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tests/batch/plugins/DummyPlugin/__init__.py | j-h-m/Media-Journaling-Tool | 0 | 190003 | # =============================================================================
# Authors: PAR Government
# Organization: DARPA
#
# Copyright (c) 2016 PAR Government
# All rights reserved.
#==============================================================================
import maskgen
def transform(img,source,target,**kwargs):
return None,None
# the actual link name to be used.
# the category to be shown
def operation():
return {'name':'Blur',
'category':'Filter',
'description':'Gaussian Blur',
'software':'maskgen',
'version':maskgen.__version__,
'transitions': [
'image.image'
]
}
def suffix():
return None | [
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install_and_run.py | encukou/mufl | 1 | 107635 | import sys
if sys.version_info < (3, 8):
exit('This game requires Python 3.8+')
import os
from pathlib import Path
import subprocess
HERE = Path(__file__).parent
venv_path = HERE / 'venv'
possible_python_locations = 'bin/python', 'scripts/python'
def run(args, **kwargs):
kwargs.setdefault('check', True)
print('Running:', ' '.join(str(s) for s in args))
subprocess.run(args, **kwargs)
if not venv_path.exists():
run([sys.executable, '-m', 'venv', venv_path])
for loc in possible_python_locations:
interp_path = venv_path / loc
if interp_path.exists():
break
else:
exit('Could not find Python in virtualenv :(')
environ = dict(os.environ)
environ['PYTHONPATH'] = 'vendor'
reqs = Path('requirements.txt').read_text().splitlines()
run([interp_path, '-m', 'pip', 'install', '--no-deps', *reqs], env=environ)
run([interp_path, '-m', 'pip', 'check'], env=environ, check=False)
run([interp_path, '-m', 'mufl'], env=environ)
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dimred/data/oldloader1.py | kulkarnisp/dim-red | 1 | 190070 | import numpy as np
import os,sys
import matplotlib.pyplot as plt
import pathlib
import pandas as pd
# import plotly.express as px
# ipath__ = pathlib.Path(__file__) #.parent.resolve()
# ipath__= os.path.normpath(ipath__).split(os.path.sep)
# datapath__ = os.path.join(*ipath__[:-3],"datasets/")
datapath__ = os.path.abspath(os.path.join(os.path.dirname( __file__ ), '..','..', 'datasets'))
# from utils import normalise, featurise
class LoadMPI():
def __init__(self,data='hcci'):
self.inipath = "/home/shubham/strial/Combust/hcci/data/"
self.fpath = self.inipath.replace("hcci",data)
self.loadFile(data)
def loadFile(self, val="hcci"):
flist = [f for f in os.listdir(self.fpath) if f.endswith(".mpi")]
self.flist = sorted(flist, key=lambda f: float(f[-20:-10]) )
self.selTime(0)
self.loadOptions()
self.loadVariables()
def loadOptions(self):
if "hcci" in self.fpath:
self.nx = 672
self.ny = 672
self.badOffset = 0
self.species = "varhcci.txt"
else:
self.nx = 3600
self.ny = 1800
self.badOffset = 89266
self.species = "varisml.txt"
def loadVariables(self,ipath=None):
if ipath is None:
ipath = pathlib.Path(__file__).parent.resolve()
# ipath = "/home/shubham/Projects/Anomaly/src/unsup/"
fr = open(os.path.join(ipath,self.species),"r")
ychem = fr.read()
# jack = raw.split()
# sparo = [v for i,v in enumerate(jack) if (i+1)%3==0]
# ychem = " ".join(sparo)
ychem += " T P u v w"
variables = ychem.split(" ")
self.idvar = {i:v for i,v in enumerate(variables)}
self.varid = {v:i for i,v in enumerate(variables)}
self.variables = self.varid
self.nv = len(variables)
self.i = 0
def selTime(self,index):
## path remains same just the file changes
self.fid = index
self.file = self.flist[index]
self.filer = open(self.fpath+self.file,"rb")
def selSpec(self,index):
## file remains same, just index changes
self.i = index
def getDat(self,time):
### be careful with this function ; memory sensitive
self.selTime(time)
a = np.fromfile(self.filer,
count=self.nx*self.ny*self.nv,dtype="float64")
dat = a.reshape((self.nx,self.ny,self.nv),order="F")
return dat
def getTime(self,time):
return self.getDat(time)
def getHrr(self):
n = self.file.find('E')
root = self.file[n-6:n+4]
a = np.fromfile(self.fpath[:-5]+"hrr/hrr."+root+".mpi",
count=self.nx*self.ny*1,dtype="float64")
dat = a.reshape((self.nx,self.ny,1), order="F")
return dat
def getMat(self,species = None):
if species is None:
species = self.i
# i = self.variables[t]
self.filer.seek(species*8*self.nx*self.ny+self.badOffset)
a = np.fromfile(self.filer,
count=self.nx*self.ny,dtype="float64")
T = a.reshape(self.nx,self.ny,order="F")
return T
def getTrain(self, j):
self.file = self.flist[j]
y = self.getHrr()
x = self. getDat(j)
return x,y
def plotImage(self,time=10,species=0):
self.selTime(time)
self.selSpec(species)
T = self.getMat(self.i)
# plt.figure(figsize=(6,6))
fig = plt.imshow(T,cmap = "jet",aspect=1)
titler = self.idvar[self.i] + f" at T{self.filer}"
plt.title(self.file)
plt.colorbar()
def stPlot(self,saver="temp.png",titler=None,species=0):
T = self.getMat(self.i)
plt.figure(figsize=(6,6))
fig = plt.imshow(T,cmap = "jet",aspect=1)
if titler is None:
titler = self.idvar[self.i] + f" at T{self.filer}"
plt.title(self.file)
plt.colorbar()
if saver!=0:
plt.savefig(saver)
plt.show()
return fig
def dyPlot(self,px=plt):
T = self.getMat()
fig = px.imshow(T,
color_continuous_scale="jet",
title=self.file)
fig.update_layout(
autosize=False,
width=800,
height=800,)
return fig
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2537,
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2
] |
tkgeom/__init__.py | ezsolti/TKworkshop | 0 | 92277 | __package__ = 'tkgeom'
__title__ = 'tkgeom'
__description__ = '2D geometry module as an example for the TK workshop'
__copyright__ = '2019, <NAME>'
__version__ = '1.0.0'
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] |
backend/core/jobs/__init__.py | makakken/roseguarden | 0 | 149384 | """
The roseguarden project
Copyright (C) 2018-2020 <NAME>,
This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with
this program. If not, see <http://www.gnu.org/licenses/>.
"""
__authors__ = ["<NAME>"]
__contact__ = "<EMAIL>"
__credits__ = []
__license__ = "GPLv3"
from datetime import datetime, timedelta
from flask import Blueprint
from core.jobs.job import Job
from core.jobs.jobManager import JobManager
from core.logs import logManager
from inspect import isclass
jobs_bp = Blueprint('jobs', __name__)
jobManager = JobManager()
def trigger_job(job_key, args, user):
logManager.info("User {} triggered job {}".format(user.email, job_key))
job_id = jobManager.run_job(user, job_key, args, datetime.now() + timedelta(seconds=5), log_trigger=True)
return job_id
def add_dated_job(user, job, args, date=None, workspace=None, max_instances=10):
if date is None:
date = datetime.now()
key = ""
if workspace is not None:
if type(workspace) == str:
key += workspace + '/'
elif isclass(workspace):
logManager.error("Class parameters are not allowed for add_dated_job")
return
else:
key += workspace.name + '/'
if type(job) == str:
key += job
elif isclass(workspace):
logManager.error("Class parameters are not allowed for add_dated_job")
return
elif issubclass(type(job), Job):
key += job.name
else:
logManager.error("Unknown type of job in add_dated_job")
return
jobManager.run_job(user, key, args, date, max_instances)
def print_job_list():
actual_jobs = jobManager.scheduler.get_jobs()
print(actual_jobs)
all_jobs = jobManager.jobstore.get_all_jobs()
print(all_jobs)
from core.jobs import routes # noqa: F401
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src/history/migrations/0003_auto_20200710_0608.py | ritvikmahajan17/scrum-2 | 8 | 126882 | <filename>src/history/migrations/0003_auto_20200710_0608.py
# Generated by Django 3.0.7 on 2020-07-10 00:38
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('project', '0004_auto_20200701_0437'),
('log', '0010_auto_20200710_0608'),
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('history', '0002_auto_20200610_0234'),
]
operations = [
migrations.AlterField(
model_name='history',
name='logger',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='log.Logger'),
),
migrations.AlterField(
model_name='history',
name='project',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='project.Project'),
),
migrations.AlterField(
model_name='history',
name='team',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='project.Team'),
),
migrations.AlterField(
model_name='history',
name='user',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL),
),
]
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lisa/target.py | mrkajetanp/lisa | 0 | 1659 | # SPDX-License-Identifier: Apache-2.0
#
# Copyright (C) 2018, ARM Limited and contributors.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from datetime import datetime
import os
import os.path
import contextlib
import shlex
from collections.abc import Mapping
import copy
import sys
import argparse
import textwrap
import functools
import inspect
import pickle
import tempfile
from types import ModuleType, FunctionType
from operator import itemgetter
import devlib
from devlib.exception import TargetStableError
from devlib.utils.misc import which
from devlib.platform.gem5 import Gem5SimulationPlatform
from lisa.utils import Loggable, HideExekallID, resolve_dotted_name, get_subclasses, import_all_submodules, LISA_HOME, RESULT_DIR, LATEST_LINK, setup_logging, ArtifactPath, nullcontext, ExekallTaggable, memoized
from lisa.assets import ASSETS_PATH
from lisa.conf import SimpleMultiSrcConf, KeyDesc, LevelKeyDesc, TopLevelKeyDesc,Configurable
from lisa.generic import TypedList
from lisa.platforms.platinfo import PlatformInfo
class PasswordKeyDesc(KeyDesc):
def pretty_format(self, v):
return '<password>'
# Make sure all submodules of devlib.module are imported so the classes
# are all created before we list them
import_all_submodules(devlib.module)
_DEVLIB_AVAILABLE_MODULES = {
cls.name
for cls in get_subclasses(devlib.module.Module)
if (
getattr(cls, 'name', None)
# early modules try to connect to UART and do very
# platform-specific things we are not interested in
and getattr(cls, 'stage') != 'early'
)
}
class TargetConf(SimpleMultiSrcConf, HideExekallID):
"""
Target connection settings.
Only keys defined below are allowed, with the given meaning and type:
{generated_help}
An instance can be created by calling :class:`~TargetConf` with a
dictionary. The top-level `target-conf` key is not needed here:
.. code-block:: python
TargetConf({{
'name': 'myboard',
'host': 192.0.2.1,
'kind': 'linux',
'username': 'foo',
'password': '<PASSWORD>',
}})
Or alternatively, from a YAML configuration file:
Content of target_conf.yml:
.. literalinclude:: ../target_conf.yml
:language: YAML
::
TargetConf.from_yaml_map('target_conf.yml')
The following special YAML tags can be used in the configuration file:
.. code-block:: YAML
target-conf:
# "!env:<type> ENV_VAR_NAME" can be used to reference an
# environment variable.
name: !env:str BOARD_NAME
port: !env:int PORT
.. note:: Only load trusted YAML files as it can lead to abritrary code
execution.
.. note:: That structure in a YAML file is allowed and will work:
* file foo.yml::
target-conf:
name: myboard
* file bar.yml::
target-conf:
!include foo.yml
This will result in that structure which would normally be invalid, but
is handled as a special case::
target-conf:
target-conf:
name: myboard
"""
STRUCTURE = TopLevelKeyDesc('target-conf', 'target connection settings', (
KeyDesc('name', 'Board name, free-form value only used to embelish logs', [str]),
KeyDesc('kind', 'Target kind. Can be "linux" (ssh) or "android" (adb)', [str]),
KeyDesc('host', 'Hostname or IP address of the host', [str, None]),
KeyDesc('username', 'SSH username. On ADB connections, "root" username will root adb upon target connection', [str, None]),
PasswordKeyDesc('password', 'SSH password', [str, None]),
KeyDesc('port', 'SSH or ADB server port', [int, None]),
KeyDesc('device', 'ADB device. Takes precedence over "host"', [str, None]),
KeyDesc('keyfile', 'SSH private key file', [str, None]),
KeyDesc('strict-host-check', 'Equivalent to StrictHostKeyChecking option of OpenSSH', [bool, None]),
KeyDesc('workdir', 'Remote target workdir', [str]),
KeyDesc('tools', 'List of tools to install on the target', [TypedList[str]]),
KeyDesc('lazy-platinfo', 'Lazily autodect the platform information to speed up the connection', [bool]),
LevelKeyDesc('wait-boot', 'Wait for the target to finish booting', (
KeyDesc('enable', 'Enable the boot check', [bool]),
KeyDesc('timeout', 'Timeout of the boot check', [int]),
)),
LevelKeyDesc('devlib', 'devlib configuration', (
# Using textual name of the Platform allows this YAML configuration
# to not use any python-specific YAML tags, so TargetConf files can
# be parsed and produced by any other third-party code
LevelKeyDesc('platform', 'devlib.platform.Platform subclass specification', (
KeyDesc('class', 'Name of the class to use', [str]),
KeyDesc('args', 'Keyword arguments to build the Platform object', [Mapping]),
)),
KeyDesc('excluded-modules', 'List of devlib modules to *not* load', [TypedList[str]]),
KeyDesc('file-xfer', 'File transfer method. Can be "sftp" (default) or "scp". (Only valid for linux targets)', [TypedList[str]]),
))
))
DEFAULT_SRC = {
'devlib': {
'platform': {
'class': 'devlib.platform.Platform'
}
}
}
class Target(Loggable, HideExekallID, ExekallTaggable, Configurable):
"""
Wrap :class:`devlib.target.Target` to provide additional features on top of
it.
{configurable_params}
:param devlib_platform: Instance of :class:`devlib.platform.Platform` to
use to build the :class:`devlib.target.Target`
:type devlib_platform: devlib.platform.Platform
:param plat_info: Platform information attached to this target, for the
benefits of user code.
:type plat_info: lisa.platforms.platinfo.PlatformInfo
You need to provide the information needed to connect to the
target. For SSH targets that means "host", "username" and
either "password" or "keyfile". All other fields are optional if
the relevant features aren't needed.
.. note:: The wrapping of :class:`devlib.target.Target` is done using
composition, as opposed to inheritance. This allows swapping the exact
class used under the hood, and avoids messing up with ``devlib``
internal members.
"""
ADB_PORT_DEFAULT = 5555
SSH_PORT_DEFAULT = 22
CRITICAL_TASKS = {
'linux': [
'init',
# We want to freeze everything except PID 1, we don't want to let
# sysmted-journald or systemd-timesyncd running.
'systemd[^-]',
'dbus',
'sh',
'ssh',
'rsyslogd',
'jbd2'
],
'android': [
'sh', 'adbd',
'usb', 'transport',
# We don't actually need this task but on Google Pixel it apparently
# cannot be frozen, so the cgroup state gets stuck in FREEZING if we
# try to freeze it.
'thermal-engine',
# Similar issue with HiKey960, the board will crash if this is frozen
# for too long.
'watchdogd',
]
}
"""
Dictionary mapping OS name to list of task names that we can't afford to
freeze when using :meth:`freeze_userspace`.
"""
CONF_CLASS = TargetConf
INIT_KWARGS_KEY_MAP = {
'devlib_excluded_modules': ['devlib', 'excluded-modules'],
'devlib_file_xfer': ['devlib', 'file-xfer'],
'wait_boot': ['wait-boot', 'enable'],
'wait_boot_timeout': ['wait-boot', 'timeout'],
}
def __init__(self, kind, name='<noname>', tools=[], res_dir=None,
plat_info=None, lazy_platinfo=False, workdir=None, device=None, host=None, port=None,
username=None, password=<PASSWORD>, keyfile=None, strict_host_check=None,
devlib_platform=None, devlib_excluded_modules=[], devlib_file_xfer=None,
wait_boot=True, wait_boot_timeout=10,
):
# pylint: disable=dangerous-default-value
super().__init__()
logger = self.get_logger()
self.name = name
res_dir = res_dir if res_dir else self._get_res_dir(
root=os.path.join(LISA_HOME, RESULT_DIR),
relative='',
name=f'{self.__class__.__qualname__}-{self.name}',
append_time=True,
symlink=True
)
self._res_dir = res_dir
os.makedirs(self._res_dir, exist_ok=True)
if os.listdir(self._res_dir):
raise ValueError(f'res_dir must be empty: {self._res_dir}')
if plat_info is None:
plat_info = PlatformInfo()
else:
# Make a copy of the PlatformInfo so we don't modify the original
# one we were passed when adding the target source to it
plat_info = copy.copy(plat_info)
logger.info(f'User-defined platform information:\n{plat_info}')
self.plat_info = plat_info
# Take the board name from the target configuration so it becomes
# available for later inspection. That board name is mostly free form
# and no specific value should be expected for a given kind of board
# (i.e. a Juno board might be named "foo-bar-juno-on-my-desk")
if name:
self.plat_info.add_src('target-conf', dict(name=name))
# Determine file transfer method. Currently avaliable options
# are 'sftp' and 'scp', defaults to sftp.
if devlib_file_xfer and devlib_file_xfer not in ('scp', 'sftp'):
raise ValueError(f'Invalid file transfer method: {devlib_file_xfer}')
use_scp = devlib_file_xfer == 'scp'
self._installed_tools = set()
self.target = self._init_target(
kind=kind,
name=name,
workdir=workdir,
device=device,
host=host,
port=port,
username=username,
password=password,
keyfile=keyfile,
strict_host_check=strict_host_check,
use_scp=use_scp,
devlib_platform=devlib_platform,
wait_boot=wait_boot,
wait_boot_timeout=wait_boot_timeout,
)
devlib_excluded_modules = set(devlib_excluded_modules)
# Sorry, can't let you do that. Messing with cgroups in a systemd
# system is pretty bad idea.
if self._uses_systemd:
logger.warning('Will not load cgroups devlib module: target is using systemd, which already uses cgroups')
devlib_excluded_modules.add('cgroups')
self._devlib_loadable_modules = _DEVLIB_AVAILABLE_MODULES - devlib_excluded_modules
# Initialize binary tools to deploy
if tools:
logger.info(f'Tools to install: {tools}')
self.install_tools(tools)
# Autodetect information from the target, after the Target is
# initialized. Expensive computations are deferred so they will only be
# computed when actually needed.
rta_calib_res_dir = ArtifactPath.join(self._res_dir, 'rta_calib')
os.makedirs(rta_calib_res_dir)
self.plat_info.add_target_src(self, rta_calib_res_dir, deferred=lazy_platinfo, fallback=True)
logger.info(f'Effective platform information:\n{self.plat_info}')
@property
@memoized
def _uses_systemd(self):
try:
# Check if systemd is being used, according to:
# https://www.freedesktop.org/software/systemd/man/sd_booted.html
self.execute('test -d /run/systemd/system/', check_exit_code=True)
except TargetStableError:
return False
else:
return True
def is_module_available(self, module):
"""
Check if the given devlib module is available.
:returns: ``True`` if module is available, ``False`` otherwise.
:param module: Devlib module to check.
:type module: str
.. note:: This will attempt to load the module if it's not loaded
already, and bail out if it fails to load.
"""
if module not in _DEVLIB_AVAILABLE_MODULES:
raise ValueError(f'"{module}" is not a devlib module')
try:
getattr(self, module)
except Exception: # pylint: disable=broad-except
return False
else:
return True
def __getattr__(self, attr):
"""
Forward all non-overriden attributes/method accesses to the underlying
:class:`devlib.target.Target`.
.. note:: That will not forward special methods like __str__, since the
interpreter bypasses __getattr__ when looking them up.
.. note:: Devlib modules are loaded on demand when accessed.
"""
def get():
return getattr(self.target, attr)
try:
return get()
except AttributeError:
# Load the module on demand
if attr in self._devlib_loadable_modules:
self.get_logger().info(f'Loading target devlib module {attr}')
self.target.install_module(attr)
return get()
# If it was not in the loadable list, it
# has been excluded explicitly
elif attr in _DEVLIB_AVAILABLE_MODULES:
# pylint: disable=raise-missing-from
raise AttributeError(f'Devlib target module {attr} was explicitly excluded, not loading it')
# Something else that does not exist ...
else:
raise
def __dir__(self):
"""
List our attributes plus the ones from the underlying target, and the
devlib modules that could be loaded on-demand.
"""
attrs = set(super().__dir__()) | set(dir(self.target)) | self._devlib_loadable_modules
return sorted(attrs)
@classmethod
def from_conf(cls, conf: TargetConf, res_dir: ArtifactPath = None, plat_info: PlatformInfo = None) -> 'Target':
cls.get_logger().info(f'Target configuration:\n{conf}')
kwargs = cls.conf_to_init_kwargs(conf)
kwargs['res_dir'] = res_dir
kwargs['plat_info'] = plat_info
# Create a devlib Platform instance out of the configuration file
devlib_platform_conf = conf['devlib']['platform']
devlib_platform_cls = resolve_dotted_name(devlib_platform_conf['class'])
devlib_platform_kwargs = copy.copy(devlib_platform_conf.get('args', {}))
# Hack for Gem5 devlib Platform, that requires a "host_output_dir"
# argument computed at runtime.
# Note: lisa.target.Gem5SimulationPlatformWrapper should be used instead
# of the original one to benefit from mapping configuration
if issubclass(devlib_platform_cls, Gem5SimulationPlatform):
devlib_platform_kwargs.setdefault('host_output_dir', res_dir)
# Actually build the devlib Platform object
devlib_platform = devlib_platform_cls(**devlib_platform_kwargs)
kwargs['devlib_platform'] = devlib_platform
cls.check_init_param(**kwargs)
return cls(**kwargs)
@classmethod
def from_default_conf(cls):
"""
Create a :class:`Target` from the YAML configuration file pointed by
``LISA_CONF`` environment variable.
.. note:: Only load trusted YAML files as it can lead to abritrary code
execution.
"""
path = os.environ['LISA_CONF']
return cls.from_one_conf(path)
@classmethod
def from_one_conf(cls, path):
"""
Create a :class:`Target` from a single YAML configuration file.
This file will be used to provide a :class:`TargetConf` and
:class:`lisa.platforms.platinfo.PlatformInfo` instances.
.. note:: Only load trusted YAML files as it can lead to abritrary code
execution.
"""
conf = TargetConf.from_yaml_map(path)
try:
plat_info = PlatformInfo.from_yaml_map(path)
except Exception as e: # pylint: disable=broad-except
cls.get_logger().warning(f'No platform information could be found: {e}')
plat_info = None
return cls.from_conf(conf=conf, plat_info=plat_info)
@classmethod
# Keep the signature without *args and **kwargs so that it's usable by exekall
def from_cli(cls, argv=None, params=None) -> 'Target':
"""
Same as :meth:`from_custom_cli` without the custom parameters
capabilities.
:return: A connected :class:`Target`
"""
_, target = cls.from_custom_cli(argv=argv, params=params)
return target
@classmethod
def from_custom_cli(cls, argv=None, params=None):
"""
Create a Target from command line arguments.
:param argv: The list of arguments. ``sys.argv[1:]`` will be used if
this is ``None``.
:type argv: list(str)
:param params: Dictionary of custom parameters to add to the parser. It
is in the form of
``{param_name: {dict of ArgumentParser.add_argument() options}}``.
:type params: dict(str, dict)
:return: A tuple ``(args, target)``
.. note:: This method should not be relied upon to implement long-term
scripts, it's more designed for quick scripting.
"""
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description=textwrap.dedent(
"""
Connect to a target using the provided configuration in order
to run a test.
EXAMPLES
--conf can point to a YAML target configuration file
with all the necessary connection information:
$ {script} --conf my_target.yml
Alternatively, --kind must be set along the relevant credentials:
$ {script} --kind linux --host 192.0.2.1 --username root --password <PASSWORD>
In both cases, --conf can also contain a PlatformInfo YAML description.
Note: only load trusted YAML files as it can lead to abritrary
code execution.
""".format(
script=os.path.basename(sys.argv[0])
)))
parser.add_argument("--conf", '-c',
help="Path to a TargetConf and PlatformInfo yaml file. Other options will override what is specified in the file."
)
parser.add_argument("--kind", "-k",
choices=["android", "linux", "host"],
help="The kind of target to connect to.")
device_group = parser.add_mutually_exclusive_group()
device_group.add_argument("--device", "-d",
help="The ADB ID of the target. Superseeds --host. Only applies to Android kind.")
device_group.add_argument("--host", "-n",
help="The hostname/IP of the target.")
parser.add_argument("--username", "-u",
help="Login username. Only applies to Linux kind.")
parser.add_argument("--password", <PASSWORD>",
help="Login password. Only applies to Linux kind.")
parser.add_argument("--log-level",
default='info',
choices=('warning', 'info', 'debug'),
help="Verbosity level of the logs.")
parser.add_argument("--res-dir", "-o",
help="Result directory of the created Target. If no directory is specified, a default location under $LISA_HOME will be used.")
params = params or {}
for param, settings in params.items():
parser.add_argument(f'--{param}', **settings)
custom_params = {k.replace('-', '_') for k in params.keys()}
# Options that are not a key in TargetConf must be listed here
not_target_conf_opt = {
'platform_info', 'log_level', 'res_dir', 'conf',
}
not_target_conf_opt.update(custom_params)
args = parser.parse_args(argv)
setup_logging(level=args.log_level.upper())
target_conf = TargetConf()
platform_info = None
if args.conf:
# Tentatively load a PlatformInfo from the conf file
with contextlib.suppress(KeyError, ValueError):
platform_info = PlatformInfo.from_yaml_map(args.conf)
# Load the TargetConf from the file, and update it with command
# line arguments
try:
conf = TargetConf.from_yaml_map(args.conf)
except (KeyError, ValueError):
pass
else:
target_conf.add_src(args.conf, conf)
target_conf.add_src('command-line', {
k: v for k, v in vars(args).items()
if v is not None and k not in not_target_conf_opt
})
# Some sanity check to get better error messages
if 'kind' not in target_conf:
parser.error('--conf with target configuration or any of the connection options is required')
if args.kind == 'android':
if ('host' not in target_conf) and ('device' not in target_conf):
parser.error('--host or --device must be specified')
if args.kind == 'linux':
for required in ['host', 'username', 'password']:
if required not in target_conf:
parser.error(f'--{required} must be specified')
custom_args = {
param: value
for param, value in vars(args).items()
if param in custom_params
}
custom_args = argparse.Namespace(**custom_args)
return custom_args, cls.from_conf(conf=target_conf, plat_info=platform_info, res_dir=args.res_dir)
def _init_target(self, kind, name, workdir, device, host,
port, username, password, keyfile, strict_host_check, use_scp,
devlib_platform,
wait_boot, wait_boot_timeout,
):
"""
Initialize the Target
"""
logger = self.get_logger()
conn_settings = {}
resolved_username = username or 'root'
logger.debug(f'Setting up {kind} target...')
# If the target is Android, we need just (eventually) the device
if kind == 'android':
devlib_target_cls = devlib.AndroidTarget
# Workaround for ARM-software/devlib#225
workdir = workdir or '/data/local/tmp/devlib-target'
if device:
pass
elif host:
port = port or self.ADB_PORT_DEFAULT
device = f'{host}:{port}'
else:
device = 'DEFAULT'
conn_settings['device'] = device
# If the username was explicitly set to "root", root the target as
# early as possible
conn_settings['adb_as_root'] = (username == 'root')
elif kind == 'linux':
devlib_target_cls = devlib.LinuxTarget
conn_settings.update(
username=resolved_username,
port=port or self.SSH_PORT_DEFAULT,
host=host,
strict_host_check=True if strict_host_check is None else strict_host_check,
use_scp=False if use_scp is None else use_scp,
)
# Configure password or SSH keyfile
if keyfile:
conn_settings['keyfile'] = keyfile
else:
conn_settings['password'] = password
elif kind == 'host':
devlib_target_cls = devlib.LocalLinuxTarget
# If we are given a password, assume we can use it as a sudo
# password.
conn_settings.update(
unrooted=password is None,
password=password,
)
else:
raise ValueError(f'Unsupported platform type {kind}')
settings = '\n '.join(
f' {key}: {val}'
for key, val in conn_settings.items()
if key != 'password'
)
logger.debug(f'{kind} {name} target connection settings:\n {settings}')
########################################################################
# Devlib Platform configuration
########################################################################
if not devlib_platform:
devlib_platform = devlib.platform.Platform()
########################################################################
# Create devlib Target object
########################################################################
target = devlib_target_cls(
platform=devlib_platform,
load_default_modules=False,
connection_settings=conn_settings,
working_directory=workdir,
connect=False,
)
target.connect(check_boot_completed=wait_boot, timeout=wait_boot_timeout)
# None as username means adb root will be attempted, but failure will
# not prevent from connecting to the target.
if kind == 'android' and username is None:
try:
target.adb_root(enable=True)
except Exception as e: # pylint: disable=broad-except
logger.warning(f'"adb root" failed: {e}')
logger.debug(f'Target info: {dict(abi=target.abi, cpuinfo=target.cpuinfo, workdir=target.working_directory)}')
target.setup()
logger.info(f"Connected to target {(name or '')}")
return target
def get_res_dir(self, name=None, append_time=True, symlink=True):
"""
Returns a directory managed by LISA to store results.
Usage of that function is reserved to interactive use or simple scripts.
Tests should not rely on that as the created folder will not be tracked
by any external entity, which means the results will be lost in some
automated environment.
:param name: Name of the results directory
:type name: str
:param append_time: If True, the current datetime will be appended to
the given ``name``. If ``name`` is None, the directory name will be
the current datetime.
:type append_time: bool
:param symlink: Create a symlink named ``results_latest`` to the newly
created results directory
:type symlink: bool
"""
if isinstance(self._res_dir, ArtifactPath):
root = self._res_dir.root
relative = self._res_dir.relative
else:
root = self._res_dir
relative = ''
return self._get_res_dir(
root=root,
relative=relative,
name=name,
append_time=append_time,
symlink=symlink,
)
def _get_res_dir(self, root, relative, name, append_time, symlink):
logger = self.get_logger()
while True:
time_str = datetime.now().strftime('%Y%m%d_%H%M%S.%f')
if not name:
name = time_str
elif append_time:
name = f"{name}-{time_str}"
# If we were given an ArtifactPath with an existing root, we
# preserve that root so it can be relocated as the caller wants it
res_dir = ArtifactPath(root, os.path.join(relative, name))
# Compute base installation path
logger.info(f'Creating result directory: {res_dir}')
# It will fail if the folder already exists. In that case,
# append_time should be used to ensure we get a unique name.
try:
os.makedirs(res_dir)
break
except FileExistsError:
# If the time is used in the name, there is some hope that the
# next time it will succeed
if append_time:
logger.info('Directory already exists, retrying ...')
continue
else:
raise
if symlink:
res_lnk = os.path.join(LISA_HOME, LATEST_LINK)
with contextlib.suppress(FileNotFoundError):
os.remove(res_lnk)
# There may be a race condition with another tool trying to create
# the link
with contextlib.suppress(FileExistsError):
os.symlink(res_dir, res_lnk)
return res_dir
def install_tools(self, tools):
"""
Install tools additional to those specified in the test config 'tools'
field
:param tools: The list of names of tools to install
:type tools: list(str)
"""
def bin_path(tool):
binary = os.path.join(ASSETS_PATH, 'binaries', self.abi, tool)
if not os.path.isfile(binary):
binary = os.path.join(ASSETS_PATH, 'binaries', 'scripts', tool)
return binary
tools = set(tools) - self._installed_tools
# TODO: compute the checksum of the tool + install location and keep
# that in _installed_tools, so we are sure to be correct
for tool in map(bin_path, tools):
self.target.install(tool)
self._installed_tools.add(tool)
@contextlib.contextmanager
def freeze_userspace(self):
"""
Context manager that lets you freeze the userspace.
.. note:: A number of situations prevent from freezing anything. When
that happens, a warning is logged but no exception is raised, so
it's a best-effort approach.
"""
logger = self.get_logger()
if not self.is_rooted:
logger.warning('Could not freeze userspace: target is not rooted')
cm = nullcontext
elif not self.is_module_available('cgroups'):
logger.warning('Could not freeze userspace: "cgroups" devlib module is necessary')
cm = nullcontext
else:
controllers = [s.name for s in self.cgroups.list_subsystems()]
if 'freezer' not in controllers:
logger.warning('Could not freeze userspace: freezer cgroup controller not available on the target')
cm = nullcontext
else:
exclude = copy.copy(self.CRITICAL_TASKS[self.target.os])
# Do not freeze the process in charge of de-freezing, otherwise we
# will freeze to death and a machine hard reboot will be required
if isinstance(self.target, devlib.LocalLinuxTarget):
exclude.append(str(os.getpid()))
@contextlib.contextmanager
def cm():
logger.info(f"Freezing all tasks except: {','.join(exclude)}")
try:
yield self.cgroups.freeze(exclude)
finally:
logger.info('Un-freezing userspace tasks')
self.cgroups.freeze(thaw=True)
with cm() as x:
yield x
@contextlib.contextmanager
def disable_idle_states(self):
"""
Context manager that lets you disable all idle states
"""
logger = self.get_logger()
logger.info('Disabling idle states for all domains')
try:
cpuidle = self.cpuidle
except AttributeError:
logger.warning('Could not disable idle states, cpuidle devlib module is not loaded')
cm = nullcontext
else:
@contextlib.contextmanager
def cm():
try:
for cpu in range(self.plat_info['cpus-count']):
cpuidle.disable_all(cpu)
yield
finally:
logger.info('Re-enabling idle states for all domains')
for cpu in range(self.plat_info['cpus-count']):
cpuidle.enable_all(cpu)
with cm() as x:
yield x
def get_tags(self):
return {'board': self.name}
@classmethod
def _make_remote_snippet(cls, name, code_str, module, kwargs, global_vars, out_tempfiles):
# Inject the parameters inside the wrapper's globals so that it can
# access them. It's harmless as they would shadow any global name
# anyway, and it's restricted to the wrapper using eval()
global_vars = {
**global_vars,
**kwargs,
}
# Treat the modules separately as they cannot be pickled
modules = {
name: mod
for name, mod in global_vars.items()
if isinstance(mod, ModuleType)
}
def can_include(f):
return (
isinstance(f, FunctionType) and
# Only allow inlining of functions defined in the same module so that:
# 1. there is no name clash risk
# 2. we don't inline the whole world, which could lead to a
# number of problems that could appear after another module
# is updated or so. We only inline local things that are in
# direct control
f.__module__ == module
)
def add_func(f, name):
# Disallow decorated functions since their definition depends on
# external callable we cannot control
if hasattr(f, '__wrapped__'):
raise TypeError('Decorated functions cannot be called from remote functions')
closure_vars = {
name: val
for var_dct in inspect.getclosurevars(f)
if isinstance(var_dct, Mapping)
for name, val in var_dct.items()
}
funcs[name] = (f, cls._get_code(f)[1])
for _name, _f in closure_vars.items():
if _f is not f and can_include(_f):
add_func(_f, _name)
modules.update(
(name, mod)
for name, mod in closure_vars.items()
if isinstance(mod, ModuleType)
)
funcs = {}
for f_name, f in global_vars.items():
if can_include(f):
add_func(f, f_name)
code_str += '\n' + '\n'.join(map(itemgetter(1), funcs.values()))
non_pickled = set(modules.keys()) | set(funcs.keys())
global_vars = {
name: val
for name, val in global_vars.items()
if name not in non_pickled
}
if modules:
modules = f"import {', '.join(sorted(modules))}"
else:
modules = ''
script = textwrap.dedent('''
import pickle
import sys
def wrapper():
{modules}
{code}
return {f}({kwargs})
try:
out = eval(wrapper.__code__, pickle.loads({globals}))
except BaseException as e:
out = e
out_is_excep = True
else:
out_is_excep = False
out = pickle.dumps(out)
out_tempfile = {out_tempfiles}[1] if out_is_excep else {out_tempfiles}[0]
with open(out_tempfile, 'wb') as f:
f.write(out)
''').format(
f=name,
code=textwrap.dedent(code_str).replace('\n', '\n' + ' ' * 4),
modules=modules,
out_tempfiles=repr(out_tempfiles),
globals=repr(pickle.dumps(global_vars)),
kwargs=', '.join(
f'{name}={name}'
for name in kwargs.keys()
)
)
return script
@staticmethod
def _get_code(f):
lines, _ = inspect.getsourcelines(f)
# Remove decorators, as they are either undefined or just were used to
# feed the function to us
lines = [
line
for line in lines
if not line.strip().startswith('@')
]
code_str = textwrap.dedent(''.join(lines))
name = f.__name__
return (name, code_str)
def execute_python(self, f, args, kwargs, **execute_kwargs):
"""
Executes the given Python function ``f`` with the provided positional
and keyword arguments.
The return value or any exception is pickled back and is
returned/raised in the host caller.
:Variable keyword arguments: Forwarded to :meth:`execute` that
will spawn the Python interpreter on the target
.. note:: Closure variables are supported, but mutating them will not
be reflected in the caller's context. Also, functions that are
referred to will be:
* bundled in the script if it is defined in the same module
* referred to by name, assuming it comes from a module that is
installed on the target and that this module is in scope. If
that is not the case, a :exc:`NameError` will be raised.
.. attention:: Decorators are ignored and not applied.
"""
sig = inspect.signature(f)
kwargs = sig.bind(*args, **kwargs).arguments
closure_vars = inspect.getclosurevars(f)
name, code_str = self._get_code(f)
def mktemp():
return self.execute(
f'mktemp -p {shlex.quote(self.working_directory)}'
).strip()
def read_output(path):
with tempfile.TemporaryDirectory() as d:
name = os.path.join(d, 'out')
self.pull(path, name)
with open(name, 'rb') as f:
return pickle.loads(f.read())
def parse_output(paths, err):
val, excep = paths
try:
return read_output(val)
# If the file is empty, we probably got an exception
except EOFError:
# pylint: disable=raise-missing-from
try:
excep = read_output(excep)
# If we can't even read the exception, raise the initial one
# from devlib
except EOFError:
raise err if err is not None else ValueError('No exception was raised or value returned by the function')
else:
raise excep
out_tempfiles = tuple()
try:
out_tempfiles = (mktemp(), mktemp())
snippet = self._make_remote_snippet(
name=name,
code_str=code_str,
module=f.__module__,
kwargs=kwargs,
global_vars={
**closure_vars.globals,
**closure_vars.nonlocals,
},
out_tempfiles=out_tempfiles
)
cmd = ['python3', '-c', snippet]
cmd = ' '.join(map(shlex.quote, cmd))
try:
self.execute(cmd, **execute_kwargs)
except Exception as e: # pylint: disable=broad-except
err = e
else:
err = None
return parse_output(out_tempfiles, err)
finally:
for path in out_tempfiles:
self.remove(path)
def remote_func(self, **kwargs):
"""
Decorates a given function to execute remotely using
:meth:`execute_python`::
target = Target(...)
@target.remote_func(timeout=42)
def foo(x, y):
return x + y
# Execute the function on the target transparently
val = foo(1, y=2)
:Variable keyword arguments: Forwarded to :meth:`execute` that
will spawn the Python interpreter on the target
"""
def wrapper_param(f):
@functools.wraps(f)
def wrapper(*f_args, **f_kwargs):
return self.execute_python(f, f_args, f_kwargs, **kwargs)
return wrapper
return wrapper_param
class Gem5SimulationPlatformWrapper(Gem5SimulationPlatform):
def __init__(self, system, simulator, **kwargs):
simulator_args = copy.copy(simulator.get('args', []))
system_platform = system['platform']
# Get gem5 binary arguments
simulator_args.append('--listener-mode=on')
simulator_args.append(system_platform['description'])
simulator_args.extend(system_platform.get('args', []))
simulator_args.extend((
f"--kernel {system['kernel']}",
f"--dtb {system['dtb']}",
f"--disk-image {system['disk']}"
))
diod_path = which('diod')
if diod_path is None:
raise RuntimeError('Failed to find "diod" on your host machine, check your installation or your PATH variable')
# Setup virtio
# Brackets are there to let the output dir be created automatically
virtio_args = [
f'--which-diod={diod_path}',
'--workload-automation-vio={}',
]
simulator_args.extend(virtio_args)
# Quote/escape arguments and build the command line
gem5_args = ' '.join(shlex.quote(a) for a in simulator_args)
super().__init__(
gem5_args=gem5_args,
gem5_bin=simulator['bin'],
**kwargs
)
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8069,
29889,
5527,
1053,
12545,
15329,
29903,
2214,
16376,
29892,
7670,
19617,
29892,
21597,
2558,
19617,
29892,
7488,
10108,
2558,
19617,
29892,
3991,
21115,
13,
3166,
301,
8069,
29889,
19206,
1053,
14213,
287,
1293,
13,
13,
3166,
301,
8069,
29889,
12120,
29879,
29889,
572,
271,
3888,
1053,
28096,
3401,
13,
13,
13,
1990,
25280,
2558,
19617,
29898,
2558,
19617,
1125,
13,
1678,
822,
5051,
29918,
4830,
29898,
1311,
29892,
325,
1125,
13,
4706,
736,
12801,
5630,
16299,
13,
13,
13,
29937,
8561,
1854,
599,
1014,
7576,
310,
2906,
1982,
29889,
5453,
526,
19673,
577,
278,
4413,
13,
29937,
526,
599,
2825,
1434,
591,
1051,
963,
13,
5215,
29918,
497,
29918,
1491,
7576,
29898,
3359,
1982,
29889,
5453,
29897,
13,
29918,
2287,
29963,
5265,
29933,
29918,
26612,
6227,
6181,
29918,
6720,
14849,
17101,
353,
426,
13,
1678,
1067,
29879,
29889,
978,
13,
1678,
363,
1067,
29879,
297,
679,
29918,
1491,
13203,
29898,
3359,
1982,
29889,
5453,
29889,
7355,
29897,
13,
1678,
565,
313,
13,
4706,
679,
5552,
29898,
25932,
29892,
525,
978,
742,
6213,
29897,
13,
4706,
396,
4688,
10585,
1018,
304,
4511,
304,
501,
8322,
322,
437,
1407,
13,
4706,
396,
7481,
29899,
14940,
2712,
591,
526,
451,
8852,
297,
13,
4706,
322,
679,
5552,
29898,
25932,
29892,
525,
19190,
1495,
2804,
525,
799,
368,
29915,
13,
1678,
1723,
13,
29913,
13,
13,
13,
1990,
17157,
16376,
29898,
15427,
15329,
29903,
2214,
16376,
29892,
379,
680,
1252,
1416,
497,
1367,
1125,
13,
1678,
9995,
13,
1678,
17157,
3957,
6055,
29889,
13,
13,
1678,
9333,
6611,
3342,
2400,
526,
6068,
29892,
411,
278,
2183,
6593,
322,
1134,
29901,
13,
13,
1678,
426,
13525,
29918,
8477,
29913,
13,
13,
1678,
530,
2777,
508,
367,
2825,
491,
5432,
584,
1990,
18078,
30022,
8667,
16376,
29952,
411,
263,
13,
1678,
8600,
29889,
450,
2246,
29899,
5563,
421,
5182,
29899,
5527,
29952,
1820,
338,
451,
4312,
1244,
29901,
13,
13,
1678,
6317,
775,
29899,
1271,
1057,
3017,
13,
13,
4706,
17157,
16376,
3319,
29912,
13,
9651,
525,
978,
2396,
525,
1357,
3377,
742,
13,
9651,
525,
3069,
2396,
29871,
29896,
29929,
29906,
29889,
29900,
29889,
29906,
29889,
29896,
29892,
13,
9651,
525,
14380,
2396,
525,
9389,
742,
13,
9651,
525,
6786,
2396,
525,
5431,
742,
13,
9651,
525,
5630,
2396,
12801,
25711,
17013,
29958,
742,
13,
4706,
500,
1800,
13,
13,
1678,
1394,
5136,
6703,
29892,
515,
263,
612,
23956,
5285,
934,
29901,
13,
13,
1678,
10576,
310,
3646,
29918,
5527,
29889,
21053,
29901,
13,
13,
1678,
6317,
16333,
2856,
1057,
29772,
5182,
29918,
5527,
29889,
21053,
13,
4706,
584,
11675,
29901,
612,
23956,
13,
13,
1678,
4761,
13,
13,
4706,
17157,
16376,
29889,
3166,
29918,
25162,
29918,
1958,
877,
5182,
29918,
5527,
29889,
21053,
1495,
13,
13,
13,
1678,
450,
1494,
4266,
612,
23956,
8282,
508,
367,
1304,
297,
278,
5285,
934,
29901,
13,
13,
1678,
6317,
775,
29899,
1271,
1057,
612,
23956,
13,
13,
4706,
3646,
29899,
5527,
29901,
13,
9651,
396,
376,
29991,
6272,
29901,
29966,
1853,
29958,
12524,
29963,
29918,
26865,
29918,
5813,
29908,
508,
367,
1304,
304,
3407,
385,
13,
9651,
396,
5177,
2286,
29889,
13,
9651,
1024,
29901,
1738,
6272,
29901,
710,
16437,
17011,
29918,
5813,
13,
9651,
2011,
29901,
1738,
6272,
29901,
524,
349,
8476,
13,
13,
1678,
6317,
4443,
1057,
9333,
2254,
9311,
287,
612,
23956,
2066,
408,
372,
508,
3275,
304,
633,
768,
29878,
653,
775,
13,
4706,
8225,
29889,
13,
13,
1678,
6317,
4443,
1057,
2193,
3829,
297,
263,
612,
23956,
934,
338,
6068,
322,
674,
664,
29901,
13,
13,
4706,
334,
934,
7953,
29889,
21053,
1057,
13,
13,
9651,
3646,
29899,
5527,
29901,
13,
18884,
1024,
29901,
590,
3377,
13,
13,
4706,
334,
934,
2594,
29889,
21053,
1057,
13,
13,
9651,
3646,
29899,
5527,
29901,
13,
18884,
1738,
2856,
7953,
29889,
21053,
13,
13,
4706,
910,
674,
1121,
297,
393,
3829,
607,
723,
12891,
367,
8340,
29892,
541,
13,
4706,
338,
16459,
408,
263,
4266,
1206,
1057,
13,
13,
9651,
3646,
29899,
5527,
29901,
13,
18884,
3646,
29899,
5527,
29901,
13,
462,
1678,
1024,
29901,
590,
3377,
13,
1678,
9995,
13,
13,
1678,
29486,
29965,
1783,
11499,
353,
7488,
10108,
2558,
19617,
877,
5182,
29899,
5527,
742,
525,
5182,
3957,
6055,
742,
313,
13,
4706,
7670,
19617,
877,
978,
742,
525,
28397,
1024,
29892,
3889,
29899,
689,
995,
871,
1304,
304,
953,
6596,
728,
10748,
742,
518,
710,
11724,
13,
4706,
7670,
19617,
877,
14380,
742,
525,
8667,
2924,
29889,
1815,
367,
376,
9389,
29908,
313,
15269,
29897,
470,
376,
2843,
29908,
313,
328,
29890,
29897,
742,
518,
710,
11724,
13,
13,
4706,
7670,
19617,
877,
3069,
742,
525,
8514,
978,
470,
5641,
3211,
310,
278,
3495,
742,
518,
710,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
6786,
742,
525,
1799,
29950,
8952,
29889,
1551,
319,
4051,
12368,
29892,
376,
4632,
29908,
8952,
674,
3876,
594,
29890,
2501,
3646,
3957,
742,
518,
710,
29892,
6213,
11724,
13,
4706,
25280,
2558,
19617,
877,
5630,
742,
525,
1799,
29950,
4800,
742,
518,
710,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
637,
742,
525,
1799,
29950,
470,
319,
4051,
1923,
2011,
742,
518,
524,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
10141,
742,
525,
3035,
29933,
4742,
29889,
323,
6926,
9399,
663,
975,
376,
3069,
29908,
742,
518,
710,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
1989,
1445,
742,
525,
1799,
29950,
2024,
1820,
934,
742,
518,
710,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
710,
919,
29899,
3069,
29899,
3198,
742,
525,
6108,
27445,
304,
3767,
919,
8514,
2558,
5596,
292,
2984,
310,
4673,
1799,
29950,
742,
518,
11227,
29892,
6213,
11724,
13,
4706,
7670,
19617,
877,
1287,
3972,
742,
525,
20224,
3646,
664,
3972,
742,
518,
710,
11724,
13,
4706,
7670,
19617,
877,
8504,
742,
525,
1293,
310,
8492,
304,
2601,
373,
278,
3646,
742,
518,
24933,
287,
1293,
29961,
710,
5262,
511,
13,
4706,
7670,
19617,
877,
433,
1537,
29899,
572,
271,
3888,
742,
525,
29931,
834,
2354,
1120,
356,
312,
278,
7481,
2472,
304,
6210,
701,
278,
3957,
742,
518,
11227,
11724,
13,
4706,
21597,
2558,
19617,
877,
10685,
29899,
4777,
742,
525,
15716,
363,
278,
3646,
304,
8341,
6579,
292,
742,
313,
13,
9651,
7670,
19617,
877,
12007,
742,
525,
20701,
278,
6579,
1423,
742,
518,
11227,
11724,
13,
9651,
7670,
19617,
877,
15619,
742,
525,
10851,
310,
278,
6579,
1423,
742,
518,
524,
11724,
13,
4706,
1723,
511,
13,
4706,
21597,
2558,
19617,
877,
3359,
1982,
742,
525,
3359,
1982,
5285,
742,
313,
13,
9651,
396,
5293,
1426,
950,
1024,
310,
278,
28096,
6511,
445,
612,
23956,
5285,
13,
9651,
396,
304,
451,
671,
738,
3017,
29899,
14940,
612,
23956,
8282,
29892,
577,
17157,
16376,
2066,
508,
13,
9651,
396,
367,
21213,
322,
7371,
491,
738,
916,
4654,
29899,
22633,
775,
13,
9651,
21597,
2558,
19617,
877,
12120,
742,
525,
3359,
1982,
29889,
12120,
29889,
21889,
19481,
21992,
742,
313,
13,
18884,
7670,
19617,
877,
1990,
742,
525,
1170,
310,
278,
770,
304,
671,
742,
518,
710,
11724,
13,
18884,
7670,
19617,
877,
5085,
742,
525,
2558,
1742,
6273,
304,
2048,
278,
28096,
1203,
742,
518,
15845,
11724,
13,
9651,
1723,
511,
13,
9651,
7670,
19617,
877,
735,
13347,
29899,
7576,
742,
525,
1293,
310,
2906,
1982,
10585,
304,
334,
1333,
29930,
2254,
742,
518,
24933,
287,
1293,
29961,
710,
5262,
511,
13,
9651,
7670,
19617,
877,
1445,
29899,
29916,
571,
742,
525,
2283,
6782,
1158,
29889,
1815,
367,
376,
29879,
23102,
29908,
313,
4381,
29897,
470,
376,
1557,
29886,
1642,
313,
11730,
2854,
363,
10542,
22525,
29897,
742,
518,
24933,
287,
1293,
29961,
710,
5262,
511,
13,
13,
308,
876,
13,
268,
876,
13,
13,
1678,
22236,
29918,
29903,
10363,
353,
426,
13,
4706,
525,
3359,
1982,
2396,
426,
13,
9651,
525,
12120,
2396,
426,
13,
18884,
525,
1990,
2396,
525,
3359,
1982,
29889,
12120,
29889,
21889,
29915,
13,
9651,
500,
13,
4706,
500,
13,
1678,
500,
13,
13,
13,
1990,
17157,
29898,
3403,
29531,
29892,
379,
680,
1252,
1416,
497,
1367,
29892,
1222,
1416,
497,
8176,
29531,
29892,
12782,
21115,
1125,
13,
1678,
9995,
13,
1678,
399,
2390,
584,
1990,
18078,
3359,
1982,
29889,
5182,
29889,
8667,
29952,
304,
3867,
5684,
5680,
373,
2246,
310,
13,
1678,
372,
29889,
13,
13,
1678,
426,
2917,
21115,
29918,
7529,
29913,
13,
13,
1678,
584,
3207,
2906,
1982,
29918,
12120,
29901,
2799,
749,
310,
584,
1990,
18078,
3359,
1982,
29889,
12120,
29889,
21889,
29952,
304,
13,
4706,
671,
304,
2048,
278,
584,
1990,
18078,
3359,
1982,
29889,
5182,
29889,
8667,
29952,
13,
1678,
584,
1853,
2906,
1982,
29918,
12120,
29901,
2906,
1982,
29889,
12120,
29889,
21889,
13,
13,
1678,
584,
3207,
18870,
29918,
3888,
29901,
28096,
2472,
10959,
304,
445,
3646,
29892,
363,
278,
13,
4706,
23633,
310,
1404,
775,
29889,
13,
1678,
584,
1853,
18870,
29918,
3888,
29901,
301,
8069,
29889,
12120,
29879,
29889,
572,
271,
3888,
29889,
21889,
3401,
13,
13,
1678,
887,
817,
304,
3867,
278,
2472,
4312,
304,
4511,
304,
278,
13,
1678,
3646,
29889,
1152,
22343,
22525,
393,
2794,
376,
3069,
613,
376,
6786,
29908,
322,
13,
1678,
2845,
376,
5630,
29908,
470,
376,
1989,
1445,
1642,
2178,
916,
4235,
526,
13136,
565,
13,
1678,
278,
8018,
5680,
9455,
29915,
29873,
4312,
29889,
13,
13,
1678,
6317,
4443,
1057,
450,
28489,
310,
584,
1990,
18078,
3359,
1982,
29889,
5182,
29889,
8667,
29952,
338,
2309,
773,
13,
4706,
15259,
29892,
408,
15869,
304,
20328,
29889,
910,
6511,
2381,
20304,
278,
2684,
13,
4706,
770,
1304,
1090,
278,
298,
2092,
29892,
322,
4772,
29879,
4473,
292,
701,
411,
4954,
3359,
1982,
16159,
13,
4706,
7463,
5144,
29889,
13,
1678,
9995,
13,
13,
1678,
319,
4051,
29918,
15082,
29918,
23397,
353,
29871,
29945,
29945,
29945,
29945,
13,
1678,
22343,
29918,
15082,
29918,
23397,
353,
29871,
29906,
29906,
13,
13,
1678,
15600,
1806,
2965,
1964,
29918,
29911,
3289,
17557,
353,
426,
13,
4706,
525,
9389,
2396,
518,
13,
9651,
525,
2344,
742,
13,
9651,
396,
1334,
864,
304,
3889,
911,
4129,
5174,
349,
1367,
29871,
29896,
29892,
591,
1016,
29915,
29873,
864,
304,
1235,
13,
9651,
396,
10876,
4378,
287,
29899,
29926,
2905,
2741,
470,
1788,
29881,
29899,
3706,
948,
2252,
2734,
29889,
13,
9651,
525,
5205,
29881,
29961,
21583,
29962,
742,
13,
9651,
525,
2585,
375,
742,
13,
9651,
525,
845,
742,
13,
9651,
525,
15269,
742,
13,
9651,
525,
2288,
952,
1188,
29881,
742,
13,
9651,
525,
29926,
6448,
29906,
29915,
13,
4706,
21251,
13,
4706,
525,
2843,
2396,
518,
13,
9651,
525,
845,
742,
525,
328,
6448,
742,
13,
9651,
525,
28685,
742,
525,
27882,
742,
13,
9651,
396,
1334,
1016,
29915,
29873,
2869,
817,
445,
3414,
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13,
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7865,
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367,
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13,
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565,
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3888,
338,
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13,
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29918,
3888,
353,
28096,
3401,
580,
13,
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1683,
29901,
13,
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396,
8561,
263,
3509,
310,
278,
28096,
3401,
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6623,
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13,
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3888,
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27392,
877,
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451,
2254,
274,
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1982,
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29901,
3646,
338,
773,
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607,
2307,
3913,
274,
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13,
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1982,
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13,
13,
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1982,
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1359,
519,
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7576,
353,
903,
2287,
29963,
5265,
29933,
29918,
26612,
6227,
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6720,
14849,
17101,
448,
2906,
1982,
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735,
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7576,
13,
13,
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7581,
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304,
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13,
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13,
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304,
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13,
13,
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397,
300,
522,
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515,
278,
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278,
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338,
13,
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800,
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316,
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577,
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674,
871,
367,
13,
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13,
13,
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364,
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353,
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316,
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573,
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13,
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4928,
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13,
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13,
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9995,
13,
4706,
5399,
565,
278,
2183,
2906,
1982,
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338,
3625,
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13,
13,
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18280,
29901,
4954,
5574,
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565,
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3625,
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4954,
8824,
16159,
6467,
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13,
13,
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3207,
3883,
29901,
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1982,
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304,
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13,
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29901,
851,
13,
13,
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910,
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304,
2254,
278,
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322,
289,
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297,
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26612,
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6720,
14849,
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13,
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12020,
7865,
2392,
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11838,
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5038,
338,
451,
263,
2906,
1982,
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1495,
13,
13,
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1018,
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13,
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679,
5552,
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13,
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13,
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13,
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599,
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957,
2429,
264,
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29914,
5696,
2130,
267,
304,
278,
14407,
13,
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1990,
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3359,
1982,
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5182,
29889,
8667,
1412,
13,
13,
4706,
6317,
4443,
1057,
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674,
451,
6375,
4266,
3519,
763,
4770,
710,
1649,
29892,
1951,
278,
13,
9651,
26997,
491,
3364,
267,
4770,
657,
5552,
1649,
746,
3063,
963,
701,
29889,
13,
13,
4706,
6317,
4443,
1057,
9481,
1982,
10585,
526,
7500,
373,
9667,
746,
20592,
29889,
13,
4706,
9995,
13,
13,
4706,
822,
679,
7295,
13,
9651,
736,
679,
5552,
29898,
1311,
29889,
5182,
29892,
12421,
29897,
13,
13,
4706,
1018,
29901,
13,
9651,
736,
679,
580,
13,
4706,
5174,
23833,
2392,
29901,
13,
9651,
396,
16012,
278,
3883,
373,
9667,
13,
9651,
565,
12421,
297,
1583,
3032,
3359,
1982,
29918,
1359,
519,
29918,
7576,
29901,
13,
18884,
1583,
29889,
657,
29918,
21707,
2141,
3888,
29898,
29888,
29915,
23456,
3646,
2906,
1982,
3883,
426,
5552,
29913,
1495,
13,
18884,
1583,
29889,
5182,
29889,
6252,
29918,
5453,
29898,
5552,
29897,
13,
18884,
736,
679,
580,
13,
9651,
396,
960,
372,
471,
451,
297,
278,
2254,
519,
1051,
29892,
372,
13,
9651,
396,
756,
1063,
429,
13347,
9479,
13,
9651,
25342,
12421,
297,
903,
2287,
29963,
5265,
29933,
29918,
26612,
6227,
6181,
29918,
6720,
14849,
17101,
29901,
13,
18884,
396,
282,
2904,
524,
29901,
11262,
29922,
22692,
29899,
27259,
29899,
3166,
13,
18884,
12020,
23833,
2392,
29898,
29888,
29915,
16618,
1982,
3646,
3883,
426,
5552,
29913,
471,
9479,
429,
13347,
29892,
451,
8363,
372,
1495,
13,
9651,
396,
12538,
1683,
393,
947,
451,
1863,
2023,
13,
9651,
1683,
29901,
13,
18884,
12020,
13,
13,
1678,
822,
4770,
3972,
12035,
1311,
1125,
13,
4706,
9995,
13,
4706,
2391,
1749,
8393,
2298,
278,
6743,
515,
278,
14407,
3646,
29892,
322,
278,
13,
4706,
2906,
1982,
10585,
393,
1033,
367,
7500,
373,
29899,
2310,
392,
29889,
13,
4706,
9995,
13,
4706,
12421,
29879,
353,
731,
29898,
9136,
2141,
1649,
3972,
1649,
3101,
891,
731,
29898,
3972,
29898,
1311,
29889,
5182,
876,
891,
1583,
3032,
3359,
1982,
29918,
1359,
519,
29918,
7576,
13,
4706,
736,
12705,
29898,
5552,
29879,
29897,
13,
13,
1678,
732,
1990,
5696,
13,
1678,
822,
515,
29918,
5527,
29898,
25932,
29892,
1970,
29901,
17157,
16376,
29892,
620,
29918,
3972,
29901,
3012,
7060,
2605,
353,
6213,
29892,
18870,
29918,
3888,
29901,
28096,
3401,
353,
6213,
29897,
1599,
525,
8667,
2396,
13,
4706,
1067,
29879,
29889,
657,
29918,
21707,
2141,
3888,
29898,
29888,
29915,
8667,
5285,
3583,
29876,
29912,
5527,
29913,
1495,
13,
4706,
9049,
5085,
353,
1067,
29879,
29889,
5527,
29918,
517,
29918,
2344,
29918,
19290,
29898,
5527,
29897,
13,
4706,
9049,
5085,
1839,
690,
29918,
3972,
2033,
353,
620,
29918,
3972,
13,
4706,
9049,
5085,
1839,
572,
271,
29918,
3888,
2033,
353,
18870,
29918,
3888,
13,
13,
4706,
396,
6204,
263,
2906,
1982,
28096,
2777,
714,
310,
278,
5285,
934,
13,
4706,
2906,
1982,
29918,
12120,
29918,
5527,
353,
1970,
1839,
3359,
1982,
16215,
12120,
2033,
13,
13,
4706,
2906,
1982,
29918,
12120,
29918,
25932,
353,
8814,
29918,
29881,
15048,
29918,
978,
29898,
3359,
1982,
29918,
12120,
29918,
5527,
1839,
1990,
11287,
13,
4706,
2906,
1982,
29918,
12120,
29918,
19290,
353,
3509,
29889,
8552,
29898,
3359,
1982,
29918,
12120,
29918,
5527,
29889,
657,
877,
5085,
742,
6571,
876,
13,
13,
4706,
396,
379,
547,
363,
15170,
29945,
2906,
1982,
28096,
29892,
393,
6858,
263,
376,
3069,
29918,
4905,
29918,
3972,
29908,
13,
4706,
396,
2980,
15712,
472,
10073,
29889,
13,
4706,
396,
3940,
29901,
301,
8069,
29889,
5182,
29889,
29954,
331,
29945,
8942,
2785,
21889,
15646,
881,
367,
1304,
2012,
13,
4706,
396,
310,
278,
2441,
697,
304,
14169,
515,
10417,
5285,
13,
4706,
565,
338,
1491,
1990,
29898,
3359,
1982,
29918,
12120,
29918,
25932,
29892,
15170,
29945,
8942,
2785,
21889,
1125,
13,
9651,
2906,
1982,
29918,
12120,
29918,
19290,
29889,
842,
4381,
877,
3069,
29918,
4905,
29918,
3972,
742,
620,
29918,
3972,
29897,
13,
13,
4706,
396,
12823,
2048,
278,
2906,
1982,
28096,
1203,
13,
4706,
2906,
1982,
29918,
12120,
353,
2906,
1982,
29918,
12120,
29918,
25932,
29898,
1068,
3359,
1982,
29918,
12120,
29918,
19290,
29897,
13,
4706,
9049,
5085,
1839,
3359,
1982,
29918,
12120,
2033,
353,
2906,
1982,
29918,
12120,
13,
13,
4706,
1067,
29879,
29889,
3198,
29918,
2344,
29918,
3207,
29898,
1068,
19290,
29897,
13,
4706,
736,
1067,
29879,
29898,
1068,
19290,
29897,
13,
13,
1678,
732,
1990,
5696,
13,
1678,
822,
515,
29918,
4381,
29918,
5527,
29898,
25932,
1125,
13,
4706,
9995,
13,
4706,
6204,
263,
584,
1990,
18078,
8667,
29952,
515,
278,
612,
23956,
5285,
934,
11520,
491,
13,
4706,
4954,
29931,
3235,
29909,
29918,
6007,
29943,
16159,
5177,
2286,
29889,
13,
13,
4706,
6317,
4443,
1057,
9333,
2254,
9311,
287,
612,
23956,
2066,
408,
372,
508,
3275,
304,
633,
768,
29878,
653,
775,
13,
9651,
8225,
29889,
13,
4706,
9995,
13,
4706,
2224,
353,
2897,
29889,
21813,
1839,
29931,
3235,
29909,
29918,
6007,
29943,
2033,
13,
4706,
736,
1067,
29879,
29889,
3166,
29918,
650,
29918,
5527,
29898,
2084,
29897,
13,
13,
1678,
732,
1990,
5696,
13,
1678,
822,
515,
29918,
650,
29918,
5527,
29898,
25932,
29892,
2224,
1125,
13,
4706,
9995,
13,
4706,
6204,
263,
584,
1990,
18078,
8667,
29952,
515,
263,
2323,
612,
23956,
5285,
934,
29889,
13,
13,
4706,
910,
934,
674,
367,
1304,
304,
3867,
263,
584,
1990,
18078,
8667,
16376,
29952,
322,
13,
4706,
584,
1990,
18078,
29880,
8069,
29889,
12120,
29879,
29889,
572,
271,
3888,
29889,
21889,
3401,
29952,
8871,
29889,
13,
13,
4706,
6317,
4443,
1057,
9333,
2254,
9311,
287,
612,
23956,
2066,
408,
372,
508,
3275,
304,
633,
768,
29878,
653,
775,
13,
9651,
8225,
29889,
13,
4706,
9995,
13,
4706,
1970,
353,
17157,
16376,
29889,
3166,
29918,
25162,
29918,
1958,
29898,
2084,
29897,
13,
4706,
1018,
29901,
13,
9651,
18870,
29918,
3888,
353,
28096,
3401,
29889,
3166,
29918,
25162,
29918,
1958,
29898,
2084,
29897,
13,
4706,
5174,
8960,
408,
321,
29901,
396,
282,
2904,
524,
29901,
11262,
29922,
6729,
328,
29899,
19499,
13,
9651,
1067,
29879,
29889,
657,
29918,
21707,
2141,
27392,
29898,
29888,
29915,
3782,
7481,
2472,
1033,
367,
1476,
29901,
426,
29872,
29913,
1495,
13,
9651,
18870,
29918,
3888,
353,
6213,
13,
4706,
736,
1067,
29879,
29889,
3166,
29918,
5527,
29898,
5527,
29922,
5527,
29892,
18870,
29918,
3888,
29922,
572,
271,
29918,
3888,
29897,
13,
13,
1678,
732,
1990,
5696,
13,
1678,
396,
19152,
278,
12608,
1728,
334,
5085,
322,
3579,
19290,
577,
393,
372,
29915,
29879,
502,
519,
491,
429,
1416,
497,
13,
1678,
822,
515,
29918,
11303,
29898,
25932,
29892,
1852,
29894,
29922,
8516,
29892,
8636,
29922,
8516,
29897,
1599,
525,
8667,
2396,
13,
4706,
9995,
13,
4706,
19491,
408,
584,
29885,
621,
18078,
3166,
29918,
6341,
29918,
11303,
29952,
1728,
278,
2888,
4128,
13,
4706,
27108,
29889,
13,
13,
4706,
584,
2457,
29901,
319,
6631,
584,
1990,
18078,
8667,
29952,
13,
4706,
9995,
13,
4706,
17117,
3646,
353,
1067,
29879,
29889,
3166,
29918,
6341,
29918,
11303,
29898,
19218,
29922,
19218,
29892,
8636,
29922,
7529,
29897,
13,
4706,
736,
3646,
13,
13,
1678,
732,
1990,
5696,
13,
1678,
822,
515,
29918,
6341,
29918,
11303,
29898,
25932,
29892,
1852,
29894,
29922,
8516,
29892,
8636,
29922,
8516,
1125,
13,
4706,
9995,
13,
4706,
6204,
263,
17157,
515,
1899,
1196,
6273,
29889,
13,
13,
4706,
584,
3207,
1852,
29894,
29901,
450,
1051,
310,
6273,
29889,
4954,
9675,
29889,
19218,
29961,
29896,
29901,
7961,
29952,
674,
367,
1304,
565,
13,
3986,
445,
338,
4954,
8516,
29952,
1412,
13,
4706,
584,
1853,
1852,
29894,
29901,
1051,
29898,
710,
29897,
13,
13,
4706,
584,
3207,
8636,
29901,
13343,
310,
2888,
4128,
304,
788,
304,
278,
13812,
29889,
739,
13,
9651,
338,
297,
278,
883,
310,
13,
9651,
4954,
29912,
3207,
29918,
978,
29901,
426,
8977,
310,
23125,
11726,
29889,
1202,
29918,
23516,
580,
3987,
930,
29952,
1412,
13,
4706,
584,
1853,
8636,
29901,
9657,
29898,
710,
29892,
9657,
29897,
13,
13,
4706,
584,
2457,
29901,
319,
18761,
4954,
29898,
5085,
29892,
3646,
3569,
29952,
13,
13,
4706,
6317,
4443,
1057,
910,
1158,
881,
451,
367,
337,
2957,
2501,
304,
2334,
1472,
29899,
8489,
13,
9651,
12078,
29892,
372,
29915,
29879,
901,
8688,
363,
4996,
2471,
292,
29889,
13,
4706,
9995,
13,
4706,
13812,
353,
1852,
5510,
29889,
15730,
11726,
29898,
13,
9651,
883,
2620,
29918,
1990,
29922,
1191,
5510,
29889,
22131,
9868,
29648,
18522,
29892,
13,
9651,
6139,
29922,
726,
6312,
29889,
7176,
296,
29898,
13,
18884,
9995,
13,
18884,
14971,
304,
263,
3646,
773,
278,
4944,
5285,
297,
1797,
13,
18884,
304,
1065,
263,
1243,
29889,
13,
13,
18884,
8528,
19297,
17101,
13,
13,
18884,
1192,
5527,
508,
1298,
304,
263,
612,
23956,
3646,
5285,
934,
13,
18884,
411,
599,
278,
5181,
3957,
2472,
29901,
13,
18884,
395,
426,
2154,
29913,
1192,
5527,
590,
29918,
5182,
29889,
21053,
13,
13,
18884,
20360,
29892,
1192,
14380,
1818,
367,
731,
3412,
278,
8018,
16140,
29901,
13,
18884,
395,
426,
2154,
29913,
1192,
14380,
10542,
1192,
3069,
29871,
29896,
29929,
29906,
29889,
29900,
29889,
29906,
29889,
29896,
1192,
6786,
3876,
1192,
5630,
529,
25711,
17013,
29958,
13,
13,
18884,
512,
1716,
4251,
29892,
1192,
5527,
508,
884,
1712,
263,
28096,
3401,
612,
23956,
6139,
29889,
13,
13,
18884,
3940,
29901,
871,
2254,
9311,
287,
612,
23956,
2066,
408,
372,
508,
3275,
304,
633,
768,
29878,
653,
13,
18884,
775,
8225,
29889,
13,
18884,
5124,
1642,
4830,
29898,
13,
462,
1678,
2471,
29922,
359,
29889,
2084,
29889,
6500,
3871,
29898,
9675,
29889,
19218,
29961,
29900,
2314,
13,
462,
4961,
13,
13,
4706,
13812,
29889,
1202,
29918,
23516,
703,
489,
5527,
613,
17411,
29883,
742,
13,
9651,
1371,
543,
2605,
304,
263,
17157,
16376,
322,
28096,
3401,
343,
8807,
934,
29889,
5901,
3987,
674,
5712,
825,
338,
6790,
297,
278,
934,
1213,
13,
4706,
1723,
13,
13,
4706,
13812,
29889,
1202,
29918,
23516,
703,
489,
14380,
613,
11663,
29895,
613,
13,
9651,
19995,
29922,
3366,
2843,
613,
376,
9389,
613,
376,
3069,
12436,
13,
9651,
1371,
543,
1576,
2924,
310,
3646,
304,
4511,
304,
23157,
13,
13,
4706,
4742,
29918,
2972,
353,
13812,
29889,
1202,
29918,
6149,
1474,
29918,
735,
7009,
573,
29918,
2972,
580,
13,
4706,
4742,
29918,
2972,
29889,
1202,
29918,
23516,
703,
489,
10141,
613,
11663,
29881,
613,
13,
462,
9651,
1371,
543,
1576,
319,
4051,
3553,
310,
278,
3646,
29889,
5670,
344,
5779,
1192,
3069,
29889,
9333,
16058,
304,
5669,
2924,
23157,
13,
4706,
4742,
29918,
2972,
29889,
1202,
29918,
23516,
703,
489,
3069,
613,
11663,
29876,
613,
13,
462,
9651,
1371,
543,
1576,
3495,
978,
29914,
5690,
310,
278,
3646,
23157,
13,
13,
4706,
13812,
29889,
1202,
29918,
23516,
703,
489,
6786,
613,
11663,
29884,
613,
13,
462,
9651,
1371,
543,
11049,
8952,
29889,
9333,
16058,
304,
8074,
2924,
23157,
13,
4706,
13812,
29889,
1202,
29918,
23516,
703,
489,
5630,
613,
529,
25711,
17013,
28341,
13,
462,
9651,
1371,
543,
11049,
4800,
29889,
9333,
16058,
304,
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13,
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3207,
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7529,
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5527,
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13,
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323,
296,
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2254,
263,
28096,
3401,
515,
278,
1970,
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13,
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411,
3030,
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19303,
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2558,
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1958,
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322,
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13,
13,
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1423,
304,
679,
2253,
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13,
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13,
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738,
310,
278,
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2704,
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13,
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13,
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13,
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13,
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363,
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297,
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13,
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13,
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3972,
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13,
13,
1678,
822,
903,
2344,
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5182,
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1311,
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2924,
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1024,
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664,
3972,
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4742,
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4800,
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13,
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4632,
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13,
13,
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13,
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338,
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313,
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278,
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13,
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565,
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525,
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13,
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2906,
1982,
29918,
5182,
29918,
25932,
353,
2906,
1982,
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8136,
8667,
13,
13,
9651,
396,
5244,
11316,
363,
9033,
29924,
29899,
20415,
29914,
3359,
1982,
29937,
29906,
29906,
29945,
13,
9651,
664,
3972,
353,
664,
3972,
470,
8207,
1272,
29914,
2997,
29914,
7050,
29914,
3359,
1982,
29899,
5182,
29915,
13,
13,
9651,
565,
4742,
29901,
13,
18884,
1209,
13,
9651,
25342,
3495,
29901,
13,
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2011,
353,
2011,
470,
1583,
29889,
3035,
29933,
29918,
15082,
29918,
23397,
13,
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4742,
353,
285,
29915,
29912,
3069,
6177,
29912,
637,
10162,
13,
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1683,
29901,
13,
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4742,
353,
525,
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29915,
13,
13,
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11009,
29918,
11027,
1839,
10141,
2033,
353,
4742,
13,
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396,
960,
278,
8952,
471,
9479,
731,
304,
376,
4632,
613,
3876,
278,
3646,
408,
13,
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396,
4688,
408,
1950,
13,
9651,
11009,
29918,
11027,
1839,
328,
29890,
29918,
294,
29918,
4632,
2033,
353,
313,
6786,
1275,
525,
4632,
1495,
13,
13,
4706,
25342,
2924,
1275,
525,
9389,
2396,
13,
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2906,
1982,
29918,
5182,
29918,
25932,
353,
2906,
1982,
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24085,
8667,
13,
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11009,
29918,
11027,
29889,
5504,
29898,
13,
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8952,
29922,
9778,
1490,
29918,
6786,
29892,
13,
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2011,
29922,
637,
470,
1583,
29889,
1799,
29950,
29918,
15082,
29918,
23397,
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13,
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3495,
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13,
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3069,
29918,
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29922,
5574,
565,
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3069,
29918,
3198,
338,
6213,
1683,
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29918,
3069,
29918,
3198,
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13,
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671,
29918,
1557,
29886,
29922,
8824,
565,
671,
29918,
1557,
29886,
338,
6213,
1683,
671,
29918,
1557,
29886,
29892,
13,
9651,
1723,
13,
13,
9651,
396,
1281,
4532,
4800,
470,
22343,
1820,
1445,
13,
9651,
565,
1820,
1445,
29901,
13,
18884,
11009,
29918,
11027,
1839,
1989,
1445,
2033,
353,
1820,
1445,
13,
9651,
1683,
29901,
13,
18884,
11009,
29918,
11027,
1839,
5630,
2033,
353,
4800,
13,
4706,
25342,
2924,
1275,
525,
3069,
2396,
13,
9651,
2906,
1982,
29918,
5182,
29918,
25932,
353,
2906,
1982,
29889,
7717,
24085,
8667,
13,
9651,
396,
960,
591,
526,
2183,
263,
4800,
29892,
5251,
591,
508,
671,
372,
408,
263,
9196,
13,
9651,
396,
4800,
29889,
13,
9651,
11009,
29918,
11027,
29889,
5504,
29898,
13,
18884,
443,
4632,
287,
29922,
5630,
338,
6213,
29892,
13,
18884,
4800,
29922,
5630,
29892,
13,
9651,
1723,
13,
4706,
1683,
29901,
13,
9651,
12020,
7865,
2392,
29898,
29888,
29915,
25807,
29884,
3016,
287,
7481,
1134,
426,
14380,
29913,
1495,
13,
13,
4706,
6055,
353,
11297,
29876,
1678,
15300,
7122,
29898,
13,
9651,
285,
29915,
1678,
426,
1989,
6177,
426,
791,
10162,
13,
9651,
363,
1820,
29892,
659,
297,
11009,
29918,
11027,
29889,
7076,
580,
13,
9651,
565,
1820,
2804,
525,
5630,
29915,
13,
4706,
1723,
13,
4706,
17927,
29889,
8382,
29898,
29888,
29915,
29912,
14380,
29913,
426,
978,
29913,
3646,
3957,
6055,
3583,
29876,
1678,
426,
11027,
29913,
1495,
13,
13,
4706,
835,
13383,
13383,
13383,
13383,
4136,
29937,
13,
4706,
396,
9481,
1982,
28096,
5285,
13,
4706,
835,
13383,
13383,
13383,
13383,
4136,
29937,
13,
13,
4706,
565,
451,
2906,
1982,
29918,
12120,
29901,
13,
9651,
2906,
1982,
29918,
12120,
353,
2906,
1982,
29889,
12120,
29889,
21889,
580,
13,
13,
13,
4706,
835,
13383,
13383,
13383,
13383,
4136,
29937,
13,
4706,
396,
6204,
2906,
1982,
17157,
1203,
13,
4706,
835,
13383,
13383,
13383,
13383,
4136,
29937,
13,
13,
4706,
3646,
353,
2906,
1982,
29918,
5182,
29918,
25932,
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13,
9651,
7481,
29922,
3359,
1982,
29918,
12120,
29892,
13,
9651,
2254,
29918,
4381,
29918,
7576,
29922,
8824,
29892,
13,
9651,
3957,
29918,
11027,
29922,
13082,
29918,
11027,
29892,
13,
9651,
1985,
29918,
12322,
29922,
1287,
3972,
29892,
13,
9651,
4511,
29922,
8824,
29892,
13,
4706,
1723,
13,
13,
4706,
3646,
29889,
6915,
29898,
3198,
29918,
4777,
29918,
5729,
9446,
29922,
10685,
29918,
4777,
29892,
11815,
29922,
10685,
29918,
4777,
29918,
15619,
29897,
13,
13,
4706,
396,
6213,
408,
8952,
2794,
594,
29890,
3876,
674,
367,
16388,
29892,
541,
10672,
674,
13,
4706,
396,
451,
5557,
515,
16791,
304,
278,
3646,
29889,
13,
4706,
565,
2924,
1275,
525,
2843,
29915,
322,
8952,
338,
6213,
29901,
13,
9651,
1018,
29901,
13,
18884,
3646,
29889,
328,
29890,
29918,
4632,
29898,
12007,
29922,
5574,
29897,
13,
9651,
5174,
8960,
408,
321,
29901,
396,
282,
2904,
524,
29901,
11262,
29922,
6729,
328,
29899,
19499,
13,
18884,
17927,
29889,
27392,
29898,
29888,
11838,
328,
29890,
3876,
29908,
5229,
29901,
426,
29872,
29913,
1495,
13,
13,
4706,
17927,
29889,
8382,
29898,
29888,
29915,
8667,
5235,
29901,
426,
8977,
29898,
19266,
29922,
5182,
29889,
19266,
29892,
26403,
3888,
29922,
5182,
29889,
21970,
3888,
29892,
664,
3972,
29922,
5182,
29889,
22899,
29918,
12322,
2915,
1495,
13,
13,
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3646,
29889,
14669,
580,
13,
13,
4706,
17927,
29889,
3888,
29898,
29888,
29908,
20971,
2954,
304,
3646,
426,
29898,
978,
470,
27255,
27195,
13,
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736,
3646,
13,
13,
1678,
822,
679,
29918,
690,
29918,
3972,
29898,
1311,
29892,
1024,
29922,
8516,
29892,
9773,
29918,
2230,
29922,
5574,
29892,
9878,
828,
682,
29922,
5574,
1125,
13,
4706,
9995,
13,
4706,
16969,
263,
3884,
8745,
491,
365,
3235,
29909,
304,
3787,
2582,
29889,
13,
13,
4706,
10783,
482,
310,
393,
740,
338,
21676,
304,
28923,
671,
470,
2560,
12078,
29889,
13,
4706,
4321,
29879,
881,
451,
19104,
373,
393,
408,
278,
2825,
4138,
674,
451,
367,
5702,
287,
13,
4706,
491,
738,
7029,
7855,
29892,
607,
2794,
278,
2582,
674,
367,
5714,
297,
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] |
action-enigma2.py | torstenzey/snipsenigma2 | 0 | 162503 | <reponame>torstenzey/snipsenigma2
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import paho.mqtt.client as mqtt
import json
import httplib
def on_connect(client, userdata, flags, rc):
mqtt.subscribe('hermes/intent/torstenzey:switch_to')
mqtt.subscribe('hermes/intent/torstenzey:television_on')
mqtt.subscribe('hermes/intent/torstenzey:television_off')
mqtt.subscribe('hermes/intent/torstenzey:volume_down')
mqtt.subscribe('hermes/intent/torstenzey:volume_up')
mqtt.subscribe('hermes/intent/torstenzey:zap_forward')
mqtt.subscribe('hermes/intent/torstenzey:zap_backward')
def on_message(client, userdata, msg):
# Parse the json response
intent_json = json.loads(msg.payload)
intentName = intent_json['intent']['intentName']
slots = intent_json['slots']
# slot = slots[0]['value']['value']
print('Intent {}'.format(intentName))
for slot in slots:
slot_name = slot['slotName']
raw_value = slot['rawValue']
value = slot['value']['value']
print('Slot {} -> \n\tRaw: {} \tValue: {}'.format(slot_name, raw_value, value))
con = httplib.HTTPConnection('192.168.178.206')
if 'torstenzey:television_on' == intentName :
con.request("GET", "/web/powerstate?newstate=4")
elif 'torstenzey:television_off' == intentName :
con.request("GET", "/web/powerstate?newstate=5")
elif 'torstenzey:volume_down' == intentName :
con.request("GET", "/web/vol?set=down")
elif 'torstenzey:volume_up' == intentName :
con.request("GET", "/web/vol?set=up")
elif 'torstenzey:zap_forward' == intentName :
con.request("GET", "/web/remotecontrol?command=106")
elif 'torstenzey:zap_forward' == intentName :
con.request("GET", "/web/remotecontrol?command=105")
elif 'torstenzey:switch_to' == intentName and 'ARD' == slot :
con.request("GET", "/web/remotecontrol?command=105")
print(con.getresponse().status)
con.close()
mqtt = mqtt.Client()
mqtt.on_connect = on_connect
mqtt.on_message = on_message
mqtt.connect('127.0.0.1', 1883)
mqtt.loop_forever()
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study_algorithm/python/Linked List/Cycle Check.py | AlphaSunny/study | 0 | 89793 | <gh_stars>0
class Node(object):
def __init__(self,value):
self.value = value
self.nextnode = None
def cycle_check(node):
# Begin both markers at the first node
marker1 = node
marker2 = node
# Go until end of list
while marker2 != None and marker2.nextnode != None:
# Note
marker1 = marker1.nextnode
marker2 = marker2.nextnode.nextnode
# Check if the markers have matched
if marker2 == marker1:
return True
# Case where marker ahead reaches the end of the list
return False
"""
RUN THIS CELL TO TEST YOUR SOLUTION
"""
from nose.tools import assert_equal
# CREATE CYCLE LIST
a = Node(1)
b = Node(2)
c = Node(3)
a.nextnode = b
b.nextnode = c
c.nextnode = a # Cycle Here!
# CREATE NON CYCLE LIST
x = Node(1)
y = Node(2)
z = Node(3)
x.nextnode = y
y.nextnode = z
#############
class TestCycleCheck(object):
def test(self,sol):
assert_equal(sol(a),True)
assert_equal(sol(x),False)
print "ALL TEST CASES PASSED"
# Run Tests
t = TestCycleCheck()
t.test(cycle_check) | [
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Algorithms/032_TREE.py | ChaoticMarauder/Project_Rosalind | 0 | 28278 | def connected_tree(n, edge_list):
current_edges = len(edge_list)
edges_needed = (n-1) - current_edges
return edges_needed
def main():
with open('datasets/rosalind_tree.txt') as input_file:
input_data = input_file.read().strip().split('\n')
n = int(input_data.pop(0))
edge_list = list(map(int,edge.split()) for edge in input_data)
edges_needed = connected_tree(n, edge_list)
print(str(edges_needed))
with open('solutions/rosalind_tree.txt', 'w') as output_file:
output_file.write(str(edges_needed))
if(__name__=='__main__'):
main()
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aoc_cas/aoc2021/day9.py | TedCassirer/advent-of-code | 1 | 112574 | def getGrid(data):
return [[int(n) for n in row] for row in data.splitlines()]
def lowPoints(grid):
M, N = len(grid), len(grid[0])
for y, row in enumerate(grid):
for x, n in enumerate(row):
right = grid[y][x + 1] if x != N - 1 else 9
up = grid[y - 1][x] if y != 0 else 9
left = grid[y][x - 1] if x != 0 else 9
down = grid[y + 1][x] if y != M - 1 else 9
if n < min((right, up, left, down)):
yield y, x
def bfs(grid, y, x):
if grid[y][x] == 9:
return []
M, N = len(grid), len(grid[0])
basin = set()
stack = [(y, x)]
while stack:
y, x = stack.pop()
if (y, x) in basin or y < 0 or y == M or x < 0 or x == N or grid[y][x] == 9:
continue
basin.add((y, x))
stack.extend([(y + 1, x), (y - 1, x), (y, x + 1), (y, x - 1)])
return basin
def part1(data):
grid = getGrid(data)
return sum(1 + grid[y][x] for y, x in lowPoints(grid))
def part2(data):
grid = getGrid(data)
M, N = len(grid), len(grid[0])
basins = []
seen = set()
for y in range(M):
for x in range(N):
if (y, x) in seen:
continue
basin = bfs(grid, y, x)
basins.append(len(basin))
seen.update(basin)
b1, b2, b3 = sorted(basins, reverse=True)[:3]
return b1 * b2 * b3
if __name__ == "__main__":
from aocd import get_data
data = get_data(year=2021, day=9)
print(part1(data))
print(part2(data))
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rmon/processes/__init__.py | gnkr8/rmon | 1 | 145395 | <reponame>gnkr8/rmon
from .base import Process
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tests/band_tests.py | fortyninemaps/karta | 84 | 189578 | <reponame>fortyninemaps/karta<gh_stars>10-100
import unittest
import numpy as np
import numpy.testing as npt
from karta.raster import SimpleBand, CompressedBand
from karta.raster.band import BandIndexer
class GenericBandTests(object):
""" Tests that all Band classes must pass """
def test_get_dtype(self):
band = self.type((64, 64), np.float64, **self.initkwargs)
self.assertEqual(band.dtype, np.float64)
#def test_setblock_getblock_striped(self):
# x, y = np.meshgrid(np.arange(832), np.arange(1024))
# d = (x**2+np.sqrt(y))[::2, ::3]
# band = self.type((1024, 1024), np.float64, **self.initkwargs)
# bi = BandIndexer([band])
# bi[::2, 128:960:3, 0] = d
# self.assertEqual(np.sum(bi[::2, 128:960:3, 0]-d), 0.0)
def test_setblock_getblock_full(self):
x, y = np.meshgrid(np.arange(1024), np.arange(1024))
d = x**2+np.sqrt(y)
band = self.type((1024, 1024), np.float64, **self.initkwargs)
band.setblock(0, 0, d)
self.assertEqual(np.sum(band.getblock(0, 0, 1024, 1024) - d), 0.0)
def test_setblock_getblock_partial(self):
x, y = np.meshgrid(np.arange(1024), np.arange(832))
d = x**2+np.sqrt(y)
band = self.type((1024, 1024), np.float64, **self.initkwargs)
band.setblock(128, 0, d)
self.assertEqual(np.sum(band.getblock(128, 0, 832, 1024) - d), 0.0)
def test_get_scalar(self):
x, y = np.meshgrid(np.arange(1024), np.arange(1024))
d = x**2+np.sqrt(y)
band = self.type((1024, 1024), np.float64, **self.initkwargs)
band.setblock(0, 0, d)
self.assertTrue(band.getblock(4, 3, 1, 1).shape, (1, 1))
self.assertEqual(band.getblock(4, 3, 1, 1)[0], 11.0)
def test_initval(self):
band = self.type((1024, 1024), np.float64, initval=0.0)
self.assertTrue(band is not None)
class SimpleBandTests(unittest.TestCase, GenericBandTests):
def setUp(self):
self.type = SimpleBand
self.initkwargs = dict()
class CompressedBandTests(unittest.TestCase, GenericBandTests):
def setUp(self):
self.type = CompressedBand
self.initkwargs = dict(chunksize=(256, 256))
class BandIndexerTests(unittest.TestCase):
def test_get_set_typeerror(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer = BandIndexer(bands)
with self.assertRaises(TypeError):
indexer[None]
with self.assertRaises(TypeError):
indexer[None] = 3.0
def test_get_masked(self):
values = np.ones([16, 16])
band = CompressedBand((16, 16), np.float32)
band.setblock(0, 0, values)
indexer = BandIndexer([band])
mask = np.zeros([16, 16], dtype=np.bool)
mask[8:, 2:] = True
self.assertEqual(np.sum(indexer[mask]), 112)
def test_set_masked(self):
values = np.ones([16, 16])
band = CompressedBand((16, 16), np.float32)
band.setblock(0, 0, values)
indexer = BandIndexer([band])
mask = np.zeros([16, 16], dtype=np.bool)
mask[8:, 2:] = True
indexer[mask] = -1
self.assertEqual(np.sum(indexer[:,:]), 32)
def test_get_errors(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer = BandIndexer(bands)
with self.assertRaises(TypeError):
indexer["a", 0, 0]
with self.assertRaises(TypeError):
indexer[0, [1, 3], 0]
with self.assertRaises(TypeError):
indexer[0, 0, None]
def test_set_errors(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer = BandIndexer(bands)
with self.assertRaises(TypeError):
indexer["a", 0, 0] = 1.0
with self.assertRaises(TypeError):
indexer[0, [1, 3], 0] = 1.0
with self.assertRaises(TypeError):
indexer[0, 0, None] = 1.0
def test_get_integer(self):
values = np.ones([16, 16])
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
result = indexer[10,2]
npt.assert_equal(result, np.array([1.0, 2.0, 3.0]))
result = indexer[10,2,:]
npt.assert_equal(result, np.array([1.0, 2.0, 3.0]))
# make sure it works with a scalar band index
result = indexer[10,2,1]
self.assertEqual(result, 2.0)
def test_set_integer(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer = BandIndexer(bands)
indexer[3,4,0] = -1.0
self.assertEqual(bands[0].getblock(3, 4, 1, 1)[0], -1.0)
indexer[4,5,:] = np.array([1.0, 2.0, 3.0])
self.assertEqual(bands[0].getblock(4, 5, 1, 1)[0], 1.0)
self.assertEqual(bands[1].getblock(4, 5, 1, 1)[0], 2.0)
self.assertEqual(bands[2].getblock(4, 5, 1, 1)[0], 3.0)
indexer[5,6,:] = 5.0
self.assertEqual(bands[0].getblock(5, 6, 1, 1)[0], 5.0)
self.assertEqual(bands[1].getblock(5, 6, 1, 1)[0], 5.0)
self.assertEqual(bands[2].getblock(5, 6, 1, 1)[0], 5.0)
def test_get_slice(self):
values = np.ones([16, 16])
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
result = indexer[4:7,2:8,:]
self.assertEqual(result.shape, (3, 6, 3))
npt.assert_equal(result[0,0,:], np.array([1.0, 2.0, 3.0]))
result = indexer[12:]
self.assertEqual(result.shape, (4, 16, 3))
npt.assert_equal(result[0,0,:], np.array([1.0, 2.0, 3.0]))
# make sure it works with a scalar band index
result = indexer[4:7,2:8,1]
self.assertEqual(result.shape, (3, 6))
npt.assert_equal(result, 2.0)
def test_set_slice(self):
values = np.ones([16, 16])
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer = BandIndexer(bands)
indexer[:,:,0] = values
indexer[:,:,1:] = 2*values
npt.assert_equal(bands[0].getblock(0, 0, 16, 16), 1.0)
npt.assert_equal(bands[1].getblock(0, 0, 16, 16), 2.0)
npt.assert_equal(bands[2].getblock(0, 0, 16, 16), 2.0)
indexer[:,:,1:] = np.dstack([2*values, 3*values])
npt.assert_equal(bands[1].getblock(0, 0, 16, 16), 2.0)
npt.assert_equal(bands[2].getblock(0, 0, 16, 16), 3.0)
def test_get_mask2(self):
values = np.ones([3, 3])
bands = [CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
mask = np.array([[True, False, False], [False, True, False], [False, False, True]])
result = indexer[mask]
npt.assert_equal(np.tile(np.array([1, 2, 3]), (3, 1)), result)
def test_set_mask2(self):
values = np.ones([3, 3])
bands = [CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
mask = np.array([[True, False, False], [False, True, False], [False, False, True]])
indexer[mask] = -1
for band in bands:
self.assertEqual(band.getblock(0, 0, 1, 1)[0], -1.0)
self.assertEqual(band.getblock(1, 1, 1, 1)[0], -1.0)
self.assertEqual(band.getblock(2, 2, 1, 1)[0], -1.0)
def test_get_mask3(self):
values = np.ones([3, 3])
bands = [CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
# Create mask in band, row, column order than use np.moveaxis to put in
# row, column, band order for karta
mask = np.array([
[[True, False, False], [False, True, False], [False, False, True]],
[[False, False, False], [False, False, False], [False, True, False]],
[[True, False, False], [False, False, False], [True, False, True]]])
result = indexer[np.moveaxis(mask, 0, -1)]
expected = np.array([1, 3, 1, 3, 2, 1, 3])
npt.assert_equal(expected, result)
def test_set_mask3(self):
values = np.ones([3, 3])
bands = [CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32),
CompressedBand((3, 3), np.float32)]
bands[0].setblock(0, 0, values)
bands[1].setblock(0, 0, 2*values)
bands[2].setblock(0, 0, 3*values)
indexer = BandIndexer(bands)
# Create mask in band, row, column order than use np.moveaxis to put in
# row, column, band order for karta
mask = np.array([
[[True, False, False], [False, True, False], [False, False, True]],
[[False, False, False], [False, False, False], [False, True, False]],
[[True, False, False], [False, False, False], [True, False, True]]])
indexer[np.moveaxis(mask, 0, -1)] = -1
self.assertEqual(bands[0].getblock(0, 0, 1, 1)[0], -1)
self.assertEqual(bands[1].getblock(2, 1, 1, 1)[0], -1)
self.assertEqual(bands[2].getblock(0, 0, 1, 1)[0], -1)
self.assertEqual(bands[2].getblock(2, 0, 1, 1)[0], -1)
def test_set_masked_scalar(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
mask = np.zeros([16, 16], dtype=np.bool)
mask[8:, 2:] = True
indexer = BandIndexer(bands)
indexer[:,:] = np.zeros([16, 16])
indexer[mask] = 1.0
self.assertEqual(np.sum(indexer[:,:]), 336)
def test_set_masked_array(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
mask = np.zeros([16, 16], dtype=np.bool)
mask[8:, 2:] = True
indexer = BandIndexer(bands)
indexer[:,:,:] = np.zeros([16, 16])
indexer[mask] = np.ones(8*14)
self.assertEqual(np.sum(indexer[:,:]), 336)
def test_shape(self):
bands = [CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32),
CompressedBand((16, 16), np.float32)]
indexer1 = BandIndexer([bands[0]])
self.assertEqual(indexer1.shape, (16, 16))
indexer3 = BandIndexer(bands)
self.assertEqual(indexer3.shape, (16, 16))
if __name__ == "__main__":
unittest.main()
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receipt2vec/models/BaseEncoder.py | TinkoffCreditSystems/receipt2vec | 4 | 166070 | <gh_stars>1-10
from torch.nn import Module
from allennlp.common.registrable import Registrable
from abc import abstractmethod, abstractclassmethod, ABCMeta
from typing import Any, T, Type
class BaseEncoder(Module, Registrable, metaclass=ABCMeta):
def __init__(self):
super(BaseEncoder, self).__init__()
@property
@abstractmethod
def path_to_model(self) -> str:
pass
@property
@abstractmethod
def max_bpe_token(self) -> int:
pass
@abstractmethod
def forward(self, *args: Any, **kwargs: Any) -> None:
pass
@abstractclassmethod
def load_from_last_checkpoint(cls, *args: Any, **kwargs: Any) -> Type[T]:
pass
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protos/model_pb2.py | ChenCongGit/Chinese-aster | 6 | 157963 | <filename>protos/model_pb2.py
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: Chinese_aster/protos/model.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
import Chinese_aster.protos.feature_extractor_pb2
import Chinese_aster.protos.predictor_pb2
import Chinese_aster.protos.spatial_transformer_pb2
import Chinese_aster.protos.loss_pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='Chinese_aster/protos/model.proto',
package='Chinese_aster.protos',
serialized_pb=_b('\n Chinese_aster/protos/model.proto\x12\x14\x43hinese_aster.protos\x1a,Chinese_aster/protos/feature_extractor.proto\x1a$Chinese_aster/protos/predictor.proto\x1a.Chinese_aster/protos/spatial_transformer.proto\x1a\x1f\x43hinese_aster/protos/loss.proto\"{\n\x05Model\x12\x63\n\"multi_predictors_recognition_model\x18\x01 \x01(\x0b\x32\x35.Chinese_aster.protos.MultiPredictorsRecognitionModelH\x00\x42\r\n\x0bmodel_oneof\"\xb9\x02\n\x1fMultiPredictorsRecognitionModel\x12\x45\n\x13spatial_transformer\x18\x01 \x01(\x0b\x32(.Chinese_aster.protos.SpatialTransformer\x12\x41\n\x11\x66\x65\x61ture_extractor\x18\x02 \x01(\x0b\x32&.Chinese_aster.protos.FeatureExtractor\x12\x32\n\tpredictor\x18\x03 \x03(\x0b\x32\x1f.Chinese_aster.protos.Predictor\x12#\n\x14keypoint_supervision\x18\x04 \x01(\x08:\x05\x66\x61lse\x12\x33\n\x0fregression_loss\x18\x05 \x01(\x0b\x32\x1a.Chinese_aster.protos.Loss')
,
dependencies=[Chinese_aster.protos.feature_extractor_pb2.DESCRIPTOR,Chinese_aster.protos.predictor_pb2.DESCRIPTOR,Chinese_aster.protos.spatial_transformer_pb2.DESCRIPTOR,Chinese_aster.protos.loss_pb2.DESCRIPTOR,])
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
_MODEL = _descriptor.Descriptor(
name='Model',
full_name='Chinese_aster.protos.Model',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='multi_predictors_recognition_model', full_name='Chinese_aster.protos.Model.multi_predictors_recognition_model', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name='model_oneof', full_name='Chinese_aster.protos.Model.model_oneof',
index=0, containing_type=None, fields=[]),
],
serialized_start=223,
serialized_end=346,
)
_MULTIPREDICTORSRECOGNITIONMODEL = _descriptor.Descriptor(
name='MultiPredictorsRecognitionModel',
full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='spatial_transformer', full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel.spatial_transformer', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='feature_extractor', full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel.feature_extractor', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='predictor', full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel.predictor', index=2,
number=3, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='keypoint_supervision', full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel.keypoint_supervision', index=3,
number=4, type=8, cpp_type=7, label=1,
has_default_value=True, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='regression_loss', full_name='Chinese_aster.protos.MultiPredictorsRecognitionModel.regression_loss', index=4,
number=5, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
extension_ranges=[],
oneofs=[
],
serialized_start=349,
serialized_end=662,
)
_MODEL.fields_by_name['multi_predictors_recognition_model'].message_type = _MULTIPREDICTORSRECOGNITIONMODEL
_MODEL.oneofs_by_name['model_oneof'].fields.append(
_MODEL.fields_by_name['multi_predictors_recognition_model'])
_MODEL.fields_by_name['multi_predictors_recognition_model'].containing_oneof = _MODEL.oneofs_by_name['model_oneof']
_MULTIPREDICTORSRECOGNITIONMODEL.fields_by_name['spatial_transformer'].message_type = Chinese_aster.protos.spatial_transformer_pb2._SPATIALTRANSFORMER
_MULTIPREDICTORSRECOGNITIONMODEL.fields_by_name['feature_extractor'].message_type = Chinese_aster.protos.feature_extractor_pb2._FEATUREEXTRACTOR
_MULTIPREDICTORSRECOGNITIONMODEL.fields_by_name['predictor'].message_type = Chinese_aster.protos.predictor_pb2._PREDICTOR
_MULTIPREDICTORSRECOGNITIONMODEL.fields_by_name['regression_loss'].message_type = Chinese_aster.protos.loss_pb2._LOSS
DESCRIPTOR.message_types_by_name['Model'] = _MODEL
DESCRIPTOR.message_types_by_name['MultiPredictorsRecognitionModel'] = _MULTIPREDICTORSRECOGNITIONMODEL
Model = _reflection.GeneratedProtocolMessageType('Model', (_message.Message,), dict(
DESCRIPTOR = _MODEL,
__module__ = 'Chinese_aster.protos.model_pb2'
# @@protoc_insertion_point(class_scope:Chinese_aster.protos.Model)
))
_sym_db.RegisterMessage(Model)
MultiPredictorsRecognitionModel = _reflection.GeneratedProtocolMessageType('MultiPredictorsRecognitionModel', (_message.Message,), dict(
DESCRIPTOR = _MULTIPREDICTORSRECOGNITIONMODEL,
__module__ = 'Chinese_aster.protos.model_pb2'
# @@protoc_insertion_point(class_scope:Chinese_aster.protos.MultiPredictorsRecognitionModel)
))
_sym_db.RegisterMessage(MultiPredictorsRecognitionModel)
# @@protoc_insertion_point(module_scope)
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] |
scripts/master/master_gen.py | yjbanov/chromium_build | 0 | 74846 | <reponame>yjbanov/chromium_build<filename>scripts/master/master_gen.py
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import ast
import os
from buildbot.changes.filter import ChangeFilter
from buildbot.schedulers.basic import SingleBranchScheduler
from buildbot.schedulers.timed import Nightly
from buildbot.status.mail import MailNotifier
from buildbot import util
from config_bootstrap import Master
from common import chromium_utils
from master import gitiles_poller
from master import master_utils
from master import repo_poller
from master import slaves_list
from master.factory import annotator_factory
def PopulateBuildmasterConfig(BuildmasterConfig, builders_path,
active_master_cls):
"""Read builders_path and populate a build master config dict."""
builders = chromium_utils.ReadBuildersFile(builders_path)
_Populate(BuildmasterConfig, builders, active_master_cls)
def _Populate(BuildmasterConfig, builders, active_master_cls):
m_annotator = annotator_factory.AnnotatorFactory(active_master_cls)
c = BuildmasterConfig
c['logCompressionLimit'] = False
c['projectName'] = active_master_cls.project_name
c['projectURL'] = Master.project_url
c['buildbotURL'] = active_master_cls.buildbot_url
# This sets c['db_url'] to the database connect string in found in
# the .dbconfig in the master directory, if it exists. If this is
# a production host, it must exist.
chromium_utils.DatabaseSetup(
c,
require_dbconfig=active_master_cls.is_production_host)
c['builders'] = _ComputeBuilders(builders, m_annotator)
c['schedulers'] = _ComputeSchedulers(builders)
c['change_source'], tag_comparator = _ComputeChangeSourceAndTagComparator(
builders)
# The 'slaves' list defines the set of allowable buildslaves. List all the
# slaves registered to a builder. Remove dupes.
c['slaves'] = master_utils.AutoSetupSlaves(
c['builders'],
Master.GetBotPassword(),
missing_recipients=['<EMAIL>'])
# This does some sanity checks on the configuration.
slaves = slaves_list.BaseSlavesList(
chromium_utils.GetSlavesFromBuilders(builders),
builders['master_classname'])
master_utils.VerifySetup(c, slaves)
default_public_html = os.path.join(chromium_utils.BUILD_DIR,
'masters', 'master.chromium',
'public_html')
public_html = builders.get('public_html', default_public_html)
# Adds common status and tools to this master.
# TODO: Look at the logic in this routine to see if any of the logic
# in this routine can be moved there to simplify things.
master_utils.AutoSetupMaster(c, active_master_cls,
public_html=public_html,
templates=builders['templates'],
tagComparator=tag_comparator,
enable_http_status_push=active_master_cls.is_production_host)
# TODO: AutoSetupMaster's settings for the following are too low to be
# useful for most projects. We should fix that.
c['buildHorizon'] = 3000
c['logHorizon'] = 3000
# Must be at least 2x the number of slaves.
c['eventHorizon'] = 200
def _ComputeBuilders(builders, m_annotator):
actual_builders = []
def cmp_fn(a, b):
a_cat = builders['builders'][a].get('category')
b_cat = builders['builders'][b].get('category')
if a_cat != b_cat:
return 1 if a_cat > b_cat else -1
if a != b:
return 1 if a > b else -1
return 0
for builder_name in sorted(builders['builders'], cmp=cmp_fn):
builder_data = builders['builders'][builder_name]
has_schedulers = bool(
builder_data.get('scheduler', builder_data.get('schedulers')))
# We will automatically merge all build requests for any
# builder that can be scheduled; this is normally the behavior
# we want for repo-triggered builders and cron-triggered builders.
# You can override this behavior by setting the mergeRequests field though.
merge_requests = builder_data.get('mergeRequests', has_schedulers)
slavebuilddir = builder_data.get('slavebuilddir',
util.safeTranslate(builder_name))
factory = m_annotator.BaseFactory(
recipe=builder_data['recipe'],
max_time=builder_data.get('builder_timeout_s'),
factory_properties=builder_data.get('properties')
)
actual_builders.append({
'auto_reboot': builder_data.get('auto_reboot', True),
'mergeRequests': merge_requests,
'name': builder_name,
'factory': factory,
'slavebuilddir': slavebuilddir,
'slavenames': chromium_utils.GetSlaveNamesForBuilder(builders,
builder_name),
'category': builder_data.get('category'),
'trybot': builder_data.get('trybot'),
})
return actual_builders
def _ComputeSchedulers(builders):
scheduler_to_builders = {}
for builder_name, builder_data in builders['builders'].items():
scheduler_names = builder_data.get('schedulers', [])
if 'scheduler' in builder_data:
scheduler_names.append(builder_data['scheduler'])
for scheduler_name in scheduler_names:
if scheduler_name:
if scheduler_name not in builders['schedulers']:
raise ValueError('unknown scheduler "%s"' % scheduler_name)
scheduler_to_builders.setdefault(
scheduler_name, []).append(builder_name)
schedulers = []
for scheduler_name, scheduler_values in builders['schedulers'].items():
scheduler_type = scheduler_values['type']
builder_names = scheduler_to_builders[scheduler_name]
if scheduler_type == 'git_poller':
# git_poller pollers group changes, so we match on our specific repository
# to ensure that we only pick up changes from our poller.
schedulers.append(SingleBranchScheduler(
name=scheduler_name,
change_filter=ChangeFilter(
repository=scheduler_values['git_repo_url'],
branch=scheduler_values.get('branch', 'master'),
),
treeStableTimer=scheduler_values.get('treeStableTimer', 60),
builderNames=builder_names))
elif scheduler_type == 'repo_poller':
# repo_poller pollers punt changes that use the scheduler name as their
# category (see _ComputeChangeSourceAndTagComparator). Matching on this
# ensures that we only match changes from our poller.
schedulers.append(SingleBranchScheduler(
name=scheduler_name,
change_filter=ChangeFilter(
category=str(scheduler_name),
),
treeStableTimer=scheduler_values.get('treeStableTimer', 60),
builderNames=builder_names))
elif scheduler_type == 'cron':
schedulers.append(Nightly(
name=scheduler_name,
branch='master',
minute=scheduler_values['minute'],
hour=scheduler_values['hour'],
builderNames=builder_names))
else:
raise ValueError('unsupported scheduler type "%s"' % scheduler_type)
return schedulers
def _ComputeChangeSourceAndTagComparator(builders):
change_source = []
tag_comparator = None
git_urls_to_branches = {}
for scheduler_config in builders['schedulers'].values():
if scheduler_config['type'] != 'git_poller':
continue
url = scheduler_config['git_repo_url']
branch = scheduler_config.get('branch', 'master')
git_urls_to_branches.setdefault(url, set()).add(branch)
for url, branches in git_urls_to_branches.iteritems():
change_source.append(
gitiles_poller.GitilesPoller(url, branches=list(branches)))
for scheduler_name, scheduler_config in builders['schedulers'].iteritems():
if scheduler_config['type'] != 'repo_poller':
continue
rev_link_template = scheduler_config.get('rev_link_template')
branch = scheduler_config.get('branch')
branches = [branch] if branch is not None else None
change_source.append(repo_poller.RepoPoller(
repo_url=scheduler_config['repo_url'],
manifest='manifest',
category=str(scheduler_name),
repo_branches=branches,
pollInterval=300,
revlinktmpl=rev_link_template))
# We have to set the tag_comparator to something, but if we have multiple
# repos, the tag_comparator will not work properly (it's meaningless).
# It's not clear if there's a good answer to this.
if change_source:
tag_comparator = change_source[0].comparator
return change_source, tag_comparator
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4993,
29892,
4055,
29918,
510,
17954,
13,
2
] |
2021/07.py | EwwPhysics/advent-of-code | 0 | 70239 | <filename>2021/07.py
from statistics import mean, median
import math
with open("input.txt") as fin:
positions = [int(i) for i in fin.read().split(",")]
def p1():
m = median(positions)
return sum(abs(m - x) for x in positions)
def p2():
m = mean(positions)
res = float("inf")
for m in range(math.floor(m) - 1, math.floor(m) + 1):
res = min(res, sum(abs(m - x) / 2 * (abs(m - x) + 1) for x in positions))
return res
print(p2())
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test/hello.py | marcosfede/ec-archlinux | 0 | 1604324 | <gh_stars>0
# Copyright (c) 2011 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
#
# Simple test as an example
#
def test(helper):
helper.wait_output("--- UART initialized")
helper.ec_command("version")
ro = helper.wait_output("RO:\s*(?P<ro>\S+)", use_re=True)["ro"]
wa = helper.wait_output("RW-A:\s*(?P<a>\S+)", use_re=True)["a"]
wb = helper.wait_output("RW-B:\s*(?P<b>\S*)", use_re=True)["b"]
helper.trace("Version (RO/A/B) %s / %s / %s\n" % (ro, wa, wb))
return True # PASS !
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] |
devops-console/apps/teams/models.py | lilinghell/devops | 4 | 52439 | <gh_stars>1-10
from django.db import models
from django.utils.translation import ugettext_lazy as _
from users.models import User
from common.mixin import BaseModelMixin
__all__ = ["Team", "Member"]
class Team(BaseModelMixin):
name = models.CharField(max_length=128, null=True, unique=True, verbose_name=_("TeamName"))
description = models.TextField(null=True, blank=True, verbose_name=_("描述信息"))
parent = models.ForeignKey('Team', null=True, blank=True, related_name="child_teams", on_delete=models.SET_NULL,
verbose_name=_("上级team"))
owner = models.ForeignKey(User, related_name="owner_teams", on_delete=models.SET_NULL, null=True,
verbose_name=_("小组负责人"))
class Meta:
ordering = ["-created_at"]
db_table = "teams"
class Member(BaseModelMixin):
"""
成员，包含团队成员、项目成员、应用成员等等
"""
TEAM_MEMBER = "TeamMember"
TEAM_ADMIN = "TeamAdmin"
APP_MEMBER = "AppMember"
PROJECT_MEMBER = "ProjectMember"
TYPE_CHOICES = ((TEAM_MEMBER, "TeamMember"), (APP_MEMBER, "AppMember"), (PROJECT_MEMBER, "ProjectMember"))
SOURCE_APP = "application"
SOURCE_TEAM = "team"
SOURCE_PROJECT = "project"
SOURCE_CHOICES = ((SOURCE_TEAM, "team"), (SOURCE_APP, "application"), (SOURCE_PROJECT, "project"))
user = models.ForeignKey(User, related_name="members", on_delete=models.CASCADE)
source_id = models.IntegerField(verbose_name=_("来源ID"))
source_type = models.CharField(choices=SOURCE_CHOICES, max_length=32, null=False,
verbose_name=_("member type ，比如team、project、app等"))
type = models.CharField(choices=TYPE_CHOICES, max_length=32, verbose_name=_("成员类型"))
access_level = models.IntegerField(verbose_name=_("访问权限"), default=10)
notification_level = models.IntegerField(null=True, verbose_name=_("notification_level"))
class Meta:
ordering = ["-created_at", "access_level"]
unique_together = [('source_id', 'source_type', 'user')]
db_table = "members"
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] |
hash&heap/0685_First_Unique_Number_in_Data_Stream.py | adwardlee/leetcode_solutions | 0 | 116596 | <filename>hash&heap/0685_First_Unique_Number_in_Data_Stream.py
'''
Description
Given a continuous stream of data, write a function that returns the first unique number (including the last number) when the terminating number arrives. If the terminating number is not found, return -1.
Example
Example1
Input:
[1, 2, 2, 1, 3, 4, 4, 5, 6]
5
Output: 3
Example2
Input:
[1, 2, 2, 1, 3, 4, 4, 5, 6]
7
Output: -1
Example3
Input:
[1, 2, 2, 1, 3, 4]
3
Output: 3
'''
class Solution:
"""
@param nums: a continuous stream of numbers
@param number: a number
@return: returns the first unique number
"""
def firstUniqueNumber(self, nums, number):
# Write your code here
onedict = {}
flag = False
for i, x in enumerate(nums):
if x not in onedict:
onedict[x] = [1, i]
else:
onedict[x][0] += 1
if number == x:
flag = True
break
if flag == True:
oncelist = []
for key in onedict:
if onedict[key][0] == 1:
oncelist.append([key, onedict[key][1]])
x = 2e30
returnkey = None
for one in oncelist:
if one[1] < x:
x = one[1]
returnkey = one[0]
return returnkey
else:
return -1 | [
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factom_core/blocks/admin_block.py | sourcery-ai-bot/factom-core | 0 | 59675 | <reponame>sourcery-ai-bot/factom-core<filename>factom_core/blocks/admin_block.py
import hashlib
from dataclasses import dataclass, field
from typing import List
from factom_core.block_elements.admin_messages import *
from factom_core.utils import varint
from .directory_block import DirectoryBlock
@dataclass
class AdminBlockHeader:
CHAIN_ID = bytes.fromhex("000000000000000000000000000000000000000000000000000000000000000a")
prev_back_reference_hash: bytes
height: int
expansion_area: bytes
message_count: int
body_size: int
def __post_init__(self):
# TODO: value assertions
pass
def marshal(self) -> bytes:
buf = bytearray()
buf.extend(AdminBlockHeader.CHAIN_ID)
buf.extend(self.prev_back_reference_hash)
buf.extend(struct.pack(">I", self.height))
buf.extend(varint.encode(len(self.expansion_area)))
buf.extend(self.expansion_area)
buf.extend(struct.pack(">I", self.message_count))
buf.extend(struct.pack(">I", self.body_size))
return bytes(buf)
@classmethod
def unmarshal(cls, raw: bytes):
h, data = AdminBlockHeader.unmarshal_with_remainder(raw)
assert len(data) == 0, "Extra bytes remaining!"
return h
@classmethod
def unmarshal_with_remainder(cls, raw: bytes):
chain_id, data = raw[:32], raw[32:]
assert chain_id == AdminBlockHeader.CHAIN_ID
prev_back_reference_hash, data = data[:32], data[32:]
height, data = struct.unpack(">I", data[:4])[0], data[4:]
expansion_size, data = varint.decode(data)
expansion_area, data = data[:expansion_size], data[expansion_size:]
# TODO: unmarshal header expansion area
message_count, data = struct.unpack(">I", data[:4])[0], data[4:]
body_size, data = struct.unpack(">I", data[:4])[0], data[4:]
return (
AdminBlockHeader(
prev_back_reference_hash=prev_back_reference_hash,
height=height,
expansion_area=expansion_area,
message_count=message_count,
body_size=body_size,
),
data,
)
@dataclass
class AdminBlockBody:
messages: List[AdminMessage] = field(default_factory=list)
def __post_init__(self):
# TODO: value assertions
pass
def marshal(self) -> bytes:
buf = bytearray()
for message in self.messages:
if type(message) is int:
buf.append(message)
continue
buf.append(message.__class__.ADMIN_ID)
buf.extend(message.marshal())
return bytes(buf)
@classmethod
def unmarshal(cls, raw: bytes, message_count: int):
body, data = cls.unmarshal_with_remainder(raw, message_count)
assert len(data) == 0, "Extra bytes remaining!"
return body
@classmethod
def unmarshal_with_remainder(cls, raw: bytes, message_count: int):
data = raw
messages = []
for _ in range(message_count):
admin_id, data = data[0], data[1:]
msg = None
if admin_id == MinuteNumber.ADMIN_ID: # Deprecated in M2
size = MinuteNumber.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MinuteNumber.unmarshal(msg_data)
elif admin_id == DirectoryBlockSignature.ADMIN_ID:
size = DirectoryBlockSignature.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = DirectoryBlockSignature.unmarshal(msg_data)
elif admin_id == MatryoshkaHashReveal.ADMIN_ID:
size = MatryoshkaHashReveal.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MatryoshkaHashReveal.unmarshal(msg_data)
elif admin_id == MatryoshkaHashAddOrReplace.ADMIN_ID:
size = MatryoshkaHashAddOrReplace.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MatryoshkaHashAddOrReplace.unmarshal(msg_data)
elif admin_id == ServerCountIncrease.ADMIN_ID:
size = ServerCountIncrease.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = ServerCountIncrease.unmarshal(msg_data)
elif admin_id == AddFederatedServer.ADMIN_ID:
size = AddFederatedServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServer.unmarshal(msg_data)
elif admin_id == AddAuditServer.ADMIN_ID:
size = AddAuditServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuditServer.unmarshal(msg_data)
elif admin_id == RemoveFederatedServer.ADMIN_ID:
size = RemoveFederatedServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = RemoveFederatedServer.unmarshal(msg_data)
elif admin_id == AddFederatedServerSigningKey.ADMIN_ID:
size = AddFederatedServerSigningKey.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServerSigningKey.unmarshal(msg_data)
elif admin_id == AddFederatedServerBitcoinAnchorKey.ADMIN_ID:
size = AddFederatedServerBitcoinAnchorKey.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServerBitcoinAnchorKey.unmarshal(msg_data)
elif admin_id == ServerFaultHandoff.ADMIN_ID:
msg = ServerFaultHandoff() # No data on chain for message
elif admin_id == CoinbaseDescriptor.ADMIN_ID:
msg, data = CoinbaseDescriptor.unmarshal_with_remainder(data)
elif admin_id == CoinbaseDescriptorCancel.ADMIN_ID:
msg, data = CoinbaseDescriptorCancel.unmarshal_with_remainder(data)
elif admin_id == AddAuthorityFactoidAddress.ADMIN_ID:
size = AddAuthorityFactoidAddress.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuthorityFactoidAddress.unmarshal(msg_data)
elif admin_id == AddAuthorityEfficiency.ADMIN_ID:
size = AddAuthorityEfficiency.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuthorityFactoidAddress.unmarshal(msg_data)
elif admin_id <= 0x0E:
msg = admin_id
print(f'Unsupported admin message type {msg} found')
if msg is not None:
messages.append(msg)
assert len(messages) == message_count, "Unexpected message count"
return AdminBlockBody(messages=messages), data
def construct_header(self, prev_back_reference_hash: bytes, height: int) -> AdminBlockHeader:
"""
Seals the admin block by constructing and returning its header
"""
return AdminBlockHeader(
prev_back_reference_hash=prev_back_reference_hash,
height=height,
expansion_area=b"",
message_count=len(self.messages),
body_size=len(self.marshal()),
)
@dataclass
class AdminBlock:
header: AdminBlockHeader
body: AdminBlockBody
_cached_lookup_hash: bytes = None
_cached_back_reference_hash: bytes = None
def __post_init__(self):
# TODO: value assertions
pass
@property
def lookup_hash(self):
if self._cached_lookup_hash is not None:
return self._cached_lookup_hash
self._cached_lookup_hash = hashlib.sha256(self.marshal()).digest()
return self._cached_lookup_hash
@property
def back_reference_hash(self):
if self._cached_back_reference_hash is not None:
return self._cached_back_reference_hash
self._cached_back_reference_hash = hashlib.sha512(self.marshal()).digest()[:32]
return self._cached_back_reference_hash
def marshal(self) -> bytes:
buf = bytearray()
buf.extend(self.header.marshal())
buf.extend(self.body.marshal())
return bytes(buf)
@classmethod
def unmarshal(cls, raw: bytes):
"""Returns a new AdminBlock object, unmarshalling given bytes according to:
https://github.com/FactomProject/FactomDocs/blob/master/factomDataStructureDetails.md#administrative-block
Useful for working with a single ablock out of context, pulled directly from a factomd database for instance.
AdminBlock created will not include contextual metadata, such as timestamp
"""
block, data = cls.unmarshal_with_remainder(raw)
assert len(data) == 0, "Extra bytes remaining!"
return block
@classmethod
def unmarshal_with_remainder(cls, raw: bytes):
header, data = AdminBlockHeader.unmarshal_with_remainder(raw)
messages = []
for _ in range(header.message_count):
admin_id, data = data[0], data[1:]
msg = None
if admin_id == MinuteNumber.ADMIN_ID: # Deprecated in M2
size = MinuteNumber.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MinuteNumber.unmarshal(msg_data)
elif admin_id == DirectoryBlockSignature.ADMIN_ID:
size = DirectoryBlockSignature.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = DirectoryBlockSignature.unmarshal(msg_data)
elif admin_id == MatryoshkaHashReveal.ADMIN_ID:
size = MatryoshkaHashReveal.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MatryoshkaHashReveal.unmarshal(msg_data)
elif admin_id == MatryoshkaHashAddOrReplace.ADMIN_ID:
size = MatryoshkaHashAddOrReplace.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = MatryoshkaHashAddOrReplace.unmarshal(msg_data)
elif admin_id == ServerCountIncrease.ADMIN_ID:
size = ServerCountIncrease.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = ServerCountIncrease.unmarshal(msg_data)
elif admin_id == AddFederatedServer.ADMIN_ID:
size = AddFederatedServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServer.unmarshal(msg_data)
elif admin_id == AddAuditServer.ADMIN_ID:
size = AddAuditServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuditServer.unmarshal(msg_data)
elif admin_id == RemoveFederatedServer.ADMIN_ID:
size = RemoveFederatedServer.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = RemoveFederatedServer.unmarshal(msg_data)
elif admin_id == AddFederatedServerSigningKey.ADMIN_ID:
size = AddFederatedServerSigningKey.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServerSigningKey.unmarshal(msg_data)
elif admin_id == AddFederatedServerBitcoinAnchorKey.ADMIN_ID:
size = AddFederatedServerBitcoinAnchorKey.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddFederatedServerBitcoinAnchorKey.unmarshal(msg_data)
elif admin_id == ServerFaultHandoff.ADMIN_ID:
msg = ServerFaultHandoff() # No data on chain for message
elif admin_id == CoinbaseDescriptor.ADMIN_ID:
msg, data = CoinbaseDescriptor.unmarshal_with_remainder(data)
elif admin_id == CoinbaseDescriptorCancel.ADMIN_ID:
msg, data = CoinbaseDescriptorCancel.unmarshal_with_remainder(data)
elif admin_id == AddAuthorityFactoidAddress.ADMIN_ID:
size = AddAuthorityFactoidAddress.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuthorityFactoidAddress.unmarshal(msg_data)
elif admin_id == AddAuthorityEfficiency.ADMIN_ID:
size = AddAuthorityEfficiency.MESSAGE_SIZE
msg_data, data = data[:size], data[size:]
msg = AddAuthorityFactoidAddress.unmarshal(msg_data)
elif admin_id <= 0x0E:
msg = admin_id
print(
"Unsupported admin message type {} found at Admin Block {}".format(
msg, header.height
)
)
if msg is not None:
messages.append(msg)
assert len(messages) == header.message_count, "Unexpected message count at Admin Block {}".format(header.height)
body = AdminBlockBody(messages=messages)
return AdminBlock(header=header, body=body), data
def add_context(self, directory_block: DirectoryBlock):
pass
def to_dict(self):
return {
"lookup_hash": self.lookup_hash.hex(),
"back_reference_hash": self.header.prev_back_reference_hash.hex(),
"height": self.header.height,
"expansion_area": self.header.expansion_area.hex(),
"message_count": self.header.message_count,
"body_size": self.header.body_size,
"messages": [m.to_dict() for m in self.body.messages],
}
def __str__(self):
return "{}(height={}, hash={})".format(self.__class__.__name__, self.header.height, self.lookup_hash.hex())
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] |
configfiles/emailsend.py | dgome/HL-StarterKit | 5 | 137761 | <gh_stars>1-10
#!/bin/bash
#Created by : <EMAIL> | <NAME>
import email, smtplib, ssl, os
from email import encoders
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.application import MIMEApplication
##Loading Environment
with open('.hlc.env', 'r') as fh:
vars_dict = dict(
tuple(line.split('='))
for line in fh.readlines() if not line.startswith('#')
)
#print(vars_dict)
os.environ.update(vars_dict)
subject = "Mail generated through fabric configrator tool"
body = "Attached Configuration files in tar.gz format ="
receiver_email = os.environ.get("TOEMLADDRESS")
### gmail
sender_email = '<EMAIL>'
smtp_server = 'smtp.gmail.com'
sender_pass = '<PASSWORD>'
port = 587 # For starttls
# Create a multipart message and set headers
message = MIMEMultipart()
message["From"] = sender_email
message["To"] = receiver_email
message["Subject"] = subject
message["Bcc"] = receiver_email # Recommended for mass emails
# Create the plain-text and HTML version of your message
text = """\
Hi,
Attached the Configuration files that generated for your Hyperledger fabric
Note : If you received as unname attachment, pls rename to {somename}.tar.gz
Thanks
Support Team
KSTECH
"""
html = """\
<html>
<body>
<p>Hi,<br>
Attached the Configuration files that generated for your Hyperledger fabric<br>
Note : If you received as unname attachment, pls rename to {somename}.tar.gz
Thanks
Support Team
KSTECH
</p>
</body>
</html>
"""
# Add body to email
#message.attach(MIMEText(text, "plain"))
body_part = MIMEText(text, 'plain')
#message.attach(MIMEText(html, "html")
filen = os.environ.get("DOMAIN_NAME").replace('\n','')
path1= '/tmp/'
filext = '.tar.gz'
file_name = os.path.join( filen + filext)
attach_file_name = os.path.join(filen)
#attach_file_name = os.path.join( path1, filen + "." + filext)
#print (attach_file_name)
# Open PDF file in binary mode
# with open(file_name, "rb") as attachment:
# # Add file as application/octet-stream
# # Email client can usually download this automatically as attachment
# part = MIMEBase("application", "x-gzip")
# part.set_payload(attachment.read())
# Add body to email
message.attach(body_part)
# open and read the file in binary
with open(file_name,'rb') as file:
# Attach the file with filename to the email
message.attach(MIMEApplication(file.read(), Name=file_name))
# Encode file in ASCII characters to send by email
# encoders.encode_base64(part)
# part.add_header('Content-Decomposition', "attachment; filename=\"%s.tar.gz\"" % (attach_file_name))
# message.attach(part)
# Turn these into plain/html MIMEText objects
part1 = MIMEText(text, "plain")
part2 = MIMEText(html, "html")
# Add HTML/plain-text parts to MIMEMultipart message
# The email client will try to render the last part first
#message.attach(part1)
#message.attach(part2)
# Add attachment to message and convert message to string
#message.attach(part)
text = message.as_string()
# Log in to server using secure context and send email
context = ssl.create_default_context()
try :
with smtplib.SMTP(smtp_server, port) as server:
server.starttls(context=context)
server.login(sender_email, sender_pass)
server.sendmail(sender_email, receiver_email, text)
print ("Successfully sent email")
server.quit()
except smtplib.SMTPException as e :
print ("Error: unable to send email", e )
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] |
storage/cloud.py | labdave/Aries | 2 | 94806 | <gh_stars>1-10
import os
import datetime
import logging
import threading
from io import FileIO
from abc import ABC
from .base import StorageObject, StoragePrefixBase, StorageIOSeekable
logger = logging.getLogger(__name__)
class BucketStorageObject(StorageObject):
"""Represents a cloud storage object associated with a bucket.
This object may not correspond to an actual object in the bucket, e.g. a folder in Google or S3 bucket.
"""
# Caches clients for each scheme
cache_dict = dict()
# Expiration time for each client
cache_expire = dict()
# Ensure that only one thread can initialize the client at one time
# Multiple threads initializing the s3 client at the same time may cause a KeyError: 'credential_provider'
# https://github.com/boto/boto3/issues/1592
client_lock = threading.Lock()
# The number of seconds before the client expires.
CACHE_EXPIRE_SEC = 1200
def __init__(self, uri):
StorageObject.__init__(self, uri)
self._client = None
self._bucket = None
self._blob = None
@classmethod
def get_cached(cls, obj_id, init_method):
"""Gets an unexpired object by obj_id from cache, creates one using init_method() if needed.
"""
cached_obj = cls.cache_dict.get(obj_id)
now = datetime.datetime.now()
if cached_obj:
client_expire = cls.cache_expire.get(obj_id)
# Use the cached client if it is not expired.
if client_expire and client_expire > now:
return cached_obj
obj = init_method()
cls.cache_dict[obj_id] = obj
cls.cache_expire[obj_id] = now + datetime.timedelta(seconds=cls.CACHE_EXPIRE_SEC)
return obj
def get_client(self):
obj_id = self.scheme
with self.client_lock:
return self.get_cached(obj_id, self.init_client)
def get_bucket(self):
obj_id = "%s://%s" % (self.scheme, self.bucket_name)
return self.get_cached(obj_id, self.init_bucket)
@property
def bucket_name(self):
"""The name of the Cloud Storage bucket as a string."""
return self.hostname
@property
def client(self):
if not self._client:
self._client = self.get_client()
return self._client
@property
def bucket(self):
if not self._bucket:
self._bucket = self.get_bucket()
return self._bucket
def is_file(self):
"""Determine if the object is a file.
This will return False if the object does not exist or the object is a folder.
"""
if self.path.endswith("/"):
return False
if not self.exists():
return False
return True
def init_client(self):
raise NotImplementedError()
def init_bucket(self):
raise NotImplementedError()
def exists(self):
raise NotImplementedError()
class CloudStoragePrefix(StoragePrefixBase, ABC):
def blobs(self, delimiter=""):
"""All blobs with the same prefix as this object
The type of blobs depends on the actual implementation of the blobs() method.
The delimiter causes a list operation to roll up all the keys that share a common prefix into a single result.
See Also: https://docs.aws.amazon.com/AmazonS3/latest/dev/ListingKeysHierarchy.html
"""
raise NotImplementedError()
class CloudStorageIO(StorageIOSeekable):
def __init__(self, uri):
"""
"""
StorageIOSeekable.__init__(self, uri)
# Path of the temp local file
self.temp_path = None
# Stores the temp local FileIO object
self.__file_io = None
# Cache the size information
# TODO: use cached property
self.__size = None
@property
def size(self):
if not self.__size:
if self.__file_io:
return os.fstat(self.__file_io.fileno).st_size
self.__size = self.get_size()
return self.__size
def seek(self, pos, whence=0):
if self.__file_io:
self._offset = self.__file_io.seek(pos, whence)
return self._offset
return self._seek(pos, whence)
def tell(self):
if self.__file_io:
self._offset = self.__file_io.tell()
return self._offset
def local(self):
"""Creates a local copy of the file.
"""
if not self.__file_io:
file_obj = self.create_temp_file()
# Download file if appending or updating
if self.exists() and ('a' in self.mode or '+' in self.mode):
self.download(file_obj)
# Close the temp file and open it with FileIO
file_obj.close()
mode = "".join([c for c in self.mode if c in "rw+ax"])
self.__file_io = FileIO(file_obj.name, mode)
self.temp_path = file_obj.name
return self
def read(self, size=None):
"""Reads the file from the Google Cloud bucket to memory
Returns: Bytes containing the contents of the file.
"""
start = self.tell()
if self.__file_io:
self.__file_io.seek(start)
b = self.__file_io.read(size)
else:
if not self.exists():
raise FileNotFoundError("File %s does not exists." % self.uri)
file_size = self.size
# TODO: size unknown?
if not file_size:
return b""
if start >= file_size:
return b""
end = file_size - 1
if size:
end = start + size - 1
if end > file_size - 1:
end = file_size - 1
# logger.debug("Reading from %s to %s" % (start, end))
b = self.read_bytes(start, end)
self._offset += len(b)
return b
def write(self, b):
"""Writes data into the file.
Args:
b: Bytes data
Returns: The number of bytes written into the file.
"""
if self.closed:
raise ValueError("write to closed file %s" % self.uri)
# Create a temp local file
self.local()
# Write data from buffer to file
self.__file_io.seek(self.tell())
size = self.__file_io.write(b)
self._offset += size
return size
def __rm_temp(self):
if self.temp_path and os.path.exists(self.temp_path):
os.unlink(self.temp_path)
logger.debug("Deleted temp file %s of %s" % (self.temp_path, self.uri))
self.temp_path = None
return
def open(self, mode='r', *args, **kwargs):
"""Opens the file for writing
"""
if not self._closed:
self.close()
super().open(mode)
self._closed = False
# Reset offset position when open
self.seek(0)
if 'a' in self.mode:
# Move to the end of the file if open in appending mode.
self.seek(0, 2)
elif 'w' in self.mode:
# Create empty local file
self.local()
return self
def close(self):
"""Flush and close the file.
This method has no effect if the file is already closed.
"""
if self._closed:
return
if self.__file_io:
if not self.__file_io.closed:
self.__file_io.close()
self.__file_io = None
if self.temp_path:
logger.debug("Uploading file to %s" % self.uri)
with open(self.temp_path, 'rb') as f:
self.upload(f)
# Remove __temp_file if it exists.
self.__rm_temp()
# Set _closed attribute
self._closed = True
@property
def updated_time(self):
raise NotImplementedError()
def exists(self):
raise NotImplementedError()
def get_size(self):
raise NotImplementedError()
def delete(self):
raise NotImplementedError()
def upload(self, from_file_obj):
raise NotImplementedError()
def download(self, to_file_obj):
"""Downloads the data to a file object
Caution: This method does not call flush()
"""
raise NotImplementedError()
def read_bytes(self, start, end):
"""Reads bytes from position start to position end, inclusive
"""
raise NotImplementedError()
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2
] |
virtool/caches/models.py | virtool/virtool | 39 | 89785 | from sqlalchemy import Column, DateTime, Enum, Integer, String
from sqlalchemy.sql.schema import UniqueConstraint
from virtool.pg.base import Base
from virtool.samples.models import ArtifactType
class SampleArtifactCache(Base):
"""
SQL model to store a cached sample artifact
"""
__tablename__ = "sample_artifacts_cache"
__table_args__ = (UniqueConstraint("key", "name", "sample"),)
id = Column(Integer, primary_key=True)
key = Column(String, nullable=False)
name = Column(String, nullable=False)
name_on_disk = Column(String)
sample = Column(String, nullable=False)
size = Column(Integer)
type = Column(Enum(ArtifactType), nullable=False)
uploaded_at = Column(DateTime)
class SampleReadsCache(Base):
"""
SQL model to store cached sample reads files
"""
__tablename__ = "sample_reads_cache"
__tableargs__ = (UniqueConstraint("key", "name", "sample"),)
id = Column(Integer, primary_key=True)
key = Column(String, nullable=False)
name = Column(String(length=13), nullable=False)
name_on_disk = Column(String, nullable=False)
sample = Column(String, nullable=False)
size = Column(Integer)
uploaded_at = Column(DateTime)
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] |
2750/solution_bubble.py | bossm0n5t3r/BOJ | 2 | 1618051 | <gh_stars>1-10
def sol():
data = []
for _ in range(int(input())):
data.append(int(input()))
bubble(data)
return data
def bubble(data):
while True:
flag = False
for index in range(len(data) - 1):
if data[index] > data[index + 1]:
temp = data[index]
data[index] = data[index + 1]
data[index + 1] = temp
flag = True
if not flag:
break
return data
if __name__ == "__main__":
for i in sol():
print(i)
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7295,
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1596,
29898,
29875,
29897,
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2
] |
pynq_networking/lib/mqttsn_sw.py | Xilinx/PYNQ-Networking | 40 | 30489 | <filename>pynq_networking/lib/mqttsn_sw.py<gh_stars>10-100
# Copyright (c) 2017, Xilinx, Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
# OR BUSINESS INTERRUPTION). HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import struct
import logging
logging.getLogger("kamene.runtime").setLevel(logging.ERROR)
from kamene.all import *
from .mqttsn import *
__author__ = "<NAME>"
__copyright__ = "Copyright 2017, Xilinx"
__email__ = "<EMAIL>"
""" Kamene implementation of the MQTTSN protocol """
def valid_ack(ack, t):
if isinstance(ack[IP].payload, ICMP):
print("Error response:")
ack[IP].payload.show()
return False
if not isinstance(ack[MQTTSN].payload, t):
print("Unexpected response should have been " + str(t) + ":")
ack.payload.show()
return False
return True
class MQTT_Client:
def __init__(self, serverIP, serverPort, name, verbose=0):
self.serverIP = serverIP
self.serverPort = serverPort
self.client = name
self.verbose = verbose
def __enter__(self):
try:
self.connect()
except Exception:
raise Exception
return self
def __exit__(self, type, value, traceback):
self.disconnect()
def connect(self):
"""Establish the connection.
Return the valid acknowledgement.
"""
connack = sr1(IP(dst=self.serverIP) /
UDP(sport=50000, dport=self.serverPort) /
MQTTSN() / MQTTSN_CONNECT(client=self.client),
verbose=self.verbose)
return valid_ack(connack, MQTTSN_CONNACK)
def disconnect(self):
"""Destroy the connection.
The rsmb tends to respond without the disconnect payload.
"""
_ = send(IP(dst=self.serverIP) /
UDP(sport=50000, dport=self.serverPort) /
MQTTSN() / MQTTSN_DISCONNECT(),
verbose=self.verbose)
def register(self, topic):
"""Register the given topic.
Return the associated topicID.
"""
regack = sr1(IP(dst=self.serverIP) /
UDP(sport=50000, dport=self.serverPort) /
MQTTSN() / MQTTSN_REGISTER(topic=topic),
verbose=self.verbose)
if not valid_ack(regack, MQTTSN_REGACK):
raise RuntimeError("register() not acknowledged.")
return regack[MQTTSN_REGACK].topicID
def publish(self, topicID, message, qos=1):
"""Publish on the given topicID with the given message.
With qos=1, it will guarantee the delivery.
Return bool indicating success.
"""
frame = IP(dst=self.serverIP) / \
UDP(sport=50000, dport=self.serverPort) / \
MQTTSN() / MQTTSN_PUBLISH(qos=qos,
topicID=topicID, message=message)
if qos == 0:
send(frame, verbose=self.verbose)
if qos == 1:
puback_frame = sr1(frame, verbose=self.verbose)
if not valid_ack(puback_frame, MQTTSN_PUBACK):
return False
return True
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] |
toggl_dinero/dinero.py | esben/toggl-dinero | 1 | 135632 | """This module contains a class for providing access to Dinero API."""
from oauthlib.oauth2 import LegacyApplicationClient
from requests_oauthlib import OAuth2Session
import json
import logging
# Dinero invoice creation procedure
#
# Get an OAuth2 token from https://authz.dinero.dk/dineroapi/oauth/token
# and attach that to all following requests (see https://api.dinero.dk/docs)
#
# Get list of organisations, and use that to resolve/get organisation id
# (Geanix ApS).
#
# Get list of contacts, and use that to resolve contact client name to
# contactGuid number.
#
# Make create invoice request
# - ContactGuid
# - Language (da-DK / en-GB)
# - ProductLines[]
# - BaseAmountValue
# - Description (project title)
# - Quantity (hours)
# - Unit ("hours")
DINERO_TOKEN_URL = 'https://authz.dinero.dk/dineroapi/oauth/token'
class DineroAPI:
"""A connection object for accessing Dinero API."""
API_URL_V1 = 'https://api.dinero.dk/v1'
API_URL_V1_2 = 'https://api.dinero.dk/v1.2'
def __init__(self, client_id, client_secret, api_key, name=None):
"""
Create a new instance.
:param client_id: Dinero client ID.
:param client_secret: Dinero client secret.
:param api_key: Dinero API key.
:param name: Name of organization to work/on.
"""
client = LegacyApplicationClient(client_id=client_id)
oauth = OAuth2Session(client=client)
token = oauth.fetch_token(token_url=DINERO_TOKEN_URL,
username=api_key, password=<PASSWORD>_key,
client_id=client_id,
client_secret=client_secret)
self.session = oauth
self.token = token
if not self.set_organization(name):
raise Exception('Could not set organization')
def set_organization(self, name=None):
"""Set the Dinero organization to work with/on.
:param name: Name of organization.
"""
url = f'{self.API_URL_V1}/organizations'
params = {'fields': 'name,id'}
orgs = self.session.get(url, params=params).json()
if name is None:
if len(orgs) == 1:
self.organization = orgs[0]['id']
return self.organization
else:
return None
for org in orgs:
if org['name'] == name:
self.organization = org['id']
return self.organization
return None
def get_contacts(self):
"""Get all contacts of current organization."""
url = f'{self.API_URL_V1}/{self.organization}/contacts'
return self.session.get(url)
def get_contact(self, contact):
"""Get named contact of current organization."""
url = f'{self.API_URL_V1}/{self.organization}/contacts/{contact}'
return self.session.get(url)
def update_contact(self, contact, data):
"""
Update contact information in current organization.
:param contact: Contact id to change.
:param data: Update contact data to upload.
"""
url = f'{self.API_URL_V1}/{self.organization}/contacts/{contact}'
self.session.put(url, json=data)
def _get_matching_contact(self, fields, match_fn):
url = f'{self.API_URL_V1}/{self.organization}/contacts'
params = {
'fields': fields,
'page': 0}
while True:
contacts = self.session.get(url, params=params).json()
for contact in contacts['Collection']:
match = match_fn(contact)
if match:
return match
results = contacts['Pagination']['Result']
pagesize = contacts['Pagination']['PageSize']
if results < pagesize:
break
params['page'] += 1
return None
def contact_id(self, name):
"""Get contact ID of named contact."""
def name_match(c):
if c['name'] == name:
return c['contactGuid']
else:
return None
return self._get_matching_contact('name,contactGuid', name_match)
def contact_with_external_reference(self, key, value):
"""
Get contact ID of contact with matching ExternalReference.
The ExternalReference field is assumed to be a JSON object, and a
contact matches if the ExternalReference JSON object has a key/value
match.
:param key: Key to match.
:param value: Value to match.
"""
def extref_match(c):
extref = c.get('ExternalReference')
if extref is None:
return None
try:
extref = json.loads(extref)
except Exception as e:
logging.warn(f'Bad ExternalReference value: {e}: {extref}')
return None
if extref.get(key) == value:
return c['contactGuid']
return None
return self._get_matching_contact(
'name,contactGuid,ExternalReference', extref_match)
def create_invoice(self, contact, product_lines=[],
language=None, currency=None, comment=None, date=None):
"""
Create draft invoice.
:param contact: Contact ID.
:param product_lines: Product lines for the invoices API.
:param language: Language of the invoice.
:param currency: Currency to use for the invoice.
:param comment: Comment to add to invoice.
:param date: Invoice date.
"""
url = f'{self.API_URL_V1}/{self.organization}/invoices'
if language == 'da':
language = 'da-DK'
elif language == 'en':
language = 'en-GB'
body = {
'ContactGuid': contact,
'Currency': currency,
'Language': language,
'Comment': comment,
'Date': date,
'ProductLines': product_lines,
}
body = {k: v for (k, v) in body.items() if v is not None}
resp = self.session.post(url, json=body)
if not resp.ok:
print('Error: Creating invoice failed: ' +
f'{resp.status_code} {resp.reason}')
print(resp.text)
def get_draft_invoice(self, contact):
"""
Get existing draft invoice.
Exactly one draft invoice is expected to exist for the contact. If no
or more than one draft voice exists for the customer, this function
returns None.
:param contact: Contact ID to get draft invoice for.
:return: Invoice data or None.
"""
url = f'{self.API_URL_V1}/{self.organization}/invoices'
params = {'fields': "Guid,Date,Description",
'statusFilter': 'Draft',
'queryFilter': f"ContactGuid eq '{contact}'"}
resp = self.session.get(url, params=params)
if not resp.ok:
print('Error: Getting invoice list failed: ' +
f'{resp.status_code} {resp.reason}')
print(resp.text)
return None
invoices = resp.json()['Collection']
if len(invoices) == 0:
print('Error: No draft invoice found')
return None
if len(invoices) > 1:
print('Error: Multiple draft invoices found')
return None
guid = invoices[0]['Guid']
url = f'{self.API_URL_V1}/{self.organization}/invoices/{guid}'
resp = self.session.get(url, headers={'Accept': 'application/json'})
if not resp.ok:
print('Error: Getting invoice failed: ' +
f'{resp.status_code} {resp.reason}')
print(resp.text)
return None
invoice = resp.json()
return invoice
def update_invoice(self, invoice):
"""
Update existing draft invoice.
:param guid: Invoice data.
"""
guid = invoice['Guid']
# API v1 does not support Text lines, so we need to use at least v1.2
url = f'{self.API_URL_V1_2}/{self.organization}/invoices/{guid}'
resp = self.session.put(url, json=invoice)
if not resp.ok:
print('Error: Updating invoice failed: ' +
f'{resp.status_code} {resp.reason}')
print(resp.text)
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] |
equity/__init__.py | mitpokerbots/equity | 1 | 106799 | <reponame>mitpokerbots/equity<gh_stars>1-10
import os
from flask import Flask, request, render_template
from flask_sslify import SSLify
from pbots_calc import calc
app = Flask(__name__)
config_object_str = 'equity.config.ProdConfig' if os.environ.get('PRODUCTION', False) else 'equity.config.DevConfig'
app.config.from_object(config_object_str)
def get_cards(s, all=False):
if s.strip() == '' and all:
return 'xx'
return s.strip()
@app.route('/', methods=['GET', 'POST'])
def index():
if request.method == 'GET':
return render_template('index.html')
else:
board = get_cards(request.form['board'])
hole = get_cards(request.form['hole'], all=True)
opponent = get_cards(request.form['opponent'], all=True)
discard = get_cards(request.form['discard'])
result = calc(hole + ":" + opponent, board, discard, 100000)
if result is None:
return render_template('index.html', result='fail', hole=hole, opponent=opponent, board=board, discard=discard)
return render_template('index.html', result='success', evs=result.ev, hole=hole, opponent=opponent, board=board, discard=discard)
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mtsv/parsing.py | ktaed/MTSv | 0 | 156360 | import argparse
import configparser
import os
import sys
import ast
import logging
import numpy as np
from contextlib import suppress
from glob import glob
from collections import namedtuple
from mtsv.utils import(error, warn, specfile_read)
from mtsv.argutils import (read, export)
from mtsv import (DEFAULT_LOG_FNAME, DEFAULT_CFG_FNAME)
logger = logging.getLogger(__name__)
SECTIONS = [
"READPREP", "BINNING", "SUMMARY",
"ANALYZE", "EXTRACT", "WGFAST", "CONCOCT"]
split = str.split
strip = str.strip
rsplit = str.rsplit
bsplit = bytes.split
bstrip = bytes.strip
brsplit = bytes.rsplit
def make_sub_parser(subparser, cmd, cmd_class):
global_defaults = get_global_config(cmd_class.config_section)
help_str = global_defaults["_meta_{}".format(cmd)]["help"]
p = subparser.add_parser(
cmd, help=help_str,
description="Additional Snakemake commands may also be provided")
for arg, desc in global_defaults.items():
if "_meta" in arg:
continue
if 'type' in desc:
desc['type'] = TYPES[desc['type']]
if 'choices' in desc and 'help' in desc:
desc['help'] += " Choices are {}".format(desc['choices'])
if 'default' in desc and 'help' in desc:
desc['help'] += " (default: {})".format(desc['default'])
if 'required' in desc and 'help' in desc:
desc['help'] += " [REQUIRED]"
if 'action' in desc and desc['action'] in ACTIONS:
desc['action'] = getattr(
sys.modules[__name__], desc['action'])
arg = "--{}".format(arg)
if 'positional' in desc:
del desc['positional']
p.add_argument(
arg, **desc
)
add_default_arguments(p)
p.set_defaults(cmd_class=cmd_class)
def create_config_file(config_file):
cfg_file_str = ""
for cmd in SECTIONS:
spec = specfile_read(cmd)
opts = read.from_yaml(spec)
meta = opts['_meta_{}'.format(cmd.lower())]
del opts['_meta_{}'.format(cmd.lower())]
opts['_meta'] = meta
cfg_file_str += export.to_config(
cmd, opts) + "\n"
config_file.write(cfg_file_str)
config_file.close()
def get_global_config(include_cmds):
args_dict = {}
for cmd in include_cmds:
spec = specfile_read(cmd.lower())
args_from_yaml = read.from_yaml(spec)
for key, value in args_from_yaml.items():
if key in args_dict:
# for full pipeline, ensure that
# the outfile version replaces
# any input files so argparse does
# not assume they should be present
if 'out' in args_dict[key]['type']:
continue
args_dict[key] = value
return args_dict
def format_cml_params(include_cmd, args, ignore, include):
command_list = []
for arg, desc in get_global_config([include_cmd]).items():
if '_meta' in arg:
continue
if 'positional' in desc:
continue
if arg in ignore:
continue
if arg in args and args[arg] is not None:
try:
val = args[arg].name
except AttributeError:
val = str(args[arg])
command_list += ["--{}".format(arg), val]
for incl in include:
command_list.append(incl)
return " ".join(command_list)
def add_default_arguments(parser):
parser.add_argument(
'--wd', '-wd', "--working_dir", type=str,
default=os.getcwd(),
help="Specify working directory to place output. "
"(default: {})".format(os.getcwd())
)
parser.add_argument(
'-c', "--config", type=outfile_type,
help="Specify path to config file path, "
"relative to working directory, "
"not required if using default config. "
)
parser.add_argument(
'-lf', "--log_file", type=outfile_type,
default=os.path.join("./Logs", DEFAULT_LOG_FNAME),
help="Set log file path, "
"absolute or relative to working dir. "
"(default: ./Logs/{})".format(DEFAULT_LOG_FNAME)
)
parser.add_argument(
'-t', "--threads", type=positive_int,
default=4,
help="Number of worker threads to spawn. (default: 4)"
)
def get_missing_sections(config_file):
config = configparser.ConfigParser()
config.read(config_file)
return [s for s in SECTIONS if s not in config.sections()]
def parse_config_sections(config_file, sections):
config = configparser.ConfigParser()
config.read(config_file)
config_for_sections = {}
try:
for section in sections:
with suppress(configparser.NoSectionError):
for cmd, val in config.items(section):
# Only add if there is a value
# avoids adding optional params
if val:
config_for_sections[cmd] = val
except configparser.ParsingError:
error(
"Cannot parse config file: {}".format(
config_file.name))
return config_for_sections
def path_type(input_path):
'''Path_type is for paths that should already exist.
If path exists, returns absolute path, otherwise raise
ArgumentTypeError'''
if not os.path.isdir(input_path):
raise argparse.ArgumentTypeError("Not a valid path")
return os.path.abspath(input_path)
def flag_type(input_val):
if input_val != "T" and input_val != "F":
raise argparse.ArgumentTypeError(
"Invalid flag, must be either T or F")
if input_val == "T":
return True
if input_val == "F":
return False
def project_dir_type(input_path):
'''Creates a project directory if one does not exist and
Throws PermissionError if there are no permissions to create
directory. Returns absolute path to directory.'''
input_path = os.path.abspath(input_path)
if not os.path.isdir(input_path):
try:
os.mkdir(input_path)
except PermissionError:
error(
"No permission to make directory: {}".format(input_path))
if os.getcwd() != input_path:
os.chdir(input_path)
return input_path
def path_list_type(input_paths):
'''Returns list of absolute paths using glob'''
if not isinstance(input_paths, (list,)):
input_paths = [input_paths]
glob_list = []
for path in input_paths:
glob_list += glob(path)
if not glob_list:
raise argparse.ArgumentTypeError("Not a valid path")
return list({os.path.abspath(path) for path in glob_list})
def arg_list_type(args):
""" Returns a list of arguments """
new_args = []
for arg in args:
arg = [a.replace("\'","").replace("\"", "") for a in arg.split()]
new_args += arg
return new_args
class Cmds(argparse.Action):
def __init__(self, option_strings, dest, nargs='+', **kwargs):
super(Cmds, self).__init__(option_strings, dest, nargs, **kwargs)
def __call__(self, parser, namespace, values, option_string=None):
values = arg_list_type(values)
setattr(namespace, self.dest, values)
class Glob(argparse.Action):
def __init__(self, option_strings, dest, nargs='+', **kwargs):
super(Glob, self).__init__(option_strings, dest, nargs, **kwargs)
def __call__(self, parser, namespace, values, option_string=None):
values = path_list_type(values)
setattr(namespace, self.dest, values)
def outpath_type(input_path):
'''Outpath_type creates a directory if one does not exist.
Throws PermissionError if there are no permissions to create
directory. If path already exists and it is not empty, a warning
is issued. Returns absolute path to directory.'''
input_path = os.path.abspath(input_path)
try:
os.mkdir(input_path)
logger.info("Creating directory: {}".format(input_path))
except PermissionError:
error(
"No permission to make directory: {}".format(input_path))
except OSError:
logger.info(
"Directory already exists: {}. ".format(input_path))
if os.listdir(input_path):
warn("Files in {} may be overwritten!".format(input_path))
return input_path
def file_type(input_file):
'''File type is for input files that
should already exist.
Check if input_file is a file.
If yes, return absolute path to
file else throw ArgumentTypeError
exception'''
input_file = os.path.abspath(input_file)
if not os.path.isfile(input_file):
raise argparse.ArgumentTypeError(
"Not a valid file path: {}".format(input_file))
return input_file
def outfile_type(input_file):
'''Checks that path to file exists,
if it doesn't, the path is created,
returns abs path to file. PermissionError
exception when there is no permission to
create directory'''
input_file = os.path.abspath(input_file)
path = os.path.dirname(input_file)
if not os.path.isdir(path):
try:
os.mkdir(path)
except PermissionError:
error(
"No permission to create file: {}".format(input_file)
)
return input_file
def write_handle_type(input_file):
'''Returns a handle to an outfile'''
return open(outfile_type(input_file), 'w')
def read_handle_type(input_file):
'''Returns a handle to an infile'''
return open(file_type(input_file), 'r')
def nonneg_int(input_val):
''' Make a non negative int type for argparse'''
try:
input_val = int(input_val)
if input_val < 0:
raise ValueError
except ValueError:
raise argparse.ArgumentTypeError("Negative integer not valid")
return input_val
def proportion(input_val):
"""make proportion type for argparse"""
try:
input_val = float(input_val)
if input_val > 1 or input_val < 0:
raise ValueError
except ValueError:
raise argparse.ArgumentTypeError("Not a proportion")
return input_val
def positive_int(input_val):
'''Make a positive int type for argparse'''
try:
input_val = int(input_val)
if input_val <= 0:
raise ValueError
except ValueError:
raise argparse.ArgumentTypeError("Not a positive integer")
return input_val
Record = namedtuple('Record', ['read_id', 'counts', 'taxa', 'read_name'])
def parse_output_row(row):
read_name, taxa = split(row, ":")
taxa = np.array([tax for tax in split(taxa, ",")], dtype=int)
counts = np.array([c for c in split(read_name, "_")[1:]], dtype=int)
read_id = split(read_name, "_")[0]
return Record(
read_id=read_id, counts=counts, taxa=taxa, read_name=read_name)
def parse_output_row_bytes(row):
read_name, taxa = bsplit(row, b":")
taxa = np.array([tax for tax in bsplit(taxa, b",")], dtype=int)
counts = np.array([c for c in bsplit(read_name, b"_")[1:]], dtype=int)
read_id = bsplit(read_name, b"_")[0]
return Record(
read_id=read_id, counts=counts, taxa=taxa, read_name=read_name)
def parse_query_id(query_id):
return np.array([int(q) for q in query_id.split("_")[1:]])
def make_table(columns, headers):
if len(headers) != len(columns):
raise ValueError(
"Header does not match number of columns")
max_sizes = []
table = ""
for column, header in zip(columns, headers):
max_sizes.append( max([len(str(c)) for c in column] + [len(str(header))]) )
div = " ".join(["=" * size for size in max_sizes]) + "\n"
table += div
fmt = []
for i, sz in zip(range(len(columns)), max_sizes):
fmt.append("{{{0}:<{1}}}".format(i, sz))
fmt = " ".join(fmt) + "\n"
# add header
table += fmt.format(*headers)
table += div
for row in [*zip(*columns)]:
table += fmt.format(*row)
table += div
return table
TYPES = {
'int': int,
'str': str,
'float': float,
'bool': bool,
'list': ast.literal_eval,
'file_type': file_type,
'outfile_type': outfile_type,
'path_type': path_type,
'outpath_type': outpath_type,
'positive_int': positive_int,
'nonneg_int': nonneg_int,
'proportion': proportion,
'project_dir_type': project_dir_type,
'write_handle_type': write_handle_type,
'read_handle_type': read_handle_type,
'path_list_type': path_list_type,
'flag_type': flag_type,
'arg_list_type': arg_list_type
}
ACTIONS = {'Glob': Glob, 'Cmds': Cmds}
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auc_vs_p50_1_model_v2_val_folds.py | kkraoj/lfmc_for_ignitions | 0 | 109126 | # -*- coding: utf-8 -*-
"""
Created on Mon May 25 22:33:04 2020
@author: kkrao
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import sklearn.ensemble
import sklearn.metrics
import sklearn.model_selection
import statsmodels.api as sm
import init
sns.set(style='ticks',font_scale = 0.9)
def assemble_df(buffer = "lfmc_variogram"):
columns = ['system:index', 'BurnDate', 'FirstDay', 'LastDay', 'QA', 'Uncertainty',
'area', 'erc_t_15_inside', 'erc_t_15_outside',
'landcover', 'lfmc_t_1_inside', 'lfmc_t_1_outside', 'ppt_t_1_inside',
'ppt_t_1_outside', 'system:time_start', 'vpd_t_4_inside',
'vpd_t_4_outside', 'year', '.geo', 'lfmc_t_1_seasonal_mean_inside',
'lfmc_t_1_seasonal_mean_outside', 'lfmc_t_2_inside', 'lfmc_t_2_outside',
'fwi_t_4_inside', 'fwi_t_4_outside', 'p50']
if buffer == "lfmc_variogram":
df = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_with_climate_500m_variogram.csv"))
dfr = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_extra_lfmc_vars_500m_variogram.csv"))
dfr = dfr[['lfmc_t_1_seasonal_mean_inside','lfmc_t_1_seasonal_mean_outside', 'lfmc_t_2_inside', 'lfmc_t_2_outside']]
df = df.join(dfr)
dfr = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_fwi_500m_variogram.csv"))
dfr = dfr[['fwi_t_4_inside','fwi_t_4_outside']]
df = df.join(dfr)
elif buffer == "constant":
df = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_with_climate_fwi_extra_lfmc_vars_constant_buffer_20km_width_10km.csv"))
elif buffer == "vpd_variogram":
df = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_LFMC_climate_FWI_500m_variogram_of_vpd_4_oct_2021.csv"))
elif buffer == "lfmc_variogram_large":
df = pd.read_csv(os.path.join(init.dir_data, "fire_collection_median_LFMC_climate_FWI_500m_variogram_of_LFMC_100km_max.csv"))
dfr = pd.read_csv(os.path.join(init.dir_data, "fire_collection_500m_with_p50.csv"))
dfr = dfr[['p50']]
df = df.join(dfr)
df = df.loc[df.landcover.isin(init.lc_dict.keys())]
df['landcover'] = df.landcover.map(init.lc_dict)
df = df[columns]
return df
def plot_p50_hist(df):
fig, ax = plt.subplots(figsize = (3,3))
df.p50.hist(ax = ax)
ax.set_xlabel('P50 (Mpa)')
ax.set_ylabel('Frequency')
#%% just lfmc first
def auc_by_cat(clf, ndf, ndf_dict, test_index, kind = 'occurence'):
auc = pd.DataFrame(index = [0],columns = ndf_dict.keys())
for cat in auc.columns:
select = ndf_dict[cat]
select = select[select].index
select = list(set(select)&set(test_index))
sub = ndf.loc[select].copy()
if kind == "occurence":
X = sub.drop(['fire'], axis = 1).values
y = sub['fire'].values
try:
auc.loc[0,cat] = sklearn.metrics.roc_auc_score(y,clf.predict(X))
except ValueError:
print(f"[INFO] No data for this fold in {cat}. Skipping.")
auc.loc[0,cat] = sklearn.metrics.roc_auc_score(y,clf.predict(X))
return auc
def calc_auc_occurence(dfsub, category_dict, category, clf, folds = 3, n_cv_reps = 5):
df = dfsub.copy()
auc = pd.DataFrame(index = range(folds),columns = category_dict.keys())
ndf = pd.DataFrame()
for var in ['outside','inside']:
cols = [col for col in df.columns if var in col] + [category]
# cols.remove('lfmc_t_1_%s'%var)
data = df[cols].copy()
new_cols = [col.split('_')[0] for col in data.columns]
data.columns = (new_cols)
data['fire'] = int(var=='inside')
ndf = pd.concat([ndf, data], axis = 0).reset_index(drop=True)
ndf = ndf.sample(frac=1).reset_index(drop=True)
ndf.dropna(inplace = True)
ndf_dict = {}
for i in ndf[category].unique():
ndf_dict[i] = ndf[category]==i
ndf = ndf.drop(category, axis = 1)
X = ndf.drop(['fire'], axis = 1).values
y = ndf['fire'].values
for rep in n_cv_reps
kf = sklearn.model_selection.KFold(n_splits=folds, shuffle = False, random_state = 42)
for index, (train_index, test_index) in enumerate(kf.split(X)):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
try:
clf.fit(X_train, y_train)
# rfc_disp = sklearn.metrics.plot_roc_curve(clf, X, y, ax=ax,label = lc,color = color_dict[lc])
auc.loc[index, :] = auc_by_cat(clf, ndf, ndf_dict, test_index, kind = 'occurence').values
except:
print("Could not fit RF")
auc.loc[index,:] = np.nan
auc.loc[0,:] = auc.mean()
auc = auc.drop(auc.index.difference([0]), axis = 0)
return auc
def ensemble_auc(dfsub, category_dict, category, clf, seeds = 5, label = 'All variables'):
dummy = calc_auc_occurence(dfsub, category_dict, category, clf)
aucs = np.expand_dims(dummy.values, axis = 2)
for
for seed in range(seeds):
print(f"[INFO] Fitting RF for iteration {itr}/{iters}")
clf.random_state = seed
auc = np.expand_dims(calc_auc_occurence(dfsub, category_dict, category, clf).values, axis = 2)
print(f"[INFO] Average AUC = {auc.mean(axis = 1)[0][0]:0.2f}")
aucs = np.append(aucs,auc, axis = 2)
# print("aucs ready")
dummy.loc[:,:] = np.nanmean(aucs.astype(float), axis = 2)
mean = dummy.copy()
dummy.loc[:,:] = np.nanquantile(aucs.astype(float), 0.05, axis = 2)
ql = (dummy.copy() - mean).abs() ## for plotting we need absolute
dummy.loc[:,:] = np.nanquantile(aucs.astype(float), 0.95, axis = 2)
qu = dummy.copy() - mean
return mean, ql, qu
def calc_aucs(dfs, category_dict, category, replace_by_random = True):
df = dfs.copy()
allVars = pd.DataFrame(index = [0],columns = category_dict.keys())
onlyClimate = allVars.copy()
cols = [col for col in df.columns if 'lfmc' in col]+['landcover']
# cols = ['landcover']
cols+=[col for col in df.columns if 'erc' in col]
cols+=[col for col in df.columns if 'ppt' in col]
cols+=[col for col in df.columns if 'vpd' in col]
cols+=[col for col in df.columns if 'fwi' in col]
df = df[cols]
df['lfmc_t_1_inside_anomaly'] = df['lfmc_t_1_inside'] - df['lfmc_t_1_seasonal_mean_inside']
df['lfmc_t_1_outside_anomaly'] = df['lfmc_t_1_outside'] - df['lfmc_t_1_seasonal_mean_outside']
df.drop(['lfmc_t_1_seasonal_mean_inside','lfmc_t_1_seasonal_mean_outside'],axis = 1, inplace = True)
###testing with random numbers instead of LFMC
# df.loc[:,remove_lfmc] = np.zeros(shape = df.loc[:,remove_lfmc].shape)
# clf = sklearn.ensemble.RandomForestClassifier(max_depth=15, min_samples_leaf = 5, random_state=0, oob_score = True,n_estimators = 50)
clf = sklearn.ensemble.RandomForestClassifier(max_depth=8, random_state=0, oob_score = True,n_estimators = 50)
allVars= ensemble_auc(df, category_dict,category, clf)
# allVars = calc_auc(df, size_dict, clf)
remove_lfmc = [col for col in df.columns if 'lfmc' in col]
if replace_by_random:
###testing with random numbers instead of LFMC
df.loc[:,remove_lfmc] = np.random.uniform(size = df.loc[:,remove_lfmc].shape)
onlyClimate = ensemble_auc(df,category_dict, category, clf)
else:
onlyClimate = ensemble_auc(df.drop(remove_lfmc, axis = 1), category_dict,category, clf)
onlyClimate.index.name = "only climate"
allVars.index.name = "all variables"
df = pd.DataFrame({"all_vars":allVars.iloc[0], "only_climate":onlyClimate.iloc[0]})
df = df.sort_values("all_vars", ascending = True)
return df
def plot_importance(df):
fig, ax1= plt.subplots(figsize = (3,3))
ax1.barh(width = df.only_climate,y = df.index,edgecolor = list(df.index.map(init.color_dict).values), color = "w")
ax1.barh(width = df.all_vars - df.only_climate,y = df.index,left = df.only_climate, \
color = list(df.index.map(init.color_dict).values), \
edgecolor = list(df.index.map(init.color_dict).values),\
xerr = df[['lower_q', 'upper_q']].T.values,\
)
ax1.set_ylabel("")
ax1.set_xlabel('AUC')
ax1.set_xlim(0.5,1)
# ax1.set_title("Small fires")
##############################################################################
df = assemble_df(buffer = "lfmc_variogram_large")
df = df.loc[df.BurnDate>=150]
# df = df.loc[df.area>=1]
LC_DICT = {}
for i in df.landcover.unique():
LC_DICT[i] = df.landcover==i
P50_DICT = {'low':(df.p50>=-5),
'high': (df.p50<-5),
}
# plot_p50_hist(df)
auc = calc_aucs(df, LC_DICT, category = "landcover", replace_by_random = True)
plot_box(auc)
# print(mean)
# print(std)
##############################################################################
#%%invs
# for lc in LC_DICT.keys():
# sub = df.loc[df.landcover==lc]
# fig, ax = plt.subplots(figsize = (3,3))
# ax.hist(sub.lfmc_t_2_inside, color = "orange", alpha = 0.5, density = True, label = "Inside", bins = 100)
# ax.hist(sub.lfmc_t_2_outside, color = "blue", alpha = 0.5, density = True, label = "Outside", bins = 100)
# ax.set_xlabel("LFMC_t_1")
# ax.set_ylabel("Frequency")
# plt.show()
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] |
setup.py | Luke-Poeppel/treeplotter | 7 | 108357 | <reponame>Luke-Poeppel/treeplotter<filename>setup.py
####################################################################################################
# File: setup.py
# Purpose: Setup of the package.
#
# Author: <NAME>
#
# Location: Kent, CT 2021
####################################################################################################
from setuptools import setup, find_packages
VERSION = "0.5.0"
with open('README.md') as f:
long_description = f.read()
setup(
name="treeplotter",
version=VERSION,
author="<NAME>",
author_email="<EMAIL>",
description="Python package for tree plotting.",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/Luke-Poeppel/treeplotter",
packages=find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
python_requires='>=3.7',
include_package_data=True,
package_data={"treeplotter": ["VERSION"]},
install_requires=[
"click",
"jsonpickle",
"jinja2",
"Wand",
],
extras_require={
"dev": [
"flake8",
"pre-commit",
"pytest",
]
},
entry_points={
"console_scripts": [
"treeplotter = treeplotter.cli:treeplotter"
]
},
) | [
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explore/utils.py | WilliamQLiu/improved-parakeet | 2 | 93211 | from cStringIO import StringIO
from xml.etree import ElementTree as ET
import requests
from scrapy.selector import Selector, XmlXPathSelector
from scrapy.spider import Spider
def parse_single_element(element, name):
"""
Helper function to parse a single XML element for name,
returns dict of the key and text.
"""
data = {}
for key in element:
if key.tag == name:
data[name] = key.text
return data
def parse_single_listing(listing):
"""
Parse an individual listing for the following:
Location - StreetAddress
ListingDetails - Price, MlsId, MlsName, DateListed
BasicDetails - Description, Bathrooms
RichDetails - Appliances
"""
location_results = listing.iter('Location')
for item in location_results:
loc_data = parse_single_element(item, 'StreetAddress')
listing_results = listing.iter('ListingDetails')
for item in listing_results:
listing_data = parse_single_element(item, 'Price')
print listing_data
def get_data_feed(url):
""" Get a data feed from url, return dataframe """
response = requests.get(url)
tree = ElementTree.fromstring(response.content)
tree.write('sample_data.xml')
for listing in tree.getchildren():
parse_single_listing(listing)
def write_xml_to_file(url, location):
""" GET XML from 'url', write to local file 'location' """
try:
response = requests.get(url)
if response.status_code == 200:
file = open(location, 'w')
file.write(response.content)
file.close()
return "Successfully wrote to file"
return ("Error %s with unexpected response status code" %
response.status_code)
except requests.exceptions.ConnectionError as e:
return ("Error %e with connecting to url" % e)
def read_xml_schema(xml_schema):
""" returns xml_schema (XSD) file as a string """
with open(xml_schema, 'r') as schema_file:
schema = schema_file.read()
return schema
if __name__ == '__main__':
print 'Running'
local_file = 'sample_data.xml'
schema_file = 'schema.xsd'
# get our xml data from a url source
write_xml_to_file(
url='http://syndication.enterprise.websiteidx.com/feeds/BoojCodeTest.xml',
location=local_file)
# verify data against a schema
#schema = read_xml_schema(schema_file)
#valid = StringIO(schema)
#MrXMLParse.run()
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oandapy/exceptions.py | extreme4all/oandapy | 0 | 22661 | <gh_stars>0
"""Exceptions."""
class OandaError(Exception):
""" Generic error class, catches oanda response errors
"""
def __init__(self, error_response):
self.error_response = error_response
msg = f"OANDA API returned error code {error_response['code']} ({error_response['message']}) "
super(OandaError, self).__init__(msg)
class BadEnvironment(Exception):
"""environment should be: sandbox, practice or live."""
def __init__(self, environment):
msg = f"Environment '{environment}' does not exist"
super(BadEnvironment, self).__init__(msg)
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extensisq/common.py | WRKampi/extensisq | 2 | 103993 | <reponame>WRKampi/extensisq<filename>extensisq/common.py
import numpy as np
from math import sqrt, copysign
from warnings import warn
import logging
from scipy.integrate._ivp.common import (
validate_max_step, norm, validate_first_step, warn_extraneous)
from scipy.integrate._ivp.base import OdeSolver, DenseOutput
from scipy.integrate._ivp.rk import MIN_FACTOR, MAX_FACTOR
NFS = np.array(0) # failed step counter
def validate_tol(rtol, atol, y):
"""Validate tolerance values. atol can be scalar or array-like, rtol a
scalar. The bound values are from RKSuite. These differ from those in
scipy. Bounds are applied without warning.
"""
atol = np.asarray(atol)
if atol.ndim > 0 and atol.shape != (y.size, ):
raise ValueError("`atol` has wrong shape.")
if np.any(atol < 0):
raise ValueError("`atol` must be positive.")
if not isinstance(rtol, float):
raise ValueError("`rtol` must be a float.")
if rtol < 0:
raise ValueError("`rtol` must be positive.")
# atol cannot be exactly zero.
# For double precision float: sqrt(tiny) ~ 1.5e-154
tiny = np.finfo(y.dtype).tiny
atol = np.maximum(atol, sqrt(tiny))
# rtol is bounded from both sides.
# The lower bound is lower than in scipy.
epsneg = np.finfo(y.dtype).epsneg
rtol = np.minimum(np.maximum(rtol, 10 * epsneg), 0.01)
return rtol, atol
class RungeKutta(OdeSolver):
"""Base class for explicit runge kutta methods.
This implementation mainly follows the scipy implementation. The current
differences are:
- Conventional (non FSAL) methods are detected and failed steps cost
one function evaluation less than with the scipy implementation.
- A different, more elaborate estimate for the size of the first step
is used.
- Horner's rule is used for dense output calculation.
- A failed step counter is added.
- The stepsize near the end of the integration is different:
- look ahead to prevent too small step sizes
- linear extrapolation if the last step is too small despite it.
- the min_step accounts for the distance between C-values
- the scale (weight) is smoothed differently
- a different tolerance validation is used.
- stiffness detection is added, can be turned off
- second order stepsize control is added.
"""
# effective number of stages
n_stages: int = NotImplemented
# order of the main method
order: int = NotImplemented
# order of the secondary embedded method
error_estimator_order: int = NotImplemented
# runge kutta coefficient matrix
A: np.ndarray = NotImplemented # shape: [n_stages, n_stages]
# output coefficients (weights)
B: np.ndarray = NotImplemented # shape: [n_stages]
# time fraction coefficients (nodes)
C: np.ndarray = NotImplemented # shape: [n_stages]
# error coefficients (weights Bh - B)
E: np.ndarray = NotImplemented # shape: [n_stages + 1]
# dense output interpolation coefficients
P: np.ndarray = NotImplemented # shape: [n_stages + 1,
# order_polynomial]
# Parameters for stiffness detection, optional
stbrad: float = NotImplemented # radius of the arc
tanang: float = NotImplemented # tan(valid angle < pi/2)
# Parameters for stepsize control, optional
sc_params = NotImplemented # tuple, or str
def _init_min_step_parameters(self):
"""Define the parameters h_min_a and h_min_b for the min_step rule:
min_step = max(h_min_a * abs(t), h_min_b)
from RKSuite.
"""
# minimum difference between distinct C-values
cdiff = 1.
for c1 in self.C:
for c2 in self.C:
diff = abs(c1 - c2)
if diff:
cdiff = min(cdiff, diff)
if cdiff < 1e-3:
cdiff = 1e-3
logging.warning(
'Some C-values of this Runge Kutta method are nearly the '
'same but not identical. This limits the minimum stepsize'
'You may want to check the implementation of this method.')
# determine min_step parameters
epsneg = np.finfo(self.y.dtype).epsneg
tiny = np.finfo(self.y.dtype).tiny
h_min_a = 10 * epsneg / cdiff
h_min_b = sqrt(tiny)
return h_min_a, h_min_b
def _init_stiffness_detection(self, nfev_stiff_detect):
if not (isinstance(nfev_stiff_detect, int) and nfev_stiff_detect >= 0):
raise ValueError(
"`nfev_stiff_detect` must be a non-negative integer.")
self.nfev_stiff_detect = nfev_stiff_detect
if NotImplemented in (self.stbrad, self.tanang):
# disable stiffness detection if not implemented
if nfev_stiff_detect not in (5000, 0):
warn("This method does not implement stiffness detection. "
"Changing the value of nfev_stiff_detect does nothing.")
self.nfev_stiff_detect = 0
self.jflstp = 0 # failed step counter, last 40
if self.nfev_stiff_detect:
self.okstp = 0 # successful step counter
self.havg = 0.0 # average stepsize
def _init_sc_control(self, sc_params):
coefs = {"G": (0.7, -0.4, 0, 0.9),
"S": (0.6, -0.2, 0, 0.9),
"W": (2, -1, -1, 0.8),
"standard": (1, 0, 0, 0.9)}
if self.sc_params == NotImplemented:
# use standard controller if not specified otherwise
sc_params = sc_params or "standard"
else:
# use default controller of method if not specified otherwise
sc_params = sc_params or self.sc_params
if (isinstance(sc_params, str) and sc_params in coefs):
kb1, kb2, a, g = coefs[sc_params]
elif isinstance(sc_params, tuple) and len(sc_params) == 4:
kb1, kb2, a, g = sc_params
else:
raise ValueError('sc_params should be a tuple of length 3 or one '
'of the strings "G", "S", "W" or "standard"')
# set all parameters
self.minbeta1 = kb1 * self.error_exponent
self.minbeta2 = kb2 * self.error_exponent
self.minalpha = -a
self.safety = g
self.safety_sc = g ** (kb1 + kb2)
self.min_error_norm = (MAX_FACTOR/g) ** (1/self.error_exponent)
self.standard_sc = True # for first step
def __init__(self, fun, t0, y0, t_bound, max_step=np.inf, rtol=1e-3,
atol=1e-6, vectorized=False, first_step=None,
nfev_stiff_detect=5000, sc_params=None, **extraneous):
warn_extraneous(extraneous)
super(RungeKutta, self).__init__(fun, t0, y0, t_bound, vectorized,
support_complex=True)
self.max_step = validate_max_step(max_step)
self.rtol, self.atol = validate_tol(rtol, atol, self.y)
self.f = self.fun(self.t, self.y)
if self.f.dtype != self.y.dtype:
raise TypeError('dtypes of solution and derivative do not match')
self.error_exponent = -1 / (self.error_estimator_order + 1)
self._init_stiffness_detection(nfev_stiff_detect)
self.h_min_a, self.h_min_b = self._init_min_step_parameters()
self._init_sc_control(sc_params)
# size of first step:
if first_step is None:
b = self.t + self.direction * min(
abs(self.t_bound - self.t), self.max_step)
self.h_abs = abs(h_start(
self.fun, self.t, b, self.y, self.f,
self.error_estimator_order, self.rtol, self.atol))
else:
self.h_abs = validate_first_step(first_step, t0, t_bound)
self.K = np.empty((self.n_stages + 1, self.n), self.y.dtype)
self.FSAL = 1 if self.E[self.n_stages] else 0
self.h_previous = None
self.y_old = None
NFS[()] = 0 # global failed step counter
def _step_impl(self):
# mostly follows the scipy implementation of scipy's RungeKutta
t = self.t
y = self.y
h_abs, min_step = self._reassess_stepsize(t, y)
if h_abs is None:
# linear extrapolation for last step
return True, None
# loop until the step is accepted
step_accepted = False
step_rejected = False
while not step_accepted:
if h_abs < min_step:
return False, self.TOO_SMALL_STEP
h = h_abs * self.direction
t_new = t + h
# calculate stages needed for output
self.K[0] = self.f
for i in range(1, self.n_stages):
self._rk_stage(h, i)
# calculate error norm and solution
y_new, error_norm = self._comp_sol_err(y, h)
# evaluate error
if error_norm < 1:
step_accepted = True
# don't trust very small error_norm values
error_norm = max(self.min_error_norm, error_norm)
if self.standard_sc:
factor = self.safety * error_norm ** self.error_exponent
self.standard_sc = False
else:
# use second order SC controller
h_ratio = h / self.h_previous
factor = self.safety_sc * (
error_norm ** self.minbeta1 *
self.error_norm_old ** self.minbeta2 *
h_ratio ** self.minalpha)
factor = min(MAX_FACTOR, max(MIN_FACTOR, factor))
if step_rejected:
factor = min(1, factor)
h_abs *= factor
else:
step_rejected = True
h_abs *= max(MIN_FACTOR,
self.safety * error_norm ** self.error_exponent)
NFS[()] += 1
self.jflstp += 1 # for stiffness detection
if np.isnan(error_norm) or np.isinf(error_norm):
return False, "Overflow or underflow encountered."
if not self.FSAL:
# evaluate ouput point for interpolation and next step
self.K[self.n_stages] = self.fun(t + h, y_new)
# store for next step, interpolation and stepsize control
self.h_previous = h
self.y_old = y
self.h_abs = h_abs
self.f = self.K[self.n_stages].copy()
self.error_norm_old = error_norm
# output
self.t = t_new
self.y = y_new
# stiffness detection
self._diagnose_stiffness()
return True, None
def _reassess_stepsize(self, t, y):
# limit step size
h_abs = self.h_abs
min_step = max(self.h_min_a * (abs(t) + h_abs), self.h_min_b)
if h_abs < min_step or h_abs > self.max_step:
h_abs = min(self.max_step, max(min_step, h_abs))
self.standard_sc = True
# handle final integration steps
d = abs(self.t_bound - t) # remaining interval
if d < 2 * h_abs:
if d > h_abs:
# h_abs < d < 2 * h_abs: "look ahead".
# split d over last two steps. This reduces the chance of a
# very small last step.
h_abs = max(0.5 * d, min_step)
self.standard_sc = True
elif d >= min_step:
# d <= h_abs: Don't step over t_bound
h_abs = d
else:
# d < min_step: use linear extrapolation in this rare case
h = self.t_bound - t
y_new = y + h * self.f
self.h_previous = h
self.y_old = y
self.t = self.t_bound
self.y = y_new
self.f = None # signals _dense_output_impl
logging.warning(
'Linear extrapolation was used in the final step.')
return None, min_step
return h_abs, min_step
def _estimate_error(self, K, h):
# exclude K[-1] if not FSAL. It could contain nan or inf
return h * (K[:self.n_stages + self.FSAL].T @
self.E[:self.n_stages + self.FSAL])
def _estimate_error_norm(self, K, h, scale):
return norm(self._estimate_error(K, h) / scale)
def _comp_sol_err(self, y, h):
"""Compute solution and error.
The calculation of `scale` differs from scipy: The average instead of
the maximum of abs(y) of the current and previous steps is used.
"""
y_new = y + h * (self.K[:self.n_stages].T @ self.B)
scale = self.atol + self.rtol * 0.5*(np.abs(y) + np.abs(y_new))
if self.FSAL:
# do FSAL evaluation if needed for error estimate
self.K[self.n_stages, :] = self.fun(self.t + h, y_new)
error_norm = self._estimate_error_norm(self.K, h, scale)
return y_new, error_norm
def _rk_stage(self, h, i):
"""compute a single RK stage"""
dy = h * (self.K[:i, :].T @ self.A[i, :i])
self.K[i] = self.fun(self.t + self.C[i] * h, self.y + dy)
def _dense_output_impl(self):
"""return denseOutput, detect if step was extrapolated linearly"""
if self.f is None:
# output was extrapolated linearly
return LinearDenseOutput(self.t_old, self.t, self.y_old, self.y)
# normal output
Q = self.K.T @ self.P
return HornerDenseOutput(self.t_old, self.t, self.y_old, Q)
def _diagnose_stiffness(self):
"""Stiffness detection.
Test only if there are many recent step failures, or after many
function evaluations have been done.
Warn the user if the problem is diagnosed as stiff.
Original source: RKSuite.f, https://www.netlib.org/ode/rksuite/
"""
if self.nfev_stiff_detect == 0:
return
self.okstp += 1
h = self.h_previous
self.havg = 0.9 * self.havg + 0.1 * h # exp moving average
# reset after the first 20 steps to:
# - get stepsize on scale
# - reduce the effect of a possible initial transient
if self.okstp == 20:
self.havg = h
self.jflstp = 0
# There are lots of failed steps (lotsfl = True) if 10 or more step
# failures occurred in the last 40 successful steps.
if self.okstp % 40 == 39:
lotsfl = self.jflstp >= 10
self.jflstp = 0 # reset each 40 steps
else:
lotsfl = False
# Test for stifness after each nfev_stiff_detect evaluations
# then toomch = True
many_steps = self.nfev_stiff_detect//self.n_stages
toomch = self.okstp % many_steps == many_steps - 1
# If either too much work has been done or there are lots of failed
# steps, test for stiffness.
if toomch or lotsfl:
# Regenerate weight vector
avgy = 0.5 * (np.abs(self.y) + np.abs(self.y_old))
tiny = np.finfo(self.y.dtype).tiny
wt = np.maximum(avgy, sqrt(tiny))
# and error vector, wich is a good initial perturbation vector
v0 = np.atleast_1d(self._estimate_error(self.K, self.h_previous))
# stiff_a determines whether the problem is stiff. In some
# circumstances it is UNSURE. The decision depends on two things:
# whether the step size is being restricted on grounds of stability
# and whether the integration to t_bound can be completed in no
# more than nfev_stiff_detect function evaluations.
stif, rootre = stiff_a(
self.fun, self.t, self.y, self.h_previous, self.havg,
self.t_bound, self.nfev_stiff_detect, wt, self.f, v0,
self.n_stages, self.stbrad, self.tanang)
# inform the user about stiffness with warning messages
# the messages about remaining work have been removed from the
# original code.
if stif is None:
# unsure about stiffness
if rootre is None:
# no warning is given
logging.info('Stiffness detection did not converge')
if not rootre:
# A complex pair of roots has been found near the imaginary
# axis, where the stability boundary of the method is not
# well defined.
# A warning is given only if there are many failed steps.
# This reduces the chance of a false positive diagnosis.
if lotsfl:
warn('Your problem has a complex pair of dominant '
'roots near the imaginary axis. There are '
'many recently failed steps. You should '
'probably change to a code intended for '
'oscillatory problems.')
else:
logging.info(
'The problem has a complex pair of dominant roots '
'near the imaginary axis. There are not many '
'failed steps.')
else:
# this should not happen
logging.warning(
'stif=None, rootre=True; this should not happen')
elif stif:
# the problem is stiff
if rootre is None:
# this should not happen
logging.warning(
'stif=True, rootre=None; this should not happen')
elif rootre:
warn('Your problem has a real dominant root '
'and is diagnosed as stiff. You should probably '
'change to a code intended for stiff problems.')
else:
warn('Your problem has a complex pair of dominant roots '
'and is diagnosed as stiff. You should probably '
'change to a code intended for stiff problems.')
else:
# stif == False
# no warning is given
if rootre is None:
logging.info(
'Stiffness detection has diagnosed the problem as '
'non-stiff, without performing power iterations')
elif rootre:
logging.info(
'The problem has a real dominant root '
'and is not stiff')
else:
logging.info(
'The problem has a complex pair of dominant roots '
'and is not stiff')
def h_start(df, a, b, y, yprime, morder, rtol, atol):
"""h_shart computes a starting step size to be used in solving initial
value problems in ordinary differential equations.
This method is developed by <NAME> and described in [1]_. This function
is a Python translation of the Fortran source code [2]_. The two main
modifications are:
using the RMS norm from scipy.integrate
allowing for complex valued input
Parameters
----------
df : callable
Right-hand side of the system. The calling signature is fun(t, y).
Here t is a scalar. The ndarray y has has shape (n,) and fun must
return array_like with the same shape (n,).
a : float
This is the initial point of integration.
b : float
This is a value of the independent variable used to define the
direction of integration. A reasonable choice is to set `b` to the
first point at which a solution is desired. You can also use `b , if
necessary, to restrict the length of the first integration step because
the algorithm will not compute a starting step length which is bigger
than abs(b-a), unless `b` has been chosen too close to `a`. (it is
presumed that h_start has been called with `b` different from `a` on
the machine being used.
y : array_like, shape (n,)
This is the vector of initial values of the n solution components at
the initial point `a`.
yprime : array_like, shape (n,)
This is the vector of derivatives of the n solution components at the
initial point `a`. (defined by the differential equations in
subroutine `df`)
morder : int
This is the order of the formula which will be used by the initial
value method for taking the first integration step.
rtol : float
Relative tolereance used by the differential equation method.
atol : float or array_like
Absolute tolereance used by the differential equation method.
Returns
-------
float
An appropriate starting step size to be attempted by the differential
equation method.
References
----------
.. [1] <NAME>, "Starting step size for an ODE solver", Journal of
Computational and Applied Mathematics, Vol. 9, No. 2, 1983,
pp. 177-191, ISSN 0377-0427.
https://doi.org/10.1016/0377-0427(83)90040-7
.. [2] Slatec Fortran code dstrt.f.
https://www.netlib.org/slatec/src/
"""
# needed to pass scipy unit test:
if y.size == 0:
return np.inf
# compensate for modified call list
neq = y.size
spy = np.empty_like(y)
pv = np.empty_like(y)
etol = atol + rtol * np.abs(y)
# `small` is a small positive machine dependent constant which is used for
# protecting against computations with numbers which are too small relative
# to the precision of floating point arithmetic. `small` should be set to
# (approximately) the smallest positive DOUBLE PRECISION number such that
# (1. + small) > 1. on the machine being used. The quantity small**(3/8)
# is used in computing increments of variables for approximating
# derivatives by differences. Also the algorithm will not compute a
# starting step length which is smaller than 100*small*ABS(A).
# `big` is a large positive machine dependent constant which is used for
# preventing machine overflows. A reasonable choice is to set big to
# (approximately) the square root of the largest DOUBLE PRECISION number
# which can be held in the machine.
big = sqrt(np.finfo(y.dtype).max)
small = np.nextafter(np.finfo(y.dtype).epsneg, 1.0)
# following dhstrt.f from here
dx = b - a
absdx = abs(dx)
relper = small**0.375
# compute an approximate bound (dfdxb) on the partial derivative of the
# equation with respect to the independent variable. protect against an
# overflow. also compute a bound (fbnd) on the first derivative locally.
da = copysign(max(min(relper * abs(a), absdx), 100.0 * small * abs(a)), dx)
da = da or relper * dx
sf = df(a + da, y) # evaluate
yp = sf - yprime
delf = norm(yp)
dfdxb = big
if delf < big * abs(da):
dfdxb = delf / abs(da)
fbnd = norm(sf)
# compute an estimate (dfdub) of the local lipschitz constant for the
# system of differential equations. this also represents an estimate of the
# norm of the jacobian locally. three iterations (two when neq=1) are used
# to estimate the lipschitz constant by numerical differences. the first
# perturbation vector is based on the initial derivatives and direction of
# integration. the second perturbation vector is formed using another
# evaluation of the differential equation. the third perturbation vector
# is formed using perturbations based only on the initial values.
# components that are zero are always changed to non-zero values (except
# on the first iteration). when information is available, care is taken to
# ensure that components of the perturbation vector have signs which are
# consistent with the slopes of local solution curves. also choose the
# largest bound (fbnd) for the first derivative.
# perturbation vector size is held constant for all iterations. compute
# this change from the size of the vector of initial values.
dely = relper * norm(y)
dely = dely or relper
dely = copysign(dely, dx)
delf = norm(yprime)
fbnd = max(fbnd, delf)
if delf:
# use initial derivatives for first perturbation
spy[:] = yprime
yp[:] = yprime
else:
# cannot have a null perturbation vector
spy[:] = 0.0
yp[:] = 1.0
delf = norm(yp)
dfdub = 0.0
lk = min(neq + 1, 3)
for k in range(1, lk + 1):
# define perturbed vector of initial values
pv[:] = y + dely / delf * yp
if k == 2:
# use a shifted value of the independent variable in computing
# one estimate
yp[:] = df(a + da, pv) # evaluate
pv[:] = yp - sf
else:
# evaluate derivatives associated with perturbed vector and
# compute corresponding differences
yp[:] = df(a, pv) # evaluate
pv[:] = yp - yprime
# choose largest bounds on the first derivative and a local lipschitz
# constant
fbnd = max(fbnd, norm(yp))
delf = norm(pv)
if delf >= big * abs(dely):
# protect against an overflow
dfdub = big
break
dfdub = max(dfdub, delf / abs(dely))
if k == lk:
break
# choose next perturbation vector
delf = delf or 1.0
if k == 2:
dy = y.copy() # vec
dy[:] = np.where(dy, dy, dely / relper)
else:
dy = pv.copy() # abs removed (complex)
dy[:] = np.where(dy, dy, delf)
spy[:] = np.where(spy, spy, yp)
# use correct direction if possible.
yp[:] = np.where(spy, np.copysign(dy.real, spy.real), dy.real)
if np.issubdtype(y.dtype, np.complexfloating):
yp[:] += 1j*np.where(spy, np.copysign(dy.imag, spy.imag), dy.imag)
delf = norm(yp)
# compute a bound (ydpb) on the norm of the second derivative
ydpb = dfdxb + dfdub * fbnd
# define the tolerance parameter upon which the starting step size is to be
# based. a value in the middle of the error tolerance range is selected.
tolexp = np.log10(etol)
tolsum = tolexp.sum()
tolmin = min(tolexp.min(), big)
tolp = 10.0 ** (0.5 * (tolsum / neq + tolmin) / (morder + 1))
# compute a starting step size based on the above first and second
# derivative information
# restrict the step length to be not bigger than abs(b-a).
# (unless b is too close to a)
h = absdx
if ydpb == 0.0 and fbnd == 0.0:
# both first derivative term (fbnd) and second derivative term (ydpb)
# are zero
if tolp < 1.0:
h = absdx * tolp
elif ydpb == 0.0:
# only second derivative term (ydpb) is zero
if tolp < fbnd * absdx:
h = tolp / fbnd
else:
# second derivative term (ydpb) is non-zero
srydpb = sqrt(0.5 * ydpb)
if tolp < srydpb * absdx:
h = tolp / srydpb
# further restrict the step length to be not bigger than 1/dfdub
if dfdub: # `if` added (div 0)
h = min(h, 1.0 / dfdub)
# finally, restrict the step length to be not smaller than
# 100*small*abs(a). however, if a=0. and the computed h underflowed to
# zero, the algorithm returns small*abs(b) for the step length.
h = max(h, 100.0 * small * abs(a))
h = h or small * abs(b)
# now set direction of integration
h = copysign(h, dx)
return h
class HornerDenseOutput(DenseOutput):
"""use Horner's rule for the evaluation of the dense output polynomials.
"""
def __init__(self, t_old, t, y_old, Q):
super(HornerDenseOutput, self).__init__(t_old, t)
self.h = t - t_old
self.Q = Q * self.h
self.y_old = y_old
def _call_impl(self, t):
# scaled time
x = (t - self.t_old) / self.h
# Horner's rule:
y = self.Q.T[-1, :, np.newaxis] * x
for q in reversed(self.Q.T[:-1]):
y += q[:, np.newaxis]
y *= x
y += self.y_old[:, np.newaxis]
# need this `if` to pass scipy's unit tests. I'm not sure why.
if t.shape:
return y
else:
return y[:, 0]
class LinearDenseOutput(DenseOutput):
"""Linear interpolator.
This class can be used if the output was obtained by extrapolation (if the
end point was too close to perform a normal integration step).
"""
def __init__(self, t_old, t, y_old, y):
super(LinearDenseOutput, self).__init__(t_old, t)
self.h = t - t_old
self.y_old = y_old[:, np.newaxis]
self.dy = (y - y_old)[:, np.newaxis]
def _call_impl(self, t):
t = np.atleast_1d(t)
x = (t - self.t_old) / self.h
# linear interpolation
y = x * self.dy
y += self.y_old
# need this `if` to pass scipy's unit tests. I'm not sure why.
if t.shape:
return y
else:
return y[:, 0]
class CubicDenseOutput(HornerDenseOutput):
"""Cubic, C1 continuous interpolator
"""
def __init__(self, t_old, t, y_old, y, f_old, f):
# transform input
h = t - t_old
dy = (y - y_old)
K = np.stack([f_old, dy/h, f])
P = np.array([[1.0, -2.0, 1.0],
[0.0, 3.0, -2.0],
[0.0, -1.0, 1.0]])
Q = K.T @ P
super(CubicDenseOutput, self).__init__(t_old, t, y_old, Q)
def stiff_a(fun, x, y, hnow, havg, xend, maxfcn, wt, fxy, v0, cost,
stbrad, tanang):
"""`stiff_a` diagnoses stiffness for an explicit Runge-Kutta code.
It may be useful for other explicit methods too.
A nonlinear power method is used to find the dominant eigenvalues of the
problem. These are compared to the stability regions of the method to
assess if the problem is stiff. Convergence of the power iterations is
carefully monitored [1]. This is a Python translation of [2].
The assessment is not free. Several derivative function evaluations are
done. This function should not be called each step, but only if either many
step failures have been observed, or a lot of work has been done.
Support for complex valued problems is added in a quick and dirty way.
The original complex vectors are represented by real vectors of twice the
length with the real and imaginary parts of the original. If the dominant
eigenvalue of the problem is complex, then its complex conjugate is also
found. This does not seem to interfere with the stiffness assessment.
Parameters
----------
fun : callable
Right-hand side of the system. The calling signature is fun(t, y).
Here t is a scalar. The ndarray y has has shape (n,) and fun must
return array_like with the same shape (n,).
x : float
Current value of the independent variable (time); `t` in scipy
y : array_like, shape (n,)
Current approximate solution.
hnow : float
Size of the last integration step.
havg : float
Average step size.
xend : float
Final value of the independent variable (time): `t_bound` in scipy.
maxfcn : int
An acceptable number of function evaluations for the integration. The
Stiffness test is not done if `xend` is expected to be reached in fewer
than `maxfcn` steps; the value False is returned in that case.
Prediction uses `havg` and `cost`.
wt : array_like, shape (n,)
Array with positive, non-zero weights. Values near the magnitude of `y`
during the last integration step should work well.
fxy : array_like, shape (n,)
fxy = fun(x, y). It is an input argument because it's usually available
from the integrator.
v0 : array_like, shape (n,)
A perturbation vector to start the power iteration to find the dominant
eigenvalues for stiffness detection. The error vector (difference
between two embedded solutions) works well for Runge Kutta methods.
cost : int
Effective number of function evaluations per step if the integration
method.
stbrad : float
The stability boundary of the method is approximated as a circular arc
around the origin. `stbrad` is the radius of this arc.
tanang : float
The stability boundary of the method is approximated as a circular arc
around the origin. This approximation becomes inaccurate near the
imaginary axis. `tanang` is the tangent of the angle in the upper left
half-plane for which the approximation is still accurate. A eigenvalue
z for which
-z.imag/z.real = tan(angle(-z)) <= tanang
can be assessed. Outside this range, the value None (unsure) is
returned. A warning is given in that case, because this information may
still be useful to the user.
Returns
-------
stif : None or bool
Result of the stiffness detection: True if the problem is stiff,
False if it is not stiff, and None if unsure.
rootre : None or bool
Complex type of root found in stiffness detection: True if the root is
real, False if it is complex, and None if unknown.
References
----------
[1] <NAME>, "Diagnosing Stiffness for Runge–Kutta Methods", SIAM
Journal on Scientific and Statistical Computing, Vol. 12, No. 2, 1991,
pp. 260-272, https://doi.org/10.1137/0912015
[2] Original source: RKSuite.f, https://www.netlib.org/ode/rksuite/
"""
epsneg = np.finfo(y.dtype).epsneg
rootre = None # uncertain
# If the problem is complex, create double length real vectors of the
# original complex vectors
if np.issubdtype(y.dtype, np.complexfloating):
def expand_complex(v): return np.concatenate((v.real, v.imag))
def contract_complex(v): return v[:v.size//2] + v[v.size//2:]*1j
def f(x, y): return expand_complex(fun(x, contract_complex(y)))
y = expand_complex(y)
fxy = expand_complex(fxy)
v0 = expand_complex(v0)
wt = np.concatenate((wt, wt))
else:
f = fun
# If the current step size differs substantially from the average,
# the problem is not stiff.
if abs(hnow/havg) > 5 or abs(hnow/havg) < 0.2:
stif = False
return stif, rootre
# The average step size is used to predict the cost in function evaluations
# of finishing the integration to xend. If this cost is no more than
# maxfcn, the problem is declared not stiff: If the step size is being
# restricted on grounds of stability, it will stay close to havg.
# The prediction will then be good, but the cost is too low to consider the
# problem stiff. If the step size is not close to havg, the problem is not
# stiff. Either way there is no point to testing for a step size
# restriction due to stability.
xtrfcn = cost * abs((xend - x) / havg)
if xtrfcn <= maxfcn:
stif = False
return stif, rootre
# There have been many step failures or a lot of work has been done. Now
# we must determine if this is due to the stability characteristics of the
# formula. This is done by calculating the dominant eigenvalues of the
# local Jacobian and then testing whether havg corresponds to being on the
# boundary of the stability region.
# The size of y[:] provides scale information needed to approximate
# the Jacobian by differences.
ynrm = sqrt((y/wt) @ (y/wt))
sqrrmc = sqrt(epsneg)
scale = ynrm * sqrrmc
if scale == 0.0:
# Degenerate case. y[:] is (almost) the zero vector so the scale is
# not defined. The input vector v0[:] is the difference between y[:]
# and a lower order approximation to the solution that is within the
# error tolerance. When y[:] vanishes, v0[:] is itself an acceptable
# approximate solution, so we take scale from it, if this is possible.
ynrm = sqrt((v0/wt) @ (v0/wt))
scale = ynrm * sqrrmc
if scale == 0.0:
stif = None # uncertain
return stif, rootre
v0v0 = (v0/wt) @ (v0/wt)
if v0v0 == 0.0:
# Degenerate case. v0[:] is (almost) the zero vector so cannot
# be used to define a direction for an increment to y[:]. Try a
# "random" direction.
v0[:] = 1.0
v0v0 = (v0/wt) @ (v0/wt)
v0nrm = sqrt(v0v0)
v0 /= v0nrm
v0v0 = 1.0
# Use a nonlinear power method to estimate the two dominant eigenvalues.
# v0[:] is often very rich in the two associated eigenvectors. For this
# reason the computation is organized with the expectation that a minimal
# number of iterations will suffice. Indeed, it is necessary to recognize
# a kind of degeneracy when there is a dominant real eigenvalue. The
# subroutine stiff_b does this. In the first try, ntry = 0, a Rayleigh
# quotient for such an eigenvalue is initialized as rold. After each
# iteration, REROOT computes a new Rayleigh quotient and tests whether the
# two approximations agree to one tenth of one per cent and the eigenvalue,
# eigenvector pair satisfy a stringent test on the residual. rootre = True
# signals that a single dominant real root has been found.
maxtry = 8
for ntry in range(maxtry):
v1, v1v1 = stiff_d(v0, havg, x, y, f, fxy, wt, scale, v0v0)
# The quantity sqrt(v1v1/v0v0) is a lower bound for the product of havg
# and a Lipschitz constant. If it should be LARGE, stiffness is not
# restricting the step size to the stability region. The principle is
# clear enough, but the real reason for this test is to recognize an
# extremely inaccurate computation of v1v1 due to finite precision
# arithmetic in certain degenerate circumstances.
LARGE = 1.0e10
if sqrt(v1v1) > LARGE * sqrt(v0v0):
stif = None # uncertain
rootre = None # uncertain
return stif, rootre
v0v1 = (v0/wt) @ (v1/wt)
if ntry == 0:
rold = v0v1 / v0v0
# This is the first Rayleigh quotient approximating the product of
# havg and a dominant real eigenvalue. If it should be very small,
# the problem is not stiff. It is important to test for this
# possibility so as to prevent underflow and degeneracies in the
# subsequent iteration.
cubrmc = epsneg ** (1/3)
if abs(rold) < cubrmc:
stif = False
rootre = None # uncertain
return stif, rootre
else:
rold, rho, root1, root2, rootre = stiff_b(v1v1, v0v1, v0v0, rold)
if rootre:
break
v2, v2v2 = stiff_d(v1, havg, x, y, f, fxy, wt, scale, v1v1)
v0v2 = (v0/wt) @ (v2/wt)
v1v2 = (v1/wt) @ (v2/wt)
rold, rho, root1, root2, rootre = stiff_b(v2v2, v1v2, v1v1, rold)
if rootre:
break
# Fit a quadratic in the eigenvalue to the three successive iterates
# v0[:], v1[:], v2[:] of the power method to get a first approximation
# to a pair of eigenvalues. A test made earlier in stiff_b implies
# that the quantity det1 here will not be too small.
det1 = v0v0 * v1v1 - v0v1**2
alpha1 = (-v0v0 * v1v2 + v0v1 * v0v2)/det1
beta1 = (v0v1 * v1v2 - v1v1 * v0v2)/det1
# Iterate again to get v3, test again for degeneracy, and then fit a
# quadratic to v1[:], v2[:], v3[:] to get a second approximation to a
# pair of eigenvalues.
v3, v3v3 = stiff_d(v2, havg, x, y, f, fxy, wt, scale, v2v2)
v1v3 = (v1/wt) @ (v3/wt)
v2v3 = (v2/wt) @ (v3/wt)
rold, rho, root1, root2, rootre = stiff_b(v3v3, v2v3, v2v2, rold)
if rootre:
break
det2 = v1v1 * v2v2 - v1v2**2
alpha2 = (-v1v1 * v2v3 + v1v2 * v1v3)/det2
beta2 = (v1v2 * v2v3 - v2v2 * v1v3)/det2
# First test the residual of the quadratic fit to see if we might
# have determined a pair of eigenvalues.
res2 = abs(v3v3 + v2v2*alpha2**2 + v1v1*beta2**2 + 2*v2v3*alpha2 +
2*v1v3*beta2 + 2*v1v2*alpha2*beta2)
if res2 <= 1e-6 * v3v3:
# Calculate the two approximate pairs of eigenvalues.
r1, r2 = stiff_c(alpha1, beta1)
root1, root2 = stiff_c(alpha2, beta2)
# The test for convergence is done on the larger root of the second
# approximation. It is complicated by the fact that one pair of
# roots might be real and the other complex. First calculate the
# spectral radius rho of havg*J as the magnitude of root1. Then
# see if one of the roots r1, r2 is within one per cent of root1.
# A subdominant root may be very poorly approximated if its
# magnitude is much smaller than rho -- this does not matter in our
# use of these eigenvalues.
rho = sqrt(root1[0]**2 + root1[1]**2)
D1 = (root1[0] - r1[0])**2 + (root1[1] - r1[1])**2
D2 = (root1[0] - r2[0])**2 + (root1[1] - r2[1])**2
DIST = sqrt(min(D1, D2))
if DIST <= 0.001*rho:
break
# Do not have convergence yet. Because the iterations are cheap, and
# because the convergence criterion is stringent, we are willing to try
# a few iterations.
v3nrm = sqrt(v3v3)
v0 = v3/v3nrm
v0v0 = 1.0
else:
# Iterations did not converge
stif = None # uncertain
rootre = None # uncertain
return stif, rootre
# Iterations have converged
# We now have the dominant eigenvalues. Decide if the average step size is
# being restricted on grounds of stability. Check the real parts of the
# eigenvalues. First see if the dominant eigenvalue is in the left half
# plane -- there won't be a stability restriction unless it is. If there
# is another eigenvalue of comparable magnitude with a positive real part,
# the problem is not stiff. If the dominant eigenvalue is too close to the
# imaginary axis, we cannot diagnose stiffness.
rootre = root1[1] == 0.0
# print(ntry, (root1[0] + root1[1]*1j)/havg,
# (root2[0] + root2[1]*1j)/havg, rootre)
if root1[0] > 0.0:
stif = False
return stif, rootre
rho2 = sqrt(root2[0]**2 + root2[1]**2)
if rho2 >= 0.9 * rho and root2[0] > 0.0:
stif = False
return stif, rootre
if abs(root1[1]) > abs(root1[0]) * tanang:
stif = None # uncertain
return stif, rootre
# If the average step size corresponds to being well within the stability
# region, the step size is not being restricted because of stability.
stif = rho >= 0.9 * stbrad
return stif, rootre
def stiff_b(v1v1, v0v1, v0v0, rold):
"""called from stiff_a().
Decide if the iteration has degenerated because of a strongly dominant
real eigenvalue. Have just computed the latest iterate. v1v1 is its dot
product with itself, v0v1 is the dot product of the previous iterate with
the current one, and v0v0 is the dot product of the previous iterate with
itself. rold is a previous Rayleigh quotient approximating a dominant real
eigenvalue. It must be computed directly the first time the subroutine is
called. It is updated each call to stiff_b, hence is available for
subsequent calls.
If there is a strongly dominant real eigenvalue, rootre is set True,
root1[:] returns the eigenvalue, rho returns the magnitude of the
eigenvalue, and root2[:] is set to zero.
Original source: RKSuite.f, https://www.netlib.org/ode/rksuite/
"""
# real and imag parts of roots are returned in a list
root1 = [0.0, 0.0]
root2 = [0.0, 0.0]
r = v0v1 / v0v0
rho = abs(r)
det = v0v0 * v1v1 - v0v1**2
res = abs(det / v0v0)
rootre = det == 0.0 or (res <= 1e-6 * v1v1 and
abs(r - rold) <= 0.001 * rho)
if rootre:
root1[0] = r
rold = r
return rold, rho, root1, root2, rootre
def stiff_c(alpha, beta):
"""called from stiff_a().
This subroutine computes the two complex roots r1 and r2 of the
quadratic equation x**2 + alpha*x + beta = 0. The magnitude of r1 is
greater than or equal to the magnitude of r2. r1 and r2 are returned as
vectors of two components with the first being the real part of the complex
number and the second being the imaginary part.
Original source: RKSuite.f, https://www.netlib.org/ode/rksuite/
"""
# real and imag parts of roots are returned in a list
r1 = [0.0, 0.0]
r2 = [0.0, 0.0]
temp = alpha / 2
disc = temp**2 - beta
if disc == 0.0:
# Double root.
r1[0] = r2[0] = -temp
return r1, r2
sqdisc = sqrt(abs(disc))
if disc < 0.0:
# Complex conjugate roots.
r1[0] = r2[0] = -temp
r1[1] = sqdisc
r2[1] = -sqdisc
else:
# Real pair of roots. Calculate the bigger one in r1[0].
if temp > 0.0:
r1[0] = -temp - sqdisc
else:
r1[0] = -temp + sqdisc
r2[0] = beta / r1[0]
return r1, r2
def stiff_d(v, havg, x, y, f, fxy, wt, scale, vdotv):
"""called from stiff_a().
For an input vector v[:], this subroutine computes a vector z[:] that
approximates the product havg*J*V where havg is an input scalar and J is
the Jacobian matrix of a function f evaluated at the input arguments
(x, y[:]). This function is defined by a subroutine of the form
f[:] = f(t, u) that when given t and u[:], returns the value of the
function in f[:]. The input vector fxy[:] is defined by f(x, y). Scaling
is a delicate matter. A weighted Euclidean norm is used with the
(positive) weights provided in wt[:]. The input scalar scale is the square
root of the unit roundoff times the norm of y[:]. The square of the norm
of the input vector v[:] is input as vdotv. The routine outputs the square
of the norm of the output vector z[:] as zdotz.
Original source: RKSuite.f, https://www.netlib.org/ode/rksuite/
"""
# scale v[:] so that it can be used as an increment to y[:]
# for an accurate difference approximation to the Jacobian.
temp1 = scale/sqrt(vdotv)
z = f(x, y + temp1 * v) # evaluate
# Form the difference approximation. At the same time undo
# the scaling of v[:] and introduce the factor of havg.
z = havg/temp1 * (z - fxy)
zdotz = (z/wt) @ (z/wt)
return z, zdotz
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src/clarityv2/homepage/urls.py | Clarity-89/clarityv2 | 0 | 24179 | <reponame>Clarity-89/clarityv2<gh_stars>0
from django.urls import path
from .views import HomepageView
urlpatterns = [
path('', HomepageView.as_view(), name='home'),
]
| [
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tools/merge.py | mrjrty/rpaframework | 518 | 121276 | #!/usr/bin/env python3
import argparse
import json
import os
from pathlib import Path
FILENAME = "latest.json"
def main():
parser = argparse.ArgumentParser()
parser.add_argument("source", help="Path to directory of JSONs")
parser.add_argument("destination", help="Path to destination JSON")
args = parser.parse_args()
dirname = Path(args.source)
output = {}
for filename in sorted(os.listdir(dirname)):
if filename == FILENAME:
continue
with open(dirname / filename, "r") as infile:
lib = json.load(infile)
assert lib["name"] not in output, "Duplicate library"
output[lib["name"]] = lib
with open(args.destination, "w") as outfile:
json.dump(output, outfile, indent=4)
if __name__ == "__main__":
main()
| [
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] |
boardgame/connectfour/connectfourviewer.py | suryaambrose/boardgame | 0 | 24341 | import os
import sys
from ..gameviewer import GameViewer
class ConnectFourViewer(GameViewer):
def __init__(self):
super(ConnectFourViewer, self).__init__([6,7])
def showState(self, state):
os.system("clear")
sys.stdout.write("x\y|")
for k in range(0, self.map_width):
sys.stdout.write("%d "%(k))
sys.stdout.write("\n")
for i in range(0, self.map_height):
sys.stdout.write(" %d "%(i))
for j in range(0, self.map_width):
sys.stdout.write("|")
if state._board[i][j] is not None:
sys.stdout.write(self.symbol_map[state._board[i][j]])
else:
sys.stdout.write(" ")
sys.stdout.write("|\n")
def waitForAMove(self):
while True:
try:
played_column = raw_input("Type where you wish to play (e.g. 1 for column 1):")
c = int(played_column)
break
except Exception, e:
print e
return c | [
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index.py | flyingraijin98/Naive-Bayes-Spam-Classifier | 0 | 135049 | <reponame>flyingraijin98/Naive-Bayes-Spam-Classifier<filename>index.py
from collections import Counter
import pandas as pd
import stop_words
import random
class NLP():
def __init__(self):
self.vocab = None
def count_vectorizer(self, text, train=True, stop_word=None, view=False):
lower_case_documents = []
documents = text
for i in documents:
lower_case_documents.append(i.lower())
if view:
print('Step: Applying Lower Case.... Done\n')
# print(lower_case_documents)
sans_punctuation_documents = []
import string
for i in lower_case_documents:
punctuation = string.punctuation
k = ""
for j in i:
if j not in punctuation:
k += j
sans_punctuation_documents.append(k)
if view:
print('Step: Removed Punctuation....\n')
print(sans_punctuation_documents)
if stop_word == None:
stop_word = list(stop_words.ENGLISH_STOP_WORDS)
preprocessed_documents = []
for i in sans_punctuation_documents:
sentence = []
for word in i.split():
if word not in stop_word:
sentence.append(word)
preprocessed_documents.append(sentence)
if train != True:
return preprocessed_documents
if view:
print('Step: Bag of Words... Done\n')
print(preprocessed_documents)
frequency_list = []
from collections import Counter
for i in preprocessed_documents:
frequency_list.append(dict(Counter(i)))
if view:
print('Step: Frequency of words... Done\n')
# often called as vocabulary
all_words = list(set([j for i in preprocessed_documents for j in i]))
for doc in frequency_list:
for word in all_words:
if word not in list(doc.keys()):
doc[word] = 0
df = pd.DataFrame(frequency_list)
df = df[sorted(list(df.columns))]
self.vocab = df.columns.to_list()
if view:
print('Step: Count vectorizer... Done\n')
print(df.head())
return df
nlp = NLP()
class NaiveBayes():
def __init__(self, text, label):
self.text = text
self.label = label
self.cond_probs = {}
self.features = []
self.classes = []
self.class_prob = {}
def fit(self, view=False):
text = self.text
label = self.label
bow = nlp.count_vectorizer(text)
self.features = bow.columns.to_list()
if view:
print('Your BoW is:\n', bow)
classes = label
self.classes = list(Counter(classes).keys())
bow['out'] = classes
bow_class = bow.groupby(by='out', axis=0)
if view:
print('Your BoW is testing:\n')
# count of each class examples
counts = bow_class.count()
if view:
print(counts)
print
# used for prediction
class_prob = counts / counts.sum(axis=0)
class_prob = dict(class_prob.mean(axis=1))
self.class_prob = class_prob
if view:
print(class_prob)
# count of each word on each class
self.count_words_class = bow_class.sum()
# find prob of word in each class.... no. of that word in class / total word in class
prob_w_c = (bow_class.sum() + 1) / (counts )
if view:
print("chenck the testing prob")
print(prob_w_c)
# find p(word/class)
prob_w_c = round(prob_w_c, 5)
self.cond_probs = prob_w_c
if view:
print(prob_w_c)
def classes_(self):
"""
A method to see all classes counts for each word.
"""
return self.count_words_class
def predict(self, example):
txt = nlp.count_vectorizer(example, train=False)
words = dict(Counter(txt[0]))
vocab = self.features
classes = self.classes
class_prob = self.class_prob
p = self.cond_probs
prob_zero = class_prob['0']
prob_one = class_prob['1']
for w in words.keys():
if w in vocab:
prob_zero = prob_zero * p[w][0]
prob_one = prob_one * p[w][1]
else:
prob_zero = prob_zero * 10
prob_one = prob_one * 10
if (prob_zero < prob_one):
return 1
else:
return 0
f = open("dataset_NB.txt", "r")
t = f.read().splitlines()
f.close()
# print(np.shape(t))
a = random.sample(t, len(t))
X = []
Y = []
all_txt = []
classes = []
for i in a:
X.append(i[:-1])
Y.append(i[-1])
append_list_x = []
append_list_y = []
train_range_1 = 0
for k in range(7):
train_range_2=train_range_1 + 1000//7
append_list_x = X[0:train_range_1]
append_list_y = Y[0:train_range_1]
all_txt = X[train_range_2:] + append_list_x
classes = Y[train_range_2:] + append_list_y
testX = X[train_range_1:train_range_2]
testY = Y[train_range_1:train_range_2]
nb = NaiveBayes(all_txt, classes)
nb.fit()
count_total = 0
count_metrics = 0
res = 0
for i in range(0, len(testY)):
testY[i] = int(testY[i])
for i in testX:
a = 0
count_total = count_total + 1
res = nb.predict([i])
if res == testY[a]:
count_metrics = count_metrics + 1
else:
count_metrics = count_metrics + 0
a = a + 1
accuracy_final = count_metrics / count_total
print("Accuracy of fold %d is"%k,end = "")
print(accuracy_final)
train_range_1 = train_range_1 + 1000//7
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water_channel_assembly/sub_model.py | iorodeo/water_channel_mechanics | 0 | 1602642 | <filename>water_channel_assembly/sub_model.py
from __future__ import division
import scipy
from py2scad import *
class SubModel(object):
def __init__(self,params):
self.params = params
self.parts = {}
self.__make_mount_plate()
self.__make_hydrofoil()
self.__make_nozzle()
self.__make_anterior_cap()
self.__make_motor_housing()
self.__make_fluid_housing()
def __make_mount_plate(self):
self.mount_plate_x = self.params['mount_plate_length']
self.mount_plate_y = self.params['mount_plate_length']
self.mount_plate_z = self.params['mount_plate_thickness']
mount_plate = Cube(size=[self.mount_plate_x,self.mount_plate_y,self.mount_plate_z])
self.parts['mount_plate'] = mount_plate
def __make_hydrofoil(self):
self.hydrofoil_y = self.params['hydrofoil_width']
self.hydrofoil_x = self.params['hydrofoil_length']
self.hydrofoil_z = self.params['hydrofoil_height']
hydrofoil = Cylinder(r1=0.5,r2=0.5,h=self.hydrofoil_z)
hydrofoil = Scale(hydrofoil,v=[self.hydrofoil_x,self.hydrofoil_y,1])
# x_shift = 0.5*l
# hydrofoil_tz = 0.5*h + 0.5*self.params['body_diameter']
self.hydrofoil_tz = self.hydrofoil_z/2 + self.mount_plate_z/2
hydrofoil = Translate(hydrofoil,v=[0,0,-self.hydrofoil_tz])
self.parts['hydrofoil'] = hydrofoil
def __make_nozzle(self):
h = self.params['nozzle_length']
r2 = 0.5*self.params['body_diameter']
r1 = 0.5*self.params['nozzle_exit_diameter']
epsilon = self.params['nozzle_trans_param']
nozzle = make_nozzle(r1,r2,h,epsilon)
nozzle = Rotate(nozzle,a=90,v=[0,1,0])
self.nozzle_tx = -self.params['fluid_housing_length'] - 0.5*h - self.hydrofoil_x/2
self.nozzle_tz = -self.hydrofoil_tz - self.hydrofoil_z/2 - self.params['body_diameter']/2
nozzle = Translate(nozzle,v=[self.nozzle_tx,0,self.nozzle_tz])
self.parts['nozzle'] = nozzle
def __make_anterior_cap(self):
r = 0.5*self.params['body_diameter']
h = self.params['anterior_cap_length']
cap = bullet(r,h)
cap = Rotate(cap,a=90,v=[0,1,0])
self.anterior_cap_tx = self.params['motor_housing_length'] - self.hydrofoil_x/2
self.anterior_cap_tz = self.nozzle_tz
cap = Translate(cap,v=[self.anterior_cap_tx,0,self.anterior_cap_tz])
self.parts['anterior_cap'] = cap
def __make_fluid_housing(self):
r = 0.5*self.params['body_diameter']
h = self.params['fluid_housing_length']
fuild_housing = Cylinder(r1=r, r2=r, h=h)
fuild_housing = Rotate(fuild_housing,a=90,v=[0,1,0])
self.fluid_housing_tx = -h/2 - self.hydrofoil_x/2
self.fluid_housing_tz = self.nozzle_tz
fuild_housing = Translate(fuild_housing,v=[self.fluid_housing_tx,0,self.fluid_housing_tz])
self.parts['fuild_housing'] = fuild_housing
def __make_motor_housing(self):
r = 0.5*self.params['body_diameter']
h = self.params['motor_housing_length']
motor_housing = Cylinder(r1=r, r2=r, h=h)
motor_housing = Rotate(motor_housing,a=90,v=[0,1,0])
self.motor_housing_tx = h/2 - self.hydrofoil_x/2
self.motor_housing_tz = self.nozzle_tz
motor_housing = Translate(motor_housing,v=[self.motor_housing_tx,0,self.motor_housing_tz])
self.parts['motor_housing'] = motor_housing
def get_assembly(self):
# Create union of all parts
sub = Union(self.parts.values())
# Shift so that sub is centered w.r.t to hydrofoil
# x_shift = -0.5*self.params['hydrofoil_length']
# sub = Translate(sub,v=[x_shift,0,0])
# Shidt so that top of hydrofoil is at z=0
# z_shift = -0.5*self.params['body_diameter'] - self.params['hydrofoil_height']
sub_tz = -self.params['mount_plate_thickness']/2
sub = Translate(sub,v=[0,0,sub_tz])
return sub
def bullet(r,h):
"""
Creates a bullet shaped object with radius r and height h.
"""
sphere = Sphere(r=1)
cut_cube = Cube(size=[3*r, 3*r, 3*r])
cut_cube = Translate(cut_cube,v=[0,0,-1.5*r])
bullet = Difference([sphere, cut_cube])
vscale = [r,r,h]
bullet = Scale(bullet,v=vscale)
return [bullet]
def make_nozzle(r1, r2, h, epsilon, num_pts = 100):
"""
Creates submarine tail section
r1 = bottom radius
r2 = top radius
h = height
epsilon = transition parameter
"""
x = scipy.linspace(-0.5*h, 0.5*h,num_pts)
y = -scipy.arctan(epsilon*x)
# Shift to get correct radii
y = scipy.absolute(r2-r1)*y/(y.max() -y.min())
y = y +r1 - y.min()
# Create polygon and rotate into position
poly = curve2polygon(x,y)
poly = Rotate(poly,a=-90,v=[0,0,1])
# Revolve
part = Rotate_Extrude(poly)
return part
def curve2polygon(x_pts,y_pts):
"""
Creates a 2D polygon from an x,y curve
"""
points = []
for x,y in zip(x_pts, y_pts):
points.append([x,y])
points.append([x_pts[-1], 0])
points.append([x_pts[0],0])
points.reverse()
paths = [range(0,len(points))]
poly = Polygon(points=points, paths=paths)
return poly
# -----------------------------------------------------------------------------
if __name__ == "__main__":
from params import sub_model_params
sub = SubModel(params=sub_model_params)
sub_assem = sub.get_assembly()
prog = SCAD_Prog()
prog.fn = 70
prog.add(sub_assem)
prog.write('sub_model.scad')
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] |
mayan/apps/documents/tests/test_links.py | bonitobonita24/Mayan-EDMS | 343 | 28898 | from django.urls import reverse
from ..links.document_file_links import (
link_document_file_delete, link_document_file_download_quick
)
from ..links.favorite_links import (
link_document_favorites_add, link_document_favorites_remove
)
from ..links.trashed_document_links import link_document_restore
from ..models import TrashedDocument
from ..permissions import (
permission_document_file_delete, permission_document_file_download,
permission_document_view, permission_trashed_document_restore
)
from .base import GenericDocumentViewTestCase
from .mixins.favorite_document_mixins import FavoriteDocumentTestMixin
class FavoriteDocumentLinkTestCase(
FavoriteDocumentTestMixin, GenericDocumentViewTestCase
):
def test_favorite_document_add_link_no_permission(self):
self._create_test_document_stub()
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_add.resolve(context=context)
self.assertEqual(resolved_link, None)
def test_favorite_document_add_link_with_access(self):
self._create_test_document_stub()
self.grant_access(
obj=self.test_document_stub, permission=permission_document_view
)
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_add.resolve(context=context)
self.assertNotEqual(resolved_link, None)
def test_favorite_document_add_link_external_user_with_access(self):
self._create_test_user()
self._create_test_document_stub()
self.grant_access(
obj=self.test_document_stub, permission=permission_document_view
)
self._test_document_favorite_add(user=self.test_user)
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_add.resolve(context=context)
self.assertNotEqual(resolved_link, None)
def test_favorite_document_remove_link_no_permission(self):
self._create_test_document_stub()
self._test_document_favorite_add()
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_remove.resolve(context=context)
self.assertEqual(resolved_link, None)
def test_favorite_document_remove_link_with_access(self):
self._create_test_document_stub()
self.grant_access(
obj=self.test_document_stub, permission=permission_document_view
)
self._test_document_favorite_add()
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_remove.resolve(context=context)
self.assertNotEqual(resolved_link, None)
def test_favorite_document_remove_link_external_user_with_access(self):
self._create_test_user()
self._create_test_document_stub()
self.grant_access(
obj=self.test_document_stub, permission=permission_document_view
)
self._test_document_favorite_add(user=self.test_user)
self.add_test_view(test_object=self.test_document)
context = self.get_test_view()
resolved_link = link_document_favorites_remove.resolve(context=context)
self.assertEqual(resolved_link, None)
class DocumentsLinksTestCase(GenericDocumentViewTestCase):
def test_document_file_delete_link_no_permission(self):
self._upload_test_document_file()
self.assertTrue(self.test_document.files.count(), 2)
self.add_test_view(test_object=self.test_document.files.first())
context = self.get_test_view()
resolved_link = link_document_file_delete.resolve(context=context)
self.assertEqual(resolved_link, None)
def test_document_file_delete_link_with_permission(self):
self._upload_test_document_file()
self.assertTrue(self.test_document.files.count(), 2)
self.grant_access(
obj=self.test_document,
permission=permission_document_file_delete
)
self.add_test_view(test_object=self.test_document.files.first())
context = self.get_test_view()
resolved_link = link_document_file_delete.resolve(context=context)
self.assertNotEqual(resolved_link, None)
self.assertEqual(
resolved_link.url,
reverse(
viewname=link_document_file_delete.view,
args=(self.test_document.files.first().pk,)
)
)
def test_document_file_download_link_no_permission(self):
self.add_test_view(test_object=self.test_document.file_latest)
context = self.get_test_view()
resolved_link = link_document_file_download_quick.resolve(context=context)
self.assertEqual(resolved_link, None)
def test_document_file_download_link_with_permission(self):
self.grant_access(
obj=self.test_document,
permission=permission_document_file_download
)
self.add_test_view(test_object=self.test_document.file_latest)
context = self.get_test_view()
resolved_link = link_document_file_download_quick.resolve(context=context)
self.assertNotEqual(resolved_link, None)
self.assertEqual(
resolved_link.url,
reverse(
viewname=link_document_file_download_quick.view,
args=(self.test_document.file_latest.pk,)
)
)
class TrashedDocumentsLinksTestCase(GenericDocumentViewTestCase):
def setUp(self):
super().setUp()
self.test_document.delete()
self.test_trashed_document = TrashedDocument.objects.get(
pk=self.test_document.pk
)
self.add_test_view(test_object=self.test_trashed_document)
self.context = self.get_test_view()
def test_trashed_document_restore_link_no_permission(self):
resolved_link = link_document_restore.resolve(context=self.context)
self.assertEqual(resolved_link, None)
def test_trashed_document_restore_link_with_permission(self):
self.grant_access(
obj=self.test_document, permission=permission_trashed_document_restore
)
resolved_link = link_document_restore.resolve(context=self.context)
self.assertNotEqual(resolved_link, None)
self.assertEqual(
resolved_link.url,
reverse(
viewname=link_document_restore.view,
args=(self.test_trashed_document.pk,)
)
)
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baghchal/matchup.py | neupane11/ai-wmacevoy | 0 | 131545 | from random import Random
from game import Game
from const import Const
from randomagent import RandomAgent
from agent import Agent
class Matchup:
'''
Pit two agents against each other in a game
'''
def __init__(self, verbose : bool = True):
self._game = Game()
self._goatAgent : Agent = RandomAgent(self._game, Const.MARK_GOAT)
self._tigerAgent : Agent = RandomAgent(self._game,Const.MARK_TIGER)
self._verbose = verbose
def turn(self) -> None:
if self._game.over:
if self._verbose:
print("game over - " + Const.stateStr(game.state))
print(game)
return
if self._game.state == Const.STATE_TURN_GOAT:
move=self._goatAgent.propose()
self._game.play(move)
if self._verbose:
print("after goat move " + str(move) + ":")
print(self._game)
if self._game.state == Const.STATE_TURN_TIGER:
move=self._tigerAgent.propose()
self._game.play(move)
if self._verbose:
print("after tiger move " + str(move) + ":")
print(self._game)
@property
def game(self) -> Game:
return self._game
@property
def over(self) -> bool:
return self._game.over
@property
def tigerAgent(self) -> Agent:
return self._tigerAgent
@tigerAgent.setter
def tigerAgent(self,value : Agent) -> None:
value.game = self._game
value.side = Const.MARK_TIGER
self._tigerAgent = value
@property
def goatAgent(self) -> Agent:
return self._goatAgent
@goatAgent.setter
def goatAgent(self,value : Agent) -> None:
value.game = self._game
value.side = Const.MARK_GOAT
self._goatAgent = value
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PyScraper/server/models/project.py | nikan1996/PyScraper | 0 | 53129 | #!/usr/bin/env python
# encoding: utf-8
"""
@author:nikan
@file: project.py
@time: 2018/5/14 下午4:20
"""
import datetime
from sqlalchemy import text
from sqlalchemy.dialects import mysql
from PyScraper.server.extensions import db
class Project(db.Model):
__tablename__ = "project"
project_id = db.Column(db.Integer, autoincrement=True, primary_key=True, doc="自增id")
project_name = db.Column(db.String(191), nullable=False, doc="项目名称")
setting = db.Column(mysql.JSON, doc="项目配置")
cron_config = db.Column(mysql.JSON, doc="项目调度配置")
tag = db.Column(db.String(191), doc="项目标签")
status = db.Column(db.String(191), nullable=False, default='stop', doc="项目状态")
is_deleted = db.Column(db.Boolean, default=0, doc="项目是否删除的标记")
update_timestamp = db.Column(db.TIMESTAMP, server_default=text('CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP'), doc="更新时间")
create_timestamp = db.Column(db.TIMESTAMP, default=datetime.datetime.now, doc="创建时间")
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mealpy/utils/visualize/linechart.py | thieu1995/mealpy | 162 | 26424 | #!/usr/bin/env python
# ------------------------------------------------------------------------------------------------------%
# Created by "Thieu" at 17:12, 09/07/2021 %
# %
# Email: <EMAIL> %
# Homepage: https://www.researchgate.net/profile/Nguyen_Thieu2 %
# Github: https://github.com/thieu1995 %
# ------------------------------------------------------------------------------------------------------%
import platform
from matplotlib import pyplot as plt
from numpy import arange
from pathlib import Path
import re
LIST_LINESTYLES = [
'-', # solid line style
'--', # dashed line style
'-.', # dash-dot line style
':', # point marker
's', # square marker
'*', # star marker
'p', # pentagon marker
'+', # plus marker
'x', # x marker
'd', # thin diamond marker
]
LIST_COLORS = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728',
'#9467bd', '#8c564b', '#e377c2', '#7f7f7f',
'#bcbd22', '#17becf']
def __clean_filename__(filename):
chars_to_remove = ["`", "~", "!", "@", "#", "$", "%", "^", "&", "*", ":", ",", "<", ">", ";", "+", "|"]
regular_expression = '[' + re.escape(''.join(chars_to_remove)) + ']'
temp = filename.encode("ascii", "ignore")
fname = temp.decode() # Removed all non-ascii characters
fname = re.sub(regular_expression, '', fname) # Removed all special characters
fname.replace("_", "-") # Replaced _ by -
return fname
def __check_filepath__(filename):
filename.replace("\\", "/") # For better handling the parent folder
if "/" in filename:
list_names = filename.split("/")[:-1] # Remove last element because it is filename
filepath = "/".join(list_names)
print(f"Fucking for real? {filepath}")
Path(filepath).mkdir(parents=True, exist_ok=True)
return filename
def _draw_line_(data=None, title=None, linestyle='-', color='b', x_label="#Iteration", y_label="Function Value",
filename=None, exts=(".png", ".pdf"), verbose=True):
x = arange(0, len(data))
y = data
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.plot(x, y, linestyle=linestyle, color=color,)
plt.legend() # show a legend on the plot
if filename is not None:
filepath = __check_filepath__(__clean_filename__(filename))
for idx, ext in enumerate(exts):
plt.savefig(f"{filepath}{ext}", bbox_inches='tight')
if platform.system() != "Linux" and verbose:
plt.show()
plt.close()
def _draw_multi_line_(data=None, title=None, list_legends=None, list_styles=None, list_colors=None,
x_label="#Iteration", y_label="Function Value", filename=None, exts=(".png", ".pdf"), verbose=True):
x = arange(0, len(data[0]))
for idx, y in enumerate(data):
plt.plot(x, y, label=list_legends[idx], markerfacecolor=list_colors[idx], linestyle=list_styles[idx])
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.legend() # show a legend on the plot
if filename is not None:
filepath = __check_filepath__(__clean_filename__(filename))
for idx, ext in enumerate(exts):
plt.savefig(f"{filepath}{ext}", bbox_inches='tight')
if platform.system() != "Linux" and verbose:
plt.show()
plt.close()
def _draw_multi_line_in_same_figure_(data=None, title=None, list_legends=None, list_styles=None, list_colors=None,
x_label="#Iteration", y_label="Objective", filename=None, exts=(".png", ".pdf"), verbose=True):
n_lines = len(data)
len_lines = len(data[0])
x = arange(0, len_lines)
if n_lines == 1:
fig, ax = plt.subplots()
if list_legends is None:
ax.plot(x, data[0])
else:
ax.plot(x, data[0], label=list_legends[0])
ax.set_title(title)
elif n_lines > 1:
fig, ax_list = plt.subplots(n_lines, sharex=True)
fig.suptitle(title)
for idx, ax in enumerate(ax_list):
if list_legends is None:
ax.plot(x, data[idx], markerfacecolor=list_colors[idx], linestyle=list_styles[idx])
else:
ax.plot(x, data[idx], label=list_legends[idx], markerfacecolor=list_colors[idx], linestyle=list_styles[idx])
ax.set_ylabel(f"Objective {idx + 1}")
if idx == (n_lines - 1):
ax.set_xlabel(x_label)
if filename is not None:
filepath = __check_filepath__(__clean_filename__(filename))
for idx, ext in enumerate(exts):
plt.savefig(f"{filepath}{ext}", bbox_inches='tight')
if platform.system() != "Linux" and verbose:
plt.show()
plt.close()
def export_convergence_chart(data=None, title="Convergence Chart", linestyle='-', color='b', x_label="#Iteration",
y_label="Function Value", filename="convergence_chart", exts=(".png", ".pdf"), verbose=True):
_draw_line_(data, title=title, linestyle=linestyle, color=color, x_label=x_label, y_label=y_label,
filename=filename, exts=exts, verbose=verbose)
def export_explore_exploit_chart(data=None, title="Exploration vs Exploitation Percentages", list_legends=("Exploration %", "Exploitation %"),
list_styles=('-', '-'), list_colors=('blue', 'orange'), x_label="#Iteration", y_label="Percentage",
filename="explore_exploit_chart", exts=(".png", ".pdf"), verbose=True):
_draw_multi_line_(data=data, title=title, list_legends=list_legends, list_styles=list_styles, list_colors=list_colors,
x_label=x_label, y_label=y_label, filename=filename, exts=exts, verbose=verbose)
def export_diversity_chart(data=None, title='Diversity Measurement Chart', list_legends=None,
list_styles=None, list_colors=None, x_label="#Iteration", y_label="Diversity Measurement",
filename="diversity_chart", exts=(".png", ".pdf"), verbose=True):
if list_styles is None:
list_styles = LIST_LINESTYLES[:len(data)]
if list_colors is None:
list_colors = LIST_COLORS[:len(data)]
_draw_multi_line_(data=data, title=title, list_legends=list_legends, list_styles=list_styles, list_colors=list_colors,
x_label=x_label, y_label=y_label, filename=filename, exts=exts, verbose=verbose)
def export_objectives_chart(data=None, title="Objectives chart", list_legends=None, list_styles=None, list_colors=None,
x_label="#Iteration", y_label="Function Value", filename="Objective-chart", exts=(".png", ".pdf"), verbose=True):
if list_styles is None:
list_styles = LIST_LINESTYLES[:len(data)]
if list_colors is None:
list_colors = LIST_COLORS[:len(data)]
_draw_multi_line_in_same_figure_(data=data, title=title, list_legends=list_legends, list_styles=list_styles, list_colors=list_colors,
x_label=x_label, y_label=y_label, filename=filename, exts=exts, verbose=verbose)
def export_trajectory_chart(data=None, n_dimensions=1, title="Trajectory of some first agents after generations", list_legends=None,
list_styles=None, list_colors=None, x_label="#Iteration", y_label="X1",
filename="1d_trajectory", exts=(".png", ".pdf"), verbose=True):
if list_styles is None:
list_styles = LIST_LINESTYLES[:len(data)]
if list_colors is None:
list_colors = LIST_COLORS[:len(data)]
if n_dimensions == 1:
x = arange(0, len(data[0]))
for idx, y in enumerate(data):
plt.plot(x, y, label=list_legends[idx], markerfacecolor=list_colors[idx], linestyle=list_styles[idx])
elif n_dimensions == 2:
for idx, point in enumerate(data):
plt.plot(point[0], point[1], label=list_legends[idx], markerfacecolor=list_colors[idx], linestyle=list_styles[idx])
plt.title(title)
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.legend() # show a legend on the plot
if filename is not None:
filepath = __check_filepath__(__clean_filename__(filename))
for idx, ext in enumerate(exts):
plt.savefig(f"{filepath}{ext}", bbox_inches='tight')
if platform.system() != "Linux" and verbose:
plt.show()
plt.close()
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] |
tests/test_ioutils.py | BiocomputeLab/curveball | 8 | 116860 | <filename>tests/test_ioutils.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# This file is part of curveball.
# https://github.com/yoavram/curveball
# Licensed under the MIT license:
# http://www.opensource.org/licenses/MIT-license
# Copyright (c) 2015, <NAME> <<EMAIL>>
from unittest import TestCase, main
from builtins import str
import tempfile
import os
import shutil
import zipfile
import pkg_resources
import curveball
import pandas as pd
RANDOM_SEED = int(os.environ.get('RANDOM_SEED', 0))
class CurveballCSVTestCase(TestCase):
def setUp(self):
self.filename = pkg_resources.resource_filename("data", "Tecan_210115.csv")
self.plate = pd.read_csv(pkg_resources.resource_filename("plate_templates", "G-RG-R.csv"))
def test_read_curveball_csv(self):
df = curveball.ioutils.read_curveball_csv(self.filename)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (4992, 9))
self.assertEqual(df.columns.tolist() , ['Time', u'Temp. [\xb0C]', 'Cycle Nr.', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color'])
def test_write_curveball_csv(self):
df = curveball.models.randomize(random_seed=RANDOM_SEED)
f, fn = tempfile.mkstemp()
curveball.ioutils.write_curveball_csv(df, fn)
df1 = pd.read_csv(fn)
pd.util.testing.assert_frame_equal(df, df1, check_dtype=False)
class TecanXLSXTestCase(TestCase):
def setUp(self):
self.filename = pkg_resources.resource_filename("data", "Tecan_210115.xlsx")
self.plate = pd.read_csv(pkg_resources.resource_filename("plate_templates", "G-RG-R.csv"))
def test_read_tecan_xlsx_OD(self):
df = curveball.ioutils.read_tecan_xlsx(self.filename, 'OD')
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (8544, 9))
self.assertEqual(df.columns.tolist() , ['Time', u'Temp. [\xb0C]', 'Cycle Nr.', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color'])
def test_read_tecan_xlsx_full(self):
df = curveball.ioutils.read_tecan_xlsx(self.filename, ('OD', 'Green', 'Red'))
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (8352, 15))
self.assertEqual(sorted(df.columns.tolist()) , sorted(['Time_OD', u'Temp. [\xb0C]_OD', 'Cycle Nr.', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color', 'Time_Green', u'Temp. [\xb0C]_Green', 'Green', 'Time', u'Temp. [\xb0C]', 'Red']))
def test_read_tecan_xlsx_12hrs(self):
df = curveball.ioutils.read_tecan_xlsx(self.filename, 'OD', max_time=12)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (4992, 9))
self.assertEqual(df.columns.tolist() , ['Time', u'Temp. [\xb0C]', 'Cycle Nr.', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color'])
def test_read_tecan_xlsx_with_plate(self):
df = curveball.ioutils.read_tecan_xlsx(self.filename, 'OD', plate=self.plate)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (8544, 9))
self.assertEqual(df.columns.tolist() , ['Time', u'Temp. [\xb0C]', 'Cycle Nr.', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color'])
class BioTekXLSXTestCase(TestCase):
def setUp(self):
self.filename = pkg_resources.resource_filename("data", "BioTekSynergy.xlsx")
def test_read_biotek_xlsx(self):
df = curveball.ioutils.read_biotek_xlsx(self.filename)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.columns.tolist(), ['Time', u'T\xb0 600', 'Well', 'OD', 'Row', 'Col', 'Strain', 'Color'])
# class XMLTestCase(TestCase):
# def setUp(self):
# self.zip_filename = pkg_resources.resource_filename("data", "Tecan_210115.xlsx")
# self.zip_filename = os.path.join("data", "20130211_dh.zip")
# self.folder = tempfile.mkdtemp()
# self.zipfile = zipfile.ZipFile(self.zip_filename)
# self.zipfile.extractall(self.folder)
# self.plate = pd.read_csv(pkg_resources.resource_filename("plate_templates", "checkerboard.csv"))
# def tearDown(self):
# shutil.rmtree(self.folder)
# def test_read_tecan_xml_with_plate(self):
# df = curveball.ioutils.read_tecan_xml(os.path.join(self.folder, "*.xml"), 'OD', plate=self.plate)
# self.assertIsNotNone(df)
# self.assertIsInstance(df, pd.DataFrame)
# self.assertEqual(df.shape, (2016, 8))
# self.assertEqual(df.columns.tolist() , ['OD', 'Well', 'Row', 'Col', 'Time', 'Filename', 'Strain', 'Color'])
class SunriseTestCase(TestCase):
def setUp(self):
self.filename = pkg_resources.resource_filename("data", "Sunrise_180515_0916.xlsx")
self.plate = pd.read_csv(pkg_resources.resource_filename("plate_templates", "G-RG-R.csv"))
def test_read_sunrise_xlsx(self):
df = curveball.ioutils.read_sunrise_xlsx(self.filename)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (96, 8))
self.assertEqual(sorted(df.columns.tolist()) , sorted([u'Time', u'Well', u'OD', u'Row', u'Col', 'Strain', 'Color', 'Filename']))
# commented out 18JUN19 due to travis-ci failure:
# ValueError: You are trying to merge on object and int64 columns. If you wish to proceed you should use pd.concat
# def test_read_sunrise_xlsx_plate(self):
# df = curveball.ioutils.read_sunrise_xlsx(self.filename, plate=self.plate)
# self.assertIsNotNone(df)
# self.assertIsInstance(df, pd.DataFrame)
# self.assertEqual(df.shape, (96, 8))
# self.assertEqual(sorted(df.columns.tolist()) , sorted([u'Time', u'Well', u'OD', u'Row', u'Col', 'Strain', 'Color', 'Filename']))
class MatTestCase(TestCase):
def setUp(self):
self.filename = pkg_resources.resource_filename("data", "plate_9_OD.mat")
self.plate = pd.read_csv(pkg_resources.resource_filename("plate_templates", "checkerboard.csv"))
def test_read_tecan_mat(self):
df = curveball.ioutils.read_tecan_mat(self.filename, plate=self.plate)
self.assertIsNotNone(df)
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(df.shape, (2496, 8))
self.assertEqual(df.columns.tolist() , [u'Cycle Nr.', u'Time', u'Well', u'OD', u'Row', u'Col', 'Strain', 'Color'])
if __name__ == '__main__':
main()
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model/QuerySpecificBBCluster.py | nihilistsumo/Blackbox_clustering | 1 | 45255 | from model.BBCluster import CustomSentenceTransformer, OptimCluster, euclid_dist
from experiments.treccar_run import prepare_cluster_data_train_only, prepare_cluster_data2, get_trec_dat, \
get_paratext_dict
from util.Data import InputTRECCARExample
import numpy as np
import torch
import torch.nn as nn
from torch import Tensor
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from typing import Dict, Iterable, List
import transformers
from sentence_transformers import SentenceTransformer
from sentence_transformers import models
from sentence_transformers.evaluation import SentenceEvaluator
from sentence_transformers.util import batch_to_device
from sklearn.cluster import AgglomerativeClustering
from sklearn.metrics import adjusted_rand_score, normalized_mutual_info_score, adjusted_mutual_info_score
from tqdm.autonotebook import trange
from clearml import Task
import pickle
import argparse
import random
random.seed(42)
torch.manual_seed(42)
np.random.seed(42)
def prepare_cluster_data_train(pages_file, art_qrels, top_qrels, paratext):
page_paras, rev_para_top, _ = get_trec_dat(art_qrels, top_qrels, None)
ptext_dict = get_paratext_dict(paratext)
top_cluster_data = []
pages = []
with open(pages_file, 'r') as f:
for l in f:
pages.append(l.rstrip('\n'))
for i in trange(len(pages)):
page = pages[i]
paras = page_paras[page]
paratexts = [ptext_dict[p] for p in paras]
top_sections = list(set([rev_para_top[p] for p in paras]))
if len(top_sections) < 2:
continue
top_labels = [top_sections.index(rev_para_top[p]) for p in paras]
query_text = ' '.join(page.split('enwiki:')[1].split('%20'))
top_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=paras, texts=paratexts,
label=np.array(top_labels)))
print('Total data instances: %5d' % len(top_cluster_data))
return top_cluster_data
def prepare_cluster_data_for_eval(art_qrels, top_qrels, paratext, do_filter, val_samples):
page_paras, rev_para_top, _ = get_trec_dat(art_qrels, top_qrels, None)
len_paras = np.array([len(page_paras[page]) for page in page_paras.keys()])
print('mean paras: %.2f, std: %.2f, max paras: %.2f' % (np.mean(len_paras), np.std(len_paras), np.max(len_paras)))
ptext_dict = get_paratext_dict(paratext)
top_cluster_data = []
pages = list(page_paras.keys())
skipped_pages = 0
max_num_doc = max([len(page_paras[p]) for p in page_paras.keys()])
for i in trange(len(pages)):
page = pages[i]
paras = page_paras[page]
paratexts = [ptext_dict[p] for p in paras]
top_sections = list(set([rev_para_top[p] for p in paras]))
top_labels = [top_sections.index(rev_para_top[p]) for p in paras]
query_text = ' '.join(page.split('enwiki:')[1].split('%20'))
n = len(paras)
if do_filter:
if n < 20 or n > 200:
skipped_pages += 1
continue
paras = paras[:max_num_doc] if n >= max_num_doc else paras + ['dummy'] * (max_num_doc - n)
paratexts = paratexts[:max_num_doc] if n >= max_num_doc else paratexts + [''] * (max_num_doc - n)
top_labels = top_labels[:max_num_doc] if n >= max_num_doc else top_labels + [-1] * (max_num_doc - n)
if do_filter:
if len(set(top_labels)) < 2 or n / len(set(top_labels)) < 2.5:
## the page should have at least 2 top level sections and n/k should be at least 2.5
skipped_pages += 1
continue
top_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=paras, texts=paratexts,
label=np.array(top_labels)))
if val_samples > 0:
top_cluster_data = top_cluster_data[:val_samples]
print('Total data instances: %5d' % len(top_cluster_data))
return top_cluster_data
class QuerySpecificClusterModel(nn.Module):
def __init__(self, path:str=None, query_transformer:CustomSentenceTransformer=None,
psg_transformer:CustomSentenceTransformer=None, device:torch.device=None):
super(QuerySpecificClusterModel, self).__init__()
if path is not None:
self.query_model = CustomSentenceTransformer(path+'/query_model')
self.psg_model = CustomSentenceTransformer(path+'/psg_model')
else:
self.query_model = query_transformer
self.psg_model = psg_transformer
self.optim = OptimCluster
self.device = device
def save(self, path):
self.query_model.save(path+'/query_model')
self.psg_model.save(path+'/psg_model')
def _get_scheduler(self, optimizer, scheduler: str, warmup_steps: int, t_total: int):
"""
Taken from SentenceTransformers
Returns the correct learning rate scheduler
"""
scheduler = scheduler.lower()
if scheduler == 'constantlr':
return transformers.get_constant_schedule(optimizer)
elif scheduler == 'warmupconstant':
return transformers.get_constant_schedule_with_warmup(optimizer, num_warmup_steps=warmup_steps)
elif scheduler == 'warmuplinear':
return transformers.get_linear_schedule_with_warmup(optimizer, num_warmup_steps=warmup_steps,
num_training_steps=t_total)
elif scheduler == 'warmupcosine':
return transformers.get_cosine_schedule_with_warmup(optimizer, num_warmup_steps=warmup_steps,
num_training_steps=t_total)
elif scheduler == 'warmupcosinewithhardrestarts':
return transformers.get_cosine_with_hard_restarts_schedule_with_warmup(optimizer,
num_warmup_steps=warmup_steps,
num_training_steps=t_total)
else:
raise ValueError("Unknown scheduler {}".format(scheduler))
def query_batch_collate_fn(self, batch):
num_texts = len(batch[0].texts)
queries = []
texts = [[] for _ in range(num_texts)]
labels = []
for example in batch:
queries.append(example.q_context)
for idx, text in enumerate(example.texts):
texts[idx].append(text)
labels.append(example.label)
labels = torch.tensor(labels).to(self.device)
q_tokenized = self.query_model.tokenize(queries)
batch_to_device(q_tokenized, self.device)
psg_features = []
for idx in range(num_texts):
p_tokenized = self.psg_model.tokenize(texts[idx])
batch_to_device(p_tokenized, self.device)
psg_features.append(p_tokenized)
return q_tokenized, psg_features, labels
def forward(self, query_feature: Dict[str, Tensor], passage_features: Iterable[Dict[str, Tensor]], labels: Tensor):
n = labels.shape[1]
query_embedding = self.query_model(query_feature)['sentence_embedding']
# its the scaling vector, so each element in vector should be [0, 1]
psg_embeddings = torch.stack([self.psg_model(passages)['sentence_embedding']
for passages in passage_features], dim=1)
scaled_psg_embeddings = torch.tile(query_embedding.unsqueeze(1), (1, n, 1)) * psg_embeddings
return scaled_psg_embeddings
class BBClusterLossModel(nn.Module):
def __init__(self, model: QuerySpecificClusterModel, device, lambda_val: float, reg_const: float):
super(BBClusterLossModel, self).__init__()
self.model = model
self.lambda_val = lambda_val
self.reg = reg_const
self.optim = OptimCluster()
self.device = device
def true_adj_mat(self, label):
n = label.numel()
adj_mat = torch.zeros((n, n))
for i in range(n):
for j in range(n):
if i == j or label[i] == label[j]:
adj_mat[i][j] = 1.0
return adj_mat
def forward(self, query_feature: Dict[str, Tensor], passage_features: Iterable[Dict[str, Tensor]], labels: Tensor):
batch_size = labels.shape[0]
n = labels.shape[1]
ks = [torch.unique(labels[i]).numel() for i in range(batch_size)]
true_adjacency_mats = torch.stack([self.true_adj_mat(labels[i]) for i in range(batch_size)]).to(self.device)
query_embedding = self.model.query_model(query_feature)['sentence_embedding']
# its the scaling vector, so each element in vector should be [0, 1]
psg_embeddings = torch.stack([self.model.psg_model(passages)['sentence_embedding']
for passages in passage_features], dim=1)
scaled_psg_embeddings = torch.tile(query_embedding.unsqueeze(1), (1, n, 1)) * psg_embeddings
embeddings_dist_mats = torch.stack([euclid_dist(scaled_psg_embeddings[i]) for i in range(batch_size)])
mean_similar_dist = (embeddings_dist_mats * true_adjacency_mats).sum() / true_adjacency_mats.sum()
mean_dissimilar_dist = (embeddings_dist_mats * (1.0 - true_adjacency_mats)).sum() / (
1 - true_adjacency_mats).sum()
adjacency_mats = self.optim.apply(embeddings_dist_mats, self.lambda_val, ks).to(self.device)
err_mats = adjacency_mats * (1.0 - true_adjacency_mats) + (1.0 - adjacency_mats) * true_adjacency_mats
err_mean = err_mats.mean(dim=0).sum()
loss = err_mean + self.reg * (mean_similar_dist - mean_dissimilar_dist)
return loss
class BBClusterRNNLossModel(nn.Module):
def __init__(self, model: QuerySpecificClusterModel, device, lambda_val: float, reg_const: float):
super(BBClusterRNNLossModel, self).__init__()
self.model = model
self.lambda_val = lambda_val
self.reg = reg_const
self.optim = OptimCluster()
self.device = device
def true_adj_mat(self, label):
n = label.numel()
adj_mat = torch.zeros((n, n))
for i in range(n):
for j in range(n):
if i == j or label[i] == label[j]:
adj_mat[i][j] = 1.0
return adj_mat
def forward(self, query_feature: Dict[str, Tensor], passage_features: Iterable[Dict[str, Tensor]], labels: Tensor):
batch_size = labels.shape[0]
n = labels.shape[1]
ks = [torch.unique(labels[i]).numel() for i in range(batch_size)]
true_adjacency_mats = torch.stack([self.true_adj_mat(labels[i]) for i in range(batch_size)]).to(self.device)
psg_embeddings = torch.stack([self.model.psg_model(passages)['sentence_embedding']
for passages in passage_features], dim=1)
scaling_vector = torch.tensor([0])
# obtain the scaling vector from psg_embeddngs using RNN
scaled_psg_embeddings = torch.tile(scaling_vector.unsqueeze(1), (1, n, 1)) * psg_embeddings
embeddings_dist_mats = torch.stack([euclid_dist(scaled_psg_embeddings[i]) for i in range(batch_size)])
mean_similar_dist = (embeddings_dist_mats * true_adjacency_mats).sum() / true_adjacency_mats.sum()
mean_dissimilar_dist = (embeddings_dist_mats * (1.0 - true_adjacency_mats)).sum() / (
1 - true_adjacency_mats).sum()
adjacency_mats = self.optim.apply(embeddings_dist_mats, self.lambda_val, ks).to(self.device)
err_mats = adjacency_mats * (1.0 - true_adjacency_mats) + (1.0 - adjacency_mats) * true_adjacency_mats
err_mean = err_mats.mean(dim=0).sum()
loss = err_mean + self.reg * (mean_similar_dist - mean_dissimilar_dist)
return loss
class QueryClusterEvaluator(SentenceEvaluator):
def __init__(self, queries: List[str], passages: List[List[str]], labels: List[Tensor], use_model_device=True):
self.queries = queries
self.passages = passages
self.labels = labels
self.use_model_device = use_model_device
@classmethod
def from_input_examples(cls, examples: List[InputTRECCARExample], use_model_device, **kwargs):
queries = []
passages = []
labels = []
for example in examples:
queries.append(example.q_context)
passages.append(example.texts)
labels.append(torch.from_numpy(example.label))
return cls(queries=queries, passages=passages, labels=labels, use_model_device=use_model_device, **kwargs)
def euclid_dist(self, x):
dist_mat = torch.norm(x[:, None] - x, dim=2, p=2)
return dist_mat
def __call__(self, model, output_path: str = None, epoch: int = -1, steps: int = -1) -> float:
rand_scores, nmi_scores, ami_scores = [], [], []
model_device = model.device
if not self.use_model_device:
model.cpu()
for i in trange(len(self.queries), desc="Evaluating on val", smoothing=0.05):
query = self.queries[i]
passages_to_cluster = [self.passages[i][p] for p in range(len(self.passages[i]))
if len(self.passages[i][p])>0]
true_label = self.labels[i][:len(passages_to_cluster)]
query_feature = model.query_model.tokenize(query)
doc_features = model.psg_model.tokenize(passages_to_cluster)
if self.use_model_device:
batch_to_device(doc_features, model_device)
query_embedding = model.query_model(query_feature)['sentence_embedding']
psg_embeddings = model.psg_model(doc_features)['sentence_embedding']
scaled_psg_embeddings = query_embedding * psg_embeddings
embeddings_dist_mat = self.euclid_dist(scaled_psg_embeddings)
cl = AgglomerativeClustering(n_clusters=torch.unique(true_label).numel(), affinity='precomputed',
linkage='average')
cluster_label = cl.fit_predict(embeddings_dist_mat.detach().cpu().numpy())
rand_scores.append(adjusted_rand_score(true_label.numpy(), cluster_label))
nmi_scores.append(normalized_mutual_info_score(true_label.numpy(), cluster_label))
ami_scores.append(adjusted_mutual_info_score(true_label.numpy(), cluster_label))
mean_rand = np.mean(np.array(rand_scores))
mean_nmi = np.mean(np.array(nmi_scores))
mean_ami = np.mean(np.array(ami_scores))
print("\nRAND: %.5f, NMI: %.5f, AMI: %.5f\n" % (mean_rand, mean_nmi, mean_ami), flush=True)
if not self.use_model_device:
model.to(model_device)
return mean_rand
def train(train_cluster_data, val_cluster_data, test_cluster_data, output_path, eval_steps,
num_epochs, warmup_frac, lambda_val, reg, use_model_device, max_train_size=-1, train_psg_model=False,
model_name='distilbert-base-uncased', out_features=256, steps_per_epoch=None, weight_decay=0.01,
optimizer_class=transformers.AdamW, scheduler='WarmupLinear', optimizer_params={'lr':2e-5},
show_progress_bar=True, max_grad_norm=1, save_best_model=True):
tensorboard_writer = SummaryWriter('./tensorboard_logs')
task = Task.init(project_name='Query Specific BB Clustering', task_name='query_bbc_fixed_lambda')
config_dict = {'lambda_val': lambda_val, 'reg': reg}
config_dict = task.connect(config_dict)
if torch.cuda.is_available():
device = torch.device('cuda')
print('CUDA is available and using device: '+str(device))
else:
device = torch.device('cpu')
print('CUDA not available, using device: '+str(device))
### Configure sentence transformers for training and train on the provided dataset
# Use Huggingface/transformers model (like BERT, RoBERTa, XLNet, XLM-R) for mapping tokens to embeddings
query_word_embedding_model = models.Transformer(model_name)
# Apply mean pooling to get one fixed sized sentence vector
query_pooling_model = models.Pooling(query_word_embedding_model.get_word_embedding_dimension(),
pooling_mode_mean_tokens=True,
pooling_mode_cls_token=False,
pooling_mode_max_tokens=False)
query_dense_model = models.Dense(in_features=query_pooling_model.get_sentence_embedding_dimension(),
out_features=out_features,
activation_function=nn.Sigmoid())
psg_word_embedding_model = models.Transformer(model_name)
# Apply mean pooling to get one fixed sized sentence vector
psg_pooling_model = models.Pooling(psg_word_embedding_model.get_word_embedding_dimension(),
pooling_mode_mean_tokens=True,
pooling_mode_cls_token=False,
pooling_mode_max_tokens=False)
psg_dense_model = models.Dense(in_features=psg_pooling_model.get_sentence_embedding_dimension(),
out_features=out_features,
activation_function=nn.Tanh())
query_model = CustomSentenceTransformer(modules=[query_word_embedding_model, query_pooling_model,
query_dense_model])
psg_model = SentenceTransformer(modules=[psg_word_embedding_model, psg_pooling_model, psg_dense_model])
model = QuerySpecificClusterModel(query_transformer=query_model, psg_transformer=psg_model, device=device)
train_dataloader = DataLoader(train_cluster_data, shuffle=True, batch_size=1)
evaluator = QueryClusterEvaluator.from_input_examples(val_cluster_data, use_model_device)
test_evaluator = QueryClusterEvaluator.from_input_examples(test_cluster_data, use_model_device)
warmup_steps = int(len(train_dataloader) * num_epochs * warmup_frac) # 10% of train data
print("Untrained performance")
model.to(device)
evaluator(model)
train_dataloader.collate_fn = model.query_batch_collate_fn
# Train the model
best_score = -9999999
if steps_per_epoch is None or steps_per_epoch == 0:
steps_per_epoch = len(train_dataloader)
num_train_steps = int(steps_per_epoch * num_epochs)
param_optimizer = list(model.named_parameters())
no_decay = ['bias', 'LayerNorm.bias', 'LayerNorm.weight']
optimizer_grouped_parameters = [
{'params': [p for n, p in param_optimizer if not any(nd in n for nd in no_decay)],
'weight_decay': weight_decay},
{'params': [p for n, p in param_optimizer if any(nd in n for nd in no_decay)], 'weight_decay': 0.0}
]
data_iter = iter(train_dataloader)
optimizer = optimizer_class(optimizer_grouped_parameters, **optimizer_params)
scheduler_obj = model._get_scheduler(optimizer, scheduler=scheduler, warmup_steps=warmup_steps,
t_total=num_train_steps)
config = {'epochs': num_epochs, 'steps_per_epoch': steps_per_epoch}
global_step = 0
loss_model = BBClusterLossModel(model, device, lambda_val, reg)
for epoch in trange(config.get('epochs'), desc="Epoch", disable=not show_progress_bar):
training_steps = 0
running_loss_0 = 0.0
model.zero_grad()
model.train()
if not train_psg_model:
for m in model.psg_model.modules():
m.training = False
for _ in trange(config.get('steps_per_epoch'), desc="Iteration", smoothing=0.05, disable=not show_progress_bar):
try:
data = next(data_iter)
except StopIteration:
data_iter = iter(train_dataloader)
data = next(data_iter)
query_feature, psg_features, labels = data
if max_train_size > 0 and labels.shape[1] > max_train_size:
print('skipping instance with '+str(labels.shape[1])+' passages')
continue
loss_val = loss_model(query_feature, psg_features, labels)
running_loss_0 += loss_val.item()
loss_val.backward()
torch.nn.utils.clip_grad_norm_(model.parameters(), max_grad_norm)
optimizer.step()
optimizer.zero_grad()
scheduler_obj.step()
training_steps += 1
global_step += 1
if eval_steps > 0 and training_steps % eval_steps == 0:
tensorboard_writer.add_scalar('training_loss', running_loss_0 / eval_steps, global_step)
# logger.report_scalar('Loss', 'training_loss', iteration=global_step, v
# alue=running_loss_0/evaluation_steps)
running_loss_0 = 0.0
# self._eval_during_training(evaluator, output_path, save_best_model, epoch, training_steps, callback)
if evaluator is not None:
score = evaluator(model, output_path=output_path, epoch=epoch, steps=training_steps)
tensorboard_writer.add_scalar('val_ARI', score, global_step)
# logger.report_scalar('Training progress', 'val_ARI', iteration=global_step, value=score)
if score > best_score:
best_score = score
if save_best_model:
print('Saving model at: ' + output_path)
model.save(output_path)
model.zero_grad()
model.train()
if not train_psg_model:
for m in model.psg_model.modules():
m.training = False
if evaluator is not None:
score = evaluator(model, output_path=output_path, epoch=epoch, steps=training_steps)
tensorboard_writer.add_scalar('val_ARI', score, global_step)
# logger.report_scalar('Training progress', 'val_ARI', iteration=global_step, value=score)
if score > best_score:
best_score = score
if save_best_model:
model.save(output_path)
if test_evaluator is not None:
best_model = QuerySpecificClusterModel(output_path)
if torch.cuda.is_available():
model.to(torch.device('cpu'))
best_model.to(device)
test_ari = test_evaluator(best_model)
best_model.to(torch.device('cpu'))
model.to(device)
else:
test_ari = test_evaluator(best_model)
tensorboard_writer.add_scalar('test_ARI', test_ari, global_step)
# logger.report_scalar('Training progress', 'test_ARI', iteration=global_step, value=test_ari)
if evaluator is None and output_path is not None: # No evaluator, but output path: save final model version
model.save(output_path)
def save_sqst_dataset(train_pages_file, art_qrels, top_qrels, paratext, val_samples, outdir):
page_paras, rev_para_top, _ = get_trec_dat(art_qrels, top_qrels, None)
ptext_dict = get_paratext_dict(paratext)
train_cluster_data = []
test_cluster_data = []
pages = []
with open(train_pages_file, 'r') as f:
for l in f:
pages.append(l.rstrip('\n'))
for i in trange(len(pages)):
page = pages[i]
paras = page_paras[page]
page_sec_para_dict = {}
for p in paras:
sec = rev_para_top[p]
if sec not in page_sec_para_dict.keys():
page_sec_para_dict[sec] = [p]
else:
page_sec_para_dict[sec].append(p)
sections = list(set([rev_para_top[p] for p in paras]))
train_paras = []
test_paras = []
for s in page_sec_para_dict.keys():
test_paras += page_sec_para_dict[s][:len(page_sec_para_dict[s])//2]
train_paras += page_sec_para_dict[s][len(page_sec_para_dict[s])//2:]
test_labels = [sections.index(rev_para_top[p]) for p in test_paras]
train_labels = [sections.index(rev_para_top[p]) for p in train_paras]
test_paratexts = [ptext_dict[p] for p in test_paras]
train_paratexts = [ptext_dict[p] for p in train_paras]
query_text = ' '.join(page.split('enwiki:')[1].split('%20'))
test_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=test_paras,
texts=test_paratexts, label=np.array(test_labels)))
train_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=train_paras,
texts=train_paratexts, label=np.array(train_labels)))
random.shuffle(test_cluster_data)
val_cluster_data = test_cluster_data[:val_samples]
test_cluster_data = test_cluster_data[val_samples:]
with open(outdir + '/sqst_treccar_train.pkl', 'wb') as f:
pickle.dump(train_cluster_data, f)
with open(outdir + '/sqst_treccar_val.pkl', 'wb') as f:
pickle.dump(val_cluster_data, f)
with open(outdir + '/sqst_treccar_test.pkl', 'wb') as f:
pickle.dump(test_cluster_data, f)
print('No. of data instances - Train: %5d, Val: %5d, Test: %5d' % (len(train_cluster_data), len(val_cluster_data),
len(test_cluster_data)))
def save_squt_dataset(train_pages_file, art_qrels, top_qrels, paratext, val_samples, outdir):
page_paras, rev_para_top, _ = get_trec_dat(art_qrels, top_qrels, None)
ptext_dict = get_paratext_dict(paratext)
train_cluster_data = []
test_cluster_data = []
pages = []
with open(train_pages_file, 'r') as f:
for l in f:
pages.append(l.rstrip('\n'))
for i in trange(len(pages)):
page = pages[i]
paras = page_paras[page]
page_sec_para_dict = {}
for p in paras:
sec = rev_para_top[p]
if sec not in page_sec_para_dict.keys():
page_sec_para_dict[sec] = [p]
else:
page_sec_para_dict[sec].append(p)
sections = list(set([rev_para_top[p] for p in paras]))
random.shuffle(sections)
test_sections, train_sections = sections[:len(sections)//2], sections[len(sections)//2:]
train_paras = []
test_paras = []
for s in test_sections:
test_paras += page_sec_para_dict[s]
for s in train_sections:
train_paras += page_sec_para_dict[s]
test_labels = [sections.index(rev_para_top[p]) for p in test_paras]
train_labels = [sections.index(rev_para_top[p]) for p in train_paras]
test_paratexts = [ptext_dict[p] for p in test_paras]
train_paratexts = [ptext_dict[p] for p in train_paras]
query_text = ' '.join(page.split('enwiki:')[1].split('%20'))
test_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=test_paras,
texts=test_paratexts, label=np.array(test_labels)))
train_cluster_data.append(InputTRECCARExample(qid=page, q_context=query_text, pids=train_paras,
texts=train_paratexts, label=np.array(train_labels)))
random.shuffle(test_cluster_data)
val_cluster_data = test_cluster_data[:val_samples]
test_cluster_data = test_cluster_data[val_samples:]
with open(outdir + '/squt_treccar_train.pkl', 'wb') as f:
pickle.dump(train_cluster_data, f)
with open(outdir + '/squt_treccar_val.pkl', 'wb') as f:
pickle.dump(val_cluster_data, f)
with open(outdir + '/squt_treccar_test.pkl', 'wb') as f:
pickle.dump(test_cluster_data, f)
print(
'No. of data instances - Train: %5d, Val: %5d, Test: %5d' % (len(train_cluster_data), len(val_cluster_data),
len(test_cluster_data)))
def save_sbert_embeds(sbert_model_name, pages_path, art_qrels, paratext_file, outpath):
sbert = SentenceTransformer(sbert_model_name)
page_paras, _, _ = get_trec_dat(art_qrels, None, None)
paratext_dict = get_paratext_dict(paratext_file)
paras = []
paratexts = []
with open(pages_path, 'r') as f:
for l in f:
page = l.rstrip('\n')
paras += page_paras[page]
paratexts += [paratext_dict[p] for p in page_paras[page]]
print(str(len(paratexts))+' paras to be encoded')
para_embeddings = sbert.encode(paratexts, show_progress_bar=True)
para_data = {'paraids': paras, 'paravecs': para_embeddings}
with open(outpath, 'wb') as f:
pickle.dump(para_data, f)
def main():
parser = argparse.ArgumentParser(description='Run treccar experiments')
parser.add_argument('-in', '--input_dir', default='/home/sk1105/sumanta/trec_dataset/train')
parser.add_argument('-out', '--output_model_path', default='/home/sk1105/sumanta/bb_cluster_models/temp_model')
parser.add_argument('-mn', '--model_name', default='distilbert-base-uncased')
parser.add_argument('-ls', '--loss', default='bb')
parser.add_argument('-lm', '--lambda_val', type=float, default=200.0)
parser.add_argument('-b', '--beta', type=float, default=10.0)
parser.add_argument('-rg', '--reg_const', type=float, default=2.5)
parser.add_argument('-ep', '--num_epoch', type=int, default=3)
parser.add_argument('-ws', '--warmup', type=float, default=0.1)
parser.add_argument('-es', '--eval_steps', type=int, default=100)
parser.add_argument('-md', '--max_sample_size', type=int, default=-1)
parser.add_argument('-ext', '--exp_type', default='sqst')
parser.add_argument('--gpu_eval', default=False, action='store_true')
parser.add_argument('--train_psg_model', default=False, action='store_true')
args = parser.parse_args()
input_dir = args.input_dir
output_path = args.output_model_path
model_name = args.model_name
loss_name = args.loss
lambda_val = args.lambda_val
beta = args.beta
reg = args.reg_const
epochs = args.num_epoch
warmup_fraction = args.warmup
eval_steps = args.eval_steps
max_sample_size = args.max_sample_size
exp_type = args.exp_type
gpu_eval = args.gpu_eval
train_psg_model = args.train_psg_model
if exp_type == 'sqst':
with open(input_dir + '/sqst/sqst_treccar_train.pkl', 'rb') as f:
train_cluster_data = pickle.load(f)
with open(input_dir + '/sqst/sqst_treccar_val.pkl', 'rb') as f:
val_cluster_data = pickle.load(f)
with open(input_dir + '/sqst/sqst_treccar_test.pkl', 'rb') as f:
test_cluster_data = pickle.load(f)
elif exp_type == 'squt':
with open(input_dir + '/squt/squt_treccar_train.pkl', 'rb') as f:
train_cluster_data = pickle.load(f)
with open(input_dir + '/squt/squt_treccar_val.pkl', 'rb') as f:
val_cluster_data = pickle.load(f)
with open(input_dir + '/squt/squt_treccar_test.pkl', 'rb') as f:
test_cluster_data = pickle.load(f)
print('Data loaded, starting to train')
train(train_cluster_data, val_cluster_data, test_cluster_data, output_path, eval_steps, epochs, warmup_fraction,
lambda_val, reg, gpu_eval, max_train_size=max_sample_size, train_psg_model=train_psg_model,
model_name=model_name)
if __name__ == '__main__':
main() | [
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basic_synthesizer/basic_synthesizer.py | Privacy-Police/Differential-Privacy | 0 | 182724 | <reponame>Privacy-Police/Differential-Privacy
import pandas as pd
from categorical import CategoricalDistribution
from gaussian import GaussianDistribution
class BasicSynthesizer:
"""
Basic Synthesizer to compare with Normalizing Flows model
"""
def __init__(self, dataset):
self.dataset = dataset
self.analyze_dataset()
def analyze_dataset(self):
self.columns = {} # column_name : Distribution
for column_name, _ in self.dataset.iteritems():
column = self.dataset[column_name]
if str(column.dtype) == 'int64' or str(column.dtype) == 'float64':
self.columns[column_name] = GaussianDistribution(column)
elif str(column.dtype) == 'object':
self.columns[column_name] = CategoricalDistribution(column)
else:
print('Unrecognized column type!')
def sample(self, n):
generated_columns = [pd.Series(dist.sample(n), name=column_name) for column_name, dist in self.columns.items()]
return pd.concat(generated_columns, axis=1)
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13,
13,
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2
] |
src/sgp_ausgabe.py | TheresaHeim/Adafruit_Blinka | 0 | 127350 | <filename>src/sgp_ausgabe.py
""" Example for using the SGP30 with CircuitPython and the Adafruit library"""
import time
import board
import busio
import adafruit_sgp30
i2c = busio.I2C(board.SCL, board.SDA, frequency=100000)
# Create library object on our I2C port
sgp30 = adafruit_sgp30.Adafruit_SGP30(i2c)
("SGP30 serial #", [hex(i) for i in sgp30.serial])
sgp30.iaq_init()
sgp30.set_iaq_baseline(0x986b, 0x8a6a)
elapsed_sec =0
datei = open('textdatei.txt','a')
while elapsed_sec < 7200:
print("eCO2 = %d ppm \t TVOC = %d ppb" % (sgp30.eCO2, sgp30.TVOC))
datei.write("%d ppm \t TVOC = %d ppb \n" % (sgp30.eCO2, sgp30.TVOC))
time.sleep(1)
elapsed_sec += 1
#if elapsed_sec > 10:
# elapsed_sec = 0
# print(
# "**** Baseline values: eCO2 = 0x%x, TVOC = 0x%x"
# % (sgp30.baseline_eCO2, sgp30.baseline_TVOC)
# )
datei.close()
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src/wi/utils/decorators.py | cc1-cloud/cc1 | 11 | 66230 | # -*- coding: utf-8 -*-
# @COPYRIGHT_begin
#
# Copyright [2010-2014] Institute of Nuclear Physics PAN, Krakow, Poland
#
# 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.
#
# @COPYRIGHT_end
"""@package src.wi.utils.decorators
@author <NAME>
@author <NAME>
"""
import logging
from django.conf import settings
from django.http import HttpResponseRedirect
from django.utils.http import urlquote
from wi.utils import REDIRECT_FIELD_NAME
from wi.utils.messages_ajax import success
from wi.utils.messages_codes import auth_error_text
def django_view(fun):
"""
Logs any exception thrown by a view.
"""
wi_logger = logging.getLogger('wi_logger')
def wrapper(*args, **kwargs):
"""
Returned decorated function.
"""
try:
ret = fun(*args, **kwargs)
except Exception, ex:
wi_logger.exception('General exception: %s' % str(ex))
raise ex
return ret
wrapper.__module__ = fun.__module__
wrapper.__name__ = fun.__name__
wrapper.__doc__ = fun.__doc__
return wrapper
login_url = settings.LOGIN_URL
cm_login_url = '/admin_cm/login/'
def user_permission(view_func):
"""
\b Decorator for views with logged user permissions.
"""
def wrap(request, *args, **kwds):
"""
Returned decorated function.
"""
if 'user' in request.session:
return view_func(request, *args, **kwds)
if request.is_ajax():
return success(unicode(auth_error_text), status=8002)
path = urlquote(request.get_full_path())
tup = login_url, REDIRECT_FIELD_NAME, path
return HttpResponseRedirect('%s?%s=%s' % tup)
return wrap
def admin_clm_permission(view_func):
"""
\b Decorator for views with logged Cloud Manager admin permissions.
"""
def wrap(request, *args, **kwds):
"""
Returned decorated function.
"""
if 'user' in request.session and request.session['user'].is_admin_clm:
return view_func(request, *args, **kwds)
if request.is_ajax():
return success(auth_error_text, status=8003)
path = urlquote(request.get_full_path())
tup = login_url, REDIRECT_FIELD_NAME, path
return HttpResponseRedirect('%s?%s=%s' % tup)
return wrap
def admin_cm_permission(view_func):
"""
\b Decorator for views with logged Cluster Manager admin permissions.
"""
def wrap(request, *args, **kwds):
"""
Returned decorated function.
"""
if 'user' in request.session and request.session['user'].is_logged_admin_cm:
return view_func(request, *args, **kwds)
if request.is_ajax():
return success(auth_error_text, status=8004)
path = urlquote(request.get_full_path())
tup = cm_login_url, REDIRECT_FIELD_NAME, path
return HttpResponseRedirect('%s?%s=%s' % tup)
return wrap
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queryable_properties/managers.py | W1ldPo1nter/django-queryable-properties | 36 | 15128 | # encoding: utf-8
from __future__ import unicode_literals
import six
from django.db.models import Manager
from django.db.models.query import QuerySet
from .compat import (ANNOTATION_SELECT_CACHE_NAME, ANNOTATION_TO_AGGREGATE_ATTRIBUTES_MAP, chain_query, chain_queryset,
ModelIterable, ValuesQuerySet)
from .exceptions import QueryablePropertyDoesNotExist, QueryablePropertyError
from .query import QueryablePropertiesQueryMixin
from .utils import get_queryable_property
from .utils.internal import InjectableMixin, QueryPath, QueryablePropertyReference
class QueryablePropertiesIterable(InjectableMixin):
"""
An iterable that yields the actual results of a queryset while correctly
processing columns of queryable properties. It is closely related to
Django's BaseIterable and will be used as a mixin for its subclasses in all
(recent) Django versions that have it. In all other (older) versions, this
class will be used as a standalone iterable instead.
"""
def __init__(self, queryset, *args, **kwargs):
"""
Initialize a new iterable for the given queryset. If an iterable is
given it will be used to retrieve the model instances before applying
queryable properties logic (standalone usage for older Django
versions). Otherwise, the __iter__ implementation of the base class
is used to get the model instances (usage as mixin).
:param QuerySet queryset: The queryset to perform the database query
for.
:param collections.Iterable iterable: The optional iterable to use for
standalone usage.
:param args: Positional arguments to pass through to the base class
initialization when used as a mixin.
:param kwargs: Keyword arguments to pass through to the base class
initialization when used as a mixin.
:keyword collections.Iterable iterable: The optional iterable to use
for standalone usage.
"""
self.queryset = queryset
# Only perform the super call if the class is used as a mixin
if self.__class__.__bases__ != (InjectableMixin,):
super(QueryablePropertiesIterable, self).__init__(queryset, *args, **kwargs)
self.iterable = kwargs.get('iterable') or super(QueryablePropertiesIterable, self).__iter__()
self.yields_model_instances = ((ModelIterable is not None and isinstance(self, ModelIterable)) or
(ValuesQuerySet is not None and not isinstance(self.queryset, ValuesQuerySet)))
def __iter__(self):
"""
Yield the model objects for the queryset associated with this iterator
with their correctly processed selected queryable properties.
:return: A generator that yields the model objects.
"""
original_query = self.queryset.query
try:
self.queryset.query = chain_query(original_query)
final_aliases = self._setup_queryable_properties()
for obj in self.iterable:
if self.yields_model_instances:
# Retrieve the annotation values from each renamed
# attribute and use it to populate the cache for the
# corresponding queryable property on each object while
# removing the weird, renamed attributes.
for changed_name, property_ref in six.iteritems(final_aliases):
value = getattr(obj, changed_name)
delattr(obj, changed_name)
if property_ref:
property_ref.descriptor.set_cached_value(obj, value)
yield obj
finally:
self.queryset.query = original_query
def _setup_queryable_properties(self):
"""
Perform the required setup to correctly process queryable property
values.
Change the internal aliases of the annotations that belong to queryable
properties in the query of the associated queryset to something unique
and return a dictionary mapping the queryable properties to the changed
aliases. This is necessary to allow Django to populate the annotation
attributes on the resulting model instances, which would otherwise call
the setter of the queryable properties. This way, Django can populate
attributes with different names and avoid using the setter methods.
Also make sure that ordering by queryable properties works in older
Django versions.
:return: A dictionary mapping the final aliases for queryable
properties to the corresponding references to be able to
retrieve the values from the DB and apply them to the correct
property. The property reference may be None, indicating that
the retrieved value should be discarded.
:rtype: dict[str, QueryablePropertyReference | None]
"""
query = self.queryset.query
final_aliases = {}
select = dict(query.annotation_select)
for property_ref in query._queryable_property_annotations:
annotation_name = six.text_type(property_ref.full_path)
# Older Django versions don't work with the annotation select dict
# when it comes to ordering, so queryable property annotations used
# for ordering need special treatment.
order_by_occurrences = []
if ANNOTATION_TO_AGGREGATE_ATTRIBUTES_MAP: # pragma: no cover
order_by_occurrences = [index for index, field_name in enumerate(query.order_by)
if field_name in (annotation_name, '-{}'.format(annotation_name))]
if order_by_occurrences and annotation_name not in select and annotation_name in query.annotations:
select[annotation_name] = query.annotations[annotation_name]
final_aliases[annotation_name] = None
if not self.yields_model_instances or annotation_name not in select:
# The queryable property annotation does not require selection
# or no renaming needs to occur since the queryset doesn't
# yield model instances.
continue
# Suffix the original annotation name with the lookup separator to
# create a non-clashing name: both model field an queryable
# property names are not allowed to contain the separator and a
# relation path ending with the separator would be invalid as well.
changed_name = six.text_type(property_ref.full_path + '')
final_aliases[changed_name] = final_aliases.pop(annotation_name, property_ref)
select[changed_name] = select.pop(annotation_name)
for index in order_by_occurrences: # pragma: no cover
# Apply the changed names to the ORDER BY clause.
query.order_by[index] = query.order_by[index].replace(annotation_name, changed_name)
# Patch the correct select property on the query with the new names,
# since this property is used by the SQL compiler to build the actual
# SQL query (which is where the changed names should be used).
setattr(query, ANNOTATION_SELECT_CACHE_NAME, select)
return final_aliases
class QueryablePropertiesQuerySetMixin(InjectableMixin):
"""
A mixin for Django's :class:`django.db.models.QuerySet` objects that allows
to use queryable properties in filters, annotations and update queries.
"""
def init_injected_attrs(self):
# To work correctly, a query using the QueryablePropertiesQueryMixin is
# required. If the current query is not using the mixin already, it
# will be dynamically injected into the query. That way, other Django
# extensions using custom query objects are also supported.
class_name = 'QueryableProperties' + self.query.__class__.__name__
self.query = QueryablePropertiesQueryMixin.inject_into_object(chain_query(self.query), class_name)
@property
def _iterable_class(self):
# Override the regular _iterable_class attribute of recent Django
# versions with a property that also stores the value in the instance
# dict, but automatically mixes the QueryablePropertiesModelIterable
# into the base class on getter access if the base class yields model
# instances. That way, the queryable properties extensions stays
# compatible to custom iterable classes while querysets can still be
# pickled due to the base class being in the instance dict.
cls = self.__dict__['_iterable_class']
return QueryablePropertiesIterable.mix_with_class(cls, 'QueryableProperties' + cls.__name__)
@_iterable_class.setter
def _iterable_class(self, value):
self.__dict__['_iterable_class'] = value
def _clone(self, klass=None, *args, **kwargs):
if klass: # pragma: no cover
# In older Django versions, the class of the queryset may be
# replaced with a dynamically created class based on the current
# class and the value of klass while cloning (e.g when using
# .values()). Therefore this needs to be re-injected to be on top
# of the MRO again to enable queryable properties functionality.
klass = QueryablePropertiesQuerySetMixin.mix_with_class(klass, 'QueryableProperties' + klass.__name__)
args = (klass,) + args
clone = super(QueryablePropertiesQuerySetMixin, self)._clone(*args, **kwargs)
# Since the _iterable_class property may return a dynamically created
# class, the value of a clone must be reset to the base class.
if '_iterable_class' in self.__dict__:
clone._iterable_class = self.__dict__['_iterable_class']
return clone
def _resolve_update_kwargs(self, **kwargs):
"""
Look for the names of queryable properties in the given keyword
arguments for an update query and correctly resolve them into their
actual keyword arguments.
:param kwargs: Keyword arguments of an update query.
:return: A dictionary containing the resolved arguments.
:rtype: dict
"""
original_names = set(kwargs)
for original_name in original_names:
try:
prop = get_queryable_property(self.model, original_name)
except QueryablePropertyDoesNotExist:
continue
if not prop.get_update_kwargs:
raise QueryablePropertyError('Queryable property "{}" does not implement queryset updating.'
.format(prop))
# Call the method recursively since queryable properties can build
# upon each other.
additional_kwargs = self._resolve_update_kwargs(
**prop.get_update_kwargs(self.model, kwargs.pop(original_name)))
# Make sure that there are no conflicting values after resolving
# the update keyword arguments of the queryable properties.
for additional_name, value in six.iteritems(additional_kwargs):
if additional_name in kwargs and kwargs[additional_name] != value:
raise QueryablePropertyError(
'Updating queryable property "{prop}" would change field "{field}", but a conflicting value '
'was set for this field by another queryable property or explicitly in the update arguments.'
.format(prop=prop, field=additional_name)
)
kwargs[additional_name] = value
return kwargs
def select_properties(self, *names):
"""
Add the annotations of the queryable properties with the specified
names to this query. The annotation values will be cached in the
properties of resulting model instances, regardless of the regular
caching behavior of the queried properties.
:param names: Names of queryable properties.
:return: A copy of this queryset with the added annotations.
:rtype: QuerySet
"""
queryset = chain_queryset(self)
for name in names:
property_ref = QueryablePropertyReference(get_queryable_property(self.model, name), self.model, QueryPath())
# A full GROUP BY is required if the query is not limited to
# certain fields. Since only certain types of queries had the
# _fields attribute in old Django versions, fall back to checking
# for existing selection, on which the GROUP BY would be based.
full_group_by = not getattr(self, '_fields', self.query.select)
with queryset.query._add_queryable_property_annotation(property_ref, full_group_by, select=True):
pass
return queryset
def iterator(self, *args, **kwargs):
# Recent Django versions use the associated iterable class for the
# iterator() implementation, where the QueryablePropertiesModelIterable
# will be already mixed in. In older Django versions, use a standalone
# QueryablePropertiesModelIterable instead to perform the queryable
# properties processing.
iterable = super(QueryablePropertiesQuerySetMixin, self).iterator(*args, **kwargs)
if '_iterable_class' not in self.__dict__: # pragma: no cover
return iter(QueryablePropertiesIterable(self, iterable=iterable))
return iterable
def update(self, **kwargs):
# Resolve any queryable properties into their actual update kwargs
# before calling the base update method.
kwargs = self._resolve_update_kwargs(**kwargs)
return super(QueryablePropertiesQuerySetMixin, self).update(**kwargs)
class QueryablePropertiesQuerySet(QueryablePropertiesQuerySetMixin, QuerySet):
"""
A special queryset class that allows to use queryable properties in its
filter conditions, annotations and update queries.
"""
pass
if hasattr(Manager, 'from_queryset'):
QueryablePropertiesManager = Manager.from_queryset(QueryablePropertiesQuerySet)
else: # pragma: no cover
class QueryablePropertiesManager(Manager):
def get_queryset(self):
return QueryablePropertiesQuerySet(self.model, using=self._db)
get_query_set = get_queryset
def select_properties(self, *names):
return self.get_queryset().select_properties(*names)
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] |
tali/train.py | AntreasAntoniou/TALI-lightning-hydra-dev | 0 | 153065 | <gh_stars>0
import os
import pathlib
from typing import Dict, List, Optional
import hydra
import torch
from omegaconf import DictConfig
from pytorch_lightning import (
Callback,
LightningDataModule,
LightningModule,
seed_everything,
Trainer,
)
from pytorch_lightning.loggers import LightningLoggerBase
from pytorch_lightning.tuner.tuning import Tuner
from wandb.util import generate_id
from tali.base import utils
log = utils.get_logger(__name__)
from tali.utils.storage import (
google_storage_rsync_gs_to_local,
)
def train_eval(config: DictConfig) -> List[Dict[str, float]]:
"""Contains training pipeline.
Instantiates all PyTorch Lightning objects from config.
Args:
config (DictConfig): Configuration composed by Hydra.
Returns:
Optional[float]: Metric score for hyperparameter optimization.
"""
if config.get("seed"):
seed_everything(config.seed, workers=True)
checkpoint_path = None
if config.resume:
log.info("Continue from existing checkpoint")
if not pathlib.Path(f"{config.current_experiment_dir}").exists():
os.makedirs(f"{config.current_experiment_dir}", exist_ok=True)
if "gs_file_monitor" in config.callbacks:
google_storage_rsync_gs_to_local(
bucket_name=config.callbacks.gs_file_monitor.bucket_name,
experiments_root_dir=config.callbacks.gs_file_monitor.experiments_root_dir,
experiment_name=config.callbacks.gs_file_monitor.experiment_name,
exclude_list=config.callbacks.gs_file_monitor.exclude_list,
options_list=config.callbacks.gs_file_monitor.options_list,
)
checkpoint_path = f"{config.current_experiment_dir}/checkpoints/last.ckpt"
log.info(checkpoint_path)
if not pathlib.Path(checkpoint_path).exists():
checkpoint_path = None
else:
log.info("Starting from scratch")
# shutil.rmtree(config.current_experiment_dir)
if not pathlib.Path(f"{config.current_experiment_dir}").exists():
os.makedirs(f"{config.current_experiment_dir}", exist_ok=True)
log.info(f"Instantiating datamodule <{config.datamodule._target_}>")
datamodule: LightningDataModule = hydra.utils.instantiate(
config.datamodule, _recursive_=False
)
datamodule.setup(stage="fit")
log.info(f"Instantiating model <{config.model._target_}>")
model: LightningModule = hydra.utils.instantiate(config.model, _recursive_=False)
dummy_data_dict = datamodule.get_dummy_batch()
# str_data_descr_dict = {
# key: value.shape if isinstance(value, torch.Tensor) else value
# for key, value in dummy_data_dict.items()
# }
# log.info(f"Data description: {str_data_descr_dict}")
dummy_data_dict = {
key: value
for key, value in dummy_data_dict.items()
if isinstance(value, torch.Tensor)
}
dummy_data_device_dict = {
key: value.device
for key, value in dummy_data_dict.items()
if isinstance(value, torch.Tensor)
}
log.info(f"Data description: {dummy_data_device_dict}")
_ = model.forward(dummy_data_dict)
log.info(f"Model description: {model.device}")
callbacks: List[Callback] = []
if "callbacks" in config:
for _, cb_conf in config.callbacks.items():
if "_target_" in cb_conf:
if (
cb_conf["_target_"]
== "tali.base.callbacks.wandb_callbacks.LogConfigInformation"
):
cb_conf["config"] = dict(config)
log.info(f"Instantiating callback <{cb_conf._target_}>")
callbacks.append(
hydra.utils.instantiate(cb_conf, _recursive_=False)
)
else:
log.info(f"Instantiating callback <{cb_conf._target_}>")
callbacks.append(hydra.utils.instantiate(cb_conf))
os.environ["WANDB_RESUME"] = "allow"
os.environ["WANDB_RUN_ID"] = generate_id()
# Init lightning loggers
logger: List[LightningLoggerBase] = []
if "logger" in config:
for _, lg_conf in config.logger.items():
if "_target_" in lg_conf:
log.info(f"Instantiating logger <{lg_conf._target_}>")
logger.append(hydra.utils.instantiate(lg_conf))
# Init lightning trainer
log.info(f"Instantiating trainer <{config.trainer._target_}>")
trainer: Trainer = hydra.utils.instantiate(
config.trainer,
callbacks=callbacks,
logger=logger,
_convert_="partial",
)
if config.trainer.auto_scale_batch_size:
tuner = Tuner(trainer)
new_batch_size = tuner.scale_batch_size(
model,
datamodule=datamodule,
mode="power",
init_val=2 * torch.cuda.device_count(),
)
datamodule.batch_size = new_batch_size
config.datamodule.batch_size = new_batch_size
if config.mode.fit:
log.info("Starting training!")
trainer.validate(model=model, datamodule=datamodule, ckpt_path=checkpoint_path)
trainer.fit(model=model, datamodule=datamodule, ckpt_path=checkpoint_path)
if config.mode.test and not config.trainer.get("fast_dev_run"):
datamodule.setup(stage="test")
log.info("Starting testing!")
trainer.test(
model=model,
datamodule=datamodule,
ckpt_path=trainer.checkpoint_callback.best_model_path,
)
# Make sure everything closed properly
log.info("Finalizing!")
# Print path to best checkpoint
if not config.trainer.get("fast_dev_run"):
log.info(f"Best model ckpt at {trainer.checkpoint_callback.best_model_path}")
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] |
com/l3harrisbc/client/client.py | fedcalderon/L3H-Python-BookClub-Spring2020 | 0 | 160842 | #
# Hello World client in Python
# Connects REQ socket to tcp://localhost:5555
# Sends "Hello" to server, expects "World" back
#
# Adding ZeroMQ messaging library
import zmq
# Adding Python's logging library
import logging
print("Hello Client")
# Configuring logging example
logging.basicConfig(filename='client.log', filemode='w', format='%(asctime)s - %(levelname)s - CLIENT - %(message)s', datefmt='%d-%b-%y %H:%M:%S')
# In order to start ZeroMQ, create a context
context = zmq.Context()
# Create a zmq socket to talk to the server
socket = context.socket(zmq.REQ)
# Connect zmq socket to localhost
socket.connect("tcp://localhost:5555")
# Show message on console
print("Connecting to hello server…")
# Show message on the log file
logging.warning("Connecting to hello server…")
# Create a string variable to store user inputs and initialize to empty
user_input = ""
# Start an infinite loop
while user_input != "q":
user_input = input("Type a msg ('q' to quit program): ")
if user_input != "q":
# The socket can send literal strings to the server
socket.send_string(user_input)
logging.warning(f"Message to server: {user_input}")
# Get the reply.
message = socket.recv()
logging.warning(f"Reply from server: {message}")
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msgsender_sdk/api/custom_sender/list_support_infom_pb2.py | easyopsapis/easyops-api-python | 5 | 124733 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: list_support_infom.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='list_support_infom.proto',
package='custom_sender',
syntax='proto3',
serialized_options=None,
serialized_pb=_b('\n\x18list_support_infom.proto\x12\rcustom_sender\"\x9b\x02\n\x19ListSupportInformResponse\x12;\n\x04\x64\x61ta\x18\x01 \x03(\x0b\x32-.custom_sender.ListSupportInformResponse.Data\x12\x0c\n\x04page\x18\x02 \x01(\x05\x12\x11\n\tpage_size\x18\x03 \x01(\x05\x12\r\n\x05tatal\x18\x04 \x01(\x05\x12\x0b\n\x03msg\x18\x05 \x01(\t\x12\x0c\n\x04\x63ode\x18\x06 \x01(\x05\x1av\n\x04\x44\x61ta\x12\x1f\n\x17\x63ol_of_cmdb_user_object\x18\x01 \x01(\t\x12\x0e\n\x06\x65nable\x18\x02 \x01(\x08\x12\x13\n\x0bplugin_name\x18\x03 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x04 \x01(\t\x12\x13\n\x0binform_type\x18\x05 \x01(\t\"\x8c\x01\n ListSupportInformResponseWrapper\x12\x0c\n\x04\x63ode\x18\x01 \x01(\x05\x12\x13\n\x0b\x63odeExplain\x18\x02 \x01(\t\x12\r\n\x05\x65rror\x18\x03 \x01(\t\x12\x36\n\x04\x64\x61ta\x18\x04 \x01(\x0b\x32(.custom_sender.ListSupportInformResponseb\x06proto3')
)
_LISTSUPPORTINFORMRESPONSE_DATA = _descriptor.Descriptor(
name='Data',
full_name='custom_sender.ListSupportInformResponse.Data',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='col_of_cmdb_user_object', full_name='custom_sender.ListSupportInformResponse.Data.col_of_cmdb_user_object', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='enable', full_name='custom_sender.ListSupportInformResponse.Data.enable', index=1,
number=2, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='plugin_name', full_name='custom_sender.ListSupportInformResponse.Data.plugin_name', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='description', full_name='custom_sender.ListSupportInformResponse.Data.description', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='inform_type', full_name='custom_sender.ListSupportInformResponse.Data.inform_type', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=209,
serialized_end=327,
)
_LISTSUPPORTINFORMRESPONSE = _descriptor.Descriptor(
name='ListSupportInformResponse',
full_name='custom_sender.ListSupportInformResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='data', full_name='custom_sender.ListSupportInformResponse.data', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='page', full_name='custom_sender.ListSupportInformResponse.page', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='page_size', full_name='custom_sender.ListSupportInformResponse.page_size', index=2,
number=3, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='tatal', full_name='custom_sender.ListSupportInformResponse.tatal', index=3,
number=4, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='msg', full_name='custom_sender.ListSupportInformResponse.msg', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='code', full_name='custom_sender.ListSupportInformResponse.code', index=5,
number=6, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[_LISTSUPPORTINFORMRESPONSE_DATA, ],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=44,
serialized_end=327,
)
_LISTSUPPORTINFORMRESPONSEWRAPPER = _descriptor.Descriptor(
name='ListSupportInformResponseWrapper',
full_name='custom_sender.ListSupportInformResponseWrapper',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='code', full_name='custom_sender.ListSupportInformResponseWrapper.code', index=0,
number=1, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='codeExplain', full_name='custom_sender.ListSupportInformResponseWrapper.codeExplain', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='error', full_name='custom_sender.ListSupportInformResponseWrapper.error', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='data', full_name='custom_sender.ListSupportInformResponseWrapper.data', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=330,
serialized_end=470,
)
_LISTSUPPORTINFORMRESPONSE_DATA.containing_type = _LISTSUPPORTINFORMRESPONSE
_LISTSUPPORTINFORMRESPONSE.fields_by_name['data'].message_type = _LISTSUPPORTINFORMRESPONSE_DATA
_LISTSUPPORTINFORMRESPONSEWRAPPER.fields_by_name['data'].message_type = _LISTSUPPORTINFORMRESPONSE
DESCRIPTOR.message_types_by_name['ListSupportInformResponse'] = _LISTSUPPORTINFORMRESPONSE
DESCRIPTOR.message_types_by_name['ListSupportInformResponseWrapper'] = _LISTSUPPORTINFORMRESPONSEWRAPPER
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
ListSupportInformResponse = _reflection.GeneratedProtocolMessageType('ListSupportInformResponse', (_message.Message,), {
'Data' : _reflection.GeneratedProtocolMessageType('Data', (_message.Message,), {
'DESCRIPTOR' : _LISTSUPPORTINFORMRESPONSE_DATA,
'__module__' : 'list_support_infom_pb2'
# @@protoc_insertion_point(class_scope:custom_sender.ListSupportInformResponse.Data)
})
,
'DESCRIPTOR' : _LISTSUPPORTINFORMRESPONSE,
'__module__' : 'list_support_infom_pb2'
# @@protoc_insertion_point(class_scope:custom_sender.ListSupportInformResponse)
})
_sym_db.RegisterMessage(ListSupportInformResponse)
_sym_db.RegisterMessage(ListSupportInformResponse.Data)
ListSupportInformResponseWrapper = _reflection.GeneratedProtocolMessageType('ListSupportInformResponseWrapper', (_message.Message,), {
'DESCRIPTOR' : _LISTSUPPORTINFORMRESPONSEWRAPPER,
'__module__' : 'list_support_infom_pb2'
# @@protoc_insertion_point(class_scope:custom_sender.ListSupportInformResponseWrapper)
})
_sym_db.RegisterMessage(ListSupportInformResponseWrapper)
# @@protoc_insertion_point(module_scope)
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problems/leetcode/lt-456.py | neerajp99/algorithms | 1 | 199696 | # 456. 132 Pattern
"""
Given an array of n integers nums, a 132 pattern is a subsequence of three integers nums[i], nums[j] and nums[k]
such that i < j < k and nums[i] < nums[k] < nums[j].
Return true if there is a 132 pattern in nums, otherwise, return false.
Follow up: The O(n^2) is trivial, could you come up with the O(n logn) or the O(n) solution?
Input: nums = [3,1,4,2]
Output: true
Explanation: There is a 132 pattern in the sequence: [1, 4, 2].
"""
class Solution:
def find132pattern(self, nums: List[int]) -> bool:
# Initialzed the stack
stack = []
# Handling the edge case, if there are less than 3 elements
if len(set(nums)) < 3:
return False
# Precomputing the minimum value array with first index same as first index of nums array
# to get arr[i] in O(1)
minVal = [nums[0]]
for i in range(1, len(nums)):
minVal.append(min(nums[i], minVal[-1]))
# Loop over for "j" index from right to left as "i"th index is fixed and can be taken from minVal
for i in range(len(nums) - 1, -1, -1):
# If the ith element is greater than the minimim ith element then only move forward
if nums[i] > minVal[i]:
# Remove the value from the top of the stack if "arr[k]" is smaller than the minimum
while stack and stack[-1] <= minVal[i]:
stack.pop()
# If arr[i] < arr[k] < arr[j], return True
if stack and minVal[i] < stack[-1] < nums[i]:
return True
stack.append(nums[i])
return False
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tests/modules/__init__.py | RecursionSpace/OpenPod | 1 | 146699 | ''' Required for tests to recognize folder and perform tests. '''
| [
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tests/greedy/test_oblate_system.py | rodluger/starry | 116 | 34794 | import starry
import numpy as np
import matplotlib.pyplot as plt
import pytest
@pytest.mark.parametrize("ydeg,nw", [[0, None], [0, 10], [1, None], [1, 10]])
def test_system(ydeg, nw):
# Oblate map
map = starry.Map(udeg=2, ydeg=ydeg, oblate=True, nw=nw)
map[1] = 0.5
map[2] = 0.25
map.omega = 0.5
map.beta = 1.23
map.tpole = 8000
map.f = 1 - 2 / (map.omega ** 2 + 2)
map.obl = 30
# Compute system flux
star = starry.Primary(map, r=1.5)
planet = starry.Secondary(starry.Map(amp=0, nw=nw), porb=1.0, r=0.1, m=0)
sys = starry.System(star, planet)
t = np.linspace(-0.1, 0.1, 1000)
flux_sys = sys.flux(t, integrated=True)
# Compute map flux manually
x, y, z = sys.position(t)
xo = x[1] / star._r
yo = y[1] / star._r
flux_map = map.flux(xo=xo, yo=yo, ro=planet._r / star._r, integrated=True)
# Check that they agree
assert np.allclose(flux_map, flux_sys)
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Pytorch/GANs/4 cGAN/dataset.py | muehlburger/Machine-Learning-Collection | 0 | 97745 | import pandas as pd
from torch.utils.data import (
Dataset,
DataLoader,
)
import torch.nn as nn
import torch
from torchaudio import transforms
class APGDataset(Dataset):
def __init__(self, csv_file, root_dir, transforms=None):
self.data = pd.read_csv(csv_file)
self.root_dir = root_dir
self.transforms = transforms
def __len__(self):
return len(self.data)
def __getitem__(self, item):
x_data = self.data.iloc[item, 0:21]
x_data = torch.tensor(x_data)
y_label = torch.tensor(int(self.data.iloc[item, 21]))
return (x_data.float(), y_label)
def write_to_total():
# Import training data
dataset_train = pd.read_csv("dataset/APG/csvDataFeaturesTrain.csv", delimiter=';')
dataset_test = pd.read_csv("dataset/APG/csvDataFeaturesTest.csv", delimiter=';')
X = dataset_train.append(dataset_test)
X.groupby('attack').count()
X['attack'] = X['attack'].map({0:0, 1:1, 2:1, 3:1, 4:1})
X.to_csv("dataset/APG/total.csv", index=False)
def test():
dataset = APGDataset(csv_file="dataset/APG/total.csv", root_dir="dataset/APG/", transforms=transforms.Tensor())
dataloader = DataLoader(dataset=dataset, batch_size=4096, shuffle=True)
for batch_idx, (data, targets) in enumerate(dataloader):
data = data.to(device="cpu")
labels = targets.to(device="cpu")
print(data.shape, labels.shape)
#test() | [
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records/12-09/ffff.py | AaronYang2333/CSCI_570 | 36 | 5022 | <filename>records/12-09/ffff.py<gh_stars>10-100
__author__ = '<NAME>'
__email__ = '<EMAIL>'
__date__ = '12/9/2020 4:18 PM'
from abc import abstractmethod
class Product(object):
@abstractmethod
def setMsg(self, msg="default info"):
self.msg = msg
@abstractmethod
def info(self):
print(self.msg)
class DefaultObj(Product):
def __init__(self):
super().setMsg()
class Factory(object):
@abstractmethod
def produce(self):
return DefaultObj()
class PC(Product):
def __init__(self):
self.setMsg('pc info')
class LAPTOP(Product):
def __init__(self):
self.setMsg('laptop info')
class PCFactory(Factory):
def produce(self):
return PC()
class LAPTOPFactory(Factory):
def produce(self):
return LAPTOP()
if __name__ == '__main__':
ss = Factory().produce()
pc = PCFactory().produce()
laptop = LAPTOPFactory().produce()
pc.info()
laptop.info()
ss.info()
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] |
exceltogdx/exceltogdx.py | diw-berlin/exceltogdx | 0 | 158533 | <filename>exceltogdx/exceltogdx.py
from gdxpds import load_gdxcc
from gdxpds.write_gdx import Translator
from openpyxl import load_workbook
from io import BytesIO
import pandas as pd
import numpy as np
import logging
import os
import re
logging.getLogger('gdxpds').setLevel(logging.ERROR)
def xlsdynamicecke(typ, cell, rdim, cdim, sheetname, wb, verbose=False):
'''
Returns a list of row and col of bottom-left corner of a table in pandas indexing format (from zero to inf).
It stops when there is an empty cell in index (rows) or headings (columns).
typ: string 'set' or 'par'
cell: string in excel format of top-right table corner cell.
rdim: indicates the number of columns from the beginning are sets
cdim: indicates the number of rows from the top are sets
sheetname: self-explanatory
wb: is the workbook of an excel file instance of 'from openpyxl import load_workbook'
eg. xlsdynamicecke('set', C5', 1, 0, 'sheet1', workbook.object)
return set or table coord.
'''
cell = cell.upper()
sheet = wb[sheetname]
string = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
def col2num(letters):
'''
column letter to column number
'''
num = 0
for c in letters:
if c in string:
num = num * 26 + (ord(c.upper()) - ord('A')) + 1
return num
def colnum_string(n):
strings = ""
while n > 0:
n, remainder = divmod(n - 1, 26)
strings = chr(65 + remainder) + strings
return strings
def natural_keys(text):
'''
alist.sort(key=natural_keys) sorts in human order
http://nedbatchelder.com/blog/200712/human_sorting.html
(See Toothy's implementation in the comments)
'''
def atoi(text):
return int(text) if text.isdigit() else text
return [atoi(c) for c in re.split(r'(\d+)', text)]
cut = 0
for s in cell:
if s in string:
cut += 1
else:
break
rowstr = cell[cut:]
colstr = cell[:cut]
row = int(rowstr)
col = col2num(colstr.upper())
if typ == 'par':
if cdim == 0:
j = 0
for i, r in enumerate(sheet.iter_rows(min_row=row, min_col=col, max_col=col, values_only=True)):
j = i
if r[0] is None:
j = i - 1
break
max_col = rdim + 1
max_row = row + j
rng = colnum_string(col) + str(row - 1) + ':' + colnum_string(max_col) + str(max_row)
data = sheet[rng]
output = [[cells.value for cells in row] for row in data]
if verbose:
print(rng)
print(output[:3])
else:
j = 0
for i, c in enumerate(sheet.iter_cols(min_row=row, max_row=row, min_col=col+rdim, values_only=True)):
j = i
if c[0] is None:
j = i - 1
break
max_col = col + j + rdim
for i, r in enumerate(sheet.iter_rows(min_row=row+cdim+1, min_col=col, max_col=col, values_only=True)):
j = i
if r[0] is None:
j = i - 1
break
max_row = row + j + cdim + 1
rng = cell + ':' + colnum_string(max_col) + str(max_row)
data = sheet[rng]
output = [[cells.value for cells in row] for row in data]
if verbose:
print(rng)
print(output[:3])
elif typ == 'set':
setls = []
if rdim == 1:
for i, r in enumerate(sheet.iter_rows(min_row=row, min_col=col, max_col=col, values_only=True)):
if r[0] is not None:
setls.append(r[0])
else:
break
if all([isinstance(s, (int, float)) for s in list(set(setls))]):
output = sorted(list(set(setls)))
else:
output = sorted(list(set(setls)), key=natural_keys)
elif cdim == 1:
for i, c in enumerate(sheet.iter_cols(min_row=row, max_row=row, min_col=col, values_only=True)):
if c[0] is not None:
setls.append(c[0])
else:
break
if all([isinstance(s, (int, float)) for s in list(set(setls))]):
output = sorted(list(set(setls)))
else:
output = sorted(list(set(setls)), key=natural_keys)
else:
raise ValueError('Set must have either rdim or cdim as 1, check dim in py sheet')
del sheet
return output
def exceltogdx(excel_file, gdx_file, csv_file=None, csv_copy=None, verbose=False, gams_dir=None):
'''
excel_file: input file path
gdx_file: output file path
csv_file: if None, it looks at excel file to find sheet with name 'py'
that contains the instructions to get sets and parameters.
Otherwise, csv file path.
csv_copy: indicate folder where csv files are saved. None (Default): no csv files are created.
'''
load_gdxcc(gams_dir)
if csv_file is None:
mapping = pd.read_excel(excel_file, sheet_name='py', index_col='symbol', engine='openpyxl')
else:
mapping = pd.read_csv(csv_file, index_col='symbol')
print(f"Loading excel file: {excel_file}")
with open(excel_file, 'rb') as f:
datas = BytesIO(f.read())
wb = load_workbook(datas, data_only=True)
dc = {}
df = pd.DataFrame()
for k, v in mapping.iterrows():
if verbose:
print(v['type'],': ', k)
xlsvalues = xlsdynamicecke(v['type'], v['startcell'], v['rdim'], v['cdim'], v['sheet_name'], wb, verbose=verbose)
if v['type'] == 'par':
df = pd.DataFrame(xlsvalues)
if v['cdim'] == 0:
df = df.T.set_index(0, append=False).T
try:
df = df.set_index(df.columns[list(range(v['rdim']))].to_list())
except KeyError:
raise KeyError("each rdim in parameter '{}' must have a heading (Don't leave it empty), not required for cdim".format(k))
df.index.names = list(range(1,df.index.nlevels+1))
elif v['cdim'] == 1:
df = df.T.set_index(0, append=False).T
try:
df = df.set_index(df.columns[list(range(v['rdim']))].to_list())
except KeyError:
raise KeyError("each rdim in parameter '{}' must have a heading (Don't leave it empty), not required for cdim".format(k))
df = df.stack([0]*df.columns.nlevels)
df.index.names = list(range(1,df.index.nlevels+1))
df = pd.DataFrame(df)
elif v['cdim'] > 1:
df = df.T.set_index(list(range(v['cdim'])), append=False).T
try:
df = df.set_index(df.columns[list(range(v['rdim']))].to_list())
except KeyError:
raise KeyError("each rdim in parameter '{}' must have a heading (Don't leave it empty), not required for cdim".format(k))
df = df.stack([0]*df.columns.nlevels)
df.index.names = list(range(1,df.index.nlevels+1))
df = pd.DataFrame(df)
else:
raise Exception('is "{}" a parameter?, verify cdim on "py" sheet. cdim must be positive integer'.format(k))
df = df.reset_index().rename(columns={df.columns.to_list()[-1]: 'value'}).astype(object)
df.loc[df[df['value'].astype('str').str.lower() == 'inf'].index, 'value'] = np.inf
df.loc[df[df['value'].astype('str').str.lower() == '+inf'].index, 'value'] = np.inf
df.loc[df[df['value'].astype('str').str.lower() == '-inf'].index, 'value'] = -np.inf
df.loc[df[df['value'].astype('str').str.lower() == 'eps'].index, 'value'] = np.finfo(float).eps # np.nextafter(0,1)
df.loc[:,[c for c in df.columns if (c != 'value' and df[c].dtypes == float)]] = df[[c for c in df.columns if (c != 'value' and df[c].dtypes == float)]].astype(int)
df.loc[:,[c for c in df.columns if c != 'value']] = df[[c for c in df.columns if c != 'value']].astype(str)
dc[k] = df.rename(columns={c: '*' for c in df.columns if c != 'value'})
elif v['type'] == 'set':
df = pd.DataFrame({'*': xlsvalues})
df.loc[:, 'value'] = 'True'
df.dropna(inplace=True)
dc[k] = df
if csv_copy is not None:
os.makedirs(csv_copy, exist_ok=True)
name = v['type'] + '_' + k + '.csv'
df.to_csv(os.path.join(csv_copy, name), index=False)
os.makedirs(os.path.abspath(os.path.join(gdx_file, os.pardir)), exist_ok=True)
print(f'Generating gdx file: {gdx_file}')
translator = Translator(dc)
translator.gams_dir = gams_dir
translator.save_gdx(gdx_file)
translator.gdx
print('GDX Done!')
return dc | [
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] |
rest_framework/fields.py | treyhunner/django-rest-framework | 0 | 133853 | import copy
import datetime
import inspect
import warnings
from django.core import validators
from django.core.exceptions import ObjectDoesNotExist, ValidationError
from django.core.urlresolvers import resolve, get_script_prefix
from django.conf import settings
from django.forms import widgets
from django.forms.models import ModelChoiceIterator
from django.utils.encoding import is_protected_type, smart_unicode
from django.utils.translation import ugettext_lazy as _
from rest_framework.reverse import reverse
from rest_framework.compat import parse_date, parse_datetime
from rest_framework.compat import timezone
from urlparse import urlparse
def is_simple_callable(obj):
"""
True if the object is a callable that takes no arguments.
"""
return (
(inspect.isfunction(obj) and not inspect.getargspec(obj)[0]) or
(inspect.ismethod(obj) and len(inspect.getargspec(obj)[0]) <= 1)
)
class Field(object):
creation_counter = 0
empty = ''
type_name = None
def __init__(self, source=None):
self.parent = None
self.creation_counter = Field.creation_counter
Field.creation_counter += 1
self.source = source
def initialize(self, parent, field_name):
"""
Called to set up a field prior to field_to_native or field_from_native.
parent - The parent serializer.
model_field - The model field this field corresponds to, if one exists.
"""
self.parent = parent
self.root = parent.root or parent
self.context = self.root.context
def field_from_native(self, data, field_name, into):
"""
Given a dictionary and a field name, updates the dictionary `into`,
with the field and it's deserialized value.
"""
return
def field_to_native(self, obj, field_name):
"""
Given and object and a field name, returns the value that should be
serialized for that field.
"""
if obj is None:
return self.empty
if self.source == '*':
return self.to_native(obj)
if self.source:
value = obj
for component in self.source.split('.'):
value = getattr(value, component)
if is_simple_callable(value):
value = value()
else:
value = getattr(obj, field_name)
return self.to_native(value)
def to_native(self, value):
"""
Converts the field's value into it's simple representation.
"""
if is_simple_callable(value):
value = value()
if is_protected_type(value):
return value
elif hasattr(value, '__iter__') and not isinstance(value, (dict, basestring)):
return [self.to_native(item) for item in value]
elif isinstance(value, dict):
return dict(map(self.to_native, (k, v)) for k, v in value.items())
return smart_unicode(value)
def attributes(self):
"""
Returns a dictionary of attributes to be used when serializing to xml.
"""
if self.type_name:
return {'type': self.type_name}
return {}
class WritableField(Field):
"""
Base for read/write fields.
"""
default_validators = []
default_error_messages = {
'required': _('This field is required.'),
'invalid': _('Invalid value.'),
}
widget = widgets.TextInput
default = None
def __init__(self, source=None, read_only=False, required=None,
validators=[], error_messages=None, widget=None,
default=None, blank=None):
super(WritableField, self).__init__(source=source)
self.read_only = read_only
if required is None:
self.required = not(read_only)
else:
assert not read_only, "Cannot set required=True and read_only=True"
self.required = required
messages = {}
for c in reversed(self.__class__.__mro__):
messages.update(getattr(c, 'default_error_messages', {}))
messages.update(error_messages or {})
self.error_messages = messages
self.validators = self.default_validators + validators
self.default = default if default is not None else self.default
self.blank = blank
# Widgets are ony used for HTML forms.
widget = widget or self.widget
if isinstance(widget, type):
widget = widget()
self.widget = widget
def validate(self, value):
if value in validators.EMPTY_VALUES and self.required:
raise ValidationError(self.error_messages['required'])
def run_validators(self, value):
if value in validators.EMPTY_VALUES:
return
errors = []
for v in self.validators:
try:
v(value)
except ValidationError as e:
if hasattr(e, 'code') and e.code in self.error_messages:
message = self.error_messages[e.code]
if e.params:
message = message % e.params
errors.append(message)
else:
errors.extend(e.messages)
if errors:
raise ValidationError(errors)
def field_from_native(self, data, field_name, into):
"""
Given a dictionary and a field name, updates the dictionary `into`,
with the field and it's deserialized value.
"""
if self.read_only:
return
try:
native = data[field_name]
except KeyError:
if self.default is not None:
native = self.default
else:
if self.required:
raise ValidationError(self.error_messages['required'])
return
value = self.from_native(native)
if self.source == '*':
if value:
into.update(value)
else:
self.validate(value)
self.run_validators(value)
into[self.source or field_name] = value
def from_native(self, value):
"""
Reverts a simple representation back to the field's value.
"""
return value
class ModelField(WritableField):
"""
A generic field that can be used against an arbitrary model field.
"""
def __init__(self, *args, **kwargs):
try:
self.model_field = kwargs.pop('model_field')
except:
raise ValueError("ModelField requires 'model_field' kwarg")
super(ModelField, self).__init__(*args, **kwargs)
def from_native(self, value):
rel = getattr(self.model_field, "rel", None)
if rel is not None:
return rel.to._meta.get_field(rel.field_name).to_python(value)
else:
return self.model_field.to_python(value)
def field_to_native(self, obj, field_name):
value = self.model_field._get_val_from_obj(obj)
if is_protected_type(value):
return value
return self.model_field.value_to_string(obj)
def attributes(self):
return {
"type": self.model_field.get_internal_type()
}
##### Relational fields #####
# Not actually Writable, but subclasses may need to be.
class RelatedField(WritableField):
"""
Base class for related model fields.
If not overridden, this represents a to-one relationship, using the unicode
representation of the target.
"""
widget = widgets.Select
cache_choices = False
empty_label = None
default_read_only = True # TODO: Remove this
def __init__(self, *args, **kwargs):
self.queryset = kwargs.pop('queryset', None)
super(RelatedField, self).__init__(*args, **kwargs)
self.read_only = kwargs.pop('read_only', self.default_read_only)
def initialize(self, parent, field_name):
super(RelatedField, self).initialize(parent, field_name)
if self.queryset is None and not self.read_only:
try:
manager = getattr(self.parent.opts.model, self.source or field_name)
if hasattr(manager, 'related'): # Forward
self.queryset = manager.related.model._default_manager.all()
else: # Reverse
self.queryset = manager.field.rel.to._default_manager.all()
except:
raise
msg = ('Serializer related fields must include a `queryset`' +
' argument or set `read_only=True')
raise Exception(msg)
### We need this stuff to make form choices work...
# def __deepcopy__(self, memo):
# result = super(RelatedField, self).__deepcopy__(memo)
# result.queryset = result.queryset
# return result
def prepare_value(self, obj):
return self.to_native(obj)
def label_from_instance(self, obj):
"""
Return a readable representation for use with eg. select widgets.
"""
desc = smart_unicode(obj)
ident = smart_unicode(self.to_native(obj))
if desc == ident:
return desc
return "%s - %s" % (desc, ident)
def _get_queryset(self):
return self._queryset
def _set_queryset(self, queryset):
self._queryset = queryset
self.widget.choices = self.choices
queryset = property(_get_queryset, _set_queryset)
def _get_choices(self):
# If self._choices is set, then somebody must have manually set
# the property self.choices. In this case, just return self._choices.
if hasattr(self, '_choices'):
return self._choices
# Otherwise, execute the QuerySet in self.queryset to determine the
# choices dynamically. Return a fresh ModelChoiceIterator that has not been
# consumed. Note that we're instantiating a new ModelChoiceIterator *each*
# time _get_choices() is called (and, thus, each time self.choices is
# accessed) so that we can ensure the QuerySet has not been consumed. This
# construct might look complicated but it allows for lazy evaluation of
# the queryset.
return ModelChoiceIterator(self)
def _set_choices(self, value):
# Setting choices also sets the choices on the widget.
# choices can be any iterable, but we call list() on it because
# it will be consumed more than once.
self._choices = self.widget.choices = list(value)
choices = property(_get_choices, _set_choices)
### Regular serializier stuff...
def field_to_native(self, obj, field_name):
value = getattr(obj, self.source or field_name)
return self.to_native(value)
def field_from_native(self, data, field_name, into):
if self.read_only:
return
value = data.get(field_name)
into[(self.source or field_name)] = self.from_native(value)
class ManyRelatedMixin(object):
"""
Mixin to convert a related field to a many related field.
"""
widget = widgets.SelectMultiple
def field_to_native(self, obj, field_name):
value = getattr(obj, self.source or field_name)
return [self.to_native(item) for item in value.all()]
def field_from_native(self, data, field_name, into):
if self.read_only:
return
try:
# Form data
value = data.getlist(self.source or field_name)
except:
# Non-form data
value = data.get(self.source or field_name)
else:
if value == ['']:
value = []
into[field_name] = [self.from_native(item) for item in value]
class ManyRelatedField(ManyRelatedMixin, RelatedField):
"""
Base class for related model managers.
If not overridden, this represents a to-many relationship, using the unicode
representations of the target, and is read-only.
"""
pass
### PrimaryKey relationships
class PrimaryKeyRelatedField(RelatedField):
"""
Represents a to-one relationship as a pk value.
"""
default_read_only = False
# TODO: Remove these field hacks...
def prepare_value(self, obj):
return self.to_native(obj.pk)
def label_from_instance(self, obj):
"""
Return a readable representation for use with eg. select widgets.
"""
desc = smart_unicode(obj)
ident = smart_unicode(self.to_native(obj.pk))
if desc == ident:
return desc
return "%s - %s" % (desc, ident)
# TODO: Possibly change this to just take `obj`, through prob less performant
def to_native(self, pk):
return pk
def from_native(self, data):
if self.queryset is None:
raise Exception('Writable related fields must include a `queryset` argument')
try:
return self.queryset.get(pk=data)
except ObjectDoesNotExist:
msg = "Invalid pk '%s' - object does not exist." % smart_unicode(data)
raise ValidationError(msg)
def field_to_native(self, obj, field_name):
try:
# Prefer obj.serializable_value for performance reasons
pk = obj.serializable_value(self.source or field_name)
except AttributeError:
# RelatedObject (reverse relationship)
obj = getattr(obj, self.source or field_name)
return self.to_native(obj.pk)
# Forward relationship
return self.to_native(pk)
class ManyPrimaryKeyRelatedField(ManyRelatedField):
"""
Represents a to-many relationship as a pk value.
"""
default_read_only = False
def prepare_value(self, obj):
return self.to_native(obj.pk)
def label_from_instance(self, obj):
"""
Return a readable representation for use with eg. select widgets.
"""
desc = smart_unicode(obj)
ident = smart_unicode(self.to_native(obj.pk))
if desc == ident:
return desc
return "%s - %s" % (desc, ident)
def to_native(self, pk):
return pk
def field_to_native(self, obj, field_name):
try:
# Prefer obj.serializable_value for performance reasons
queryset = obj.serializable_value(self.source or field_name)
except AttributeError:
# RelatedManager (reverse relationship)
queryset = getattr(obj, self.source or field_name)
return [self.to_native(item.pk) for item in queryset.all()]
# Forward relationship
return [self.to_native(item.pk) for item in queryset.all()]
def from_native(self, data):
if self.queryset is None:
raise Exception('Writable related fields must include a `queryset` argument')
try:
return self.queryset.get(pk=data)
except ObjectDoesNotExist:
msg = "Invalid pk '%s' - object does not exist." % smart_unicode(data)
raise ValidationError(msg)
### Slug relationships
class SlugRelatedField(RelatedField):
default_read_only = False
def __init__(self, *args, **kwargs):
self.slug_field = kwargs.pop('slug_field', None)
assert self.slug_field, 'slug_field is required'
super(SlugRelatedField, self).__init__(*args, **kwargs)
def to_native(self, obj):
return getattr(obj, self.slug_field)
def from_native(self, data):
if self.queryset is None:
raise Exception('Writable related fields must include a `queryset` argument')
try:
return self.queryset.get(**{self.slug_field: data})
except ObjectDoesNotExist:
raise ValidationError('Object with %s=%s does not exist.' %
(self.slug_field, unicode(data)))
class ManySlugRelatedField(ManyRelatedMixin, SlugRelatedField):
pass
### Hyperlinked relationships
class HyperlinkedRelatedField(RelatedField):
"""
Represents a to-one relationship, using hyperlinking.
"""
pk_url_kwarg = 'pk'
slug_field = 'slug'
slug_url_kwarg = None # Defaults to same as `slug_field` unless overridden
default_read_only = False
def __init__(self, *args, **kwargs):
try:
self.view_name = kwargs.pop('view_name')
except:
raise ValueError("Hyperlinked field requires 'view_name' kwarg")
self.slug_field = kwargs.pop('slug_field', self.slug_field)
default_slug_kwarg = self.slug_url_kwarg or self.slug_field
self.pk_url_kwarg = kwargs.pop('pk_url_kwarg', self.pk_url_kwarg)
self.slug_url_kwarg = kwargs.pop('slug_url_kwarg', default_slug_kwarg)
self.format = kwargs.pop('format', None)
super(HyperlinkedRelatedField, self).__init__(*args, **kwargs)
def get_slug_field(self):
"""
Get the name of a slug field to be used to look up by slug.
"""
return self.slug_field
def to_native(self, obj):
view_name = self.view_name
request = self.context.get('request', None)
format = self.format or self.context.get('format', None)
pk = getattr(obj, 'pk', None)
if pk is None:
return
kwargs = {self.pk_url_kwarg: pk}
try:
return reverse(view_name, kwargs=kwargs, request=request, format=format)
except:
pass
slug = getattr(obj, self.slug_field, None)
if not slug:
raise ValidationError('Could not resolve URL for field using view name "%s"' % view_name)
kwargs = {self.slug_url_kwarg: slug}
try:
return reverse(self.view_name, kwargs=kwargs, request=request, format=format)
except:
pass
kwargs = {self.pk_url_kwarg: obj.pk, self.slug_url_kwarg: slug}
try:
return reverse(self.view_name, kwargs=kwargs, request=request, format=format)
except:
pass
raise ValidationError('Could not resolve URL for field using view name "%s"', view_name)
def from_native(self, value):
# Convert URL -> model instance pk
# TODO: Use values_list
if self.queryset is None:
raise Exception('Writable related fields must include a `queryset` argument')
if value.startswith('http:') or value.startswith('https:'):
# If needed convert absolute URLs to relative path
value = urlparse(value).path
prefix = get_script_prefix()
if value.startswith(prefix):
value = '/' + value[len(prefix):]
try:
match = resolve(value)
except:
raise ValidationError('Invalid hyperlink - No URL match')
if match.url_name != self.view_name:
raise ValidationError('Invalid hyperlink - Incorrect URL match')
pk = match.kwargs.get(self.pk_url_kwarg, None)
slug = match.kwargs.get(self.slug_url_kwarg, None)
# Try explicit primary key.
if pk is not None:
queryset = self.queryset.filter(pk=pk)
# Next, try looking up by slug.
elif slug is not None:
slug_field = self.get_slug_field()
queryset = self.queryset.filter(**{slug_field: slug})
# If none of those are defined, it's an error.
else:
raise ValidationError('Invalid hyperlink')
try:
obj = queryset.get()
except ObjectDoesNotExist:
raise ValidationError('Invalid hyperlink - object does not exist.')
return obj
class ManyHyperlinkedRelatedField(ManyRelatedMixin, HyperlinkedRelatedField):
"""
Represents a to-many relationship, using hyperlinking.
"""
pass
class HyperlinkedIdentityField(Field):
"""
Represents the instance, or a property on the instance, using hyperlinking.
"""
pk_url_kwarg = 'pk'
slug_field = 'slug'
slug_url_kwarg = None # Defaults to same as `slug_field` unless overridden
def __init__(self, *args, **kwargs):
# TODO: Make view_name mandatory, and have the
# HyperlinkedModelSerializer set it on-the-fly
self.view_name = kwargs.pop('view_name', None)
self.format = kwargs.pop('format', None)
self.slug_field = kwargs.pop('slug_field', self.slug_field)
default_slug_kwarg = self.slug_url_kwarg or self.slug_field
self.pk_url_kwarg = kwargs.pop('pk_url_kwarg', self.pk_url_kwarg)
self.slug_url_kwarg = kwargs.pop('slug_url_kwarg', default_slug_kwarg)
super(HyperlinkedIdentityField, self).__init__(*args, **kwargs)
def field_to_native(self, obj, field_name):
request = self.context.get('request', None)
format = self.format or self.context.get('format', None)
view_name = self.view_name or self.parent.opts.view_name
kwargs = {self.pk_url_kwarg: obj.pk}
try:
return reverse(view_name, kwargs=kwargs, request=request, format=format)
except:
pass
slug = getattr(obj, self.slug_field, None)
if not slug:
raise ValidationError('Could not resolve URL for field using view name "%s"' % view_name)
kwargs = {self.slug_url_kwarg: slug}
try:
return reverse(self.view_name, kwargs=kwargs, request=request, format=format)
except:
pass
kwargs = {self.pk_url_kwarg: obj.pk, self.slug_url_kwarg: slug}
try:
return reverse(self.view_name, kwargs=kwargs, request=request, format=format)
except:
pass
raise ValidationError('Could not resolve URL for field using view name "%s"', view_name)
##### Typed Fields #####
class BooleanField(WritableField):
type_name = 'BooleanField'
widget = widgets.CheckboxInput
default_error_messages = {
'invalid': _(u"'%s' value must be either True or False."),
}
empty = False
# Note: we set default to `False` in order to fill in missing value not
# supplied by html form. TODO: Fix so that only html form input gets
# this behavior.
default = False
def from_native(self, value):
if value in ('t', 'True', '1'):
return True
if value in ('f', 'False', '0'):
return False
return bool(value)
class CharField(WritableField):
type_name = 'CharField'
def __init__(self, max_length=None, min_length=None, *args, **kwargs):
self.max_length, self.min_length = max_length, min_length
super(CharField, self).__init__(*args, **kwargs)
if min_length is not None:
self.validators.append(validators.MinLengthValidator(min_length))
if max_length is not None:
self.validators.append(validators.MaxLengthValidator(max_length))
def validate(self, value):
"""
Validates that the value is supplied (if required).
"""
# if empty string and allow blank
if self.blank and not value:
return
else:
super(CharField, self).validate(value)
def from_native(self, value):
if isinstance(value, basestring) or value is None:
return value
return smart_unicode(value)
class ChoiceField(WritableField):
type_name = 'ChoiceField'
widget = widgets.Select
default_error_messages = {
'invalid_choice': _('Select a valid choice. %(value)s is not one of the available choices.'),
}
def __init__(self, choices=(), *args, **kwargs):
super(ChoiceField, self).__init__(*args, **kwargs)
self.choices = choices
def _get_choices(self):
return self._choices
def _set_choices(self, value):
# Setting choices also sets the choices on the widget.
# choices can be any iterable, but we call list() on it because
# it will be consumed more than once.
self._choices = self.widget.choices = list(value)
choices = property(_get_choices, _set_choices)
def validate(self, value):
"""
Validates that the input is in self.choices.
"""
super(ChoiceField, self).validate(value)
if value and not self.valid_value(value):
raise ValidationError(self.error_messages['invalid_choice'] % {'value': value})
def valid_value(self, value):
"""
Check to see if the provided value is a valid choice.
"""
for k, v in self.choices:
if isinstance(v, (list, tuple)):
# This is an optgroup, so look inside the group for options
for k2, v2 in v:
if value == smart_unicode(k2):
return True
else:
if value == smart_unicode(k):
return True
return False
class EmailField(CharField):
type_name = 'EmailField'
default_error_messages = {
'invalid': _('Enter a valid e-mail address.'),
}
default_validators = [validators.validate_email]
def from_native(self, value):
ret = super(EmailField, self).from_native(value)
if ret is None:
return None
return ret.strip()
def __deepcopy__(self, memo):
result = copy.copy(self)
memo[id(self)] = result
#result.widget = copy.deepcopy(self.widget, memo)
result.validators = self.validators[:]
return result
class DateField(WritableField):
type_name = 'DateField'
default_error_messages = {
'invalid': _(u"'%s' value has an invalid date format. It must be "
u"in YYYY-MM-DD format."),
'invalid_date': _(u"'%s' value has the correct format (YYYY-MM-DD) "
u"but it is an invalid date."),
}
empty = None
def from_native(self, value):
if value in validators.EMPTY_VALUES:
return None
if isinstance(value, datetime.datetime):
if timezone and settings.USE_TZ and timezone.is_aware(value):
# Convert aware datetimes to the default time zone
# before casting them to dates (#17742).
default_timezone = timezone.get_default_timezone()
value = timezone.make_naive(value, default_timezone)
return value.date()
if isinstance(value, datetime.date):
return value
try:
parsed = parse_date(value)
if parsed is not None:
return parsed
except ValueError:
msg = self.error_messages['invalid_date'] % value
raise ValidationError(msg)
msg = self.error_messages['invalid'] % value
raise ValidationError(msg)
class DateTimeField(WritableField):
type_name = 'DateTimeField'
default_error_messages = {
'invalid': _(u"'%s' value has an invalid format. It must be in "
u"YYYY-MM-DD HH:MM[:ss[.uuuuuu]][TZ] format."),
'invalid_date': _(u"'%s' value has the correct format "
u"(YYYY-MM-DD) but it is an invalid date."),
'invalid_datetime': _(u"'%s' value has the correct format "
u"(YYYY-MM-DD HH:MM[:ss[.uuuuuu]][TZ]) "
u"but it is an invalid date/time."),
}
empty = None
def from_native(self, value):
if value in validators.EMPTY_VALUES:
return None
if isinstance(value, datetime.datetime):
return value
if isinstance(value, datetime.date):
value = datetime.datetime(value.year, value.month, value.day)
if settings.USE_TZ:
# For backwards compatibility, interpret naive datetimes in
# local time. This won't work during DST change, but we can't
# do much about it, so we let the exceptions percolate up the
# call stack.
warnings.warn(u"DateTimeField received a naive datetime (%s)"
u" while time zone support is active." % value,
RuntimeWarning)
default_timezone = timezone.get_default_timezone()
value = timezone.make_aware(value, default_timezone)
return value
try:
parsed = parse_datetime(value)
if parsed is not None:
return parsed
except ValueError:
msg = self.error_messages['invalid_datetime'] % value
raise ValidationError(msg)
try:
parsed = parse_date(value)
if parsed is not None:
return datetime.datetime(parsed.year, parsed.month, parsed.day)
except ValueError:
msg = self.error_messages['invalid_date'] % value
raise ValidationError(msg)
msg = self.error_messages['invalid'] % value
raise ValidationError(msg)
class IntegerField(WritableField):
type_name = 'IntegerField'
default_error_messages = {
'invalid': _('Enter a whole number.'),
'max_value': _('Ensure this value is less than or equal to %(limit_value)s.'),
'min_value': _('Ensure this value is greater than or equal to %(limit_value)s.'),
}
def __init__(self, max_value=None, min_value=None, *args, **kwargs):
self.max_value, self.min_value = max_value, min_value
super(IntegerField, self).__init__(*args, **kwargs)
if max_value is not None:
self.validators.append(validators.MaxValueValidator(max_value))
if min_value is not None:
self.validators.append(validators.MinValueValidator(min_value))
def from_native(self, value):
if value in validators.EMPTY_VALUES:
return None
try:
value = int(str(value))
except (ValueError, TypeError):
raise ValidationError(self.error_messages['invalid'])
return value
class FloatField(WritableField):
type_name = 'FloatField'
default_error_messages = {
'invalid': _("'%s' value must be a float."),
}
def from_native(self, value):
if value in validators.EMPTY_VALUES:
return None
try:
return float(value)
except (TypeError, ValueError):
msg = self.error_messages['invalid'] % value
raise ValidationError(msg)
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1.0/VIOS/website/urls.py | suyanan/vioser | 1 | 1616346 | from django.conf.urls import url
from . import views
app_name = 'website'
urlpatterns = [
url(r'^manual/$',views.manual,name='manual'),
url(r'^reference/$',views.reference,name='reference'),
url(r'^faq/$',views.faq,name='faq'),
url(r'^contact$',views.contact,name='contact'),
url(r'^vios_intro$',views.vios_intro,name='vios_intro'),
]
| [
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dbtools/admin.py | snowminc/Groupformer | 1 | 53710 | <filename>dbtools/admin.py
from django.contrib import admin
# Register your models here.
from .models import *
class GroupFormerAdmin(admin.ModelAdmin):
search_fields = ['class_section']
class ProjectAdmin(admin.ModelAdmin):
search_fields = ['project_name']
class AttributeAdmin(admin.ModelAdmin):
pass
class ParticipantAdmin(admin.ModelAdmin):
pass
class AttrChoiceAdmin(admin.ModelAdmin):
pass
class ProjChoiceAdmin(admin.ModelAdmin):
pass
admin.site.register(GroupFormer, GroupFormerAdmin)
admin.site.register(Project, ProjectAdmin)
admin.site.register(Attribute, AttributeAdmin)
admin.site.register(Participant, ParticipantAdmin)
admin.site.register(attribute_selection, AttrChoiceAdmin)
admin.site.register(project_selection, ProjChoiceAdmin)
| [
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taskflow/repository.bzl | dldt/third_party.bzl | 1 | 157762 | <gh_stars>1-10
load("@bazel_tools//tools/build_defs/repo:utils.bzl", "maybe")
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def taskflow_repository():
maybe(
http_archive,
name = "taskflow",
urls = [
"https://github.com/taskflow/taskflow/archive/refs/tags/v3.2.0.zip",
],
sha256 = "dec011fcd9d73ae4bd8ae4d2714c2c108a013d5f27761d77aa33ea28f516ac8a",
strip_prefix = "taskflow-3.2.0/",
build_file = "@third_party//taskflow:package.BUILD",
)
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1723,
13,
2
] |
terrain_following/src/image_processor.py | ZhiangChen/ros_vision | 0 | 18758 | #!/usr/bin/env python
"""
<NAME>
Nov 2019
"""
import rospy
from sensor_msgs.msg import Image
from sensor_msgs.msg import Imu
from cv_bridge import CvBridge, CvBridgeError
import numpy as np
import cv2
class Image_Processor(object):
def __init__(self):
rospy.Subscriber("/r200/depth/image_raw", Image, self.record_callback)
self.delta_time = 0
self.bridge = CvBridge()
print("Image processor node initialized!")
def start_recording(self, save_path, delta_time=1):
self.save_path = save_path
self.frame = 0
self.delta_time = delta_time
def record_callback(self, data):
print("callback works")
if self.delta_time >0:
image = self.bridge.imgmsg_to_cv2(data, "bgr8")
print(image.shape)
cv2.imwrite(self.save_path + str(self.frame) + ".png", image)
rospy.sleep(self.delta_time)
self.frame += 1
if __name__ == '__main__':
rospy.init_node('image_processor', anonymous=True)
IMP = Image_Processor()
IMP.start_recording("/home/zhiang/Pictures/terrain_boulder/")
try:
rospy.spin()
except rospy.ROSInterruptException:
print("Node killed!") | [
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app/__init__.py | paulmunyao/Daily-Dossier-News | 0 | 48124 | from flask import Flask
from config import DevelopmentConfig
app = Flask(__name__)
app.config.from_object(DevelopmentConfig)
from app import routes,errors | [
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neurovault/apps/statmaps/tests/test_qa.py | abitrolly/NeuroVault | 68 | 23271 | import os
import nibabel as nb
import numpy as np
from django.test import TestCase
from neurovault.apps.statmaps.models import BaseStatisticMap
from neurovault.apps.statmaps.utils import is_thresholded, infer_map_type
class QATest(TestCase):
def setUp(self):
this_path = os.path.abspath(os.path.dirname(__file__))
self.brain = nb.load(os.path.join(this_path, "../static", "anatomical", "MNI152.nii.gz"))
self.roi_map = nb.load(os.path.join(this_path, "test_data", "statmaps", "WA3.nii.gz"))
self.parcellation = nb.load(os.path.join(this_path, "test_data", "TTatlas.nii.gz"))
# We will fill in brain mask with this percentage of randomly placed values
self.ratios = [0.0,0.1,0.15,0.2,0.25,0.3,0.4,0.5,0.6,0.96, 0.98]
self.thresholded = [False,False,False,False,False,False,False,False,False,True,True]
def testThresholded(self):
for p,t in zip(self.ratios, self.thresholded):
empty_data = np.ones(self.brain.shape)
if p != 0.0:
number_voxels = int(np.floor(p * empty_data.size))
random_idx = np.random.choice(range(empty_data.size), number_voxels, replace=False)
empty_data[np.unravel_index(random_idx, empty_data.shape)] = 0
empty_nii = nb.Nifti1Image(empty_data,affine=self.brain.get_affine(),header=self.brain.get_header())
is_thr, ratio_bad = is_thresholded(nii_obj=empty_nii)
print "Zeroed %s of values, is_thresholded returns [%s:%s]" %(p,is_thr,ratio_bad)
self.assertAlmostEqual(p, ratio_bad, delta=0.001)
self.assertEquals(t, is_thr)
def testInferMapType(self):
self.assertEquals(infer_map_type(self.roi_map), BaseStatisticMap.R)
self.assertEquals(infer_map_type(self.parcellation), BaseStatisticMap.Pa)
self.assertEquals(infer_map_type(self.brain), BaseStatisticMap.OTHER) | [
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data_tests/test_data.py | warwickmm/openelections-data-tests | 0 | 154587 | <reponame>warwickmm/openelections-data-tests
import csv
import glob
import os
import unittest
from typing import Iterator
from data_tests.duplicate_entries import DuplicateEntries
def get_csv_files(root_path: str) -> Iterator[str]:
for file in glob.glob(os.path.join(root_path, "[0-9]" * 4, "**", "*"), recursive=True):
if file.lower().endswith(".csv"):
yield file
class DuplicateEntriesTest(unittest.TestCase):
root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir))
def test_duplicate_entries(self):
for csv_file in get_csv_files(DuplicateEntriesTest.root_path):
short_path = os.path.relpath(csv_file, start=DuplicateEntriesTest.root_path)
with self.subTest(msg=f"{short_path}"):
data_test = DuplicateEntries()
with open(csv_file, "r") as csv_data:
reader = csv.reader(csv_data)
for row in reader:
data_test.test(row)
self.assertTrue(data_test.passed, data_test.get_failure_message())
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sleap/__init__.py | Tyelab/sleap | 0 | 94600 | <reponame>Tyelab/sleap
import logging
import sys
# Setup logging to stdout
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
# Import submodules we want available at top-level
from sleap.version import __version__, versions
from sleap.io.dataset import Labels, load_file
from sleap.io.video import Video, load_video
from sleap.instance import LabeledFrame, Instance, PredictedInstance, Track
from sleap.skeleton import Skeleton
import sleap.nn
from sleap.nn.data import pipelines
from sleap.nn import inference
from sleap.nn.inference import load_model
from sleap.nn.system import use_cpu_only, disable_preallocation
from sleap.nn.system import summary as system_summary
from sleap.nn.config import TrainingJobConfig, load_config
from sleap.nn.evals import load_metrics
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IPQualityScore/BinaryOption.py | IPQualityScore/PythonIPQSDBReader | 0 | 83246 | class BinaryOption:
def __init__(self):
self.__data = None
def SetData(self, bit):
self.__data = bit
def Has(self, value):
return (self.__data & value)
def Set(self, value):
self.__data = self.__data | value
@staticmethod
def Create(value):
result = BinaryOption()
result.SetData(value)
return result
IPV4MAP = 1 << 0
IPV6MAP = 1 << 1
BLACKLISTFILE = 1 << 2
BINARYDATA = 1 << 7
TREEDATA = 1 << 2
STRINGDATA = 1 << 3
SMALLINTDATA = 1 << 4
INTDATA = 1 << 5
FLOATDATA = 1 << 6
ISPROXY = 1 << 0
ISVPN = 1 << 1
ISTOR = 1 << 2
ISCRAWLER = 1 << 3
ISBOT = 1 << 4
RECENTABUSE = 1 << 5
ISBLACKLISTED = 1 << 6
ISPRIVATE = 1 << 7
ISMOBILE = 1 << 0
HASOPENPORTS = 1 << 1
ISHOSTINGPROVIDER = 1 << 2
ACTIVEVPN = 1 << 3
ACTIVETOR = 1 << 4
PUBLICACCESSPOINT = 1 << 5
RESERVEDONE = 1 << 6
RESERVEDTWO = 1 << 7
RESERVEDTHREE = 1 << 0
RESERVEDFOUR = 1 << 1
RESERVEDFIVE = 1 << 2
CONNECTIONTYPEONE = 1 << 3
CONNECTIONTYPETWO = 1 << 4
CONNECTIONTYPETHREE = 1 << 5
ABUSEVELOCITYONE = 1 << 6
ABUSEVELOCITYTWO = 1 << 7
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imageledger/urls.py | creativecommons/open-ledger | 46 | 114898 | from django.urls import include, path, re_path
from django.views.generic import RedirectView
from django.urls import reverse_lazy
from django.http import QueryDict
from rest_framework.urlpatterns import format_suffix_patterns
from django_cas_ng.views import login as cas_login, logout as cas_logout, callback as cas_callback
from imageledger.views import search_views, api_views, list_views, favorite_views, tag_views, site_views
from imageledger.forms import FIELD_DEFAULT
class MetRedirectView(RedirectView):
permanent = True
query_string = True
pattern_name = 'search-met'
def get_redirect_url(self, *args, **kwargs):
url = reverse_lazy('index') + '?'
qd = QueryDict('', mutable=True, )
qd.update({'providers': 'met'})
qd.setlistdefault('search_fields', FIELD_DEFAULT)
url += qd.urlencode()
return url
urlpatterns = [
# Custom search URLs
path('themet', MetRedirectView.as_view(), name='search-met'),
path('', search_views.index, name='index'),
path('image/detail', search_views.by_image, name="by-image"),
re_path('image/detail/(?P<identifier>.*)', search_views.detail, name="detail"),
# CAS
path('accounts/login', cas_login, name='cas_ng_login'),
path('accounts/logout', cas_logout, name='cas_ng_logout'),
path('accounts/callback', cas_callback, name='cas_ng_proxy_callback'),
# Other auth-related pages
path('accounts/profile', site_views.profile, name="profile"),
path('accounts/delete', site_views.delete_account, name="delete-account"),
# Lists (public)
path('list/<slug:slug>/', list_views.OLListDetail.as_view(), name='list-detail'),
# Lists (user admin)
path('list/add/', list_views.OLListCreate.as_view(), name='my-list-add'),
path('list/mine/<slug:slug>/', list_views.OLListUpdate.as_view(), name='my-list-update'),
path('list/mine/<slug:slug>/delete', list_views.OLListDelete.as_view(), name='my-list-delete'),
path('lists/mine', list_views.OLOwnedListList.as_view(), name="my-lists"),
# Favorites
path('favorites/mine', favorite_views.FavoriteList.as_view(), name='my-favorites'),
# User tags
path('tags/mine', tag_views.UserTagsList.as_view(), name='my-tags'),
path('tags/mine/<slug:slug>/', tag_views.UserTagsDetail.as_view(), name='my-tags-detail'),
# About and other static pages
path('about', site_views.about, name='about'),
path('health', site_views.health, name='health'),
path('robots.txt', site_views.robots, name='robots'),
]
apipatterns = [
# List API
path('api/v1/lists', api_views.ListList.as_view()),
path('api/v1/autocomplete/lists', api_views.ListAutocomplete.as_view()),
path('api/v1/lists/<slug:slug>', api_views.ListDetail.as_view()),
# Favorite API
path('api/v1/images/favorite/<str:identifier>', api_views.FavoriteDetail.as_view()),
path('api/v1/images/favorites', api_views.FavoriteList.as_view()),
# User Tags API
path('api/v1/images/tags', api_views.UserTagDetail.as_view()),
path('api/v1/images/tags/<str:identifier>/<str:tag>', api_views.UserTagDetail.as_view()),
path('api/v1/images/tags/<str:identifier>', api_views.UserTagsList.as_view()),
path('api/v1/autocomplete/tags', api_views.UserTagsAutocomplete.as_view()),
]
apipatterns = format_suffix_patterns(apipatterns)
urlpatterns += apipatterns
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python/place_molex_conn.py | willdickson/roman_led_frame | 0 | 33447 | from __future__ import print_function
import os
import sys
import pcbnew
import numpy as np
import pprint
def inch_to_nanometer(value):
return (value*25.4)*1e6
def nanometer_to_inch(value):
return value/(25.4*1.e6)
def nm_to_mm(value):
return value*1.e-6
def mm_to_nm(value):
return value*1.e6
def print_module_info(module):
ref = module.GetReference()
pos = module.GetPosition()
x = nanometer_to_inch(pos.x)
y = nanometer_to_inch(pos.y)
angle = 0.1*module.GetOrientation()
print(' R: {}'.format(ref))
print(' X: {}'.format(x))
print(' Y: {}'.format(y))
print(' A: {}'.format(angle))
print()
def get_placement_data(param):
placement_data = {}
for i, ref in enumerate(param['ref_list']):
x = param['x_start'] + i*param['x_step']
y = param['y_value']
angle = param['angle']
placement_data[ref] = {'angle': angle, 'x': x, 'y': y}
return placement_data
def place_pcb_modules(filename, placement_data):
print()
print('loading pcb: {}'.format(filename))
print()
pcb = pcbnew.LoadBoard(filename)
print()
print('done')
print()
for module in pcb.GetModules():
ref_str = str(module.GetReference())
try:
data = placement_data[ref_str]
except KeyError:
continue
print_module_info(module)
# Move to new position
pos = module.GetPosition()
angle = 0.1*module.GetOrientation()
x_new = data['x']
y_new = data['y']
angle_new = data['angle']
pos.x = int(mm_to_nm(x_new))
pos.y = int(mm_to_nm(y_new))
module.SetPosition(pos)
module.SetOrientation(10.0*angle_new)
print_module_info(module)
pathname, basename = os.path.split(filename)
new_basename = 'mod_{}'.format(basename)
new_filename = os.path.join(pathname,new_basename)
pcb.Save(new_filename)
# ---------------------------------------------------------------------------------------
if __name__ == '__main__':
param = {
'ref_list': ['J{}'.format(i) for i in range(1,19)],
'y_value' : 56.0,
'x_start' : 50.0+39.5,
'x_step' : 13.0,
'angle' : 180.0,
}
placement_data = get_placement_data(param)
if 0:
print('led_data')
print()
pp = pprint.PrettyPrinter(indent=2)
pp.pprint(placement_data)
print()
print('modules')
print()
filename = sys.argv[1]
place_pcb_modules(filename, placement_data)
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hypha/apply/projects/models/project.py | slifty/hypha | 0 | 14203 | import collections
import decimal
import json
import logging
from django.apps import apps
from django.conf import settings
from django.contrib.contenttypes.fields import GenericRelation
from django.contrib.postgres.fields import JSONField
from django.core.exceptions import ValidationError
from django.core.validators import MinValueValidator
from django.db import models
from django.db.models import Count, F, Max, OuterRef, Subquery, Sum, Value
from django.db.models.functions import Cast, Coalesce
from django.db.models.signals import post_delete
from django.dispatch.dispatcher import receiver
from django.urls import reverse
from django.utils import timezone
from django.utils.translation import gettext_lazy as _
from wagtail.contrib.settings.models import BaseSetting, register_setting
from wagtail.core.fields import StreamField
from addressfield.fields import ADDRESS_FIELDS_ORDER
from hypha.apply.funds.models.mixins import AccessFormData
from hypha.apply.stream_forms.blocks import FormFieldsBlock
from hypha.apply.stream_forms.files import StreamFieldDataEncoder
from hypha.apply.stream_forms.models import BaseStreamForm
from hypha.apply.utils.storage import PrivateStorage
from .vendor import Vendor
logger = logging.getLogger(__name__)
def contract_path(instance, filename):
return f'projects/{instance.project_id}/contracts/{filename}'
def document_path(instance, filename):
return f'projects/{instance.project_id}/supporting_documents/{filename}'
COMMITTED = 'committed'
CONTRACTING = 'contracting'
IN_PROGRESS = 'in_progress'
CLOSING = 'closing'
COMPLETE = 'complete'
PROJECT_STATUS_CHOICES = [
(COMMITTED, _('Committed')),
(CONTRACTING, _('Contracting')),
(IN_PROGRESS, _('In Progress')),
(CLOSING, _('Closing')),
(COMPLETE, _('Complete')),
]
class ProjectQuerySet(models.QuerySet):
def active(self):
# Projects that are not finished.
return self.exclude(status=COMPLETE)
def in_progress(self):
# Projects that users need to interact with, submitting reports or payment request.
return self.filter(
status__in=(IN_PROGRESS, CLOSING,)
)
def complete(self):
return self.filter(status=COMPLETE)
def in_approval(self):
return self.filter(
is_locked=True,
status=COMMITTED,
approvals__isnull=True,
)
def by_end_date(self, desc=False):
order = getattr(F('proposed_end'), 'desc' if desc else 'asc')(nulls_last=True)
return self.order_by(order)
def with_amount_paid(self):
return self.annotate(
amount_paid=Coalesce(Sum('invoices__paid_value'), Value(0)),
)
def with_last_payment(self):
return self.annotate(
last_payment_request=Max('invoices__requested_at'),
)
def with_outstanding_reports(self):
Report = apps.get_model('application_projects', 'Report')
return self.annotate(
outstanding_reports=Subquery(
Report.objects.filter(
project=OuterRef('pk'),
).to_do().order_by().values('project').annotate(
count=Count('pk'),
).values('count'),
output_field=models.IntegerField(),
)
)
def with_start_date(self):
return self.annotate(
start=Cast(
Subquery(
Contract.objects.filter(
project=OuterRef('pk'),
).approved().order_by(
'approved_at'
).values('approved_at')[:1]
),
models.DateField(),
)
)
def for_table(self):
return self.with_amount_paid().with_last_payment().with_outstanding_reports().select_related(
'report_config',
'submission__page',
'lead',
)
class Project(BaseStreamForm, AccessFormData, models.Model):
lead = models.ForeignKey(settings.AUTH_USER_MODEL, null=True, on_delete=models.SET_NULL, related_name='lead_projects')
submission = models.OneToOneField("funds.ApplicationSubmission", on_delete=models.CASCADE)
user = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.SET_NULL, null=True, related_name='owned_projects')
title = models.TextField()
vendor = models.ForeignKey(
"application_projects.Vendor",
on_delete=models.SET_NULL,
null=True, blank=True, related_name='projects'
)
value = models.DecimalField(
default=0,
max_digits=10,
decimal_places=2,
validators=[MinValueValidator(decimal.Decimal('0.01'))],
)
proposed_start = models.DateTimeField(_('Proposed Start Date'), null=True)
proposed_end = models.DateTimeField(_('Proposed End Date'), null=True)
status = models.TextField(choices=PROJECT_STATUS_CHOICES, default=COMMITTED)
form_data = JSONField(encoder=StreamFieldDataEncoder, default=dict)
form_fields = StreamField(FormFieldsBlock(), null=True)
# tracks read/write state of the Project
is_locked = models.BooleanField(default=False)
# tracks updates to the Projects fields via the Project Application Form.
user_has_updated_details = models.BooleanField(default=False)
activities = GenericRelation(
'activity.Activity',
content_type_field='source_content_type',
object_id_field='source_object_id',
related_query_name='project',
)
created_at = models.DateTimeField(auto_now_add=True)
sent_to_compliance_at = models.DateTimeField(null=True)
objects = ProjectQuerySet.as_manager()
def __str__(self):
return self.title
@property
def status_display(self):
return self.get_status_display()
def get_address_display(self):
try:
address = json.loads(self.vendor.address)
except (json.JSONDecodeError, AttributeError):
return ''
else:
return ', '.join(
address.get(field)
for field in ADDRESS_FIELDS_ORDER
if address.get(field)
)
@classmethod
def create_from_submission(cls, submission):
"""
Create a Project from the given submission.
Returns a new Project or the given ApplicationSubmissions existing
Project.
"""
if not settings.PROJECTS_ENABLED:
logging.error(f'Tried to create a Project for Submission ID={submission.id} while projects are disabled')
return None
# OneToOne relations on the targetted model cannot be accessed without
# an exception when the relation doesn't exist (is None). Since we
# want to fail fast here, we can use hasattr instead.
if hasattr(submission, 'project'):
return submission.project
# See if there is a form field named "legal name", if not use user name.
legal_name = submission.get_answer_from_label('legal name') or submission.user.full_name
vendor, _ = Vendor.objects.get_or_create(
user=submission.user
)
vendor.name = legal_name
vendor.address = submission.form_data.get('address', '')
vendor.save()
return Project.objects.create(
submission=submission,
user=submission.user,
title=submission.title,
vendor=vendor,
value=submission.form_data.get('value', 0),
)
@property
def start_date(self):
# Assume project starts when OTF are happy with the first signed contract
first_approved_contract = self.contracts.approved().order_by('approved_at').first()
if not first_approved_contract:
return None
return first_approved_contract.approved_at.date()
@property
def end_date(self):
# Aiming for the proposed end date as the last day of the project
# If still ongoing assume today is the end
return max(
self.proposed_end.date(),
timezone.now().date(),
)
def paid_value(self):
return self.invoices.paid_value()
def unpaid_value(self):
return self.invoices.unpaid_value()
def clean(self):
if self.proposed_start is None:
return
if self.proposed_end is None:
return
if self.proposed_start > self.proposed_end:
raise ValidationError(_('Proposed End Date must be after Proposed Start Date'))
def save(self, *args, **kwargs):
creating = not self.pk
if creating:
files = self.extract_files()
else:
self.process_file_data(self.form_data)
super().save(*args, **kwargs)
if creating:
self.process_file_data(files)
def editable_by(self, user):
if self.editable:
return True
# Approver can edit it when they are approving
return user.is_approver and self.can_make_approval
@property
def editable(self):
if self.status not in (CONTRACTING, COMMITTED):
return True
# Someone has approved the project - consider it locked while with contracting
if self.approvals.exists():
return False
# Someone must lead the project to make changes
return self.lead and not self.is_locked
def get_absolute_url(self):
if settings.PROJECTS_ENABLED:
return reverse('apply:projects:detail', args=[self.id])
return '#'
@property
def can_make_approval(self):
return self.is_locked and self.status == COMMITTED
def can_request_funding(self):
"""
Should we show this Project's funding block?
"""
return self.status in (CLOSING, IN_PROGRESS)
@property
def can_send_for_approval(self):
"""
Wrapper to expose the pending approval state
We don't want to expose a "Sent for Approval" state to the end User so
we infer it from the current status being "Comitted" and the Project
being locked.
"""
correct_state = self.status == COMMITTED and not self.is_locked
return correct_state and self.user_has_updated_details
@property
def requires_approval(self):
return not self.approvals.exists()
def get_missing_document_categories(self):
"""
Get the number of documents required to meet each DocumentCategorys minimum
"""
# Count the number of documents in each category currently
existing_categories = DocumentCategory.objects.filter(packet_files__project=self)
counter = collections.Counter(existing_categories)
# Find the difference between the current count and recommended count
for category in DocumentCategory.objects.all():
current_count = counter[category]
difference = category.recommended_minimum - current_count
if difference > 0:
yield {
'category': category,
'difference': difference,
}
@property
def is_in_progress(self):
return self.status == IN_PROGRESS
@property
def has_deliverables(self):
return self.deliverables.exists()
# def send_to_compliance(self, request):
# """Notify Compliance about this Project."""
# messenger(
# MESSAGES.SENT_TO_COMPLIANCE,
# request=request,
# user=request.user,
# source=self,
# )
# self.sent_to_compliance_at = timezone.now()
# self.save(update_fields=['sent_to_compliance_at'])
@register_setting
class ProjectSettings(BaseSetting):
compliance_email = models.TextField("Compliance Email")
vendor_setup_required = models.BooleanField(default=True)
class Approval(models.Model):
project = models.ForeignKey("Project", on_delete=models.CASCADE, related_name="approvals")
by = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.CASCADE, related_name="approvals")
created_at = models.DateTimeField(auto_now_add=True)
class Meta:
unique_together = ['project', 'by']
def __str__(self):
return _('Approval of {project} by {user}').format(project=self.project, user=self.by)
class ContractQuerySet(models.QuerySet):
def approved(self):
return self.filter(is_signed=True, approver__isnull=False)
class Contract(models.Model):
approver = models.ForeignKey(settings.AUTH_USER_MODEL, null=True, on_delete=models.SET_NULL, related_name='contracts')
project = models.ForeignKey("Project", on_delete=models.CASCADE, related_name="contracts")
file = models.FileField(upload_to=contract_path, storage=PrivateStorage())
is_signed = models.BooleanField("Signed?", default=False)
created_at = models.DateTimeField(auto_now_add=True)
approved_at = models.DateTimeField(null=True)
objects = ContractQuerySet.as_manager()
@property
def state(self):
return _('Signed') if self.is_signed else _('Unsigned')
def __str__(self):
return _('Contract for {project} ({state})').format(project=self.project, state=self.state)
def get_absolute_url(self):
return reverse('apply:projects:contract', args=[self.project.pk, self.pk])
class PacketFile(models.Model):
category = models.ForeignKey("DocumentCategory", null=True, on_delete=models.CASCADE, related_name="packet_files")
project = models.ForeignKey("Project", on_delete=models.CASCADE, related_name="packet_files")
title = models.TextField()
document = models.FileField(upload_to=document_path, storage=PrivateStorage())
def __str__(self):
return _('Project file: {title}').format(title=self.title)
def get_remove_form(self):
"""
Get an instantiated RemoveDocumentForm with this class as `instance`.
This allows us to build instances of the RemoveDocumentForm for each
instance of PacketFile in the supporting documents template. The
standard Delegated View flow makes it difficult to create these forms
in the view or template.
"""
from ..forms import RemoveDocumentForm
return RemoveDocumentForm(instance=self)
@receiver(post_delete, sender=PacketFile)
def delete_packetfile_file(sender, instance, **kwargs):
# Remove the file and don't save the base model
instance.document.delete(False)
class DocumentCategory(models.Model):
name = models.CharField(max_length=254)
recommended_minimum = models.PositiveIntegerField()
def __str__(self):
return self.name
class Meta:
ordering = ('name',)
verbose_name_plural = 'Document Categories'
class Deliverable(models.Model):
name = models.TextField()
available_to_invoice = models.IntegerField(default=1)
unit_price = models.DecimalField(
max_digits=10,
decimal_places=2,
validators=[MinValueValidator(decimal.Decimal('0.01'))],
)
project = models.ForeignKey(
Project,
null=True, blank=True,
on_delete=models.CASCADE,
related_name='deliverables'
)
def __str__(self):
return self.name
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wraeblast/insights.py | darvid/wraeblast | 26 | 178492 | import collections.abc
import enum
import os
from typing import (
TYPE_CHECKING,
Annotated,
Any,
AsyncGenerator,
Optional,
Union,
)
import aiohttp
import inflection
import numpy as np
import pandas as pd
import pydantic
import structlog
import uplink
import uplink.converters
from pandera.decorators import check_io, check_output
from pandera.errors import SchemaError
from pandera.model import SchemaModel
from pandera.model_components import Field
from pandera.typing import Series, String
from wraeblast import constants, errors
from wraeblast.filtering.elements import ItemFilter
from wraeblast.filtering.parsers.extended import env
if TYPE_CHECKING:
import uplink.commands
from wraeblast.filtering.parsers.extended import config
logger = structlog.get_logger()
QcutItemsType = list[tuple[pd.Interval, pd.DataFrame]]
SingleInfluencedQcutItemsType = list[
tuple[tuple[tuple[str, ...], pd.Interval], pd.DataFrame]
]
InsightsResultType = tuple[
Union["CurrencyType", "ItemType"],
pd.DataFrame,
]
InsightsType = Union["CurrencyType", "ItemType"]
quantiles = {
"quartile": 4,
"quintile": 5,
"decile": 10,
"percentile": 100,
}
shard_names_to_orb_names = {
"Transmutation Shard": "Orb of Transmutation",
"Alteration Shard": "Orb of Alteration",
"Alchemy Shard": "Orb of Alteration",
"Annulment Shard": "Orb of Annulment",
"Binding Shard": "Orb of Binding",
"Horizon Shard": "Orb of Horizons",
"Harbinger's Shard": "Harbinger's Orb",
"Engineer's Shard": "Engineer's Orb",
"Ancient Shard": "Ancient Orb",
"Chaos Shard": "Chaos Orb",
"Mirror Shard": "Mirror of Kalandra",
"Exalted Shard": "Exalted Orb",
"Regal Shard": "Regal Orb",
}
_cache = pd.HDFStore(os.getenv("WRAEBLAST_CACHE", "./.wbinsights.h5"))
class InflectedEnumMixin(enum.Enum):
@property
def underscored_value(self) -> str:
return inflection.underscore(self.value)
@property
def pluralized_underscored_value(self) -> str:
return inflection.pluralize(self.underscored_value)
class CurrencyType(InflectedEnumMixin, enum.Enum):
CURRENCY = "Currency"
FRAGMENT = "Fragment"
class ItemType(InflectedEnumMixin, enum.Enum):
ARTIFACT = "Artifact"
BASE_TYPE = "BaseType"
BEAST = "Beast"
BLIGHTED_MAP = "BlightedMap"
CLUSTER_JEWEL = "ClusterJewel"
DELIRIUM_ORB = "DeliriumOrb"
DIVINATION_CARD = "DivinationCard"
ESSENCE = "Essence"
FOSSIL = "Fossil"
HELMET_ENCHANT = "HelmetEnchant"
INCUBATOR = "Incubator"
INVITATION = "Invitation"
MAP = "Map"
OIL = "Oil"
PROPHECY = "Prophecy"
RESONATOR = "Resonator"
SCARAB = "Scarab"
SKILL_GEM = "SkillGem"
UNIQUE_ACCESSORY = "UniqueAccessory"
UNIQUE_ARMOUR = "UniqueArmour"
UNIQUE_FLASK = "UniqueFlask"
UNIQUE_JEWEL = "UniqueJewel"
UNIQUE_MAP = "UniqueMap"
UNIQUE_WEAPON = "UniqueWeapon"
VIAL = "Vial"
WATCHSTONE = "Watchstone"
@property
def key_name(self) -> str:
return inflection.pluralize(inflection.underscore(self.value))
@uplink.response_handler
def raise_for_status(response):
"""Checks whether or not the response was successful."""
if 200 <= response.status_code < 300:
return response
raise errors.UnsuccessfulInsightsRequest(
f"error {response.status_code}: {response.url}"
)
def get_all_insights_types() -> list[InsightsType]:
return [*CurrencyType, *ItemType]
def get_display_value(
chaos_value: float,
exalted_exchange_value: int,
round_down_by: int = 1,
precision: int = 0,
) -> str:
if chaos_value < exalted_exchange_value:
if round_down_by:
chaos_value = env.round_down(chaos_value, round_down_by)
return f"{chaos_value}c"
else:
return f"{chaos_value / exalted_exchange_value:.{precision}f}ex"
def get_insights_type_by_value(s: str) -> InsightsType:
for t in get_all_insights_types():
if t.value == s:
return t
raise KeyError(s)
def get_quantile_tuple(q: str) -> tuple[str, int]:
if q.startswith("D"):
return ("decile", int(q[1:]))
elif q.startswith("P"):
return ("percentile", int(q[1:]))
elif q.startswith("QU"):
return ("quintile", int(q[2:]))
elif q.startswith("Q"):
return ("quartile", int(q[1:]))
else:
raise RuntimeError(f"invalid quantile: {q}")
async def get_economy_overview(
league: str,
client: "NinjaConsumer",
type_: InsightsType,
) -> pd.DataFrame:
"""Request an economy overview from poe.ninja."""
if type_ in CurrencyType:
meth = client.get_currency_overview
elif type_ in ItemType:
meth = client.get_item_overview
else:
raise RuntimeError()
logger.info(
"overview.get",
client=".".join([client.__module__, client.__class__.__name__]),
type=type_.value,
)
return await meth(league=league, type=type_.value) # type: ignore
async def get_dataframes(
league: str,
types: list[InsightsType],
) -> AsyncGenerator[InsightsResultType, None]:
"""Request all economy overviews from poe.ninja."""
logger.info("all_insights.get", league=league)
session = aiohttp.ClientSession()
client = uplink.AiohttpClient(session=session)
ninja = NinjaConsumer(
base_url=NinjaConsumer.default_base_url,
client=client,
)
for t in types:
overview = await get_economy_overview(
league=league,
client=ninja,
type_=t,
)
yield (t, overview)
await session.close()
async def initialize_insights_cache(
league: str,
cache: Optional[pd.HDFStore] = None,
no_sync: bool = False,
) -> pd.HDFStore:
"""Fetch and cache economy insights as needed."""
if cache is None:
cache = _cache
# log = logger.bind(league=league, cache_dir=cache.directory)
log = logger.bind(league=league)
log.info("cache.initialize", league=league)
missing_dataframes = []
for t in get_all_insights_types():
try:
df = cache.get(f"i_{t.value}")
log.debug("cache.hit", type=t.value)
except KeyError:
log.debug("cache.miss", type=t.value)
missing_dataframes.append(t)
if missing_dataframes and no_sync:
raise errors.WraeblastError("insights cache is incomplete")
async for t, df in get_dataframes(
league=league,
types=missing_dataframes,
):
log.info(
"overview.response",
lines=df.shape[0],
type=t.value,
)
cache.put(f"i_{t.value}", df, format="table")
return cache
async def initialize_filter_context(
initialize_cache: bool = True,
league: Optional[str] = None,
cache: Optional[pd.HDFStore] = None,
no_sync: bool = False,
) -> "ItemFilterContext":
"""Create an ``ItemFilterContext`` from cached economy data."""
if initialize_cache:
if league is None:
raise RuntimeError("league must be provided if initializing cache")
cache = await initialize_insights_cache(
league=league,
cache=cache,
no_sync=no_sync,
)
elif cache is None:
cache = _cache
else:
raise RuntimeError("cache not provided")
economy_data = {}
for t in get_all_insights_types():
overview = cache.get(f"i_{t.value}")
economy_data[t.pluralized_underscored_value] = overview
return ItemFilterContext(data=economy_data)
def _parse_name_and_details_id(
name: str, details_id: str
) -> tuple[Optional[int], tuple[constants.Influence, ...]]:
tokens = details_id.split("-")
ilvl_and_influences = tokens[name.count(" ") + name.count("-") + 1 :]
try:
return (
int(ilvl_and_influences[0]),
tuple(
constants.Influence(i.capitalize())
for i in ilvl_and_influences[1:]
),
)
except (IndexError, ValueError):
return (None, tuple())
def get_quantile_thresholds(df: pd.DataFrame) -> list[dict[str, float]]:
groups = df.groupby(list(quantiles.keys()), as_index=False)
return groups.agg({"chaos_value": "min"}).to_dict( # type: ignore
"records"
)
class NinjaCurrencyOverviewSchema(SchemaModel):
currency_type_name: Series[String]
chaos_equivalent: Series[float]
details_id: Series[String]
pay_id: Series[float] = Field(alias="pay.id", nullable=True)
pay_league_id: Series[float] = Field(alias="pay.league_id", nullable=True)
pay_pay_currency_id: Series[float] = Field(
alias="pay.pay_currency_id", nullable=True
)
pay_get_currency_id: Series[float] = Field(
alias="pay.get_currency_id", nullable=True
)
pay_sample_time_utc: Series[
Annotated[pd.DatetimeTZDtype, "ns", "utc"]
] = Field(alias="pay.sample_time_utc", coerce=True, nullable=True)
pay_count: Series[float] = Field(alias="pay.count", nullable=True)
pay_value: Series[float] = Field(alias="pay.value", nullable=True)
pay_data_point_count: Series[float] = Field(
alias="pay.data_point_count", ge=0, coerce=True, nullable=True
)
pay_includes_secondary: Series[bool] = Field(
alias="pay.includes_secondary", coerce=True, nullable=True
)
pay_listing_count: Series[float] = Field(
alias="pay.listing_count", coerce=True, nullable=True
)
class NinjaItemOverviewSchema(SchemaModel):
id: Series[int]
name: Series[String]
item_class: Series[int]
flavour_text: Optional[Series[String]]
chaos_value: Series[float]
exalted_value: Series[float]
count: Series[int]
details_id: Series[String]
# listing_count: Series[int]
icon: Optional[Series[String]] = Field(nullable=True)
base_type: Optional[Series[String]] = Field(nullable=True)
gem_level: Optional[Series[float]] = Field(nullable=True)
gem_quality: Optional[Series[float]] = Field(nullable=True)
item_level: Optional[Series[float]] = Field(nullable=True)
level_required: Optional[Series[float]] = Field(nullable=True)
links: Optional[Series[float]] = Field(nullable=True)
map_tier: Optional[Series[float]] = Field(nullable=True)
stack_size: Optional[Series[float]] = Field(nullable=True)
variant: Optional[Series[String]] = Field(nullable=True)
class Config:
coerce = True
class ExtendedNinjaOverviewSchema(SchemaModel):
item_name: Series[String]
chaos_value: Series[float]
alt_quality: Series[String]
is_alt_quality: Series[bool]
chaos_value: Series[float]
chaos_value_log: Series[float]
quartile: Series[int]
quintile: Series[int]
decile: Series[int]
percentile: Series[int]
base_type: Optional[Series[String]] = Field(nullable=True)
gem_level: Optional[Series[float]] = Field(nullable=True)
gem_quality: Optional[Series[float]] = Field(nullable=True)
influences: Optional[Series[String]] = Field(nullable=True)
level_required: Optional[Series[float]] = Field(nullable=True)
links: Optional[Series[float]] = Field(nullable=True)
map_tier: Optional[Series[float]] = Field(nullable=True)
num_influences: Optional[Series[int]] = Field(nullable=True)
orb_name: Optional[Series[String]] = Field(nullable=True)
stack_size: Optional[Series[float]] = Field(nullable=True)
uber_blight: Optional[Series[bool]] = Field(nullable=True)
variant: Optional[Series[String]] = Field(nullable=True)
class PostProcessedNinjaOverviewSchema(ExtendedNinjaOverviewSchema):
exalted_value: Series[float]
display_value: Series[String]
@check_output(ExtendedNinjaOverviewSchema)
def transform_ninja_df(df: pd.DataFrame) -> pd.DataFrame:
currency_overview_schema = NinjaCurrencyOverviewSchema.to_schema()
item_overview_schema = NinjaItemOverviewSchema.to_schema()
is_currency_overview = False
df = df.fillna(0)
try:
df = currency_overview_schema.validate(df)
is_currency_overview = True
except SchemaError as e:
df = item_overview_schema.validate(df)
if is_currency_overview:
try:
shards = []
for shard_name, orb_name in shard_names_to_orb_names.items():
if not df[df["currency_type_name"] == shard_name].empty:
continue
orb_value = (
df[df["currency_type_name"] == orb_name][
"chaos_equivalent"
].iloc[0]
if orb_name != "Chaos Orb"
else 1
)
shards.append(
{
"currency_type_name": shard_name,
"chaos_equivalent": orb_value / 20,
}
)
df = df.append(
shards,
verify_integrity=True,
sort=True,
ignore_index=True,
)
except IndexError:
pass
if "sparkline.data" in df.columns:
df = df.loc[df["sparkline.data"].str.len() != 0]
output = pd.DataFrame()
output["item_name"] = (
df["currency_type_name"]
if "currency_type_name" in df.columns
else df["name"]
)
if not is_currency_overview:
output["scourged"] = output["item_name"].map(
lambda name: name.startswith("Scourged")
)
for label in ("currency_type_name", "skill_gem_name"):
if label in df.columns:
output["item_name"] = df[label]
if "map_tier" in df.columns:
output["uber_blight"] = df["name"].map(
lambda name: name.startswith("Blight-ravaged")
)
if (
"base_type" in df.columns
and not df[
df["base_type"].str.contains("Cluster Jewel", na=False)
].empty
):
try:
output["cluster_jewel_enchantment"] = df["name"].map(
lambda name: constants.get_cluster_jewel_passive(name).value
)
output["cluster_jewel_passives_min"] = df["trade_info"].apply(
lambda trade_info: [
ti
for ti in trade_info
if ti["mod"] == "enchant.stat_3086156145"
][0]["min"]
)
output["cluster_jewel_passives_max"] = df["trade_info"].apply(
lambda trade_info: [
ti
for ti in trade_info
if ti["mod"] == "enchant.stat_3086156145"
][0]["max"]
)
output["cluster_jewel_passives"] = output[
"cluster_jewel_passives_min"
]
except (KeyError, IndexError) as e:
# TODO: Find a way to filter out unique cluster jewels better
pass
output["alt_quality"] = ""
output["is_alt_quality"] = False
alt_filter = (
output["item_name"].str.startswith("Anomalous")
| output["item_name"].str.startswith("Divergent")
| output["item_name"].str.startswith("Phantasmal")
)
if not output[alt_filter].empty:
output.loc[alt_filter, "is_alt_quality"] = True
output.loc[alt_filter, "alt_quality"] = output["item_name"].apply(
lambda s: s[: s.find(" ")],
)
output.loc[alt_filter, "item_name"] = output["item_name"].apply(
lambda s: s[s.find(" ") + 1 :],
)
if "name" in df.columns and "details_id" in df.columns:
output["influences"] = df.apply(
lambda r: "/".join(
i.value
for i in _parse_name_and_details_id(
str(r["name"]),
str(r["details_id"]),
)[1]
),
axis=1,
)
output["num_influences"] = (
df["variant"].str.count("/").fillna(0).astype(int)
if "variant" in df.columns
else 0
)
for column in (
"base_type",
"level_required",
"links",
"gem_level",
"gem_quality",
"map_tier",
"stack_size",
):
if column in df.columns:
output[column] = df[column]
if column == "links":
output[column] = output[column].fillna(0)
output["chaos_value"] = (
df["chaos_equivalent"]
if "chaos_equivalent" in df.columns
else df["chaos_value"]
)
# Normalized chaos values
# XXX: since log(0) is -inf, the min chaos value of the dataframe replaces
# rows with a chaos value of 0
min_chaos_value = output.loc[
output["chaos_value"] != 0, "chaos_value"
].min()
output["chaos_value"].replace(0, min_chaos_value, inplace=True) # type: ignore
output["chaos_value_log"] = np.log(output["chaos_value"])
# Pre-defined quantiles (quartiles, quintiles, percentiles)
for label, q in quantiles.items():
labels = None
if isinstance(q, (list, tuple)):
q, labels = q
output[label] = pd.qcut(
output["chaos_value"].rank(method="first", numeric_only=True),
q=q,
labels=False if labels is None else None,
precision=0,
duplicates="drop",
)
if labels is not None:
output[label] = output[label].map(dict(enumerate(labels)))
return output
def json_normalize(data: dict[Any, Any]) -> pd.DataFrame:
df = pd.json_normalize(data)
df.columns = [inflection.underscore(c) for c in df.columns]
return df
@uplink.install
class NinjaDataFrameFactory(uplink.converters.Factory):
def create_response_body_converter(self, cls, request_definition):
return lambda response: transform_ninja_df(
df=json_normalize(response.json()["lines"]),
)
uplink_retry = uplink.retry(
when=uplink.retry.when.status(503) | uplink.retry.when.raises(Exception),
stop=uplink.retry.stop.after_attempt(5)
| uplink.retry.stop.after_delay(10),
backoff=uplink.retry.backoff.jittered(multiplier=0.5),
)
@raise_for_status
@uplink_retry
@uplink.returns.json
@uplink.json
@uplink.get
def get_json() -> uplink.commands.RequestDefinitionBuilder:
"""Template for GET requests with JSON as both request and response."""
@raise_for_status
@uplink_retry
@uplink.get
def get_dataframe() -> uplink.commands.RequestDefinitionBuilder:
...
class NinjaConsumer(uplink.Consumer):
default_base_url = "https://poe.ninja/api/data/"
@uplink.ratelimit(calls=2, period=150)
@get_dataframe("CurrencyOverview") # type: ignore
def get_currency_overview(
self,
league: uplink.Query(type=str), # type: ignore
type: uplink.Query(type=CurrencyType), # type: ignore
) -> pd.DataFrame:
...
@uplink.ratelimit(calls=2, period=150)
@get_dataframe("CurrencyHistory") # type: ignore
def get_currency_history(
self,
league: uplink.Query(type=str), # type: ignore
type: uplink.Query(type=CurrencyType), # type: ignore
currency_id: uplink.Query("currencyId", type=int), # type: ignore
) -> pd.DataFrame:
...
@uplink.ratelimit(calls=30, period=150)
@get_dataframe("ItemOverview") # type: ignore
def get_item_overview(
self,
league: uplink.Query(type=str), # type: ignore
type: uplink.Query(type=ItemType), # type: ignore
) -> pd.DataFrame:
...
class ItemFilterContext(pydantic.BaseModel):
"""Entrypoint for accessing economy data from poe.ninja."""
data: dict[str, pd.DataFrame]
_exalted_value: int = pydantic.PrivateAttr(default=0)
_quantile_thresholds: dict[
str, list[dict[str, float]]
] = pydantic.PrivateAttr(default_factory=list)
class Config:
arbitrary_types_allowed = True
def __init__(self, **data) -> None:
super().__init__(**data)
self._exalted_value = self.data["currencies"][
self.data["currencies"].item_name == "Exalted Orb"
].iloc[0]["chaos_value"]
self._quantile_thresholds = {
k: get_quantile_thresholds(df) for k, df in self.data.items()
}
self.data = {
k: self._post_process(k, df) for k, df in self.data.items()
}
def get_display_value(
self,
chaos_value: float,
round_down_by: int = 1,
precision: int = 0,
):
return get_display_value(
chaos_value=chaos_value,
exalted_exchange_value=self._exalted_value,
round_down_by=round_down_by,
precision=precision,
)
def get_quantiles_for_threshold(
self,
key: str,
min_chaos_value: float,
) -> Optional[dict[str, float]]:
for threshold in self._quantile_thresholds[key]:
if threshold["chaos_value"] >= min_chaos_value:
return threshold
return self._quantile_thresholds[key][-1]
@pydantic.validator("data")
def data_must_contain_all_types(
cls, v: dict[str, pd.DataFrame]
) -> dict[str, pd.DataFrame]:
for type_ in [*CurrencyType, *ItemType]:
if type_.pluralized_underscored_value not in v:
raise ValueError(f"{type_} missing from filter context")
return v
@check_io(
df=ExtendedNinjaOverviewSchema.to_schema(),
out=PostProcessedNinjaOverviewSchema.to_schema(),
)
def _post_process(self, key: str, df: pd.DataFrame) -> pd.DataFrame:
df["exalted_value"] = df["chaos_value"].apply(
lambda x: x / self._exalted_value
)
df["display_value"] = df["chaos_value"].apply(
lambda x: get_display_value(
chaos_value=x,
exalted_exchange_value=self._exalted_value,
precision=2,
)
)
return df
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] |
tests/test_coesa.py | TheMagicNacho/artemis-nozzle | 89 | 183283 | # coding: utf-8
"""
Tests of the U.S. 1976 Standard Atmosphere implementation. All of them are
validated against the `standard`_.
.. _`standard`: http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19770009539_1977009539.pdf
"""
from __future__ import division, absolute_import
import numpy as np
from numpy.testing import (assert_equal, assert_almost_equal,
assert_array_equal, assert_array_almost_equal)
import scipy as sp
import scipy.constants
from skaero.atmosphere import coesa, util
def _C2K(val):
"""Convert Celsius to Kelvins."""
return scipy.constants.convert_temperature([val], 'C', 'K')
def test_sea_level():
"""Tests sea level values.
"""
h = 0.0
expected_h = 0.0
expected_T = _C2K(15)
expected_p = sp.constants.atm
expected_rho = 1.2250
h, T, p, rho = coesa.table(h)
assert_equal(h, expected_h)
assert_equal(T, expected_T)
assert_equal(p, expected_p)
assert_almost_equal(rho, expected_rho, decimal=4)
def test_sea_level_0d_array():
"""Tests sea level values using zero dimension array.
"""
h = np.array(0.0)
expected_h = np.array(0.0)
expected_T = np.array(_C2K(15))
expected_p = np.array(sp.constants.atm)
expected_rho = np.array(1.2250)
h, T, p, rho = coesa.table(h)
assert_array_equal(h, expected_h)
assert_array_almost_equal(T, expected_T)
assert_array_almost_equal(p, expected_p)
assert_array_almost_equal(rho, expected_rho)
def test_sea_level_nd_array():
"""Tests sea level values using n dimension array.
"""
h = np.array([0.0, 0.0, 0.0])
expected_h = np.array([0.0, 0.0, 0.0])
expected_T = np.array([288.15] * 3)
expected_p = np.array([101325.0] * 3)
expected_rho = np.array([1.2250] * 3)
h, T, p, rho = coesa.table(h)
assert_array_equal(h, expected_h)
assert_array_almost_equal(T, expected_T)
assert_array_almost_equal(p, expected_p)
assert_array_almost_equal(rho, expected_rho)
def test_geometric_to_geopotential():
z = np.array([50.0, 5550.0, 10450.0])
h = util.geometric_to_geopotential(z)
expected_h = np.array([50.0, 5545.0, 10433.0])
assert_array_almost_equal(h, expected_h, decimal=0)
def test_under_1000m():
"""Tests for altitude values under 1000.0 m
"""
z = np.array([50.0, 550.0, 850.0])
h = util.geometric_to_geopotential(z)
expected_h = np.array([50.0, 550.0, 850.0])
expected_T = np.array([287.825, 284.575, 282.626])
expected_p = np.array([100720.0, 94890.0, 91523.0])
expected_rho = np.array([1.2191, 1.1616, 1.1281])
h, T, p, rho = coesa.table(h)
assert_array_almost_equal(h, expected_h, decimal=0)
assert_array_almost_equal(T, expected_T, decimal=3)
assert_array_almost_equal(p, expected_p, decimal=-1)
assert_array_almost_equal(rho, expected_rho, decimal=4)
def test_under_11km():
"""Tests for altitude values between 1 and 11 km
"""
z = np.array([500.0, 2500.0, 6500.0, 9000.0, 11000.0])
h = util.geometric_to_geopotential(z)
expected_h = np.array([500.0, 2499.0, 6493.0, 8987.0, 10981.0])
expected_T = np.array([284.900, 271.906, 245.943, 229.733, 216.774])
expected_p = np.array([95461.0, 74691.0, 44075.0, 30800.0, 22699.0])
expected_rho = np.array([1.1673, 0.95695, 0.62431, 0.46706, 0.36480])
h, T, p, rho = coesa.table(h)
assert_array_almost_equal(h, expected_h, decimal=0)
assert_array_almost_equal(T, expected_T, decimal=3)
assert_array_almost_equal(p, expected_p, decimal=0)
assert_array_almost_equal(rho, expected_rho, decimal=4)
def test_under_35km():
"""Tests for altitude values between 11 and 35 km
"""
z = np.array([15000.0, 25000.0, 35000.0])
h = util.geometric_to_geopotential(z)
expected_h = np.array([14965.0, 24902., 34808.0])
expected_T = np.array([216.65, 221.552, 236.513])
expected_p = np.array([12111.0, 2549.2, 574.59])
expected_rho = np.array([0.19476, 0.040084, 0.0084634])
h, T, p, rho = coesa.table(h)
assert_array_almost_equal(h, expected_h, decimal=0)
assert_array_almost_equal(T, expected_T, decimal=3)
assert_array_almost_equal(p, expected_p, decimal=0)
assert_array_almost_equal(rho, expected_rho, decimal=5)
def test_under_86km():
"""Tests for altitude values between 35 and 86 km
"""
z = np.array([50000.0, 70000.0, 86000.0])
h = util.geometric_to_geopotential(z)
expected_h = np.array([49610.0, 69238., 84852.0])
expected_T = np.array([270.65, 219.585, 186.87])
expected_p = np.array([79.779, 5.2209, 0.37338])
expected_rho = np.array([0.0010269, 0.000082829, 0.000006958])
h, T, p, rho = coesa.table(h)
assert_array_almost_equal(h, expected_h, decimal=0)
assert_array_almost_equal(T, expected_T, decimal=2)
assert_array_almost_equal(p, expected_p, decimal=3)
assert_array_almost_equal(rho, expected_rho, decimal=7)
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] |
setup.py | Leschonander/Jump-Bike-D.C-Python-API-Wrapper | 0 | 197758 | from setuptools import setup
setup(name = "Jump Bike DC API Wrapper",
url = 'https://github.com/Leschonander/Jump-Bike-D.C-Python-API-Wrapper',
author = "<NAME>",
author_email = '<EMAIL>',
packages=['src'],
install_requires=['requests'],
version = '0.1',
license = 'MIT',
description = "Python Wrapper for Jump Bike D.C's open API.",
long_description = open('README.md').read()
) | [
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parser/fase2/team29/analizer_pl/interpreter.py | estabanmike/tytus | 0 | 132793 | <gh_stars>0
from re import S
from sys import path
from os.path import dirname as dir
path.append(dir(path[0]))
from analizer_pl.C3D.operations import block
from analizer_pl.reports import BnfGrammar
from analizer_pl.abstract import global_env
import analizer_pl.grammar as grammar
def traducir(input):
result = grammar.parse(input)
lexerErrors = grammar.returnLexicalErrors()
syntaxErrors = grammar.returnSyntacticErrors()
env = global_env.GlobalEnvironment()
c3d = "from sys import path\n"
c3d += "from os.path import dirname as dir\n"
c3d += "path.append(dir(path[0]))\n"
c3d += "from analizer import interpreter as fase1\n"
c3d += "from goto import with_goto\n"
c3d += 'dbtemp = ""\n'
c3d += "stack = []\n"
c3d += "\n"
optimizacion = c3d
if len(lexerErrors) + len(syntaxErrors) == 0 and result:
for r in result:
if r:
c3d += r.execute(env).value
else:
c3d += "Instruccion SQL \n"
f = open("test-output/c3d.py", "w+")
f.write(c3d)
f.close()
optimizacion += grammar.optimizer_.optimize()
f = open("test-output/c3dopt.py", "w+")
f.write(optimizacion)
f.close()
semanticErrors = []
functions = functionsReport(env)
symbols = symbolReport()
obj = {
"lexical": lexerErrors,
"syntax": syntaxErrors,
"semantic": semanticErrors,
"symbols": symbols,
"functions": functions,
}
# grammar.InitTree()
BnfGrammar.grammarReport()
return obj
def symbolReport():
environments = block.environments
report = []
for env in environments:
envName = env[0]
env = env[1]
vars = env.variables
enc = [["ID", "Tipo", "Fila", "Columna", "Declarada en"]]
filas = []
for (key, symbol) in vars.items():
r = [
symbol.value,
symbol.type.name if symbol.type else "UNKNOWN",
symbol.row,
symbol.column,
envName,
]
filas.append(r)
enc.append(filas)
report.append(enc)
environments = list()
return report
def functionsReport(env):
rep = [["Tipo", "ID", "Tipo de Retorno", "No. de Parametros"], []]
for (f, x) in env.functions.items():
r = []
r.append(x.type)
r.append(x.id)
if x.returnType:
r.append(x.returnType.name)
else:
r.append("NULL")
r.append(x.params)
rep[1].append(r)
return rep
s = """
CREATE FUNCTION ValidaRegistros(tabla varchar(50),cantidad integer) RETURNS integer AS $$
DECLARE
resultado INTEGER;
retorna INTEGER;
BEGIN
if tabla = 'tbProducto' then
resultado := (SELECT md5('23') si, puta as sho) ;
if cantidad = resultado then
retorna = 1;
else
retorna = 0;
end if;
end if;
if tabla = 'tbProductoUp' then
resultado := (SELECT COUNT(*) FROM tbProducto where estado = 2);
if cantidad = resultado then
retorna = 1;
else
retorna = 0;
end if;
end if;
if tabla = 'tbbodega' then
resultado := (SELECT COUNT(*) FROM tbbodega);
if cantidad = resultado then
retorna = 1;
else
retorna = 0;
end if;
end if;
RETURN retorna;
END;
$$ LANGUAGE plpgsql;
delete from tbbodega as tb where idbodega = 4 and idbodega = 5;
"""
s2 = """
CREATE FUNCTION foo(texto text, b boolean) RETURNS text AS $$
BEGIN
update tbbodega set bodega = texto||"fr", id = 1 where idbodega = 4;
update tbbodega set bodega = "fr" where idbodega = 4;
return texto;
END;
$$ LANGUAGE plpgsql;
CREATE FUNCTION myFuncion(texto text, b boolean) RETURNS text AS $$
BEGIN
INSERT INTO tbProducto values(1,'Laptop Lenovo',md5(texto),1);
SELECT 3-5>4 and -3=texto as sho, texto between symmetric 2 and 3 as alv;
select * from tbCalificacion;
select * from tbventa where ventaregistrada = false;
select * from tbempleadopuesto group by departamento;
select *
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido;
select v.id+foo(texto, 3)
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido,fechaventa
limit 1;
select *
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido
UNION
select DISTINCT *
from tbventa V,tbempleado E
where V.idempleado = texto
group by 1,2,3
order by 1;
b = texto between symmetric 2 and 3;
RETURN (3+1)*-1;
END;
$$ LANGUAGE plpgsql;
select *
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido;
select (3+3)*5;
select *
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido
UNION
select DISTINCT *
from tbventa V,tbempleado E
where V.idempleado = texto
group by 1,2,3
order by col ,1 ;
"""
s3 = """
select E.* from tabla;
select departamento,count(*) CantEmpleados
from tbempleadopuesto
group by departamento;
select primernombre,segundonombre,primerapellido,sum(montoventa)
from tbventa V,tbempleado E
where V.idempleado = E.idempleado
group by primernombre,segundonombre,primerapellido;
create table tblibrosalario
( idempleado integer not null,
aniocalculo integer not null CONSTRAINT aniosalario CHECK (aniocalculo > 0),
mescalculo integer not null CONSTRAINT mescalculo CHECK (mescalculo > 0),
salariobase money not null,
comision decimal,
primary key(idempleado)
);
EXECUTE md5("francisco");
update tbbodega set bodega = 'bodega zona 9' where idbodega = 4;
update tbbodega set bodega = DEFAULT where idbodega = 4;
"""
s4 = """
CREATE FUNCTION ValidaRegistros(tabla varchar(50),cantidad integer) RETURNS integer AS $$
DECLARE resultado INTEGER;
retorna INTEGER;
BEGIN
if tabla = 'tbProducto' then
resultado := not ((4+4*10/3) NOT IN (SELECT COUNT(*) FROM tbProducto));
retorna = 0;
end if;
if tabla = 'tbProductoUp' then
resultado := xd IN (SELECT * FROM tbProducto where estado = 2);
retorna = 1;
end if;
if tabla = 'tbbodega' then
resultado := EXISTS (SELECT COUNT(*) FROM tbbodega);
retorna = 2;
end if;
RETURN retorna;
END;
$$ LANGUAGE plpgsql;
"""
traducir(s4)
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] |
x64/ascii/mixedcase/__init__.py | mitthu/alpha3 | 137 | 180154 | import rm64
encoders = rm64.encoders
for encoder in encoders:
encoder["case"] = "mixedcase"
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Task2F.py | J-uliette/Warning-System | 0 | 173679 | <filename>Task2F.py
from floodsystem.flood import stations_highest_rel_level
from floodsystem.stationdata import build_station_list, update_water_levels
from floodsystem.plot import plot_water_level_with_fit
from floodsystem.datafetcher import fetch_measure_levels
import datetime
N=5
p=4
dt = 2 #parameters
stations = build_station_list() #build list of stations
update_water_levels(stations)
finallist = stations_highest_rel_level(stations, N) #get 5 highest risk stations
for i in range(len(finallist)): #iterate over 5 stations
dates, levels = fetch_measure_levels(finallist[i][0].measure_id, dt=datetime.timedelta(days=dt)) #get the dates and levels
plot_water_level_with_fit(finallist[i], dates, levels, p) | [
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] |
python_exercises/52Primes_iterator.py | Matheus-IT/lang-python-related | 0 | 181285 | <gh_stars>0
class Primes:
def __init__(self, first, last=None):
self.curr = None
if last is None:
self.first = 2
self.last = first
else:
self.first = first
self.last = last
def __iter__(self):
return self
def __next__(self):
if self.curr is None:
self.curr = 2
return self.curr
while self.curr < self.last:
self.curr += 1
if Primes.__prime(self.curr):
return self.curr
raise StopIteration()
def __prime(n):
for d in range(2, n):
if n % d == 0:
return False
return True
for p in Primes(100):
print(p)
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] |
gnu_linux_box/utils/gcp_translate.py | shivag1992/WearableIntelligenceSystem | 0 | 125832 | import os
import sys
import threading
from queue import Empty
from google.cloud import translate
os.environ["GOOGLE_APPLICATION_CREDENTIALS"]=os.path.join(os.path.dirname(__file__), "creds.json")
def translate_text(translation_client, text="<NAME>", project_id="wearableai", source_language="es", target_language="en"):
"""Translating Text.
text : single string - text to be translated
"""
location = "global"
parent = f"projects/{project_id}/locations/{location}"
print("Translate text is : {}".format(text))
print("Translate source_language is : {}".format(source_language))
# Detail on supported types can be found here:
# https://cloud.google.com/translate/docs/supported-formats
response = translation_client.translate_text(
request={
"parent": parent,
"contents": [text],
"mime_type": "text/plain", # mime types: text/plain, text/html
"source_language_code": source_language,
"target_language_code": target_language,
}
)
# return the translation for each input text provided
return response.translations[0].translated_text
def run_google_translate(translate_q, obj_q, source_language="es"):
print("starting translate service")
#make translation client
client = translate.TranslationServiceClient()
t = threading.currentThread()
t.do_run = True
while True:
#check if our thread kill switch has been activated
if not getattr(t, "do_run", True):
return
try:
transcript_obj = translate_q.get(timeout=1)
if transcript_obj["is_final"]:
transcript = transcript_obj["transcript"]
result = translate_text(client, transcript, source_language=source_language)
print("Translation result: {}".format(result))
obj_q.put({"type" : "translate_result", "data" : result})
except Exception as e:
print(e)
pass
if __name__ == "__main__":
if len(sys.argv) > 1:
print("Translated text: {}".format(translate_text(sys.argv[1])))
else:
print("Translated text: {}".format(translate_text()))
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resources/character.py | WareDave/flaskRepo | 0 | 1614194 | <filename>resources/character.py
from flask import Blueprint, jsonify, request
from playhouse.shortcuts import model_to_dict
from flask_login import current_user, login_required
import models
characters = Blueprint('characters', 'characters')
print()
# Index route
@characters.route('/', methods=["GET"])
def get_all_characters():
try:
characters = [model_to_dict(character) for character in models.Character.select().where(models.Character.loggedUser_id == current_user.id)]
print(characters)
for character in characters:
character['loggedUser'].pop('password')
return jsonify(data=characters, status={"code": 200, "message": "Success"})
except models.DoesNotExist:
return jsonify(data={}, status={"code": 400, "message": "Error getting the resources"})
# Create route
@characters.route('/', methods=["POST"])
@login_required
def create_characters():
try:
payload = request.get_json()
payload['loggedUser'] = current_user.id
character = models.Character.create(**payload)
print(character.__dict__)
character_dict = model_to_dict(character)
return jsonify(data = character_dict, status = {"code": 201, "message": "Success"})
except models.DoesNotExist:
return jsonify(data={}, status={"code": 400, "message": "Error creating the resources"})
# Show route
@characters.route('/<id>', methods=["GET"])
def get_one_characters(id):
try:
character = models.Character.get_by_id(id)
print(character)
character_dict = model_to_dict(character)
return jsonify(data = character_dict, status={"code": 200, "message": f"Found character with id {character.id}"})
except models.DoesNotExist:
return jsonify(data={}, status={"code": 400, "message": "Error getting one resource"})
# Update route
@characters.route('/<id>', methods=["PUT"])
def update_characters(id):
try:
payload = request.get_json()
query = models.Character.update(**payload).where(models.Character.id == id)
query.execute()
updated_character = model_to_dict(models.Character.get_by_id(id))
return jsonify(data=updated_character, status={"code": 200, "message": f"Resourced updated successfully"})
except models.DoesNotExist:
return jsonify(data={}, status={"code": 400, "message": "Error updating one resource"})
# Delete route
@characters.route('/<id>', methods=["DELETE"])
def delete_character(id):
try:
query = models.Character.delete().where(models.Character.id == id)
query.execute()
return jsonify(data='Resource successfully deleted', status={"code": 200, "message": "Resource successfully deleted"})
except models.DoesNotExist:
return jsonify(data={}, status={"code": 400, "message": "Error deleting resource"})
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classifier/crossValClass.py | alexander7161/FaceGen | 1 | 82421 | <reponame>alexander7161/FaceGen
from datasets import load_csv
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import constants
import numpy as np
import random
import pandas as pd
from datasets import get_testing_data
# Class for cross validation
class CrossVal(object):
# Shuffle data using random
def shuffleData(self, data):
return data.sample(frac=1).reset_index(drop=True)
# Splits data into K splits with k folds.
def createSplits(self, shuffledData, folds):
# Split list x into k lists
def foldList(x, k):
return [x.loc[i::k] for i in range(k)]
splits = foldList(shuffledData, folds)
return splits
def getSplit(self, i, splits):
# Copy folds to temporary variable.
splitsCopy = splits[:]
# Take the ith fold as test data.
test = splitsCopy[i]
# Remove test data from folds.
splitsCopy.pop(i)
# concat the remaining data as training data.
train = pd.concat(splitsCopy)
return train, test
# Take ith fold as test data.
# Train a classifier with the remaining data.
# return the accuracy of the given classifier.
def getAccuracy(self, classifier, i, splits, columns, epochs, run_name):
train, test = self.getSplit(i, splits)
datagen = ImageDataGenerator(rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
batch_size = 32
train_generator = datagen.flow_from_dataframe(
dataframe=train,
directory="./face_data/age_gender",
x_col="filename",
y_col=columns,
target_size=(
constants.IMG_HEIGHT, constants.IMG_WIDTH),
batch_size=batch_size,
class_mode='raw',
seed=1)
validation_generator = datagen.flow_from_dataframe(
dataframe=test,
directory="./face_data/age_gender",
x_col="filename",
y_col=columns,
target_size=(
constants.IMG_HEIGHT, constants.IMG_WIDTH),
batch_size=batch_size,
class_mode='raw',
seed=1)
c = classifier(outputs=4, run_name=run_name)
# Train classifier on training data.
c.fit(train_generator, validation_generator, columns, epochs)
# Get accuracy for the test data.
test_generator, columns = get_testing_data("overall")
loss, accuracy = c.evaluate(test_generator)
return accuracy
# Perfoms K-fold cross validation on the provided data and classifier.
# Returns accuracy and standard deviation of accuracies.
def trainTestSplit(self, classifier, run_name, epochs=30, folds=10):
ffhq_data, columns = load_csv("./face_data/age_gender/labels.csv")
shuffledData = self.shuffleData(ffhq_data)
# Split data into K folds
splits = self.createSplits(shuffledData, folds)
# Collect accuracies for each fold.
accuracies = [self.getAccuracy(classifier, i, splits, columns, epochs, "%s/%d" % (run_name, i))
for i in range(folds)]
# Compute mean accuracy.
accuracy = np.mean(accuracies)
std = np.std(accuracies)
return accuracy, std
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] |
pyit/cops/tab_indentation.py | ysv/pyit | 0 | 152275 | from pyit.cop import IRawFileCop, Cop
from pyit.offence import Offence
class TabIndentationCop(Cop):
COP_CONFIG = {}
TAB_INDENT = '\t'
__implements__ = [IRawFileCop]
offences = []
def __init__(self, cop_conf=None):
if cop_conf is None:
self.cop_conf = {**self.DEFAULT_CONFIG, **self.COP_CONFIG}
else:
self.cop_conf = {**self.DEFAULT_CONFIG, **self.COP_CONFIG, **cop_conf}
@classmethod
def name(cls):
return 'tab_indentation_cop'
def process_file(self, lines, filename):
if not self.processable():
return
for i, line in enumerate(lines):
tab_index = line.find(self.TAB_INDENT)
if tab_index != -1:
off = Offence(
cop_name=self.name(),
location=(i + 1, tab_index),
message="Indentation contains tab.",
filename=filename,
severity='warning'
)
self.offences.append(off)
| [
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2
] |
prep_scripts/depth/demo.py | nhh1501/SynthText-vietnamese | 0 | 83279 | <gh_stars>0
import argparse
import torch
import torch.nn.parallel
from models import modules, net, resnet, densenet, senet
import numpy as np
import loaddata_demo as loaddata
import pdb
import matplotlib.image
import matplotlib.pyplot as plt
plt.set_cmap("jet")
def define_model(is_resnet, is_densenet, is_senet):
if is_resnet:
original_model = resnet.resnet50(pretrained = True)
Encoder = modules.E_resnet(original_model)
model = net.model(Encoder, num_features=2048, block_channel = [256, 512, 1024, 2048])
if is_densenet:
original_model = densenet.densenet161(pretrained=True)
Encoder = modules.E_densenet(original_model)
model = net.model(Encoder, num_features=2208, block_channel = [192, 384, 1056, 2208])
if is_senet:
original_model = senet.senet154(pretrained='imagenet')
Encoder = modules.E_senet(original_model)
model = net.model(Encoder, num_features=2048, block_channel = [256, 512, 1024, 2048])
return model
def main():
model = define_model(is_resnet=False, is_densenet=False, is_senet=True)
model = torch.nn.DataParallel(model).cuda()
model.load_state_dict(torch.load('./pretrained_model/model_senet'))
model.eval()
nyu2_loader = loaddata.readNyu2('data/demo/img_nyu2.png')
test(nyu2_loader, model)
def test(nyu2_loader, model):
for i, image in enumerate(nyu2_loader):
image = torch.autograd.Variable(image, volatile=True).cuda()
out = model(image)
matplotlib.image.imsave('data/demo/out.png', out.view(out.size(2),out.size(3)).data.cpu().numpy())
if __name__ == '__main__':
main()
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] |
integreat_cms/sitemap/views.py | Carlosbogo/integreat-cms | 1 | 131898 | <reponame>Carlosbogo/integreat-cms
"""
This module contains views for generating the sitemap dynamically.
The views are class-based patches of the inbuilt views :func:`~django.contrib.sitemaps.views.index` and
:func:`~django.contrib.sitemaps.views.sitemap` of the :mod:`django.contrib.sitemaps` :doc:`django:ref/contrib/sitemaps`.
"""
import logging
from django.conf import settings
from django.contrib.sites.shortcuts import get_current_site
from django.http import Http404
from django.shortcuts import get_object_or_404
from django.urls import reverse
from django.utils.http import http_date
from django.views.generic.base import TemplateResponseMixin, View
from ..cms.constants import region_status
from ..cms.models import Region
from .utils import get_sitemaps
logger = logging.getLogger(__name__)
class SitemapIndexView(TemplateResponseMixin, View):
"""
This view allows to generate a sitemap index dynamically.
It is a patched version of :func:`django.contrib.sitemaps.views.index` with the following changes:
* Sitemaps dynamically queried on each request, not on the application startup
* :attr:`~integreat_cms.core.settings.WEBAPP_URL` is used for the domain instead of the host of the sitemap
* Empty sitemaps are not included in the index
"""
#: The template to render (see :class:`~django.views.generic.base.TemplateResponseMixin`)
template_name = "sitemap_index.xml"
#: The content type to use for the response (see :class:`~django.views.generic.base.TemplateResponseMixin`)
content_type = "application/xml"
def get(self, request, *args, **kwargs):
"""
This function handles a get request
:param request: The current request
:type request: ~django.http.HttpRequest
:param args: The supplied args
:type args: list
:param kwargs: The supplied keyword args
:type kwargs: dict
:return: The rendered template response
:rtype: ~django.template.response.TemplateResponse
"""
logger.debug("Sitemap index requested with args %r and kwargs %r", args, kwargs)
sitemaps = []
# Only add active regions to the sitemap index
for region in Region.objects.filter(status=region_status.ACTIVE):
# Only add active languages to the sitemap index
for language_tree_node in region.language_tree_nodes.filter(active=True):
# Only add sitemaps with actual content (empty list evaluates to False)
if get_sitemaps(region, language_tree_node.language):
sitemap_url = reverse(
"sitemap",
kwargs={
"region_slug": region.slug,
"language_slug": language_tree_node.slug,
},
)
absolute_url = f"{settings.WEBAPP_URL}{sitemap_url}"
sitemaps.append(absolute_url)
logger.debug("Sitemap index: %r", sitemaps)
return self.render_to_response({"sitemaps": sitemaps})
class SitemapView(TemplateResponseMixin, View):
"""
This view allows to generate a sitemap dynamically.
A sitemap contains the urls of multiple :class:`~integreat_cms.sitemap.sitemaps.WebappSitemap` instances, one for each content type.
It is a patched version of :func:`django.contrib.sitemaps.views.sitemap` with the following changes:
* Sitemaps dynamically queried on each request, not on the application startup
* HTTP 404 returned if sitemap is empty
* Support for pagination was dropped (only needed with more than 50000 urls per region and language)
"""
#: The template to render (see :class:`~django.views.generic.base.TemplateResponseMixin`)
template_name = "sitemap.xml"
#: The content type to use for the response (see :class:`~django.views.generic.base.TemplateResponseMixin`)
content_type = "application/xml"
def get(self, request, *args, **kwargs):
"""
This function handles a get request
:param request: The current request
:type request: ~django.http.HttpRequest
:param args: The supplied args
:type args: list
:param kwargs: The supplied keyword args (should contain ``region_slug`` and ``language_slug``)
:type kwargs: dict
:raises ~django.http.Http404: Raises a HTTP 404 if the either the region or language does not exist or is invalid
or if the sitemap is empty.
:return: The rendered template response
:rtype: ~django.template.response.TemplateResponse
"""
logger.debug("Sitemap requested with args %r and kwargs %r", args, kwargs)
# Only return a sitemap if the region is active
region = get_object_or_404(
Region, slug=kwargs.get("region_slug"), status=region_status.ACTIVE
)
# Only return a sitemap if the language is active
language = get_object_or_404(
region.language_tree_nodes,
language__slug=kwargs.get("language_slug"),
active=True,
).language
sitemaps = get_sitemaps(region, language)
# Only return a sitemap if it contains any elements
if not sitemaps:
raise Http404
# Join the lists of all urls of all sitemaps
urls = sum(
[sitemap.get_urls(site=get_current_site(request)) for sitemap in sitemaps],
[],
)
# Pick the latest last_modified if all sitemaps
last_modified = max([sitemap.latest_lastmod for sitemap in sitemaps])
logger.debug("Sitemap urls %r", urls)
response = self.render_to_response({"urlset": urls})
response["Last-Modified"] = http_date(last_modified.timestamp())
return response
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] |
bioparser/msigdb.py | dhimmel/serg-pycode | 0 | 119959 | <reponame>dhimmel/serg-pycode
import os
import csv
import data
# http://www.broadinstitute.org/gsea/downloads.jsp
abbrev_to_name = {
'c1.all': 'positional gene sets',
'c2.all': 'all curated gene sets',
'c2.cgp': 'chemical and genetic perturbations',
'c2.cp.all': 'all canonical pathways',
'c2.cp.biocarta': 'BioCarta gene sets',
'c2.cp.kegg': 'KEGG gene sets',
'c2.cp.reactome': 'Reactome gene sets',
'c3.all': 'all motif gene sets',
'c3.mir': 'microRNA targets',
'c3.tft': 'transcription factor targets',
'c4.all': 'all computational gene sets',
'c4.cgn': ' cancer gene neighborhoods',
'c4.cm': 'cancer modules',
'c5.all': 'all GO gene sets',
'c5.bp': 'GO biological processes',
'c5.cc': 'GO cellular components',
'c5.mf': 'GO molecular functions',
'c6.all': 'all oncogenic signatures gene sets',
'c7.all': 'all immunologic signatures gene sets'
}
class MSigDB(object):
def __init__(self, directory=None):
if directory is None:
directory = data.current_path('msigdb')
self.directory = directory
self.abbrev_to_name = abbrev_to_name
@staticmethod
def gmt_row_generator(path):
"""
(name, description, members)
"""
read_file = open(path)
reader = csv.reader(read_file, delimiter='\t')
for row in reader:
yield row[0], row[1], row[2:]
read_file.close()
def get_gmt_path(self, abbrev, version='v4.0', id_type='entrez'):
filename = '{}.{}.{}.gmt'.format(abbrev, version, id_type)
path = os.path.join(self.directory, filename)
return path
def gene_set_generator(self, abbrev):
identifiers_to_genes = data.Data().hgnc.identifiers_to_genes
path = self.get_gmt_path(abbrev, id_type='entrez')
for name, description, members in self.gmt_row_generator(path):
genes = identifiers_to_genes(members, id_type='entrez')
yield name, description, genes
if __name__ == '__main__':
msigdb = MSigDB()
for abbrev in abbrev_to_name.keys():
list(msigdb.gene_set_generator(abbrev))
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] |
2_Regression/ARX_Regression/empirical_id.py | abe-mart/arduino | 1 | 19291 | import numpy as np
import apm_id as arx
######################################################
# Configuration
######################################################
# number of terms
ny = 2 # output coefficients
nu = 1 # input coefficients
# number of inputs
ni = 1
# number of outputs
no = 1
# load data and parse into columns
data = np.loadtxt('data_step_test.csv',delimiter=',')
######################################################
# generate time-series model
arx.apm_id(data,ni,nu,ny)
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] |
old/ML models/SGD_Classifier.py | saisankargochhayat/doot | 0 | 145740 | <gh_stars>0
from sklearn.linear_model import SGDClassifier
# import pprint
data = []
labels = []
train_data = []
train_labels = []
test_data = []
test_labels = []
with open("../Server/sampledata.csv", 'r') as ppd:
for line in ppd:
attr = line.split(',')
data.append(attr)
with open("../Server/samplelabel.csv", 'r') as ppd:
for line in ppd:
attr = line.split(',')
labels.append(attr[0][0:len(attr[0])-1])
# with open("a_f_train.csv", 'r') as ppd:
# for line in ppd:
# attr = line.split(',')
# data.append(map(float, attr[0:31]))
# labels.append(attr[31][0:-1])
# with open("a_f_test1.csv", 'r') as ppd:
# for line in ppd:
# attr = line.split(',')
# test_data.append(map(float, attr[0:31]))
# test_labels.append(attr[31][0:-1])
#
# with open("a_f_test2.csv", 'r') as ppd:
# for line in ppd:
# attr = line.split(',')
# test_data.append(map(float, attr[0:31]))
# test_labels.append(attr[31][0:-1])
# with open("a_f_test.csv", 'r') as ppd:
# for line in ppd:
# attr = line.split(',')
# test_data.append(map(float, attr[0:31]))
# test_labels.append(attr[31][0:-1])
# with open("a_f_test3.csv", 'r') as ppd:
# for line in ppd:
# attr = line.split(',')
# test_data.append(map(float, attr[0:31]))
# test_labels.append(attr[31][0:-1])
from sklearn.cross_validation import train_test_split
train_data, test_data, train_labels, test_labels = train_test_split(data, labels, test_size = .5)
clf = SGDClassifier(loss="hinge", penalty="l2")
clf.fit(train_data,train_labels)
predictions = clf.predict(test_data)
# for i in range(len(predictions)):
# print predictions[i], test_labels[i]
#with open("data1", 'w') as _file:
# _file.write(pprint.pformat(data1))
from sklearn.metrics import accuracy_score
print(accuracy_score(test_labels, predictions))
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genhernquist/Normalisation.py | lauralwatkins/genhernquist | 2 | 108679 | <gh_stars>1-10
#!/usr/bin/env python
from astropy import units as u
from .Cumulative3D import Cumulative3D
def Normalisation(total, rs, alpha, beta, gamma):
"""
Normalisation of a generalised Hernquist model required to have a total
cumulative quantity.
INPUTS
total : total quantity enclosed (can have unit)
rs : scale radius of model (requires unit)
alpha : sharpness of transition between inner and outer
beta : outer logarithmic slope
gamma : inner logarithmic slope
"""
# make a trial normalisation with units from the total and the scale radius
trial_norm = 1*u.Quantity(total).unit/rs.unit**3
# calculate the cumulative total for the trial normalisation
trial_total = Cumulative3D(rs*1e4, trial_norm, rs, alpha, beta,
gamma)
# the normalisation for the target total is a simple rescaling
normalisation = trial_norm*total/trial_total
return normalisation
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investopedia_api/option_trade.py | kevihiiin/investopedia_simulator_api | 0 | 147400 | <filename>investopedia_api/option_trade.py
import re
import warnings
from lxml import html
from ratelimit import limits, sleep_and_retry
from investopedia_api.session_singleton import Session
from investopedia_api.trade_common import OrderType, Duration, Trade
from investopedia_api.utils import UrlHelper
class OptionTrade(Trade):
def __init__(
self,
contract,
quantity,
trade_type,
order_type=OrderType.MARKET(),
duration=Duration.GOOD_TILL_CANCELLED(),
send_email=True):
self.security_type = 'option'
self.base_url = UrlHelper.route('tradeoption')
self.submit_url = UrlHelper.route('tradeoption_submit')
super().__init__(contract.base_symbol, quantity,
trade_type, order_type, duration, send_email)
self.contract = contract
self.prepared_trade = None
@property
def contract(self):
return self._contract
@contract.setter
def contract(self, contract):
tt = 's'
if self.trade_type == 'BUY_TO_OPEN':
tt = 'b'
self.query_params.update({
'ap': contract.ask,
'bid': contract.bid,
'sym': contract.contract_name,
't': contract.contract_type.lower()[0],
's': contract.strike_price,
'msym': contract.raw['Month'],
'tt': tt
})
self._contract = contract
@sleep_and_retry
@limits(calls=6, period=30)
def _get_max_shares(self):
if self.form_token is None:
self.refresh_form_token()
uri = UrlHelper.set_query(self.base_url, self.query_params)
self.form_data['isShowMax'] = 1
resp = Session().post(uri, data=self.form_data)
tree = html.fromstring(resp.text)
self.form_data['isShowMax'] = 0
self.refresh_form_token(tree)
fon = lambda x: x[0] if len(x)> 0 else None
try:
xpath1 = '//div[@id="limitDiv"]/span[@id="limitationLabel"]/text()'
xpath2 = '//div[@id="limitDiv"]/span/text()'
text = fon(tree.xpath(xpath1)) or fon(tree.xpath(xpath2))
shares_match = re.search(
r'maximum\s*of\s*(\d+)\s*(?:shares|option)', text)
return int(shares_match.group(1))
except Exception as e:
error = e
warnings.warn("Unable to determine max shares: %s" % e)
return
return 0
def go_to_preview(self):
session = Session()
self.form_data.update({'btnReview': 'Preview+Order', 'isShowMax': 0})
uri = UrlHelper.set_query(UrlHelper.route(
'tradeoption'), self.query_params)
return session.post(uri, data=self.form_data)
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yt_concate/pipeline/steps/preflight.py | ThatMrWayne/yout_concate | 0 | 195297 | <filename>yt_concate/pipeline/steps/preflight.py
import logging
from yt_concate.pipeline.steps.step import Step
class Preflight(Step):
def process(self, inputs, utils, data):
logger = logging.getLogger('record')
logger.info('In preflight.')
utils.create_downloads_dirs()
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tests/test_simpleflow/test_format.py | mookerji/simpleflow | 0 | 147817 | import json
import os
import unittest
import random
import boto
from moto import mock_s3
from simpleflow import constants, format
from simpleflow.storage import push_content
@mock_s3
class TestFormat(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
# reset jumbo fields bucket so most tests will have jumbo fields disabled
os.environ["SIMPLEFLOW_JUMBO_FIELDS_BUCKET"] = ""
def setup_jumbo_fields(self, bucket):
os.environ["SIMPLEFLOW_JUMBO_FIELDS_BUCKET"] = bucket
self.conn = boto.connect_s3()
self.conn.create_bucket(bucket.split("/")[0])
def test_encode_none(self):
self.assertEquals(
format.encode(None, 1),
None
)
def test_encode_smaller(self):
MAX_LENGTH = random.randint(10, 1000)
message = 'A' * (MAX_LENGTH // 2)
self.assertEquals(
format.encode(message, MAX_LENGTH),
message,
)
def test_encode_longer(self):
MAX_LENGTH = random.randint(10, 1000)
message = 'A' * 1000
with self.assertRaisesRegexp(ValueError, "Message too long"):
format.encode(message, MAX_LENGTH)
def test_identity_doesnt_use_jumbo_fields(self):
self.setup_jumbo_fields("jumbo-bucket")
message = 'A' * (constants.MAX_RESULT_LENGTH * 2)
with self.assertRaisesRegexp(ValueError, "Message too long"):
format.identity(message)
def test_jumbo_fields_encoding_without_directory(self):
self.setup_jumbo_fields("jumbo-bucket")
message = 'A' * 64000
encoded = format.result(message)
# => simpleflow+s3://jumbo-bucket/f6ea95a<...>ea3 64002
assert encoded.startswith("simpleflow+s3://jumbo-bucket/")
self.assertEquals(encoded.split()[1], "64002")
key = encoded.split()[0].replace("simpleflow+s3://jumbo-bucket/", "")
self.assertEquals(
self.conn.get_bucket("jumbo-bucket").get_key(key).get_contents_as_string(encoding='utf-8'),
json.dumps(message),
)
def test_jumbo_fields_encoding_with_directory(self):
self.setup_jumbo_fields("jumbo-bucket/with/subdir")
message = 'A' * 64000
encoded = format.result(message)
# => simpleflow+s3://jumbo-bucket/with/subdir/f6ea95a<...>ea3 64002
assert encoded.startswith("simpleflow+s3://jumbo-bucket/with/subdir/")
self.assertEquals(encoded.split()[1], "64002")
key = encoded.split()[0].replace("simpleflow+s3://jumbo-bucket/", "")
self.assertEquals(
self.conn.get_bucket("jumbo-bucket").get_key(key).get_contents_as_string(encoding='utf-8'),
json.dumps(message),
)
def test_jumbo_fields_with_directory_strip_trailing_slash(self):
self.setup_jumbo_fields("jumbo-bucket/with/subdir/")
message = 'A' * 64000
encoded = format.result(message)
assert not encoded.startswith("simpleflow+s3://jumbo-bucket/with/subdir//")
def test_jumbo_fields_encoding_raise_if_encoded_form_overflows_thresholds(self):
# 'reason' field is limited to 256 chars for instance
self.setup_jumbo_fields("jumbo-bucket/with/a/very/long/name/" + "a" * 256)
message = 'A' * 500
with self.assertRaisesRegexp(ValueError, "Jumbo field signature is longer than"):
format.reason(message)
def test_decode(self):
self.setup_jumbo_fields("jumbo-bucket")
push_content("jumbo-bucket", "abc", "decoded jumbo field yay!")
cases = [
[None, None],
["foo bar baz", "foo bar baz"],
['"a string"', "a string"],
['[1, 2]', [1, 2]],
["simpleflow+s3://jumbo-bucket/abc 24", "decoded jumbo field yay!"],
]
for case in cases:
self.assertEquals(case[1], format.decode(case[0]))
def test_decode_no_parse_json(self):
self.setup_jumbo_fields("jumbo-bucket")
push_content("jumbo-bucket", "abc", "decoded jumbo field yay!")
cases = [
[None, None],
["foo bar baz", "foo bar baz"],
['"a string"', '"a string"'],
['[1, 2]', "[1, 2]"],
["simpleflow+s3://jumbo-bucket/abc 24", "decoded jumbo field yay!"],
]
for case in cases:
self.assertEquals(case[1], format.decode(case[0], parse_json=False))
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] |
geometry_utils/tests/test_bound_box.py | NOAA-ORR-ERD/geometry_utils | 0 | 13482 | #!/usr/bin/env python
"""
Test code for the BBox Object
"""
import numpy as np
import pytest
from geometry_utils.bound_box import (BBox,
asBBox,
NullBBox,
InfBBox,
fromBBArray,
from_points,
)
class TestConstructors():
def test_creates(self):
B = BBox(((0, 0), (5, 5)))
assert isinstance(B, BBox)
def test_type(self):
B = np.array(((0, 0), (5, 5)))
assert not isinstance(B, BBox)
def testDataType(self):
B = BBox(((0, 0), (5, 5)))
assert B.dtype == np.float
def testShape(self):
B = BBox((0, 0, 5, 5))
assert B.shape == (2, 2)
def testShape2(self):
with pytest.raises(ValueError):
BBox((0, 0, 5))
def testShape3(self):
with pytest.raises(ValueError):
BBox((0, 0, 5, 6, 7))
def testArrayConstruction(self):
A = np.array(((4, 5), (10, 12)), np.float_)
B = BBox(A)
assert isinstance(B, BBox)
def testMinMax(self):
with pytest.raises(ValueError):
BBox((0, 0, -1, 6))
def testMinMax2(self):
with pytest.raises(ValueError):
BBox((0, 0, 1, -6))
def testMinMax3(self):
# OK to have a zero-sized BB
B = BBox(((0, 0), (0, 5)))
assert isinstance(B, BBox)
def testMinMax4(self):
# OK to have a zero-sized BB
B = BBox(((10., -34), (10., -34.0)))
assert isinstance(B, BBox)
def testMinMax5(self):
# OK to have a tiny BB
B = BBox(((0, 0), (1e-20, 5)))
assert isinstance(B, BBox)
def testMinMax6(self):
# Should catch tiny difference
with pytest.raises(ValueError):
BBox(((0, 0), (-1e-20, 5)))
class TestAsBBox():
def testPassThrough(self):
B = BBox(((0, 0), (5, 5)))
C = asBBox(B)
assert B is C
def testPassThrough2(self):
B = ((0, 0), (5, 5))
C = asBBox(B)
assert B is not C
def testPassArray(self):
# Different data type
A = np.array(((0, 0), (5, 5)))
C = asBBox(A)
assert A is not C
def testPassArray2(self):
# same data type -- should be a view
A = np.array(((0, 0), (5, 5)), np.float_)
C = asBBox(A)
A[0, 0] = -10
assert C[0, 0] == A[0, 0]
class TestIntersect():
def testSame(self):
B = BBox(((-23.5, 456), (56, 532.0)))
C = BBox(((-23.5, 456), (56, 532.0)))
assert B.Overlaps(C)
def testUpperLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((0, 12), (10, 32.0)))
assert B.Overlaps(C)
def testUpperRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((12, 12), (25, 32.0)))
assert B.Overlaps(C)
def testLowerRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((12, 5), (25, 15)))
assert B.Overlaps(C)
def testLowerLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 5), (8.5, 15)))
assert B.Overlaps(C)
def testBelow(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 5), (8.5, 9.2)))
assert not B.Overlaps(C)
def testAbove(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 25.001), (8.5, 32)))
assert not B.Overlaps(C)
def testLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((4, 8), (4.95, 32)))
assert not B.Overlaps(C)
def testRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((17.1, 8), (17.95, 32)))
assert not B.Overlaps(C)
def testInside(self):
B = BBox(((-15, -25), (-5, -10)))
C = BBox(((-12, -22), (-6, -8)))
assert B.Overlaps(C)
def testOutside(self):
B = BBox(((-15, -25), (-5, -10)))
C = BBox(((-17, -26), (3, 0)))
assert B.Overlaps(C)
def testTouch(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((15, 8), (17.95, 32)))
assert B.Overlaps(C)
def testCorner(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((15, 25), (17.95, 32)))
assert B.Overlaps(C)
def testZeroSize(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((15, 25), (15, 25)))
assert B.Overlaps(C)
def testZeroSize2(self):
B = BBox(((5, 10), (5, 10)))
C = BBox(((15, 25), (15, 25)))
assert not B.Overlaps(C)
def testZeroSize3(self):
B = BBox(((5, 10), (5, 10)))
C = BBox(((0, 8), (10, 12)))
assert B.Overlaps(C)
def testZeroSize4(self):
B = BBox(((5, 1), (10, 25)))
C = BBox(((8, 8), (8, 8)))
assert B.Overlaps(C)
class TestEquality():
def testSame(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = BBox(((1.0, 2.0), (5., 10.)))
assert B == C
def testIdentical(self):
B = BBox(((1.0, 2.0), (5., 10.)))
assert B == B
def testNotSame(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = BBox(((1.0, 2.0), (5., 10.1)))
assert not B == C
def testWithArray(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = np.array(((1.0, 2.0), (5., 10.)))
assert B == C
def testWithArray2(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = np.array(((1.0, 2.0), (5., 10.)))
assert C == B
def testWithArray3(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = np.array(((1.01, 2.0), (5., 10.)))
assert not C == B
class TestInside():
def testSame(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = BBox(((1.0, 2.0), (5., 10.)))
assert B.Inside(C)
def testPoint(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = BBox(((3.0, 4.0), (3.0, 4.0)))
assert B.Inside(C)
def testPointOutside(self):
B = BBox(((1.0, 2.0), (5., 10.)))
C = BBox(((-3.0, 4.0), (0.10, 4.0)))
assert not B.Inside(C)
def testUpperLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((0, 12), (10, 32.0)))
assert not B.Inside(C)
def testUpperRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((12, 12), (25, 32.0)))
assert not B.Inside(C)
def testLowerRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((12, 5), (25, 15)))
assert not B.Inside(C)
def testLowerLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 5), (8.5, 15)))
assert not (B.Inside(C))
def testBelow(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 5), (8.5, 9.2)))
assert not (B.Inside(C))
def testAbove(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((-10, 25.001), (8.5, 32)))
assert not (B.Inside(C))
def testLeft(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((4, 8), (4.95, 32)))
assert not (B.Inside(C))
def testRight(self):
B = BBox(((5, 10), (15, 25)))
C = BBox(((17.1, 8), (17.95, 32)))
assert not (B.Inside(C))
class TestPointInside():
def testPointIn(self):
B = BBox(((1.0, 2.0), (5., 10.)))
P = (3.0, 4.0)
assert (B.PointInside(P))
def testUpperLeft(self):
B = BBox(((5, 10), (15, 25)))
P = (4, 30)
assert not (B.PointInside(P))
def testUpperRight(self):
B = BBox(((5, 10), (15, 25)))
P = (16, 30)
assert not (B.PointInside(P))
def testLowerRight(self):
B = BBox(((5, 10), (15, 25)))
P = (16, 4)
assert not (B.PointInside(P))
def testLowerLeft(self):
B = BBox(((5, 10), (15, 25)))
P = (-10, 5)
assert not (B.PointInside(P))
def testBelow(self):
B = BBox(((5, 10), (15, 25)))
P = (10, 5)
assert not (B.PointInside(P))
def testAbove(self):
B = BBox(((5, 10), (15, 25)))
P = (10, 25.001)
assert not (B.PointInside(P))
def testLeft(self):
B = BBox(((5, 10), (15, 25)))
P = (4, 12)
assert not (B.PointInside(P))
def testRight(self):
B = BBox(((5, 10), (15, 25)))
P = (17.1, 12.3)
assert not (B.PointInside(P))
def testPointOnTopLine(self):
B = BBox(((1.0, 2.0), (5., 10.)))
P = (3.0, 10.)
assert (B.PointInside(P))
def testPointLeftTopLine(self):
B = BBox(((1.0, 2.0), (5., 10.)))
P = (-3.0, 10.)
assert not (B.PointInside(P))
def testPointOnBottomLine(self):
B = BBox(((1.0, 2.0), (5., 10.)))
P = (3.0, 5.)
assert (B.PointInside(P))
def testPointOnLeft(self):
B = BBox(((-10., -10.), (-1.0, -1.0)))
P = (-10, -5.)
assert (B.PointInside(P))
def testPointOnRight(self):
B = BBox(((-10., -10.), (-1.0, -1.0)))
P = (-1, -5.)
assert (B.PointInside(P))
def testPointOnBottomRight(self):
B = BBox(((-10., -10.), (-1.0, -1.0)))
P = (-1, -10.)
assert (B.PointInside(P))
class Test_from_points():
def testCreate(self):
Pts = np.array(((5, 2), (3, 4), (1, 6)), np.float64)
B = from_points(Pts)
assert (B[0, 0] == 1.0 and
B[0, 1] == 2.0 and
B[1, 0] == 5.0 and
B[1, 1] == 6.0)
def testCreateInts(self):
Pts = np.array(((5, 2), (3, 4), (1, 6)))
B = from_points(Pts)
assert (B[0, 0] == 1.0 and
B[0, 1] == 2.0 and
B[1, 0] == 5.0 and
B[1, 1] == 6.0)
def testSinglePoint(self):
Pts = np.array((5, 2), np.float_)
B = from_points(Pts)
assert (B[0, 0] == 5. and
B[0, 1] == 2.0 and
B[1, 0] == 5. and
B[1, 1] == 2.0)
def testListTuples(self):
Pts = [(3, 6.5), (13, 43.2), (-4.32, -4), (65, -23), (-0.0001,
23.432)]
B = from_points(Pts)
assert (B[0, 0] == -4.32 and
B[0, 1] == -23.0 and
B[1, 0] == 65.0 and
B[1, 1] == 43.2)
class TestMerge():
A = BBox(((-23.5, 456), (56, 532.0)))
B = BBox(((-20.3, 460), (54, 465))) # B should be completely inside A
C = BBox(((-23.5, 456), (58, 540.))) # up and to the right or A
D = BBox(((-26.5, 12), (56, 532.0)))
def testInside(self):
C = self.A.copy()
C.Merge(self.B)
assert (C == self.A)
def testFullOutside(self):
C = self.B.copy()
C.Merge(self.A)
assert (C == self.A)
def testUpRight(self):
A = self.A.copy()
A.Merge(self.C)
assert (A[0] == self.A[0] and A[1] == self.C[1])
def testDownLeft(self):
A = self.A.copy()
A.Merge(self.D)
assert (A[0] == self.D[0] and A[1] == self.A[1])
class TestWidthHeight():
B = BBox(((1.0, 2.0), (5., 10.)))
def testWidth(self):
assert (self.B.Width == 4.0)
def testWidth2(self):
assert (self.B.Height == 8.0)
def testSetW(self):
with pytest.raises(AttributeError):
self.B.Height = 6
def testSetH(self):
with pytest.raises(AttributeError):
self.B.Width = 6
class TestCenter():
B = BBox(((1.0, 2.0), (5., 10.)))
def testCenter(self):
assert ((self.B.Center == (3.0, 6.0)).all())
def testSetCenter(self):
with pytest.raises(AttributeError):
self.B.Center = (6, 5)
class TestBBarray():
BBarray = np.array((((-23.5, 456), (56, 532.0)), ((-20.3, 460),
(54, 465)), ((-23.5, 456), (58, 540.)), ((-26.5,
12), (56, 532.0))), dtype=np.float)
BB = asBBox(((-26.5, 12.), (58., 540.)))
def testJoin(self):
BB = fromBBArray(self.BBarray)
assert BB == self.BB
class TestNullBBox():
B1 = NullBBox()
B2 = NullBBox()
B3 = BBox(((1.0, 2.0), (5., 10.)))
def testValues(self):
assert (np.alltrue(np.isnan(self.B1)))
def testIsNull(self):
assert (self.B1.IsNull)
def testEquals(self):
assert ((self.B1 == self.B2) is True)
def testNotEquals(self):
assert not self.B1 == self.B3
def testNotEquals2(self):
assert not self.B3 == self.B1
def testMerge(self):
C = self.B1.copy()
C.Merge(self.B3)
assert C == self.B3, 'merge failed, got: %s' % C
def testOverlaps(self):
assert self.B1.Overlaps(self.B3) is False
def testOverlaps2(self):
assert self.B3.Overlaps(self.B1) is False
class TestInfBBox():
B1 = InfBBox()
B2 = InfBBox()
B3 = BBox(((1.0, 2.0), (5., 10.)))
NB = NullBBox()
def testValues(self):
assert (np.alltrue(np.isinf(self.B1)))
# def testIsNull(self):
# assert ( self.B1.IsNull )
def testEquals(self):
assert self.B1 == self.B2
def testNotEquals(self):
assert not self.B1 == self.B3
def testNotEquals2(self):
assert self.B1 != self.B3
def testNotEquals3(self):
assert not self.B3 == self.B1
def testMerge(self):
C = self.B1.copy()
C.Merge(self.B3)
assert C == self.B2, 'merge failed, got: %s' % C
def testMerge2(self):
C = self.B3.copy()
C.Merge(self.B1)
assert C == self.B1, 'merge failed, got: %s' % C
def testOverlaps(self):
assert (self.B1.Overlaps(self.B2) is True)
def testOverlaps2(self):
assert (self.B3.Overlaps(self.B1) is True)
def testOverlaps3(self):
assert (self.B1.Overlaps(self.B3) is True)
def testOverlaps4(self):
assert (self.B1.Overlaps(self.NB) is True)
def testOverlaps5(self):
assert (self.NB.Overlaps(self.B1) is True)
class TestSides():
B = BBox(((1.0, 2.0), (5., 10.)))
def testLeft(self):
assert self.B.Left == 1.0
def testRight(self):
assert self.B.Right == 5.0
def testBottom(self):
assert self.B.Bottom == 2.0
def testTop(self):
assert self.B.Top == 10.0
class TestAsPoly():
B = BBox(((5, 0), (10, 20)))
corners = np.array([(5., 0.), (5., 20.), (10., 20.), (10., 0.)],
dtype=np.float64)
def testCorners(self):
print(self.B.AsPoly())
assert np.array_equal(self.B.AsPoly(), self.corners)
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] |
vfp2py/fxp_read.py | wroldwiedbwe/vfp2py | 36 | 1602501 | # coding=utf-8
from __future__ import absolute_import, division, print_function
import io
import sys
import os
import struct
from math import floor, log10
from datetime import datetime, timedelta
from collections import OrderedDict
import re
import errno
import dbf
HEADER_SIZE = 0x29
FOOTER_ENTRY_SIZE = 0x19
ENCRYPTED_IDENTIFIER = b'\xfe\xf2\xee'
IDENTIFIER = b'\xfe\xf2\xff'
def checksum_calc(string):
chunk = string[0]
chunka = (chunk & 0xF0) >> 4
chunkb = (chunk & 0x0F) >> 0
chunk = string[1]
chunkc = (chunk & 0xF0) >> 4
chunkd = (chunk & 0x0F) >> 0
for chunk in string:
chunka ^= (chunk & 0xF0) >> 4
chunkb ^= (chunk & 0x0F) >> 0
chunk = (chunka << 9) + ((chunka ^ chunkb) << 5)
chunka, chunkb, chunkc, chunkd = (
chunka ^ chunkb ^ chunkc ^ ((chunk & 0xF000) >> 12),
chunkd ^ ((chunk & 0x0F00) >> 8),
chunka ^ ((chunk & 0x00F0) >> 4),
chunka ^ chunkb ^ ((chunk & 0x000F) >> 0),
)
return (chunka << 12) + (chunkb << 8) + (chunkc << 4) + (chunkd << 0)
class BinaryFix(object):
def __init__(self, name, open_params):
self.fid = io.open(name, open_params)
def read(self, length=None):
return bytearray(self.fid.read(length))
def write(self, string):
self.fid.write(string)
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
self.fid.close()
def seek(self, pos, start_pos=0):
self.fid.seek(pos, start_pos)
def tell(self):
return self.fid.tell()
def open(name, open_params):
return BinaryFix(name, open_params)
class FXPName(object):
def __init__(self, name):
self.name = str(name)
def __repr__(self):
return self.name
class FXPAlias(FXPName):
def __repr__(self):
return self.name + '.'
class FXPNumber(object):
def __init__(self, number, digits, dec_digits=0):
self.number = number
digits -= dec_digits
digits = max(digits, 0)
self.format_string = '{{:0{}.{}f}}'.format(digits, dec_digits)
def __repr__(self):
return self.format_string.format(self.number)
class FXPCurrency(object):
def __init__(self, number, digits, dec_digits=0):
self.number = number
self.dec_digits = dec_digits
digits -= dec_digits
digits = max(digits, 0)
self.digits = digits
def __repr__(self):
base = 10**self.dec_digits
return '${}.{}'.format(self.number // base, self.number % base)
def round_sig(x, sig):
if x == 0:
return 0.
return round(x, sig-int(floor(log10(abs(x))))-1)
def read_string(fid, *args):
return fid.read(read_ushort(fid)).decode('ISO-8859-1')
def read_single_quoted_string(fid, *args):
return FXPName("'{}'".format(read_string(fid)))
def read_double_quoted_string(fid, *args):
return FXPName('"{}"'.format(read_string(fid)))
def read_int8(fid, *args):
digits = fid.read(1)[0]
return FXPNumber(fid.read(1)[0], digits)
def read_int16(fid, *args):
digits = fid.read(1)[0]
return FXPNumber(read_short(fid), digits)
def read_int32(fid, *args):
digits = fid.read(1)[0]
return FXPNumber(read_int(fid), digits)
def read_double(fid, *args):
digits = fid.read(1)[0] - 1
dec_digits = fid.read(1)[0]
return FXPNumber(struct.unpack('<d', fid.read(8))[0], digits, dec_digits)
def read_float(fid, *args):
return FXPNumber(struct.unpack('<i', fid.read(4))[0] / 65536., 10, 4)
def read_currency(fid, *args):
digits = fid.read(1)[0] - 1
dec_digits = fid.read(1)[0]
return FXPCurrency(struct.unpack('<q', fid.read(8))[0], digits, dec_digits)
def read_datetimeexpr(fid):
days = struct.unpack('<d', fid.read(8))[0]
if not days:
return None
days = timedelta(days - 2440588)
days=timedelta(seconds=round(days.total_seconds()))
return datetime.utcfromtimestamp(0) + days
def read_datetime(fid, *args):
dt = read_datetimeexpr(fid)
if not dt:
return '{ / / }'
return '{{^{}}}'.format(dt)
def read_date(fid, *args):
dt = read_datetimeexpr(fid)
if not dt:
return '{ / / }'
return '{{^{}}}'.format(dt.date())
def read_alias(fid, names, *args):
return FXPAlias(names[read_ushort(fid)])
def read_special_alias(fid, *args):
return FXPAlias(SPECIAL_NAMES[fid.read(1)[0]])
def read_system_alias(fid, *args):
return FXPAlias(SYSTEM_NAMES[fid.read(1)[0]])
def read_system_name(fid, *args):
return FXPName(SYSTEM_NAMES[fid.read(1)[0]])
def read_menu_system_name(fid, *args):
return FXPName(MENU_SYSTEM_NAMES[fid.read(1)[0]])
def read_name(fid, names):
return FXPName(names[read_ushort(fid)])
def read_raw(fid, length):
return ' '.join('{:02x}'.format(d) for d in fid.read(length))
def read_next_code(fid, names, expr=None):
if expr is None:
expr = []
codeval = fid.read(1)[0]
if codeval == END_EXPR:
return codeval
if codeval == PARAMETER_MARK:
code = codeval
elif codeval == SQL_SUBQUERY:
length = read_ushort(fid)
final = fid.tell() + length
fid.read(1)
code = FXPName('(SELECT {})'.format(parse_subline(fid, length, final, names, [])))
elif codeval in FUNCTIONS:
code = FUNCTIONS[codeval]
if codeval in (0xE5, 0xF6):
code = code(fid, names)
while expr and type(expr[-1]) is FXPAlias:
code = FXPName(repr(expr.pop()) + repr(code))
code = repr(code)
elif callable(code):
code = code(fid)
parameters = []
while expr:
parameter = expr.pop()
if parameter == PARAMETER_MARK:
break
parameters.insert(0, parameter)
code += '({})'.format(', '.join(repr(p) for p in parameters))
if codeval == 0xE5:
code = FXPAlias(code)
else:
code = FXPName(code)
elif codeval in OPERATORS:
code = OPERATORS[codeval]
if code[1] == 0:
return read_next_code(fid, names, expr)
elif code[1] > 0:
parameters = [p for p in reversed([expr.pop() for i in range(code[1])])]
if len(parameters) == 1:
code = FXPName('({} {})'.format(code[0], repr(parameters[0])))
else:
code = FXPName('({})'.format((' ' + code[0] + ' ').join(repr(p) for p in parameters)))
else:
code = code[0]
elif codeval in VALUES:
code = VALUES[codeval]
if callable(code):
code = code(fid, names)
if codeval in (0xF0, 0xF1):
return read_next_code(fid, names, expr)
if type(code) is FXPName:
while expr and type(expr[-1]) is FXPAlias:
code = FXPName(repr(expr.pop()) + repr(code))
elif type(code) is FXPAlias:
pass
elif type(code) in (float, int):
code = FXPName(repr(code))
else:
code = FXPName(code)
else:
raise KeyError(hex(codeval))
return code
def read_expr(fid, names, *args):
expr = []
while True:
code = read_next_code(fid, names, expr)
if code == END_EXPR:
break
if code:
expr.append(code)
if len(expr) == 1:
return expr[0]
return expr
def read_setcode(fid, length):
return ['SET ' + SETCODES[fid.read(1)[0]]]
def read_text(fid, length):
length = read_ushort(fid)
return [''.join(chr(x) for x in fid.read(length))]
class Token(object):
def __init__(self, tokenstr, tokenval):
self.str = tokenstr
self.val = tokenval
def __repr__(self):
return repr('{}({})'.format(self.str, self.val))
END_EXPR = 0xFD;
PARAMETER_MARK = 0x43;
SQL_SUBQUERY = 0xE8
SPECIAL_NAMES = {
0x0D: 'M',
}
SYSTEM_NAMES = {
0x00: '_ALIGNMENT',
0x05: '_PAGENO',
0x19: '_DBLCLICK',
0x1A: '_CALCVALUE',
0x1B: '_CALCMEM',
0x1C: '_DIARYDATE',
0x1D: '_CLIPTEXT',
0x1E: '_TEXT',
0x1F: '_PRETEXT',
0x20: '_TALLY',
0x21: '_CUROBJ',
0x22: '_MLINE',
0x23: '_THROTTLE',
0x24: '_GENMENU',
0x2F: '_STARTUP',
0x30: '_TRANSPORT',
0x31: '_BEAUTIFY',
0x32: '_DOS',
0x33: '_MAC',
0x34: '_UNIX',
0x35: '_WINDOWS',
0x36: '_SPELLCHK',
0x37: '_SHELL',
0x39: '_SCREEN',
0x3A: '_BUILDER',
0x3B: '_CONVERTER',
0x3C: '_WIZARD',
0x3D: '_TRIGGERLEVEL',
0x3E: '_ASCIICOLS',
0x3F: '_ASCIIROWS',
0x40: '_BROWSER',
0x41: '_SCCTEXT',
0x42: '_COVERAGE',
0x43: '_VFP',
0x44: '_GALLERY',
0x45: '_GETEXPR',
0x46: '_INCLUDE',
0x47: '_GENHTML',
0x49: '_SAMPLES',
0x4A: '_TASKLIST',
0x4B: '_ObjectBrowser',
0x4D: '_FOXCODE',
0x4E: '_FoxTask',
0x4F: '_CODESENSE',
0x50: '_INCSEEK',
0x51: '_PAGETOTAL',
0x52: '_FOXREF',
0x53: '_TOOLBOX',
0x54: '_TASKPANE',
0x55: '_REPORTBUILDER',
0x56: '_REPORTPREVIEW',
0x57: '_REPORTOUTPUT',
}
MENU_SYSTEM_NAMES = {
0x02: '_MSYSMENU',
0x03: '_MSM_SYSTM',
0x04: '_MSM_FILE',
0x05: '_MSM_EDIT',
0x08: '_MSM_PROG',
0x09: '_MSM_WINDO',
0x0A: '_MSM_VIEW',
0x0B: '_MSM_TOOLS',
0x0D: '_MSYSTEM',
0x10: '_MST_HPSCH',
0x12: '_MST_MACRO',
0x13: '_MST_SP100',
0x1B: '_MST_SP200',
0x1E: '_MST_TECHS',
0x1F: '_MST_ABOUT',
0x22: '_MST_VFPWEB',
0x23: '_MFILE',
0x24: '_MFI_NEW',
0x25: '_MFI_OPEN',
0x26: '_MFI_CLOSE',
0x27: '_MFI_CLALL',
0x28: '_MFI_SP100',
0x29: '_MFI_SAVE',
0x2A: '_MFI_SAVAS',
0x2B: '_MFI_REVRT',
0x2C: '_MFI_SP200',
0x2F: '_MFI_SYSPRINT',
0x31: '_MFI_SP300',
0x32: '_MFI_QUIT',
0x33: '_MFI_PREVU',
0x34: '_MFI_PGSET',
0x35: '_MFI_IMPORT',
0x36: '_MFI_EXPORT',
0x37: '_MFI_SP400',
0x38: '_MFI_SEND',
0x39: '_MEDIT',
0x3A: '_MED_UNDO',
0x3B: '_MED_REDO',
0x3C: '_MED_SP100',
0x3D: '_MED_CUT',
0x3E: '_MED_COPY',
0x3F: '_MED_PASTE',
0x40: '_MED_PSTLK',
0x41: '_MED_CLEAR',
0x42: '_MED_SP200',
0x43: '_MED_INSOB',
0x44: '_MED_OBJ',
0x45: '_MED_LINK',
0x47: '_MED_SP300',
0x48: '_MED_SLCTA',
0x49: '_MED_SP400',
0x4A: '_MED_GOTO',
0x4B: '_MED_FIND',
0x4D: '_MED_REPL',
0x4F: '_MED_SP500',
0x50: '_MED_BEAUT',
0x51: '_MED_PREF',
0x70: '_MPROG',
0x71: '_MPR_DO',
0x72: '_MPR_SP100',
0x73: '_MPR_CANCL',
0x74: '_MPR_RESUM',
0x76: '_MPR_COMPL',
0x7C: '_MPR_SUSPEND',
0x7D: '_MWINDOW',
0x7E: '_MWI_ARRAN',
0x7F: '_MWI_HIDE',
0x82: '_MWI_CLEAR',
0x83: '_MWI_SP100',
0x88: '_MWI_ROTAT',
0x8A: '_MWI_SP200',
0x8B: '_MWI_CMD',
0x8C: '_MWI_VIEW',
0x8D: '_MVI_TOOLB',
0x8E: '_MVIEW',
0x90: '_MTOOLS',
0x91: '_MTL_WZRDS',
0x92: '_MTL_SP100',
0x93: '_MTL_SP200',
0x94: '_MTL_SP300',
0x95: '_MTL_SP400',
0x96: '_MTL_OPTNS',
0x97: '_MTL_BROWSER',
0x98: '_MTI_FOXCODE',
0x99: '_MTL_DEBUGGER',
0x9A: '_MTI_TRACE',
0x9E: '_MTI_LOCALS',
0x9F: '_MTI_DBGOUT',
0xA0: '_MTI_CALLSTACK',
0xC4: '_MSM_TEXT',
0xE6: '_MST_MSDNS',
0xED: '_MTL_GALLERY',
0xEE: '_MTL_COVERAGE',
0xEF: '_MTI_TASKLIST',
0xF1: '_MTI_DOCVIEW',
0xF2: '_MTI_BREAKPOINT',
0xF4: '_MED_LISTMEMBERS',
0xF5: '_MED_QUICKINFO',
0xF6: '_MED_BKMKS',
0xFD: '_MWI_CASCADE',
0xFE: '_MWI_DOCKABLE',
}
COMMANDS = {
#Commands are identified by a single byte as shown in the following list:
0x00: 'SELECT',
0x01: lambda fid, length: ['RAW CODE: ' + fid.read(length).decode('ISO-8859-1')],
0x02: '?',
0x03: '??',
0x04: '@',
0x05: 'ACCEPT',
0x06: 'APPEND',
0x07: 'ASSIST',
0x08: 'AVERAGE',
0x09: 'BROWSE',
0x0A: 'CALL',
0x0B: 'CANCEL',
0x0C: 'CASE',
0x0D: 'CHANGE',
0x0E: 'CLEAR',
0x0F: 'CLOSE',
0x10: 'CONTINUE',
0x11: 'COPY',
0x12: 'COUNT',
0x13: 'CREATE',
0x14: 'DELETE',
0x15: 'DIMENSION',
0x16: 'DIR',
0x17: 'DISPLAY',
0x18: 'DO',
0x19: 'EDIT',
0x1A: 'EJECT',
0x1B: 'ELSE',
0x1C: 'ENDCASE',
0x1D: 'ENDDO',
0x1E: 'ENDIF',
0x1F: 'ENDTEXT',
0x20: 'ERASE',
0x21: 'EXIT',
0x22: 'FIND',
0x23: 'GO',
0x24: 'HELP',
0x25: 'IF',
0x26: 'INDEX',
0x27: 'INPUT',
0x28: 'INSERT',
0x29: 'JOIN',
0x2A: 'LABEL',
0x2B: 'LIST',
0x2C: 'LOAD',
0x2D: 'LOCATE',
0x2E: 'LOOP',
0x2F: 'MODIFY',
0x30: lambda fid, length: ['NOTE'] + [fid.read(length).decode('ISO-8859-1')],#'NOTE',
0x31: 'ON',
0x32: 'OTHERWISE',
0x33: 'PACK',
0x34: 'PARAMETERS',
0x35: 'PRIVATE',
0x36: 'PROCEDURE',
0x37: 'PUBLIC',
0x38: 'QUIT',
0x39: 'READ',
0x3A: 'RECALL',
0x3B: 'REINDEX',
0x3C: 'RELEASE',
0x3D: 'RENAME',
0x3E: 'REPLACE',
0x3F: 'REPORT',
0x40: 'RESTORE',
0x41: 'RESUME',
0x42: 'RETURN',
0x43: 'RUN',
0x44: 'SAVE',
0x45: 'SEEK',
0x46: 'SELECT',
0x47: read_setcode,
0x48: 'SKIP',
0x49: 'SORT',
0x4A: 'STORE',
0x4B: 'SUM',
0x4C: 'SUSPEND',
0x4D: 'TEXT',
0x4E: 'TOTAL',
0x4F: 'TYPE',
0x50: 'UPDATE',
0x51: 'USE',
0x52: 'WAIT',
0x53: 'ZAP',
0x54: lambda fid, length: [], #variable assignment
0x55: 'ENDPROC\n',
0x56: 'EXPORT',
0x57: 'IMPORT',
0x58: 'RETRY',
0x5A: 'UNLOCK',
0x5B: 'FLUSH',
0x5C: 'KEYBOARD',
0x5D: 'MENU',
0x5E: 'SCATTER',
0x5F: 'GATHER',
0x60: 'SCROLL',
0x68: 'CREATE',
0x69: 'ALTER',
0x6A: 'DROP',
0x6F: 'SELECT',
0x70: 'UPDATE',
0x71: 'DELETE',
0x72: 'INSERT',
0x73: 'DEFINE',
0x74: 'ACTIVATE',
0x75: 'DEACTIVATE',
0x76: 'PRINTJOB',
0x77: 'ENDPRINTJOB',
0x79: '???',
0x7A: 'MOVE',
0x7B: 'ON', #CLEAR ON event
0x7C: 'DECLARE',
0x7D: 'CALCULATE',
0x7E: 'SCAN',
0x7F: 'ENDSCAN',
0x80: 'SHOW',
0x81: 'PLAY',
0x82: 'GETEXPR',
0x83: 'COMPILE',
0x84: 'FOR',
0x85: 'ENDFOR',
0x86: '=', #expression,
0x87: 'HIDE',
0x89: 'SIZE',
0x8A: 'PUSH',
0x8B: 'POP',
0x8C: 'ZOOM',
0x8D: '\\',
0x8E: '\\\\',
0x8F: 'BUILD',
0x90: 'EXTERNAL',
0x93: 'BLANK',
0x95: 'OPEN',
0x96: 'ADD',
0x97: 'REMOVE',
0x99: lambda fid, length: [], #function call
0x9B: 'BEGIN',
0x9C: 'ROLLBACK',
0x9D: 'END',
0x9E: 'add hidden method',
0x9F: 'HIDDEN',
0xA0: 'VALIDATE',
0xA1: 'PROTECTED',
0xA2: 'add method',
0xA3: 'add protected method',
0xA6: 'WITH',
0xA7: 'ENDWITH',
0xA8: 'ERROR',
0xA9: 'ASSERT',
0xAA: 'DEBUGOUT',
0xAB: 'FREE',
0xAC: 'NODEFAULT',
0xAD: 'MOUSE',
0xAE: 'LOCAL',
0xAF: 'LPARAMETERS',
0xB0: 'CD',
0xB1: 'MKDIR',
0xB2: 'RMDIR',
0xB3: 'DEBUG',
0xB4: lambda fid, length: ['BAD CODE: ' + fid.read(length).decode('ISO-8859-1')],
0xB5: 'FOR EACH',
0xB6: 'ENDFOREACH',
0xB7: 'DOEVENTS',
0xB9: 'IMPLEMENTS',
0xBA: 'TRY',
0xBB: 'CATCH',
0xBC: 'FINALLY',
0xBD: 'THROW',
0xBE: 'ENDTRY',
0xFB: read_text,
}
SETCODES = {
0x01: 'ALTERNATE',
0x02: 'BELL',
0x03: 'CARRY',
0x05: 'CENTURY',
0x07: 'COLOR',
0x09: 'CONFIRM',
0x0A: 'CONSOLE',
0x0B: 'DATE',
0x0C: 'DEBUG',
0x0E: 'DEFAULT',
0x0D: 'DECIMALS',
0x0F: 'DELETED',
0x15: 'ESCAPE',
0x16: 'EXACT',
0x17: 'EXCLUSIVE',
0x18: 'FIELDS',
0x1A: 'FILTER',
0x1B: 'FIXED',
0x1C: 'FORMAT',
0x1D: 'FUNCTION',
0x1E: 'HEADINGS',
0x1F: 'HELP',
0x21: 'INDEX',
0x23: 'MARGIN',
0x24: 'MEMOWIDTH',
0x26: 'MESSAGE',
0x27: 'ODOMETER',
0x28: 'ORDER',
0x29: 'PATH',
0x2A: 'PRINTER',
0x2B: 'PROCEDURE',
0x2D: 'RELATION',
0x2E: 'SAFETY',
0x30: 'STATUS',
0x31: 'STEP',
0x32: 'TALK',
0x35: 'TYPEAHEAD',
0x36: 'UNIQUE',
0x37: 'VIEW',
0x39: 'HOURS',
0x3A: 'MARK',
0x3B: 'POINT',
0x3C: 'SEPERATOR',
0x3D: 'BORDER',
0x3E: 'CLOCK',
0x40: 'SPACE',
0x41: 'COMPATIBLE',
0x42: 'AUTOSAVE',
0x43: 'BLOCKSIZE',
0x45: 'DEVELOPMENT',
0x46: 'NEAR',
0x48: 'REFRESH',
0x49: 'LOCK',
0x4C: 'WINDOW',
0x4D: 'REPROCESS',
0x4E: 'SKIP',
0x51: 'FULLPATH',
0x54: 'RESOURCE',
0x55: 'TOPIC',
0x57: 'LOGERRORS',
0x59: 'SYSMENU',
0x5A: 'NOTIFY',
0x5C: 'MACKEY',
0x5D: 'CURSOR',
0x5E: 'UDFPARMS',
0x5F: 'MULTILOCKS',
0x60: 'TEXTMERGE',
0x61: 'OPTIMIZE',
0x62: 'LIBRARY',
0x64: 'ANSI',
0x65: 'TRBETWEEN',
0x66: 'PDSETUP',
0x68: 'KEYCOMP',
0x69: 'PALETTE',
0x6A: 'READBORDER',
0x6B: 'COLLATE',
0x6D: 'NOCPTRANS',
0x77: 'NULL',
0x79: 'TAG',
0x7B: 'CPDIALOG',
0x7C: 'CPCOMPILE',
0x7D: 'SECONDS',
0x7E: 'CLASSLIB',
0x7F: 'DATABASE',
0x80: 'DATASESSION',
0x81: 'FDOW',
0x82: 'FWEEK',
0x83: 'SYSFORMATS',
0x84: 'OLEOBJECT',
0x85: 'ASSERTS',
0x86: 'COVERAGE',
0x87: 'EVENTTRACKING',
0x88: 'NULLDISPLAY',
0x89: 'EVENTLIST',
0x8D: 'BROWSEIME',
0x8E: 'STRICTDATE',
0x8F: 'AUTOINCERROR',
0x90: 'ENGINEBEHAVIOR',
0x91: 'TABLEVALIDATE',
0x92: 'SQLBUFFERING',
0x94: 'TABLEPROMPT',
0xFE: '\n',
}
CLAUSES = {
0x01: 'ADDITIVE',
0x02: 'ALIAS',
0x03: 'ALL',
0x04: 'ARRAY',
0x05: 'AT',
0x06: 'BAR',
0x07: ',',
0x08: 'BLANK',
0x0C: 'CLEAR',
0x0D: 'COLOR',
0x0E: 'DEFAULT',
0x0F: 'DOUBLE',
0x11: 'FIELDS',
0x12: 'FILE',
0x13: 'FOR',
0x14: 'FORM',
0x15: 'FROM',
0x16: 'IN',
0x17: 'KEY',
0x18: '(@ or LIKE)',
0x1A: 'MACROS',
0x1B: 'MEMO',
0x1C: 'MENU',
0x1D: 'MESSAGE',
0x1E: 'NEXT',
0x1F: 'OFF',
0x20: 'ON',
0x21: 'PRINTER',
0x22: 'PROMPT',
0x23: 'RECORD',
0x24: 'REST',
0x25: 'SAVE',
0x26: 'SCREEN',
0x27: 'TITLE',
0x28: 'TO',
0x29: 'TOP',
0x30: 'NOOPTIMIZE',
0x2B: 'WHILE',
0x2C: 'WINDOW',
0x2E: 'OBJECT',
0x31: 'TABLE',
0x32: 'LABEL',
0x33: 'REPORT',
0x36: 'BOTTOM',
0x38: 'BY',
0x39: 'NOCONSOLE',
0x3A: 'NOWAIT',
0x3B: 'PLAIN',
0x3C: 'DESCENDING',
0x3D: 'NOWINDOW',
0x40: 'FONT',
0x41: 'STYLE',
0x42: 'RGB',
0x48: 'CASE',
0x49: 'ID',
0x4A: 'NAME',
0x4B: 'PROGRAM',
0x4C: 'QUERY',
0x4E: 'SCHEME',
0x4F: 'CLASS',
0x51: 'AS',
0x52: 'CLASSLIB',
0x56: 'DLLS',
0x57: 'SHORT',
0x58: 'LEFT',
0x59: 'RIGHT',
0x5B: 'RTLJUSTIFY',
0x5C: 'LTRJUSTIFY',
0x5F: 'PICTRES',
0xE5: read_name, #user defined function alias
0xF6: read_name, #user defined function
0xFC: read_expr,
END_EXPR: 'END EXPR', #0xFD
0xFE: '\n'
}
MULTICLAUSES = {
0x10: ('=', 'ERROR'),
0xBB: ('XL5', 'WITH BUFFERING='),
0xBC: ('INTO', 'ACTIVATE', 'COMMAND', 'PAD'),
0xBD: ('CENTER', 'CURSOR', 'TRANSACTION', 'APP', 'MINIMIZE', 'ESCAPE'),
0xBE: ('PROCEDURE', 'DELIMITED', 'EXE', 'DISTINCT', 'DOS', 'PAGE'),
0xBF: ('UNKNOWN', 'MIN', 'FLOAT'),
0xC0: ('HAVING', 'FREE', 'LOCAL', 'FOOTER'),
0xC1: ('LINE', 'TRIGGER', 'GLOBAL', 'GET'),
0xC2: ('SHARED', 'DATABASE', 'DROP', 'GETS', 'NOINIT'),
0xC3: ('ORDER BY', 'OF', 'REPLACE', 'NOCLOSE'),
0xC4: ('SAY', 'VIEWS'),
0xC5: ('VALUES', 'DBLCLICK'),
0xC6: ('POPUP', 'WHERE', 'DLL', 'DRAG', 'EXCLUDE'),
0xC7: ('*', 'STEP', 'XLS', 'MARK'),
0xC8: ('READ', 'MARGIN', 'RPD', 'READERROR'),
0xCA: ('TAG', 'SET', 'FORCE', 'NOMINIMIZE', 'EXIT'),
0xCB: ('STATUS', 'RECOMPILE', 'PRIMARY', 'WRK'),
0xCC: ('STRUCTURE', 'RELATIVE', 'FOREIGN', 'PROTECTED'),
0xCD: ('SHUTDOWN', 'NOFILTER'),
0xCE: ('TIMEOUT', 'UPDATE'),
0xCF: ('SHADOW',),
0xD0: ('NOCLEAR', 'SELECTION'),
0xD1: ('WITH', 'INTEGER', 'CONNECTION'),
0xD2: ('NOMARGIN',),
0xD3: ('UNIQUE', 'SIZE'),
0xD4: ('TYPE', 'LONG', 'SYSTEM'),
0xD5: ('EVENTS', 'CSV', 'COLUMN'),
0xD6: ('STRING', 'SHEET', 'NORM'),
0xD7: ('READWRITE',),
}
VALUES = {
0x2D: '.F.',
0x61: '.T.',
0xE4: '.NULL.',
0xD9: read_double_quoted_string,
0xDB: '',
0xDE: read_currency,
0xDF: '::',
0xE0: read_name,
0xE1: read_system_alias,
0xE2: '.',
0xE3: read_alias,
0xE6: read_datetime,
0xE7: read_float,
SQL_SUBQUERY: 'SQL SUBQUERY', #0xE8
0xE9: read_int32,
0xEB: read_next_code,
0xEC: read_menu_system_name,
0xED: read_system_name,
0xEE: read_date,
0xF0: lambda fid, *args: '(SHORT CIRCUIT AND IN {})'.format(read_ushort(fid)),
0xF1: lambda fid, *args: '(SHORT CIRCUIT OR IN {})'.format(read_ushort(fid)),
0xF2: lambda fid, *args: '(SHORT CIRCUIT IIF IN {})'.format(read_ushort(fid)),
0xF3: lambda fid, *args: '(SHORT CIRCUIT IIF IN {})'.format(read_ushort(fid)),
0xF4: read_alias,
0xF5: read_special_alias,
0xF7: read_name,
0xF8: read_int8,
0xF9: read_int16,
0xFA: read_double,
0xFB: read_single_quoted_string,
0xFC: read_expr,
0xFF: lambda fid, *args: 'ff ' + read_raw(fid, 2),
}
OPERATORS = {
0x00: ('NOP', 0),
0x01: ('$', 2),
0x03: ('END PAREN', 0),
0x04: ('*', 2),
0x05: ('^', 2),
0x06: ('+', 2),
0x07: (',', 2),
0x08: ('-', 2),
0x09: ('AND', 2),
0x0A: ('NOT', 1),
0x0B: ('OR', 2),
0x0C: ('/', 2),
0x0D: ('<', 2),
0x0E: ('<=', 2),
0x0F: ('!=', 2),
0x10: ('=', 2),
0x11: ('>', 2),
0x12: ('>=', 2),
0x14: ('==', 2),
0x18: ('@', -1),
0xCC: ('', 1),
}
FUNCTIONS = {
0x19: 'ABS',
0x1A: lambda fid: EXTENDED1[fid.read(1)[0]],
0x1B: 'ALIAS',
0x1C: 'ASC',
0x1D: 'AT',
0x1E: 'BOF',
0x1F: 'CDOW',
0x20: 'CHR',
0x21: 'CMONTH',
0x22: 'COL',
0x23: 'CTOD',
0x24: 'DATE',
0x25: 'DAY',
0x26: 'DBF',
0x27: 'DELETED',
0x28: 'DISKSPACE',
0x29: 'DOW',
0x2A: 'DTOC',
0x2B: 'EOF',
0x2C: 'ERROR',
0x2E: 'FCOUNT',
0x2F: 'FIELD',
0x30: 'FILE',
0x31: 'FKLABEL',
0x32: 'FKMAX',
0x33: 'FLOCK',
0x34: 'FOUND',
0x35: 'GETENV',
0x36: 'IIF',
0x37: 'INKEY',
0x38: 'INT',
0x39: 'ISALPHA',
0x3A: 'ISCOLOR',
0x3B: 'ISLOWER',
0x3C: 'ISUPPER',
0x3D: 'LEFT',
0x3E: 'LEN',
0x3F: 'LOCK',
0x40: 'LOWER',
0x41: 'LTRIM',
0x42: 'LUPDATE',
PARAMETER_MARK: 'MARK PARAMETERS', #0x43
0x44: 'MAX',
0x45: 'MESSAGE',
0x46: 'MIN',
0x47: 'MOD',
0x48: 'MONTH',
0x49: 'NDX',
0x4A: 'OS',
0x4B: 'PCOL',
0x4C: 'PROW',
0x4D: 'READKEY',
0x4E: 'RECCOUNT',
0x4F: 'RECNO',
0x50: 'RECSIZE',
0x51: 'REPLICATE',
0x52: 'RIGHT',
0x53: 'RLOCK',
0x54: 'ROUND',
0x55: 'ROWS',
0x56: 'RTRIM',
0x57: 'SELECT',
0x58: 'SPACE',
0x59: 'SQRT',
0x5A: 'STR',
0x5B: 'STUFF',
0x5C: 'SUBSTR',
0x5D: 'SYS',
0x5E: 'TIME',
0x5F: 'TRANSFORM',
0x60: 'TRIM',
0x62: 'TYPE',
0x64: 'UPDATED',
0x66: 'UPPER',
0x67: 'VAL',
0x68: 'VERSION',
0x69: 'YEAR',
0x6A: 'DMY',
0x6B: 'MDY',
0x6C: 'BAR',
0x6D: 'KEY',
0x6F: 'MEMORY',
0x70: 'MENU',
0x72: 'PAD',
0x73: 'POPUP',
0x74: 'PROGRAM',
0x75: 'PV',
0x76: 'SET',
0x77: 'CEILING',
0x7A: 'FLOOR',
0x7B: 'FV',
0x7C: 'LASTKEY',
0x7D: 'LIKE',
0x7E: 'LOOKUP',
0x7F: 'CDX',
0x80: 'MEMLINES',
0x81: 'MLINE',
0x82: 'ORDER',
0x83: 'PAYMENT',
0x84: 'PRINTSTATUS',
0x85: 'PROMPT',
0x86: 'RAND',
0x87: 'VARREAD',
0x89: 'RTOD',
0x8A: 'SEEK',
0x8B: 'SIGN',
0x8C: 'TAG',
0x8D: 'DTOR',
0x8E: 'DTOS',
0x8F: 'SCHEME',
0x90: 'FOPEN',
0x91: 'FCLOSE',
0x92: 'FREAD',
0x93: 'FWRITE',
0x94: 'FERROR',
0x95: 'FCREATE',
0x96: 'FSEEK',
0x97: 'FGETS',
0x98: 'FFLUSH',
0x99: 'FPUTS',
0x9B: 'ALLTRIM',
0x9C: 'ATLINE',
0x9D: 'CHRTRAN',
0x9E: 'FILTER',
0x9F: 'RELATION',
0xA0: 'TARGET',
0xA1: 'EMPTY',
0xA2: 'FEOF',
0xA3: 'HEADER',
0xA5: 'RAT',
0xA6: 'RATC',
0xA7: 'SECONDS',
0xA8: 'STRTRAN',
0xAA: 'USED',
0xAB: 'BETWEEN',
0xAC: 'CHRSAW',
0xAD: 'INLIST',
0xAE: 'ISDIGIT',
0xAF: 'OCCURS',
0xB0: 'PADC',
0xB1: 'PADL',
0xB2: 'PADR',
0xB3: 'FSIZE',
0xB4: 'SROWS',
0xB5: 'SCOLS',
0xB6: 'WCOLS',
0xB7: 'WROWS',
0xB8: 'ATC',
0xB9: 'ATCLINE',
0xBA: 'CURDIR',
0xBC: 'PROPER',
0xBB: 'FULLPATH',
0xBD: 'WEXISTS',
0xBE: 'WONTOP',
0xBF: 'WOUTPUT',
0xC0: 'WVISIBLE',
0xC1: 'GETFILE',
0xC2: 'PUTFILE',
0xC3: 'GOMONTH',
0xC4: 'PARAMETERS',
0xC5: 'MCOL',
0xC6: 'MDOWN',
0xC7: 'MROW',
0xC8: 'WLCOL',
0xC9: 'WLROW',
0xCB: 'FCHSIZE',
0xCD: 'ALEN',
0xCE: 'EVALUATE',
0xD1: 'ISNULL',
0xD2: 'NVL',
0xE5: read_name, #user defined function alias
0xEA: lambda fid: EXTENDED2[fid.read(1)[0]],
0xF6: read_name, #user defined function
}
EXTENDED1 = {
0x00: 'DISPLAYPATH',
0x01: 'CURSORTOXML',
0x02: 'XMLTOCURSOR',
0x03: 'GETINTERFACE',
0x04: 'BINDEVENT',
0x05: 'RAISEEVENT',
0x06: 'ADOCKSTATE',
0x07: 'GETCURSORADAPTER',
0x08: 'UNBINDEVENTS',
0x09: 'AEVENTS',
0x0A: 'ADDPROPERTY',
0x0E: 'ICASE',
0x0C: 'EVL',
0x0F: 'CAST',
0x10: 'ASQLHANDLES',
0x11: 'SETRESULTSET',
0x12: 'GETRESULTSET',
0x13: 'CLEARRESULTSET',
0x14: 'SQLIDLEDISCONNECT',
0x15: 'ISMEMOFETCHED',
0x16: 'GETAUTOINCVALUE',
0x17: 'MAKETRANSACTABLE',
0x18: 'ISTRANSACTABLE',
0x19: 'ISPEN',
}
EXTENDED2 = {
#This list contains all those functions that are available through the 0xEA (extended function) code:
0x00: 'PRMPAD',
0x01: 'PRMBAR',
0x02: 'MRKPAD',
0x03: 'MRKBAR',
0x04: 'CNTPAD',
0x05: 'CNTBAR',
0x06: 'GETPAD',
0x07: 'GETBAR',
0x08: 'MWINDOW',
0x09: 'OBJNUM',
0x0A: 'WPARENT',
0x0B: 'WCHILD',
0x0C: 'RDLEVEL',
0x0D: 'ACOPY',
0x0E: 'AINS',
0x0F: 'ADEL',
0x10: 'ASORT',
0x11: 'ASCAN',
0x12: 'AELEMENT',
0x13: 'ASUBSCRIPT',
0x14: 'AFIELDS',
0x15: 'ADIR',
0x16: 'LOCFILE',
0x17: 'WBORDER',
0x18: 'ON',
0x19: '', #Some sort of array indicator?
0x1A: 'WLAST',
0x1B: 'SKPBAR',
0x1C: 'SKPPAD',
0x1D: 'WMAXIMUM',
0x1E: 'WMINIMUM',
0x1F: 'WREAD',
0x20: 'WTITLE',
0x21: 'GETPEM',
0x23: 'TXTWIDTH',
0x24: 'FONTMETRIC',
0x25: 'SYSMETRIC',
0x26: 'WFONT',
0x27: 'GETFONT',
0x28: 'AFONT',
0x29: 'DDEADVISE',
0x2A: 'DDEENABLED',
0x2B: 'DDEEXECUTE',
0x2C: 'DDEINITIATE',
0x2D: 'DDEPOKE',
0x2E: 'DDEREQUEST',
0x2F: 'DDESETSERVICE',
0x30: 'DDESETTOPIC',
0x31: 'DDETERMINATE',
0x32: 'DDELASTERROR',
0x33: 'GETDIR',
0x34: 'DDEABORTTRANS',
0x35: 'DDESETOPTION',
0x36: 'OEMTOANSI',
0x38: 'RGBSCHEME',
0x39: 'CPCONVERT',
0x3A: 'CPCURRENT',
0x3B: 'CPDBF',
0x3C: 'IDXCOLLATE',
0x3E: 'CAPSLOCK',
0x3F: 'NUMLOCK',
0x40: 'INSMODE',
0x41: 'SOUNDEX',
0x42: 'DIFFERENCE',
0x43: 'COS',
0x44: 'SIN',
0x45: 'TAN',
0x46: 'ACOS',
0x47: 'ASIN',
0x48: 'ATAN',
0x49: 'ATN2',
0x4A: 'LOG',
0x4B: 'LOG10',
0x4C: 'EXP',
0x4D: 'PI',
0x4E: 'CREATEOBJECT',
0x4F: 'BARPROMPT',
0x51: 'HOME',
0x53: 'FOR',
0x54: 'UNIQUE',
0x55: 'DESCENDING',
0x56: 'TAGCOUNT',
0x57: 'TAGNO',
0x58: 'FDATE',
0x59: 'FTIME',
0x5A: 'ISBLANK',
0x5B: 'ISMOUSE',
0x5C: 'GETOBJECT',
0x5D: 'OBJTOCLIENT',
0x5E: 'RGB',
0x5F: 'OLDVAL',
0x60: 'ASELOBJ',
0x61: 'ACLASS',
0x62: 'AMEMBERS',
0x63: 'COMPOBJ',
0x64: 'SQLCANCEL',
0x65: 'SQLCOLUMNS',
0x66: 'SQLCONNECT',
0x67: 'SQLDISCONNECT',
0x68: 'PEMSTATUS',
0x69: 'SQLEXEC',
0x6A: 'SQLGETPROP',
0x6B: 'SQLMORERESULTS',
0x6C: 'SQLSETPROP',
0x6D: 'SQLTABLES',
0x6E: 'FLDLIST',
0x6F: 'PRTINFO',
0x70: 'KEYMATCH',
0x71: 'OBJVAR',
0x72: 'NORMALIZE',
0x73: 'ISREADONLY',
0x74: 'PCOUNT',
0x78: 'MESSAGEBOX',
0x79: 'AUSED',
0x7A: 'AERROR',
0x7B: 'SQLCOMMIT',
0x7C: 'SQLROLLBACK',
0x7D: 'MTON',
0x7E: 'NTOM',
0x7F: 'DTOT',
0x80: 'TTOD',
0x81: 'TTOC',
0x82: 'CTOT',
0x83: 'HOUR',
0x84: 'MINUTE',
0x85: 'SEC',
0x86: 'DATETIME',
0x87: 'REQUERY',
0x88: 'CURSORSETPROP',
0x89: 'CURSORGETPROP',
0x8A: 'DBSETPROP',
0x8B: 'DBGETPROP',
0x8C: 'GETCOLOR',
0x8D: 'PRIMARY',
0x8E: 'CANDIDATE',
0x8F: 'CURVAL',
0x90: 'GETFLDSTATE',
0x91: 'SETFLDSTATE',
0x92: 'GETNEXTMODIFIED',
0x93: 'TABLEUPDATE',
0x94: 'TABLEREVERT',
0x95: 'ADATABASES',
0x96: 'DBC',
0x98: 'ADBOBJECTS',
0x99: 'APRINTERS',
0x9A: 'GETPRINTER',
0x9B: 'GETPICT',
0x9C: 'WEEK',
0x9D: 'REFRESH',
0x9E: 'GETCP',
0x9F: 'SQLSTRINGCONNECT',
0xA0: 'CREATEBINARY',
0xA1: 'DODEFAULT',
0xA2: 'ISEXCLUSIVE',
0xA3: 'TXNLEVEL',
0xA4: 'DBUSED',
0xA5: 'AINSTANCE',
0xA6: 'INDBC',
0xA7: 'BITLSHIFT',
0xA8: 'BITRSHIFT',
0xA9: 'BITAND',
0xAA: 'BITOR',
0xAB: 'BITNOT',
0xAC: 'BITXOR',
0xAD: 'BITSET',
0xAE: 'BITTEST',
0xAF: 'BITCLEAR',
0xB0: 'AT_C',
0xB1: 'ATCC',
0xB2: 'RATLINE',
0xB3: 'LEFTC',
0xB4: 'RIGHTC',
0xB5: 'SUBSTRC',
0xB6: 'STUFFC',
0xB7: 'LENC',
0xB8: 'CHRTRANC',
0xBA: 'LIKEC',
0xBC: 'IMESTATUS',
0xBD: 'ISLEADBYTE',
0xBE: 'STRCONV',
0xBF: 'BINTOC',
0xC0: 'CTOBIN',
0xC1: 'ISFLOCKED',
0xC2: 'ISRLOCKED',
0xC3: 'LOADPICTURE',
0xC4: 'SAVEPICTURE',
0xC5: 'SQLPREPARE',
0xC6: 'DIRECTORY',
0xC7: 'CREATEOFFLINE',
0xC8: 'DROPOFFLINE',
0xC9: 'AGETCLASS',
0xCA: 'AVCXCLASSES',
0xCB: 'STRTOFILE',
0xCC: 'FILETOSTR',
0xCD: 'ADDBS',
0xCE: 'DEFAULTEXT',
0xCF: 'DRIVETYPE',
0xD0: 'FORCEEXT',
0xD1: 'FORCEPATH',
0xD2: 'JUSTDRIVE',
0xD3: 'JUSTEXT',
0xD4: 'JUSTFNAME',
0xD5: 'JUSTPATH',
0xD6: 'JUSTSTEM',
0xD7: 'INDEXSEEK',
0xD8: 'COMRETURNERROR',
0xD9: 'VARTYPE',
0xDA: 'ALINES',
0xDB: 'NEWOBJECT',
0xDC: 'AMOUSEOBJ',
0xDD: 'COMCLASSINFO',
0xE0: 'ANETRESOURCES',
0xE1: 'AGETFILEVERSION',
0xE2: 'CREATEOBJECTEX',
0xE3: 'COMARRAY',
0xE4: 'EXECSCRIPT',
0xE5: 'XMLUPDATEGRAM',
0xE6: 'COMPROP',
0xE7: 'ATAGINFO',
0xE8: 'ASTACKINFO',
0xE9: 'EVENTHANDLER',
0xEA: 'EDITSOURCE',
0xEB: 'ADLLS',
0xEC: 'QUARTER',
0xED: 'GETWORDCOUNT',
0xEE: 'GETWORDNUM',
0xEF: 'ALANGUAGE',
0xF0: 'STREXTRACT',
0xF1: 'INPUTBOX',
0xF2: 'APROCINFO',
0xF3: 'WDOCKABLE',
0xF4: 'ASESSIONS',
0xF5: 'TEXTMERGE',
0xFD: 'MIN',
}
CLAUSES.update(VALUES)
def read_short(fid):
return struct.unpack('<h', fid.read(2))[0]
def read_ushort(fid):
return struct.unpack('<H', fid.read(2))[0]
def read_int(fid):
return struct.unpack('<i', fid.read(4))[0]
def read_uint(fid):
return struct.unpack('<I', fid.read(4))[0]
def parse_subline(fid, length, final, names, line):
while fid.tell() < final:
clauseval = fid.read(1)[0]
if clauseval in CLAUSES:
clause = CLAUSES[clauseval]
if clauseval in MULTICLAUSES:
clause = ' or '.join(MULTICLAUSES[clauseval])
if clauseval == 0xF6 or clauseval == 0xF7:
clause = clause(fid, names)
while line and type(line[-1]) is FXPAlias:
clause = FXPName(repr(line.pop()) + repr(clause))
elif callable(clause):
clause = clause(fid, names)
else:
clause = FXPName(clause)
line.append(clause)
if len(line) > 1 and isinstance(line[-2], int):
line.pop(-2)
fid.seek(final - length)
try:
line = [' '.join(repr(l) for l in line)]
except:
pass
line + [read_raw(fid, length)] + [fid.tell() - length]
return line[0]
def parse_line(fid, length, names):
final = fid.tell() + length
line = []
command = COMMANDS[fid.read(1)[0]]
if callable(command):
line += [FXPName(c) for c in command(fid, length-1)]
else:
line.append(FXPName(command))
return parse_subline(fid, length, final, names, line)
def read_code_line_area(fid, names, final_fpos):
d = []
while fid.tell() < final_fpos:
try:
start_pos = fid.tell()
length = read_ushort(fid)
d.append(parse_line(fid, length-2, names))
except:
import traceback
traceback.print_exc()
fid.seek(start_pos)
length = read_ushort(fid)
line = read_raw(fid, length-2)
print(line, file=sys.stderr)
d.append(line)
return ''.join(d)
def read_code_name_list(fid):
num_entries = read_ushort(fid)
return [read_string(fid) for i in range(num_entries)]
def change_named_value(expr, names):
expr = expr.split()[1]
if expr.endswith('.'):
return names[int(expr[:-1])] + '.'
else:
return names[int(expr)]
return expr
def concatenate_aliases(codes, names):
codes = codes[:]
new_codes = []
while codes:
code = codes.pop(0)
if isinstance(code, str) and code.startswith('NAME '):
code = change_named_value(code, names)
while code.endswith('.'):
code += change_named_value(codes.pop(0), names)
if isinstance(code, str) and code.startswith('SPECIAL_NAME '):
code = change_named_value(code, SPECIAL_NAMES)
while code.endswith('.'):
code += change_named_value(codes.pop(0), names)
new_codes.append(code)
return new_codes
def read_code_block(fid):
tot_length = read_ushort(fid)
if tot_length == 0:
tot_length = read_uint(fid)
start_pos = fid.tell()
fid.seek(fid.tell() + tot_length)
names = read_code_name_list(fid)
fid.seek(start_pos)
return read_code_line_area(fid, names, start_pos+tot_length)
def convert_date(date_bits):
year = ((date_bits & 0xfe000000) >> 25) + 1980
month = (date_bits & 0x1e00000) >> 21
day = (date_bits & 0x1f0000) >> 16
hour = (date_bits & 0xf800) >> 11
minute = (date_bits & 0x7e0) >> 5
second = (date_bits & 0x1f) << 1
return datetime(year, month, day, hour, minute, second)
def read_procedure_header(fid):
return OrderedDict((
('name', read_string(fid)),
('pos', read_uint(fid)),
('class_flag', read_short(fid)),
('class', read_short(fid)),
))
def read_class_header(fid):
return {
'name': read_string(fid),
'parent': read_string(fid),
'pos': read_uint(fid),
'reserved': fid.read(2),
}
def read_line_info(fid):
return read_raw(fid, 2)
def read_source_info(fid):
unknown1, unknown2, unknown3, line_num_start = struct.unpack('IIII', fid.read(16))
return line_num_start, unknown1, unknown2, unknown3
def read_until_null(fid):
string = fid.read(1)
while string[-1] != 0:
string += fid.read(1)
if string:
string = string[:-1]
return string.decode('ISO-8859-1')
def read_fxp_file_block(fid, start_pos, name_pos):
fid.seek(start_pos)
fmt = '<hhiiiiiiIIB'
num_procedures, num_classes, main_codepos, procedure_pos, class_pos, source_info_pos, num_code_lines, code_lines_pos, date, original_name_pos, codepage = struct.unpack(fmt, fid.read(struct.calcsize(fmt)))
procedure_pos += start_pos
class_pos += start_pos
code_lines_pos += start_pos
source_info_pos += start_pos
date = convert_date(date)
codepage = dbf.code_pages[255 - codepage]
fid.seek(name_pos + original_name_pos)
original_name = read_until_null(fid)
for item in ('num_procedures', 'num_classes', 'main_codepos', 'procedure_pos', 'class_pos', 'source_info_pos', 'num_code_lines', 'code_lines_pos', 'date', 'original_name', 'codepage'):
print('{} = {!r}'.format(item, eval(item)))
fid.seek(procedure_pos)
procedures = [OrderedDict((key, val) for key, val in zip(('name', 'pos', 'class_flag', 'class'), ('', main_codepos, 0, -1)))]
procedures += [read_procedure_header(fid) for i in range(num_procedures)]
fid.seek(class_pos, 0)
classes = [read_class_header(fid) for i in range(num_classes)]
fid.seek(code_lines_pos)
line_info = [read_line_info(fid) for i in range(num_code_lines)]
fid.seek(source_info_pos)
source_info = [read_source_info(fid) for i in range(num_procedures + num_classes + 1)]
for proc_or_cls in procedures + classes:
fid.seek(proc_or_cls['pos'] + start_pos)
proc_or_cls['code'] = read_code_block(fid)
proc_or_cls.pop('pos')
return procedures, classes
def fxp_read(fxp_file, output_dir=None):
with open(fxp_file, 'rb') as fid:
header_bytes = fid.read(HEADER_SIZE)
if len(header_bytes) < HEADER_SIZE:
raise Exception('File header too short')
identifier, head, num_files, main_file, footer_pos, name_pos, name_len, reserved, checksum = struct.unpack('<3s2sHHIII18sH', header_bytes)
if identifier == ENCRYPTED_IDENTIFIER:
print(repr(header_bytes))
raise Exception('Encrypted file')
if identifier != IDENTIFIER:
print('bad header')
raise Exception('bad header: {!r}'.format(identifier))
if checksum != checksum_calc(header_bytes[:-4]):
raise Exception('bad checksum')
for item in ('head', 'num_files', 'main_file', 'footer_pos', 'name_pos', 'name_len', 'reserved', 'checksum'):
print('{} = {!r}'.format(item, eval(item)))
print()
if output_dir:
try:
os.makedirs(output_dir)
except OSError as e:
if e.errno != errno.EEXIST:
raise
fid.seek(footer_pos)
footer_entries = [struct.unpack('<BIIII8s', fid.read(FOOTER_ENTRY_SIZE)) for i in range(num_files)]
output = OrderedDict()
for i, (file_type, file_start, file_stop, dirname_start, filename_start, reserved) in enumerate(footer_entries):
if i == main_file:
print('MAIN')
fid.seek(name_pos + dirname_start)
dirname = read_until_null(fid)
fid.seek(name_pos + filename_start)
filename = read_until_null(fid)
for item in ('file_type', 'file_start', 'file_stop', 'dirname_start', 'filename_start', 'reserved', 'dirname', 'filename'):
print('{} = {!r}'.format(item, eval(item)))
if file_type == 0:
try:
output[filename] = read_fxp_file_block(fid, file_start, name_pos)
except:
pass
if output_dir:
with open(os.path.join(output_dir, filename), 'wb') as outfid:
fid.seek(file_start)
blocklen = file_stop - file_start
filename_blocklen = len(dirname) + len(filename) + 3
new_footer_pos = HEADER_SIZE + blocklen + filename_blocklen
new_name_pos = HEADER_SIZE + blocklen
header_data = bytearray(struct.pack('<5sHHIII', IDENTIFIER, 1, 0, new_footer_pos, new_name_pos, filename_blocklen))
header_data += b'\x00' * 16
outfid.write(header_data)
outfid.write(b'\x00' * 2)
outfid.write(struct.pack('<H', checksum_calc(header_data)))
file_start = outfid.tell()
outfid.write(fid.read(blocklen))
file_stop = outfid.tell()
outfid.write(b'\x00')
outfid.write((dirname + '\x00').encode('ISO-8859-1'))
outfid.write((filename + '\x00').encode('ISO-8859-1'))
outfid.write(struct.pack('<BIIII', file_type, file_start, file_stop, 1, 1 + len(dirname) + 1))
outfid.write(b'\x00' * 8)
else:
if output_dir:
with open(os.path.join(output_dir, filename), 'wb') as outfid:
fid.seek(file_start)
outfid.write(fid.read(file_stop - file_start))
print()
if output_dir:
for filename in output:
with open(os.path.join(output_dir, os.path.splitext(filename)[0]) + '.prg', 'wb') as outfid:
procedures, classes = output[filename]
for proc in procedures:
if not proc['class_flag']:
if proc['name']:
outfid.write('PROCEDURE {}\n'.format(proc['name']).encode('ISO-8859-1'))
outfid.write(proc['code'].encode('ISO-8859-1'))
for cls in classes:
outfid.write('DEFINE CLASS {} AS {}\n'.format(cls['name'], cls['parent']).encode('ISO-8859-1'))
for line in cls['code'].splitlines(True):
match = re.match(r'add (hidden |protected |)?method ([0-9]*)', line)
if match:
qualifier = match.groups()[0]
proc = procedures[int(match.groups()[1])]
outfid.write('{}PROCEDURE {}\n'.format(qualifier, proc['name']).encode('ISO-8859-1'))
outfid.write(proc['code'].encode('ISO-8859-1'))
else:
outfid.write(line)
for filename in output:
import pprint
printer = pprint.PrettyPrinter(depth=10, indent=4)
procedures, classes = output[filename]
printer.pprint(filename)
printer.pprint(procedures)
printer.pprint(classes)
if __name__ == '__main__':
fxp_read(sys.argv[1], sys.argv[2] if len(sys.argv) > 2 else None)
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] |
utils/app.py | dlzcn/MemoryMonitor | 0 | 176569 | <reponame>dlzcn/MemoryMonitor
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# ******************************************************
# @author: <NAME> - <EMAIL>
# @date (created): 2019-06-27 11:31
# @file: app.py
# @brief:
# @internal:
# revision: 8
# last modified: 2019-11-28 15:41:23
# *****************************************************
import os
import sys
import logging
import multiprocessing
from typing import Tuple, Union
from logging.handlers import QueueHandler, QueueListener, RotatingFileHandler
def open_file(filename):
if sys.platform == "win32":
os.startfile(filename)
else:
import subprocess
opener = "open" if sys.platform == "darwin" else "xdg-open"
subprocess.call([opener, filename])
def get_script_path():
return os.path.dirname(os.path.realpath(sys.argv[0]))
def get_application_path():
# determine if application is a script file or frozen exe
if getattr(sys, 'frozen', False):
application_path = os.path.dirname(sys.executable)
elif sys.argv[0]:
application_path = os.path.dirname(os.path.realpath(sys.argv[0]))
elif __file__:
application_path = os.path.dirname(__file__)
else:
application_path = os.getcwd()
return application_path
class WriteStream(object):
""" The new Stream Object which replaces the default stream associated with sys.stdout
This object just puts data in a queue!
"""
def __init__(self, queue):
self.queue = queue
def write(self, text):
self.queue.put(text)
def flush(self):
return
def logger_init_for_worker(q: multiprocessing.Queue):
""" Init logger in worker process
:param q: multiprocess.Queue
"""
# all records from worker processes go to qh and then into q
qh = QueueHandler(q)
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
logger.addHandler(qh)
def logger_init_main(filename=None, mp=False) -> \
Tuple[Union[QueueListener, None], Union[multiprocessing.Queue, None]]:
""" Init logger for current process
:param filename: str or None
File rotating handler will be used if filename is given. Otherwise stream handler is used
:param mp: bool
Set Ture if you want to handle logging information in worker process
:return: Tuple
QueueListner, multiprocessing.Queue
"""
# this is the handler for all log records
if filename is not None:
handler = RotatingFileHandler(
filename, encoding='utf-8', maxBytes=1 << 22, backupCount=10)
else:
handler = logging.StreamHandler()
if multiprocessing:
handler.setFormatter(
logging.Formatter(
fmt='%(asctime)s %(levelname)-8s: %(process)-6s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S'
)
)
else:
handler.setFormatter(
logging.Formatter(
fmt='%(asctime)s %(levelname)-8s: %(message)s',
datefmt='%Y-%m-%d %H:%M:%S'
)
)
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
# add the handler to the logger so records from this process are handled
logger.addHandler(handler)
if mp:
q = multiprocessing.Queue()
# ql gets records from the queue and sends them to the handler
ql = QueueListener(q, handler)
ql.start()
return ql, q
else:
return None, None
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theory/conditionals.py | librity/nc_pyjobs | 0 | 161797 | # python3 theory/conditionals.py
def plus(a, b):
if type(a) is int or type(a) is float:
if type(b) is int or type(b) is float:
return a + b
else:
return None
else:
return None
print(plus(1, '10'))
def can_drink(age):
print(f"You are {age} years old.")
if age < 18:
print("You can't drink.")
elif age == 18 or age == 19:
print("Go easy on it cowbow.")
elif age > 19 and age < 25:
print("Buckle up son.")
else:
print("Enjoy your drink!")
can_drink(17)
can_drink(19)
can_drink(21)
can_drink(25)
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2
] |
gamesystem.py | cristilianojr/JOKENPOH | 1 | 9454 | <reponame>cristilianojr/JOKENPOH
import random
from tkinter import PhotoImage
"""
Esse arquivo define os estados do game
"""
def ia_chocer():
"""IA faz a escolha de um numero aleatório"""
posibility = ['rock', 'paper', 'scissor']
value = posibility[random.randint(0, 2)]
return value
def battle_verification(player_choice, ia_choice):
state_victoryorlose = ''
if player_choice == 'rock':
if ia_choice == 'rock':
state_victoryorlose = 'draw'
elif ia_choice == 'scissor':
state_victoryorlose = 'victory'
elif ia_choice == 'paper':
state_victoryorlose = 'defeat'
elif player_choice == 'scissor':
if ia_choice == 'rock':
state_victoryorlose = 'defeat'
elif ia_choice == 'scissor':
state_victoryorlose = 'draw'
elif ia_choice == 'paper':
state_victoryorlose = 'victory'
elif player_choice == 'paper':
if ia_choice == 'rock':
state_victoryorlose = 'victory'
elif ia_choice == 'scissor':
state_victoryorlose = 'defeat'
elif ia_choice == 'paper':
state_victoryorlose = 'draw'
return state_victoryorlose
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conda/core/link.py | astrojuanlu/conda | 0 | 76814 | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function, unicode_literals
from collections import defaultdict
from logging import getLogger
import os
from os.path import join
from subprocess import CalledProcessError, check_call
import sys
from traceback import format_exc
import warnings
from .linked_data import (get_python_version_for_prefix, linked_data as get_linked_data,
load_meta)
from .package_cache import PackageCache
from .path_actions import (CompilePycAction, CreateApplicationEntryPointAction,
CreateLinkedPackageRecordAction, CreatePrivateEnvMetaAction,
CreatePythonEntryPointAction, LinkPathAction, MakeMenuAction,
RemoveLinkedPackageRecordAction, RemoveMenuAction,
RemovePrivateEnvMetaAction, UnlinkPathAction)
from .. import CondaMultiError
from .._vendor.auxlib.collection import first
from .._vendor.auxlib.ish import dals
from ..base.context import context
from ..common.compat import iteritems, itervalues, on_win, text_type
from ..common.path import (explode_directories, get_all_directories, get_bin_directory_short_path,
get_major_minor_version,
get_python_site_packages_short_path)
from ..exceptions import (KnownPackageClobberError, SharedLinkPathClobberError,
UnknownPackageClobberError, maybe_raise)
from ..gateways.disk.delete import rm_rf
from ..gateways.disk.read import isfile, lexists, read_package_info
from ..gateways.disk.test import hardlink_supported, softlink_supported
from ..models.dist import Dist
from ..models.enums import LinkType
try:
from cytoolz.itertoolz import concat, concatv, groupby
except ImportError:
from .._vendor.toolz.itertoolz import concat, concatv, groupby # NOQA
log = getLogger(__name__)
def determine_link_type(extracted_package_dir, target_prefix):
source_test_file = join(extracted_package_dir, 'info', 'index.json')
if context.always_copy:
return LinkType.copy
if context.always_softlink:
return LinkType.softlink
if hardlink_supported(source_test_file, target_prefix):
return LinkType.hardlink
if context.allow_softlinks and softlink_supported(source_test_file, target_prefix):
return LinkType.softlink
return LinkType.copy
def make_unlink_actions(transaction_context, target_prefix, linked_package_data):
# no side effects in this function!
unlink_path_actions = tuple(UnlinkPathAction(transaction_context, linked_package_data,
target_prefix, trgt)
for trgt in linked_package_data.files)
remove_menu_actions = RemoveMenuAction.create_actions(transaction_context,
linked_package_data,
target_prefix)
meta_short_path = '%s/%s' % ('conda-meta', Dist(linked_package_data).to_filename('.json'))
remove_conda_meta_actions = (RemoveLinkedPackageRecordAction(transaction_context,
linked_package_data,
target_prefix, meta_short_path),)
_all_d = get_all_directories(axn.target_short_path for axn in unlink_path_actions)
all_directories = sorted(explode_directories(_all_d, already_split=True), reverse=True)
directory_remove_actions = tuple(UnlinkPathAction(transaction_context, linked_package_data,
target_prefix, d, LinkType.directory)
for d in all_directories)
if linked_package_data.preferred_env is not None:
app_entry_point_short_path = os.path.join(get_bin_directory_short_path(),
linked_package_data.name)
unlink_app_entry_point = UnlinkPathAction(transaction_context, linked_package_data,
context.root_prefix, app_entry_point_short_path),
unlink_path_actions = unlink_path_actions + unlink_app_entry_point
private_envs_meta_action = RemovePrivateEnvMetaAction(
transaction_context, linked_package_data, target_prefix),
else:
private_envs_meta_action = ()
return tuple(concatv(
remove_menu_actions,
unlink_path_actions,
directory_remove_actions,
private_envs_meta_action,
remove_conda_meta_actions,
))
class UnlinkLinkTransaction(object):
@classmethod
def create_from_dists(cls, index, target_prefix, unlink_dists, link_dists):
# This constructor method helps to patch into the 'plan' framework
linked_packages_data_to_unlink = tuple(load_meta(target_prefix, dist)
for dist in unlink_dists)
log.debug("instantiating UnlinkLinkTransaction with\n"
" target_prefix: %s\n"
" unlink_dists:\n"
" %s\n"
" link_dists:\n"
" %s\n",
target_prefix,
'\n '.join(text_type(d) for d in unlink_dists),
'\n '.join(text_type(d) for d in link_dists))
pkg_dirs_to_link = tuple(PackageCache[dist].extracted_package_dir for dist in link_dists)
assert all(pkg_dirs_to_link)
packages_info_to_link = tuple(read_package_info(index[dist], pkg_dir)
for dist, pkg_dir in zip(link_dists, pkg_dirs_to_link))
return UnlinkLinkTransaction(target_prefix, linked_packages_data_to_unlink,
packages_info_to_link)
def __init__(self, target_prefix, linked_packages_data_to_unlink, packages_info_to_link):
# type: (str, Sequence[Dist], Sequence[PackageInfo]) -> NoneType
# order of unlink_dists and link_dists will be preserved throughout
# should be given in dependency-sorted order
self.target_prefix = target_prefix
self.linked_packages_data_to_unlink = linked_packages_data_to_unlink
self.packages_info_to_link = packages_info_to_link
self._prepared = False
self._verified = False
def prepare(self):
if self._prepared:
return
# gather information from disk and caches
self.prefix_linked_data = get_linked_data(self.target_prefix)
link_types = tuple(determine_link_type(pkg_info.extracted_package_dir, self.target_prefix)
for pkg_info in self.packages_info_to_link)
# make all the path actions
# no side effects allowed when instantiating these action objects
transaction_context = dict()
python_version = self.get_python_version(self.target_prefix,
self.linked_packages_data_to_unlink,
self.packages_info_to_link)
transaction_context['target_python_version'] = python_version
sp = get_python_site_packages_short_path(python_version)
transaction_context['target_site_packages_short_path'] = sp
unlink_actions = tuple((lnkd_pkg_data, make_unlink_actions(transaction_context,
self.target_prefix,
lnkd_pkg_data))
for lnkd_pkg_data in self.linked_packages_data_to_unlink)
link_actions = (
(pkg_info, self.make_link_actions(transaction_context, pkg_info,
self.target_prefix, lt))
for pkg_info, lt in zip(self.packages_info_to_link, link_types)
)
self.all_actions = tuple(per_pkg_actions for per_pkg_actions in
concatv(unlink_actions, link_actions))
# type: Tuple[pkg_data, Tuple[PathAction]]
self.num_unlink_pkgs = len(unlink_actions)
self._prepared = True
@staticmethod
def _verify_individual_level(all_actions):
# run all per-action verify methods
# one of the more important of these checks is to verify that a file listed in
# the packages manifest (i.e. info/files) is actually contained within the package
for _, pkg_actions in all_actions:
for axn in pkg_actions:
if axn.verified:
continue
error_result = axn.verify()
if error_result:
log.debug("Verification error in action %s", axn)
log.debug(format_exc())
yield error_result
@staticmethod
def _verify_transaction_level(target_prefix, all_actions, num_unlink_pkgs):
# further verification of the whole transaction
# for each path we are creating in link_actions, we need to make sure
# 1. each path either doesn't already exist in the prefix, or will be unlinked
# 2. there's only a single instance of each path
# paths are case-insensitive on windows apparently
lower_on_win = lambda p: p.lower() if on_win else p
unlink_paths = set(lower_on_win(axn.target_short_path)
for _, pkg_actions in all_actions[:num_unlink_pkgs]
for axn in pkg_actions
if isinstance(axn, UnlinkPathAction))
# we can get all of the paths being linked by looking only at the
# CreateLinkedPackageRecordAction actions
create_lpr_actions = (axn
for _, pkg_actions in all_actions[num_unlink_pkgs:]
for axn in pkg_actions
if isinstance(axn, CreateLinkedPackageRecordAction))
link_paths_dict = defaultdict(list)
for axn in create_lpr_actions:
for path in axn.linked_package_record.files:
path = lower_on_win(path)
link_paths_dict[path].append(axn)
if path not in unlink_paths and lexists(join(target_prefix, path)):
# we have a collision; at least try to figure out where it came from
linked_data = get_linked_data(target_prefix)
colliding_linked_package_record = first(
(lpr for lpr in itervalues(linked_data)),
key=lambda lpr: path in lpr.files
)
if colliding_linked_package_record:
yield KnownPackageClobberError(Dist(axn.linked_package_record), path,
Dist(colliding_linked_package_record),
context)
else:
yield UnknownPackageClobberError(Dist(axn.linked_package_record), path,
context)
for path, axns in iteritems(link_paths_dict):
if len(axns) > 1:
yield SharedLinkPathClobberError(
path, tuple(Dist(axn.linked_package_record) for axn in axns), context
)
def verify(self):
if not self._prepared:
self.prepare()
exceptions = tuple(exc for exc in concatv(
self._verify_individual_level(self.all_actions),
self._verify_transaction_level(self.target_prefix, self.all_actions,
self.num_unlink_pkgs),
) if exc)
if exceptions:
maybe_raise(CondaMultiError(exceptions), context)
else:
log.info(exceptions)
self._verified = True
def execute(self):
if not self._verified:
self.verify()
pkg_idx = 0
try:
for pkg_idx, (pkg_data, actions) in enumerate(self.all_actions):
self._execute_actions(self.target_prefix, self.num_unlink_pkgs, pkg_idx,
pkg_data, actions)
except Exception as execute_multi_exc:
# reverse all executed packages except the one that failed
rollback_excs = []
if context.rollback_enabled:
failed_pkg_idx = pkg_idx
reverse_actions = self.all_actions[:failed_pkg_idx]
for pkg_idx, (pkg_data, actions) in reversed(tuple(enumerate(reverse_actions))):
excs = self._reverse_actions(self.target_prefix, self.num_unlink_pkgs,
pkg_idx, pkg_data, actions)
rollback_excs.extend(excs)
raise CondaMultiError(tuple(concatv(
(execute_multi_exc.errors
if isinstance(execute_multi_exc, CondaMultiError)
else (execute_multi_exc,)),
rollback_excs,
)))
else:
for pkg_idx, (pkg_data, actions) in enumerate(self.all_actions):
for axn_idx, action in enumerate(actions):
action.cleanup()
@staticmethod
def _execute_actions(target_prefix, num_unlink_pkgs, pkg_idx, pkg_data, actions):
axn_idx, action, is_unlink = 0, None, True
try:
dist = Dist(pkg_data)
is_unlink = pkg_idx <= num_unlink_pkgs - 1
if is_unlink:
log.info("===> UNLINKING PACKAGE: %s <===\n"
" prefix=%s\n",
dist, target_prefix)
else:
log.info("===> LINKING PACKAGE: %s <===\n"
" prefix=%s\n"
" source=%s\n",
dist, target_prefix, pkg_data.extracted_package_dir)
run_script(target_prefix if is_unlink else pkg_data.extracted_package_dir,
Dist(pkg_data),
'pre-unlink' if is_unlink else 'pre-link',
target_prefix if is_unlink else None)
for axn_idx, action in enumerate(actions):
action.execute()
run_script(target_prefix, Dist(pkg_data), 'post-unlink' if is_unlink else 'post-link')
except Exception as e: # this won't be a multi error
# reverse this package
log.debug("Error in action #%d for pkg_idx #%d %r", axn_idx, pkg_idx, action)
log.debug(format_exc())
reverse_excs = ()
if context.rollback_enabled:
log.error("An error occurred while %s package '%s'.\n"
"%r\n"
"Attempting to roll back.\n",
'uninstalling' if is_unlink else 'installing', Dist(pkg_data), e)
reverse_excs = UnlinkLinkTransaction._reverse_actions(
target_prefix, num_unlink_pkgs, pkg_idx, pkg_data, actions,
reverse_from_idx=axn_idx
)
raise CondaMultiError(tuple(concatv(
(e,),
reverse_excs,
)))
@staticmethod
def _reverse_actions(target_prefix, num_unlink_pkgs, pkg_idx, pkg_data, actions,
reverse_from_idx=-1):
# reverse_from_idx = -1 means reverse all actions
dist = Dist(pkg_data)
is_unlink = pkg_idx <= num_unlink_pkgs - 1
if is_unlink:
log.info("===> REVERSING PACKAGE UNLINK: %s <===\n"
" prefix=%s\n",
dist, target_prefix)
else:
log.info("===> REVERSING PACKAGE LINK: %s <===\n"
" prefix=%s\n",
dist, target_prefix)
log.debug("reversing pkg_idx #%d from axn_idx #%d", pkg_idx, reverse_from_idx)
exceptions = []
reverse_actions = actions if reverse_from_idx < 0 else actions[:reverse_from_idx+1]
for axn_idx, action in reversed(tuple(enumerate(reverse_actions))):
try:
action.reverse()
except Exception as e:
log.debug("action.reverse() error in action #%d for pkg_idx #%d %r", axn_idx,
pkg_idx, action)
log.debug(format_exc())
exceptions.append(e)
return exceptions
@staticmethod
def get_python_version(target_prefix, linked_packages_data_to_unlink, packages_info_to_link):
# this method determines the python version that will be present at the
# end of the transaction
linking_new_python = next((package_info for package_info in packages_info_to_link
if package_info.index_json_record.name == 'python'),
None)
if linking_new_python:
# is python being linked? we're done
full_version = linking_new_python.index_json_record.version
assert full_version
return get_major_minor_version(full_version)
# is python already linked and not being unlinked? that's ok too
linked_python_version = get_python_version_for_prefix(target_prefix)
if linked_python_version:
find_python = (lnkd_pkg_data for lnkd_pkg_data in linked_packages_data_to_unlink
if lnkd_pkg_data.name == 'python')
unlinking_this_python = next(find_python, None)
if unlinking_this_python is None:
# python is not being unlinked
return linked_python_version
# there won't be any python in the finished environment
return None
@staticmethod
def make_link_actions(transaction_context, package_info, target_prefix, requested_link_type):
required_quad = transaction_context, package_info, target_prefix, requested_link_type
file_link_actions = LinkPathAction.create_file_link_actions(*required_quad)
create_directory_actions = LinkPathAction.create_directory_actions(
*required_quad, file_link_actions=file_link_actions
)
create_menu_actions = MakeMenuAction.create_actions(*required_quad)
python_entry_point_actions = CreatePythonEntryPointAction.create_actions(*required_quad)
compile_pyc_actions = CompilePycAction.create_actions(*required_quad,
file_link_actions=file_link_actions)
application_entry_point_actions = CreateApplicationEntryPointAction.create_actions(
*required_quad
)
private_envs_meta_actions = CreatePrivateEnvMetaAction.create_actions(*required_quad)
all_target_short_paths = tuple(axn.target_short_path for axn in concatv(
file_link_actions,
python_entry_point_actions,
compile_pyc_actions,
application_entry_point_actions,
))
meta_create_actions = CreateLinkedPackageRecordAction.create_actions(
*required_quad, all_target_short_paths=all_target_short_paths
)
# the ordering here is significant
return tuple(concatv(
meta_create_actions,
create_directory_actions,
file_link_actions,
python_entry_point_actions,
compile_pyc_actions,
create_menu_actions,
application_entry_point_actions,
private_envs_meta_actions,
))
def run_script(prefix, dist, action='post-link', env_prefix=None):
"""
call the post-link (or pre-unlink) script, and return True on success,
False on failure
"""
path = join(prefix,
'Scripts' if on_win else 'bin',
'.%s-%s.%s' % (dist.name, action, 'bat' if on_win else 'sh'))
if not isfile(path):
return True
env = os.environ.copy()
if action == 'pre-link':
env[str('SOURCE_DIR')] = str(prefix)
warnings.warn(dals("""
Package %s uses a pre-link script. Pre-link scripts are potentially dangerous.
This is because pre-link scripts have the ability to change the package contents in the
package cache, and therefore modify the underlying files for already-created conda
environments. Future versions of conda may deprecate and ignore pre-link scripts.
""" % dist))
if on_win:
try:
command_args = [os.environ['COMSPEC'], '/c', path]
except KeyError:
return False
else:
shell_path = '/bin/sh' if 'bsd' in sys.platform else '/bin/bash'
command_args = [shell_path, path]
env[str('ROOT_PREFIX')] = sys.prefix
env[str('PREFIX')] = str(env_prefix or prefix)
env[str('PKG_NAME')] = str(dist.name)
env[str('PKG_VERSION')] = str(dist.version)
env[str('PKG_BUILDNUM')] = str(dist.build_number)
try:
log.debug("for %s at %s, executing script: $ %s",
dist, env[str('PREFIX')], ' '.join(command_args))
return _run_script(command_args, env)
finally:
messages(prefix)
def _run_script(command_args, env):
try:
check_call(command_args, env=env)
except CalledProcessError:
return False
else:
return True
def messages(prefix):
path = join(prefix, '.messages.txt')
if isfile(path):
with open(path) as fi:
fh = sys.stderr if context.json else sys.stdout
fh.write(fi.read())
rm_rf(path)
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] |
api_server.py | ChristianKreuzberger/computer.vision.101 | 0 | 30228 | <reponame>ChristianKreuzberger/computer.vision.101
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
import numpy as np
import keras
from keras.applications import imagenet_utils
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras.preprocessing import image
from keras.preprocessing.image import img_to_array
from keras.regularizers import l2
from PIL import Image
from flask import Flask
from flask_restful import Api, Resource, reqparse
import werkzeug
input_shape = (28, 28, 1)
num_classes = 10
def build_model():
model = Sequential()
model.add(Conv2D(32, (3, 3), padding='same', kernel_regularizer=l2(0.01), input_shape=input_shape))
model.add(Activation('relu'))
model.add(Conv2D(32, (5, 5), kernel_regularizer=l2(0.01)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), padding='same', kernel_regularizer=l2(0.01)))
model.add(Activation('relu'))
model.add(Conv2D(64, (5, 5), kernel_regularizer=l2(0.01)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(num_classes))
model.add(Activation('softmax'))
return model
model = build_model()
model.summary()
model.compile(loss='categorical_crossentropy',
optimizer='adam',
metrics=['accuracy'])
model.load_weights("fashion-mnist-90.h5")
model._make_predict_function()
mapping = {
0: "T-shirt/top",
1: "Trouser",
2: "Pullover",
3: "Dress",
4: "Coat",
5: "Sandal",
6: "Shirt",
7: "Sneaker",
8: "Bag",
9: "Ankle boot"
}
app = Flask(__name__)
api = Api(app)
@app.route('/')
def get_index():
return """
<html>
<head>
<title>Classify Image</title>
</head>
<body>
<form method="post" action="/classify" enctype="multipart/form-data">
File: <input type="file" name="image" /><br />
<input type="submit">
</form>
</body>
</html>
"""
@app.route('/classify', methods=['POST'])
def post_image():
parse = reqparse.RequestParser()
parse.add_argument('image', type=werkzeug.datastructures.FileStorage, location='files')
args = parse.parse_args()
if not 'image' in args or not args['image']:
return {
'message': "Please provide an image"
}, 400
img_stream = args['image'].stream
prepared_image = image.load_img(img_stream, target_size=(28, 28))
# convert input image to gray scale
prepared_image = prepared_image.convert('L')
# convert the image to a numpy array
prepared_image = image.img_to_array(prepared_image)
prepared_image = np.expand_dims(prepared_image, axis=0)
# and finally reshape the array
prepared_image = prepared_image.reshape(1, 28, 28, 1)
result = model.predict_classes(prepared_image)
classification = result[0]
import json
return json.dumps({
"classifications": result.tolist(),
"string": mapping[classification]
})
app.run(debug=True, host="0.0.0.0")
# Test with
# curl -F image=@`pwd`/fashion-mnist-handbag.png -X POST http://127.0.0.1:5000/classify
# curl -F image=@`pwd`/fashion-mnist-shoe.png -X POST http://127.0.0.1:5000/classify
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11_testing_best_practices/generate_maze_faster.py | krother/maze_run | 7 | 17856 |
# Improved version of the code from chapter 03
# created in chapter 11 to accelerate execution
import random
XMAX, YMAX = 19, 16
def create_grid_string(dots, xsize, ysize):
"""
Creates a grid of size (xx, yy)
with the given positions of dots.
"""
grid = ""
for y in range(ysize):
for x in range(xsize):
grid += "." if (x, y) in dots else "#"
grid += "\n"
return grid
def get_all_dot_positions(xsize, ysize):
"""Returns a list of (x, y) tuples covering all positions in a grid"""
return [(x,y) for x in range(1, xsize-1) for y in range(1, ysize-1)]
def get_neighbors(x, y):
"""Returns a list with the 8 neighbor positions of (x, y)"""
return [
(x, y-1), (x, y+1), (x-1, y), (x+1, y),
(x-1, y-1), (x+1, y-1), (x-1, y+1), (x+1, y+1)
]
def generate_dot_positions(xsize, ysize):
"""Creates positions of dots for a random maze"""
positions = get_all_dot_positions(xsize, ysize)
random.shuffle(positions)
dots = set()
for x, y in positions:
neighbors = get_neighbors(x, y)
free = [nb in dots for nb in neighbors]
if free.count(True) < 5:
dots.add((x, y))
return dots
def create_maze(xsize, ysize):
"""Returns a xsize*ysize maze as a string"""
dots = generate_dot_positions(xsize, ysize)
maze = create_grid_string(dots, xsize, ysize)
return maze
if __name__ == '__main__':
dots = set(((1,1), (1,2), (1,3), (2,2), (3,1), (3,2), (3,3)))
print(create_grid_string(dots, 5, 5))
positions = get_all_dot_positions(5, 5)
print(create_grid_string(positions, 5, 5))
neighbors = get_neighbors(3, 2)
print(create_grid_string(neighbors, 5, 5))
maze = create_maze(12, 7)
print(maze)
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] |
Chatbot.py | CeFlorian/ChatBot | 0 | 157474 | <filename>Chatbot.py
from chatterbot import ChatBot
from chatterbot.trainers import ListTrainer
from chatterbot.trainers import ChatterBotCorpusTrainer
import discord
import base64
from Crypto import Random
from Crypto.Hash import SHA256
from Crypto.Cipher import AES
def cipherAES(password, iv):
key = SHA256.new(password).digest()
return AES.new(key, AES.MODE_CFB, iv)
def encrypt2(plaintext, password):
iv = Random.new().read(AES.block_size)
return base64.b64encode(iv + cipherAES(password, iv).encrypt(plaintext))
def decrypt2(ciphertext, password):
d = base64.b64decode(ciphertext)
iv, ciphertext = d[:AES.block_size], d[AES.block_size:]
return cipherAES(password, iv).decrypt(ciphertext)
llaveEncripted = '<KEY>'
llave = decrypt2(llaveEncripted, b'mypass').decode("utf-8")
chat = ChatBot('Boty')
"""
talk = ['Hola', 'Que tal',
'Tengo una pregunta', 'Si, dime',
'Cuantos cursos puedo llevar en la univerisidad?', 'Lo normal son 5 cursos, para mas información acerca de los cursos y requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Cuales cursos puedo llevar en el semestre?', 'Dime de que semestre quieres conocer los cursos que corresponden',
'Primer ciclo', 'Al primer semestre correponden los siguientes cursos:\n 1590-001. DESARROLLO HUMANO Y PROFESIONAL,\n 1590-002. METODOLOGIA DE LA INVESTIGACION,\n 1590-003. CONTABILIDAD I,\n 1590-004. INTRODUCCION A LOS SISTEMAS DE COMPUTO,\n 1590-005. LOGICA DE SISTEMAS,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Segundo ciclo', 'Al segundo semestre correponden los siguientes cursos:\n 1590-006. PRECALCULO,\n 1590-007. ALGEBRA LINEAL,\n 1590-008. ALGORITMOS,\n 1590-009. CONTABILIDAD II,\n 1590-010. MATEMATICA DISCRETA,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Tercer ciclo', 'Al tercer semestre correponden los siguientes cursos:\n 1590-011. FISICA I,\n 1590-012. PROGRAMACION I,\n 1590-013. CALCULO I,\n 1590-014. PROCESO ADMINISTRATIVO,\n 1590-015. DERECHO INFORMATICO,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Cuarto ciclo', 'Al cuarto semestre correponden los siguientes cursos:\n 1590-016. MICROECONOMIA,\n 1590-017. PROGRAMACION II,\n 1590-018. CALCULO II,\n 1590-019. ESTADISTICA I,\n 1590-020. FISICA II,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Quinto ciclo', 'Al quinto semestre correponden los siguientes cursos:\n 1590-021. METODOS NUMERICOS,\n 1590-022. PROGRAMACION III,\n 1590-023. EMPRENDEDORES DE NEGOCIOS,\n 1590-024. ELECTRONICA ANALOGICA,\n 1590-025. ESTADISTICA II,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Sexto ciclo','Al sexto semestre correponden los siguientes cursos: 1590026 INVESTIGACION DE OPERACIONES. 1590027 BASES DE DATOS. 1590028 AUTOMATAS Y LENGUAJES FORMALES. 1590029 SISTEMAS OPERATIVOS I. 1590030 ELECTRONICA DIGITAL.',
'Septimo ciclo', 'Al septimo semestre correponden los siguientes cursos: 1590031 BASES DE DATOS II. 1590032 ANALISIS DE SISTEMAS I. 1590033 SISTEMAS OPERATIVOS II. 1590034 ARQUITECTURA DE COMPUTADORAS I. 1590035 COMPILADORES.',
'Octavo ciclo', 'Al octavo semestre correponden los siguientes cursos: 1590036 DESARROLLO WEB. 1590037 ANALISIS DE SISTEMAS II. 1590038 REDES DE COMPUTADORAS I. 1590039 ETICA PROFESIONAL. 1590040 ARQUITECTURA DE COMPUTADORAS II.',
'Noveno ciclo', 'Al noveno semestre correponden los siguientes cursos: 1590041 ADMINISTRACION DE TECNOLOGIAS DE INFORMACION. 1590042 INGENIERIA DE SOFTWARE. 1590043 PROYECTOD DE GRADUACION I. 1590044 REDES DE COMPUTADORAS II. 1590045 INTELIGENCIA ARTIFICIA.',
'Decimo ciclo','Al decimo semestre correponden los siguientes cursos: 1590046 TELECOMUNICACIONES. 1590047 SEMINARIOS DE TECNOLOGIAS DE INFORMACION. 1590048 ASEGURAMIENTO DE LA CALIDAD DEL SOFTWARE. 1590049 PROYECTO DE GRADUACION II. 1590050 SEGURIDAD Y AUDITORIA DE SISTEMAS.',
'Como puedo inscribirme en linea?', 'Los pasos para inscribirse son: 1. Entregar documentación en Registro y Control Académico\n 2. Pago de Matrícula\n 3. Asignación de Cursos. Los pagos puedes hacerlos por medio de la pagina de la Universidad: https://apps2.umg.edu.gt/pagos/,\r\n o\r por medio de tu banca en linea. \n Para obtener mas información sobre requisitos de ingreso visitar: https://umg.edu.gt/info/aspirantes \n Y para llenar formulario de nuevo estudiante visitar: https://apps2.umg.edu.gt/nuevosestudiantes/ Y para información sobre inscripciones visitar https://umg.edu.gt/info/inscripciones \n Y para asignar cursos en linea puedes visitar: https://umg.edu.gt/info/estudiantes/asignaciones',
'Cuales son los pasos para graduarme', 'Son los siguientes: a) 1000 horas de práctica laboral profesional: a partir del 7mo. ciclo b) Evaluación general en áreas de conocimiento (escalonado en 3 etapas): 1. Area de ciencias de la ingeniería: aprobado del 1 al 6o ciclo e inglés intermedios 4. 2. Área de análisis, diseño y Desarrollo: Aprobados del 1o. al 8o. ciclos e inglés avanzados II 3. Área de administración de tecnologías de información: Aprobados del 1o. al 10o. ciclo e inglés avanzados IV c) Trabajo de graduación ó 50% de créditos de una de las maestrías autorizadas.',
'Como hago un examen extraordinario', 'Debes de pagar 100 quetzales en tu banco y luego presentarsela a tu catedratico para tener el derecho',
'Por que no veo mi nota en el sistema', 'Puede ser por dos razones:\n 1.No estas solvente\n 2.No te examinaste',
'Cual es el proceso de cierre?, 'El proceso de cierre es el siguiente, debes tener ganados los 50 cursos que tiene la carrera para que puedas cerrar tu pensum.',
'Como apruebo mi proyecto de graduación?', '.Llevar un control de las asesorías y entrega de borradores de su Trabajo, al docente asesor y al revisor, por medio escrito haciendo constar fechas de entrega y devolución de los mismos, con las correcciones o enmiendas pertinentes. En otras palabras, el estudiante deberá llevar una bitácora del desarrollo del Trabajo de Graduación. Para mas info visita:http://cdn.umg.edu.gt/pdf/pregrados/arquitectura/normativos/normativo_trabajo_graduacion.pdf'
'Muchas gracias', 'Es un placer, Saludos']
"""
trainer = ChatterBotCorpusTrainer(chat)
trainer.train("chatterbot.corpus.spanish")
trainer = ListTrainer(chat)
#trainer.train(talk)
trainer.train(['Hola', 'Hola, como te va?',
'Tengo una pregunta', 'Si, dime...'
])
trainer.train(['como puedo inscribirme en linea', 'Los pasos para inscribirse son: 1. Entregar documentación en Registro y Control Académico\n 2. Pago de Matrícula\n 3. Asignación de Cursos. Los pagos puedes hacerlos por medio de la pagina de la Universidad: https://apps2.umg.edu.gt/pagos/,\r\n o\r por medio de tu banca en linea. \n Para obtener mas información sobre requisitos de ingreso visitar: https://umg.edu.gt/info/aspirantes \n Y para llenar formulario de nuevo estudiante visitar: https://apps2.umg.edu.gt/nuevosestudiantes/ Y para información sobre inscripciones visitar https://umg.edu.gt/info/inscripciones \n Y para asignar cursos en linea puedes visitar: https://umg.edu.gt/info/estudiantes/asignaciones',
'Cuales son los pasos para graduarme', 'Son los siguientes: a) 1000 horas de práctica laboral profesional: a partir del 7mo. ciclo b) Evaluación general en áreas de conocimiento (escalonado en 3 etapas): 1. Area de ciencias de la ingeniería: aprobado del 1 al 6o ciclo e inglés intermedios 4. 2. Área de análisis, diseño y Desarrollo: Aprobados del 1o. al 8o. ciclos e inglés avanzados II 3. Área de administración de tecnologías de información: Aprobados del 1o. al 10o. ciclo e inglés avanzados IV c) Trabajo de graduación ó 50% de créditos de una de las maestrías autorizadas.',
'como hago un examen extraordinario', 'Debes de pagar 100 quetzales en tu banco y luego presentarsela a tu catedratico para tener el derecho',
'por que no veo mi nota en el sistema', 'Puede ser por dos razones:\n 1.No estas solvente\n 2.No te examinaste',
'muchas gracias', 'Es un placer, Saludos'
])
trainer.train(['cuales y que cursos puedo llevar en el semestre', 'Dime de que semestre quieres conocer los cursos que corresponden',
'cuantos cursos llevaria en la U Universidad', 'Lo normal son 5 cursos, para mas información acerca de los cursos y requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'primer 1er 1 ciclo', 'Al primer semestre correponden los siguientes cursos:\n 1590-001. DESARROLLO HUMANO Y PROFESIONAL,\n 1590-002. METODOLOGIA DE LA INVESTIGACION,\n 1590-003. CONTABILIDAD I,\n 1590-004. INTRODUCCION A LOS SISTEMAS DE COMPUTO,\n 1590-005. LOGICA DE SISTEMAS,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'segundo 2do 2 ciclo', 'Al segundo semestre correponden los siguientes cursos:\n 1590-006. PRECALCULO,\n 1590-007. ALGEBRA LINEAL,\n 1590-008. ALGORITMOS,\n 1590-009. CONTABILIDAD II,\n 1590-010. MATEMATICA DISCRETA,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'tercer 3ro 3 ciclo', 'Al tercer semestre correponden los siguientes cursos:\n 1590-011. FISICA I,\n 1590-012. PROGRAMACION I,\n 1590-013. CALCULO I,\n 1590-014. PROCESO ADMINISTRATIVO,\n 1590-015. DERECHO INFORMATICO,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'cuarto 4to 4 ciclo', 'Al cuarto semestre correponden los siguientes cursos:\n 1590-016. MICROECONOMIA,\n 1590-017. PROGRAMACION II,\n 1590-018. CALCULO II,\n 1590-019. ESTADISTICA I,\n 1590-020. FISICA II,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'quinto ciclo', 'Al quinto semestre correponden los siguientes cursos:\n 1590-021. METODOS NUMERICOS,\n 1590-022. PROGRAMACION III,\n 1590-023. EMPRENDEDORES DE NEGOCIOS,\n 1590-024. ELECTRONICA ANALOGICA,\n 1590-025. ESTADISTICA II,\n para mas información acerca de los cursos y sus requisitos puedes visitar: https://apps2.umg.edu.gt/pensum',
'Sexto ciclo','Al sexto semestre correponden los siguientes cursos: 1590026 INVESTIGACION DE OPERACIONES. 1590027 BASES DE DATOS. 1590028 AUTOMATAS Y LENGUAJES FORMALES. 1590029 SISTEMAS OPERATIVOS I. 1590030 ELECTRONICA DIGITAL.',
'Septimo ciclo', 'Al septimo semestre correponden los siguientes cursos: 1590031 BASES DE DATOS II. 1590032 ANALISIS DE SISTEMAS I. 1590033 SISTEMAS OPERATIVOS II. 1590034 ARQUITECTURA DE COMPUTADORAS I. 1590035 COMPILADORES.',
'Oct<NAME>', 'Al octavo semestre correponden los siguientes cursos: 1590036 DESARROLLO WEB. 1590037 ANALISIS DE SISTEMAS II. 1590038 REDES DE COMPUTADORAS I. 1590039 ETICA PROFESIONAL. 1590040 ARQUITECTURA DE COMPUTADORAS II.',
'Noveno ciclo', 'Al noveno semestre correponden los siguientes cursos: 1590041 ADMINISTRACION DE TECNOLOGIAS DE INFORMACION. 1590042 INGENIERIA DE SOFTWARE. 1590043 PROYECTOD DE GRADUACION I. 1590044 REDES DE COMPUTADORAS II. 1590045 INTELIGENCIA ARTIFICIA.',
'Decimo ciclo','Al decimo semestre correponden los siguientes cursos: 1590046 TELECOMUNICACIONES. 1590047 SEMINARIOS DE TECNOLOGIAS DE INFORMACION. 1590048 ASEGURAMIENTO DE LA CALIDAD DEL SOFTWARE. 1590049 PROYECTO DE GRADUACION II. 1590050 SEGURIDAD Y AUDITORIA DE SISTEMAS.',
])
#"""
#while True:
# peticion = input('Tu: ')
# respuesta = chat.get_response(peticion)
# print('BOOT: ', respuesta)
disparate='Así no va!'
entradaAnterior=""
respAnterior=""
async def validaciones(peticion):
global disparate
global entradaAnterior
global respAnterior
if respAnterior == '¿Qué debería haber dicho?':
entradaCorreccion = peticion
trainer.train([entradaAnterior, entradaCorreccion])
respuesta = "He aprendiendo que cuando digas {} debo responder {}".format(entradaAnterior, entradaCorreccion)
elif peticion == disparate:
respuesta = '¿Qué debería haber dicho?'
else:
entradaAnterior = peticion
respuesta = chat.get_response(peticion)
respAnterior = respuesta
return respuesta
while True:
cliente = discord.Client()
@cliente.event
async def on_message(mensaje):
if mensaje.author == cliente.user:
return
peticion = mensaje.content
respuesta = await validaciones(peticion)
if not respuesta or respuesta == '':
await mensaje.channel.send('No se ha podido obtener respuesta, por favor intente nuevamente.')
else:
await mensaje.channel.send(respuesta)
cliente.run(llave)
"""
while True:
peticion = input('Tu: ')
respuesta = chat.get_response(peticion)
if respAnterior == '¿Qué debería haber dicho?':
entradaCorreccion = peticion
trainer.train([entradaAnterior, entradaCorreccion])
respuesta = "He aprendiendo que cuando digas {} debo responder {}".format(entradaAnterior, entradaCorreccion)
if peticion == 'Asi no va!':
respuesta = '¿Qué debería haber dicho?'
else:
entradaAnterior = peticion
respAnterior = respuesta
print('BOOT: ', respuesta)
"""
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2890,
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2311,
8443,
13,
1678,
736,
2967,
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29890,
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440,
718,
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8096,
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5630,
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316,
1232,
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2858,
5054,
275,
12870,
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1998,
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29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
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4141,
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398,
23592,
13,
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17669,
6201,
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417,
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3031,
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14515,
2818,
264,
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29945,
29929,
29900,
29899,
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29900,
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349,
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29907,
1964,
29907,
29965,
3927,
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1660,
29954,
4574,
5194,
29902,
3919,
29949,
5012,
17900,
315,
1964,
1367,
3035,
5012,
29931,
7791,
7818,
12982,
1525,
29889,
29871,
29896,
29945,
29929,
29900,
29900,
29946,
29929,
13756,
29979,
13845,
29949,
5012,
18016,
3035,
29965,
2477,
2725,
1944,
29889,
29871,
29896,
29945,
29929,
29900,
29900,
29945,
29900,
3725,
29954,
4574,
1367,
3035,
612,
319,
15789,
1806,
1955,
10764,
5012,
317,
9047,
26862,
29903,
29889,
23592,
13,
4706,
525,
1523,
29877,
2653,
23162,
1663,
699,
20397,
1004,
427,
26241,
29973,
742,
525,
29286,
2331,
359,
1702,
1663,
699,
20397,
344,
1487,
29901,
29871,
29896,
29889,
4284,
1727,
279,
1842,
2709,
427,
2169,
19150,
343,
11264,
7255,
15335,
1417,
29905,
29876,
29871,
29906,
29889,
349,
4425,
316,
5345,
29878,
13984,
29905,
29876,
29871,
29941,
29889,
1094,
647,
2709,
316,
315,
1295,
359,
29889,
4602,
10203,
359,
2653,
11696,
14557,
5409,
1277,
19301,
316,
425,
10203,
1099,
316,
425,
12824,
29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
13573,
359,
29914,
2053,
29878,
29905,
29876,
288,
29905,
29878,
1277,
19301,
316,
5291,
9892,
1113,
427,
26241,
29889,
320,
29876,
12994,
14403,
759,
5516,
29717,
4166,
5054,
275,
12870,
316,
2348,
28857,
1998,
3673,
29901,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
4692,
381,
3794,
320,
29876,
612,
1702,
301,
2435,
279,
883,
1070,
601,
316,
15671,
13497,
12361,
1998,
3673,
29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
29876,
434,
23517,
342,
4749,
3794,
29914,
29871,
612,
1702,
29717,
4166,
1663,
699,
6739,
2884,
1998,
3673,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
1144,
699,
6739,
2884,
320,
29876,
612,
1702,
408,
647,
279,
18580,
359,
427,
26241,
2653,
11696,
1998,
3673,
29901,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
342,
4749,
3794,
29914,
294,
647,
6027,
23592,
13,
4706,
525,
29907,
950,
267,
1487,
1232,
2331,
359,
1702,
10591,
279,
1004,
742,
525,
29903,
265,
1232,
29673,
29901,
263,
29897,
29871,
29896,
29900,
29900,
29900,
4029,
294,
316,
544,
18343,
983,
10212,
284,
13091,
1848,
29901,
263,
8019,
628,
29871,
29955,
4346,
29889,
18286,
417,
289,
29897,
382,
4387,
2709,
2498,
427,
3976,
12588,
316,
11515,
9043,
313,
267,
1052,
265,
912,
427,
29871,
29941,
634,
481,
294,
1125,
29871,
29896,
29889,
18320,
316,
274,
819,
3465,
316,
425,
24386,
631,
1553,
29901,
11712,
29890,
912,
628,
29871,
29896,
394,
29871,
29953,
29877,
18286,
417,
321,
5102,
1006,
2168,
2363,
29871,
29946,
29889,
29871,
29906,
29889,
7260,
5638,
316,
385,
2464,
15773,
29892,
10267,
8266,
343,
2726,
279,
20426,
29901,
319,
22795,
2255,
628,
29871,
29896,
29877,
29889,
394,
29871,
29947,
29877,
29889,
18286,
5409,
321,
5102,
1029,
4096,
2255,
1944,
29871,
29941,
29889,
7260,
5638,
316,
4113,
12496,
1290,
316,
20790,
1189,
8577,
316,
29717,
29901,
319,
22795,
2255,
628,
29871,
29896,
29877,
29889,
394,
29871,
29896,
29900,
29877,
29889,
18286,
417,
321,
5102,
1029,
4096,
2255,
6599,
274,
29897,
3201,
29890,
7069,
316,
10591,
2709,
17604,
29871,
29945,
29900,
29995,
316,
2181,
2487,
12870,
316,
1185,
316,
1869,
611,
16444,
8577,
8478,
466,
3922,
29889,
23592,
13,
4706,
525,
1523,
29877,
298,
4425,
443,
4392,
264,
4805,
4194,
2628,
742,
525,
10251,
267,
316,
10203,
279,
29871,
29896,
29900,
29900,
439,
6618,
2122,
427,
5291,
9892,
1111,
343,
19102,
2198,
1503,
3100,
263,
5291,
274,
630,
3605,
1417,
1702,
22975,
560,
14923,
1859,
23592,
13,
4706,
525,
29925,
272,
712,
694,
2453,
29877,
3737,
451,
29874,
427,
560,
10502,
742,
525,
29925,
29884,
2742,
724,
1277,
3248,
8006,
2873,
3583,
29876,
29871,
29896,
29889,
3782,
22388,
899,
794,
29872,
29905,
29876,
29871,
29906,
29889,
3782,
734,
4392,
262,
4350,
23592,
13,
4706,
525,
29907,
950,
831,
560,
14177,
29877,
316,
274,
6349,
14579,
525,
6489,
14177,
29877,
316,
274,
6349,
831,
560,
18436,
29892,
2553,
267,
22975,
9581,
2255,
1232,
29871,
29945,
29900,
18580,
359,
712,
10258,
425,
22750,
1702,
712,
2653,
287,
294,
274,
3127,
279,
5291,
10420,
398,
29889,
23592,
13,
4706,
525,
1523,
29877,
21783,
434,
833,
3737,
28255,
316,
10591,
2709,
29973,
742,
15300,
29931,
280,
1707,
443,
2761,
316,
1869,
27985,
272,
8577,
343,
875,
1727,
29874,
316,
9820,
3665,
2361,
316,
480,
3201,
29890,
7069,
29892,
394,
1574,
2016,
27985,
272,
343,
394,
337,
19188,
29892,
1277,
19301,
3966,
9296,
447,
27182,
1040,
279,
1238,
27148,
316,
875,
1727,
29874,
343,
316,
1555,
16249,
316,
1232,
21436,
359,
29892,
378,
1869,
14515,
14980,
288,
427,
2460,
355,
294,
13499,
262,
5326,
29889,
1174,
16255,
27555,
3417,
29892,
560,
13497,
12361,
316,
495,
29976,
19804,
1707,
1185,
2586,
25968,
2207,
628,
27862,
628,
3201,
29890,
7069,
316,
1632,
13467,
2709,
29889,
12994,
5516,
5235,
1998,
2028,
29901,
1124,
597,
13687,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
5140,
29914,
1457,
629,
2255,
29914,
19862,
4496,
2002,
29914,
12324,
29002,
29914,
12324,
11692,
29918,
3018,
29890,
7069,
29918,
5105,
29884,
16337,
29889,
5140,
29915,
30004,
13,
4706,
525,
29924,
987,
294,
2646,
3465,
742,
525,
14190,
443,
2174,
2265,
29892,
3956,
566,
359,
2033,
30004,
13,
4706,
9995,
30004,
13,
4706,
6756,
13,
3018,
4983,
353,
678,
2620,
29933,
327,
12521,
13364,
5323,
4983,
29898,
13496,
8443,
13,
3018,
4983,
29889,
14968,
703,
305,
2620,
7451,
29889,
2616,
13364,
29889,
9653,
728,
1159,
539,
6756,
13,
29871,
6756,
13,
3018,
4983,
353,
2391,
5323,
4983,
29898,
13496,
8443,
13,
29937,
3018,
4983,
29889,
14968,
29898,
29873,
2235,
8443,
13,
30004,
13,
30004,
13,
3018,
4983,
29889,
14968,
18959,
29950,
2963,
742,
525,
29950,
2963,
29892,
1986,
734,
2947,
29973,
23592,
13,
4706,
525,
29911,
22260,
1185,
16177,
16138,
742,
525,
25598,
29892,
270,
603,
856,
29915,
30004,
13,
308,
2314,
30004,
13,
30004,
13,
3018,
4983,
29889,
14968,
18959,
23700,
2653,
23162,
1663,
699,
20397,
1004,
427,
26241,
742,
525,
29286,
2331,
359,
1702,
1663,
699,
20397,
344,
1487,
29901,
29871,
29896,
29889,
4284,
1727,
279,
1842,
2709,
427,
2169,
19150,
343,
11264,
7255,
15335,
1417,
29905,
29876,
29871,
29906,
29889,
349,
4425,
316,
5345,
29878,
13984,
29905,
29876,
29871,
29941,
29889,
1094,
647,
2709,
316,
315,
1295,
359,
29889,
4602,
10203,
359,
2653,
11696,
14557,
5409,
1277,
19301,
316,
425,
10203,
1099,
316,
425,
12824,
29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
13573,
359,
29914,
2053,
29878,
29905,
29876,
288,
29905,
29878,
1277,
19301,
316,
5291,
9892,
1113,
427,
26241,
29889,
320,
29876,
12994,
14403,
759,
5516,
29717,
4166,
5054,
275,
12870,
316,
2348,
28857,
1998,
3673,
29901,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
4692,
381,
3794,
320,
29876,
612,
1702,
301,
2435,
279,
883,
1070,
601,
316,
15671,
13497,
12361,
1998,
3673,
29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
29876,
434,
23517,
342,
4749,
3794,
29914,
29871,
612,
1702,
29717,
4166,
1663,
699,
6739,
2884,
1998,
3673,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
1144,
699,
6739,
2884,
320,
29876,
612,
1702,
408,
647,
279,
18580,
359,
427,
26241,
2653,
11696,
1998,
3673,
29901,
2045,
597,
398,
29887,
29889,
6085,
29889,
4141,
29914,
3888,
29914,
342,
4749,
3794,
29914,
294,
647,
6027,
23592,
13,
539,
525,
29907,
950,
267,
1487,
1232,
2331,
359,
1702,
10591,
279,
1004,
742,
525,
29903,
265,
1232,
29673,
29901,
263,
29897,
29871,
29896,
29900,
29900,
29900,
4029,
294,
316,
544,
18343,
983,
10212,
284,
13091,
1848,
29901,
263,
8019,
628,
29871,
29955,
4346,
29889,
18286,
417,
289,
29897,
382,
4387,
2709,
2498,
427,
3976,
12588,
316,
11515,
9043,
313,
267,
1052,
265,
912,
427,
29871,
29941,
634,
481,
294,
1125,
29871,
29896,
29889,
18320,
316,
274,
819,
3465,
316,
425,
24386,
631,
1553,
29901,
11712,
29890,
912,
628,
29871,
29896,
394,
29871,
29953,
29877,
18286,
417,
321,
5102,
1006,
2168,
2363,
29871,
29946,
29889,
29871,
29906,
29889,
7260,
5638,
316,
385,
2464,
15773,
29892,
10267,
8266,
343,
2726,
279,
20426,
29901,
319,
22795,
2255,
628,
29871,
29896,
29877,
29889,
394,
29871,
29947,
29877,
29889,
18286,
5409,
321,
5102,
1029,
4096,
2255,
1944,
29871,
29941,
29889,
7260,
5638,
316,
4113,
12496,
1290,
316,
20790,
1189,
8577,
316,
29717,
29901,
319,
22795,
2255,
628,
29871,
29896,
29877,
29889,
394,
29871,
29896,
29900,
29877,
29889,
18286,
417,
321,
5102,
1029,
4096,
2255,
6599,
274,
29897,
3201,
29890,
7069,
316,
10591,
2709,
17604,
29871,
29945,
29900,
29995,
316,
2181,
2487,
12870,
316,
1185,
316,
1869,
611,
16444,
8577,
8478,
466,
3922,
29889,
23592,
13,
4706,
525,
23700,
298,
4425,
443,
4392,
264,
4805,
4194,
2628,
742,
525,
10251,
267,
316,
10203,
279,
29871,
29896,
29900,
29900,
439,
6618,
2122,
427,
5291,
9892,
1111,
343,
19102,
2198,
1503,
3100,
263,
5291,
274,
630,
3605,
1417,
1702,
22975,
560,
14923,
1859,
23592,
13,
4706,
525,
1971,
712,
694,
2453,
29877,
3737,
451,
29874,
427,
560,
10502,
742,
525,
29925,
29884,
2742,
724,
1277,
3248,
8006,
2873,
3583,
29876,
29871,
29896,
29889,
3782,
22388,
899,
794,
29872,
29905,
29876,
29871,
29906,
29889,
3782,
734,
4392,
262,
4350,
23592,
13,
4706,
525,
29885,
987,
294,
2646,
3465,
742,
525,
14190,
443,
2174,
2265,
29892,
3956,
566,
359,
29915,
30004,
13,
308,
2314,
30004,
13,
3018,
4983,
29889,
14968,
18959,
29883,
950,
267,
343,
712,
18580,
359,
2653,
23162,
19804,
1707,
427,
560,
3031,
15679,
742,
525,
29928,
603,
316,
712,
3031,
15679,
439,
631,
267,
11515,
261,
1232,
18580,
359,
712,
3928,
264,
23592,
13,
4706,
525,
4979,
424,
359,
18580,
359,
19804,
1707,
423,
427,
425,
501,
12824,
742,
525,
3410,
4226,
1487,
29871,
29945,
18580,
359,
29892,
1702,
5516,
29717,
1274,
24340,
316,
1232,
18580,
359,
343,
5054,
275,
12870,
2653,
11696,
1998,
3673,
29901,
2045,
597,
13371,
29906,
29889,
398,
29887,
29889,
6085,
29889,
4141,
29914,
29886,
575,
398,
742,
6756,
13,
4706,
525,
558,
4193,
29871,
29896,
261,
29871,
29896,
18286,
417,
742,
525,
2499,
7130,
3031,
15679,
14515,
2818,
264,
1232,
29673,
18580,
359,
3583,
29876,
29871,
29896,
29945,
29929,
29900,
29899,
29900,
29900,
29896,
29889,
18539,
1718,
1672,
2208,
29949,
379,
29965,
1529,
6632,
612,
13756,
29943,
2890,
2725,
1964,
2053,
29876,
29871,
29896,
29945,
29929,
29900,
29899,
29900,
29900,
29906,
29889,
341,
2544,
29949,
3970,
14480,
10764,
5012,
17900,
2672,
12064,
1254,
6259,
2477,
2725,
2053,
29876,
29871,
29896,
29945,
29929,
29900,
29899,
29900,
29900,
29941,
29889,
8707,
29911,
2882,
6227,
1367,
3035,
306,
2053,
29876,
29871,
29896,
29945,
29929,
29900,
29899,
29900,
29900,
29946,
29889,
19578,
1672,
14849,
4174,
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15945,
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13,
2
] |
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