content
stringlengths 1
1.04M
| input_ids
listlengths 1
774k
| ratio_char_token
float64 0.38
22.9
| token_count
int64 1
774k
|
|---|---|---|---|
import os,sys
from caffe.proto import caffe_pb2
import google.protobuf.text_format as txtf
prototxt_file=sys.argv[1]
to_prototxt_file=sys.argv[2]
hold_layers=sys.argv[3].split(',')
model=caffe_pb2.NetParameter()
with open(prototxt_file,'r') as f:
txtf.Merge(f.read(),model)
f.close()
active_layers={}
i=0
for layer in model.layer:
if len(layer.param)>0:
isActive=False
for param in layer.param:
isActive=param.lr_mult>0 or param.decay_mult>0
if isActive:
break
active_layers[layer.name]=i
i+=1
print active_layers
print model.layer[active_layers['cls']]
for lname in active_layers.keys():
if lname in hold_layers:
continue
nParam=len(model.layer[active_layers[lname]].param)
for n in range(nParam):
model.layer[active_layers[lname]].param[n].lr_mult=0
model.layer[active_layers[lname]].param[n].decay_mult=0
with open(to_prototxt_file,'w') as f:
f.write(str(model))
f.close()
print 'finished'
|
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58,
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4083,
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62,
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28,
15,
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220,
220,
220,
220,
220,
220,
220,
2746,
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62,
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58,
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12501,
323,
62,
16680,
28,
15,
198,
198,
4480,
1280,
7,
1462,
62,
11235,
313,
742,
62,
7753,
4032,
86,
11537,
355,
277,
25,
198,
220,
220,
220,
277,
13,
13564,
7,
2536,
7,
19849,
4008,
198,
220,
220,
220,
277,
13,
19836,
3419,
198,
198,
4798,
705,
43952,
6
] | 2.117043 | 487 |
import base64
import json
import pickle
from typing import Optional, TYPE_CHECKING, Type, Dict, Any, Union
from ...helper import compress_bytes, decompress_bytes
if TYPE_CHECKING:
from ...typing import T
|
[
11748,
2779,
2414,
198,
11748,
33918,
198,
11748,
2298,
293,
198,
6738,
19720,
1330,
32233,
11,
41876,
62,
50084,
2751,
11,
5994,
11,
360,
713,
11,
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2751,
25,
198,
220,
220,
220,
422,
2644,
774,
13886,
1330,
309,
628
] | 3.349206 | 63 |
from .rest_api_base import *
# First Metrics Methods appear in API 3.9
|
[
6738,
764,
2118,
62,
15042,
62,
8692,
1330,
1635,
198,
198,
2,
3274,
3395,
10466,
25458,
1656,
287,
7824,
513,
13,
24,
628,
198
] | 3.083333 | 24 |
from factory import Faker
from factory.django import DjangoModelFactory
|
[
6738,
8860,
1330,
376,
3110,
198,
6738,
8860,
13,
28241,
14208,
1330,
37770,
17633,
22810,
628
] | 4.5625 | 16 |
"""2021 - Day 16 Part 2: Packet Decoder."""
from src.year2021.day16a import BITS
|
[
37811,
1238,
2481,
532,
3596,
1467,
2142,
362,
25,
6400,
316,
34580,
526,
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13,
1941,
1238,
2481,
13,
820,
1433,
64,
1330,
347,
29722,
628
] | 2.827586 | 29 |
banyakPerulangan = 10
i = 0
while (i < banyakPerulangan):
print('Hello World')
i += 1
|
[
65,
1092,
461,
5990,
377,
37089,
796,
838,
198,
72,
796,
657,
198,
4514,
357,
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275,
1092,
461,
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220,
3601,
10786,
15496,
2159,
11537,
198,
220,
220,
220,
1312,
15853,
352
] | 2.325 | 40 |
from .base import DependencyBase, dataclass
@dataclass
class Tag(DependencyBase):
""" Dependency on an arbitrary tag
Usage:
use this tag as a named signal to invalidate records
Example:
update_dashboard_for_admins = Tag('update-dashboard-for-admins')
cache.put(
'articles-list',
[...],
dependencies=[
update_dashboard_for_admins,
...
]
)
cache.invalidate(update_dashboard_for_admins)
"""
name: str
__slots__ = 'name',
PREFIX = 'tag'
|
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220,
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7,
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220,
220,
220,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2644,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
12940,
13,
259,
12102,
378,
7,
19119,
62,
42460,
3526,
62,
1640,
62,
324,
42951,
8,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1438,
25,
965,
198,
220,
220,
220,
11593,
6649,
1747,
834,
796,
705,
3672,
3256,
628,
220,
220,
220,
22814,
47084,
796,
705,
12985,
6,
628
] | 2.103571 | 280 |
import os
from django.db import models
from django.contrib.auth.models import User
from django.urls import reverse
from django.dispatch import receiver
from django.db.models.signals import post_delete, post_save
from django.conf import settings
from django.core.validators import int_list_validator
from taggit.managers import TaggableManager
# Create your models here.
@receiver(post_save, sender=Task)
@receiver(post_delete, sender=Task)
|
[
11748,
28686,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
4981,
198,
6738,
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14208,
13,
3642,
822,
13,
18439,
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11787,
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7621,
18300,
13,
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1330,
309,
9460,
540,
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2,
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7,
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198,
31,
260,
39729,
7,
7353,
62,
33678,
11,
29788,
28,
25714,
8,
198
] | 3.308824 | 136 |
from fitrate.utils import gcd, nthrt, prod
|
[
6738,
4197,
4873,
13,
26791,
1330,
308,
10210,
11,
299,
400,
17034,
11,
40426,
628,
628
] | 2.875 | 16 |
# Generated by Django 3.0.8 on 2020-10-22 04:45
from django.db import migrations
|
[
2,
2980,
515,
416,
37770,
513,
13,
15,
13,
23,
319,
12131,
12,
940,
12,
1828,
8702,
25,
2231,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
628
] | 2.766667 | 30 |
import machine
import time
|
[
11748,
4572,
198,
11748,
640,
198
] | 4.5 | 6 |
import torch
import torch.nn as nn
from utils.miscellaneous import progress_bar
|
[
11748,
28034,
198,
11748,
28034,
13,
20471,
355,
299,
77,
198,
198,
6738,
3384,
4487,
13,
25413,
25673,
1330,
4371,
62,
5657
] | 3.636364 | 22 |
import os
import cv2
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.patches import Polygon
from .dataset_localization import DatasetLocalization
from odin.utils import Iterator
from .visulizer_interface import VisualizerInterface
from odin.classes import strings as labels_str
|
[
11748,
28686,
198,
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269,
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17,
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11748,
299,
32152,
355,
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198,
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29487,
355,
458,
83,
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2603,
29487,
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13,
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12280,
14520,
198,
6738,
764,
19608,
292,
316,
62,
12001,
1634,
1330,
16092,
292,
316,
14565,
1634,
198,
6738,
16298,
259,
13,
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1330,
40806,
1352,
198,
6738,
764,
4703,
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62,
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198,
6738,
16298,
259,
13,
37724,
1330,
13042,
355,
14722,
62,
2536,
628
] | 3.607143 | 84 |
'''
Es un méotod de compresión muy sencillo.
Bonzip
'''
import bz2
#Cadena binaria
cadena = b'Este es eun ejemplo del formato de compresion Bonzip, sirve para comprimir TODO.'
cadena_comprimida = bz2.compress(cadena)
print(cadena_comprimida)#b"BZh91AY&SY\xbf\xb8:\xfa\x00\x00\x06\x15\x80@\x04\x08\x00.\xa3\xde@ \x00Hj\x9f\xaayL\xd3'\xa8 \xd4\xd3\xd2i\xa0hb)\xd3Aw\x8d2\x12\x8c\xf8\xc6\xa2q\xc2\x15\xf8-\x1a\xad\x85B\xc6`+\xe1\xfdr>\t\x12.\xe4\x8ap\xa1!\x7fpu\xf4"
#para descromprimir
print(bz2.decompress(cadena_comprimida))
|
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] | 1.753289 | 304 |
import re
import random
|
[
11748,
302,
198,
11748,
4738,
628,
198
] | 3.714286 | 7 |
# test_spiderfootplugin.py
import pytest
import unittest
from sflib import SpiderFoot
from spiderfoot import SpiderFootDb, SpiderFootEvent, SpiderFootPlugin, SpiderFootTarget
@pytest.mark.usefixtures
class TestSpiderFootPlugin(unittest.TestCase):
"""
Test SpiderFoot
"""
def test_init(self):
"""
Test __init__(self)
"""
sfp = SpiderFootPlugin()
self.assertIsInstance(sfp, SpiderFootPlugin)
def test_updateSocket(self):
"""
Test _updateSocket(self, sock)
"""
sfp = SpiderFootPlugin()
sfp._updateSocket(None)
self.assertEqual('TBD', 'TBD')
def test_clearListeners(self):
"""
Test clearListeners(self)
"""
sfp = SpiderFootPlugin()
sfp.clearListeners()
self.assertEqual('TBD', 'TBD')
def test_setup(self):
"""
Test setup(self, sf, userOpts=dict())
"""
sfp = SpiderFootPlugin()
sfp.setup(None)
sfp.setup(None, None)
self.assertEqual('TBD', 'TBD')
def test_enrichTargetargument_target_should_enrih_target(self):
"""
Test enrichTarget(self, target)
"""
sfp = SpiderFootPlugin()
sfp.enrichTarget(None)
self.assertEqual('TBD', 'TBD')
def test_setTarget_should_set_a_target(self):
"""
Test setTarget(self, target)
"""
sfp = SpiderFootPlugin()
target = SpiderFootTarget("spiderfoot.net", "INTERNET_NAME")
sfp.setTarget(target)
get_target = sfp.getTarget().targetValue
self.assertIsInstance(get_target, str)
self.assertEqual("spiderfoot.net", get_target)
def test_setTarget_argument_target_invalid_type_should_raise_TypeError(self):
"""
Test setTarget(self, target)
"""
sfp = SpiderFootPlugin()
invalid_types = [None, "", list(), dict(), int()]
for invalid_type in invalid_types:
with self.subTest(invalid_type=invalid_type):
with self.assertRaises(TypeError):
sfp.setTarget(invalid_type)
def test_set_dbhargument_dbh_should_set_database_handle(self):
"""
Test setDbh(self, dbh)
"""
sfdb = SpiderFootDb(self.default_options, False)
sfp = SpiderFootPlugin()
sfp.setDbh(sfdb)
self.assertIsInstance(sfp.__sfdb__, SpiderFootDb)
def test_setScanId_argument_id_should_set_a_scan_id(self):
"""
Test setScanId(self, id)
"""
sfp = SpiderFootPlugin()
scan_id = '1234'
sfp.setScanId(scan_id)
get_scan_id = sfp.getScanId()
self.assertIsInstance(get_scan_id, str)
self.assertEqual(scan_id, get_scan_id)
def test_setScanId_argument_id_invalid_type_should_raise_TypeError(self):
"""
Test setScanId(self, id)
"""
sfp = SpiderFootPlugin()
invalid_types = [None, list(), dict(), int()]
for invalid_type in invalid_types:
with self.subTest(invalid_type=invalid_type):
with self.assertRaises(TypeError):
sfp.setScanId(invalid_type)
def test_getScanId_should_return_a_string(self):
"""
Test getScanId(self)
"""
sfp = SpiderFootPlugin()
scan_id = 'example scan id'
sfp.setScanId(scan_id)
get_scan_id = sfp.getScanId()
self.assertIsInstance(get_scan_id, str)
self.assertEqual(scan_id, get_scan_id)
def test_getScanId_unitialised_scanid_should_raise_TypeError(self):
"""
Test getScanId(self)
"""
sfp = SpiderFootPlugin()
with self.assertRaises(TypeError):
sfp.getScanId()
def test_getTarget_should_return_a_string(self):
"""
Test getTarget(self)
"""
sfp = SpiderFootPlugin()
target = SpiderFootTarget("spiderfoot.net", "INTERNET_NAME")
sfp.setTarget(target)
get_target = sfp.getTarget().targetValue
self.assertIsInstance(get_target, str)
self.assertEqual("spiderfoot.net", get_target)
def test_getTarget_unitialised_target_should_raise(self):
"""
Test getTarget(self)
"""
sfp = SpiderFootPlugin()
with self.assertRaises(TypeError):
sfp.getTarget()
def test_register_listener(self):
"""
Test registerListener(self, listener)
"""
sfp = SpiderFootPlugin()
sfp.registerListener(None)
self.assertEqual('TBD', 'TBD')
def test_setOutputFilter_should_set_output_filter(self):
"""
Test setOutputFilter(self, types)
"""
sfp = SpiderFootPlugin()
output_filter = "test filter"
sfp.setOutputFilter("test filter")
self.assertEqual(output_filter, sfp.__outputFilter__)
def test_tempStorage_should_return_a_dict(self):
"""
Test tempStorage(self)
"""
sfp = SpiderFootPlugin()
temp_storage = sfp.tempStorage()
self.assertIsInstance(temp_storage, dict)
def test_notifyListeners_should_notify_listener_modules(self):
"""
Test notifyListeners(self, sfEvent)
"""
sfp = SpiderFootPlugin()
sfdb = SpiderFootDb(self.default_options, False)
sfp.setDbh(sfdb)
event_type = 'ROOT'
event_data = 'test data'
module = 'test module'
source_event = None
evt = SpiderFootEvent(event_type, event_data, module, source_event)
sfp.notifyListeners(evt)
self.assertEqual('TBD', 'TBD')
def test_notifyListeners_output_filter_matched_should_notify_listener_modules(self):
"""
Test notifyListeners(self, sfEvent)
"""
sfp = SpiderFootPlugin()
sfdb = SpiderFootDb(self.default_options, False)
sfp.setDbh(sfdb)
target = SpiderFootTarget("spiderfoot.net", "INTERNET_NAME")
sfp.setTarget(target)
event_type = 'ROOT'
event_data = 'test data'
module = 'test module'
source_event = None
evt = SpiderFootEvent(event_type, event_data, module, source_event)
event_type = 'test event type'
event_data = 'test data'
module = 'test module'
source_event = evt
evt = SpiderFootEvent(event_type, event_data, module, source_event)
sfp.__outputFilter__ = event_type
sfp.notifyListeners(evt)
self.assertEqual('TBD', 'TBD')
def test_notifyListeners_output_filter_unmatched_should_not_notify_listener_modules(self):
"""
Test notifyListeners(self, sfEvent)
"""
sfp = SpiderFootPlugin()
sfdb = SpiderFootDb(self.default_options, False)
sfp.setDbh(sfdb)
target = SpiderFootTarget("spiderfoot.net", "INTERNET_NAME")
sfp.setTarget(target)
event_type = 'ROOT'
event_data = 'test data'
module = 'test module'
source_event = None
evt = SpiderFootEvent(event_type, event_data, module, source_event)
event_type = 'test event type'
event_data = 'test data'
module = 'test module'
source_event = evt
evt = SpiderFootEvent(event_type, event_data, module, source_event)
sfp.__outputFilter__ = "example unmatched event type"
sfp.notifyListeners(evt)
self.assertEqual('TBD', 'TBD')
def test_notifyListeners_event_type_and_data_same_as_source_event_source_event_should_story_only(self):
"""
Test notifyListeners(self, sfEvent)
"""
sfp = SpiderFootPlugin()
sfdb = SpiderFootDb(self.default_options, False)
sfp.setDbh(sfdb)
event_type = 'ROOT'
event_data = 'test data'
module = 'test module'
source_event = None
evt = SpiderFootEvent(event_type, event_data, module, source_event)
event_type = 'test event type'
event_data = 'test data'
module = 'test module'
source_event = evt
evt = SpiderFootEvent(event_type, event_data, module, source_event)
source_event = evt
evt = SpiderFootEvent(event_type, event_data, module, source_event)
source_event = evt
evt = SpiderFootEvent(event_type, event_data, module, source_event)
sfp.notifyListeners(evt)
self.assertEqual('TBD', 'TBD')
def test_notifyListeners_argument_sfEvent_invalid_event_should_raise_TypeError(self):
"""
Test notifyListeners(self, sfEvent)
"""
sfp = SpiderFootPlugin()
invalid_types = [None, "", list(), dict(), int()]
for invalid_type in invalid_types:
with self.subTest(invalid_type=invalid_type):
with self.assertRaises(TypeError):
sfp.notifyListeners(invalid_type)
def test_checkForStop(self):
"""
Test checkForStop(self)
"""
sfp = SpiderFootPlugin()
sfp.__sfdb__ = DatabaseStub()
sfp.__scanId__ = 'example scan id'
# pseudo-parameterized test
scan_statuses = [
(None, False),
("anything", False),
("RUNNING", False),
("ABORT-REQUESTED", True)
]
for status, expectedReturnValue in scan_statuses:
returnValue = sfp.checkForStop()
self.assertEqual(returnValue, expectedReturnValue, status)
def test_watchedEvents_should_return_a_list(self):
"""
Test watchedEvents(self)
"""
sfp = SpiderFootPlugin()
watched_events = sfp.watchedEvents()
self.assertIsInstance(watched_events, list)
def test_producedEvents_should_return_a_list(self):
"""
Test producedEvents(self)
"""
sfp = SpiderFootPlugin()
produced_events = sfp.producedEvents()
self.assertIsInstance(produced_events, list)
def test_handleEvent(self):
"""
Test handleEvent(self, sfEvent)
"""
event_type = 'ROOT'
event_data = 'example event data'
module = ''
source_event = ''
evt = SpiderFootEvent(event_type, event_data, module, source_event)
sfp = SpiderFootPlugin()
sfp.handleEvent(evt)
def test_start(self):
"""
Test start(self)
"""
sf = SpiderFoot(self.default_options)
sfp = SpiderFootPlugin()
sfp.sf = sf
sfp.start()
|
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] | 2.162667 | 4,875 |
# Copyright The PyTorch Lightning team.
#
# 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.
"""Helper functions to help with reproducibility of models. """
import logging
import os
import random
from typing import Optional
import numpy as np
import torch
from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_7, rank_zero_warn
from pytorch_lightning.utilities.distributed import rank_zero_only
log = logging.getLogger(__name__)
def seed_everything(seed: Optional[int] = None, workers: bool = False) -> int:
"""
Function that sets seed for pseudo-random number generators in:
pytorch, numpy, python.random
In addition, sets the following environment variables:
- `PL_GLOBAL_SEED`: will be passed to spawned subprocesses (e.g. ddp_spawn backend).
- `PL_SEED_WORKERS`: (optional) is set to 1 if ```workers=True``.
Args:
seed: the integer value seed for global random state in Lightning.
If `None`, will read seed from `PL_GLOBAL_SEED` env variable
or select it randomly.
workers: if set to ``True``, will properly configure all dataloaders passed to the
Trainer with a ``worker_init_fn``. If the user already provides such a function
for their dataloaders, setting this argument will have no influence. See also:
:func:`~pytorch_lightning.utilities.seed.pl_worker_init_function`.
"""
max_seed_value = np.iinfo(np.uint32).max
min_seed_value = np.iinfo(np.uint32).min
try:
if seed is None:
seed = os.environ.get("PL_GLOBAL_SEED")
seed = int(seed)
except (TypeError, ValueError):
seed = _select_seed_randomly(min_seed_value, max_seed_value)
rank_zero_warn(f"No correct seed found, seed set to {seed}")
if not (min_seed_value <= seed <= max_seed_value):
rank_zero_warn(f"{seed} is not in bounds, numpy accepts from {min_seed_value} to {max_seed_value}")
seed = _select_seed_randomly(min_seed_value, max_seed_value)
# using `log.info` instead of `rank_zero_info`,
# so users can verify the seed is properly set in distributed training.
log.info(f"Global seed set to {seed}")
os.environ["PL_GLOBAL_SEED"] = str(seed)
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
os.environ["PL_SEED_WORKERS"] = f"{int(workers)}"
return seed
def reset_seed() -> None:
"""
Reset the seed to the value that :func:`pytorch_lightning.utilities.seed.seed_everything` previously set.
If :func:`pytorch_lightning.utilities.seed.seed_everything` is unused, this function will do nothing.
"""
seed = os.environ.get("PL_GLOBAL_SEED", None)
workers = os.environ.get("PL_SEED_WORKERS", False)
if seed is not None:
seed_everything(int(seed), workers=bool(workers))
def pl_worker_init_function(worker_id: int, rank: Optional = None) -> None: # pragma: no cover
"""
The worker_init_fn that Lightning automatically adds to your dataloader if you previously set
set the seed with ``seed_everything(seed, workers=True)``.
See also the PyTorch documentation on
`randomness in DataLoaders <https://pytorch.org/docs/stable/notes/randomness.html#dataloader>`_.
"""
# implementation notes: https://github.com/pytorch/pytorch/issues/5059#issuecomment-817392562
global_rank = rank if rank is not None else rank_zero_only.rank
process_seed = torch.initial_seed()
# back out the base seed so we can use all the bits
base_seed = process_seed - worker_id
log.debug(
f'Initializing random number generators of process {global_rank} worker {worker_id} with base seed {base_seed}'
)
ss = np.random.SeedSequence([base_seed, worker_id, global_rank])
# use 128 bits (4 x 32-bit words)
np.random.seed(ss.generate_state(4))
# Spawn distinct SeedSequences for the PyTorch PRNG and the stdlib random module
torch_ss, stdlib_ss = ss.spawn(2)
# PyTorch 1.7 and above takes a 64-bit seed
dtype = np.uint64 if _TORCH_GREATER_EQUAL_1_7 else np.uint32
torch.manual_seed(torch_ss.generate_state(1, dtype=dtype)[0])
# use 128 bits expressed as an integer
stdlib_seed = (stdlib_ss.generate_state(2, dtype=np.uint64).astype(object) * [1 << 64, 1]).sum()
random.seed(stdlib_seed)
|
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329,
262,
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220,
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62,
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11,
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62,
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13,
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7,
17,
8,
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22,
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357,
19282,
8019,
62,
824,
13,
8612,
378,
62,
5219,
7,
17,
11,
288,
4906,
28,
37659,
13,
28611,
2414,
737,
459,
2981,
7,
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8,
1635,
685,
16,
9959,
5598,
11,
352,
35944,
16345,
3419,
198,
220,
220,
220,
4738,
13,
28826,
7,
19282,
8019,
62,
28826,
8,
198
] | 2.76484 | 1,752 |
from distutils.log import error
import errno
import numpy as np
import json
import argparse
import time
from tqdm import tqdm
import cv2
import logging
import sys, os
import torch
import torchvision
import torch.nn as nn
from torch import optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from torchvision.transforms import transforms
from sklearn.metrics import f1_score
from sampler import BalancedBatchSampler
from models import Resnext_Model, Densenet_Model
from dataloader import MBV_Dataset
sys.path.append(os.path.dirname(__file__))
from train_util import Train_Util
sys.path.append(os.path.dirname(__file__))
from utils import *
from mbv_config import MBV_Config
import mbv_config
import argparse
if __name__ == "__main__":
train()
|
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1330,
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285,
65,
85,
62,
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1330,
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53,
62,
16934,
198,
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285,
65,
85,
62,
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198,
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1822,
29572,
628,
628,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
4512,
3419,
198
] | 3.226721 | 247 |
import json
import click
from tabulate import tabulate
from spplib.cli import util
@click.group()
@util.pass_context
def cli(ctx, **kwargs):
"""VM resource.
"""
pass
@cli.command()
@util.pass_context
@click.argument('pattern')
|
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198,
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] | 2.714286 | 91 |
from django.contrib import admin
from .models import immobilien
admin.site.register(immobilien, immobilienAdmin)
# Register your models here.
|
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] | 3.560976 | 41 |
class Alarma():
"""clase del objeto alarma"""
|
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4871,
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1619,
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] | 2.722222 | 18 |
begin_unit
comment|'# Licensed under the Apache License, Version 2.0 (the "License"); you may not'
nl|'\n'
comment|'# use this file except in compliance with the License. You may obtain a copy'
nl|'\n'
comment|'# of the License at'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# http://www.apache.org/licenses/LICENSE-2.0'
nl|'\n'
comment|'#'
nl|'\n'
comment|'# Unless required by applicable law or agreed to in writing, software'
nl|'\n'
comment|'# distributed under the License is distributed on an "AS IS" BASIS,'
nl|'\n'
comment|'# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.'
nl|'\n'
comment|'# See the License for the specific language governing permissions and'
nl|'\n'
comment|'# limitations under the License.'
nl|'\n'
nl|'\n'
name|'import'
name|'nova'
op|'.'
name|'compute'
op|'.'
name|'flavors'
newline|'\n'
name|'import'
name|'nova'
op|'.'
name|'compute'
op|'.'
name|'monitors'
newline|'\n'
name|'import'
name|'nova'
op|'.'
name|'conf'
newline|'\n'
nl|'\n'
nl|'\n'
DECL|function|list_opts
name|'def'
name|'list_opts'
op|'('
op|')'
op|':'
newline|'\n'
indent|' '
name|'return'
op|'['
nl|'\n'
op|'('
string|"'DEFAULT'"
op|','
nl|'\n'
name|'nova'
op|'.'
name|'compute'
op|'.'
name|'flavors'
op|'.'
name|'flavor_opts'
op|','
nl|'\n'
op|')'
op|','
nl|'\n'
op|']'
newline|'\n'
dedent|''
endmarker|''
end_unit
|
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198,
437,
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263,
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] | 2.23913 | 598 |
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
from numpy import pi,abs,exp,log,log10
from scipy import optimize
class RoweOptimization():
'''
Optimizing the Rowe Model onto a training set. The key parameters to adjust
are as follows:
- G_ee
- G_ei
- G_ese
- G_esre
- G_srs
- alpha
- beta
- t0
- A_EMG
- f_EMG
'''
def optimize(self, param_list, tol=None):
'''
Fits the model using the listed parameters.
'''
# Define the function w.r.t. the parameters. The vector P has the same
# length as params, with 1-1 coordinate correspondance.
EEG_fun = lambda P: self.mod.update_and_compute_P(P, param_list, self.freqs)
chi_fun = lambda P: sum(((EEG_fun(P) - self.output) / self.output)**2)
# Get initial parameter values
P0 = []
for j in range(len(param_list)):
P0.append(getattr(self.mod, param_list[j]))
P0 = np.array(P0)
# Obtain the bounds for the optimization procedure w.r.t. the selected
# parameters.
bounds_list = []
for k in range(len(param_list)):
bound_attr_str = 'bound_' + param_list[k]
# Check if model has the bound attribute.
if not hasattr(self.mod, bound_attr_str):
bounds_list.append((None,None))
else:
bounds_list.append(tuple(getattr(self.mod, bound_attr_str)))
bounds_tuple = tuple(bounds_list)
# Initiate the optimization
result = optimize.minimize(chi_fun, P0, bounds=bounds_list, tol=tol)
return result
if __name__ == '__main__':
task = 'optimize'
if task == 'optimize':
# Get training data
text_file = np.loadtxt('EEG_data.csv', skiprows=1, delimiter=',')
freqs = text_file[1:,0]
powers = text_file[1:,1]*10**24
N = min(len(freqs), len(powers))
train_data = [(freqs[k], powers[k]) for k in range(N)]
rowe_opt = RoweOptimization(train=train_data)
param_list = ['G_ee',
'G_ei',
'G_ese',
'G_esre',
'G_srs',
'alpha',
'beta',
't0',
'A_EMG'
]
result = rowe_opt.optimize(param_list, tol=5)
model_powers = rowe_opt.mod.compute_P(freqs)
plt.plot(freqs, powers, 'r--',
freqs, model_powers)
plt.show()
elif task == 'graph':
freqs = np.linspace(0.2,100, num=50)
mod = Rowe2015Model()
EEG = mod.compute_P(freqs) - mod.compute_P_EEG(freqs)
df_EEG = pd.DataFrame(np.squeeze(EEG))
df_EEG.abs().plot(logx=True,logy=True)
|
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201,
198,
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47764,
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13,
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28,
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28,
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8,
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220,
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201,
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220,
220,
201,
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201,
198,
220,
220,
220,
220,
220,
220,
220,
220
] | 1.754261 | 1,819 |
#graph_visualize.py
from graphviz import Digraph
import pairwise
# Given a vector of the form generated in pairwise.py for
# easy reading into NNs, produce a diagram of the represented graph
|
[
2,
34960,
62,
41464,
1096,
13,
9078,
198,
198,
6738,
4823,
85,
528,
1330,
7367,
1470,
198,
11748,
5166,
3083,
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198,
2,
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3555,
656,
399,
47503,
11,
4439,
257,
16362,
286,
262,
7997,
4823,
198
] | 3.660377 | 53 |
from machine.corpora import (
DictionaryTextAlignmentCorpus,
DictionaryTextCorpus,
MemoryText,
MemoryTextAlignmentCollection,
ParallelTextCorpus,
)
|
[
6738,
4572,
13,
10215,
38851,
1330,
357,
198,
220,
220,
220,
28261,
8206,
2348,
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11,
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220,
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198,
220,
220,
220,
42945,
8206,
45680,
385,
11,
198,
8,
628,
628,
628,
198
] | 2.949153 | 59 |
from unicodedata import name
import unittest
from app.models import Vote, User
|
[
6738,
28000,
9043,
1045,
1330,
1438,
198,
11748,
555,
715,
395,
198,
6738,
598,
13,
27530,
1330,
19175,
11,
11787,
198
] | 3.761905 | 21 |
import sys
# recursive search through bag dictionary:
# given a bag string, return only the name of the bag:
# ex: 1 light blue returns light blue
# given a bag string, return the quantity:
# ex: 1 light blue returns 1
f = open(sys.argv[1],"r")
L = []
for item in f:
L.append(item.strip())
# dictionary where key is bag and values are which bags can be stored:
bag_contains = dict()
for rule in L:
rule_list = rule.split(" ")
# this bag is always going to be the first 2 words:
this_bag = rule_list[0] + " " + rule_list[1]
# insert into dictionary:
if this_bag not in bag_contains:
bag_contains[this_bag] = []
i = 3
# loop through rest of list:
while i < len(rule_list):
word = rule_list[i].strip(",").strip(".")
# if we find a bag, grab the last 2 words (these will be the color)
if (word == "bag" or word == "bags"):
current_bag = rule_list[i-3] + " " + rule_list[i-2] + " " + rule_list[i-1]
# this means no bags
if get_bag(current_bag) != "no other":
bag_contains[this_bag].append(current_bag)
i += 1
print(search(bag_contains,"2 dark green"))
print(search(bag_contains,"1 shiny gold"))
|
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] | 2.73012 | 415 |
"One user repeatedly logs in, logs out. Allow interleaving with other actions"
from WebModel import Login, Logout
actions = (Login, Logout) # just these to allow interleaving
initial = 0
accepting = (0,)
graph = ((0, (Login, ( 'VinniPuhh', 'Correct' ), 'Success'), 1),
(1, (Logout, ( 'VinniPuhh', ), None), 0))
|
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] | 2.762712 | 118 |
import os
from django.test import TestCase
from django.contrib.staticfiles import finders
|
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] | 3.444444 | 27 |
import dlib
import cv2
import numpy as np
import sys
import models
import NonLinearLeastSquares
import ImageProcessing
from drawing import *
import FaceRendering
import utils
import os
import subprocess
print "Press T to draw the keypoints and the 3D model"
print "Press R to start recording to a video file"
#you need to download shape_predictor_68_face_landmarks.dat from the link below and unpack it where the solution file is
#http://sourceforge.net/projects/dclib/files/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2
#loading the keypoint detection model, the image and the 3D model
predictor_path = "../shape_predictor_68_face_landmarks.dat"
face_cvv_detector_path ="../mmod_human_face_detector.dat"
image_name = "../bnl/images/"+sys.argv[1]
#the smaller this value gets the faster the detection will work
#if it is too small, the user's face might not be detected
maxImageSizeForDetection = 960
#detector = dlib.cnn_face_detection_model_v1(face_cvv_detector_path)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predictor_path)
mean3DShape, blendshapes, mesh, idxs3D, idxs2D = utils.load3DFaceModel("../candide.npz")
projectionModel = models.OrthographicProjectionBlendshapes(blendshapes.shape[0])
modelParams = None
lockedTranslation = False
drawOverlay = False
cap = cv2.VideoCapture("../data/"+sys.argv[2]+".mp4")
fourcc = cv2.VideoWriter_fourcc(*'XVID')
# Check if camera opened successfully
if (cap.isOpened()== False):
print("Error opening video stream or file")
cameraImg = cap.read()[1]
writer = None
if writer is None:
print "Starting video writer"
writer = cv2.VideoWriter("../bnl/videos/"+sys.argv[1]+"-out.avi", fourcc, 25,(cameraImg.shape[1], cameraImg.shape[0]))
if writer.isOpened():
print "Writer succesfully opened"
else:
writer = None
print "Writer opening failed"
textureImg = cv2.imread(image_name)
textureCoords = utils.getFaceTextureCoords(textureImg, mean3DShape, blendshapes, idxs2D, idxs3D, detector, predictor)
renderer = FaceRendering.FaceRenderer(cameraImg, textureImg, textureCoords, mesh)
while True:
cameraImg = cap.read()[1]
try:
shapes2D = utils.getFaceKeypoints(cameraImg, detector, predictor, maxImageSizeForDetection)
if shapes2D is not None:
for shape2D in shapes2D:
#3D model parameter initialization
modelParams = projectionModel.getInitialParameters(mean3DShape[:, idxs3D], shape2D[:, idxs2D])
#3D model parameter optimization
modelParams = NonLinearLeastSquares.GaussNewton(modelParams, projectionModel.residual, projectionModel.jacobian, ([mean3DShape[:, idxs3D], blendshapes[:, :, idxs3D]], shape2D[:, idxs2D]), verbose=0)
#rendering the model to an image
shape3D = utils.getShape3D(mean3DShape, blendshapes, modelParams)
renderedImg = renderer.render(shape3D)
#blending of the rendered face with the image
mask = np.copy(renderedImg[:, :, 0])
renderedImg = ImageProcessing.colorTransfer(cameraImg, renderedImg, mask)
cameraImg = ImageProcessing.blendImages(renderedImg, cameraImg, mask,0.1)
#drawing of the mesh and keypoints
if drawOverlay:
drawPoints(cameraImg, shape2D.T)
drawProjectedShape(cameraImg, [mean3DShape, blendshapes], projectionModel, mesh, modelParams, lockedTranslation)
if writer is not None:
writer.write(cameraImg)
cv2.imshow('image', cameraImg)
key = cv2.waitKey(1)
if key == 27:
break
if key == ord('t'):
drawOverlay = not drawOverlay
except:
print("An exception occurred")
break
print "Stopping video writer"
writer.release()
writer = None
os.chdir('C://Users/Asus/')
# ffmpeg -i 1569831566308.jpeg-out.avi -i ../../data/superVideo2.mp4 -map 0:0 -map 1:1 -shortest 1569831566308.jpeg-out.mp4
subprocess.call(["ffmpeg", "-i", "../bnl/videos/"+sys.argv[1]+"-out.avi", "-i ", "../data/"+sys.argv[2]+".mp4", "-map ", "0:0", "-map ", "1:1", "-shortest", "../bnl/videos/"+sys.argv[1]+"-out.mp4" ])
|
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198
] | 2.419977 | 1,762 |
from auxiliar import receberInt
from time import sleep
# main
contador(1, 10, 1)
contador(10, 0, 2)
contador(receberInt('Digite o inicio: '), receberInt('Digite o fim: '), receberInt('Digite o passo: '))
input('\n\nPressione <enter> para continuar')
|
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# Generated by Django 2.2.2 on 2019-07-05 12:44
from django.db import migrations
|
[
2,
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628
] | 2.766667 | 30 |
import pickle
import numpy as np
import gurobipy as gp
from gurobipy import GRB
from tqdm.notebook import trange, tqdm
|
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] | 2.818182 | 44 |
# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/09_matching.ipynb (unless otherwise specified).
__all__ = ['calculate_distance', 'calib_table', 'align', 'calculate_deltas', 'align_files', 'align_datasets',
'get_probability', 'match_datasets']
# Cell
import pandas as pd
import numpy as np
def calculate_distance(table_1: pd.DataFrame, table_2: pd.DataFrame, offset_dict: dict, calib: bool = False) -> (list, int):
"""Calculate the distance between two precursors for different columns
Distance can either be relative or absolute.
An example for a minimal offset_dict is: offset_dict = {'mass':'absolute'}
Args:
table_1 (pd.DataFrame): Dataframe with precusor data.
table_2 (pd.DataFrame): Dataframe with precusor data.
offset_dict (dict): Dictionary with column names and how the distance should be calculated.
calib (bool): Flag to indicate that distances should be calculated on calibrated columns. Defaults to False.
Raises:
KeyError: If either table_1 or table_2 is not indexed by precursor
"""
if table_1.index.name != 'precursor':
raise KeyError('table_1 is not indexed by precursor')
if table_2.index.name != 'precursor':
raise KeyError('table_2 is not indexed by precursor')
shared_precursors = list(set(table_1.index).intersection(set(table_2.index)))
table_1_ = table_1.loc[shared_precursors]
table_2_ = table_2.loc[shared_precursors]
table_1_ = table_1_.groupby('precursor').mean()
table_2_ = table_2_.groupby('precursor').mean()
deltas = []
for col in offset_dict:
if calib:
col_ = col+'_calib'
else:
col_ = col
if offset_dict[col] == 'absolute':
deltas.append(np.nanmedian(table_1_[col_] - table_2_[col_]))
elif offset_dict[col] == 'relative':
deltas.append(np.nanmedian((table_1_[col_] - table_2_[col_]) / (table_1_[col_] + table_2_[col_]) * 2))
else:
raise NotImplementedError(f"Calculating delta for {offset_dict[col_]} not implemented.")
return deltas, len(shared_precursors)
# Cell
def calib_table(table: pd.DataFrame, delta: pd.Series, offset_dict: dict):
"""
Apply offset to a table. Different operations for offsets exist.
Offsets will be saved with a '_calib'-suffix. If this does not already exist,
it will be created.
Args:
table_1 (pd.DataFrame): Dataframe with data.
delta (pd.Series): Series cotaining the offset.
offset_dict (dict): Dictionary with column names and how the distance should be calculated.
Raises:
NotImplementedError: If the type of vonversion is not implemented.
"""
for col in offset_dict:
if (col not in table.columns) and (col+'_apex' in table.columns):
col_ = col+'_apex'
else:
col_ = col
if offset_dict[col] == 'absolute':
table[col+'_calib'] = table[col_]-delta[col]
elif offset_dict[col] == 'relative':
table[col+'_calib'] = (1-delta[col_])*table[col]
else:
raise NotImplementedError(offset_dict[col])
# Cell
import logging
from sklearn.linear_model import LinearRegression
def align(deltas: pd.DataFrame, filenames: list, weights:np.ndarray=None) -> np.ndarray:
"""Align multiple datasets.
This function creates a matrix to represent the shifts from each dataset to another.
This effectively is an overdetermined equation system and is solved with a linear regression.
Args:
deltas (pd.DataFrame): Distances from each dataset to another.
filenames (list): The filenames of the datasts that were compared.
weights (np.ndarray, optional): Distances can be weighted by their number of shared elements. Defaults to None.
Returns:
np.ndarray: alignment values.
"""
matrix = []
for i in range(len(deltas)):
start, end = deltas.index[i]
start_idx = filenames.index(start)
end_idx = filenames.index(end)
lines = np.zeros(len(filenames)-1)
lines[start_idx:end_idx] = 1
matrix.append(lines)
# Remove nan values
not_nan = ~deltas.isnull().any(axis=1)
matrix = np.array(matrix)
matrix = matrix[not_nan]
deltas_ = deltas[not_nan]
if len(deltas) < matrix.shape[1]:
logging.info('Low overlap between datasets detected. Alignment may fail.')
if weights is not None:
reg = LinearRegression(fit_intercept=False).fit(matrix, deltas_.values, sample_weight = weights[not_nan])
score= reg.score(matrix, deltas_.values)
else:
reg = LinearRegression(fit_intercept=False).fit(matrix, deltas_.values)
score= reg.score(matrix, deltas_.values)
logging.info(f"Regression score is {score}")
x = reg.predict(np.eye(len(filenames)-1))
return x
# Cell
import alphapept.io
import os
from typing import Callable
def calculate_deltas(combos: list, calib:bool = False, callback:Callable=None) -> (pd.DataFrame, np.ndarray, dict):
"""Wrapper function to calculate the distances of multiple files.
In here, we define the offset_dict to make a relative comparison for mz and mobility and absolute for rt.
TODO: This function could be speed-up by parallelization
Args:
combos (list): A list containing tuples of filenames that should be compared.
calib (bool): Boolean flag to indicate distance should be calculated on calibrated data.
callback (Callable): A callback function to track progress.
Returns:
pd.DataFrame: Dataframe containing the deltas of the files
np.ndarray: Numpy array containing the weights of each comparison (i.e. number of shared elements)
dict: Offset dictionary whicch was used for comparing.
"""
offset_dict = {}
deltas = pd.DataFrame()
weights = []
for i, combo in enumerate(combos):
file1 = os.path.splitext(combo[0])[0] + '.ms_data.hdf'
file2 = os.path.splitext(combo[1])[0] + '.ms_data.hdf'
df_1 = alphapept.io.MS_Data_File(file1).read(dataset_name="peptide_fdr").set_index('precursor')
df_2 = alphapept.io.MS_Data_File(file2).read(dataset_name="peptide_fdr").set_index('precursor')
if not offset_dict:
offset_dict = {'mz':'relative', 'rt':'absolute'}
if 'mobility' in df_1.columns:
logging.info("Also using mobility for calibration.")
offset_dict['mobility'] = 'relative'
cols = list(offset_dict.keys())
if len(deltas) == 0:
deltas = pd.DataFrame(columns = cols)
dists, weight = calculate_distance(df_1, df_2, offset_dict, calib = calib)
deltas = deltas.append(pd.DataFrame([dists], columns = cols, index=[combo]))
weights.append(weight)
if callback:
callback((i+1)/len(combos))
return deltas, np.array(weights), offset_dict
# Cell
import pandas as pd
from itertools import combinations
import numpy as np
import os
import functools
#There is no unit test for align_files and align_datasets as they are wrappers and should be covered by the quick_test
def align_files(filenames: list, alignment: pd.DataFrame, offset_dict: dict):
"""
Wrapper function that aligns a list of files.
Args:
filenames (list): A list with raw file names.
alignment (pd.DataFrame): A pandas dataframe containing the alignment information.
offset_dict (dict): Dictionary with column names and how the distance should be calculated.
"""
for idx, filename in enumerate(filenames):
file = os.path.splitext(filename)[0] + '.ms_data.hdf'
for column in ['peptide_fdr', 'feature_table']:
df = alphapept.io.MS_Data_File(file).read(dataset_name=column)
calib_table(df, alignment.iloc[idx], offset_dict)
logging.info(f"Saving {file} - {column}.")
ms_file = alphapept.io.MS_Data_File(file, is_overwritable=True)
ms_file.write(df, dataset_name=column)
def align_datasets(settings:dict, callback:callable=None):
"""
Wrapper function that aligns all experimental files specified a settings file.
Args:
settings (dict): A list with raw file names.
callback (Callable): Callback function to indicate progress.
"""
filenames = settings['experiment']['file_paths']
if callback:
cb = functools.partial(progress_wrapper, 0, 2)
else:
cb = None
if len(filenames) > 1:
combos = list(combinations(filenames, 2))
deltas, weights, offset_dict = calculate_deltas(combos, callback=cb)
cols = list(offset_dict.keys())
before_sum = deltas.abs().sum().to_dict()
before_mean = deltas.abs().mean().to_dict()
logging.info(f'Total deviation before calibration {before_sum}')
logging.info(f'Mean deviation before calibration {before_mean}')
logging.info(f'Solving equation system')
alignment = pd.DataFrame(align(deltas, filenames, weights), columns = cols)
alignment = pd.concat([pd.DataFrame(np.zeros((1, alignment.shape[1])), columns= cols), alignment])
alignment -= alignment.mean()
logging.info(f'Solving equation system complete.')
logging.info(f'Applying offset')
align_files(filenames, -alignment, offset_dict)
if cb:
cb = functools.partial(progress_wrapper, 1, 2)
deltas, weights, offset_dict = calculate_deltas(combos, calib=True, callback=cb)
after_sum = deltas.abs().sum().to_dict()
after_mean = deltas.abs().mean().to_dict()
logging.info(f'Total deviation after calibration {after_sum}')
logging.info(f'Mean deviation after calibration {after_mean}')
change_sum = {k:v/before_sum[k] for k,v in after_sum.items()}
change_mean = {k:v/before_mean[k] for k,v in after_mean.items()}
logging.info(f'Change (after/before) total deviation {change_sum}')
logging.info(f'Change (after/before) mean deviation {change_mean}')
else:
logging.info('Only 1 dataset present. Skipping alignment.')
# Cell
from scipy import stats
def get_probability(df: pd.DataFrame, ref: pd.DataFrame, sigma:pd.DataFrame, index:int)-> float:
"""Probablity estimate of a transfered identification using the Mahalanobis distance.
The function calculates the probability that a feature is a reference feature.
The reference features containing std deviations so that a probability can be estimated.
It is required that the data frames are matched, meaning that the first entry in df matches to the first entry in ref.
Args:
df (pd.DataFrame): Dataset containing transferered features
ref (pd.DataFrame): Dataset containing reference features
sigma (pd.DataFrame): Dataset containing the standard deviations of the reference features
index (int): Index to the datframes that should be compared
Returns:
float: Mahalanobis distance
"""
sigma = sigma.iloc[index].values
sigma = sigma*np.eye(len(sigma))
mu = ref.iloc[index].values
x = df.iloc[index].values
try:
m_dist_x = np.dot((x-mu).transpose(), np.linalg.inv(sigma))
m_dist_x = np.dot(m_dist_x, (x-mu))
_ = stats.chi2.cdf(m_dist_x, len(mu))
except Exception as e:
_ = np.nan
return _
# Cell
from sklearn.neighbors import KDTree
from .utils import assemble_df
# This function is a wrapper function and has currently has no unit test
# The function will be revised when implementing issue #255: https://github.com/MannLabs/alphapept/issues/255
def match_datasets(settings:dict, callback:Callable = None):
"""Match datasets: Wrapper function to match datasets based on a settings file.
Args:
settings (dict): Dictionary containg specifications of the run
callback (Callable): Callback function to indicate progress.
"""
if len(settings['experiment']['file_paths']) > 2:
xx = alphapept.utils.assemble_df(settings, field='peptide_fdr')
base_col = ['precursor']
alignment_cols = ['mz_calib','rt_calib']
extra_cols = ['score','decoy','target']
if 'mobility' in xx.columns:
alignment_cols += ['mobility_calib']
use_mobility = True
else:
use_mobility = False
grouped = xx[base_col + alignment_cols + extra_cols].groupby('precursor').mean()
std_ = xx[base_col + alignment_cols].groupby('precursor').std()
grouped[[_+'_std' for _ in alignment_cols]] = std_
std_range = np.nanmedian(std_.values, axis=0)
match_p_min = settings['matching']['match_p_min']
match_d_min = settings['matching']['match_d_min']
filenames = settings['experiment']['file_paths']
lookup_dict = xx.set_index('precursor')[['sequence']].to_dict()
for idx, filename in enumerate(filenames):
file = os.path.splitext(filename)[0] + '.ms_data.hdf'
df = alphapept.io.MS_Data_File(file).read(dataset_name='peptide_fdr')
features = alphapept.io.MS_Data_File(file).read(dataset_name='feature_table')
features['feature_idx'] = features.index
matching_set = set(grouped.index) - set(df['precursor'])
logging.info(f'Trying to match file {file} with database of {len(matching_set):,} unidentified candidates')
mz_range = std_range[0]
rt_range = std_range[1]
tree_points = features[alignment_cols].values
tree_points[:,0] = tree_points[:,0]/mz_range
tree_points[:,1] = tree_points[:,1]/rt_range
query_points = grouped.loc[matching_set][alignment_cols].values
query_points[:,0] = query_points[:,0]/mz_range
query_points[:,1] = query_points[:,1]/rt_range
if use_mobility:
logging.info("Using mobility")
i_range = std_range[2]
tree_points[:,2] = tree_points[:,2]/i_range
query_points[:,2] = query_points[:,2]/i_range
matching_tree = KDTree(tree_points, metric="minkowski")
dist, idx = matching_tree.query(query_points, k=1)
matched = features.iloc[idx[:,0]]
for _ in extra_cols:
matched[_] = grouped.loc[matching_set, _].values
to_keep = dist < match_d_min
matched = matched[to_keep]
ref = grouped.loc[matching_set][alignment_cols][to_keep]
sigma = std_.loc[matching_set][to_keep]
logging.info(f'{len(matched):,} possible features for matching based on distance of {match_d_min}')
matched['matching_p'] = [get_probability(matched[alignment_cols], ref, sigma, i) for i in range(len(matched))]
matched['precursor'] = grouped.loc[matching_set][to_keep].index.values
matched = matched[matched['matching_p']< match_p_min]
logging.info(f'{len(matched):,} possible features for matching based on probability of {match_p_min}')
matched['type'] = 'matched'
for _ in lookup_dict.keys():
matched[_] = [lookup_dict[_][x] for x in matched['precursor']]
df['type'] = 'msms'
df['matching_p'] = np.nan
shared_columns = set(matched.columns).intersection(set(df.columns))
df_ = pd.concat([df, matched[shared_columns]], ignore_index=True)
logging.info(f"Saving {file} - peptide_fdr.")
ms_file = alphapept.io.MS_Data_File(file, is_overwritable=True)
ms_file.write(df_, dataset_name='peptide_fdr')
else:
logging.info('Less than 3 datasets present. Skipping matching.')
|
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13845,
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25,
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22058,
621,
513,
40522,
1944,
13,
3661,
4501,
12336,
2637,
8
] | 2.44501 | 6,483 |
# AUTOGENERATED! DO NOT EDIT! File to edit: 40b_service_filesystem.ipynb (unless otherwise specified).
__all__ = ['sort_posts', 'posts_list_to_dict', 'migrate', 'ServiceFilesystem', 'before_request', 'after_request',
'init_service']
# Cell
import json,uuid,datetime,re
from pathlib import Path
from operator import attrgetter
# Cell
# Cell
def posts_list_to_dict(posts,key='id'):
"Convert a list of dictionaries to a dictionary of dictionaries"
return {post[key]:post for post in posts}
# Cell
# Cell
# TODO: DRY
# Cell
# Cell
# Cell
|
[
2,
47044,
7730,
1677,
1137,
11617,
0,
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10560,
56,
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198,
2,
12440,
198,
198,
2,
12440,
198,
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2,
12440
] | 2.756098 | 205 |
"""
graph.py
useful graph collection
author: @alexzander
"""
# python
import os
# core package
from core.system import *
from core.json__ import *
from exceptions import *
from core.path__ import *
# from exceptions import * (same thing, it works)
|
[
201,
198,
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201,
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13,
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11,
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201,
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] | 2.607143 | 112 |
from ..formatHandlerBase import formatHandlerBase
from ..formatName import formatName
from ...data import dataFileBase,DataType,method,excitationValue,datafileSelector
from ...utils import getValFromCell
import numpy as np
@formatName("line")
|
[
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198,
31,
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5376,
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4943
] | 3.967213 | 61 |
"""
Script for building FMPasteBox
Usage:
python setup.py py2app
"""
from distutils.core import setup
from setuptools.extension import Extension
import py2app
import FMPasteBoxVersion
setup(
name = FMPasteBoxVersion.appname,
version = FMPasteBoxVersion.version,
description = FMPasteBoxVersion.description,
long_description = FMPasteBoxVersion.longdescription,
author = FMPasteBoxVersion.author,
app=[{
'script': "FMPasteBox.py",
"plist": {
"NSPrincipalClass": 'NSApplication',
"CFBundleIdentifier": FMPasteBoxVersion.bundleID,
"CFBundleName": FMPasteBoxVersion.appnameshort,
"CFBundleSignature": FMPasteBoxVersion.creator,
"CFBundleShortVersionString": FMPasteBoxVersion.version,
"CFBundleGetInfoString": FMPasteBoxVersion.description,
"NSHumanReadableCopyright": FMPasteBoxVersion.copyright,
}
}],
data_files=[
"English.lproj/MainMenu.nib",
"English.lproj/Preferences.nib",
#"English.lproj/FMPasteBoxDocument.nib",
"+icon/FMPasteBox.icns",
#"+icon/FMPasteBoxFile.icns",
],
options={
"py2app": {
"iconfile": "+icon/FMPasteBox.icns",
# "packages": [],
"excludes": ["TkInter", 'Tcl', 'Tk'],
}
} )
|
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366,
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51,
565,
3256,
705,
51,
74,
6,
4357,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
1782,
1267,
628
] | 2.187097 | 620 |
from __future__ import print_function
import argparse
import os
import sys, glob, itertools, math
from typing import List, Dict
from PIL import Image, ImageFont, ImageDraw
import torch
from ..srcnn.srcnn_run import SRCNNPreProcessor, SRCNNPreProcessorGen
from src.srgan.srgan_module import Generator as SRGANGenerator
from ..srcnn.srcnn_module import *
supportedModels = {
"srcnn": SRCNN,
"srcnn-bnorm": SRCNNBatchNorm,
"srcnn-residual": SRCNNR,
"srgan": lambda: SRGANGenerator(scale_factor=2),
}
class PytorchSRVisulizator:
"""
Visualizes pytorch nn.models:
* model files should contain only the state dict, because the Model classes can't be pickled at runtime.
* model dir must follow this hierarch:
modeldir
| model.pth #final model file
| checkpoints
| model_epoch_{}.pth # '{}' is replaced with epoch number
"""
@staticmethod
if __name__ == "__main__":
parser = argparse.ArgumentParser("SRCNN visualizer")
PytorchSRVisulizator.add_arguments_to(parser)
config = parser.parse_args()
print(config)
visualizer = PytorchSRVisulizator(config)
visualizer.visualize()
|
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5874,
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] | 2.754717 | 424 |
import h5py
import numpy as np
from .. import Transition
from ..callbacks import StoreStates2Hdf5
HDF5_PATH = "/tmp/test_humblerl_callback.hdf5"
class TestStoreTransitions2Hdf5(object):
"""Test callback on 3D (e.g. images) and continuous states."""
|
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] | 2.88764 | 89 |
'''
File: test_accounts.py
Author: Zachary King
Defines unit tests for accounts.py.
Tests all account features.
'''
from __future__ import print_function
import unittest
import os
from oink import accounts, db
class TestAccounts(unittest.TestCase):
'''Defines unit tests for adding and removing accounts.'''
def setUp(self):
'''Setup testing databse.'''
# Creates the testing database
os.mkdir('testdb')
with open(r'testdb\oink.db', 'w') as fout:
pass
db.connect('testdb')
accounts.setup()
def tearDown(self):
'''Destroys the testing database.'''
db.disconnect()
os.remove(r'testdb\oink.db')
os.rmdir('testdb')
def test_add_new_account(self):
'''Test for adding a new account.'''
cur = db.cursor()
# Add a new account
accounts.add_account(12345, 'TestAddAccount', 100.00, '2017-1-1')
self.assertEqual(cur.execute('SELECT COUNT(*) FROM accounts').fetchone()[0], 1)
accounts.add_account(54321, 'TestAddAccount2', 0.01, '2017-1-1')
self.assertEqual(cur.execute('SELECT COUNT(*) FROM accounts').fetchone()[0], 2)
def test_remove_account(self):
'''Test to remove an existing account.'''
cur = db.cursor()
# Insert a new account
cur.execute('INSERT INTO accounts VALUES (024, "TestRemoveAccount", 0.00, "2017-1-1")')
self.assertEqual(cur.rowcount, 1)
# Remove the accont
accounts.delete('TestRemoveAccount')
cur.execute('SELECT COUNT(*) FROM accounts')
self.assertEqual(cur.fetchone()[0], 0)
def test_add_null_account_number(self):
'''Tests NOT NULL constraint of database for account number'''
# Try to insert NULL as account number
with self.assertRaises(ValueError):
accounts.add_account(None, 'TestNullNumAccount', 0.0, '2017-1-1')
with self.assertRaises(ValueError):
accounts.add_account('', 'TestNullNumAccount', 0.0, '2017-1-1')
def test_add_null_account_name(self):
'''Tests NOT NULL constraint of database for account name'''
# Try to insert NULL as account name
with self.assertRaises(ValueError):
accounts.add_account(987, None, 0.0, '2017-1-1')
with self.assertRaises(ValueError):
accounts.add_account(789, '', 0.0, '2017-1-1')
def test_add_null_start_balance(self):
'''Tests NOT NULL constraint of databse for account starting balance'''
# Try to insert NULL as account starting balance
with self.assertRaises(ValueError):
accounts.add_account(111, 'TestNullStartBalanceAccount', None, '2017-1-1')
def test_add_negative_start_balance(self):
'''Tests inserting a negative starting balace for a new account'''
with self.assertRaises(ValueError):
accounts.add_account(222, 'TestNegativeStartingBalance', -100.0, '2017-1-1')
def test_add_null_created_date(self):
'''Tests NOT NULL constraint for account created_on'''
with self.assertRaises(ValueError):
accounts.add_account(333, 'TestNullCreatedOn', 0.0, '')
with self.assertRaises(ValueError):
accounts.add_account(333, 'TestNullCreatedOn', 0.0, None)
if __name__ == '__main__':
unittest.main()
|
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5504,
13,
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3256,
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8,
628,
198,
361,
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705,
834,
12417,
834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.423937 | 1,387 |
# Generated by Django 3.2.9 on 2021-11-07 02:05
from django.db import migrations, models
|
[
2,
2980,
515,
416,
37770,
513,
13,
17,
13,
24,
319,
33448,
12,
1157,
12,
2998,
7816,
25,
2713,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
from siptrackweb.views import helpers
|
[
6738,
264,
10257,
39638,
12384,
13,
33571,
1330,
49385,
198
] | 3.8 | 10 |
import re
from setuptools import setup
version = ""
with open("w2n/__init__.py") as f:
search = re.search(r'^__version__\s*=\s*[\'"]([^\'"]*)[\'"]', f.read(), re.MULTILINE)
if search is not None:
version = search.group(1)
else:
raise RuntimeError("Could not grab version string")
if not version:
raise RuntimeError("version is not set")
with open("README.rst") as f:
readme = f.read()
setup(
name='longsphinx-word2number',
packages=['w2n'],
version=version,
license='MIT',
description='Convert number words eg. three hundred and forty two to numbers (342). '
'Forked for https://github.com/WaltWh/LongSphinx, not intended for public use.',
author='Akshay Nagpal & Walt Whiteside',
author_email='[email protected]',
url='https://github.com/WaltWh/w2n', # use the URL to the GitHub repo
download_url='https://github.com/WaltWh/w2n/tarball/1.2',
keywords=['numbers', 'convert', 'words'], # arbitrary keywords
classifiers=[
'Intended Audience :: Developers',
'Programming Language :: Python :: 3.10'
],
long_description=readme,
long_description_content_type="text/x-rst",
python_requires=">=3.10.0", # Probably not, but I haven't tested anything else
test_suite="unit_testing"
)
|
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] | 2.545455 | 517 |
import joblib
import logging
from typing import Tuple
from catboost import CatBoostRegressor
from environs import Env
import numpy as np
import pandas as pd
from sklearn import metrics
from bedrock_client.bedrock.analyzer import ModelTask, ModelTypes
from bedrock_client.bedrock.analyzer.model_analyzer import ModelAnalyzer
from bedrock_client.bedrock.api import BedrockApi
from bedrock_client.bedrock.metrics.collector import (
BaselineMetricCollector,
FeatureHistogramCollector,
InferenceHistogramCollector
)
from bedrock_client.bedrock.metrics.encoder import MetricEncoder
env = Env()
OUTPUT_MODEL_PATH = env("OUTPUT_MODEL_PATH")
TRAIN_DATA_PATH = env("TRAIN_DATA_PATH")
TEST_DATA_PATH = env("TEST_DATA_PATH")
CONFIG_FAI = {
"large_rings": {
"group_a": [1],
"group_a_name": "Large",
"group_b": [0],
"group_b_name": "Small"
}
}
def load_dataset(filepath: str,
target: str) -> Tuple[pd.core.frame.DataFrame,
np.ndarray]:
"""
Loads the dataset and returns the features as a pandas dataframe and
the target variable as a numpy array.
:param filepath: Path to load the data
:type filepath: str
:param target: Target variable
:type target: str
:return: The features pandas dataframe and the target numpy array
:rtype: tuple[pandas.core.frame.DataFrame, numpy.ndarray]
"""
df = pd.read_csv(filepath).drop('Type', axis=1) # Removes 'Type' column
df['large_rings'] = (df['Rings'] > 10).astype(int)
# Ensure nothing missing
original_len = len(df)
df.dropna(how="any", axis=0, inplace=True)
num_rows_dropped = original_len - len(df)
if num_rows_dropped > 0:
print(f"Warning - dropped {num_rows_dropped} rows with NA data.")
y = df[target].values
df.drop(target, axis=1, inplace=True)
return df, y
def train_catboost_model(X: pd.core.frame.DataFrame,
y: np.ndarray,
verbose: bool = False) -> CatBoostRegressor:
"""
Scales the features and trains a logistic regression model.
:param X: Features for training
:type X: pandas.core.frame.DataFrame
:param y: Target variable
:type y: numpy.ndarray
:param verbose: Whether to print additional info
:type verbose: bool
:return: Trained CatBoostRegressor model
:rtype: catboost.CatBoostRegressor
"""
verbose and print('\nTRAIN\nScaling...')
model = CatBoostRegressor(iterations=100,
learning_rate=0.1,
depth=5)
verbose and print('Fitting...')
model.fit(X, y)
verbose and print('Done training.')
return model
def compute_log_metrics(model: CatBoostRegressor,
x_test: pd.core.frame.DataFrame,
y_test: np.ndarray):
"""
Computes, prints and log metrics.
:param model: Trained CatBoostRegressor model
:type model: catboost.CatBoostRegressor
:param x_test: Features for testing
:type x_test: pandas.core.frame.DataFrame
:param y_test: Target variable data for testing
:type y_test: numpy.ndarray
:return: Test predicted probability and predictions
:rtype: tuple[numpy.ndarray, numpy.ndarray]
"""
y_pred = model.predict(x_test)
mae = metrics.mean_absolute_error(y_test, y_pred)
mse = metrics.mean_squared_error(y_test, y_pred)
r2_score = metrics.r2_score(y_test, y_pred)
print("\nEVALUATION\n"
f"\tMean absolute error = {mae:.4f}\n"
f"\tMean squared error = {mse:.4f}\n"
f"\tR2 regression score function = {r2_score:.4f}\n")
# Bedrock Logger: captures model metrics
bedrock = BedrockApi(logging.getLogger(__name__))
bedrock.log_metric("MAE", mae)
bedrock.log_metric("MSE", mse)
bedrock.log_metric("R2", r2_score)
return y_pred
if __name__ == '__main__':
main()
|
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#!/usr/bin/env python
# coding: utf-8
# # PC/NC classification by CNN
#
# The convolutional neural network (CNN) was invented for image processing.
# We can use Conv1D layers for processing string sequences.
# How well does CNN work on human RNA as a binary classifier of protein-coding/non-coding?
#
# Assume user downloaded files from GenCode 38 [FTP](http://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_38/)
# to a subdirectory called data.
#
# The learning curve is strange: up then down. I suspect the CNN is learning the fact that we padded sequences with T to make them uniform length.
# In[1]:
import time
show_time()
# In[2]:
PC_FILENAME='gencode.v38.pc_transcripts.fa.gz'
NC_FILENAME='gencode.v38.lncRNA_transcripts.fa.gz'
# In[3]:
PC_SEQUENCES=20000 # how many protein-coding sequences
NC_SEQUENCES=20000 # how many non-coding sequences
PC_TESTS=1000
NC_TESTS=1000
BASES=1000 # how long is each sequence
ALPHABET=4 # how many different letters are possible
INPUT_SHAPE_2D = (BASES,ALPHABET,1) # Conv2D needs 3D inputs
INPUT_SHAPE = (BASES,ALPHABET) # Conv1D needs 2D inputs
FILTERS = 32 # how many different patterns the model looks for
NEURONS = 32
DROP_RATE = 0.2
WIDTH = 3 # how wide each pattern is, in bases
STRIDE_2D = (1,1) # For Conv2D how far in each direction
STRIDE = 1 # For Conv1D, how far between pattern matches, in bases
EPOCHS=50 # how many times to train on all the data
SPLITS=5 # SPLITS=3 means train on 2/3 and validate on 1/3
FOLDS=3 # train the model this many times (range 1 to SPLITS)
# In[4]:
import sys
import csv
try:
from google.colab import drive
IN_COLAB = True
print("On Google CoLab, mount cloud-local file, get our code from GitHub.")
PATH='/content/drive/'
#drive.mount(PATH,force_remount=True) # hardly ever need this
drive.mount(PATH) # Google will require login credentials
DATAPATH=PATH+'My Drive/data/' # must end in "/"
import requests
r = requests.get('https://raw.githubusercontent.com/ShepherdCode/Soars2021/master/SimTools/RNA_gen.py')
with open('RNA_gen.py', 'w') as f:
f.write(r.text)
from RNA_gen import *
r = requests.get('https://raw.githubusercontent.com/ShepherdCode/Soars2021/master/SimTools/RNA_describe.py')
with open('RNA_describe.py', 'w') as f:
f.write(r.text)
from RNA_describe import *
r = requests.get('https://raw.githubusercontent.com/ShepherdCode/Soars2021/master/SimTools/RNA_prep.py')
with open('RNA_prep.py', 'w') as f:
f.write(r.text)
from RNA_prep import *
except:
print("CoLab not working. On my PC, use relative paths.")
IN_COLAB = False
DATAPATH='../data/' # must end in "/"
sys.path.append("..") # append parent dir in order to use sibling dirs
from SimTools.RNA_gen import *
from SimTools.RNA_describe import *
from SimTools.RNA_prep import *
MODELPATH="BestModel" # saved on cloud instance and lost after logout
#MODELPATH=DATAPATH+MODELPATH # saved on Google Drive but requires login
if not assert_imported_RNA_gen():
print("ERROR: Cannot use RNA_gen.")
if not assert_imported_RNA_prep():
print("ERROR: Cannot use RNA_prep.")
# In[5]:
from os import listdir
#from zipfile import ZipFile
import gzip
import numpy as np
import pandas as pd
from scipy import stats # mode
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_score
from keras.models import Sequential
from keras.layers import Dense,Embedding,Dropout
from keras.layers import Conv1D,Conv2D
from keras.layers import Flatten,MaxPooling1D,MaxPooling2D
from keras.losses import BinaryCrossentropy
# tf.keras.losses.BinaryCrossentropy
import matplotlib.pyplot as plt
from matplotlib import colors
mycmap = colors.ListedColormap(['red','blue']) # list color for label 0 then 1
np.set_printoptions(precision=2)
# In[6]:
# In[7]:
PC_FULLPATH=DATAPATH+PC_FILENAME
NC_FULLPATH=DATAPATH+NC_FILENAME
pcdf=load_gencode(PC_FULLPATH,1)
print("PC seqs loaded:",len(pcdf))
ncdf=load_gencode(NC_FULLPATH,0)
print("NC seqs loaded:",len(ncdf))
# In[8]:
# In[9]:
from sklearn.model_selection import train_test_split
pc_all = pcdf['sequence']
nc_all = ncdf['sequence']
# The split function also shuffles
pc_train,pc_test=train_test_split(pc_all,test_size=0.10,random_state=1234)
nc_train,nc_test=train_test_split(nc_all,test_size=0.10,random_state=1234)
# In[10]:
# Use code from our SimTools library.
UNIFORM_LENGTH=1000
MAXIMUM_LENGTH=2000
pc_seqs=uniform_length(pc_train,UNIFORM_LENGTH,MAXIMUM_LENGTH-500)
print("PC seqs ready:",len(pc_seqs))
nc_seqs=uniform_length(nc_train,UNIFORM_LENGTH,MAXIMUM_LENGTH+2000)
print("NC seqs ready:",len(nc_seqs))
X,y = prepare_inputs_len_x_alphabet(pc_seqs,nc_seqs,ALPHABET) # shuffles
print("Data ready")
# In[11]:
model = make_DNN()
print(model.summary())
# In[12]:
from keras.callbacks import ModelCheckpoint
# In[13]:
show_time()
do_cross_validation(X,y)
show_time()
# In[13]:
|
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1303,
32299,
829,
198,
4798,
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6601,
3492,
4943,
628,
198,
2,
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58,
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198,
198,
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198,
4798,
7,
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2,
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3419,
628,
198,
2,
554,
58,
1485,
5974,
628,
628,
198
] | 2.636788 | 1,930 |
from distutils.core import setup
import py2exe
setup(console=['client.py'])
setup(console=['server.py'])
setup(console=['stun.py'])
|
[
6738,
1233,
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] | 2.634615 | 52 |
#!/usr/bin/env python
import os
import sys
from pyramid.config import Configurator
from sqlalchemy import engine_from_config
from sqlalchemy.orm import sessionmaker
from sqlalchemy.orm import scoped_session
from chatter3.models import Base
from pyramid.paster import (
get_appsettings,
setup_logging,
)
DBSession = scoped_session(sessionmaker())
here = os.path.dirname(__file__)
if __name__ == "__main__": # pragma: no cover
main()
|
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3419,
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] | 3 | 151 |
import numpy as np
import tensorflow as tf
|
[
11748,
299,
32152,
355,
45941,
198,
11748,
11192,
273,
11125,
355,
48700,
628,
198
] | 3.214286 | 14 |
# -*- coding: utf-8 -*-
# Copyright (C) 2011-2019 Mag. Christian Tanzer All rights reserved
# Glasauergasse 32, A--1130 Wien, Austria. [email protected]
# ****************************************************************************
# This module is part of the package JNJ.
#
# This module is licensed under the terms of the BSD 3-Clause License
# <http://www.c-tanzer.at/license/bsd_3c.html>.
# ****************************************************************************
#
#++
# Name
# JNJ.Media_Defaults
#
# Purpose
# Provide defaults for media fragments in html/*.media
#
# Revision Dates
# 1-Jan-2011 (CT) Creation
# 2-Jan-2011 (CT) Creation continued
# 4-Jan-2011 (CT) Creation continued..
# 14-Jan-2011 (CT) Use `GTW.Parameters.Definition` to allow lazy
# references with `P` and `P_dict`
# 22-Mar-2011 (CT) `afs`
# 22-Mar-2011 (CT) `afs` continued
# 29-Mar-2011 (CT) `afs` continued..
# 30-Mar-2011 (CT) `afs` continued...
# 19-May-2011 (CT) `afs` continued....
# 16-Oct-2011 (MG) `Debugger` added
# 24-Oct-2011 (CT) `color_spec_heading_rev` added
# 24-Oct-2011 (CT) `tablesorter` added
# 24-Nov-2011 (CT) Add `color_spec_selected_rev`
# 23-Feb-2012 (CT) Add `color_status_{bad,good,missing}`, `afs.status_size`
# 23-Feb-2012 (CT) Add `color_bg_bad` and `color_bg_missing`
# 1-Mar-2012 (CT) Change `pg_main_max_width` from `Em (50)` to `Em (45)`
# 8-Mar-2012 (CT) Add `color_bg_menu`
# 10-Aug-2012 (CT) Add `color_spec_sub_heading`, `color_spec_term`
# 7-Mar-2013 (CT) Add `border_added` and `border_deleted`
# 3-Apr-2013 (CT) Add `Rule`, `Rule.clearfix`
# 8-Apr-2013 (CT) Add lots of rules to `Rule`, e.g., `disabled`, `focus`...
# 7-Jan-2014 (CT) Add some more muted colors
# 21-Jan-2014 (CT) Add `breakpoint`
# 20-Feb-2014 (CT) Add `Rule.pg_nav_show`, `.pg_nav_show_a`
# 20-Feb-2014 (CT) Add `breakpoint.broad` and `.very_narrow`
# 8-Apr-2014 (CT) Improve `clearfix`
# 12-Apr-2014 (CT) Use `Border.P`, not `P_Border`
# 15-May-2014 (CT) Add `color_lightest_grey`
# 15-May-2014 (CT) Add `breakpoint.quite_narrow`
# 9-Jul-2014 (CT) Add `Rule.rotate_45_left`
# 26-Aug-2014 (CT) Add `pure` parameters
# 3-Sep-2014 (CT) Add `Rule.hidden`
# 3-Dec-2014 (CT) Add `color.alphabet_max_contrast_colors` and
# `color.kellys_max_contrast_colors`
# 16-Jan-2015 (CT) Change `nav_col.width` and `col_padding` to unit `Rem`
# 23-Jan-2015 (CT) Add `color_jnd_grey`, reduce contrast of `color_spec_row1`
# 23-Jan-2015 (CT) Factor `line_height*` parameters
# 15-Feb-2015 (CT) Add `menu_icon`
# 24-Mar-2015 (CT) Add `Rule.input_focus`
# 8-Apr-2015 (CT) Change `font_family_print` to "serif" to void font
# substitution by the printer
# 2-Dec-2015 (CT) Fix `Rule.visited`
# 2-Dec-2015 (CT) Change `nav_col.color_spec_link_current.background_color`
# 31-Dec-2015 (CT) Change `pg_nav_show` to allow embedded rel-nav buttons
# 11-Oct-2016 (CT) Import from `CHJ`, not `GTW`
# 27-Dec-2016 (CT) Add `breakpoint.really_narrow`
# 12-Jan-2017 (CT) Add `breakpoint.supports_two_column`
# 13-Jan-2017 (CT) Add `body_margin`, `hidden_collapse`, `target_visible`,
# `visible`
# 16-Jan-2017 (CT) Add `border_double`, `border_simple_light`
# 16-Jan-2017 (CT) Change `nav_col` to `nav.main`; modernize nav styling
# 16-Jan-2017 (CT) Add `nav.header`, `nav.rel`
# 19-Jan-2017 (CT) Add `Rule.main_nav_off`, `.main_nav_on`
# 10-May-2017 (CT) Add system-specific fonts to `font_family_normal`
# 28-May-2017 (CT) Add missing `"` in `font_family_normal`
# 29-Mar-2018 (CT) Add `system-ui` to `font_family_normal`
# 15-Apr-2019 (CT) Add `nord colors`
# ««revision-date»»···
#--
from _CHJ._CSS.import_CSS import *
from _CHJ.Parameters import \
( Definition, P, P_dict, Rule_Definition
, Rule, Rule_Attr, Rule_Child, Rule_Class, Rule_Pseudo, Rule_Sibling
)
Color.formatter = RGB_X
class Media_Defaults (Definition) :
"""Provide defaults for CSS fragments in html/*.css"""
# end class color
color_bg_bad = RGB_X ("#FFEEEE")
color_bg_menu = RGB_X ("#DDEEFF")
color_bg_missing = RGB_X ("#FFFFBB")
color_desc = RGB_X ("#666666")
color_focus = SVG_Color ("yellow")
color_heading = RGB_X ("#34444D")
color_heading_closed = RGB_X ("#56666E")
color_heading_sub = RGB_X ("#78888F")
color_jnd_grey = RGB_X ("#F8F8F8")
color_lightest_grey = RGB_X ("#F6F6F6")
color_lighter_grey = RGB_X ("#EDEDED")
color_light_grey = RGB_X ("#DEDEDE")
color_border_grey = RGB_X ("#CCCCCC")
color_medium_grey = RGB_X ("#BEBEBE")
color_half_grey = RGB_X ("#888888")
color_dark_grey = RGB_X ("#444444")
color_darker_grey = RGB_X ("#222222")
color_selected = RGB_X ("#FF6633")
color_status_bad = RGB_X ("#FF6666")
color_status_good = RGB_X ("#AAEEAA")
color_status_missing = RGB_X ("#FFDD00")
color_target = RGB_X ("#FF6633")
css_arrow_color = SVG_Color ("red")
css_arrow_width = Em (1./2)
block_margin_bottom = Em (1./2)
body_margin = TRBL (Em (0.2), Em (0.5))
border_added = "1px solid " + P.color.m_red
border_button = "2px outset " + P.color_medium_grey
border_deleted = "1px solid " + P.color.m_blue
border_double = "2px solid " + P.color_medium_grey
border_double_light = "2px solid " + P.color_light_grey
border_selected = "2px solid " + P.color_selected
border_simple = "1px solid " + P.color_medium_grey
border_simple_light = "1px solid " + P.color_light_grey
button_spec = P_dict \
( border = P.border_button
, cursor = "pointer"
, margin = TRBL0 (t = Em (1./4), b = Em (3./4))
, padding = TRBL (Em (0.5), Em (1.5))
, ** Border (radius = Px (10))
)
col_padding = Rem (0.3125) ### Px (5)
background_color = P.color.p_white
link_color = RGB_X ("#0000EE")
no_link_color = RGB_X ("#333333")
text_color = RGB_X ("#000033")
visited_color = RGB_X ("#551A8B")
# end class afs
class breakpoint (Definition) :
"""Breakpoints for responsive rules"""
really_narrow = P_dict \
( max_width = Px (360)
)
very_narrow = P_dict \
( max_width = Px (420)
)
quite_narrow = P_dict \
( max_width = Px (480)
)
narrow = P_dict \
( max_width = Px (680)
)
small_device = P_dict \
( max_device_width = Px (767)
)
supports_two_column = P_dict \
( min_width = Px (768)
)
broad = P_dict \
( min_width = Px (1280)
)
wide = P_dict \
( min_width = Px (1600)
)
# end class breakpoint
# end class cal
# end class menu_icon
# end class nav
class pure (Definition) :
"""Parameters of `pure` css as of version v0.4.2."""
input_focus_border_color = RGB_X ("#129FEA")
label_width = Em (10.0)
label_margin_right = Em (1.0)
aside_indent = label_width + label_margin_right
# end class pure
# end class tablesorter
# end class Rule
color_spec_error = P_dict \
( background_color = P.background_color
, color = P.color_status_bad
)
color_spec_gallery_heading = P_dict \
( background_color = RGB_P (50, 75, 100)
, color = P.nav.main.background_color
)
color_spec_heading = P_dict \
( background_color = P.background_color
, color = P.color_selected
)
color_spec_normal = P_dict \
( background_color = P.background_color
, color = P.text_color
)
color_spec_pg_head = P_dict \
( background_color = P.background_color
, color = RGB_X ("#0200DE")
)
color_spec_row1 = color_spec_meta = P_dict \
( background_color = "transparent"
, color = P.text_color
)
color_spec_row2 = color_spec_message = P_dict \
( background_color = P.color_lightest_grey
, color = P.text_color
)
color_spec_selected = P_dict \
( background_color = SVG_Color ("yellow")
, color = SVG_Color ("red")
)
color_spec_selected_rev= P_dict \
( background_color = SVG_Color ("red")
, color = SVG_Color ("yellow")
)
color_spec_strong = P_dict \
( background_color = P.background_color
, color = SVG_Color ("blue")
)
color_spec_sub_heading = P_dict \
( background_color = P.background_color
, color = P.color_half_grey
)
color_spec_term = P_dict \
( background_color = RGB_X ("#E6E6E6")
, color = P.color_dark_grey
)
del_spec = P_dict \
( text_decoration = "line-through"
# XXX ???
)
font_family_normal = \
( """"system-ui","-apple-system", BlinkMacSystemFont, """
""""Segoe UI", Roboto, "Fira Sans", """
""""Lucida Grande", verdana, sans-serif"""
)
font_family_pre = \
""""Lucida Sans Typewriter", "Lucida Console", "Courier New", Courier, monospace"""
font_family_print = "serif"
### Don't use specific fonts for `print` because font substitution done
### by a printer can look terribly ugly
font_spec_normal = P_dict \
( font_family = P.font_family_normal
, font_style = "normal"
, font_weight = "normal"
, line_height = P.line_height_normal
)
font_spec_print = P_dict \
( font_spec_normal
, font_family = P.font_family_print
)
font_spec_em = P_dict \
( font_spec_normal
, font_weight = "bold"
)
font_spec_pre = P_dict \
( font_spec_normal
, font_family = P.font_family_pre
)
grid_table_border = "3px ridge gray"
h1_font_size = Percent (125)
h1_font_weight = "bold"
hbox_spec = P_dict \
( display = "block"
, overflow = "hidden"
)
hr_spec = P_dict \
( border = 0
, border_top = "1px solid #CCC"
, display = "block"
, height = Px (1)
, margin = TRBL (Em (1), 0)
, padding = 0
)
input_margin = TRBL (Em (0.1), 0)
input_padding = Em (0.2)
ins_spec = P_dict \
( text_decoration = "none"
# XXX ???
)
line_height_heading = 2.00
line_height_larger = 1.875
line_height_normal = 1.44
line_height_input = 1.143
outline_focus = "2px solid " + P.color_focus
outline_target = "2px dotted " + P.color_target
pg_body_margin_lr = Em (3.6)
pg_head_height = "auto"
pg_header_nav_height = Rem (3.5)
pg_main_max_width = Em (45)
pg_main_min_width = Em (15)
pg_short_nav_font_size = Rem (1.20)
pg_short_nav_top = Em (3)
thumbnail_size = Px (155)
thumbnail_selected_color = P.color_selected
# end class Debugger
# end class Media_Defaults
### __END__ JNJ.Media_Defaults
|
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220,
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62,
28341,
62,
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220,
220,
220,
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220,
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8,
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40901,
62,
7857,
220,
220,
220,
220,
220,
220,
220,
220,
796,
350,
87,
357,
18742,
8,
198,
220,
220,
220,
40901,
62,
34213,
62,
8043,
796,
350,
13,
8043,
62,
34213,
628,
220,
220,
220,
1303,
886,
1398,
31687,
1362,
198,
198,
2,
886,
1398,
6343,
62,
7469,
13185,
198,
198,
21017,
11593,
10619,
834,
449,
41074,
13,
13152,
62,
7469,
13185,
198
] | 1.984519 | 6,201 |
#list comprehension
cubes = [cube**3 for cube in range(1,11)]
print(cubes)
|
[
2,
4868,
35915,
198,
198,
66,
29080,
796,
685,
40296,
1174,
18,
329,
23441,
287,
2837,
7,
16,
11,
1157,
15437,
198,
4798,
7,
66,
29080,
8,
198
] | 2.714286 | 28 |
import tkinter as tk
from tkinter import messagebox, filedialog, simpledialog, scrolledtext
from tkinter import PhotoImage
from tkinter import ttk
import subprocess
from threading import Thread
import time
import tempfile
from os import path
import sys
try:
from . import settings
except ImportError:
# Running from source
import settings
# Contains the graphics featured on the buttons
graphics_directory = path.join(path.dirname(__file__), "graphics")
'''
Hiearchy of Tkinter frames:
GuiWindow.master = tk.Tk()
GuiWindow(ttk.Frame)
BatchingFrame.frame(ttk.Frame)
BatchingFrame.vbar(ttk.Scrollbar)
BatchingFrame(tk.Canvas)
BatchingFrame.canvas_content(tk.Frame)
Note: this is an amalgamation of code from different projects.
It could probably be simplified dramatically.
'''
class GuiWindow(ttk.Frame):
'''
Highest level window and frame.
Here we set the name and size of the window,
and prepare for hosting the actual content of the program.
If unittest is set to True, we don't start the
mainloop, but wait for a script to trigger
events and manually update the GUI.
'''
class BatchingFrame(tk.Canvas):
'''
This is the place where the widgets corresponding
to scripts live.
It is also the brain of the program, and controls
the state of the different scripts, the launching of
scripts, etc...
'''
def remove_all(self):
'''
Removes all the Scripts, from the last to the first,
excluding the topmost InsertWidget
'''
for position in range(len(self.scripts) - 1, 0, -1):
self.remove(position)
def build_output_window(self):
'''
Shows the output window which contains the
continuously updated output of the currently
running script (stdout and stderr).
Or, if no script is running, contains
the content of the latest run script.
'''
if self.output_window_visible:
# the output is already visible
# in this case bring the window to the top
self.output_window.lift()
self.output_window.attributes("-topmost", True)
self.output_window.attributes("-topmost", False)
return
# Open up the output window
self.output_window = tk.Toplevel(self.master)
self.output_window.title("Script queuer | Output")
self.output_window.geometry("400x400")
# Keep track of the window being visible
self.output_window_visible = True
# Window size cannot be reduced beyond
# a certain size
self.output_window.minsize(200, 150)
# When closing the window run self.on_closing_output_window
self.output_window.protocol("WM_DELETE_WINDOW",
self.on_closing_output_window)
# Put a scrollable text region in it, and make is stretchable
self.output_text_widget = ScrolledLabel(self.output_window)
self.output_text_widget.grid(column=0, row=0, sticky='news')
self.output_window.rowconfigure(0, weight=1)
self.output_window.columnconfigure(0, weight=1)
# Add a button to toggle following the output / autoscrolling
b = ToggleAutoscrollButton(self.output_window, text='Autoscroll')
b.grid(column=0, row=1, sticky='nws')
if self.running_script is not None:
# Is there is no running script,
# show the log of the last run script
self.output_text_widget.insert(self.running_script.log)
self.scroll_output_window_down()
def on_closing_output_window(self):
'''
Function called when the output window is closed
'''
# Keep track of the window state
self.output_window_visible = False
# Close the window
self.output_window.destroy()
def insert(self, position, script_path=None):
'''
Will insert a new script after the row indicated by
the input integer `position`.
Optionally one can specify the script path (for
unittesting purposes).
'''
if script_path is None:
# If no script path was provided
# prompt user for file name
if self.latest_searched_directory == None:
script_path = filedialog.askopenfilename()
else:
# If a script was already inserted,
# open the file prompt at the same directory
script_path = filedialog.askopenfilename(
initialdir=self.latest_searched_directory)
if script_path == "":
# User cancelled
return
# keep track of the directory the user navigated to
self.latest_searched_directory = path.dirname(script_path)
# Creates a new script widget, by default it will be queued
sw = ScriptWidget(self, script_path=script_path, state='queued')
# add it to the list of scripts
self.scripts.insert(position + 1, sw)
# update the scripts states and graphical information
self.update_script_widgets()
def move(self, position, new_position=None):
'''
Move a script from a position (row `position`) to a
new position (after row `new_position`).
The new position will be chosen in a popup window
by the user, or given as a kwarg (for unittesting purposes).
'''
if new_position is None:
# No postion was given: prompt user
# with a popup window
# Determine message to be displayed in popup
if self.state == 'running':
# If running, do not allow script to be placed in first postion
# (above the script which is running)
message = " 1 = place below row 1\n2 = place below row 2\n etc..."
minvalue = 1
else:
# If stopped
message = " 0 = place first \n 1 = place below row 1\n etc..."
minvalue = 0
# Open popup window
new_position = tk.simpledialog.askinteger("Move to",
message,
parent=self.master,
minvalue=minvalue,
maxvalue=len(
self.scripts))
if new_position is None:
# User cancelled
return
# the position the user sees does not
# take into account the rows of "done" scripts
# position_0 is the position of the first "not done"
# script.
new_position += self.position_0
# Insert the script at the new position
self.scripts.insert(new_position, self.scripts[position])
# Remove the script at the old position
if new_position > position:
self.scripts.pop(position)
else:
# If the script is moved up, then
# the old position is actually +1
self.scripts.pop(position + 1)
# Update script states and graphical information
self.update_script_widgets()
def remove(self, position):
'''
Remove a script from a position.
'''
# Destroy the ScriptWidget object
self.scripts[position].destroy()
# Remove it from the self.scripts list
self.scripts.pop(position)
# Update script states and graphical information
self.update_script_widgets()
def run(self, position):
'''
Run the script located at row `position`
'''
# Useful information about the script to be run
self.running_script = self.scripts[position]
script_path = self.scripts[position].script_path
self.running_script_position = position
self.running_script.log = ''
# Delete the contents of the output window
if self.output_window_visible:
self.output_text_widget.clear()
# Start the script and
# setup the communication
# with subprocess
self.start_script_process(script_path)
# Start the periodic monitoring of the script,
# to capture the output, but also detect the end/error
self.after(self.t_output_monitoring, self.monitor_script_process)
# Update the states of this object and the script
self.state = 'running'
self.running_script.state = 'running'
# Update script states and graphical information
self.update_script_widgets()
def start_script_process(self, script):
'''
Start the script subprocess
--- the -u option foces stdout, stderr streams to be
unbuffered, which allows us to collect these outputs in real tim,
rather than wait to the end of the scripts
--- the cwd is chosen to be the folder in which
the script is located
'''
self.script_process = subprocess.Popen(['python', '-u', script],
cwd=path.dirname(script),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
bufsize=1)
'''
This list will be populated
with contents of the subprocess
`stdout` by the `reader` function in a
seperate thread.
It's the bridge between the subprocess
and the log file and output window.
'''
self.line_buffer = []
# in a seperate thread, collect the output
# of the subprocess and load it into
# line_buffer list
self.buffer_filling_thread = Thread(target=reader,
args=(self.script_process.stdout,
self.line_buffer))
self.buffer_filling_thread.daemon = True
self.buffer_filling_thread.start()
def write_to_output(self, to_write):
'''
write `to_write` both to the output window
and to the log file of the running scripts
'''
if self.output_window_visible:
self.output_text_widget.insert(to_write)
self.running_script.log += to_write
def monitor_script_process(self):
'''
Whilst the script is running, copy what the
`reader` function has put into the `self.line_buffer`
and write it to the output and log files.
This function will detect when the running script crashed
or ended, append the output/log accordingly, and
run the next queued script.
'''
# write all contents of the `self.line_buffer` list
# to the output/log
while self.line_buffer:
self.write_to_output(self.line_buffer.pop(0).decode("utf-8"))
# if autoscroll is activated, scroll the output window
# to the latest written
if self.output_window.follow:
self.scroll_output_window_down()
# poll checks on the status of the subprocess
poll = self.script_process.poll()
if poll is None:
# Hasnt crashed or ended
# monitor again in a time `self.t_output_monitoring`
self.after(self.t_output_monitoring, self.monitor_script_process)
else:
self.treat_end_of_script(poll)
self.treat_next_queued_script(poll)
def treat_end_of_script(self, poll):
'''
Called whenever a script crashes or ends.
Appends the output/log to give maximum
information to the user about causes of crashes.
'''
if poll != 0:
# Something went wrong
while True:
# Get Error Log and write to output/log
line = self.script_process.stderr.readline()
if not line:
break
else:
self.write_to_output(line.decode("utf-8"))
# Scroll the output window to the bottom
self.scroll_output_window_down()
# If `self.state` is stopped, then it's the user
# who interrupted the script, write this into the output\log
if self.state == 'stopped':
self.write_to_output(self.interrupted_error_message)
# Scroll the output window to the bottom
self.scroll_output_window_down()
def treat_next_queued_script(self, poll):
'''
Called when a script crashes or ends,
to carry out the actions which follow:
- starting a new queued script if the
script ended/crashed on its own
- stopping the run if the user forced a stop
- notifying the user via email if enabled
'''
if poll != 0 and self.state == 'stopped':
# User interrupted the script
# The script is stopped and made ready to go again
self.running_script.state = 'ready'
# It is also duplicated and marked above as a
# stopped script, so that the user may also inspect the
# logging file
stopped = self.running_script
duplicate = ScriptWidget(self,
script_path=stopped.script_path,
state='ended')
duplicate.success = 'stopped'
duplicate.log = stopped.log
self.scripts.insert(self.running_script_position, duplicate)
# Update script states and graphical information
self.update_script_widgets()
else:
if poll != 0:
# Script stopped because of an error
self.running_script.state = 'ended'
self.running_script.success = 'failed'
elif poll == 0:
# Script successfully ended
self.running_script.state = 'ended'
self.running_script.success = 'done'
if settings.gmail_notifications['enable']:
self.gmail_notify()
if self.running_script_position + 1 < len(self.scripts):
# more scripts are queued: run the next one
self.run(position=self.running_script_position + 1)
else:
# no more scripts to be run: just update visual information
self.state = 'stopped'
self.update_script_widgets()
def stop(self):
'''
Triggered by a user clicking the stop button
all one needs to do is set the state to `stopped`
and force the script to stop, the automatic
monitoring of the running script in `monitor_script_process`
will take care of the following actions
'''
self.state = 'stopped'
# Interrupt process
self.script_process.kill()
def update_script_widgets(self):
'''
Updates the states of the ScriptWidget objects
and updates the graphical information displayed.
All is determined by the `self.states` list
and the `self.state` variable.
'''
# The self.scripts list should never be empty
# as a failsafe we always populate it in that case
# with the insert widget
if len(self.scripts) == 0:
self.scripts = [InsertWidget(self)]
return
# The row is a property of the non-done scripts
# it is displayed in the GUI starting from 1
row = 1
for i, s in enumerate(self.scripts):
# All scripts are given a position, running from 0 upwards
# this is not necessarily the same as the row and acts
# as a unique identifier of the script
s.position = i
# Scripts which are done are given no row information
s.row = None
if s.state in ['running', 'ready', 'queued'] or row > 1:
if row == 1:
# First script running/to-run
# Helps in converting rows given by the user
# to the position identifier of a script
self.position_0 = i
# Since this is the first script which has not already been run
# it should be either running or stopped
if self.state == 'running':
s.state = 'running'
self.running_script = s
self.running_script_position = i
elif self.state == 'stopped':
s.state = 'ready'
elif row > 1:
# this script is lower down the queue:
# if they were just moved for example, we should
# adjust their state accordingly
s.state = 'queued'
# These non-done scripts are given a row
s.row = row
row += 1
for i, s in enumerate(self.scripts):
# Place the script in the grid
s.grid(row=i, column=0, sticky='news')
# Populate it with buttons etc...
s.add_widgets()
# Adjust the scrollable region of the GUI
self.update()
self.config(scrollregion=self.bbox("all"))
def build_gridframe(self):
"""
This frame will be divided into a grid hosting the
canvas, scrollbars, (and potentially a menubar in the future if needed)
"""
self.frame = ttk.Frame()
# Places the Frame widget self.frame in the parent
# in a grid
self.frame.grid()
# Configure the frames grid
self.frame.grid(sticky="nswe") # make frame container sticky
self.frame.rowconfigure(0, weight=1) # make canvas expandable in x
self.frame.columnconfigure(0, weight=1) # make canvas expandable in y
def build_menubar(self):
"""
Builds the File, Edit, ... menu bar situated at the top of
the window.
Not used for the moment...
"""
# initialize the menubar object
self.menubar = tk.Menu(self.frame)
####################################
# FILE cascade menu build
####################################
# add new item to the menubar
menu = tk.Menu(self.menubar, tearoff=0)
self.menubar.add_cascade(label="File", menu=menu)
####################################
# VIEW cascade menu build
####################################
# add new item to the menubar
menu = tk.Menu(self.menubar, tearoff=0)
self.menubar.add_cascade(label="View", menu=menu)
# add cascade menu items
menu.add_command(label="Output", command=self.build_output_window)
# Add the menubar to the application
self.master.config(menu=self.menubar)
def build_scrollbars(self):
"""
Builds a vertical scrollbars and places
it in the window
"""
self.vbar = ttk.Scrollbar(self.frame, orient="vertical")
self.vbar.grid(row=0, column=1, sticky="ns")
def build_canvas(self):
"""
Initializes the canvas from which this object inherits and
places it in the grid of our frame
"""
tk.Canvas.__init__(
self,
self.frame,
bd=0,
highlightthickness=0,
yscrollcommand=self.vbar.set,
confine=False,
bg="white",
)
self.grid(row=0, column=0, sticky="nswe")
def configure_scrollbars(self):
"""
Define what functions the scrollbars should call
when we interact with them, and make scrolling
on the mouse do something similar
"""
self.vbar.configure(command=self.scroll_y)
self.bind("<MouseWheel>", self.scroll_y_wheel)
def scroll_y(self, *args, **kwargs):
"""
Is called when the user interacts with the vertical scroll bar
"""
# stop from scolling up beyond a certain point
if float(args[1]) < 0:
args = (args[0], "0")
# shift canvas vertically
self.yview(*args)
time.sleep(0.01)
# Update scrollable area
self.update()
self.config(scrollregion=self.bbox("all"))
def scroll_y_wheel(self, event):
"""
Triggered by the user scrolling (in combination with no particular key presses).
"""
# Determine which direction the user is scrolling
# if using windows, then event.delta has also a different
# amplitude depending on how fast the user is scrolling,
# but we ignore that
if event.num == 5 or event.delta < 0:
direction = 1
if event.num == 4 or event.delta > 0:
direction = -1
# Move the canvas appropriately, and stop
# the user from scrolling to far out
if direction == 1:
if self.canvasy(self.winfo_height()) < 2 * self.bbox("all")[3]:
self.yview_scroll(direction, tk.UNITS)
elif direction == -1:
if self.canvasy(0) > self.bbox("all")[1]:
self.yview_scroll(direction, tk.UNITS)
self.update()
# if we scroll above the top row, move a little down..
if self.canvasy(0) < self.bbox("all")[1]:
self.yview_moveto(0)
# Update the scrollable region
self.update()
self.config(scrollregion=self.bbox("all"))
def build_canvas_content(self):
'''
Build a window which will contain the widgets
'''
self.canvas_content = tk.Frame(self)
self.create_window((0, 0),
window=self.canvas_content,
anchor='nw',
width=1000)
self.canvas_content.columnconfigure(0, weight=1)
class ScriptWidget(tk.Frame):
'''
Widget (tkinter frame) in which are stored all the graphical
elements and information about a script.
'''
def next_script_state(self):
'''
Returns the state of the script below the current
one. Returns None is this is the last script.
'''
try:
return self.parent.scripts[self.position + 1].state
except IndexError:
# This script is last in line
return None
def add_widgets(self):
'''
Builds all graphical elements
depending on the state and information
about the script.
'''
# remove all previously bult graphical elements
for w in self.all_widgets:
w.destroy()
self.all_widgets = []
##################
# INSERT BUTTON
##################
if self.next_script_state() in ['ready', 'queued', None]:
b = ImageButton(
self,
image='insert.gif',
command=(lambda: self.parent.insert(self.position)))
else:
b = ImageButton(self, image='half_blank.gif')
b.config(state=tk.DISABLED)
b.grid(row=0, column=0, sticky='swe', padx=(5, 0))
self.all_widgets.append(b)
##################
# ROW LABEL
##################
if self.state == 'ended':
l = ImageLabel(self, image='blank.gif', compound=tk.CENTER)
else:
l = ImageLabel(self,
image='blank.gif',
compound=tk.CENTER,
text=self.row)
l.grid(row=0, column=1, sticky='new')
self.all_widgets.append(l)
##################
# STATE LABEL
##################
if self.state == 'ended':
text = self.success
else:
text = self.state
b = ImageLabel(self,
text=text,
image='label_' + self.state + self.success + ".gif",
compound=tk.CENTER)
b.grid(row=0, column=2, sticky='new')
self.all_widgets.append(b)
##################
# REMOVE BUTTON
##################
if self.state == 'running':
b = ImageButton(self, image='blank.gif')
b.config(state=tk.DISABLED)
else:
b = ImageButton(
self,
image='remove.gif',
command=(lambda: self.parent.remove(self.position)))
b.grid(row=0, column=3, sticky='new', pady=self.pady)
self.all_widgets.append(b)
##################
# MOVE BUTTON
##################
if self.state in ['queued', 'ready']:
b = ImageButton(self,
image='move.gif',
command=(lambda: self.parent.move(self.position)))
else:
b = ImageButton(self, image='blank.gif')
b.config(state=tk.DISABLED)
b.grid(row=0, column=4, sticky='new', pady=self.pady)
self.all_widgets.append(b)
##################
# RUN/STOP BUTTON
##################
if self.state == 'running':
b = ImageButton(self, image='stop.gif', command=self.parent.stop)
elif self.state == 'ready':
b = ImageButton(self,
image='run.gif',
command=(lambda: self.parent.run(self.position)))
else:
b = ImageButton(self, image='blank.gif')
b.config(state=tk.DISABLED)
b.grid(row=0, column=5, sticky='new', pady=self.pady)
self.all_widgets.append(b)
##################
# LOG/OUTPUT BUTTON
##################
if self.state == 'ended':
b = ImageButton(self,
text="view log",
command=self.view_log,
image='blank.gif',
compound=tk.CENTER)
elif self.state in ['running', 'ready']:
b = ImageButton(self,
text="view output",
command=self.parent.build_output_window,
image='blank.gif',
compound=tk.CENTER)
else:
b = ImageButton(self,
text="",
command=self.parent.build_output_window,
image='blank.gif',
compound=tk.CENTER)
b.config(state=tk.DISABLED)
self.all_widgets.append(b)
b.grid(row=0, column=6, sticky='ne', pady=self.pady, padx=(2, 10))
##################
# SCRIPT PATH LABEL
##################
b = tk.Label(
self,
text=self.script_path,
anchor=tk.W,
)
b.grid(row=0,
column=7,
columnspan=1,
sticky='new',
pady=self.pady,
padx=(0, 40))
self.columnconfigure(7, weight=1)
self.all_widgets.append(b)
self.update()
# Wrap the path text
b.config(wraplength=b.winfo_width() - 50)
class InsertWidget(ScriptWidget):
'''Like Script Widget, but with just an insert button.
'''
def add_widgets(self):
'''
Add the graphical elements of the widget
'''
if self.next_script_state() in ['ready', 'queued', None]:
b = ImageButton(
self,
image='insert.gif',
command=(lambda: self.parent.insert(self.position)))
else:
b = ImageButton(self, image='half_blank.gif')
b.config(state=tk.DISABLED)
b.grid(row=0, column=0, sticky='swe', padx=(5, 0))
class ImageButton(ttk.Button):
'''Wrapper around the ttk.Button class
which automizes the importation of the
buttons picture.
'''
class ImageLabel(ttk.Label):
"""docstring for ImageButton"""
class ToggleAutoscrollButton(tk.Radiobutton):
"""Button which turns auto scrolling on and off.
"""
def click(self):
'''
Called upon clicking the button
'''
if self.state.get():
# If autoscrolling is on
self.config(value=False)
self.parent.follow = False
else:
# If autoscrolling is off
self.config(value=True)
self.state.set(True)
self.parent.follow = True
class ScrolledLabel(scrolledtext.ScrolledText):
"""wrapper around scrolledtext, to make
the text read-only
"""
def reader(f, buffer):
'''Utility function runing in a thread
which transfers any lines from the
pipe `f` into the list `buffer`
'''
while True:
line = f.readline()
if line:
buffer.append(line)
else:
break
if __name__ == '__main__':
GuiWindow()
|
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220,
12656,
4600,
69,
63,
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262,
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22252,
63,
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705,
7061,
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220,
220,
981,
6407,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1627,
796,
277,
13,
961,
1370,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
1627,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
11876,
13,
33295,
7,
1370,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1962,
72,
27703,
3419
] | 2.150588 | 13,693 |
import coursera_requests as c
import sys
try:
# c.getCourseraCategories()
c.getCourseraCourses()
# c.getCourseraInstructors()
# c.getCourseraSessions()
# c.getCourseraUniversities()
except:
print ("Unexpected error:", sys.exc_info()[0])
raise
|
[
11748,
1093,
2655,
64,
62,
8897,
3558,
355,
269,
198,
11748,
25064,
198,
198,
28311,
25,
198,
2,
220,
197,
66,
13,
1136,
25877,
2655,
64,
34,
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3419,
198,
197,
66,
13,
1136,
25877,
2655,
64,
34,
39975,
3419,
198,
2,
220,
197,
66,
13,
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25877,
2655,
64,
43993,
669,
3419,
198,
2,
220,
197,
66,
13,
1136,
25877,
2655,
64,
50,
6202,
3419,
198,
2,
220,
197,
66,
13,
1136,
25877,
2655,
64,
3118,
1191,
871,
3419,
198,
16341,
25,
198,
197,
4798,
5855,
52,
42072,
4049,
25,
1600,
25064,
13,
41194,
62,
10951,
3419,
58,
15,
12962,
198,
197,
40225
] | 2.403846 | 104 |
#!/usr/bin/python
# Copyright 2012, Kevin Ko <[email protected]>. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
#
# Generates an 8-bit log base 2 table.
# Print out an inverse 8-bit log table
print "-1, 0, 1, 1," # log(i) for i in 0, 1, 2, 3
print "2, 2, 2, 2," # ... 4, 5, 6, 7
print "3, 3, 3, 3, 3, 3, 3, 3," # ... 8-15
lt(4) # 16-31
# 32-63
[lt(5) for i in xrange(2)]
# 64-127
[lt(6) for i in xrange(4)]
# 128-255
[lt(7) for i in xrange(8)]
|
[
2,
48443,
14629,
14,
8800,
14,
29412,
198,
198,
2,
15069,
2321,
11,
7939,
17634,
1279,
365,
7114,
31,
69,
3080,
316,
13,
785,
28401,
220,
1439,
2489,
10395,
13,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
257,
347,
10305,
12,
7635,
198,
2,
5964,
326,
460,
307,
1043,
287,
262,
38559,
24290,
2393,
13,
198,
2,
198,
2,
2980,
689,
281,
807,
12,
2545,
2604,
2779,
362,
3084,
13,
198,
198,
2,
12578,
503,
281,
34062,
807,
12,
2545,
2604,
3084,
198,
4798,
27444,
16,
11,
657,
11,
352,
11,
352,
553,
220,
1303,
2604,
7,
72,
8,
329,
1312,
287,
657,
11,
352,
11,
362,
11,
513,
198,
4798,
366,
17,
11,
362,
11,
362,
11,
362,
553,
220,
220,
1303,
2644,
604,
11,
642,
11,
718,
11,
767,
198,
4798,
366,
18,
11,
513,
11,
513,
11,
513,
11,
513,
11,
513,
11,
513,
11,
513,
553,
220,
1303,
2644,
807,
12,
1314,
198,
2528,
7,
19,
8,
220,
1303,
1467,
12,
3132,
198,
198,
2,
3933,
12,
5066,
198,
58,
2528,
7,
20,
8,
329,
1312,
287,
2124,
9521,
7,
17,
15437,
198,
198,
2,
5598,
12,
16799,
198,
58,
2528,
7,
21,
8,
329,
1312,
287,
2124,
9521,
7,
19,
15437,
198,
198,
2,
13108,
12,
13381,
198,
58,
2528,
7,
22,
8,
329,
1312,
287,
2124,
9521,
7,
23,
15437,
198
] | 2.313043 | 230 |
from LibSerial4.LibSerial4 import Serial, Uart
|
[
6738,
7980,
32634,
19,
13,
25835,
32634,
19,
1330,
23283,
11,
471,
433
] | 3.538462 | 13 |
# Generated by Django 2.1.2 on 2018-11-22 17:40
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
|
[
2,
2980,
515,
416,
37770,
362,
13,
16,
13,
17,
319,
2864,
12,
1157,
12,
1828,
1596,
25,
1821,
198,
198,
6738,
42625,
14208,
13,
10414,
1330,
6460,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
198,
11748,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
628
] | 3.019231 | 52 |
if __name__ == "__main__":
print(fun(5)) # Always returns 25
|
[
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
3601,
7,
12543,
7,
20,
4008,
1303,
16622,
5860,
1679,
198
] | 2.538462 | 26 |
import matplotlib.pyplot as plt
import sys
"""
Utility script to plot Execution time Vs Number of vertices based on the log-files obtained by running tests/*.sh
"""
lines = open(sys.argv[1]).readlines()[1::2]
x = map(lambda xx: 5*eval(xx.strip().split('\t')[1].split(' ')[1]), lines[::2])
# x = map(lambda xx: 400*eval(xx.strip().split(' ')[1].split('\t')[0]), lines[::2])
y = map(lambda xx: eval(xx.split(' ')[2]), lines[1::2])
t = {}
c = {}
for xx in x:
c[xx] = 0
t[xx] = 0
for i in range(len(y)):
xx = x[i]
t[xx] += y[i]
c[xx] += 1
y_plot = []
for i in range(len(y)):
xx = x[i]
y_plot.append(t[xx]*0.0001*25/c[xx])
# y_plot.append(t[xx]*14.711*0.6*0.5*10*16/c[xx])
print x
print y_plot
# print t[700]*10.0/c[700]
# print y_plot
plt.xlabel("Edges | Number of vertices = 5000")
# plt.xlabel("Vertices")
plt.ylabel("Execution time ( s )")
plt.plot(x,y_plot,'ro')
plt.show()
|
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879,
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284,
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640,
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1063,
1912,
319,
262,
2604,
12,
16624,
6492,
416,
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5254,
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13,
1477,
198,
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198,
6615,
796,
1280,
7,
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13,
853,
85,
58,
16,
35944,
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6615,
3419,
58,
16,
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17,
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87,
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3975,
7,
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31383,
25,
642,
9,
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7,
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13,
36311,
22446,
35312,
10786,
59,
83,
11537,
58,
16,
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705,
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16,
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3951,
58,
3712,
17,
12962,
198,
2,
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796,
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7,
50033,
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25,
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9,
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7,
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13,
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705,
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16,
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58,
15,
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3951,
58,
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17,
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88,
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7,
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705,
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17,
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3951,
58,
16,
3712,
17,
12962,
198,
83,
796,
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198,
66,
796,
23884,
198,
1640,
31383,
287,
2124,
25,
198,
220,
220,
220,
269,
58,
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60,
796,
657,
198,
220,
220,
220,
256,
58,
5324,
60,
796,
657,
198,
1640,
1312,
287,
2837,
7,
11925,
7,
88,
8,
2599,
198,
220,
220,
220,
31383,
796,
2124,
58,
72,
60,
198,
220,
220,
220,
256,
58,
5324,
60,
15853,
331,
58,
72,
60,
198,
220,
220,
220,
269,
58,
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60,
15853,
352,
198,
88,
62,
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796,
17635,
198,
1640,
1312,
287,
2837,
7,
11925,
7,
88,
8,
2599,
198,
220,
220,
220,
31383,
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2124,
58,
72,
60,
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220,
220,
220,
331,
62,
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13,
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7,
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58,
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60,
9,
15,
13,
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9,
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14,
66,
58,
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1303,
331,
62,
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60,
9,
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22,
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13,
21,
9,
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20,
9,
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14,
66,
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2,
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58,
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60,
9,
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13,
15,
14,
66,
58,
9879,
60,
198,
2,
3601,
331,
62,
29487,
198,
198,
489,
83,
13,
87,
18242,
7203,
7407,
3212,
930,
7913,
286,
9421,
1063,
796,
23336,
4943,
198,
2,
458,
83,
13,
87,
18242,
7203,
42369,
1063,
4943,
198,
489,
83,
13,
2645,
9608,
7203,
23002,
1009,
640,
357,
264,
1267,
4943,
198,
198,
489,
83,
13,
29487,
7,
87,
11,
88,
62,
29487,
4032,
305,
11537,
198,
489,
83,
13,
12860,
3419,
198
] | 2.161905 | 420 |
"""
Test CLI for metric integration.
"""
from argparse import ArgumentParser
from getpass import getuser
from time import sleep
from microcosm.api import create_object_graph
from microcosm.loaders import load_from_dict
from microcosm_metrics.naming import name_for
def publish():
"""
Publish a metric (for testing).
"""
args = parse_args()
statsd = create_statsd_client(args)
if args.action == "increment":
statsd.increment(name_for(getuser(), args.action))
elif args.action == "histogram":
statsd.histogram(name_for(getuser(), args.action), 1.0)
try:
# wait a little to allow the delivery of the metric before we exit
sleep(1.0)
except KeyboardInterrupt:
pass
|
[
37811,
198,
14402,
43749,
329,
18663,
11812,
13,
198,
198,
37811,
198,
6738,
1822,
29572,
1330,
45751,
46677,
198,
6738,
651,
6603,
1330,
651,
7220,
198,
6738,
640,
1330,
3993,
198,
198,
6738,
4580,
6966,
76,
13,
15042,
1330,
2251,
62,
15252,
62,
34960,
198,
6738,
4580,
6966,
76,
13,
2220,
364,
1330,
3440,
62,
6738,
62,
11600,
198,
198,
6738,
4580,
6966,
76,
62,
4164,
10466,
13,
77,
3723,
1330,
1438,
62,
1640,
628,
628,
198,
4299,
7715,
33529,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
8525,
1836,
257,
18663,
357,
1640,
4856,
737,
628,
220,
220,
220,
37227,
198,
220,
220,
220,
26498,
796,
21136,
62,
22046,
3419,
198,
220,
220,
220,
9756,
67,
796,
2251,
62,
34242,
67,
62,
16366,
7,
22046,
8,
628,
220,
220,
220,
611,
26498,
13,
2673,
6624,
366,
24988,
434,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
9756,
67,
13,
24988,
434,
7,
3672,
62,
1640,
7,
1136,
7220,
22784,
26498,
13,
2673,
4008,
198,
220,
220,
220,
1288,
361,
26498,
13,
2673,
6624,
366,
10034,
21857,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
9756,
67,
13,
10034,
21857,
7,
3672,
62,
1640,
7,
1136,
7220,
22784,
26498,
13,
2673,
828,
352,
13,
15,
8,
628,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4043,
257,
1310,
284,
1249,
262,
7585,
286,
262,
18663,
878,
356,
8420,
198,
220,
220,
220,
220,
220,
220,
220,
3993,
7,
16,
13,
15,
8,
198,
220,
220,
220,
2845,
31973,
9492,
3622,
25,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198
] | 2.766667 | 270 |
from metrics import *
from itembased_recommender_system import *
import shelve
import matplotlib.pyplot as plt
genData('base','u2.base')
genData('test','u2.test')
print("data ready")
base = transform(shelve.open('base'))
test = transform(shelve.open('test'))
##base = {'max':{'odin doma':3,'labirint straha':5,'detektiv':2,'komnata':4},
## 'dima':{'odin doma':5,'labirint straha':1,'detektiv':5},
## 'alex':{'odin doma':5,'pila':2,'komnata':3,'grabim bank':3,'labirint straha':1,'detektiv':4,'dom s privideniamy':3},
## 'den':{'odin doma':2,'grabim bank':3,'labirint straha':5,'dom s privideniamy':5},
## 'kirill':{'grabim bank':3,'labirint straha':4,'detektiv':1,'dom s privideniamy':5},
## 'olga':{'odin doma':3,'pila':4,'detektiv':4,'komnata':1,'dom s privideniamy':3},
## 'lera':{'odin doma':4,'pila':3,'grabim bank':4,'labirint straha':1},
## 'anna':{'pila':4,'grabim bank':2,'labirint straha':5,'komnata':4,'detektiv':4,'dom s privideniamy':4}}
##
##test = {'max':{'pila':4,'dom s privideniamy':3},
## 'dima':{'pila':2,'dom s privideniamy':1},
## 'kirill':{'odin doma':3,'pila':4},
## 'olga':{'grabim bank':4,'labirint straha':1}}
print("opened with size %d"%len(base))
tr = transform(base)
print("transformed")
ns = [30,100,200,300,500,0]
##ns = [1,2,3,4,5,6]
cls = ['b','g','r','c','m','y']
markers = ['.',',','o','v','^','<','>','p','*','+']
cls_n = 0
for n in ns:
metrix = [JMSD,PCC,CPCC,SPCC,Jaccard,MSD,COS,ACOS]
maes = {}
for sim in metrix:
if (n != 0):
itMtr = itemMatrix(tr,n,sim)
else:
itMtr = itemMatrix(tr,n,sim,False)
orig_recs = {}
test_recs = {}
for user in test:
orig_recs[user] = {}
test_recs[user] = {}
for item in test[user]:
rec = recommendOne(base,tr,itMtr,item,user)
if (rec != 200):
orig_recs[user][item] = rec
test_recs[user][item] = test[user][item]
mae = MAE(test_recs,orig_recs)
print("Mae for %s is %f"%(sim.__name__,mae))
maes[sim.__name__] = mae
print(maes)
labels = sorted(maes)
x = [0,1,2,3,4,5,6,7]
y = [maes[i] for i in labels]
plt.plot(x,y,color = cls[cls_n],marker = markers[cls_n],linewidth=1.5,label = 'k = '+str(n))
## plt.plot(x,y,'ko')
cls_n += 1
plt.title('maes, user-based')
plt.axis([-1,8,0.7,1.1])
plt.ylabel('MAE')
plt.xlabel('metrics')
plt.xticks(x,labels,rotation='vertical')
plt.subplots_adjust(bottom=0.15)
plt.legend()
##for i,j in zip(x,y):
## plt.annotate(str(round(j,4)),xy=(i-0.5,j+0.01))
plt.show()
##plt.savefig('E:/Diploma/results/maes-item-based_n'+str(n)+'.png')
|
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201,
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6738,
2378,
3106,
62,
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62,
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1330,
1635,
201,
198,
11748,
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303,
201,
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29487,
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13,
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19,
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3438,
264,
1953,
14029,
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988,
83,
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4458,
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11537,
201,
198
] | 1.842479 | 1,549 |
from qiskit.circuit.quantumcircuit import QuantumCircuit, QuantumRegister, ClassicalRegister
|
[
6738,
10662,
1984,
270,
13,
21170,
5013,
13,
40972,
388,
21170,
5013,
1330,
29082,
31560,
5013,
11,
29082,
38804,
11,
43680,
38804
] | 4.181818 | 22 |
import json
import logging
from urllib.parse import urlencode, parse_qs
from urllib.request import urlopen
from django.conf import settings
from oauth.exceptions import QQAPIException
logger = logging.getLogger('django')
class OauthQQ(object):
"""
QQ认证工具类
"""
def get_auth_url(self):
"""
生成访问qq的拼接路径
:return:
"""
parameters = {
'response_type': 'code',
'client_id': self.app_id,
'redirect_uri': self.redirect_uri,
'state': self.state,
'scope': 'get_user_info',
}
return 'https://graph.qq.com/oauth2.0/authorize?' + urlencode(parameters)
def get_access_token(self, code):
"""
获取QQ的access_token
:param code: 重定向域路径中code
:return: access_token
"""
parameters = {
'grant_type': 'authorization_code',
'client_id': self.app_id,
'client_secret': self.app_key,
'code': code,
'redirect_uri': self.redirect_uri
}
url = 'https://graph.qq.com/oauth2.0/token?' + urlencode(parameters)
# access_token=FE04************************CCE2&expires_in=7776000&refresh_token=88E4************************BE14
try:
response = urlopen(url).read().decode()
response_dict = parse_qs(response)
access_token = response_dict.get("access_token")[0]
except Exception as e:
logger.error(e)
raise QQAPIException('获取access_token异常')
return access_token
def get_openid(self, access_token):
"""
获取QQ用户的openid
:param access_token: 服务器获取的access_token
:return: openid
"""
url = 'https://graph.qq.com/oauth2.0/me?access_token=' + access_token
# callback( {"client_id":"YOUR_APPID","openid":"YOUR_OPENID"} );
try:
reponse = urlopen(url).read().decode()
# TODO:可以换种方式操作字符串
reponse_dict = json.loads(reponse[10:-4])
except Exception as e:
logger.error(e)
raise QQAPIException('获取openid异常')
return reponse_dict.get('openid')
|
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] | 1.895147 | 1,154 |
#
# aac_state_base.py, doom-net
#
# Created by Andrey Kolishchak on 01/21/17.
#
import os
import datetime
import glob
from multiprocessing.pool import ThreadPool
from threading import Thread
import time
import h5py
import bisect
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import numpy as np
from device import device
from model import Model
from state_model import StateModel
from state_controller import AdvantageActorCriticController
import vizdoom
|
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2,
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] | 3.563758 | 149 |
# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""utils"""
import sys
from pathlib import Path
lib_dir = (Path(__file__).parent / '..').resolve()
if str(lib_dir) not in sys.path:
sys.path.insert(0, str(lib_dir))
############################
# operations for all tasks #
############################
|
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2,
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329,
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628
] | 3.944681 | 235 |
"""
vtelem - Test the channel-group registry's correctness.
"""
# module under test
from vtelem.enums.primitive import Primitive
from vtelem.channel.group_registry import ChannelGroupRegistry
from vtelem.telemetry.environment import TelemetryEnvironment
# internal
from . import EnumA
def test_group_registry_basic():
"""Test simple functionality of a group registry."""
env = TelemetryEnvironment(2 ** 8)
assert env.add_from_enum(EnumA) >= 0
reg = ChannelGroupRegistry(env)
groups = [
reg.create_group("a"),
reg.create_group("b"),
reg.create_group("c"),
]
# add channels to each group
for group in groups:
reg.add_channel(group, "a", Primitive.UINT32, 1.0)
reg.add_channel(group, "b", Primitive.UINT32, 1.0)
reg.add_channel(group, "c", Primitive.UINT32, 1.0)
reg.add_enum_channel(group, "test_enum", "enum_a", 1.0)
# write channels in each group
for group in groups:
with reg.group(group) as data:
data["a"] = 1
data["b"] = 2
data["c"] = 3
data["test_enum"] = "b"
# read channels in each group to make sure correct values were written
for group in groups:
with reg.group(group) as data:
assert data["a"] == 1
assert data["b"] == 2
assert data["c"] == 3
assert data["test_enum"] == "b"
|
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] | 2.389831 | 590 |
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
res = [line.strip().split('\t') for line in open("sizes.txt").readlines()]
a = []
for line in res:
sizes = [int(i) for i in line[1].split(',')]
strands = [j for j in line[2].split(',')]
for si, st in zip(sizes, strands):
a.append((line[0], si, st))
df = pd.DataFrame(a, columns=['name', 'length', 'strand1'])
df.loc[df.strand1 == "True", 'strand'] = '-'
df.loc[df.strand1 == "False", 'strand'] = '+'
df.replace(dict(d6843='Patient1',
d5945='Patient2'),
regex=True,
inplace=True
)
plt.close("all")
sns.swarmplot(x="name", y="length", data=df, hue="strand")
plt.legend(loc='upper left', title="strand", frameon=False)
plt.show()
|
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28,
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220,
220,
220,
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220,
220,
220,
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198,
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83,
13,
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7203,
439,
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82,
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13,
2032,
1670,
29487,
7,
87,
2625,
3672,
1600,
331,
2625,
13664,
1600,
1366,
28,
7568,
11,
37409,
2625,
2536,
392,
4943,
198,
489,
83,
13,
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437,
7,
17946,
11639,
45828,
1364,
3256,
3670,
2625,
2536,
392,
1600,
5739,
261,
28,
25101,
8,
198,
489,
83,
13,
12860,
3419,
198
] | 2.170868 | 357 |
from itertools import starmap, filterfalse, zip_longest
from itertools import chain
import functools
from functools import reduce as reduce_
import operator
from collections import namedtuple
import toolz
from toolz import pipe as pipe_, compose as compose_
from ._iterators import _iterators_controller, _controlled_iterator
"""
designing a lookup scheme.
accepts any Iterable
for each item in this iterable
- computes a key value from the item data using a provided callable
- checks if a provided lookup map contains this key
if yes:
- outputs this item optionally enriched with the lookup data using
another provided callable
if no:
if rejects are enabled:
- outputs this item in a separate iterator
"""
@stream_converter.dispatch(tuple, tuple)
@stream_converter.dispatch(dict, dict)
@stream_converter.dispatch(namedtuple, namedtuple)
@stream_converter.dispatch(tuple, dict, key_type=str)
@stream_converter.dispatch(tuple, dict, key_type=int)
@stream_converter.dispatch(tuple, namedtuple)
@stream_converter.dispatch(dict, tuple)
@stream_converter.dispatch(dict, namedtuple)
@stream_converter.dispatch(namedtuple, dict)
@stream_converter.dispatch(namedtuple, tuple)
def xargs(g, funcs, as_iterable=False):
"""returns a function that accepts a tuple as an arguments and then
maps each element of this tuple to one of the funcs generating another
tuple in the process. Finally, the function g is called with the tuple
elements as arguments.
If the tuple does not contain enough elements to map all the funcs,
the last element is repeated to provide an argument to the remaining funcs
"""
return inner
|
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198,
220,
220,
220,
37227,
628,
220,
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1441,
8434,
198
] | 3.280769 | 520 |
# -*- coding: utf-8 -*-
"""Mocks for tests."""
from typing import Optional, Tuple
import torch
from torch import nn
from pykeen.models import EntityRelationEmbeddingModel, Model
from pykeen.nn.emb import EmbeddingSpecification, RepresentationModule
from pykeen.triples import TriplesFactory
__all__ = [
'CustomRepresentations',
'MockModel',
]
class CustomRepresentations(RepresentationModule):
"""A custom representation module with minimal implementation."""
class MockModel(EntityRelationEmbeddingModel):
"""A mock model returning fake scores."""
def _generate_fake_scores(self, batch: torch.LongTensor) -> torch.FloatTensor:
"""Generate fake scores s[b, i] = i of size (batch_size, num_entities)."""
batch_size = batch.shape[0]
batch_scores = self.scores.view(1, -1).repeat(batch_size, 1)
assert batch_scores.shape == (batch_size, self.num_entities)
return batch_scores
|
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2,
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13,
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7,
16,
11,
532,
16,
737,
44754,
7,
43501,
62,
7857,
11,
352,
8,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
15458,
62,
1416,
2850,
13,
43358,
6624,
357,
43501,
62,
7857,
11,
2116,
13,
22510,
62,
298,
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8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
15458,
62,
1416,
2850,
198
] | 2.883792 | 327 |
import re
def email(value):
"""Validate an email address
>>> email("[email protected]")
True
>>> email("barneydino.com")
'An email address must contain a single @'
"""
usernameRE = re.compile(r"^[^ \t\n\r@<>()]+$", re.I)
domainRE = re.compile(r'''
^(?:[a-z0-9][a-z0-9\-]{0,62}\.)+ # (sub)domain - alpha followed by 62max chars (63 total)
[a-z]{2,}$ # TLD
''', re.I | re.VERBOSE)
messages = dict(
empty='Please enter an email address',
noAt='An email address must contain a single @',
badUsername='The username portion of the email address is invalid'
' (the portion before the @: {username!s}',
socketError='An error occured when trying to connect to the server:'
' {error!s}',
badDomain='The domain portion of the email address is invalid'
' (the portion after the @: {domain!s}',
domainDoesNotExist='The domain of the email address does not exist'
' (the portion after the @: {domain!s}')
if not value:
return messages['empty']
value = value.strip()
splitted = value.split('@', 1)
try:
username, domain=splitted
except ValueError:
return messages['noAt']
if not usernameRE.search(username):
return messages['badUsername'].format(username=username)
if not domainRE.search(domain):
return messages['badDomain'].format(domain=domain)
return True
def url(value):
"""Validate a URL completely
>>> url("ixmat.us")
True
>>> url("ixmat")
'You must provide a full domain name (like ixmat.com)'
"""
messages = dict(
noScheme='You must start your URL with http://, https://, etc',
badURL='That is not a valid URL',
httpError='An error occurred when trying to access the URL: {error!s}',
socketError='An error occured when trying to connect to the server: {error!s}',
notFound='The server responded that the page could not be found',
status='The server responded with a bad status code ({status!s})',
noTLD='You must provide a full domain name (like {domain!s}.com)')
url_re = re.compile(r'''
^(http|https)://
(?:[%:\w]*@)? # authenticator
(?: # ip or domain
(?P<ip>(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?))|
(?P<domain>[a-z0-9][a-z0-9\-]{,62}\.)* # subdomain
(?P<tld>[a-z]{2,63}|xn--[a-z0-9\-]{2,59}) # top level domain
)
(?::[0-9]{1,5})? # port
# files/delims/etc
(?P<path>/[a-z0-9\-\._~:/\?#\[\]@!%\$&\'\(\)\*\+,;=]*)?
$
''', re.I | re.VERBOSE)
scheme_re = re.compile(r'^[a-zA-Z]+:')
value = value.strip()
if not scheme_re.search(value):
value = "http://" + value
value = encode_idna(value)
match = scheme_re.search(value)
if not match:
return messages['noScheme']
value = match.group(0).lower() + value[len(match.group(0)):]
match = url_re.search(value)
if not match:
return messages['badURL']
if not match.group('domain'):
return messages['noTLD'].format(domain=match.group('tld'))
return True
|
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] | 2.11995 | 1,609 |
import json
import urllib
import requests
import Config
import logging
logging.basicConfig(level=logging.DEBUG)
# Class to access the new Twitch 'HELIX' API
# The class receives it's authentication from a dictionary (HEADERS) in the Config.py file.
# The "Bearer" token must have the required scopes to perform successful API calls.
# Function to make a JSON request to the Twitch API
# Get the ID of a given username
# Gather all available data for a specified user
# Get first 100 moderators of a channel. "Pagination" must be used for more than 100 results.
# Request requires a valid Bearer (Helix Oauth) token.
# Check if a specified user is a moderator in the channel
# Check if a specified user is following the channel
# Check if a viewer is subscribed to teh channel
# Creates a clip from the live stream. Test when live as
# when not live it shows a previously created clip.
# Check if a user is banned from the channel
# Get followed channel since date
# The following functions use the Twitch V5 API and require a separate token (OAuth)
# The below will retrieve current "Chatters" in a channel.
# THESE ARE NOT A TWITCH API FUNCTIONS - UNDOCUMENTED
# This has a delayed refresh time (currently unknown).
# Note: Due to some viewers/bots being connected anon to the channel
# this will only show chatters and not all viewers.
|
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] | 3.644501 | 391 |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import os
g_playerDict = {'player1':u"nobody",
'player2':u"nobody",
'player3':u"nobody",
'player4':u"nobody",
'player5':u"nobody",
'player6':u"nobody",
'player7':u"nobody",
'player8':u"nobody",
'player9':u"nobody",
'player10':u"nobody",
'player11':u"nobody",
'player12':u"nobody",
'player13':u"nobody",
'player14':u"nobody",
'player15':u"nobody",
'player16':u"nobody",
}
|
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#!E:\py_virtual_env\saas_project\Scripts\python.exe
# -*- coding: utf-8 -*-
from django import forms
from web import models
from django.core.validators import RegexValidator,ValidationError
from django.core.exceptions import ValidationError
from django.conf import settings
from django_redis import get_redis_connection
from utils import encrypt
from utils.tencent.sms import send_sms_single
import random
|
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3758,
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198,
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] | 3.222222 | 126 |
'''
When squirrels get together for a party, they like to have cigars. A squirrel
party is successful when the number of cigars is between 40 and 60,
inclusive. Unless it is the weekend, in which case there is no upper bound on
the number of cigars. Return True if the party with the given values is
successful, or False otherwise.
'''
|
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] | 4.148148 | 81 |
class NotifyIcon(Component, IComponent, IDisposable):
"""
Specifies a component that creates an icon in the notification area. This class cannot be inherited.
NotifyIcon()
NotifyIcon(container: IContainer)
"""
def Dispose(self):
""" Dispose(self: NotifyIcon,disposing: bool) """
pass
def GetService(self, *args):
"""
GetService(self: Component,service: Type) -> object
Returns an object that represents a service provided by the System.ComponentModel.Component or
by its System.ComponentModel.Container.
service: A service provided by the System.ComponentModel.Component.
Returns: An System.Object that represents a service provided by the System.ComponentModel.Component,or
null if the System.ComponentModel.Component does not provide the specified service.
"""
pass
def MemberwiseClone(self, *args):
"""
MemberwiseClone(self: MarshalByRefObject,cloneIdentity: bool) -> MarshalByRefObject
Creates a shallow copy of the current System.MarshalByRefObject object.
cloneIdentity: false to delete the current System.MarshalByRefObject object's identity,which will cause the
object to be assigned a new identity when it is marshaled across a remoting boundary. A value of
false is usually appropriate. true to copy the current System.MarshalByRefObject object's
identity to its clone,which will cause remoting client calls to be routed to the remote server
object.
Returns: A shallow copy of the current System.MarshalByRefObject object.
MemberwiseClone(self: object) -> object
Creates a shallow copy of the current System.Object.
Returns: A shallow copy of the current System.Object.
"""
pass
def ShowBalloonTip(self, timeout, tipTitle=None, tipText=None, tipIcon=None):
"""
ShowBalloonTip(self: NotifyIcon,timeout: int,tipTitle: str,tipText: str,tipIcon: ToolTipIcon)
Displays a balloon tip with the specified title,text,and icon in the taskbar for the specified
time period.
timeout: The time period,in milliseconds,the balloon tip should display.
tipTitle: The title to display on the balloon tip.
tipText: The text to display on the balloon tip.
tipIcon: One of the System.Windows.Forms.ToolTipIcon values.
ShowBalloonTip(self: NotifyIcon,timeout: int)
Displays a balloon tip in the taskbar for the specified time period.
timeout: The time period,in milliseconds,the balloon tip should display.
"""
pass
def __enter__(self, *args):
"""
__enter__(self: IDisposable) -> object
Provides the implementation of __enter__ for objects which implement IDisposable.
"""
pass
def __exit__(self, *args):
"""
__exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object)
Provides the implementation of __exit__ for objects which implement IDisposable.
"""
pass
def __init__(self, *args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self, container=None):
"""
__new__(cls: type)
__new__(cls: type,container: IContainer)
"""
pass
BalloonTipIcon = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets or sets the icon to display on the balloon tip associated with the System.Windows.Forms.NotifyIcon.
Get: BalloonTipIcon(self: NotifyIcon) -> ToolTipIcon
Set: BalloonTipIcon(self: NotifyIcon)=value
"""
BalloonTipText = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets or sets the text to display on the balloon tip associated with the System.Windows.Forms.NotifyIcon.
Get: BalloonTipText(self: NotifyIcon) -> str
Set: BalloonTipText(self: NotifyIcon)=value
"""
BalloonTipTitle = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets or sets the title of the balloon tip displayed on the System.Windows.Forms.NotifyIcon.
Get: BalloonTipTitle(self: NotifyIcon) -> str
Set: BalloonTipTitle(self: NotifyIcon)=value
"""
CanRaiseEvents = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets a value indicating whether the component can raise an event.
"""
ContextMenu = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets or sets the shortcut menu for the icon.
Get: ContextMenu(self: NotifyIcon) -> ContextMenu
Set: ContextMenu(self: NotifyIcon)=value
"""
ContextMenuStrip = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets or sets the shortcut menu associated with the System.Windows.Forms.NotifyIcon.
Get: ContextMenuStrip(self: NotifyIcon) -> ContextMenuStrip
Set: ContextMenuStrip(self: NotifyIcon)=value
"""
DesignMode = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Gets a value that indicates whether the System.ComponentModel.Component is currently in design mode.
"""
Events = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Gets the list of event handlers that are attached to this System.ComponentModel.Component.
"""
Icon = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Gets or sets the current icon.
Get: Icon(self: NotifyIcon) -> Icon
Set: Icon(self: NotifyIcon)=value
"""
Tag = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Gets or sets an object that contains data about the System.Windows.Forms.NotifyIcon.
Get: Tag(self: NotifyIcon) -> object
Set: Tag(self: NotifyIcon)=value
"""
Text = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Gets or sets the ToolTip text displayed when the mouse pointer rests on a notification area icon.
Get: Text(self: NotifyIcon) -> str
Set: Text(self: NotifyIcon)=value
"""
Visible = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Gets or sets a value indicating whether the icon is visible in the notification area of the taskbar.
Get: Visible(self: NotifyIcon) -> bool
Set: Visible(self: NotifyIcon)=value
"""
BalloonTipClicked = None
BalloonTipClosed = None
BalloonTipShown = None
Click = None
DoubleClick = None
MouseClick = None
MouseDoubleClick = None
MouseDown = None
MouseMove = None
MouseUp = None
|
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] | 2.750582 | 2,578 |
import os
import pandas as pd
import rampwf as rw
from sklearn.model_selection import ShuffleSplit
import numpy as np
problem_title = 'Salary prediction'
_target_column_name = 'SalaryUSD'
# A value which will be used to create wrapper objects for y_pred
Predictions = rw.prediction_types.make_regression()
# An object implementing the workflow
workflow = rw.workflows.Estimator()
score_types = [
rw.score_types.RMSE(name='rmse', precision=3),
]
# READ DATA
|
[
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62,
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796,
685,
201,
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220,
220,
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374,
86,
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62,
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26224,
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28,
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201,
198,
60,
201,
198,
201,
198,
201,
198,
2,
20832,
42865,
201,
198,
201,
198
] | 2.729282 | 181 |
"""
IRC message logger.
Enables logging of messages to flat files.
"""
import threading
from datetime import datetime
from kochira import config
from kochira.service import Service, Config
from pathlib import Path
service = Service(__name__, __doc__)
@service.config
@service.setup
@service.shutdown
@service.hook("sighup")
@service.hook("own_message", priority=10000)
@service.hook("own_notice", priority=10000)
@service.hook("invite", priority=10000)
@service.hook("join", priority=10000)
@service.hook("kill", priority=10000)
@service.hook("kick", priority=10000)
@service.hook("mode_change", priority=10000)
@service.hook("channel_message", priority=10000)
@service.hook("private_message", priority=10000)
@service.hook("nick_change", priority=10000)
@service.hook("channel_notice", priority=10000)
@service.hook("private_notice", priority=10000)
@service.hook("part", priority=10000)
@service.hook("topic_change", priority=10000)
@service.hook("quit", priority=10000)
@service.hook("ctcp_action", priority=10000)
|
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31,
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28,
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8,
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28,
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8,
628,
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31,
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13,
25480,
7203,
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62,
3803,
1600,
8475,
28,
49388,
8,
628,
198,
31,
15271,
13,
25480,
7203,
47391,
1600,
8475,
28,
49388,
8,
628,
198,
31,
15271,
13,
25480,
7203,
310,
13155,
62,
2673,
1600,
8475,
28,
49388,
8,
198
] | 3.191045 | 335 |
import json
from unittest import main
from unittest.mock import patch
from common import ClassifierTestCaseWithMockClassifiers
from classifier import __VERSION__
from classifier.ml import Classifier
if __name__ == "__main__":
main()
|
[
11748,
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198,
6738,
555,
715,
395,
1330,
1388,
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198,
198,
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361,
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6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
1388,
3419,
198
] | 3.43662 | 71 |
# third party
import argparse
import csv
import random
import re
import subprocess
from dataclasses import fields, is_dataclass
from functools import reduce
from io import StringIO
from typing import List, Optional
import numpy as np
import torch
import torch.jit
import torch.nn as nn
from gym import spaces
import gym
# Necessary for my KFAC implementation.
# https://github.com/openai/baselines/blob/master/baselines/common/tf_util.py#L87
@torch.jit.script
RESET = "\033[0m"
def hierarchical_parse_args(parser: argparse.ArgumentParser, include_positional=False):
"""
:return:
{
group1: {**kwargs}
group2: {**kwargs}
...
**kwargs
}
"""
args = parser.parse_args()
positional = list(get_positionals(parser._action_groups))
nonpositional = dict(get_nonpositionals(parser._action_groups))
optional = nonpositional.pop("optional arguments")
nonpositional = {**nonpositional, **optional}
if include_positional:
return positional, nonpositional
return nonpositional
|
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220,
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220,
220,
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1859,
198,
220,
220,
220,
1441,
1729,
1930,
1859,
628,
628,
628,
198
] | 2.81039 | 385 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-License-Identifier: GPL-3.0
#
# GNU Radio Python Flow Graph
# Title: Flatsat RX Test
# Author: dev
# GNU Radio version: 3.9.3.0
from distutils.version import StrictVersion
if __name__ == '__main__':
import ctypes
import sys
if sys.platform.startswith('linux'):
try:
x11 = ctypes.cdll.LoadLibrary('libX11.so')
x11.XInitThreads()
except:
print("Warning: failed to XInitThreads()")
import os
import sys
sys.path.append(os.environ.get('GRC_HIER_PATH', os.path.expanduser('~/.grc_gnuradio')))
from PyQt5 import Qt
from gnuradio import eng_notation
from gnuradio import qtgui
from gnuradio.filter import firdes
import sip
from flatsat_rx import flatsat_rx # grc-generated hier_block
from gnuradio import analog
from gnuradio import blocks
import pmt
from gnuradio import digital
from gnuradio import filter
from gnuradio import gr
from gnuradio.fft import window
import signal
from argparse import ArgumentParser
from gnuradio.eng_arg import eng_float, intx
from gnuradio import uhd
import time
from gnuradio.filter import pfb
from gnuradio.qtgui import Range, RangeWidget
from PyQt5 import QtCore
from usersegment_tx import usersegment_tx # grc-generated hier_block
import satellites.hier
import test_flatsat_rx_epy_block_0_0_0_0_0_0 as epy_block_0_0_0_0_0_0 # embedded python block
from gnuradio import qtgui
if __name__ == '__main__':
main()
|
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198,
198,
6738,
19967,
333,
324,
952,
1330,
10662,
83,
48317,
628,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 2.585664 | 572 |
from random import randint
import os
from PIL import Image
path='final'
classnames=os.listdir(path)
images=[]
f1=open('input_index.txt','w')
for temp in classnames:
images.append(Image.open('final/'+temp))
f1.write(temp+"\n")
f1.close()
k=len(images)
im2=[]
for i in range(k):
img=images[i]
im2.append(img)
h=0
for i in range(k):
h=h+40*im2[i].size[1]/im2[i].size[0]+5
result = Image.new('L', (40,h),'white')
lp=0
for i in range(k):
img=im2[i]
img=img.convert('L')
print 'before ',
print img.size
h=40*img.size[1]/img.size[0]
if h<1:
h=1
img=img.resize((40,h),Image.ANTIALIAS)
print 'after ',
print img.size
result.paste(img, box=(0, lp))
lp=lp+5+img.size[1]
result.save('res.png')
|
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411,
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198
] | 2.072464 | 345 |
#!/usr/bin/python
# (c) 2018, NetApp, Inc
# GNU General Public License v3.0+ (see COPYING or
# https://www.gnu.org/licenses/gpl-3.0.txt)
'''
Element Software Node Network Interfaces - Bond 1G and 10G configuration
'''
from __future__ import absolute_import, division, print_function
__metaclass__ = type
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'certified'}
DOCUMENTATION = '''
module: na_elementsw_network_interfaces
short_description: NetApp Element Software Configure Node Network Interfaces
extends_documentation_fragment:
- netapp.solidfire
version_added: '2.7'
author: NetApp Ansible Team (@carchi8py) <[email protected]>
description:
- Configure Element SW Node Network Interfaces for Bond 1G and 10G IP address.
options:
method:
description:
- Type of Method used to configure the interface.
- method depends on other settings such as the use of a static IP address, which will change the method to static.
- loopback - Used to define the IPv4 loopback interface.
- manual - Used to define interfaces for which no configuration is done by default.
- dhcp - May be used to obtain an IP address via DHCP.
- static - Used to define Ethernet interfaces with statically allocated IPv4 addresses.
choices: ['loopback', 'manual', 'dhcp', 'static']
required: true
ip_address_1g:
description:
- IP address for the 1G network.
required: true
ip_address_10g:
description:
- IP address for the 10G network.
required: true
subnet_1g:
description:
- 1GbE Subnet Mask.
required: true
subnet_10g:
description:
- 10GbE Subnet Mask.
required: true
gateway_address_1g:
description:
- Router network address to send packets out of the local network.
required: true
gateway_address_10g:
description:
- Router network address to send packets out of the local network.
required: true
mtu_1g:
description:
- Maximum Transmission Unit for 1GbE, Largest packet size that a network protocol can transmit.
- Must be greater than or equal to 1500 bytes.
default: '1500'
mtu_10g:
description:
- Maximum Transmission Unit for 10GbE, Largest packet size that a network protocol can transmit.
- Must be greater than or equal to 1500 bytes.
default: '1500'
dns_nameservers:
description:
- List of addresses for domain name servers.
dns_search_domains:
description:
- List of DNS search domains.
bond_mode_1g:
description:
- Bond mode for 1GbE configuration.
choices: ['ActivePassive', 'ALB', 'LACP']
default: 'ActivePassive'
bond_mode_10g:
description:
- Bond mode for 10GbE configuration.
choices: ['ActivePassive', 'ALB', 'LACP']
default: 'ActivePassive'
lacp_1g:
description:
- Link Aggregation Control Protocol useful only if LACP is selected as the Bond Mode.
- Slow - Packets are transmitted at 30 second intervals.
- Fast - Packets are transmitted in 1 second intervals.
choices: ['Fast', 'Slow']
default: 'Slow'
lacp_10g:
description:
- Link Aggregation Control Protocol useful only if LACP is selected as the Bond Mode.
- Slow - Packets are transmitted at 30 second intervals.
- Fast - Packets are transmitted in 1 second intervals.
choices: ['Fast', 'Slow']
default: 'Slow'
virtual_network_tag:
description:
- This is the primary network tag. All nodes in a cluster have the same VLAN tag.
'''
EXAMPLES = """
- name: Set Node network interfaces configuration for Bond 1G and 10G properties
tags:
- elementsw_network_interfaces
na_elementsw_network_interfaces:
hostname: "{{ elementsw_hostname }}"
username: "{{ elementsw_username }}"
password: "{{ elementsw_password }}"
method: static
ip_address_1g: 10.226.109.68
ip_address_10g: 10.226.201.72
subnet_1g: 255.255.255.0
subnet_10g: 255.255.255.0
gateway_address_1g: 10.193.139.1
gateway_address_10g: 10.193.140.1
mtu_1g: 1500
mtu_10g: 9000
bond_mode_1g: ActivePassive
bond_mode_10g: LACP
lacp_10g: Fast
"""
RETURN = """
msg:
description: Success message
returned: success
type: str
"""
import traceback
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils._text import to_native
import ansible.module_utils.netapp as netapp_utils
HAS_SF_SDK = netapp_utils.has_sf_sdk()
try:
from solidfire.models import Network, NetworkConfig
HAS_SF_SDK = True
except Exception:
HAS_SF_SDK = False
class ElementSWNetworkInterfaces(object):
"""
Element Software Network Interfaces - Bond 1G and 10G Network configuration
"""
def set_network_config(self):
"""
set network configuration
"""
try:
self.sfe.set_network_config(network=self.network_object)
except Exception as exception_object:
self.module.fail_json(msg='Error network setting for node %s' % (to_native(exception_object)),
exception=traceback.format_exc())
def get_network_params_object(self):
"""
Get Element SW Network object
:description: get Network object
:return: NetworkConfig object
:rtype: object(NetworkConfig object)
"""
try:
bond_1g_network = NetworkConfig(method=self.method,
address=self.ip_address_1g,
netmask=self.subnet_1g,
gateway=self.gateway_address_1g,
mtu=self.mtu_1g,
dns_nameservers=self.dns_nameservers,
dns_search=self.dns_search_domains,
bond_mode=self.bond_mode_1g,
bond_lacp_rate=self.lacp_1g,
virtual_network_tag=self.virtual_network_tag)
bond_10g_network = NetworkConfig(method=self.method,
address=self.ip_address_10g,
netmask=self.subnet_10g,
gateway=self.gateway_address_10g,
mtu=self.mtu_10g,
dns_nameservers=self.dns_nameservers,
dns_search=self.dns_search_domains,
bond_mode=self.bond_mode_10g,
bond_lacp_rate=self.lacp_10g,
virtual_network_tag=self.virtual_network_tag)
network_object = Network(bond1_g=bond_1g_network,
bond10_g=bond_10g_network)
return network_object
except Exception as e:
self.module.fail_json(msg='Error with setting up network object for node 1G and 10G configuration : %s' % to_native(e),
exception=to_native(e))
def apply(self):
"""
Check connection and initialize node with cluster ownership
"""
changed = False
result_message = None
self.network_object = self.get_network_params_object()
if self.network_object is not None:
self.set_network_config()
changed = True
else:
result_message = "Skipping changes, No change requested"
self.module.exit_json(changed=changed, msg=result_message)
def main():
"""
Main function
"""
elementsw_network_interfaces = ElementSWNetworkInterfaces()
elementsw_network_interfaces.apply()
if __name__ == '__main__':
main()
|
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16,
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796,
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11,
198,
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2209,
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70,
11,
198,
220,
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2010,
27932,
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13,
7266,
3262,
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11,
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24308,
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10494,
1014,
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62,
16,
70,
11,
198,
220,
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84,
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198,
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288,
5907,
62,
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263,
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14933,
263,
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11,
198,
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] | 2.166231 | 3,826 |
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 28 10:14:42 2020
@author: Thomas
"""
#!/usr/bin/env python
#Lora Base Server
#Reads Data from the ESP32 Lora Receiver via serial Port and generates a CSV file for each LoRa sensor client
import time
import serial
import re
import datetime
import os.path
myDataFileName="/home/pi/BienenWaageMessdaten"
ser = serial.Serial(
port='/dev/ttyUSB0',
#port='COM15',
baudrate = 115200,
parity=serial.PARITY_NONE,
stopbits=serial.STOPBITS_ONE,
bytesize=serial.EIGHTBITS,
timeout=1
)
measurements=[]
currentSensorData=sensorData(sensorID=[-1])
datasetReady=False
while 1:
x=ser.readline()
#print(x)
parsedInput=str(x).split('\\t',)
SensorIDVal=parseSerialInput("Sensor ID",parsedInput[0])
if SensorIDVal is not None:
currentSensorData=sensorData(sensorID=SensorIDVal)
if "Sensor ID" in parsedInput[0]:
d = datetime.datetime.now()
timeNow=time.mktime(d.timetuple()) #get posix time
currentSensorData.receiveTime=convertDateTime(d)
currentSensorData.receiveTimePosix=timeNow
for paramString in parsedInput:
SensorIDVal=parseSerialInput("Sensor ID",paramString)
if SensorIDVal is not None:
currentSensorData.sensorID=SensorIDVal
weightVal=parseSerialInput("Weight",paramString)
if weightVal is not None:
currentSensorData.weight=weightVal
voltageVal=parseSerialInput("Voltage",paramString)
if voltageVal is not None:
currentSensorData.voltage=voltageVal
rssidVal=parseSerialInput("RSSID",paramString)
if rssidVal is not None:
currentSensorData.RSSID=rssidVal
swarmAlarmVal=parseSerialInput("Swarm Alarm",paramString)
if swarmAlarmVal is not None:
currentSensorData.swarmAlarm=swarmAlarmVal
else:
continue
outputDataLine=getOutputDataLine(currentSensorData)
print(outputDataLine)
appendLineToFile(myDataFileName+'Sensor'+str(int(currentSensorData.sensorID[0]))+'.txt',outputDataLine)
# =============================================================================
# SensorIDVal=parseSerialInput("Sensor ID",str(x))
#
# if SensorIDVal is not None:
# datasetReady=True
# #timeNow=str(datetime.datetime.now())
#
# d = datetime.datetime.now()
#
# timeNow=time.mktime(d.timetuple())
# #timeNow=convertDateTime(datetime.datetime.now())
# print("Create new SensorDataSet with sensorID: ",SensorIDVal)
# newSensorData=sensorData(sensorID=SensorIDVal,receiveTime=timeNow)
# print("Created new SensorDataSet with sensorID: ",SensorIDVal)
# #append currentSensorData after the first Dataset has been read completely
# #Thats when SensorIDVal is call for the second time
# print ("CurrentSensorData: ",currentSensorData.sensorID)
# if currentSensorData.sensorID[0]>-1: # if the currentSensorData is not completely new...
# measurements.append(currentSensorData)
# outputDataLine=getOutputDataLine(currentSensorData)
# csd=currentSensorData.sensorID
# print ("Output: ",outputDataLine)
# appendLineToFile(myDataFileName+'Sensor'+str(int(SensorIDVal[0]))+'.txt',outputDataLine)
#
#
#
# currentSensorData=newSensorData
#
# if datasetReady:
# weightVal=parseSerialInput("Weight",str(x))
# if weightVal is not None:
# currentSensorData.weight=weightVal
#
# voltageVal=parseSerialInput("Voltage",str(x))
# if voltageVal is not None:
# currentSensorData.voltage=voltageVal
#
# rssidVal=parseSerialInput("RSSID",str(x))
# if rssidVal is not None:
# currentSensorData.RSSID=rssidVal
#
# swarmAlarmVal=parseSerialInput("Swarm Alarm",str(x))
# if swarmAlarmVal is not None:
# currentSensorData.swarmAlarm=swarmAlarmVal
#
# =============================================================================
|
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] | 2.022477 | 2,358 |
from copy import copy
|
[
6738,
4866,
1330,
4866,
628,
628
] | 4.166667 | 6 |
# -*- coding: utf-8 -*-
"""
Downloader for ogs5.
.. currentmodule:: ogs5py.tools.download
Downloader
^^^^^^^^^^
A downloading routine to get the OSG5 executable.
.. autosummary::
download_ogs
add_exe
reset_download
OGS5PY_CONFIG
----
"""
import os
import shutil
import tarfile
import zipfile
from urllib.request import urlretrieve, urlopen
import tempfile
import platform
import lxml.html
# TemporaryDirectory not avialable in python2
# from: https://gist.github.com/cpelley/10e2eeaf60dacc7956bb
TemporaryDirectory = getattr(
tempfile, "TemporaryDirectory", _TemporaryDirectory
)
# https://stackoverflow.com/a/34615446/6696397
def get_links(url, ext, build=None):
"""Get links from url ending with ext and containing build."""
sublinks = []
connection = urlopen(url)
dom = lxml.html.fromstring(connection.read())
for link in dom.xpath("//a/@href"):
if not link or not link.endswith(ext):
continue # skip unwanted
if build is None or "build_" + build + "/" in link:
sublinks.append(
url + link if not link.startswith("http") else link
)
return sublinks
RELEASE = "https://ogsstorage.blob.core.windows.net/binaries/ogs5/"
BUILD = "https://jenkins.opengeosys.org/job/ufz/job/ogs5/job/master/"
STABLE = BUILD + "lastStableBuild/"
SUCCESS = BUILD + "lastSuccessfulBuild/"
# https://stackoverflow.com/a/53222876/6696397
OGS5PY_CONFIG = os.path.join(
os.environ.get("APPDATA")
or os.environ.get("XDG_CONFIG_HOME")
or os.path.join(os.environ["HOME"], ".config"),
"ogs5py",
)
"""str: Standard config path for ogs5py."""
URLS = {
"5.7": {
"Linux": (
RELEASE + "ogs-5.7.0-Linux-2.6.32-573.8.1.el6.x86_64-x64.tar.gz"
),
"Windows": RELEASE + "ogs-5.7.0-Windows-6.1.7601-x64.zip",
"Darwin": RELEASE + "ogs-5.7.0-Darwin-15.2.0-x64.tar.gz",
},
"5.7.1": {
"Windows": (
"https://github.com/ufz/ogs5/releases/download/"
+ "5.7.1/ogs-5.7.1-Windows-x64.zip"
)
},
"5.8": {
"Linux": (
RELEASE + "ogs-5.8-Linux-2.6.32-754.3.5.el6.x86_64-x64.tar.gz"
),
"Windows": RELEASE + "ogs-5.8-Windows-x64.zip",
},
}
def download_ogs(
version="5.7", system=None, path=OGS5PY_CONFIG, name=None, build=None
):
"""
Download the OGS5 executable.
Parameters
----------
version : :class:`str`, optional
Version to download ("5.7", "5.8", "latest" or "stable").
Default: "5.7"
system : :class:`str`, optional
Target system (Linux, Windows, Darwin). Default: platform.system()
path : :class:`str`, optional
Destination path. Default: :any:`OGS5PY_CONFIG`
name : :class:`str`, optional
Destination file name. Default "ogs[.exe]"
build : :class:`str`, optional
If system is "Linux" and version is "latest" or "stable",
you can select a certain build from the ogs 5 builds:
* "BRNS": Biogeochemical Reaction Network Simulator
* "FEM": Finite Element Method
* "GEMS": Gibbs Energy Minimization Solver
* "IPQC": IPhreeqc
* "LIS": Library of Iterative Solvers
* "MKL": Intel Math Kernel Library
* "MPI": Message Passing Interface
* "PETSC": Portable, Extensible Toolkit for Scientific Computation
* "PETSC_GEMS": PETSC and GEMS
* "PQC": PHREEQC
* "SP": Sparse solver
Returns
-------
dest : :class:`str`
If an OGS5 executable was successfully downloaded, the file-path
is returned.
Notes
-----
There is only an executable on "Darwin" for version "5.7".
Taken from:
* https://www.opengeosys.org/ogs-5/
* https://jenkins.opengeosys.org/job/ufz/job/ogs5/job/master/
"""
URLS["latest"] = {
"Linux": get_links(SUCCESS, "tar.gz", build="FEM")[0],
"Windows": get_links(SUCCESS, "zip", build=None)[0],
}
URLS["stable"] = {
"Linux": get_links(STABLE, "tar.gz", build="FEM")[0],
"Windows": get_links(STABLE, "zip", build=None)[0],
}
system = platform.system() if system is None else system
path = os.path.abspath(path)
if not os.path.exists(path):
os.makedirs(path)
if version not in URLS:
raise ValueError(
"'{}': unknown version. Use: {}".format(version, list(URLS))
)
urls_version = URLS[version]
if system not in urls_version:
raise ValueError(
"'{}': unsupported system for version '{}'. Use: {}".format(
system, version, list(urls_version)
)
)
if system == "Linux" and build is not None:
if version not in ["stable", "latest"]:
raise ValueError(
"Use version 'stable' or 'latest' for specific build."
)
base_url = STABLE if version == "stable" else SUCCESS
links = get_links(base_url, ".tar.gz", build)
if len(links) != 1:
raise ValueError(
"Can't find unique version for build '{}'. Found: {}".format(
build, links
)
)
ogs_url = links[0]
elif build is None or build == "FEM":
ogs_url = urls_version[system]
else:
raise ValueError(
"system='{}', build='{}': Could not find matching exe.".format(
system, build
)
)
print("Downloading: ", ogs_url)
ext = ".tar.gz" if ogs_url.endswith(".tar.gz") else ".zip"
if name is None:
name = "ogs.exe" if system == "Windows" else "ogs"
dest = os.path.join(path, name)
with TemporaryDirectory() as tmpdirname:
data_filename = os.path.join(tmpdirname, "data" + ext)
urlretrieve(ogs_url, data_filename)
# extract the data
if ext == ".tar.gz":
z_file = tarfile.open(data_filename, "r:gz")
names = z_file.getnames()
else:
z_file = zipfile.ZipFile(data_filename)
names = z_file.namelist()
found = ""
for file in names:
if os.path.basename(file).startswith("ogs"):
found = file
break
if found:
z_file.extract(member=found, path=tmpdirname)
shutil.copy(os.path.join(tmpdirname, found), dest)
z_file.close()
return dest if found else None
def add_exe(ogs_exe, dest_name=None):
"""
Add an OGS5 exe to :any:`OGS5PY_CONFIG`.
Parameters
----------
ogs_exe : :class:`str`
Path to the ogs executable to be copied.
dest_name : :class:`str`, optional
Destination file name. Default: basename of ogs_exe
Returns
-------
dest : :class:`str`
If an OGS5 executable was successfully copied, the file-path
is returned.
"""
if platform.system() == "Windows" and ogs_exe[-4:] == ".lnk":
print("Don't use file links under windows...")
return None
if os.path.islink(ogs_exe):
ogs_exe = os.path.realpath(ogs_exe)
if os.path.exists(ogs_exe) and os.path.isfile(ogs_exe):
dest_name = (
os.path.basename(ogs_exe) if dest_name is None else dest_name
)
dest = os.path.join(OGS5PY_CONFIG, dest_name)
shutil.copy(ogs_exe, dest)
return dest
print("The given ogs_exe does not exist...")
return None
def reset_download():
"""Reset all downloads in :any:`OGS5PY_CONFIG`."""
shutil.rmtree(OGS5PY_CONFIG, ignore_errors=True)
|
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13,
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13,
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13,
397,
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776,
7,
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8,
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13,
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13,
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287,
37902,
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25,
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220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
24018,
90,
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10354,
6439,
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13,
5765,
25,
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1911,
18982,
7,
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11,
1351,
7,
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1267,
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5298,
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220,
220,
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220,
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220,
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220,
220,
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24018,
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25,
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25,
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5298,
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7,
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1267,
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267,
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62,
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58,
15,
60,
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220,
220,
1288,
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318,
6045,
393,
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6624,
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37,
3620,
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220,
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220,
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267,
14542,
62,
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2956,
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62,
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58,
10057,
60,
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220,
220,
2073,
25,
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220,
220,
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5298,
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12331,
7,
198,
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220,
220,
220,
220,
220,
220,
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220,
366,
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3256,
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11639,
90,
92,
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407,
1064,
12336,
409,
68,
526,
13,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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1080,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
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1267,
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3601,
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62,
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13,
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1,
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62,
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13,
437,
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13,
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13344,
1,
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220,
220,
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318,
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25,
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220,
220,
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1438,
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13,
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1,
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6624,
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1,
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1,
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2244,
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13,
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13,
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7,
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11,
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220,
351,
46042,
43055,
3419,
355,
45218,
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3672,
25,
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220,
220,
220,
220,
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1366,
62,
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13,
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13,
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3672,
11,
366,
7890,
1,
1343,
1070,
8,
198,
220,
220,
220,
220,
220,
220,
220,
19016,
1186,
30227,
7,
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62,
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11,
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62,
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8,
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220,
220,
220,
220,
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1303,
7925,
262,
1366,
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6624,
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13,
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1298,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
62,
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796,
13422,
7753,
13,
9654,
7,
7890,
62,
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11,
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81,
25,
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220,
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220,
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3891,
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220,
2073,
25,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
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19974,
7753,
13,
41729,
8979,
7,
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62,
34345,
8,
198,
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220,
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220,
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3891,
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1976,
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13,
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46331,
3419,
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1043,
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13538,
198,
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220,
220,
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220,
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329,
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287,
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25,
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13,
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13,
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7,
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737,
9688,
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1,
2599,
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220,
220,
220,
220,
220,
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2270,
198,
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220,
220,
220,
220,
220,
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611,
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25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1976,
62,
7753,
13,
2302,
974,
7,
19522,
28,
9275,
11,
3108,
28,
22065,
15908,
3672,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4423,
346,
13,
30073,
7,
418,
13,
6978,
13,
22179,
7,
22065,
15908,
3672,
11,
1043,
828,
2244,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1976,
62,
7753,
13,
19836,
3419,
198,
220,
220,
220,
1441,
2244,
611,
1043,
2073,
6045,
628,
198,
4299,
751,
62,
13499,
7,
18463,
62,
13499,
11,
2244,
62,
3672,
28,
14202,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
3060,
281,
440,
14313,
20,
409,
68,
284,
1058,
1092,
25,
63,
7730,
50,
20,
47,
56,
62,
10943,
16254,
44646,
628,
220,
220,
220,
40117,
198,
220,
220,
220,
24200,
438,
198,
220,
220,
220,
267,
14542,
62,
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1058,
1058,
4871,
25,
63,
2536,
63,
198,
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220,
220,
220,
220,
220,
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10644,
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284,
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18984,
13,
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2244,
62,
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25,
63,
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47671,
11902,
198,
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220,
220,
220,
220,
220,
45657,
2393,
1438,
13,
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25,
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286,
267,
14542,
62,
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16409,
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35656,
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2244,
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220,
220,
220,
1002,
281,
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14313,
20,
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373,
7675,
18984,
11,
262,
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12,
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198,
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220,
220,
220,
220,
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318,
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13,
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3419,
6624,
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1,
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58,
12,
19,
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74,
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220,
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3601,
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3987,
470,
779,
2393,
6117,
739,
9168,
9313,
8,
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1441,
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7,
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2244,
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1267,
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220,
220,
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2244,
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13,
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13,
22179,
7,
7730,
50,
20,
47,
56,
62,
10943,
16254,
11,
2244,
62,
3672,
8,
198,
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220,
220,
220,
220,
220,
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4423,
346,
13,
30073,
7,
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62,
13499,
11,
2244,
8,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2244,
198,
220,
220,
220,
3601,
7203,
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class ViewCropRegionShapeManager(object, IDisposable):
""" A class that provides access to settings related to the crop assigned to a view or a reference callout. """
def Dispose(self):
""" Dispose(self: ViewCropRegionShapeManager) """
pass
def GetAnnotationCropShape(self):
"""
GetAnnotationCropShape(self: ViewCropRegionShapeManager) -> CurveLoop
Gets the annotation crop box assigned to the view.
Returns: The annotation crop boundary.
"""
pass
def GetCropShape(self):
"""
GetCropShape(self: ViewCropRegionShapeManager) -> IList[CurveLoop]
Gets the crop boundaries that are curently active.
Returns: The crop boundaries.
"""
pass
def GetSplitRegionMaximum(self, regionIndex):
"""
GetSplitRegionMaximum(self: ViewCropRegionShapeManager,regionIndex: int) -> float
Returns the proportional location of the maximum boundary of the specified
split crop region.
regionIndex: Index of region to be split horizontally (numbering starts with 0).
Returns: A value from 0 to 1 representing the maximum location for the regions split
boundary.
This number represents the location as a ratio along the
non-split rectangular crop.
"""
pass
def GetSplitRegionMinimum(self, regionIndex):
"""
GetSplitRegionMinimum(self: ViewCropRegionShapeManager,regionIndex: int) -> float
Returns the proportional location of the minimum boundary of the specified
split crop region.
regionIndex: Index of region to be split horizontally (numbering starts with 0).
Returns: A value from 0 to 1 representing the minimum location for the regions split
boundary.
This number represents the location as a ratio along the
non-split rectangular crop.
"""
pass
def IsCropRegionShapeValid(self, boundary):
"""
IsCropRegionShapeValid(self: ViewCropRegionShapeManager,boundary: CurveLoop) -> bool
Verifies that boundary represents one closed curve loop without
self-intersections,
consisting of non-zero length straight lines in a plane
parallel to the view plane.
boundary: The crop boundary.
Returns: True if the passed crop boundary represents one closed curve loop without
self-intersections,
consisting of non-zero length straight lines in a plane
parallel to the view plane.
"""
pass
def ReleaseUnmanagedResources(self, *args):
""" ReleaseUnmanagedResources(self: ViewCropRegionShapeManager,disposing: bool) """
pass
def RemoveCropRegionShape(self):
"""
RemoveCropRegionShape(self: ViewCropRegionShapeManager)
Removes any non-rectangular boundary of the view's crop.
"""
pass
def RemoveSplit(self):
"""
RemoveSplit(self: ViewCropRegionShapeManager)
Removes any split applied to the view's crop.
"""
pass
def RemoveSplitRegion(self, regionIndex):
"""
RemoveSplitRegion(self: ViewCropRegionShapeManager,regionIndex: int)
Removes one region in split crop.
regionIndex: Index of region to be deleted (numbering starts with 0).
"""
pass
def SetCropShape(self, boundary):
"""
SetCropShape(self: ViewCropRegionShapeManager,boundary: CurveLoop)
Sets the boundary of the view's crop to the specified shape.
boundary: The crop boundary.
"""
pass
def SplitRegionHorizontally(self, regionIndex, leftPart, rightPart):
"""
SplitRegionHorizontally(self: ViewCropRegionShapeManager,regionIndex: int,leftPart: float,rightPart: float)
Splits horizontally one region in split crop.
regionIndex: Index of region to be split horizontally (numbering starts with 0).
leftPart: Relative portion of the original region to become the new left region (0 to 1).
rightPart: Relative portion of the original region to become the new right region (0 to 1).
"""
pass
def SplitRegionVertically(self, regionIndex, topPart, bottomPart):
"""
SplitRegionVertically(self: ViewCropRegionShapeManager,regionIndex: int,topPart: float,bottomPart: float)
Splits vertically one region in split crop.
regionIndex: Index of region to be split vertically (numbering starts with 0).
topPart: Relative portion of the original region to become the new top region (0 to 1).
bottomPart: Relative portion of the original region to become the new bottom region (0 to
1).
"""
pass
def __enter__(self, *args):
""" __enter__(self: IDisposable) -> object """
pass
def __exit__(self, *args):
""" __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """
pass
def __init__(self, *args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
def __repr__(self, *args):
""" __repr__(self: object) -> str """
pass
BottomAnnotationCropOffset = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""The offset from the bottom of the view crop that determines the location of the annotation crop bottom boundary.
Get: BottomAnnotationCropOffset(self: ViewCropRegionShapeManager) -> float
Set: BottomAnnotationCropOffset(self: ViewCropRegionShapeManager)=value
"""
CanBeSplit = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Verifies that the crop of the associated view is permitted to have multiple regions.
Get: CanBeSplit(self: ViewCropRegionShapeManager) -> bool
"""
CanHaveAnnotationCrop = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Verifies that the view is allowed to have an annotation crop.
Get: CanHaveAnnotationCrop(self: ViewCropRegionShapeManager) -> bool
"""
CanHaveShape = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Verifies that the crop of the associated view is permitted to have a non-rectangular shape.
Get: CanHaveShape(self: ViewCropRegionShapeManager) -> bool
"""
IsSplitHorizontally = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Whether or not the view's crop is split (and the split is horizontal).
Get: IsSplitHorizontally(self: ViewCropRegionShapeManager) -> bool
"""
IsSplitVertically = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Whether or not the view's crop is split (and the split is vertical).
Get: IsSplitVertically(self: ViewCropRegionShapeManager) -> bool
"""
IsValidObject = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""Specifies whether the .NET object represents a valid Revit entity.
Get: IsValidObject(self: ViewCropRegionShapeManager) -> bool
"""
LeftAnnotationCropOffset = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""The offset from the left of the view crop that determines the location of the annotation crop left boundary.
Get: LeftAnnotationCropOffset(self: ViewCropRegionShapeManager) -> float
Set: LeftAnnotationCropOffset(self: ViewCropRegionShapeManager)=value
"""
NumberOfSplitRegions = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""The number of split crop regions (1 if the crop is not currently split).
Get: NumberOfSplitRegions(self: ViewCropRegionShapeManager) -> int
"""
RightAnnotationCropOffset = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""The offset from the right of the view crop that determines the location of the annotation crop right boundary.
Get: RightAnnotationCropOffset(self: ViewCropRegionShapeManager) -> float
Set: RightAnnotationCropOffset(self: ViewCropRegionShapeManager)=value
"""
ShapeSet = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Whether or not the view crop has a non-rectangular shape set.
Get: ShapeSet(self: ViewCropRegionShapeManager) -> bool
"""
Split = property(lambda self: object(), lambda self, v: None, lambda self: None)
"""Whether or not the view crop is split.
Get: Split(self: ViewCropRegionShapeManager) -> bool
"""
TopAnnotationCropOffset = property(
lambda self: object(), lambda self, v: None, lambda self: None
)
"""The offset from the top of the view crop that determines the location of the annotation crop top boundary.
Get: TopAnnotationCropOffset(self: ViewCropRegionShapeManager) -> float
Set: TopAnnotationCropOffset(self: ViewCropRegionShapeManager)=value
"""
|
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] | 2.790083 | 3,368 |
# Databricks notebook source
INSTGUYIKQEFVDAVPNQI
DFXKJDJFAIGTQDFPNZXIHFBFJBXNSCAQMMDSAPVIFVULKEPYGJRUNILQPXYXVGWBNVBHBWSUEGQTKHMFFROKHGJKPJ
OCRRFSYKRPOYFVBAHSCCPHGHUA
ORMCLMKXZAKDXRSGAXPHGQDBBOGQKFQYRLQQ
AKVWPNWJGXQTKSYPSLNOUXSWVYRQ
YVOFGDXZWZHFASZQCMZFKHUUBCFUILVBZPHAAMMPWQPOCWRGVAHLTM
NCUOQLVTIVWIMABZGYRFYFLMOIUDXEPZTMNSDTHDYWKAINMG
UJKXTIQSHVGBGMWYWHLVZJL
RDVCHBNRWRCSEUFZCIRJYEECZIIYXHARBS
OASOKPNORKQTXEWQTQCWFBCZJRAFHVHRFKMUSOWSDDJNLP
HQACLBDITTEMCSLKEUOLWVAFECHWDEWSMPJJLADNOORIOWFFQBXUHBP
KCOEBZYAQCFAFLRNZTJGGNXZLRUGEDYMKBMBAIDKKLFAZUCARVQCPUTQPKMKXWPVTSGRMOLJNYGNMYGTJASOUBCMX
YXOVQMGQLPZNAQSKHUIKOJHCGKJKLZJWJZKRNSNGQCRMCHEWNNHMSEWWGJZKHSWTOYXOGXSO
JSHVIDOARPSYHMPG
VDTAPXXSHWBWLVPOOLFJEQBVZRDYQWSBGPTSLSKPXVTUOZZFXXVIFEWQJJKTYLHCEPPOOEYB
YGYUMVULDSZBEWELXBTASPDVYUKZORKFQZMLRQKJCPYRRINVLAUSTTEGGPQJVBAMHAYIHFY
RXTBRRWTGLSRQPPYWZFNNXUABDGXDPYGYHEVNPLHWVOADDQJWQEWMONTUADOMV
YKOYLHAREBGQERUXDMJBSZHYPIIIRZTVMKXVWDCNOFHIAJZZSRJMMFQHCGCWYJYVBYQDBZLXLKMBOE
NDLBRNSZCHXOZCSDTBJEC
BURTEUHPAWQUUWDBQQWDIVWHGRBAKKBATTBNDLNRZTIYLCPPIPOMVGLMJVXZCNASMHYPWSHTDDOLOQLBQORYWLYZETQ
PUMXIXFBWKXVIFAB
FEWWASRUZCEZVRRPNWCJNASCAKNVHDSRAMAQGTGRHSFCJPXZIXDJWBEDXZRRKLUEECYMK
RQPBYDZGSMFQZXGVUMXLEZFHJFXAACTOQHIUQQMHLXFTZGBPPEYSAXXGDZIZOQCYBWIQYKEBTHBGMEKNWMGGR
RPOTNUMNVYNIM
ASFTCBFRGKQXMJXFHMXUHUVBIEEQURNIIPGZQBTZUCMRTF
FHFDAFRLXKVNJDUTSJKZODTSXTFENNSBEDLWCUICYSZTMQNQYAOJYRL
BRXHCYYPLPYENXXYYBQBSEGAKNAGFMIMHWOATNDTJSUWOFJEJMSBGMNGMKKHQLSJGNGKB
ZKUDOFKJSSQTWZXOOLTHLGBWWRTUWVAUZIIEGSHPFDYSORQDIXESGZLL
MDREQOCVTVBHHDOBQGIOHPWKTYYXCURTDKWANRYHZTXMWWKUEZXWNQFMXSEWWYGL
MWUOYEOJYZUBKZDSMYGCNAVFZVXCDOETRKTSMJDZMNQFQTFJZMUHVQCHDMCRZIFRKVCVC
ROQHBIPMNTEBHEBKXSFJEDNLKICRSCPULYUYEJZGDUCLDDFUXWWBAEFROFACUQKRDUJFVHRHVVMNLYVNWXVKI
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] | 1.542709 | 1,159 |
import torch
import torch.nn as nn
__all__ = [
'blocks_dict',
'InvertedResidual',
'conv_1x1_bn',
'conv_bn'
]
blocks_dict = {
'k3r3':lambda inp, oup, stride : InvertedResidual(inp, oup, 3, 1, stride, 3),
'k3r6':lambda inp, oup, stride : InvertedResidual(inp, oup, 3, 1, stride, 6),
'k5r3':lambda inp, oup, stride : InvertedResidual(inp, oup, 5, 2, stride, 3),
'k5r6':lambda inp, oup, stride : InvertedResidual(inp, oup, 5, 2, stride, 6),
'k7r3':lambda inp, oup, stride : InvertedResidual(inp, oup, 7, 3, stride, 3),
'k7r6':lambda inp, oup, stride : InvertedResidual(inp, oup, 7, 3, stride, 6),
}
|
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] | 2.094771 | 306 |
import h5py
import numpy as np
import pandas as pd
import os
from argparse import ArgumentParser
if __name__ == '__main__':
parser = ArgumentParser()
parser.add_argument('ifile_os')
parser.add_argument('ifile_pfs')
# parser.add_argument('-e', '--event_col', default='OSEvent')
# parser.add_argument('-t', '--time_col', default='TTDy')
# parser.add_argument('--txcol', type=str, default='SBRT')
# parser.add_argument('--drop', help='drop columns', nargs='+', type=str)
# parser.add_argument('--droprows', help='drop rows where [cols] have value --droprowsval', nargs='+', type=str)
# parser.add_argument(
# '--droprowsval', help='value at which to drop the rows from --droprows, default 1', type=int, default=1)
# parser.add_argument('--droprows2', help='drop rows where [cols] have value --droprowsval2', nargs='+', type=str)
# parser.add_argument(
# '--droprowsval2', help='value at which to drop the rows from --droprows2, default 0', type=int, default=0)
args = parser.parse_args()
print(args)
df = pd.read_csv(args.ifile_os)
# print(df)
drop_sbrtVS = ['Treatment', 'RFA', 'SBRT_OR_RFA']
drop_rfaVS = ['Treatment', 'SBRT', 'SBRT_OR_RFA']
drop_sbrtORrfa = ['Treatment', 'SBRT', 'RFA']
#
# THIS IS FOR OS FIRST
frac = 0.5
ds = {
'SBRT_train': df[df.SBRT == 1].sample(frac=frac),
'RFA_train': df[df.RFA == 1].sample(frac=frac),
'NONE_train': df[df.SBRT_OR_RFA == 0].sample(frac=frac)
}
ds |= {
'SBRT_test': df.loc[df[df.SBRT == 1].index.symmetric_difference(ds['SBRT_train'].index)],
'RFA_test': df.loc[df[df.RFA == 1].index.symmetric_difference(ds['RFA_train'].index)],
'NONE_test': df.loc[df[df.SBRT_OR_RFA == 0].index.symmetric_difference(ds['NONE_train'].index)],
}
df_sbrtVSnone = {
'train': pd.concat([ds['SBRT_train'], ds['NONE_train']]).drop(columns=drop_sbrtVS),
'test': pd.concat([ds['SBRT_test'], ds['NONE_test']]).drop(columns=drop_sbrtVS)
}
df_rfaVSnone = {
'train': pd.concat([ds['RFA_train'], ds['NONE_train']]).drop(columns=drop_rfaVS),
'test': pd.concat([ds['RFA_test'], ds['NONE_test']]).drop(columns=drop_rfaVS)
}
df_sbrtVSrfa = {
'train': pd.concat([ds['SBRT_train'], ds['RFA_train']]).drop(columns=drop_sbrtVS),
'test': pd.concat([ds['SBRT_test'], ds['RFA_test']]).drop(columns=drop_sbrtVS)
}
df_sbrtORrfa = {
'train': pd.concat([ds['SBRT_train'], ds['RFA_train'], ds['NONE_train']]).drop(columns=drop_sbrtORrfa),
'test': pd.concat([ds['SBRT_test'], ds['RFA_test'], ds['NONE_test']]).drop(columns=drop_sbrtORrfa)
}
ofile_os = os.path.join(os.path.dirname(args.ifile_os), 'liver_os_sbrtVSnone.hd5')
dataframes_to_hd5(df_sbrtVSnone, ofile_os, 'OSEvent', 'TTDy')
ofile_os = os.path.join(os.path.dirname(args.ifile_os), 'liver_os_rfaVSnone.hd5')
dataframes_to_hd5(df_rfaVSnone, ofile_os, 'OSEvent', 'TTDy')
ofile_os = os.path.join(os.path.dirname(args.ifile_os), 'liver_os_sbrtVSrfa.hd5')
dataframes_to_hd5(df_sbrtVSrfa, ofile_os, 'OSEvent', 'TTDy')
ofile_os = os.path.join(os.path.dirname(args.ifile_os), 'liver_os_sbrtORrfa.hd5')
dataframes_to_hd5(df_sbrtORrfa, ofile_os, 'OSEvent', 'TTDy')
#
# USE INDICES FROM OS FOR PFS
df_PFS = pd.read_csv(args.ifile_pfs)
df_sbrtVSnone_pfs = {
'train': df_PFS.loc[df_sbrtVSnone['train'].index].drop(columns=drop_sbrtVS),
'test': df_PFS.loc[df_sbrtVSnone['test'].index].drop(columns=drop_sbrtVS)
}
df_rfaVSnone_pfs = {
'train': df_PFS.loc[df_rfaVSnone['train'].index].drop(columns=drop_rfaVS),
'test': df_PFS.loc[df_rfaVSnone['test'].index].drop(columns=drop_rfaVS)
}
df_sbrtVSrfa_pfs = {
'train': df_PFS.loc[df_sbrtVSrfa['train'].index].drop(columns=drop_sbrtVS),
'test': df_PFS.loc[df_sbrtVSrfa['test'].index].drop(columns=drop_sbrtVS)
}
df_sbrtORrfa_pfs = {
'train': df_PFS.loc[df_sbrtORrfa['train'].index].drop(columns=drop_sbrtORrfa),
'test': df_PFS.loc[df_sbrtORrfa['test'].index].drop(columns=drop_sbrtORrfa)
}
ofile_pfs = os.path.join(os.path.dirname(args.ifile_os), 'liver_pfs_sbrtVSnone.hd5')
dataframes_to_hd5(df_sbrtVSnone_pfs, ofile_pfs, 'PFSEvent', 'TTPy')
ofile_pfs = os.path.join(os.path.dirname(args.ifile_os), 'liver_pfs_rfaVSnone.hd5')
dataframes_to_hd5(df_rfaVSnone_pfs, ofile_pfs, 'PFSEvent', 'TTPy')
ofile_pfs = os.path.join(os.path.dirname(args.ifile_os), 'liver_pfs_sbrtVSrfa.hd5')
dataframes_to_hd5(df_sbrtVSrfa_pfs, ofile_pfs, 'PFSEvent', 'TTPy')
ofile_pfs = os.path.join(os.path.dirname(args.ifile_os), 'liver_pfs_sbrtORrfa.hd5')
dataframes_to_hd5(df_sbrtORrfa_pfs, ofile_pfs, 'PFSEvent', 'TTPy')
|
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] | 1.994635 | 2,423 |
from minicps.devices import PLC
from utils import *
import random
import logging
import time
import socket
import json
import select
import signal
import sys
SENSOR_ADDR = IP['lit101']
LIT101 = ('LIT101', 1)
LIT102 = ('LIT102', 1)
if __name__ == '__main__':
lit101 = Lit101(name='lit101',state=STATE,protocol=LIT101_PROTOCOL,memory=GENERIC_DATA,disk=GENERIC_DATA)
|
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# Generated by Django 2.2.5 on 2019-09-15 10:58
from django.db import migrations
|
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] | 2.766667 | 30 |
'''
End to end testing
'''
import shutil
import os
from ConfigParser import SafeConfigParser
import textwrap
import hashlib
import pexpect
import sys
import leveldb
import backup
import tempfile
from backup import dump_database
from myutils import path_leaf
TEST_CONFIG_NAME = "config"
TEST_DROPBOX_NAME = "dropbox"
TEST_TO_BACKUP_DIR = "to_backup"
TEST_DATABASE_DIR = "db"
TEST_PATH = os.path.dirname(os.path.abspath(__file__)) + '/test/'
#Path wehre db will be recovered
DB_RECOVERY_PATH = os.path.dirname(os.path.abspath(__file__)) + '/foo/'
PASSWORD = "alamakota"
BACKUP_TOOL = "python ./ds.py "
def reset_dropbox_dir(config):
'''
Remove dropbox dropbox directory
'''
dropbox_dir = config.get('DropBox', 'drop_box_dir')
shutil.rmtree(dropbox_dir)
os.makedirs(dropbox_dir)
def reset_db(config):
'''
Remove databse
'''
db_dir = config.get('DB', 'db_path')
shutil.rmtree(db_dir)
os.makedirs(db_dir)
def reset_to_backup_dir(config):
'''
Remove directory to backed up
'''
to_backup_dir = config.get('Backup', 'to_backup')
shutil.rmtree(to_backup_dir)
os.makedirs(to_backup_dir)
def create_test_config():
'''
Creates config file for testing purposes
'''
aa = """\
[Credentials]
password=alamakota
[DropBox]
drop_box_dir = {drop_box_dir}
[DB]
#Database MUST not be in backed up folder as it's being changed
#during backup process. Program backs up databse itself by
#gzipping, encryptying and putting in drobox folder as "dbmapping"
db_path = {db_path}
[Backup]
to_backup = {to_backup}
to_exclude =
"""
context = {
"drop_box_dir":TEST_PATH+TEST_DROPBOX_NAME+"/",
"db_path":TEST_PATH+TEST_DATABASE_DIR+"/",
"to_backup":TEST_PATH+TEST_TO_BACKUP_DIR+"/",
"passord":PASSWORD
}
if not os.path.exists(TEST_PATH):
os.makedirs(TEST_PATH)
with open(TEST_PATH+'/'+TEST_CONFIG_NAME, 'w') as cfgfile:
cfgfile.write(textwrap.dedent(aa.format(**context)))
if not os.path.exists(context["drop_box_dir"]):
os.makedirs(context["drop_box_dir"])
if not os.path.exists(context["db_path"]):
os.makedirs(context["db_path"])
if not os.path.exists(context["to_backup"]):
os.makedirs(context["to_backup"])
if not os.path.exists(DB_RECOVERY_PATH):
os.makedirs(DB_RECOVERY_PATH)
def clear(config):
'''
Clears all created files, directories and exits
'''
db_dir = config.get('DB', 'db_path')
if os.path.exists(db_dir):
shutil.rmtree(db_dir)
dropbox_dir = config.get('DropBox', 'drop_box_dir')
if os.path.exists(dropbox_dir):
shutil.rmtree(dropbox_dir)
to_backup_dir = config.get('Backup', 'to_backup')
if os.path.exists(to_backup_dir):
shutil.rmtree(to_backup_dir)
os.remove(TEST_PATH+TEST_CONFIG_NAME)
def clear_all():
'''
Remove all in one shot
'''
if os.path.exists(TEST_PATH):
shutil.rmtree(TEST_PATH)
if os.path.exists(DB_RECOVERY_PATH):
shutil.rmtree(DB_RECOVERY_PATH)
def test1():
'''
Initially dropbox folder is empty and databse is empty.
Check if file is backed up and restored correctly
'''
print '-'*50
print "Test 1"
clear_all()
create_test_config()
config = SafeConfigParser()
config.read(TEST_PATH+TEST_CONFIG_NAME)
file_to_backup = config.get('Backup', 'to_backup')+'/some_file'
with open(file_to_backup, 'w') as some_file:
some_file.write('Very first line')
checksum_before = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Restore
os.remove(file_to_backup)
child = pexpect.spawn(BACKUP_TOOL + "restore -d" + TEST_PATH+
TEST_DROPBOX_NAME + " -r" + DB_RECOVERY_PATH)
child.expect('Password: ')
child.sendline(PASSWORD)
print child.read()
checksum_after = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
if checksum_before != checksum_after:
print "Test 1 failed!"
sys.exit(1)
else:
print "Test 1 ok"
def test2():
'''
Initally dropbox folder is empty and database is empty.
Check if modified file is backed up and restored correctly.
'''
print '-'*50
print "Test 2"
clear_all()
create_test_config()
config = SafeConfigParser()
config.read(TEST_PATH+TEST_CONFIG_NAME)
file_to_backup = config.get('Backup', 'to_backup')+'/some_file'
with open(file_to_backup, 'w') as some_file:
some_file.write('Very first line')
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Modification
with open(file_to_backup, 'a') as some_file:
some_file.write('The second line')
checksum_before = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Restore
os.remove(file_to_backup)
child = pexpect.spawn(BACKUP_TOOL + "restore -d " + TEST_PATH+
TEST_DROPBOX_NAME + " -r " + DB_RECOVERY_PATH)
child.expect('Password: ')
child.sendline(PASSWORD)
print child.read()
checksum_after = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
if checksum_before != checksum_after:
print "Test 2 failed!"
sys.exit(1)
db = leveldb.LevelDB(config.get('DB', 'db_path'))
dump_file = os.path.join(tempfile.gettempdir(), '') + 'foo'
entries = dump_database(db, dump_file)
if entries != 1:
print "Test 2 failed!"
sys.exit(1)
print "Test 2 ok"
def test3():
'''
Initally dropbox folder is empty and database is empty.
Check if deleted files in source folder is deleted from dropbox as well
'''
print '-'*50
print "Test 3"
clear_all()
create_test_config()
config = SafeConfigParser()
config.read(TEST_PATH+TEST_CONFIG_NAME)
file_to_backup = config.get('Backup', 'to_backup')+'/some_file'
with open(file_to_backup, 'w') as some_file:
some_file.write('Very first line')
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Delete
os.remove(file_to_backup)
#Backup again
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Check if file doesn't exist
for subdir, dirs, files in os.walk(config.get('DropBox','drop_box_dir')):
for f in files:
#Meta entry is not in database
if path_leaf(f) == backup.META_DB_NAME + ".xyz":
continue
else:
print "Test 3 failed - deleted file exists in dropbox folder"
sys.exit(1)
#Database shall not contain any entry
entries = 0
db = leveldb.LevelDB(config.get('DB', 'db_path'))
dump_file = os.path.join(tempfile.gettempdir(), '') + 'foo'
entries = dump_database(db, dump_file)
if entries != 0:
print "Test 3 failed - deleted file has entry in database"
sys.exit(1)
print "Test 3 ok"
def test4():
'''
Initally dropbox folder is empty and database is empty.
Check if deleted source folder (which contains files) causes deletion
of this files from dropbox folder.
'''
print '-'*50
print "Test 4"
clear_all()
create_test_config()
config = SafeConfigParser()
config.read(TEST_PATH+TEST_CONFIG_NAME)
directory_to_backup = config.get('Backup', 'to_backup')+'/some_dir'
os.makedirs(directory_to_backup)
file_to_backup = config.get('Backup', 'to_backup')+'/some_dir/some_file1'
with open(file_to_backup, 'w') as some_file:
some_file.write('Very first line')
file_to_backup = config.get('Backup', 'to_backup')+'/some_dir/some_file2'
with open(file_to_backup, 'w') as some_file:
some_file.write('The other very first line')
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Delete
shutil.rmtree(directory_to_backup)
#Backup again
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Check if file doesn't exist
for subdir, dirs, files in os.walk(config.get('DropBox','drop_box_dir')):
for f in files:
#Meta entry is not in database
if path_leaf(f) == backup.META_DB_NAME + ".xyz":
continue
else:
print "Test 4 failed - deleted file exists in dropbox folder"
sys.exit(1)
#Database shall not contain any entry
entries = 0
db = leveldb.LevelDB(config.get('DB', 'db_path'))
dump_file = os.path.join(tempfile.gettempdir(), '') + 'foo'
entries = dump_database(db, dump_file)
if entries != 0:
print "Test 4 failed - deleted file has entry in database"
sys.exit(1)
print "Test 4 ok"
def test5():
'''
Initially dropbox folder is empty and databse is empty.
Check if file is backed + directory up and restored correctly.
It's very much alike test1 but here file is in subdirectory of
backed up directory
'''
print '-'*50
print "Test 5"
clear_all()
create_test_config()
config = SafeConfigParser()
config.read(TEST_PATH+TEST_CONFIG_NAME)
subdir = config.get('Backup', 'to_backup')+'/dir/'
os.makedirs(subdir)
file_to_backup = subdir + 'some_file'
with open(file_to_backup, 'w') as some_file:
some_file.write('Very first line')
checksum_before = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
#Backup
os.system(BACKUP_TOOL + "backup -c" + TEST_PATH + "/" + TEST_CONFIG_NAME)
#Restore
os.remove(file_to_backup)
child = pexpect.spawn(BACKUP_TOOL + "restore -d" + TEST_PATH+
TEST_DROPBOX_NAME + " -r" + DB_RECOVERY_PATH)
child.expect('Password: ')
child.sendline(PASSWORD)
print child.read()
checksum_after = hashlib.md5(open(file_to_backup, 'rb').read()).hexdigest()
if checksum_before != checksum_after:
print "Test 5 failed!"
sys.exit(1)
else:
print "Test 5 ok"
def run_tests():
'''
Run test cases
'''
test1()
test2()
test3()
test4()
test5()
clear_all()
if __name__ == "__main__":
#TEST_PATH = os.path.dirname(os.path.abspath(__file__)) + '/test/'
run_tests()
|
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9288,
14,
6,
198,
220,
220,
220,
1057,
62,
41989,
3419,
628
] | 2.280568 | 4,580 |
"""
This cog deals all the lookup commands
"""
import asyncio
from discord.ext import commands, tasks
import discord
from lookupAPI import nookipediaAPI, localLookup
import os
from dotenv import load_dotenv
load_dotenv(".env")
|
[
37811,
198,
1212,
43072,
7529,
477,
262,
35847,
9729,
198,
37811,
198,
11748,
30351,
952,
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13,
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] | 3.59375 | 64 |
import hashlib
import os
import pytest
from aiohttp import ClientSession
from lyricsfinder.extractors.azlyrics import AZLyrics
from lyricsfinder.utils import Request
|
[
11748,
12234,
8019,
198,
11748,
28686,
198,
198,
11748,
12972,
9288,
198,
6738,
257,
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] | 3.755556 | 45 |
# settings for councils scraper
BOUNDARIES_URL = "https://ons-cache.s3.amazonaws.com/Local_Authority_Districts_April_2019_Boundaries_UK_BFE.geojson"
EC_COUNCIL_CONTACT_DETAILS_API_URL = (
"https://electoralcommission.org.uk/api/v1/data/local-authorities.json"
)
OLD_TO_NEW_MAP = {}
NEW_COUNCILS = []
WELSH_COUNCIL_NAMES = {
"AGY": "Cyngor Sir Ynys Môn", # Isle of Anglesey County Council
"BGE": "Cyngor Bwrdeistref Sirol Pen-y-bont ar Ogwr", # Bridgend County Borough Council
"BGW": "Cyngor Bwrdeistref Sirol Blaenau Gwent", # Blaenau Gwent County Borough Council
"CAY": "Cyngor Bwrdeistref Sirol Caerffili", # Caerphilly County Borough Council
"CGN": "Cyngor Sir Ceredigion", # Ceredigion County Council
"CMN": "Cyngor Sir Gaerfyrddin", # Carmarthenshire County Council
"CRF": "Cyngor Caerdydd", # Cardiff Council
"CWY": "Cyngor Bwrdeistref Sirol Conwy", # Conwy County Borough Council
"DEN": "Cyngor Sir Ddinbych", # Denbighshire County Council
"FLN": "Cyngor Sir y Fflint", # Flintshire County Council
"GWN": "Cyngor Sir Gwynedd", # Gwynedd Council
"MON": "Cyngor Sir Fynwy", # Monmouthshire County Council
"MTY": "Cyngor Bwrdeistref Sirol Merthyr Tudful", # Merthyr Tydfil County Borough Council
"NTL": "Cyngor Bwrdeistref Sirol Castell-nedd Port Talbot", # Neath Port Talbot County Borough Council
"NWP": "Cyngor Dinas Casnewydd", # Newport City Council
"PEM": "Cyngor Sir Penfro", # Pembrokeshire County Council
"POW": "Cyngor Sir Powys", # Powys County Council
"RCT": "Cyngor Bwrdeistref Sirol Rhondda Cynon Taf", # Rhondda Cynon Taf County Borough Council
"SWA": "Cyngor Sir a Dinas Abertawe", # City and County of Swansea
"TOF": "Cyngor Bwrdeistref Sirol Torfaen", # Torfaen County Borough Council
"VGL": "Cyngor Bwrdeistref Sirol Bro Morgannwg", # The Vale of Glamorgan County Borough Council
"WRX": "Cyngor Bwrdeistref Sirol Wrecsam", # Wrexham County Borough Council
}
|
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286,
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220,
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273,
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2934,
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1600,
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1303,
370,
21510,
2763,
3418,
48114,
4281,
198,
92,
198
] | 2.531646 | 790 |
from enum import Enum
from typing import Iterator, List, Optional, Tuple
import re
_PUNCTUATION = {
"(": _Token(_TokenType.LPAREN),
")": _Token(_TokenType.RPAREN),
"{": _Token(_TokenType.LBRACE),
"}": _Token(_TokenType.RBRACE),
"[": _Token(_TokenType.LBRACK),
"]": _Token(_TokenType.RBRACK),
",": _Token(_TokenType.COMMA),
":": _Token(_TokenType.COLON),
}
_KWS = {
"in": _Keyword.IN,
"out": _Keyword.OUT,
"inout": _Keyword.INOUT,
}
_STARTIDENTCHAR = re.compile(r"[A-Za-z]")
_IDENTCHAR = re.compile(r"[A-Za-z0-9\-_<>]")
class _peekable():
"Wrap iterator with lookahead to both peek and test exhausted"
# Code by Terry Jan Reedy, intentionally submitted to the python-ideas
# mailing list for inclusion into itertools.
# https://mail.python.org/pipermail//python-ideas/2013-February/019633.html
_NONE = object()
def _parse_type_sig(lex) -> (InOutness, str, str, Optional[str]):
"""
"inout bool bShow" -> (InOutness.INOUT, "bool", "bShow", None)
"in enum[EInventorySlot] Slot" -> (InOutness.IN, "enum", "Slot", "EInventorySlot")
"""
param_kind = _kw_to_inout(
_expect(lex, _TokenType.KW, "inoutness", "tuple param"))
tup_type = _expect(lex, _TokenType.IDENT, "type", "tuple param").ident
local_type = None
if _try_eat(lex, _TokenType.LBRACK):
local_type = _expect(lex, _TokenType.IDENT, "local type",
"tuple param").ident
_expect(lex, _TokenType.RBRACK, "inoutness", "tuple param")
name = _expect(lex, _TokenType.IDENT, "param name", "tuple param")
if name.ident.lower() == "self":
raise ParseError(f"{name} not a valid local variable name")
return param_kind, tup_type, name.ident, local_type
|
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7,
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1,
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220,
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62,
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11,
1438,
13,
738,
11,
1957,
62,
4906,
628,
198
] | 2.33377 | 764 |
import sys
import numpy as np
import math
from collections import Counter
if __name__ == "__main__":
if len(sys.argv) != 6:
print("Usage:build_kNN.py <training_data> <test_data> <k_val> <similarity_func> <sys_output>")
exit(-1)
else:
trainingData, features = readData(sys.argv[1])
testData, _ = readData(sys.argv[2])
candidate, truth = knn(trainingData,testData, int(sys.argv[3]), int(sys.argv[4]),sys.argv[5])
writeMatrix(candidate, truth)
|
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3551,
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20540,
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8
] | 2.328638 | 213 |
from django import forms
from . import models
STATES = [
('AL', 'AL'), ('AK', 'AK'), ('AZ', 'AZ'), ('AR', 'AR'), ('CA', 'CA'),
('CO', 'CO'), ('CT', 'CT'), ('DC', 'DC'), ('DE', 'DE'), ('FL', 'FL'),
('GA', 'GA'), ('HI', 'HI'), ('ID', 'ID'), ('IL', 'IL'), ('IN', 'IN'),
('IA', 'IA'), ('KS', 'KS'), ('KY', 'KY'), ('LA', 'LA'), ('ME', 'ME'),
('MD', 'MD'), ('MA', 'MA'), ('MI', 'MI'), ('MN', 'MN'), ('MS', 'MS'),
('MO', 'MO'), ('MT', 'MT'), ('NE', 'NE'), ('NV', 'NV'), ('NH', 'NH'),
('NJ', 'NJ'), ('NM', 'NM'), ('NY', 'NY'), ('NC', 'NC'), ('ND', 'ND'),
('OH', 'OH'), ('OK', 'OK'), ('OR', 'OR'), ('PA', 'PA'), ('RI', 'RI'),
('SC', 'SC'), ('SD', 'SD'), ('TN', 'TN'), ('TX', 'TX'), ('UT', 'UT'),
('VT', 'VT'), ('VA', 'VA'), ('WA', 'WA'), ('WV', 'WV'), ('WI', 'WI'),
('WY', 'WY')
]
class IngredientForm(forms.ModelForm):
"""Form allowing a new Ingredient to be created"""
class Meta:
"""Defines the model the form uses and what fields to use"""
model = models.Ingredient
fields = ['name']
def clean_name(self):
"""Over-ride the value for name and title case it"""
name = self.cleaned_data['name']
return name.title()
class PizzaForm(forms.ModelForm):
"""Form allowing a new Pizza object to be created"""
class Meta:
"""Defines the model the form uses and what fields to use"""
model = models.Pizza
fields = ['city', 'state', 'crust', 'ingredients', 'name', 'summary']
# Over-ride the State field to be a state selector
widgets = {'state': forms.Select(choices=STATES)}
|
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220,
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62,
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220,
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47,
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220,
220,
220,
220,
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220,
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278,
23320,
3256,
705,
3672,
3256,
705,
49736,
20520,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
3827,
12,
13154,
262,
1812,
2214,
284,
307,
257,
1181,
31870,
198,
220,
220,
220,
220,
220,
220,
220,
40803,
796,
1391,
6,
5219,
10354,
5107,
13,
17563,
7,
6679,
1063,
28,
2257,
29462,
38165,
628
] | 2.431784 | 667 |
# This sample tests the reportIncompatibleMethodOverride
# configuration option.
# This should generate an error if reportIncompatibleMethodOverride
# is enabled.
# This should generate an error if reportIncompatibleMethodOverride
# is enabled.
|
[
2,
770,
6291,
5254,
262,
989,
818,
38532,
17410,
37961,
198,
2,
8398,
3038,
13,
198,
220,
220,
220,
1303,
770,
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220,
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989,
818,
38532,
17410,
37961,
198,
220,
220,
220,
1303,
318,
9343,
13,
628
] | 4.109375 | 64 |
from ixnetwork_restpy.base import Base
from ixnetwork_restpy.files import Files
|
[
6738,
220,
844,
27349,
62,
2118,
9078,
13,
8692,
1330,
7308,
198,
6738,
220,
844,
27349,
62,
2118,
9078,
13,
16624,
1330,
13283,
628
] | 3.375 | 24 |
# -*- coding:utf-8 -*-
# file: rancher_api
# author: Mundy
# date: 2017/9/1 0001
"""
rancher api调用
"""
import json
import requests
from django.conf import settings
# --------requests设置--------
time_out = 8
headers = {
'content-type': 'application/json',
'Accept': 'application/json',
}
# 调用receiver_hooks api
|
[
2,
532,
9,
12,
19617,
25,
40477,
12,
23,
532,
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12,
198,
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807,
198,
50145,
796,
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198,
220,
220,
220,
705,
11299,
12,
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705,
31438,
14,
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3256,
198,
220,
220,
220,
705,
38855,
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705,
31438,
14,
17752,
3256,
198,
92,
628,
198,
198,
2,
5525,
108,
225,
18796,
101,
260,
39729,
62,
25480,
82,
40391,
628
] | 2.439394 | 132 |
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