code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import os
import time
import requests
from tweepy.parsers import JSONParser
from tweepy.error import TweepError, RateLimitError, is_rate_limit_error_message
from tweepy.models import Status
MEDIA_ENDPOINT_URL = 'https://upload.twitter.com/1.1/media/upload.json'
POST_TWEET_URL = 'https://api.twitter.com/1.1/statuses/... | docker/cpdpbot/cpdpbot/video_tweet.py | import os
import time
import requests
from tweepy.parsers import JSONParser
from tweepy.error import TweepError, RateLimitError, is_rate_limit_error_message
from tweepy.models import Status
MEDIA_ENDPOINT_URL = 'https://upload.twitter.com/1.1/media/upload.json'
POST_TWEET_URL = 'https://api.twitter.com/1.1/statuses/... | 0.282988 | 0.086787 |
from pyfiglet import Figlet
f = Figlet(font='slant')
print('Script Created by : ')
print(f.renderText('gaurav'))
sound = int(input("Do you want sound : 1 for yes , 2 for no : "))
sound = 0 if sound == 2 else 1
print('****************************************************')
if sound :
print("Sound is set to on ! \nOn... | script.py | from pyfiglet import Figlet
f = Figlet(font='slant')
print('Script Created by : ')
print(f.renderText('gaurav'))
sound = int(input("Do you want sound : 1 for yes , 2 for no : "))
sound = 0 if sound == 2 else 1
print('****************************************************')
if sound :
print("Sound is set to on ! \nOn... | 0.257205 | 0.219118 |
from abc import ABC, abstractmethod
import tensorflow as tf
from cvnn import logger
import sys
from typing import Union
from cvnn.layers import t_layers_shape
class Optimizer(ABC):
def __init__(self):
pass
def compile(self, shape: t_layers_shape) -> None:
pass
def optimize(self, variable... | cvnn/optimizers.py | from abc import ABC, abstractmethod
import tensorflow as tf
from cvnn import logger
import sys
from typing import Union
from cvnn.layers import t_layers_shape
class Optimizer(ABC):
def __init__(self):
pass
def compile(self, shape: t_layers_shape) -> None:
pass
def optimize(self, variable... | 0.834171 | 0.468243 |
from smbus2 import SMBus, i2c_msg
_ADS1X15_DEFAULT_ADDRESS = 0x48
_ADS1X15_POINTER_CONVERSION = 0x00
_ADS1X15_POINTER_CONFIG = 0x01
_ADS1X15_CONFIG_OS_SINGLE = 0x8000
_ADS1X15_CONFIG_MUX_OFFSET = 12
_ADS1X15_CONFIG_COMP_QUE_DISABLE = 0x0003
_ADS1X15_CONFIG_GAIN = {
2 / 3: 0x0000,
1: 0x0200,
2: 0x0400,
... | components/ADC_LCD/ads1115/ads1x15.py | from smbus2 import SMBus, i2c_msg
_ADS1X15_DEFAULT_ADDRESS = 0x48
_ADS1X15_POINTER_CONVERSION = 0x00
_ADS1X15_POINTER_CONFIG = 0x01
_ADS1X15_CONFIG_OS_SINGLE = 0x8000
_ADS1X15_CONFIG_MUX_OFFSET = 12
_ADS1X15_CONFIG_COMP_QUE_DISABLE = 0x0003
_ADS1X15_CONFIG_GAIN = {
2 / 3: 0x0000,
1: 0x0200,
2: 0x0400,
... | 0.766031 | 0.36923 |
from urllib.parse import quote_plus
from requests import get
import os
import globals
token = os.environ['TOKEN']
url = f'https://api.telegram.org/bot{token}/'
__all__ = [
'chunks',
'copy_file_name',
'delete',
'download_file',
'escape_md',
'get_reply',
'send',
'send... | functions/utils.py | from urllib.parse import quote_plus
from requests import get
import os
import globals
token = os.environ['TOKEN']
url = f'https://api.telegram.org/bot{token}/'
__all__ = [
'chunks',
'copy_file_name',
'delete',
'download_file',
'escape_md',
'get_reply',
'send',
'send... | 0.148417 | 0.073663 |
import numpy as np
from scipy.linalg import pinv
def distance_vec_rep_of_fibers(fi):
'''This function calculates the distance of each point on the fiber fr m th first point
Input:
fi - a (n,3) np.ndarray of a single fiber. n is the number of points that represent the fiber
Output:
d... | clustering/poly_representaion_fibers.py | import numpy as np
from scipy.linalg import pinv
def distance_vec_rep_of_fibers(fi):
'''This function calculates the distance of each point on the fiber fr m th first point
Input:
fi - a (n,3) np.ndarray of a single fiber. n is the number of points that represent the fiber
Output:
d... | 0.822759 | 0.810329 |
import os
from django.db import models
from django.contrib.auth.models import User
from ckeditor_uploader.fields import RichTextUploadingField
from applications.alumniprofile.models import Profile
from applications.events_news.models import Event
from applications.gallery.models import Album
def upload_photo(instance... | applications/chapter/models.py | import os
from django.db import models
from django.contrib.auth.models import User
from ckeditor_uploader.fields import RichTextUploadingField
from applications.alumniprofile.models import Profile
from applications.events_news.models import Event
from applications.gallery.models import Album
def upload_photo(instance... | 0.444806 | 0.113973 |
import os
import torch
import numpy as np
from utils.datasets import DeepFashionDataset
from torchvision.transforms import Compose
from torchvision.transforms import Resize
from torchvision.transforms import ToTensor
from torchvision.transforms import Normalize
from config.deep_fashion import DeepFashionConfig as cfg
f... | plt_emb.py | import os
import torch
import numpy as np
from utils.datasets import DeepFashionDataset
from torchvision.transforms import Compose
from torchvision.transforms import Resize
from torchvision.transforms import ToTensor
from torchvision.transforms import Normalize
from config.deep_fashion import DeepFashionConfig as cfg
f... | 0.529507 | 0.54468 |
import importlib
import json
from typing import Dict, List, Optional
import requests
from pydantic import BaseSettings, Field, root_validator, validator
from pydantic.types import Path
DEFAULT_CONFIG_FILE_PATH = str(Path.home().joinpath(".emmet.json"))
class EmmetSettings(BaseSettings):
"""
Settings for the... | emmet-core/emmet/core/settings.py | import importlib
import json
from typing import Dict, List, Optional
import requests
from pydantic import BaseSettings, Field, root_validator, validator
from pydantic.types import Path
DEFAULT_CONFIG_FILE_PATH = str(Path.home().joinpath(".emmet.json"))
class EmmetSettings(BaseSettings):
"""
Settings for the... | 0.797004 | 0.362997 |
import random
import sys
import multiprocessing
from collections import namedtuple
from wicked21st.graph import load_graph, Graph, save_graph, Cascades
import graphviz
DEBUG = False
rand = random.Random(42)
if len(sys.argv) > 1:
graph_file = sys.argv[1]
else:
import config
graph_file = config.GRAPH
... | graph_to_cascades.py |
import random
import sys
import multiprocessing
from collections import namedtuple
from wicked21st.graph import load_graph, Graph, save_graph, Cascades
import graphviz
DEBUG = False
rand = random.Random(42)
if len(sys.argv) > 1:
graph_file = sys.argv[1]
else:
import config
graph_file = config.GRAPH
... | 0.192388 | 0.291813 |
# template file: justice_py_sdk_codegen/__main__.py
# justice-iam-service (5.10.1)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# pylint... | accelbyte_py_sdk/ext/iam.py |
# template file: justice_py_sdk_codegen/__main__.py
# justice-iam-service (5.10.1)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# pylint... | 0.375248 | 0.039122 |
import os
import gzip
import logging
import numpy as np
import unidecode
from transformers import AutoTokenizer
from probing.data.base_data import BaseDataset, DataFields
class WLSTMFields(DataFields):
_fields = (
'probe_target', 'label', 'probe_target_len', 'target_idx',
'raw_idx', 'raw_target... | probing/data/sentence_probe_data.py |
import os
import gzip
import logging
import numpy as np
import unidecode
from transformers import AutoTokenizer
from probing.data.base_data import BaseDataset, DataFields
class WLSTMFields(DataFields):
_fields = (
'probe_target', 'label', 'probe_target_len', 'target_idx',
'raw_idx', 'raw_target... | 0.609524 | 0.121165 |
from os.path import abspath
from os.path import dirname
from os.path import join
from glob import glob
import subprocess
from Bio import SeqIO
from click.testing import CliRunner
import click
import pandas as pd
import pytest
from click_demultiplex import cli
from click_demultiplex import commands
ROOT = abspath(d... | tests/test_commands.py |
from os.path import abspath
from os.path import dirname
from os.path import join
from glob import glob
import subprocess
from Bio import SeqIO
from click.testing import CliRunner
import click
import pandas as pd
import pytest
from click_demultiplex import cli
from click_demultiplex import commands
ROOT = abspath(d... | 0.413596 | 0.372619 |
import argparse
import numpy as np
from data_loader import load_data
from train import train
np.random.seed(555)
parser = argparse.ArgumentParser()
# movie
parser.add_argument('--dataset', type=str, default='movie', help='which dataset to use')
parser.add_argument('--n_epochs', type=int, default=20, help='the numbe... | src/main.py | import argparse
import numpy as np
from data_loader import load_data
from train import train
np.random.seed(555)
parser = argparse.ArgumentParser()
# movie
parser.add_argument('--dataset', type=str, default='movie', help='which dataset to use')
parser.add_argument('--n_epochs', type=int, default=20, help='the numbe... | 0.564939 | 0.099558 |
import unittest
from actionlib.simple_action_client import SimpleActionClient
import rospy
from actionlib_msgs.msg import GoalStatus
from std_msgs.msg import Int32
from std_srvs.srv import SetBool, SetBoolRequest, SetBoolResponse
from actionlib_tutorials.msg import (FibonacciAction, FibonacciGoal, FibonacciResult,
... | ros_bt_py/test/rostest/test_ros_leaf_utility.py |
import unittest
from actionlib.simple_action_client import SimpleActionClient
import rospy
from actionlib_msgs.msg import GoalStatus
from std_msgs.msg import Int32
from std_srvs.srv import SetBool, SetBoolRequest, SetBoolResponse
from actionlib_tutorials.msg import (FibonacciAction, FibonacciGoal, FibonacciResult,
... | 0.508788 | 0.249527 |
from dataclasses import dataclass, field
from datetime import datetime
from notion.client import NotionClient
from notion.collection import CollectionView, CollectionRowBlock, NotionDate
from utils import MetaSingleton
from typing import Dict, List, Set
import logging
logger = logging.getLogger(__name__)
def check_a... | nbot/clients/notion_db.py | from dataclasses import dataclass, field
from datetime import datetime
from notion.client import NotionClient
from notion.collection import CollectionView, CollectionRowBlock, NotionDate
from utils import MetaSingleton
from typing import Dict, List, Set
import logging
logger = logging.getLogger(__name__)
def check_a... | 0.66769 | 0.100481 |
__author__ = "<NAME>"
__maintainer__ = __author__
import cython
import numpy as np
from .general import AbstractDetector
class FKMDetector(AbstractDetector):
"""Rainflow detector as described in FKM non linear.
The algorithm has been published by Clormann & Seeger 1985 and has
been cited heavily since... | src/pylife/stress/rainflow/fkm.py |
__author__ = "<NAME>"
__maintainer__ = __author__
import cython
import numpy as np
from .general import AbstractDetector
class FKMDetector(AbstractDetector):
"""Rainflow detector as described in FKM non linear.
The algorithm has been published by Clormann & Seeger 1985 and has
been cited heavily since... | 0.850748 | 0.421076 |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Category',
fields=[
('category', models.CharField(max_leng... | studenthub/games/trivia/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Category',
fields=[
('category', models.CharField(max_leng... | 0.61057 | 0.188511 |
import argparse
import logging
import numpy as np
from cv2 import resize
from lib.scene import Pose
from lib.homography import getFrameFlattening, getFramePxlsInMeter
import lib.conventions
from lib.iterateScenes import iterateCamerasPoses
def makePitchAndSizeMaps(camera_id, pose_id, dry_run=False):
''' Generates ... | shuffler/lib/scenes/MakePitchAndSizeMaps.py |
import argparse
import logging
import numpy as np
from cv2 import resize
from lib.scene import Pose
from lib.homography import getFrameFlattening, getFramePxlsInMeter
import lib.conventions
from lib.iterateScenes import iterateCamerasPoses
def makePitchAndSizeMaps(camera_id, pose_id, dry_run=False):
''' Generates ... | 0.620852 | 0.263762 |
import unittest
import numpy as np
import matplotlib.pyplot as plt
import lmfit
from pycqed.analysis.tools.plotting import SI_prefix_and_scale_factor
from pycqed.analysis.tools.plotting import set_xlabel, set_ylabel
from pycqed.analysis.tools.plotting import SI_val_to_msg_str
from pycqed.analysis.tools.plotting import... | pycqed/tests/analysis/test_tools_plotting.py | import unittest
import numpy as np
import matplotlib.pyplot as plt
import lmfit
from pycqed.analysis.tools.plotting import SI_prefix_and_scale_factor
from pycqed.analysis.tools.plotting import set_xlabel, set_ylabel
from pycqed.analysis.tools.plotting import SI_val_to_msg_str
from pycqed.analysis.tools.plotting import... | 0.752104 | 0.529385 |
import time
import praw
__all__ = ['PrawOAuth2Mini']
REDIRECT_URL = 'http://127.0.0.1:9999/authorize_callback'
SCOPES = ['identity', 'read']
EXPIRY_DURATION = 3500
class PrawOAuth2Mini:
"""
Creates a `PrawOAuth2Mini` instance. `PrawOAuth2Mini` meant to be
used in the bot and it needs valid `access_to... | prawoauth2/PrawOAuth2Mini.py |
import time
import praw
__all__ = ['PrawOAuth2Mini']
REDIRECT_URL = 'http://127.0.0.1:9999/authorize_callback'
SCOPES = ['identity', 'read']
EXPIRY_DURATION = 3500
class PrawOAuth2Mini:
"""
Creates a `PrawOAuth2Mini` instance. `PrawOAuth2Mini` meant to be
used in the bot and it needs valid `access_to... | 0.63375 | 0.257187 |
import random
class FewshotSampleBase:
'''
Abstract Class
DO NOT USE
Build your own Sample class and inherit from this class
'''
def __init__(self):
self.class_count = {}
def get_class_count(self):
'''
return a dictionary of {class_name:count} in format {any : int}
... | src/fewnerd/fewnerd/util/fewshotsampler.py | import random
class FewshotSampleBase:
'''
Abstract Class
DO NOT USE
Build your own Sample class and inherit from this class
'''
def __init__(self):
self.class_count = {}
def get_class_count(self):
'''
return a dictionary of {class_name:count} in format {any : int}
... | 0.68742 | 0.320901 |
import matplotlib.pyplot as plt
import numpy as np
from misc.ansi_color_codes import ACC
def gen_plot(timeline, filename, title):
if not isinstance(timeline, list):
timeline = [timeline]
plt.figure(10000)
plt.clf()
for i in range(len(timeline)): plt.plot(timeline[i])
plt.title(title)
... | misc/output.py |
import matplotlib.pyplot as plt
import numpy as np
from misc.ansi_color_codes import ACC
def gen_plot(timeline, filename, title):
if not isinstance(timeline, list):
timeline = [timeline]
plt.figure(10000)
plt.clf()
for i in range(len(timeline)): plt.plot(timeline[i])
plt.title(title)
... | 0.423458 | 0.447702 |
import os
import shutil
import subprocess
print " "
print "==============================="
print "| Frostfall Release Builder |"
print "| \/ |"
print "| _\_\/\/_/_ |"
print "| _\_\/_/_ |"
print "| __/_/\_\__ |"
print "| / /\/\ \ ... | Frostfall_BuildRelease.py | import os
import shutil
import subprocess
print " "
print "==============================="
print "| Frostfall Release Builder |"
print "| \/ |"
print "| _\_\/\/_/_ |"
print "| _\_\/_/_ |"
print "| __/_/\_\__ |"
print "| / /\/\ \ ... | 0.096025 | 0.033812 |
import logging
from makobot.utils import reaction_to_int
logger = logging.getLogger(__name__)
class Plugin(object):
@property
def enabled(self):
"""
REturns true if the plugin has been enabled or false if not.
Typically this will check if the necessary environment variables are
... | makobot/plugins/base.py |
import logging
from makobot.utils import reaction_to_int
logger = logging.getLogger(__name__)
class Plugin(object):
@property
def enabled(self):
"""
REturns true if the plugin has been enabled or false if not.
Typically this will check if the necessary environment variables are
... | 0.550124 | 0.351172 |
import datetime
from django.urls import reverse
from systori.lib.testing import ClientTestCase
from ..project.factories import ProjectFactory
from .factories import JobFactory, GroupFactory, TaskFactory, LineItemFactory
from .models import Task, Job, ProgressReport, ExpendReport
from .views import JobCopy, JobPaste
... | systori/apps/task/test_views.py | import datetime
from django.urls import reverse
from systori.lib.testing import ClientTestCase
from ..project.factories import ProjectFactory
from .factories import JobFactory, GroupFactory, TaskFactory, LineItemFactory
from .models import Task, Job, ProgressReport, ExpendReport
from .views import JobCopy, JobPaste
... | 0.427516 | 0.226891 |
#%% Imports
import numpy as np
from calib_main import calib_main
from load_pickle import load_pickle
#%% Version number
version_num = 'V9'
#%% data path
directory = 'F:\\Arbeit und Uni\\MasterArbeit\\'
# path to the pupil capture data
data_directory = directory + 'Pupil_VR_Recordings\\'
# path to the cali... | Calib_Tools/calib_start.py | #%% Imports
import numpy as np
from calib_main import calib_main
from load_pickle import load_pickle
#%% Version number
version_num = 'V9'
#%% data path
directory = 'F:\\Arbeit und Uni\\MasterArbeit\\'
# path to the pupil capture data
data_directory = directory + 'Pupil_VR_Recordings\\'
# path to the cali... | 0.378804 | 0.171685 |
import sympy as sy
import numpy as np
from scipy.signal import cont2discrete
class CostModel(object):
def __init__(self, NX=None, NU=None):
assert NX != None
assert NU != None
self.NX = NX
self.NU = NU
self.Lqq, self.Luu, self.Luq, \
self.Lq, self.Lu, self.L,\
... | classic_gym/cost/__init__.py | import sympy as sy
import numpy as np
from scipy.signal import cont2discrete
class CostModel(object):
def __init__(self, NX=None, NU=None):
assert NX != None
assert NU != None
self.NX = NX
self.NU = NU
self.Lqq, self.Luu, self.Luq, \
self.Lq, self.Lu, self.L,\
... | 0.628977 | 0.656878 |
"""Tests for the file-like object implementation using the SleuthKit (TSK)."""
import os
import unittest
from dfvfs.file_io import tsk_file_io
from dfvfs.lib import definitions
from dfvfs.lib import errors
from dfvfs.path import factory as path_spec_factory
from dfvfs.resolver import context
from tests.file_io impor... | tests/file_io/tsk_file_io.py | """Tests for the file-like object implementation using the SleuthKit (TSK)."""
import os
import unittest
from dfvfs.file_io import tsk_file_io
from dfvfs.lib import definitions
from dfvfs.lib import errors
from dfvfs.path import factory as path_spec_factory
from dfvfs.resolver import context
from tests.file_io impor... | 0.563858 | 0.344774 |
import numpy as np
def normalize(np_values, _=None):
mean = np.mean(np_values)
normalized = np_values - int(mean)
return normalized
def subtract_min(np_values, _=None):
minimum = np.min(np_values)
result = np_values - int(minimum)
return result
def none(np_values, _=None):
return np_v... | code/Backend/analysis-tool/preprocessing.py |
import numpy as np
def normalize(np_values, _=None):
mean = np.mean(np_values)
normalized = np_values - int(mean)
return normalized
def subtract_min(np_values, _=None):
minimum = np.min(np_values)
result = np_values - int(minimum)
return result
def none(np_values, _=None):
return np_v... | 0.463201 | 0.745445 |
from common import date_utils
from datetime import datetime
from collections import namedtuple
import unittest
Range = namedtuple('Range', ['start', 'end'])
"""
From root directory TeamUp: python3 -m test.test_date_utils
"""
class TestDaysOverlap(unittest.TestCase):
def test_no_overlap(self):
self.longMe... | test/test_date_utils.py | from common import date_utils
from datetime import datetime
from collections import namedtuple
import unittest
Range = namedtuple('Range', ['start', 'end'])
"""
From root directory TeamUp: python3 -m test.test_date_utils
"""
class TestDaysOverlap(unittest.TestCase):
def test_no_overlap(self):
self.longMe... | 0.515132 | 0.703155 |
import logging
import sys
from os.path import dirname, realpath, isdir, isfile, join
from abstract_data import abstract_info_list
LOGGER = logging.getLogger(__name__)
class AbstractHelp(object):
def __init__(self, title, year, dataset_doi, desc_filename):
self.title = title
self.year = year
... | scripts/tabular_test_data/code/abstract_help.py | import logging
import sys
from os.path import dirname, realpath, isdir, isfile, join
from abstract_data import abstract_info_list
LOGGER = logging.getLogger(__name__)
class AbstractHelp(object):
def __init__(self, title, year, dataset_doi, desc_filename):
self.title = title
self.year = year
... | 0.319865 | 0.233171 |
from sqlalchemy import Column, Integer, String
from . import Base
class Timetable(Base):
"""
Map class for table timetable.
- **timetable_id**: Integer, primary_key.
- **open_hour**: Integer, not null.
- **open_minute**: Integer, not null.
- **close_hour**: Integer, not nul... | alchemist_lib/database/timetable.py | from sqlalchemy import Column, Integer, String
from . import Base
class Timetable(Base):
"""
Map class for table timetable.
- **timetable_id**: Integer, primary_key.
- **open_hour**: Integer, not null.
- **open_minute**: Integer, not null.
- **close_hour**: Integer, not nul... | 0.695855 | 0.15444 |
from typing import Dict, Optional
from overrides import overrides
import torch
from allennlp.models.model import Model
from allennlp.data import Vocabulary, TextFieldTensors
from allennlp.training.metrics import Average, Auc
from torch import Tensor
from transformers import BertModel, BertForSequenceClassification
... | src/models/hatefulmememodel.py | from typing import Dict, Optional
from overrides import overrides
import torch
from allennlp.models.model import Model
from allennlp.data import Vocabulary, TextFieldTensors
from allennlp.training.metrics import Average, Auc
from torch import Tensor
from transformers import BertModel, BertForSequenceClassification
... | 0.952486 | 0.278373 |
import pandas as pd
import numpy as np
import json
import os
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
def kmeans_relevance(similarity_matrix):
"""
Using cosine similarities computes kmeans clustering
:similarity_matrix: rows -> queries, columns -> document ids
:r... | models/tf_idf2kmeans.py | import pandas as pd
import numpy as np
import json
import os
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
def kmeans_relevance(similarity_matrix):
"""
Using cosine similarities computes kmeans clustering
:similarity_matrix: rows -> queries, columns -> document ids
:r... | 0.562417 | 0.607576 |
from div_free_interpolation import *
from discrete_shell_potential import *
import datetime
import numpy as np
import os
from shape_utils import *
from base_tools import *
from param import *
import matplotlib.pyplot as plt
import scipy.io
def np_to_torch(m, long=False):
if long:
return torch.as_tensor(m,... | interpolation/eval_interpolation.py | from div_free_interpolation import *
from discrete_shell_potential import *
import datetime
import numpy as np
import os
from shape_utils import *
from base_tools import *
from param import *
import matplotlib.pyplot as plt
import scipy.io
def np_to_torch(m, long=False):
if long:
return torch.as_tensor(m,... | 0.34632 | 0.481088 |
from modules.whos_on_first_common import ButtonPosition
SCREEN_TO_BUTTON_TO_READ = {
"YES": ButtonPosition.middle_left,
"FIRST": ButtonPosition.top_right,
"DISPLAY": ButtonPosition.bottom_right,
"OKAY": ButtonPosition.top_right,
"SAYS": ButtonPosition.bottom_right,
"NOTHING": ButtonPosition.mid... | src/modules/whos_on_first_solution.py | from modules.whos_on_first_common import ButtonPosition
SCREEN_TO_BUTTON_TO_READ = {
"YES": ButtonPosition.middle_left,
"FIRST": ButtonPosition.top_right,
"DISPLAY": ButtonPosition.bottom_right,
"OKAY": ButtonPosition.top_right,
"SAYS": ButtonPosition.bottom_right,
"NOTHING": ButtonPosition.mid... | 0.266166 | 0.435241 |
import os
import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
import xml.etree.ElementTree as et
import mujoco_py
class PusherEnv3DofEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
self.reference_path = os.path.joi... | envs/pusher3dof.py | import os
import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
import xml.etree.ElementTree as et
import mujoco_py
class PusherEnv3DofEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
self.reference_path = os.path.joi... | 0.390243 | 0.239305 |
import pandas as pd
from argparse import ArgumentParser
import glob
import shutil
import os
import uuid
import random
def main(target_folder, csv_path, out_folder, dry_run = False, train_test_split=0.8):
filenames = glob.glob(os.path.join(target_folder, "*.jpg"))
ids = []
ages = []
imagenos = []
... | src/pseudonomize.py | import pandas as pd
from argparse import ArgumentParser
import glob
import shutil
import os
import uuid
import random
def main(target_folder, csv_path, out_folder, dry_run = False, train_test_split=0.8):
filenames = glob.glob(os.path.join(target_folder, "*.jpg"))
ids = []
ages = []
imagenos = []
... | 0.228673 | 0.143818 |
from nonebot import on_command
from nonebot.adapters import Bot
from nonebot.adapters.cqhttp import GROUP, GroupMessageEvent, Message, MessageSegment
from nonebot.typing import T_State
from modules.user_info import UserInfo
from utils.log import logger
from .accident import random_accident
from .data_source import *
f... | plugins/russian_roulette/__init__.py | from nonebot import on_command
from nonebot.adapters import Bot
from nonebot.adapters.cqhttp import GROUP, GroupMessageEvent, Message, MessageSegment
from nonebot.typing import T_State
from modules.user_info import UserInfo
from utils.log import logger
from .accident import random_accident
from .data_source import *
f... | 0.169337 | 0.148078 |
import gzip
from diskcache import FanoutCache, Disk
from diskcache.core import BytesType, MODE_BINARY, BytesIO
from pathlib import Path
from .logconf import logging
log = logging.getLogger(__name__)
log.setLevel(logging.WARN)
log.setLevel(logging.INFO)
log.setLevel(logging.DEBUG)
# Cache Directory
# Currently using ... | utils/disk.py | import gzip
from diskcache import FanoutCache, Disk
from diskcache.core import BytesType, MODE_BINARY, BytesIO
from pathlib import Path
from .logconf import logging
log = logging.getLogger(__name__)
log.setLevel(logging.WARN)
log.setLevel(logging.INFO)
log.setLevel(logging.DEBUG)
# Cache Directory
# Currently using ... | 0.615781 | 0.216012 |
import argparse
import json
import os
import pickle
import sys
import stanfordnlp
from tqdm import tqdm
from utils import (
WORD_MAP_FILENAME,
decode_caption,
get_caption_without_special_tokens,
IMAGES_META_FILENAME,
DATA_CAPTIONS,
DATA_COCO_SPLIT,
POS_TAGGED_CAPTIONS_FILENAME,
)
# stanf... | data_preprocessing_utils/pos_tag_captions.py |
import argparse
import json
import os
import pickle
import sys
import stanfordnlp
from tqdm import tqdm
from utils import (
WORD_MAP_FILENAME,
decode_caption,
get_caption_without_special_tokens,
IMAGES_META_FILENAME,
DATA_CAPTIONS,
DATA_COCO_SPLIT,
POS_TAGGED_CAPTIONS_FILENAME,
)
# stanf... | 0.299003 | 0.12787 |
from functools import wraps
import logging
import types
from selenium.common import exceptions as selenium_ex
LOGGER = logging.getLogger(__name__)
class FreshWebElement(object):
"""
Selenium WebElement proxy/wrapper watching over errors
due to element staleness.
"""
__ATTEMPTS = 5
__STALE... | webstr/selenium/webelement.py |
from functools import wraps
import logging
import types
from selenium.common import exceptions as selenium_ex
LOGGER = logging.getLogger(__name__)
class FreshWebElement(object):
"""
Selenium WebElement proxy/wrapper watching over errors
due to element staleness.
"""
__ATTEMPTS = 5
__STALE... | 0.712732 | 0.085061 |
import ast
import glob
import os
import re
import shlex
import shutil
import signal
import sys
import termios
import threading
import tty
from utils import _utils
CUSTOM_DIC_PATH = "docs/common/custom_dic"
HUNSPELL_CMD = [
"hunspell",
"-a", # Pipe mode
"-d",
"en_GB", # Graphcore uses en_GB for doc... | scripts/check_spelling.py |
import ast
import glob
import os
import re
import shlex
import shutil
import signal
import sys
import termios
import threading
import tty
from utils import _utils
CUSTOM_DIC_PATH = "docs/common/custom_dic"
HUNSPELL_CMD = [
"hunspell",
"-a", # Pipe mode
"-d",
"en_GB", # Graphcore uses en_GB for doc... | 0.386416 | 0.14851 |
# GrovePi + Rotary Angle Sensor (Potentiometer) + LED
# http://www.seeedstudio.com/wiki/Grove_-_Rotary_Angle_Sensor
# http://www.seeedstudio.com/wiki/Grove_-_LED_Socket_Kit
'''
The MIT License (MIT)
GrovePi for the Raspberry Pi: an open source platform for connecting Grove Sensors to the Raspberry Pi.
Copyright (C) ... | 02_iot-raspbian/04_button-led.py |
# GrovePi + Rotary Angle Sensor (Potentiometer) + LED
# http://www.seeedstudio.com/wiki/Grove_-_Rotary_Angle_Sensor
# http://www.seeedstudio.com/wiki/Grove_-_LED_Socket_Kit
'''
The MIT License (MIT)
GrovePi for the Raspberry Pi: an open source platform for connecting Grove Sensors to the Raspberry Pi.
Copyright (C) ... | 0.723212 | 0.298019 |
import datetime as dt
import re
from data import store as store
from utils import ui
_logger = ui.get_logger()
class Option:
def __init__(self, ticker: str, product: str, strike: str, expiry: dt.datetime):
# Specified
self.ticker = ticker
self.product = product
self.strike = stri... | options/option.py | import datetime as dt
import re
from data import store as store
from utils import ui
_logger = ui.get_logger()
class Option:
def __init__(self, ticker: str, product: str, strike: str, expiry: dt.datetime):
# Specified
self.ticker = ticker
self.product = product
self.strike = stri... | 0.545286 | 0.20454 |
from collections import OrderedDict
import tensorflow as tf
from ..tfcompat import variables_initializer, global_variables
__all__ = [
'ensure_default_session', 'get_variable_values',
'get_variable_values_as_dict', 'get_uninitialized_variables',
'ensure_variables_initialized',
]
def ensure_default_sess... | madoka/utils/tfhelper/session.py | from collections import OrderedDict
import tensorflow as tf
from ..tfcompat import variables_initializer, global_variables
__all__ = [
'ensure_default_session', 'get_variable_values',
'get_variable_values_as_dict', 'get_uninitialized_variables',
'ensure_variables_initialized',
]
def ensure_default_sess... | 0.891271 | 0.442034 |
from unittest.mock import mock_open, patch
import pytest
from satosa.metadata_creation.description import ContactPersonDesc, UIInfoDesc, OrganizationDesc, MetadataDescription
class TestContactPersonDesc(object):
def test_to_dict(self):
desc = ContactPersonDesc()
desc.contact_type = "test"
... | tests/satosa/metadata_creation/test_description.py | from unittest.mock import mock_open, patch
import pytest
from satosa.metadata_creation.description import ContactPersonDesc, UIInfoDesc, OrganizationDesc, MetadataDescription
class TestContactPersonDesc(object):
def test_to_dict(self):
desc = ContactPersonDesc()
desc.contact_type = "test"
... | 0.627951 | 0.477798 |
import re
from ..message_server import Message
from ..util import app_logging
log = app_logging.getLogger('Log Utils')
code = re.compile('%CODE')
class FlowModInfo(object):
"""
All we need to retrieve FlowMod from Database.
"""
def __init__(self, entry):
dpid, flow_mod = entry
self.... | adapters/pox/ext/debugger/elt/logger/util.py | import re
from ..message_server import Message
from ..util import app_logging
log = app_logging.getLogger('Log Utils')
code = re.compile('%CODE')
class FlowModInfo(object):
"""
All we need to retrieve FlowMod from Database.
"""
def __init__(self, entry):
dpid, flow_mod = entry
self.... | 0.506591 | 0.147955 |
from os import PathLike
from pathlib import Path
from typing import (
Any,
Callable,
Container,
Dict,
Iterable,
List,
Optional,
Sequence,
Tuple,
TypeVar,
Union,
overload,
)
import click
import joblib
import numpy as np
import tqdm
import yaml
from sklearn.base import Ba... | ertk/utils.py |
from os import PathLike
from pathlib import Path
from typing import (
Any,
Callable,
Container,
Dict,
Iterable,
List,
Optional,
Sequence,
Tuple,
TypeVar,
Union,
overload,
)
import click
import joblib
import numpy as np
import tqdm
import yaml
from sklearn.base import Ba... | 0.871448 | 0.32546 |
__doc__ = """
Script to use jellyfish to get kmer information
Input: fasta/fastq file
Output: kmer information, one of:
1. hash: binary hash of counts
2. stats: summary stats
3. dump: profile (kmer seq - count)
4. histo: histogram (count - abundance)
5. histo ranked: count, abundance, count*abundance, reverse... | scripts/kmer-tool.py | __doc__ = """
Script to use jellyfish to get kmer information
Input: fasta/fastq file
Output: kmer information, one of:
1. hash: binary hash of counts
2. stats: summary stats
3. dump: profile (kmer seq - count)
4. histo: histogram (count - abundance)
5. histo ranked: count, abundance, count*abundance, reverse... | 0.282295 | 0.211539 |
# instead of using yearly performance (return and volatility)
# use monthly data
import numpy as np
import pandas as pd
from pandas_datareader import data as wb
import matplotlib.pyplot as plt
# matplotlib inline
import scipy.optimize as sco
# load data for portfolio
mixed_tickers = []
with open('./data/mixed_portf... | stock_selection/optimization.py |
# instead of using yearly performance (return and volatility)
# use monthly data
import numpy as np
import pandas as pd
from pandas_datareader import data as wb
import matplotlib.pyplot as plt
# matplotlib inline
import scipy.optimize as sco
# load data for portfolio
mixed_tickers = []
with open('./data/mixed_portf... | 0.709925 | 0.680507 |
import requests
from bs4 import BeautifulSoup
import datetime
import pandas as pd
URL = "http://www1.river.go.jp"
DAT_HEAD_ROWS = 9
class _DataPage(object):
def __init__(self):
self._url_base = ""
self._kind = 1
self.begin_date = ""
self.end_date = ""
self.s... | mlit/data_page.py | import requests
from bs4 import BeautifulSoup
import datetime
import pandas as pd
URL = "http://www1.river.go.jp"
DAT_HEAD_ROWS = 9
class _DataPage(object):
def __init__(self):
self._url_base = ""
self._kind = 1
self.begin_date = ""
self.end_date = ""
self.s... | 0.245356 | 0.071819 |
u"""
compute_tide_corrections.py
Written by <NAME> (09/2021)
Calculates tidal elevations for correcting elevation or imagery data
Uses OTIS format tidal solutions provided by Ohio State University and ESR
http://volkov.oce.orst.edu/tides/region.html
https://www.esr.org/research/polar-tide-models/list-of-polar-... | pyTMD/compute_tide_corrections.py | u"""
compute_tide_corrections.py
Written by <NAME> (09/2021)
Calculates tidal elevations for correcting elevation or imagery data
Uses OTIS format tidal solutions provided by Ohio State University and ESR
http://volkov.oce.orst.edu/tides/region.html
https://www.esr.org/research/polar-tide-models/list-of-polar-... | 0.865764 | 0.748881 |
from django import test
from django.shortcuts import resolve_url
from django.test import TestCase
from django.test.utils import override_settings
from mock import patch
from django_opt_out.models import OptOut
from django_opt_out.plugins.sparkpost import send_email, signals
from .test_views import CaptureSignal
clas... | tests/test_sparkpost.py | from django import test
from django.shortcuts import resolve_url
from django.test import TestCase
from django.test.utils import override_settings
from mock import patch
from django_opt_out.models import OptOut
from django_opt_out.plugins.sparkpost import send_email, signals
from .test_views import CaptureSignal
clas... | 0.448909 | 0.161122 |
import design
import debug
from tech import drc, info
from vector import vector
import contact
from ptx import ptx
from globals import OPTS
class single_level_column_mux(design.design):
"""
This module implements the columnmux bitline cell used in the design.
Creates a single columnmux cell.
"""
d... | compiler/modules/single_level_column_mux.py | import design
import debug
from tech import drc, info
from vector import vector
import contact
from ptx import ptx
from globals import OPTS
class single_level_column_mux(design.design):
"""
This module implements the columnmux bitline cell used in the design.
Creates a single columnmux cell.
"""
d... | 0.489015 | 0.2243 |
import os
import tensorflow as tf
from keras import backend as K
from keras import metrics
from keras.callbacks import TensorBoard
from keras.layers import Conv2D, MaxPooling2D, UpSampling2D
from keras.models import Sequential
from keras.optimizers import Adadelta
from keras.preprocessing.image import ImageDataGenerat... | model/autoencoder.py | import os
import tensorflow as tf
from keras import backend as K
from keras import metrics
from keras.callbacks import TensorBoard
from keras.layers import Conv2D, MaxPooling2D, UpSampling2D
from keras.models import Sequential
from keras.optimizers import Adadelta
from keras.preprocessing.image import ImageDataGenerat... | 0.787482 | 0.505981 |
import unittest
from ie.isde import ComplexTypes, ISDEDatasetMetadata, RDFNamespaces
class ISDETools(unittest.TestCase):
_ie_marine_data__dataset_1000 = r"https://irishspatialdataexchange.blob.core.windows.net/metadata/xml/ie_marine_data__dataset_1000.xml"
_ie_nbdc_dataset_BioMar = r"http://www.isde.ie/geon... | test.py | import unittest
from ie.isde import ComplexTypes, ISDEDatasetMetadata, RDFNamespaces
class ISDETools(unittest.TestCase):
_ie_marine_data__dataset_1000 = r"https://irishspatialdataexchange.blob.core.windows.net/metadata/xml/ie_marine_data__dataset_1000.xml"
_ie_nbdc_dataset_BioMar = r"http://www.isde.ie/geon... | 0.645455 | 0.453746 |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0012_alter_user_first_name_max_length'),
]
operations = [
migrations.CreateModel(
name... | users/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0012_alter_user_first_name_max_length'),
]
operations = [
migrations.CreateModel(
name... | 0.523908 | 0.167559 |
from .response import Response
from ..simplates import Simplate, SimplateDefaults, SimplateException
class Static(object):
"""Model a static HTTP resource.
"""
def __init__(self, website, fspath, raw, media_type):
self.website = website
self.raw = raw
self.media_type = media_type
... | aspen/http/resource.py | from .response import Response
from ..simplates import Simplate, SimplateDefaults, SimplateException
class Static(object):
"""Model a static HTTP resource.
"""
def __init__(self, website, fspath, raw, media_type):
self.website = website
self.raw = raw
self.media_type = media_type
... | 0.480235 | 0.113187 |
from easyai.base_name.model_name import ModelName
from easyai.base_name.backbone_name import BackboneName
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.block_name import LayerType, BlockType
from easyai.base_name.loss_name import LossType
from easyai.loss.utility.cross_... | easyai/model/seg/pspnet_seg.py | from easyai.base_name.model_name import ModelName
from easyai.base_name.backbone_name import BackboneName
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.block_name import LayerType, BlockType
from easyai.base_name.loss_name import LossType
from easyai.loss.utility.cross_... | 0.864425 | 0.191517 |
import datetime
from dateutil.relativedelta import relativedelta
from itsdangerous import TimedJSONWebSignatureSerializer as Serializer
from MESAeveryday import login_manager, app, bcrypt
from flask_login import UserMixin
from flask import flash
import os
from sqlalchemy import Column, Integer, String, create_engine, F... | MESAeveryday/models.py | import datetime
from dateutil.relativedelta import relativedelta
from itsdangerous import TimedJSONWebSignatureSerializer as Serializer
from MESAeveryday import login_manager, app, bcrypt
from flask_login import UserMixin
from flask import flash
import os
from sqlalchemy import Column, Integer, String, create_engine, F... | 0.386416 | 0.121869 |
__author__ = 'mnowotka'
#-----------------------------------------------------------------------------------------------------------------------
from chembl_beaker.beaker import app
from bottle import request
from chembl_beaker.beaker.core_apps.conversions.impl import _ctab2smiles, _smiles2ctab, _inchi2ctab, _ctab2sm... | chembl_beaker/beaker/core_apps/conversions/views.py | __author__ = 'mnowotka'
#-----------------------------------------------------------------------------------------------------------------------
from chembl_beaker.beaker import app
from bottle import request
from chembl_beaker.beaker.core_apps.conversions.impl import _ctab2smiles, _smiles2ctab, _inchi2ctab, _ctab2sm... | 0.47098 | 0.104249 |
import os
from unittest import TestCase
import pandas as pd
import plotly.graph_objects as go
from pandas.testing import assert_frame_equal
from moonstone.parsers.metadata import MetadataParser, YAMLBasedMetadataParser
class TestMetadataParser(TestCase):
def setUp(self):
self.metadata_file = os.path.joi... | tests/parsers/test_metadata.py | import os
from unittest import TestCase
import pandas as pd
import plotly.graph_objects as go
from pandas.testing import assert_frame_equal
from moonstone.parsers.metadata import MetadataParser, YAMLBasedMetadataParser
class TestMetadataParser(TestCase):
def setUp(self):
self.metadata_file = os.path.joi... | 0.605099 | 0.439326 |
from urllib import parse
from celery import shared_task, states
from celery.canvas import group
from django.conf import settings
from django.db import transaction
from extras.tasks import CurrentUserTaskMixin
from registry.models import CatalougeService, WebFeatureService, WebMapService
from registry.models.metadata i... | backend/registry/tasks/service.py | from urllib import parse
from celery import shared_task, states
from celery.canvas import group
from django.conf import settings
from django.db import transaction
from extras.tasks import CurrentUserTaskMixin
from registry.models import CatalougeService, WebFeatureService, WebMapService
from registry.models.metadata i... | 0.34632 | 0.086362 |
import os
import numpy as np
import cobra
from enzyme import enzyme
from warnings import filterwarnings
class TestFBAModel:
def setup_class(self):
modelPath='../data/external/yeast_7.6/yeast_7.6.xml'
filterwarnings('ignore', 'charge of s_[0-9][0-9][0-9][0-9] is not a number ()')
filterwarn... | flux_balance_analysis/test_code.py | import os
import numpy as np
import cobra
from enzyme import enzyme
from warnings import filterwarnings
class TestFBAModel:
def setup_class(self):
modelPath='../data/external/yeast_7.6/yeast_7.6.xml'
filterwarnings('ignore', 'charge of s_[0-9][0-9][0-9][0-9] is not a number ()')
filterwarn... | 0.505615 | 0.423518 |
import sys
import regex as re
__author__ = '<NAME>'
__license__ = 'MIT License'
__version__ = '1.0.0'
__status__ = '4 - Beta Development'
class MultiRegex(object):
simple = False
regexes = ()
def __init__(self):
try:
self._rx = re.compile('|'.join(self.regexes), flag... | nielsenTools/multiregex.py | import sys
import regex as re
__author__ = '<NAME>'
__license__ = 'MIT License'
__version__ = '1.0.0'
__status__ = '4 - Beta Development'
class MultiRegex(object):
simple = False
regexes = ()
def __init__(self):
try:
self._rx = re.compile('|'.join(self.regexes), flag... | 0.154058 | 0.405213 |
from cgitb import text
from cloudant import Cloudant
from flask import Flask, render_template, request, jsonify, url_for, redirect
import atexit
import os
import json
import xml.etree.ElementTree as ET
tree = ET.parse('catalog.xml')
root = tree.getroot()
app = Flask(__name__, static_url_path='')
db_name = 'mydb'
cl... | hello.py | from cgitb import text
from cloudant import Cloudant
from flask import Flask, render_template, request, jsonify, url_for, redirect
import atexit
import os
import json
import xml.etree.ElementTree as ET
tree = ET.parse('catalog.xml')
root = tree.getroot()
app = Flask(__name__, static_url_path='')
db_name = 'mydb'
cl... | 0.322526 | 0.046486 |
import argparse
import json
import numpy as np
import os
# manually selected list
benchs_list = {
"raw": ["cartpolereduced", "BNNOnProteinStructure", "BNNOnYearPrediction"],
"surro": ["ParamNetReducedAdultOnTimeBenchmark", "ParamNetReducedHiggsOnTimeBenchmark",
"ParamNetReducedLetterOnTimeBenchmark", "ParamNetRed... | scripts/get_runtime.py | import argparse
import json
import numpy as np
import os
# manually selected list
benchs_list = {
"raw": ["cartpolereduced", "BNNOnProteinStructure", "BNNOnYearPrediction"],
"surro": ["ParamNetReducedAdultOnTimeBenchmark", "ParamNetReducedHiggsOnTimeBenchmark",
"ParamNetReducedLetterOnTimeBenchmark", "ParamNetRed... | 0.233357 | 0.230205 |
import re
import requests
import logging
from copy import deepcopy
from typing import List, Dict
from logging import Logger
from datetime import timedelta, datetime
import fbchat
from fbchat import Client, User, Message, Mention, ThreadType
class Reporter(Client):
debug: bool
logger: Logger
maxage: time... | veritaserum/reporter.py | import re
import requests
import logging
from copy import deepcopy
from typing import List, Dict
from logging import Logger
from datetime import timedelta, datetime
import fbchat
from fbchat import Client, User, Message, Mention, ThreadType
class Reporter(Client):
debug: bool
logger: Logger
maxage: time... | 0.610221 | 0.072505 |
from django.db import models, migrations
from django.conf import settings
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('core', '0001_initial'),
]
operations = [
migrations.CreateModel(
... | ecs/meetings/migrations/0001_initial.py | from django.db import models, migrations
from django.conf import settings
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('core', '0001_initial'),
]
operations = [
migrations.CreateModel(
... | 0.560373 | 0.184768 |
from .base import Base
from utilities import authenticate
import requests
import datetime
class reservations(Base):
"""Make 'get reservations' function calls to Teem
with parameters passed via CLI"""
Rooms = {
'showcase': 130700,
'pistachio': 218764,
'almond': 218763,
'2... | teem/commands/reservations.py | from .base import Base
from utilities import authenticate
import requests
import datetime
class reservations(Base):
"""Make 'get reservations' function calls to Teem
with parameters passed via CLI"""
Rooms = {
'showcase': 130700,
'pistachio': 218764,
'almond': 218763,
'2... | 0.330471 | 0.112065 |
from django import forms
from django.utils.translation import gettext_lazy as _
from .base import ChangeSettingsForm
class ChangeThreadsSettingsForm(ChangeSettingsForm):
settings = [
"attachment_403_image",
"attachment_404_image",
"daily_post_limit",
"hourly_post_limit",
"... | misago/misago/conf/admin/forms/threads.py | from django import forms
from django.utils.translation import gettext_lazy as _
from .base import ChangeSettingsForm
class ChangeThreadsSettingsForm(ChangeSettingsForm):
settings = [
"attachment_403_image",
"attachment_404_image",
"daily_post_limit",
"hourly_post_limit",
"... | 0.602997 | 0.118793 |
import sys
from socket import *
import threading
import time
import datetime as dt
# The argument of client
servername = sys.argv[1]
serverPort = sys.argv[2]
udpPort = sys.argv[3]
serverPort = int(serverPort)
# Create the TCP socket
clientSocket = socket(AF_INET, SOCK_STREAM)
clientSocket.connect((serve... | code/testclient.py | import sys
from socket import *
import threading
import time
import datetime as dt
# The argument of client
servername = sys.argv[1]
serverPort = sys.argv[2]
udpPort = sys.argv[3]
serverPort = int(serverPort)
# Create the TCP socket
clientSocket = socket(AF_INET, SOCK_STREAM)
clientSocket.connect((serve... | 0.126515 | 0.050518 |
import numpy as np
import cv2
import glob
import pickle
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
# Class that holds both the left and right line tracking data
class tracker():
# Constructor?
def __init__(self, Mywindow_width, Mywindow_height, Mymargin,
My_ym = ... | tracker.py | import numpy as np
import cv2
import glob
import pickle
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
# Class that holds both the left and right line tracking data
class tracker():
# Constructor?
def __init__(self, Mywindow_width, Mywindow_height, Mymargin,
My_ym = ... | 0.678647 | 0.339663 |
import os
import time
import typing
import typer
from hrflow_importer.importer.worker import send_batch_to_hrflow
from hrflow_importer.utils.config.config import config #TODO improve module naming for import
from hrflow import Hrflow
PIPELINES_LOGS_FILE = "{}/importer_logs.txt".format(config.STORAGE_DIRECTORY_PATH)
... | src/hrflow_importer/import_cli.py | import os
import time
import typing
import typer
from hrflow_importer.importer.worker import send_batch_to_hrflow
from hrflow_importer.utils.config.config import config #TODO improve module naming for import
from hrflow import Hrflow
PIPELINES_LOGS_FILE = "{}/importer_logs.txt".format(config.STORAGE_DIRECTORY_PATH)
... | 0.215598 | 0.169681 |
import torch
import torch.nn as nn
import torch.nn.functional as F
def logsumexp_2d(tensor):
tensor_flatten = tensor.view(tensor.size(0), tensor.size(1), -1)
s, _ = torch.max(tensor_flatten, dim=2, keepdim=True)
outputs = s + (tensor_flatten - s).exp().sum(dim=2, keepdim=True).log()
return outputs
d... | ibug/age_estimation/module.py | import torch
import torch.nn as nn
import torch.nn.functional as F
def logsumexp_2d(tensor):
tensor_flatten = tensor.view(tensor.size(0), tensor.size(1), -1)
s, _ = torch.max(tensor_flatten, dim=2, keepdim=True)
outputs = s + (tensor_flatten - s).exp().sum(dim=2, keepdim=True).log()
return outputs
d... | 0.935553 | 0.696479 |
import unittest
def interleavedp(begins,ends,m=None) :
if( len(begins) != len(ends) ) :
print 'begin-end token number mismatch'
# Should learn to throw...
return False
if m :
if len(m) > len(begins) :
print 'excess else tokens'
return False
ok... | components/elm/src/external_models/sbetr/3rd-party/pfunit/bin/mods/pre/interleavedp.py |
import unittest
def interleavedp(begins,ends,m=None) :
if( len(begins) != len(ends) ) :
print 'begin-end token number mismatch'
# Should learn to throw...
return False
if m :
if len(m) > len(begins) :
print 'excess else tokens'
return False
ok... | 0.276105 | 0.524395 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import unittest
import numpy as np
import tensorflow as tf
import gym
from easy_rl.agents import agents
from easy_rl.models import DQNModel
from easy_rl.utils.window_stat import WindowStat
from easy_rl.models ... | tests/test_convergence.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import unittest
import numpy as np
import tensorflow as tf
import gym
from easy_rl.agents import agents
from easy_rl.models import DQNModel
from easy_rl.utils.window_stat import WindowStat
from easy_rl.models ... | 0.741674 | 0.18462 |
from typing import List, Optional, Union
import pyinflect # noqa: F401
import spacy
from nltk.tokenize.treebank import TreebankWordDetokenizer
from spacy.symbols import AUX, NOUN, PRON, PROPN, VERB, aux, cc, nsubj
from spacy.tokens import Span, Token
from spacy.tokens.doc import Doc
from initialize import spacy_nlp
... | transformations/yes_no_question/transformation.py | from typing import List, Optional, Union
import pyinflect # noqa: F401
import spacy
from nltk.tokenize.treebank import TreebankWordDetokenizer
from spacy.symbols import AUX, NOUN, PRON, PROPN, VERB, aux, cc, nsubj
from spacy.tokens import Span, Token
from spacy.tokens.doc import Doc
from initialize import spacy_nlp
... | 0.875242 | 0.283949 |
import numpy as np
import matplotlib.pyplot as plt
# importing the numpy & matplot libraries to help manipulate the data, and giving them shorthand names
# Alternately I could import these into iPython while testing. Remember I'm working on a multivariate dataset
data = np.genfromtxt('Data/Iris.csv', delimiter... | NumpyData.py |
import numpy as np
import matplotlib.pyplot as plt
# importing the numpy & matplot libraries to help manipulate the data, and giving them shorthand names
# Alternately I could import these into iPython while testing. Remember I'm working on a multivariate dataset
data = np.genfromtxt('Data/Iris.csv', delimiter... | 0.410402 | 0.614857 |
from pubnub import utils
from pubnub.endpoints.endpoint import Endpoint
from pubnub.enums import HttpMethod, PNOperationType
from pubnub.exceptions import PubNubException
from pubnub.models.consumer.message_count import PNMessageCountResult
class MessageCount(Endpoint):
MESSAGE_COUNT_PATH = '/v3/history/sub-key/%... | pubnub/endpoints/message_count.py | from pubnub import utils
from pubnub.endpoints.endpoint import Endpoint
from pubnub.enums import HttpMethod, PNOperationType
from pubnub.exceptions import PubNubException
from pubnub.models.consumer.message_count import PNMessageCountResult
class MessageCount(Endpoint):
MESSAGE_COUNT_PATH = '/v3/history/sub-key/%... | 0.622574 | 0.077343 |
import torch
from torch import nn
from torch.nn import functional as F
from torch_geometric.nn import MessagePassing, global_mean_pool
from torch_geometric.utils import degree, dense_to_sparse
from torch_geometric.nn import ECConv
from torch_scatter import scatter_add
def _make_block_diag(mats, mat_sizes):
block_d... | MolRep/Models/graph_based/ECC.py | import torch
from torch import nn
from torch.nn import functional as F
from torch_geometric.nn import MessagePassing, global_mean_pool
from torch_geometric.utils import degree, dense_to_sparse
from torch_geometric.nn import ECConv
from torch_scatter import scatter_add
def _make_block_diag(mats, mat_sizes):
block_d... | 0.866175 | 0.559771 |
"""Generated protocol buffer code."""
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_databa... | terra_sdk/protobuf/ibc/core/types/v1/genesis_pb2.py | """Generated protocol buffer code."""
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_databa... | 0.329715 | 0.070336 |
__author__ = '<NAME>'
__email__ = '<EMAIL>'
__status__ = 'Development'
__license__ = 'Apache 2.0'
import wx
import massoc
from massoc.scripts.main import resource_path
from wx.lib.pubsub import pub
from massoc.GUI.intro import IntroPanel
from massoc.GUI.input import InputPanel
from massoc.GUI.process import ProcessPan... | massocGUI.py | __author__ = '<NAME>'
__email__ = '<EMAIL>'
__status__ = 'Development'
__license__ = 'Apache 2.0'
import wx
import massoc
from massoc.scripts.main import resource_path
from wx.lib.pubsub import pub
from massoc.GUI.intro import IntroPanel
from massoc.GUI.input import InputPanel
from massoc.GUI.process import ProcessPan... | 0.422505 | 0.168309 |
from typing import Dict
from python import DOCUMENT_ID, TOPIC_ID
from python.handwritten_baseline.pipeline.data.base import Dataset, BaselineDataProcessorStage
class DataReducerStage(BaselineDataProcessorStage):
def __init__(self, pos, config, config_global, logger):
super(DataReducerStage, self).__init... | python/handwritten_baseline/pipeline/data/processing/reducer.py | from typing import Dict
from python import DOCUMENT_ID, TOPIC_ID
from python.handwritten_baseline.pipeline.data.base import Dataset, BaselineDataProcessorStage
class DataReducerStage(BaselineDataProcessorStage):
def __init__(self, pos, config, config_global, logger):
super(DataReducerStage, self).__init... | 0.661923 | 0.480844 |
from .models import MovieNightEvent, Movie, UserAttendence, LocationPermission
from rest_framework import serializers
from django.utils import timezone
from django.contrib.auth.models import User
from .utils import badgify
import pytz
def strfdelta(tdelta, fmt):
d = {"days": abs(tdelta.days)}
d["hours"], re... | userhandling/serializers.py | from .models import MovieNightEvent, Movie, UserAttendence, LocationPermission
from rest_framework import serializers
from django.utils import timezone
from django.contrib.auth.models import User
from .utils import badgify
import pytz
def strfdelta(tdelta, fmt):
d = {"days": abs(tdelta.days)}
d["hours"], re... | 0.456894 | 0.165088 |
import tensorflow as tf
import cv2
import matplotlib.pyplot as plt
import numpy as np
def gradient_penalty_loss(averaged_output, x_hat):
gradients = tf.gradients(averaged_output, x_hat)[0]
gradients_sqr = tf.square(gradients)
gradients_sqr_sum = tf.reduce_sum(gradients_sqr, axis=np.arange(1, len(gradients... | stargan/utils.py | import tensorflow as tf
import cv2
import matplotlib.pyplot as plt
import numpy as np
def gradient_penalty_loss(averaged_output, x_hat):
gradients = tf.gradients(averaged_output, x_hat)[0]
gradients_sqr = tf.square(gradients)
gradients_sqr_sum = tf.reduce_sum(gradients_sqr, axis=np.arange(1, len(gradients... | 0.72331 | 0.533641 |
import xmlrpclib
from threading import Thread
from SimpleXMLRPCServer import SimpleXMLRPCServer
config = {}
def initialize():
global ccu_url, _gateway_is_connected
ccu_ip = config["ccu_ip"]
ccu_port = config["ccu_port"]
ccu_url = "http://{ip}:{port}".format(ip=ccu_ip, port=ccu_port)
_gateway_is... | wirehome.services.homematic.ccu/1.0.0/script.py | import xmlrpclib
from threading import Thread
from SimpleXMLRPCServer import SimpleXMLRPCServer
config = {}
def initialize():
global ccu_url, _gateway_is_connected
ccu_ip = config["ccu_ip"]
ccu_port = config["ccu_port"]
ccu_url = "http://{ip}:{port}".format(ip=ccu_ip, port=ccu_port)
_gateway_is... | 0.485844 | 0.095771 |
import torndb
import logging
import json
import environment
COMPANY_SERVICE =\
torndb.Connection(
'mysql',
'company_service',
user=environment.get_user(),
password=<PASSWORD>(),
)
def release():
COMPANY_SERVICE.close()
class Crawler(object):
'''
爬虫的持久化对象
''... | database.py | import torndb
import logging
import json
import environment
COMPANY_SERVICE =\
torndb.Connection(
'mysql',
'company_service',
user=environment.get_user(),
password=<PASSWORD>(),
)
def release():
COMPANY_SERVICE.close()
class Crawler(object):
'''
爬虫的持久化对象
''... | 0.285671 | 0.074905 |
import textwrap
from exceptions import Error
class TextTable(object):
def __init__(self, field_names, **kwargs):
'''
Arguments:
field_names - list or tuple of field names
vertical_str - vertical separator betwwen each columns
'''
self._field_names = field_names
... | src/texttable.py | import textwrap
from exceptions import Error
class TextTable(object):
def __init__(self, field_names, **kwargs):
'''
Arguments:
field_names - list or tuple of field names
vertical_str - vertical separator betwwen each columns
'''
self._field_names = field_names
... | 0.568655 | 0.23292 |
from __future__ import print_function
from __future__ import absolute_import
from past.builtins import basestring
import os
import shutil
import sys
import time
class OutputWrangler:
"""
This is used in place of an output file when forking to trivially
parallelize computations.
For example, if you hav... | python/util/fork.py | from __future__ import print_function
from __future__ import absolute_import
from past.builtins import basestring
import os
import shutil
import sys
import time
class OutputWrangler:
"""
This is used in place of an output file when forking to trivially
parallelize computations.
For example, if you hav... | 0.338186 | 0.165357 |
import tensorflow as tf
from MemoryNetwork import MemoryNetwork
import babi_dataset_utils as bb
import os
import numpy as np
import matplotlib.pyplot as plt
import sys
import errno
flags = tf.app.flags
# dataset configs
flags.DEFINE_string("dataset_selector", "babi", "dataset selector: 'babi' or 'penn' [babi]")
flags... | main.py | import tensorflow as tf
from MemoryNetwork import MemoryNetwork
import babi_dataset_utils as bb
import os
import numpy as np
import matplotlib.pyplot as plt
import sys
import errno
flags = tf.app.flags
# dataset configs
flags.DEFINE_string("dataset_selector", "babi", "dataset selector: 'babi' or 'penn' [babi]")
flags... | 0.470493 | 0.259088 |
class StatementsRouter:
route_app_labels = {'auth', 'contenttypes', 'session', 'admin', 'statements'}
def db_for_read(self, model, **hints):
"""
Attempts to read auth and contenttypes models go to auth_db.
"""
if model._meta.app_label in self.route_app_labels:
return... | mysite/routers/db_routers.py | class StatementsRouter:
route_app_labels = {'auth', 'contenttypes', 'session', 'admin', 'statements'}
def db_for_read(self, model, **hints):
"""
Attempts to read auth and contenttypes models go to auth_db.
"""
if model._meta.app_label in self.route_app_labels:
return... | 0.489015 | 0.154983 |
from keystoneauth1 import adapter
import mock
from openstack.tests.unit import base
from otcextensions.sdk import sdk_resource
# Only a basic tests for extended functionality are implemented since
# the _list code is copied from sdk.resource to override headers
# TODO(agoncharov) make sense to implement (copy) exis... | otcextensions/tests/unit/sdk/test_sdk_resource.py | from keystoneauth1 import adapter
import mock
from openstack.tests.unit import base
from otcextensions.sdk import sdk_resource
# Only a basic tests for extended functionality are implemented since
# the _list code is copied from sdk.resource to override headers
# TODO(agoncharov) make sense to implement (copy) exis... | 0.35031 | 0.247669 |
class Terminal:
def __init__(self, estimates, regcoeffs):
self._estimates = estimates
self._regcoeffs = regcoeffs
def Process(self, entity):
entity.time_Sysp = entity.allTime
# Entities receiving no treatment OR palliative treatment (for recurrence)... | Code/SysP_Terminal.py | class Terminal:
def __init__(self, estimates, regcoeffs):
self._estimates = estimates
self._regcoeffs = regcoeffs
def Process(self, entity):
entity.time_Sysp = entity.allTime
# Entities receiving no treatment OR palliative treatment (for recurrence)... | 0.541409 | 0.294114 |
import time
import rospy
import rospkg
import os
import sys
import numpy as np
import tensorflow as tf
from styx_msgs.msg import TrafficLight
from io import StringIO
MINIMUM_CONFIDENCE = 0.4
class TLClassifier(object):
def __init__(self, simulator):
# current_path = os.path.dirname(os.path.realpath(__fi... | ros/src/tl_detector/light_classification/tl_classifier.py | import time
import rospy
import rospkg
import os
import sys
import numpy as np
import tensorflow as tf
from styx_msgs.msg import TrafficLight
from io import StringIO
MINIMUM_CONFIDENCE = 0.4
class TLClassifier(object):
def __init__(self, simulator):
# current_path = os.path.dirname(os.path.realpath(__fi... | 0.704668 | 0.357147 |
import functools
from typing import Optional
from absl import logging
from growneuron.imagenet import data_util
import tensorflow.compat.v2 as tf
import tensorflow_datasets as tfds
def build_input_fn(
builder,
global_batch_size,
topology,
is_training,
image_size = 224):
"""Build input function.... | growneuron/imagenet/data.py | import functools
from typing import Optional
from absl import logging
from growneuron.imagenet import data_util
import tensorflow.compat.v2 as tf
import tensorflow_datasets as tfds
def build_input_fn(
builder,
global_batch_size,
topology,
is_training,
image_size = 224):
"""Build input function.... | 0.938513 | 0.454714 |
import pandas as pd
pd.options.mode.chained_assignment = None
from datetime import datetime
#Carga de datos
Regions = ["WYJ", "YVR"]
WeatherData = {}
HouseFeatures = pd.DataFrame()
HouseData = pd.DataFrame()
#Cargar Caracacteristicas de casa
with open(r"Data/HouseHold/Features.csv") as file:
HouseFeatures = pd.re... | FormatDataConsumption.py | import pandas as pd
pd.options.mode.chained_assignment = None
from datetime import datetime
#Carga de datos
Regions = ["WYJ", "YVR"]
WeatherData = {}
HouseFeatures = pd.DataFrame()
HouseData = pd.DataFrame()
#Cargar Caracacteristicas de casa
with open(r"Data/HouseHold/Features.csv") as file:
HouseFeatures = pd.re... | 0.210198 | 0.216529 |
# Built-ins
import os
import warnings
import datetime
import threading
# Package
import __init__
from elf import utils
from elf.webio import get_soup
from elf.webio import download_page
from elf.parsing import parsetable
warnings.warn('EDGAR search-by-text can only search 3 years back. Use alternative downloader if... | search_by_text.py |
# Built-ins
import os
import warnings
import datetime
import threading
# Package
import __init__
from elf import utils
from elf.webio import get_soup
from elf.webio import download_page
from elf.parsing import parsetable
warnings.warn('EDGAR search-by-text can only search 3 years back. Use alternative downloader if... | 0.286768 | 0.371593 |