uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ffd8bdb6aa37285922a26992 | train | function | @cli.group()
def microk8s():
pass
| @cli.group()
def microk8s():
| pass
| seconds.',
color='green',
)
kubeflow_info(controller, model)
@cli.command()
@click.argument('CONTROLLER')
@click.option('--model', default='kubeflow')
def info(controller, model):
kubeflow_info(controller, model)
@cli.group()
def microk8s():
| 64 | 64 | 13 | 10 | 54 | RFMVasconcelos/bundle-kubeflow | scripts/cli.py | Python | microk8s | microk8s | 365 | 367 | 365 | 366 | f1fac5252377ee73a61469fc99fe578eb0b4d688 | bigcode/the-stack | train |
968ca8b28fc60b176bb104cb | train | function | def juju(*args, env=None, die=True):
run('juju', *args, env=env, die=die)
| def juju(*args, env=None, die=True):
| run('juju', *args, env=env, die=die)
|
import subprocess
import sys
import tempfile
import textwrap
import time
from pathlib import Path
import click
import yaml
DEFAULT_CONTROLLERS = {'microk8s': 'uk8s', 'aws': 'ckkf'}
def juju(*args, env=None, die=True):
| 63 | 64 | 28 | 12 | 51 | RFMVasconcelos/bundle-kubeflow | scripts/cli.py | Python | juju | juju | 18 | 19 | 18 | 18 | b104c13fd47afa9a2bed8ab94fa1c4ebe39cc690 | bigcode/the-stack | train |
235696a56f475d0b1af3b1f1 | train | function | @cli.command(name='deploy-to')
@click.argument('CONTROLLER')
@click.option('--cloud')
@click.option('--model', default='kubeflow')
@click.option('--channel', default='stable')
@click.option('--public-address')
@click.option('--build/--no-build', default=False)
@click.option('-o', '--overlays', multiple=True)
@click.pas... | @cli.command(name='deploy-to')
@click.argument('CONTROLLER')
@click.option('--cloud')
@click.option('--model', default='kubeflow')
@click.option('--channel', default='stable')
@click.option('--public-address')
@click.option('--build/--no-build', default=False)
@click.option('-o', '--overlays', multiple=True)
@click.pas... | password_overlay = {
"applications": {
"dex-auth": {"options": {"static-username": "admin", "static-password": password}},
"katib-db": {"options": {"root_password": get_random_pass()}},
"modeldb-db": {"options": {"root_password": get_random_pass()}},
"oidc-gat... | _ip
except (KeyError, subprocess.CalledProcessError) as err:
pass
# If all else fails, just use localhost
return 'localhost'
def get_random_pass():
"""Generates decently long random password."""
return ''.join(random.choices(string.ascii_uppercase + string.digits, k=30))
#######
# CLI ... | 256 | 256 | 1,169 | 140 | 115 | RFMVasconcelos/bundle-kubeflow | scripts/cli.py | Python | deploy_to | deploy_to | 219 | 355 | 219 | 232 | 862e7ef2d875ef8b82a1d652f4d465718afd9180 | bigcode/the-stack | train |
1d38301e6960460cdd1b4222 | train | class | class Game:
"""A basis for all games on the Surrogate.tv platform
Game consists of callback methods, which are automatically called
by the game engine during the game loop. All messaging with the game
engine is done through GameIO class, which is accessed through self.io.
The game loop is started w... | class Game:
| """A basis for all games on the Surrogate.tv platform
Game consists of callback methods, which are automatically called
by the game engine during the game loop. All messaging with the game
engine is done through GameIO class, which is accessed through self.io.
The game loop is started with a run() ... | ]
NOT_IMPLEMENTED_DEFAULT_INFO = "not implemented."
NOT_IMPLEMENTED_ADDITIONAL_INFO = {
"on_init": " No inputs/outputs were registered.",
"on_config": " Using the current set.",
}
# Mapping from GE event to Game loop event names and handler names
# This is used for logging and starting the correct event handle... | 256 | 256 | 3,124 | 3 | 253 | IvarK/surrortg-sdk | surrortg/game.py | Python | Game | Game | 60 | 489 | 60 | 60 | 736298b1446fb67baa5d9bd16b9f1df50404ad4b | bigcode/the-stack | train |
403d23a1f4be250a6309afda | train | class | class RobotHelperX(RobotHelper):
def __init__(self, startworld=True, usereal = True, autorotate = False):
super(RobotHelperX, self).__init__(startworld=startworld, autorotate = autorotate)
import robotconn.yumirapid.yumi_robot as yr
import robotconn.yumirapid.yumi_state as ys
import... | class RobotHelperX(RobotHelper):
| def __init__(self, startworld=True, usereal = True, autorotate = False):
super(RobotHelperX, self).__init__(startworld=startworld, autorotate = autorotate)
import robotconn.yumirapid.yumi_robot as yr
import robotconn.yumirapid.yumi_state as ys
import robotconn.rpc.phoxi.phoxi_client ... | Primitive(startarmjnts, direction, distance, [], [[]], obstaclecmlist, type="source")
if len(path) > 0:
return path
else:
return None
def startworld(self, autorotate = False):
"""
:return:
"""
# 1700, -1000, -1000, 300
self.base = pa... | 256 | 256 | 907 | 8 | 247 | Photon26/wrs-main-210414 | 0000_huri/robothelper.py | Python | RobotHelperX | RobotHelperX | 278 | 369 | 278 | 279 | 7278ecc1f72bca12dfc846c34e3565f51bab7828 | bigcode/the-stack | train |
d17216639ce63a99866d1085 | train | class | class RobotHelper(object):
def __init__(self, startworld=True, autorotate = False):
"""
helper function to simplify everything
:return:
"""
self.env = yumisetting.Env()
self.obscmlist = self.env.getstationaryobslist()
self.rgthndfa = yi.YumiIntegratedFactor... | class RobotHelper(object):
| def __init__(self, startworld=True, autorotate = False):
"""
helper function to simplify everything
:return:
"""
self.env = yumisetting.Env()
self.obscmlist = self.env.getstationaryobslist()
self.rgthndfa = yi.YumiIntegratedFactory()
self.lfthndfa = ... | import numpy as np
import utiltools.robotmath as rm
from robotsim.robots.dualarm.yumi import yumi
from robotsim.robots.dualarm.yumi import yumimesh, yumiball
import environment.suitayuminotop as yumisetting
import manipulation.grip.yumiintegrated.yumiintegrated as yi
from pandaplotutils import pandactrl
from motion imp... | 162 | 256 | 2,415 | 5 | 156 | Photon26/wrs-main-210414 | 0000_huri/robothelper.py | Python | RobotHelper | RobotHelper | 18 | 276 | 18 | 19 | f2d251d7794db3455cdaa8cf4ad1ba1606eb0174 | bigcode/the-stack | train |
a8d0980db58e833f19dd3fa4 | train | class | class Employee:
def __init__(self, name, manager):
self.name = name
self.manager = manager
def __repr__(self):
return f"{self.name}, {self.manager}"
| class Employee:
| def __init__(self, name, manager):
self.name = name
self.manager = manager
def __repr__(self):
return f"{self.name}, {self.manager}"
| = cursor.execute("""
SELECT CONCAT(e.name, ' (', e.job_title, ' )') AS "Employee",
CONCAT(m.name, ' (', m.job_title, ' )') AS "Manager"
FROM employees e
LEFT JOIN employees m
ON e.manager_id = m.id;
""")
class Employee:
| 64 | 64 | 44 | 3 | 61 | kzborisov/SoftUni | 4. Python Web (January 2022)/4.1 Python Web Basics (January 2022)/django_101/postgresSQL/main.py | Python | Employee | Employee | 21 | 27 | 21 | 21 | 5dea9c85e9170d0c5e25a372aa8ce2d103582511 | bigcode/the-stack | train |
c18b1d831941524e48f857f1 | train | class | class RawLoaderTestCase(unittest.TestCase):
def _verify_schema1_content(self, schema: SchemaDefinition, source_file,
addl_checks: Callable[[SchemaDefinition], None]=None) -> None:
expected = loads(f"""{{
"default_prefix": "http://example.org/{source_file}/",
... | class RawLoaderTestCase(unittest.TestCase):
| def _verify_schema1_content(self, schema: SchemaDefinition, source_file,
addl_checks: Callable[[SchemaDefinition], None]=None) -> None:
expected = loads(f"""{{
"default_prefix": "http://example.org/{source_file}/",
"name": "{source_file}",
"id... | import os
import unittest
from typing import Callable
from jsonasobj import as_json, loads, load, as_dict, JsonObj
from linkml_model.meta import SchemaDefinition
from linkml.utils.rawloader import load_raw_schema
from linkml.utils.schemaloader import SchemaLoader
from tests.test_utils.environment import env
class Raw... | 78 | 256 | 893 | 9 | 68 | bpow/linkml | tests/test_utils/test_load_raw_schema.py | Python | RawLoaderTestCase | RawLoaderTestCase | 13 | 102 | 13 | 14 | b30dcf11ed8f4fffcd19a0abe5f4e06d0d2647a1 | bigcode/the-stack | train |
a912aa08c987692e287d8693 | train | function | def get_repos_dir(vivp_dir):
"""returns the repos directory withing vivp_dir"""
return os.path.join(vivp_dir, VPACKAGE_HIDDEN, REPOS) | def get_repos_dir(vivp_dir):
| """returns the repos directory withing vivp_dir"""
return os.path.join(vivp_dir, VPACKAGE_HIDDEN, REPOS) | else:
return False
except:
return False
return True
def get_cache_dir(vivp_dir):
"""returns the chache directory withing vivp_dir"""
return os.path.join(vivp_dir, VPACKAGE_HIDDEN)
def get_repos_dir(vivp_dir):
| 64 | 64 | 40 | 10 | 54 | AdityaNG/VPM | libvivp/utils.py | Python | get_repos_dir | get_repos_dir | 90 | 92 | 90 | 90 | 85b73616dda9b4eff8614a1bd91f3dcfb849aa39 | bigcode/the-stack | train |
d725cd13b43f6dce6ce8c1da | train | function | def replaceAll(s, subs, rep):
"""
Replaces all substrings in a string with another string
"""
count = 0
for i in s:
if i == subs:
count += 1
return s.replace(subs, rep, count)
| def replaceAll(s, subs, rep):
| """
Replaces all substrings in a string with another string
"""
count = 0
for i in s:
if i == subs:
count += 1
return s.replace(subs, rep, count)
| ░ ▒ ░ ░ ░░ ░▒ ░
░░ ▒ ░ ░░ ░░
░ ░ ░
░ ░ """
def replaceAll(s, subs, rep):
| 64 | 64 | 61 | 9 | 55 | AdityaNG/VPM | libvivp/utils.py | Python | replaceAll | replaceAll | 22 | 30 | 22 | 22 | 9073b07ab5be5d6ba48b777a8a27083f7c790425 | bigcode/the-stack | train |
c250b6b1bde58d764df30d13 | train | function | def make_safe(s):
"""Replaces all spaces with '\\ '"""
return replaceAll(s, " ", "\\ ")
| def make_safe(s):
| """Replaces all spaces with '\\ '"""
return replaceAll(s, " ", "\\ ")
| All(s, subs, rep):
"""
Replaces all substrings in a string with another string
"""
count = 0
for i in s:
if i == subs:
count += 1
return s.replace(subs, rep, count)
def make_safe(s):
| 64 | 64 | 25 | 5 | 59 | AdityaNG/VPM | libvivp/utils.py | Python | make_safe | make_safe | 33 | 35 | 33 | 33 | c9a8dfa5740eb99cbde5d6fd83d39c9ba9025c1c | bigcode/the-stack | train |
885ed8c940dbeb97a3adf31d | train | function | def is_valid_git_url(u):
"""Returns True if u is a valid git URL, False otherwise"""
try:
a = urlparse(u)
if a.netloc == "github.com":
return True
else:
return False
except:
return False
return True
| def is_valid_git_url(u):
| """Returns True if u is a valid git URL, False otherwise"""
try:
a = urlparse(u)
if a.netloc == "github.com":
return True
else:
return False
except:
return False
return True
| _file(vivp_dir, d):
"""Returns True if d is a file within the directory vivp_dir, False otherwise"""
try:
open(os.path.join(vivp_dir, d), "r")
return True
except IOError:
return False
def is_valid_git_url(u):
| 64 | 64 | 64 | 7 | 56 | AdityaNG/VPM | libvivp/utils.py | Python | is_valid_git_url | is_valid_git_url | 72 | 82 | 72 | 72 | db20e138c50e2749141342e815eb010efebadb3a | bigcode/the-stack | train |
65dbab1de0f710645508f28d | train | function | def is_sub_file(vivp_dir, d):
"""Returns True if d is a file within the directory vivp_dir, False otherwise"""
try:
open(os.path.join(vivp_dir, d), "r")
return True
except IOError:
return False
| def is_sub_file(vivp_dir, d):
| """Returns True if d is a file within the directory vivp_dir, False otherwise"""
try:
open(os.path.join(vivp_dir, d), "r")
return True
except IOError:
return False
| _file(d):
"""Returns True if d is a vpackage.json, False otherwise"""
# TODO : Validate the vpackage.json structure and validity
try:
open(d, "r")
return True
except IOError:
return False
def is_sub_file(vivp_dir, d):
| 64 | 64 | 60 | 11 | 52 | AdityaNG/VPM | libvivp/utils.py | Python | is_sub_file | is_sub_file | 63 | 69 | 63 | 63 | 29fbd48f54c1013647d97b23269bf39f372951b6 | bigcode/the-stack | train |
4fc1b5d768b00b468fb5eb3c | train | function | def get_cache_dir(vivp_dir):
"""returns the chache directory withing vivp_dir"""
return os.path.join(vivp_dir, VPACKAGE_HIDDEN)
| def get_cache_dir(vivp_dir):
| """returns the chache directory withing vivp_dir"""
return os.path.join(vivp_dir, VPACKAGE_HIDDEN)
| Returns True if u is a valid git URL, False otherwise"""
try:
a = urlparse(u)
if a.netloc == "github.com":
return True
else:
return False
except:
return False
return True
def get_cache_dir(vivp_dir):
| 64 | 64 | 37 | 9 | 54 | AdityaNG/VPM | libvivp/utils.py | Python | get_cache_dir | get_cache_dir | 85 | 87 | 85 | 85 | 8fc640b2e3548cab48319c88e36d8c993e49411c | bigcode/the-stack | train |
78a555be7d3e7762c8aadcbe | train | function | def is_vivp_file(d):
"""Returns True if d is a vpackage.json, False otherwise"""
# TODO : Validate the vpackage.json structure and validity
try:
open(d, "r")
return True
except IOError:
return False
| def is_vivp_file(d):
| """Returns True if d is a vpackage.json, False otherwise"""
# TODO : Validate the vpackage.json structure and validity
try:
open(d, "r")
return True
except IOError:
return False
| .path.exists(os.path.join(d, VPACKAGE_JSON)):
return False
# TODO : Validate the vpackage.json file
try: # Check if git repo
g = Git(d)
g.remote()
except:
return False
return True
def is_vivp_file(d):
| 64 | 64 | 58 | 8 | 55 | AdityaNG/VPM | libvivp/utils.py | Python | is_vivp_file | is_vivp_file | 53 | 60 | 53 | 53 | 28986e4127f78a2edadcec5e842b41c92e16b1c0 | bigcode/the-stack | train |
bd87a1218bb3527ba43548f8 | train | function | def is_vivp_dir(d):
"""Returns True if d is a vivp directory, False otherwise"""
return os.path.exists(os.path.join(d, VPACKAGE_JSON))
if not os.path.exists(os.path.join(d, VPACKAGE_JSON)):
return False
# TODO : Validate the vpackage.json file
try: # Check if git repo
g = Git(d)
... | def is_vivp_dir(d):
| """Returns True if d is a vivp directory, False otherwise"""
return os.path.exists(os.path.join(d, VPACKAGE_JSON))
if not os.path.exists(os.path.join(d, VPACKAGE_JSON)):
return False
# TODO : Validate the vpackage.json file
try: # Check if git repo
g = Git(d)
g.remote()
... |
for i in s:
if i == subs:
count += 1
return s.replace(subs, rep, count)
def make_safe(s):
"""Replaces all spaces with '\\ '"""
return replaceAll(s, " ", "\\ ")
def is_vivp_dir(d):
| 63 | 64 | 97 | 8 | 55 | AdityaNG/VPM | libvivp/utils.py | Python | is_vivp_dir | is_vivp_dir | 38 | 50 | 38 | 38 | 56f445573b808731652fe60feb9e4c59e5dbfb4e | bigcode/the-stack | train |
fa605ed7bdb69010292dabab | train | function | def halve_until_1(start):
element = start
while True:
if element < 1:
break
yield element
element = int(element / 2)
| def halve_until_1(start):
| element = start
while True:
if element < 1:
break
yield element
element = int(element / 2)
| def halve_until_1(start):
| 7 | 64 | 39 | 7 | 0 | evolutics/sparse-approximation | src/lib/sequence.py | Python | halve_until_1 | halve_until_1 | 1 | 7 | 1 | 1 | c2cc8da2115fdca6fbe06854e6dd81c2fd2ca660 | bigcode/the-stack | train |
e622812f37547302bbcd6ac2 | train | function | def ostu(img):
area = 0
image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转灰度
blur = cv2.GaussianBlur(image, (5, 5), 0) # 阈值一定要设为 0 ！高斯模糊
ret3, th3 = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) # 二值化 0 = black ; 1 = white
# cv2.namedWindow("image", cv2.WINDOW_FREERATIO)
# c... | def ostu(img):
| area = 0
image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转灰度
blur = cv2.GaussianBlur(image, (5, 5), 0) # 阈值一定要设为 0 ！高斯模糊
ret3, th3 = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) # 二值化 0 = black ; 1 = white
# cv2.namedWindow("image", cv2.WINDOW_FREERATIO)
# cv2.imshow('imag... | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
# from PIL import Image
# INFO 2020/6/12 16:12 liliangbin 获取砂子的面积
############################################二值化砂子像素统计
def ostu(img):
| 64 | 66 | 220 | 5 | 58 | BorrowHome/flasky-sandbox | app/utils/areas_height/areaS.py | Python | ostu | ostu | 10 | 26 | 10 | 10 | 3706091ebe6b0cce91f6e8a72f228cfb2209d850 | bigcode/the-stack | train |
b90271d63f3912c5776e55ae | train | function | def trick_or_treat():
"""
heavily borrowed from chanrankim's trick_or_treat.ipynb
"""
return 'trick' if random.random() < .5 else 'treat'
| def trick_or_treat():
| """
heavily borrowed from chanrankim's trick_or_treat.ipynb
"""
return 'trick' if random.random() < .5 else 'treat'
| import random
def trick_or_treat():
| 9 | 64 | 44 | 6 | 2 | Pseudo-Lab/halloween_devfest | 2021/seokhyunseo/give_some_candies_or_not.py | Python | trick_or_treat | trick_or_treat | 4 | 8 | 4 | 4 | 66ff2e8b2e68da0a22b0f804a7b24d71cfc24355 | bigcode/the-stack | train |
bddbf4d11f837c7f15bffca9 | train | function | def give_some_candies_or_not(tot):
"""
tot : string
trick or treat!
return:
# of candies: int (1~50) if treat
None: None if trick
"""
num_of_candies = random.randint(1, 50)
if tot == 'treat':
return num_of_candies
else:
return None
| def give_some_candies_or_not(tot):
| """
tot : string
trick or treat!
return:
# of candies: int (1~50) if treat
None: None if trick
"""
num_of_candies = random.randint(1, 50)
if tot == 'treat':
return num_of_candies
else:
return None
| import random
def trick_or_treat():
"""
heavily borrowed from chanrankim's trick_or_treat.ipynb
"""
return 'trick' if random.random() < .5 else 'treat'
def give_some_candies_or_not(tot):
| 58 | 64 | 87 | 11 | 47 | Pseudo-Lab/halloween_devfest | 2021/seokhyunseo/give_some_candies_or_not.py | Python | give_some_candies_or_not | give_some_candies_or_not | 11 | 23 | 11 | 11 | 81bf72096209fc47827406a77c6201b3b488177d | bigcode/the-stack | train |
0277e82de004059c61815ecf | train | class | class CTFDumper:
def __init__(self, url, threads=10):
self.url = url
self.threads_num = threads
self.tasks = queue.Queue()
self.results_submissions = queue.Queue()
self.results_users = queue.Queue()
def _worker(self):
def get_submission_data(submission_task):
... | class CTFDumper:
| def __init__(self, url, threads=10):
self.url = url
self.threads_num = threads
self.tasks = queue.Queue()
self.results_submissions = queue.Queue()
self.results_users = queue.Queue()
def _worker(self):
def get_submission_data(submission_task):
page_num... | import requests, queue, re, urllib.parse, json, threading, tqdm, time
import pandas as pd
class CTFDumper:
| 29 | 256 | 1,122 | 6 | 22 | Ccamm/ctfdumper | ctfdumper/ctfdumper.py | Python | CTFDumper | CTFDumper | 4 | 156 | 4 | 5 | c4153fc1a0c21368373add4ef204cdf37759f78e | bigcode/the-stack | train |
2082aef4fcd99d965b41ff3b | train | function | def positive_nonzero_int(val):
ival = positive_int(val)
if ival == 0:
raise argparse.ArgumentTypeError("must be nonzero")
return ival
| def positive_nonzero_int(val):
| ival = positive_int(val)
if ival == 0:
raise argparse.ArgumentTypeError("must be nonzero")
return ival
|
def positive_int(val):
try:
ival = int(val)
except ValueError:
raise argparse.ArgumentTypeError("must be an integer")
if ival < 0:
raise argparse.ArgumentTypeError("must be positive")
return ival
def positive_nonzero_int(val):
| 64 | 64 | 40 | 7 | 56 | ploth/bcc | tools/offcputime.py | Python | positive_nonzero_int | positive_nonzero_int | 32 | 36 | 32 | 32 | 720b662a485f9d05161c93eeeda4b3f28e764097 | bigcode/the-stack | train |
82b1dc1d68ff3d79e568639f | train | function | def stack_id_err(stack_id):
# -EFAULT in get_stackid normally means the stack-trace is not availible,
# Such as getting kernel stack trace in userspace code
return (stack_id < 0) and (stack_id != -errno.EFAULT)
| def stack_id_err(stack_id):
# -EFAULT in get_stackid normally means the stack-trace is not availible,
# Such as getting kernel stack trace in userspace code
| return (stack_id < 0) and (stack_id != -errno.EFAULT)
| if ival == 0:
raise argparse.ArgumentTypeError("must be nonzero")
return ival
def stack_id_err(stack_id):
# -EFAULT in get_stackid normally means the stack-trace is not availible,
# Such as getting kernel stack trace in userspace code
| 64 | 64 | 59 | 40 | 23 | ploth/bcc | tools/offcputime.py | Python | stack_id_err | stack_id_err | 38 | 41 | 38 | 40 | efe739a3af70fd5f6965f19a9bf70b5903ac2b3d | bigcode/the-stack | train |
e9b4219068c570875d54329c | train | function | def positive_int(val):
try:
ival = int(val)
except ValueError:
raise argparse.ArgumentTypeError("must be an integer")
if ival < 0:
raise argparse.ArgumentTypeError("must be positive")
return ival
| def positive_int(val):
| try:
ival = int(val)
except ValueError:
raise argparse.ArgumentTypeError("must be an integer")
if ival < 0:
raise argparse.ArgumentTypeError("must be positive")
return ival
| License")
#
# 13-Jan-2016 Brendan Gregg Created this.
from __future__ import print_function
from bcc import BPF
from sys import stderr
from time import sleep, strftime
import argparse
import errno
import signal
# arg validation
def positive_int(val):
| 64 | 64 | 56 | 5 | 58 | ploth/bcc | tools/offcputime.py | Python | positive_int | positive_int | 22 | 30 | 22 | 22 | b63cb63e1de24e3a68fabdc5dce953b0abd3c54d | bigcode/the-stack | train |
0f419befd0ee410bbfb605a9 | train | function | def signal_ignore(signal, frame):
print()
| def signal_ignore(signal, frame):
| print()
| argparse.SUPPRESS)
args = parser.parse_args()
if args.pid and args.tgid:
parser.error("specify only one of -p and -t")
folded = args.folded
duration = int(args.duration)
debug = 0
# signal handler
def signal_ignore(signal, frame):
| 64 | 64 | 10 | 7 | 56 | ploth/bcc | tools/offcputime.py | Python | signal_ignore | signal_ignore | 109 | 110 | 109 | 109 | e60c0d1f4a3f90513571687f80bcbf356d24c880 | bigcode/the-stack | train |
c82ef3cc4d773d991840146f | train | function | def get_blocking_entities_at_location(entities, destination_x, destination_y):
for entity in entities:
if entity.blocks and entity.x == destination_x and entity.y == destination_y:
return entity
return None
| def get_blocking_entities_at_location(entities, destination_x, destination_y):
| for entity in entities:
if entity.blocks and entity.x == destination_x and entity.y == destination_y:
return entity
return None
| to move towards the player (closer to the corridor opening)
self.move_towards(target.x, target.y, game_map, entities)
# Delete the path to free memory
libtcod.path_delete(my_path)
def get_blocking_entities_at_location(entities, destination_x, destination_y):
| 64 | 64 | 47 | 16 | 48 | pypedreams/apoc | entity.py | Python | get_blocking_entities_at_location | get_blocking_entities_at_location | 130 | 135 | 130 | 130 | f23d52430b00e1c847d19c88c7e0214fcf49c76d | bigcode/the-stack | train |
bdc1747b79cf65cde5a2a2e7 | train | class | class Entity:
"""
A generic object to represent players, enemies, items, etc.
"""
def __init__(self, x, y, char, color, name, blocks=False, render_order=RenderOrder.CORPSE, fighter=None, ai=None,
item=None, inventory=None, stairs=None, level=None, equipment=None, equippable=None):
... | class Entity:
| """
A generic object to represent players, enemies, items, etc.
"""
def __init__(self, x, y, char, color, name, blocks=False, render_order=RenderOrder.CORPSE, fighter=None, ai=None,
item=None, inventory=None, stairs=None, level=None, equipment=None, equippable=None):
self.x = x
... | import libtcodpy as libtcod
import math
from components.item import Item
from render_functions import RenderOrder
class Entity:
| 29 | 256 | 1,127 | 3 | 25 | pypedreams/apoc | entity.py | Python | Entity | Entity | 10 | 127 | 10 | 10 | ab9bad0e56c683ea8b6158ab093f5b7c4063e0ec | bigcode/the-stack | train |
6ccfcf74564441f99da2cb91 | train | function | def test_span_extensions():
try:
nlp.add_pipe("contextual spellchecker")
except BaseException:
print("contextual SpellCheck already in pipeline")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_score = {
doc[2]: [],
doc[3... | def test_span_extensions():
| try:
nlp.add_pipe("contextual spellchecker")
except BaseException:
print("contextual SpellCheck already in pipeline")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_score = {
doc[2]: [],
doc[3]: [],
doc[4]: [
... | value in doc._.score_spellCheck.values()
for word_score in value
] == [
word_score[0] for value in gold_score.values() for word_score in value
]
assert [
word_score[1]
for value in doc._.score_spellCheck.values()
for word_score in value
] == approx(
[
... | 134 | 134 | 447 | 5 | 129 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_span_extensions | test_span_extensions | 427 | 482 | 427 | 427 | 6bf202840e38bbfed123da57774bef8120405f99 | bigcode/the-stack | train |
43a4f4dc1e0a6650fd1c9fce | train | function | def test_doc_extensions():
nlp.add_pipe("contextual spellchecker")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_suggestion = {
doc[4]: "million",
doc[13]: "million",
}
gold_outcome = (
"Income was $9.4 million compared to ... | def test_doc_extensions():
| nlp.add_pipe("contextual spellchecker")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_suggestion = {
doc[4]: "million",
doc[13]: "million",
}
gold_outcome = (
"Income was $9.4 million compared to the prior year of $2.7 mill... | Sentence)
(misspellings, doc) = checker.misspell_identify(doc)
doc, suggestions = checker.candidate_generator(doc, misspellings)
selectedWord = checker.candidate_ranking(doc, suggestions)
# changes made after v0.1
# assert selectedWord ==
# {doc[key]: value for key, value in misspell.items()}
... | 195 | 195 | 653 | 5 | 189 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_doc_extensions | test_doc_extensions | 347 | 424 | 347 | 347 | dd1f7a11925a90a124d502cf44e8c6b8d9caae25 | bigcode/the-stack | train |
560dad33b486cd46578b3ff7 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Mr Bond should be skipped", 1),
("Amitabh Bachan should not be in mis spell", 0),
("Amitabh Bachan shuld not be in mis spell", 1),
],
)
def test_skipName_misspellIdentify(inputSentence, misspell):
print("Start name not in m... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Mr Bond should be skipped", 1),
("Amitabh Bachan should not be in mis spell", 0),
("Amitabh Bachan shuld not be in mis spell", 1),
],
)
def test_skipName_misspellIdentify(inputSentence, misspell):
| print("Start name not in misspell word test\n")
doc = nlp(inputSentence)
# Number should not be skipped for misspell
assert doc[misspell] not in checker.misspell_identify(doc)[0]
| @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Mr Bond should be skipped", 1),
("Amitabh Bachan should not be in mis spell", 0),
("Amitabh Bachan shuld not be in mis spell", 1),
],
)
def test_skipName_misspellIdentify(inputSentence, misspell):
| 77 | 64 | 128 | 77 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_skipName_misspellIdentify | test_skipName_misspellIdentify | 98 | 110 | 98 | 106 | 568bc555c784b60e8ee731f0df372e1004cd6024 | bigcode/the-stack | train |
3c1f99cac9c0363ec0a56da2 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
)
],
)
def test_type_misspellIdentify(inputSentence, misspell):
print("Start type correction test for spelling mistake identifica... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
)
],
)
def test_type_misspellIdentify(inputSentence, misspell):
| print("Start type correction test for spelling mistake identification\n")
doc = nlp(inputSentence)
assert isinstance(checker.misspell_identify(doc)[0], type(misspell))
assert isinstance(checker.misspell_identify(doc)[1], type(doc))
assert checker.misspell_identify(doc)[1] == doc
| doc)
@pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
)
],
)
def test_type_misspellIdentify(inputSentence, misspell):
| 64 | 64 | 134 | 62 | 2 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_type_misspellIdentify | test_type_misspellIdentify | 38 | 52 | 38 | 47 | 35090af68bb5501236c95ca56afb071049300ba4 | bigcode/the-stack | train |
055e9c30e9d299f00d609c9f | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
True,
),
("This package was introduced in 2020", False),
],
)
def test_extension_candidateGenerator(inputSentence, misspell):
doc ... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
True,
),
("This package was introduced in 2020", False),
],
)
def test_extension_candidateGenerator(inputSentence, misspell):
| doc = nlp(inputSentence)
(misspellings, doc) = checker.misspell_identify(doc)
checker.candidate_generator(doc, misspellings)
assert doc._.performed_spellCheck == misspell
| @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
True,
),
("This package was introduced in 2020", False),
],
)
def test_extension_candidateGenerator(inputSentence, misspell):
| 69 | 64 | 117 | 69 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_extension_candidateGenerator | test_extension_candidateGenerator | 220 | 234 | 220 | 230 | b06e748a50d589382bc9692075dd30c55ee77b7f | bigcode/the-stack | train |
cbccad185ae2f9902df1822e | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
("million", 0.59422),
("billion", 0.24349),
(",", 0.08809),
... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
("million", 0.59422),
("billion", 0.24349),
(",", 0.08809),
... | doc = nlp(inputSentence)
(misspellings, doc) = checker.misspell_identify(doc)
doc, suggestions = checker.candidate_generator(doc, misspellings)
# changes after v0.1.0
assert [tokIndex.i for tokIndex in doc._.score_spellCheck.keys()] == [
tokIndex for tokIndex in misspell.keys()
]
as... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
("million", 0.59422),
("billion", 0.24349),
(",", 0.08809),
... | 408 | 183 | 613 | 408 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_extension2_candidateGenerator | test_extension2_candidateGenerator | 237 | 310 | 237 | 288 | 5c1b28732d3d305de6eaa23b3b7434c0bf59a3e0 | bigcode/the-stack | train |
1327537821c2b274237b81a7 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
),
("This packge was cretaed in 2020", [1, 3]),
],
)
def test_identify_misspellIdentify(inputSentence, misspell):
print("... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
),
("This packge was cretaed in 2020", [1, 3]),
],
)
def test_identify_misspellIdentify(inputSentence, misspell):
| print("Start misspell word identifation test\n")
doc = nlp(inputSentence)
checkerReturn = checker.misspell_identify(doc)[0]
assert isinstance(checkerReturn, list)
# Changed the approach after v0.1.0
assert [tok.text_with_ws for tok in checkerReturn] == [
doc[i].text_with_ws for i in miss... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
[4, 13],
),
("This packge was cretaed in 2020", [1, 3]),
],
)
def test_identify_misspellIdentify(inputSentence, misspell):
| 83 | 64 | 193 | 83 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_identify_misspellIdentify | test_identify_misspellIdentify | 55 | 74 | 55 | 65 | 6eea027800b14d33e23f59ca073f3a76ce5fff77 | bigcode/the-stack | train |
5090a246442f80c58eb3420e | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
"million",
"billion",
",",
"trillion",
... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
"million",
"billion",
",",
"trillion",
... | print("Start misspell word identifation test\n")
doc = nlp(inputSentence)
(misspellings, doc) = checker.misspell_identify(doc)
doc, suggestions = checker.candidate_generator(doc, misspellings)
# changed after v1.0 because of deepCopy creatng issue with ==
# gold_suggestions = {doc[key]: value fo... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{
4: [
"million",
"billion",
",",
"trillion",
... | 225 | 108 | 363 | 225 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_identify_candidateGenerator | test_identify_candidateGenerator | 154 | 215 | 154 | 205 | f834704c57eee0dfef931ac6b49b01f8d59af496 | bigcode/the-stack | train |
4776fb5d8d922e24c2b6a171 | train | function | def test_warning():
nlp = spacy.load("en_core_web_sm")
if "contextual spellchecker" not in nlp.pipe_names:
nlp.add_pipe("contextual spellchecker")
# merge_ents = nlp.create_pipe("merge_entities")
nlp.add_pipe("merge_entities")
doc = nlp(
"Income was $9.4 milion compared to the prior ... | def test_warning():
| nlp = spacy.load("en_core_web_sm")
if "contextual spellchecker" not in nlp.pipe_names:
nlp.add_pipe("contextual spellchecker")
# merge_ents = nlp.create_pipe("merge_entities")
nlp.add_pipe("merge_entities")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion.... | doc[4]._.get_suggestion_spellCheck == gold_suggestions
# Match words and score separately to incorporate approx fn in pytest
assert [word_score[0] for word_score in doc[4]._.score_spellCheck] == [
word_score[0] for word_score in gold_score
]
assert [
word_score[1] for word_score in doc[... | 139 | 139 | 466 | 4 | 135 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_warning | test_warning | 520 | 573 | 520 | 520 | f087dad91d8b9d9740041b9278b06c44add1b333 | bigcode/the-stack | train |
774fc2741ca5acf5ff7c4544 | train | function | @pytest.mark.parametrize(
"max_edit_distance,expected_spell_check_flag",
[(0, False), (1, False), (2, True), (3, True)],
)
def test_max_edit_dist(max_edit_distance, expected_spell_check_flag):
nlp = spacy.load("en_core_web_sm")
if "contextual spellchecker" in nlp.pipe_names:
nlp.remove_pipe("con... | @pytest.mark.parametrize(
"max_edit_distance,expected_spell_check_flag",
[(0, False), (1, False), (2, True), (3, True)],
)
def test_max_edit_dist(max_edit_distance, expected_spell_check_flag):
| nlp = spacy.load("en_core_web_sm")
if "contextual spellchecker" in nlp.pipe_names:
nlp.remove_pipe("contextual spellchecker")
# checker_edit_dist = ContextualSpellCheck(max_edit_dist=max_edit_distance)
nlp.add_pipe(
"contextual spellchecker", config={"max_edit_dist": max_edit_distance}
... | _sm")
ContextualSpellCheck(nlp, "contextualSpellCheck", model_name=model_name)
except OSError:
pytest.fail("Specificed model is not present in transformers")
except Exception as uncatched_error:
pytest.fail(str(uncatched_error))
@pytest.mark.parametrize(
"max_edit_distance,expected_s... | 108 | 108 | 360 | 51 | 57 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_max_edit_dist | test_max_edit_dist | 625 | 657 | 625 | 629 | 579303aa85e20ae72740bf91ebe8886c86e15280 | bigcode/the-stack | train |
fffbab59b48fedc4f78e2ab0 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com shuld be skipped", 0),
("bollywood.in shuld not be in mis spell", 0),
],
)
def test_type_candidateGenerator(inputSentence, misspell):
doc = nlp(inputSentence)
misspell, doc = checker.misspell_identify(doc)
as... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com shuld be skipped", 0),
("bollywood.in shuld not be in mis spell", 0),
],
)
def test_type_candidateGenerator(inputSentence, misspell):
| doc = nlp(inputSentence)
misspell, doc = checker.misspell_identify(doc)
assert isinstance(checker.candidate_generator(doc, misspell), tuple)
assert isinstance(checker.candidate_generator(doc, misspell)[0], type(doc))
assert isinstance(checker.candidate_generator(doc, misspell)[1], dict)
| _identify(doc)[0]
@pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com shuld be skipped", 0),
("bollywood.in shuld not be in mis spell", 0),
],
)
def test_type_candidateGenerator(inputSentence, misspell):
| 64 | 64 | 130 | 58 | 6 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_type_candidateGenerator | test_type_candidateGenerator | 139 | 151 | 139 | 146 | 2dd9e405bf5deb0dbf01f6f0b5aae7ad45124d5a | bigcode/the-stack | train |
9fcd019deb961b2caca1df5f | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com should be skipped", 0),
("bollywood.in should not be in mis spell", 0),
],
)
def test_skipURL_misspellIdentify(inputSentence, misspell):
print("Start URL not in misspell word test\n")
doc = nlp(inputSentence)
... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com should be skipped", 0),
("bollywood.in should not be in mis spell", 0),
],
)
def test_skipURL_misspellIdentify(inputSentence, misspell):
| print("Start URL not in misspell word test\n")
doc = nlp(inputSentence)
assert doc[misspell] not in checker.misspell_identify(doc)[0]
| ify(doc)[0]
@pytest.mark.parametrize(
"inputSentence, misspell",
[
("eng-movies.com should be skipped", 0),
("bollywood.in should not be in mis spell", 0),
],
)
def test_skipURL_misspellIdentify(inputSentence, misspell):
| 64 | 64 | 99 | 59 | 5 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_skipURL_misspellIdentify | test_skipURL_misspellIdentify | 126 | 136 | 126 | 133 | 82a28de3f81155dcf5e01b05d7cad5641d5f59d2 | bigcode/the-stack | train |
44e3f27d510c9d98554ad43b | train | function | def test_bert_model_name():
model_name = "a_random_model"
error_message = (
f"Can't load config for '{model_name}'. Make sure that:\n\n"
f"- '{model_name}' is a correct model identifier listed on \
'https://huggingface.co/models'\n\n"
f"- or '{model_name}' is the correct path to a direct... | def test_bert_model_name():
| model_name = "a_random_model"
error_message = (
f"Can't load config for '{model_name}'. Make sure that:\n\n"
f"- '{model_name}' is a correct model identifier listed on \
'https://huggingface.co/models'\n\n"
f"- or '{model_name}' is the correct path to a directory \
containing a config.js... | Check(
nlp, "contextualSpellCheck", vocab_path=testVocab, debug=True
)
with open(orgDebugFilePath) as f1:
with open(debugPathFile) as f2:
assert f1.read() == f2.read()
def test_bert_model_name():
| 64 | 64 | 142 | 7 | 57 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_bert_model_name | test_bert_model_name | 598 | 611 | 598 | 598 | 006c94742e755a18f5493f3aa70d2ae8f4a01c11 | bigcode/the-stack | train |
80056b0935d38dfcab2a3192 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Bond@movies.com should be skipped", 0),
("Amitabh.Bachan@bollywood.in should not be in mis spell", 0),
],
)
def test_skipEmail_misspellIdentify(inputSentence, misspell):
print("Start Email not in misspell word test\n")
doc = nl... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Bond@movies.com should be skipped", 0),
("Amitabh.Bachan@bollywood.in should not be in mis spell", 0),
],
)
def test_skipEmail_misspellIdentify(inputSentence, misspell):
| print("Start Email not in misspell word test\n")
doc = nlp(inputSentence)
assert doc[misspell] not in checker.misspell_identify(doc)[0]
| @pytest.mark.parametrize(
"inputSentence, misspell",
[
("Bond@movies.com should be skipped", 0),
("Amitabh.Bachan@bollywood.in should not be in mis spell", 0),
],
)
def test_skipEmail_misspellIdentify(inputSentence, misspell):
| 65 | 64 | 105 | 65 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_skipEmail_misspellIdentify | test_skipEmail_misspellIdentify | 113 | 123 | 113 | 120 | 0eafa2f2eed49b597d596f60e58484fc58f77879 | bigcode/the-stack | train |
1a19666371da2eb9294a33fe | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
3,
),
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
12,
),
("This packge ... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
3,
),
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
12,
),
("This packge ... | print("Start number not in misspell word test\n")
doc = nlp(inputSentence)
# Number should not be skipped for misspell
assert doc[misspell] not in checker.misspell_identify(doc)[0]
| @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
3,
),
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
12,
),
("This packge ... | 106 | 64 | 157 | 106 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_skipNumber_misspellIdentify | test_skipNumber_misspellIdentify | 77 | 95 | 77 | 91 | 0a0ccc84ddccb875a524c5f61bb145748f2ceb48 | bigcode/the-stack | train |
f2db300c5d2d5a8cccbb7290 | train | function | def test_correct_model_name():
model_name = "TurkuNLP/bert-base-finnish-cased-v1"
try:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(nlp, "contextualSpellCheck", model_name=model_name)
except OSError:
pytest.fail("Specificed model is not present in transformers")
except... | def test_correct_model_name():
| model_name = "TurkuNLP/bert-base-finnish-cased-v1"
try:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(nlp, "contextualSpellCheck", model_name=model_name)
except OSError:
pytest.fail("Specificed model is not present in transformers")
except Exception as uncatched_error:
... | config.json file\n\n"
)
with pytest.raises(OSError) as e:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(nlp, "contextualSpellCheck", model_name=model_name)
assert e == error_message
def test_correct_model_name():
| 64 | 64 | 97 | 6 | 57 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_correct_model_name | test_correct_model_name | 614 | 622 | 614 | 614 | 46272709b08425c9146198fe4a6f8badc62f6392 | bigcode/the-stack | train |
bc563d85c7d4fa06f193c7c4 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 million \
compared to the prior year of $2.7 million.",
[],
),
("who is Rajat Goel?", []),
("He released this package in year 2020!", []),
],
)
def test_no_misspellIdentify(input... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 million \
compared to the prior year of $2.7 million.",
[],
),
("who is Rajat Goel?", []),
("He released this package in year 2020!", []),
],
)
def test_no_misspellIdentify(input... | print("Start no spelling mistake test\n")
doc = nlp(inputSentence)
assert checker.misspell_identify(doc) == (misspell, doc)
| @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 million \
compared to the prior year of $2.7 million.",
[],
),
("who is Rajat Goel?", []),
("He released this package in year 2020!", []),
],
)
def test_no_misspellIdentify(input... | 84 | 64 | 119 | 84 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_no_misspellIdentify | test_no_misspellIdentify | 20 | 35 | 20 | 32 | 552f08d7fcf7c7f0e98a2f95b994a2e351733265 | bigcode/the-stack | train |
e8c12eb889f12e144c908c51 | train | function | def test_compatible_spacyPipeline():
nlp.add_pipe("contextual spellchecker")
assert "contextual spellchecker" in nlp.pipe_names
nlp.remove_pipe("contextual spellchecker")
assert "contextual spellchecker" not in nlp.pipe_names
| def test_compatible_spacyPipeline():
| nlp.add_pipe("contextual spellchecker")
assert "contextual spellchecker" in nlp.pipe_names
nlp.remove_pipe("contextual spellchecker")
assert "contextual spellchecker" not in nlp.pipe_names
| misspell.items()}
assert [tok.i for tok in selectedWord.keys()] == [
tok for tok in misspell.keys()
]
assert [tokString for tokString in selectedWord.values()] == [
tok for tok in misspell.values()
]
def test_compatible_spacyPipeline():
| 63 | 64 | 59 | 8 | 55 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_compatible_spacyPipeline | test_compatible_spacyPipeline | 339 | 344 | 339 | 339 | 070d82a7ac5b1d0fa707c634dda24773a01824ef | bigcode/the-stack | train |
708bc844b91d482b5d2d04fd | train | function | @pytest.mark.parametrize(
"input_sentence,expected_outcome,\
expected_suggestion_doc,possible_misspel_index,misspell_suggestion",
[
(
"This is not a pure Python Spell Checking based on Peter Norvig’s \
blog post on setting up a simple spell checking algorithm.",
"",
{... | @pytest.mark.parametrize(
"input_sentence,expected_outcome,\
expected_suggestion_doc,possible_misspel_index,misspell_suggestion",
[
(
"This is not a pure Python Spell Checking based on Peter Norvig’s \
blog post on setting up a simple spell checking algorithm.",
"",
{... | nlp_lg = spacy.load("en_core_web_lg")
# checker_deep_tokenize =
# ContextualSpellCheck(nlp,"contextualSpellCheck",max_edit_dist=3)
nlp_lg.add_pipe("contextual spellchecker", config={"max_edit_dist": 3})
doc = nlp_lg(input_sentence)
# To check the status of `performed_spell_check` flag
asser... | @pytest.mark.parametrize(
"input_sentence,expected_outcome,\
expected_suggestion_doc,possible_misspel_index,misspell_suggestion",
[
(
"This is not a pure Python Spell Checking based on Peter Norvig’s \
blog post on setting up a simple spell checking algorithm.",
"",
{... | 211 | 123 | 410 | 211 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_doc_extensions_bug | test_doc_extensions_bug | 660 | 709 | 660 | 691 | 3792e312bbef97b4a89fadb78461cbaf24d7aac4 | bigcode/the-stack | train |
f136b0d7b3f51ecefcdaff93 | train | function | def test_vocab_file():
with warnings.catch_warnings(record=True) as w:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(
nlp, "contextualSpellCheck", vocab_path="testing.txt"
)
assert any([issubclass(i.category, UserWarning) for i in w])
assert any(["Using ... | def test_vocab_file():
| with warnings.catch_warnings(record=True) as w:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(
nlp, "contextualSpellCheck", vocab_path="testing.txt"
)
assert any([issubclass(i.category, UserWarning) for i in w])
assert any(["Using default vocab" in str(i... | million")
assert e.type is ValueError
try:
nlp = spacy.load("en_core_web_sm")
ContextualSpellCheck(nlp, "contextualSpellCheck", max_edit_dist="3.1")
except Exception as uncatched_error:
pytest.fail(str(uncatched_error))
def test_vocab_file():
| 71 | 71 | 238 | 5 | 66 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_vocab_file | test_vocab_file | 576 | 595 | 576 | 576 | 263d04f079983aab6b60e60f9111017033947c15 | bigcode/the-stack | train |
c0bc593b1823f3a4a07623e0 | train | function | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{4: "million", 13: "million"},
),
("This package was introduced in 2020", {}),
],
)
def test_ranking_candidateRanking(inputSentence, m... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{4: "million", 13: "million"},
),
("This package was introduced in 2020", {}),
],
)
def test_ranking_candidateRanking(inputSentence, m... | doc = nlp(inputSentence)
(misspellings, doc) = checker.misspell_identify(doc)
doc, suggestions = checker.candidate_generator(doc, misspellings)
selectedWord = checker.candidate_ranking(doc, suggestions)
# changes made after v0.1
# assert selectedWord ==
# {doc[key]: value for key, value in m... | @pytest.mark.parametrize(
"inputSentence, misspell",
[
(
"Income was $9.4 milion compared to the prior year of $2.7 milion.",
{4: "million", 13: "million"},
),
("This package was introduced in 2020", {}),
],
)
def test_ranking_candidateRanking(inputSentence, m... | 79 | 64 | 215 | 79 | 0 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_ranking_candidateRanking | test_ranking_candidateRanking | 313 | 336 | 313 | 323 | 8f8f4b165b50834a2920dbc55d2ed07b0de29728 | bigcode/the-stack | train |
b8aa91f3b5ae95dd361a671d | train | function | def test_token_extension():
if "contextual spellchecker" not in nlp.pipe_names:
nlp.add_pipe("contextual spellchecker")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_suggestions = "million"
gold_score = [
("million", 0.59422),
... | def test_token_extension():
| if "contextual spellchecker" not in nlp.pipe_names:
nlp.add_pipe("contextual spellchecker")
doc = nlp(
"Income was $9.4 milion compared to the prior year of $2.7 milion."
)
gold_suggestions = "million"
gold_score = [
("million", 0.59422),
("billion", 0.24349),
... | ] == approx(
[
word_score[1]
for value in gold_score.values()
for word_score in value
],
rel=1e-4,
abs=1e-4,
)
# assert doc[2:6]._.score_spellCheck ==
# approx(gold_score,rel=1e-4, abs=1e-4)
nlp.remove_pipe("contextual spellchecker")
... | 98 | 98 | 328 | 5 | 93 | dc-aichara/contextualSpellCheck | contextualSpellCheck/tests/test_contextualSpellCheck.py | Python | test_token_extension | test_token_extension | 485 | 517 | 485 | 485 | 74e443ea18da80e728fd1e058f32b3a7663e505d | bigcode/the-stack | train |
26947dfc055fceb66cb9daef | train | function | def timeout(duration, default=None):
def decorator(func):
class InterruptableThread(threading.Thread):
def __init__(self, args, kwargs):
threading.Thread.__init__(self)
self.args = args
self.kwargs = kwargs
self.result = default
... | def timeout(duration, default=None):
| def decorator(func):
class InterruptableThread(threading.Thread):
def __init__(self, args, kwargs):
threading.Thread.__init__(self)
self.args = args
self.kwargs = kwargs
self.result = default
self.daemon = True
... | from sklearn.cluster import DBSCAN
class TestTimeoutException(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
# thanks to https://gist.github.com/vadimg/2902788
def timeout(duration, default=None):
| 64 | 64 | 194 | 7 | 56 | sherbold/replication-kit-2020-smoke-testing | generated-tests/sklearn/test_SKLEARN_DBSCAN.py | Python | timeout | timeout | 24 | 52 | 24 | 24 | f0cd944e960ad6d960f1169f8e34a10e2e387154 | bigcode/the-stack | train |
a297efdaf809c7495d4b1ba2 | train | class | class test_SKLEARN_DBSCAN(unittest.TestCase):
params = [("{'p':None,'min_samples':5,'leaf_size':50,'metric':'euclidean','n_jobs':None,'eps':0.1,'algorithm':'auto',}", {'p':None,'min_samples':5,'leaf_size':50,'metric':'euclidean','n_jobs':None,'eps':0.1,'algorithm':'auto',}),
("{'p':None,'min_samples'... | class test_SKLEARN_DBSCAN(unittest.TestCase):
| params = [("{'p':None,'min_samples':5,'leaf_size':50,'metric':'euclidean','n_jobs':None,'eps':0.1,'algorithm':'auto',}", {'p':None,'min_samples':5,'leaf_size':50,'metric':'euclidean','n_jobs':None,'eps':0.1,'algorithm':'auto',}),
("{'p':None,'min_samples':5,'leaf_size':50,'metric':'euclidean','n_jobs'... |
class TestTimeoutException(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
# thanks to https://gist.github.com/vadimg/2902788
def timeout(duration, default=None):
def decorator(func):
class InterruptableThread(threading.Thread)... | 256 | 256 | 3,803 | 11 | 244 | sherbold/replication-kit-2020-smoke-testing | generated-tests/sklearn/test_SKLEARN_DBSCAN.py | Python | test_SKLEARN_DBSCAN | test_SKLEARN_DBSCAN | 54 | 315 | 54 | 55 | 1b7ea1a33093b5a7ce0ab8921fe79ab69ad477e1 | bigcode/the-stack | train |
dcc231be9e2f8af201bc646c | train | class | class TestTimeoutException(Exception):
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
| class TestTimeoutException(Exception):
| def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
| threading
import functools
import inspect
import math
import warnings
import traceback
from parameterized import parameterized
from scipy.io.arff import loadarff
from scipy.stats import ttest_1samp, ks_2samp
from sklearn.cluster import DBSCAN
class TestTimeoutException(Exception):
| 64 | 64 | 34 | 6 | 57 | sherbold/replication-kit-2020-smoke-testing | generated-tests/sklearn/test_SKLEARN_DBSCAN.py | Python | TestTimeoutException | TestTimeoutException | 17 | 21 | 17 | 17 | 9f2d76cf9a4b7b15b7e682a99d1a7ce9592e70cb | bigcode/the-stack | train |
9c65f56f31230b576a170d0b | train | function | def test_datetime_from_iso_timestamp():
# arrange
t = VatsimGeneral(
"1", # version
"1", # reload
"00000", # update
"2021-04-27T18:39:55", # timestamp
1, # connected clients
1, # unique clients
)
# act
dt = t.get_datetime()
print(dt.timetz.__... | def test_datetime_from_iso_timestamp():
# arrange
| t = VatsimGeneral(
"1", # version
"1", # reload
"00000", # update
"2021-04-27T18:39:55", # timestamp
1, # connected clients
1, # unique clients
)
# act
dt = t.get_datetime()
print(dt.timetz.__repr__)
# assert
assert dt == datetime.fromis... | from datetime import datetime
import pytest
from ..models.models import VatsimGeneral
def test_datetime_from_iso_timestamp():
# arrange
| 29 | 64 | 128 | 11 | 17 | ahuimanu/vatsimlib | tests/test_models.py | Python | test_datetime_from_iso_timestamp | test_datetime_from_iso_timestamp | 7 | 22 | 7 | 8 | 9e0b5bbbe2d424d83e5a166fcc28ed0d2b9474a5 | bigcode/the-stack | train |
87969e60d8aa61130bceb719 | train | function | def test_generator_local_git_repo_root_directory():
"""Generator for tests requiring operation in a git repository.
This will move into a temporary directory which is a git repository. It
will then return the tests with the given script and settings list.
When called by nosetests, nosetests will run e... | def test_generator_local_git_repo_root_directory():
| """Generator for tests requiring operation in a git repository.
This will move into a temporary directory which is a git repository. It
will then return the tests with the given script and settings list.
When called by nosetests, nosetests will run every yielded test function.
Yields:
A :... | _creation_fails_if_located_inside_local_git_repository_root_directory",
'arguments': "test_module_git_root_directory",
'exception_type': "VerificationError",
'exception_string': "Currently in a git repository, please move elsewhere and try again.",
},
]
def test_generator_local_git_repo_r... | 64 | 64 | 161 | 9 | 55 | hir12111/dls_ade | system_testing/start_new_module/local_verification_tests.py | Python | test_generator_local_git_repo_root_directory | test_generator_local_git_repo_root_directory | 78 | 103 | 78 | 78 | e811bfcb7c951e941e3d8b11958a8327f06989ed | bigcode/the-stack | train |
9fe81c6e198ac29c28f8e113 | train | function | def test_generator_conflicting_filepaths_expected():
"""Generator for tests involving a conflict of filepaths.
This will move into a temporary directory which already has a number of
folders that will conflict with the file creation process. It
will then return the tests with the given script and setti... | def test_generator_conflicting_filepaths_expected():
| """Generator for tests involving a conflict of filepaths.
This will move into a temporary directory which already has a number of
folders that will conflict with the file creation process. It
will then return the tests with the given script and settings list.
When called by nosetests, nosetests wi... | VerificationError",
'exception_string': "Directory testB21/testB21-EA-IOC-01 already exists, please move elsewhere and try again.",
'create_folder': "testB21/testB21-EA-IOC-01"
},
]
def test_generator_conflicting_filepaths_expected():
| 64 | 64 | 183 | 9 | 55 | hir12111/dls_ade | system_testing/start_new_module/local_verification_tests.py | Python | test_generator_conflicting_filepaths_expected | test_generator_conflicting_filepaths_expected | 35 | 62 | 35 | 35 | 5d19b47e509c011dc4824e4f67f6b1e3fa8bbf43 | bigcode/the-stack | train |
7610c711718b4912bdab2eb2 | train | class | class TranslateService:
translator = Translator()
def __init__(self):
return
def translate(self, text, src, dest):
t = self.translator.translate(text, src=src, dest=dest)
return t.text
| class TranslateService:
| translator = Translator()
def __init__(self):
return
def translate(self, text, src, dest):
t = self.translator.translate(text, src=src, dest=dest)
return t.text
| from googletrans import Translator
class TranslateService:
| 10 | 64 | 52 | 4 | 5 | alejandro-mosso/language-service | app/translate/services.py | Python | TranslateService | TranslateService | 4 | 13 | 4 | 5 | 7998f529d8280cc2ee0e6820ed0cd79bfa53a5be | bigcode/the-stack | train |
90a9aaa48c78552190638fc2 | train | function | def random_name_generator(first, second, x):
"""
Generates random names.
Arguments:
- list of first names
- list of last names
- number of random names
"""
names = []
for i in range(x):
names.append("{0} {1}".format(choice(first), choice(second)))
r... | def random_name_generator(first, second, x):
| """
Generates random names.
Arguments:
- list of first names
- list of last names
- number of random names
"""
names = []
for i in range(x):
names.append("{0} {1}".format(choice(first), choice(second)))
return set(names)
| from random import choice
def random_name_generator(first, second, x):
| 15 | 64 | 75 | 10 | 4 | webdevhub42/Lambda | WEEKS/CD_Sata-Structures/_RESOURCES/python-prac/python-scripts/scripts/13_random_name_generator.py | Python | random_name_generator | random_name_generator | 4 | 15 | 4 | 4 | 4334aea2d2a8400fd29600a1fab76ed9226596a6 | bigcode/the-stack | train |
1c4376ddaf609f6413038982 | train | function | @register.inclusion_tag("admin/includes/recent_comments.html", takes_context=True)
def recent_comments(context):
"""
Dashboard widget for displaying recent comments.
"""
latest = context["settings"].COMMENTS_NUM_LATEST
comments = ThreadedComment.objects.all().select_related("user")
context["comm... | @register.inclusion_tag("admin/includes/recent_comments.html", takes_context=True)
def recent_comments(context):
| """
Dashboard widget for displaying recent comments.
"""
latest = context["settings"].COMMENTS_NUM_LATEST
comments = ThreadedComment.objects.all().select_related("user")
context["comments"] = comments.order_by("-id")[:latest]
return context.flatten()
| _comments"].get(parent_id, []),
"no_comments": parent_id is None and not context["all_comments"],
"replied_to": replied_to,
}
)
return context.flatten()
@register.inclusion_tag("admin/includes/recent_comments.html", takes_context=True)
def recent_comments(context):
| 64 | 64 | 80 | 22 | 42 | DatCGI2net/mezzanine | mezzanine/generic/templatetags/comment_tags.py | Python | recent_comments | recent_comments | 68 | 76 | 68 | 69 | 12db31872da18904fbc564a54146f29b49c4e60c | bigcode/the-stack | train |
84c5ae96f7acd553de862c29 | train | function | @register.filter
def comment_filter(comment_text):
"""
Passed comment text to be rendered through the function defined
by the ``COMMENT_FILTER`` setting. If no function is defined
(the default), Django's ``linebreaksbr`` and ``urlize`` filters
are used.
"""
filter_func = settings.COMMENT_FIL... | @register.filter
def comment_filter(comment_text):
| """
Passed comment text to be rendered through the function defined
by the ``COMMENT_FILTER`` setting. If no function is defined
(the default), Django's ``linebreaksbr`` and ``urlize`` filters
are used.
"""
filter_func = settings.COMMENT_FILTER
if not filter_func:
def filter_fun... | widget for displaying recent comments.
"""
latest = context["settings"].COMMENTS_NUM_LATEST
comments = ThreadedComment.objects.all().select_related("user")
context["comments"] = comments.order_by("-id")[:latest]
return context.flatten()
@register.filter
def comment_filter(comment_text):
| 64 | 64 | 129 | 10 | 54 | DatCGI2net/mezzanine | mezzanine/generic/templatetags/comment_tags.py | Python | comment_filter | comment_filter | 79 | 95 | 79 | 80 | c2c5167bdbda0db2caa6cfc8237c86100e797061 | bigcode/the-stack | train |
7c31f9fddedb0f384eb37f22 | train | function | @register.inclusion_tag("generic/includes/comments.html", takes_context=True)
def comments_for(context, obj):
"""
Provides a generic context variable name for the object that
comments are being rendered for.
"""
form_class = import_dotted_path(settings.COMMENT_FORM_CLASS)
form = form_class(conte... | @register.inclusion_tag("generic/includes/comments.html", takes_context=True)
def comments_for(context, obj):
| """
Provides a generic context variable name for the object that
comments are being rendered for.
"""
form_class = import_dotted_path(settings.COMMENT_FORM_CLASS)
form = form_class(context["request"], obj)
context_form = context.get("posted_comment_form", form)
context.update(
{
... | reverse
from mezzanine import template
from mezzanine.conf import settings
from mezzanine.generic.models import ThreadedComment
from mezzanine.utils.importing import import_dotted_path
register = template.Library()
@register.inclusion_tag("generic/includes/comments.html", takes_context=True)
def comments_for(context... | 64 | 64 | 146 | 22 | 42 | DatCGI2net/mezzanine | mezzanine/generic/templatetags/comment_tags.py | Python | comments_for | comments_for | 14 | 33 | 14 | 15 | 62319d68c6f0686e1c3a26ccd77deb41f8c138fa | bigcode/the-stack | train |
fb8c2d64c94a0b79af926937 | train | function | @register.inclusion_tag("generic/includes/comment.html", takes_context=True)
def comment_thread(context, parent):
"""
Return a list of child comments for the given parent, storing all
comments in a dict in the context when first called, using parents
as keys for retrieval on subsequent recursive calls f... | @register.inclusion_tag("generic/includes/comment.html", takes_context=True)
def comment_thread(context, parent):
| """
Return a list of child comments for the given parent, storing all
comments in a dict in the context when first called, using parents
as keys for retrieval on subsequent recursive calls from the
comments template.
"""
if "all_comments" not in context:
comments = defaultdict(list)
... | "posted_comment_form": context_form
if context_form.target_object == obj
else form,
"unposted_comment_form": form,
"comment_url": reverse("comment"),
"object_for_comments": obj,
}
)
return context.flatten()
@register.inclusion_tag("generic/inc... | 78 | 78 | 263 | 22 | 56 | DatCGI2net/mezzanine | mezzanine/generic/templatetags/comment_tags.py | Python | comment_thread | comment_thread | 36 | 65 | 36 | 37 | 061fe239106c412f8ce161044a817e034be33a54 | bigcode/the-stack | train |
6d37aa215268fe952a50c4ad | train | function | def by_id(
move_data: DataFrame,
id_: Optional[int] = None,
label_id: Optional[Text] = TRAJ_ID,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
"""
Filters trajectories points according to specified trajectory id.
Parameters
----------
... | def by_id(
move_data: DataFrame,
id_: Optional[int] = None,
label_id: Optional[Text] = TRAJ_ID,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| """
Filters trajectories points according to specified trajectory id.
Parameters
----------
move_data : dataframe
The input trajectory data
id_ : int
Specifies the number of the id used to filter the trajectories points
label_id : str, optional
The label of the colum... | return move_data.drop(index=move_data[~filter_].index, inplace=inplace)
def by_id(
move_data: DataFrame,
id_: Optional[int] = None,
label_id: Optional[Text] = TRAJ_ID,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| 81 | 81 | 273 | 61 | 20 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | by_id | by_id | 214 | 249 | 214 | 220 | ba4d1b0a048fb85042e1cbe987d64e7622b64e7b | bigcode/the-stack | train |
2ed1322fdaa66bdfa4fb9647 | train | function | def by_datetime(
move_data: DataFrame,
start_datetime: Optional[Text] = None,
end_datetime: Optional[Text] = None,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False,
) -> Optional[DataFrame]:
"""
Filters trajectories points according to specified time range.
Parameters... | def by_datetime(
move_data: DataFrame,
start_datetime: Optional[Text] = None,
end_datetime: Optional[Text] = None,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False,
) -> Optional[DataFrame]:
| """
Filters trajectories points according to specified time range.
Parameters
----------
move_data : dataframe
The input trajectory data
start_datetime : str
The start date and time (Datetime format) of the time range, by default None
end_datetime : str
The end date ... | [2])
& (move_data[LONGITUDE] <= bbox[3])
)
if filter_out:
filter_ = ~filter_
return move_data.drop(index=move_data[~filter_].index, inplace=inplace)
def by_datetime(
move_data: DataFrame,
start_datetime: Optional[Text] = None,
end_datetime: Optional[Text] = None,
filter_out:... | 112 | 112 | 375 | 61 | 51 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | by_datetime | by_datetime | 125 | 171 | 125 | 131 | c6b0ef1f00988a8d42fd39e6c1db6280f0a71492 | bigcode/the-stack | train |
f0b2541b0e3898e3833a3dff | train | function | def by_tid(
move_data: DataFrame,
tid_: Optional[Text] = None,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
"""
Filters trajectories points according to a specified trajectory tid.
Parameters
----------
move_data : dataframe
... | def by_tid(
move_data: DataFrame,
tid_: Optional[Text] = None,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| """
Filters trajectories points according to a specified trajectory tid.
Parameters
----------
move_data : dataframe
The input trajectory data
tid_ : str
Specifies the number of the tid used to filter the trajectories points
label_tid : str, optional
The label of th... | Returns dataframe with trajectories points filtered by id or None
"""
return by_label(move_data, id_, label_id, filter_out, inplace)
def by_tid(
move_data: DataFrame,
tid_: Optional[Text] = None,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| 79 | 79 | 265 | 49 | 30 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | by_tid | by_tid | 252 | 285 | 252 | 257 | 3488c43b2e1580489300f466f6f1b26841623b09 | bigcode/the-stack | train |
374f8a7731bf7bf7c14ca26a | train | function | def clean_trajectories_short_and_few_points(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TID,
min_trajectory_distance: Optional[float] = 100,
min_points_per_trajectory: Optional[int] = 2,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional... | def clean_trajectories_short_and_few_points(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TID,
min_trajectory_distance: Optional[float] = 100,
min_points_per_trajectory: Optional[int] = 2,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional... | """
Eliminates from the given dataframe trajectories with fewer points and shorter length.
Parameters
----------
move_data : dataframe
The input trajectory data
label_id : str, optional
The label of the column which contains the tid of the trajectories, by default TID
min_tr... | '\n...Tids before drop: %s'
% move_df[label_tid].unique().shape[0]
)
move_df.drop(index=idx, inplace=True)
logger.debug(
'\n...Tids after drop: %s'
% move_df[label_tid].unique().shape[0]
)
logger.debug(
'\n...Shape - before drop: %... | 227 | 227 | 757 | 114 | 112 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_trajectories_short_and_few_points | clean_trajectories_short_and_few_points | 855 | 942 | 855 | 862 | b57d82252731946250848272f82027457f457f64 | bigcode/the-stack | train |
c65b265fb2390f028e91050f | train | function | def clean_gps_nearby_points_by_speed(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
speed_radius: Optional[float] = 0.0,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'Dask... | def clean_gps_nearby_points_by_speed(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
speed_radius: Optional[float] = 0.0,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'Dask... | """
Removes points from the trajectories with smaller speed of travel.
Parameters
----------
move_data : dataframe
The input trajectory data
label_id : str, optional
Indicates the label of the id column in the user dataframe, be defalt TRAJ_ID
speed_radius : float, optional... | arg2=radius_area,
outliers=False
)
if not inplace:
return move_df
def clean_gps_nearby_points_by_speed(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
speed_radius: Optional[float] = 0.0,
label_dtype: Optional[Callable] = np.flo... | 123 | 123 | 412 | 100 | 22 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_gps_nearby_points_by_speed | clean_gps_nearby_points_by_speed | 653 | 707 | 653 | 659 | 1e3b7427004338d8c0dd158be5fc322e45ea0434 | bigcode/the-stack | train |
9cc3edd59c644958fdb68c0b | train | function | def clean_gps_jumps_by_distance(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
jump_coefficient: Optional[float] = 3.0,
threshold: Optional[float] = 1,
label_dtype: Optional[callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional... | def clean_gps_jumps_by_distance(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
jump_coefficient: Optional[float] = 3.0,
threshold: Optional[float] = 1,
label_dtype: Optional[callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional... | """
Removes the trajectories points that are outliers from the dataframe.
Parameters
----------
move_data : dataframe
The input trajectory data
label_id : str, optional
Indicates the label of the id column in the user dataframe, by default TRAJ_ID
jump_coefficient : float, ... | logger.debug('%s GPS points were dropped' % sum_drop)
return move_data
def clean_gps_jumps_by_distance(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
jump_coefficient: Optional[float] = 3.0,
threshold: Optional[float] = 1,
label_dtype: Opt... | 130 | 130 | 435 | 111 | 18 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_gps_jumps_by_distance | clean_gps_jumps_by_distance | 534 | 592 | 534 | 541 | e8844532b2ddfeae1c65354ac6b75b49238852b2 | bigcode/the-stack | train |
defca5a3071a33269f861696 | train | function | def clean_consecutive_duplicates(
move_data: DataFrame,
subset: Optional[Union[int, Text]] = None,
keep: Optional[Union[Text, bool]] = 'first',
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
"""
Removes consecutive duplicate rows of the Dataframe.
Optionally only certain columns ... | def clean_consecutive_duplicates(
move_data: DataFrame,
subset: Optional[Union[int, Text]] = None,
keep: Optional[Union[Text, bool]] = 'first',
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| """
Removes consecutive duplicate rows of the Dataframe.
Optionally only certain columns can be consider.
Parameters
----------
move_data : dataframe
The input trajectory data
subset : Array of strs, optional
Specifies Column label or sequence of labels, considered for
... | logger.debug('...Filtering jumps \n')
return move_data.drop(index=move_data[~filter_].index, inplace=inplace)
else:
logger.warning('...Distances features were not created')
return move_data
def clean_consecutive_duplicates(
move_data: DataFrame,
subset: Optional[Union[int, Text]] =... | 106 | 106 | 356 | 58 | 47 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_consecutive_duplicates | clean_consecutive_duplicates | 354 | 399 | 354 | 359 | 8d1cdc1c86d31bff57d5432f2984c3a7847d8ece | bigcode/the-stack | train |
17edb5869607f130a1d488ab | train | function | def by_bbox(
move_data: DataFrame,
bbox: Tuple[int, int, int, int],
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
"""
Filters points of the trajectories according to specified bounding box.
Parameters
----------
move_data : dataframe
... | def by_bbox(
move_data: DataFrame,
bbox: Tuple[int, int, int, int],
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| """
Filters points of the trajectories according to specified bounding box.
Parameters
----------
move_data : dataframe
The input trajectories data
bbox : tuple
Tuple of 4 elements, containing the minimum and maximum values
of latitude and longitude of the bounding box.
... | .cos(lat))
lonmin = lon - delta_lon
lonmax = lon + delta_lon
return np.rad2deg([latmin, lonmin, latmax, lonmax])
def by_bbox(
move_data: DataFrame,
bbox: Tuple[int, int, int, int],
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| 91 | 91 | 305 | 51 | 40 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | by_bbox | by_bbox | 84 | 122 | 84 | 89 | 91f10be252344e76cbf8fa1cc64d3a020b623393 | bigcode/the-stack | train |
57ff0c194b694d473114740e | train | function | def _filter_speed_max_radius(move_data: DataFrame, **kwargs):
"""
Filters from a dataframe rows with current or previous row features exceeding value.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
**kwargs : arguments
- arg1 : feature
- arg2 : val... | def _filter_speed_max_radius(move_data: DataFrame, **kwargs):
| """
Filters from a dataframe rows with current or previous row features exceeding value.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
**kwargs : arguments
- arg1 : feature
- arg2 : value
Returns
-------
DataFrame
Filtered dat... | - arg1 : feature
- arg2 : value
Returns
-------
DataFrame
Filtered dataframe.
"""
return move_data[move_data[kwargs['arg1']] <= kwargs['arg2']]
def _filter_speed_max_radius(move_data: DataFrame, **kwargs):
| 63 | 64 | 148 | 15 | 48 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | _filter_speed_max_radius | _filter_speed_max_radius | 423 | 445 | 423 | 423 | 7975ffa549e40cbbac7802d76388ed4d9a6812cc | bigcode/the-stack | train |
1ec2909353494aca7778c9ac | train | function | def get_bbox_by_radius(
coordinates: Tuple[float, float], radius: Optional[float] = 1000
) -> List:
"""
Defines minimum and maximum coordinates, given a distance radius from a point.
Parameters
----------
coords : tuple (lat, lon)
The coordinates of point
radius: float, optional (1... | def get_bbox_by_radius(
coordinates: Tuple[float, float], radius: Optional[float] = 1000
) -> List:
| """
Defines minimum and maximum coordinates, given a distance radius from a point.
Parameters
----------
coords : tuple (lat, lon)
The coordinates of point
radius: float, optional (1000 by default)
Returns
-------
array
coordinates min and max of the bbox
Refe... | .utils.log import logger
if TYPE_CHECKING:
from pymove.core.dask import DaskMoveDataFrame
from pymove.core.pandas import PandasMoveDataFrame
def get_bbox_by_radius(
coordinates: Tuple[float, float], radius: Optional[float] = 1000
) -> List:
| 68 | 68 | 228 | 30 | 37 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | get_bbox_by_radius | get_bbox_by_radius | 46 | 81 | 46 | 48 | 25e06799dd3584cff1907917b7457c940b0da1e6 | bigcode/the-stack | train |
511f48434d3b209eae338033 | train | function | def _filter_data(move_data: DataFrame, f: callable, kwargs: Dict):
"""
Filter the dataframe using condition from given function.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
f : function
Filtering function
**kwargs : arguments
- arg1 : featur... | def _filter_data(move_data: DataFrame, f: callable, kwargs: Dict):
| """
Filter the dataframe using condition from given function.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
f : function
Filtering function
**kwargs : arguments
- arg1 : feature
- arg2 : value
- outliers : special behavior if c... | ['arg1']].shift(1)) > kwargs['arg2'])
| (np.nan_to_num(move_data[kwargs['arg1']]) > kwargs['arg2'])
)
return move_data[filter_]
def _filter_data(move_data: DataFrame, f: callable, kwargs: Dict):
| 65 | 65 | 218 | 18 | 46 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | _filter_data | _filter_data | 448 | 486 | 448 | 448 | a0039111aa89feb101d22a3c6d8e9548b23404a3 | bigcode/the-stack | train |
9ca771f41fbc929d99af0649 | train | function | def _filter_single_by_max(move_data: DataFrame, **kwargs):
"""
Filters from a dataframe rows with features below value.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
**kwargs : arguments
- arg1 : feature
- arg2 : value
Returns
-------
... | def _filter_single_by_max(move_data: DataFrame, **kwargs):
| """
Filters from a dataframe rows with features below value.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
**kwargs : arguments
- arg1 : feature
- arg2 : value
Returns
-------
DataFrame
Filtered dataframe.
"""
return ... | 1)
else:
filter_ = (move_data[subset].shift(n) != move_data[subset]).any(axis=1)
return move_data.drop(index=move_data[~filter_].index, inplace=inplace)
def _filter_single_by_max(move_data: DataFrame, **kwargs):
| 64 | 64 | 101 | 15 | 49 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | _filter_single_by_max | _filter_single_by_max | 402 | 420 | 402 | 402 | 741a54d30af892eb4939a93dce0315b6319d3e67 | bigcode/the-stack | train |
1a949754466a35faac3e1fa3 | train | function | def outliers(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
jump_coefficient: Optional[float] = 3.0,
threshold: Optional[float] = 1,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']]:
"""
Filt... | def outliers(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
jump_coefficient: Optional[float] = 3.0,
threshold: Optional[float] = 1,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']]:
| """
Filters trajectories points that are outliers.
Parameters
----------
move_data : dataframe
The input trajectory data
jump_coefficient : float, optional
by default 3
threshold : float, optional
Minimum value that the distance features must have
in order to... | be altered to contain
the result of the filtering, otherwise a copy will be returned, by default False
Returns
-------
DataFrame
Returns a dataframe with trajectories points filtered or None
"""
return by_label(move_data, tid_, TID, filter_out, inplace)
def outliers(
move_data... | 152 | 152 | 509 | 90 | 62 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | outliers | outliers | 288 | 351 | 288 | 294 | 56394f2d1547f641447fbeefe596eae11feb9158 | bigcode/the-stack | train |
775efa0e761bd9cb815af14d | train | function | def by_label(
move_data: DataFrame,
value: Any,
label_name: Text,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
"""
Filters trajectories points according to specified value and column label.
Parameters
----------
move_data : datafr... | def by_label(
move_data: DataFrame,
value: Any,
label_name: Text,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| """
Filters trajectories points according to specified value and column label.
Parameters
----------
move_data : dataframe
The input trajectory data
value : The value to be use to filter the trajectories
Specifies the value used to filter the trajectories points
label_name :... | start_datetime
if filter_out:
filter_ = ~filter_
return move_data.drop(index=move_data[~filter_].index, inplace=inplace)
def by_label(
move_data: DataFrame,
value: Any,
label_name: Text,
filter_out: Optional[bool] = False,
inplace: Optional[bool] = False
) -> Optional[DataFrame]:
| 85 | 85 | 284 | 50 | 35 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | by_label | by_label | 174 | 211 | 174 | 180 | 3c26a096e4e38967e96b4ee035417991e932e774 | bigcode/the-stack | train |
df2b8d7983f3c1c153fe10a4 | train | function | def clean_trajectories_with_few_points(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_tid: Optional[Text] = TID,
min_points_per_trajectory: Optional[int] = 2,
inplace: Optional[bool] = False
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']]:
"""
Removes from ... | def clean_trajectories_with_few_points(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_tid: Optional[Text] = TID,
min_points_per_trajectory: Optional[int] = 2,
inplace: Optional[bool] = False
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']]:
| """
Removes from the given dataframe, trajectories with fewer points.
Parameters
----------
move_data : dataframe
The input trajectory data
label_tid : str, optional
The label of the column which contains the tid of the trajectories, by default TID
min_points_per_trajectory:... | (
label_id=label_id, label_dtype=label_dtype
)
logger.debug(
'\nClean gps points with speed max > %s meters by seconds'
% speed_max
)
move_df = _clean_gps(
move_df,
_filter_speed_max_radius,
arg1=SPEED_TO_PREV,
arg2=speed_max,
out... | 182 | 182 | 608 | 86 | 95 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_trajectories_with_few_points | clean_trajectories_with_few_points | 776 | 852 | 776 | 781 | 2a0812ba61062dc579d84ea5c942cda9c241635a | bigcode/the-stack | train |
a0cc1b9219cbe4471a86a8a1 | train | function | def clean_id_by_time_max(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
time_max: Optional[float] = 3600,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']... | def clean_id_by_time_max(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
time_max: Optional[float] = 3600,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveDataFrame']... | """
Clears GPS points with time by ID greater than a user-defined limit.
Parameters
----------
move_data: dataframe.
The input data.
label_id: str, optional
The label of the column which contains the id of the trajectories,
by default TRAJ_ID
time_max: float, optiona... | ids_before_drop, move_df[label_id].unique().shape[0])
)
move_df.drop(index=idx, inplace=True)
logger.debug(
'\n...Shape - before drop: %s - after drop: %s'
% (shape_before_drop, move_df.shape)
)
if not inplace:
return move_df
def clean_id_by_time_max(... | 168 | 168 | 562 | 95 | 72 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_id_by_time_max | clean_id_by_time_max | 945 | 1,014 | 945 | 951 | 0e68749b01203de2947954aa85ca4c98c31484e9 | bigcode/the-stack | train |
67e1fe99f544c809cd3ce531 | train | function | def _clean_gps(move_data: DataFrame, f: callable, **kwargs):
"""
Cleans gps points from a dataframe using condition from given function.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
f : function
Filtering function
**kwargs : arguments
- arg1 ... | def _clean_gps(move_data: DataFrame, f: callable, **kwargs):
| """
Cleans gps points from a dataframe using condition from given function.
Parameters
----------
move_data : dataframe
Dataframe to be filtered.
f : function
Filtering function
**kwargs : arguments
- arg1 : feature
- arg2 : value
- outliers : special... | threshold=kwargs['arg2'],
inplace=False
)
else:
filter_data_points = f(
move_data,
arg1=kwargs['arg1'],
arg2=kwargs['arg2'],
inplace=False
)
rows_to_drop = filter_data_points.shape[0]
return filter_data_points, r... | 92 | 92 | 307 | 18 | 73 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | _clean_gps | _clean_gps | 489 | 531 | 489 | 489 | bcf2436ec5e780ee940712806317ed2155b5bbac | bigcode/the-stack | train |
4755023a5b290d824acd4956 | train | function | def clean_gps_nearby_points_by_distances(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
radius_area: Optional[float] = 10.0,
label_dtype: Optional[callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', '... | def clean_gps_nearby_points_by_distances(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
radius_area: Optional[float] = 10.0,
label_dtype: Optional[callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', '... | """
Removes points from the trajectories with smaller distance from the point before.
Parameters
----------
move_data : dataframe
The input trajectory data
label_id : str, optional
Indicates the label of the id column in the user dataframe, by default TRAJ_ID
radius_area : ... | ,
arg2=threshold,
outliers=True
)
if not inplace:
return move_df
def clean_gps_nearby_points_by_distances(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
radius_area: Optional[float] = 10.0,
label_dtype: Optional[callable... | 126 | 126 | 423 | 102 | 23 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_gps_nearby_points_by_distances | clean_gps_nearby_points_by_distances | 595 | 650 | 595 | 601 | ef3e96e2e7c7aef819248765bf7bbd2731f11e08 | bigcode/the-stack | train |
df745ec25572a4807bd3dc87 | train | function | def clean_gps_speed_max_radius(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
speed_max: Optional[float] = 50.0,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveData... | def clean_gps_speed_max_radius(
move_data: Union['PandasMoveDataFrame', 'DaskMoveDataFrame'],
label_id: Optional[Text] = TRAJ_ID,
speed_max: Optional[float] = 50.0,
label_dtype: Optional[Callable] = np.float64,
inplace: Optional[bool] = False,
) -> Optional[Union['PandasMoveDataFrame', 'DaskMoveData... | """
Removes trajectories points with higher speed.
Given any point p of the trajectory, the point will
be removed if one of the following happens: if the travel speed from the
point before p to p is greater than the max value of speed between adjacent
points set by the user. Or the travel spee... | \n'
% speed_radius
)
move_df = _clean_gps(
move_df,
_filter_single_by_max,
arg1=SPEED_TO_PREV,
arg2=speed_radius,
outliers=False
)
if not inplace:
return move_df
def clean_gps_speed_max_radius(
move_data: Union['PandasMoveDataFrame', 'DaskMove... | 159 | 159 | 533 | 97 | 61 | safarzadeh-reza/PyMove | pymove/preprocessing/filters.py | Python | clean_gps_speed_max_radius | clean_gps_speed_max_radius | 710 | 773 | 710 | 716 | 9001c52f92d35359508d3d823f75bf0206a38e83 | bigcode/the-stack | train |
25d814485012b10f0350e62e | train | class | class Book:
def __init__(self,
readme_fpath='README.md',
outpath='content',
toc_path='_toc.md',
):
self.outpath = outpath
self.parser = ReadmeParser(fpath=readme_fpath)
def generate_stubs(self):
self.stubs = []
... | class Book:
| def __init__(self,
readme_fpath='README.md',
outpath='content',
toc_path='_toc.md',
):
self.outpath = outpath
self.parser = ReadmeParser(fpath=readme_fpath)
def generate_stubs(self):
self.stubs = []
for topic in... | bibtex entries, that would be a better
# data structure to parse for this. Oh well. Later. Bibtex + jinja. Noted.
from loguru import logger
from collections import defaultdict
from unidecode import unidecode
import string
from pathlib import Path
class Book:
| 64 | 64 | 176 | 3 | 60 | dmarx/anthology-of-modern-ml | readme2book.py | Python | Book | Book | 23 | 46 | 23 | 23 | c80b2a115271f46b7af0adf9a7416dee925e766e | bigcode/the-stack | train |
2285f1174564c29ce3596c30 | train | class | class Stub:
_header = """---
jupytext:
formats: md:myst
text_representation:
extension: .md
format_name: myst
kernelspec:
display_name: Python 3
language: python
name: python3
---"""
_pdf_embed_template = """```{{code-cell}} ipython3
:tags: [hide-input]
import panel as pn
pn.extension()
pdf_... | class Stub:
| _header = """---
jupytext:
formats: md:myst
text_representation:
extension: .md
format_name: myst
kernelspec:
display_name: Python 3
language: python
name: python3
---"""
_pdf_embed_template = """```{{code-cell}} ipython3
:tags: [hide-input]
import panel as pn
pn.extension()
pdf_pane = pn.pa... | headings' not in topic:
continue
for subtopic, entries in topic['subheadings'].items():
for entry in entries:
stub = Stub(entry, depth=3)
self.stubs.append(stub)
# write stub to disk
stub.write(se... | 96 | 96 | 320 | 3 | 92 | dmarx/anthology-of-modern-ml | readme2book.py | Python | Stub | Stub | 50 | 94 | 50 | 50 | 6ff3fe8687c5d945a762979c8a5297d338215020 | bigcode/the-stack | train |
f3caf5ea77c9532edcfb932d | train | class | class ReadmeParser:
def __init__(self, fpath='README.md'):
self.fpath = fpath
self.read()
self.entries = self.parse()
def read(self):
with open(self.fpath, 'rb') as f:
text = f.read()
self.text = text.decode("utf-8")
def parse(self):
... | class ReadmeParser:
| def __init__(self, fpath='README.md'):
self.fpath = fpath
self.read()
self.entries = self.parse()
def read(self):
with open(self.fpath, 'rb') as f:
text = f.read()
self.text = text.decode("utf-8")
def parse(self):
self.errors = []... | code-cell}} ipython3
:tags: [hide-input]
import panel as pn
pn.extension()
pdf_pane = pn.pane.PDF('{pdf_url}', width=700, height=1000)
pdf_pane
```"""
def __init__(self, item, depth=1):
self.item = item
self.depth=depth
@property
def title(self):
h = '#'*self.depth
return f... | 254 | 256 | 980 | 5 | 249 | dmarx/anthology-of-modern-ml | readme2book.py | Python | ReadmeParser | ReadmeParser | 98 | 228 | 98 | 98 | 7340cc5ae0375077926c9d4d738b622dad2037e1 | bigcode/the-stack | train |
bb80943e3037117de4da0d5c | train | class | class PolyNondom:
"""Enumerates and visualises different sets of (non-dominated) points.
.. glossary::
non-dominated point
A point *y* is non-dominated (in the point set P) if there is no other
point *z* in P such that *z_i <= y_i* for all i with at least one
strict inequali... | class PolyNondom:
| """Enumerates and visualises different sets of (non-dominated) points.
.. glossary::
non-dominated point
A point *y* is non-dominated (in the point set P) if there is no other
point *z* in P such that *z_i <= y_i* for all i with at least one
strict inequality.
domin... | param tuple item: Point belonging to point set
"""
self.points.add(item)
def update(self, items):
"""Add items to points.
:param iterable items: Points belonging to point set
"""
self.points.update(items)
def add_visualised_items(self, items):
"""Add it... | 256 | 256 | 4,471 | 6 | 249 | asbestian/polynondom | polynondom.py | Python | PolyNondom | PolyNondom | 293 | 747 | 293 | 293 | 0cce8a1774ed4f8200719ce853febb6217efff8a | bigcode/the-stack | train |
7a871897530901166c4fc3f3 | train | class | class AssignmentDomain(GenericDomain):
"""Feasible domain of an assignment problem.
The assignment problem has a number of agents and a(n equal) number
of tasks. Any agent can be assigned to perform any task. A feasible
solution is given by an assignment of agents to tasks in such a way
that... | class AssignmentDomain(GenericDomain):
| """Feasible domain of an assignment problem.
The assignment problem has a number of agents and a(n equal) number
of tasks. Any agent can be assigned to perform any task. A feasible
solution is given by an assignment of agents to tasks in such a way
that each agent is one task and all tasks a... | self.dim = dim
def __iter__(self):
"""Iterator for generic domain."""
raise NotImplementedError
def __str__(self):
"""String representation of domain."""
return self.__class__.__name__ + str(set([elem for elem in self]))
class AssignmentDomain(GenericDomain):
| 63 | 64 | 214 | 6 | 57 | asbestian/polynondom | polynondom.py | Python | AssignmentDomain | AssignmentDomain | 70 | 95 | 70 | 70 | 3ef0cde6a3c4a322571b7fa062323bfc63a4d1db | bigcode/the-stack | train |
7c9b80a4c77274be7700d89f | train | class | class ExplicitDomain(GenericDomain):
"""Explicitely given feasible domain.
:ivar Iterable domain: Feasible domain
:Example: ed = ExplicitDomain(3, some_iterable)
"""
def __init__(self, dim, domain):
"""Initialises feasible domain via given domain."""
super().__init__(dim)
... | class ExplicitDomain(GenericDomain):
| """Explicitely given feasible domain.
:ivar Iterable domain: Feasible domain
:Example: ed = ExplicitDomain(3, some_iterable)
"""
def __init__(self, dim, domain):
"""Initialises feasible domain via given domain."""
super().__init__(dim)
assert isinstance(self.domain... | def __init__(self, dim):
"""Initialises feasible domain given by standard cube."""
super().__init__(dim)
def __iter__(self):
"""Iterator for cube domain."""
for prod in product(range(2), repeat=self.dim):
yield prod
class ExplicitDomain(GenericDomain):
| 64 | 64 | 116 | 6 | 57 | asbestian/polynondom | polynondom.py | Python | ExplicitDomain | ExplicitDomain | 114 | 132 | 114 | 114 | 6992b37e520635b0cbb4fb5113042e610663e364 | bigcode/the-stack | train |
57cb10207c39c5c1b5323b8f | train | class | class Points:
"""Represents certain set of points in objective space.
:ivar str _id: Identifier for points
:ivar str _color: Color used for visualisation of points
:ivar list _visualised_items: Container for visualised items
:ivar set points: Container for points
"""
def __init__(self, ide... | class Points:
| """Represents certain set of points in objective space.
:ivar str _id: Identifier for points
:ivar str _color: Color used for visualisation of points
:ivar list _visualised_items: Container for visualised items
:ivar set points: Container for points
"""
def __init__(self, identifier, color... | for line in file:
bracket_open = line.find("[")
bracket_close = line.find("]")
if bracket_open == -1 or bracket_close == -1:
continue
else:
substring = line[bracket_open+1:brac... | 135 | 135 | 451 | 3 | 131 | asbestian/polynondom | polynondom.py | Python | Points | Points | 215 | 291 | 215 | 215 | a45b7a44119378a8ffab66f834ca6321d5c56f3b | bigcode/the-stack | train |
663205ed942ac418eb8699e7 | train | class | class Error(Exception):
"""Base class for exceptions."""
| class Error(Exception):
| """Base class for exceptions."""
| ArgumentParser
from collections import Iterable
from itertools import combinations, permutations, product, zip_longest
import logging
import math
from numpy import array, dot, linspace, meshgrid
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d
class Error(Exception):
| 64 | 64 | 11 | 4 | 59 | asbestian/polynondom | polynondom.py | Python | Error | Error | 40 | 41 | 40 | 40 | 3be9f5161f6c49104c86bf17e33b4291a93be7cd | bigcode/the-stack | train |
25dd50faa178c73ab1fea7f9 | train | class | class InfeasibleBoxError(Error):
"""Rectangular box is infeasible."""
| class InfeasibleBoxError(Error):
| """Rectangular box is infeasible."""
| product, zip_longest
import logging
import math
from numpy import array, dot, linspace, meshgrid
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d
class Error(Exception):
"""Base class for exceptions."""
class InfeasibleBoxError(Error):
| 64 | 64 | 17 | 8 | 56 | asbestian/polynondom | polynondom.py | Python | InfeasibleBoxError | InfeasibleBoxError | 43 | 44 | 43 | 43 | 1ed425f0b7052022f73cc82c5af53744d8dc5173 | bigcode/the-stack | train |
d1a6f33a00491c1377f1501a | train | class | class CubeDomain(GenericDomain):
"""Feasible domain given by the vertices of an n-dimensional standard cube.
:Example: cd = CubeDomain(3)
"""
def __init__(self, dim):
"""Initialises feasible domain given by standard cube."""
super().__init__(dim)
def __iter__(self):
""... | class CubeDomain(GenericDomain):
| """Feasible domain given by the vertices of an n-dimensional standard cube.
:Example: cd = CubeDomain(3)
"""
def __init__(self, dim):
"""Initialises feasible domain given by standard cube."""
super().__init__(dim)
def __iter__(self):
"""Iterator for cube domain."""
... | Iterator for assignment domain."""
for perm in permutations(list(range(self.num_agents))):
feas_sol = [0]*self.dim
for i, val in enumerate(perm):
feas_sol[i*self.num_agents + val] = 1
yield tuple(feas_sol)
class CubeDomain(GenericDomain):
| 64 | 64 | 94 | 6 | 58 | asbestian/polynondom | polynondom.py | Python | CubeDomain | CubeDomain | 98 | 111 | 98 | 98 | cc4c4ed6a687a5fa8d262d053f718a87d637f95c | bigcode/the-stack | train |
5754fe39b9b5fcb6004e1e56 | train | function | def get_cmd_line_parser():
"""Command line interface."""
parser = ArgumentParser(description='Enumerates and visualises different \
sets of non-dominated points')
parent_parser = ArgumentParser(add_help=False)
parent_parser.add_argument('-f', '--file', metavar="i... | def get_cmd_line_parser():
| """Command line interface."""
parser = ArgumentParser(description='Enumerates and visualises different \
sets of non-dominated points')
parent_parser = ArgumentParser(add_help=False)
parent_parser.add_argument('-f', '--file', metavar="input_file", type=str,
... | , 3)
x_z = meshgrid(x, z, sparse=True)
y_z = meshgrid(y, z, sparse=True)
for i in interval1:
self._ax.plot_surface(i, *y_z, facecolors=my_face_color, alpha=my_alpha)
for i in interval2:
self._ax.plot_surface(x_z[0], ... | 153 | 153 | 511 | 6 | 147 | asbestian/polynondom | polynondom.py | Python | get_cmd_line_parser | get_cmd_line_parser | 750 | 787 | 750 | 750 | 2dcad0f069bada5e9f94e7850ed588931eadfc58 | bigcode/the-stack | train |
ab03a60830203ee110fc5bb3 | train | class | class Objectives:
"""Represents the objectives of a multi-criteria optimisation problem.
:ivar list objectives: Objective functions
"""
def __init__(self):
"""Initialise with no objectives."""
self._objectives = []
def length(self):
if self._objectives:
for... | class Objectives:
| """Represents the objectives of a multi-criteria optimisation problem.
:ivar list objectives: Objective functions
"""
def __init__(self):
"""Initialise with no objectives."""
self._objectives = []
def length(self):
if self._objectives:
for i, j in combinati... | )
"""
def __init__(self, dim):
"""Initialises feasible domain given by standard cube."""
super().__init__(dim)
def __iter__(self):
"""Iterator for cube domain."""
for prod in product(range(2), repeat=self.dim):
yield prod
class ExplicitDomain(GenericDomain):
... | 180 | 180 | 603 | 3 | 176 | asbestian/polynondom | polynondom.py | Python | Objectives | Objectives | 135 | 213 | 135 | 135 | 7a8328e8af516ee0e5570c15e9583b6a0e23d4d6 | bigcode/the-stack | train |
e4cfecc9ffc688b90c60f388 | train | class | class GenericDomain:
"""Feasible domain of a generic optimisation problem.
:ivar int dim: Dimension of feasible domain
.. note:: Do not use this class directly.
"""
def __init__(self, dim):
"""Initialises generic domain.
:param: int dim: Dimension of feasible dom... | class GenericDomain:
| """Feasible domain of a generic optimisation problem.
:ivar int dim: Dimension of feasible domain
.. note:: Do not use this class directly.
"""
def __init__(self, dim):
"""Initialises generic domain.
:param: int dim: Dimension of feasible domain
"""
... | numpy import array, dot, linspace, meshgrid
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import axes3d
class Error(Exception):
"""Base class for exceptions."""
class InfeasibleBoxError(Error):
"""Rectangular box is infeasible."""
class GenericDomain:
| 64 | 64 | 129 | 4 | 60 | asbestian/polynondom | polynondom.py | Python | GenericDomain | GenericDomain | 46 | 67 | 46 | 46 | 186bd440762e4e700ee5c4ec8d49ce96d730f6e3 | bigcode/the-stack | train |
2134e6ac5a303e1891bcef4d | train | class | class TextSystem(object):
def __init__(self, args):
self.text_detector = predict_det.TextDetector(args)
self.text_recognizer = predict_rec.TextRecognizer(args)
self.use_angle_cls = args.use_angle_cls
self.drop_score = args.drop_score
if self.use_angle_cls:
self.te... | class TextSystem(object):
| def __init__(self, args):
self.text_detector = predict_det.TextDetector(args)
self.text_recognizer = predict_rec.TextRecognizer(args)
self.use_angle_cls = args.use_angle_cls
self.drop_score = args.drop_score
if self.use_angle_cls:
self.text_classifier = predict_cl... | # 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 pe... | 235 | 235 | 784 | 5 | 230 | jiashanyao/PaddleOCR | tools/infer/predict_system.py | Python | TextSystem | TextSystem | 39 | 118 | 39 | 39 | c3236d671a88dbec6ce9c20cf08b43c768ba763f | bigcode/the-stack | train |
2500a4513547cc9472cd8632 | train | function | def main(args):
image_file_list = get_image_file_list(args.image_dir)
text_sys = TextSystem(args)
is_visualize = True
font_path = args.vis_font_path
drop_score = args.drop_score
for image_file in image_file_list:
img, flag = check_and_read_gif(image_file)
if not flag:
... | def main(args):
| image_file_list = get_image_file_list(args.image_dir)
text_sys = TextSystem(args)
is_visualize = True
font_path = args.vis_font_path
drop_score = args.drop_score
for image_file in image_file_list:
img, flag = check_and_read_gif(image_file)
if not flag:
img = cv2.imrea... | ][0]))
_boxes = list(sorted_boxes)
for i in range(num_boxes - 1):
if abs(_boxes[i + 1][0][1] - _boxes[i][0][1]) < 10 and \
(_boxes[i + 1][0][0] < _boxes[i][0][0]):
tmp = _boxes[i]
_boxes[i] = _boxes[i + 1]
_boxes[i + 1] = tmp
return _boxes
def mai... | 111 | 111 | 370 | 4 | 106 | jiashanyao/PaddleOCR | tools/infer/predict_system.py | Python | main | main | 142 | 183 | 142 | 142 | 902283d76006fc88e3c2208835b0adc4cc97a0b5 | bigcode/the-stack | train |
6e9736857c40c18b64840d5f | train | function | def sorted_boxes(dt_boxes):
"""
Sort text boxes in order from top to bottom, left to right
args:
dt_boxes(array):detected text boxes with shape [4, 2]
return:
sorted boxes(array) with shape [4, 2]
"""
num_boxes = dt_boxes.shape[0]
sorted_boxes = sorted(dt_boxes, key=lambda x:... | def sorted_boxes(dt_boxes):
| """
Sort text boxes in order from top to bottom, left to right
args:
dt_boxes(array):detected text boxes with shape [4, 2]
return:
sorted boxes(array) with shape [4, 2]
"""
num_boxes = dt_boxes.shape[0]
sorted_boxes = sorted(dt_boxes, key=lambda x: (x[0][1], x[0][0]))
_bo... | for box, rec_reuslt in zip(dt_boxes, rec_res):
text, score = rec_reuslt
if score >= self.drop_score:
filter_boxes.append(box)
filter_rec_res.append(rec_reuslt)
return filter_boxes, filter_rec_res
def sorted_boxes(dt_boxes):
| 64 | 64 | 200 | 6 | 57 | jiashanyao/PaddleOCR | tools/infer/predict_system.py | Python | sorted_boxes | sorted_boxes | 121 | 139 | 121 | 121 | 98f0446b45c993e3a921859c3b200461264fbc3a | bigcode/the-stack | train |
a13f09aa9ff2af03eca59c58 | train | function | @routes.route('/', strict_slashes=True)
def home():
return render_template('home.html')
| @routes.route('/', strict_slashes=True)
def home():
| return render_template('home.html')
| request, Response, render_template
from model.roads import Roads
from pyldapi import ContainerRenderer
import conf
import ast
import folium
print(__name__)
routes = Blueprint('controller', __name__)
DEFAULT_ITEMS_PER_PAGE=50
@routes.route('/', strict_slashes=True)
def home():
| 64 | 64 | 20 | 12 | 51 | GeoscienceAustralia/FSDF-Roads | API/controller/routes.py | Python | home | home | 12 | 14 | 12 | 13 | 55ac5ff05a86653ab20a1ea4ad45d465e2a631b9 | bigcode/the-stack | train |
0345f7ec0cc2415f736f772f | train | function | @routes.route('/rds/<string:roads_id>')
def road(roads_id):
roads = Roads(request, request.base_url)
return roads.render()
| @routes.route('/rds/<string:roads_id>')
def road(roads_id):
| roads = Roads(request, request.base_url)
return roads.render()
| folium.PolyLine(points, color="red", weight=2.5, opacity=1, popup = name, tooltip=tooltip).add_to(folium_map)
return folium_map.get_root().render()
@routes.route('/rds/<string:roads_id>')
def road(roads_id):
| 64 | 64 | 33 | 18 | 46 | GeoscienceAustralia/FSDF-Roads | API/controller/routes.py | Python | road | road | 99 | 102 | 99 | 100 | 118738938d7471777713cf55203aae1f3b47b719 | bigcode/the-stack | train |
2cbf9d579100457fc6ce742c | train | function | @routes.route('/rds/')
def roads():
# Search specific items using keywords
search_string = request.values.get('search')
try:
# get the register length from the online DB
sql = 'SELECT COUNT(*) FROM "transportroads"'
if search_string:
sql += '''WHERE UPPER(cast("id" as t... | @routes.route('/rds/')
def roads():
# Search specific items using keywords
| search_string = request.values.get('search')
try:
# get the register length from the online DB
sql = 'SELECT COUNT(*) FROM "transportroads"'
if search_string:
sql += '''WHERE UPPER(cast("id" as text)) LIKE '%{search_string}%' OR UPPER("name") LIKE '%{search_string}%';
... | from flask import Blueprint, request, Response, render_template
from model.roads import Roads
from pyldapi import ContainerRenderer
import conf
import ast
import folium
print(__name__)
routes = Blueprint('controller', __name__)
DEFAULT_ITEMS_PER_PAGE=50
@routes.route('/', strict_slashes=True)
def home():
return r... | 95 | 143 | 478 | 18 | 77 | GeoscienceAustralia/FSDF-Roads | API/controller/routes.py | Python | roads | roads | 17 | 70 | 17 | 19 | ab2461d0d210ad2fa6086dccba464d62e808a57e | bigcode/the-stack | train |
0ca09ac1032656920551d8a7 | train | function | @routes.route('/map')
def show_map():
'''
Function to render a map around the specified line
'''
name = request.values.get('name')
coords_list = ast.literal_eval(request.values.get('coords'))[0]
# swap x & y for mapping
points = []
for coords in coords_list:
points.append(tuple... | @routes.route('/map')
def show_map():
| '''
Function to render a map around the specified line
'''
name = request.values.get('name')
coords_list = ast.literal_eval(request.values.get('coords'))[0]
# swap x & y for mapping
points = []
for coords in coords_list:
points.append(tuple([coords[1], coords[0]]))
ave_lat... | _of_items,
profiles=None,
default_profile_token=None,
super_register=None,
page_size_max=1000,
register_template=None,
per_page=per_page,
... | 64 | 64 | 205 | 10 | 54 | GeoscienceAustralia/FSDF-Roads | API/controller/routes.py | Python | show_map | show_map | 73 | 96 | 73 | 74 | 0d2e538be6a99844342462aac49549387fd7f59c | bigcode/the-stack | train |
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