas.backends.CASBackend" AUTHENTICATION_BACKENDS = config( "AUTHENTICATION_BACKENDS", default=("lms.envs.fun.backends.ProxyRateLimitModelBackend",), ) DEFAULT_FILE_STORAGE = config( "DEFAULT_FILE_STORAGE", default="django.core.files.storage.FileSystemStorage" ) # Specific setting for the File Upload Service to store media in a bucket. FILE_UPLOAD_STORAGE_BUCKET_NAME = config( "FILE_UPLOAD_STORAGE_BUCKET_NAME", default="uploads" ) FILE_UPLOAD_STORAGE_PREFIX = config( "FILE_UPLOAD_STORAGE_PREFIX", default=FILE_UPLOAD_STORAGE_PREFIX ) # If there is a database called 'read_replica', you can use the use_read_replica_if_available # function in util/query.py, which is useful for very large database reads DATABASE_ENGINE = config("DATABASE_ENGINE", default="django.db.backends.mysql") DATABASE_HOST = config("DATABASE_HOST", default="mysql") DATABASE_PORT = config("DATABASE_PORT", default=3306, formatter=int) DATABASE_NAME = config("DATABASE_NAME", default="edxapp") DATABASE_USER = config("DATABASE_USER", default="edxapp_user") DATABASE_PASSWORD = config("DATABASE_PASSWORD", default="password") DATABASES = config( "DATABASES", default={ "default": { "ENGINE": DATABASE_ENGINE, "HOST": DATABASE_HOST, "PORT": DATABASE_PORT, "NAME": DATABASE_NAME, "USER": DATABASE_USER, "PASSWORD": DATABASE_PASSWORD, } }, formatter=json.loads, ) # Enable automatic transaction management on all databases # https://docs.djangoproject.com/en/1.8/topics/db/transactions/#tying-transactions-to-http-requests # This needs to be true for all databases for database_name in DATABASES: DATABASES[database_name]["ATOMIC_REQUESTS"] = True XQUEUE_INTERFACE = config( "XQUEUE_INTERFACE", default={"url": None, "basic_auth": None, "django_auth": None}, formatter=json.loads, ) # Configure the MODULESTORE MODULESTORE = convert_module_store_setting_if_needed( config("MODULESTORE", default=MODULESTORE, formatter=json.loads) ) MONGODB_PASSWORD = config("MONGODB_PASSWORD", default="") MONGODB_HOST = config("MONGODB_HOST", default="mongodb") MONGODB_PORT = config("MONGODB_PORT", default=27017, formatter=int) MONGODB_NAME = config("MONGODB_NAME", default="edxapp") MONGODB_USER = config("MONGODB_USER", default=None) MONGODB_SSL = config("MONGODB_SSL", default=False, formatter=bool) MONGODB_REPLICASET = config("MONGODB_REPLICASET", default=None) # Accepted read_preference value can be found here https://github.com/mongodb/mongo-python-driver/blob/2.9.1/pymongo/read_preferences.py#L54 MONGODB_READ_PREFERENCE = config("MONGODB_READ_PREFERENCE", default="PRIMARY") DOC_STORE_CONFIG = config( "DOC_STORE_CONFIG", default={ "collection": "modulestore", "host": MONGODB_HOST, "port": MONGODB_PORT, "db": MONGODB_NAME, "user": MONGODB_USER, "password": <PASSWORD>, "ssl": MONGODB_SSL, "replicaSet": MONGODB_REPLICASET, "read_preference": MONGODB_READ_PREFERENCE, }, formatter=json.loads, ) update_module_store_settings(MODULESTORE, doc_store_settings=DOC_STORE_CONFIG) MONGODB_LOG = config("MONGODB_LOG", default={}, formatter=json.loads) CONTENTSTORE = config( "CONTENTSTORE", default={ "DOC_STORE_CONFIG": DOC_STORE_CONFIG, "ENGINE": "xmodule.contentstore.mongo.MongoContentStore", }, formatter=json.loads, ) EMAIL_HOST_USER = config("EMAIL_HOST_USER", default="") # django default is '' EMAIL_HOST_PASSWORD = config("EMAIL_HOST_PASSWORD", default="") # django default is '' # Datadog for events! DATADOG = config("DATADOG", default={}, formatter=json.loads) # TODO: deprecated (compatibility with previous settings) DATADOG_API = config("DATADOG_API", default=None) # Analytics dashboard server ANALYTICS_SERVER_URL = config("ANALYTICS_SERVER_URL", default=None) ANALYTICS_API_KEY = config("ANALYTICS_API_KEY", default="") # Analytics data source ANALYTICS_DATA_URL = config("ANALYTICS_DATA_URL", default=ANALYTICS_DATA_URL) ANALYTICS_DATA_TOKEN = config("ANALYTICS_DATA_TOKEN", default=ANALYTICS_DATA_TOKEN) # Analytics Dashboard # when True this setting add a link in instructor dashbord to analytics insight service ANALYTICS_DASHBOARD_URL = config( "ANALYTICS_DASHBOARD_URL", default=False, formatter=bool ) ANALYTICS_DASHBOARD_NAME = config( "ANALYTICS_DASHBOARD_NAME", default=PLATFORM_NAME + " Insights" ) # Mailchimp New User List MAILCHIMP_NEW_USER_LIST_ID = config("MAILCHIMP_NEW_USER_LIST_ID", default=None) # Zendesk ZENDESK_USER = config("ZENDESK_USER", default=None) ZENDESK_API_KEY = config("ZENDESK_API_KEY", default=None) # API Key for inbound requests from Notifier service EDX_API_KEY = config("EDX_API_KEY", default=None) # Celery Broker # For redis sentinel use the redis-sentinel transport CELERY_BROKER_TRANSPORT = config("CELERY_BROKER_TRANSPORT", default="redis") CELERY_BROKER_USER = config("CELERY_BROKER_USER", default="") CELERY_BROKER_PASSWORD = config("CELERY_BROKER_PASSWORD", default="") CELERY_BROKER_HOST = config("CELERY_BROKER_HOST", default="redis") CELERY_BROKER_PORT = config("CELERY_BROKER_PORT", default=6379, formatter=int) CELERY_BROKER_VHOST = config("CELERY_BROKER_VHOST", default=0, formatter=int) if CELERY_BROKER_TRANSPORT == "redis-sentinel": # register redis sentinel schema in celery register() BROKER_URL = "{transport}://{user}:{password}@{host}:{port}/{vhost}".format( transport=CELERY_BROKER_TRANSPORT, user=CELERY_BROKER_USER, password=<PASSWORD>, host=CELERY_BROKER_HOST, port=CELERY_BROKER_PORT, vhost=CELERY_BROKER_VHOST, ) # To use redis-sentinel, refer to the documenation here # https://celery-redis-sentinel.readthedocs.io/en/latest/ BROKER_TRANSPORT_OPTIONS = config( "BROKER_TRANSPORT_OPTIONS", default={}, formatter=json.loads ) # upload limits STUDENT_FILEUPLOAD_MAX_SIZE = config( "STUDENT_FILEUPLOAD_MAX_SIZE", default=STUDENT_FILEUPLOAD_MAX_SIZE, formatter=int ) # Event tracking TRACKING_BACKENDS.update(config("TRACKING_BACKENDS", default={}, formatter=json.loads)) EVENT_TRACKING_BACKENDS["tracking_logs"]["OPTIONS"]["backends"].update( config("EVENT_TRACKING_BACKENDS", default={}, formatter=json.loads) ) EVENT_TRACKING_BACKENDS["segmentio"]["OPTIONS"]["processors"][0]["OPTIONS"][ "whitelist" ].extend( config("EVENT_TRACKING_SEGMENTIO_EMIT_WHITELIST", default=[], formatter=json.loads) ) TRACKING_SEGMENTIO_WEBHOOK_SECRET = config( "TRACKING_SEGMENTIO_WEBHOOK_SECRET", default=TRACKING_SEGMENTIO_WEBHOOK_SECRET ) TRACKING_SEGMENTIO_ALLOWED_TYPES = config( "TRACKING_SEGMENTIO_ALLOWED_TYPES", default=TRACKING_SEGMENTIO_ALLOWED_TYPES, formatter=json.loads, ) TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES = config( "TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES", default=TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES, formatter=json.loads, ) TRACKING_SEGMENTIO_SOURCE_MAP = config( "TRACKING_SEGMENTIO_SOURCE_MAP", default=TRACKING_SEGMENTIO_SOURCE_MAP, formatter=json.loads, ) # Student identity verification settings VERIFY_STUDENT = config("VERIFY_STUDENT", default=VERIFY_STUDENT, formatter=json.loads) # Grades download GRADES_DOWNLOAD_ROUTING_KEY = config( "GRADES_DOWNLOAD_ROUTING_KEY", default=HIGH_MEM_QUEUE ) GRADES_DOWNLOAD = config( "GRADES_DOWNLOAD", default=GRADES_DOWNLOAD, formatter=json.loads ) GRADES_DOWNLOAD = config("GRADES_DOWNLOAD", default=GRADES_DOWNLOAD) # financial reports FINANCIAL_REPORTS = config( "FINANCIAL_REPORTS", default=FINANCIAL_REPORTS, formatter=json.loads ) ##### ACCOUNT LOCKOUT DEFAULT PARAMETERS ##### MAX_FAILED_LOGIN_ATTEMPTS_ALLOWED = config( "MAX_FAILED_LOGIN_ATTEMPTS_ALLOWED", default=5, formatter=int ) MAX_FAILED_LOGIN_ATTEMPTS_LOCKOUT_PERIOD_SECS = config( "MAX_FAILED_LOGIN_ATTEMPTS_LOCKOUT_PERIOD_SECS", default=15 60, formatter=int ) MICROSITE_CONFIGURATION = config( "MICROSITE_CONFIGURATION", default={}, formatter=json.loads ) MICROSITE_ROOT_DIR = path(config("MICROSITE_ROOT_DIR", default="")) #### PASSWORD POLICY SETTINGS ##### PASSWORD_MIN_LENGTH = config("PASSWORD_MIN_LENGTH", default=12, formatter=int) PASSWORD_MAX_LENGTH = config("PASSWORD_MAX_LENGTH", default=None, formatter=int) PASSWORD_COMPLEXITY = config( "PASSWORD_COMPLEXITY", default={"UPPER": 1, "LOWER": 1, "DIGITS": 1}, formatter=json.loads, ) PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD = config( "PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD", default=PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD, formatter=int, ) PASSWORD_DICTIONARY = config("PASSWORD_DICTIONARY", default=[], formatter=json.loads) ### INACTIVITY SETTINGS #### SESSION_INACTIVITY_TIMEOUT_IN_SECONDS = config( "SESSION_INACTIVITY_TIMEOUT_IN_SECONDS", default=None, formatter=int ) ##### LMS DEADLINE DISPLAY TIME_ZONE ####### TIME_ZONE_DISPLAYED_FOR_DEADLINES = config( "TIME_ZONE_DISPLAYED_FOR_DEADLINES", default=TIME_ZONE_DISPLAYED_FOR_DEADLINES ) ##### X-Frame-Options response header settings ##### X_FRAME_OPTIONS = config("X_FRAME_OPTIONS", default=X_FRAME_OPTIONS) ##### Third-party auth options ################################################ if FEATURES.get("ENABLE_THIRD_PARTY_AUTH"): # The reduced session expiry time during the third party login pipeline. (Value in seconds) SOCIAL_AUTH_PIPELINE_TIMEOUT = config("SOCIAL_AUTH_PIPELINE_TIMEOUT", default=600) # The SAML private/public key values do not need the delimiter lines (such as # "-----BEGIN PRIVATE KEY-----", default="-----END PRIVATE KEY-----" etc.) but they may be included # if you want (though it's easier to format the key values as JSON without the delimiters). SOCIAL_AUTH_SAML_SP_PRIVATE_KEY = config( "SOCIAL_AUTH_SAML_SP_PRIVATE_KEY", default="" ) SOCIAL_AUTH_SAML_SP_PUBLIC_CERT = config( "SOCIAL_AUTH_SAML_SP_PUBLIC_CERT", default="" ) SOCIAL_AUTH_OAUTH_SECRETS = config( "SOCIAL_AUTH_OAUTH_SECRETS", default={}, formatter=json.loads ) SOCIAL_AUTH_LTI_CONSUMER_SECRETS = config( "SOCIAL_AUTH_LTI_CONSUMER_SECRETS", default={}, formatter=json.loads ) # third_party_auth config moved to ConfigurationModels. This is for data migration only: THIRD_PARTY_AUTH_OLD_CONFIG = config("THIRD_PARTY_AUTH", default=None) if ( config("THIRD_PARTY_AUTH_SAML_FETCH_PERIOD_HOURS", default=24, formatter=int) is not None ): CELERYBEAT_SCHEDULE["refresh-saml-metadata"] = { "task": "third_party_auth.fetch_saml_metadata", "schedule": datetime.timedelta( hours=config( "THIRD_PARTY_AUTH_SAML_FETCH_PERIOD_HOURS", default=24, formatter=int, ) ), } # The following can be used to integrate a custom login form with third_party_auth. # It should be a dict where the key is a word passed via ?auth_entry=, and the value is a # dict with an arbitrary 'secret_key' and a 'url'. THIRD_PARTY_AUTH_CUSTOM_AUTH_FORMS = config( "THIRD_PARTY_AUTH_CUSTOM_AUTH_FORMS", default={}, formatter=json.loads ) ##### OAUTH2 Provider ############## if FEATURES.get("ENABLE_OAUTH2_PROVIDER"): OAUTH_OIDC_ISSUER = config("OAUTH_OIDC_ISSUER", default=None) OAUTH_ENFORCE_SECURE = config("OAUTH_ENFORCE_SECURE", default=True, formatter=bool) OAUTH_ENFORCE_CLIENT_SECURE = config( "OAUTH_ENFORCE_CLIENT_SECURE", default=True, formatter=bool ) ##### ADVANCED_SECURITY_CONFIG ##### ADVANCED_SECURITY_CONFIG = config( "ADVANCED_SECURITY_CONFIG", default={}, formatter=json.loads ) ##### GOOGLE ANALYTICS IDS ##### GOOGLE_ANALYTICS_ACCOUNT = config("GOOGLE_ANALYTICS_ACCOUNT", default=None) GOOGLE_ANALYTICS_LINKEDIN = config("GOOGLE_ANALYTICS_LINKEDIN", default=None) ##### OPTIMIZELY PROJECT ID ##### OPTIMIZELY_PROJECT_ID = config("OPTIMIZELY_PROJECT_ID", default=OPTIMIZELY_PROJECT_ID) #### Course Registration Code length #### REGISTRATION_CODE_LENGTH = config("REGISTRATION_CODE_LENGTH", default=8, formatter=int) # REGISTRATION CODES DISPLAY INFORMATION INVOICE_CORP_ADDRESS = config("INVOICE_CORP_ADDRESS", default=INVOICE_CORP_ADDRESS) INVOICE_PAYMENT_INSTRUCTIONS = config( "INVOICE_PAYMENT_INSTRUCTIONS", default=INVOICE_PAYMENT_INSTRUCTIONS ) # Which access.py permission names to check; # We default this to the legacy permission 'see_exists'. COURSE_CATALOG_VISIBILITY_PERMISSION = config( "COURSE_CATALOG_VISIBILITY_PERMISSION", default=COURSE_CATALOG_VISIBILITY_PERMISSION ) COURSE_ABOUT_VISIBILITY_PERMISSION = config( "COURSE_ABOUT_VISIBILITY_PERMISSION", default=COURSE_ABOUT_VISIBILITY_PERMISSION ) # Enrollment API Cache Timeout ENROLLMENT_COURSE_DETAILS_CACHE_TIMEOUT = config( "ENROLLMENT_COURSE_DETAILS_CACHE_TIMEOUT", default=60, formatter=int ) # PDF RECEIPT/INVOICE OVERRIDES PDF_RECEIPT_TAX_ID = config("PDF_RECEIPT_TAX_ID", default=PDF_RECEIPT_TAX_ID) PDF_RECEIPT_FOOTER_TEXT = config( "PDF_RECEIPT_FOOTER_TEXT", default=PDF_RECEIPT_FOOTER_TEXT ) PDF_RECEIPT_DISCLAIMER_TEXT = config( "PDF_RECEIPT_DISCLAIMER_TEXT", default=PDF_RECEIPT_DISCLAIMER_TEXT ) PDF_RECEIPT_BILLING_ADDRESS = config( "PDF_RECEIPT_BILLING_ADDRESS", default=PDF_RECEIPT_BILLING_ADDRESS ) PDF_RECEIPT_TERMS_AND_CONDITIONS = config( "PDF_RECEIPT_TERMS_AND_CONDITIONS", default=PDF_RECEIPT_TERMS_AND_CONDITIONS ) PDF_RECEIPT_TAX_ID_LABEL = config( "PDF_RECEIPT_TAX_ID_LABEL", default=PDF_RECEIPT_TAX_ID_LABEL ) PDF_RECEIPT_LOGO_PATH = config("PDF_RECEIPT_LOGO_PATH", default=PDF_RECEIPT_LOGO_PATH) PDF_RECEIPT_COBRAND_LOGO_PATH = config( "PDF_RECEIPT_COBRAND_LOGO_PATH", default=PDF_RECEIPT_COBRAND_LOGO_PATH ) PDF_RECEIPT_LOGO_HEIGHT_MM = config( "PDF_RECEIPT_LOGO_HEIGHT_MM", default=PDF_RECEIPT_LOGO_HEIGHT_MM, formatter=int ) PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM = config( "PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM", default=PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM, formatter=int, ) if ( FEATURES.get("ENABLE_COURSEWARE_SEARCH") or FEATURES.get("ENABLE_DASHBOARD_SEARCH") or FEATURES.get("ENABLE_COURSE_DISCOVERY") or FEATURES.get("ENABLE_TEAMS") ): # Use ElasticSearch as the search engine herein SEARCH_ENGINE = "search.elastic.ElasticSearchEngine" ELASTIC_SEARCH_CONFIG = config( "ELASTIC_SEARCH_CONFIG", default=[{}], formatter=json.loads ) # Facebook app FACEBOOK_API_VERSION = config("FACEBOOK_API_VERSION", default=None) FACEBOOK_APP_SECRET = config("FACEBOOK_APP_SECRET", default=None) FACEBOOK_APP_ID = config("FACEBOOK_APP_ID", default=None) XBLOCK_SETTINGS = config("XBLOCK_SETTINGS", default={}, formatter=json.loads) XBLOCK_SETTINGS.setdefault("VideoDescriptor", {})["licensing_enabled"] = FEATURES.get( "LICENSING", False ) XBLOCK_SETTINGS.setdefault("VideoModule", {})["YOUTUBE_API_KEY"] = config( "YOUTUBE_API_KEY", default=YOUTUBE_API_KEY ) ##### CDN EXPERIMENT/MONITORING FLAGS ##### CDN_VIDEO_URLS = config("CDN_VIDEO_URLS", default=CDN_VIDEO_URLS) ONLOAD_BEACON_SAMPLE_RATE = config( "ONLOAD_BEACON_SAMPLE_RATE", default=ONLOAD_BEACON_SAMPLE_RATE ) ##### ECOMMERCE API CONFIGURATION SETTINGS ##### ECOMMERCE_PUBLIC_URL_ROOT = config( "ECOMMERCE_PUBLIC_URL_ROOT", default=ECOMMERCE_PUBLIC_URL_ROOT ) ECOMMERCE_API_URL = config("ECOMMERCE_API_URL", default=ECOMMERCE_API_URL) ECOMMERCE_API_TIMEOUT = config( "ECOMMERCE_API_TIMEOUT", default=ECOMMERCE_API_TIMEOUT, formatter=int ) ECOMMERCE_SERVICE_WORKER_USERNAME = config( "ECOMMERCE_SERVICE_WORKER_USERNAME", default=ECOMMERCE_SERVICE_WORKER_USERNAME ) ECOMMERCE_API_TIMEOUT = config("ECOMMERCE_API_TIMEOUT", default=ECOMMERCE_API_TIMEOUT) ECOMMERCE_API_SIGNING_KEY = config( "ECOMMERCE_API_SIGNING_KEY", default=ECOMMERCE_API_SIGNING_KEY ) ##### Custom Courses for EdX ##### if FEATURES.get("CUSTOM_COURSES_EDX"): INSTALLED_APPS += ("lms.djangoapps.ccx",) FIELD_OVERRIDE_PROVIDERS += ( "lms.djangoapps.ccx.overrides.CustomCoursesForEdxOverrideProvider", ) CCX_MAX_STUDENTS_ALLOWED = config( "CCX_MAX_STUDENTS_ALLOWED", default=CCX_MAX_STUDENTS_ALLOWED ) ##### Individual Due Date Extensions ##### if FEATURES.get("INDIVIDUAL_DUE_DATES"): FIELD_OVERRIDE_PROVIDERS += ( "courseware.student_field_overrides.IndividualStudentOverrideProvider", ) ##### Self-Paced Course Due Dates ##### FIELD_OVERRIDE_PROVIDERS += ( "courseware.self_paced_overrides.SelfPacedDateOverrideProvider", ) # PROFILE IMAGE CONFIG PROFILE_IMAGE_BACKEND = config("PROFILE_IMAGE_BACKEND", default=PROFILE_IMAGE_BACKEND) PROFILE_IMAGE_SECRET_KEY = config( "PROFILE_IMAGE_SECRET_KEY", default=PROFILE_IMAGE_SECRET_KEY ) PROFILE_IMAGE_MAX_BYTES = config( "PROFILE_IMAGE_MAX_BYTES", default=PROFILE_IMAGE_MAX_BYTES, formatter=int ) PROFILE_IMAGE_MIN_BYTES = config( "PROFILE_IMAGE_MIN_BYTES", default=PROFILE_IMAGE_MIN_BYTES, formatter=int ) PROFILE_IMAGE_DEFAULT_FILENAME = "images/profiles/default" # EdxNotes config EDXNOTES_PUBLIC_API = config("EDXNOTES_PUBLIC_API", default=EDXNOTES_PUBLIC_API) EDXNOTES_INTERNAL_API = config("EDXNOTES_INTERNAL_API", default=EDXNOTES_INTERNAL_API) ##### Credit Provider Integration ##### CREDIT_PROVIDER_SECRET_KEYS = config( "CREDIT_PROVIDER_SECRET_KEYS", default={}, formatter=json.loads ) ##################### LTI Provider ##################### if FEATURES.get("ENABLE_LTI_PROVIDER"): INSTALLED_APPS += ("lti_provider",) LTI_USER_EMAIL_DOMAIN = config("LTI_USER_EMAIL_DOMAIN", default="lti.example.com") # For more info on this, see the notes in common.py LTI_AGGREGATE_SCORE_PASSBACK_DELAY = config( "LTI_AGGREGATE_SCORE_PASSBACK_DELAY", default=LTI_AGGREGATE_SCORE_PASSBACK_DELAY ) ##################### Credit Provider help link #################### CREDIT_HELP_LINK_URL = config("CREDIT_HELP_LINK_URL", default=CREDIT_HELP_LINK_URL) #### JWT configuration #### JWT_ISSUER = config("JWT_ISSUER", default=JWT_ISSUER) JWT_EXPIRATION = config("JWT_EXPIRATION", default=JWT_EXPIRATION) ################# PROCTORING CONFIGURATION ################## PROCTORING_BACKEND_PROVIDER = config( "PROCTORING_BACKEND_PROVIDER", default=PROCTORING_BACKEND_PROVIDER ) PROCTORING_SETTINGS = config( "PROCTORING_SETTINGS", default=PROCTORING_SETTINGS, formatter=json.loads ) ################# MICROSITE #################### MICROSITE_CONFIGURATION = config( "MICROSITE_CONFIGURATION", default={}, formatter=json.loads ) MICROSITE_ROOT_DIR = path(config("MICROSITE_ROOT_DIR", default="")) # Cutoff date for granting audit certificates if config("AUDIT_CERT_CUTOFF_DATE", default=None): AUDIT_CERT_CUTOFF_DATE = dateutil.parser.parse( config("AUDIT_CERT_CUTOFF_DATE", default=AUDIT_CERT_CUTOFF_DATE) ) ################ CONFIGURABLE LTI CONSUMER ############### # Add just the standard LTI consumer by default, forcing it to open in a new window and ask # the user before sending email and username: LTI_XBLOCK_CONFIGURATIONS = config( "LTI_XBLOCK_CONFIGURATIONS", default=[ { "display_name": "LTI consumer", "pattern": ".", "hidden_fields": [ "ask_to_send_email", "ask_to_send_username", "new_window", ], "defaults": { "ask_to_send_email": True, "ask_to_send_username": True, "launch_target": "new_window", }, } ], formatter=json.loads, ) LTI_XBLOCK_SECRETS = config("LTI_XBLOCK_SECRETS", default={}, formatter=json.loads) ################################ FUN stuff ################################ SITE_VARIANT = "lms" # Environment's name displayed in FUN's backoffice ENVIRONMENT = config("ENVIRONMENT", default="no set") BASE_ROOT = path("/edx/app/edxapp/") # Fun-apps configuration INSTALLED_APPS += ( "backoffice", "bootstrapform", "ckeditor", "course_dashboard", "course_pages", "courses_api", "courses", "easy_thumbnails", "edx_gea", "forum_contributors", "fun_api", "fun_certificates", "fun_instructor", "fun", "funsite", "haystack", "masquerade", "newsfeed", "password_container", "payment_api", "payment", "pure_pagination", "raven.contrib.django.raven_compat", "rest_framework.authtoken", "teachers", "universities", "videoproviders", ) ROOT_URLCONF = "fun.lms.urls" # Related Richie platform url PLATFORM_RICHIE_URL = config("PLATFORM_RICHIE_URL", default=None) # Haystack configuration (default is minimal working configuration) HAYSTACK_CONNECTIONS = config( "HAYSTACK_CONNECTIONS", default={ "default": {"ENGINE": "courses.search_indexes.ConfigurableElasticSearchEngine"} }, formatter=json.loads, ) CKEDITOR_UPLOAD_PATH = "./" CKEDITOR_CONFIGS = { "default": { "toolbar": [ [ "Undo", "Redo", "-", "Bold", "Italic", "Underline", "-", "Link", "Unlink", "Anchor", "-", "Format", "-", "SpellChecker", "Scayt", "-", "Maximize", ], [ "HorizontalRule", "-", "Table", "-", "BulletedList", "NumberedList", "-", "Cut", "Copy", "Paste", "PasteText", "PasteFromWord", "-", "SpecialChar", "-", "Source", ], ], "toolbarCanCollapse": False, "entities": False, "width": 955, "uiColor": "#9AB8F3", }, "news": { # Redefine path where the news images/files are uploaded. This would # better be done at runtime with the 'reverse' function, but # unfortunately there is no way around defining this in the settings # file. "filebrowserUploadUrl": "/news/ckeditor/upload/", "filebrowserBrowseUrl": "/news/ckeditor/browse/", "toolbar_Full": [ [ "Styles", "Format", "Bold", "Italic", "Underline", "Strike", "SpellChecker", "Undo", "Redo", ], ["Image", "Flash", "Table", "HorizontalRule"], ["NumberedList", "BulletedList", "Blockquote", "TextColor", "BGColor"], ["Smiley", "SpecialChar"], ["Source"], ], }, } # ### FUN-APPS SETTINGS ### # This is dist-packages path where all fun-apps are FUN_BASE_ROOT = path(os.path.dirname(pkgutil.get_loader("funsite").filename)) SHARED_ROOT = DATA_DIR / "shared" # Add FUN applications templates directories to MAKO template finder before edX's ones MAKO_TEMPLATES["main"] = [ # overrides template in edx-platform/lms/templates FUN_BASE_ROOT / "funsite/templates/lms", FUN_BASE_ROOT / "funsite/templates", FUN_BASE_ROOT / "course_pages/templates", FUN_BASE_ROOT / "payment/templates", FUN_BASE_ROOT / "course_dashboard/templates", FUN_BASE_ROOT / "newsfeed/templates", FUN_BASE_ROOT / "fun_certificates/templates", ] + MAKO_TEMPLATES["main"] # JS static override DEFAULT_TEMPLATE_ENGINE["DIRS"].append(FUN_BASE_ROOT / "funsite/templates/lms") FUN_SMALL_LOGO_RELATIVE_PATH = "funsite/images/logos/funmooc173.png" FUN_BIG_LOGO_RELATIVE_PATH = "funsite/images/logos/funmoocfp.png" FAVICON_PATH = "fun/images/favicon.ico" # Locale paths # Here we rewrite LOCAL_PATHS to give precedence to our applications above edx-platform's ones, # then we add xblocks which provide translations as there is no native mechanism to handle this # See Xblock i18n: http://www.libremente.eu/2017/12/06/edx-translation/ LOCALIZED_FUN_APPS = [ "backoffice", "course_dashboard", "course_pages", "courses", "fun_api", "fun_certificates", "funsite", "newsfeed", "payment", "universities", "videoproviders", ] LOCALE_PATHS = [FUN_BASE_ROOT / app / "locale" for app in LOCALIZED_FUN_APPS] LOCALE_PATHS.append(REPO_ROOT / "conf/locale") # edx-platform locales LOCALE_PATHS.append(path(pkgutil.get_loader("proctor_exam").filename) / "locale") # -- Certificates CERTIFICATES_DIRECTORY_NAME = "attestations" FUN_LOGO_PATH = FUN_BASE_ROOT / "funsite/static" / FUN_BIG_LOGO_RELATIVE_PATH FUN_ATTESTATION_LOGO_PATH = ( FUN_BASE_ROOT / "funsite/static" / "funsite/images/logos/funmoocattest.png" ) STUDENT_NAME_FOR_TEST_CERTIFICATE = "Test User" # Videofront subtitles cache CACHES["video_subtitles"] = { "BACKEND": "django.core.cache.backends.filebased.FileBasedCache", "KEY_PREFIX": "video_subtitles", "LOCATION": DATA_DIR / "video_subtitles_cache", } # Course image thumbnails FUN_THUMBNAIL_OPTIONS = { "small": {"size": (270, 152), "crop": "smart"}, "big": {"size": (337, 191), "crop": "smart"}, "about": {"size": (730, 412), "crop": "scale"}, "facebook": { "size": (600, 315), "crop": "smart", }, # https://developers.facebook.com/docs/sharing/best-practices } THUMBNAIL_PRESERVE_EXTENSIONS = True THUMBNAIL_EXTENSION = "png" ##### ORA2 ###### ORA2_FILEUPLOAD_BACKEND = "swift" ORA2_SWIFT_KEY = config("ORA2_SWIFT_KEY", default="") ORA2_SWIFT_URL = config("ORA2_SWIFT_URL", default="") # Prefix for uploads of example-based assessment AI classifiers # This can be used to separate uploads for different environments ORA2_FILE_PREFIX = config("ORA2_FILE_PREFIX", default=ORA2_FILE_PREFIX) # Profile image upload PROFILE_IMAGE_BACKEND = { "class": "storages.backends.overwrite.OverwriteStorage", "options": { "location": os.path.join(MEDIA_ROOT, "profile-images/"), "base_url": os.path.join(MEDIA_URL, "profile-images/"), }, } ENABLE_ADWAYS_FOR_COURSES = config( "ENABLE_ADWAYS_FOR_COURSES", default=[], formatter=json.loads ) # Add our v3 CSS and JS files to assets compilation pipeline to make them available in courseware. # On FUN v3 frontend, which do not use edX's templates, those files are loaded # by funsite/templates/funsite/parts/base.html and css/lms-main.css PIPELINE_CSS["style-vendor"]["source_filenames"].append("fun/css/cookie-banner.css") PIPELINE_CSS["style-vendor"]["source_filenames"].append("funsite/css/header.css") PIPELINE_CSS["style-vendor"]["source_filenames"].append("funsite/css/footer.css") # can't find any common group for group in ["base_vendor", "main_vendor"]: PIPELINE_JS[group]["source_filenames"].append("funsite/js/header.js") PIPELINE_JS[group]["source_filenames"].append("fun/js/cookie-banner.js") # Glowbl GLOWBL_LTI_ENDPOINT = config( "GLOWBL_LTI_ENDPOINT", default="http://ltiapps.net/test/tp.php" ) GLOWBL_LTI_KEY = config("GLOWBL_LTI_KEY", default="jisc.ac.uk") GLOWBL_LTI_SECRET = config("GLOWBL_LTI_SECRET", default="secret") GLOWBL_LTI_ID = config("GLOWBL_LTI_ID", default="testtoolconsumer") GLOWBL_LAUNCH_URL = config( "GLOWBL_LAUNCH_URL", default="http://ltiapps.net/test/tp.php" ) GLOWBL_COLL_OPT = config("GLOWBL_COLL_OPT", default="FunMoocJdR") DEFAULT_TEMPLATE_ENGINE["DIRS"].append(FUN_BASE_ROOT / "funsite/templates/lms") DEFAULT_TEMPLATE_ENGINE["OPTIONS"]["context_processors"].append( "fun.context_processor.fun_settings" ) TEMPLATES = [DEFAULT_TEMPLATE_ENGINE] # This force Edx Studio to use our own video provider Xblock on default button FUN_DEFAULT_VIDEO_PLAYER = "libcast_xblock" MIDDLEWARE_CLASSES += ( "fun.middleware.LegalAcceptance", "backoffice.middleware.PathLimitedMasqueradeMiddleware", ) class LazyChoicesSorter(object): def __init__(self, choices): self.choices = choices def __iter__(self): for choice in sorted(self.choices, key=lambda peer: peer[1]): yield choice # These are the allowed subtitle languages, we have the same list on Videofront server # We remove 2 deprecated chinese language codes which do not exist on Django 1.10 VideoFront SUBTITLE_SUPPORTED_LANGUAGES = LazyChoicesSorter( (code, ugettext_lazy(lang)) for code, lang in global_settings.LANGUAGES if code not in ("zh-cn", "zh-tw") ) ANONYMIZATION_KEY = config("ANONYMIZATION_KEY", default="") RAVEN_CONFIG = config("RAVEN_CONFIG", default={"dsn": ""}, formatter=json.loads) ELASTICSEARCH_INDEX_SETTINGS = { "settings": { "analysis": { "filter": { "elision": { "type": "elision", "articles": ["l", "m", "t", "qu", "n", "s", "j", "d"], } }, "analyzer": { "custom_french_analyzer": { "tokenizer": "letter", "filter": [ "asciifolding", "lowercase", "french_stem", "elision", "stop", "word_delimiter", ], } }, } } } FUN_MKTG_URLS = config("FUN_MKTG_URLS", default={}, formatter=json.loads) # Default visibility of student's profile to other students ACCOUNT_VISIBILITY_CONFIGURATION["default_visibility"] = "private" # A user is verified if he has an approved SoftwareSecurePhotoVerification entry # this setting will create a dummy SoftwareSecurePhotoVerification for user in # paybox success callback view. A this point, we think it's better to create a # dummy one than to remove verifying process in edX FUN_ECOMMERCE_DEBUG_NO_NOTIFICATION = config( "FUN_ECOMMERCE_DEBUG_NO_NOTIFICATION", default=False, formatter=bool ) ECOMMERCE_NOTIFICATION_URL = config("ECOMMERCE_NOTIFICATION_URL", default=None) PAYMENT_ADMIN = "<EMAIL>" # List of pattern definitions to automatically add verified users to a cohort # If value is [] this feature is disabled # Otherwise this setting is a list of # tuple values (r"<course id regex>", "<cohort name>"). # e.g: if you want to enable this feature for a particular course you can set # this setting to # [ # (r"<course id>", "cohort name"), # ] VERIFIED_COHORTS = config("VERIFIED_COHORTS", default=[]) # Force Edx to use `libcast_xblock` as default video player # in the studio (big green button) and if any xblock is called `video` XBLOCK_SELECT_FUNCTION = prefer_fun_video if "sentry" in LOGGING.get("handlers"): LOGGING["handlers"]["sentry"]["environment"] = "development" # Configure gelf handler to listen on graylog server LOGGING["loggers"][""]["handlers"].append("gelf") LOGGING["loggers"]["tracking"]["handlers"].append("gelf") LOGGING["handlers"]["gelf"] = { "level": "DEBUG", "class": "djehouty.libgelf.handlers.GELFTCPSocketHandler", "host": "graylog", "port": 12201, "null_character": True, } DEBUG = True REQUIRE_DEBUG = True EMAIL_BACKEND = config( "EMAIL_BACKEND", default="django.core.mail.backends.console.EmailBackend" ) PIPELINE_ENABLED = False STATICFILES_STORAGE = "openedx.core.storage.DevelopmentStorage" ALLOWED_HOSTS = [""] FEATURES["AUTOMATIC_AUTH_FOR_TESTING"] = True # ORA2 fileupload ORA2_FILEUPLOAD_BACKEND = "filesystem" ORA2_FILEUPLOAD_ROOT = os.path.join(SHARED_ROOT, "openassessment_submissions") ORA2_FILEUPLOAD_CACHE_ROOT = os.path.join( SHARED_ROOT, "openassessment_submissions_cache" ) AUTHENTICATION_BACKENDS = config( "AUTHENTICATION_BACKENDS", default=["django.contrib.auth.backends.ModelBackend"], formatter=json.loads 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catkin_ws/src/o2as_routines/scripts/kitting.py	DevwratJoshi/ur-o2as	0	1615468	#!/usr/bin/env python import sys import copy import rospy import geometry_msgs.msg import tf_conversions import tf from math import pi import numpy as np from collections import namedtuple from o2as_msgs.srv import * import actionlib from o2as_msgs.msg import * # from o2as_usb_relay.srv import * from graspability_estimation.srv import * # from o2as_graspability_estimation.srv import * from std_msgs.msg import Bool from o2as_routines.base import O2ASBaseRoutines import rospkg rp = rospkg.RosPack() import csv import os import random import math from geometry_msgs.msg import Polygon, Point32 from PIL import Image as ImagePIL from PIL import ImageDraw as ImageDrawPIL from sensor_msgs.msg import Image from cv_bridge import CvBridge, CvBridgeError import cv2 LOG_LEVEL = log_level = rospy.DEBUG # LOG_LEVEL = log_level = rospy.INFO CroppedArea = namedtuple("CroppedArea", ["min_row", "max_row", "min_col", "max_col"]) class kitting_order_entry(): """ Object that tracks if its order was fulfilled, and the number of attempts spent on it. """ def __init__(self, part_id, set_number, number_in_set, bin_name, target_frame, ee_to_use, item_name, dropoff_height, bin_is_inclined): self.part_id = part_id # The part id self.set_number = set_number self.number_in_set = number_in_set self.bin_name = bin_name self.target_frame = target_frame self.ee_to_use = ee_to_use self.item_name = item_name self.dropoff_height = dropoff_height self.bin_is_inclined = bin_is_inclined self.attempts = 0 self.fulfilled = False self.in_feeder = False def clamp(n, minn, maxn): """Constrain a number n to the interval [minn, maxn]""" return min(max(n, minn), maxn) class KittingClass(O2ASBaseRoutines): """ This contains the routine used to run the kitting task. See base.py for shared convenience functions. """ def __init__(self): super(KittingClass, self).__init__() #subscribe to gripper position self._inner_gripper_pos_sub = rospy.Subscriber("o2as_precision_gripper/inner_gripper_motor_pos", std_msgs.msg.Int32, self.update_motorPosition) self._motorPos = -1 # services self._feeder_srv = rospy.ServiceProxy("o2as_usb_relay/set_power", o2as_msgs.srv.SetPower) self._suction = actionlib.SimpleActionClient('o2as_fastening_tools/suction_control', SuctionControlAction) self._suctioned = False self._suction_state = rospy.Subscriber("suction_tool/screw_suctioned", Bool, self._suction_state_callback) # self._suction.wait_for_server() self._search_grasp = rospy.ServiceProxy("search_grasp", SearchGrasp) self.search_grasp_client = actionlib.SimpleActionClient("search_grasp_phoxi", o2as_msgs.msg.SearchGraspPhoxiAction) # action self.blob_detection_client = actionlib.SimpleActionClient('blob_detection_action', o2as_msgs.msg.blobDetectionAction) # Image Subscriber for monitoring self.img_blob_topic = "o2as_blob_detection/img_w_blob" #self.img_blob_sub = rospy.Subscriber(self.img_blob_topic, Image, self.image_blob_callback) # Image Publisher for monitoring self.bridge = CvBridge() self.img_inner_pick_topic = "o2as_monitor/vision_res" self.img_inner_pick_pub = rospy.Publisher(self.img_inner_pick_topic, Image, latch=True, queue_size=10) self.current_img_w_goal = Image() self.current_img_w_blob = Image() #for gazebo # self.cameraMatK = np.array([[554.3827128226441, 0.0, 320.5], # [0.0, 554.3827128226441, 240.5], # [0.0, 0.0, 1.0]]) #for ID Realsense on robot ID6141 width 640 height 360 self.cameraMatK = np.array([[461.605774, 0.0, 318.471497], [0.0, 461.605804, 180.336258], [0.0, 0.0, 1.0]]) #For phoxi in omron self.cameraPhoxiMatK = np.array([[2226.52477235, 0.0, 978.075053258], [0.0, 2226.52477235, 775.748572147], [0.0, 0.0, 1.0]]) self.initial_setup() rospy.sleep(.5) # Initialize debug monitor self.start_task_timer() self.log_to_debug_monitor(text="Init", category="task") self.log_to_debug_monitor(text="Init", category="subtask") self.log_to_debug_monitor(text="Init", category="operation") rospy.loginfo("Kitting class started up!") def update_motorPosition(self, msg): self._motorPos = msg.data def initial_setup(self): ### First, set up internal parameters ### Then, read order file and create the list to iterate through # Used for validating grasp poses. This measures only the inside borders of the bin. self.bin_1_width = .11 self.bin_1_length = .11 self.bin_2_width = .16 self.bin_2_length = .09 self.bin_3_width = .20 self.bin_3_length = .16 self.initial_phoxi_image_recorded = False self.max_candidates_from_phoxi = 3 # Used to prepare the suction place poses (because the UR linear driver goes through a singularity sometimes) self.joints_above_set_1_tray_2 = [0.6957670450210571, -1.5090416113482874, 1.9396471977233887, -0.4243395964251917, 0.7138931751251221, -3.1503987948047083] self.joints_above_set_2_tray_2 = [1.195457935333252, -1.6689851919757288, 2.0958428382873535, -0.4254062811480921, 1.2131953239440918, -3.146900002156393] self.joints_above_set_3_tray_2 = [0.550778865814209, -1.4439471403705042, 1.867344856262207, -0.42732316652406865, -1.0016759077655237, -3.134343926106588] self.joints_above_set_1_tray_1 = [1.333075761795044, -1.8985555807696741, 2.2680954933166504, -0.3765481154071253, 2.572127342224121, -3.1496201197253626] self.grasp_strategy = { "part_4" : "suction", "part_5" : "suction", "part_6" : "robotiq_gripper", "part_7" : "suction", "part_8" : "suction", "part_9" : "precision_gripper_from_inside", "part_10": "precision_gripper_from_inside", "part_11": "suction", # Can be one of the grippers "part_12": "suction", # Can be precision_gripper_from_outside in inclined bin "part_13": "suction", # Should be precision_gripper_from_inside "part_14": "precision_gripper_from_outside", "part_15": "precision_gripper_from_inside", "part_16": "precision_gripper_from_inside", "part_17": "precision_gripper_from_outside", "part_18": "precision_gripper_from_outside"} # How high the end effector should hover over the tray when delivering the item self.dropoff_heights = { "part_4" : 0.03, "part_5" : 0.02, "part_6" : 0.01, "part_7" : 0.04, "part_8" : 0.01, "part_9" : 0.005, "part_10": 0.005, "part_11": 0.01, "part_12": 0.01, "part_13": 0.01, "part_14": 0.005, "part_15": 0.005, "part_16": 0.005, "part_17": 0.005, "part_18": 0.005} # NEEDS MANUAL CALIBRATION self.precision_gripper_pick_heights = { "part_9" : 0.00, "part_10": 0.00, "part_14": 0.00, "part_15": 0.00, "part_16": 0.00, "part_17": 0.00, "part_18": 0.00} # How high the end effector should insert the bin when pick up the item. self.insert_offsets = { "part_4" : 0.000, "part_5" : 0.000, "part_6" : 0.002, "part_7" : 0.000, "part_8" : 0.000, "part_9" : 0.003, "part_10": 0.002, "part_11": 0.000, "part_12": 0.000, "part_13": 0.000, "part_14": 0.000, "part_15": 0.002, "part_16": 0.0005, "part_17": 0.0035, "part_18": 0.0025 } self.grasp_candidates = { 4 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 5 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 6 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 7 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 8 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 9 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 10: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 11: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 12: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 13: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 14: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 15: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 16: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 17: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 18: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] } } # self.part_bin_list = { # "part_4" : "bin2_1", # "part_5" : "bin2_1", # "part_6" : "bin3_1", # "part_8" : "bin2_2", # "part_9" : "bin1_1", # "part_10" : "bin1_1", # "part_11" : "bin2_3", # "part_12" : "bin1_2", # "part_13" : "bin2_4", # "part_14" : "bin1_1", # "part_15" : "bin1_2", # "part_16" : "bin1_3", # "part_17" : "bin1_4", # "part_18" : "bin1_5"} self.part_bin_list = rospy.get_param("part_bin_list") self.part_position_in_tray = { "part_4" : "tray_1_partition_4", "part_5" : "tray_2_partition_6", "part_6" : "tray_1_partition_3", "part_7" : "tray_1_partition_2", "part_8" : "tray_2_partition_1", "part_9" : "tray_2_partition_4", "part_10": "tray_2_partition_7", "part_11": "tray_1_partition_1", "part_12": "tray_2_partition_3", "part_13": "tray_1_partition_5", "part_14": "tray_2_partition_2", "part_15": "tray_2_partition_5", "part_16": "tray_2_partition_8", "part_17": "tray_2_this_is_a_screw_so_should_be_ignored", "part_18": "tray_2_this_is_a_screw_so_should_be_ignored" } # This can be copied from kitting_part_bin_list_auto.yaml # Possible values: "left", "right" # "left" means the right side of the bin is higher than the left. It leans to the left. self.bin_for_this_part_is_inclined = { "part_4" : False, # motor "part_5" : False, # small pulley "part_6" : False, # belt "part_7" : False, # bearing "part_8" : False, # shaft "part_9" : False, # end cap "part_10" : False, # output spacer "part_11" : False, # output pulley "part_12" : False, # idler spacer "part_13" : False, # idler pulley/bearing "part_14" : False, # idler pin "part_15" : False, # m6 nut "part_16" : False, # m6 washer "part_17" : False, # m4 screw "part_18" : False} # m3 screw # The "from_behind" orientation is slightly turned to avoid the robot locking up self.suction_orientation_from_behind = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi10/180)) self.suction_orientation_left_bins = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/4)) self.suction_orientation_right_bins = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/4)) self.suction_orientation_from_45 = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/4)) self.suction_orientation_from_side = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/2)) self.downward_orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, 0)) self.downward_orientation_2 = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi)) ### Create the item list self.order_list_raw, self.ordered_items = self.read_order_file() rospy.loginfo("Received order list:") rospy.loginfo(self.order_list_raw) ### Sort by grasp strategy self.screw_items = [] self.screws = dict() self.screws["m3"] = [] self.screws["m4"] = [] self.suction_items = [] self.robotiq_gripper_items = [] self.precision_gripper_items = [] for order_item in self.ordered_items: if order_item.part_id in [17,18]: rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of screw items") self.screw_items.append(order_item) if order_item.part_id == 17: self.screws["m4"].append(order_item) elif order_item.part_id == 18: self.screws["m3"].append(order_item) elif order_item.ee_to_use == "suction": rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of suction items") self.suction_items.append(order_item) elif order_item.ee_to_use == "robotiq_gripper": rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of robotiq_gripper items") self.robotiq_gripper_items.append(order_item) elif "precision_gripper" in order_item.ee_to_use: rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of precision gripper items") self.precision_gripper_items.append(order_item) def read_order_file(self): """Read in the order file, return kitting_list and order_entry_list. kitting_list is a list of lists with only the part IDs that are ordered. order_entry_list is a list of kitting_entry_item objects.""" order_entry_list = [] kitting_list = [] kitting_list.append([]) kitting_list.append([]) kitting_list.append([]) with open(os.path.join(rp.get_path("o2as_scene_description"), "config", "kitting_order_file.csv"), 'r') as f: reader = csv.reader(f) header = next(reader) # [0, 1, 2, 3, 4] = ["Set", "No.", "ID", "Name", "Note"] for data in reader: kitting_list[int(data[0])-1].append(int(data[2])) order_entry_list.append(kitting_order_entry(part_id=int(data[2]), set_number=int(data[0]), number_in_set=int(data[1]), bin_name=self.part_bin_list["part_" + data[2]], target_frame="set_" + data[0] + "_" + self.part_position_in_tray["part_" + data[2]], ee_to_use=self.grasp_strategy["part_" + data[2]], item_name=data[4], dropoff_height=self.dropoff_heights["part_" + data[2]], bin_is_inclined=self.bin_for_this_part_is_inclined["part_" + data[2]])) return kitting_list, order_entry_list ################ ----- Routines ################ ################ def pick(self, robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height = 0.05, special_pick = False): # If the pick uses suction, pass it to the local function. Otherwise to the parent class. if gripper_command == "suction": object_pose.pose.position.z += approach_height self.move_lin(robot_name, object_pose, speed_fast, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height picked = self.pick_using_dual_suction_gripper(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z += approach_height self.move_lin(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height if self._suctioned: object_pose.pose.position.z += approach_height + .05 self.move_lin(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height + .05 return self._suctioned else: return super(KittingClass, self).pick(robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height, special_pick) def place(self, robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height = 0.05, lift_up_after_place = True): # If the place uses suction, pass it to the local function. Otherwise to the parent class. if gripper_command == "suction": above_place_pose = copy.deepcopy(object_pose) place_pose = copy.deepcopy(object_pose) above_place_pose.pose.position.z += approach_height + grasp_height place_pose.pose.position.z += grasp_height + .03 # rospy.loginfo("Going above tray.") # self.move_lin(robot_name, above_place_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") rospy.loginfo("Placing in tray.") self.move_lin(robot_name, place_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") self.suck(turn_suction_on=False, eject=True) rospy.sleep(2.0) self.suck(turn_suction_on=False, eject=False) self.move_lin(robot_name, above_place_pose, speed_fast, end_effector_link="b_bot_suction_tool_tip_link") return True else: return super(KittingClass, self).place(robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height, lift_up_after_place) def set_feeder_power(self, turn_on=True): if not self.use_real_robot: return True req = o2as_msgs.srv.SetPowerRequest() req.port = 2 req.on = turn_on res = self._feeder_srv.call(req) return res.success def _suction_state_callback(self, msg): self._suctioned = msg.data def suck(self, turn_suction_on=False, eject=False): # Judge success or fail using pressure status. if not self.use_real_robot: return True goal = SuctionControlGoal() goal.fastening_tool_name = "suction_tool" goal.turn_suction_on = turn_suction_on goal.eject_screw = False self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) if not turn_suction_on: goal.eject_screw = True self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) goal.eject_screw = False self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) return self._suction.get_result() def pick_using_dual_suction_gripper(self, group_name, pose_goal_stamped, speed, end_effector_link="b_bot_suction_tool_tip_link"): rospy.loginfo("Try picking up by suction.") res = self.suck(True) if not res: return False rospy.loginfo("Pushing into the bin.") if self.use_real_robot: self.do_linear_push("b_bot", force=5.0, wait=True, direction="Y+", max_approach_distance=.092, forward_speed=.04) self.confirm_to_proceed("Went to the target. Press enter") # The max_approach_distance parameter affects how far the robot goes into the bin res = True else: res = self.move_lin(group_name, pose_goal_stamped, speed, end_effector_link=end_effector_link) return res def naive_pick(self, group_name, bin_id, speed_fast = 1.0, speed_slow = 1.0, approach_height = 0.05, bin_eff_height = 0.07, bin_eff_xoff = 0, bin_eff_yoff = 0, bin_eff_deg_angle = 0,end_effector_link = ""): #Place gripper above bin goal_pose_above = geometry_msgs.msg.PoseStamped() goal_pose_above.header.frame_id = bin_id goal_pose_above.pose.position.x = bin_eff_xoff goal_pose_above.pose.position.y = bin_eff_yoff goal_pose_above.pose.position.z = bin_eff_height goal_pose_above.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2 , 0)) res = self.move_lin(group_name, goal_pose_above, speed=speed_fast, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to the target.") return False #Open the gripper self.send_gripper_command(gripper= "precision_gripper_inner", command="close") self.precision_gripper_inner_open() rospy.sleep(1) #Descend rospy.loginfo("Descend on target.") goal_pose_descend = copy.deepcopy(goal_pose_above) goal_pose_descend.pose.position.z = goal_pose_descend.pose.position.z - approach_height res = self.move_lin(group_name, goal_pose_descend, speed=speed_slow, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to above the target bin.") return False #Close the gripper self.send_gripper_command(gripper= "precision_gripper_inner", command="open") self.precision_gripper_inner_close() rospy.sleep(1) #Ascend rospy.loginfo("Ascend with target.") goal_pose_ascend = copy.deepcopy(goal_pose_descend) goal_pose_ascend.pose.position.z = goal_pose_ascend.pose.position.z + approach_height res = self.move_lin(group_name, goal_pose_ascend, speed=speed_slow, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to above the target bin.") return False def pick_screw_with_precision_gripper(self, bin_id, screw_size, speed_fast = 1.0, speed_slow = .1, approach_height = 0.05, bin_eff_height = 0.07, bin_eff_deg_angle = 0,end_effector_link = ""): success_pick = False #Close the gripper and save the motor position self.send_gripper_command(gripper= "precision_gripper_inner", command="open") rospy.sleep(0.1) close_pos = rospy.get_param("/precision_gripper_server/inner_close_motor_position", 2222) posx = 0 posy = 0 posz = 0.08 while (not success_pick): pick_pose = geometry_msgs.msg.PoseStamped() pick_pose.header.frame_id = bin_id pick_pose.pose.orientation = self.downward_orientation gripper_command = "inner_gripper_from_outside" self.pick("a_bot", pick_pose, 0.0, speed_fast = 1.0, speed_slow = 0.15, gripper_command=gripper_command, approach_height = 0.05) #Check posture of the screw rospy.loginfo("Begin check motion") over_bin_3_joint_pose = [0.5639523868982476, -1.2023834734104668, 2.084380077110544, -4.115980903386012, -1.350262946004677, 1.5910085738144437] self.move_joints("a_bot", over_bin_3_joint_pose, speed=.5, force_ur_script=self.use_real_robot) over_bin_3_inclined_joint_pose = [0.5646427393623301, -1.202333924982511, 2.040723585395901, -4.197616886811121, -1.3550737620026068, 1.6180429123653095] self.move_joints("a_bot", over_bin_3_inclined_joint_pose, speed=.5, force_ur_script=self.use_real_robot) #Open just a bit the gripper if(screw_size == 4): open_range = 80 elif(screw_size == 3): open_range = 60 else: rospy.logerror("Screw size is wrong") open_range = 0 rospy.loginfo("begin inner open slightly") self.precision_gripper_inner_open_slightly(open_range) rospy.loginfo("ending inner open slightly") rospy.sleep(1.0) #Close the gripper fully self.send_gripper_command(gripper= "precision_gripper_inner", command="close") rospy.sleep(1.0) #Check the motor position success_pick = True if(abs(self._motorPos - close_pos) > 25 ): rospy.loginfo("Screw was picked successfully. self._motorPos = " + str(self._motorPos)) success_pick = True else: rospy.loginfo("Did not pick screw") return False if not self.use_real_robot: rospy.loginfo("Assume success for the simulation") success_pick = True above_handover_joint_pose = [1.3983707427978516, -1.343994442616598, 2.048433780670166, -4.056087795888082, -1.9765618483172815, 1.4695862531661987] self.move_joints("a_bot", above_handover_joint_pose, speed=.3, force_ur_script=self.use_real_robot) self.go_to_named_pose("screw_handover", "a_bot", force_ur_script=self.use_real_robot) self.precision_gripper_inner_open_slightly(open_range) return True def mask_bin(self, group_name, bin_id): mask_margin = 0.0 point_top1 = geometry_msgs.msg.PointStamped() point_top1.header.frame_id = str(bin_id)+"_bottom_front_right_corner" point_top1.point = geometry_msgs.msg.Point(-mask_margin, -mask_margin, 0.0) point_top2 = geometry_msgs.msg.PointStamped() point_top2.header.frame_id = str(bin_id)+"_bottom_back_right_corner" point_top2.point = geometry_msgs.msg.Point(mask_margin, -mask_margin, 0.0) point_top3 = geometry_msgs.msg.PointStamped() point_top3.header.frame_id = str(bin_id)+"_bottom_back_left_corner" point_top3.point = geometry_msgs.msg.Point(mask_margin, mask_margin, 0.0) point_top4 = geometry_msgs.msg.PointStamped() point_top4.header.frame_id = str(bin_id)+"_bottom_front_left_corner" point_top4.point = geometry_msgs.msg.Point(-mask_margin, mask_margin, 0.0) #TODO change the fisheye from to the depth frame in casse of offset. but fisheye should e ok since the two images are aligned (depth and rgb) after the real sense node point_top1_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top1).point point_top2_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top2).point point_top3_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top3).point point_top4_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top4).point #print("point_top1_cam") #print(point_top1_cam) #print("point_top2_cam") #print(point_top2_cam) #print("point_top3_cam") #print(point_top3_cam) #print("point_top4_cam") #print(point_top4_cam) #point_test_center_cam = geometry_msgs.msg.Point(0, 0, 0.4) #print(point_test_center_cam) #TODO project the 4 points in the depth plane (which projection matrix to use from the camera) #projection matrix #554.3827128226441, 0.0, 320.5, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 1.0 # #P: [554.3827128226441, 0.0, 320.5, -38.80678989758509, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 0.0, 1.0, 0.0] #TODO take the parameters from the /camera_info topic instead point_top1_cam_np = np.array([point_top1_cam.x, point_top1_cam.y, point_top1_cam.z]) point_top2_cam_np = np.array([point_top2_cam.x, point_top2_cam.y, point_top2_cam.z]) point_top3_cam_np = np.array([point_top3_cam.x, point_top3_cam.y, point_top3_cam.z]) point_top4_cam_np = np.array([point_top4_cam.x, point_top4_cam.y, point_top4_cam.z]) #used to test the projection #point_test_center_cam_np = np.array([point_test_center_cam.x, point_test_center_cam.y, point_test_center_cam.z]) #need the camera parameter of the phoxy point_top1_img_np = self.cameraPhoxiMatK.dot(point_top1_cam_np) point_top2_img_np = self.cameraPhoxiMatK.dot(point_top2_cam_np) point_top3_img_np = self.cameraPhoxiMatK.dot(point_top3_cam_np) point_top4_img_np = self.cameraPhoxiMatK.dot(point_top4_cam_np) #point_test_center_img_np = self.cameraMatK.dot(point_test_center_cam_np) #print(point_top1_img_np) #print(point_top2_img_np) #print(point_top3_img_np) #print(point_top4_img_np) #print(point_test_center_img_np) in_polygon = Polygon() in_polygon.points = [Point32(point_top1_img_np[0]/point_top1_img_np[2],point_top1_img_np[1]/point_top1_img_np[2],0), Point32(point_top2_img_np[0]/point_top2_img_np[2],point_top2_img_np[1]/point_top2_img_np[2],0), Point32(point_top3_img_np[0]/point_top3_img_np[2],point_top3_img_np[1]/point_top3_img_np[2],0), Point32(point_top4_img_np[0]/point_top4_img_np[2],point_top4_img_np[1]/point_top4_img_np[2],0)] polygon = [ (in_polygon.points[0].x,in_polygon.points[0].y), (in_polygon.points[1].x,in_polygon.points[1].y), (in_polygon.points[2].x,in_polygon.points[2].y), (in_polygon.points[3].x,in_polygon.points[3].y)] mask_img = ImagePIL.new('L', (2064,1544), 0) ImageDrawPIL.Draw(mask_img).polygon(polygon, outline = 1, fill = 255) mask_image_np = np.array(mask_img) namefile = "mask_phoxi_"+str(bin_id)+".png" mask_img.save(namefile,'PNG') def view_bin(self, group_name, bin_id, part_id, speed_fast = 1.0, speed_slow = 1.0, bin_eff_height = 0.2, bin_eff_xoff = 0, bin_eff_deg_angle = 20,end_effector_link = ""): # TODO: adjust the x,z and end effector orientatio for optimal view of the bin to use with the \search_grasp service goal_pose = geometry_msgs.msg.PoseStamped() goal_pose.header.frame_id = bin_id goal_pose.pose.position.x = bin_eff_xoff - .1 goal_pose.pose.position.y = -.05 goal_pose.pose.position.z = bin_eff_height - .1 goal_pose.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2, 0)) res = self.move_lin(group_name, goal_pose, speed_slow, end_effector_link="") if not res: rospy.loginfo("Couldn't go to the target.") #TODO Problem with gazebo controller while controlling the robot with movelin return False #TODO Ensure that the the motion is finished before generating the mask. #TODO not sure if the sleep is necessary is move_lin wait for the motion to be finished? rospy.sleep(2) mask_margin = 0.0 point_top1 = geometry_msgs.msg.PointStamped() point_top1.header.frame_id = str(bin_id)+"_bottom_front_right_corner" point_top1.point = geometry_msgs.msg.Point(-mask_margin, -mask_margin, 0.0) point_top2 = geometry_msgs.msg.PointStamped() point_top2.header.frame_id = str(bin_id)+"_bottom_back_right_corner" point_top2.point = geometry_msgs.msg.Point(mask_margin, -mask_margin, 0.0) point_top3 = geometry_msgs.msg.PointStamped() point_top3.header.frame_id = str(bin_id)+"_bottom_back_left_corner" point_top3.point = geometry_msgs.msg.Point(mask_margin, mask_margin, 0.0) point_top4 = geometry_msgs.msg.PointStamped() point_top4.header.frame_id = str(bin_id)+"_bottom_front_left_corner" point_top4.point = geometry_msgs.msg.Point(-mask_margin, mask_margin, 0.0) #TODO change the fisheye from to the depth frame in casse of offset. but fisheye should e ok since the two images are aligned (depth and rgb) after the real sense node point_top1_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top1).point point_top2_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top2).point point_top3_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top3).point point_top4_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top4).point #point_test_center_cam = geometry_msgs.msg.Point(0, 0, 0.4) #print(point_test_center_cam) #TODO project the 4 points in the depth plane (which projection matrix to use from the camera) #projection matrix #554.3827128226441, 0.0, 320.5, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 1.0 # #P: [554.3827128226441, 0.0, 320.5, -38.80678989758509, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 0.0, 1.0, 0.0] #TODO take the parameters from the /camera_info topic instead point_top1_cam_np = np.array([point_top1_cam.x, point_top1_cam.y, point_top1_cam.z]) point_top2_cam_np = np.array([point_top2_cam.x, point_top2_cam.y, point_top2_cam.z]) point_top3_cam_np = np.array([point_top3_cam.x, point_top3_cam.y, point_top3_cam.z]) point_top4_cam_np = np.array([point_top4_cam.x, point_top4_cam.y, point_top4_cam.z]) #used to test the projection #point_test_center_cam_np = np.array([point_test_center_cam.x, point_test_center_cam.y, point_test_center_cam.z]) point_top1_img_np = self.cameraMatK.dot(point_top1_cam_np) point_top2_img_np = self.cameraMatK.dot(point_top2_cam_np) point_top3_img_np = self.cameraMatK.dot(point_top3_cam_np) point_top4_img_np = self.cameraMatK.dot(point_top4_cam_np) #point_test_center_img_np = self.cameraMatK.dot(point_test_center_cam_np) mask_polygon = Polygon() mask_polygon.points = [Point32(point_top1_img_np[0]/point_top1_img_np[2],point_top1_img_np[1]/point_top1_img_np[2],0), Point32(point_top2_img_np[0]/point_top2_img_np[2],point_top2_img_np[1]/point_top2_img_np[2],0), Point32(point_top3_img_np[0]/point_top3_img_np[2],point_top3_img_np[1]/point_top3_img_np[2],0), Point32(point_top4_img_np[0]/point_top4_img_np[2],point_top4_img_np[1]/point_top4_img_np[2],0)] goal = o2as_msgs.msg.blobDetectionGoal() goal.maskCorner = mask_polygon goal.param_part_id = "part_" + str(part_id) self.blob_detection_client.send_goal(goal) self.blob_detection_client.wait_for_result() result = self.blob_detection_client.get_result() #rospy.loginfo(result) #TODO select which poses to choose in the array if result: poseArrayRes = geometry_msgs.msg.PoseArray() #TODO Sort pose in the midle of the bin #min x min y in the bin frame if(result.success): poseArrayRes = result.posesDetected distanceToBinCenter = [] for i in range(len(poseArrayRes.poses)): pointCam = geometry_msgs.msg.PointStamped() #simulation only poseArrayRes.header.frame_id = "a_bot_camera_calibrated_frame_link" pointCam.header = poseArrayRes.header pointCam.point = poseArrayRes.poses[i].position pointBin = self.listener.transformPoint(bin_id, pointCam).point distanceToBinCenter.append(math.sqrt(pointBin.xpointBin.x + pointBin.ypointBin.y)) minPoseIndex = np.argmin(distanceToBinCenter) rospy.loginfo("point closest to the bin center in the xy plane") rospy.loginfo(poseArrayRes.poses[minPoseIndex]) #Transform point from camera reference to bin reference pointPartCam = geometry_msgs.msg.PointStamped() pointPartCam.header = poseArrayRes.header pointPartCam.point = poseArrayRes.poses[minPoseIndex].position pointPartBin = self.listener.transformPoint(bin_id, pointPartCam) rospy.loginfo("Pose in bin") rospy.loginfo(pointPartBin) #Transform point from camera reference to bin reference goal_part = geometry_msgs.msg.PoseStamped() goal_part.header.frame_id = pointPartBin.header.frame_id goal_part.pose.position.x = pointPartBin.point.x goal_part.pose.position.y = pointPartBin.point.y goal_part.pose.position.z = pointPartBin.point.z goal_part.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2 , 0)) self.current_img_w_blob = copy.deepcopy(result.blobImage) self.draw_point3D_after_view_bin(pointPartCam) return goal_part else: rospy.loginfo("no pose detected") #TODO if nothing is detected move the camera a bit to try to detect somethin return False def draw_point3D_after_view_bin(self, pointPartCam): ### Project the goal on the image plane using the camera matrix like for the mask #Transform Point in camera reference point3D_to_draw = geometry_msgs.msg.PointStamped() point3D_to_draw = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", pointPartCam) #Copy the results # Project the point to the camera plane pointPart_cam_np = np.array([point3D_to_draw.point.x, point3D_to_draw.point.y, point3D_to_draw.point.z]) pointPart_img_np = self.cameraMatK.dot(pointPart_cam_np) #Transfom into pixel coordinate pointPart_pix= pointCam = geometry_msgs.msg.Point(pointPart_img_np[0]/pointPart_img_np[2],pointPart_img_np[1]/pointPart_img_np[2],0) img_blob_cv = self.bridge.imgmsg_to_cv2(self.current_img_w_blob , desired_encoding="passthrough") #img_blob_cv_np = np.asarray(img_blob_cv)[:, :, ::-1] #Draw the circle in orange for the propose pose cv2.circle(img_blob_cv,(int(pointPart_pix.x),int(pointPart_pix.y)), 3, (0,255,0), 4) self.current_img_w_goal = self.bridge.cv2_to_imgmsg(img_blob_cv, "rgb8") #publish the results try: print("publish") self.img_inner_pick_pub.publish(self.current_img_w_goal) except CvBridgeError as e: print(e) def place_screw_in_tray(self, screw_size, set_number, hole_number): """ Places a screw in a tray. A screw needs to be carried by the screw tool! """ # Use this command to equip the screw tool: do_change_tool_action(self, "c_bot", equip=True, screw_size = 4) if not screw_size==3 and not screw_size==4: rospy.logerr("Screw size needs to be 3 or 4!") return False # Turn to the right to face the feeders self.go_to_named_pose("feeder_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) pose_tray = geometry_msgs.msg.PoseStamped() pose_tray.header.frame_id = "set_" + str(set_number) + "_tray_2_screw_m" + str(screw_size) + "_" + str(hole_number) if set_number == 1: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(pi/2, 0, 0)) pose_tray.pose.position.x = -.01 elif set_number == 2: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(pi/4, 0, 0)) pose_tray.pose.position.x = -.005 elif set_number == 3: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, 0, 0)) pose_tray.pose.position.x = -.005 if screw_size == 3: pose_tray.pose.position.x += .005 success = self.do_place_action("c_bot", pose_tray, tool_name = "screw_tool", screw_size=screw_size) if not success: return False self.go_to_named_pose("feeder_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) return True ################ ----- Demos ################ ################ def pick_screw_from_bin_and_put_into_feeder(self, item, max_attempts = 5): robot_name = "a_bot" end_effector_link = "a_bot_precision_gripper_tip_link" if item.part_id == 17: screw_size = 4 elif item.part_id == 18: screw_size = 3 attempts = 0 while attempts < max_attempts: attempts += 1 item.attempts += 1 rospy.loginfo("Attempting to pick screw. Item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Attempt nr. " + str(item.attempts)) # Attempt to pick the item pick_pose = self.get_random_pose_in_bin(item) if not item.bin_is_inclined: pick_pose.pose.orientation = self.downward_orientation_2 if item.part_id == 18: #M3 pick_pose.pose.position.z = .005 # MAGIC NUMBER! Depends on the amount of screws in the bin! if item.part_id == 17: #M4 pick_pose.pose.position.z = .00 # MAGIC NUMBER! Depends on the amount of screws in the bin! gripper_command = "inner_gripper_from_outside" self.pick(robot_name, pick_pose, 0.0, speed_fast = 1.0, speed_slow = 0.3, gripper_command=gripper_command, approach_height = 0.04) screw_picked = self.check_pick(item.part_id) if not screw_picked and self.use_real_robot: rospy.logerr("Failed an attempt to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Reattempting. Current attempts: " + str(attempts)) continue self.put_screw_in_feeder(screw_size) item.in_feeder = True rospy.loginfo("Delivered screw m" + str(screw_size) + " to feeder (item nr." + str(item.number_in_set) + " from set " + str(item.set_number)) return True return False def get_random_pose_in_bin(self, item): pick_pose = geometry_msgs.msg.PoseStamped() pick_pose.header.frame_id = item.bin_name if "bin1" in item.bin_name: bin_length = self.bin_1_width bin_width = self.bin_1_length elif "bin2" in item.bin_name: bin_length = self.bin_2_width bin_width = self.bin_2_length elif "bin3" in item.bin_name: bin_length = self.bin_3_width bin_width = self.bin_3_length pick_pose.pose.position.x += -bin_length/2 + random.random()bin_length pick_pose.pose.orientation = self.downward_orientation_2 if item.bin_is_inclined: rospy.loginfo("Applying position for inclined bin") if "bin1" in item.bin_name: if item.bin_is_inclined == "left": pick_pose.pose.position.y = -.035 elif item.bin_is_inclined == "right": pick_pose.pose.position.y = .035 else: # Does not work because the width values are not strictly true (but safe for the regular random pick) pick_pose.pose.position.y = bin_width/2-.01 pick_pose.pose.position.z = .01 if "precision_gripper" in item.ee_to_use: pick_pose.pose.position.z = self.precision_gripper_pick_heights["part_"+str(item.part_id)] if item.part_id in [9, 16, 17,18]: pick_pose.pose.orientation = geometry_msgs.msg.Quaternion(tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/2)) if item.part_id in [16, 17,18]: pick_pose.pose.position.z = 0.0 if item.part_id in [9]: pick_pose.pose.position.y += .005random.random() pick_pose.pose.position.z = 0.005 rospy.loginfo(pick_pose.pose) else: pick_pose.pose.position.y += -bin_width/2 + random.random()bin_width return pick_pose def get_grasp_candidates_from_phoxi(self, item, take_new_image=False): """This requests a list of grasp positions and takes a new image with the phoxi if take_new_image is True.""" goal = o2as_msgs.msg.SearchGraspPhoxiGoal() goal.part_id = item.part_id goal.bin_name = item.bin_name goal.gripper_type = item.ee_to_use goal.update_image = take_new_image try: self.search_grasp_client.send_goal(goal) self.search_grasp_client.wait_for_result(rospy.Duration(7.0)) resp_search_grasp = self.search_grasp_client.get_result() except: rospy.logerr("Could not get grasp from Phoxi") return False if resp_search_grasp: if resp_search_grasp.success: poses_in_bin = list() pose0 = geometry_msgs.msg.PointStamped() pose0.header.frame_id = "a_phoxi_m_sensor" number_of_pose_candidates = min(self.max_candidates_from_phoxi, resp_search_grasp.result_num) for i in range(number_of_pose_candidates): object_position = copy.deepcopy(pose0) object_position.point = geometry_msgs.msg.Point( resp_search_grasp.pos3D[i].x, resp_search_grasp.pos3D[i].y, resp_search_grasp.pos3D[i].z) # TODO We should talk about how to use rotiqz which the two_finger approaches. rospy.logdebug("\nGrasp point in %s: (x, y, z) = (%f, %f, %f)", object_position.header.frame_id, object_position.point.x, object_position.point.y, object_position.point.z) obj_pose_in_camera = geometry_msgs.msg.PoseStamped() obj_pose_in_camera.header = object_position.header obj_pose_in_camera.pose.position = object_position.point obj_pose_in_camera.pose.orientation.w = 1.0 # pose_in_bin = geometry_msgs.msg.PoseStamped() # pose_in_bin.header.frame_id = item.bin_name pose_in_bin = self.listener.transformPose(item.bin_name, obj_pose_in_camera) pose_in_bin.pose.orientation = self.downward_orientation if item.ee_to_use in ["precision_gripper_from_outside", "robotiq_gripper"]: pose_in_bin.pose.orientation = geometry_msgs.msg.Quaternion( tf_conversions.transformations.quaternion_from_euler(0, pi/2, -resp_search_grasp.rotipz[i])) poses_in_bin.append(pose_in_bin) self.publish_marker(pose_in_bin, "aist_vision_result") rospy.loginfo("Calculated " + str(number_of_pose_candidates) + " candidates for item nr. " + str(item.part_id) + " in bin " + str(item.bin_name)) rospy.logdebug(poses_in_bin) return poses_in_bin else: rospy.loginfo("Could not find a pose via phoxi.") return False def treat_screws_in_feeders(self): """ Picks the screws when they have been in the feeder long enough """ self.screws_in_feeder = dict() self.screws_done["m4"] = True self.screws_done["m3"] = True self.screws_in_feeder["m3"] = False self.screws_in_feeder["m4"] = False for item in self.ordered_items: if not item.fulfilled: if item.part_id == 17: screw_size = 4 elif item.part_id == 18: screw_size = 3 else: continue rospy.loginfo("Found an undelivered screw in the order: item nr. " + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")") self.screws_done["m"+str(screw_size)] = False if item.in_feeder: self.screws_in_feeder["m"+str(screw_size)] = True if (not self.screws_done["m4"] and self.screws_in_feeder["m4"]) or (not self.screws_done["m3"] and self.screws_in_feeder["m3"]): if not self.screws_in_feeder["m4"] and not self.screws_in_feeder["m3"]: rospy.loginfo("No screws are in the feeders. Skipping.") return if (rospy.Time.now() - self.screw_delivery_time) > rospy.Duration(1): #180 self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("suction_ready_back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) for screw_size in [4,3]: if rospy.is_shutdown(): return if not self.screws_done["m"+str(screw_size)]: rospy.loginfo("=== Picking m" + str(screw_size) + " screws from feeder") self.go_to_named_pose("tool_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.do_change_tool_action("c_bot", equip=True, screw_size=screw_size) for item in self.screws["m"+str(screw_size)]: if rospy.is_shutdown(): return if item.in_feeder: if self.pick_screw_from_feeder(screw_size, attempts=2): self.place_screw_in_tray(screw_size, item.set_number, self.screws_placed["m"+str(screw_size)][item.set_number]+1) self.screws_placed["m"+str(screw_size)][item.set_number] += 1 self.fulfilled_items += 1 item.in_feeder = False item.fulfilled = True else: rospy.loginfo("Failed to pick an m" + str(screw_size) + " screw from the feeder") break if rospy.is_shutdown(): return self.go_to_named_pose("tool_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.do_change_tool_action("c_bot", equip=False, screw_size=screw_size) self.go_to_named_pose("back", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if self.screws_done["m4"] and self.screws_done["m3"]: self.set_feeder_power(False) return def make_pose_safe_for_bin(self, pick_pose, item): """ This makes sure that the pick_pose is not outside the bin or would cause a collision.""" if "bin1" in item.bin_name: bin_length = self.bin_1_width bin_width = self.bin_1_length elif "bin2" in item.bin_name: bin_length = self.bin_2_width bin_width = self.bin_2_length elif "bin3" in item.bin_name: bin_length = self.bin_3_width bin_width = self.bin_3_length safe_pose = copy.deepcopy(pick_pose) safe_pose.pose.position.x = clamp(pick_pose.pose.position.x, -bin_length/2 - .02, bin_length/2 - .02) safe_pose.pose.position.y = clamp(pick_pose.pose.position.y, -bin_width/2 - .02, bin_width/2 - .02) safe_pose.pose.position.z = clamp(pick_pose.pose.position.z, 0, 0.1) if safe_pose.pose.position.x != pick_pose.pose.position.x or safe_pose.pose.position.y != pick_pose.pose.position.y: rospy.loginfo("Pose was adjusted in make_pose_safe_for_bin. Before: " + str(pick_pose.pose.position.x) + ", " + str(pick_pose.pose.position.y) + ", " + str(pick_pose.pose.position.z) + ". After: " + str(safe_pose.pose.position.x) + ", " + str(safe_pose.pose.position.y) + ", " + str(safe_pose.pose.position.z) + ".") #TODO: Adjust the gripper orientation when close to the border return safe_pose def attempt_item(self, item, max_attempts = 5): """This function attempts to pick an item. It increases the item.attempts counter each time it does, and sets item.fulfilled to True if item is delivered.""" if "precision_gripper" in item.ee_to_use: robot_name = "a_bot" elif "robotiq_gripper" in item.ee_to_use: robot_name = "b_bot" elif item.ee_to_use == "suction": robot_name = "b_bot" if item.fulfilled: rospy.logerr("This item is already fulfilled. Something is going wrong.") return False take_new_image = False if not self.initial_phoxi_image_recorded: self.initial_phoxi_image_recorded = True take_new_image = True ### Vision is skipped # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # if self.grasp_candidates[item.part_id]["pick_was_successful"]: # # If the pick was successful for an item, the scene has changed, so a new image needs to be taken # rospy.loginfo("Resetting grasp candidates for item " + str(item.part_id)) # self.grasp_candidates[item.part_id]["pick_was_successful"] = False # self.grasp_candidates[item.part_id]["vision_was_attempted"] = False # self.grasp_candidates[item.part_id]["positions"] = [] # take_new_image = True # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # self.go_to_named_pose("suction_ready_back", "b_bot") # elif "precision_gripper" in item.ee_to_use: # self.go_to_named_pose("taskboard_intermediate_pose", "a_bot") # if not self.grasp_candidates[item.part_id]["vision_was_attempted"]: # # Vision is only attempted once, unless it succeeds in picking # phoxi_res = self.get_grasp_candidates_from_phoxi(item, take_new_image) # # self.grasp_candidates[item.part_id]["vision_was_attempted"] = True # #### Line above is uncommented to force new vision result every time # take_new_image = False # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # self.go_to_named_pose("suction_pick_ready", "b_bot") # elif "precision_gripper" in item.ee_to_use: # self.go_to_named_pose("kitting_pick_ready", "a_bot") # if phoxi_res: # self.grasp_candidates[item.part_id]["positions"].extend(phoxi_res) # rospy.loginfo("self.grasp_candidates: ") # rospy.loginfo(self.grasp_candidates[item.part_id]["positions"][0]) # Go to preparatory pose if item.ee_to_use == "suction": rospy.loginfo("Going to preparatory pose before picking from bins") bin_center = geometry_msgs.msg.PoseStamped() bin_center.header.frame_id = item.bin_name bin_center.pose.orientation.w = 1.0 bin_center_on_table = self.listener.transformPose("workspace_center", bin_center).pose.position if bin_center_on_table.y > .1: self.go_to_named_pose("suction_ready_right_bins", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) else: self.go_to_named_pose("suction_ready_left_bins", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) elif "precision_gripper" in item.ee_to_use: self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) elif "robotiq_gripper" in item.ee_to_use: self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) attempts = 0 grasp_candidate_came_from_realsense = False grasp_candidate_from_vision = False while attempts < max_attempts and not rospy.is_shutdown(): attempts += 1 item.attempts += 1 rospy.loginfo("=== Attempting item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Attempt nr. " + str(item.attempts)) # Get the pick_pose for the item, either random or from vision pick_pose = self.get_random_pose_in_bin(item) grasp_candidate_from_vision = False ### Realsense vision result is skipped if item.ee_to_use == "precision_gripper_from_inside" and not item.bin_is_inclined and not item.part_id in [17, 18]: pick_pose.pose.position.z = self.precision_gripper_pick_heights["part_" + str(item.part_id)] rospy.loginfo("Assigned pick height: " + str(pick_pose.pose.position.z)) # res_view_bin = self.view_bin(robot_name, item.bin_name, item.part_id) # grasp_candidate_came_from_realsense = True # if res_view_bin: # pick_pose = res_view_bin # pick_pose.pose.position.z -= .025 # MAGIC NUMBER (to compensate for the Realsense calibration) if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # for test run: if grasp_candidates is 0, item picking is skipped. while self.grasp_candidates[item.part_id]["positions"]: pick_pose = self.grasp_candidates[item.part_id]["positions"].pop(0) rospy.logwarn("ADDING A MAGIC ADJUSTMENT TO THE PHOXI RESULT") pick_pose.pose.position.y += -.002 if pick_pose.pose.position.z <= 0.005 and item.ee_to_use == "suction": rospy.loginfo("Discarded a grasp candidate:") rospy.loginfo(pick_pose.pose.position) pick_pose = self.get_random_pose_in_bin(item) # Reset to a random pose if the grasp candidate was bad continue # pick_pose.pose.position.z -= self.insert_offsets["part_"+str(item.part_id)] rospy.loginfo("Got pose from phoxi grasp candidates:") rospy.loginfo(pick_pose.pose.position) grasp_candidate_from_vision = True if item.ee_to_use == "robotiq_gripper": self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if item.ee_to_use == "suction": # Orientation needs to be adjusted for suction tool bin_center = geometry_msgs.msg.PoseStamped() bin_center.header.frame_id = item.bin_name bin_center.pose.orientation.w = 1.0 bin_center_on_table = self.listener.transformPose("workspace_center", bin_center).pose.position if bin_center_on_table.y > .1: pick_pose.pose.orientation = self.suction_orientation_right_bins else: pick_pose.pose.orientation = self.suction_orientation_left_bins else: # Precision_gripper, robotiq_gripper if not item.bin_is_inclined: pick_pose.pose.orientation = self.downward_orientation_2 if item.part_id == 6: # Belt pick_pose.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/2)) approach_height = 0.1 speed_slow = 0.1 speed_fast = 1.0 if item.ee_to_use == "precision_gripper_from_inside": gripper_command = "inner_gripper_from_inside" approach_height = .05 elif item.ee_to_use == "precision_gripper_from_outside": gripper_command = "inner_gripper_from_outside" approach_height = .05 elif item.ee_to_use == "suction": gripper_command = "suction" approach_height = 0.1 - pick_pose.pose.position.z speed_slow = 0.05 speed_fast = 1.0 elif item.ee_to_use == "robotiq_gripper": approach_height = .15 speed_slow = .2 gripper_command = "" else: gripper_command = "" pick_pose = self.make_pose_safe_for_bin(pick_pose, item) if grasp_candidate_from_vision: self.log_to_debug_monitor("Picking pose result from vision", "subtask") elif grasp_candidate_came_from_realsense: self.log_to_debug_monitor("Picking pose result from realsense", "subtask") else: self.log_to_debug_monitor("Picking random pose", "subtask") if "precision_gripper" in item.ee_to_use: pose_above_bin = copy.deepcopy(pick_pose) pose_above_bin.pose.position.z += .15 self.go_to_pose_goal("a_bot", pose_above_bin, speed=speed_fast, move_lin=True) item_picked = self.pick(robot_name, pick_pose, 0.0, speed_fast = speed_fast, speed_slow = .05, gripper_command=gripper_command, approach_height = approach_height) if not self.use_real_robot: item_picked = True if item_picked and grasp_candidate_from_vision: self.grasp_candidates[item.part_id]["pick_was_successful"] = True # TODO: Check grasp success via grasp width for robotiq gripper and vision for precision gripper if "precision_gripper" in item.ee_to_use: item_picked = self.check_pick(item.part_id) # Suction is checked inside the pick function if not item_picked: rospy.logerr("Failed an attempt to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Reattempting. Current attempts: " + str(attempts)) if item.ee_to_use == "suction": self.suck(False) continue # Attempt to place the item place_pose = geometry_msgs.msg.PoseStamped() place_pose.header.frame_id = item.target_frame required_intermediate_pose = [] if item.ee_to_use == "suction": # This is inconvenient to set up because the trays are rotated. tray_2s are rotated 180 degrees relative to set_1_tray_1 # SUCTION_PREP_POSES place_pose.pose.orientation, required_intermediate_pose = self.get_tray_placement_orientation_for_suction_in_kitting( set_number=item.set_number, tray_number=int(place_pose.header.frame_id[11])) if not place_pose.pose.orientation.w and not place_pose.pose.orientation.x and not place_pose.pose.orientation.y: rospy.logerr("SOMETHING WENT WRONG, ORIENTATION IS NOT ASSIGNED") else: # Precision_gripper, robotiq_gripper place_pose.pose.orientation = self.downward_orientation approach_height = .05 if "precision_gripper" in item.ee_to_use: self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=1.5, acceleration=1.0, force_ur_script=self.use_real_robot) approach_height = .03 elif item.ee_to_use == "suction": if required_intermediate_pose: rospy.loginfo("Going to intermediate pose") self.go_to_named_pose(required_intermediate_pose, "b_bot", speed=1.5, acceleration=1.0, force_ur_script=self.use_real_robot) # Approach the place pose with controllrighacceleration value rospy.loginfo("Approaching place pose") if item.set_number in [2,3] and item.target_frame[11] == '1': # Tray 1 self.go_to_named_pose("suction_ready_left_bins", "b_bot", speed=.1) self.go_to_named_pose("suction_place_intermediate_pose_for_sets_2_and_3", "b_bot", speed=.1) self.force_moveit_linear_motion = True place_pose.pose.position.z += .08 self.move_lin(robot_name, place_pose, speed = 0.3, acceleration = 0.08, end_effector_link = "b_bot_suction_tool_tip_link") place_pose.pose.position.z -= .08 if item.part_id == 6: if pick_pose.pose.position.x > 0: place_pose.pose.position.y = -0.06 else: place_pose.pose.position.y = 0.06 self.place(robot_name, place_pose,grasp_height=item.dropoff_height, speed_fast = 0.5, speed_slow = 0.02, gripper_command=gripper_command, approach_height = approach_height) if item.ee_to_use == "suction": self.force_moveit_linear_motion = False # If successful self.fulfilled_items += 1 item.fulfilled = True rospy.loginfo("Delivered item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")! Total items delivered: " + str(self.fulfilled_items)) return True rospy.logerr("Was not able to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")! Total attempts: " + str(item.attempts)) # TODO: Move up safely if not successful # self.move_lin(robot_name, place_pose, speed = 0.3, acceleration = 0.08, end_effector_link = "b_bot_suction_tool_tip_link") return False def kitting_task(self): # Strategy: # - Start with suction tool + m4 tool equipped # - Pick all the screws in the current set and put them in the feeders, so they will be ready to be picked # - Go through all items that require suction, so the tool is equipped only once does not have to be re-equipped # - Go through items that are picked by the a_bot or b_bot grippers # - When the screws are ready, pick and place them # - Try to pick and return any excess screws # Ideally, we can fit all the trays into the scene. self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("back", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("suction_ready_back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) start_time = rospy.Time.now() self.start_task_timer() self.log_to_debug_monitor(text="Kitting", category="task") time_limit = rospy.Duration(1140) # 19 minutes self.fulfilled_items = 0 self.screws_done = dict() self.screws_placed = dict() self.screws_done["m4"] = (len(self.screws["m4"]) == 0) self.screws_done["m3"] = (len(self.screws["m3"]) == 0) self.screws_placed["m4"] = {1:0, 2:0, 3:0} self.screws_placed["m3"] = {1:0, 2:0, 3:0} # ==== 1. First, do an initial attempt on picking all items, ordered by the tool that they are picked with (screws, suction, precision_gripper, robotiq) # self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # for item in self.screw_items: # self.log_to_debug_monitor("Pick screw no. " + str(item.part_id) + " and put into feeder", "subtask") # if rospy.is_shutdown(): # break # # item.in_feeder = True # Used to skip the screws and enable the feeder pickup # self.pick_screw_from_bin_and_put_into_feeder(item, 10) # self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # rospy.loginfo("==== Done with screw pickup pass") self.screw_delivery_time = rospy.Time.now() # rospy.sleep(2) self.treat_screws_in_feeders() for item in self.suction_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.treat_screws_in_feeders() self.attempt_item(item, 3) # self.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool self.go_to_named_pose("suction_ready_back", "b_bot") rospy.loginfo("==== Done with first suction pass") for item in self.precision_gripper_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.attempt_item(item, 3) self.go_to_named_pose("back", "a_bot") rospy.loginfo("==== Done with first precision gripper pass") self.treat_screws_in_feeders() self.treat_screws_in_feeders() # for item in self.robotiq_gripper_items: # self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") # self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # if rospy.is_shutdown(): # break # self.attempt_item(item, 3) # self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() # ==== 2. Second, loop through all the items that were not successfully picked on first try, and place the screws when they are assumed to be ready. all_done = False # while False: while not all_done and not rospy.is_shutdown(): rospy.loginfo("Entering the loop to recover failed items and pick screws") # Check all items, find which groups are done, then reattempt those that are unfinished all_done = True suction_done = True precision_gripper_done = True robotiq_gripper_done = True self.screws_done["m4"] = True self.screws_done["m3"] = True for item in self.ordered_items: if not item.fulfilled: rospy.loginfo("Found an undelivered item in the order: item nr. " + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")") all_done = False if "precision_gripper" in item.ee_to_use: precision_gripper_done = False elif "robotiq_gripper" in item.ee_to_use: robotiq_gripper_done = False elif item.ee_to_use == "suction": suction_done = False if item.part_id == 17: self.screws_done["m4"] = False elif item.part_id == 18: self.screws_done["m3"] = False self.treat_screws_in_feeders() if not precision_gripper_done: rospy.loginfo("Reattempting the remaining precision gripper items") self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) for item in self.precision_gripper_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.attempt_item(item) self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() # if not robotiq_gripper_done: # rospy.loginfo("Reattempting the remaining robotiq gripper items") # self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # for item in self.robotiq_gripper_items: # self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") # if rospy.is_shutdown(): # break # self.attempt_item(item) # self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() if not suction_done: self.reset_grasp_candidates() rospy.loginfo("Reattempting the remaining suction items") # self.do_change_tool_action("b_bot", equip=True, screw_size=50) # 50 = suction tool for item in self.suction_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break if not item.fulfilled: self.go_to_named_pose("suction_pick_ready", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.attempt_item(item, 5) # self.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if (rospy.Time.now()-start_time) > time_limit: rospy.logerr("Time limit reached! Breaking out of the loop.") break if all_done: rospy.loginfo("Completed the task.") else: rospy.loginfo("STOPPED THE TASK") return if __name__ == '__main__': try: kit = KittingClass() i = 1 while i: rospy.loginfo("Enter 1 to equip suction tool.") rospy.loginfo("Enter 11 to unequip suction tool.") rospy.loginfo("Enter 2 to move the robots home to starting positions.") rospy.loginfo("Enter 3 to suction attachment test with b_bot using suction tool.") rospy.loginfo("Enter 60 to pick screw from bin with a_bot.") rospy.loginfo("Enter 61 to hand over screw from a_bot to c_bot.") rospy.loginfo("Enter 62 to move robots back.") rospy.loginfo("Enter 71, 72... to test phoxi on item 1, 2...") rospy.loginfo("Enter 81, 82... to move b_bot suction to trays...") rospy.loginfo("Enter 90 to move a_bot to kitting_pick_ready.") rospy.loginfo("Enter 91, 92... to do view_bin on bin1_1, bin1_2...") rospy.loginfo("Enter START to start the task.") rospy.loginfo("Enter x to exit.") i = raw_input() if i == '1': kit.do_change_tool_action("b_bot", equip=True, screw_size=50) # 50 = suction tool if i == '11': kit.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool if i == '2': kit.go_to_named_pose("back", "a_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("back", "c_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("suction_ready_back", "b_bot", force_ur_script=kit.use_real_robot) elif i == 'START' or i == 'start' or i == '5000': kit.kitting_task() elif i == "60": kit.go_to_named_pose("home", "a_bot", force_ur_script=kit.use_real_robot) kit.pick_screw_with_precision_gripper(kit.part_bin_list["part_17"], screw_size= 4) elif i == "61": kit.pick_screw_from_precision_gripper(screw_size=4) elif i == "62": kit.go_to_named_pose("screw_ready", "c_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("back", "a_bot", force_ur_script=kit.use_real_robot) elif i in ["71", "72", "73", "74", "75", "76", "77", "78", "79"]: item = kit.ordered_items[int(i)-71] rospy.loginfo("Checking for item id " + str(item.part_id) + " in " + item.bin_name) obj_pose = kit.get_grasp_candidates_from_phoxi(item, True) elif i == "80": kit.go_to_named_pose("suction_pick_ready", "b_bot", force_ur_script=kit.use_real_robot) elif i in ["81", "82", "83", "84"]: place_pose = geometry_msgs.msg.PoseStamped() if i == "81": place_pose.header.frame_id = "set_1_tray_2_partition_4" elif i == "82": place_pose.header.frame_id = "set_2_tray_2_partition_4" elif i == "83": place_pose.header.frame_id = "set_3_tray_2_partition_4" elif i == "84": place_pose.header.frame_id = "set_1_tray_1_partition_3" # SUCTION_PREP_POSES place_pose.pose.orientation = kit.get_tray_placement_orientation_for_suction_in_kitting( set_number=int(place_pose.header.frame_id[4]), tray_number=int(place_pose.header.frame_id[11])) kit.go_to_named_pose("back", "c_bot") kit.go_to_named_pose("back", "b_bot") kit.go_to_named_pose("screw_ready", robot_name) place_pose.pose.position.z = .08 kit.move_lin("b_bot", place_pose, .1, end_effector_link="b_bot_suction_tool_tip_link") elif i == "90": kit.go_to_named_pose("kitting_pick_ready", "a_bot", force_ur_script=kit.use_real_robot) elif i in ["91", "92", "93", "94", "95"]: if i == "91": part_id = 16 elif i == "92": part_id = 9 elif i == "93": part_id = 15 elif i == "94": part_id = 17 elif i == "95": part_id = 18 kit.view_bin("a_bot", "bin1_" + i[1], part_id) elif i == "x": break print "============ Done!" except rospy.ROSInterruptException: pass	[ 1, 18787, 4855, 29914, 2109, 29914, 6272, 3017, 13, 13, 5215, 10876, 13, 5215, 3509, 13, 5215, 696, 1028, 29891, 13, 5215, 16303, 29918, 1516, 3174, 29889, 7645, 13, 5215, 15886, 29918, 535, 26100, 13, 5215, 15886, 13, 3166, 5844, 1053, 2930, 13, 5215, 12655, 408, 7442, 13, 3166, 16250, 1053, 4257, 23583, 13, 13, 3166, 288, 29906, 294, 29918, 1516, 3174, 29889, 29879, 15291, 1053, 334, 13, 5215, 3158, 1982, 13, 3166, 288, 29906, 294, 29918, 1516, 3174, 29889, 7645, 1053, 334, 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example.py	duanyytop/ckb-sdk-python	1	55675	<gh_stars>1-10 from ckb_toolkit.core.signer import sign_tx from ckb_toolkit.core.rpc import RPCClient from ckb_toolkit.core.hash import ckb_blake160 from ckb_toolkit.core.hex_coder import hex_to_bytes, hex_from_bytes from ckb_toolkit.address.address import generateShortAddress, generateFullAddress from coincurve import PublicKey, PrivateKey import json unsigned_raw_tx = {'version': '0x0', 'cell_deps': [{'out_point': {'tx_hash': '0xbd262c87a84c08ea3bc141700cf55c1a285009de0e22c247a8d9597b4fc491e6', 'index': '0x2'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0xd346695aa3293a84e9f985448668e9692892c959e7e83d6d8042e59c08b8cf5c', 'index': '0x0'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0x03dd2a5594ed2d79196b396c83534e050ba0ad07fa5c1cd61a7094f9fb60a592', 'index': '0x0'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0xf8de3bb47d055cdf460d93a2a6e1b05f7432f9777c8c474abf4eec1d4aee5d37', 'index': '0x0'}, 'dep_type': 'dep_group'}], 'header_deps': [ ], 'inputs': [{'previous_output': {'tx_hash': '0xad375e8c40fdf42187ecbec79f7ddcae72017ce7773a4762421f3f50722dccb0', 'index': '0x1'}, 'since': '0x0'}], 'outputs': [{'capacity': '0x31eb3c002', 'lock': {'code_hash': '0x9bd7e06f3ecf4be0f2fcd2188b23f1b9fcc88e5d4b65a8637b17723bbda3cce8', 'args': '0xed893ca482474e66b5779e57dc1d5281f9033e4f', 'hash_type': 'type'}, 'type': {'code_hash': '0xb1837b5ad01a88558731953062d1f5cb547adf89ece01e8934a9f0aeed2d959f', 'args': '0xf90f9c38b0ea0815156bbc340c910d0a21ee57cf0000003700000002', 'hash_type': 'type'}}], 'outputs_data': ['0x000000000000000000c000'], 'witnesses': ['0x']} private_key = 'd52a6cb37ce90aed79a96ea9976668fbdbe16d6eac3611d5b15de388168da2c3' public_key = PrivateKey.from_hex(private_key).public_key.format() args = ckb_blake160(public_key)[2:] address = generateShortAddress(args, network = "testnet") print(address) lock = {'code_hash': '9bd7e06f3ecf4be0f2fcd2188b23f1b9fcc88e5d4b65a8637b17723bbda3cce8', 'hash_type': 'type', 'args': args} full_address = generateFullAddress(lock, network = "testnet") print(full_address) tx = sign_tx(unsigned_raw_tx, private_key) print(tx) rpc = RPCClient('https://testnet.ckb.dev/rpc') tx_hash = rpc.request('send_transaction', tx) print(tx_hash)	[ 1, 529, 12443, 29918, 303, 1503, 29958, 29896, 29899, 29896, 29900, 13, 3166, 274, 21066, 29918, 10154, 7354, 29889, 3221, 29889, 4530, 261, 1053, 1804, 29918, 7508, 13, 3166, 274, 21066, 29918, 10154, 7354, 29889, 3221, 29889, 29878, 6739, 1053, 390, 9026, 4032, 13, 3166, 274, 21066, 29918, 10154, 7354, 29889, 3221, 29889, 8568, 1053, 274, 21066, 29918, 17530, 446, 29896, 29953, 29900, 13, 3166, 274, 21066, 29918, 10154, 7354, 29889, 3221, 29889, 20970, 29918, 29883, 6119, 1053, 15090, 29918, 517, 29918, 13193, 29892, 15090, 29918, 3166, 29918, 13193, 13, 3166, 274, 21066, 29918, 10154, 7354, 29889, 7328, 29889, 7328, 1053, 5706, 21322, 7061, 29892, 5706, 13658, 7061, 13, 3166, 19480, 2764, 345, 1053, 5236, 2558, 29892, 12230, 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src/aria/aria/reading/__init__.py	tliron/aria-ng	0	143402	# # Copyright (c) 2016 GigaSpaces Technologies Ltd. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # from .exceptions import ReaderException, ReaderNotFoundError, ReaderSyntaxError, AlreadyReadException from .reader import Reader from .source import ReaderSource, DefaultReaderSource from .context import ReadingContext from .raw import RawReader from .locator import Locator from .yaml import YamlReader from .json import JsonReader from .jinja import JinjaReader __all__ = ( 'ReaderException', 'ReaderNotFoundError', 'ReaderSyntaxError', 'AlreadyReadException', 'Reader', 'ReaderSource', 'DefaultReaderSource', 'ReadingContext', 'RawReader', 'Locator', 'YamlReader', 'JsonReader', 'JinjaReader')	[ 1, 396, 13, 29937, 14187, 1266, 313, 29883, 29897, 29871, 29906, 29900, 29896, 29953, 402, 4324, 5592, 3302, 8364, 11763, 19806, 29889, 2178, 10462, 21676, 29889, 13, 29937, 29871, 13, 29937, 10413, 21144, 1090, 278, 13380, 19245, 29892, 10079, 29871, 29906, 29889, 29900, 313, 1552, 376, 29931, 293, 1947, 1496, 366, 1122, 13, 29937, 451, 671, 445, 934, 5174, 297, 752, 13036, 411, 278, 19245, 29889, 887, 1122, 4017, 13, 29937, 263, 3509, 310, 278, 19245, 472, 13, 29937, 29871, 13, 29937, 418, 1732, 597, 1636, 29889, 4288, 29889, 990, 29914, 506, 11259, 29914, 27888, 1430, 1660, 29899, 29906, 29889, 29900, 13, 29937, 29871, 13, 29937, 25870, 3734, 491, 22903, 4307, 470, 15502, 304, 297, 5007, 29892, 7047, 13, 29937, 13235, 1090, 278, 19245, 338, 13235, 373, 385, 376, 3289, 8519, 29908, 350, 3289, 3235, 29892, 399, 1806, 8187, 2692, 13, 29937, 399, 1718, 29934, 13566, 29059, 6323, 8707, 29928, 22122, 29903, 8079, 13764, 29979, 476, 22255, 29892, 2845, 4653, 470, 2411, 2957, 29889, 2823, 278, 13, 29937, 19245, 363, 278, 2702, 4086, 14765, 1076, 11239, 322, 27028, 13, 29937, 1090, 278, 19245, 29889, 13, 29937, 13, 13, 3166, 869, 11739, 29879, 1053, 830, 1664, 2451, 29892, 830, 1664, 17413, 2392, 29892, 830, 1664, 16676, 2392, 29892, 838, 2040, 6359, 2451, 13, 3166, 869, 16950, 1053, 830, 1664, 13, 3166, 869, 4993, 1053, 830, 1664, 4435, 29892, 13109, 6982, 4435, 13, 3166, 869, 4703, 1053, 21439, 2677, 13, 3166, 869, 1610, 1053, 22038, 6982, 13, 3166, 869, 2029, 1061, 1053, 5976, 1061, 13, 3166, 869, 25162, 1053, 612, 8807, 6982, 13, 3166, 869, 3126, 1053, 14355, 6982, 13, 3166, 869, 28789, 1764, 1053, 29779, 1764, 6982, 13, 13, 1649, 497, 1649, 353, 313, 13, 1678, 525, 6982, 2451, 742, 13, 1678, 525, 6982, 17413, 2392, 742, 13, 1678, 525, 6982, 16676, 2392, 742, 13, 1678, 525, 2499, 2040, 6359, 2451, 742, 13, 1678, 525, 6982, 742, 13, 1678, 525, 6982, 4435, 742, 13, 1678, 525, 4592, 6982, 4435, 742, 13, 1678, 525, 6359, 292, 2677, 742, 13, 1678, 525, 22131, 6982, 742, 13, 1678, 525, 3524, 1061, 742, 13, 1678, 525, 29979, 8807, 6982, 742, 13, 1678, 525, 8148, 6982, 742, 13, 1678, 525, 29967, 262, 1764, 6982, 1495, 13, 2 ]
pymars/tests/test_drg.py	kbronstein56/pyMARS	39	47179	"""Tests for drg module""" import sys import os import pkg_resources import pytest import numpy as np import networkx as nx import cantera as ct from ..sampling import data_files, InputIgnition from ..drg import graph_search, create_drg_matrix, run_drg, trim_drg, reduce_drg # Taken from http://stackoverflow.com/a/22726782/1569494 try: from tempfile import TemporaryDirectory except ImportError: from contextlib import contextmanager import shutil import tempfile import errno @contextmanager def TemporaryDirectory(): name = tempfile.mkdtemp() try: yield name finally: try: shutil.rmtree(name) except OSError as e: # Reraise unless ENOENT: No such file or directory # (ok if directory has already been deleted) if e.errno != errno.ENOENT: raise def relative_location(file): file_path = os.path.join(file) return pkg_resources.resource_filename(__name__, file_path) def check_equal(list1, list2): """Check whether two lists have the same contents (regardless of order). Taken from https://stackoverflow.com/a/12813909 Parameters ---------- list1 : list First list, containing all of a particular type list2: list Second list, containing all of a particular type Returns ------- bool ``True`` if lists are equal """ return len(list1) == len(list2) and sorted(list1) == sorted(list2) class TestCreateDRGMatrix: """Tests for create_drg_matrix method""" def test_qss_artificial(self): """Test using four species artificial model with QSS species from 2006 DRG paper. # R \approx F / 1e3 """ R1 = ct.Reaction.fromCti('''reaction('F => R', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('R => P', [1.0e3, 0.0, 0.0])''') R3 = ct.Reaction.fromCti('''reaction('R => Pp', [1.0, 0.0, 0.0])''') F = ct.Species('F', 'H:1') R = ct.Species('R', 'H:1') P = ct.Species('P', 'H:1') Pp = ct.Species('Pp', 'H:1') for sp in [F, R, P, Pp]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, R, P, Pp], reactions=[R1, R2, R3] ) state = 1000, ct.one_atm, [1., 1./1.e3, 0., 0.] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0, 0], [0.5, 0, 0.5, 0.51e-3], [0, 1.0, 0, 0], [0, 1, 0, 0] ]) assert np.allclose(correct, matrix, rtol=1e-3) def test_pe_artificial(self): """Test using three species artificial model with PE reactions from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('F <=> R', [1.0e3, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('R <=> P', [1.0, 0.0, 0.0])''') F = ct.Species('F', 'H:1') R = ct.Species('R', 'H:1') P = ct.Species('P', 'H:1') for sp in [F, R, P]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, R, P], reactions=[R1, R2] ) conc_R = 0.1 conc_F = ((1 + 1e-3)conc_R - (1/2e3))/(1 - (1/2e3)) conc_P = 1.0 - (conc_R + conc_F) state = 1000, ct.one_atm, [conc_F, conc_R, conc_P] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [1./3., 0, 2./3.], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) def test_dormant_modes(self): """Test using three species artificial model with dormant modes from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('A <=> B', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('B <=> C', [1.0e-3, 0.0, 0.0])''') A = ct.Species('A', 'H:1') B = ct.Species('B', 'H:1') C = ct.Species('C', 'H:1') for sp in [A, B, C]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[A, B, C], reactions=[R1, R2] ) state = 1000, ct.one_atm, [1.0, 2.0, 1.0] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [1/(1+1e-3), 0, 1e-3/(1+1e-3)], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) conc_A = 1.370536 conc_B = 1.370480 conc_C = 1.258985 state = 1000, ct.one_atm, [conc_A, conc_B, conc_C] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [abs(conc_A-conc_B)/(abs(conc_A-conc_B)+1e-3abs(conc_B-conc_C)), 0, 1e-3abs(conc_B-conc_C)/(abs(conc_A-conc_B)+1e-3*abs(conc_B-conc_C)) ], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) @pytest.mark.skip def testArtificial(self): """Uses artificial mechanism to test""" # Load model path_to_original = relative_location("artificial-mechanism.cti") solution_object = ct.Solution(path_to_original) # Pull out timestep one denomenator and numerator dicts ic_one = rate_edge_data[list(rate_edge_data.keys())[0]] tstep_one = ic_one[list(ic_one.keys())[0]] denoms = tstep_one[0] numers = tstep_one[1] # Expected values for denomenators expected_denoms = {} expected_denoms["H2O"] = 1.9573216e-13 expected_denoms["H2"] = .00025854374 expected_denoms["O2"] = 9.7866081e-14 expected_denoms["H"] = .00051708749 assert np.isclose(expected_denoms["H2O"], denoms["H2O"],abs_tol=1.0e-17) assert np.isclose(expected_denoms["H2"], denoms["H2"],abs_tol=1.0e-10) assert np.isclose(expected_denoms["O2"], denoms["O2"],abs_tol=1.0e-18) assert np.isclose(expected_denoms["H"], denoms["H"],abs_tol=1.0e-10) expected_numers = {} expected_numers["H2O_H2"] = 1.9573216e-13 expected_numers["H2O_O2"] = 1.9573216e-13 expected_numers["H2_O2"] = 1.9573216e-13 expected_numers["H2_H2O"] = 1.9573216e-13 expected_numers["O2_H2"] = 9.7866081e-14 expected_numers["O2_H2O"] = 9.7866081e-14 expected_numers["H2_H"] = .00025854374 expected_numers["H_H2"] = .00051708749 assert np.isclose(expected_numers["H2O_H2"],numers["H2O_H2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2O_O2"],numers["H2O_O2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2_O2"],numers["H2_O2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2_H2O"],numers["H2_H2O"],abs_tol=1.0e-17) assert np.isclose(expected_numers["O2_H2"],numers["O2_H2"],abs_tol=1.0e-18) assert np.isclose(expected_numers["O2_H2O"],numers["O2_H2O"],abs_tol=1.0e-18) assert np.isclose(expected_numers["H2_H"],numers["H2_H"],abs_tol=1.0e-18) assert np.isclose(expected_numers["H_H2"],numers["H_H2"],abs_tol=1.0e-18) class TestTrimDRG: """Tests for trim_drg method""" def test_simple(self): matrix = np.array([[0, 1, 0.1], [0.5, 0, 0.5], [0.5, 0.5, 0]]) names = ['A', 'B', 'C'] reached = trim_drg(matrix, names, ['A'], 0.2) assert check_equal(reached, names) reached = trim_drg(matrix, names, ['A'], 0.6) assert check_equal(reached, ['A', 'B']) def test_uncoupled_group(self): """Test of simple five-component graph from DRG papers. """ matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['A'], 0.1) assert check_equal(reached, ['A', 'B', 'D']) matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['E'], 0.1) assert check_equal(reached, ['E', 'F']) def test_uncoupled_group2(self): """Test of simple five-component graph from DRG papers. """ matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0.15, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['A'], 0.1) assert check_equal(reached, ['A', 'B', 'C', 'D']) reached = trim_drg(matrix, names, ['A'], 0.2) assert check_equal(reached, ['A', 'B', 'D']) def test_csp_mech5(self): """Test of simple mech 5 from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('F => P', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('F => R', [1.0e-2, 0.0, 0.0])''') R3 = ct.Reaction.fromCti('''reaction('R => P', [1.0e2, 0.0, 0.0])''') F = ct.Species('F', 'H:1') P = ct.Species('P', 'H:1') R = ct.Species('R', 'H:1') for sp in [F, P, R]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, P, R], reactions=[R1, R2, R3] ) state = 1000, ct.one_atm, [1.0, 1.0, 1.0e-4] matrix = create_drg_matrix(state, model) reached = trim_drg(matrix, ['F', 'P', 'R'], ['F'], 0.1) assert check_equal(reached, ['F', 'P']) class TestGraphSearch: """Tests for graph_search method""" #generate test graph #starting from A, nodes A,E,C,F,D,I,H,O should be the only nodes found def testGraphSearchOneInput(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), # ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) subgraph = nx.DiGraph([(u,v,d) for u,v,d in graph.edges(data=True) if d['weight'] > 0]) #temporary solution essential_nodes = graph_search(subgraph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] #generate test graph #starting from A, nodes A,E,C,F,D,I,H,O should be the only nodes found def testGraphSearchOneInput2(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), # ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) subgraph = nx.DiGraph([(u,v,d) for u,v,d in graph.edges(data=True) if d['weight'] > 0]) #temporary solution essential_nodes = graph_search(subgraph, 'G') assert 'G' in essential_nodes for n in ['A','B', 'C', 'D', 'J', 'K', 'I', 'O', 'F', 'E', 'H', 'M', 'N']: assert n not in essential_nodes assert [n in essential_nodes for n in [ 'G', 'L']] def testGraphSearch3Inputs(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from( [ ('C','F', 1), ('A','C', 1), #('A','F', 0), ('A','N', 0), ('N','C', 1), ('C','D', 1), ('D','I', 1), ('I','O', 1), ('A','E', 1), #('E','G', 0), ('G','I', 0), ('G','M', 0), ('G','L', 1), ('E','H', 1), #('H','J', 0) ]) target_species= ['A', 'C', 'D'] essential_nodes = graph_search(graph, target_species) assert 'A' in essential_nodes assert 'C' in essential_nodes assert 'D' in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']: assert n in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']: assert n not in essential_nodes def testgraphsearch_no_targets (self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, []) assert not essential_nodes @pytest.mark.xfail def testGraphshearchwithatargetThatsnotinGraph(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, 'Z') assert 'Z' in essential_nodes def testGraphsearchforinfinteloops(self): graph = nx.DiGraph() graph.add_nodes_from(['A', 'B', 'C', 'D', 'E']) graph.add_weighted_edges_from( [('A', 'B', 1), ('B', 'C', 1), ('C', 'D', 1), ('D', 'E',1), ('E', 'A', 1)] ) essential_nodes= graph_search(graph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'B', 'E']] @pytest.mark.xfail def testGraphShearchWithATargetThatsNotInGraphAndOneThatIs(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, ['B', 'Z']) assert 'B' in essential_nodes def testGraphsearchwithListofLength1(self): graph = nx.DiGraph() graph.add_node('A') essential_nodes = graph_search(graph, 'A') assert 'A' in essential_nodes assert len(essential_nodes) == 1 def testGraphSearchWithTwoOfTheSameItemInTheGraph(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F',0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] def testGraphSearchWithTwoOfTheSameItemInTheTargetList(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, ['A','A']) assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] class TestReduceDRG: def test_gri_reduction_multiple_cases(self): """Tests reduce_drg method with multiple cases""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), InputIgnition( kind='constant volume', pressure=1.0, temperature=1200.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data = np.genfromtxt( relative_location(os.path.join('assets', 'example_ignition_data.dat')), delimiter=',' ) model = ct.Solution(model_file) matrices = [] for state in data: matrices.append(create_drg_matrix((state[0], state[1], state[2:]), model)) with TemporaryDirectory() as temp_dir: reduced_model = reduce_drg( model_file, ['CH4', 'O2'], ['N2'], 0.14, matrices, conditions, np.array([1.066766136745876281e+00, 4.334773545084597696e-02]), previous_model=None, threshold_upper=None, num_threads=1, path=temp_dir ) expected_species = [ 'H2', 'H', 'O', 'O2', 'OH', 'H2O', 'HO2', 'H2O2', 'C', 'CH', 'CH2', 'CH2(S)', 'CH3', 'CH4', 'CO', 'CO2', 'HCO', 'CH2O', 'CH2OH', 'CH3O', 'C2H2', 'C2H3', 'C2H4', 'C2H5', 'C2H6', 'HCCO', 'CH2CO', 'N', 'NH', 'NNH', 'NO', 'N2O', 'HNO', 'CN', 'HCN', 'H2CN', 'HCNN', 'NCO', 'N2', 'CH2CHO' ] assert check_equal(reduced_model.model.species_names, expected_species) assert reduced_model.model.n_reactions == 245 assert round(reduced_model.error, 2) == 3.64 def test_gri_reduction_limbo(self): """Tests reduce_drg method with limbo species""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data = np.genfromtxt( relative_location(os.path.join('assets', 'example_ignition_data.dat')), delimiter=',' ) model = ct.Solution(model_file) matrices = [] for state in data: matrices.append(create_drg_matrix((state[0], state[1], state[2:]), model)) with TemporaryDirectory() as temp_dir: reduced_model = reduce_drg( model_file, ['CH4', 'O2'], ['N2'], 0.14, matrices, conditions, np.array([1.066766136745876281e+00]), previous_model=None, threshold_upper=0.6, num_threads=1, path=temp_dir ) expected_species = [ 'H2', 'H', 'O', 'O2', 'OH', 'H2O', 'HO2', 'H2O2', 'C', 'CH', 'CH2', 'CH2(S)', 'CH3', 'CH4', 'CO', 'CO2', 'HCO', 'CH2O', 'CH2OH', 'CH3O', 'C2H2', 'C2H3', 'C2H4', 'C2H5', 'C2H6', 'HCCO', 'CH2CO', 'N', 'NH', 'NNH', 'NO', 'N2O', 'HNO', 'CN', 'HCN', 'H2CN', 'HCNN', 'NCO', 'N2', 'CH2CHO' ] expected_limbo_species = ['H', 'CH3', 'CH4', 'OH', 'HO2', 'O', 'H2O', 'O2'] assert check_equal(reduced_model.model.species_names, expected_species) assert check_equal(reduced_model.limbo_species, expected_limbo_species) class TestRunDRG: def test_gri_reduction(self): """Tests driver run_drg method""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), InputIgnition( kind='constant volume', pressure=1.0, temperature=1200.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data_files['output_ignition'] = relative_location( os.path.join('assets', 'example_ignition_output.txt') ) data_files['data_ignition'] 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stagifyapi/api/migrations/0004_create_artist.py	Davee02/Stagify	0	101718	<reponame>Davee02/Stagify # Generated by Django 3.1.3 on 2020-12-10 14:25 import api.models from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("api", "0003_delete_old"), ] operations = [ migrations.CreateModel( name="Artist", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("displayname", models.CharField(max_length=500)), ("description", models.CharField(max_length=10000)), ( "avatar", models.FileField( storage=api.models.select_storage, upload_to="artist_avatars" ), ), ], ), ]	[ 1, 529, 276, 1112, 420, 29958, 29928, 1351, 29872, 29900, 29906, 29914, 855, 351, 1598, 13, 29937, 3251, 630, 491, 15337, 29871, 29941, 29889, 29896, 29889, 29941, 373, 29871, 29906, 29900, 29906, 29900, 29899, 29896, 29906, 29899, 29896, 29900, 29871, 29896, 29946, 29901, 29906, 29945, 13, 13, 5215, 7882, 29889, 9794, 13, 3166, 9557, 29889, 2585, 1053, 9725, 800, 29892, 4733, 13, 13, 13, 1990, 341, 16783, 29898, 26983, 800, 29889, 29924, 16783, 1125, 13, 13, 1678, 9962, 353, 518, 13, 4706, 4852, 2754, 613, 376, 29900, 29900, 29900, 29941, 29918, 8143, 29918, 1025, 4968, 13, 1678, 4514, 13, 13, 1678, 6931, 353, 518, 13, 4706, 9725, 800, 29889, 4391, 3195, 29898, 13, 9651, 1024, 543, 9986, 391, 613, 13, 9651, 4235, 11759, 13, 18884, 313, 13, 462, 1678, 376, 333, 613, 13, 462, 1678, 4733, 29889, 12300, 3073, 29898, 13, 462, 4706, 4469, 29918, 11600, 29922, 5574, 29892, 13, 462, 4706, 7601, 29918, 1989, 29922, 5574, 29892, 13, 462, 4706, 28755, 29922, 8824, 29892, 13, 462, 4706, 26952, 29918, 978, 543, 1367, 613, 13, 462, 1678, 10353, 13, 18884, 10353, 13, 18884, 4852, 4990, 978, 613, 4733, 29889, 27890, 29898, 3317, 29918, 2848, 29922, 29945, 29900, 29900, 8243, 13, 18884, 4852, 8216, 613, 4733, 29889, 27890, 29898, 3317, 29918, 2848, 29922, 29896, 29900, 29900, 29900, 29900, 8243, 13, 18884, 313, 13, 462, 1678, 376, 485, 14873, 613, 13, 462, 1678, 4733, 29889, 2283, 3073, 29898, 13, 462, 4706, 8635, 29922, 2754, 29889, 9794, 29889, 2622, 29918, 12925, 29892, 6441, 29918, 517, 543, 442, 391, 29918, 485, 271, 1503, 29908, 13, 462, 1678, 10353, 13, 18884, 10353, 13, 9651, 21251, 13, 4706, 10353, 13, 1678, 4514, 13, 2 ]

trainer/train_debug.py

naivelogic/dotatron

0

1610322

<reponame>naivelogic/dotatron #!/usr/bin/python import os import torch import warnings warnings.filterwarnings("ignore", category=FutureWarning) from detectron2.config import * from detectron2 import model_zoo from detectron2.data import DatasetCatalog, MetadataCatalog from detectron2.engine import launch from rotated_trainer import RotatedTrainer from dota2kit_data_tools import dotatron_loader from detectron2.engine import default_setup import logging logger = logging.getLogger("detectron2") torch.cuda.set_device(0) # multi from cfg_lib import base_dota_cfg from dota_project import DOTA2CLASSES def main(args): #DATA_FOLDER = "/mnt/omreast_users/phhale/open_ds/DOTA_aerial_images/" OUTPUT_PATHS="/home/redne/LUIA_challenge_dev/tron_dota/prod_v2/output/x3/x1" TRAIN_PATH = '/home/redne/LUIA_challenge_dev/repos/DOTA_devkit_YOLO/examplesplit' DatasetCatalog.clear() MetadataCatalog.clear() DatasetCatalog.register("Train", lambda: dotatron_loader(dataset_dir=TRAIN_PATH, load_dataset=False, classlist=DOTA2CLASSES, dataset_load_name='train_dota2kit_prodv2')) MetadataCatalog.get("Train").set(thing_classes=DOTA2CLASSES) cfg = base_dota_cfg() cfg.DATASETS.TRAIN = (["Train"]) cfg.DATASETS.TEST = () cfg.MODEL.ROI_HEADS.NUM_CLASSES = len(DOTA2CLASSES) cfg.VIS_PERIOD = 10 #50 cfg.OUTPUT_DIR= OUTPUT_PATHS os.makedirs(cfg.OUTPUT_DIR, exist_ok=True) #lets just check our output dir exists cfg.freeze() # make the configuration unchangeable during the training process default_setup(cfg, args) cfg.dump() trainer = RotatedTrainer(cfg) #trainer.resume_or_load(resume=True) trainer.resume_or_load(resume=False) return trainer.train() if __name__ == '__main__': torch.cuda.empty_cache() from custom_arg_parsers import custom_default_argument_parser args = custom_default_argument_parser().parse_args() print("Command Line Args:", args) torch.backends.cudnn.benchmark = True launch( main, args.num_gpus, num_machines=args.num_machines, machine_rank=args.machine_rank, dist_url=args.dist_url, args=(args,), )

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pyskyqremote/classes/device.py

RogerSelwyn/pyskyqremote

0

119010

"""Methods for retrieving device information.""" import json import logging from dataclasses import dataclass, field from ..const import (CURRENT_SPEED, CURRENT_TRANSPORT_STATE, CURRENT_TRANSPORT_STATUS, DEFAULT_TRANSPORT_SPEED, DEFAULT_TRANSPORT_STATE, KNOWN_COUNTRIES, REST_PATH_DEVICEINFO, REST_PATH_SYSTEMINFO, SKY_STATE_NOMEDIA, SKY_STATE_OFF, SKY_STATE_PAUSED, SKY_STATE_PLAYING, SKY_STATE_STANDBY, SKY_STATE_STOPPED, SKY_STATE_TRANSITIONING, SKY_STATE_UNSUPPORTED, UPNP_GET_TRANSPORT_INFO) _LOGGER = logging.getLogger(__name__) class DeviceInformation: """Sky Q device information retrieval methods.""" def __init__(self, remote_config): """Initialise the device information class.""" self._remote_config = remote_config self._device_access = remote_config.device_access self._port = remote_config.port def get_transport_information(self): """Get the transport information from the SkyQ box.""" response = self._device_access.call_sky_soap_service(UPNP_GET_TRANSPORT_INFO) if response is not None: return TransportInfo( response[CURRENT_TRANSPORT_STATE], response[CURRENT_TRANSPORT_STATUS], response[CURRENT_SPEED], ) return TransportInfo( SKY_STATE_OFF, DEFAULT_TRANSPORT_STATE, DEFAULT_TRANSPORT_SPEED ) def get_system_information(self): """Get the system information from the SkyQ box.""" return self._device_access.retrieve_information(REST_PATH_SYSTEMINFO) def get_device_information(self, override_country): """Get the device information from the SkyQ box.""" device_info = self._device_access.retrieve_information(REST_PATH_DEVICEINFO) if not device_info: return None system_info = self.get_system_information() as_version = device_info["ASVersion"] ip_address = device_info["IPAddress"] country_code = device_info["countryCode"] gateway = device_info["gateway"] hardware_model = system_info["hardwareModel"] device_type = system_info["deviceType"] hardware_name = device_info["hardwareName"] manufacturer = system_info["manufacturer"] model_number = device_info["modelNumber"] serial_number = device_info["serialNumber"] version_number = device_info["versionNumber"] bouquet = device_info["bouquet"] subbouquet = device_info["subbouquet"] wake_reason = system_info["wakeReason"] system_uptime = system_info["systemUptime"] hdr_capable = system_info["hdrCapable"] uhd_capable = system_info["uhdCapable"] used_country_code = override_country or country_code.upper() if not used_country_code: _LOGGER.error("E0010 - No country identified: %s", self._remote_config.host) return None if used_country_code in KNOWN_COUNTRIES: used_country_code = KNOWN_COUNTRIES[used_country_code] return Device( as_version, ip_address, country_code, used_country_code, hardware_model, hardware_name, device_type, gateway, manufacturer, model_number, serial_number, version_number, bouquet, subbouquet, wake_reason, system_uptime, hdr_capable, uhd_capable, ) @dataclass class Device: """SkyQ Device Class.""" ASVersion: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) IPAddress: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) countryCode: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) used_country_code: str = field( init=True, repr=True, compare=False, ) hardwareModel: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) hardwareName: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) deviceType: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) gateway: str = field( init=True, repr=True, compare=False, ) manufacturer: str = field( init=True, repr=True, compare=False, ) modelNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) serialNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) versionNumber: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) bouquet: str = field( init=True, repr=True, compare=False, ) subbouquet: str = field( init=True, repr=True, compare=False, ) wakeReason: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) systemUptime: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) hdrCapable: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) uhdCapable: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) def as_json(self) -> str: """Return a JSON string representing this device info.""" return json.dumps(self, cls=_DeviceJSONEncoder) def device_decoder(obj): """Decode programme object from json.""" device = json.loads(obj) if "__type__" in device and device["__type__"] == "__device__": return Device(**device["attributes"]) return device class _DeviceJSONEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, Device): attributes = dict(vars(o)) return { "__type__": "__device__", "attributes": attributes, } @dataclass class TransportInfo: """SkyQ TransportInfo Class.""" CurrentTransportState: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) CurrentTransportStatus: str = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) CurrentSpeed: float = field( # pylint: disable=invalid-name init=True, repr=True, compare=False, ) state: str = None def __post_init__(self): """Post process the transport setup.""" self.state = self.CurrentTransportState if self.CurrentTransportState in [SKY_STATE_NOMEDIA, SKY_STATE_STOPPED]: self.state = SKY_STATE_STANDBY if self.CurrentTransportState in [SKY_STATE_PLAYING, SKY_STATE_TRANSITIONING]: self.state = SKY_STATE_PLAYING if self.CurrentTransportState == SKY_STATE_PAUSED: self.state = SKY_STATE_PAUSED if self.CurrentTransportState == SKY_STATE_UNSUPPORTED: self.CurrentTransportState = None def as_json(self) -> str: """Return a JSON string representing this app info.""" return json.dumps(self, cls=_TransportInfoJSONEncoder) def transportinfo_decoder(obj): """Decode programme object from json.""" transportinfo = json.loads(obj) if "__type__" in transportinfo and transportinfo["__type__"] == "__transportinfo__": return TransportInfo(**transportinfo["attributes"]) return transportinfo class _TransportInfoJSONEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, TransportInfo): attributes = dict(vars(o)) return { "__type__": "__transportinfo__", "attributes": attributes, }

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school/migrations/0001_initial.py

muzamilqadir786/smartchild

0

1605010

<reponame>muzamilqadir786/smartchild # -*- coding: utf-8 -*- # Generated by Django 1.10.4 on 2016-12-13 07:18 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Fee', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fee_paid', models.DecimalField(decimal_places=2, default=0, max_digits=6)), ('date_of_payment', models.DateField(auto_now_add=True)), ], ), migrations.CreateModel( name='FeeCategory', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fee_category', models.CharField(blank=True, choices=[('M', 'Monthly_Fee'), ('A', 'Admission_Fee')], default='M', max_length=30, null=True)), ('amount', models.DecimalField(decimal_places=2, max_digits=6)), ('description', models.TextField()), ], options={ 'ordering': ('id',), 'verbose_name': 'Fee Categories', }, ), migrations.CreateModel( name='Level', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('level', models.CharField(choices=[('Playgroup', 'Playgroup'), ('Nursery', 'Nursery'), ('PREP', 'PREP'), ('1st Grade', '1st Grade'), ('2nd Grade', '2nd Grade'), ('3rd Grade', '3rd Grade'), ('4th Grade', '4th Grade')], max_length=30)), ], ), migrations.CreateModel( name='Student', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(blank=True, max_length=30, null=True)), ('last_name', models.CharField(blank=True, max_length=30, null=True)), ('father_name', models.CharField(blank=True, max_length=30, null=True)), ('mother_name', models.CharField(blank=True, max_length=30, null=True)), ('gender', models.CharField(choices=[('M', 'Male'), ('F', 'Female')], default='M', max_length=1)), ('mobile_code', models.CharField(choices=[(b'0300', b'0300'), (b'0301', b'0301'), (b'0302', b'0302'), (b'0303', b'0303'), (b'0304', b'0304'), (b'0305', b'0305'), (b'0306', b'0306'), (b'0307', b'0307'), (b'0308', b'0308'), (b'0309', b'0309'), (b'0310', b'0310'), (b'0311', b'0311'), (b'0312', b'0312'), (b'0313', b'0313'), (b'0314', b'0314'), (b'0315', b'0315'), (b'0320', b'0320'), (b'0321', b'0321'), (b'0322', b'0322'), (b'0323', b'0323'), (b'0324', b'0324'), (b'0331', b'0331'), (b'0332', b'0332'), (b'0333', b'0333'), (b'0334', b'0334'), (b'0335', b'0335'), (b'0336', b'0336'), (b'0337', b'0337'), (b'0340', b'0340'), (b'0341', b'0341'), (b'0342', b'0342'), (b'0343', b'0343'), (b'0344', b'0344'), (b'0345', b'0345'), (b'0346', b'0346'), (b'0347', b'0347'), (b'0348', b'0348'), (b'0349', b'0349')], default='0300', max_length=4)), ('seven_digit_phone', models.CharField(blank=True, max_length=7, null=True)), ('address', models.CharField(blank=True, max_length=200, null=True)), ('date_of_birth', models.DateField(default='1/1/2000')), ('level', models.ForeignKey(blank=True, on_delete=django.db.models.deletion.CASCADE, to='school.Level')), ], ), migrations.AddField( model_name='fee', name='fee_category', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='school.FeeCategory'), ), migrations.AddField( model_name='fee', name='student', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='school.Student'), ), ]

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archieve/2020/day3b.py

jabra98/aoc

0

107429

<reponame>jabra98/aoc<gh_stars>0 def main(): grid = open("data.txt").readlines() for i in range(0, len(grid)): grid[i] = grid[i][:-1] x_width = len(grid[i]) y_length = len(grid) ctr = 0 y_pos = 0 x_pos = 0 product = 1 for i in [[1,1], [3,1], [5,1], [7,1], [1,2]]: while y_pos < y_length: if grid[y_pos][x_pos % x_width] == '#': ctr += 1 x_pos += i[0] y_pos += i[1] print(ctr) product *= ctr x_pos=0 y_pos=0 ctr=0 print(product) main()

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daisy/convenience.py

rhoadesScholar/daisy

0

1612953

from .cl_monitor import CLMonitor from .server import Server from .tcp import IOLooper from multiprocessing.pool import ThreadPool from multiprocessing import Event def run_blockwise(tasks): '''Schedule and run the given tasks. Args: list_of_tasks: The tasks to schedule over. Return: bool: `True` if all blocks in the given `tasks` were successfully run, else `False` ''' stop_event = Event() IOLooper.clear() pool = ThreadPool(processes=1) result = pool.apply_async(_run_blockwise, args=(tasks, stop_event)) try: return result.get() except KeyboardInterrupt: stop_event.set() return result.get() def _run_blockwise(tasks, stop_event): server = Server(stop_event=stop_event) cl_monitor = CLMonitor(server) # noqa return server.run_blockwise(tasks)

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Tools/decrypt_ulog.py

lgarciaos/Firmware

4,224

33612

#!/usr/bin/env python3 from Crypto.PublicKey import RSA from Crypto.Cipher import PKCS1_OAEP from Crypto.Cipher import ChaCha20 from Crypto.Hash import SHA256 import binascii import argparse #from pathlib import Path import sys if __name__ == "__main__": parser = argparse.ArgumentParser(description="""CLI tool to decrypt an ulog file\n""") parser.add_argument("ulog_file", help=".ulog file", nargs='?', default=None) parser.add_argument("ulog_key", help=".ulogk, encrypted key", nargs='?', default=None) parser.add_argument("rsa_key", help=".pem format key for decrypting the ulog key", nargs='?', default=None) args = parser.parse_args() # Only generate a key pair, don't sign if not args.ulog_file or not args.ulog_key or not args.rsa_key: print('Need all arguments, the encrypted ulog file, the key and the key decryption key') sys.exit(1); # Read the private RSA key to decrypt the cahcha key with open(args.rsa_key, 'rb') as f: r = RSA.importKey(f.read(), passphrase='') # Read the encrypted xchacha key and the nonce with open(args.ulog_key, 'rb') as f: ulog_key_header = f.read(22) # Parse the header try: # magic if not ulog_key_header.startswith(bytearray("ULogKey".encode())): raise Exception() # version if ulog_key_header[7] != 1: raise Exception() # expected key exchange algorithm (RSA_OAEP) if ulog_key_header[16] != 4: raise Exception() key_size = ulog_key_header[19] << 8 | ulog_key_header[18]; nonce_size = ulog_key_header[21] << 8 | ulog_key_header[20]; ulog_key_cipher = f.read(key_size) nonce = f.read(nonce_size) except: print("Keyfile format error") sys.exit(1); # Decrypt the xchacha key cipher_rsa = PKCS1_OAEP.new(r,SHA256) ulog_key = cipher_rsa.decrypt(ulog_key_cipher) #print(binascii.hexlify(ulog_key)) # Read and decrypt the .ulgc cipher = ChaCha20.new(key=ulog_key, nonce=nonce) with open(args.ulog_file, 'rb') as f: with open(args.ulog_file.rstrip(args.ulog_file[-1]), 'wb') as out: out.write(cipher.decrypt(f.read()))

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packages/core/minos-microservice-common/minos/common/protocol/avro/base.py

minos-framework/minos-python

247

162959

<gh_stars>100-1000 import io from typing import ( Any, Union, ) from fastavro import ( parse_schema, reader, writer, ) from ...exceptions import ( MinosProtocolException, ) from ..abc import ( MinosBinaryProtocol, ) class MinosAvroProtocol(MinosBinaryProtocol): """Minos Avro Protocol class.""" @classmethod def encode(cls, value: Any, schema: Any, *args, batch_mode: bool = False, **kwargs) -> bytes: """Encoder in avro for database Values all the headers are converted in fields with double underscore name the body is a set fields coming from the data type. :param value: The data to be stored. :param schema: The schema relative to the data. :param args: Additional positional arguments. :param batch_mode: If ``True`` the data is processed as a list of models, otherwise the data is processed as a single model. :param kwargs: Additional named arguments. :return: A bytes object. """ if not batch_mode: value = [value] if not isinstance(schema, list): schema = [schema] try: raw_schema = cls._parse_schema(schema) return cls._write_data(value, raw_schema) except Exception as exc: raise MinosProtocolException(f"Error encoding data: {exc!r}") @staticmethod def _parse_schema(schema: list[dict[str, Any]]) -> dict[str, Any]: named_schemas = {} for item in schema[1::-1]: parse_schema(item, named_schemas) return parse_schema(schema[0], named_schemas, expand=True) @staticmethod def _write_data(value: list[dict[str, Any]], schema: dict[str, Any]): with io.BytesIO() as file: writer(file, schema, value) file.seek(0) content = file.getvalue() return content @classmethod def decode(cls, data: bytes, *args, batch_mode: bool = False, **kwargs) -> Any: """Decode the given bytes of data into a single dictionary or a sequence of dictionaries. :param data: A bytes object. :param args: Additional positional arguments. :param batch_mode: If ``True`` the data is processed as a list of models, otherwise the data is processed as a single model. :param kwargs: Additional named arguments. :return: A dictionary or a list of dictionaries. """ try: with io.BytesIO(data) as file: ans = list(reader(file)) except Exception as exc: raise MinosProtocolException(f"Error decoding the avro bytes: {exc}") if not batch_mode: if len(ans) > 1: raise MinosProtocolException( f"The 'batch_mode' argument was set to {False!r} but data contains multiple values: {ans!r}" ) ans = ans[0] return ans # noinspection PyUnusedLocal @classmethod def decode_schema(cls, data: bytes, *args, **kwargs) -> Union[dict[str, Any], list[dict[str, Any]]]: """Decode the given bytes of data into a single dictionary or a sequence of dictionaries. :param data: A bytes object. :param args: Additional positional arguments. :param kwargs: Additional named arguments. :return: A tuple or a list of tuples. """ try: with io.BytesIO(data) as file: r = reader(file) schema = r.writer_schema except Exception as exc: raise MinosProtocolException(f"Error getting avro schema: {exc}") return schema

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src/LASER/utils/__init__.py

BigBird01/LASER

7

93894

from .logger_util import * from .argument_types import *

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rain_atten/powerlaw.py

bzohidov/TomoRain

0

156301

#------------------------------------------------------------------------------- # Name: powerlaw.py # Purpose: This is a set of power law coefficients(a,b) for the calculation of # empirical rain attenuation model A = a*R^b. #------------------------------------------------------------------------------- def get_coef_ab(freq, mod_type = 'MP'): ''' Returns power law coefficients according to model type (mod_type) at a given frequency[Hz]. Input: freq - frequency, [Hz]. Optional: mod_type - model type for power law. This can be 'ITU_R2005', 'MP','GAMMA'. By default, mode_type = 'ITU_R2005'. Output: a,b - power law coefficients. ''' if mod_type == 'ITU_R2005': a = {'18': 0.07393, '23': 0.1285, '38': 0.39225} b = {'18':1.0404605978, '23': 0.99222272,'38':0.8686641682} elif mod_type == 'MP': a = {'18': 0.05911087, '23': 0.1080751, '38': 0.37898495} b = {'18': 1.08693514, '23': 1.05342886, '38': 0.92876888} elif mod_type=='GAMMA': a = {'18': 0.04570854, '23': 0.08174184, '38': 0.28520923} b = {'18': 1.09211488, '23': 1.08105214, '38': 1.01426258} freq = int(freq/1e9) return a[str(freq)], b[str(freq)]

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curriculum/07_game_02_circle_clash_2_DAYS/07_game_02_circle_clash_day_1/07_02_02_circle_clash_advanced.py

google/teknowledge

31

52030

from tkinter import * # the game data for the initial game state def init(): data.playerX = 250 data.playerY = 550 data.circleX = 250 data.circleY = 0 data.gameOver = False # events updating the game data def keyPressed(event): if event.keysym == "Right" and data.playerX < 550: data.playerX += 5 elif event.keysym == "Left" and data.playerX > 0: data.playerX -= 5 def moveCircle(): if not data.gameOver: data.circleY += 10 # the game data updating the game state def timerFired(): moveCircle() if checkCollision(data.playerX, data.playerY, data.circleX, data.circleY, 10, 50): data.gameOver = True if data.circleY > 600: data.gameOver = True def checkCollision(x1, y1, x2, y2, r1, r2): distance = ((x2 - x1) ** 2 + (y2 - y1) ** 2) ** 0.5 return distance <= r1 + r2 # the game state updating what is drawn def redrawAll(canvas): canvas.create_oval(data.playerX - 10, data.playerY - 10, data.playerX + 10, data.playerY + 10, fill="red") canvas.create_oval(data.circleX - 50, data.circleY - 50, data.circleX + 50, data.circleY + 50, \ fill="yellow") if data.gameOver: canvas.create_text(300, 250, text="Game Over", font=" Arial 20") # Challenge 2.1 - Make it so that at the top of the screen it says "Score: __" # where the __ is a number that increases every time timerFired() happens. # Challenge 2.2 - Make it so that every third time timerFired() happens a new # circle is added to the top of the screen with random x position, color, # and size. # Suggested way to do this: # 1. Make a data.timer variable that starts at 0 and increases by 1 every # timerFired() and a data.circles variable that starts as []. # 2. When data.timer gets to 3, reset it to 0 and call a new function # createNewCircle(). # 3. Write createNewCircle() to append a tuple to data.circles of the # format: # (xCoordinate, yCoordinate, radiusSize, colorString) # 4. In redrawAll(), loop over the data.circles list and draw each circle. # 5. In timerFired(), every second, move each circle's yPosition down by # 10 pixels. # BONUS Challenge 2.3 - Make the game better with your own ideas! # The coding world is now yours for the exploring :) # ***** DO NOT MODIFY BELOW HERE ***** # # animation setup code class Struct(object): pass data = Struct() def run(width=600, height=600): def redrawAllWrapper(canvas): canvas.delete(ALL) redrawAll(canvas) canvas.update() def keyPressedWrapper(event, canvas): keyPressed(event) redrawAllWrapper(canvas) def timerFiredWrapper(canvas): timerFired() redrawAllWrapper(canvas) # pause, then call timerFired again canvas.after(data.timerDelay, timerFiredWrapper, canvas) # Set up data and call init data.width = width data.height = height data.timerDelay = 200 # milliseconds init() # create the root and the canvas root = Tk() canvas = Canvas(root, width=data.width, height=data.height) canvas.pack() # set up events root.bind("<Key>", lambda event: keyPressedWrapper(event, canvas)) timerFiredWrapper(canvas) # and launch the app root.mainloop() # blocks until window is closed print("bye!") run()

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activecampaign/admin/__init__.py

pmiguelima/django-activecampaign

1

142539

<filename>activecampaign/admin/__init__.py from .list import List from .message import Message from .campaign import Campaign

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python/practice/rules.py

icefoxen/lang

0

180169

# Heh, found this on a Usenet sig. reduce(lambda x,y:x+y,map(lambda x:chr(ord(x)^42),tuple('zS^BED\nX_FOY\x0b')))

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Leetcode/week_6/multi_threaded_merge_sort.py

SamSamhuns/wallbreakers_projekts

1

16463

import threading def merge_sort(arr): def _merge(arr1, arr2): i, j = 0, 0 l1, l2 = len(arr1), len(arr2) arr_sorted = [0] * (l1 + l2) idx = 0 while i < l1 and j < l2: if arr1[i] < arr2[j]: arr_sorted[idx] = arr1[i] i += 1 else: arr_sorted[idx] = arr2[j] j += 1 idx += 1 while i < l1: arr_sorted[idx] = arr1[i] i += 1 idx += 1 while j < l2: arr_sorted[idx] = arr2[j] j += 1 idx += 1 return arr_sorted def _recursive_sort(arr): if len(arr) == 1: return arr mid = len(arr) // 2 left_arr = _recursive_sort(arr[:mid]) right_arr = _recursive_sort(arr[mid:]) return _merge(left_arr, right_arr) return _recursive_sort(arr) def merge_sort_inplace(arr): def _merge(arr, start, mid, end): start2 = mid + 1 while start <= mid and start2 <= end: if arr[start] <= arr[start2]: # elem in right place start += 1 else: orig_start2 = arr[start2] idx = start2 # shift all elements between start and start2 # to the right by one place while idx != start: arr[idx] = arr[idx - 1] idx -= 1 arr[start] = orig_start2 start += 1 mid += 1 start2 += 1 def _recursive_sort(arr, left, right): if left < right: mid = left + ((right - left) // 2) _recursive_sort(arr, left, mid) _recursive_sort(arr, mid + 1, right) _merge(arr, left, mid, right) _recursive_sort(arr, 0, len(arr) - 1) def _merge(arr, start, mid, end): start2 = mid + 1 while start <= mid and start2 <= end: if arr[start] <= arr[start2]: # elem in right place start += 1 else: orig_start2 = arr[start2] idx = start2 # shift all elements to the right by one place while idx != start: arr[idx] = arr[idx - 1] idx -= 1 arr[start] = orig_start2 start += 1 mid += 1 start2 += 1 def _recursive_sort(arr, left, right): if left < right: mid = left + ((right - left) // 2) _recursive_sort(arr, left, mid) _recursive_sort(arr, mid + 1, right) _merge(arr, left, mid, right) # _recursive_sort(arr, 0, len(arr) - 1) if __name__ == "__main__": ar = [2, 4, 1, 2, 4, 5, 8, 2, 351, 2, 0] thread1 = threading.Thread( target=_recursive_sort, args=(ar, 0, len(ar) // 2),) thread2 = threading.Thread( target=_recursive_sort, args=(ar, (len(ar) // 2) + 1, len(ar) - 1,)) thread1.start() thread2.start() thread1.join() thread2.join() _merge(ar, 0, len(ar) // 2, len(ar) - 1) print(ar)

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main.py

impressive8/Practice

197

44090

# =================================== # Import the libraries # =================================== import numpy as np from matplotlib import pylab as plt import imaging import utility import os,sys # =================================== # Which stages to run # =================================== do_add_noise = False do_black_level_correction = True do_lens_shading_correction = True do_bad_pixel_correction = True do_channel_gain_white_balance = True do_bayer_denoise = False do_demosaic = True do_demosaic_artifact_reduction = True do_color_correction = True do_gamma = True do_chromatic_aberration_correction = True do_tone_mapping = True do_memory_color_enhancement = True do_noise_reduction = True do_sharpening = True do_distortion_correction = False # =================================== # Remove all the .png files os.system("rm images/*.png") # =================================== # =================================== # raw image and set up the metadata # =================================== # uncomment the image_name to run it via pipeline image_name = "DSC_1339_768x512_rggb" # image content: Rose rggb # image_name = "DSC_1339_768x512_gbrg" # image content: Rose gbrg # image_name = "DSC_1339_768x512_grbg" # image content: Rose grbg # image_name = "DSC_1339_768x512_bggr" # image content: Rose bggr # image_name = "DSC_1320_2048x2048_rggb" # image content: Potrait # image_name = "DSC_1372_6032x4032_rggb" # image content: Downtown San Jose # image_name = "DSC_1372_12096x6032_rgb_out_demosaic" # image content: Downtown San Jose after demosaic # read the raw image temp = np.fromfile("images/" + image_name + ".raw", dtype="uint16", sep="") if (image_name == "DSC_1339_768x512_rggb"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_gbrg"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_gbrg", temp) raw.set_color_space("raw") raw.set_bayer_pattern("gbrg") raw.set_channel_gain((1.0, 1.34375, 1.94921875, 1.0)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_grbg"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_grbg", temp) raw.set_color_space("raw") raw.set_bayer_pattern("grbg") raw.set_channel_gain((1.0, 1.94921875, 1.34375, 1.0)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1339_768x512_bggr"): temp = temp.reshape([512, 768]) raw = imaging.ImageInfo("1339_768x512_bggr", temp) raw.set_color_space("raw") raw.set_bayer_pattern("bggr") raw.set_channel_gain((1.34375, 1.0, 1.0, 1.94921875,)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColorMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1320_2048x2048_rggb"): temp = temp.reshape([2048, 2048]) raw = imaging.ImageInfo("1320_2048x2048_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1372_6032x4032_rggb"): temp = temp.reshape([4032, 6032]) raw = imaging.ImageInfo("DSC_1372_6032x4032_rggb", temp) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) data = raw.data elif (image_name == "DSC_1372_12096x6032_rgb_out_demosaic"): temp = temp.reshape([12096, 6032]) temp = np.float32(temp) data = np.empty((4032, 6032, 3), dtype=np.float32) data[:, :, 0] = temp[0:4032, :] data[:, :, 1] = temp[4032 : 2*4032, :] data[:, :, 2] = temp[2*4032 : 3*4032, :] raw = imaging.ImageInfo("DSC_1372_12096x6032_rgb_out_demosaic", data) raw.set_color_space("raw") raw.set_bayer_pattern("rggb") raw.set_channel_gain((1.94921875, 1.0, 1.0, 1.34375)) # Please shuffle the values # depending on bayer_pattern raw.set_bit_depth(14) raw.set_black_level((600, 600, 600, 600)) raw.set_white_level((15520, 15520, 15520, 15520)) # the ColotMatrix2 found from the metadata raw.set_color_matrix([[.9020, -.2890, -.0715],\ [-.4535, 1.2436, .2348],\ [-.0934, .1919, .7086]]) else: print("Warning! image_name not recognized.") # =================================== # Add noise # =================================== if do_add_noise: noise_mean = 0 noise_standard_deviation = 100 seed = 100 clip_range = [600, 65535] data = utility.synthetic_image_generate(\ raw.get_width(), raw.get_height()).create_noisy_image(\ data, noise_mean, noise_standard_deviation, seed, clip_range) else: pass # =================================== # Black level correction # =================================== if do_black_level_correction: data = imaging.black_level_correction(data, \ raw.get_black_level(),\ raw.get_white_level(),\ [0, 2**raw.get_bit_depth() - 1]) utility.imsave(data, "images/" + image_name + "_out_black_level_correction.png", "uint16") else: pass # =================================== # Lens shading correction # =================================== if do_lens_shading_correction: # normally dark_current_image and flat_field_image are # captured in the image quality lab using flat field chart # here we are synthetically generating thouse two images dark_current_image, flat_field_image = utility.synthetic_image_generate(\ raw.get_width(), raw.get_height()).create_lens_shading_correction_images(\ 0, 65535, 40000) # save the dark_current_image and flat_field_image for viewing utility.imsave(dark_current_image, "images/" + image_name + "_dark_current_image.png", "uint16") utility.imsave(flat_field_image, "images/" + image_name + "_flat_field_image.png", "uint16") data = imaging.lens_shading_correction(data).flat_field_compensation(\ dark_current_image, flat_field_image) # data = lsc.approximate_mathematical_compensation([0.01759, -28.37, -13.36]) utility.imsave(data, "images/" + image_name + "_out_lens_shading_correction.png", "uint16") else: pass # =================================== # Bad pixel correction # =================================== if do_bad_pixel_correction: neighborhood_size = 3 data = imaging.bad_pixel_correction(data, neighborhood_size) utility.imsave(data, "images/" + image_name + "_out_bad_pixel_correction.png", "uint16") else: pass # =================================== # Channel gain for white balance # =================================== if do_channel_gain_white_balance: data = imaging.channel_gain_white_balance(data,\ raw.get_channel_gain()) utility.imsave(data, "images/" + image_name + "_out_channel_gain_white_balance.png", "uint16") else: pass # =================================== # Bayer denoising # =================================== if do_bayer_denoise: # bayer denoising parameters neighborhood_size = 5 initial_noise_level = 65535 * 10 / 100 hvs_min = 1000 hvs_max = 2000 clip_range = [0, 65535] threshold_red_blue = 1300 # data is the denoised output, ignoring the second output data, _ = imaging.bayer_denoising(data).utilize_hvs_behavior(\ raw.get_bayer_pattern(), initial_noise_level, hvs_min, hvs_max, threshold_red_blue, clip_range) utility.imsave(data, "images/" + image_name + "_out_bayer_denoising.png", "uint16") # utility.imsave(np.clip(texture_degree_debug*65535, 0, 65535), "images/" + image_name + "_out_texture_degree_debug.png", "uint16") else: pass # =================================== # Demosacing # =================================== if do_demosaic: #data = imaging.demosaic(data, raw.get_bayer_pattern()).mhc(False) data = imaging.demosaic(data, raw.get_bayer_pattern()).directionally_weighted_gradient_based_interpolation() utility.imsave(data, "images/" + image_name + "_out_demosaic.png", "uint16") else: pass # =================================== # Demosaic artifact reduction # =================================== if do_demosaic_artifact_reduction: data = imaging.demosaic(data).post_process_local_color_ratio(0.80 * 65535) utility.imsave(data, "images/" + image_name + "_out_local_color_ratio.png", "uint16") edge_detection_kernel_size = 5 edge_threshold = 0.05 # first output is main output, second output is edge_location is a debug output data, _ = imaging.demosaic(data).post_process_median_filter(edge_detection_kernel_size, edge_threshold) utility.imsave(data, "images/" + image_name + "_out_median_filter.png", "uint16") # utility.imsave(edge_location*65535, "images/" + image_name + "_edge_location.png", "uint16") else: pass # =================================== # Color correction # =================================== if do_color_correction: data = imaging.color_correction(data, raw.get_color_matrix()).apply_cmatrix() utility.imsave(data, "images/" + image_name + "_out_color_correction.png", "uint16") else: pass # =================================== # Gamma # =================================== if do_gamma: # brightening data = imaging.nonlinearity(data, "brightening").luma_adjustment(80.) # gamma by value #data = imaging.nonlinearity(data, "gamma").by_value(1/2.2, [0, 65535]) # gamma by table # data = imaging.nonlinearity(data, "gamma").by_table("tables/gamma_2.4.txt", "gamma", [0, 65535]) # gamma by value data = imaging.nonlinearity(data, "gamma").by_equation(-0.9, -8.0, [0, 65535]) utility.imsave(data, "images/" + image_name + "_out_gamma.png", "uint16") else: pass # =================================== # Chromatic aberration correction # =================================== if do_chromatic_aberration_correction: nsr_threshold = 90. cr_threshold = 6425./2 data = imaging.chromatic_aberration_correction(data).purple_fringe_removal(nsr_threshold, cr_threshold) utility.imsave(data, "images/" + image_name + "_out_purple_fringe_removal.png", "uint16") else: pass # =================================== # Tone mapping # =================================== if do_tone_mapping: data = imaging.tone_mapping(data).nonlinear_masking(1.0) utility.imsave(data, "images/" + image_name + "_out_tone_mapping_nl_masking.png", "uint16") # data = imaging.tone_mapping(data).dynamic_range_compression("normal", [-25., 260.], [0, 65535]) # utility.imsave(data, "images/" + image_name + "_out_tone_mapping_drc.png", "uint16") else: pass # =================================== # Memory color enhancement # =================================== if do_memory_color_enhancement: # target_hue = [30., -115., 100.] # hue_preference = [45., -90., 130.] # hue_sigma = [20., 10., 5.] # is_both_side = [True, False, False] # multiplier = [0.6, 0.6, 0.6] # chroma_preference = [25., 17., 30.] # chroma_sigma = [10., 10., 5.] target_hue = [30., -125., 100.] hue_preference = [20., -118., 130.] hue_sigma = [20., 10., 5.] is_both_side = [True, False, False] multiplier = [0.6, 0.6, 0.6] chroma_preference = [25., 14., 30.] chroma_sigma = [10., 10., 5.] data = imaging.memory_color_enhancement(data).by_hue_squeeze(target_hue,\ hue_preference,\ hue_sigma,\ is_both_side,\ multiplier,\ chroma_preference,\ chroma_sigma) utility.imsave(data, "images/" + image_name + "_out_memory_color_enhancement.png", "uint16") else: pass # =================================== # Noise reduction # =================================== if do_noise_reduction: # sigma filter parameters neighborhood_size = 7 sigma = [1000, 500, 500] data = imaging.noise_reduction(data).sigma_filter(neighborhood_size, sigma) utility.imsave(data, "images/" + image_name + "_out_noise_reduction.png", "uint16") else: pass # =================================== # Sharpening # =================================== if do_sharpening: data = imaging.sharpening(data).unsharp_masking() utility.imsave(data, "images/" + image_name + "_out_sharpening.png", "uint16") else: pass # =================================== # Distortion correction # =================================== if do_distortion_correction: correction_type="barrel-1" strength=0.5 zoom_type="fit" clip_range=[0, 65535] data = imaging.distortion_correction(data).empirical_correction(correction_type, strength, zoom_type, clip_range) utility.imsave(data, "images/" + image_name + "_out_distortion_correction.png", "uint16") else: pass

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src/pywriter/csv/csv_file.py

peter88213/PyWriter

1

169947

<reponame>peter88213/PyWriter """Provide a generic class for csv file import. Other csv file representations inherit from this class. Copyright (c) 2021 <NAME> For further information see https://github.com/peter88213/PyWriter Published under the MIT License (https://opensource.org/licenses/mit-license.php) """ import os import csv from pywriter.model.novel import Novel class CsvFile(Novel): """csv file representation. - Records are separated by line breaks. - Data fields are delimited by the _SEPARATOR character. """ EXTENSION = '.csv' # overwrites Novel.EXTENSION _SEPARATOR = ',' # delimits data fields within a record. rowTitles = [] def read(self): """Parse the csv file located at filePath, fetching the rows. Check the number of fields in each row. Return a message beginning with SUCCESS or ERROR. Override the superclass method. """ self.rows = [] cellsPerRow = len(self.rowTitles) try: with open(self.filePath, newline='', encoding='utf-8') as f: reader = csv.reader(f, delimiter=self._SEPARATOR) for row in reader: # Each row read from the csv file is returned # as a list of strings if len(row) != cellsPerRow: return 'ERROR: Wrong csv structure.' self.rows.append(row) except(FileNotFoundError): return 'ERROR: "' + os.path.normpath(self.filePath) + '" not found.' except: return 'ERROR: Can not parse "' + os.path.normpath(self.filePath) + '".' return 'SUCCESS' def get_list(self, text): """Split a sequence of comma separated strings into a list of strings. Remove leading and trailing spaces, if any. """ elements = [] tempList = text.split(',') for element in tempList: elements.append(element.lstrip().rstrip()) return elements

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lib/src/align/aligner/basic/BasicAlignerStrategy.py

thormeier-fhnw-repos/ip619bb-i4ds02-audio-text-alignment

0

169960

<reponame>thormeier-fhnw-repos/ip619bb-i4ds02-audio-text-alignment<filename>lib/src/align/aligner/basic/BasicAlignerStrategy.py from typing import List from lib.src.align.aligner.AbstractAlignerStrategy import AbstractAlignerStrategy from lib.src.align.utils.transcript_to_sentences import transcript_to_sentences from lib.src.model.Sentence import Sentence from pydub import AudioSegment import time from bin._bin import bin_print class BasicAlignerStrategy(AbstractAlignerStrategy): """ Basic alignment based on sentence length. """ @staticmethod def perform_alignment(transcript: str, wav_path: str, verbosity: int) -> List["Sentence"]: """ Performs a basic alignment :param transcript: Path to transcript :param wav_path: Path to wav file :param verbosity: Verbosity level :return: Aligned sentences """ start_time = time.time() audio_segment = AudioSegment.from_wav(wav_path) duration = audio_segment.duration_seconds with open(transcript, encoding="utf-8") as f: transcript = f.read() transcript = transcript.replace("\n", " ") sentences = transcript_to_sentences(transcript) number_of_chars_total = sum([len(sentence.sentence) for sentence in sentences]) start = 0.0 for sentence in sentences: end = start + len(sentence.sentence) / number_of_chars_total * duration sentence.interval.start = start sentence.interval.end = end start = end end_time = time.time() bin_print(verbosity, 2, "Time elapsed for", wav_path, ":", (end_time - start_time)) return sentences

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imgaug/augmenters/flip.py

pAoenix/image-Augmented

1

3912

<reponame>pAoenix/image-Augmented """ Augmenters that apply mirroring/flipping operations to images. Do not import directly from this file, as the categorization is not final. Use instead :: from imgaug import augmenters as iaa and then e.g. :: seq = iaa.Sequential([ iaa.Fliplr((0.0, 1.0)), iaa.Flipud((0.0, 1.0)) ]) List of augmenters: * Fliplr * Flipud """ from __future__ import print_function, division, absolute_import from .. import parameters as iap import numpy as np import six.moves as sm from .meta import Augmenter class Fliplr(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long """ Flip/mirror input images horizontally. Parameters ---------- p : number or StochasticParameter, optional(default=0) Probability of each image to get flipped. name : string, optional(default=None) See `Augmenter.__init__()` deterministic : bool, optional(default=False) See `Augmenter.__init__()` random_state : int or np.random.RandomState or None, optional(default=None) See `Augmenter.__init__()` Examples -------- >>> aug = iaa.Fliplr(0.5) would horizontally flip/mirror 50 percent of all input images. >>> aug = iaa.Fliplr(1.0) would horizontally flip/mirror all input images. """ def __init__(self, p=0, name=None, deterministic=False, random_state=None): super(Fliplr, self).__init__(name=name, deterministic=deterministic, random_state=random_state) self.p = iap.handle_probability_param(p, "p") def _augment_images(self, images, random_state, parents, hooks): nb_images = len(images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i in sm.xrange(nb_images): if samples[i] == 1: images[i] = np.fliplr(images[i]) return images def _augment_heatmaps(self, heatmaps, random_state, parents, hooks): arrs_flipped = self._augment_images( [heatmaps_i.arr_0to1 for heatmaps_i in heatmaps], random_state=random_state, parents=parents, hooks=hooks ) for heatmaps_i, arr_flipped in zip(heatmaps, arrs_flipped): heatmaps_i.arr_0to1 = arr_flipped return heatmaps def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks): nb_images = len(keypoints_on_images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i, keypoints_on_image in enumerate(keypoints_on_images): if samples[i] == 1: width = keypoints_on_image.shape[1] for keypoint in keypoints_on_image.keypoints: keypoint.x = (width - 1) - keypoint.x return keypoints_on_images def get_parameters(self): return [self.p] class Flipud(Augmenter): # pylint: disable=locally-disabled, unused-variable, line-too-long """ Flip/mirror input images vertically. Parameters ---------- p : number or StochasticParameter, optional(default=0) Probability of each image to get flipped. name : string, optional(default=None) See `Augmenter.__init__()` deterministic : bool, optional(default=False) See `Augmenter.__init__()` random_state : int or np.random.RandomState or None, optional(default=None) See `Augmenter.__init__()` Examples -------- >>> aug = iaa.Flipud(0.5) would vertically flip/mirror 50 percent of all input images. >>> aug = iaa.Flipud(1.0) would vertically flip/mirror all input images. """ def __init__(self, p=0, name=None, deterministic=False, random_state=None): super(Flipud, self).__init__(name=name, deterministic=deterministic, random_state=random_state) self.p = iap.handle_probability_param(p, "p") def _augment_images(self, images, random_state, parents, hooks): nb_images = len(images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i in sm.xrange(nb_images): if samples[i] == 1: images[i] = np.flipud(images[i]) return images def _augment_heatmaps(self, heatmaps, random_state, parents, hooks): arrs_flipped = self._augment_images( [heatmaps_i.arr_0to1 for heatmaps_i in heatmaps], random_state=random_state, parents=parents, hooks=hooks ) for heatmaps_i, arr_flipped in zip(heatmaps, arrs_flipped): heatmaps_i.arr_0to1 = arr_flipped return heatmaps def _augment_keypoints(self, keypoints_on_images, random_state, parents, hooks): nb_images = len(keypoints_on_images) samples = self.p.draw_samples((nb_images,), random_state=random_state) for i, keypoints_on_image in enumerate(keypoints_on_images): if samples[i] == 1: height = keypoints_on_image.shape[0] for keypoint in keypoints_on_image.keypoints: keypoint.y = (height - 1) - keypoint.y return keypoints_on_images def get_parameters(self): return [self.p]

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reid_main.py

yujheli/ARN

26

61077

<reponame>yujheli/ARN<filename>reid_main.py from __future__ import print_function, division import os import numpy as np import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets from torch.utils.data import DataLoader from torchvision.utils import make_grid from torchvision import transforms as trans from tensorboardX import SummaryWriter from argparse import ArgumentParser from reid_network import AdaptReID_model from reid_dataset import AdaptReID_Dataset from reid_evaluate import evaluate from reid_loss import * import config parser = ArgumentParser() parser.add_argument("--use_gpu", default=2, type=int) parser.add_argument("--source_dataset", choices=['CUHK03', 'Duke', 'Market', 'MSMT17_V1'], type=str) parser.add_argument("--target_dataset", choices=['CUHK03', 'Duke', 'Market', 'MSMT17_V1'], type=str) parser.add_argument("--batch_size", default=8, type=int) parser.add_argument("--learning_rate", default=1e-4, type=float) parser.add_argument("--total_epochs", default=1000, type=int) parser.add_argument("--w_loss_rec", default=0.1, type=float) parser.add_argument("--w_loss_dif", default=0.1, type=float) parser.add_argument("--w_loss_mmd", default=0.1, type=float) parser.add_argument("--w_loss_ctr", default=1.0, type=float) parser.add_argument("--dist_metric", choices=['L1', 'L2', 'cosine', 'correlation'], type=str) parser.add_argument("--rank", default=1, type=int) parser.add_argument("--model_dir", default='model', type=str) parser.add_argument("--model_name", default='basic_10cls', type=str) parser.add_argument("--pretrain_model_name", default=None, type=str) args = parser.parse_args() total_batch = 4272 transform_list = [trans.RandomHorizontalFlip(p=0.5), trans.Resize(size=(config.IMAGE_HEIGHT, config.IMAGE_WIDTH)),\ trans.ToTensor(), trans.Normalize(mean=config.MEAN, std=config.STD)] def setup_gpu(): assert torch.cuda.is_available() torch.backends.cudnn.benchmark = True print('Using GPU: {}'.format(args.use_gpu)) def tb_visualize(image): return (image+1.0)*0.5 def get_batch(data_iter, data_loader): try: _, batch = next(data_iter) except: data_iter = enumerate(data_loader) _, batch = next(data_iter) if batch['image'].size(0) < args.batch_size: batch, data_iter = get_batch(data_iter, data_loader) return batch, data_iter def save_model(model, step): model_path = '{}/{}/{}_{}.pth.tar'.format(args.model_dir ,args.model_name ,args.model_name, step) torch.save(model.state_dict(), model_path) def train(): print('Model name: {}'.format(args.model_name)) classifier_output_dim = config.get_dataoutput(args.source_dataset) model = AdaptReID_model(backbone='resnet-50', classifier_output_dim=classifier_output_dim).cuda() # print(model.state_dict()) print("Loading pre-trained model...") checkpoint = torch.load('{}/{}.pth.tar'.format(args.model_dir, args.pretrain_model_name)) for name, param in model.state_dict().items(): print(name) if name not in ['classifier.linear.weight','classifier.linear.bias']: model.state_dict()[name].copy_(checkpoint[name]) # if args.pretrain_model_name is not None: # model.load_state_dict(torch.load('{}/{}.pth.tar'.format(args.model_dir, args.pretrain_model_name))) sourceData = AdaptReID_Dataset(dataset_name=args.source_dataset, mode='source', transform=trans.Compose(transform_list)) targetData = AdaptReID_Dataset(dataset_name=args.target_dataset, mode='train', transform=trans.Compose(transform_list)) sourceDataloader = DataLoader(sourceData, batch_size=args.batch_size, shuffle=True) targetDataloader = DataLoader(targetData, batch_size=args.batch_size, shuffle=True) source_iter = enumerate(sourceDataloader) target_iter = enumerate(targetDataloader) model_opt = optim.SGD(filter(lambda p: p.requires_grad, model.parameters()), lr=args.learning_rate, momentum=0.9, weight_decay=0.0005) writer = SummaryWriter('log/{}'.format(args.model_name)) match, junk = None, None for epoch in range(args.total_epochs): for batch_idx in range(total_batch): model.train() step = epoch*total_batch + batch_idx print('{}: epoch: {}/{} step: {}/{} ({:.2f}%)'.format(args.model_name, epoch+1, args.total_epochs, step+1, total_batch, float(batch_idx+1)*100.0/total_batch)) source_batch, source_iter = get_batch(source_iter, sourceDataloader) target_batch, target_iter = get_batch(target_iter, targetDataloader) source_image, source_label, _ = split_datapack(source_batch) target_image, _, _ = split_datapack(target_batch) feature_t_et_avg, feature_t_ec_avg, image_t_, pred_t, feature_s_es_avg, feature_s_ec_avg, image_s_, pred_s\ = model(image_t=target_image, image_s=source_image) #calculate loss loss_rec = loss_rec_func(image_s_, source_image) + loss_rec_func(image_t_, target_image) loss_cls = loss_cls_func(pred_s, source_label) loss_dif = loss_dif_func(feature_t_et_avg, feature_t_ec_avg) + loss_dif_func(feature_s_es_avg, feature_s_ec_avg) loss_mmd = loss_mmd_func(feature_t_ec_avg, feature_s_ec_avg) loss_ctr = loss_ctr_func(feature_s_ec_avg, source_label) loss = loss_cls + loss_rec*args.w_loss_rec + loss_dif*args.w_loss_dif + loss_ctr*args.w_loss_ctr + loss_mmd*args.w_loss_mmd #update model model_opt.zero_grad() loss.backward() model_opt.step() #write to tenserboardX if (step+1)%100==0: writer.add_image('source image', tb_visualize(source_image), step) writer.add_image('target image', tb_visualize(target_image), step) writer.add_image('source image_rec', tb_visualize(image_s_), step) writer.add_image('target image_rec', tb_visualize(image_t_), step) writer.add_scalar('loss_rec', loss_rec, step) writer.add_scalar('loss_cls', loss_cls, step) writer.add_scalar('loss_dif', loss_dif, step) writer.add_scalar('loss_ctr', loss_ctr, step) writer.add_scalar('loss_mmd', loss_ctr, step) writer.add_scalar('loss', loss, step) #evaluate if (step+1)%2000==0: rank_score, match, junk = evaluate(args, model, transform_list, match, junk) writer.add_scalar('rank1_score', rank_score, step) save_model(model, step) writer.close() setup_gpu() train()

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scripts/libfranka_gui_gripper_run.py

nbfigueroa/franka_interactive_controllers

6

8052

#!/usr/bin/env python3 import shlex from tkinter import * from tkinter import messagebox from psutil import Popen top = Tk() top.title("Franka Gripper Control") top.geometry("300x75") def open(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 1')) messagebox.showinfo("Open Gripper", "Gripper Opened") node_process.terminate() def close(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 0')) messagebox.showinfo("Close Gripper", "Gripper Closed") node_process.terminate() B1 = Button(top, text = "Open Gripper", command = open) B1.place(x = 30,y = 20) B2 = Button(top, text = "Close Gripper", command = close) B2.place(x = 160,y = 20) top.mainloop()

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Numpy-project/code.py

nish700/ga-learner-dsmp-repo

0

133963

# -------------- # Importing header files import numpy as np # Path of the file has been stored in variable called 'path' #New record new_record=[[50, 9, 4, 1, 0, 0, 40, 0]] #Code starts here data = np.genfromtxt(path, delimiter=',' ,skip_header=1) census = np.concatenate((data,np.asarray(new_record))) print(census, type(census)) # -------------- #Code starts here import numpy as np age = census[:,0] # indexing an array, all rows and only the first column max_age = max(age) min_age = min(age) age_mean = np.mean(age) age_std = np.std(age) print(age) print(max_age) print(min_age) print(age_mean) print(age_std) # -------------- #Code starts here race_0 = census[census[:,2] == 0] race_1 = census[census[:,2] == 1] race_2 = census[census[:,2] == 2] race_3 = census[census[:,2] == 3] race_4 = census[census[:,2] == 4] len_0 = len(race_0) len_1 = len(race_1) len_2 = len(race_2) len_3 = len(race_3) len_4 = len(race_4) len_race = [len_0,len_1,len_2,len_3,len_4] minority_race = len_race.index(min(len_race)) print(minority_race) # -------------- #Code starts here senior_citizens = census[census[:,0]>60] working_hours_sum = sum(senior_citizens[:,6]) senior_citizens_len = len(senior_citizens) avg_working_hours = working_hours_sum/senior_citizens_len # print(working_hours_sum) print(avg_working_hours) # -------------- #Code starts here import numpy as np high = census[census[:,1]>10] low = census[census[:,1]<=10] avg_pay_high = np.mean(high[:,7]) avg_pay_low = np.mean(low[:,7]) print(avg_pay_high) print(avg_pay_low)

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usernamerules/simple.py

74wny0wl/entusergenerator

1

60751

<filename>usernamerules/simple.py def simple(user_data, with_separator=''): return [with_separator.join(user_data)]

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pylinex/basis/GramSchmidtBasis.py

CU-NESS/pylinex

0

159564

<gh_stars>0 """ File: pylinex/basis/GramSchmidtBasis.py Author: <NAME> Date: 3 Sep 2017 Description: File containing subclass of Basis which implements a set of basis vectors created through a Gram-Schmidt orthogonalization procedure. """ from __future__ import division import numpy as np from ..expander import NullExpander from .Basis import Basis def orthonormal_basis(seed_vectors, error=None): """ Creates an orthonormal basis from the given seed vectors using a Gram-Schmidt orthogonalization procedure. seed_vectors: vectors with which to generate new modes using the Gram-Schmidt orthogonalization procedure error: 1D numpy.ndarray containing error values with which to define 'orthogonal' returns: a set of basis vectors. a numpy.ndarray of the same shape as the seed vectors """ if type(error) is type(None): error = np.ones_like(seed_vectors[0]) inverse_error = 1 / error covariance = np.diag(error ** 2) inverse_covariance = np.diag(inverse_error ** 2) correction_matrix = inverse_covariance.copy() def dot_product(u, v): return np.dot(u * inverse_error, v * inverse_error) basis = [] for degree in range(len(seed_vectors)): pbv = seed_vectors[degree] cpbv = np.dot(pbv, correction_matrix) basis.append(np.dot(covariance, cpbv) / np.sqrt(np.dot(pbv, cpbv))) CinvF = np.reshape(np.dot(inverse_covariance, basis[-1]), (-1, 1)) correction_matrix -= np.dot(CinvF, CinvF.T) return np.array(basis) def orthonormal_polynomial_basis(num_points, max_degree, error=None): """ Creates a new Legendre polynomial-like basis with the given number of points and basis vectors. num_points: number of points to include in the basis vectors max_degree: one less than the number of basis vectors desired error: 1D numpy.ndarray with which to define 'orthogonal' returns: 2D numpy.ndarray of shape (md+1,np) where md is the max_degree given and np is the num_points given """ xs = np.linspace(-1, 1, num_points) seed_vectors = [(xs ** degree) for degree in range(max_degree + 1)] return orthonormal_basis(seed_vectors, error=error) def orthonormal_harmonic_basis(num_points, max_degree, error=None): """ Creates a new Fourier series-like basis with the given number of points and basis vectors. num_points: number of points to include in the basis vectors max_degree: determines number of basis vectors returned error: 1D numpy.ndarray with which to define 'orthogonal' returns: 2D numpy.ndarray of shape (2*md+1,np) where md is the max_degree given and np is the num_points given """ xs = np.linspace(-np.pi, np.pi, num_points) num_basis = (2 * max_degree) + 1 def vector(index): scaled_xs = (((index + 1) // 2) * xs) is_sin = bool(index % 2) if is_sin: return np.sin(scaled_xs) else: return np.cos(scaled_xs) seed_vectors = np.array([vector(i) for i in range(num_basis)]) return orthonormal_basis(seed_vectors, error=error) class GramSchmidtBasis(Basis): """ Class representing a Basis object whose vectors are calculated through a Gram-Schmidt orthogonalization procedure. """ def __init__(self, seed_vectors, error=None, expander=None,\ translation=None): """ Initializes the new GramSchmidtBasis object. seed_vectors: the vectors with which to generate further modes through the Gram-Schmidt orthogonalization procedure error: the error with which to define 'orthogonal' expander: if None, no expansion is applied otherwise, expander must be an Expander object. translation: if None, no constant additive is included in the results of calling this Basis. otherwise: should be a 1D numpy.ndarray of the same length as the seed vectors. It is the (unexpanded) result of calling the basis on a zero-vector of parameters """ if isinstance(seed_vectors, Basis): basis = orthonormal_basis(seed_vectors.basis, error=error) else: basis = orthonormal_basis(seed_vectors, error=error) Basis.__init__(self, basis, expander=expander, translation=translation) @property def even_subbasis(self): """ Property storing the subbasis of this one which contains only the even functions (as long as the even-index seed vectors given to the initializer were even). Returns Basis object. """ return self[::2] @property def odd_subbasis(self): """ Property storing the subbasis of this one which contains only the odd functions (as long as the odd-index seed vectors given to the initializer were odd). Returns Basis object. """ return self[1::2]

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daemon/lib/traceroute.py

shawnduong/CyberTrace

2

40371

<reponame>shawnduong/CyberTrace import subprocess def traceroute(dest: str) -> dict: """ Trace the route to some destination IP and return a dict of intermediates. In order to prevent the daemon itself from needing to run with elevated privileges, this is primarily handled by the system's traceroute utility. """ # Sanitize input. for char in dest: if char not in "ABCDEFabcdef12345567890.:": return -1 # Run system traceroute. p = subprocess.Popen(["traceroute", "-q 1", dest], stdout=subprocess.PIPE) d = p.stdout.read().decode("utf-8") hops = {} # Parse the output. for line in d.split("\n"): try: tokens = line.split() n = int(tokens[0]) if tokens[1] == "*": ip = "?" else: ip = tokens[2].strip("(").strip(")") hops[n] = ip except: pass return hops

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test_api.py

atifar/mini-key-value

0

26779

def test_check_sanity(client): resp = client.get('/sanity') assert resp.status_code == 200 assert 'Sanity check passed.' == resp.data.decode() # 'list collections' tests def test_get_api_root(client): resp = client.get('/', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert 'keys_url' in resp_data assert len(resp_data) == 1 assert resp_data['keys_url'][-5:] == '/keys' def test_delete_api_root_not_allowed(client): resp = client.delete('/', content_type='application/json') assert resp.status_code == 405 # 'list keys' tests def test_get_empty_keys_list(client): resp = client.get('/keys', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert len(resp_data) == 0 def test_get_nonempty_keys_list(client, keys, add_to_keys): add_to_keys({'key': 'babboon', 'value': 'Larry'}) add_to_keys({'key': 'bees', 'value': ['Ann', 'Joe', 'Dee']}) resp = client.get('/keys', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert isinstance(resp_data, list) assert len(resp_data) == 2 for doc_idx in (0, 1): for k in ('key', 'http_url'): assert k in resp_data[doc_idx] if resp_data[doc_idx]['key'] == 'babboon': assert resp_data[doc_idx]['http_url'][-13:] == '/keys/babboon' else: assert resp_data[doc_idx]['http_url'][-10:] == '/keys/bees' def test_delete_on_keys_not_allowed(client): resp = client.delete('/keys', content_type='application/json') assert resp.status_code == 405 # 'get a key' tests def test_get_existing_key(client, keys, add_to_keys): add_to_keys({'key': 'babboon', 'value': 'Larry'}) add_to_keys({'key': 'bees', 'value': ['Ann', 'Joe', 'Dee']}) resp = client.get('/keys/bees', content_type='application/json') assert resp.status_code == 200 resp_data = resp.get_json() assert isinstance(resp_data, dict) for k in ('key', 'http_url', 'value'): assert k in resp_data assert resp_data['key'] == 'bees' assert resp_data['http_url'][-10:] == '/keys/bees' assert resp_data['value'] == ['Ann', 'Joe', 'Dee'] def test_get_nonexisting_key(client, keys): resp = client.get('/keys/bees', content_type='application/json') assert resp.status_code == 404 def test_post_on_a_key_not_allowed(client): resp = client.post('/keys/bees', content_type='application/json') assert resp.status_code == 405 # 'create a key' tests def test_create_new_key(client, keys): new_doc = {'key': 'oscillator', 'value': 'Colpitts'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 201 resp_data = resp.get_json() assert isinstance(resp_data, dict) for k in ('key', 'http_url', 'value'): assert k in resp_data assert resp_data['key'] == new_doc['key'] assert resp_data['value'] == new_doc['value'] assert resp_data['http_url'][-16:] == '/keys/oscillator' def test_create_duplicate_key(client, keys, add_to_keys): new_doc = {'key': 'oscillator', 'value': 'Colpitts'} add_to_keys(new_doc.copy()) resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == "Can't create duplicate key (oscillator)." def test_create_new_key_missing_key(client, keys): new_doc = {'value': 'Colpitts'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Please provide the missing "key" parameter!' def test_create_new_key_missing_value(client, keys): new_doc = {'key': 'oscillator'} resp = client.post( '/keys', json=new_doc, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Please provide the missing "value" ' \ 'parameter!' # 'update a key' tests def test_update_a_key_existing(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) update_value = {'value': ['Pierce', 'Hartley']} resp = client.put( '/keys/oscillator', json=update_value, content_type='application/json' ) assert resp.status_code == 204 def test_update_a_key_nonexisting(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) update_value = {'value': ['Pierce', 'Hartley']} resp = client.put( '/keys/gadget', json=update_value, content_type='application/json' ) assert resp.status_code == 400 resp_data = resp.get_json() assert 'error' in resp_data assert resp_data['error'] == 'Update failed.' # 'delete a key' tests def test_delete_a_key_existing(client, keys, add_to_keys): add_to_keys({'key': 'oscillator', 'value': 'Colpitts'}) resp = client.delete( '/keys/oscillator', content_type='application/json' ) assert resp.status_code == 204 def test_delete_a_key_nonexisting(client, keys): resp = client.delete( '/keys/oscillator', content_type='application/json' ) assert resp.status_code == 404

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TSNE/clustering.py

KatherLab/Pathology_Adversarial

0

114995

<reponame>KatherLab/Pathology_Adversarial # -*- coding: utf-8 -*- """ Created on Tue Jul 13 2021 @author: dcifci """ import numpy as np import seaborn as sns import pandas as pd import matplotlib.pyplot as plt import matplotlib as mpl from sklearn.manifold import TSNE from dataclasses import dataclass from sklearn.decomposition import PCA @dataclass class DataClustering(): """A class for holding clustering objects""" name_project: str npy_feature_vectors: str npy_labels: str ss_im_names: str def load_data(self): self.df = pd.read_csv(self.ss_im_names) self.X = np.load(self.npy_feature_vectors) self.y = np.load(self.npy_labels) def cluster_tSNE(self): self.load_data() tsne = TSNE(n_components=2) X_2d = tsne.fit_transform(self.X) self.df["labels"] = self.y.T.reshape(-1) self.df["comp-1"] = X_2d[:,0] self.df["comp-2"] = X_2d[:,1] def cluster_PCA_tSNE(self): self.load_data() pca = PCA(n_components=50) pca_result = pca.fit_transform(self.X) tsne = TSNE(n_components=2, perplexity=5) X_2d = tsne.fit_transform(pca_result) self.df["labels"] = self.y.T.reshape(-1) self.df["comp-1"] = X_2d[:,0] self.df["comp-2"] = X_2d[:,1] def plot_scatter(self): plt.figure(figsize=(16,10)) n_classes = len(self.df["labels"].unique()) sns.scatterplot(x="comp-1", y="comp-2", hue=self.df.labels.tolist(), palette=sns.color_palette("hls", n_classes), data=self.df).set(title="T-SNE projection") #plt.show() plt.savefig("./out_visuals/out_scatter_dots_" + self.name_project + ".png") def plot_imgs(self): fig, ax = plt.subplots() plt.figure(figsize=(16,10)) x_min = int(self.df["comp-1"].min()) x_max = int(self.df["comp-1"].max()) y_min = int(self.df["comp-2"].min()) y_max = int(self.df["comp-2"].max()) for im in self.df["im_names"]: with mpl.cbook.get_sample_data(im) as file: arr_image = plt.imread(file) ax.set_xlim([x_min-30, x_max+30]) ax.set_ylim([y_min-30, y_max+30]) ax.set_title("t-SNE projection with images") ax.set_xlabel('comp-1') ax.set_ylabel('comp-2') ax.lines = [] #ax.axis("off") #ax.set_visible(False) idx = self.df[self.df["im_names"] == im].index.values[0] x = self.df["comp-1"][idx] y = self.df["comp-2"][idx] axin = ax.inset_axes([x,y,2,2],transform=ax.transData) axin.imshow(arr_image, cmap="gray") axin.axis("off") #plt.show() # fig.set_size_inches(20, 20) fig.savefig("./out_visuals/out_imgs_" + self.name_project + ".tiff", format="tiff", dpi=1000)

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src/citycode.py

masaminh/weatherapi

0

170616

"""市町村コード関係の関数群.""" from collections import namedtuple Urls = namedtuple('Urls', 'hourly') def get_cityname(code): """市町村名を取得する. Arguments: code {str} -- 市町村コード Returns: str -- 市町村名 """ if code != '01101': return None return "札幌市中央区" def get_tenkijp_urls(code): """tenki.jpのurlを取得する. Arguments: code {str} -- 市町村コード Returns: Urls -- tenki.jpのURL情報 """ if code != '01101': return None urls = Urls( hourly='https://tenki.jp/forecast/1/2/1400/1101/1hour.html') return urls def get_weathernews_urls(code): """weathernewsのurlを取得する. Arguments: code {str} -- 市町村コード Returns: Urls -- weathernewsのURL情報 """ if code != '01101': return None urls = Urls( hourly='https://weathernews.jp/onebox/tenki/hokkaido/01101/') return urls

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main.py

chillum1718/EffcientNetV2

0

3054

<filename>main.py import argparse import csv import os import torch import tqdm from torch import distributed from torch.utils import data from torchvision import datasets from torchvision import transforms from nets import nn from utils import util data_dir = os.path.join('..', 'Dataset', 'IMAGENET') def batch(images, target, model, criterion=None): images = images.cuda() target = target.cuda() if criterion: with torch.cuda.amp.autocast(): loss = criterion(model(images), target) return loss else: return util.accuracy(model(images), target, top_k=(1, 5)) def train(args): epochs = 350 batch_size = 288 util.set_seeds(args.rank) model = nn.EfficientNet().cuda() lr = batch_size * torch.cuda.device_count() * 0.256 / 4096 optimizer = nn.RMSprop(util.add_weight_decay(model), lr, 0.9, 1e-3, momentum=0.9) ema = nn.EMA(model) if args.distributed: model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.local_rank]) else: model = torch.nn.DataParallel(model) criterion = nn.CrossEntropyLoss().cuda() normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) dataset = datasets.ImageFolder(os.path.join(data_dir, 'train'), transforms.Compose([util.RandomResize(), transforms.ColorJitter(0.4, 0.4, 0.4), transforms.RandomHorizontalFlip(), util.RandomAugment(), transforms.ToTensor(), normalize])) if args.distributed: sampler = torch.utils.data.distributed.DistributedSampler(dataset) else: sampler = None loader = data.DataLoader(dataset, batch_size, sampler=sampler, num_workers=8, pin_memory=True) scheduler = nn.StepLR(optimizer) amp_scale = torch.cuda.amp.GradScaler() with open(f'weights/{scheduler.__str__()}.csv', 'w') as f: if args.local_rank == 0: writer = csv.DictWriter(f, fieldnames=['epoch', 'acc@1', 'acc@5']) writer.writeheader() best_acc1 = 0 for epoch in range(0, epochs): if args.distributed: sampler.set_epoch(epoch) if args.local_rank == 0: print(('\n' + '%10s' * 2) % ('epoch', 'loss')) bar = tqdm.tqdm(loader, total=len(loader)) else: bar = loader model.train() for images, target in bar: loss = batch(images, target, model, criterion) optimizer.zero_grad() amp_scale.scale(loss).backward() amp_scale.step(optimizer) amp_scale.update() ema.update(model) torch.cuda.synchronize() if args.local_rank == 0: bar.set_description(('%10s' + '%10.4g') % ('%g/%g' % (epoch + 1, epochs), loss)) scheduler.step(epoch + 1) if args.local_rank == 0: acc1, acc5 = test(ema.model.eval()) writer.writerow({'acc@1': str(f'{acc1:.3f}'), 'acc@5': str(f'{acc5:.3f}'), 'epoch': str(epoch + 1).zfill(3)}) util.save_checkpoint({'state_dict': ema.model.state_dict()}, acc1 > best_acc1) best_acc1 = max(acc1, best_acc1) if args.distributed: torch.distributed.destroy_process_group() torch.cuda.empty_cache() def test(model=None): if model is None: model = nn.EfficientNet() model.load_state_dict(torch.load('weights/best.pt', 'cpu')['state_dict']) model = model.cuda() model.eval() normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) dataset = datasets.ImageFolder(os.path.join(data_dir, 'val'), transforms.Compose([transforms.Resize(416), transforms.CenterCrop(384), transforms.ToTensor(), normalize])) loader = data.DataLoader(dataset, 48, num_workers=os.cpu_count(), pin_memory=True) top1 = util.AverageMeter() top5 = util.AverageMeter() with torch.no_grad(): for images, target in tqdm.tqdm(loader, ('%10s' * 2) % ('acc@1', 'acc@5')): acc1, acc5 = batch(images, target, model) torch.cuda.synchronize() top1.update(acc1.item(), images.size(0)) top5.update(acc5.item(), images.size(0)) acc1, acc5 = top1.avg, top5.avg print('%10.3g' * 2 % (acc1, acc5)) if model is None: torch.cuda.empty_cache() else: return acc1, acc5 def print_parameters(): model = nn.EfficientNet().eval() _ = model(torch.zeros(1, 3, 224, 224)) params = sum(p.numel() for p in model.parameters()) print(f'Number of parameters: {int(params)}') def benchmark(): shape = (1, 3, 384, 384) util.torch2onnx(nn.EfficientNet().export().eval(), shape) util.onnx2caffe() util.print_benchmark(shape) def main(): # python -m torch.distributed.launch --nproc_per_node=3 main.py --train parser = argparse.ArgumentParser() parser.add_argument("--local_rank", default=0, type=int) parser.add_argument('--benchmark', action='store_true') parser.add_argument('--train', action='store_true') parser.add_argument('--test', action='store_true') args = parser.parse_args() args.distributed = False args.rank = 0 if 'WORLD_SIZE' in os.environ: args.distributed = int(os.environ['WORLD_SIZE']) > 1 if args.distributed: torch.cuda.set_device(args.local_rank) torch.distributed.init_process_group(backend='nccl', init_method='env://') args.rank = torch.distributed.get_rank() if args.local_rank == 0: if not os.path.exists('weights'): os.makedirs('weights') if args.local_rank == 0: print_parameters() if args.benchmark: benchmark() if args.train: train(args) if args.test: test() if __name__ == '__main__': main()

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test/functional/test-framework/storage_devices/disk.py

josehu07/open-cas-linux-mf

2

85835

<filename>test/functional/test-framework/storage_devices/disk.py # # Copyright(c) 2019-2020 Intel Corporation # SPDX-License-Identifier: BSD-3-Clause-Clear # import itertools from enum import IntEnum from test_utils import disk_finder from test_utils.output import CmdException from test_utils.size import Unit from test_tools import disk_utils, fs_utils from storage_devices.device import Device from datetime import timedelta from test_utils.os_utils import wait from core.test_run import TestRun import json import re class DiskType(IntEnum): hdd = 0 hdd4k = 1 sata = 2 nand = 3 optane = 4 class DiskTypeSetBase: def resolved(self): raise NotImplementedError() def types(self): raise NotImplementedError() def json(self): return json.dumps({ "type": "set", "values": [t.name for t in self.types()] }) def __lt__(self, other): return min(self.types()) < min(other.types()) def __le__(self, other): return min(self.types()) <= min(other.types()) def __eq__(self, other): return min(self.types()) == min(other.types()) def __ne__(self, other): return min(self.types()) != min(other.types()) def __gt__(self, other): return min(self.types()) > min(other.types()) def __ge__(self, other): return min(self.types()) >= min(other.types()) class DiskTypeSet(DiskTypeSetBase): def __init__(self, *args): self.__types = set(*args) def resolved(self): return True def types(self): return self.__types class DiskTypeLowerThan(DiskTypeSetBase): def __init__(self, disk_name): self.__disk_name = disk_name def resolved(self): return self.__disk_name in TestRun.disks def types(self): if not self.resolved(): raise LookupError("Disk type not resolved!") disk_type = TestRun.disks[self.__disk_name].disk_type return set(filter(lambda d: d < disk_type, [*DiskType])) def json(self): return json.dumps({ "type": "operator", "name": "lt", "args": [self.__disk_name] }) class Disk(Device): def __init__( self, path, disk_type: DiskType, serial_number, block_size, ): Device.__init__(self, path) self.device_name = path.split('/')[-1] self.serial_number = serial_number self.block_size = Unit(block_size) self.disk_type = disk_type self.partitions = [] def create_partitions( self, sizes: [], partition_table_type=disk_utils.PartitionTable.gpt): disk_utils.create_partitions(self, sizes, partition_table_type) def umount_all_partitions(self): TestRun.LOGGER.info( f"Umounting all partitions from: {self.system_path}") cmd = f'umount -l {self.system_path}*?' TestRun.executor.run(cmd) def remove_partitions(self): for part in self.partitions: if part.is_mounted(): part.unmount() if disk_utils.remove_partitions(self): self.partitions.clear() def is_detected(self): if self.serial_number: serial_numbers = disk_finder.get_all_serial_numbers() if self.serial_number not in serial_numbers: return False else: self.device_name = serial_numbers[self.serial_number] self.system_path = f"/dev/{self.device_name}" for part in self.partitions: part.system_path = disk_utils.get_partition_path( part.parent_device.system_path, part.number) return True elif self.system_path: output = fs_utils.ls_item(f"{self.system_path}") return fs_utils.parse_ls_output(output)[0] is not None raise Exception("Couldn't check if device is detected by the system") def wait_for_plug_status(self, should_be_visible): if not wait(lambda: should_be_visible == self.is_detected(), timedelta(minutes=1), timedelta(seconds=1)): raise Exception(f"Timeout occurred while tying to " f"{'plug' if should_be_visible else 'unplug'} disk.") def plug(self): if self.is_detected(): return self.execute_plug_command() self.wait_for_plug_status(True) def unplug(self): if not self.is_detected(): return if not self.device_name: raise Exception("Couldn't unplug disk without disk id in /dev/.") self.execute_unplug_command() self.wait_for_plug_status(False) if self.serial_number: self.device_name = None @staticmethod def plug_all_disks(): TestRun.executor.run_expect_success(NvmeDisk.plug_all_command) TestRun.executor.run_expect_success(SataDisk.plug_all_command) def __str__(self): disk_str = f'system path: {self.system_path}, type: {self.disk_type}, ' \ f'serial: {self.serial_number}, size: {self.size}, ' \ f'block size: {self.block_size}, partitions:\n' for part in self.partitions: disk_str += f'\t{part}' return disk_str @staticmethod def create_disk(path, disk_type: DiskType, serial_number, block_size): if disk_type is DiskType.nand or disk_type is DiskType.optane: return NvmeDisk(path, disk_type, serial_number, block_size) else: return SataDisk(path, disk_type, serial_number, block_size) class NvmeDisk(Disk): plug_all_command = "echo 1 > /sys/bus/pci/rescan" def __init__(self, path, disk_type, serial_number, block_size): Disk.__init__(self, path, disk_type, serial_number, block_size) def execute_plug_command(self): TestRun.executor.run_expect_success(NvmeDisk.plug_all_command) def execute_unplug_command(self): if TestRun.executor.run( f"echo 1 > /sys/block/{self.device_name}/device/remove").exit_code != 0: output = TestRun.executor.run( f"echo 1 > /sys/block/{self.device_name}/device/device/remove") if output.exit_code != 0: raise CmdException(f"Failed to unplug PCI disk using sysfs.", output) class SataDisk(Disk): plug_all_command = "for i in $(find -H /sys/devices/ -path '*/scsi_host/*/scan' -type f); " \ "do echo '- - -' > $i; done;" def __init__(self, path, disk_type, serial_number, block_size): self.plug_command = SataDisk.plug_all_command Disk.__init__(self, path, disk_type, serial_number, block_size) def execute_plug_command(self): TestRun.executor.run_expect_success(self.plug_command) def execute_unplug_command(self): TestRun.executor.run_expect_success( f"echo 1 > {self.get_sysfs_properties(self.device_name).full_path}/device/delete") def get_sysfs_properties(self, device_name): ls_command = f"$(find -H /sys/devices/ -name {device_name} -type d)" output = fs_utils.ls_item(f"{ls_command}") sysfs_addr = fs_utils.parse_ls_output(output)[0] if not sysfs_addr: raise Exception(f"Failed to find sysfs address: ls -l {ls_command}") dirs = sysfs_addr.full_path.split('/') scsi_address = dirs[-3] matches = re.search( r"^(?P<controller>\d+)[-:](?P<port>\d+)[-:](?P<target>\d+)[-:](?P<lun>\d+)$", scsi_address) controller_id = matches["controller"] port_id = matches["port"] target_id = matches["target"] lun = matches["lun"] host_path = "/".join(itertools.takewhile(lambda x: not x.startswith("host"), dirs)) self.plug_command = f"echo '{port_id} {target_id} {lun}' > " \ f"{host_path}/host{controller_id}/scsi_host/host{controller_id}/scan" return sysfs_addr

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Python3/0947-Most-Stones-Removed-with-Same-Row-or-Column/soln.py

wyaadarsh/LeetCode-Solutions

5

1608142

class Solution: def removeStones(self, stones): """ :type stones: List[List[int]] :rtype: int """ parent = {} def find(x): if x != parent[x]: parent[x] = find(parent[x]) return parent[x] def union(x, y): parent.setdefault(x, x) parent.setdefault(y, y) parent[find(x)] = find(y) for x, y in stones: union(x, ~y) return len(stones) - len({find(x) for x in parent})

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clearfile.py

redcapattitide/Python

0

134225

f = open('C:/Users/Tom/Documents/Python/Bot/Receptura/Recept/Recept/bin/Release/moves_info.txt','w',encoding='UTF-8') f.close()

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pgmpy/factors/base.py

Stoffle/pgmpy

0

135871

from abc import abstractmethod from pgmpy.extern.six.moves import reduce class BaseFactor(object): """ Base class for Factors. Any Factor implementation should inherit this class. """ def __init__(self, *args, **kwargs): pass @abstractmethod def is_valid_cpd(self): pass def factor_product(*args): """ Returns factor product over `args`. Parameters ---------- args: `BaseFactor` instances. factors to be multiplied Returns ------- BaseFactor: `BaseFactor` representing factor product over all the `BaseFactor` instances in args. Examples -------- >>> from pgmpy.factors.discrete import DiscreteFactor >>> from pgmpy.factors import factor_product >>> phi1 = DiscreteFactor(['x1', 'x2', 'x3'], [2, 3, 2], range(12)) >>> phi2 = DiscreteFactor(['x3', 'x4', 'x1'], [2, 2, 2], range(8)) >>> phi = factor_product(phi1, phi2) >>> phi.variables ['x1', 'x2', 'x3', 'x4'] >>> phi.cardinality array([2, 3, 2, 2]) >>> phi.values array([[[[ 0, 0], [ 4, 6]], [[ 0, 4], [12, 18]], [[ 0, 8], [20, 30]]], [[[ 6, 18], [35, 49]], [[ 8, 24], [45, 63]], [[10, 30], [55, 77]]]]) """ if not all(isinstance(phi, BaseFactor) for phi in args): raise TypeError("Arguments must be factors") # Check if all of the arguments are of the same type elif len(set(map(type, args))) != 1: raise NotImplementedError( "All the args are expected to ", "be instances of the same factor class." ) return reduce(lambda phi1, phi2: phi1 * phi2, args) def factor_divide(phi1, phi2): """ Returns `DiscreteFactor` representing `phi1 / phi2`. Parameters ---------- phi1: Factor The Dividend. phi2: Factor The Divisor. Returns ------- DiscreteFactor: `DiscreteFactor` representing factor division `phi1 / phi2`. Examples -------- >>> from pgmpy.factors.discrete import DiscreteFactor >>> from pgmpy.factors import factor_product >>> phi1 = DiscreteFactor(['x1', 'x2', 'x3'], [2, 3, 2], range(12)) >>> phi2 = DiscreteFactor(['x3', 'x1'], [2, 2], range(1, 5)) >>> phi = factor_divide(phi1, phi2) >>> phi.variables ['x1', 'x2', 'x3'] >>> phi.cardinality array([2, 3, 2]) >>> phi.values array([[[ 0. , 0.33333333], [ 2. , 1. ], [ 4. , 1.66666667]], [[ 3. , 1.75 ], [ 4. , 2.25 ], [ 5. , 2.75 ]]]) """ if not isinstance(phi1, BaseFactor) or not isinstance(phi2, BaseFactor): raise TypeError("phi1 and phi2 should be factors instances") # Check if all of the arguments are of the same type elif type(phi1) != type(phi2): raise NotImplementedError( "All the args are expected to be instances", "of the same factor class." ) return phi1.divide(phi2, inplace=False)

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src/utils.py

headout/dagen-airflow

2

147251

<filename>src/utils.py __loader = None def get_template_loader(): from dagen.loader import TemplateLoader # Avoid circular imports global __loader if __loader is None: __loader = TemplateLoader() return __loader def get_managed_dags(): loader = get_template_loader() if not loader.template_classes: loader.load_templates() return loader.get_managed_dags() def refresh_dagen_templates(): loader = get_template_loader() loader.load_templates(only_if_updated=False)

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tess_exoplanet_search/jobs.py

jbcurtin/bert-etl-tess-exoplanet-search

0

68329

from bert import binding, utils, constants @binding.follow('noop') def create_data(): work_queue, done_queue, ologger = utils.comm_binders(create_data) for idx in range(0, 100): done_queue.put({ 'idx': idx }) @binding.follow(create_data, pipeline_type=constants.PipelineType.CONCURRENT) def calculate_data(): import math work_queue, done_queue, ologger = utils.comm_binders(calculate_data) for details in work_queue: details['calculated-result'] = math.pow(details['idx'], 2) done_queue.put(details) @binding.follow(calculate_data, pipeline_type=constants.PipelineType.CONCURRENT) def variation(): work_queue, done_queue, ologger = utils.comm_binders(variation) for details in work_queue: for key, value in details.items(): ologger.info(f'Key[{key}], Value[{value}], Alteration[{value % 5}]')

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api/beers/migrations/0031_matchfilter.py

haavardnk/Vinmonopolet-x-Untappd

0

178631

<filename>api/beers/migrations/0031_matchfilter.py<gh_stars>0 # Generated by Django 3.1.4 on 2020-12-11 07:30 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('beers', '0030_beer_match_manually'), ] operations = [ migrations.CreateModel( name='MatchFilter', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ], ), ]

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migrations/versions/e1c435b9e9dc_.py

vipshae/todo-lister

0

20381

<reponame>vipshae/todo-lister """empty message Revision ID: e1c435b9e9dc Revises: <PASSWORD> Create Date: 2020-06-11 14:22:00.453626 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'e1c435b9e9dc' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.alter_column('todolists', 'completed', existing_type=sa.BOOLEAN(), nullable=False) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.alter_column('todolists', 'completed', existing_type=sa.BOOLEAN(), nullable=True) # ### end Alembic commands ###

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starbursts/plots/mpl.sr_fe_5Gyr_burst.py

rcooke-ast/VICE

22

124896

import visuals import matplotlib.pyplot as plt import vice import sys def plot_sr_fe_tracks(ax): plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun", "sr", "crimson", '-') plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun", "fe", "black", ':') plot_track(ax, "../../simulations/sudden_5Gyr_5e9Msun_riaexp", "fe", "black", '--') plot_legend(ax) def plot_track(ax, name, ref, color, linestyle): """ Plots [O/X]-[X/H] tracks on a matplotlib subplot Args: ===== ax: The name of the subplot name: The name of the VICE output ref: The symbol for the reference element color: The color of the line linestyle: The linestyle to use """ out = vice.output(name) ax.plot(out.history["[%s/h]" % (ref)], out.history["[o/%s]" % (ref)], c = visuals.colors()[color], linestyle = linestyle) def plot_legend(ax): lines = 3 * [None] linestyles = ['-', ':', '--'] colors = ["red", "black", "black"] labels = ["Sr", r"Fe; $R_\text{Ia}\propto t^{-1.1}$", r"Fe; $R_\text{Ia}\propto e^{-t/\tau_\text{Ia}}$"] for i in range(3): lines[i] = ax.plot([1, 2], [1, 2], c = visuals.colors()[colors[i]], linestyle = linestyles[i], label = labels[i])[0] leg = ax.legend(loc = visuals.mpl_loc()["lower left"], ncol = 1, bbox_to_anchor = (0.01, 0.01), frameon = False) for i in range(3): lines[i].remove() if __name__ == "__main__": ax = visuals.subplots(1, 1) ax.set_xlabel("[X/H]") ax.set_ylabel("[O/X]") plot_sr_fe_tracks(ax) ax.set_xlim([-1.7, 0.1]) ax.set_ylim([0., 0.6]) plt.tight_layout() plt.savefig(sys.argv[1]) plt.clf()

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treebuilder/spinn_cnn/model.py

NLP-Discourse-SoochowU/cdtb_dp2018

6

134603

<reponame>NLP-Discourse-SoochowU/cdtb_dp2018 # -*- coding: utf-8 -*- """ @Author: oisc <<EMAIL>> @Date: 2018/5/4 @Description: SPINN shift reduce model Ref: <NAME>, <NAME>, <NAME>, et al. A fast unified model for parsing and sentence understanding[J]. 2016. """ from collections import deque import torch import torch.nn as nn import torch.nn.functional as nnfunc import numpy as np UNK = "<UNK>" PAD = "<PAD>" class SPINNState: def __init__(self, stack, buffer, tracking): self.stack = stack self.buffer = buffer self.tracking = tracking def __copy__(self): stack = [(hs.clone(), cs.clone()) for hs, cs in self.stack] buffer = deque([(hb.clone(), cb.clone()) for hb, cb in self.buffer]) h, c = self.tracking tracking = h.clone(), c.clone() return SPINNState(stack, buffer, tracking) class Reducer(nn.Module): def __init__(self, hidden_size): nn.Module.__init__(self) self.hidden_size = hidden_size self.comp = nn.Linear(self.hidden_size * 3, self.hidden_size * 5) def forward(self, state): (h1, c1), (h2, c2) = state.stack[-2], state.stack[-1] tracking = state.tracking[0].view(-1) a, i, f1, f2, o = self.comp(torch.cat([h1, h2, tracking])).chunk(5) c = a.tanh() * i.sigmoid() + f1.sigmoid() * c1 + f2.sigmoid() * c2 h = o.sigmoid() * c.tanh() return h, c class Tracker(nn.Module): def __init__(self, hidden_size): nn.Module.__init__(self) self.hidden_size = hidden_size self.rnn = nn.LSTMCell(3 * self.hidden_size, hidden_size) def init_state(self): return tuple(torch.zeros(self.hidden_size).view(1, -1) for _ in range(2)) def forward(self, state): stack, buffer, tracking = state.stack, state.buffer, state.tracking (s2h, _), (s1h, _) = stack[-2], stack[-1] b1h, _ = buffer[0] cell_input = torch.cat([s2h, s1h, b1h]).view(1, -1) tracking = self.rnn(cell_input, tracking) return tracking class MLP(nn.Module): def __init__(self, hidden_size, num_layers, dropout_p, num_classes): nn.Module.__init__(self) self.linears = nn.ModuleList([nn.Linear(hidden_size, hidden_size) for _ in range(num_layers-1)]) self.activations = nn.ModuleList([nn.ReLU() for _ in range(num_layers - 1)]) self.dropouts = nn.ModuleList([nn.Dropout(p=dropout_p) for _ in range(num_layers - 1)]) self.logits = nn.Linear(hidden_size, num_classes) def forward(self, hidden): for linear, dropout, activation in zip(self.linears, self.dropouts, self.activations): hidden = linear(hidden) hidden = activation(hidden) hidden = dropout(hidden) return self.logits(hidden) class SPINN(nn.Module): def __init__(self, hidden_size, proj_dropout, mlp_layers, mlp_dropout, edu_cutoff, position_embedding_size, unigram_filter_num, bigram_filter_num, trigram_filter_num, pos_vocab, pos_embedding_size, word_vocab, word_embedding, labels): nn.Module.__init__(self) self.hidden_size = hidden_size # build word vocab and initialize embedding word2idx = {UNK: 0, PAD: 1} for word in word_vocab: word2idx[word] = len(word2idx) self.word2idx = word2idx self.wordemb_size = word_embedding.shape[1] word_embedding = np.vstack([ np.random.normal(word_embedding.std(), word_embedding.var(), (2, self.wordemb_size)), word_embedding]) self.wordemb = nn.Embedding.from_pretrained(torch.FloatTensor(word_embedding), freeze=False) # build pos vocab and initialize embedding pos2idx = {UNK: 0, PAD: 1} for pos in pos_vocab: pos2idx[pos] = len(pos2idx) self.pos2idx = pos2idx self.posemb = nn.Embedding(len(self.pos2idx), pos_embedding_size) # word position embedding self.edu_cutoff = edu_cutoff self.position_embedding_size = position_embedding_size self.positionemb = nn.Embedding(edu_cutoff + 1, position_embedding_size) # convolution layer cnn_input_width = self.wordemb_size + pos_embedding_size + position_embedding_size self.edu_unigram_cnn = nn.Conv2d(1, unigram_filter_num, (1, cnn_input_width), padding=(0, 0)) self.edu_bigram_cnn = nn.Conv2d(1, bigram_filter_num, (2, cnn_input_width), padding=(1, 0)) self.edu_trigram_cnn = nn.Conv2d(1, trigram_filter_num, (3, cnn_input_width), padding=(2, 0)) # build label index self.label_size = len(labels) self.labels = list(labels) self.label2idx = {label: i for i, label in enumerate(self.labels)} self.dumb = nn.Parameter(torch.randn(self.hidden_size * 2)) self.dumb.requires_grad = True self.tracker = Tracker(self.hidden_size) self.reducer = Reducer(self.hidden_size) self.proj = nn.Linear(self.wordemb_size * 2 + pos_embedding_size + unigram_filter_num + bigram_filter_num + trigram_filter_num, self.hidden_size * 2) self.proj_dropout = nn.Dropout(proj_dropout) self.mlp = MLP(hidden_size, mlp_layers, mlp_dropout, self.label_size) def new_state(self, conf): stack = [self.dumb.chunk(2), self.dumb.chunk(2)] buffer = deque() for idx in conf.buffer: buffer.append(self.node_encode(conf.discourse, idx)) buffer.append(self.dumb.chunk(2)) tracker_init_state = self.tracker.init_state() state = SPINNState(stack, buffer, tracker_init_state) state = self.update_tracking(state) return state def forward(self, state): tracking_h = state.tracking[0].view(-1) return self.mlp(tracking_h) def score(self, state): label_score = nnfunc.softmax(self(state), dim=0).tolist() return dict(zip(self.labels, label_score)) def shift(self, state): state.stack.append(state.buffer.popleft()) return self.update_tracking(state) def reduce(self, state): reduced = self.reducer(state) state.stack.pop() state.stack.pop() state.stack.append(reduced) return self.update_tracking(state) def update_tracking(self, state): tracking = self.tracker(state) state.tracking = tracking return state def edu_cnn_encode(self, word_emb, tags_emb, position_emb): cnn_input = torch.cat([word_emb, tags_emb, position_emb], dim=1) # convolution input size (batch, in_chanel, seq_len, features_size) cnn_input = cnn_input.view(1, 1, cnn_input.size(0), cnn_input.size(1)) # convolution output size (batch, filter_num, seq_strip_times) unigram_output = nnfunc.relu(self.edu_unigram_cnn(cnn_input)).squeeze(-1) bigram_output = nnfunc.relu(self.edu_bigram_cnn(cnn_input)).squeeze(-1) trigram_output = nnfunc.relu(self.edu_trigram_cnn(cnn_input)).squeeze(-1) # max pooling unigram_feats = nnfunc.max_pool1d(unigram_output, kernel_size=unigram_output.size(2)).view(-1) bigram_feats = nnfunc.max_pool1d(bigram_output, kernel_size=bigram_output.size(2)).view(-1) trigram_feats = nnfunc.max_pool1d(trigram_output, kernel_size=trigram_output.size(2)).view(-1) return torch.cat([unigram_feats, bigram_feats, trigram_feats], dim=0) def node_encode(self, discourse, node_index): node = discourse[node_index] words = [word if word in self.word2idx else UNK for tag, word in discourse.tags(node.span)] or [PAD] tags = [tag if tag in self.pos2idx else UNK for tag, word in discourse.tags(node.span)] or [PAD] positions = [i + 1 if i < self.edu_cutoff else self.edu_cutoff for i, word in enumerate(discourse.words(node.span))] or [0] word_emb = self.wordemb(torch.Tensor([self.word2idx[word] for word in words]).long()) tags_emb = self.posemb(torch.Tensor([self.pos2idx[tag] for tag in tags]).long()) position_emb = self.positionemb(torch.Tensor(positions).long()) w1 = word_emb[0] w2 = word_emb[-1] t1 = tags_emb[0] cnn_emb = self.edu_cnn_encode(word_emb, tags_emb, position_emb) edu_emb = torch.cat([w1, w2, t1, cnn_emb]) proj = self.proj(edu_emb) proj_dropout = self.proj_dropout(proj) return proj_dropout.chunk(2)

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hug/__init__.py

zhwei820/aio_hug

3

71893

<filename>hug/__init__.py """hug/__init__.py Everyone needs a hug every once in a while. Even API developers. Hug aims to make developing Python driven APIs as simple as possible, but no simpler. Hug's Design Objectives: - Make developing a Python driven API as succint as a written definition. - The framework should encourage code that self-documents. - It should be fast. Never should a developer feel the need to look somewhere else for performance reasons. - Writing tests for APIs written on-top of Hug should be easy and intuitive. - Magic done once, in an API, is better then pushing the problem set to the user of the API. - Be the basis for next generation Python APIs, embracing the latest technology. Copyright (C) 2016 <NAME> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from __future__ import absolute_import from hug import (authentication, directives, exceptions, format, input_format, introspect, middleware, output_format, redirect, route, transform, types, use, validate) from hug._version import current from hug.api import API from hug.decorators import (default_input_format, default_output_format, directive, extend_api, middleware_class, request_middleware, response_middleware, startup, wraps) from hug.route import (call, connect, delete, exception, get, get_post, head, http, not_found, object, options, patch, post, put, sink, static, trace) from hug.types import create as type from hug import development_runner # isort:skip from hug import defaults # isort:skip - must be imported last for defaults to have access to all modules try: # pragma: no cover - defaulting to uvloop if it is installed import uvloop import asyncio asyncio.set_event_loop_policy(uvloop.EventLoopPolicy()) except (ImportError, AttributeError): pass __version__ = current

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utils/hpelm/tests/unittest_elm.py

mohyunho/ENAS_ELM

187

196435

<gh_stars>100-1000 # -*- coding: utf-8 -*- """ Created on Tue Mar 15 22:04:41 2016 @author: akusok """ import os import tempfile from unittest import TestCase import numpy as np import sys from hpelm import ELM class TestCorrectness(TestCase): def test_AddNeurons_WorksWithLongType(self): if sys.version_info[0] == 2: ltype = long else: ltype = int model = ELM(3, 2) L = ltype(10) model.add_neurons(L, 'tanh') def test_CrossValidation_ReturnsError(self): model = ELM(5, 2) model.add_neurons(10, 'tanh') X = np.random.rand(100, 5) T = np.random.rand(100, 2) err = model.train(X, T, 'CV', k=3) self.assertIsNotNone(err) def test_ClassificationError_CorrectWithMultipleClasses(self): T = np.zeros((100, 5)) T[:, 0] = 1 Y = np.zeros((100, 5)) Y[:, 1] = 1 model = ELM(1, 5, classification='c') self.assertEqual(1, model.error(T, Y)) def test_MultilabelError_CorrectWithMultipleClasses(self): T = np.zeros((100, 5)) T[:, 0] = 1 Y = np.zeros((100, 5)) Y[:, 1] = 1 model = ELM(1, 5, classification='ml') self.assertEqual(0.4, model.error(T, Y)) def test_LOO_CanSelectMoreThanOneNeuron(self): X = np.random.rand(100, 5) T = np.random.rand(100, 2) for _ in range(10): model = ELM(5, 2) model.add_neurons(5, 'lin') model.train(X, T, 'LOO') max1 = model.nnet.L if max1 > 1: break self.assertGreater(max1, 1) def test_LOOandOP_CanSelectMoreThanOneNeuron(self): X = np.random.rand(100, 5) T = np.random.rand(100, 2) for _ in range(10): model = ELM(5, 2) model.add_neurons(5, 'lin') model.train(X, T, 'LOO', 'OP') max2 = model.nnet.L if max2 > 1: break self.assertGreater(max2, 1)

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dsmlbc5/eda/eda.py

tahayasindemir/dsmlbc5

13

140379

<filename>dsmlbc5/eda/eda.py<gh_stars>10-100 """EDA Modülüne hoş geldiniz. Bedava bööörek var.""" import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt def check_df(dataframe, head=5): """Hello boyöööööz""" print("##################### Shape #####################") print(dataframe.shape) print("##################### Types #####################") print(dataframe.dtypes) print("##################### Head #####################") print(dataframe.head(head)) print("##################### Tail #####################") print(dataframe.tail(head)) print("##################### NA #####################") print(dataframe.isnull().sum()) print("##################### Quantiles #####################") print(dataframe.quantile([0, 0.05, 0.50, 0.95, 0.99, 1]).T) def cat_summary(dataframe, col_name, plot=False): """Gocuk.com""" print(pd.DataFrame({col_name: dataframe[col_name].value_counts(), "Ratio": 100 * dataframe[col_name].value_counts() / len(dataframe)})) print("##########################################") if plot: sns.countplot(x=dataframe[col_name], data=dataframe) plt.show() def num_summary(dataframe, numerical_col, plot=False): quantiles = [0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 0.95, 0.99] print(dataframe[numerical_col].describe(quantiles).T) if plot: dataframe[numerical_col].hist(bins=20) plt.xlabel(numerical_col) plt.title(numerical_col) plt.show() def grab_col_names(dataframe, cat_th=10, car_th=20): """ Veri setindeki kategorik, numerik ve kategorik fakat kardinal değişkenlerin isimlerini verir. Not: Kategorik değişkenlerin içerisine numerik görünümlü kategorik değişkenler de dahildir. Parameters ------ dataframe: dataframe Değişken isimleri alınmak istenilen dataframe cat_th: int, optional numerik fakat kategorik olan değişkenler için sınıf eşik değeri car_th: int, optinal kategorik fakat kardinal değişkenler için sınıf eşik değeri Returns ------ cat_cols: list Kategorik değişken listesi num_cols: list Numerik değişken listesi cat_but_car: list Kategorik görünümlü kardinal değişken listesi Examples ------ import seaborn as sns df = sns.load_dataset("iris") print(grab_col_names(df)) Notes ------ cat_cols + num_cols + cat_but_car = toplam değişken sayısı num_but_cat cat_cols'un içerisinde. Return olan 3 liste toplamı toplam değişken sayısına eşittir: cat_cols + num_cols + cat_but_car = değişken sayısı """ # cat_cols, cat_but_car cat_cols = [col for col in dataframe.columns if dataframe[col].dtypes == "O"] num_but_cat = [col for col in dataframe.columns if dataframe[col].nunique() < cat_th and dataframe[col].dtypes != "O"] cat_but_car = [col for col in dataframe.columns if dataframe[col].nunique() > car_th and dataframe[col].dtypes == "O"] cat_cols = cat_cols + num_but_cat cat_cols = [col for col in cat_cols if col not in cat_but_car] # num_cols num_cols = [col for col in dataframe.columns if dataframe[col].dtypes != "O"] num_cols = [col for col in num_cols if col not in num_but_cat] # print(f"Observations: {dataframe.shape[0]}") # print(f"Variables: {dataframe.shape[1]}") # print(f'cat_cols: {len(cat_cols)}') # print(f'num_cols: {len(num_cols)}') # print(f'cat_but_car: {len(cat_but_car)}') # print(f'num_but_cat: {len(num_but_cat)}') return cat_cols, num_cols, cat_but_car def target_summary_with_cat(dataframe, target, categorical_col): print(pd.DataFrame({"TARGET_MEAN": dataframe.groupby(categorical_col)[target].mean()}), end="\n\n\n") def target_summary_with_cat_extended(dataframe, target, categorical_col): """ Veri setindeki Target colonunu, girilen kategorik colona gore gruplayip - mean - count - ratio sonuclarini ekrana yazdirir. Parameters ------ dataframe: dataframe Target ve Kategorik kolonlarin bulundugu dataframe target: str Sonucun getirilecegi hedef degisken categorical_col: str Gruplanmak istenen kategorik kolon Returns ------ None Examples ------ import pandas as pd in: df = pd.DataFrame({'Animal': ['Falcon', 'Falcon', 'Falcon', 'Parrot', 'Parrot'], 'Max Speed': [310, 330, 340, 24, 28]}) in: df out: Animal Max Speed 0 Falcon 310 1 Falcon 330 2 Falcon 340 3 Parrot 24 4 Parrot 28 in: target_summary_with_cat_extended(df, 'Max Speed', 'Animal') out: TARGET_MEAN TARGET_CCOUNT RATIO Animal Falcon 326.6667 3 60.0000 Parrot 26.0000 2 40.0000 Notes ------ None """ print(pd.DataFrame({"TARGET_MEAN": dataframe.groupby(categorical_col)[target].mean(), "TARGET_CCOUNT": dataframe.groupby(categorical_col)[target].count(), "RATIO": 100 * dataframe[categorical_col].value_counts() / len(dataframe)}), end="\n\n\n") def target_summary_with_num(dataframe, target, numerical_col): print(dataframe.groupby(target).agg({numerical_col: "mean"}), end="\n\n\n") def high_correlated_cols(dataframe, plot=False, corr_th=0.90): corr = dataframe.corr() cor_matrix = corr.abs() upper_triangle_matrix = cor_matrix.where(np.triu(np.ones(cor_matrix.shape), k=1).astype(np.bool)) drop_list = [col for col in upper_triangle_matrix.columns if any(upper_triangle_matrix[col] > corr_th)] if plot: import seaborn as sns import matplotlib.pyplot as plt sns.set(rc={'figure.figsize': (15, 15)}) sns.heatmap(corr, cmap="RdBu") plt.show() return drop_list

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pyfibre/gui/pyfibre_plugin.py

franklongford/ImageCol

2

1609715

<reponame>franklongford/ImageCol<filename>pyfibre/gui/pyfibre_plugin.py from envisage.api import Plugin from envisage.ui.tasks.api import TaskFactory from traits.api import List from pyfibre.ids import TASKS, MULTI_IMAGE_FACTORIES from pyfibre.gui.pyfibre_main_task import PyFibreMainTask class PyFibreGUIPlugin(Plugin): """ The Plugin containing the PyFibre UI. This contains the factories which create the Tasks (currently Main)""" id = 'pyfibre.core.pyfibre_gui_plugin' name = 'PyFibre GUI' tasks = List(contributes_to=TASKS) def _tasks_default(self): return [TaskFactory(id='pyfibre.pyfibre_main_task', name='PyFibre GUI (Main)', factory=self._create_main_task) ] def _create_main_task(self): factories = self.application.get_extensions( MULTI_IMAGE_FACTORIES) pyfibre_main_task = PyFibreMainTask( multi_image_factories=factories, ) return pyfibre_main_task

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deprecated/code_manager/javascript_parser/pre_process_constant.py

utarsuno/quasar_source

7

188638

<filename>deprecated/code_manager/javascript_parser/pre_process_constant.py<gh_stars>1-10 # coding=utf-8 """This module, pre_process_constant.py, provides an abstraction for JS constants to pre-process.""" class PreProcessConstant(object): """Represents a constant to pre-process.""" def __init__(self, raw_line): self._raw = raw_line self._variable = None self._value = None self._initialize() def _initialize(self): """Gets the constant name.""" r = self._raw.lstrip().rstrip() r = r[r.index('const ') + len('const '):] r = r[:r.index(';')] self._variable = r[:r.index('=')].lstrip().rstrip() self._value = r[r.index('=') + 1:].lstrip().rstrip() @property def variable(self) -> str: """Returns the name of this constant/variable.""" return self._variable @property def value(self) -> str: """Returns the value of this constant/variable.""" return self._value def parse_out_constants(lines_to_parse): """Returns the lines with certain constants parsed out.""" constants = [] first_pass = [] final_pass = [] for line in lines_to_parse: if 'const' in line and '#pre-process_global_constant' in line: constants.append(PreProcessConstant(line)) else: first_pass.append(line) for l in first_pass: line = l for c in constants: if c.variable in line: line = line.replace(c.variable, c.value) final_pass.append(line) return final_pass

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missingdata/tests/test_missingdata.py

jubyraju1979/new

13

189659

#!/usr/bin/env python # -*- coding: utf-8 -*- """Tests for `missingdata` package.""" from os import makedirs from os.path import join as pjoin import numpy as np import pandas as pd from missingdata.base import blackholes # from quilt.data.ResidentMario import missingno_data # collisions = missingno_data.nyc_collision_factors() # collisions = collisions.replace("nan", np.nan) in_dir = '/Volumes/data/work/rotman/CANBIND/data/Tier1_v1' proc_dir = pjoin(in_dir, 'processing') miss_vis_dir = pjoin(proc_dir, 'missingdata_vis') makedirs(miss_vis_dir, exist_ok=True) path_tier1 = pjoin(in_dir, 'Canbind.Primary.Variables.20190114.xlsx') tier1_full = pd.read_excel(path_tier1) np.random.seed(342) rows = np.random.randint(0, 180, 150) cols = np.append([0, 1], np.random.randint(2, 120, 100)) # keeping cols 0 and 1 tier1 = tier1_full.iloc[rows, cols] path_dict_tier1 = pjoin(in_dir, 'Canbind.Tier.1.variables.DICT.0002.xlsx') dict_tier1 = pd.read_excel(path_dict_tier1) col_groups = dict_tier1['Category'].values.astype('str') var_catg = np.genfromtxt(pjoin(proc_dir, 'variable_to_category.txt'), dtype='str', delimiter=',') subjlabel_dx = np.genfromtxt(pjoin(proc_dir, 'subjlabel_to_diagnosis.txt'), dtype='str', delimiter=',') catg = {var: catg for var, catg in var_catg} diag = {lbl: dx for lbl, dx in subjlabel_dx} row_groups = [diag[slbl] if slbl in diag else 'Unknown' for slbl in tier1['SUBJLABEL']] col_groups = [catg[varb] if varb in catg else 'Unknown' for varb in tier1.columns] # making them short row_groups = [r[:4] for r in row_groups] col_groups = [c[:4] for c in col_groups] min_missing = 0.00 freq_thresh_show_labels = .01 out_path = pjoin(miss_vis_dir, 'missing_data_trial_minmiss{}perc_freqmissthresh{}.pdf' ''.format(100 * min_missing, 100 * freq_thresh_show_labels)) # # missing data viz # fig, ax_frame, \ # ax_freq_over_row, ax_freq_over_col, \ # ax_row_groups, ax_col_groups = blackholes(tier1, # label_rows_with='SUBJLABEL', # freq_thresh_show_labels=freq_thresh_show_labels, # out_path=out_path, # show_fig=True) # fig, ax_frame, ax_freq_over_row, ax_freq_over_col, ax_row_groups, ax_col_groups \ # = blackholes(tier1, # filter_spec_samples=(min_missing, 1.0), # filter_spec_variables=(min_missing, 1.0), # label_rows_with='SUBJLABEL', # freq_thresh_show_labels=freq_thresh_show_labels, # out_path=out_path, # show_fig=True) fig, ax_frame, ax_freq_over_row, ax_freq_over_col, ax_row_groups, ax_col_groups = \ blackholes(tier1, label_rows_with='SUBJLABEL', group_rows_by=row_groups, group_cols_by=col_groups, freq_thresh_show_labels=freq_thresh_show_labels, out_path=out_path, show_fig=True) print()

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src/artists/migrations/0003_auto_20191025_0454.py

slee981/sos-music-project

0

176428

<filename>src/artists/migrations/0003_auto_20191025_0454.py # Generated by Django 2.2.1 on 2019-10-25 04:54 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('artists', '0002_auto_20191025_0444'), ] operations = [ migrations.AlterModelTable( name='artist', table='artists', ), ]

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game.py

Rafael705/pong-game

0

1617430

<gh_stars>0 import pygame, sys, random # ------- # CLASSES # ------- class Paddle: def __init__(self, screen, color, posX, posY, width, height): self.screen = screen self.color = color self.posX = posX self.posY = posY self.width = width self.height = height self.state = 'stopped' self.draw() def draw(self): pygame.draw.rect( self.screen, self.color, (self.posX, self.posY, self.width, self.height) ) def move(self): if self.state == 'up': self.posY -= 0.8 elif self.state == 'down': self.posY += 0.8 def clamp(self): if self.posY <= 0: self.posY = 0 if self.posY + self.height >= HEIGHT: self.posY = HEIGHT - self.height def restart_pos(self): self.posY = HEIGHT//2 - self.height//2 self.state = 'stopped' self.draw() class Ball: def __init__(self, screen, color, posX, posY, radius): self.screen = screen self.color = color self.posX = posX self.posY = posY self.dx = 0 self.dy = 0 self.radius = radius self.draw() def draw(self): pygame.draw.circle( self.screen, self.color, (self.posX, self.posY), self.radius ) def start(self): self.dx = 1 self.dy = 1 def move(self): self.posX += self.dx self.posY += self.dy def increase_speed(self, velX): self.dx += velX def wall_collision(self): self.dy = -self.dy def paddle_collision(self): self.dx = -self.dx def restart_pos(self): self.posX = WIDTH//2 self.posY = HEIGHT//2 self.dx = 0 self.dy = 0 self.draw() class PlayerScore: def __init__(self, screen, points, posX, posY): self.screen = screen self.points = points self.posX = posX self.posY = posY self.font = pygame.font.SysFont("monospace", 80, bold=True) self.label = self.font.render(self.points, 0, WHITE) self.show() def show(self): self.screen.blit(self.label, (self.posX - self.label.get_rect().width // 2, self.posY)) def increase(self): points = int(self.points) + 1 self.points = str(points) self.label = self.font.render(self.points, 0, WHITE) def restart(self): self.points = '0' self.label = self.font.render(self.points, 0, WHITE) class CollisionManager: def between_ball_and_paddle1(self, ball, paddle): ballX = ball.posX ballY = ball.posY paddleX = paddle.posX paddleY = paddle.posY if ballY + ball.radius > paddleY and ballY - ball.radius < paddleY + paddle.height: if ballX - ball.radius <= paddleX + paddle.width: return True return False def between_ball_and_paddle2(self, ball, paddle): ballX = ball.posX ballY = ball.posY paddleX = paddle.posX paddleY = paddle.posY if ballY + ball.radius > paddleY and ballY - ball.radius < paddleY + paddle.height: if ballX + ball.radius >= paddleX: return True return False def between_ball_and_walls(self, ball): ballY = ball.posY if ballY - ball.radius <= 0: return True if ballY + ball.radius >= HEIGHT: return True return False def between_ball_and_goal1(self, ball): return ball.posX + ball.radius <= 0 def between_ball_and_goal2(self, ball): return ball.posX - ball.radius >= WIDTH # --------- # CONSTANTS # --------- WIDTH, HEIGHT = 900, 500 BLACK = (0, 0, 0) WHITE = (255, 255, 255) RED = (255, 0, 0) # SCREEN pygame.init() screen = pygame.display.set_mode( (WIDTH, HEIGHT) ) pygame.display.set_caption('PONG') # --------- # FUNCTIONS # --------- def draw_board(): screen.fill( BLACK ) pygame.draw.line( screen, WHITE, (WIDTH//2, 0), (WIDTH//2, HEIGHT), 5 ) def restart(): draw_board() score1.restart() score2.restart() ball.restart_pos() paddle1.restart_pos() paddle2.restart_pos() draw_board() # ------- # OBJECTS # ------- paddle1 = Paddle( screen, WHITE, 15, HEIGHT//2 - 60, 20, 120 ) paddle2 = Paddle( screen, WHITE, WIDTH - 20 - 15, HEIGHT//2 - 60, 20, 120 ) ball = Ball( screen, WHITE, WIDTH//2, HEIGHT//2, 10 ) ball = Ball( screen, WHITE, WIDTH//2, HEIGHT//2, 10) collision = CollisionManager() score1 = PlayerScore( screen, '0', WIDTH//4, 15 ) score2 = PlayerScore( screen, '0', WIDTH - WIDTH//4, 15 ) # --------- # VARIABLES # --------- playing = False # -------- # MAINLOOP # -------- while True: for event in pygame.event.get(): if event.type == pygame.QUIT: sys.exit() if event.type == pygame.KEYDOWN: if event.key == pygame.K_p and not playing: ball.start() playing = True if event.key == pygame.K_r and playing: restart() playing = False if event.key == pygame.K_w: paddle1.state = 'up' if event.key == pygame.K_s: paddle1.state = 'down' if event.key == pygame.K_UP: paddle2.state = 'up' if event.key == pygame.K_DOWN: paddle2.state = 'down' # if event.type == pygame.KEYUP: # paddle1.state = 'stopped' # paddle2.state = 'stopped' if playing: draw_board() # ball ball.move() ball.draw() # paddle 1 paddle1.move() paddle1.clamp() paddle1.draw() # paddle 2 paddle2.move() paddle2.clamp() paddle2.draw() # wall collision if collision.between_ball_and_walls(ball): print('Point') ball.wall_collision() # paddle1 collision if collision.between_ball_and_paddle1(ball, paddle1): ball.paddle_collision() # paddle2 collision if collision.between_ball_and_paddle2(ball, paddle2): ball.paddle_collision() # GOAL OF PLAYER 1 ! if collision.between_ball_and_goal2(ball): draw_board() score1.increase() ball.restart_pos() paddle1.restart_pos() paddle2.restart_pos() playing = False # GOAL OF PLAYER 2! if collision.between_ball_and_goal1(ball): draw_board() score2.increase() ball.restart_pos() paddle1.restart_pos() paddle2.restart_pos() playing = False score1.show() score2.show() pygame.display.update()

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paraments.py

JoenHune/DQN-Meets-Atari

0

56730

<gh_stars>0 import sys import tensorflow as tf2 DEFAULT_GPU_LIST = [0, 1, 2] SCALE = 2 MEMORY_LENGTH = 1000000 STACK_LENGTH = 4 BATCH_SIZE = 64 LEARNING_RATE = 0.00025 GAMMA = 0.9 EPSILON = 1.0 EPSILON_MIN = 0.01 EPSILON_DECAY = 0.00003 GIVEN_GPU = [eval(sys.argv[1])] if len(sys.argv) > 1 else DEFAULT_GPU_LIST def get_strategy(gpu_visible=None): gpu_total = tf2.config.experimental.list_physical_devices(device_type="GPU") gpu_candidates = [] if gpu_visible is None: gpu_visible = GIVEN_GPU for gpu_id in gpu_visible: if 0 <= gpu_id < len(gpu_total): gpu_candidates.append(gpu_total[gpu_id]) tf2.config.experimental.set_visible_devices(devices=gpu_candidates, device_type="GPU") print("gpu_total :", gpu_total, "| gpu_candidates :", gpu_candidates) strategy = tf2.distribute.OneDeviceStrategy(device="/cpu:0") if len(gpu_candidates) == 1: strategy = tf2.distribute.OneDeviceStrategy(device="/gpu:0") elif len(gpu_candidates) > 1: strategy = tf2.distribute.MirroredStrategy() return strategy

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aulaDjango/py3.5/bin/django-admin.py

tmenegaz/django

0

85931

<reponame>tmenegaz/django<gh_stars>0 #!/home/tmenegaz/Documentos/cimatec/2016.2/escolaTecnica/mundoSenai/django/aula/aulaDjango/py3.5/bin/python3.5 from django.core import management if __name__ == "__main__": management.execute_from_command_line()

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Dataset/2DGS_FD_Solver[RK4].py

paulpuren/PhySR

6

177463

import torch import torch.nn as nn import numpy as np import scipy.io as scio import os import matplotlib.pyplot as plt os.environ['CUDA_VISIBLE_DEVICES'] = '0' torch.manual_seed(1) np.random.seed(1) lapl_op = [[[[ 0, 0, -1/12, 0, 0], [ 0, 0, 4/3, 0, 0], [-1/12, 4/3, -5, 4/3, -1/12], [ 0, 0, 4/3, 0, 0], [ 0, 0, -1/12, 0, 0]]]] # ============ define relevant functions ============= # https://github.com/benmaier/reaction-diffusion/blob/master/gray_scott.ipynb def apply_laplacian(mat, dx = 0.01): # dx is inversely proportional to N """This function applies a discretized Laplacian in periodic boundary conditions to a matrix For more information see https://en.wikipedia.org/wiki/Discrete_Laplace_operator#Implementation_via_operator_discretization """ # the cell appears 4 times in the formula to compute # the total difference neigh_mat = -5*mat.copy() # Each direct neighbor on the lattice is counted in # the discrete difference formula neighbors = [ ( 4/3, (-1, 0) ), ( 4/3, ( 0,-1) ), ( 4/3, ( 0, 1) ), ( 4/3, ( 1, 0) ), (-1/12, (-2, 0)), (-1/12, (0, -2)), (-1/12, (0, 2)), (-1/12, (2, 0)), ] # shift matrix according to demanded neighbors # and add to this cell with corresponding weight for weight, neigh in neighbors: neigh_mat += weight * np.roll(mat, neigh, (0,1)) return neigh_mat/dx**2 # Define the update formula for chemicals A and B def update(A, B, DA, DB, f, k, delta_t): """Apply the Gray-Scott update formula""" # compute the diffusion part of the update diff_A = DA * apply_laplacian(A) diff_B = DB * apply_laplacian(B) # Apply chemical reaction reaction = A*B**2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1-A) diff_B -= (k+f) * B A += diff_A * delta_t B += diff_B * delta_t return A, B def GetEachTerm(A, B, DA, DB, f, k, delta_t, dx): lap_A = DA * apply_laplacian(A,dx) lap_B = DB * apply_laplacian(B,dx) # Apply chemical reaction reaction = A * B ** 2 # Apply birth/death, linear term lin_A = f * (1 - A) lin_B = (k + f) * B return lap_A, lap_B, reaction, lin_A, lin_B def update_rk4(A0, B0, DA, DB, f, k, delta_t, dx): """Update with Runge-kutta-4 method See https://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods """ ############# Stage 1 ############## # compute the diffusion part of the update diff_A = DA * apply_laplacian(A0, dx) diff_B = DB * apply_laplacian(B0, dx) # Apply chemical reaction reaction = A0 * B0 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A0) diff_B -= (k + f) * B0 K1_a = diff_A K1_b = diff_B ############# Stage 1 ############## A1 = A0 + K1_a * delta_t/2.0 B1 = B0 + K1_b * delta_t/2.0 diff_A = DA * apply_laplacian(A1, dx) diff_B = DB * apply_laplacian(B1, dx) # Apply chemical reaction reaction = A1 * B1 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A1) diff_B -= (k + f) * B1 K2_a = diff_A K2_b = diff_B ############# Stage 2 ############## A2 = A0 + K2_a * delta_t/2.0 B2 = B0 + K2_b * delta_t/2.0 diff_A = DA * apply_laplacian(A2, dx) diff_B = DB * apply_laplacian(B2, dx) # Apply chemical reaction reaction = A2 * B2 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A2) diff_B -= (k + f) * B2 K3_a = diff_A K3_b = diff_B ############# Stage 3 ############## A3 = A0 + K3_a * delta_t B3 = B0 + K3_b * delta_t diff_A = DA * apply_laplacian(A3, dx) diff_B = DB * apply_laplacian(B3, dx) # Apply chemical reaction reaction = A3 * B3 ** 2 diff_A -= reaction diff_B += reaction # Apply birth/death diff_A += f * (1 - A3) diff_B -= (k + f) * B3 K4_a = diff_A K4_b = diff_B # Final solution A = A0 + delta_t*(K1_a+2*K2_a+2*K3_a+K4_a)/6.0 B = B0 + delta_t*(K1_b+2*K2_b+2*K3_b+K4_b)/6.0 return A, B def get_initial_A_and_B(N, random_influence = 0.2): """get the initial chemical concentrations""" # get initial homogeneous concentrations A = (1-random_influence) * np.ones((N,N)) B = np.zeros((N,N)) # put some noise on there A += random_influence * np.random.random((N,N)) B += random_influence * np.random.random((N,N)) # initial disturbance N1, N2, N3 = N//4-4, N//2, 3*N//4 r = int(N/10.0) # initial disturbance 1 A[N1-r:N1+r, N1-r:N1+r] = 0.50 B[N1-r:N1+r, N1-r:N1+r] = 0.25 # # initial disturbance 2 # A[N1-r:N1+r, N3-r:N3+r] = 0.50 # B[N1-r:N1+r, N3-r:N3+r] = 0.25 # # # initial disturbance 3 # A[N3-r:N3+r, N3-r:N3+r] = 0.50 # B[N3-r:N3+r, N3-r:N3+r] = 0.25 # # # initial disturbance 4 # A[N3-r:N3+r, N1-r:N1+r] = 0.50 # B[N3-r:N3+r, N1-r:N1+r] = 0.25 # initial disturbance 5 A[N2-r:N2+r, N2-r:N2+r] = 0.50 B[N2-r:N2+r, N2-r:N2+r] = 0.25 # # # initial disturbance 6 # A[N2-r:N2+r, N3-r:N3+r] = 0.50 # B[N2-r:N2+r, N3-r:N3+r] = 0.25 return A, B def postProcess(output, N, xmin, xmax, ymin, ymax, num, batch, save_path): ''' num: Number of time step ''' x = np.linspace(xmin, xmax, N+1)[:-1] y = np.linspace(ymin, ymax, N+1)[:-1] x_star, y_star = np.meshgrid(x, y) u_pred = output[num, 0, :, :] # v_star = true[num+25, 1, 1:-1, 1:-1] v_pred = output[num, 1, :, :] fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) fig.subplots_adjust(hspace=0.3, wspace=0.3) cf = ax[0].scatter(x_star, y_star, c=u_pred, alpha=0.95, edgecolors='none', cmap='hot', marker='s', s=2) ax[0].axis('square') ax[0].set_xlim([xmin, xmax]) ax[0].set_ylim([ymin, ymax]) cf.cmap.set_under('black') cf.cmap.set_over('white') ax[0].set_title('u-FDM') fig.colorbar(cf, ax=ax[0], extend='both') cf = ax[1].scatter(x_star, y_star, c=v_pred, alpha=0.95, edgecolors='none', cmap='hot', marker='s', s=2) # ax[1].axis('square') ax[1].set_xlim([xmin, xmax]) ax[1].set_ylim([ymin, ymax]) cf.cmap.set_under('black') cf.cmap.set_over('white') ax[1].set_title('v-FDM') fig.colorbar(cf, ax=ax[1], extend='both') # plt.draw() plt.savefig(save_path + '/uv_[b=%d][t=%d].png'%(batch, num)) plt.close('all') if __name__ == '__main__': #################### generate data ##################### # =========== define model parameters ========== # dt should be 1/2 of dx # Diffusion coefficients DA = 0.16 #2*10**-5 DB = 0.08 #DA/4 # define birth/death rates f = 0.06 #1/25 k = 0.062 #3/50 # grid size N = 256 # 128 # update in time delta_t = 1.0 #1.0/2 # spatial step dx = 1.0 #1.0 / N # intialize the chemical concentrations, random_incluence=0 A, B = get_initial_A_and_B(N, random_influence = 0.0) A_record = A.copy()[None,...] B_record = B.copy()[None,...] N_simulation_steps = 15000 for step in range(N_simulation_steps): # Runge-kutta scheme #A, B = update(A, B, DA, DB, f, k, delta_t) A, B = update_rk4(A, B, DA, DB, f, k, delta_t, dx) if step%5 ==0: print(step) A_record = np.concatenate((A_record, A[None,...]), axis=0) B_record = np.concatenate((B_record, B[None,...]), axis=0) UV = np.concatenate((A_record[None,...], B_record[None,...]), axis=0) save_path = './2DGS_IC1_2x3001x256x256.mat' scio.savemat(save_path, {'uv': UV}) # Plot the result output = np.transpose(UV, [1, 0, 2, 3]) fig_save_path = './2DGS/' for i in range(21): postProcess(output, N, 0, N*dx, 0, N*dx, num=150*i, batch=1,save_path=fig_save_path) plt.figure() plt.plot(UV[0, :, 50, 50], alpha=0.6, label='rk4, dt=1.0') plt.legend() # plt.show() plt.savefig(fig_save_path + '/fig[x=50,y=50].png')

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vagrant/tournament/tournament.py

sxw031/fullstack-nanodegree-vm

0

1611187

#!/usr/bin/env python # # tournament.py -- implementation of a Swiss-system tournament # # A Swiss-System tournament is a kind of game or sports tournament in which players # are not eliminated when they are lose a match, but are paired in each round with opponents # having approximately the same win-loss record. import psycopg2 def connect(database_name="tournament"): """Connect to the PostgreSQL database. Returns a database connection.""" try: db = psycopg2.connect("dbname={}".format(database_name)) cursor = db.cursor() return db,cursor except: print ("<error message>") def deleteMatches(): """Remove all the match records from the database.""" db, db_cursor = connect() query = "DELETE FROM matches" db_cursor.execute(query) db.commit() db.close() def deletePlayers(): """Remove all the player records from the database.""" db, db_cursor = connect() query = "TRUNCATE players" db_cursor.execute(query) db.commit() db.close() def countPlayers(): """Returns the number of players currently registered.""" db, db_cursor = connect() query = "SELECT COUNT(id) AS num FROM players" db_cursor.execute(query) results = db_cursor.fetchone() db.close() if results: return results[0]; else: return '0' def registerPlayer(name): """Adds a player to the tournament database. The database assigns a unique serial id number for the player. (This should be handled by your SQL database schema, not in your Python code.) Args: name: the player's full name (need not be unique). """ db, db_cursor = connect() query = "INSERT INTO players (name) VALUES (%s)" parameter = (name,) db_cursor.execute(query, parameter) db.commit() db.close() def playerStandings(): """Returns a list of the players and their win records, sorted by wins. The first entry in the list should be the player in first place, or a player tied for first place if there is currently a tie. Returns: A list of tuples, each of which contains (id, name, wins, matches): id: the player's unique id (assigned by the database) name: the player's full name (as registered) wins: the number of matches the player has won matches: the number of matches the player has played """ db, db_cursor = connect() query = "SELECT * FROM total_wins;" db_cursor.execute(query) results = db_cursor.fetchall() db.close() return results def reportMatch(winner, loser): """Records the outcome of a single match between two players. Args: winner: the id number of the player who won loser: the id number of the player who lost """ db, db_cursor = connect() query = "INSERT INTO matches (winner, loser) VALUES (%s, %s)" parameter = (winner, loser,) db_cursor.execute(query, parameter) db.commit() db.close() def swissPairings(): """Returns a list of pairs of players for the next round of a match. Assuming that there are an even number of players registered, each player appears exactly once in the pairings. Each player is paired with another player with an equal or nearly-equal win record, that is, a player adjacent to him or her in the standings. Returns: A list of tuples, each of which contains (id1, name1, id2, name2) id1: the first player's unique id name1: the first player's name id2: the second player's unique id name2: the second player's name """ db, db_cursor = connect() results = playerStandings() pairings = [] count = len(results) for x in range (0, count-1, 2): paired_list = (results[x][0], results[x][1], results[x+1][0],results[x+1][1]) pairings.append(paired_list) db.close() return pairings

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pepys_import/file/highlighter/support/export.py

debrief/pepys-import

4

30001

import html from tqdm import tqdm from .color_picker import color_for, html_color_for, mean_color_for def export_report(filename, chars, dict_colors, include_key=False): """ Export a HTML report showing all the extraction usages for the file. :param filename: Output filename :param chars: Characters array (should be HighlightedFile.chars) :param dict_colors: Dictionary specifying colors to use (should be HighlightedFile.dict_colors) :param include_key: Whether to include a key at the bottom defining the usages of the colors This basically loops through all of the characters in the characters array, and then creates the relevant <span> tags for each character based on the usages stored for that character. """ output_strings = [] html_header = """<html> <head> </head> <body style="font-family: Courier"> """ output_strings.append(html_header) last_hash = "" for char in tqdm(chars): letter = char.letter this_hash = "" this_message = "" colors = [] multi_usages = len(char.usages) > 1 for usage in char.usages: this_hash += usage.tool_field needs_new_line = this_message != "" colors.append(color_for(usage.tool_field, dict_colors)) if needs_new_line: this_message += "" if multi_usages: this_message += "-" this_message += usage.tool_field + ", " + usage.message # do we have anything to shade? if this_hash != "": # generate/retrieve a color for this hash new_color = mean_color_for(colors) hex_color = html_color_for(new_color) # are we already in hash? if last_hash != "": # is it the different to this one? if last_hash != this_hash: # ok, close the span output_strings.append("</span>") # start a new span output_strings.append( f"<span title='{this_message}' style=\"background-color:{hex_color}\">" ) else: output_strings.append( f"<span title='{this_message}' style=\"background-color:{hex_color}\">" ) elif last_hash != "": output_strings.append("</span>") # just check if it's newline if letter == "\n": output_strings.append("<br>") else: # Escape the letter as otherwise the XML from XML files gets # interpreted by browsers as (invalid) HTML output_strings.append(html.escape(letter)) last_hash = this_hash if last_hash != "": output_strings.append("</span>") # also provide a key if include_key: output_strings.append("<hr/><h3>Color Key</h3><ul>") for key in dict_colors: color = dict_colors[key] hex_color = html_color_for(color) output_strings.append( f'<li><span style="background-color:{hex_color}">{key}</span></li>' ) output_strings.append("</ul>") html_footer = """</body> </html>""" output_strings.append(html_footer) with open(filename, "w") as f: f.write("".join(output_strings))

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app/routers/openstack/sizes.py

skyworkflows/swm-cloud-gate

3

46341

<reponame>skyworkflows/swm-cloud-gate import typing from fastapi import APIRouter, Header from .connector import OpenStackConnector from .models import convert_to_flavor CONNECTOR = OpenStackConnector() ROUTER = APIRouter() @ROUTER.get("/openstack/flavors") async def list_flavors(username: str = Header(None), password: str = Header(None)): CONNECTOR.reinitialize(username, password, "compute") flavor_list: typing.List[ImageInfo] = [] for item in CONNECTOR.list_sizes(): flavor_list.append(convert_to_flavor(item)) return {"flavors": flavor_list}

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state/state_example_01.py

brandaoplaster/learning-design-patterns-in-python

0

1601781

from __future__ import annotations from abc import ABC, abstractmethod class Order: """ Context """ def __init__(self) -> None: self.state: OrderState = PaymentPending(self) def pending(self) -> None: print("Trying to pending()") self.state.pending() print("Current state ~>", self.state) print() def approve(self) -> None: print("Trying to run approve()") self.state.approve() print("Current state ~>", self.state) print() def reject(self) -> None: print("Trying to reject()") self.state.reject() print("Current state ~>", self.state) print() class OrderState(ABC): def __init__(self, order: Order) -> None: self.order = order @abstractmethod def pending(self) -> None: pass @abstractmethod def approve(self) -> None: pass @abstractmethod def reject(self) -> None: pass def __str__(self): return self.__class__.__name__ class PaymentPending(OrderState): def pending(self) -> None: print("payment declined") def approve(self) -> None: self.order.state = PaymentApproved(self.order) print("payment declined") def reject(self) -> None: self.order.state = PaymentRejected(self.order) print() class PaymentApproved(OrderState): def pending(self) -> None: self.order.state = PaymentPending(self.order) print("pending payment") def approve(self) -> None: print("Payment already approved") def reject(self) -> None: self.order.state = PaymentRejected(self.order) print("payment declined") class PaymentRejected(OrderState): def pending(self) -> None: print("Payment declined. I will not move to pending.") def approve(self) -> None: print("payment declined") def reject(self) -> None: print("payment declined") if __name__ == "__main__": order = Order() order.pending() order.approve() order.pending() order.reject() order.pending() order.approve()

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data_structures/stacks_and_queues/stack/node.py

michaelsklepowich/data_structures_and_algorithms

0

125455

class Node: def __init__(self, value, _next=None): self._value = value self._next = _next def __str__(self): return f'{self._value}' def __repr__(self): return f'<Node | Val: {self._value} | Next: {self._next}>'

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01_Diag_Dispersion_Bicis.py

JosefinaMedina/Deep-Learning-2021-P1

0

91804

<gh_stars>0 import matplotlib.pyplot as plt import pandas as pd import seaborn as sns import os import chardet os.chdir('../Datos//') nomArch = 'SeoulBikeData.csv' with open(nomArch, 'rb') as f: result = chardet.detect(f.read()) df= pd.read_csv(nomArch, encoding=result['encoding']) print(df.dtypes) sns.heatmap(df[['Temperature(°C)','Rented Bike Count','Humidity(%)','Visibility (10m)']].corr(), square=True, annot=True) plt.figure() plt.scatter(df['Temperature(°C)'],df['Rented Bike Count'], marker='o') plt.xlabel('Temperature(°C)') plt.ylabel('Rented Bike Count') plt.figure() plt.scatter(df['Humidity(%)'],df['Visibility (10m)'], marker='o') plt.xlabel('Humidity(%)') plt.ylabel('Visibility (10m)')

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IoT/presentation/plots/step_plot.py

Mohitsharma44/CUSP-GX-6004-C

5

53208

import matplotlib.pyplot as plt import numpy as np plt.style.use('seaborn-darkgrid') x = range(8) y = np.linspace(1.1, 5.0, 8) ylabel = map(lambda num: bin(num)[2:], x) xlabel = map(lambda num: "{0:.2f}".format(num), y) plt.step(x, y) plt.yticks(y, ylabel) plt.xticks(x, xlabel, rotation=45) plt.ylabel("Binary Output") plt.xlabel("Analog Input") plt.savefig("adc.png", transparent=True)

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robot-server/tests/service/json_api/test_response.py

mrod0101/opentrons

0

2129

<filename>robot-server/tests/service/json_api/test_response.py from pytest import raises from pydantic import ValidationError from robot_server.service.json_api.response import ( ResponseDataModel, ResponseModel, MultiResponseModel, ) from tests.service.helpers import ItemResponseModel def test_attributes_as_dict() -> None: MyResponse = ResponseModel[ResponseDataModel, None] obj_to_validate = { "data": {"id": "123"}, "links": None, } my_response_object = MyResponse(**obj_to_validate) assert my_response_object.dict() == { "links": None, "data": { "id": "123", }, } def test_attributes_as_item_model() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": {"id": "123", "name": "apple", "quantity": 10, "price": 1.20}, } my_response_obj = ItemResponse(**obj_to_validate) assert my_response_obj.dict() == { "links": None, "data": { "id": "123", "name": "apple", "quantity": 10, "price": 1.20, }, } def test_list_item_model() -> None: ItemResponse = MultiResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": [ {"id": "123", "name": "apple", "quantity": 10, "price": 1.20}, {"id": "321", "name": "banana", "quantity": 20, "price": 2.34}, ], } my_response_obj = ItemResponse(**obj_to_validate) assert my_response_obj.dict() == { "links": None, "data": [ { "id": "123", "name": "apple", "quantity": 10, "price": 1.20, }, { "id": "321", "name": "banana", "quantity": 20, "price": 2.34, }, ], } def test_attributes_as_item_model_empty_dict() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] obj_to_validate = { "links": None, "data": { "id": "123", }, } with raises(ValidationError) as e: ItemResponse(**obj_to_validate) assert e.value.errors() == [ { "loc": ("data", "name"), "msg": "field required", "type": "value_error.missing", }, { "loc": ("data", "quantity"), "msg": "field required", "type": "value_error.missing", }, { "loc": ("data", "price"), "msg": "field required", "type": "value_error.missing", }, ] def test_response_constructed_with_resource_object() -> None: ItemResponse = ResponseModel[ItemResponseModel, None] item = ItemResponseModel(id="abc123", name="pear", price=1.2, quantity=10) data = item.dict() assert ItemResponse(data=data, links=None).dict() == { "links": None, "data": { "id": "abc123", "name": "pear", "price": 1.2, "quantity": 10, }, } def test_response_constructed_with_resource_object_list() -> None: ItemResponse = MultiResponseModel[ItemResponseModel, None] items = [ ItemResponseModel(id="1", name="apple", price=1.5, quantity=3), ItemResponseModel(id="2", name="pear", price=1.2, quantity=10), ItemResponseModel(id="3", name="orange", price=2.2, quantity=5), ] response = ItemResponse(data=items, links=None) assert response.dict() == { "links": None, "data": [ { "id": "1", "name": "apple", "price": 1.5, "quantity": 3, }, { "id": "2", "name": "pear", "price": 1.2, "quantity": 10, }, { "id": "3", "name": "orange", "price": 2.2, "quantity": 5, }, ], }

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WorkingExamples/MNIST_Worker.py

iansee/FYP

0

1617385

import tensorflow as tf import h5py import collections import six from syft.workers.websocket_server import WebsocketServerWorker import torch import sys import syft import sys import argparse from torchvision import datasets from torchvision import transforms import numpy as np import tensorflow_federated as tff import os.path from tensorflow_federated.python.simulation.hdf5_client_data import HDF5ClientData fractionToUse = 5 class TrainDataset: def __init__(self,transform=None, id="h2"): fileprefix = "fed_emnist_digitsonly" dir_path = os.path.dirname("/home/mininet/") train = HDF5ClientData(os.path.join(dir_path, fileprefix + '_train.h5')) trainFile = h5py.File(os.path.join(dir_path, fileprefix + '_train.h5'), "r") _EXAMPLES_GROUP = "examples" numberofclients = len(train.client_ids) data = np.empty((0,28,28), np.float32) target = np.empty((0), np.int_) if id == "h2": offset = 0 elif id == "h3": offset = 1 elif id == "h4": offset = 2 for i in range(int(numberofclients/(3*fractionToUse))): clientdataset = collections.OrderedDict((name, ds[()]) for name, ds in sorted( six.iteritems(trainFile[HDF5ClientData._EXAMPLES_GROUP][train.client_ids[i*3*fractionToUse+offset]]))) data = np.concatenate((data, clientdataset['pixels'])) target = np.concatenate((target, clientdataset['label']), axis=0) self.target = list(target) self.data = list(data) self.transform = transform def __getitem__(self, index): x=self.data[index] y=self.target[index] if self.transform: x = self.transform(x) return x,y def __len__(self): return len(self.target) def main(_id,ip): mnist_dataset = TrainDataset(transform=transforms.Compose([ transforms.ToTensor(), transforms.Normalize( (0.1307,), (0.3081,)) ]), id=_id) hook = syft.TorchHook(torch) server = WebsocketServerWorker(id = _id,host =ip, port = 8778,hook=hook,verbose=True) print ("Worker:{}, Dataset contains {}".format(_id,str(len(mnist_dataset.data)))) dataset = syft.BaseDataset( data=mnist_dataset.data, targets=mnist_dataset.target, transform=mnist_dataset.transform ) key = "targeted" server.add_dataset(dataset, key=key) server.start() main (sys.argv[1], sys.argv[2])

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ui/controller/user_handler.py

ctwardy/sitehound

0

65811

from ui import app, Singleton import json from dao.JsonDatetimeEncoder import MyEncoder from ui import app from flask import Response, request, jsonify from utils.json_encoder import JSONEncoder from flask_login import login_required from flask_security import roles_required, utils from mongoengine import NotUniqueError from controller.InvalidException import InvalidUsage from service.user_service import get_all, delete, updateUser, get_all_roles __author__ = 'tomas' @app.route("/api/role", methods=['GET']) @login_required @roles_required('admin') def get_all_roles_api(): in_doc = get_all_roles() out_doc = MyEncoder(JSONEncoder()).encode(in_doc) return Response(json.dumps(out_doc, cls = MyEncoder), mimetype="application/json") @app.route("/api/user", methods=['GET']) @login_required @roles_required('admin') def get_all_api(): in_doc = get_all() out_doc = MyEncoder(JSONEncoder()).encode(in_doc) return Response(json.dumps(out_doc, cls = MyEncoder), mimetype="application/json") @app.route("/api/user/<id>", methods=['PUT']) @app.errorhandler(InvalidUsage) @login_required @roles_required('admin') def activate_api(id): roles = None isActive = None if 'roles' in request.json: roles = request.json['roles'] if 'isActive' in request.json: isActive = bool(request.json['isActive']) if isActive is None and roles is None: raise InvalidUsage("no update provided", status_code=409) updateUser(id, isActive, roles) return Response("{}", mimetype="application/json") @app.route("/api/user/<id>", methods=['DELETE']) @login_required @roles_required('admin') def delete_api(id): delete(id) return Response("{}", mimetype="application/json") @login_required @roles_required('admin') @app.errorhandler(InvalidUsage) @app.route('/api/user/<username>', methods=['POST']) def create_account(username): password = request.json['password'] encrypted_password = utils.encrypt_password(password) try: Singleton.getInstance().user_datastore.create_user( email=username, password=<PASSWORD>, roles=[], active=True, login_count=0) except NotUniqueError as ex: raise InvalidUsage('An username with that email already exists', status_code=409) return Response("{}", mimetype="application/json")

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scripts/python/lib/bmc.py

purushammi/power-up

0

75435

<filename>scripts/python/lib/bmc.py #!/usr/bin/env python3 # Copyright 2019 IBM Corp. # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import argparse import time import requests.exceptions import lib.logger as logger import lib.open_bmc as open_bmc import lib.ipmi as ipmi class Bmc(object): """ Creates a 'bmc' class instance. The created class establishes a connection to a BMC. The connection can be openBMC rest API or IPMI. Args: host (str): ip address or resolvable hostname. user (str): <NAME> pw (str): <PASSWORD> bmc_type (str): Indicates the type of BMC ('ipmi' or 'openbmc') """ def __init__(self, host, user, pw, bmc_type='ipmi', timeout=10): self.log = logger.getlogger() self.host = host self.user = user self.pw = pw self.bmc_type = bmc_type self.timeout = timeout self.connected = False if bmc_type == 'openbmc': self.bmc = open_bmc.login(host, user, pw) if isinstance(self.bmc, requests.sessions.Session): self.connected = True elif bmc_type == 'ipmi': self.bmc = ipmi.login(host, user, pw) if isinstance(self.bmc, ipmi.command.Command): self.connected = True else: self.log.error(f'Unsupported BMC type: {bmc_type}') def is_connected(self): return self.connected def get_host(self): return self.host def logout(self): if self.bmc_type == 'openbmc': return open_bmc.logout(self.host, self.user, self.pw, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.logout(self.host, self.user, self.pw, self.bmc) def chassis_power(self, op, timeout=5): if self.bmc_type == 'openbmc': return open_bmc.chassisPower(self.host, op, self.bmc) if self.bmc_type == 'ipmi': return ipmi.chassisPower(self.host, op, self.bmc) def host_boot_source(self, source='', timeout=5): if self.bmc_type == 'openbmc': return open_bmc.hostBootSource(self.host, source, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.hostBootSource(self.host, source, self.bmc) def host_boot_mode(self, mode='', timeout=5): if self.bmc_type == 'openbmc': return open_bmc.hostBootMode(self.host, mode, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.hostBootMode(self.host, mode, self.bmc) def bmc_reset(self, op): if self.bmc_type == 'openbmc': return open_bmc.bmcReset(self.host, op, self.bmc) elif self.bmc_type == 'ipmi': return ipmi.bmcReset(self.host, op, self.bmc) def bmc_status(self, timeout=5): if self.bmc_type == 'openbmc': return open_bmc.bmcPowerState(self.host, self.bmc, timeout) elif self.bmc_type == 'ipmi': return 'Ready' if __name__ == '__main__': """Show status of the Cluster Genesis environment Args: INV_FILE (string): Inventory file. LOG_LEVEL (string): Log level. Raises: Exception: If parameter count is invalid. """ logger.create('debug', 'debug') log = logger.getlogger() parser = argparse.ArgumentParser() parser.add_argument('host', nargs='?', help='bmc ip address', default='') parser.add_argument('user', nargs='?', help='bmc user', default='ADMIN') parser.add_argument('pw', nargs='?', help='bmc password', default='<PASSWORD>') # parser.add_argument('user', nargs='?', # help='bmc user', # default='root') # # parser.add_argument('pw', nargs='?', # help='bmc password', # default='<PASSWORD>') parser.add_argument('bmc_type', nargs='?', choices=['open', 'ipmi'], help='bmc type (open, ipmi)', default='ipmi') parser.add_argument('--print', '-p', dest='log_lvl_print', help='print log level', default='info') parser.add_argument('--file', '-f', dest='log_lvl_file', help='file log level', default='info') args = parser.parse_args() if not args.host: args.host = input('Enter bmc ip address: ') bmc = Bmc(args.host, args.user, args.pw, args.bmc_type) if bmc.is_connected(): print(f'logged into BMC {bmc}') if args.bmc_type in ('open', 'ipmi'): bmc_status = bmc.bmc_status() print(f'BMC status: {bmc_status}') # print('Rebooting bmc') # r = bmc.bmc_reset('cold') # print(f'BMC response: {r}') # if not r: # log.error(f'Failed reboot of bmc {args.host}.') # else: # print('Attempting BMC logout...') # if bmc.logout(): # print(f'Logged out of BMC {args.host}') # else: # log.debug(f'Failed to log out of BMC {args.host}') # del bmc # print('Setting host boot mode') # r = bmc.host_boot_mode('regular') # get boot source # r = bmc.host_boot_source() # print(f'host boot source: {r}') # source = 'network' # source = 'default' # print(f'Setting host boot source to {source}') # r = bmc.host_boot_source(source) # print('clossing BMC connection') # bmc.logout() print('Attempting to log back into BMC') while True: bmc = Bmc(args.host, args.user, args.pw, args.bmc_type) if bmc.is_connected(): print(f'\nsuccessfully logged back into {args.host}') break else: print('Failed login attempt') time.sleep(3) else: log.error('Failed to instantiate the bmc class') print('done')

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backend/base/urls/order_urls.py

danylott/sale-rent-real-estate-platform

0

155565

from django.urls import path from base.views import order_views as views urlpatterns = [ path("", views.get_orders, name="orders"), path("add/", views.add_order_items, name="orders-add"), path("myorders/", views.get_my_orders, name="myorders"), path("<str:pk>/", views.get_order_by_id, name="user-order"), path("<str:pk>/deliver/", views.update_order_to_delivered, name="order-delivered"), path("<str:pk>/pay/", views.update_order_to_paid, name="pay"), ]

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value_based_1.py

frankfangy/gridlab

0

32200

<reponame>frankfangy/gridlab # -*- coding: utf-8 -*- ''' 这个来源于 udacity 的讲座验证基础的概念和算法 ''' from grid_world import * import sys #from PyQt5.QtCore import QPoint, QRect, QSize, Qt #from PyQt5.QtGui import (QBrush, QPainter, QColor, QPen ) #from PyQt5.QtWidgets import (QApplication, QPushButton, QCheckBox, QGridLayout,QLabel, QWidget, QInputDialog) from PyQt5.QtWidgets import ( QLabel , QTextEdit , QPlainTextEdit , QLineEdit ) import numpy as np from random import randint import time from math import fabs class value_based(grid_world): ''' 用来实验各种算法，并图形展示，基于方块地图 ''' def __init__(self): super(value_based, self).__init__() def config_map(self): # 地图大小 , 初始map , 供子类再定义 self.map_mask = ''' 1113 1214 1111 ''' # map mask must be plus i8 (0 ~ 127 ) def config_gui(self): super(value_based, self).config_gui() self.add_ctrl( QLabel , '移动奖励' ) self.edit_moving_reward = self.add_ctrl( QLineEdit , '-0.04' , 15 ) self.add_ctrl( QLabel , '绿位奖励' ) self.edit_green_reward = self.add_ctrl( QLineEdit , '+1' , 15 ) self.add_ctrl( QLabel , '红位奖励' ) self.edit_red_reward = self.add_ctrl( QLineEdit , '-1' , 15 ) self.add_ctrl( QLabel , '运动稳定度' ) self.edit_moving_stability = self.add_ctrl( QLineEdit , '0.8' , 15 ) self.block_size = 60 # using a bigger block def reset(self): ''' 初始化地图，以及计算条件，可能会反复运算 ''' self.moving_reward = float( self.edit_moving_reward.text() ) self.green_reward = float( self.edit_green_reward.text() ) self.red_reward = float( self.edit_red_reward.text() ) self.moving_stability = float( self.edit_moving_stability.text() ) print('get config :',self.moving_reward , self.green_reward , self.red_reward , self.moving_stability ) # init value self.value_init = -100 self.value = np.zeros( ( self.map_width , self.map_height ) , float ) for x in range(self.map_width): for y in range(self.map_height): mpv = self.map[x][y] self.value[x][y] = {1:self.value_init , 2:self.value_init , 3: self.green_reward , 4:self.red_reward }.get(mpv,0) self.show_direction = False self.update() def avaliable_for_value(self,x,y): if x < 0 or x >= self.map_width or y < 0 or y >= self.map_height: return False return self.map[x][y] != 2 def calc_direction(self): self.direction = np.ndarray( ( self.map_width , self.map_height ) , dtype=np.int8 ) for x in range(self.map_width): for y in range(self.map_height): maxv = self.value_init ii = 4 # stay there if self.avaliable_for_value(x,y): v0 = self.value[x][y] for i in range(5): d = ((0,-1),(1,0),(0,1),(-1,0),(0,0))[i] nx = x + d[0] ny = y + d[1] if self.avaliable_for_value(nx,ny): if maxv < self.value[nx][ny] : ii = i maxv = self.value[nx][ny] self.direction[x][y] = ii self.show_direction = True def run_proc(self): ''' 此处是一个示范代码，子类应沿袭相同结构 ''' # setup flag self.running = True self.set_log('运算中') while self.running: updated = 0 self.value_old = self.value.copy() for x in range(self.map_width): for y in range(self.map_height): if self.map[x][y] == 1: v0 = self.value_old[x][y] maxv = self.value_init for i in range(4): d =((0,-1),(1,0),(0,1),(-1,0))[i] d1 =((-1,0),(0,-1),(1,0),(0,1))[i] d2 =((1,0),(0,1),(-1,0),(0,-1))[i] nx = x + d[0] ny = y + d[1] nx1 = x + d1[0] ny1 = y + d1[1] nx2 = x + d2[0] ny2 = y + d2[1] if self.avaliable_for_value(nx,ny): # this nx,ny is avaliable for value # 计算，如果向 nx ny 点移动，本地的value值可能是多少 v = self.value_old[nx][ny] * self.moving_stability if self.avaliable_for_value(nx1,ny1): v += (1.0-self.moving_stability )*0.5 * self.value_old[nx1][ny1] else: # 留在原地 v += (1-self.moving_stability )*0.5 * v0 if self.avaliable_for_value(nx2,ny2): v += (1-self.moving_stability )*0.5 * self.value_old[nx2][ny2] else: # 留在原地 v += (1-self.moving_stability )*0.5 * v0 if v > maxv: maxv = v # here we got the maxv if v0 - self.moving_reward < maxv: updated += fabs( v0 - maxv - self.moving_reward ) self.value[x][y] = maxv + self.moving_reward if updated < 1e-5 : break self.update() time.sleep(0.3) self.set_log('价值网络计算完成') self.calc_direction() self.running = False self.update() def draw_block(self, painter,x,y , block_map_value = None ): painter.save() if block_map_value is None: block_map_value = self.map[x][y] block_value = self.value[x][y] bkcolor = {0:(55,55,55) , 1:(222,255,222) , 2 :(111,111,111) , 3:(111,255,111) , 4:(255,0,0) }.get( block_map_value , (0,0,0) ) self.draw_background( painter, x,y , bkcolor ) if block_map_value == 1: # path block self.draw_text( painter , x,y , '%g'%(block_value) , (0,0,0) , 'd' ) if self.show_direction: self.draw_arrow(painter,x,y, 'urdlo'[ self.direction[x][y] ] , (255,0,0) , 'u' ) elif block_map_value != 2: # other self.draw_text( painter , x,y , str(block_value) , (0,0,0) , 'd' ) painter.restore() if __name__ == '__main__': run_gui( value_based )

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BasicConcepts/SyntaxErrors/Volume1_Chapter6_SyntaxErrors_Fixed.py

jpike/PythonProgrammingForKids

0

37565

# Commenting syntax errors. print("Printing out a message!") # This is a comment. floating_point_number = 1.5 * 2.7

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knox/serializers.py

liradb2000/django-rest-knox

0

177945

from django.contrib.auth import get_user_model from rest_framework import serializers from knox.models import AuthToken User = get_user_model() username_field = User.USERNAME_FIELD if hasattr(User, 'USERNAME_FIELD') else 'username' class UserSerializer(serializers.ModelSerializer): class Meta: model = User fields = (username_field,) class AuthTokenSerializer(serializers.ModelSerializer): class Meta: model = AuthToken fields = ('created', 'token_key')

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src/rgw/setup/rgw.py

Seagate/cortx-rgw-integration

2

91089

#!/usr/bin/python3 # Copyright (c) 2022 Seagate Technology LLC and/or its Affiliates # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <https://www.gnu.org/licenses/>. # For any questions about this software or licensing, # please email <EMAIL> or <EMAIL>. import os import shutil import time import errno import json from urllib.parse import urlparse from cortx.utils.security.certificate import Certificate from cortx.utils.errors import SSLCertificateError from cortx.utils.validator.v_pkg import PkgV from cortx.utils.conf_store import Conf, MappedConf from cortx.utils.conf_store.error import ConfError from cortx.utils.process import SimpleProcess from cortx.utils.schema.release import Release from cortx.utils.log import Log from cortx.rgw.setup.error import SetupError from cortx.rgw.setup.rgw_service import RgwService from cortx.utils.security.cipher import Cipher, CipherInvalidToken from cortx.rgw import const from cortx.utils.common import ExponentialBackoff class Rgw: """Represents RGW and Performs setup related actions.""" _machine_id = Conf.machine_id _conf_idx = f'{const.COMPONENT_NAME}_config' # e.g. rgw_config @staticmethod def validate(phase: str): """Perform validations.""" Log.info(f'validations started for {phase} phase.') if phase == 'post_install': # Perform RPM validations for rpms in [const.REQUIRED_RPMS]: PkgV().validate('rpms', rpms) Log.info(f'All RGW required RPMs are installed on {Rgw._machine_id} node.') elif phase == 'prepare': Rgw._file_exist(const.CONF_TMPL) Log.info(f'validations completed for {phase} phase.') return 0 @staticmethod def post_install(conf: MappedConf): """Performs post install operations.""" Log.info('PostInstall phase completed.') return 0 @staticmethod def prepare(conf: MappedConf): """Prepare for operations required before RGW can be configured.""" Log.info('Prepare phase started.') try: config_path = Rgw._get_rgw_config_path(conf) tmpl_idx = f'{const.COMPONENT_NAME}_conf_tmpl' # e.g. rgw_conf_tmpl tmpl_url = const.CONFSTORE_FILE_HANDLER + const.CONF_TMPL Rgw._load_rgw_config(tmpl_idx, tmpl_url) confstore_url = const.CONFSTORE_FILE_HANDLER + config_path Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Conf.copy(tmpl_idx, Rgw._conf_idx) Conf.save(Rgw._conf_idx) Log.info(f'{const.CONF_TMPL} config copied to {config_path}') except Exception as e: raise SetupError(errno.EINVAL, f'Error ocurred while fetching node ip, {e}') Log.info('Prepare phase completed.') return 0 @staticmethod def config(conf: MappedConf): """Performs configurations.""" Log.info('Config phase started.') Rgw._check_consul_connection(conf) config_file = Rgw._get_rgw_config_path(conf) if not os.path.exists(config_file): raise SetupError(errno.EINVAL, f'"{config_file}" config file is not present.') # Create ssl certificate Rgw._generate_ssl_cert(conf) # Create svc config Rgw._create_svc_config(conf) # Create motr trace directory for collecting m0trace files # in case admin user creation issue during mini-provisioner execution. Log.info('Creating motr trace directory for collecting m0trace files..') log_path = Rgw._get_log_dir_path(conf) motr_trace_dir = os.path.join(log_path, 'motr_trace_files') os.makedirs(motr_trace_dir, exist_ok=True) os.environ['M0_TRACE_DIR'] = motr_trace_dir Log.info('Created motr trace directory : %s' % os.environ.get('M0_TRACE_DIR')) # Read Motr HA(HAX) endpoint from data pod using hctl fetch-fids and update in config file # Use remote hax endpoint running on data pod which will be available during rgw # config phase since data pod starts before server pod. # Try HAX endpoint from data pod of same node first & if it doesnt work, # from other data pods in cluster Rgw._update_hax_endpoint_and_create_admin(conf) Log.info('Config phase completed.') return 0 @staticmethod def start(conf: MappedConf, index: str): """Create rgw admin user and start rgw service.""" Log.info(f'Configure logrotate for {const.COMPONENT_NAME} at path: {const.LOGROTATE_CONF}') Rgw._logrotate_generic(conf) # Before starting service,Verify backend store value=motr in rgw config file. Rgw._verify_backend_store_value(conf) # Create motr trace & addb stob dirctory. # Collect fid value of motr to create addb value. config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) motr_fid_key = const.MOTR_MY_FID % index motr_fid_value = Conf.get(Rgw._conf_idx, motr_fid_key) log_path = Rgw._get_log_dir_path(conf) motr_trace_dir = os.path.join(log_path, 'motr_trace_files') addb_dir = os.path.join(log_path, f'addb_files-{motr_fid_value}') os.makedirs(motr_trace_dir, exist_ok=True) os.makedirs(addb_dir, exist_ok=True) # Create rgw crash file directory rgw_core_dir = os.path.join(log_path, 'rgw_debug') os.makedirs(rgw_core_dir, exist_ok=True) Log.info('Starting radosgw service.') log_file = os.path.join(log_path, f'{const.COMPONENT_NAME}_startup.log') RgwService.start(conf, config_file, log_file, motr_trace_dir, rgw_core_dir, index) Log.info("Started radosgw service.") return 0 @staticmethod def init(conf: MappedConf): """Perform initialization.""" Log.info('Init phase completed.') return 0 @staticmethod def test(conf: MappedConf, plan: str): """Perform configuration testing.""" Log.info('Test phase completed.') return 0 @staticmethod def reset(conf: MappedConf): """Remove/Delete all the data/logs that was created by user/testing.""" Log.info('Reset phase completed.') return 0 @staticmethod def cleanup(conf: MappedConf, pre_factory: bool = False): """Remove/Delete all the data that was created after post install.""" config_path = Rgw._get_rgw_config_path(conf) if os.path.exists(config_path): os.remove(config_path) Log.info('Cleanup phase completed.') return 0 @staticmethod def _update_rgw_config(conf: MappedConf, config_index:str, config_key: str, config_val: str): """Update RGW Config based on changed Gconf values.""" for rgw_config_key, confstore_key in const.SVC_CONFIG_DICT.items(): if confstore_key == config_key: Conf.set(config_index, f'{const.CLIENT_SECTION}>{rgw_config_key}', config_val) Conf.save(config_index) @staticmethod def _remove_rgw_config(conf: MappedConf, config_index:str, config_key: str): """Remove specific key from rgw config file.""" for rgw_config_key, confstore_key in const.SVC_CONFIG_DICT.items(): if confstore_key == config_key: Conf.delete(config_index, f'{const.CLIENT_SECTION}>{rgw_config_key}') Conf.save(config_index) @staticmethod def upgrade(conf: MappedConf, changeset_path: str): """Perform upgrade steps.""" Log.info('Upgrade phase started.') conf_dir = Rgw._get_rgw_config_dir(conf) svc_conf_file = Rgw._get_rgw_config_path(conf) # Load changeset file changeset_index="rgw_changeset_index" Rgw._load_rgw_config(changeset_index, changeset_path) # Get all changed keys from changeset file. changeset_all_keys=Conf.get_keys(changeset_index) # Load deployed rgw config and take a backup. Rgw._load_rgw_config(Rgw._conf_idx, const.CONFSTORE_FILE_HANDLER + svc_conf_file) deployed_version = conf.get(const.VERSION_KEY) conf_bkp_file = os.path.join(conf_dir, const.RGW_CONF_FILE + f'.{deployed_version}') try: # Cleaning up failure config of previous upgrade. if os.path.exists(conf_bkp_file): os.remove(conf_bkp_file) # create backup of existing config file shutil.copy(svc_conf_file, conf_bkp_file) # Handle svc key & Gconf key mapping for key in changeset_all_keys: if key.startswith('new') : # Handle addition of new key # This will work if corresponding rgw config mapping is preset in const.py for this new key. new_val = Conf.get(changeset_index, key) key =key.split('new>')[1] Rgw._update_rgw_config(conf, Rgw._conf_idx, key, new_val) elif key.startswith('changed'): # Handle updation of existing key value = Conf.get(changeset_index, key) key =key.split('changed>')[1] new_val = value.split('|')[1] Rgw._update_rgw_config(conf, Rgw._conf_idx, key, new_val) elif key.startswith('deleted'): # Handle deletion of existing key key =key.split('deleted>')[1] Rgw._remove_rgw_config(conf, Rgw._conf_idx, key) # Update upgraded release version. updated_version = Release(const.RELEASE_INFO_URL).get_release_version() Conf.set(Rgw._conf_idx, 'release>version', updated_version) # Save updated config file. Conf.save(Rgw._conf_idx) # delete backup file after upgrade. os.remove(conf_bkp_file) except Exception as e: raise SetupError(errno.EINVAL, f'Upgrade failed with error: {e}') Log.info('Upgrade phase completed.') return 0 @staticmethod def _create_svc_config(conf: MappedConf): """Create svc config""" svc_name = Rgw._get_svc_name(conf) client_instance_count = Rgw._get_num_client_instances(conf, svc_name) Log.info('fetching endpoint values from hctl fetch-fids cmd.') # For running rgw service and radosgw-admin tool, # we are using same endpoints fetched from hctl fetch-fids cmd as default endpoints, # given radosgw-admin tool & rgw service not expected to run simultaneously. # Update motr fid,endpoint config in cortx_rgw.conf. instance = 1 while instance <= client_instance_count: service_endpoints = Rgw._parse_endpoint_values( conf, instance, client_instance_count, svc_name) Log.debug('Validating endpoint entries provided by fetch-fids cmd') Rgw._validate_endpoint_paramters(service_endpoints) Log.info('Validated endpoint entries provided by fetch-fids cmd successfully.') Log.info('Updating endpoint values in rgw config file.') Rgw._update_rgw_config_with_endpoints(conf, service_endpoints, instance) instance = instance + 1 # Add additional parameters of SVC & Motr to config file. Rgw._update_svc_config(conf, 'client', const.SVC_CONFIG_DICT) Rgw._update_svc_data_path_value(conf, 'client') # Before user creation,Verify backend store value=motr in rgw config file. Rgw._verify_backend_store_value(conf) Log.info(f'Configure logrotate for {const.COMPONENT_NAME} at path: {const.LOGROTATE_CONF}') Rgw._logrotate_generic(conf) @staticmethod def _get_consul_url(conf: MappedConf, seq: int = 0): """Return consul url.""" http_endpoints = Rgw._fetch_endpoint_url(conf, const.CONSUL_ENDPOINT_KEY, 'http') consul_fqdn = http_endpoints[seq].split(':')[1] consul_url = 'consul:' + consul_fqdn + ':8500' return consul_url @staticmethod @ExponentialBackoff(exception=Exception, tries=4) def _check_consul_connection(conf: MappedConf): import socket sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.settimeout(2) consul_url = Rgw._get_consul_url(conf).split('//')[-1] host, port = consul_url.split(':') result = sock.connect_ex((host, int(port))) if result != 0: raise SetupError(errno.EINVAL, f"Consul server {host:port} not reachable") @staticmethod def _fetch_endpoint_url(conf: MappedConf, confstore_endpoint_key: str, endpoint_type: str): """Fetch endpoint url based on endpoint type from cortx config.""" endpoints = Rgw._get_cortx_conf(conf, confstore_endpoint_key) endpoints_values = list(filter(lambda x: urlparse(x).scheme == endpoint_type, endpoints)) if len(endpoints_values) == 0: raise SetupError(errno.EINVAL, f'{endpoint_type} endpoint is not specified in the conf.' f' Listed endpoints: {endpoints_values}') return endpoints_values @staticmethod def _file_exist(file_path: str): """Check if a file is exists.""" if not os.path.exists(file_path): raise SetupError(errno.EINVAL, f'{file_path} file not exists.') @staticmethod def _load_rgw_config(conf_idx: str, conf_url: str): """Add/Updated key-values in given config.""" try: if conf_url is None: raise SetupError(errno.EINVAL, 'Conf url is None.') Conf.load(conf_idx, conf_url, fail_reload=False) except (AssertionError, ConfError) as e: raise SetupError(errno.EINVAL, f'Error occurred while adding the key in {conf_url} config. {e}') @staticmethod def _get_rgw_config_path(conf: MappedConf): """Return RGW config file path.""" rgw_config_dir = Rgw._get_rgw_config_dir(conf) os.makedirs(rgw_config_dir, exist_ok=True) rgw_conf_file_path = os.path.join(rgw_config_dir, const.RGW_CONF_FILE) return rgw_conf_file_path @staticmethod def _get_rgw_config_dir(conf: MappedConf): """Return RGW config directory path.""" config_path = Rgw._get_cortx_conf(conf, const.CONFIG_PATH_KEY) rgw_config_dir = os.path.join(config_path, const.COMPONENT_NAME, Rgw._machine_id) return rgw_config_dir @staticmethod def _get_log_dir_path(conf: MappedConf): """Return log dir path.""" log_path = Rgw._get_cortx_conf(conf, const.LOG_PATH_KEY) log_dir_path = os.path.join(log_path, const.COMPONENT_NAME, Rgw._machine_id) os.makedirs(log_dir_path, exist_ok=True) return log_dir_path @staticmethod def _create_rgw_user(conf: MappedConf): """Create RGW admin user.""" user_name = Rgw._get_cortx_conf(conf, const.AUTH_USER_KEY) access_key = Rgw._get_cortx_conf(conf, const.AUTH_ADMIN_KEY) auth_secret = Rgw._get_cortx_conf(conf, const.AUTH_SECRET_KEY) err_str = f'user: {user_name} exists' timeout_str = f'timed out after {const.ADMIN_CREATION_TIMEOUT} seconds' # decrypt secret key. try: cluster_id = Rgw._get_cortx_conf(conf, const.CLUSTER_ID_KEY) cipher_key = Cipher.gen_key(cluster_id, const.DECRYPTION_KEY) password = Cipher.decrypt(cipher_key, auth_secret.encode(const.UTF_ENCODING)) password = password.decode(const.UTF_ENCODING) except CipherInvalidToken as e: raise SetupError(errno.EINVAL, f'auth_secret decryption failed. {e}') rgw_config = Rgw._get_rgw_config_path(conf) create_usr_cmd = f'radosgw-admin user create --uid={user_name} --access-key \ {access_key} --secret {password} --display-name="{user_name}" \ --caps="users=*;metadata=*;usage=*;zone=*;info=*;user=*;roles=*;user-policy=*;buckets=*" \ -c {rgw_config} -n client.radosgw-admin --no-mon-config' _, err, rc, = SimpleProcess(create_usr_cmd).run(timeout=const.ADMIN_CREATION_TIMEOUT) if rc == 0: Log.info(f'RGW admin user {user_name} is created.') return 0 elif rc != 0: err = err.decode(const.UTF_ENCODING) if isinstance(err, bytes) else err if err_str in err: Log.info(f'RGW admin user {user_name} is already created,' ' Skipping user creation.') return 0 elif timeout_str in err: Log.info('RGW user creation process exceeding timeout value - ' f'{const.ADMIN_CREATION_TIMEOUT} seconds. Skipping user creation on this node.') return rc else: Log.error(f'"{create_usr_cmd}" failed with error {err}.') return rc @staticmethod def _parse_endpoint_values(conf: MappedConf, instance: int, client_instance_count: int, svc_name: str): """Fetch endpoint values from hctl fetch-fids.""" hare_config_dir = Rgw._get_hare_config_path(conf) fetch_fids_cmd = f'hctl fetch-fids -c {hare_config_dir}' decoded_out = Rgw._run_fetch_fid_cmd(fetch_fids_cmd) Rgw._validate_hctl_cmd_response(decoded_out, svc_name) endpoints = [comp for comp in decoded_out if comp['name'] == svc_name] # RGW client_instance_count should be equal/less than the # no of rgw config elements present in hctl fetch-fids output. if len(endpoints) < client_instance_count: raise SetupError(errno.EINVAL, f'The count of {svc_name} elements in hctl-fetch-fids o/p ' f'does not match with the {svc_name} client instance count.') # Fetch endpoints based on instance, # for eg. for instance=1 read 0th index rgw config list from output and so on. index = instance - 1 endpoints = endpoints[index] for ep_key, ep_value in const.RgwEndpoint.__members__.items(): if list(ep_value.value.keys())[0] in endpoints: endpoints[ep_key] = endpoints.pop(list(ep_value.value.keys())[0]) return endpoints @staticmethod def _update_rgw_config_with_endpoints(conf: MappedConf, endpoints: dict, instance: int): """Update endpoints,port and log path values to rgw config file.""" config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) log_path = Rgw._get_log_dir_path(conf) service_instance_log_file = os.path.join(log_path, f'{const.COMPONENT_NAME}-{instance}.log') radosgw_admin_log_file = os.path.join(log_path, 'radosgw-admin.log') # Update version in conf file. version = Rgw._get_cortx_conf(conf, const.VERSION_KEY) Conf.set(Rgw._conf_idx, 'release>version', version) # Update client.radosgw-admin section only once, # Update this with same config that is define for 1st instance. if instance == 1: for key, ep_value in const.RgwEndpoint.__members__.items(): value = list(ep_value.value.values())[0] Conf.set(Rgw._conf_idx, f'{const.ADMIN_SECTION}>{value}', endpoints[key]) Conf.set(Rgw._conf_idx, const.MOTR_ADMIN_FID_KEY, endpoints[const.RgwEndpoint.MOTR_PROCESS_FID.name]) Conf.set(Rgw._conf_idx, const.MOTR_ADMIN_ENDPOINT_KEY, endpoints[const.RgwEndpoint.MOTR_CLIENT_EP.name]) Conf.set(Rgw._conf_idx, const.RADOS_ADMIN_LOG_FILE_KEY, radosgw_admin_log_file) # Create separate section for each service instance in cortx_rgw.conf file. for key, ep_value in const.RgwEndpoint.__members__.items(): value = list(ep_value.value.values())[0] Conf.set(Rgw._conf_idx, f'{const.SVC_SECTION % instance}>{value}', endpoints[key]) Conf.set(Rgw._conf_idx, const.SVC_LOG_FILE % instance, service_instance_log_file) # Removed port increment support for service multiple instances. # (in case of multiple instances port value needs to be incremented.) http_port = Rgw._get_service_port(conf, 'http') https_port = Rgw._get_service_port(conf, 'https') ssl_cert_path = Rgw._get_cortx_conf(conf, const.SSL_CERT_PATH_KEY) Conf.set(Rgw._conf_idx, const.RGW_FRONTEND_KEY % instance, f'beast port={http_port} ssl_port={https_port} ssl_certificate={ssl_cert_path} ssl_private_key={ssl_cert_path}') Conf.save(Rgw._conf_idx) @staticmethod def _get_service_port(conf: MappedConf, protocol: str): """Return rgw service port value.""" port = None endpoints = conf.get(const.SVC_ENDPOINT_KEY) if endpoints: svc_endpoints = list(filter(lambda x: urlparse(x).scheme == protocol, endpoints)) port = urlparse(svc_endpoints[0]).port Log.info(f'{protocol} port value - {port}') else: # If endpoint is not present, use default port value. if protocol == 'http': port = const.DEFAULT_HTTP_PORT elif protocol == 'https': port = const.DEFAULT_HTTPS_PORT Log.info(f'{const.SVC_ENDPOINT_KEY} is not available in cluster.conf,' f' using the default value. {protocol} - {port}') return port @staticmethod def _validate_endpoint_paramters(endpoints: dict): """Validate endpoint values fetched from hctl fetch-fids cmd.""" for key, _ in const.RgwEndpoint.__members__.items(): if key not in endpoints: raise SetupError(errno.EINVAL, f'Failed to validate hare endpoint values.' f'endpoint {key} is not present.') for ept_key, ept_value in endpoints.items(): if ept_value == '': raise SetupError(errno.EINVAL, f'Invalid values for {ept_key}: {ept_value}') @staticmethod def _validate_hctl_cmd_response(decoded_out: list, svc_name: str): """Validate hctl command response.""" try: next(endpoint for endpoint in decoded_out if endpoint['name'] == svc_name) except StopIteration: raise SetupError(errno.EINVAL, 'Invalid %s endpoint values', svc_name) @staticmethod def _get_hare_config_path(conf: MappedConf): """Return config path of hare component.""" base_config_path = Rgw._get_cortx_conf(conf, const.CONFIG_PATH_KEY) hare_config_path = os.path.join(base_config_path, 'hare', 'config', Rgw._machine_id) return hare_config_path @staticmethod def _get_num_client_instances(conf: MappedConf, svc_name: str): """Read number of client instances.""" client_idx = 0 num_instances = 1 while conf.get(const.CLIENT_INSTANCE_NAME_KEY % client_idx) is not None: name = Rgw._get_cortx_conf(conf, const.CLIENT_INSTANCE_NAME_KEY % client_idx) if name == svc_name: num_instances = int(Rgw._get_cortx_conf(conf, const.CLIENT_INSTANCE_NUMBER_KEY % client_idx)) break client_idx = client_idx + 1 return num_instances @staticmethod def _get_cortx_conf(conf: MappedConf, key: str, default_value = None): """Read value from cluster config for given key""" val = conf.get(key) if val is None: if default_value is None: raise SetupError(errno.EINVAL, f'Value for {key} key is None.') else: val = default_value return val @staticmethod def _get_svc_name(conf: MappedConf): """Read service name from cluster.conf""" svc_name = None num_component = Rgw._get_cortx_conf(conf, const.NUM_COMPONENTS_KEY % Rgw._machine_id) for idx in range(0, num_component): if (Rgw._get_cortx_conf(conf, const.COMPONENT_NAME_KEY % (Rgw._machine_id, idx)) == const.COMPONENT_NAME): svc_name = Rgw._get_cortx_conf(conf, const.SVC_NAME_KEY % (Rgw._machine_id, idx), const.COMPONENT_NAME) break Log.info(f'Service name for {const.COMPONENT_NAME} is {svc_name}') return svc_name @staticmethod def _generate_ssl_cert(conf: MappedConf): """Generate SSL certificate.""" ssl_cert_path = Rgw._get_cortx_conf(conf, const.SSL_CERT_PATH_KEY) if not os.path.exists(ssl_cert_path): # Generate SSL cert. Log.info(f'"https" is enabled and SSL certificate is not present at {ssl_cert_path}.') Log.info('Generating SSL certificate.') try: ssl_cert_configs = const.SSL_CERT_CONFIGS ssl_cert_obj = Certificate.init('ssl') ssl_cert_obj.generate( cert_path=ssl_cert_path, dns_list=const.SSL_DNS_LIST, **ssl_cert_configs) except SSLCertificateError as e: raise SetupError(errno.EINVAL, f'Failed to generate self signed ssl certificate: {e}') @staticmethod def _update_hax_endpoint(conf: MappedConf, data_pod_hostname: str): """Update hax endpoint values in rgw config file.""" Log.info('Reading motr_ha_endpoint from data pod') if not data_pod_hostname: raise SetupError(errno.EINVAL, 'Invalid data pod hostname: %s', data_pod_hostname) hare_config_dir = Rgw._get_hare_config_path(conf) fetch_fids_cmd = f'hctl fetch-fids -c {hare_config_dir} --node {data_pod_hostname}' decoded_out = Rgw._run_fetch_fid_cmd(fetch_fids_cmd, data_pod_hostname) Rgw._validate_hctl_cmd_response(decoded_out, 'hax') motr_ha_endpoint = [endpoints['ep'] for endpoints in decoded_out \ if 'hax' in endpoints.values()][0] Log.info(f'Fetched motr_ha_endpoint from data pod. Endpoint: {motr_ha_endpoint}') config_path = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_path Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) ha_ep_key = list(const.RgwEndpoint.MOTR_HA_EP.value.values())[0] Conf.set(Rgw._conf_idx, f'client.radosgw-admin>{ha_ep_key}', motr_ha_endpoint) Conf.save(Rgw._conf_idx) Log.info(f'Updated motr_ha_endpoint in config file {config_path}') @staticmethod def _run_fetch_fid_cmd(fetch_fids_cmd: str, data_pod_hostname: str = None): """Run hctl fetch-fids command through SimpleProcess.""" out, err, rc = SimpleProcess(fetch_fids_cmd).run() if rc != 0: if data_pod_hostname: Log.error(f'Unable to read fid information for hostname: ' f'{data_pod_hostname}. {err}') raise SetupError(rc, 'Unable to read fid information for hostname: ' '%s. %s', data_pod_hostname, err) else: Log.error(f'Unable to read fid information. {err}') raise SetupError(rc, 'Unable to read fid information. %s', err) decoded_out = json.loads(out.decode(const.UTF_ENCODING)) return decoded_out @staticmethod def _create_admin_on_current_node(conf: MappedConf, current_data_node: str): try: Rgw._update_hax_endpoint(conf, current_data_node) Log.info('Creating admin user.') # Before creating user check if user is already created. user_status = Rgw._create_rgw_user(conf) return user_status except Exception: return -1 @staticmethod def _update_hax_endpoint_and_create_admin(conf: MappedConf): """Update motr_ha(hax) endpoint values to rgw config file and create admin.""" # admin user should be created only on one node. # 1. While creating admin user, global lock created in consul kv store. # (rgw_consul_index, cortx>rgw>volatile>rgw_lock, machine_id) # 2. Before creating admin user. # a. Check for rgw_lock in consul kv store # b. Create user only if lock value is equal to **self** machine_id # 3. If user creation attempt failed from this node, delete the lock # so other node can acquire the lock and try user creation. # 4. If user creation is successful, update lock value to 'user_created'. rgw_consul_idx = f'{const.COMPONENT_NAME}_consul_idx' # Get consul url from cortx config. consul_url = Rgw._get_consul_url(conf) # Check for rgw_lock in consul kv store. Log.info('Checking for rgw lock in consul kv store.') Rgw._load_rgw_config(rgw_consul_idx, consul_url) rgw_lock = Rgw._get_lock(rgw_consul_idx) if rgw_lock is True: # TODO: Find a way to get current data pod hostname on server node. # current_data_node = socket.gethostname().replace('server', 'data') # user_status = Rgw._create_admin_on_current_node(conf, current_data_node) # if user_status == 0: # Log.info(f'User creation is successful on "{Rgw._machine_id}" node.') # Rgw._set_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY, const.ADMIN_USER_CREATED) # else: data_pod_hostnames = Rgw._get_data_nodes(conf) # if len(data_pod_hostnames) == 1 and current_data_node == data_pod_hostnames[0]: # Log.error('Admin user creation failed') # Rgw._delete_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY) # raise SetupError(user_status, 'Admin user creation failed on' # f' "{Rgw._machine_id}" node, with all data pods - {data_pod_hostnames}') # data_pod_hostnames.remove(current_data_node) for data_pod_hostname in data_pod_hostnames: try: Rgw._update_hax_endpoint(conf, data_pod_hostname) except SetupError as e: Log.debug(f'Error occured while updating hax endpoints. {e}') continue status = Rgw._create_rgw_user(conf) if status == 0: Log.info(f'User creation is successful on "{Rgw._machine_id}" node.') Rgw._set_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY, const.ADMIN_USER_CREATED) break else: if data_pod_hostname == data_pod_hostnames[-1]: Log.error(f'Admin user creation failed with error code - {status}') Rgw._delete_consul_kv(rgw_consul_idx, const.CONSUL_LOCK_KEY) raise SetupError(status, 'Admin user creation failed on' f' "{Rgw._machine_id}" node, with all data pods - {data_pod_hostnames}') @staticmethod def _get_data_nodes(conf: MappedConf): """Return all data nodes hostname""" storage_set = Rgw._get_cortx_conf(conf, const.STORAGE_SET % Rgw._machine_id) storage_set_count = Rgw._get_cortx_conf(conf, const.STORAGE_SET_COUNT) machine_ids = [] for storage_set_index in range(0, storage_set_count): if Rgw._get_cortx_conf(conf, const.STORAGE_SET_NAME % storage_set_index) == storage_set: machine_ids = Rgw._get_cortx_conf( conf, const.STORAGE_SET_NODE % storage_set_index) data_pod_hostnames = [Rgw._get_cortx_conf(conf, const.NODE_HOSTNAME % machine_id) for machine_id in machine_ids if Rgw._get_cortx_conf(conf, const.NODE_TYPE % machine_id) == const.DATA_NODE] return data_pod_hostnames @staticmethod def _get_lock(consul_idx: str): """Get lock from consul kv.""" # if in case try-catch block code executed at the same time on all the nodes, # then all nodes will try to update rgw lock-key in consul, after updating key # it will wait for sometime(time.sleep(3)) and in next iteration all nodes will # get lock value as node-id of node who has updated the lock key at last. # and then only that node will perform the user creation operation. rgw_lock = False while True: try: rgw_lock_val = Conf.get(consul_idx, const.CONSUL_LOCK_KEY) Log.info(f'{const.CONSUL_LOCK_KEY} value - {rgw_lock_val}') if rgw_lock_val is None: Log.info(f'Setting consul kv store value for key :{const.CONSUL_LOCK_KEY}' f' and value as :{Rgw._machine_id}') Rgw._set_consul_kv(consul_idx, const.CONSUL_LOCK_KEY, Rgw._machine_id) continue elif rgw_lock_val == Rgw._machine_id: Log.info('Required lock already possessed, proceeding with RGW ' f'admin user creation on node {rgw_lock_val}') rgw_lock = True break elif rgw_lock_val != Rgw._machine_id: if rgw_lock_val == const.ADMIN_USER_CREATED: Log.info('User is already created.') break Log.info(f'RGW lock is acquired by "{rgw_lock_val}" node.') Log.info(f'Waiting for user creation to complete on "{rgw_lock_val}" node') time.sleep(3) continue except Exception as e: Log.error('Exception occured while connecting to consul service' f' endpoint {e}') break return rgw_lock @staticmethod def _set_consul_kv(consul_idx: str, key: str, value: str): """Update key value pair in consul kv store.""" Conf.set(consul_idx, key, value) Conf.save(consul_idx) time.sleep(3) Log.info(f'Updated consul kv store - {key} - {value}.') @staticmethod def _delete_consul_kv(consul_idx: str, key: str): """Delete key value pair from consul kv store.""" Log.debug(f'Deleting rgw_lock key {key}.') Conf.delete(consul_idx, key) Log.info(f'{key} key is deleted') @staticmethod def _logrotate_generic(conf: MappedConf): """ Configure logrotate utility for rgw logs.""" log_file_path = Rgw._get_log_dir_path(conf) # Configure the cron job on hourly frequency for RGW log files. try: with open(const.CRON_LOGROTATE_TMPL, 'r') as f: content = f.read() with open(const.CRON_LOGROTATE, 'w') as f: f.write(content) except Exception as e: Log.error(f"Failed to configure cron job for logrotate at {const.FREQUENCY} basis." f"ERROR:{e}") # create radosgw logrotate file. # For eg: # filepath='/etc/logrotate.d/radosgw' old_file = os.path.join(const.LOGROTATE_DIR, 'ceph') if os.path.exists(old_file): os.remove(old_file) try: with open(const.LOGROTATE_TMPL, 'r') as f: content = f.read() content = content.replace('TMP_LOG_PATH', log_file_path) with open(const.LOGROTATE_CONF, 'w') as f: f.write(content) Log.info(f'{const.LOGROTATE_TMPL} file copied to {const.LOGROTATE_CONF}') except Exception as e: Log.error(f"Failed to configure logrotate for {const.COMPONENT_NAME}. ERROR:{e}") # start cron.d service try: os.system(f"chmod +x {const.CRON_LOGROTATE}") os.system("/usr/sbin/crond start") except Exception as e: Log.error(f"Failed to start the crond service for {const.COMPONENT_NAME}. ERROR:{e}") @staticmethod def _verify_backend_store_value(conf: MappedConf): """Verify backed store value as motr.""" config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) backend_store = Conf.get(Rgw._conf_idx, const.RGW_BACKEND_STORE_KEY) if not backend_store in const.SUPPORTED_BACKEND_STORES: raise SetupError(errno.EINVAL, f'Supported rgw backend store are {const.SUPPORTED_BACKEND_STORES},' f' currently configured one is {backend_store}') @staticmethod def _update_svc_config(conf: MappedConf, client_section: str, config_key_mapping: dict): """Update config properties from confstore to rgw config file.""" svc_config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + svc_config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Log.info(f'updating parameters to {client_section} in {svc_config_file}') for config_key, confstore_key in config_key_mapping.items(): default_value = Conf.get(Rgw._conf_idx, f'{client_section}>{config_key}') if confstore_key is None: Log.info(f'config key:{config_key} not found in rgw key mapping.\ hence using default value as {default_value} specified in config file.') continue else: # fetch actual value of parameter from confstore. # if config key/value is missing in confstore then use default value mentioned in config file. config_value = conf.get(confstore_key) if config_value is not None: Log.info(f'Setting config key :{config_key} with value:{config_value} at {client_section} section') Conf.set(Rgw._conf_idx, f'{client_section}>{config_key}', str(config_value)) else : Log.info(f'GConfig entry is missing for config key :{config_key}.\ hence using default value as {default_value} specified in config file.') continue Conf.save(Rgw._conf_idx) Log.info(f'added paramters to {client_section} successfully..') @staticmethod def _update_svc_data_path_value(conf: MappedConf, client_section: str): "Update svc config file with data path key which needs pre-processing values incase of default values." # Fetch cluster-id cluster_id = Rgw._get_cortx_conf(conf, const.CLUSTER_ID_KEY) svc_config_file = Rgw._get_rgw_config_path(conf) confstore_url = const.CONFSTORE_FILE_HANDLER + svc_config_file Rgw._load_rgw_config(Rgw._conf_idx, confstore_url) Log.info(f'updating data_path paramter to {client_section} in {svc_config_file}') # Create data path's default value e.g. /var/lib/ceph/radosgw/<cluster-id> data_path_default_value = const.SVC_DATA_PATH_DEFAULT_VALUE + cluster_id confstore_data_path_value = conf.get(const.SVC_DATA_PATH_CONFSTORE_KEY) if confstore_data_path_value is not None: Log.info(f'Setting config key :{const.SVC_DATA_PATH_KEY} with value:{confstore_data_path_value}\ at {client_section} section') Conf.set(Rgw._conf_idx, f'{client_section}>{const.SVC_DATA_PATH_KEY}', str(confstore_data_path_value)) else: Log.info(f'GConfig entry is missing for config key :{const.SVC_DATA_PATH_KEY}.\ hence using default value as {data_path_default_value} specified in config file.') Conf.set(Rgw._conf_idx, f'{client_section}>{const.SVC_DATA_PATH_KEY}', str(data_path_default_value)) Conf.save(Rgw._conf_idx) Log.info(f'added config parameters to {client_section} successfully..')

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appiumbase/fixtures/page_utils.py

Pawan7593/AppiumBase

0

177243

<reponame>Pawan7593/AppiumBase<gh_stars>0 def is_xpath_selector(selector): """ A basic method to determine if a selector is an xpath selector. """ if ( selector.startswith("/") or selector.startswith("./") or selector.startswith("(") ): return True return False def is_link_text_selector(selector): """ A basic method to determine if a selector is a link text selector. """ if ( selector.startswith("link=") or selector.startswith("link_text=") or selector.startswith("text=") ): return True return False def is_partial_link_text_selector(selector): """ A basic method to determine if a selector is a partial link text selector. """ if ( selector.startswith("partial_link=") or selector.startswith("partial_link_text=") or selector.startswith("partial_text=") or selector.startswith("p_link=") or selector.startswith("p_link_text=") or selector.startswith("p_text=") ): return True return False def is_name_selector(selector): """ A basic method to determine if a selector is a name selector. """ if selector.startswith("name=") or selector.startswith("&"): return True return False def get_link_text_from_selector(selector): """ A basic method to get the link text from a link text selector. """ if selector.startswith("link="): return selector[len("link="):] elif selector.startswith("link_text="): return selector[len("link_text="):] elif selector.startswith("text="): return selector[len("text="):] return selector def get_partial_link_text_from_selector(selector): """ A basic method to get the partial link text from a partial link selector. """ if selector.startswith("partial_link="): return selector[len("partial_link="):] elif selector.startswith("partial_link_text="): return selector[len("partial_link_text="):] elif selector.startswith("partial_text="): return selector[len("partial_text="):] elif selector.startswith("p_link="): return selector[len("p_link="):] elif selector.startswith("p_link_text="): return selector[len("p_link_text="):] elif selector.startswith("p_text="): return selector[len("p_text="):] return selector def get_name_from_selector(selector): """ A basic method to get the name from a name selector. """ if selector.startswith("name="): return selector[len("name="):] if selector.startswith("&"): return selector[len("&"):] return selector def is_id_selector(selector): """ A basic method to determine whether a ID selector or not """ if ":id" in selector: return True return False

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tests/587/test_interface.py

CSUN-COMP587-F18/keras

0

79783

<reponame>CSUN-COMP587-F18/keras<gh_stars>0 from __future__ import print_function import pytest from keras.preprocessing import sequence from keras.models import Sequential from keras.layers import Dense, Dropout, Activation from keras.layers import Embedding from keras.layers import Conv1D, GlobalMaxPooling1D from keras.datasets import imdb def test_interface(): maxFeat = 5000 maxLength = 400 batchSize = 32 embed = 50 fils = 250 kernSize = 3 hidDimensions = 250 epochs = 2 (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=maxFeat) x_train = sequence.pad_sequences(x_train, maxlen=maxLength) x_test = sequence.pad_sequences(x_test, maxlen=maxLength) model = Sequential() model.add(Embedding(maxFeat, embed, input_length=maxLength)) model.add(Dropout(0.2)) model.add(Conv1D(fils, kernSize, padding='valid', activation='relu', strides=1)) model.add(GlobalMaxPooling1D()) model.add(Dense(hidDimensions)) model.add(Dropout(0.2)) model.add(Activation('relu')) model.add(Dense(1)) model.add(Activation('sigmoid')) model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) model.fit(x_train, y_train, batch_size=batchSize, epochs=epochs, validation_data=(x_test, y_test)) score, acc = model.evaluate(x_test, y_test, batch_size=batchSize) assert(acc > .8) if __name__ == '__main__': pytest.main([__file__])

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mall_spider/utils/session_id_generator.py

524243642/taobao_spider

12

116616

# coding: utf-8 from abc import ABCMeta, abstractmethod class SessionIdGenerator(object): __metaclass__ = ABCMeta @abstractmethod def generate_id(self, session): pass

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conduit/transforms/fixmatch.py

wearepal/conduit

0

199000

from dataclasses import dataclass from typing import Callable, Generic, List, Optional, TypeVar, Union from PIL import Image import numpy as np from ranzen.decorators import implements from ranzen.misc import gcopy from torch import Tensor from typing_extensions import Self from conduit.data.datasets.utils import ImageTform, apply_image_transform from conduit.data.structures import InputContainer, RawImage, concatenate_inputs __all__ = [ "FixMatchPair", "FixMatchTransform", ] X = TypeVar("X", bound=Union[Tensor, RawImage, List[Image.Image]]) @dataclass class FixMatchPair(InputContainer[X]): strong: X weak: X @implements(InputContainer) def __len__(self) -> int: if isinstance(self.strong, Image.Image): return 1 return len(self.strong) @implements(InputContainer) def __add__(self, other: Self) -> Self: copy = gcopy(self, deep=False) is_batched = isinstance(self.strong, (Tensor, np.ndarray)) and (self.strong.ndim == 4) copy.strong = concatenate_inputs(copy.strong, other.strong, is_batched=is_batched) copy.weak = concatenate_inputs(copy.weak, other.weak, is_batched=is_batched) return copy A = TypeVar("A", bound=ImageTform) class FixMatchTransform(Generic[A]): def __init__( self, strong_transform: A, *, weak_transform: A, shared_transform_start: Optional[Callable[[Union[RawImage, Tensor]], RawImage]] = None, shared_transform_end: Optional[ Callable[[Union[RawImage, Tensor]], Union[RawImage, Tensor]] ] = None, ) -> None: self.strong_transform = strong_transform self.weak_transform = weak_transform self.shared_transform_start = shared_transform_start self.shared_transform_end = shared_transform_end def __call__(self, image: RawImage) -> FixMatchPair: if self.shared_transform_start is not None: image = self.shared_transform_start(image) strongly_augmented_image = apply_image_transform( image=image, transform=self.strong_transform ) weakly_augmented_image = apply_image_transform(image=image, transform=self.weak_transform) if self.shared_transform_end is not None: strongly_augmented_image = self.shared_transform_end(strongly_augmented_image) weakly_augmented_image = self.shared_transform_end(weakly_augmented_image) return FixMatchPair(strong=strongly_augmented_image, weak=weakly_augmented_image)

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scripts/SV_modules/BioNanoDuplications.py

wongkarenhy/Full-Genome-Analysis-Pipeline

2

159776

<gh_stars>1-10 #!/usr/bin/env python3.6 import pandas as pd import os import pyranges as pr from pyranges import PyRanges from io import StringIO import numpy as np import argparse from .BioNanoDeletions import reciprocal_overlap, checkRefOverlap, checkParentsOverlap, exonOverlap, overlap_length def readsmapDup(input): colnames = ['SmapEntryID', 'QryContigID', 'RefcontigID1', 'RefcontigID2', 'QryStartPos', 'QryEndPos', 'RefStartPos', 'RefEndPos', 'Confidence', 'Type', 'XmapID1', 'XmapID2', 'LinkID', 'QryStartIdx', 'QryEndIdx', 'RefStartIdx', 'RefEndIdx', 'Zygosity', 'Genotype', 'GenotypeGroup', 'RawConfidence', 'RawConfidenceLeft', 'RawConfidenceRight', 'RawConfidenceCenter', 'SVsize'] raw_df = pd.read_csv(input, sep='\t', comment='#', names=colnames, header=None, skiprows=lambda x: x in [0]) raw_df = raw_df[['SmapEntryID', 'RefcontigID1', 'RefcontigID2', 'RefStartPos','RefEndPos', 'QryStartPos', 'QryEndPos', 'Confidence', 'Type', 'Zygosity', 'Genotype']] #confident_df = raw_df.loc[raw_df['Confidence'] > 0.5] #modulate confidence threshold here confident_df = raw_df[raw_df['Type'].str.contains('duplication')] confident_df['RefcontigID1'] = confident_df['RefcontigID1'].astype(str).str.replace("23", "X") confident_df['RefcontigID2'] = confident_df['RefcontigID2'].astype(str).str.replace("24", "Y") # calculate SV size confident_df['SV_size'] = confident_df['RefEndPos'] - confident_df['RefStartPos'] confident_df['SV_size'] = confident_df['SV_size'].abs().round(0) confident_df = confident_df.loc[confident_df['SV_size'] >= 1000] return(confident_df) def BN_duplication(args): # Load Sample sample_frame = readsmapDup(args.samplepath) # Some old BN pipeline doesn't call duplication if sample_frame.empty: return None, None # Load parent data if args.type == 'trio' or args.father_duo: father_frame = readsmapDup(args.fpath) else: father_frame = pd.DataFrame(columns=['RefStartPos', 'RefEndPos', 'RefcontigID1']) if args.type == 'trio' or args.mother_duo: mother_frame = readsmapDup(args.mpath) else: mother_frame = pd.DataFrame(columns=['RefStartPos', 'RefEndPos', 'RefcontigID1']) # Load reference ref_frame = readsmapDup(args.referencepath) # Actual fun sample_copy, mother_copy, father_copy, ref_copy = sample_frame.copy(), mother_frame.copy(), father_frame.copy(), ref_frame.copy() for df in [sample_copy, mother_copy, father_copy, ref_copy]: df['Start'], df['End'], df['Chromosome'] = df.RefStartPos, df.RefEndPos, df['RefcontigID1'] # Remove anything that overlaps with the reference filtered_sample_frame = checkRefOverlap(sample_copy, ref_copy, sample_frame) # Add column based on overlap with parents filtered_sample_frame = checkParentsOverlap(sample_copy, father_copy, filtered_sample_frame, args, 'Found_in_Father') filtered_sample_frame = checkParentsOverlap(sample_copy, mother_copy, filtered_sample_frame, args, 'Found_in_Mother') filtered_sample_frame.to_csv(args.outputdirectory + '/' + args.sampleID + '_BioNano_duplications_raw.txt', sep='\t', index = False) # Describe exon overlap filtered_sample_frame['Start'], filtered_sample_frame['End'], filtered_sample_frame['Chromosome'] = filtered_sample_frame.RefStartPos, filtered_sample_frame.RefEndPos, filtered_sample_frame['RefcontigID1'] exon_calls = exonOverlap(args, filtered_sample_frame) exon_calls.to_csv(args.outputdirectory + '/' + args.sampleID + '_Bionano_duplications_exons.txt', sep='\t', index = False) return filtered_sample_frame, exon_calls def main(): parser = argparse.ArgumentParser(description='Sample and Path arguments.') parser.add_argument("-i", "--sampleID", help="Give the sample ID", dest="sampleID", type=str, required=True) parser.add_argument("-s", "--samplepath", help="Give the full path to the sample file", dest="samplepath", type=str, required=True) parser.add_argument("-f", "--fpath", help="Give the full path to the father's file", dest="fpath", type=str, required=True) parser.add_argument("-m", "--mpath", help="Give the full path to the mother's file", dest="mpath", type=str, required=True) parser.add_argument("-r", "--referencepath", help="Give the full path to the reference file", dest="referencepath", type=str, required=True) parser.add_argument("-o", "--outputdirectory", help="Give the directory path for the output file", dest="outputdirectory", type=str, required=True) parser.add_argument("-c", "--confidence", help="Give the confidence level cutoff for the sample here", dest="confidence", type=str, default=0.5) parser.add_argument("-e", "--exons", help="Give the file with exons intervals, names, and phenotypes here", dest="exons", type=str, required=True) parser.add_argument("-g", "--genelist", help="Primary genelist with scores", dest="genelist", type=str) parser.add_argument("-t", "--type", help="Specify whether this is a trio, duo, or singleton case", dest="type", type=str) parser.add_argument("-F", help="Set this flag if this is a duo case AND only father is sequenced", dest="father_duo", action='store_true') parser.add_argument("-M", help="Set this flag if this is a duo case AND only mother is sequenced", dest="mother_duo", action='store_true') args = parser.parse_args() # Actual function BN_duplication(args) if __name__=="__main__": main()

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tests/integration/Containers.py

adnrs96/runtime

0

10448

# -*- coding: utf-8 -*- from storyruntime.Containers import Containers from storyruntime.constants.ServiceConstants import ServiceConstants import storyscript def test_containers_format_command(story): """ Ensures a simple resolve can be performed """ story_text = 'alpine echo msg:"foo"\n' story.context = {} story.app.services = { 'alpine': { ServiceConstants.config: { 'actions': { 'echo': { 'arguments': {'msg': {'type': 'string'}} } } } } } story.tree = storyscript.Api.loads(story_text).result()['tree'] assert Containers.format_command( story, story.line('1'), 'alpine', 'echo' ) == ['echo', '{"msg":"foo"}'] def test_containers_format_command_no_arguments(story): story_text = 'alpine echo\n' story.context = {} story.app.services = { 'alpine': { ServiceConstants.config: { 'actions': { 'echo': {} } } } } story.tree = storyscript.Api.loads(story_text).result()['tree'] assert Containers.format_command( story, story.line('1'), 'alpine', 'echo' ) == ['echo']

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photos/models.py

eude313/vault

0

2801

from django.db import models from cloudinary.models import CloudinaryField # Create your models here. class Category(models.Model): name = models.CharField( max_length=200, null=False, blank=False ) def __str__(self): return self.name class Photo(models.Model): category = models.ForeignKey( Category, on_delete=models.SET_NULL, null=True, blank=True ) image = CloudinaryField('image', default='') description = models.TextField() def __str__(self): return self.description

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core/tests/test_polyflow/test_workflows/test_hyperband.py

erexer/polyaxon

0

8286

<reponame>erexer/polyaxon #!/usr/bin/python # # Copyright 2018-2020 Polyaxon, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pytest from marshmallow.exceptions import ValidationError from tests.utils import BaseTestCase, assert_equal_dict from polyaxon.polyflow.matrix import V1Hyperband from polyaxon.polyflow.optimization import V1Optimization, V1OptimizationMetric @pytest.mark.workflow_mark class TestWorkflowV1Hyperbands(BaseTestCase): def test_hyperband_config(self): config_dict = { "kind": "hyperband", "maxIterations": 10, "eta": 3, "resource": {"name": "steps", "type": "int"}, "resume": False, "metric": V1OptimizationMetric( name="loss", optimization=V1Optimization.MINIMIZE ).to_dict(), "params": {"lr": {"kind": "choice", "value": [[0.1], [0.9]]}}, } config = V1Hyperband.from_dict(config_dict) assert_equal_dict(config.to_dict(), config_dict) # Raises for negative values config_dict["maxIterations"] = 0 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["maxIterations"] = -0.5 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["maxIterations"] = 3 # Add numRuns percent config_dict["eta"] = -0.5 with self.assertRaises(ValidationError): V1Hyperband.from_dict(config_dict) config_dict["eta"] = 2.9 config = V1Hyperband.from_dict(config_dict) assert_equal_dict(config.to_dict(), config_dict)

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Day 4/D4.py

avidiotic/advent-of-code

0

186805

<reponame>avidiotic/advent-of-code import re from collections import defaultdict input_file = open('Puzzle4_input.txt','r') data = input_file.read().split('\n') data.sort() entry = [(list(map(int,re.findall(r'\d+',line))), re.findall(r'[a-zA-Z].+',line)) for line in data] log_gt = defaultdict(int) log_g = defaultdict(int) log_t = defaultdict(int) for timecode, text in entry: date = str(timecode[1])+"-"+str(timecode[2]) time_end_index = timecode[4] if 'begins shift' in text[0]: guard = timecode[5] asleep = None elif 'falls asleep' in text[0]: asleep = timecode[4] elif 'wakes up' in text[0]: for t in range(asleep, timecode[4]): log_gt[(guard,t)] += 1 log_g[guard] += 1 def max_g(d): best = None for k,v in d.items(): if(best is None or v > d[best]): best = k return(best) def max_t(d): best = None for (guard, time) in d: if(guard == best_guard): if(best is None or d[(guard,time)] > d[best]): best = (guard, time) return(best[1]) best_guard = max_g(log_g) best_time = max_t(log_gt) print(best_guard * best_time) def max_gt(d): best = None for (guard,time) in d: if(best is None or d[(guard,time)] > d[best]): best = (guard,time) return(best) (best_guard, best_time) = max_gt(log_gt) print(best_guard*best_time)

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src/fresnel/f_ratio.py

JonNRb/physics506

0

52192

<gh_stars>0 txt = None with open('f_data.txt') as f: txt = f.read() lines = [i for i in txt.split('\n') if i] data = [[int(i.strip()) for i in j.split('\t')] for j in lines] import math d2r = lambda ang: ang * math.pi / 180 ratio = lambda ang_2, ang_1: math.sin(d2r(ang_1)) / math.sin(d2r(ang_2)) for point in data: print(ratio(*point)) print('avg:', sum(ratio(*point) for point in data) / len(lines))

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ofspy/interSatelliteLink.py

ehsanfar/ofspy_v2

0

138010

""" Copyright 2015 <NAME>, Massachusetts Institute of Technology Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ """ InterSatelliteLink class. """ from .transceiver import Transceiver class InterSatelliteLink(Transceiver): def __init__(self, name=None, cost=0, size=1, capacity=1, protocol=None, maxTransmitted=1, maxReceived=1): """ @param name: the name of this transceiver @type name: L{str} @param cost: the cost of this inter-satellite link @type cost: L{float} @param size: the size of this inter-satellite link @type size: L{float} @param capacity: the data capacity of this inter-satellite link @type capacity: L{int} @param protocol: the protocol of this inter-satellite link @type protocol: L{str} @param maxTransmitted: the max data transmitted by this inter-satellite link each turn @type maxTransmitted: L{int} @param maxReceived: the max data received by this inter-satellite link each turn @type maxReceived: L{int} """ Transceiver.__init__(self, name=name, cost=cost, size=size, capacity=capacity, protocol=protocol, maxTransmitted=maxTransmitted, maxReceived=maxReceived) def couldTransmit(self, data, receiver, txLocation, rxLocation, context): """ Checks if this inter-satellite link could transmit data (state-independent). @param data: the data to transmit @type data: L{Data} @param receiver: the receiver receiving the data @type receiver: L{Transceiver} @param txLocation: the transmitter location @type txLocation: L{Location} @param rxLocation: the receiver location @type rxLocation: L{Location} @param context: the context @type context: L{Context} @return: L{bool} """ return super(InterSatelliteLink, self).couldTransmit(data, receiver) \ and txLocation.isOrbit() \ and rxLocation.isOrbit() \ and (abs(txLocation.sector - rxLocation.sector) <= 1 or abs(txLocation.sector - rxLocation.sector) >= context.getNumSectors() - 1) def couldReceive(self, data, transmitter, txLocation, rxLocation, context): """ Checks if this inter-satellite link could receive data (state-independent). @param data: the data to transmit @type data: L{Data} @param transmitter: the transmitter transmitting the data @type transmitter: L{Transceiver} @param txLocation: the transmitter location @type txLocation: L{Location} @param rxLocation: the receiver location @type rxLocation: L{Location} @param context: the context @type context: L{Context} @return: L{bool} """ return super(InterSatelliteLink, self).couldReceive(data, transmitter) \ and txLocation.isOrbit() \ and rxLocation.isOrbit() \ and (abs(txLocation.sector - rxLocation.sector) <= 1 or abs(txLocation.sector - rxLocation.sector) >= context.getNumSectors() - 1) def isISL(self): """ Checks if this is an inter-satellite link. @return: L{bool} """ return True

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pytils/clock.py

d33jiang/pytils

0

28441

import functools import heapq import logging from collections import deque from threading import Condition, RLock from typing import Any, Callable, List, NamedTuple, Optional from pytils.mixins import DaemonHandler from ._config.time import DEFAULT_TIME_SUPPLIER, TimeSupplier, TimeType, ZERO_DURATION __all__ = [ 'Action', 'Clock', 'Handler', 'Schedule', 'ScheduleKey', 'SchedulingQueue', 'TimeSupplier', 'TimeType', ] _DEFAULT_MAX_TASK_QUEUE_SIZE = 4096 _MAX_SLEEP_DURATION = 12. # # Convenience Function wrap_action = functools.partial # # Data Definitions class ScheduleKey(NamedTuple): period: Optional[float] action: 'Action' class ScheduleEntry(NamedTuple): next_run: float key: 'ScheduleKey' Action = Callable[[], Any] Handler = Callable[[Action], Any] # # Clock LOGGER = logging.getLogger('pytils.clock') class Clock: def __init__( self, max_queue_size: int = _DEFAULT_MAX_TASK_QUEUE_SIZE, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self._scheduling_queue = SchedulingQueue(max_queue_size, s_time) @property def schedule(self): return self._scheduling_queue.schedule def run_scheduler(self): self.schedule.run() def start_scheduler(self): self.schedule.start() def run_handler(self): self._scheduling_queue.run() def start_handler(self): self._scheduling_queue.start() class SchedulingQueue(DaemonHandler): def __init__( self, max_queue_size: int = _DEFAULT_MAX_TASK_QUEUE_SIZE, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self._cv = Condition() self._task_queue = deque(maxlen=max_queue_size) self._schedule = Schedule(self._enqueue, s_time) @property def schedule(self): return self._schedule def handle_one(self): with self._cv: self._cv.wait_for(self._task_queue.__len__) action = self._task_queue.popleft() self._cv.notify() action() def _enqueue(self, action: Action): with self._cv: self._task_queue.append(action) self._cv.notify() class Schedule(DaemonHandler): def __init__(self, handler: Handler, s_time: TimeSupplier = DEFAULT_TIME_SUPPLIER): self.s_time = s_time self._lock = RLock() self._cv = Condition(self._lock) self._schedule = [] # type: List[ScheduleEntry] self._handler = handler def register( self, action: Action, period: Optional[TimeType], delay: Optional[TimeType] = None) -> ScheduleKey: if period <= ZERO_DURATION: raise ValueError('period must be positive or None') if delay < ZERO_DURATION: raise ValueError('delay must be non-negative or None') if not delay: delay = ZERO_DURATION key = ScheduleKey(period, action) entry = ScheduleEntry(self.s_time() + delay, key) with self._cv: self._enqueue(entry) return key def handle_one(self): with self._cv: while not self._cv.wait_for(self.has_expired, self._get_next_sleep_duration()): pass self._handle_entry(self._dequeue()) def _handle_entry(self, entry: ScheduleEntry): self._handler(self._create_readmittence_action_from_key(entry.key)) def _create_readmittence_action_from_key(self, key: ScheduleKey) -> Action: if key.period is None: return key.action def perform_action_and_readmit(): next_run = self.s_time() + key.period key.action() current_time = self.s_time() if next_run < current_time: LOGGER.warning('Scheduled task took longer than its period length to complete') self._enqueue(ScheduleEntry(max(current_time, next_run), key)) return perform_action_and_readmit def has_expired(self) -> bool: with self._lock: return bool(self._schedule) and self._schedule[0].next_run - self.s_time() <= 0 def _get_next_sleep_duration(self) -> TimeType: if self._schedule: return min(_MAX_SLEEP_DURATION, max(ZERO_DURATION, self._schedule[0].next_run - self.s_time())) else: return _MAX_SLEEP_DURATION def _enqueue(self, entry: ScheduleEntry): self._cv.notify() heapq.heappush(self._schedule, entry) def _dequeue(self) -> Optional[ScheduleEntry]: self._cv.notify() return heapq.heappop(self._schedule) if self._schedule else None

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pyjq/__init__.py

spraakbanken/pyjq

0

192198

<gh_stars>0 from .cli import cli

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splicing_annotations/countSupportingReads.py

stevenxchen/splicing-modulators

0

154382

<filename>splicing_annotations/countSupportingReads.py #Junction counter adapted from rMATS "process unique sam" ### import necessary libraries import re,os,sys,logging,time,datetime,commands,argparse; import scipy,math,pickle,pysam; from scipy import stats; def listToString(x): rVal = ''; for a in x: rVal += a+' '; return rVal; ######### basic functions ############# # #Input: #insertsize_inclusion: a numerical variable for the paired-end read inclusion form insert size #insertsize_skipping: a numerical variable for the paired-end read skipping form insert size #insertsize_mean: a numerical variable for the mean of the insert size #insertsize_var: a numerical variable for the variance of the insert size #Output: #A 2-element vector for the [fraction of the inclusion form, fraction of the skipping form] def PE_fraction(insertsize_inclusion, insertsize_skipping, insertsize_mean, insertsize_var): p1=stats.norm.cdf(insertsize_inclusion+0.5,insertsize_mean,math.sqrt(insertsize_var)); p1=p1-stats.norm.cdf(insertsize_inclusion-0.5,insertsize_mean,math.sqrt(insertsize_var)); p2=stats.norm.cdf(insertsize_skipping+0.5,insertsize_mean,math.sqrt(insertsize_var)); p2=p2-stats.norm.cdf(insertsize_skipping-0.5,insertsize_mean,math.sqrt(insertsize_var)); return([p1/(p1+p2),p2/(p1+p2)]); def getInitialCounts(): ## getting initial counts for each AS event #rValue = [[[[],[]]],[[[],[]]],[[[],[]]]]; ## count type 1, 2, and 3, Include or Skip rValue = [[[],[]],[[],[]],[[],[]]]; rValue[CT1][I]=0; rValue[CT1][S]=0; rValue[CT2][I]=0; rValue[CT2][S]=0; rValue[CT3][I]=0; rValue[CT3][S]=0; return rValue; #### end of getInitialCounts() ############################### ## SAMPLE COUNTING FUNCTIONS ## ############################### def is_unique(r): # check if read is uniquely mapped for tag in r.tags: if tag[0]=='NH': # NH is tag for number of hits if int(tag[1])==1: # uniquely mapped if NH=1 if dataType=='single': ## single end, sufficient return True; elif r.is_proper_pair: return True; return False # def processSample(sample): ## call it with processSample(sample_1, S1) something like this global anchorLength; readCount=0; ### process the given sample ### #for s1 in sample: ## for each sam file # rep = sample.index(s1); # if len(s1.strip())<1: ## incorrect split. a user might accidently put comma at the end of input sam file list # continue; ### just skip this entry, probably the last one though s1=sample; sFile = pysam.Samfile(s1.strip(),'rb'); ## open bam file e1 = {}; ## edge count here for read in sFile.fetch(): readCount=readCount+1; if (readCount % 1000000) == 0: print(str(readCount)+" reads processed..."); if not is_unique(read): continue; rL = readLength; chr = sFile.getrname(read.tid) if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; mc = read.pos+1 mString = read.cigarstring #rID = read.qname group = mc/chunk; ## group does not change, it's okay to check only one group for a junction read ## if showMe: print 'mc:'+ str(group); if 'D' in mString or 'I' in mString or 'S' in mString or 'H' in mString or 'P' in mString or 'X' in mString or '=' in mString: ## skip continue; ## go to next line ### check to see if the line is either exonic read or junction read split_mString = mString.split('M'); tor = 0; ## type of read, 0 nothing, 1 exonic read, 2 junction read if len(split_mString)==2: tor = 1; ############ exonic read ###### rL = int(split_mString[0]); ## read length specified in this mapping string mec = mc+rL-1; ## mapping end coord egroup = mec/chunk; ## group for the mapping end coord of genomic reads if rL != readLength: continue ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group if (mc>se[chr][group][c][0] and mec<=se[chr][group][c][1]): ## read on the target c_se[c][CT2][I]+=1; ### end of SE ### ### MXE #### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group if (mc>mxe[chr][group][c][0] and mec<=mxe[chr][group][c][1]): ## read on the target exon c_mxe[c][CT2][I]+=1; elif (mc>mxe[chr][group][c][2] and mec<=mxe[chr][group][c][3]): ## read on the second exon c_mxe[c][CT2][S]+=1; ## end of MXE ### ## A5SS ## if chr in a5ss: ## this chromosome has a5ss event(s) if egroup in a5ss[chr]: ## this egroup has a5ss event(s), this group is valid for positive strand only for c in a5ss[chr][egroup]: ## for each a5ss event in this group if a5ss[chr][egroup][c][4]>a5ss[chr][egroup][c][1]: ## positive strand if (mc<=(a5ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a5ss[chr][egroup][c][1] and mec>=(a5ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][egroup][c][3] and mec<=a5ss[chr][egroup][c][1]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; if group in a5ss[chr]: ## this group has a5ss event(s), this group is valid for negative strand only for c in a5ss[chr][group]: ## for each a5ss event in this group if a5ss[chr][group][c][4]<a5ss[chr][group][c][1]: ## negative strand if (mc>a5ss[chr][group][c][0] and mc<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][group][c][0] and mec<=a5ss[chr][group][c][2]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; ## end of A5SS ### ## A3SS ## if chr in a3ss: ## this chromosome has a3ss event(s) if egroup in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][egroup]: ## for each a3ss event in this group if a3ss[chr][egroup][c][4]>a3ss[chr][egroup][c][1]: ## negative strand if (mc<=(a3ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a3ss[chr][egroup][c][1] and mec>=(a3ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][egroup][c][3] and mec<=a3ss[chr][egroup][c][1]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group if a3ss[chr][group][c][4]<a3ss[chr][group][c][1]: ## positive strand if (mc>a3ss[chr][group][c][0] and mc<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][group][c][0] and mec<=a3ss[chr][group][c][2]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; ## end of A3SS ### ## RI ## if chr in ri: ## this chromosome has ri event(s) groupsToExamine = list(set([group,egroup])); ## to examine multiple groups tempProcessedRI_id={}; ## to examine multiple groups for ggg in groupsToExamine: ## for each group if ggg in ri[chr]: ## this group has ri event(s) for c in ri[chr][ggg]: ## for each ri event in this group, strand does not matter for ri events if c in tempProcessedRI_id: ## already processed this event, skip it continue; ## next c please else: ## new c here tempProcessedRI_id[c]='1'; if (mc<=(ri[chr][ggg][c][3]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][3]+(rL-junctionLength/2))) or (mc<=(ri[chr][ggg][c][4]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][4]+(rL-junctionLength/2))): ## multi-exon read supporting target c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; if (mc>ri[chr][ggg][c][3] and mec<=ri[chr][ggg][c][4]): ## exon read supporting target c_ri[c][CT2][I]+=1; ## end of RI ### ####### now take care of junction counts from junction reads ###### elif len(split_mString)>=3: ###### junction read ########### beginning=int(split_mString[0].split('N')[-1]); ending = int(split_mString[-2].split('N')[-1]); jS=mc; jE=mc-1; usedE={};## to avoid using the same read more than one time for the same event #usedG={}; ## used group, to avoid examining the same group more than once prevN=-1; nextN=-1; ## for previous junction and next junction for ec in range(0,len(split_mString)-2): ## for each coordinate secondNumber = int(split_mString[ec].split('N')[-1]); jumpNumber = int(split_mString[ec+1].split('N')[0]); lastNumber = int(split_mString[ec+1].split('N')[-1]); if ec>0: ## there is prevN prevN = int(split_mString[ec].split('N')[0]); if (ec>=0 and ec<len(split_mString)-3): ## there is nextN nextN = int(split_mString[ec+2].split('N')[0]); if (ec>=0 and ec<len(split_mString)-2): ## there iS nextN if (ec==len(split_mString)-3): nextN=-1; else: nextN = int(split_mString[ec+2].split('N')[0]); jS = jE+secondNumber; ## 1-base jE = jS+jumpNumber; ## 0-base key = chr+'_'+str(jS)+'_'+str(jE); cStart=jS-secondNumber+1; cEnd=jS; cStart_last=cStart; cEnd_last=cEnd; minAnchor = min(int(split_mString[0]), int(split_mString[-2].split('N')[1])); ## min nts going across junction if minAnchor<anchorLength: ## not a valid junction read, do not count it continue; if ec==0: ## first junction, check the first number if beginning<anchorLength: ## not a valid junction read, do not count it continue; ## next junction if ec==(len(split_mString)-3): ## check the last segment length if ending<anchorLength: ## not a valid junction read, do not count it continue; ## edge counts if key in e1: ## exist! e1[key] = e1[key]+1; else: ## new junction e1[key] = 1; group = jS/chunk; ## changing group here #if group in usedG: ## already visited this group # continue; ## next junction coord #else: ## update usedG dictioanry # usedG[group]='1'; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group, examine if the given junction is part of it seLength=se[chr][group][c][1]-se[chr][group][c][0]; upjLength=se[chr][group][c][0]-se[chr][group][c][3]; dnjLength=se[chr][group][c][4]-se[chr][group][c][1]; if (jS==se[chr][group][c][3] and jE==se[chr][group][c][0] and ((lastNumber<=seLength and nextN==-1) or (lastNumber==seLength and nextN==dnjLength))) or (jS==se[chr][group][c][1] and jE==se[chr][group][c][4] and ((secondNumber<=seLength and prevN==-1) or (secondNumber==seLength and prevN==upjLength))): ## IJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][I]+=1; c_se[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif jS==se[chr][group][c][3] and jE==se[chr][group][c][4]: ## SJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][S]+=1; c_se[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of SE ### ## MXE ### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group, examine if the given junction is part of it mxeLen1=mxe[chr][group][c][1]-mxe[chr][group][c][0]; mxeLen2=mxe[chr][group][c][3]-mxe[chr][group][c][2]; upj1Len=mxe[chr][group][c][0]-mxe[chr][group][c][5]; dnj1Len=mxe[chr][group][c][6]-mxe[chr][group][c][1]; upj2Len=mxe[chr][group][c][2]-mxe[chr][group][c][5]; dnj2Len=mxe[chr][group][c][6]-mxe[chr][group][c][3]; if (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][0] and ((lastNumber<=mxeLen1 and nextN==-1) or (lastNumber==mxeLen1 and nextN==dnj1Len))) or (jS==mxe[chr][group][c][1] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen1 and prevN==-1) or (secondNumber==mxeLen1 and prevN==upj1Len))): ## IJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][I]+=1; c_mxe[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][2] and ((lastNumber<=mxeLen2 and nextN==-1) or (lastNumber==mxeLen2 and nextN==dnj2Len))) or (jS==mxe[chr][group][c][3] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen2 and prevN==-1) or (secondNumber==mxeLen2 and prevN==upj2Len))): ## SJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][S]+=1; c_mxe[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of MXE ### ## A5SS ### if chr in a5ss: ## this chromosome has a5ss event(s) if group in a5ss[chr]: ## this group has a5ss event(s) for c in a5ss[chr][group]: ## for each a5ss event in this group, examine if the given junction is part of it if a5ss[chr][group][c][4]>a5ss[chr][group][c][1]: ## positive strand if ( jS==a5ss[chr][group][c][1] and jE==a5ss[chr][group][c][4] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][3] and jE==a5ss[chr][group][c][4] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; if (cStart_last<=(a5ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last<=a5ss[chr][group][c][1] and cEnd_last>=(a5ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## negative strand if ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][0] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][2] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: if (cStart>a5ss[chr][group][c][0] and cStart<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A5SS ### ## A3SS ### if chr in a3ss: ## this chromosome has a3ss event(s) if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group, examine if the given junction is part of it if a3ss[chr][group][c][4]>a3ss[chr][group][c][1]: ## negative strand if ( jS==a3ss[chr][group][c][1] and jE==a3ss[chr][group][c][4] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][3] and jE==a3ss[chr][group][c][4] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; if (cStart_last<=(a3ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last<=a3ss[chr][group][c][1] and cEnd_last>=(a3ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A3SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## positive strand if ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][0] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][2] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: if (cStart>a3ss[chr][group][c][0] and cStart<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A3SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A3SS ### ## RI ### if chr in ri: ## this chromosome has ri event(s) if group in ri[chr]: ## this group has ri event(s) for c in ri[chr][group]: ## for each ri event in this group, examine if the given junction is part of it if jS==ri[chr][group][c][3] and jE==ri[chr][group][c][4] : ## SJC key=':'.join(["RI",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_ri[c][CT1][S]+=1; c_ri[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite if prevN == -1: if cStart<=(ri[chr][group][c][4]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][4]+(rL-junctionLength/2)): ## multi-exon read supporting target key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite if nextN == -1: cStart_last = jE+1; cEnd_last=jE+lastNumber; ## just change cStart and cEnd then do the same process if cStart_last<=(ri[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd_last>=(ri[chr][group][c][3]+(rL-junctionLength/2)): key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of RI ### #### end of for ec ##### else: ## it is not exonic nor junction read. proceed to the next line continue; sFile.close(); #edgeFile = open(s1.strip()+'.edgeCount', 'w'); #for k in e1: # edgeFile.write(k+'\t'+str(e1[k])+'\n'); #edgeFile.close(); ##### end of processSample ###### def processSample_stranded(sample,dt,lt): ## call it with processSample_firststrand(sample_1, S1,dataType,libraryType) something like this global anchorLength; ### process the given sample ### #for s1 in sample: ## for each sam file # rep = sample.index(s1); # if len(s1.strip())<1: ## incorrect split. a user might accidently put comma at the end of input sam file list # continue; ### just skip this entry, probably the last one though s1=sample; sFile = pysam.Samfile(s1.strip(),'rb'); ## open bam file e1 = {}; ## edge count here for read in sFile.fetch(): if not is_unique(read): continue; rL = readLength; chr = sFile.getrname(read.tid) if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; mc = read.pos+1 mString = read.cigarstring #rID = read.qname group = mc/chunk; ## group does not change, it's okay to check only one group for a junction read if 'D' in mString or 'I' in mString or 'S' in mString or 'H' in mString or 'P' in mString or 'X' in mString or '=' in mString: ## skip continue; ## go to next line ### check to see if the line is either exonic read or junction read split_mString = mString.split('M'); tor = 0; ## type of read, 0 nothing, 1 exonic read, 2 junction read if len(split_mString)==2: tor = 1; ############ exonic read ###### rL = int(split_mString[0]); ## read length specified in this mapping string mec = mc+rL-1; ## mapping end coord egroup = mec/chunk; myStrand=''; sFlag=read.flag; if dt=='paired' and lt=='first': ## paired-read, firststrand if (sFlag&16 and sFlag&64) or (sFlag&32 and sFlag&128): ##'+' strand myStrand='+'; elif (sFlag&32 and sFlag&64) or (sFlag&16 and sFlag&128): ##'-' strand myStrand='-'; elif dt=='paired' and lt=='second': ## paired-read, secondstrand if (sFlag&32 and sFlag&64) or (sFlag&16 and sFlag&128): ##'+' strand myStrand='+'; elif (sFlag&16 and sFlag&64) or (sFlag&32 and sFlag&128): ##'-' strand myStrand='-'; elif dt=='single' and lt=='first': ##single-end, firststrand if sFlag&16 : ##'+' strand myStrand='+'; elif sFlag&32: ##'-' strand myStrand='-'; elif dt=='single' and lt=='second': ##single-end, secondstrand if sFlag&32 : ##'+' strand myStrand='+'; elif sFlag&16: ##'-' strand myStrand='-'; if len(myStrand)==0 or rL != readLength: ## skip this read, cannot determine the strand continue; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group if se[chr][group][c][-1]==myStrand: ## same strand if (mc>se[chr][group][c][0] and mec<=se[chr][group][c][1]): ## read on the target c_se[c][CT2][I]+=1; ### end of SE ### ### MXE #### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group if mxe[chr][group][c][-1]==myStrand: ## same strand if (mc>mxe[chr][group][c][0] and mec<=mxe[chr][group][c][1]): ## read on the target exon c_mxe[c][CT2][I]+=1; elif (mc>mxe[chr][group][c][2] and mec<=mxe[chr][group][c][3]): ## read on the second exon c_mxe[c][CT2][S]+=1; ## end of MXE ### ## A5SS ## if chr in a5ss: ## this chromosome has a5ss event(s) if egroup in a5ss[chr]: ## this egroup has a5ss event(s), valid only for positive strand only for c in a5ss[chr][egroup]: ## for each a5ss event in this group if a5ss[chr][egroup][c][-1]==myStrand: ## same strand if a5ss[chr][egroup][c][4]>a5ss[chr][egroup][c][1]: ## positive strand if (mc<=(a5ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a5ss[chr][egroup][c][1] and mec>=(a5ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][egroup][c][3] and mec<=a5ss[chr][egroup][c][1]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; if group in a5ss[chr]: ## this group has a5ss event(s), for negative strand ones only for c in a5ss[chr][group]: ## for each a5ss event in this group if a5ss[chr][group][c][-1]==myStrand: ## same strand if a5ss[chr][group][c][4]<a5ss[chr][group][c][1]: ## negative strand if (mc>a5ss[chr][group][c][0] and mc<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; if (mc>a5ss[chr][group][c][0] and mec<=a5ss[chr][group][c][2]): ## exon read supporting target c_a5ss[c][CT2][I]+=1; ## end of A5SS ### ## A3SS ## if chr in a3ss: ## this chromosome has a3ss event(s) if egroup in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][egroup]: ## for each a3ss event in this group if a3ss[chr][egroup][c][-1]==myStrand: ## same strand if a3ss[chr][egroup][c][4]>a3ss[chr][egroup][c][1]: ## negative strand if (mc<=(a3ss[chr][egroup][c][3]-(rL-junctionLength/2)+1) and mec<=a3ss[chr][egroup][c][1] and mec>=(a3ss[chr][egroup][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][egroup][c][3] and mec<=a3ss[chr][egroup][c][1]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group if a3ss[chr][group][c][-1]==myStrand: ## same strand if a3ss[chr][group][c][4]<a3ss[chr][group][c][1]: ## positive strand if (mc>a3ss[chr][group][c][0] and mc<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and mec>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; if (mc>a3ss[chr][group][c][0] and mec<=a3ss[chr][group][c][2]): ## exon read supporting target c_a3ss[c][CT2][I]+=1; ## end of A3SS ### ## RI ## if chr in ri: ## this chromosome has ri event(s) groupsToExamine = list(set([group,egroup])); ## to examine multiple groups tempProcessedRI_id={}; ## to examine multiple groups for ggg in groupsToExamine: ## for each group if ggg in ri[chr]: ## this group has ri event(s) for c in ri[chr][ggg]: ## for each ri event in this group, strand does not matter for ri events if c in tempProcessedRI_id: ## already processed this event, skip it continue; ## next c please else: ## new c here if ri[chr][ggg][c][-1]==myStrand: ## same strand if (mc<=(ri[chr][ggg][c][3]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][3]+(rL-junctionLength/2))) or (mc<=(ri[chr][ggg][c][4]-(rL-junctionLength/2)+1) and mec>=(ri[chr][ggg][c][4]+(rL-junctionLength/2))): ## multi-exon read supporting target c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; if (mc>ri[chr][ggg][c][3] and mec<=ri[chr][ggg][c][4]): ## exon read supporting target c_ri[c][CT2][I]+=1; ## end of RI ### ####### now take care of junction counts from junction reads ###### elif len(split_mString)>=3: ###### junction read ########### beginning=int(split_mString[0].split('N')[-1]); ending = int(split_mString[-2].split('N')[-1]); jS=mc; jE=mc-1; usedE={};## to avoid using the same read more than one time for the same event #usedG={}; ## used group, to avoid examining the same group more than once prevN=-1; nextN=-1; ## for previous junction and next junction for ec in range(0,len(split_mString)-2): ## for each coordinate secondNumber = int(split_mString[ec].split('N')[-1]); jumpNumber = int(split_mString[ec+1].split('N')[0]); lastNumber = int(split_mString[ec+1].split('N')[-1]); if ec>0: ## there is prevN prevN = int(split_mString[ec].split('N')[0]); if (ec>=0 and ec<len(split_mString)-3): ## there is nextN nextN = int(split_mString[ec+2].split('N')[0]); if (ec>=0 and ec<len(split_mString)-2): ## there iS nextN if (ec==len(split_mString)-3): nextN=-1; else: nextN = int(split_mString[ec+2].split('N')[0]); jS = jE+secondNumber; ## 1-base jE = jS+jumpNumber; ## 0-base key = chr+'_'+str(jS)+'_'+str(jE); cStart=jS-secondNumber+1; cEnd=jS; minAnchor = min(int(split_mString[0]), int(split_mString[-2].split('N')[1])); ## min nts going across junction if minAnchor<anchorLength: ## not a valid junction read, do not count it continue; if ec==0: ## first junction, check the first number if beginning<anchorLength: ## not a valid junction read, do not count it continue; ## next junction if ec==(len(split_mString)-3): ## check the last segment length if ending<anchorLength: ## not a valid junction read, do not count it continue; ## edge counts if key in e1: ## exist! e1[key] = e1[key]+1; else: ## new junction e1[key] = 1; group = jS/chunk; ## changing group here #if group in usedG: ## already visited this group # continue; ## next junction coord #else: ## update usedG dictioanry # usedG[group]='1'; ## SE ### if chr in se: ## this chromosome has se event(s) if group in se[chr]: ## this group has skipped exon event(s) for c in se[chr][group]: ## for each skipped exon event in this group, examine if the given junction is part of it seLength=se[chr][group][c][1]-se[chr][group][c][0]; upjLength=se[chr][group][c][0]-se[chr][group][c][3]; dnjLength=se[chr][group][c][4]-se[chr][group][c][1]; if (jS==se[chr][group][c][3] and jE==se[chr][group][c][0] and ((lastNumber<=seLength and nextN==-1) or (lastNumber==seLength and nextN==dnjLength))) or (jS==se[chr][group][c][1] and jE==se[chr][group][c][4] and ((secondNumber<=seLength and prevN==-1) or (secondNumber==seLength and prevN==upjLength))): ## IJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][I]+=1; c_se[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif jS==se[chr][group][c][3] and jE==se[chr][group][c][4]: ## SJC key=':'.join(["SE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_se[c][CT1][S]+=1; c_se[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of SE ### ## MXE ### if chr in mxe: ## this chromosome has mxe event(s) if group in mxe[chr]: ## this group has mxe event(s) for c in mxe[chr][group]: ## for each mxe event in this group, examine if the given junction is part of it mxeLen1=mxe[chr][group][c][1]-mxe[chr][group][c][0]; mxeLen2=mxe[chr][group][c][3]-mxe[chr][group][c][2]; upj1Len=mxe[chr][group][c][0]-mxe[chr][group][c][5]; dnj1Len=mxe[chr][group][c][6]-mxe[chr][group][c][1]; upj2Len=mxe[chr][group][c][2]-mxe[chr][group][c][5]; dnj2Len=mxe[chr][group][c][6]-mxe[chr][group][c][3]; if (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][0] and ((lastNumber<=mxeLen1 and nextN==-1) or (lastNumber==mxeLen1 and nextN==dnj1Len))) or (jS==mxe[chr][group][c][1] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen1 and prevN==-1) or (secondNumber==mxeLen1 and prevN==upj1Len))): ## IJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][I]+=1; c_mxe[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif (jS==mxe[chr][group][c][5] and jE==mxe[chr][group][c][2] and ((lastNumber<=mxeLen2 and nextN==-1) or (lastNumber==mxeLen2 and nextN==dnj2Len))) or (jS==mxe[chr][group][c][3] and jE==mxe[chr][group][c][6] and ((secondNumber<=mxeLen2 and prevN==-1) or (secondNumber==mxeLen2 and prevN==upj2Len))): ## SJC key=':'.join(["MXE",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_mxe[c][CT1][S]+=1; c_mxe[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite ### end of MXE ### ## A5SS ### if chr in a5ss: ## this chromosome has a5ss event(s) if group in a5ss[chr]: ## this group has a5ss event(s) for c in a5ss[chr][group]: ## for each a5ss event in this group, examine if the given junction is part of it if a5ss[chr][group][c][4]>a5ss[chr][group][c][1]: ## positive strand if ( jS==a5ss[chr][group][c][1] and jE==a5ss[chr][group][c][4] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][3] and jE==a5ss[chr][group][c][4] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart<=(a5ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd<=a5ss[chr][group][c][1] and cEnd>=(a5ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## negative strand if ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][0] ): ## IJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a5ss[chr][group][c][5] and jE==a5ss[chr][group][c][2] ): ## SJC key=':'.join(["A5SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a5ss[c][CT1][S]+=1; c_a5ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart>a5ss[chr][group][c][0] and cStart<=(a5ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a5ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a5ss[c][CT1][I]+=1; c_a5ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A5SS ### ## A3SS ### if chr in a3ss: ## this chromosome has a3ss event(s) if group in a3ss[chr]: ## this group has a3ss event(s) for c in a3ss[chr][group]: ## for each a3ss event in this group, examine if the given junction is part of it if a3ss[chr][group][c][4]>a3ss[chr][group][c][1]: ## negative strand if ( jS==a3ss[chr][group][c][1] and jE==a3ss[chr][group][c][4] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][3] and jE==a3ss[chr][group][c][4] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart<=(a3ss[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd<=a3ss[chr][group][c][1] and cEnd>=(a3ss[chr][group][c][3]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite else: ## positive strand if ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][0] ): ## IJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite elif ( jS==a3ss[chr][group][c][5] and jE==a3ss[chr][group][c][2] ): ## SJC key=':'.join(["A3SS",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_a3ss[c][CT1][S]+=1; c_a3ss[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite elif prevN == -1: cStart = jE+1; cEnd=jE+lastNumber; if (cStart>a3ss[chr][group][c][0] and cStart<=(a3ss[chr][group][c][2]-(rL-junctionLength/2)+1) and cEnd>=(a3ss[chr][group][c][2]+(rL-junctionLength/2))): ## multi-exon read supporting target key=':'.join(["A5SS",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_a3ss[c][CT1][I]+=1; c_a3ss[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of A3SS ### ## RI ### if chr in ri: ## this chromosome has ri event(s) if group in ri[chr]: ## this group has ri event(s) for c in ri[chr][group]: ## for each ri event in this group, examine if the given junction is part of it if jS==ri[chr][group][c][3] and jE==ri[chr][group][c][4] : ## SJC key=':'.join(["RI",str(c)]); if key in usedE: ## already used; continue; ## skip and go to next c c_ri[c][CT1][S]+=1; c_ri[c][CT2][S]+=1; usedE[key]=1; ## okay to overwrite if prevN == -1: if cStart<=(ri[chr][group][c][4]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][4]+(rL-junctionLength/2)): ## multi-exon read supporting target key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite if nextN == -1: cStart = jE+1; cEnd=jE+lastNumber; ## just change cStart and cEnd then do the same process if cStart<=(ri[chr][group][c][3]-(rL-junctionLength/2)+1) and cEnd>=(ri[chr][group][c][3]+(rL-junctionLength/2)): key=':'.join(["RI",str(c)]); if key not in usedE: ## read didn't cover this event before, add it c_ri[c][CT1][I]+=1; c_ri[c][CT2][I]+=1; usedE[key]=1; ## okay to overwrite ### end of RI ### #### end of for ec ##### else: ## it is not exonic nor junction read. proceed to the next line continue; sFile.close(); #edgeFile = open(s1.strip()+'.edgeCount', 'w'); #for k in e1: # edgeFile.write(k+'\t'+str(e1[k])+'\n'); #edgeFile.close(); ##### end of processSample_stranded ###### #def getId(ids,key): # for chr in ids: ## this chromosome has se event(s) # for group in ids[chr]: ## this group has skipped exon event(s) # if key in ids[chr][group]: # event_location=ids[chr][group][key]; #[tS,tE,uS,uE,dS,dE,strand] # return [chr,event_location[-1],":".join(map(str,event_location[:-1]))]; def writeInputFile2(h1,f1,id_index,cnt,sup): ## header 1,2,3, file 1,2,3, count dict, supple dict) ## print header first f1.write(h1+'\n'); for k in sorted(sup.keys()): f1.write(str(id_index[k])+'\t'+str(cnt[k][CT1][I])+'\t'+str(cnt[k][CT1][S])+'\t'+str(sup[k][CT1][0])+'\t'+str(sup[k][CT1][1])+'\n'); #f1.write(':'.join(map(str,getId(id_index,k)))+'\t'+str(cnt[k][CT1][I])+'\t'+str(cnt[k][CT1][S])+'\t'+str(sup[k][CT1][0])+'\t'+str(sup[k][CT1][1])+'\n'); ##### end of writeInputFile function ####### def main(): parser = argparse.ArgumentParser(description=''' Given a BAM file and rMATS event files, count the reads supporting the events.''') parser.add_argument('SE', help='skipped event file, generated by rMATS') parser.add_argument('MXE', help='mutually exclusive event file, generated by rMATS') parser.add_argument('A5SS', help='alternative 5 prime event file, generated by rMATS') parser.add_argument('A3SS', help='alternative 3 prime event file, generated by rMATS') parser.add_argument('RI', help='retianed intron event file, generated by rMATS') parser.add_argument('input_file', help='BAM file, previously aligned') parser.add_argument('outDir', help='output directory.') parser.add_argument('-rl', '--read_length', type=int, default=50, help='read length. Default: 50.') parser.add_argument('-jl', '--junction_length', type=int, default=84, help='junction length. Default: 84.') #parser.add_argument('-p', '--processor', type=int, default=1, # help='number of processors to use. Default: 1.') print("initializing variables...") #### global variables ################ #### default configuration values ##### #readLength=50; #junctionLength=84; global SE global MXE global A5SS global A3SS #AFE='AFE'; #ALE='ALE'; global RI global experiment experiment = 'custom'; global base base ='base'; global dataType dataType = 'paired'; ## either single or paired global samDir samDir = '.'; #input_file='.'; #outDir = 'myOutput'; email = '<EMAIL>'; libType='fr-unstranded'; ####################################### #import readLength,junctionLength,outDir,input_file args = parser.parse_args(); #events = parse_events(args.efname, args.column) #sys.stderr.write('Total number of events: {}.\n'.format(len(events))) #sample_info = parse_sample(args.sfname) #sys.stderr.write('Total number of samples: {}.\n'.format(len(sample_info['sample']))) #psi_diff(events, sample_info, args.ofname, args.iteration, args.seed, args.group_size, args.processor) global readLength; readLength = args.read_length; global junctionLength; junctionLength = args.junction_length; global input_file; input_file = args.input_file; global outDir; outDir = args.outDir; SE=args.SE; MXE=args.MXE; A5SS=args.A5SS; A3SS=args.A3SS; RI=args.RI; # print("Input File: "+input_file) print("Output Folder: "+outDir) print("Read Length: "+str(readLength)) print("Junction Length: "+str(junctionLength)) # commands.getstatusoutput('mkdir '+outDir); # ejLength = junctionLength-readLength+1; ## effective junction length global anchorLength; anchorLength = readLength-junctionLength/2; ## anchor length global CT1,CT2,CT3; CT1,CT2,CT3=0,1,2; ### count type 1,2, or 3 #S1,S2=0,1; ## sample 1 or sample 2 global I,S; I,S=0,1; ## inclusion isoform or skipping form # #pPath = outDir+'/junctions.per.sample.pickle'; #junctions = pickle.load(open(pPath)); ## junctions per sample # prefix = experiment; # ### open AS event files.. # seFile = open(SE); ## skipped exon event file mxeFile = open(MXE); ## mxe event file a5ssFile = open(A5SS); ## a5ss event file a3ssFile = open(A3SS); ## a3ss event file riFile = open(RI); ## ri event file # ### open output files here... # JC_seFile = open(outDir+'/JC.'+prefix+'.SE.MATS.input.txt', 'w'); JC_mxeFile = open(outDir+'/JC.'+prefix+'.MXE.MATS.input.txt', 'w'); JC_a5ssFile = open(outDir+'/JC.'+prefix+'.A5SS.MATS.input.txt', 'w'); JC_a3ssFile = open(outDir+'/JC.'+prefix+'.A3SS.MATS.input.txt', 'w'); JC_riFile = open(outDir+'/JC.'+prefix+'.RI.MATS.input.txt', 'w'); global chunk; chunk=1000; ## to speed up the sam file processing ############################## ## BUILD EVENT DICTIONARIES ## ############################## print("Building event dictionaries from annotation...") global se,mxe,a5ss,a3ss,afe,ale,ri se={};mxe={};a5ss={};a3ss={};afe={};ale={};ri={}; ## 7 dictionaries global id_se,id_mxe,id_a5ss,id_a3ss,id_afe,id_ale,id_ri id_se={};id_mxe={};id_a5ss={};id_a3ss={};id_afe={};id_ale={};id_ri={}; global e_se,e_mxe,e_a5ss,e_a3ss,e_afe,e_ale,e_ri e_se={};e_mxe={};e_a5ss={};e_a3ss={};e_afe={};e_ale={};e_ri={}; ## exons dictionaries global c_se,c_mxe,c_a5ss,c_a3ss,c_afe,c_ale,c_ri c_se={};c_mxe={};c_a5ss={};c_a3ss={};c_afe={};c_ale={};c_ri={}; ## count dictionaries global s_se,s_mxe,s_a5ss,s_a3ss,s_afe,s_ale,s_ri s_se={};s_mxe={};s_a5ss={};s_a3ss={};s_afe={};s_ale={};s_ri={}; ## supple dict. effective length of inclusion or skipping form for CT1,CT2,CT3 # #### SE ###### c=0; ## count numSE=0; ## number of SE numSEDup=0; ## duplicate SE id line=seFile.readline(); ## skipping header for line in seFile: ## process skipped exon events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; tS = int(ele[5]); tE = int(ele[6]); ## target exon coord uS = int(ele[7]); uE = int(ele[8]); ## upstream exon coord dS = int(ele[9]); dE = int(ele[10]); ## downstream exon coord tLen=tE-tS; ## target exon length uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length id_se[id]=":".join(map(str,[chr,strand,tS,tE,uS,uE,dS,dE])); e_se[id] = [tS,tE,uS,uE,dS,dE]; c_se[id] = getInitialCounts(); I_0= min(tLen,readLength)+readLength-4*anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2*anchorLength+1; ## effective skipping form length for JC I_1= readLength-2*anchorLength+tLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_se[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(uS/chunk, uE/chunk+1) + range(tS/chunk, tE/chunk+1) + range(dS/chunk, dE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in se: ## already processed this chromosome for i in group: ## for each possible group if i in se[chr]: ## this group is already there if id in se[chr][i]: ## not likely but this group already has the id numSEDup+=1; else: ## new SE ID se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; else: ## new group to this chromosome se[chr][i]={}; se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; else: ## first time accesing this chromosome se[chr]={}; for i in group: ## for each possible group se[chr][i]={}; se[chr][i][id] = [tS,tE,uS,uE,dS,dE,strand]; ## skipping event with coords numSE+=1; # #### MXE #### c=0; ## count numMXE=0; ## number of MXE numMXEDup=0; ## duplicate MXE id line=mxeFile.readline(); ## mxe header for line in mxeFile: ## process mxe events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; ## '+' or '-' tS = int(ele[5]); tE = int(ele[6]); ## target exon coord sS = int(ele[7]); sE = int(ele[8]); ## second exon coord if strand=='-': ## negative strand, switch target exon and second exon tS = int(ele[7]); tE = int(ele[8]); ## target exon coord sS = int(ele[5]); sE = int(ele[6]); ## second exon coord uS = int(ele[9]); uE = int(ele[10]); ## upstream exon coord (samller coord) dS = int(ele[11]); dE = int(ele[12]); ## downstream exon coord (bigger coord) tLen=tE-tS; ## target exon length sLen=sE-sS; ## second exon length uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length id_mxe[id]=":".join(map(str,[chr,strand,tS,tE,sS,sE,uS,uE,dS,dE])); e_mxe[id] = [tS,tE,sS,sE,uS,uE,dS,dE]; ## target, second, up, down (This is different from the input file) c_mxe[id] = getInitialCounts(); I_0= min(tLen,readLength)+readLength-4*anchorLength+2; ## effective inclusion form length for JC S_0= min(sLen,readLength)+readLength-4*anchorLength+2; ## effective skipping form length for JC I_1= readLength-2*anchorLength+tLen+1; ## effective inclusion form length for JC+reads on target S_1= readLength-2*anchorLength+sLen+1; ## effective inclusion form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_mxe[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(uS/chunk,uE/chunk+1)+range(tS/chunk,tE/chunk+1); group = group + range(sS/chunk,sE/chunk+1)+range(dS/chunk,dE/chunk+1);## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in mxe: ## already processed this chromosome for i in group: ## for each possible group if i in mxe[chr]: ## this group is already there if id in mxe[chr][i]: ## not likely but this group already has the id numMXEDup+=1; else: ## new MXE ID mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE += 1; else: ## new group to this chromosome mxe[chr][i]={}; mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE += 1; else: ## first time accesing this chromosome mxe[chr]={}; for i in group: ## for each possible group mxe[chr][i]={}; mxe[chr][i][id] = [tS,tE,sS,sE,uS,uE,dS,dE,strand]; ## mxe event with coords numMXE+=1; # #### A5SS #### c=0; ## count numA5SS=0; ## number of A5SS numA5SSDup=0; ## duplicate A5SS id line=a5ssFile.readline(); ## skipping header for line in a5ssFile: ## process a5ss events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; lS = int(ele[5]); lE = int(ele[6]); ## long exon coord sS = int(ele[7]); sE = int(ele[8]); ## short exon coord fS = int(ele[9]); fE = int(ele[10]); ## flanking exon coord lLen=min(lE-lS,junctionLength/2); ## long exon length sLen=min(sE-sS,junctionLength/2); ## short exon length fLen=min(fE-fS,junctionLength/2); ## flanking exon length aLen=lE-lS-(sE-sS); ## alternative SS region length id_a5ss[id]=":".join(map(str,[chr,strand,lS,lE,sS,sE,fS,fE])); e_a5ss[id] = [lS,lE,sS,sE,fS,fE]; c_a5ss[id] = getInitialCounts(); I_0= min(aLen,readLength)+readLength-4*anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2*anchorLength+1; ## effective skipping form length for JC I_1= readLength-2*anchorLength+aLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_a5ss[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(lS/chunk, lE/chunk+1) + range(fS/chunk, fE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in a5ss: ## already processed this chromosome for i in group: ## for each possible group if i in a5ss[chr]: ## this group is already there if id in a5ss[chr][i]: ## not likely but this group already has the id numA5SSDup+=1; else: ## new A5SS ID a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; else: ## new group to this chromosome a5ss[chr][i]={}; a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; else: ## first time accesing this chromosome a5ss[chr]={}; for i in group: ## for each possible group a5ss[chr][i]={}; a5ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a5ss event with coords numA5SS+=1; # ### A3SS #### c=0; ## count numA3SS=0; ## number of A3SS numA3SSDup=0; ## duplicate A3SS id line=a3ssFile.readline(); ## skipping header for line in a3ssFile: ## process a3ss events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; lS = int(ele[5]); lE = int(ele[6]); ## long exon coord sS = int(ele[7]); sE = int(ele[8]); ## short exon coord fS = int(ele[9]); fE = int(ele[10]); ## flanking exon coord lLen=min(lE-lS,junctionLength/2); ## long exon length sLen=min(sE-sS,junctionLength/2); ## short exon length fLen=min(fE-fS,junctionLength/2); ## flanking exon length aLen=lE-lS-(sE-sS); ## alternative SS region length id_a3ss[id]=":".join(map(str,[chr,strand,lS,lE,sS,sE,fS,fE])); e_a3ss[id] = [lS,lE,sS,sE,fS,fE]; c_a3ss[id] = getInitialCounts(); I_0= min(aLen,readLength)+readLength-4*anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2*anchorLength+1; ## effective skipping form length for JC I_1= readLength-2*anchorLength+aLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_a3ss[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(lS/chunk, lE/chunk+1) + range(fS/chunk, fE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in a3ss: ## already processed this chromosome for i in group: ## for each possible group if i in a3ss[chr]: ## this group is already there if id in a3ss[chr][i]: ## not likely but this group already has the id numA3SSDup+=1; else: ## new A3SS ID a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; else: ## new group to this chromosome a3ss[chr][i]={}; a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; else: ## first time accesing this chromosome a3ss[chr]={}; for i in group: ## for each possible group a3ss[chr][i]={}; a3ss[chr][i][id] = [lS,lE,sS,sE,fS,fE,strand]; ## a3ss event with coords numA3SS+=1; # #### RI #### c=0; ## count numRI=0; ## number of RI numRIDup=0; ## duplicate RI id line=riFile.readline(); ## skipping header for line in riFile: ## process ri events file c+=1; ele = line.strip().split('\t'); id = int(ele[0]); chr = ele[3]; if chr[0:3]!='chr': ## X instead of chrX, add 'chr' chr = 'chr'+chr; strand = ele[4]; rS = int(ele[5]); rE = int(ele[6]); ## ri exon coord (including up- and down-stream exons) uS = int(ele[7]); uE = int(ele[8]); ## upstream exon coord dS = int(ele[9]); dE = int(ele[10]); ## downstream exon coord uLen=min(uE-uS,junctionLength/2); ## upstream exon length dLen=min(dE-dS,junctionLength/2); ## downstream exon length riLen=rE-rS-(uE-uS)-(dE-dS); ## retained exon length id_ri[id]=":".join(map(str,[chr,strand,rS,rE,uS,uE,dS,dE])); e_ri[id] = [rS,rE,uS,uE,dS,dE]; ## ri event with coord c_ri[id] = getInitialCounts(); I_0= min(riLen,readLength)+readLength-4*anchorLength+2; ## effective inclusion form length for JC S_0= readLength-2*anchorLength+1; ## effective skipping form length for JC I_1= readLength-2*anchorLength+riLen+1; ## effective inclusion form length for JC+reads on target S_1= S_0; ## effective skipping form length for JC+reads on target I_2=0; S_2=0; ## effective length considering paired-end info.. not implemented yet s_ri[id] = [[I_0,S_0],[I_1,S_1],[I_2,S_2]]; ## effective length for CT1,CT2,CT3 group = range(rS/chunk, rE/chunk+1); ## groups this event could belong group = list(set(group)); ## remove duplicate groups if chr in ri: ## already processed this chromosome for i in group: ## for each possible group if i in ri[chr]: ## this group is already there if id in ri[chr][i]: ## not likely but this group already has the id numRIDup+=1; else: ## new RI ID ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; else: ## new group to this chromosome ri[chr][i]={}; ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; else: ## first time accesing this chromosome ri[chr]={}; for i in group: ## for each possible group ri[chr][i]={}; ri[chr][i][id] = [rS,rE,uS,uE,dS,dE,strand]; ## ri event with coord numRI+=1; print("Counting Reads...") #################################### ## Running the counting functions ## #################################### #if dataType=="skipThisForNow": ## call paired.. #logging.debug("Start processing sample_1: %s" % base_1); #processSample_PE(input_file, 72, 60); if libType=='fr-unstranded': ## unstranded.. processSample(input_file); elif libType=='fr-firststrand': ## first strand.. processSample_stranded(input_file,dataType,'first') elif libType=='fr-secondstrand': ## second strand.. processSample_stranded(input_file,dataType,'second') ### print("Writing Output...") ###################################### ## Writing out the rMATS input file ## ###################################### header = 'ID(chr:strand:SE_s:SE_e:UP_s:UP_e:DN_s:DN_e)\tIC_'+base+'\tSC_'+base+'\tIncFormLen\tSkipFormLen'; # ## SE ## writeInputFile2(header,JC_seFile,id_se,c_se,s_se); ## MXE ## writeInputFile2(header,JC_mxeFile,id_mxe,c_mxe,s_mxe); ## A5SS ##... writeInputFile2(header,JC_a5ssFile,id_a5ss,c_a5ss,s_a5ss); ## A3SS ##... writeInputFile2(header,JC_a3ssFile,id_a3ss,c_a3ss,s_a3ss); ## RI ## writeInputFile2(header,JC_riFile,id_ri,c_ri,s_ri); # print("Done!") #### close all files here ########## seFile.close() mxeFile.close() a5ssFile.close() a3ssFile.close() riFile.close() # JC_seFile.close() JC_mxeFile.close() JC_a5ssFile.close() JC_a3ssFile.close() JC_riFile.close() # sys.exit(0); # if __name__ == '__main__': main()

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util.py

asahi417/VAE

9

74889

import logging import os import numpy as np import tensorflow as tf import sys def create_log(name): """Logging.""" if os.path.exists(name): os.remove(name) logger = logging.getLogger(name) logger.setLevel(logging.DEBUG) # handler for logger file handler1 = logging.FileHandler(name) handler1.setFormatter(logging.Formatter("H1, %(asctime)s %(levelname)8s %(message)s")) # handler for standard output handler2 = logging.StreamHandler() handler2.setFormatter(logging.Formatter("H1, %(asctime)s %(levelname)8s %(message)s")) logger.addHandler(handler1) logger.addHandler(handler2) return logger def mnist_loader(): from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets mnist = read_data_sets('MNIST_data', one_hot=True) n_sample = mnist.train.num_examples return mnist, n_sample def shape_2d(_x, batch_size): _x = _x.reshape(batch_size, 28, 28) return np.expand_dims(_x, 3) def mnist_train(model, epoch, save_path="./", mode="supervised", input_image=True): """ Train model based on mini-batch of input data. :param model: :param epoch: :param save_path: :param mode: conditional, supervised, unsupervised :param input_image: True if use CNN for top of the model :return: """ # load mnist data, n = mnist_loader() n_iter = int(n / model.batch_size) # logger if not os.path.exists(save_path): os.mkdir(save_path) logger = create_log(save_path+"log") logger.info("train: data size(%i), batch num(%i), batch size(%i)" % (n, n_iter, model.batch_size)) result = [] # Initializing the tensor flow variables model.sess.run(tf.global_variables_initializer()) for _e in range(epoch): _result = [] for _b in range(n_iter): # train _x, _y = data.train.next_batch(model.batch_size) _x = shape_2d(_x, model.batch_size) if input_image else _x if mode in ["conditional", "unsupervised"]: # conditional unsupervised model feed_val = [model.summary, model.loss, model.re_loss, model.latent_loss, model.train] feed_dict = {model.x: _x, model.y: _y} if mode == "conditional" else {model.x: _x} summary, loss, re_loss, latent_loss, _ = model.sess.run(feed_val, feed_dict=feed_dict) __result = [loss, re_loss, latent_loss] elif mode == "supervised": # supervised model feed_val = [model.summary, model.loss, model.accuracy, model.train] feed_dict = {model.x: _x, model.y: _y, model.is_training: True} summary, loss, acc, _ = model.sess.run(feed_val, feed_dict=feed_dict) __result = [loss, acc] else: sys.exit("unknown mode !") _result.append(__result) model.writer.add_summary(summary, int(_b + _e * model.batch_size)) # validation if mode == "supervised": # supervised model _x = shape_2d(data.test.images, data.test.num_examples) if input_image else data.test.image _y = data.test.labels feed_dict = {model.x: _x, model.y: _y, model.is_training: False} loss, acc = model.sess.run([model.loss, model.accuracy], feed_dict=feed_dict) _result = np.append(np.mean(_result, 0), [loss, acc]) logger.info("epoch %i: acc %0.3f, loss %0.3f, train acc %0.3f, train loss %0.3f" % (_e, acc, loss, _result[1], _result[0])) else: _result = np.mean(_result, 0) logger.info("epoch %i: loss %0.3f, re loss %0.3f, latent loss %0.3f" % (_e, _result[0], _result[1], _result[2])) result.append(_result) if _e % 50 == 0: model.saver.save(model.sess, "%s/progress-%i-model.ckpt" % (save_path, _e)) np.savez("%s/progress-%i-acc.npz" % (save_path, _e), loss=np.array(result), learning_rate=model.learning_rate, epoch=epoch, batch_size=model.batch_size, clip=model.max_grad_norm) model.saver.save(model.sess, "%s/model.ckpt" % save_path) np.savez("%s/acc.npz" % save_path, loss=np.array(result), learning_rate=model.learning_rate, epoch=epoch, batch_size=model.batch_size, clip=model.max_grad_norm)

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data/pandas.py

sean-liang/crypto-quant-toolkit

0

1600481

<gh_stars>0 def with_dataframe(df, method, **kwargs): """ 包装pandas的dataframe方法为pipeline形式 """ func = getattr(df, method) new_df = func(**kwargs) return df if new_df is None or ('inplace' in kwargs and kwargs['inplace']) else new_df

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lib/googlecloudsdk/command_lib/compute/os_config/declarative.py

google-cloud-sdk-unofficial/google-cloud-sdk

2

187558

<filename>lib/googlecloudsdk/command_lib/compute/os_config/declarative.py # -*- coding: utf-8 -*- # # Copyright 2021 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Hooks for declarative commands.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals def SetDefaultPageSizeRequestHook(default_page_size): """Create a modify_request_hook that applies default_page_size to args. Args: default_page_size: The page size to use when not specified by the user. Returns: A modify_request_hook that updates `args.page_size` when not set by user. """ def Hook(unused_ref, args, request): if not args.page_size: args.page_size = int(default_page_size) return request return Hook

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augment.py

MohamedHeshamMustafa/Brain-Tumor-Automatic-Detection-and-Segmentation-

0

121498

from __future__ import absolute_import, print_function import numpy as np import sys import tensorflow as tf from util.data_loader import * from util.data_aug import * from util.parse_config import parse_config def test(config_file): # 1, load configure file config = parse_config(config_file) config_data = config['data'] # 2, Augmentation dataaug = DataAug(config_data) dataaug.aug_data() if __name__ == '__main__': if(len(sys.argv) != 2): print('Number of arguments should be 2. e.g.') print(' python test.py config17/test_all_class.txt') exit() config_file = str(sys.argv[1]) assert(os.path.isfile(config_file)) test(config_file)

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cio/plugins/txt.py

beshrkayali/content-io

6

4298

<reponame>beshrkayali/content-io # coding=utf-8 from __future__ import unicode_literals from .base import BasePlugin class TextPlugin(BasePlugin): ext = 'txt'

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HMQ/datasets/auto_augmentation_transform.py

UniSerj/ai-research

46

167742

import random from PIL import ImageOps, ImageEnhance, ImageFilter, Image import torchvision.transforms as transforms PARAMETER_MAX = 10 # What is the max 'level' a transform could be predicted def int_parameter(level, maxval) -> int: """ A function to scale between zero to max val with casting to int :param level: The level of augmentation an integer between 0 to 9 :param maxval: The maximal output value :return: A int value """ return int(level * maxval / PARAMETER_MAX) def float_parameter(level, maxval): """ A function to scale between zero to max val :param level: The level of augmentation an integer between 0 to 9 :param maxval: The maximal output value :return: A int value """ return float(level) * maxval / PARAMETER_MAX class BaseAugmentation(object): def __init__(self, p, level): """ Base Augmentation class which performed data augmentation with probability p and severity level :param p: The probability that the augmentation is performed :param level: The severity of data augmentation """ self.p = p self.level = level def __call__(self, img): if random.random() < self.p: img = self._augment(img) return img def _augment(self, img): raise NotImplemented def __repr__(self): return self.__class__.__name__ + '(p={}, level={})'.format(self.p, self.level) class AutoContrast(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform auto contrast. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.autocontrast(img) class Equalize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Equalization. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.equalize(img) class Invert(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Invert. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return ImageOps.invert(img) class Blur(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Image Blur. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return img.filter(ImageFilter.BLUR) class Smooth(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Smoothing. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ return img.filter(ImageFilter.SMOOTH) class Rotate(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform rotation. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ degrees = int_parameter(self.level, 30) if random.random() > 0.5: degrees = -degrees return img.rotate(degrees) class Posterize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Posterize. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 4) return ImageOps.posterize(img, 4 - level) class ShearX(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform ShearX. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = float_parameter(self.level, 0.3) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, level, 0, 0, 1, 0)) class ShearY(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform ShearY. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = float_parameter(self.level, 0.3) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, 0, level, 1, 0)) class TranslateX(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform TranslateX. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 10) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, level, 0, 1, 0)) class TranslateY(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform TranslateY. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 10) if random.random() > 0.5: level = -level return img.transform((32, 32), Image.AFFINE, (1, 0, 0, 0, 1, level)) class Solarize(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Solarize. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ level = int_parameter(self.level, 256) return ImageOps.solarize(img, 256 - level) class Color(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Color. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Color(img).enhance(v) class Contrast(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Contrast change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Contrast(img).enhance(v) class Brightness(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Brightness change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Brightness(img).enhance(v) class Sharpness(BaseAugmentation): def _augment(self, img): """ Data augmentation function that perform Sharpness change. :param img: PIL Image to be augmented. :return: PIL Image after augmentation """ v = float_parameter(self.level, 1.8) + .1 # going to 0 just destroys it return ImageEnhance.Sharpness(img).enhance(v) CIFAR10_AUGMENT_POLICY = transforms.RandomChoice([transforms.Compose([Invert(0.1, 7), Contrast(0.2, 6)]), transforms.Compose([Rotate(0.7, 2), TranslateX(0.3, 9)]), transforms.Compose([Sharpness(0.8, 1), Sharpness(0.9, 3)]), transforms.Compose([ShearY(0.5, 8), TranslateY(0.7, 9)]), transforms.Compose([AutoContrast(0.5, 8), Equalize(0.9, 2)]), transforms.Compose([ShearY(0.2, 7), Posterize(0.3, 7)]), transforms.Compose([Color(0.4, 3), Brightness(0.6, 7)]), transforms.Compose([Sharpness(0.3, 9), Brightness(0.7, 9)]), transforms.Compose([Equalize(0.6, 5), Equalize(0.5, 1)]), transforms.Compose([Contrast(0.6, 7), Sharpness(0.6, 5)]), transforms.Compose([Color(0.7, 7), TranslateY(0.5, 8)]), transforms.Compose([Equalize(0.3, 7), AutoContrast(0.4, 8)]), transforms.Compose([TranslateY(0.4, 3), Sharpness(0.2, 6)]), transforms.Compose([Brightness(0.9, 6), Color(0.2, 8)]), transforms.Compose([Solarize(0.5, 2), Invert(0.0, 3)]), transforms.Compose([Equalize(0.2, 0), AutoContrast(0.6, 0)]), transforms.Compose([Equalize(0.2, 8), Equalize(0.6, 4)]), transforms.Compose([Color(0.9, 9), Equalize(0.6, 6)]), transforms.Compose([AutoContrast(0.8, 4), Solarize(0.2, 8)]), transforms.Compose([Brightness(0.1, 3), Color(0.7, 0)]), transforms.Compose([Solarize(0.4, 5), AutoContrast(0.9, 3)]), transforms.Compose([TranslateY(0.9, 9), TranslateY(0.7, 9)]), transforms.Compose([AutoContrast(0.9, 2), Solarize(0.8, 3)]), transforms.Compose([Equalize(0.8, 8), Invert(0.1, 3)]), transforms.Compose([TranslateY(0.7, 9), AutoContrast(0.9, 1)])]) IMAGENET_AUGMENT_POLICY = transforms.RandomChoice([transforms.Compose([Posterize(0.4, 8), Rotate(0.6, 9)]), transforms.Compose([Solarize(0.6, 5), AutoContrast(0.6, 5)]), transforms.Compose([Equalize(0.8, 18), Equalize(0.6, 3)]), transforms.Compose([Posterize(0.6, 7), Posterize(0.6, 6)]), transforms.Compose([Equalize(0.4, 7), Solarize(0.2, 4)]), transforms.Compose([Equalize(0.4, 4), Rotate(0.8, 8)]), transforms.Compose([Solarize(0.6, 3), Equalize(0.6, 7)]), transforms.Compose([Posterize(0.8, 5), Equalize(1.0, 2)]), transforms.Compose([Rotate(0.2, 3), Solarize(0.6, 8)]), transforms.Compose([Equalize(0.6, 8), Posterize(0.4, 6)]), transforms.Compose([Rotate(0.8, 8), Color(0.4, 0)]), transforms.Compose([Rotate(0.4, 9), Equalize(0.6, 2)]), transforms.Compose([Equalize(0.0, 7), Equalize(0.8, 8)]), transforms.Compose([Invert(0.6, 4), Equalize(1.0, 8)]), transforms.Compose([Color(0.6, 4), Color(1.0, 8)]), transforms.Compose([Rotate(0.8, 8), Color(1.0, 2)]), transforms.Compose([Color(0.8, 8), Solarize(0.8, 7)]), transforms.Compose([Sharpness(0.4, 7), Invert(0.6, 8)]), transforms.Compose([ShearX(0.6, 5), Equalize(1.0, 9)]), transforms.Compose([Color(0.4, 0), Equalize(0.6, 3)]), transforms.Compose([Equalize(0.4, 7), Solarize(0.2, 4)]), transforms.Compose([Solarize(0.6, 5), AutoContrast(0.6, 5)]), transforms.Compose([Invert(0.6, 4), Equalize(1.0, 8)]), transforms.Compose([Color(0.6, 4), Contrast(1.0, 8)]), transforms.Compose([Equalize(0.8, 8), Equalize(0.6, 3)])])

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backend/course/views.py

thangplum/nova-cs322

0

116790

<filename>backend/course/views.py from rest_framework import viewsets, status from rest_framework.response import Response from django.shortcuts import get_object_or_404 from .serializers import courseSerializer, courseSerializer2 from .models import course class CourseViewSet(viewsets.ViewSet): def list(self, request): courses = course.objects.all() serializer = courseSerializer2(courses, many=True) return Response(serializer.data) def retrieve(self, request, pk=None): queryset = course.objects.all() form = get_object_or_404(queryset, pk=pk) serializer = courseSerializer(form) if ((request.user.is_instructor and form.user == request.user) or request.user.is_researcher) : return Response(serializer.data) return Response(status=status.HTTP_403_FORBIDDEN) def create(self, request): serializer = courseSerializer(data=request.data) if serializer.is_valid() and request.user.is_instructor: serializer.validated_data["user"] = request.user serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(status=status.HTTP_403_FORBIDDEN) def destroy(self, request, pk=None): instance = course.objects.get(pk=pk) if request.user.is_instructor and instance.user == request.user: instance.delete() return Response(status=status.HTTP_200_OK) return Response(status=status.HTTP_401_UNAUTHORIZED) def partial_update(self, request, pk=None): queryset = course.objects.all() form = get_object_or_404(queryset, pk=pk) serializer = courseSerializer(form, data=request.data, partial=True) if serializer.is_valid() and ((request.user.is_instructor and form.user == request.user) or request.user.is_researcher) : serializer.validated_data["user"] = request.user serializer.save() return Response(serializer.data, status=status.HTTP_200_OK) return Response(status=status.HTTP_401_UNAUTHORIZED)

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wxPython/wxGlade-0.9.1/tests/testsupport_new.py

DarkShadow4/python

0

44240

""" @copyright: 2012-2016 <NAME> (as file __init__.py) @copyright: 2016-2018 <NAME> @license: MIT (see LICENSE.txt) - THIS PROGRAM COMES WITH NO WARRANTY """ import os, sys sys.path.insert(1, os.path.dirname(sys.path[0])) import errno, fnmatch, glob, shutil, re import unittest, difflib, logging, imp import gettext t = gettext.translation(domain="wxglade", localedir="locale", fallback=True) t.install("wxglade") import common common.init_paths(None) import config config.testing = True import wxglade, codegen, compat, log if compat.PYTHON2: from StringIO import StringIO else: from io import StringIO class WXGladeBaseTest(unittest.TestCase): "Provide basic functions for all tests" longMessage = True caseDirectory = 'casefiles' # Directory with input files and (expected) result files outDirectory = 'generated' # Directory with generated result files # Language specific constants for file names: language, file prefix, file extensions language_constants = [("python","Py", ".py", ".py"),("perl","Pl", ".pl", ".pm"), ("C++","CPP", ".cpp", ".cpp"),("lisp","Lisp", ".lisp",".lisp"), ("XRC","xrc", ".xrc",".xrc")] @classmethod def setUpClass(cls): "Initialise parts of wxGlade before individual tests starts" # set icon path back to the default default #config.icons_path = 'icons' # initialise wxGlade preferences and set some useful values common.init_preferences() config.preferences.autosave = False config.preferences.write_timestamp = False config.preferences.show_progress = False config.version = '"faked test version"' # make e.g. the preview raise Exceptions config.testing = True # Determinate case and output directory cls.caseDirectory = os.path.join( os.path.dirname(__file__), cls.caseDirectory ) cls.outDirectory = os.path.join( os.path.dirname(__file__), cls.outDirectory ) if not os.path.exists(cls.outDirectory): os.mkdir(cls.outDirectory) # disable bug dialogs sys._called_from_test = True @classmethod def tearDownClass(cls): "Cleanup after all individual tests are done" # de-register own logging log.deinit() def setUp(self): "Initialise" codegen.BaseLangCodeWriter._show_warnings = False def tearDown(self): "Cleanup" pass def _read_file_lines(self, filename): "read a file, split into lines and drop 'generated by ...'" with open(filename, "rb") as f: ret = f.read() ret = ret.split( b"\r\n" if b"\r\n" in ret else b"\n" ) # drop empty lines and 'generated by...' while ret and not ret[-1]: del ret[-1] for i, line in enumerate(ret[:10]): if b'generated by wxGlade' in line: del ret[i] break return ret def _compare_files(self, expected_filename, generated_filename, check_mtime=False): self.assertTrue( os.path.isfile(generated_filename), "File %s was not generated"%generated_filename ) if check_mtime: self.assertGreater( os.stat(generated_filename).st_mtime, os.stat(expected_filename).st_mtime, "File was not overwritten" ) # open files, split into lines and convert to str/unicode expected = self._read_file_lines(expected_filename) generated = self._read_file_lines(generated_filename) if expected == generated: return False expected = [s.decode('ascii', 'replace') for s in expected] generated = [s.decode('ascii', 'replace') for s in generated] if wx.Platform == '__WXGTK__': # on gtk, the frames get resized after creation if len(expected)==len(generated): expected_ = [l for l in expected if not l.strip().startswith("<size>") and not "SetSize" in l] generated_ = [l for l in generated if not l.strip().startswith("<size>") and not "SetSize" in l] if expected_ == generated_: return False diff = difflib.unified_diff(expected, generated, fromfile=expected_filename, tofile=generated_filename, lineterm='') diff = list(diff) print( '\n'.join(diff[:40]) ) if len(diff)>40: print("...") #if compat.PYTHON3: self.assertFalse( diff, "Generated file and expected result differs:\n%s" % "\n".join(diff) ) return True def _get_inputfile_path(self, filename): "return the absolute path of a .wxg input file" basename, extension = os.path.splitext(filename) fn = os.path.join(self.caseDirectory, filename) if os.path.exists(fn): return fn return None def _get_casefile_path(self, filename): "return the absolute path of an input file or directory; for .py files, this might include _Phoenix/_Classic" basename, extension = os.path.splitext(filename) if extension.lower() == ".py": # search for version specific files if compat.IS_CLASSIC: fn = "%s_Classic%s"%(basename, extension) elif compat.IS_PHOENIX: fn = "%s_Phoenix%s"%(basename, extension) fn = os.path.join(self.caseDirectory, fn) if os.path.exists(fn): return fn # this could be a directory as well if extension.lower() == ".wxg": # search for "_Saved" version fn = "%s_Saved%s"%(basename, extension) fn = os.path.join(self.caseDirectory, fn) if os.path.exists(fn): return fn # this could be a directory as well fn = os.path.join(self.caseDirectory, filename) if os.path.exists(fn): return fn return None def _get_outputfile_path(self, filename): """return the name for an output file filename can be - a full path, where only the part relative to caseDirectory will be used - an absolute path, where only the leafname will be used - a relative path""" commonpath = os.path.commonprefix( (self.caseDirectory, filename) ) if commonpath==self.caseDirectory: leaf = filename[len(commonpath)+1:] elif os.path.isabs(filename): leaf = os.path.basename(filename) else: leaf = filename return os.path.join(self.outDirectory, leaf) class WXGladeCLITest(WXGladeBaseTest): @classmethod def setUpClass(cls): logging.disable(logging.WARNING) wxglade.init_stage1() wxglade.init_localization() wxglade.init_stage2(False) import xrc2wxg import wx import config, common, compat, main class WXGladeGUITest(WXGladeBaseTest): # as Python created an own instance for each test, we use class variables for persistent storing 'app' and 'frame': app = None # Reference to a wx.App object. The object is persistent after the creation in setUp(). frame = None # Reference to main.wxGladeFrame. The object is persistent after the creation in setUp(). nolog = None # nolog: wxWidgets Null logger to suppress error messages orig_stdout = None # original fd for stdout def mockMessageBox(self, message, caption, *args, **kwargs): "Mock object for wx.MessageBox" self._messageBox = [message, caption] def _assert_message(self, substring, caption ): self.assertTrue( self._messageBox, "No %s message generated"%caption ) generated_message, generated_caption = self._messageBox self.assertTrue( generated_caption==caption, "Expected %s message, got %s"%(caption, generated_caption) ) fmt='%s message does not match: Expected message containing "%s" \ngot wxMessageBox(message="%s", caption="%s")' msg = fmt%(caption, substring, self._messageBox[0], self._messageBox[1] ) self.assertTrue( substring in generated_message, msg ) self._messageBox = None def _assert_error_message(self, substring ): self._assert_message(substring, u"Error") def _assert_warning_message(self, substring ): self._assert_message(substring, u"Warning") def _assert_info_message(self, substring ): self._assert_message(substring, u"Information") @classmethod def setUpClass(cls): WXGladeBaseTest.setUpClass() xrc2wxg._write_timestamp = False # create an simply application cls.app = wx.App() cls.locale = wx.Locale(wx.LANGUAGE_DEFAULT) compat.wx_ArtProviderPush(main.wxGladeArtProvider()) cls.frame = main.wxGladeFrame() # suppress wx error messages cls.nolog = wx.LogNull() #cls.app.SetAssertMode(0) # avoid triggering of wx assertions; sometimes needed for debugging # hide all windows #cls.frame.Hide() #cls.frame.hide_all() @classmethod def tearDownClass(cls): cls.nolog = None def setUp(self): # redirect stdout self.orig_stdout = sys.stdout sys.stdout = StringIO() # initialise base class WXGladeBaseTest.setUp(self) # inject mock object for wxMessageBox wx.MessageBox = self.mockMessageBox self._messageBox = [] # show dialog "Code generation completed successfully" config.preferences.show_completion = True def tearDown(self): # restore original stdout if self.orig_stdout: sys.stdout = self.orig_stdout # initialise base class WXGladeBaseTest.tearDown(self) def _process_wx_events(self): "Process wx events, because we don't start the main loop" for i in range(3): wx.SafeYield() self.app.ProcessPendingEvents() def load_and_generate(self, basename, excluded=None, included=None, test_GUI=True, preview=True): "Load a wxGlade document 'basename' and generate code for all languages except the ones in list 'excluded'" if included is None: languages = set( [l[0] for l in self.language_constants] + ["wxg"] ) else: languages = set(included) if excluded is not None: languages -= set(excluded) # open file infilename = self._get_inputfile_path('%s.wxg' % basename) common.main._open_app(infilename, use_progress_dialog=False, add_to_history=False) # some shortcuts tree = common.app_tree app = tree.app if test_GUI or preview: # expand tree and show edit window first_window_node = app.node.children[0] first_window = first_window_node.widget first_window_item = first_window_node.item if test_GUI: if first_window_item.IsOk(): tree.expand() self._process_wx_events() tree.SelectItem(first_window_item) self._process_wx_events() tree.show_toplevel(first_window_node) self._process_wx_events() if preview: first_window.properties["preview"]() self._process_wx_events() if compat.PYTHON2: # the languages that failed due to differences to expected files diff_fails = [] else: # with Python 3, we use subTests subtest = 0 if "wxg" in languages: # save file again and check generated_filename = self._get_outputfile_path(infilename) compare_filename = self._get_casefile_path(infilename) # some properties may have changed on loading common.main._save_app(generated_filename) if compat.PYTHON2: if self._compare_files(compare_filename, generated_filename): diff_fails.append("wxg") else: with self.subTest(subtest): self._compare_files(compare_filename, generated_filename) subtest += 1 # try to generate code with empty output path -> will fail app.properties["output_path"].set("") app.generate_code() # first test should fail because no output file is given self._assert_error_message( u'You must specify an output file' ) # now test full code generation for language, dummy, ext, dummy in self.language_constants: if not language in languages: continue if language=="C++" and app.multiple_files: app_basename = os.path.splitext(config.default_cpp_app_name)[0] app_basename = "%s_%s"%(first_window.klass.split("_")[0], app_basename) app.app_filename = app_basename expected_filename = self._get_casefile_path( "%s.%s"%(app_basename, app.source_extension) ) # first_window.klass # 'Bug179_Frame' else: expected_filename = self._get_casefile_path( '%s%s' % (basename, ext) ) if not expected_filename: continue generated_filename = self._get_outputfile_path(expected_filename) # check for language first self.assertTrue( language in common.code_writers, "No codewriter loaded for %s" % language ) # set absolute "Output path", language and generate code if language=="C++" and app.multiple_files: app.properties["output_path"].set( os.path.dirname(generated_filename) ) else: app.properties["output_path"].set(generated_filename) app.properties["language"].set(language) self._process_wx_events() app.generate_code() self._assert_info_message(u'Code generation completed successfully') compare_files = [(expected_filename, generated_filename)] if language == 'C++': if not app.multiple_files: # compare header file as well expected_filename_h = '%s.%s' % ( os.path.splitext(expected_filename )[0], app.header_extension ) generated_filename_h = '%s.%s' % ( os.path.splitext(generated_filename)[0], app.header_extension ) compare_files.append( (expected_filename, generated_filename) ) compare_files.append( (expected_filename_h, generated_filename_h) ) else: for toplevel in app.node.children: classname = toplevel.widget.klass # class C++ file expected_filename = self._get_casefile_path( "%s.%s"%(classname, app.source_extension) ) if expected_filename: compare_files.append( (expected_filename, self._get_outputfile_path(expected_filename) ) ) # class header file expected_filename = self._get_casefile_path( "%s.%s"%(classname, app.header_extension) ) if expected_filename: compare_files.append( (expected_filename, self._get_outputfile_path(expected_filename) ) ) for expected_filename, generated_filename in compare_files: if compat.PYTHON2: # no subtests if self._compare_files(expected_filename, generated_filename): diff_fails.append(language) else: with self.subTest(subtest): self._compare_files(expected_filename, generated_filename) subtest += 1 if compat.PYTHON2: self.assertFalse(diff_fails, "Expected and generated files do not match for %s"%",".join(diff_fails)) def _copy_and_modify(self, source, target, original=None, replacement=None): if original is None: shutil.copy2( source, target ) return with open(source,"rb") as infile: content = infile.read().replace(original, replacement) with open(target, "wb") as outfile: outfile.write(content) shutil.copystat( source, target )

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src/tools/rut5_finetuning.py

JetBrains-Research/relevant-tasks-search

1

168760

<filename>src/tools/rut5_finetuning.py<gh_stars>1-10 import os from argparse import ArgumentParser import numpy as np import pandas as pd from transformers import ( AutoTokenizer, AutoModelForSeq2SeqLM, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer, ) from datasets import DatasetDict, load_metric import nltk def read_data(input_path: str, load_courses=False): """ Used for reading data from input path and returning pd.DataFrames :param input_path: path to dir with train/test/val .csv files :param load_courses: if True, loading data about courses and sections too :return: """ if not isinstance(input_path, str): raise Exception(f"You passed {type(input_path)} instead of str type") if not os.path.exists(input_path): raise FileNotFoundError(f"{input_path} doesn't exist") data_train = pd.read_csv(os.path.join(input_path, "train.csv")) data_val = pd.read_csv(os.path.join(input_path, "val.csv")) data_test = pd.read_csv(os.path.join(input_path, "test.csv")) data_train = data_train.dropna().reset_index(drop=True) data_val = data_val.dropna().reset_index(drop=True) data_test = data_test.dropna().reset_index(drop=True) if load_courses: data_courses = pd.read_csv(os.path.join(input_path, "popular_courses.csv")) data_sections = pd.read_csv(os.path.join(input_path, "popular_courses_sections.csv")) return data_train, data_val, data_test, data_courses, data_sections else: return data_train, data_val, data_test def create_dataset(input_path: str, output_path: str): """ Used for dataset's creation. You should provide input path with train/test/val .csv files and sections & courses data :param input_path: path to load train/test/val .csv files and sections & courses data :param output_path: path to save datasets :return: """ if not os.path.isdir(output_path): os.mkdir(output_path) data_train, data_val, data_test, data_courses, data_sections = read_data(input_path, load_courses=True) dataset_train = pd.DataFrame({"text": data_train.preprocessed_text, "id": data_train.id}) dataset_test = pd.DataFrame({"text": data_test.preprocessed_text, "id": data_test.id}) dataset_val = pd.DataFrame({"text": data_val.preprocessed_text, "id": data_val.id}) course2title = {} for index in data_courses.index: course2title[data_courses.at[index, "id"]] = data_courses.at[index, "title"] section2title = {} for index in data_sections.index: section2title[data_sections.at[index, "id"]] = data_sections.at[index, "title"] # Adding key word "summarize" which T5 is needed dataset_train.text = "summarize: " + dataset_train.text + " </s>" dataset_test.text = "summarize: " + dataset_test.text + " </s>" dataset_val.text = "summarize: " + dataset_val.text + " </s>" # Adding some king of summary - section_name + delimiter + course_name dataset_train["summary"] = "" dataset_test["summary"] = "" dataset_val["summary"] = "" for index in data_train.index: course_id = data_train.at[index, "course_id"] section_id = data_train.at[index, "section_id"] dataset_train.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] for index in data_test.index: course_id = data_test.at[index, "course_id"] section_id = data_test.at[index, "section_id"] dataset_test.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] for index in data_val.index: course_id = data_val.at[index, "course_id"] section_id = data_val.at[index, "section_id"] dataset_val.at[index, "summary"] = section2title[section_id] + " в курсе " + course2title[course_id] # Saving datasets to the output dir dataset_train.to_csv(os.path.join(output_path, "dataset_train.csv"), index=False, header=True) dataset_test.to_csv(os.path.join(output_path, "dataset_test.csv"), index=False, header=True) dataset_val.to_csv(os.path.join(output_path, "dataset_val.csv"), index=False, header=True) def preprocess_function(examples, tokenizer, max_length=512): """ This function is used to tokenized text in datasets Adopt by me almost without changes from https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb :param examples: dataset :param tokenizer: tokenizer to use :param max_length: max length of sequence in tokens :return: """ inputs = [doc for doc in examples["text"]] model_inputs = tokenizer(inputs, max_length=max_length, truncation=True, padding="max_length") # Setup the tokenizer for targets with tokenizer.as_target_tokenizer(): labels = tokenizer(examples["summary"], max_length=max_length, truncation=True, padding="max_length") model_inputs["labels"] = labels["input_ids"] return model_inputs def compute_metrics(eval_pred, tokenizer, metric): """ This function is used to compute ROUGE metric. Adopt by me almost without changes from https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb :param eval_pred: :param tokenizer: :param metric: :return: """ predictions, labels = eval_pred decoded_preds = tokenizer.batch_decode(predictions, skip_special_tokens=True) # Replace -100 in the labels as we can't decode them. labels = np.where(labels != -100, labels, tokenizer.pad_token_id) decoded_labels = tokenizer.batch_decode(labels, skip_special_tokens=True) # Rouge expects a newline after each sentence decoded_preds = ["\n".join(nltk.sent_tokenize(pred.strip())) for pred in decoded_preds] decoded_labels = ["\n".join(nltk.sent_tokenize(label.strip())) for label in decoded_labels] result = metric.compute(predictions=decoded_preds, references=decoded_labels, use_stemmer=True) # Extract a few results result = {key: value.mid.fmeasure * 100 for key, value in result.items()} # Add mean generated length prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in predictions] result["gen_len"] = np.mean(prediction_lens) return {k: round(v, 4) for k, v in result.items()} def train( input_path: str, output_path: str, metric_name: str = "rouge", model_checkpoint: str = "cointegrated/rut5-small" ): """ Used for training. You should provide input path with already computed datasets :param input_path: path to directory with datasets :param output_path: where to save trained model :param metric_name: metric to compute while training :param model_checkpoint: checkpoint to start finetuning :return: """ if not os.path.exists(input_path): raise FileNotFoundError(f"{input_path} doesn't exist") if not os.path.isdir(output_path): os.mkdir(output_path) raw_datasets = DatasetDict.from_csv( { "train": os.path.join(input_path, "dataset_train.csv"), "test": os.path.join(input_path, "dataset_test.csv"), "validation": os.path.join(input_path, "dataset_val.csv"), } ) metric = load_metric(metric_name) tokenizer = AutoTokenizer.from_pretrained(model_checkpoint) model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint) tokenized_datasets = raw_datasets.map(lambda x: preprocess_function(x, tokenizer), batched=True) batch_size = 4 args = Seq2SeqTrainingArguments( os.path.join(output_path, "rut5_finetuned"), evaluation_strategy="steps", eval_steps=200, learning_rate=2e-5, per_device_train_batch_size=batch_size, per_device_eval_batch_size=batch_size, weight_decay=1e-5, save_total_limit=1, save_strategy="steps", save_steps=1000, num_train_epochs=2, predict_with_generate=True, logging_steps=200, logging_first_step=True, logging_dir=os.path.join(output_path, "logs"), push_to_hub=False, ) try: nltk.data.find("tokenizers/punkt") except LookupError: nltk.download("punkt") data_collator = DataCollatorForSeq2Seq(tokenizer, model=model) trainer = Seq2SeqTrainer( model, args, train_dataset=tokenized_datasets["train"], eval_dataset=tokenized_datasets["test"], data_collator=data_collator, tokenizer=tokenizer, compute_metrics=lambda x: compute_metrics(x, tokenizer, metric), ) trainer.train() model.save_pretrained(os.path.join(output_path, "rut5_finetuned")) def configure_arg_parser() -> ArgumentParser: arg_parser = ArgumentParser() arg_parser.add_argument("-t", "--task", choices=["create_dataset", "train"], required=True) arg_parser.add_argument("-o", "--output", required=True, help="Path to output directory") arg_parser.add_argument("-i", "--input", required=True, help="Path to input directory") return arg_parser if __name__ == "__main__": __arg_parser = configure_arg_parser() __args = __arg_parser.parse_args() if __args.task == "create_dataset": create_dataset(__args.input, __args.output) elif __args.task == "train": train(__args.input, __args.output)

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Two pointers/26. Remove Duplicates from Sorted Array.py

ParisMineur/LeetCode-note

0

40410

class Solution: def removeDuplicates(self, nums: List[int]) -> int: l = len(nums) if l == 1: return 1 index = 1 num = nums[0] for i in range(1, l): if nums[i] == num: continue num = nums[i] nums[index] = nums[i] index += 1 return index

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Lesson2_Functions/8-return.py

StyvenSoft/degree-python

0

30229

<filename>Lesson2_Functions/8-return.py def divide_by_four(input_number): return input_number/4 result = divide_by_four(16) # result now holds 4 print("16 divided by 4 is " + str(result) + "!") result2 = divide_by_four(result) print(str(result) + " divided by 4 is " + str(result2) + "!") def calculate_age(current_year, birth_year): age = current_year - birth_year return age my_age = calculate_age(2049, 1993) dads_age = calculate_age(2049, 1953) print("I am "+str(my_age)+" years old and my dad is "+str(dads_age)+" years old")

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bauble/routes/auth.py

Bauble/bauble.api

0

120367

<reponame>Bauble/bauble.api<filename>bauble/routes/auth.py """ All routes in Bauble use HTTP basic auth. """ from datetime import datetime, timedelta import os import smtplib import bottle from bottle import request import sqlalchemy as sa import bauble import bauble.config as config import bauble.db as db import bauble.email as email from bauble import app, API_ROOT from bauble.middleware import basic_auth from bauble.model import User from bauble.utils import create_unique_token def create_access_token(): return create_unique_token(), datetime.now() + timedelta(weeks=2) def create_password_reset_token(): return create_unique_token(), datetime.now() + timedelta(days=1) @app.get(API_ROOT + "/login") def login(): auth = request.auth if not auth: bottle.abort(401, "No Authorization header.") username, password = auth session = db.Session() try: user = session.query(User).filter(sa.func.lower(User.email) == username.lower()).first() if not user or not user.password == password: bottle.abort(401) # not authorized user.access_token, user.access_token_expiration = create_access_token() user.last_accessed = datetime.now() session.commit() user_json = user.json() finally: session.close() return user_json @app.get(API_ROOT + "/logout") @basic_auth def logout(): request.user.access_token = None request.user.access_token_expiration = None request.session.commit() @app.post(API_ROOT + "/forgot-password") def forgot_password(): user_email = request.params.get('email', None) if not user_email and not user_email.contains('@'): bottle.abort("Valid email address required") session = None try: session = db.Session() user = session.query(User)\ .filter(sa.func.lower(User.email) == user_email.lower())\ .first() if not user: bottle.abort(422, "Could not get a user with the requested email address") token, expiration = create_password_reset_token() user.password_reset_token = token user.password_reset_token_expiration = expiration session.commit() finally: if session: session.close() app_url = config.get("BAUBLE_APP_URL") mappings = {'token': token, 'email': user_email, 'app_url': app_url} try: email.send_template('reset_password.txt', mappings, **{ 'to': user_email, 'from': '<EMAIL>', 'subject': 'Bauble Password Reset'}) except smtplib.SMTPException as exc: print(exc) bottle.abort(500, 'Could not send reset password email.') @app.post(API_ROOT + "/reset-password") def reset_password(): session = None user_email = request.json['email'] try: session = db.Session() user = session.query(User).filter(sa.func.lower(User.email) == user_email.lower()).first() if user is None: print('use is None') # TODO: is this the correct status code? bottle.abort(422, 'A user could be be found with the provided email') if request.json['token'] != user.password_reset_token or \ (request.json['token'] == user.password_reset_token and user.password_reset_token_expiration < datetime.now()): # TODO: is this the correct status code? bottle.abort(422, 'Invalid password reset token') # TODO: need to set the expiration user.password_reset_token = None user.password_reset_token_expiration = None user.password = request.json['password'] user.access_token, user.access_token_expiration = create_access_token() user.last_accesseed = datetime.now() session.commit() user_json = user.json() # except Exception as exc: # print('type(exc): ', type(exc)) # print(exc) # bottle.abort(400, "Could not get a user with the requested email address") finally: if session: session.close() return user_json

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bin/make_expmap.py

sjtuzyk/chandra-acis-analysis

3

110917

<filename>bin/make_expmap.py<gh_stars>1-10 #!/usr/bin/env python3 # # Copyright (c) 2017 <NAME> <<EMAIL>> # MIT license """ Create the spectral-weighted exposure map, which will be used to produce the exposure-corrected images and to extract the surface brightness profiles. NOTE ---- We do not use the CIAO tool ``fluximage`` to create the exposure map, because it requires an event file (other than an image) as input file. However, we want to create the exposure map directly based on the (previously created) image file. (But an event file is required to create the aspect histograms for each chip.) NOTE/CAVEAT ----------- To compute an image which gives the integrated flux over the full energy range, it may be best to first compute flux-corrected images in several narrow energy bands (where the ARF is nearly flat) and then sum those fluxed images together. Weighted exposure maps work well for an energy band where the ARF variation isn't very large, but for a full-band 0.5-10 keV image, it may not be a good idea to compute the flux by dividing the counts image by a single number. This is especially true for cases where the source spectrum varies significantly within the image; in that case, there is no general way to compute a single set of weights which will be sensible for every part of the image. References ---------- * <NAME>: An Introduction to Exposure Map http://cxc.harvard.edu/ciao/download/doc/expmap_intro.ps * CIAO: Single Chip ACIS Exposure Map and Exposure-corrected Image http://cxc.harvard.edu/ciao/threads/expmap_acis_single/ * CIAO: Multiple Chip ACIS Exposure Map and Exposure-corrected Image http://cxc.harvard.edu/ciao/threads/expmap_acis_multi/ * CIAO: Calculating Spectral Weights for mkinstmap http://cxc.harvard.edu/ciao/threads/spectral_weights/ """ import os import argparse import subprocess import logging from _context import acispy from acispy.manifest import get_manifest from acispy.ciao import setup_pfiles from acispy.acis import ACIS from acispy.header import write_keyword, copy_keyword from acispy.image import get_xygrid logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) def make_aspect_histogram(outfile, asol, evtfile, chip, clobber=False): """ Create the aspect histogram for each chip, detailing the aspect history of the observation. """ clobber = "yes" if clobber else "no" logger.info("Make aspect histogram for chip: %s" % chip) subprocess.check_call(["punlearn", "asphist"]) subprocess.check_call([ "asphist", "infile=%s" % asol, "outfile=%s" % outfile, "evtfile=%s[ccd_id=%s]" % (evtfile, chip), "clobber=%s" % clobber ]) def make_instrument_map(outfile, spectrumfile, chip, obsfile, maskfile, badpixfile, clobber=False): """ Make the spectral-weighted instrument map (effective area vs. detector position). NOTE ---- The ``obsfile`` should be a FITS file containing keywords which specify the mission, detector, SIM offsets, observation date, etc. This should be an event file; can also be a binned image file (tested OK). """ logger.info("Set bad pixel file: %s" % badpixfile) subprocess.check_call(["punlearn", "ardlib"]) subprocess.check_call(["punlearn", "acis_set_ardlib"]) subprocess.check_call([ "acis_set_ardlib", "badpixfile=%s" % badpixfile, "verbose=0" ]) clobber = "yes" if clobber else "no" pixelgrid = "1:1024:#1024,1:1024:#1024" logger.info("Make spectral-weighted instrument map for chip: %s" % chip) subprocess.check_call(["punlearn", "mkinstmap"]) subprocess.check_call([ "mkinstmap", "outfile=%s" % outfile, "spectrumfile=%s" % spectrumfile, "pixelgrid=%s" % pixelgrid, "detsubsys=ACIS-%s" % chip, "obsfile=%s" % obsfile, "maskfile=%s" % maskfile, "clobber=%s" % clobber, "mode=h" ]) def make_exposure_map(outfile, asphistfile, instmapfile, xygrid, clobber=False): """ Create the spectral-weighted exposure map by projecting the instrument map onto the sky with the aspect information. """ clobber = "yes" if clobber else "no" logger.info("Make exposure map by projecting instrument map ...") subprocess.check_call(["punlearn", "mkexpmap"]) subprocess.check_call([ "mkexpmap", "outfile=%s" % outfile, "asphistfile=%s" % asphistfile, "instmapfile=%s" % instmapfile, "xygrid=%s" % xygrid, "normalize=no", "useavgaspect=no", "clobber=%s" % clobber, "mode=h" ]) # Copy several keywords from instrument map (as ``fluximage`` does) logger.info("Copy several keywords from instrument map ...") copy_keyword(instmapfile, outfile, keyword=["SPECTRUM", "WGTFILE", "ENERG_LO", "ENERG_HI", "GRATING"]) def combine_expmaps(outfile, expmaps, clobber=False): """ Combine multiple exposure maps of each chip into a single one for ACIS-I (i.e., chips 0123). """ if len(expmaps) > 1: logger.info("Combine exposure maps: {0}".format(", ".join(expmaps))) operation = "imgout=%s" % "+".join([ "img%d" % (i+1) for i in range(len(expmaps)) ]) clobber = "yes" if clobber else "no" subprocess.check_call(["punlearn", "dmimgcalc"]) subprocess.check_call([ "dmimgcalc", "infile=%s" % ",".join(expmaps), "infile2=none", "outfile=%s[EXPMAP]" % outfile, "operation=%s" % operation, "clobber=%s" % clobber ]) # Add the lost "BUNIT" keyword during ``dmimgcalc`` write_keyword(outfile, keyword="BUNIT", value="cm**2 s") # Remove original exposure maps for single chip for f in expmaps: os.remove(f) else: logger.info("No need to combine exposure maps.") if os.path.exists(outfile) and (not clobber): raise OSError("File already exists: %s" % outfile) os.rename(expmaps[0], outfile) def threshold_expmap(expmap, cut="1.5%", clobber=False): """ The strongly variable exposure near the edge of a dithered field may produce "hot" pixels when divided into an image. Therefore, apply a threshold to the exposure map pixels that cuts the pixels with value of exposure less than this threshold. NOTE ---- The original/input exposure map is *replaced* by the threshold-cut exposure map. """ logger.info("Apply threshold to cut the exposure map: cut=%s" % cut) clobber = "yes" if clobber else "no" expmap_thresh = os.path.splitext(expmap)[0] + "_thresh.fits" subprocess.check_call(["punlearn", "dmimgthresh"]) subprocess.check_call([ "dmimgthresh", "infile=%s" % expmap, "outfile=%s" % expmap_thresh, "cut=%s" % cut, "clobber=%s" % clobber ]) os.rename(expmap_thresh, expmap) def main(): parser = argparse.ArgumentParser( description="Make spectral-weighted exposure map") parser.add_argument("-C", "--clobber", dest="clobber", action="store_true", help="overwrite existing file") parser.add_argument("-w", "--weights", dest="weights", help="spectral weights file (default: " + "'spec_weights' from manifest)") parser.add_argument("-e", "--evtfile", dest="evtfile", help="event file for aspect histogram creation " + "(default: 'evt2_clean' from manifest)") parser.add_argument("-i", "--infile", dest="infile", required=True, help="input image file") parser.add_argument("-o", "--outfile", dest="outfile", required=True, help="filename of output exposure map") args = parser.parse_args() setup_pfiles(["get_sky_limits", "asphist", "mkinstmap", "mkexpmap", "ardlib", "acis_set_ardlib", "dmimgcalc", "dmimgthresh"]) manifest = get_manifest() if args.weights: weights = args.weights else: weights = manifest.getpath("spec_weights", relative=True) if args.evtfile: evtfile = args.evtfile else: evtfile = manifest.getpath("evt2_clean", relative=True) asol = manifest.getpath("asol", relative=True, sep=",") bpix = manifest.getpath("bpix", relative=True) msk = manifest.getpath("msk", relative=True) chips = ACIS.get_chips_str(args.infile) logger.info("infile: %s" % args.infile) logger.info("output expmap: %s" % args.outfile) logger.info("weights: %s" % weights) logger.info("evtfile: %s" % evtfile) logger.info("chips: %s" % chips) logger.info("bpix: %s" % bpix) logger.info("asol: %s" % asol) logger.info("msk: %s" % msk) xygrid = get_xygrid(args.infile) logger.info("%s:xygrid: %s" % (args.infile, xygrid)) expmaps = [] for c in chips: logger.info("Processing chip %s ..." % c) asphist = "asphist_c{chip}.fits".format(chip=c) instmap = "instmap_c{chip}.fits".format(chip=c) expmap = "expmap_c{chip}.fits".format(chip=c) make_aspect_histogram(outfile=asphist, asol=asol, evtfile=evtfile, chip=c, clobber=args.clobber) make_instrument_map(outfile=instmap, spectrumfile=weights, chip=c, obsfile=args.infile, maskfile=msk, badpixfile=bpix, clobber=args.clobber) make_exposure_map(outfile=expmap, asphistfile=asphist, instmapfile=instmap, xygrid=xygrid, clobber=args.clobber) expmaps.append(expmap) # Remove intermediate files os.remove(asphist) os.remove(instmap) combine_expmaps(outfile=args.outfile, expmaps=expmaps, clobber=args.clobber) detnam = "ACIS-{0}".format(chips) logger.info("Update keyword 'DETNAM' to %s" % detnam) write_keyword(args.outfile, keyword="DETNAM", value=detnam) threshold_expmap(args.outfile, clobber=args.clobber) logger.info("Add created exposure map to manifest ...") key = "expmap" manifest.setpath(key, args.outfile) logger.info("Added '%s' to manifest: %s" % (key, manifest.get(key))) if __name__ == "__main__": main()

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protos/control_pb2_grpc.py

uni-tue-kn/p4-ipsec

13

169849

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc import control_pb2 as control__pb2 class ControlStub(object): # missing associated documentation comment in .proto file pass def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.addMACsecProtectRule = channel.unary_unary( '/Control/addMACsecProtectRule', request_serializer=control__pb2.MACsecProtectRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.addMACsecValidateRule = channel.unary_unary( '/Control/addMACsecValidateRule', request_serializer=control__pb2.MACsecValidateRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.deleteMACsecProtectRule = channel.unary_unary( '/Control/deleteMACsecProtectRule', request_serializer=control__pb2.MACsecProtectRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) self.deleteMACsecValidateRule = channel.unary_unary( '/Control/deleteMACsecValidateRule', request_serializer=control__pb2.MACsecValidateRule.SerializeToString, response_deserializer=control__pb2.control_status.FromString, ) class ControlServicer(object): # missing associated documentation comment in .proto file pass def addMACsecProtectRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def addMACsecValidateRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def deleteMACsecProtectRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def deleteMACsecValidateRule(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_ControlServicer_to_server(servicer, server): rpc_method_handlers = { 'addMACsecProtectRule': grpc.unary_unary_rpc_method_handler( servicer.addMACsecProtectRule, request_deserializer=control__pb2.MACsecProtectRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'addMACsecValidateRule': grpc.unary_unary_rpc_method_handler( servicer.addMACsecValidateRule, request_deserializer=control__pb2.MACsecValidateRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'deleteMACsecProtectRule': grpc.unary_unary_rpc_method_handler( servicer.deleteMACsecProtectRule, request_deserializer=control__pb2.MACsecProtectRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), 'deleteMACsecValidateRule': grpc.unary_unary_rpc_method_handler( servicer.deleteMACsecValidateRule, request_deserializer=control__pb2.MACsecValidateRule.FromString, response_serializer=control__pb2.control_status.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'Control', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,))

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v7/mediawiki/mediawiki.py

hardening/nikola-plugins

0

139157

# -*- coding: utf-8 -*- # Copyright © 2015 <NAME> and others. # Permission is hereby granted, free of charge, to any # person obtaining a copy of this software and associated # documentation files (the "Software"), to deal in the # Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the # Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice # shall be included in all copies or substantial portions of # the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY # KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE # WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR # PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS # OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR # OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """Implementation of compile_html based on smc.mw. You will need, of course, to install smc.mw """ from __future__ import unicode_literals import io import os import re from lxml import etree try: import smc.mw as mw except: mw = None from nikola.plugin_categories import PageCompiler from nikola.utils import makedirs, req_missing, write_metadata try: from collections import OrderedDict except ImportError: OrderedDict = dict # NOQA class CompileMediaWiki(PageCompiler): """Compile mediawiki into HTML.""" name = "mediawiki" demote_headers = True def compile_html(self, source, dest, is_two_file=True): makedirs(os.path.dirname(dest)) if mw is None: req_missing(['smc.mw'], 'build this site (compile with MediaWiki)', python=True) with io.open(dest, "w+", encoding="utf8") as out_file: with io.open(source, "r", encoding="utf8") as in_file: data = in_file.read() if not is_two_file: data = re.split('(\n\n|\r\n\r\n)', data, maxsplit=1)[-1] parser = mw.Parser(parseinfo=False, whitespace='', nameguard=False) ast = parser.parse(data, 'document', semantics=mw.Semantics(parser)) output = etree.tostring(ast, encoding='utf8').decode('utf8') out_file.write(output) def create_post(self, path, **kw): content = kw.pop('content', None) onefile = kw.pop('onefile', False) # is_page is not used by create_post as of now. kw.pop('is_page', False) metadata = {} metadata.update(self.default_metadata) metadata.update(kw) makedirs(os.path.dirname(path)) if not content.endswith('\n'): content += '\n' with io.open(path, "w+", encoding="utf8") as fd: if onefile: fd.write(write_metadata(metadata)) fd.write('\n\n') fd.write(content)

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src/mobu/autostart.py

lsst-sqre/sciencemonkey

0

176381

<reponame>lsst-sqre/sciencemonkey """Support for automatically starting flocks.""" from __future__ import annotations import yaml from .config import config from .dependencies.manager import monkey_business_manager from .models.flock import FlockConfig async def autostart() -> None: """Automatically start configured flocks. This function should be called from the startup hook of the FastAPI application. """ if not config.autostart: return with open(config.autostart, "r") as f: autostart = yaml.safe_load(f) flock_configs = [FlockConfig.parse_obj(flock) for flock in autostart] for flock_config in flock_configs: await monkey_business_manager.start_flock(flock_config)

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edx/config/lms/docker_run.py

openfun/learning-analytics-playground

1

16741

""" This is the default template for our main set of servers. This does NOT cover the content machines, which use content.py Common traits: * Use memcached, and cache-backed sessions * Use a MySQL 5.1 database """ # We intentionally define lots of variables that aren't used, and # want to import all variables from base settings files # pylint: disable=wildcard-import, unused-wildcard-import # Pylint gets confused by path.py instances, which report themselves as class # objects. As a result, pylint applies the wrong regex in validating names, # and throws spurious errors. Therefore, we disable invalid-name checking. # pylint: disable=invalid-name import datetime import dateutil from glob import glob import json import os from path import Path as path import pkgutil import platform from django.utils.translation import ugettext_lazy from django.conf import global_settings from celery_redis_sentinel import register from openedx.core.lib.logsettings import get_logger_config from path import Path as path from xmodule.modulestore.modulestore_settings import ( convert_module_store_setting_if_needed, update_module_store_settings, ) from ..common import * from .utils import Configuration, prefer_fun_video # Load custom configuration parameters from yaml files config = Configuration(os.path.dirname(__file__)) # edX has now started using "settings.ENV_TOKENS" and "settings.AUTH_TOKENS" everywhere in the # project, not just in the settings. Let's make sure our settings still work in this case ENV_TOKENS = config AUTH_TOKENS = config # SERVICE_VARIANT specifies name of the variant used, which decides what JSON # configuration files are read during startup. SERVICE_VARIANT = config("SERVICE_VARIANT", default=None) # CONFIG_ROOT specifies the directory where the JSON configuration # files are expected to be found. If not specified, use the project # directory. CONFIG_ROOT = path(config("CONFIG_ROOT", default=ENV_ROOT)) # CONFIG_PREFIX specifies the prefix of the JSON configuration files, # based on the service variant. If no variant is use, don't use a # prefix. CONFIG_PREFIX = SERVICE_VARIANT + "." if SERVICE_VARIANT else "" ################################ ALWAYS THE SAME ############################## RELEASE = config("RELEASE", default=None) DEBUG = False DEFAULT_TEMPLATE_ENGINE["OPTIONS"]["debug"] = False # IMPORTANT: With this enabled, the server must always be behind a proxy that # strips the header HTTP_X_FORWARDED_PROTO from client requests. Otherwise, # a user can fool our server into thinking it was an https connection. # See # https://docs.djangoproject.com/en/dev/ref/settings/#secure-proxy-ssl-header # for other warnings. SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") ###################################### CELERY ################################ CELERY_ALWAYS_EAGER = config("CELERY_ALWAYS_EAGER", default=False, formatter=bool) # Don't use a connection pool, since connections are dropped by ELB. BROKER_POOL_LIMIT = 0 BROKER_CONNECTION_TIMEOUT = 1 # For the Result Store, use the django cache named 'celery' CELERY_RESULT_BACKEND = config( "CELERY_RESULT_BACKEND", default="djcelery.backends.cache:CacheBackend" ) # When the broker is behind an ELB, use a heartbeat to refresh the # connection and to detect if it has been dropped. BROKER_HEARTBEAT = 60.0 BROKER_HEARTBEAT_CHECKRATE = 2 # Each worker should only fetch one message at a time CELERYD_PREFETCH_MULTIPLIER = 1 # Celery queues DEFAULT_PRIORITY_QUEUE = config( "DEFAULT_PRIORITY_QUEUE", default="edx.lms.core.default" ) HIGH_PRIORITY_QUEUE = config("HIGH_PRIORITY_QUEUE", default="edx.lms.core.high") LOW_PRIORITY_QUEUE = config("LOW_PRIORITY_QUEUE", default="edx.lms.core.low") HIGH_MEM_QUEUE = config("HIGH_MEM_QUEUE", default="edx.lms.core.high_mem") CELERY_DEFAULT_QUEUE = DEFAULT_PRIORITY_QUEUE CELERY_DEFAULT_ROUTING_KEY = DEFAULT_PRIORITY_QUEUE CELERY_QUEUES = config( "CELERY_QUEUES", default={ DEFAULT_PRIORITY_QUEUE: {}, HIGH_PRIORITY_QUEUE: {}, LOW_PRIORITY_QUEUE: {}, HIGH_MEM_QUEUE: {}, }, formatter=json.loads, ) CELERY_ROUTES = "lms.celery.Router" # Force accepted content to "json" only. If we also accept pickle-serialized # messages, the worker will crash when it's running with a privileged user (even # if it's not the root user but a user belonging to the root group, which is our # case with OpenShift). CELERY_ACCEPT_CONTENT = ["json"] CELERYBEAT_SCHEDULE = {} # For scheduling tasks, entries can be added to this dict ########################## NON-SECURE ENV CONFIG ############################## # Things like server locations, ports, etc. STATIC_ROOT_BASE = path("/edx/app/edxapp/staticfiles") STATIC_ROOT = STATIC_ROOT_BASE STATIC_URL = "/static/" STATICFILES_STORAGE = config( "STATICFILES_STORAGE", default="lms.envs.fun.storage.CDNProductionStorage" ) CDN_BASE_URL = config("CDN_BASE_URL", default=None) MEDIA_ROOT = path("/edx/var/edxapp/media/") MEDIA_URL = "/media/" # DEFAULT_COURSE_ABOUT_IMAGE_URL specifies the default image to show for courses that don't provide one DEFAULT_COURSE_ABOUT_IMAGE_URL = config( "DEFAULT_COURSE_ABOUT_IMAGE_URL", default=DEFAULT_COURSE_ABOUT_IMAGE_URL ) PLATFORM_NAME = config("PLATFORM_NAME", default=PLATFORM_NAME) # For displaying on the receipt. At Stanford PLATFORM_NAME != MERCHANT_NAME, but PLATFORM_NAME is a fine default PLATFORM_TWITTER_ACCOUNT = config( "PLATFORM_TWITTER_ACCOUNT", default=PLATFORM_TWITTER_ACCOUNT ) PLATFORM_FACEBOOK_ACCOUNT = config( "PLATFORM_FACEBOOK_ACCOUNT", default=PLATFORM_FACEBOOK_ACCOUNT ) SOCIAL_SHARING_SETTINGS = config( "SOCIAL_SHARING_SETTINGS", default=SOCIAL_SHARING_SETTINGS, formatter=json.loads ) # Social media links for the page footer SOCIAL_MEDIA_FOOTER_URLS = config( "SOCIAL_MEDIA_FOOTER_URLS", default=SOCIAL_MEDIA_FOOTER_URLS, formatter=json.loads ) CC_MERCHANT_NAME = config("CC_MERCHANT_NAME", default=PLATFORM_NAME) EMAIL_BACKEND = config( "EMAIL_BACKEND", default="django.core.mail.backends.smtp.EmailBackend" ) EMAIL_FILE_PATH = config("EMAIL_FILE_PATH", default=None) EMAIL_HOST = config("EMAIL_HOST", default="localhost") EMAIL_PORT = config("EMAIL_PORT", default=25) # django default is 25 EMAIL_USE_TLS = config("EMAIL_USE_TLS", default=False) # django default is False HTTPS = config("HTTPS", default=HTTPS) SESSION_COOKIE_DOMAIN = config("SESSION_COOKIE_DOMAIN", default=None) SESSION_COOKIE_HTTPONLY = config( "SESSION_COOKIE_HTTPONLY", default=True, formatter=bool ) SESSION_COOKIE_SECURE = config( "SESSION_COOKIE_SECURE", default=SESSION_COOKIE_SECURE, formatter=bool ) SESSION_ENGINE = config("SESSION_ENGINE", default="redis_sessions.session") SESSION_SAVE_EVERY_REQUEST = config( "SESSION_SAVE_EVERY_REQUEST", default=SESSION_SAVE_EVERY_REQUEST, formatter=bool ) # Configuration to use session with redis # To use redis, change SESSION_ENGINE to "redis_sessions.session" SESSION_REDIS_HOST = config("SESSION_REDIS_HOST", default="redis") SESSION_REDIS_PORT = config("SESSION_REDIS_PORT", default=6379, formatter=int) SESSION_REDIS_DB = config("SESSION_REDIS_DB", default=1, formatter=int) SESSION_REDIS_PASSWORD = config("SESSION_REDIS_PASSWORD", default=None) SESSION_REDIS_PREFIX = config("SESSION_REDIS_PREFIX", default="session") SESSION_REDIS_SOCKET_TIMEOUT = config( "SESSION_REDIS_SOCKET_TIMEOUT", default=1, formatter=int ) SESSION_REDIS_RETRY_ON_TIMEOUT = config( "SESSION_REDIS_RETRY_ON_TIMEOUT", default=False, formatter=bool ) SESSION_REDIS = config( "SESSION_REDIS", default={ "host": SESSION_REDIS_HOST, "port": SESSION_REDIS_PORT, "db": SESSION_REDIS_DB, # db 0 is used for Celery Broker "password": SESSION_REDIS_PASSWORD, "prefix": SESSION_REDIS_PREFIX, "socket_timeout": SESSION_REDIS_SOCKET_TIMEOUT, "retry_on_timeout": SESSION_REDIS_RETRY_ON_TIMEOUT, }, formatter=json.loads, ) SESSION_REDIS_SENTINEL_LIST = config( "SESSION_REDIS_SENTINEL_LIST", default=None, formatter=json.loads ) SESSION_REDIS_SENTINEL_MASTER_ALIAS = config( "SESSION_REDIS_SENTINEL_MASTER_ALIAS", default=None ) REGISTRATION_EXTRA_FIELDS = config( "REGISTRATION_EXTRA_FIELDS", default=REGISTRATION_EXTRA_FIELDS, formatter=json.loads ) # Set the names of cookies shared with the marketing site # These have the same cookie domain as the session, which in production # usually includes subdomains. EDXMKTG_LOGGED_IN_COOKIE_NAME = config( "EDXMKTG_LOGGED_IN_COOKIE_NAME", default=EDXMKTG_LOGGED_IN_COOKIE_NAME ) EDXMKTG_USER_INFO_COOKIE_NAME = config( "EDXMKTG_USER_INFO_COOKIE_NAME", default=EDXMKTG_USER_INFO_COOKIE_NAME ) # Override feature by feature by whatever is being redefined in the settings.yaml file CONFIG_FEATURES = config("FEATURES", default={}, formatter=json.loads) FEATURES.update(CONFIG_FEATURES) LMS_BASE = config("LMS_BASE", default="localhost:8072") CMS_BASE = config("CMS_BASE", default="localhost:8082") LMS_ROOT_URL = config("LMS_ROOT_URL", default="http://{:s}".format(LMS_BASE)) LMS_INTERNAL_ROOT_URL = config("LMS_INTERNAL_ROOT_URL", default=LMS_ROOT_URL) SITE_NAME = config("SITE_NAME", default=LMS_BASE) ALLOWED_HOSTS = config( "ALLOWED_HOSTS", default=[LMS_BASE.split(":")[0]], formatter=json.loads ) if FEATURES.get("PREVIEW_LMS_BASE"): ALLOWED_HOSTS.append(FEATURES["PREVIEW_LMS_BASE"]) # allow for environments to specify what cookie name our login subsystem should use # this is to fix a bug regarding simultaneous logins between edx.org and edge.edx.org which can # happen with some browsers (e.g. Firefox) if config("SESSION_COOKIE_NAME", default=None): # NOTE, there's a bug in Django (http://bugs.python.org/issue18012) which necessitates this # being a str() SESSION_COOKIE_NAME = str(config("SESSION_COOKIE_NAME")) CACHE_REDIS_HOST = config("CACHE_REDIS_HOST", default="redis") CACHE_REDIS_PORT = config("CACHE_REDIS_PORT", default=6379, formatter=int) CACHE_REDIS_DB = config("CACHE_REDIS_DB", default=1, formatter=int) CACHE_REDIS_BACKEND = config( "CACHE_REDIS_BACKEND", default="django_redis.cache.RedisCache" ) CACHE_REDIS_URI = "redis://{}:{}/{}".format( CACHE_REDIS_HOST, CACHE_REDIS_PORT, CACHE_REDIS_DB ) CACHE_REDIS_CLIENT = config( "CACHE_REDIS_CLIENT", default="django_redis.client.DefaultClient" ) CACHES_DEFAULT_CONFIG = { "BACKEND": CACHE_REDIS_BACKEND, "LOCATION": CACHE_REDIS_URI, "OPTIONS": {"CLIENT_CLASS": CACHE_REDIS_CLIENT}, } if "Sentinel" in CACHE_REDIS_BACKEND: CACHES_DEFAULT_CONFIG["LOCATION"] = [(CACHE_REDIS_HOST, CACHE_REDIS_PORT)] CACHES_DEFAULT_CONFIG["OPTIONS"]["SENTINEL_SERVICE_NAME"] = config( "CACHE_REDIS_SENTINEL_SERVICE_NAME", default="mymaster" ) CACHES_DEFAULT_CONFIG["OPTIONS"]["REDIS_CLIENT_KWARGS"] = {"db": CACHE_REDIS_DB} CACHES = config( "CACHES", default={ "default": dict(CACHES_DEFAULT_CONFIG, **{"KEY_PREFIX": "default"}), "general": dict(CACHES_DEFAULT_CONFIG, **{"KEY_PREFIX": "general"}), "celery": dict(CACHES_DEFAULT_CONFIG, **{"KEY_PREFIX": "celery"}), "mongo_metadata_inheritance": dict( CACHES_DEFAULT_CONFIG, **{"KEY_PREFIX": "mongo_metadata_inheritance"} ), "openassessment_submissions": dict( CACHES_DEFAULT_CONFIG, **{"KEY_PREFIX": "openassessment_submissions"} ), "loc_cache": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "edx_location_mem_cache", }, # Cache backend used by Django 1.8 storage backend while processing static files "staticfiles": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "edx_location_mem_cache", }, }, formatter=json.loads, ) # Email overrides DEFAULT_FROM_EMAIL = config("DEFAULT_FROM_EMAIL", default=DEFAULT_FROM_EMAIL) DEFAULT_FEEDBACK_EMAIL = config( "DEFAULT_FEEDBACK_EMAIL", default=DEFAULT_FEEDBACK_EMAIL ) ADMINS = config("ADMINS", default=ADMINS, formatter=json.loads) SERVER_EMAIL = config("SERVER_EMAIL", default=SERVER_EMAIL) TECH_SUPPORT_EMAIL = config("TECH_SUPPORT_EMAIL", default=TECH_SUPPORT_EMAIL) CONTACT_EMAIL = config("CONTACT_EMAIL", default=CONTACT_EMAIL) BUGS_EMAIL = config("BUGS_EMAIL", default=BUGS_EMAIL) PAYMENT_SUPPORT_EMAIL = config("PAYMENT_SUPPORT_EMAIL", default=PAYMENT_SUPPORT_EMAIL) FINANCE_EMAIL = config("FINANCE_EMAIL", default=FINANCE_EMAIL) UNIVERSITY_EMAIL = config("UNIVERSITY_EMAIL", default=UNIVERSITY_EMAIL) PRESS_EMAIL = config("PRESS_EMAIL", default=PRESS_EMAIL) # Currency PAID_COURSE_REGISTRATION_CURRENCY = config( "PAID_COURSE_REGISTRATION_CURRENCY", default=["EUR", u"\N{euro sign}"] ) # Payment Report Settings PAYMENT_REPORT_GENERATOR_GROUP = config( "PAYMENT_REPORT_GENERATOR_GROUP", default=PAYMENT_REPORT_GENERATOR_GROUP ) # Bulk Email overrides BULK_EMAIL_DEFAULT_FROM_EMAIL = config( "BULK_EMAIL_DEFAULT_FROM_EMAIL", default=BULK_EMAIL_DEFAULT_FROM_EMAIL ) BULK_EMAIL_EMAILS_PER_TASK = config( "BULK_EMAIL_EMAILS_PER_TASK", default=BULK_EMAIL_EMAILS_PER_TASK, formatter=int ) BULK_EMAIL_DEFAULT_RETRY_DELAY = config( "BULK_EMAIL_DEFAULT_RETRY_DELAY", default=BULK_EMAIL_DEFAULT_RETRY_DELAY, formatter=int, ) BULK_EMAIL_MAX_RETRIES = config( "BULK_EMAIL_MAX_RETRIES", default=BULK_EMAIL_MAX_RETRIES, formatter=int ) BULK_EMAIL_INFINITE_RETRY_CAP = config( "BULK_EMAIL_INFINITE_RETRY_CAP", default=BULK_EMAIL_INFINITE_RETRY_CAP, formatter=int, ) BULK_EMAIL_LOG_SENT_EMAILS = config( "BULK_EMAIL_LOG_SENT_EMAILS", default=BULK_EMAIL_LOG_SENT_EMAILS, formatter=bool ) BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS = config( "BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS", default=BULK_EMAIL_RETRY_DELAY_BETWEEN_SENDS, formatter=int, ) # We want Bulk Email running on the high-priority queue, so we define the # routing key that points to it. At the moment, the name is the same. # We have to reset the value here, since we have changed the value of the queue name. BULK_EMAIL_ROUTING_KEY = config("BULK_EMAIL_ROUTING_KEY", default=HIGH_PRIORITY_QUEUE) # We can run smaller jobs on the low priority queue. See note above for why # we have to reset the value here. BULK_EMAIL_ROUTING_KEY_SMALL_JOBS = LOW_PRIORITY_QUEUE # Theme overrides THEME_NAME = config("THEME_NAME", default=None) COMPREHENSIVE_THEME_DIR = path( config("COMPREHENSIVE_THEME_DIR", default=COMPREHENSIVE_THEME_DIR) ) # Marketing link overrides MKTG_URL_LINK_MAP = config("MKTG_URL_LINK_MAP", default={}, formatter=json.loads) SUPPORT_SITE_LINK = config("SUPPORT_SITE_LINK", default=SUPPORT_SITE_LINK) # Mobile store URL overrides MOBILE_STORE_URLS = config("MOBILE_STORE_URLS", default=MOBILE_STORE_URLS) # Timezone overrides TIME_ZONE = config("TIME_ZONE", default=TIME_ZONE) # Translation overrides LANGUAGES = config("LANGUAGES", default=LANGUAGES, formatter=json.loads) LANGUAGE_DICT = dict(LANGUAGES) LANGUAGE_CODE = config("LANGUAGE_CODE", default=LANGUAGE_CODE) USE_I18N = config("USE_I18N", default=USE_I18N) # Additional installed apps for app in config("ADDL_INSTALLED_APPS", default=[], formatter=json.loads): INSTALLED_APPS.append(app) WIKI_ENABLED = config("WIKI_ENABLED", default=WIKI_ENABLED, formatter=bool) local_loglevel = config("LOCAL_LOGLEVEL", default="INFO") # Configure Logging LOG_DIR = config("LOG_DIR", default=path("/edx/var/logs/edx"), formatter=path) DATA_DIR = config("DATA_DIR", default=path("/edx/app/edxapp/data"), formatter=path) # Default format for syslog logging standard_format = "%(asctime)s %(levelname)s %(process)d [%(name)s] %(filename)s:%(lineno)d - %(message)s" syslog_format = ( "[variant:lms][%(name)s][env:sandbox] %(levelname)s " "[{hostname} %(process)d] [%(filename)s:%(lineno)d] - %(message)s" ).format(hostname=platform.node().split(".")[0]) LOGGING = { "version": 1, "disable_existing_loggers": False, "handlers": { "local": { "formatter": "syslog_format", "class": "logging.StreamHandler", "level": "INFO", }, "tracking": { "formatter": "raw", "class": "logging.StreamHandler", "level": "DEBUG", }, "console": { "formatter": "standard", "class": "logging.StreamHandler", "level": "INFO", }, }, "formatters": { "raw": {"format": "%(message)s"}, "syslog_format": {"format": syslog_format}, "standard": {"format": standard_format}, }, "filters": {"require_debug_false": {"()": "django.utils.log.RequireDebugFalse"}}, "loggers": { "": {"level": "INFO", "propagate": False, "handlers": ["console", "local"]}, "tracking": {"level": "DEBUG", "propagate": False, "handlers": ["tracking"]}, }, } SENTRY_DSN = config("SENTRY_DSN", default=None) if SENTRY_DSN: LOGGING["loggers"][""]["handlers"].append("sentry") LOGGING["handlers"]["sentry"] = { "class": "raven.handlers.logging.SentryHandler", "dsn": SENTRY_DSN, "level": "ERROR", "environment": "production", "release": RELEASE, } COURSE_LISTINGS = config("COURSE_LISTINGS", default={}, formatter=json.loads) SUBDOMAIN_BRANDING = config("SUBDOMAIN_BRANDING", default={}, formatter=json.loads) VIRTUAL_UNIVERSITIES = config("VIRTUAL_UNIVERSITIES", default=[]) META_UNIVERSITIES = config("META_UNIVERSITIES", default={}, formatter=json.loads) COMMENTS_SERVICE_URL = config("COMMENTS_SERVICE_URL", default="") COMMENTS_SERVICE_KEY = config("COMMENTS_SERVICE_KEY", default="") CERT_NAME_SHORT = config("CERT_NAME_SHORT", default=CERT_NAME_SHORT) CERT_NAME_LONG = config("CERT_NAME_LONG", default=CERT_NAME_LONG) CERT_QUEUE = config("CERT_QUEUE", default="test-pull") ZENDESK_URL = config("ZENDESK_URL", default=None) FEEDBACK_SUBMISSION_EMAIL = config("FEEDBACK_SUBMISSION_EMAIL", default=None) MKTG_URLS = config("MKTG_URLS", default=MKTG_URLS, formatter=json.loads) # Badgr API BADGR_API_TOKEN = config("BADGR_API_TOKEN", default=BADGR_API_TOKEN) BADGR_BASE_URL = config("BADGR_BASE_URL", default=BADGR_BASE_URL) BADGR_ISSUER_SLUG = config("BADGR_ISSUER_SLUG", default=BADGR_ISSUER_SLUG) # git repo loading environment GIT_REPO_DIR = config( "GIT_REPO_DIR", default=path("/edx/var/edxapp/course_repos"), formatter=path ) GIT_IMPORT_STATIC = config("GIT_IMPORT_STATIC", default=True) for name, value in config("CODE_JAIL", default={}, formatter=json.loads).items(): oldvalue = CODE_JAIL.get(name) if isinstance(oldvalue, dict): for subname, subvalue in value.items(): oldvalue[subname] = subvalue else: CODE_JAIL[name] = value COURSES_WITH_UNSAFE_CODE = config( "COURSES_WITH_UNSAFE_CODE", default=[], formatter=json.loads ) ASSET_IGNORE_REGEX = config("ASSET_IGNORE_REGEX", default=ASSET_IGNORE_REGEX) # Event Tracking TRACKING_IGNORE_URL_PATTERNS = config( "TRACKING_IGNORE_URL_PATTERNS", default=TRACKING_IGNORE_URL_PATTERNS, formatter=json.loads, ) # SSL external authentication settings SSL_AUTH_EMAIL_DOMAIN = config("SSL_AUTH_EMAIL_DOMAIN", default="MIT.EDU") SSL_AUTH_DN_FORMAT_STRING = config("SSL_AUTH_DN_FORMAT_STRING", default=None) # Django CAS external authentication settings CAS_EXTRA_LOGIN_PARAMS = config( "CAS_EXTRA_LOGIN_PARAMS", default=None, formatter=json.loads ) if FEATURES.get("AUTH_USE_CAS"): CAS_SERVER_URL = config("CAS_SERVER_URL", default=None) INSTALLED_APPS.append("django_cas") MIDDLEWARE_CLASSES.append("django_cas.middleware.CASMiddleware") CAS_ATTRIBUTE_CALLBACK = config( "CAS_ATTRIBUTE_CALLBACK", default=None, formatter=json.loads ) if CAS_ATTRIBUTE_CALLBACK: import importlib CAS_USER_DETAILS_RESOLVER = getattr( importlib.import_module(CAS_ATTRIBUTE_CALLBACK["module"]), CAS_ATTRIBUTE_CALLBACK["function"], ) # Video Caching. Pairing country codes with CDN URLs. # Example: {'CN': 'http://api.xuetangx.com/edx/video?s3_url='} VIDEO_CDN_URL = config("VIDEO_CDN_URL", default={}, formatter=json.loads) # Branded footer FOOTER_OPENEDX_URL = config("FOOTER_OPENEDX_URL", default=FOOTER_OPENEDX_URL) FOOTER_OPENEDX_LOGO_IMAGE = config( "FOOTER_OPENEDX_LOGO_IMAGE", default=FOOTER_OPENEDX_LOGO_IMAGE ) FOOTER_ORGANIZATION_IMAGE = config( "FOOTER_ORGANIZATION_IMAGE", default=FOOTER_ORGANIZATION_IMAGE ) FOOTER_CACHE_TIMEOUT = config( "FOOTER_CACHE_TIMEOUT", default=FOOTER_CACHE_TIMEOUT, formatter=int ) FOOTER_BROWSER_CACHE_MAX_AGE = config( "FOOTER_BROWSER_CACHE_MAX_AGE", default=FOOTER_BROWSER_CACHE_MAX_AGE, formatter=int ) # Credit notifications settings NOTIFICATION_EMAIL_CSS = config( "NOTIFICATION_EMAIL_CSS", default=NOTIFICATION_EMAIL_CSS ) NOTIFICATION_EMAIL_EDX_LOGO = config( "NOTIFICATION_EMAIL_EDX_LOGO", default=NOTIFICATION_EMAIL_EDX_LOGO ) ############# CORS headers for cross-domain requests ################# if FEATURES.get("ENABLE_CORS_HEADERS") or FEATURES.get( "ENABLE_CROSS_DOMAIN_CSRF_COOKIE" ): CORS_ALLOW_CREDENTIALS = True CORS_ORIGIN_WHITELIST = config( "CORS_ORIGIN_WHITELIST", default=(), formatter=json.loads ) CORS_ORIGIN_ALLOW_ALL = config( "CORS_ORIGIN_ALLOW_ALL", default=False, formatter=bool ) CORS_ALLOW_INSECURE = config("CORS_ALLOW_INSECURE", default=False, formatter=bool) # If setting a cross-domain cookie, it's really important to choose # a name for the cookie that is DIFFERENT than the cookies used # by each subdomain. For example, suppose the applications # at these subdomains are configured to use the following cookie names: # # 1) foo.example.com --> "csrftoken" # 2) baz.example.com --> "csrftoken" # 3) bar.example.com --> "csrftoken" # # For the cross-domain version of the CSRF cookie, you need to choose # a name DIFFERENT than "csrftoken"; otherwise, the new token configured # for ".example.com" could conflict with the other cookies, # non-deterministically causing 403 responses. # # Because of the way Django stores cookies, the cookie name MUST # be a `str`, not unicode. Otherwise there will `TypeError`s will be raised # when Django tries to call the unicode `translate()` method with the wrong # number of parameters. CROSS_DOMAIN_CSRF_COOKIE_NAME = str(config("CROSS_DOMAIN_CSRF_COOKIE_NAME")) # When setting the domain for the "cross-domain" version of the CSRF # cookie, you should choose something like: ".example.com" # (note the leading dot), where both the referer and the host # are subdomains of "example.com". # # Browser security rules require that # the cookie domain matches the domain of the server; otherwise # the cookie won't get set. And once the cookie gets set, the client # needs to be on a domain that matches the cookie domain, otherwise # the client won't be able to read the cookie. CROSS_DOMAIN_CSRF_COOKIE_DOMAIN = config("CROSS_DOMAIN_CSRF_COOKIE_DOMAIN") # Field overrides. To use the IDDE feature, add # 'courseware.student_field_overrides.IndividualStudentOverrideProvider'. FIELD_OVERRIDE_PROVIDERS = tuple( config("FIELD_OVERRIDE_PROVIDERS", default=[], formatter=json.loads) ) ############################## SECURE AUTH ITEMS ############### # Secret things: passwords, access keys, etc. ############### XBlock filesystem field config ########## DJFS = config( "DJFS", default={ "directory_root": "/edx/var/edxapp/django-pyfs/static/django-pyfs", "type": "osfs", "url_root": "/static/django-pyfs", }, formatter=json.loads, ) ############### Module Store Items ########## HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS = config( "HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS", default={}, formatter=json.loads ) # PREVIEW DOMAIN must be present in HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS for the preview to show draft changes if "PREVIEW_LMS_BASE" in FEATURES and FEATURES["PREVIEW_LMS_BASE"] != "": PREVIEW_DOMAIN = FEATURES["PREVIEW_LMS_BASE"].split(":")[0] # update dictionary with preview domain regex HOSTNAME_MODULESTORE_DEFAULT_MAPPINGS.update({PREVIEW_DOMAIN: "draft-preferred"}) ############### Mixed Related(Secure/Not-Secure) Items ########## LMS_SEGMENT_KEY = config("LMS_SEGMENT_KEY", default=None) CC_PROCESSOR_NAME = config("CC_PROCESSOR_NAME", default=CC_PROCESSOR_NAME) CC_PROCESSOR = config("CC_PROCESSOR", default=CC_PROCESSOR) SECRET_KEY = config("SECRET_KEY", default="ThisisAnExampleKeyForDevPurposeOnly") # Authentication backends # - behind a proxy, use: "lms.envs.fun.backends.ProxyRateLimitModelBackend" # - for LTI provider, add: "lti_provider.users.LtiBackend" # - for CAS, add: "django_cas.backends.CASBackend" AUTHENTICATION_BACKENDS = config( "AUTHENTICATION_BACKENDS", default=("lms.envs.fun.backends.ProxyRateLimitModelBackend",), ) DEFAULT_FILE_STORAGE = config( "DEFAULT_FILE_STORAGE", default="django.core.files.storage.FileSystemStorage" ) # Specific setting for the File Upload Service to store media in a bucket. FILE_UPLOAD_STORAGE_BUCKET_NAME = config( "FILE_UPLOAD_STORAGE_BUCKET_NAME", default="uploads" ) FILE_UPLOAD_STORAGE_PREFIX = config( "FILE_UPLOAD_STORAGE_PREFIX", default=FILE_UPLOAD_STORAGE_PREFIX ) # If there is a database called 'read_replica', you can use the use_read_replica_if_available # function in util/query.py, which is useful for very large database reads DATABASE_ENGINE = config("DATABASE_ENGINE", default="django.db.backends.mysql") DATABASE_HOST = config("DATABASE_HOST", default="mysql") DATABASE_PORT = config("DATABASE_PORT", default=3306, formatter=int) DATABASE_NAME = config("DATABASE_NAME", default="edxapp") DATABASE_USER = config("DATABASE_USER", default="edxapp_user") DATABASE_PASSWORD = config("DATABASE_PASSWORD", default="password") DATABASES = config( "DATABASES", default={ "default": { "ENGINE": DATABASE_ENGINE, "HOST": DATABASE_HOST, "PORT": DATABASE_PORT, "NAME": DATABASE_NAME, "USER": DATABASE_USER, "PASSWORD": DATABASE_PASSWORD, } }, formatter=json.loads, ) # Enable automatic transaction management on all databases # https://docs.djangoproject.com/en/1.8/topics/db/transactions/#tying-transactions-to-http-requests # This needs to be true for all databases for database_name in DATABASES: DATABASES[database_name]["ATOMIC_REQUESTS"] = True XQUEUE_INTERFACE = config( "XQUEUE_INTERFACE", default={"url": None, "basic_auth": None, "django_auth": None}, formatter=json.loads, ) # Configure the MODULESTORE MODULESTORE = convert_module_store_setting_if_needed( config("MODULESTORE", default=MODULESTORE, formatter=json.loads) ) MONGODB_PASSWORD = config("MONGODB_PASSWORD", default="") MONGODB_HOST = config("MONGODB_HOST", default="mongodb") MONGODB_PORT = config("MONGODB_PORT", default=27017, formatter=int) MONGODB_NAME = config("MONGODB_NAME", default="edxapp") MONGODB_USER = config("MONGODB_USER", default=None) MONGODB_SSL = config("MONGODB_SSL", default=False, formatter=bool) MONGODB_REPLICASET = config("MONGODB_REPLICASET", default=None) # Accepted read_preference value can be found here https://github.com/mongodb/mongo-python-driver/blob/2.9.1/pymongo/read_preferences.py#L54 MONGODB_READ_PREFERENCE = config("MONGODB_READ_PREFERENCE", default="PRIMARY") DOC_STORE_CONFIG = config( "DOC_STORE_CONFIG", default={ "collection": "modulestore", "host": MONGODB_HOST, "port": MONGODB_PORT, "db": MONGODB_NAME, "user": MONGODB_USER, "password": <PASSWORD>, "ssl": MONGODB_SSL, "replicaSet": MONGODB_REPLICASET, "read_preference": MONGODB_READ_PREFERENCE, }, formatter=json.loads, ) update_module_store_settings(MODULESTORE, doc_store_settings=DOC_STORE_CONFIG) MONGODB_LOG = config("MONGODB_LOG", default={}, formatter=json.loads) CONTENTSTORE = config( "CONTENTSTORE", default={ "DOC_STORE_CONFIG": DOC_STORE_CONFIG, "ENGINE": "xmodule.contentstore.mongo.MongoContentStore", }, formatter=json.loads, ) EMAIL_HOST_USER = config("EMAIL_HOST_USER", default="") # django default is '' EMAIL_HOST_PASSWORD = config("EMAIL_HOST_PASSWORD", default="") # django default is '' # Datadog for events! DATADOG = config("DATADOG", default={}, formatter=json.loads) # TODO: deprecated (compatibility with previous settings) DATADOG_API = config("DATADOG_API", default=None) # Analytics dashboard server ANALYTICS_SERVER_URL = config("ANALYTICS_SERVER_URL", default=None) ANALYTICS_API_KEY = config("ANALYTICS_API_KEY", default="") # Analytics data source ANALYTICS_DATA_URL = config("ANALYTICS_DATA_URL", default=ANALYTICS_DATA_URL) ANALYTICS_DATA_TOKEN = config("ANALYTICS_DATA_TOKEN", default=ANALYTICS_DATA_TOKEN) # Analytics Dashboard # when True this setting add a link in instructor dashbord to analytics insight service ANALYTICS_DASHBOARD_URL = config( "ANALYTICS_DASHBOARD_URL", default=False, formatter=bool ) ANALYTICS_DASHBOARD_NAME = config( "ANALYTICS_DASHBOARD_NAME", default=PLATFORM_NAME + " Insights" ) # Mailchimp New User List MAILCHIMP_NEW_USER_LIST_ID = config("MAILCHIMP_NEW_USER_LIST_ID", default=None) # Zendesk ZENDESK_USER = config("ZENDESK_USER", default=None) ZENDESK_API_KEY = config("ZENDESK_API_KEY", default=None) # API Key for inbound requests from Notifier service EDX_API_KEY = config("EDX_API_KEY", default=None) # Celery Broker # For redis sentinel use the redis-sentinel transport CELERY_BROKER_TRANSPORT = config("CELERY_BROKER_TRANSPORT", default="redis") CELERY_BROKER_USER = config("CELERY_BROKER_USER", default="") CELERY_BROKER_PASSWORD = config("CELERY_BROKER_PASSWORD", default="") CELERY_BROKER_HOST = config("CELERY_BROKER_HOST", default="redis") CELERY_BROKER_PORT = config("CELERY_BROKER_PORT", default=6379, formatter=int) CELERY_BROKER_VHOST = config("CELERY_BROKER_VHOST", default=0, formatter=int) if CELERY_BROKER_TRANSPORT == "redis-sentinel": # register redis sentinel schema in celery register() BROKER_URL = "{transport}://{user}:{password}@{host}:{port}/{vhost}".format( transport=CELERY_BROKER_TRANSPORT, user=CELERY_BROKER_USER, password=<PASSWORD>, host=CELERY_BROKER_HOST, port=CELERY_BROKER_PORT, vhost=CELERY_BROKER_VHOST, ) # To use redis-sentinel, refer to the documenation here # https://celery-redis-sentinel.readthedocs.io/en/latest/ BROKER_TRANSPORT_OPTIONS = config( "BROKER_TRANSPORT_OPTIONS", default={}, formatter=json.loads ) # upload limits STUDENT_FILEUPLOAD_MAX_SIZE = config( "STUDENT_FILEUPLOAD_MAX_SIZE", default=STUDENT_FILEUPLOAD_MAX_SIZE, formatter=int ) # Event tracking TRACKING_BACKENDS.update(config("TRACKING_BACKENDS", default={}, formatter=json.loads)) EVENT_TRACKING_BACKENDS["tracking_logs"]["OPTIONS"]["backends"].update( config("EVENT_TRACKING_BACKENDS", default={}, formatter=json.loads) ) EVENT_TRACKING_BACKENDS["segmentio"]["OPTIONS"]["processors"][0]["OPTIONS"][ "whitelist" ].extend( config("EVENT_TRACKING_SEGMENTIO_EMIT_WHITELIST", default=[], formatter=json.loads) ) TRACKING_SEGMENTIO_WEBHOOK_SECRET = config( "TRACKING_SEGMENTIO_WEBHOOK_SECRET", default=TRACKING_SEGMENTIO_WEBHOOK_SECRET ) TRACKING_SEGMENTIO_ALLOWED_TYPES = config( "TRACKING_SEGMENTIO_ALLOWED_TYPES", default=TRACKING_SEGMENTIO_ALLOWED_TYPES, formatter=json.loads, ) TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES = config( "TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES", default=TRACKING_SEGMENTIO_DISALLOWED_SUBSTRING_NAMES, formatter=json.loads, ) TRACKING_SEGMENTIO_SOURCE_MAP = config( "TRACKING_SEGMENTIO_SOURCE_MAP", default=TRACKING_SEGMENTIO_SOURCE_MAP, formatter=json.loads, ) # Student identity verification settings VERIFY_STUDENT = config("VERIFY_STUDENT", default=VERIFY_STUDENT, formatter=json.loads) # Grades download GRADES_DOWNLOAD_ROUTING_KEY = config( "GRADES_DOWNLOAD_ROUTING_KEY", default=HIGH_MEM_QUEUE ) GRADES_DOWNLOAD = config( "GRADES_DOWNLOAD", default=GRADES_DOWNLOAD, formatter=json.loads ) GRADES_DOWNLOAD = config("GRADES_DOWNLOAD", default=GRADES_DOWNLOAD) # financial reports FINANCIAL_REPORTS = config( "FINANCIAL_REPORTS", default=FINANCIAL_REPORTS, formatter=json.loads ) ##### ACCOUNT LOCKOUT DEFAULT PARAMETERS ##### MAX_FAILED_LOGIN_ATTEMPTS_ALLOWED = config( "MAX_FAILED_LOGIN_ATTEMPTS_ALLOWED", default=5, formatter=int ) MAX_FAILED_LOGIN_ATTEMPTS_LOCKOUT_PERIOD_SECS = config( "MAX_FAILED_LOGIN_ATTEMPTS_LOCKOUT_PERIOD_SECS", default=15 * 60, formatter=int ) MICROSITE_CONFIGURATION = config( "MICROSITE_CONFIGURATION", default={}, formatter=json.loads ) MICROSITE_ROOT_DIR = path(config("MICROSITE_ROOT_DIR", default="")) #### PASSWORD POLICY SETTINGS ##### PASSWORD_MIN_LENGTH = config("PASSWORD_MIN_LENGTH", default=12, formatter=int) PASSWORD_MAX_LENGTH = config("PASSWORD_MAX_LENGTH", default=None, formatter=int) PASSWORD_COMPLEXITY = config( "PASSWORD_COMPLEXITY", default={"UPPER": 1, "LOWER": 1, "DIGITS": 1}, formatter=json.loads, ) PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD = config( "PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD", default=PASSWORD_DICTIONARY_EDIT_DISTANCE_THRESHOLD, formatter=int, ) PASSWORD_DICTIONARY = config("PASSWORD_DICTIONARY", default=[], formatter=json.loads) ### INACTIVITY SETTINGS #### SESSION_INACTIVITY_TIMEOUT_IN_SECONDS = config( "SESSION_INACTIVITY_TIMEOUT_IN_SECONDS", default=None, formatter=int ) ##### LMS DEADLINE DISPLAY TIME_ZONE ####### TIME_ZONE_DISPLAYED_FOR_DEADLINES = config( "TIME_ZONE_DISPLAYED_FOR_DEADLINES", default=TIME_ZONE_DISPLAYED_FOR_DEADLINES ) ##### X-Frame-Options response header settings ##### X_FRAME_OPTIONS = config("X_FRAME_OPTIONS", default=X_FRAME_OPTIONS) ##### Third-party auth options ################################################ if FEATURES.get("ENABLE_THIRD_PARTY_AUTH"): # The reduced session expiry time during the third party login pipeline. (Value in seconds) SOCIAL_AUTH_PIPELINE_TIMEOUT = config("SOCIAL_AUTH_PIPELINE_TIMEOUT", default=600) # The SAML private/public key values do not need the delimiter lines (such as # "-----BEGIN PRIVATE KEY-----", default="-----END PRIVATE KEY-----" etc.) but they may be included # if you want (though it's easier to format the key values as JSON without the delimiters). SOCIAL_AUTH_SAML_SP_PRIVATE_KEY = config( "SOCIAL_AUTH_SAML_SP_PRIVATE_KEY", default="" ) SOCIAL_AUTH_SAML_SP_PUBLIC_CERT = config( "SOCIAL_AUTH_SAML_SP_PUBLIC_CERT", default="" ) SOCIAL_AUTH_OAUTH_SECRETS = config( "SOCIAL_AUTH_OAUTH_SECRETS", default={}, formatter=json.loads ) SOCIAL_AUTH_LTI_CONSUMER_SECRETS = config( "SOCIAL_AUTH_LTI_CONSUMER_SECRETS", default={}, formatter=json.loads ) # third_party_auth config moved to ConfigurationModels. This is for data migration only: THIRD_PARTY_AUTH_OLD_CONFIG = config("THIRD_PARTY_AUTH", default=None) if ( config("THIRD_PARTY_AUTH_SAML_FETCH_PERIOD_HOURS", default=24, formatter=int) is not None ): CELERYBEAT_SCHEDULE["refresh-saml-metadata"] = { "task": "third_party_auth.fetch_saml_metadata", "schedule": datetime.timedelta( hours=config( "THIRD_PARTY_AUTH_SAML_FETCH_PERIOD_HOURS", default=24, formatter=int, ) ), } # The following can be used to integrate a custom login form with third_party_auth. # It should be a dict where the key is a word passed via ?auth_entry=, and the value is a # dict with an arbitrary 'secret_key' and a 'url'. THIRD_PARTY_AUTH_CUSTOM_AUTH_FORMS = config( "THIRD_PARTY_AUTH_CUSTOM_AUTH_FORMS", default={}, formatter=json.loads ) ##### OAUTH2 Provider ############## if FEATURES.get("ENABLE_OAUTH2_PROVIDER"): OAUTH_OIDC_ISSUER = config("OAUTH_OIDC_ISSUER", default=None) OAUTH_ENFORCE_SECURE = config("OAUTH_ENFORCE_SECURE", default=True, formatter=bool) OAUTH_ENFORCE_CLIENT_SECURE = config( "OAUTH_ENFORCE_CLIENT_SECURE", default=True, formatter=bool ) ##### ADVANCED_SECURITY_CONFIG ##### ADVANCED_SECURITY_CONFIG = config( "ADVANCED_SECURITY_CONFIG", default={}, formatter=json.loads ) ##### GOOGLE ANALYTICS IDS ##### GOOGLE_ANALYTICS_ACCOUNT = config("GOOGLE_ANALYTICS_ACCOUNT", default=None) GOOGLE_ANALYTICS_LINKEDIN = config("GOOGLE_ANALYTICS_LINKEDIN", default=None) ##### OPTIMIZELY PROJECT ID ##### OPTIMIZELY_PROJECT_ID = config("OPTIMIZELY_PROJECT_ID", default=OPTIMIZELY_PROJECT_ID) #### Course Registration Code length #### REGISTRATION_CODE_LENGTH = config("REGISTRATION_CODE_LENGTH", default=8, formatter=int) # REGISTRATION CODES DISPLAY INFORMATION INVOICE_CORP_ADDRESS = config("INVOICE_CORP_ADDRESS", default=INVOICE_CORP_ADDRESS) INVOICE_PAYMENT_INSTRUCTIONS = config( "INVOICE_PAYMENT_INSTRUCTIONS", default=INVOICE_PAYMENT_INSTRUCTIONS ) # Which access.py permission names to check; # We default this to the legacy permission 'see_exists'. COURSE_CATALOG_VISIBILITY_PERMISSION = config( "COURSE_CATALOG_VISIBILITY_PERMISSION", default=COURSE_CATALOG_VISIBILITY_PERMISSION ) COURSE_ABOUT_VISIBILITY_PERMISSION = config( "COURSE_ABOUT_VISIBILITY_PERMISSION", default=COURSE_ABOUT_VISIBILITY_PERMISSION ) # Enrollment API Cache Timeout ENROLLMENT_COURSE_DETAILS_CACHE_TIMEOUT = config( "ENROLLMENT_COURSE_DETAILS_CACHE_TIMEOUT", default=60, formatter=int ) # PDF RECEIPT/INVOICE OVERRIDES PDF_RECEIPT_TAX_ID = config("PDF_RECEIPT_TAX_ID", default=PDF_RECEIPT_TAX_ID) PDF_RECEIPT_FOOTER_TEXT = config( "PDF_RECEIPT_FOOTER_TEXT", default=PDF_RECEIPT_FOOTER_TEXT ) PDF_RECEIPT_DISCLAIMER_TEXT = config( "PDF_RECEIPT_DISCLAIMER_TEXT", default=PDF_RECEIPT_DISCLAIMER_TEXT ) PDF_RECEIPT_BILLING_ADDRESS = config( "PDF_RECEIPT_BILLING_ADDRESS", default=PDF_RECEIPT_BILLING_ADDRESS ) PDF_RECEIPT_TERMS_AND_CONDITIONS = config( "PDF_RECEIPT_TERMS_AND_CONDITIONS", default=PDF_RECEIPT_TERMS_AND_CONDITIONS ) PDF_RECEIPT_TAX_ID_LABEL = config( "PDF_RECEIPT_TAX_ID_LABEL", default=PDF_RECEIPT_TAX_ID_LABEL ) PDF_RECEIPT_LOGO_PATH = config("PDF_RECEIPT_LOGO_PATH", default=PDF_RECEIPT_LOGO_PATH) PDF_RECEIPT_COBRAND_LOGO_PATH = config( "PDF_RECEIPT_COBRAND_LOGO_PATH", default=PDF_RECEIPT_COBRAND_LOGO_PATH ) PDF_RECEIPT_LOGO_HEIGHT_MM = config( "PDF_RECEIPT_LOGO_HEIGHT_MM", default=PDF_RECEIPT_LOGO_HEIGHT_MM, formatter=int ) PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM = config( "PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM", default=PDF_RECEIPT_COBRAND_LOGO_HEIGHT_MM, formatter=int, ) if ( FEATURES.get("ENABLE_COURSEWARE_SEARCH") or FEATURES.get("ENABLE_DASHBOARD_SEARCH") or FEATURES.get("ENABLE_COURSE_DISCOVERY") or FEATURES.get("ENABLE_TEAMS") ): # Use ElasticSearch as the search engine herein SEARCH_ENGINE = "search.elastic.ElasticSearchEngine" ELASTIC_SEARCH_CONFIG = config( "ELASTIC_SEARCH_CONFIG", default=[{}], formatter=json.loads ) # Facebook app FACEBOOK_API_VERSION = config("FACEBOOK_API_VERSION", default=None) FACEBOOK_APP_SECRET = config("FACEBOOK_APP_SECRET", default=None) FACEBOOK_APP_ID = config("FACEBOOK_APP_ID", default=None) XBLOCK_SETTINGS = config("XBLOCK_SETTINGS", default={}, formatter=json.loads) XBLOCK_SETTINGS.setdefault("VideoDescriptor", {})["licensing_enabled"] = FEATURES.get( "LICENSING", False ) XBLOCK_SETTINGS.setdefault("VideoModule", {})["YOUTUBE_API_KEY"] = config( "YOUTUBE_API_KEY", default=YOUTUBE_API_KEY ) ##### CDN EXPERIMENT/MONITORING FLAGS ##### CDN_VIDEO_URLS = config("CDN_VIDEO_URLS", default=CDN_VIDEO_URLS) ONLOAD_BEACON_SAMPLE_RATE = config( "ONLOAD_BEACON_SAMPLE_RATE", default=ONLOAD_BEACON_SAMPLE_RATE ) ##### ECOMMERCE API CONFIGURATION SETTINGS ##### ECOMMERCE_PUBLIC_URL_ROOT = config( "ECOMMERCE_PUBLIC_URL_ROOT", default=ECOMMERCE_PUBLIC_URL_ROOT ) ECOMMERCE_API_URL = config("ECOMMERCE_API_URL", default=ECOMMERCE_API_URL) ECOMMERCE_API_TIMEOUT = config( "ECOMMERCE_API_TIMEOUT", default=ECOMMERCE_API_TIMEOUT, formatter=int ) ECOMMERCE_SERVICE_WORKER_USERNAME = config( "ECOMMERCE_SERVICE_WORKER_USERNAME", default=ECOMMERCE_SERVICE_WORKER_USERNAME ) ECOMMERCE_API_TIMEOUT = config("ECOMMERCE_API_TIMEOUT", default=ECOMMERCE_API_TIMEOUT) ECOMMERCE_API_SIGNING_KEY = config( "ECOMMERCE_API_SIGNING_KEY", default=ECOMMERCE_API_SIGNING_KEY ) ##### Custom Courses for EdX ##### if FEATURES.get("CUSTOM_COURSES_EDX"): INSTALLED_APPS += ("lms.djangoapps.ccx",) FIELD_OVERRIDE_PROVIDERS += ( "lms.djangoapps.ccx.overrides.CustomCoursesForEdxOverrideProvider", ) CCX_MAX_STUDENTS_ALLOWED = config( "CCX_MAX_STUDENTS_ALLOWED", default=CCX_MAX_STUDENTS_ALLOWED ) ##### Individual Due Date Extensions ##### if FEATURES.get("INDIVIDUAL_DUE_DATES"): FIELD_OVERRIDE_PROVIDERS += ( "courseware.student_field_overrides.IndividualStudentOverrideProvider", ) ##### Self-Paced Course Due Dates ##### FIELD_OVERRIDE_PROVIDERS += ( "courseware.self_paced_overrides.SelfPacedDateOverrideProvider", ) # PROFILE IMAGE CONFIG PROFILE_IMAGE_BACKEND = config("PROFILE_IMAGE_BACKEND", default=PROFILE_IMAGE_BACKEND) PROFILE_IMAGE_SECRET_KEY = config( "PROFILE_IMAGE_SECRET_KEY", default=PROFILE_IMAGE_SECRET_KEY ) PROFILE_IMAGE_MAX_BYTES = config( "PROFILE_IMAGE_MAX_BYTES", default=PROFILE_IMAGE_MAX_BYTES, formatter=int ) PROFILE_IMAGE_MIN_BYTES = config( "PROFILE_IMAGE_MIN_BYTES", default=PROFILE_IMAGE_MIN_BYTES, formatter=int ) PROFILE_IMAGE_DEFAULT_FILENAME = "images/profiles/default" # EdxNotes config EDXNOTES_PUBLIC_API = config("EDXNOTES_PUBLIC_API", default=EDXNOTES_PUBLIC_API) EDXNOTES_INTERNAL_API = config("EDXNOTES_INTERNAL_API", default=EDXNOTES_INTERNAL_API) ##### Credit Provider Integration ##### CREDIT_PROVIDER_SECRET_KEYS = config( "CREDIT_PROVIDER_SECRET_KEYS", default={}, formatter=json.loads ) ##################### LTI Provider ##################### if FEATURES.get("ENABLE_LTI_PROVIDER"): INSTALLED_APPS += ("lti_provider",) LTI_USER_EMAIL_DOMAIN = config("LTI_USER_EMAIL_DOMAIN", default="lti.example.com") # For more info on this, see the notes in common.py LTI_AGGREGATE_SCORE_PASSBACK_DELAY = config( "LTI_AGGREGATE_SCORE_PASSBACK_DELAY", default=LTI_AGGREGATE_SCORE_PASSBACK_DELAY ) ##################### Credit Provider help link #################### CREDIT_HELP_LINK_URL = config("CREDIT_HELP_LINK_URL", default=CREDIT_HELP_LINK_URL) #### JWT configuration #### JWT_ISSUER = config("JWT_ISSUER", default=JWT_ISSUER) JWT_EXPIRATION = config("JWT_EXPIRATION", default=JWT_EXPIRATION) ################# PROCTORING CONFIGURATION ################## PROCTORING_BACKEND_PROVIDER = config( "PROCTORING_BACKEND_PROVIDER", default=PROCTORING_BACKEND_PROVIDER ) PROCTORING_SETTINGS = config( "PROCTORING_SETTINGS", default=PROCTORING_SETTINGS, formatter=json.loads ) ################# MICROSITE #################### MICROSITE_CONFIGURATION = config( "MICROSITE_CONFIGURATION", default={}, formatter=json.loads ) MICROSITE_ROOT_DIR = path(config("MICROSITE_ROOT_DIR", default="")) # Cutoff date for granting audit certificates if config("AUDIT_CERT_CUTOFF_DATE", default=None): AUDIT_CERT_CUTOFF_DATE = dateutil.parser.parse( config("AUDIT_CERT_CUTOFF_DATE", default=AUDIT_CERT_CUTOFF_DATE) ) ################ CONFIGURABLE LTI CONSUMER ############### # Add just the standard LTI consumer by default, forcing it to open in a new window and ask # the user before sending email and username: LTI_XBLOCK_CONFIGURATIONS = config( "LTI_XBLOCK_CONFIGURATIONS", default=[ { "display_name": "LTI consumer", "pattern": ".*", "hidden_fields": [ "ask_to_send_email", "ask_to_send_username", "new_window", ], "defaults": { "ask_to_send_email": True, "ask_to_send_username": True, "launch_target": "new_window", }, } ], formatter=json.loads, ) LTI_XBLOCK_SECRETS = config("LTI_XBLOCK_SECRETS", default={}, formatter=json.loads) ################################ FUN stuff ################################ SITE_VARIANT = "lms" # Environment's name displayed in FUN's backoffice ENVIRONMENT = config("ENVIRONMENT", default="no set") BASE_ROOT = path("/edx/app/edxapp/") # Fun-apps configuration INSTALLED_APPS += ( "backoffice", "bootstrapform", "ckeditor", "course_dashboard", "course_pages", "courses_api", "courses", "easy_thumbnails", "edx_gea", "forum_contributors", "fun_api", "fun_certificates", "fun_instructor", "fun", "funsite", "haystack", "masquerade", "newsfeed", "password_container", "payment_api", "payment", "pure_pagination", "raven.contrib.django.raven_compat", "rest_framework.authtoken", "teachers", "universities", "videoproviders", ) ROOT_URLCONF = "fun.lms.urls" # Related Richie platform url PLATFORM_RICHIE_URL = config("PLATFORM_RICHIE_URL", default=None) # Haystack configuration (default is minimal working configuration) HAYSTACK_CONNECTIONS = config( "HAYSTACK_CONNECTIONS", default={ "default": {"ENGINE": "courses.search_indexes.ConfigurableElasticSearchEngine"} }, formatter=json.loads, ) CKEDITOR_UPLOAD_PATH = "./" CKEDITOR_CONFIGS = { "default": { "toolbar": [ [ "Undo", "Redo", "-", "Bold", "Italic", "Underline", "-", "Link", "Unlink", "Anchor", "-", "Format", "-", "SpellChecker", "Scayt", "-", "Maximize", ], [ "HorizontalRule", "-", "Table", "-", "BulletedList", "NumberedList", "-", "Cut", "Copy", "Paste", "PasteText", "PasteFromWord", "-", "SpecialChar", "-", "Source", ], ], "toolbarCanCollapse": False, "entities": False, "width": 955, "uiColor": "#9AB8F3", }, "news": { # Redefine path where the news images/files are uploaded. This would # better be done at runtime with the 'reverse' function, but # unfortunately there is no way around defining this in the settings # file. "filebrowserUploadUrl": "/news/ckeditor/upload/", "filebrowserBrowseUrl": "/news/ckeditor/browse/", "toolbar_Full": [ [ "Styles", "Format", "Bold", "Italic", "Underline", "Strike", "SpellChecker", "Undo", "Redo", ], ["Image", "Flash", "Table", "HorizontalRule"], ["NumberedList", "BulletedList", "Blockquote", "TextColor", "BGColor"], ["Smiley", "SpecialChar"], ["Source"], ], }, } # ### FUN-APPS SETTINGS ### # This is dist-packages path where all fun-apps are FUN_BASE_ROOT = path(os.path.dirname(pkgutil.get_loader("funsite").filename)) SHARED_ROOT = DATA_DIR / "shared" # Add FUN applications templates directories to MAKO template finder before edX's ones MAKO_TEMPLATES["main"] = [ # overrides template in edx-platform/lms/templates FUN_BASE_ROOT / "funsite/templates/lms", FUN_BASE_ROOT / "funsite/templates", FUN_BASE_ROOT / "course_pages/templates", FUN_BASE_ROOT / "payment/templates", FUN_BASE_ROOT / "course_dashboard/templates", FUN_BASE_ROOT / "newsfeed/templates", FUN_BASE_ROOT / "fun_certificates/templates", ] + MAKO_TEMPLATES["main"] # JS static override DEFAULT_TEMPLATE_ENGINE["DIRS"].append(FUN_BASE_ROOT / "funsite/templates/lms") FUN_SMALL_LOGO_RELATIVE_PATH = "funsite/images/logos/funmooc173.png" FUN_BIG_LOGO_RELATIVE_PATH = "funsite/images/logos/funmoocfp.png" FAVICON_PATH = "fun/images/favicon.ico" # Locale paths # Here we rewrite LOCAL_PATHS to give precedence to our applications above edx-platform's ones, # then we add xblocks which provide translations as there is no native mechanism to handle this # See Xblock i18n: http://www.libremente.eu/2017/12/06/edx-translation/ LOCALIZED_FUN_APPS = [ "backoffice", "course_dashboard", "course_pages", "courses", "fun_api", "fun_certificates", "funsite", "newsfeed", "payment", "universities", "videoproviders", ] LOCALE_PATHS = [FUN_BASE_ROOT / app / "locale" for app in LOCALIZED_FUN_APPS] LOCALE_PATHS.append(REPO_ROOT / "conf/locale") # edx-platform locales LOCALE_PATHS.append(path(pkgutil.get_loader("proctor_exam").filename) / "locale") # -- Certificates CERTIFICATES_DIRECTORY_NAME = "attestations" FUN_LOGO_PATH = FUN_BASE_ROOT / "funsite/static" / FUN_BIG_LOGO_RELATIVE_PATH FUN_ATTESTATION_LOGO_PATH = ( FUN_BASE_ROOT / "funsite/static" / "funsite/images/logos/funmoocattest.png" ) STUDENT_NAME_FOR_TEST_CERTIFICATE = "Test User" # Videofront subtitles cache CACHES["video_subtitles"] = { "BACKEND": "django.core.cache.backends.filebased.FileBasedCache", "KEY_PREFIX": "video_subtitles", "LOCATION": DATA_DIR / "video_subtitles_cache", } # Course image thumbnails FUN_THUMBNAIL_OPTIONS = { "small": {"size": (270, 152), "crop": "smart"}, "big": {"size": (337, 191), "crop": "smart"}, "about": {"size": (730, 412), "crop": "scale"}, "facebook": { "size": (600, 315), "crop": "smart", }, # https://developers.facebook.com/docs/sharing/best-practices } THUMBNAIL_PRESERVE_EXTENSIONS = True THUMBNAIL_EXTENSION = "png" ##### ORA2 ###### ORA2_FILEUPLOAD_BACKEND = "swift" ORA2_SWIFT_KEY = config("ORA2_SWIFT_KEY", default="") ORA2_SWIFT_URL = config("ORA2_SWIFT_URL", default="") # Prefix for uploads of example-based assessment AI classifiers # This can be used to separate uploads for different environments ORA2_FILE_PREFIX = config("ORA2_FILE_PREFIX", default=ORA2_FILE_PREFIX) # Profile image upload PROFILE_IMAGE_BACKEND = { "class": "storages.backends.overwrite.OverwriteStorage", "options": { "location": os.path.join(MEDIA_ROOT, "profile-images/"), "base_url": os.path.join(MEDIA_URL, "profile-images/"), }, } ENABLE_ADWAYS_FOR_COURSES = config( "ENABLE_ADWAYS_FOR_COURSES", default=[], formatter=json.loads ) # Add our v3 CSS and JS files to assets compilation pipeline to make them available in courseware. # On FUN v3 frontend, which do not use edX's templates, those files are loaded # by funsite/templates/funsite/parts/base.html and css/lms-main.css PIPELINE_CSS["style-vendor"]["source_filenames"].append("fun/css/cookie-banner.css") PIPELINE_CSS["style-vendor"]["source_filenames"].append("funsite/css/header.css") PIPELINE_CSS["style-vendor"]["source_filenames"].append("funsite/css/footer.css") # can't find any common group for group in ["base_vendor", "main_vendor"]: PIPELINE_JS[group]["source_filenames"].append("funsite/js/header.js") PIPELINE_JS[group]["source_filenames"].append("fun/js/cookie-banner.js") # Glowbl GLOWBL_LTI_ENDPOINT = config( "GLOWBL_LTI_ENDPOINT", default="http://ltiapps.net/test/tp.php" ) GLOWBL_LTI_KEY = config("GLOWBL_LTI_KEY", default="jisc.ac.uk") GLOWBL_LTI_SECRET = config("GLOWBL_LTI_SECRET", default="secret") GLOWBL_LTI_ID = config("GLOWBL_LTI_ID", default="testtoolconsumer") GLOWBL_LAUNCH_URL = config( "GLOWBL_LAUNCH_URL", default="http://ltiapps.net/test/tp.php" ) GLOWBL_COLL_OPT = config("GLOWBL_COLL_OPT", default="FunMoocJdR") DEFAULT_TEMPLATE_ENGINE["DIRS"].append(FUN_BASE_ROOT / "funsite/templates/lms") DEFAULT_TEMPLATE_ENGINE["OPTIONS"]["context_processors"].append( "fun.context_processor.fun_settings" ) TEMPLATES = [DEFAULT_TEMPLATE_ENGINE] # This force Edx Studio to use our own video provider Xblock on default button FUN_DEFAULT_VIDEO_PLAYER = "libcast_xblock" MIDDLEWARE_CLASSES += ( "fun.middleware.LegalAcceptance", "backoffice.middleware.PathLimitedMasqueradeMiddleware", ) class LazyChoicesSorter(object): def __init__(self, choices): self.choices = choices def __iter__(self): for choice in sorted(self.choices, key=lambda peer: peer[1]): yield choice # These are the allowed subtitle languages, we have the same list on Videofront server # We remove 2 deprecated chinese language codes which do not exist on Django 1.10 VideoFront SUBTITLE_SUPPORTED_LANGUAGES = LazyChoicesSorter( (code, ugettext_lazy(lang)) for code, lang in global_settings.LANGUAGES if code not in ("zh-cn", "zh-tw") ) ANONYMIZATION_KEY = config("ANONYMIZATION_KEY", default="") RAVEN_CONFIG = config("RAVEN_CONFIG", default={"dsn": ""}, formatter=json.loads) ELASTICSEARCH_INDEX_SETTINGS = { "settings": { "analysis": { "filter": { "elision": { "type": "elision", "articles": ["l", "m", "t", "qu", "n", "s", "j", "d"], } }, "analyzer": { "custom_french_analyzer": { "tokenizer": "letter", "filter": [ "asciifolding", "lowercase", "french_stem", "elision", "stop", "word_delimiter", ], } }, } } } FUN_MKTG_URLS = config("FUN_MKTG_URLS", default={}, formatter=json.loads) # Default visibility of student's profile to other students ACCOUNT_VISIBILITY_CONFIGURATION["default_visibility"] = "private" # A user is verified if he has an approved SoftwareSecurePhotoVerification entry # this setting will create a dummy SoftwareSecurePhotoVerification for user in # paybox success callback view. A this point, we think it's better to create a # dummy one than to remove verifying process in edX FUN_ECOMMERCE_DEBUG_NO_NOTIFICATION = config( "FUN_ECOMMERCE_DEBUG_NO_NOTIFICATION", default=False, formatter=bool ) ECOMMERCE_NOTIFICATION_URL = config("ECOMMERCE_NOTIFICATION_URL", default=None) PAYMENT_ADMIN = "<EMAIL>" # List of pattern definitions to automatically add verified users to a cohort # If value is [] this feature is disabled # Otherwise this setting is a list of # tuple values (r"<course id regex>", "<cohort name>"). # e.g: if you want to enable this feature for a particular course you can set # this setting to # [ # (r"<course id>", "cohort name"), # ] VERIFIED_COHORTS = config("VERIFIED_COHORTS", default=[]) # Force Edx to use `libcast_xblock` as default video player # in the studio (big green button) and if any xblock is called `video` XBLOCK_SELECT_FUNCTION = prefer_fun_video if "sentry" in LOGGING.get("handlers"): LOGGING["handlers"]["sentry"]["environment"] = "development" # Configure gelf handler to listen on graylog server LOGGING["loggers"][""]["handlers"].append("gelf") LOGGING["loggers"]["tracking"]["handlers"].append("gelf") LOGGING["handlers"]["gelf"] = { "level": "DEBUG", "class": "djehouty.libgelf.handlers.GELFTCPSocketHandler", "host": "graylog", "port": 12201, "null_character": True, } DEBUG = True REQUIRE_DEBUG = True EMAIL_BACKEND = config( "EMAIL_BACKEND", default="django.core.mail.backends.console.EmailBackend" ) PIPELINE_ENABLED = False STATICFILES_STORAGE = "openedx.core.storage.DevelopmentStorage" ALLOWED_HOSTS = ["*"] FEATURES["AUTOMATIC_AUTH_FOR_TESTING"] = True # ORA2 fileupload ORA2_FILEUPLOAD_BACKEND = "filesystem" ORA2_FILEUPLOAD_ROOT = os.path.join(SHARED_ROOT, "openassessment_submissions") ORA2_FILEUPLOAD_CACHE_ROOT = os.path.join( SHARED_ROOT, "openassessment_submissions_cache" ) AUTHENTICATION_BACKENDS = config( "AUTHENTICATION_BACKENDS", default=["django.contrib.auth.backends.ModelBackend"], formatter=json.loads )

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catkin_ws/src/o2as_routines/scripts/kitting.py

DevwratJoshi/ur-o2as

0

1615468

#!/usr/bin/env python import sys import copy import rospy import geometry_msgs.msg import tf_conversions import tf from math import pi import numpy as np from collections import namedtuple from o2as_msgs.srv import * import actionlib from o2as_msgs.msg import * # from o2as_usb_relay.srv import * from graspability_estimation.srv import * # from o2as_graspability_estimation.srv import * from std_msgs.msg import Bool from o2as_routines.base import O2ASBaseRoutines import rospkg rp = rospkg.RosPack() import csv import os import random import math from geometry_msgs.msg import Polygon, Point32 from PIL import Image as ImagePIL from PIL import ImageDraw as ImageDrawPIL from sensor_msgs.msg import Image from cv_bridge import CvBridge, CvBridgeError import cv2 LOG_LEVEL = log_level = rospy.DEBUG # LOG_LEVEL = log_level = rospy.INFO CroppedArea = namedtuple("CroppedArea", ["min_row", "max_row", "min_col", "max_col"]) class kitting_order_entry(): """ Object that tracks if its order was fulfilled, and the number of attempts spent on it. """ def __init__(self, part_id, set_number, number_in_set, bin_name, target_frame, ee_to_use, item_name, dropoff_height, bin_is_inclined): self.part_id = part_id # The part id self.set_number = set_number self.number_in_set = number_in_set self.bin_name = bin_name self.target_frame = target_frame self.ee_to_use = ee_to_use self.item_name = item_name self.dropoff_height = dropoff_height self.bin_is_inclined = bin_is_inclined self.attempts = 0 self.fulfilled = False self.in_feeder = False def clamp(n, minn, maxn): """Constrain a number n to the interval [minn, maxn]""" return min(max(n, minn), maxn) class KittingClass(O2ASBaseRoutines): """ This contains the routine used to run the kitting task. See base.py for shared convenience functions. """ def __init__(self): super(KittingClass, self).__init__() #subscribe to gripper position self._inner_gripper_pos_sub = rospy.Subscriber("o2as_precision_gripper/inner_gripper_motor_pos", std_msgs.msg.Int32, self.update_motorPosition) self._motorPos = -1 # services self._feeder_srv = rospy.ServiceProxy("o2as_usb_relay/set_power", o2as_msgs.srv.SetPower) self._suction = actionlib.SimpleActionClient('o2as_fastening_tools/suction_control', SuctionControlAction) self._suctioned = False self._suction_state = rospy.Subscriber("suction_tool/screw_suctioned", Bool, self._suction_state_callback) # self._suction.wait_for_server() self._search_grasp = rospy.ServiceProxy("search_grasp", SearchGrasp) self.search_grasp_client = actionlib.SimpleActionClient("search_grasp_phoxi", o2as_msgs.msg.SearchGraspPhoxiAction) # action self.blob_detection_client = actionlib.SimpleActionClient('blob_detection_action', o2as_msgs.msg.blobDetectionAction) # Image Subscriber for monitoring self.img_blob_topic = "o2as_blob_detection/img_w_blob" #self.img_blob_sub = rospy.Subscriber(self.img_blob_topic, Image, self.image_blob_callback) # Image Publisher for monitoring self.bridge = CvBridge() self.img_inner_pick_topic = "o2as_monitor/vision_res" self.img_inner_pick_pub = rospy.Publisher(self.img_inner_pick_topic, Image, latch=True, queue_size=10) self.current_img_w_goal = Image() self.current_img_w_blob = Image() #for gazebo # self.cameraMatK = np.array([[554.3827128226441, 0.0, 320.5], # [0.0, 554.3827128226441, 240.5], # [0.0, 0.0, 1.0]]) #for ID Realsense on robot ID61*41 width 640 height 360 self.cameraMatK = np.array([[461.605774, 0.0, 318.471497], [0.0, 461.605804, 180.336258], [0.0, 0.0, 1.0]]) #For phoxi in omron self.cameraPhoxiMatK = np.array([[2226.52477235, 0.0, 978.075053258], [0.0, 2226.52477235, 775.748572147], [0.0, 0.0, 1.0]]) self.initial_setup() rospy.sleep(.5) # Initialize debug monitor self.start_task_timer() self.log_to_debug_monitor(text="Init", category="task") self.log_to_debug_monitor(text="Init", category="subtask") self.log_to_debug_monitor(text="Init", category="operation") rospy.loginfo("Kitting class started up!") def update_motorPosition(self, msg): self._motorPos = msg.data def initial_setup(self): ### First, set up internal parameters ### Then, read order file and create the list to iterate through # Used for validating grasp poses. This measures only the inside borders of the bin. self.bin_1_width = .11 self.bin_1_length = .11 self.bin_2_width = .16 self.bin_2_length = .09 self.bin_3_width = .20 self.bin_3_length = .16 self.initial_phoxi_image_recorded = False self.max_candidates_from_phoxi = 3 # Used to prepare the suction place poses (because the UR linear driver goes through a singularity sometimes) self.joints_above_set_1_tray_2 = [0.6957670450210571, -1.5090416113482874, 1.9396471977233887, -0.4243395964251917, 0.7138931751251221, -3.1503987948047083] self.joints_above_set_2_tray_2 = [1.195457935333252, -1.6689851919757288, 2.0958428382873535, -0.4254062811480921, 1.2131953239440918, -3.146900002156393] self.joints_above_set_3_tray_2 = [0.550778865814209, -1.4439471403705042, 1.867344856262207, -0.42732316652406865, -1.0016759077655237, -3.134343926106588] self.joints_above_set_1_tray_1 = [1.333075761795044, -1.8985555807696741, 2.2680954933166504, -0.3765481154071253, 2.572127342224121, -3.1496201197253626] self.grasp_strategy = { "part_4" : "suction", "part_5" : "suction", "part_6" : "robotiq_gripper", "part_7" : "suction", "part_8" : "suction", "part_9" : "precision_gripper_from_inside", "part_10": "precision_gripper_from_inside", "part_11": "suction", # Can be one of the grippers "part_12": "suction", # Can be precision_gripper_from_outside in inclined bin "part_13": "suction", # Should be precision_gripper_from_inside "part_14": "precision_gripper_from_outside", "part_15": "precision_gripper_from_inside", "part_16": "precision_gripper_from_inside", "part_17": "precision_gripper_from_outside", "part_18": "precision_gripper_from_outside"} # How high the end effector should hover over the tray when delivering the item self.dropoff_heights = { "part_4" : 0.03, "part_5" : 0.02, "part_6" : 0.01, "part_7" : 0.04, "part_8" : 0.01, "part_9" : 0.005, "part_10": 0.005, "part_11": 0.01, "part_12": 0.01, "part_13": 0.01, "part_14": 0.005, "part_15": 0.005, "part_16": 0.005, "part_17": 0.005, "part_18": 0.005} # NEEDS MANUAL CALIBRATION self.precision_gripper_pick_heights = { "part_9" : 0.00, "part_10": 0.00, "part_14": 0.00, "part_15": 0.00, "part_16": 0.00, "part_17": 0.00, "part_18": 0.00} # How high the end effector should insert the bin when pick up the item. self.insert_offsets = { "part_4" : 0.000, "part_5" : 0.000, "part_6" : 0.002, "part_7" : 0.000, "part_8" : 0.000, "part_9" : 0.003, "part_10": 0.002, "part_11": 0.000, "part_12": 0.000, "part_13": 0.000, "part_14": 0.000, "part_15": 0.002, "part_16": 0.0005, "part_17": 0.0035, "part_18": 0.0025 } self.grasp_candidates = { 4 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 5 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 6 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 7 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 8 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 9 : { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 10: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 11: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 12: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 13: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 14: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 15: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 16: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 17: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] }, 18: { "pick_was_successful": False, "vision_was_attempted": False, "positions": [] } } # self.part_bin_list = { # "part_4" : "bin2_1", # "part_5" : "bin2_1", # "part_6" : "bin3_1", # "part_8" : "bin2_2", # "part_9" : "bin1_1", # "part_10" : "bin1_1", # "part_11" : "bin2_3", # "part_12" : "bin1_2", # "part_13" : "bin2_4", # "part_14" : "bin1_1", # "part_15" : "bin1_2", # "part_16" : "bin1_3", # "part_17" : "bin1_4", # "part_18" : "bin1_5"} self.part_bin_list = rospy.get_param("part_bin_list") self.part_position_in_tray = { "part_4" : "tray_1_partition_4", "part_5" : "tray_2_partition_6", "part_6" : "tray_1_partition_3", "part_7" : "tray_1_partition_2", "part_8" : "tray_2_partition_1", "part_9" : "tray_2_partition_4", "part_10": "tray_2_partition_7", "part_11": "tray_1_partition_1", "part_12": "tray_2_partition_3", "part_13": "tray_1_partition_5", "part_14": "tray_2_partition_2", "part_15": "tray_2_partition_5", "part_16": "tray_2_partition_8", "part_17": "tray_2_this_is_a_screw_so_should_be_ignored", "part_18": "tray_2_this_is_a_screw_so_should_be_ignored" } # This can be copied from kitting_part_bin_list_auto.yaml # Possible values: "left", "right" # "left" means the right side of the bin is higher than the left. It leans to the left. self.bin_for_this_part_is_inclined = { "part_4" : False, # motor "part_5" : False, # small pulley "part_6" : False, # belt "part_7" : False, # bearing "part_8" : False, # shaft "part_9" : False, # end cap "part_10" : False, # output spacer "part_11" : False, # output pulley "part_12" : False, # idler spacer "part_13" : False, # idler pulley/bearing "part_14" : False, # idler pin "part_15" : False, # m6 nut "part_16" : False, # m6 washer "part_17" : False, # m4 screw "part_18" : False} # m3 screw # The "from_behind" orientation is slightly turned to avoid the robot locking up self.suction_orientation_from_behind = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi*10/180)) self.suction_orientation_left_bins = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/4)) self.suction_orientation_right_bins = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/4)) self.suction_orientation_from_45 = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/4)) self.suction_orientation_from_side = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, -pi/2)) self.downward_orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, 0)) self.downward_orientation_2 = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi)) ### Create the item list self.order_list_raw, self.ordered_items = self.read_order_file() rospy.loginfo("Received order list:") rospy.loginfo(self.order_list_raw) ### Sort by grasp strategy self.screw_items = [] self.screws = dict() self.screws["m3"] = [] self.screws["m4"] = [] self.suction_items = [] self.robotiq_gripper_items = [] self.precision_gripper_items = [] for order_item in self.ordered_items: if order_item.part_id in [17,18]: rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of screw items") self.screw_items.append(order_item) if order_item.part_id == 17: self.screws["m4"].append(order_item) elif order_item.part_id == 18: self.screws["m3"].append(order_item) elif order_item.ee_to_use == "suction": rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of suction items") self.suction_items.append(order_item) elif order_item.ee_to_use == "robotiq_gripper": rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of robotiq_gripper items") self.robotiq_gripper_items.append(order_item) elif "precision_gripper" in order_item.ee_to_use: rospy.loginfo("Appended item nr." + str(order_item.number_in_set) + " from set " + str(order_item.set_number) + " (part ID:" + str(order_item.part_id) + ") to list of precision gripper items") self.precision_gripper_items.append(order_item) def read_order_file(self): """Read in the order file, return kitting_list and order_entry_list. kitting_list is a list of lists with only the part IDs that are ordered. order_entry_list is a list of kitting_entry_item objects.""" order_entry_list = [] kitting_list = [] kitting_list.append([]) kitting_list.append([]) kitting_list.append([]) with open(os.path.join(rp.get_path("o2as_scene_description"), "config", "kitting_order_file.csv"), 'r') as f: reader = csv.reader(f) header = next(reader) # [0, 1, 2, 3, 4] = ["Set", "No.", "ID", "Name", "Note"] for data in reader: kitting_list[int(data[0])-1].append(int(data[2])) order_entry_list.append(kitting_order_entry(part_id=int(data[2]), set_number=int(data[0]), number_in_set=int(data[1]), bin_name=self.part_bin_list["part_" + data[2]], target_frame="set_" + data[0] + "_" + self.part_position_in_tray["part_" + data[2]], ee_to_use=self.grasp_strategy["part_" + data[2]], item_name=data[4], dropoff_height=self.dropoff_heights["part_" + data[2]], bin_is_inclined=self.bin_for_this_part_is_inclined["part_" + data[2]])) return kitting_list, order_entry_list ################ ----- Routines ################ ################ def pick(self, robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height = 0.05, special_pick = False): # If the pick uses suction, pass it to the local function. Otherwise to the parent class. if gripper_command == "suction": object_pose.pose.position.z += approach_height self.move_lin(robot_name, object_pose, speed_fast, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height picked = self.pick_using_dual_suction_gripper(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z += approach_height self.move_lin(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height if self._suctioned: object_pose.pose.position.z += approach_height + .05 self.move_lin(robot_name, object_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") object_pose.pose.position.z -= approach_height + .05 return self._suctioned else: return super(KittingClass, self).pick(robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height, special_pick) def place(self, robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height = 0.05, lift_up_after_place = True): # If the place uses suction, pass it to the local function. Otherwise to the parent class. if gripper_command == "suction": above_place_pose = copy.deepcopy(object_pose) place_pose = copy.deepcopy(object_pose) above_place_pose.pose.position.z += approach_height + grasp_height place_pose.pose.position.z += grasp_height + .03 # rospy.loginfo("Going above tray.") # self.move_lin(robot_name, above_place_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") rospy.loginfo("Placing in tray.") self.move_lin(robot_name, place_pose, speed_slow, end_effector_link="b_bot_suction_tool_tip_link") self.suck(turn_suction_on=False, eject=True) rospy.sleep(2.0) self.suck(turn_suction_on=False, eject=False) self.move_lin(robot_name, above_place_pose, speed_fast, end_effector_link="b_bot_suction_tool_tip_link") return True else: return super(KittingClass, self).place(robot_name, object_pose, grasp_height, speed_fast, speed_slow, gripper_command, approach_height, lift_up_after_place) def set_feeder_power(self, turn_on=True): if not self.use_real_robot: return True req = o2as_msgs.srv.SetPowerRequest() req.port = 2 req.on = turn_on res = self._feeder_srv.call(req) return res.success def _suction_state_callback(self, msg): self._suctioned = msg.data def suck(self, turn_suction_on=False, eject=False): # Judge success or fail using pressure status. if not self.use_real_robot: return True goal = SuctionControlGoal() goal.fastening_tool_name = "suction_tool" goal.turn_suction_on = turn_suction_on goal.eject_screw = False self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) if not turn_suction_on: goal.eject_screw = True self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) goal.eject_screw = False self._suction.send_goal(goal) self._suction.wait_for_result(rospy.Duration(2.0)) return self._suction.get_result() def pick_using_dual_suction_gripper(self, group_name, pose_goal_stamped, speed, end_effector_link="b_bot_suction_tool_tip_link"): rospy.loginfo("Try picking up by suction.") res = self.suck(True) if not res: return False rospy.loginfo("Pushing into the bin.") if self.use_real_robot: self.do_linear_push("b_bot", force=5.0, wait=True, direction="Y+", max_approach_distance=.092, forward_speed=.04) self.confirm_to_proceed("Went to the target. Press enter") # The max_approach_distance parameter affects how far the robot goes into the bin res = True else: res = self.move_lin(group_name, pose_goal_stamped, speed, end_effector_link=end_effector_link) return res def naive_pick(self, group_name, bin_id, speed_fast = 1.0, speed_slow = 1.0, approach_height = 0.05, bin_eff_height = 0.07, bin_eff_xoff = 0, bin_eff_yoff = 0, bin_eff_deg_angle = 0,end_effector_link = ""): #Place gripper above bin goal_pose_above = geometry_msgs.msg.PoseStamped() goal_pose_above.header.frame_id = bin_id goal_pose_above.pose.position.x = bin_eff_xoff goal_pose_above.pose.position.y = bin_eff_yoff goal_pose_above.pose.position.z = bin_eff_height goal_pose_above.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2 , 0)) res = self.move_lin(group_name, goal_pose_above, speed=speed_fast, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to the target.") return False #Open the gripper self.send_gripper_command(gripper= "precision_gripper_inner", command="close") self.precision_gripper_inner_open() rospy.sleep(1) #Descend rospy.loginfo("Descend on target.") goal_pose_descend = copy.deepcopy(goal_pose_above) goal_pose_descend.pose.position.z = goal_pose_descend.pose.position.z - approach_height res = self.move_lin(group_name, goal_pose_descend, speed=speed_slow, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to above the target bin.") return False #Close the gripper self.send_gripper_command(gripper= "precision_gripper_inner", command="open") self.precision_gripper_inner_close() rospy.sleep(1) #Ascend rospy.loginfo("Ascend with target.") goal_pose_ascend = copy.deepcopy(goal_pose_descend) goal_pose_ascend.pose.position.z = goal_pose_ascend.pose.position.z + approach_height res = self.move_lin(group_name, goal_pose_ascend, speed=speed_slow, end_effector_link=end_effector_link) if not res: rospy.loginfo("Couldn't go to above the target bin.") return False def pick_screw_with_precision_gripper(self, bin_id, screw_size, speed_fast = 1.0, speed_slow = .1, approach_height = 0.05, bin_eff_height = 0.07, bin_eff_deg_angle = 0,end_effector_link = ""): success_pick = False #Close the gripper and save the motor position self.send_gripper_command(gripper= "precision_gripper_inner", command="open") rospy.sleep(0.1) close_pos = rospy.get_param("/precision_gripper_server/inner_close_motor_position", 2222) posx = 0 posy = 0 posz = 0.08 while (not success_pick): pick_pose = geometry_msgs.msg.PoseStamped() pick_pose.header.frame_id = bin_id pick_pose.pose.orientation = self.downward_orientation gripper_command = "inner_gripper_from_outside" self.pick("a_bot", pick_pose, 0.0, speed_fast = 1.0, speed_slow = 0.15, gripper_command=gripper_command, approach_height = 0.05) #Check posture of the screw rospy.loginfo("Begin check motion") over_bin_3_joint_pose = [0.5639523868982476, -1.2023834734104668, 2.084380077110544, -4.115980903386012, -1.350262946004677, 1.5910085738144437] self.move_joints("a_bot", over_bin_3_joint_pose, speed=.5, force_ur_script=self.use_real_robot) over_bin_3_inclined_joint_pose = [0.5646427393623301, -1.202333924982511, 2.040723585395901, -4.197616886811121, -1.3550737620026068, 1.6180429123653095] self.move_joints("a_bot", over_bin_3_inclined_joint_pose, speed=.5, force_ur_script=self.use_real_robot) #Open just a bit the gripper if(screw_size == 4): open_range = 80 elif(screw_size == 3): open_range = 60 else: rospy.logerror("Screw size is wrong") open_range = 0 rospy.loginfo("begin inner open slightly") self.precision_gripper_inner_open_slightly(open_range) rospy.loginfo("ending inner open slightly") rospy.sleep(1.0) #Close the gripper fully self.send_gripper_command(gripper= "precision_gripper_inner", command="close") rospy.sleep(1.0) #Check the motor position success_pick = True if(abs(self._motorPos - close_pos) > 25 ): rospy.loginfo("Screw was picked successfully. self._motorPos = " + str(self._motorPos)) success_pick = True else: rospy.loginfo("Did not pick screw") return False if not self.use_real_robot: rospy.loginfo("Assume success for the simulation") success_pick = True above_handover_joint_pose = [1.3983707427978516, -1.343994442616598, 2.048433780670166, -4.056087795888082, -1.9765618483172815, 1.4695862531661987] self.move_joints("a_bot", above_handover_joint_pose, speed=.3, force_ur_script=self.use_real_robot) self.go_to_named_pose("screw_handover", "a_bot", force_ur_script=self.use_real_robot) self.precision_gripper_inner_open_slightly(open_range) return True def mask_bin(self, group_name, bin_id): mask_margin = 0.0 point_top1 = geometry_msgs.msg.PointStamped() point_top1.header.frame_id = str(bin_id)+"_bottom_front_right_corner" point_top1.point = geometry_msgs.msg.Point(-mask_margin, -mask_margin, 0.0) point_top2 = geometry_msgs.msg.PointStamped() point_top2.header.frame_id = str(bin_id)+"_bottom_back_right_corner" point_top2.point = geometry_msgs.msg.Point(mask_margin, -mask_margin, 0.0) point_top3 = geometry_msgs.msg.PointStamped() point_top3.header.frame_id = str(bin_id)+"_bottom_back_left_corner" point_top3.point = geometry_msgs.msg.Point(mask_margin, mask_margin, 0.0) point_top4 = geometry_msgs.msg.PointStamped() point_top4.header.frame_id = str(bin_id)+"_bottom_front_left_corner" point_top4.point = geometry_msgs.msg.Point(-mask_margin, mask_margin, 0.0) #TODO change the fisheye from to the depth frame in casse of offset. but fisheye should e ok since the two images are aligned (depth and rgb) after the real sense node point_top1_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top1).point point_top2_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top2).point point_top3_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top3).point point_top4_cam = self.listener.transformPoint("a_phoxi_m_sensor", point_top4).point #print("point_top1_cam") #print(point_top1_cam) #print("point_top2_cam") #print(point_top2_cam) #print("point_top3_cam") #print(point_top3_cam) #print("point_top4_cam") #print(point_top4_cam) #point_test_center_cam = geometry_msgs.msg.Point(0, 0, 0.4) #print(point_test_center_cam) #TODO project the 4 points in the depth plane (which projection matrix to use from the camera) #projection matrix #554.3827128226441, 0.0, 320.5, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 1.0 # #P: [554.3827128226441, 0.0, 320.5, -38.80678989758509, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 0.0, 1.0, 0.0] #TODO take the parameters from the /camera_info topic instead point_top1_cam_np = np.array([point_top1_cam.x, point_top1_cam.y, point_top1_cam.z]) point_top2_cam_np = np.array([point_top2_cam.x, point_top2_cam.y, point_top2_cam.z]) point_top3_cam_np = np.array([point_top3_cam.x, point_top3_cam.y, point_top3_cam.z]) point_top4_cam_np = np.array([point_top4_cam.x, point_top4_cam.y, point_top4_cam.z]) #used to test the projection #point_test_center_cam_np = np.array([point_test_center_cam.x, point_test_center_cam.y, point_test_center_cam.z]) #need the camera parameter of the phoxy point_top1_img_np = self.cameraPhoxiMatK.dot(point_top1_cam_np) point_top2_img_np = self.cameraPhoxiMatK.dot(point_top2_cam_np) point_top3_img_np = self.cameraPhoxiMatK.dot(point_top3_cam_np) point_top4_img_np = self.cameraPhoxiMatK.dot(point_top4_cam_np) #point_test_center_img_np = self.cameraMatK.dot(point_test_center_cam_np) #print(point_top1_img_np) #print(point_top2_img_np) #print(point_top3_img_np) #print(point_top4_img_np) #print(point_test_center_img_np) in_polygon = Polygon() in_polygon.points = [Point32(point_top1_img_np[0]/point_top1_img_np[2],point_top1_img_np[1]/point_top1_img_np[2],0), Point32(point_top2_img_np[0]/point_top2_img_np[2],point_top2_img_np[1]/point_top2_img_np[2],0), Point32(point_top3_img_np[0]/point_top3_img_np[2],point_top3_img_np[1]/point_top3_img_np[2],0), Point32(point_top4_img_np[0]/point_top4_img_np[2],point_top4_img_np[1]/point_top4_img_np[2],0)] polygon = [ (in_polygon.points[0].x,in_polygon.points[0].y), (in_polygon.points[1].x,in_polygon.points[1].y), (in_polygon.points[2].x,in_polygon.points[2].y), (in_polygon.points[3].x,in_polygon.points[3].y)] mask_img = ImagePIL.new('L', (2064,1544), 0) ImageDrawPIL.Draw(mask_img).polygon(polygon, outline = 1, fill = 255) mask_image_np = np.array(mask_img) namefile = "mask_phoxi_"+str(bin_id)+".png" mask_img.save(namefile,'PNG') def view_bin(self, group_name, bin_id, part_id, speed_fast = 1.0, speed_slow = 1.0, bin_eff_height = 0.2, bin_eff_xoff = 0, bin_eff_deg_angle = 20,end_effector_link = ""): # TODO: adjust the x,z and end effector orientatio for optimal view of the bin to use with the \search_grasp service goal_pose = geometry_msgs.msg.PoseStamped() goal_pose.header.frame_id = bin_id goal_pose.pose.position.x = bin_eff_xoff - .1 goal_pose.pose.position.y = -.05 goal_pose.pose.position.z = bin_eff_height - .1 goal_pose.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2, 0)) res = self.move_lin(group_name, goal_pose, speed_slow, end_effector_link="") if not res: rospy.loginfo("Couldn't go to the target.") #TODO Problem with gazebo controller while controlling the robot with movelin return False #TODO Ensure that the the motion is finished before generating the mask. #TODO not sure if the sleep is necessary is move_lin wait for the motion to be finished? rospy.sleep(2) mask_margin = 0.0 point_top1 = geometry_msgs.msg.PointStamped() point_top1.header.frame_id = str(bin_id)+"_bottom_front_right_corner" point_top1.point = geometry_msgs.msg.Point(-mask_margin, -mask_margin, 0.0) point_top2 = geometry_msgs.msg.PointStamped() point_top2.header.frame_id = str(bin_id)+"_bottom_back_right_corner" point_top2.point = geometry_msgs.msg.Point(mask_margin, -mask_margin, 0.0) point_top3 = geometry_msgs.msg.PointStamped() point_top3.header.frame_id = str(bin_id)+"_bottom_back_left_corner" point_top3.point = geometry_msgs.msg.Point(mask_margin, mask_margin, 0.0) point_top4 = geometry_msgs.msg.PointStamped() point_top4.header.frame_id = str(bin_id)+"_bottom_front_left_corner" point_top4.point = geometry_msgs.msg.Point(-mask_margin, mask_margin, 0.0) #TODO change the fisheye from to the depth frame in casse of offset. but fisheye should e ok since the two images are aligned (depth and rgb) after the real sense node point_top1_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top1).point point_top2_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top2).point point_top3_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top3).point point_top4_cam = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", point_top4).point #point_test_center_cam = geometry_msgs.msg.Point(0, 0, 0.4) #print(point_test_center_cam) #TODO project the 4 points in the depth plane (which projection matrix to use from the camera) #projection matrix #554.3827128226441, 0.0, 320.5, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 1.0 # #P: [554.3827128226441, 0.0, 320.5, -38.80678989758509, 0.0, 554.3827128226441, 240.5, 0.0, 0.0, 0.0, 1.0, 0.0] #TODO take the parameters from the /camera_info topic instead point_top1_cam_np = np.array([point_top1_cam.x, point_top1_cam.y, point_top1_cam.z]) point_top2_cam_np = np.array([point_top2_cam.x, point_top2_cam.y, point_top2_cam.z]) point_top3_cam_np = np.array([point_top3_cam.x, point_top3_cam.y, point_top3_cam.z]) point_top4_cam_np = np.array([point_top4_cam.x, point_top4_cam.y, point_top4_cam.z]) #used to test the projection #point_test_center_cam_np = np.array([point_test_center_cam.x, point_test_center_cam.y, point_test_center_cam.z]) point_top1_img_np = self.cameraMatK.dot(point_top1_cam_np) point_top2_img_np = self.cameraMatK.dot(point_top2_cam_np) point_top3_img_np = self.cameraMatK.dot(point_top3_cam_np) point_top4_img_np = self.cameraMatK.dot(point_top4_cam_np) #point_test_center_img_np = self.cameraMatK.dot(point_test_center_cam_np) mask_polygon = Polygon() mask_polygon.points = [Point32(point_top1_img_np[0]/point_top1_img_np[2],point_top1_img_np[1]/point_top1_img_np[2],0), Point32(point_top2_img_np[0]/point_top2_img_np[2],point_top2_img_np[1]/point_top2_img_np[2],0), Point32(point_top3_img_np[0]/point_top3_img_np[2],point_top3_img_np[1]/point_top3_img_np[2],0), Point32(point_top4_img_np[0]/point_top4_img_np[2],point_top4_img_np[1]/point_top4_img_np[2],0)] goal = o2as_msgs.msg.blobDetectionGoal() goal.maskCorner = mask_polygon goal.param_part_id = "part_" + str(part_id) self.blob_detection_client.send_goal(goal) self.blob_detection_client.wait_for_result() result = self.blob_detection_client.get_result() #rospy.loginfo(result) #TODO select which poses to choose in the array if result: poseArrayRes = geometry_msgs.msg.PoseArray() #TODO Sort pose in the midle of the bin #min x min y in the bin frame if(result.success): poseArrayRes = result.posesDetected distanceToBinCenter = [] for i in range(len(poseArrayRes.poses)): pointCam = geometry_msgs.msg.PointStamped() #simulation only poseArrayRes.header.frame_id = "a_bot_camera_calibrated_frame_link" pointCam.header = poseArrayRes.header pointCam.point = poseArrayRes.poses[i].position pointBin = self.listener.transformPoint(bin_id, pointCam).point distanceToBinCenter.append(math.sqrt(pointBin.x*pointBin.x + pointBin.y*pointBin.y)) minPoseIndex = np.argmin(distanceToBinCenter) rospy.loginfo("point closest to the bin center in the xy plane") rospy.loginfo(poseArrayRes.poses[minPoseIndex]) #Transform point from camera reference to bin reference pointPartCam = geometry_msgs.msg.PointStamped() pointPartCam.header = poseArrayRes.header pointPartCam.point = poseArrayRes.poses[minPoseIndex].position pointPartBin = self.listener.transformPoint(bin_id, pointPartCam) rospy.loginfo("Pose in bin") rospy.loginfo(pointPartBin) #Transform point from camera reference to bin reference goal_part = geometry_msgs.msg.PoseStamped() goal_part.header.frame_id = pointPartBin.header.frame_id goal_part.pose.position.x = pointPartBin.point.x goal_part.pose.position.y = pointPartBin.point.y goal_part.pose.position.z = pointPartBin.point.z goal_part.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(-pi/2, pi/2 , 0)) self.current_img_w_blob = copy.deepcopy(result.blobImage) self.draw_point3D_after_view_bin(pointPartCam) return goal_part else: rospy.loginfo("no pose detected") #TODO if nothing is detected move the camera a bit to try to detect somethin return False def draw_point3D_after_view_bin(self, pointPartCam): ### Project the goal on the image plane using the camera matrix like for the mask #Transform Point in camera reference point3D_to_draw = geometry_msgs.msg.PointStamped() point3D_to_draw = self.listener.transformPoint("a_bot_camera_calibrated_frame_link", pointPartCam) #Copy the results # Project the point to the camera plane pointPart_cam_np = np.array([point3D_to_draw.point.x, point3D_to_draw.point.y, point3D_to_draw.point.z]) pointPart_img_np = self.cameraMatK.dot(pointPart_cam_np) #Transfom into pixel coordinate pointPart_pix= pointCam = geometry_msgs.msg.Point(pointPart_img_np[0]/pointPart_img_np[2],pointPart_img_np[1]/pointPart_img_np[2],0) img_blob_cv = self.bridge.imgmsg_to_cv2(self.current_img_w_blob , desired_encoding="passthrough") #img_blob_cv_np = np.asarray(img_blob_cv)[:, :, ::-1] #Draw the circle in orange for the propose pose cv2.circle(img_blob_cv,(int(pointPart_pix.x),int(pointPart_pix.y)), 3, (0,255,0), 4) self.current_img_w_goal = self.bridge.cv2_to_imgmsg(img_blob_cv, "rgb8") #publish the results try: print("publish") self.img_inner_pick_pub.publish(self.current_img_w_goal) except CvBridgeError as e: print(e) def place_screw_in_tray(self, screw_size, set_number, hole_number): """ Places a screw in a tray. A screw needs to be carried by the screw tool! """ # Use this command to equip the screw tool: do_change_tool_action(self, "c_bot", equip=True, screw_size = 4) if not screw_size==3 and not screw_size==4: rospy.logerr("Screw size needs to be 3 or 4!") return False # Turn to the right to face the feeders self.go_to_named_pose("feeder_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) pose_tray = geometry_msgs.msg.PoseStamped() pose_tray.header.frame_id = "set_" + str(set_number) + "_tray_2_screw_m" + str(screw_size) + "_" + str(hole_number) if set_number == 1: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(pi/2, 0, 0)) pose_tray.pose.position.x = -.01 elif set_number == 2: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(pi/4, 0, 0)) pose_tray.pose.position.x = -.005 elif set_number == 3: pose_tray.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, 0, 0)) pose_tray.pose.position.x = -.005 if screw_size == 3: pose_tray.pose.position.x += .005 success = self.do_place_action("c_bot", pose_tray, tool_name = "screw_tool", screw_size=screw_size) if not success: return False self.go_to_named_pose("feeder_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) return True ################ ----- Demos ################ ################ def pick_screw_from_bin_and_put_into_feeder(self, item, max_attempts = 5): robot_name = "a_bot" end_effector_link = "a_bot_precision_gripper_tip_link" if item.part_id == 17: screw_size = 4 elif item.part_id == 18: screw_size = 3 attempts = 0 while attempts < max_attempts: attempts += 1 item.attempts += 1 rospy.loginfo("Attempting to pick screw. Item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Attempt nr. " + str(item.attempts)) # Attempt to pick the item pick_pose = self.get_random_pose_in_bin(item) if not item.bin_is_inclined: pick_pose.pose.orientation = self.downward_orientation_2 if item.part_id == 18: #M3 pick_pose.pose.position.z = .005 # MAGIC NUMBER! Depends on the amount of screws in the bin! if item.part_id == 17: #M4 pick_pose.pose.position.z = .00 # MAGIC NUMBER! Depends on the amount of screws in the bin! gripper_command = "inner_gripper_from_outside" self.pick(robot_name, pick_pose, 0.0, speed_fast = 1.0, speed_slow = 0.3, gripper_command=gripper_command, approach_height = 0.04) screw_picked = self.check_pick(item.part_id) if not screw_picked and self.use_real_robot: rospy.logerr("Failed an attempt to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Reattempting. Current attempts: " + str(attempts)) continue self.put_screw_in_feeder(screw_size) item.in_feeder = True rospy.loginfo("Delivered screw m" + str(screw_size) + " to feeder (item nr." + str(item.number_in_set) + " from set " + str(item.set_number)) return True return False def get_random_pose_in_bin(self, item): pick_pose = geometry_msgs.msg.PoseStamped() pick_pose.header.frame_id = item.bin_name if "bin1" in item.bin_name: bin_length = self.bin_1_width bin_width = self.bin_1_length elif "bin2" in item.bin_name: bin_length = self.bin_2_width bin_width = self.bin_2_length elif "bin3" in item.bin_name: bin_length = self.bin_3_width bin_width = self.bin_3_length pick_pose.pose.position.x += -bin_length/2 + random.random()*bin_length pick_pose.pose.orientation = self.downward_orientation_2 if item.bin_is_inclined: rospy.loginfo("Applying position for inclined bin") if "bin1" in item.bin_name: if item.bin_is_inclined == "left": pick_pose.pose.position.y = -.035 elif item.bin_is_inclined == "right": pick_pose.pose.position.y = .035 else: # Does not work because the width values are not strictly true (but safe for the regular random pick) pick_pose.pose.position.y = bin_width/2-.01 pick_pose.pose.position.z = .01 if "precision_gripper" in item.ee_to_use: pick_pose.pose.position.z = self.precision_gripper_pick_heights["part_"+str(item.part_id)] if item.part_id in [9, 16, 17,18]: pick_pose.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/2)) if item.part_id in [16, 17,18]: pick_pose.pose.position.z = 0.0 if item.part_id in [9]: pick_pose.pose.position.y += .005*random.random() pick_pose.pose.position.z = 0.005 rospy.loginfo(pick_pose.pose) else: pick_pose.pose.position.y += -bin_width/2 + random.random()*bin_width return pick_pose def get_grasp_candidates_from_phoxi(self, item, take_new_image=False): """This requests a list of grasp positions and takes a new image with the phoxi if take_new_image is True.""" goal = o2as_msgs.msg.SearchGraspPhoxiGoal() goal.part_id = item.part_id goal.bin_name = item.bin_name goal.gripper_type = item.ee_to_use goal.update_image = take_new_image try: self.search_grasp_client.send_goal(goal) self.search_grasp_client.wait_for_result(rospy.Duration(7.0)) resp_search_grasp = self.search_grasp_client.get_result() except: rospy.logerr("Could not get grasp from Phoxi") return False if resp_search_grasp: if resp_search_grasp.success: poses_in_bin = list() pose0 = geometry_msgs.msg.PointStamped() pose0.header.frame_id = "a_phoxi_m_sensor" number_of_pose_candidates = min(self.max_candidates_from_phoxi, resp_search_grasp.result_num) for i in range(number_of_pose_candidates): object_position = copy.deepcopy(pose0) object_position.point = geometry_msgs.msg.Point( resp_search_grasp.pos3D[i].x, resp_search_grasp.pos3D[i].y, resp_search_grasp.pos3D[i].z) # TODO We should talk about how to use rotiqz which the two_finger approaches. rospy.logdebug("\nGrasp point in %s: (x, y, z) = (%f, %f, %f)", object_position.header.frame_id, object_position.point.x, object_position.point.y, object_position.point.z) obj_pose_in_camera = geometry_msgs.msg.PoseStamped() obj_pose_in_camera.header = object_position.header obj_pose_in_camera.pose.position = object_position.point obj_pose_in_camera.pose.orientation.w = 1.0 # pose_in_bin = geometry_msgs.msg.PoseStamped() # pose_in_bin.header.frame_id = item.bin_name pose_in_bin = self.listener.transformPose(item.bin_name, obj_pose_in_camera) pose_in_bin.pose.orientation = self.downward_orientation if item.ee_to_use in ["precision_gripper_from_outside", "robotiq_gripper"]: pose_in_bin.pose.orientation = geometry_msgs.msg.Quaternion( *tf_conversions.transformations.quaternion_from_euler(0, pi/2, -resp_search_grasp.rotipz[i])) poses_in_bin.append(pose_in_bin) self.publish_marker(pose_in_bin, "aist_vision_result") rospy.loginfo("Calculated " + str(number_of_pose_candidates) + " candidates for item nr. " + str(item.part_id) + " in bin " + str(item.bin_name)) rospy.logdebug(poses_in_bin) return poses_in_bin else: rospy.loginfo("Could not find a pose via phoxi.") return False def treat_screws_in_feeders(self): """ Picks the screws when they have been in the feeder long enough """ self.screws_in_feeder = dict() self.screws_done["m4"] = True self.screws_done["m3"] = True self.screws_in_feeder["m3"] = False self.screws_in_feeder["m4"] = False for item in self.ordered_items: if not item.fulfilled: if item.part_id == 17: screw_size = 4 elif item.part_id == 18: screw_size = 3 else: continue rospy.loginfo("Found an undelivered screw in the order: item nr. " + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")") self.screws_done["m"+str(screw_size)] = False if item.in_feeder: self.screws_in_feeder["m"+str(screw_size)] = True if (not self.screws_done["m4"] and self.screws_in_feeder["m4"]) or (not self.screws_done["m3"] and self.screws_in_feeder["m3"]): if not self.screws_in_feeder["m4"] and not self.screws_in_feeder["m3"]: rospy.loginfo("No screws are in the feeders. Skipping.") return if (rospy.Time.now() - self.screw_delivery_time) > rospy.Duration(1): #180 self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("suction_ready_back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) for screw_size in [4,3]: if rospy.is_shutdown(): return if not self.screws_done["m"+str(screw_size)]: rospy.loginfo("=== Picking m" + str(screw_size) + " screws from feeder") self.go_to_named_pose("tool_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.do_change_tool_action("c_bot", equip=True, screw_size=screw_size) for item in self.screws["m"+str(screw_size)]: if rospy.is_shutdown(): return if item.in_feeder: if self.pick_screw_from_feeder(screw_size, attempts=2): self.place_screw_in_tray(screw_size, item.set_number, self.screws_placed["m"+str(screw_size)][item.set_number]+1) self.screws_placed["m"+str(screw_size)][item.set_number] += 1 self.fulfilled_items += 1 item.in_feeder = False item.fulfilled = True else: rospy.loginfo("Failed to pick an m" + str(screw_size) + " screw from the feeder") break if rospy.is_shutdown(): return self.go_to_named_pose("tool_pick_ready", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.do_change_tool_action("c_bot", equip=False, screw_size=screw_size) self.go_to_named_pose("back", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if self.screws_done["m4"] and self.screws_done["m3"]: self.set_feeder_power(False) return def make_pose_safe_for_bin(self, pick_pose, item): """ This makes sure that the pick_pose is not outside the bin or would cause a collision.""" if "bin1" in item.bin_name: bin_length = self.bin_1_width bin_width = self.bin_1_length elif "bin2" in item.bin_name: bin_length = self.bin_2_width bin_width = self.bin_2_length elif "bin3" in item.bin_name: bin_length = self.bin_3_width bin_width = self.bin_3_length safe_pose = copy.deepcopy(pick_pose) safe_pose.pose.position.x = clamp(pick_pose.pose.position.x, -bin_length/2 - .02, bin_length/2 - .02) safe_pose.pose.position.y = clamp(pick_pose.pose.position.y, -bin_width/2 - .02, bin_width/2 - .02) safe_pose.pose.position.z = clamp(pick_pose.pose.position.z, 0, 0.1) if safe_pose.pose.position.x != pick_pose.pose.position.x or safe_pose.pose.position.y != pick_pose.pose.position.y: rospy.loginfo("Pose was adjusted in make_pose_safe_for_bin. Before: " + str(pick_pose.pose.position.x) + ", " + str(pick_pose.pose.position.y) + ", " + str(pick_pose.pose.position.z) + ". After: " + str(safe_pose.pose.position.x) + ", " + str(safe_pose.pose.position.y) + ", " + str(safe_pose.pose.position.z) + ".") #TODO: Adjust the gripper orientation when close to the border return safe_pose def attempt_item(self, item, max_attempts = 5): """This function attempts to pick an item. It increases the item.attempts counter each time it does, and sets item.fulfilled to True if item is delivered.""" if "precision_gripper" in item.ee_to_use: robot_name = "a_bot" elif "robotiq_gripper" in item.ee_to_use: robot_name = "b_bot" elif item.ee_to_use == "suction": robot_name = "b_bot" if item.fulfilled: rospy.logerr("This item is already fulfilled. Something is going wrong.") return False take_new_image = False if not self.initial_phoxi_image_recorded: self.initial_phoxi_image_recorded = True take_new_image = True ### Vision is skipped # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # if self.grasp_candidates[item.part_id]["pick_was_successful"]: # # If the pick was successful for an item, the scene has changed, so a new image needs to be taken # rospy.loginfo("Resetting grasp candidates for item " + str(item.part_id)) # self.grasp_candidates[item.part_id]["pick_was_successful"] = False # self.grasp_candidates[item.part_id]["vision_was_attempted"] = False # self.grasp_candidates[item.part_id]["positions"] = [] # take_new_image = True # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # self.go_to_named_pose("suction_ready_back", "b_bot") # elif "precision_gripper" in item.ee_to_use: # self.go_to_named_pose("taskboard_intermediate_pose", "a_bot") # if not self.grasp_candidates[item.part_id]["vision_was_attempted"]: # # Vision is only attempted once, unless it succeeds in picking # phoxi_res = self.get_grasp_candidates_from_phoxi(item, take_new_image) # # self.grasp_candidates[item.part_id]["vision_was_attempted"] = True # #### Line above is uncommented to force new vision result every time # take_new_image = False # if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # self.go_to_named_pose("suction_pick_ready", "b_bot") # elif "precision_gripper" in item.ee_to_use: # self.go_to_named_pose("kitting_pick_ready", "a_bot") # if phoxi_res: # self.grasp_candidates[item.part_id]["positions"].extend(phoxi_res) # rospy.loginfo("self.grasp_candidates: ") # rospy.loginfo(self.grasp_candidates[item.part_id]["positions"][0]) # Go to preparatory pose if item.ee_to_use == "suction": rospy.loginfo("Going to preparatory pose before picking from bins") bin_center = geometry_msgs.msg.PoseStamped() bin_center.header.frame_id = item.bin_name bin_center.pose.orientation.w = 1.0 bin_center_on_table = self.listener.transformPose("workspace_center", bin_center).pose.position if bin_center_on_table.y > .1: self.go_to_named_pose("suction_ready_right_bins", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) else: self.go_to_named_pose("suction_ready_left_bins", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) elif "precision_gripper" in item.ee_to_use: self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) elif "robotiq_gripper" in item.ee_to_use: self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) attempts = 0 grasp_candidate_came_from_realsense = False grasp_candidate_from_vision = False while attempts < max_attempts and not rospy.is_shutdown(): attempts += 1 item.attempts += 1 rospy.loginfo("=== Attempting item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Attempt nr. " + str(item.attempts)) # Get the pick_pose for the item, either random or from vision pick_pose = self.get_random_pose_in_bin(item) grasp_candidate_from_vision = False ### Realsense vision result is skipped if item.ee_to_use == "precision_gripper_from_inside" and not item.bin_is_inclined and not item.part_id in [17, 18]: pick_pose.pose.position.z = self.precision_gripper_pick_heights["part_" + str(item.part_id)] rospy.loginfo("Assigned pick height: " + str(pick_pose.pose.position.z)) # res_view_bin = self.view_bin(robot_name, item.bin_name, item.part_id) # grasp_candidate_came_from_realsense = True # if res_view_bin: # pick_pose = res_view_bin # pick_pose.pose.position.z -= .025 # MAGIC NUMBER (to compensate for the Realsense calibration) if item.ee_to_use == "suction" or item.ee_to_use == "robotiq_gripper": # for test run: if grasp_candidates is 0, item picking is skipped. while self.grasp_candidates[item.part_id]["positions"]: pick_pose = self.grasp_candidates[item.part_id]["positions"].pop(0) rospy.logwarn("ADDING A MAGIC ADJUSTMENT TO THE PHOXI RESULT") pick_pose.pose.position.y += -.002 if pick_pose.pose.position.z <= 0.005 and item.ee_to_use == "suction": rospy.loginfo("Discarded a grasp candidate:") rospy.loginfo(pick_pose.pose.position) pick_pose = self.get_random_pose_in_bin(item) # Reset to a random pose if the grasp candidate was bad continue # pick_pose.pose.position.z -= self.insert_offsets["part_"+str(item.part_id)] rospy.loginfo("Got pose from phoxi grasp candidates:") rospy.loginfo(pick_pose.pose.position) grasp_candidate_from_vision = True if item.ee_to_use == "robotiq_gripper": self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if item.ee_to_use == "suction": # Orientation needs to be adjusted for suction tool bin_center = geometry_msgs.msg.PoseStamped() bin_center.header.frame_id = item.bin_name bin_center.pose.orientation.w = 1.0 bin_center_on_table = self.listener.transformPose("workspace_center", bin_center).pose.position if bin_center_on_table.y > .1: pick_pose.pose.orientation = self.suction_orientation_right_bins else: pick_pose.pose.orientation = self.suction_orientation_left_bins else: # Precision_gripper, robotiq_gripper if not item.bin_is_inclined: pick_pose.pose.orientation = self.downward_orientation_2 if item.part_id == 6: # Belt pick_pose.pose.orientation = geometry_msgs.msg.Quaternion(*tf_conversions.transformations.quaternion_from_euler(0, pi/2, pi/2)) approach_height = 0.1 speed_slow = 0.1 speed_fast = 1.0 if item.ee_to_use == "precision_gripper_from_inside": gripper_command = "inner_gripper_from_inside" approach_height = .05 elif item.ee_to_use == "precision_gripper_from_outside": gripper_command = "inner_gripper_from_outside" approach_height = .05 elif item.ee_to_use == "suction": gripper_command = "suction" approach_height = 0.1 - pick_pose.pose.position.z speed_slow = 0.05 speed_fast = 1.0 elif item.ee_to_use == "robotiq_gripper": approach_height = .15 speed_slow = .2 gripper_command = "" else: gripper_command = "" pick_pose = self.make_pose_safe_for_bin(pick_pose, item) if grasp_candidate_from_vision: self.log_to_debug_monitor("Picking pose result from vision", "subtask") elif grasp_candidate_came_from_realsense: self.log_to_debug_monitor("Picking pose result from realsense", "subtask") else: self.log_to_debug_monitor("Picking random pose", "subtask") if "precision_gripper" in item.ee_to_use: pose_above_bin = copy.deepcopy(pick_pose) pose_above_bin.pose.position.z += .15 self.go_to_pose_goal("a_bot", pose_above_bin, speed=speed_fast, move_lin=True) item_picked = self.pick(robot_name, pick_pose, 0.0, speed_fast = speed_fast, speed_slow = .05, gripper_command=gripper_command, approach_height = approach_height) if not self.use_real_robot: item_picked = True if item_picked and grasp_candidate_from_vision: self.grasp_candidates[item.part_id]["pick_was_successful"] = True # TODO: Check grasp success via grasp width for robotiq gripper and vision for precision gripper if "precision_gripper" in item.ee_to_use: item_picked = self.check_pick(item.part_id) # Suction is checked inside the pick function if not item_picked: rospy.logerr("Failed an attempt to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + "). Reattempting. Current attempts: " + str(attempts)) if item.ee_to_use == "suction": self.suck(False) continue # Attempt to place the item place_pose = geometry_msgs.msg.PoseStamped() place_pose.header.frame_id = item.target_frame required_intermediate_pose = [] if item.ee_to_use == "suction": # This is inconvenient to set up because the trays are rotated. tray_2s are rotated 180 degrees relative to set_1_tray_1 # SUCTION_PREP_POSES place_pose.pose.orientation, required_intermediate_pose = self.get_tray_placement_orientation_for_suction_in_kitting( set_number=item.set_number, tray_number=int(place_pose.header.frame_id[11])) if not place_pose.pose.orientation.w and not place_pose.pose.orientation.x and not place_pose.pose.orientation.y: rospy.logerr("SOMETHING WENT WRONG, ORIENTATION IS NOT ASSIGNED") else: # Precision_gripper, robotiq_gripper place_pose.pose.orientation = self.downward_orientation approach_height = .05 if "precision_gripper" in item.ee_to_use: self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=1.5, acceleration=1.0, force_ur_script=self.use_real_robot) approach_height = .03 elif item.ee_to_use == "suction": if required_intermediate_pose: rospy.loginfo("Going to intermediate pose") self.go_to_named_pose(required_intermediate_pose, "b_bot", speed=1.5, acceleration=1.0, force_ur_script=self.use_real_robot) # Approach the place pose with controllrighacceleration value rospy.loginfo("Approaching place pose") if item.set_number in [2,3] and item.target_frame[11] == '1': # Tray 1 self.go_to_named_pose("suction_ready_left_bins", "b_bot", speed=.1) self.go_to_named_pose("suction_place_intermediate_pose_for_sets_2_and_3", "b_bot", speed=.1) self.force_moveit_linear_motion = True place_pose.pose.position.z += .08 self.move_lin(robot_name, place_pose, speed = 0.3, acceleration = 0.08, end_effector_link = "b_bot_suction_tool_tip_link") place_pose.pose.position.z -= .08 if item.part_id == 6: if pick_pose.pose.position.x > 0: place_pose.pose.position.y = -0.06 else: place_pose.pose.position.y = 0.06 self.place(robot_name, place_pose,grasp_height=item.dropoff_height, speed_fast = 0.5, speed_slow = 0.02, gripper_command=gripper_command, approach_height = approach_height) if item.ee_to_use == "suction": self.force_moveit_linear_motion = False # If successful self.fulfilled_items += 1 item.fulfilled = True rospy.loginfo("Delivered item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")! Total items delivered: " + str(self.fulfilled_items)) return True rospy.logerr("Was not able to pick item nr." + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")! Total attempts: " + str(item.attempts)) # TODO: Move up safely if not successful # self.move_lin(robot_name, place_pose, speed = 0.3, acceleration = 0.08, end_effector_link = "b_bot_suction_tool_tip_link") return False def kitting_task(self): # Strategy: # - Start with suction tool + m4 tool equipped # - Pick all the screws in the current set and put them in the feeders, so they will be ready to be picked # - Go through all items that require suction, so the tool is equipped only once does not have to be re-equipped # - Go through items that are picked by the a_bot or b_bot grippers # - When the screws are ready, pick and place them # - Try to pick and return any excess screws # Ideally, we can fit all the trays into the scene. self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("back", "c_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.go_to_named_pose("suction_ready_back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) start_time = rospy.Time.now() self.start_task_timer() self.log_to_debug_monitor(text="Kitting", category="task") time_limit = rospy.Duration(1140) # 19 minutes self.fulfilled_items = 0 self.screws_done = dict() self.screws_placed = dict() self.screws_done["m4"] = (len(self.screws["m4"]) == 0) self.screws_done["m3"] = (len(self.screws["m3"]) == 0) self.screws_placed["m4"] = {1:0, 2:0, 3:0} self.screws_placed["m3"] = {1:0, 2:0, 3:0} # ==== 1. First, do an initial attempt on picking all items, ordered by the tool that they are picked with (screws, suction, precision_gripper, robotiq) # self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # for item in self.screw_items: # self.log_to_debug_monitor("Pick screw no. " + str(item.part_id) + " and put into feeder", "subtask") # if rospy.is_shutdown(): # break # # item.in_feeder = True # Used to skip the screws and enable the feeder pickup # self.pick_screw_from_bin_and_put_into_feeder(item, 10) # self.go_to_named_pose("kitting_pick_ready", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # rospy.loginfo("==== Done with screw pickup pass") self.screw_delivery_time = rospy.Time.now() # rospy.sleep(2) self.treat_screws_in_feeders() for item in self.suction_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.treat_screws_in_feeders() self.attempt_item(item, 3) # self.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool self.go_to_named_pose("suction_ready_back", "b_bot") rospy.loginfo("==== Done with first suction pass") for item in self.precision_gripper_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.attempt_item(item, 3) self.go_to_named_pose("back", "a_bot") rospy.loginfo("==== Done with first precision gripper pass") self.treat_screws_in_feeders() self.treat_screws_in_feeders() # for item in self.robotiq_gripper_items: # self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") # self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # if rospy.is_shutdown(): # break # self.attempt_item(item, 3) # self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() # ==== 2. Second, loop through all the items that were not successfully picked on first try, and place the screws when they are assumed to be ready. all_done = False # while False: while not all_done and not rospy.is_shutdown(): rospy.loginfo("Entering the loop to recover failed items and pick screws") # Check all items, find which groups are done, then reattempt those that are unfinished all_done = True suction_done = True precision_gripper_done = True robotiq_gripper_done = True self.screws_done["m4"] = True self.screws_done["m3"] = True for item in self.ordered_items: if not item.fulfilled: rospy.loginfo("Found an undelivered item in the order: item nr. " + str(item.number_in_set) + " from set " + str(item.set_number) + " (part ID:" + str(item.part_id) + ")") all_done = False if "precision_gripper" in item.ee_to_use: precision_gripper_done = False elif "robotiq_gripper" in item.ee_to_use: robotiq_gripper_done = False elif item.ee_to_use == "suction": suction_done = False if item.part_id == 17: self.screws_done["m4"] = False elif item.part_id == 18: self.screws_done["m3"] = False self.treat_screws_in_feeders() if not precision_gripper_done: rospy.loginfo("Reattempting the remaining precision gripper items") self.go_to_named_pose("taskboard_intermediate_pose", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) for item in self.precision_gripper_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break self.attempt_item(item) self.go_to_named_pose("back", "a_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() # if not robotiq_gripper_done: # rospy.loginfo("Reattempting the remaining robotiq gripper items") # self.go_to_named_pose("home", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) # for item in self.robotiq_gripper_items: # self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") # if rospy.is_shutdown(): # break # self.attempt_item(item) # self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.treat_screws_in_feeders() if not suction_done: self.reset_grasp_candidates() rospy.loginfo("Reattempting the remaining suction items") # self.do_change_tool_action("b_bot", equip=True, screw_size=50) # 50 = suction tool for item in self.suction_items: self.log_to_debug_monitor("Pick and place item no. " + str(item.part_id), "subtask") if rospy.is_shutdown(): break if not item.fulfilled: self.go_to_named_pose("suction_pick_ready", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) self.attempt_item(item, 5) # self.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool self.go_to_named_pose("back", "b_bot", speed=2.0, acceleration=2.0, force_ur_script=self.use_real_robot) if (rospy.Time.now()-start_time) > time_limit: rospy.logerr("Time limit reached! Breaking out of the loop.") break if all_done: rospy.loginfo("Completed the task.") else: rospy.loginfo("STOPPED THE TASK") return if __name__ == '__main__': try: kit = KittingClass() i = 1 while i: rospy.loginfo("Enter 1 to equip suction tool.") rospy.loginfo("Enter 11 to unequip suction tool.") rospy.loginfo("Enter 2 to move the robots home to starting positions.") rospy.loginfo("Enter 3 to suction attachment test with b_bot using suction tool.") rospy.loginfo("Enter 60 to pick screw from bin with a_bot.") rospy.loginfo("Enter 61 to hand over screw from a_bot to c_bot.") rospy.loginfo("Enter 62 to move robots back.") rospy.loginfo("Enter 71, 72... to test phoxi on item 1, 2...") rospy.loginfo("Enter 81, 82... to move b_bot suction to trays...") rospy.loginfo("Enter 90 to move a_bot to kitting_pick_ready.") rospy.loginfo("Enter 91, 92... to do view_bin on bin1_1, bin1_2...") rospy.loginfo("Enter START to start the task.") rospy.loginfo("Enter x to exit.") i = raw_input() if i == '1': kit.do_change_tool_action("b_bot", equip=True, screw_size=50) # 50 = suction tool if i == '11': kit.do_change_tool_action("b_bot", equip=False, screw_size=50) # 50 = suction tool if i == '2': kit.go_to_named_pose("back", "a_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("back", "c_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("suction_ready_back", "b_bot", force_ur_script=kit.use_real_robot) elif i == 'START' or i == 'start' or i == '5000': kit.kitting_task() elif i == "60": kit.go_to_named_pose("home", "a_bot", force_ur_script=kit.use_real_robot) kit.pick_screw_with_precision_gripper(kit.part_bin_list["part_17"], screw_size= 4) elif i == "61": kit.pick_screw_from_precision_gripper(screw_size=4) elif i == "62": kit.go_to_named_pose("screw_ready", "c_bot", force_ur_script=kit.use_real_robot) kit.go_to_named_pose("back", "a_bot", force_ur_script=kit.use_real_robot) elif i in ["71", "72", "73", "74", "75", "76", "77", "78", "79"]: item = kit.ordered_items[int(i)-71] rospy.loginfo("Checking for item id " + str(item.part_id) + " in " + item.bin_name) obj_pose = kit.get_grasp_candidates_from_phoxi(item, True) elif i == "80": kit.go_to_named_pose("suction_pick_ready", "b_bot", force_ur_script=kit.use_real_robot) elif i in ["81", "82", "83", "84"]: place_pose = geometry_msgs.msg.PoseStamped() if i == "81": place_pose.header.frame_id = "set_1_tray_2_partition_4" elif i == "82": place_pose.header.frame_id = "set_2_tray_2_partition_4" elif i == "83": place_pose.header.frame_id = "set_3_tray_2_partition_4" elif i == "84": place_pose.header.frame_id = "set_1_tray_1_partition_3" # SUCTION_PREP_POSES place_pose.pose.orientation = kit.get_tray_placement_orientation_for_suction_in_kitting( set_number=int(place_pose.header.frame_id[4]), tray_number=int(place_pose.header.frame_id[11])) kit.go_to_named_pose("back", "c_bot") kit.go_to_named_pose("back", "b_bot") kit.go_to_named_pose("screw_ready", robot_name) place_pose.pose.position.z = .08 kit.move_lin("b_bot", place_pose, .1, end_effector_link="b_bot_suction_tool_tip_link") elif i == "90": kit.go_to_named_pose("kitting_pick_ready", "a_bot", force_ur_script=kit.use_real_robot) elif i in ["91", "92", "93", "94", "95"]: if i == "91": part_id = 16 elif i == "92": part_id = 9 elif i == "93": part_id = 15 elif i == "94": part_id = 17 elif i == "95": part_id = 18 kit.view_bin("a_bot", "bin1_" + i[1], part_id) elif i == "x": break print "============ Done!" except rospy.ROSInterruptException: pass

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example.py

duanyytop/ckb-sdk-python

1

55675

<gh_stars>1-10 from ckb_toolkit.core.signer import sign_tx from ckb_toolkit.core.rpc import RPCClient from ckb_toolkit.core.hash import ckb_blake160 from ckb_toolkit.core.hex_coder import hex_to_bytes, hex_from_bytes from ckb_toolkit.address.address import generateShortAddress, generateFullAddress from coincurve import PublicKey, PrivateKey import json unsigned_raw_tx = {'version': '0x0', 'cell_deps': [{'out_point': {'tx_hash': '0xbd262c87a84c08ea3bc141700cf55c1a285009de0e22c247a8d9597b4fc491e6', 'index': '0x2'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0xd346695aa3293a84e9f985448668e9692892c959e7e83d6d8042e59c08b8cf5c', 'index': '0x0'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0x03dd2a5594ed2d79196b396c83534e050ba0ad07fa5c1cd61a7094f9fb60a592', 'index': '0x0'}, 'dep_type': 'code'}, {'out_point': {'tx_hash': '0xf8de3bb47d055cdf460d93a2a6e1b05f7432f9777c8c474abf4eec1d4aee5d37', 'index': '0x0'}, 'dep_type': 'dep_group'}], 'header_deps': [ ], 'inputs': [{'previous_output': {'tx_hash': '0xad375e8c40fdf42187ecbec79f7ddcae72017ce7773a4762421f3f50722dccb0', 'index': '0x1'}, 'since': '0x0'}], 'outputs': [{'capacity': '0x31eb3c002', 'lock': {'code_hash': '0x9bd7e06f3ecf4be0f2fcd2188b23f1b9fcc88e5d4b65a8637b17723bbda3cce8', 'args': '0xed893ca482474e66b5779e57dc1d5281f9033e4f', 'hash_type': 'type'}, 'type': {'code_hash': '0xb1837b5ad01a88558731953062d1f5cb547adf89ece01e8934a9f0aeed2d959f', 'args': '0xf90f9c38b0ea0815156bbc340c910d0a21ee57cf0000003700000002', 'hash_type': 'type'}}], 'outputs_data': ['0x000000000000000000c000'], 'witnesses': ['0x']} private_key = 'd52a6cb37ce90aed79a96ea9976668fbdbe16d6eac3611d5b15de388168da2c3' public_key = PrivateKey.from_hex(private_key).public_key.format() args = ckb_blake160(public_key)[2:] address = generateShortAddress(args, network = "testnet") print(address) lock = {'code_hash': '9bd7e06f3ecf4be0f2fcd2188b23f1b9fcc88e5d4b65a8637b17723bbda3cce8', 'hash_type': 'type', 'args': args} full_address = generateFullAddress(lock, network = "testnet") print(full_address) tx = sign_tx(unsigned_raw_tx, private_key) print(tx) rpc = RPCClient('https://testnet.ckb.dev/rpc') tx_hash = rpc.request('send_transaction', tx) print(tx_hash)

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src/aria/aria/reading/__init__.py

tliron/aria-ng

0

143402

# # Copyright (c) 2016 GigaSpaces Technologies Ltd. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # from .exceptions import ReaderException, ReaderNotFoundError, ReaderSyntaxError, AlreadyReadException from .reader import Reader from .source import ReaderSource, DefaultReaderSource from .context import ReadingContext from .raw import RawReader from .locator import Locator from .yaml import YamlReader from .json import JsonReader from .jinja import JinjaReader __all__ = ( 'ReaderException', 'ReaderNotFoundError', 'ReaderSyntaxError', 'AlreadyReadException', 'Reader', 'ReaderSource', 'DefaultReaderSource', 'ReadingContext', 'RawReader', 'Locator', 'YamlReader', 'JsonReader', 'JinjaReader')

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pymars/tests/test_drg.py

kbronstein56/pyMARS

39

47179

"""Tests for drg module""" import sys import os import pkg_resources import pytest import numpy as np import networkx as nx import cantera as ct from ..sampling import data_files, InputIgnition from ..drg import graph_search, create_drg_matrix, run_drg, trim_drg, reduce_drg # Taken from http://stackoverflow.com/a/22726782/1569494 try: from tempfile import TemporaryDirectory except ImportError: from contextlib import contextmanager import shutil import tempfile import errno @contextmanager def TemporaryDirectory(): name = tempfile.mkdtemp() try: yield name finally: try: shutil.rmtree(name) except OSError as e: # Reraise unless ENOENT: No such file or directory # (ok if directory has already been deleted) if e.errno != errno.ENOENT: raise def relative_location(file): file_path = os.path.join(file) return pkg_resources.resource_filename(__name__, file_path) def check_equal(list1, list2): """Check whether two lists have the same contents (regardless of order). Taken from https://stackoverflow.com/a/12813909 Parameters ---------- list1 : list First list, containing all of a particular type list2: list Second list, containing all of a particular type Returns ------- bool ``True`` if lists are equal """ return len(list1) == len(list2) and sorted(list1) == sorted(list2) class TestCreateDRGMatrix: """Tests for create_drg_matrix method""" def test_qss_artificial(self): """Test using four species artificial model with QSS species from 2006 DRG paper. # R \approx F / 1e3 """ R1 = ct.Reaction.fromCti('''reaction('F => R', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('R => P', [1.0e3, 0.0, 0.0])''') R3 = ct.Reaction.fromCti('''reaction('R => Pp', [1.0, 0.0, 0.0])''') F = ct.Species('F', 'H:1') R = ct.Species('R', 'H:1') P = ct.Species('P', 'H:1') Pp = ct.Species('Pp', 'H:1') for sp in [F, R, P, Pp]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, R, P, Pp], reactions=[R1, R2, R3] ) state = 1000, ct.one_atm, [1., 1./1.e3, 0., 0.] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0, 0], [0.5, 0, 0.5, 0.5*1e-3], [0, 1.0, 0, 0], [0, 1, 0, 0] ]) assert np.allclose(correct, matrix, rtol=1e-3) def test_pe_artificial(self): """Test using three species artificial model with PE reactions from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('F <=> R', [1.0e3, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('R <=> P', [1.0, 0.0, 0.0])''') F = ct.Species('F', 'H:1') R = ct.Species('R', 'H:1') P = ct.Species('P', 'H:1') for sp in [F, R, P]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, R, P], reactions=[R1, R2] ) conc_R = 0.1 conc_F = ((1 + 1e-3)*conc_R - (1/2e3))/(1 - (1/2e3)) conc_P = 1.0 - (conc_R + conc_F) state = 1000, ct.one_atm, [conc_F, conc_R, conc_P] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [1./3., 0, 2./3.], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) def test_dormant_modes(self): """Test using three species artificial model with dormant modes from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('A <=> B', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('B <=> C', [1.0e-3, 0.0, 0.0])''') A = ct.Species('A', 'H:1') B = ct.Species('B', 'H:1') C = ct.Species('C', 'H:1') for sp in [A, B, C]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[A, B, C], reactions=[R1, R2] ) state = 1000, ct.one_atm, [1.0, 2.0, 1.0] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [1/(1+1e-3), 0, 1e-3/(1+1e-3)], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) conc_A = 1.370536 conc_B = 1.370480 conc_C = 1.258985 state = 1000, ct.one_atm, [conc_A, conc_B, conc_C] matrix = create_drg_matrix(state, model) correct = np.array([ [0, 1.0, 0], [abs(conc_A-conc_B)/(abs(conc_A-conc_B)+1e-3*abs(conc_B-conc_C)), 0, 1e-3*abs(conc_B-conc_C)/(abs(conc_A-conc_B)+1e-3*abs(conc_B-conc_C)) ], [0, 1.0, 0], ]) assert np.allclose(correct, matrix, rtol=1e-3) @pytest.mark.skip def testArtificial(self): """Uses artificial mechanism to test""" # Load model path_to_original = relative_location("artificial-mechanism.cti") solution_object = ct.Solution(path_to_original) # Pull out timestep one denomenator and numerator dicts ic_one = rate_edge_data[list(rate_edge_data.keys())[0]] tstep_one = ic_one[list(ic_one.keys())[0]] denoms = tstep_one[0] numers = tstep_one[1] # Expected values for denomenators expected_denoms = {} expected_denoms["H2O"] = 1.9573216e-13 expected_denoms["H2"] = .00025854374 expected_denoms["O2"] = 9.7866081e-14 expected_denoms["H"] = .00051708749 assert np.isclose(expected_denoms["H2O"], denoms["H2O"],abs_tol=1.0e-17) assert np.isclose(expected_denoms["H2"], denoms["H2"],abs_tol=1.0e-10) assert np.isclose(expected_denoms["O2"], denoms["O2"],abs_tol=1.0e-18) assert np.isclose(expected_denoms["H"], denoms["H"],abs_tol=1.0e-10) expected_numers = {} expected_numers["H2O_H2"] = 1.9573216e-13 expected_numers["H2O_O2"] = 1.9573216e-13 expected_numers["H2_O2"] = 1.9573216e-13 expected_numers["H2_H2O"] = 1.9573216e-13 expected_numers["O2_H2"] = 9.7866081e-14 expected_numers["O2_H2O"] = 9.7866081e-14 expected_numers["H2_H"] = .00025854374 expected_numers["H_H2"] = .00051708749 assert np.isclose(expected_numers["H2O_H2"],numers["H2O_H2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2O_O2"],numers["H2O_O2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2_O2"],numers["H2_O2"],abs_tol=1.0e-17) assert np.isclose(expected_numers["H2_H2O"],numers["H2_H2O"],abs_tol=1.0e-17) assert np.isclose(expected_numers["O2_H2"],numers["O2_H2"],abs_tol=1.0e-18) assert np.isclose(expected_numers["O2_H2O"],numers["O2_H2O"],abs_tol=1.0e-18) assert np.isclose(expected_numers["H2_H"],numers["H2_H"],abs_tol=1.0e-18) assert np.isclose(expected_numers["H_H2"],numers["H_H2"],abs_tol=1.0e-18) class TestTrimDRG: """Tests for trim_drg method""" def test_simple(self): matrix = np.array([[0, 1, 0.1], [0.5, 0, 0.5], [0.5, 0.5, 0]]) names = ['A', 'B', 'C'] reached = trim_drg(matrix, names, ['A'], 0.2) assert check_equal(reached, names) reached = trim_drg(matrix, names, ['A'], 0.6) assert check_equal(reached, ['A', 'B']) def test_uncoupled_group(self): """Test of simple five-component graph from DRG papers. """ matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['A'], 0.1) assert check_equal(reached, ['A', 'B', 'D']) matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['E'], 0.1) assert check_equal(reached, ['E', 'F']) def test_uncoupled_group2(self): """Test of simple five-component graph from DRG papers. """ matrix = np.array([ [0, 0.5, 0, 0, 0, 0], [0, 0, 0.15, 0.9, 0, 0], [0, 0.5, 0, 0.5, 0, 0], [0, 0.9, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1.0], [0, 0, 0, 0, 1.0, 0] ]) names = ['A', 'B', 'C', 'D', 'E', 'F'] reached = trim_drg(matrix, names, ['A'], 0.1) assert check_equal(reached, ['A', 'B', 'C', 'D']) reached = trim_drg(matrix, names, ['A'], 0.2) assert check_equal(reached, ['A', 'B', 'D']) def test_csp_mech5(self): """Test of simple mech 5 from 2006 DRG paper. """ R1 = ct.Reaction.fromCti('''reaction('F => P', [1.0, 0.0, 0.0])''') R2 = ct.Reaction.fromCti('''reaction('F => R', [1.0e-2, 0.0, 0.0])''') R3 = ct.Reaction.fromCti('''reaction('R => P', [1.0e2, 0.0, 0.0])''') F = ct.Species('F', 'H:1') P = ct.Species('P', 'H:1') R = ct.Species('R', 'H:1') for sp in [F, P, R]: sp.thermo = ct.ConstantCp( 300, 1000, 101325, (300, 1.0, 1.0, 1.0) ) model = ct.Solution( thermo='IdealGas', kinetics='GasKinetics', species=[F, P, R], reactions=[R1, R2, R3] ) state = 1000, ct.one_atm, [1.0, 1.0, 1.0e-4] matrix = create_drg_matrix(state, model) reached = trim_drg(matrix, ['F', 'P', 'R'], ['F'], 0.1) assert check_equal(reached, ['F', 'P']) class TestGraphSearch: """Tests for graph_search method""" #generate test graph #starting from A, nodes A,E,C,F,D,I,H,O should be the only nodes found def testGraphSearchOneInput(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), # ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) subgraph = nx.DiGraph([(u,v,d) for u,v,d in graph.edges(data=True) if d['weight'] > 0]) #temporary solution essential_nodes = graph_search(subgraph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] #generate test graph #starting from A, nodes A,E,C,F,D,I,H,O should be the only nodes found def testGraphSearchOneInput2(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), # ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) subgraph = nx.DiGraph([(u,v,d) for u,v,d in graph.edges(data=True) if d['weight'] > 0]) #temporary solution essential_nodes = graph_search(subgraph, 'G') assert 'G' in essential_nodes for n in ['A','B', 'C', 'D', 'J', 'K', 'I', 'O', 'F', 'E', 'H', 'M', 'N']: assert n not in essential_nodes assert [n in essential_nodes for n in [ 'G', 'L']] def testGraphSearch3Inputs(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from( [ ('C','F', 1), ('A','C', 1), #('A','F', 0), ('A','N', 0), ('N','C', 1), ('C','D', 1), ('D','I', 1), ('I','O', 1), ('A','E', 1), #('E','G', 0), ('G','I', 0), ('G','M', 0), ('G','L', 1), ('E','H', 1), #('H','J', 0) ]) target_species= ['A', 'C', 'D'] essential_nodes = graph_search(graph, target_species) assert 'A' in essential_nodes assert 'C' in essential_nodes assert 'D' in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']: assert n in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']: assert n not in essential_nodes def testgraphsearch_no_targets (self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, []) assert not essential_nodes @pytest.mark.xfail def testGraphshearchwithatargetThatsnotinGraph(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, 'Z') assert 'Z' in essential_nodes def testGraphsearchforinfinteloops(self): graph = nx.DiGraph() graph.add_nodes_from(['A', 'B', 'C', 'D', 'E']) graph.add_weighted_edges_from( [('A', 'B', 1), ('B', 'C', 1), ('C', 'D', 1), ('D', 'E',1), ('E', 'A', 1)] ) essential_nodes= graph_search(graph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'B', 'E']] @pytest.mark.xfail def testGraphShearchWithATargetThatsNotInGraphAndOneThatIs(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, ['B', 'Z']) assert 'B' in essential_nodes def testGraphsearchwithListofLength1(self): graph = nx.DiGraph() graph.add_node('A') essential_nodes = graph_search(graph, 'A') assert 'A' in essential_nodes assert len(essential_nodes) == 1 def testGraphSearchWithTwoOfTheSameItemInTheGraph(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F',0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, 'A') assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] def testGraphSearchWithTwoOfTheSameItemInTheTargetList(self): graph = nx.DiGraph() graph.add_nodes_from( ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O'] ) graph.add_weighted_edges_from([ #('A','F', 0), ('A','N',0), ('C','F',1.0), ('A','C',1.0), ('N','C',1.0), ('C','D',1.0), ('D','I',1.0), ('I','O',1.0), ('A','E',1.0), #('E','G',0), ('G','I',0), ('G','M',0), ('G','L',1.0), ('E','H',1.0), #('H','J',0) ]) essential_nodes = graph_search(graph, ['A','A']) assert 'A' in essential_nodes assert [n in essential_nodes for n in ['A', 'C', 'D', 'I', 'O', 'F', 'E', 'H']] assert [n not in essential_nodes for n in ['B', 'G', 'J', 'K', 'L', 'M', 'N']] class TestReduceDRG: def test_gri_reduction_multiple_cases(self): """Tests reduce_drg method with multiple cases""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), InputIgnition( kind='constant volume', pressure=1.0, temperature=1200.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data = np.genfromtxt( relative_location(os.path.join('assets', 'example_ignition_data.dat')), delimiter=',' ) model = ct.Solution(model_file) matrices = [] for state in data: matrices.append(create_drg_matrix((state[0], state[1], state[2:]), model)) with TemporaryDirectory() as temp_dir: reduced_model = reduce_drg( model_file, ['CH4', 'O2'], ['N2'], 0.14, matrices, conditions, np.array([1.066766136745876281e+00, 4.334773545084597696e-02]), previous_model=None, threshold_upper=None, num_threads=1, path=temp_dir ) expected_species = [ 'H2', 'H', 'O', 'O2', 'OH', 'H2O', 'HO2', 'H2O2', 'C', 'CH', 'CH2', 'CH2(S)', 'CH3', 'CH4', 'CO', 'CO2', 'HCO', 'CH2O', 'CH2OH', 'CH3O', 'C2H2', 'C2H3', 'C2H4', 'C2H5', 'C2H6', 'HCCO', 'CH2CO', 'N', 'NH', 'NNH', 'NO', 'N2O', 'HNO', 'CN', 'HCN', 'H2CN', 'HCNN', 'NCO', 'N2', 'CH2CHO' ] assert check_equal(reduced_model.model.species_names, expected_species) assert reduced_model.model.n_reactions == 245 assert round(reduced_model.error, 2) == 3.64 def test_gri_reduction_limbo(self): """Tests reduce_drg method with limbo species""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data = np.genfromtxt( relative_location(os.path.join('assets', 'example_ignition_data.dat')), delimiter=',' ) model = ct.Solution(model_file) matrices = [] for state in data: matrices.append(create_drg_matrix((state[0], state[1], state[2:]), model)) with TemporaryDirectory() as temp_dir: reduced_model = reduce_drg( model_file, ['CH4', 'O2'], ['N2'], 0.14, matrices, conditions, np.array([1.066766136745876281e+00]), previous_model=None, threshold_upper=0.6, num_threads=1, path=temp_dir ) expected_species = [ 'H2', 'H', 'O', 'O2', 'OH', 'H2O', 'HO2', 'H2O2', 'C', 'CH', 'CH2', 'CH2(S)', 'CH3', 'CH4', 'CO', 'CO2', 'HCO', 'CH2O', 'CH2OH', 'CH3O', 'C2H2', 'C2H3', 'C2H4', 'C2H5', 'C2H6', 'HCCO', 'CH2CO', 'N', 'NH', 'NNH', 'NO', 'N2O', 'HNO', 'CN', 'HCN', 'H2CN', 'HCNN', 'NCO', 'N2', 'CH2CHO' ] expected_limbo_species = ['H', 'CH3', 'CH4', 'OH', 'HO2', 'O', 'H2O', 'O2'] assert check_equal(reduced_model.model.species_names, expected_species) assert check_equal(reduced_model.limbo_species, expected_limbo_species) class TestRunDRG: def test_gri_reduction(self): """Tests driver run_drg method""" model_file = 'gri30.cti' # Conditions for reduction conditions = [ InputIgnition( kind='constant volume', pressure=1.0, temperature=1000.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), InputIgnition( kind='constant volume', pressure=1.0, temperature=1200.0, equivalence_ratio=1.0, fuel={'CH4': 1.0}, oxidizer={'O2': 1.0, 'N2': 3.76} ), ] data_files['output_ignition'] = relative_location( os.path.join('assets', 'example_ignition_output.txt') ) data_files['data_ignition'] = relative_location( os.path.join('assets', 'example_ignition_data.dat') ) error = 5.0 # Run DRG with TemporaryDirectory() as temp_dir: reduced_model = run_drg( model_file, conditions, [], [], error, ['CH4', 'O2'], ['N2'], num_threads=1, path=temp_dir ) # Expected answer expected_model = ct.Solution(relative_location(os.path.join('assets', 'drg_gri30.cti'))) # Make sure models are the same assert check_equal(reduced_model.model.species_names, expected_model.species_names) assert reduced_model.model.n_reactions == expected_model.n_reactions assert round(reduced_model.error, 2) == 3.64

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stagifyapi/api/migrations/0004_create_artist.py

Davee02/Stagify

0

101718

<reponame>Davee02/Stagify # Generated by Django 3.1.3 on 2020-12-10 14:25 import api.models from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("api", "0003_delete_old"), ] operations = [ migrations.CreateModel( name="Artist", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("displayname", models.CharField(max_length=500)), ("description", models.CharField(max_length=10000)), ( "avatar", models.FileField( storage=api.models.select_storage, upload_to="artist_avatars" ), ), ], ), ]

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