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# Copyright 2019 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from pants.backend.python.lint import python_format_target, python_lint_target
from pants.backend.python.lint.black import rules as black_rules
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# -*- coding: utf-8 -*-
"""
Created on Sat Aug 01 11:56:10 2015
@author: Zombie.Soc//similarities
"""
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
print ("Reconstruction of Thomson spectrometer parabolas - to check parameters")
#Parameters
# !!! 0 point coordinates in px
x0 = 825
y0 = 305
B = 0.21 #magnetic field strength in Tesla
D = 0.670 # Drift of spectrometer
q = 1.6027E-19 # elemental charge q
l = 0.05 # lenght of magnet in m
Abbildung = 0.00004521 # magnification factor m/pix
mp = 1.673E-27 # mass proton
E1 = 3.985E3 # Potential of Efield in applied Voltage
Le = 0.0098 # distance of field plates in m
EF = E1/Le
v0 = 1E7 #v0 in m/s
print("charge to mass ratio?")
ZA= input("Z/A:" ) # charge to mass number of ion
# 0.355 +/- 0.002 trace1 between C4+ und O5+
# 0.344 +/- 0.002 trace2 between C4+ und O5+
# 0.466 +/- 0.005 trace between C6+ und O7+
#0.428 +/- 0. trace after O7+
#0.405 +/-0.002 trace after C+5
#0.32 +/- 0.005 trace after C4+
#0.28 +/-0.005 trace after O5+
#now plot:
img = mpimg.imread('20140131_012ions.jpg')
imshow(img)
lum_img = img[:, :]
imgplot = plt.imshow(lum_img)
# spectral, hot, cool, ... tip was falsches ein.. dann kommen vorschläge :)
imgplot.set_cmap('binary_r')
plt.plot(xp(x0),parabely(x0,ZA),"r")
# plot - loop for elements (carbon C12, CC, O16, 015, N14, N15...)
C12 = 1.0/12.0107
C24 = 0.5/12.0107
O16 = 1.0/15.9949
O15 = 1.0/15.0031
N14 = 1.0/14.0067
N15 = 1.0/15.00011
C13 = 1.0/13.03355
C17 = 1.0/16.0226
C14 = 1.0/14.0334
C15 = 1.0/15.0106
F19 = 1.0/18.9984
#CH=1.0/(1.007276*2+12.0107)
for i in range(2,6+1):
#plt.plot(xp(x0), parabely(x0,C17*(i)),"y")
#plt.plot(xp(x0), parabely(x0,O15*(i+1)),"y")
#plt.plot(xp(x0), parabely(x0,C13*(i)),"g")
#plt.plot(xp(x0), parabely(x0,C15*(i)),"r")
#plt.plot(xp(x0), parabely(x0,C24*(i+6)),"y")
#plt.plot(xp(x0), parabely(x0,C12*(i)),"w")
plt.plot(xp(x0), parabely(x0,C12*(i)),"y")
#plt.plot(xp(x0), parabely(x0,C12*(i)+0.0015),"y--")
plt.plot(xp(x0), parabely(x0,O16*(i+1)),"b")
# plt.plot(xp(x0), parabely(x0,O16*(i+1)+0.0015),"b--")
#plt.plot(xp(x0), parabely(x0,N14*(i)),"g")
#print parabely(x0,i)
#plt.ylabel('C+',"i")0
plt.axis([0, 1032, 200, 756])
#plt.legend("+")
plt.show()
###
raw_input('press Return>')
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] | 1.858093 | 1,353 |
from selenium import webdriver
import sys
from os.path import join, abspath, dirname
import logging
from selenium.webdriver.remote.remote_connection import LOGGER as ghostdriver_logger
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from locators import homePage
from selenium.webdriver.support import expected_conditions
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from datetime import datetime
from time import sleep
logging.basicConfig(filename="python.log", level=logging.DEBUG)
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import io
import json
import math
import os
import numpy as np
from PIL import Image
from PIL import ImageFile
import tensorflow.compat.v2 as tf
from absl import logging
from absl import app
from absl import flags
import cv2
flags.DEFINE_string('acivity', 'swing', 'The class of test images.')
flags.DEFINE_string('input_dir', '/media/felicia/Data/mlb-youtube/%s_videos/rm_noise/videos', 'Path to videos.')
flags.DEFINE_string('name', 'image_bbgame_swing', 'Name of the dataset being created. This will'
'be used as a prefix.')
flags.DEFINE_string('file_pattern', '*.mp4', 'Pattern used to searh for files'
'in the given directory.')
flags.DEFINE_string('label_file', None, 'Provide a corresponding labels file'
'that stores per-frame or per-sequence labels. This info'
'will get stored.')
flags.DEFINE_string('output_dir', '/media/felicia/Data/object_detection/data/%s/', 'Output directory where'
'tfrecords will be stored.')
flags.DEFINE_integer('files_per_shard', 50, 'Number of videos to store in a'
'shard.')
flags.DEFINE_boolean('rotate', False, 'Rotate videos by 90 degrees before'
'creating tfrecords')
flags.DEFINE_boolean('resize', True, 'Resize videos to a given size.')
flags.DEFINE_integer('width', 1280, 'Width of frames in the TFRecord.')
flags.DEFINE_integer('height', 720, 'Height of frames in the TFRecord.')
flags.DEFINE_list(
'frame_labels', '', 'Comma separated list of descriptions '
'for labels given on a per frame basis. For example: '
'winding_up,early_cocking,acclerating,follow_through')
flags.DEFINE_integer('action_label',0 , 'Action label of all videos.') # swing:0, ball:1, strike:2, foul:3, hit:4
flags.DEFINE_integer('expected_segments', -1, 'Expected number of segments.')
flags.DEFINE_integer('fps', 10, 'Frames per second of video. If 0, fps will be '
'read from metadata of video.') # Original:
FLAGS = flags.FLAGS
gfile = tf.io.gfile
def video_to_frames(video_filename, rotate, fps=0, resize=False,
width=224, height=224):
"""Returns all frames from a video.
Args:
video_filename: string, filename of video.
rotate: Boolean: if True, rotates video by 90 degrees.
fps: Integer, frames per second of video. If 0, it will be inferred from
metadata of video.
resize: Boolean, if True resizes images to given size.
width: Integer, Width of image.
height: Integer, Height of image.
Raises:
ValueError: if fps is greater than the rate of video.
"""
logging.info('Loading %s', video_filename)
cap = cv2.VideoCapture(video_filename)
if fps == 0:
fps = cap.get(cv2.CAP_PROP_FPS)
keep_frequency = 1
else:
if fps > cap.get(cv2.CAP_PROP_FPS):
raise ValueError('Cannot sample at a frequency higher than FPS of video')
keep_frequency = int(float(cap.get(cv2.CAP_PROP_FPS)) / fps)
frames = []
timestamps = []
counter = 0
if cap.isOpened():
while True:
success, frame_bgr = cap.read()
if not success:
break
if counter % keep_frequency == 0:
# Convert BGR to RGB
frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
if resize:
frame_rgb = cv2.resize(frame_rgb, (width, height))
if rotate:
frame_rgb = cv2.transpose(frame_rgb)
frame_rgb = cv2.flip(frame_rgb, 1)
frames.append(frame_rgb)
timestamps.append(cap.get(cv2.CAP_PROP_POS_MSEC) / 1000.0)
counter += 1
return frames, timestamps, fps
def create_numpy(name, output_dir, input_dir, label_file, input_pattern,
files_per_shard, action_label, frame_labels,
expected_segments, orig_fps, rotate, resize, width,
height):
"""Create Numpy file from videos in a given path.
Args:
name: string, name of the dataset being created.
output_dir: string, path to output directory.
input_dir: string, path to input videos directory.
label_file: None or string, JSON file that contains annotations.
input_pattern: string, regex pattern to look up videos in directory.
files_per_shard: int, number of files to keep in each shard.
action_label: int, Label of actions in video.
frame_labels: list, list of string describing each class. Class label is
the index in list.
expected_segments: int, expected number of segments.
orig_fps: int, frame rate at which tfrecord will be created.
rotate: boolean, if True rotate videos by 90 degrees.
resize: boolean, if True resize to given height and width.
width: int, Width of frames.
height: int, Height of frames.
Raises:
ValueError: If invalid args are passed.
"""
labels={
'swing':0,'ball':1
}
ACTIVITY=FLAGS.acivity
LABEL=labels[ACTIVITY]
input_dir=input_dir%ACTIVITY
output_path=output_dir%ACTIVITY
if not gfile.exists(output_path):
logging.info('Creating output directory: %s', output_path)
gfile.makedirs(output_path)
if not isinstance(input_pattern, list):
file_pattern = os.path.join(input_dir, input_pattern)
filenames = [os.path.basename(x) for x in gfile.glob(file_pattern)]
else:
filenames = []
for file_pattern in input_pattern:
file_pattern = os.path.join(input_dir, file_pattern)
filenames += [os.path.basename(x) for x in gfile.glob(file_pattern)]
num_shards = int(math.ceil(len(filenames)/files_per_shard))
len_num_shards = len(str(num_shards))
shard_id = 0
image_minibatch=list()
step_minibatch=list()
label_minibatch=list()
video_minibatch=list()
print('-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+')
print('shard_id',shard_id)
for i, filename in enumerate(filenames):
frames, video_timestamps, _ = video_to_frames(
os.path.join(input_dir, filename),
rotate,
orig_fps,
resize=resize,
width=width,
height=height)
vid_name=os.path.splitext(filename)[0]
vid_name=str.encode(vid_name)
image_minibatch.append(frames)
# duration=video_timestamps[1]
steps=np.array([x for x in range(len(video_timestamps))])
# print(i,filename,steps,video_timestamps)
step_minibatch.append(steps)
labels=[LABEL]*len(steps)
label_minibatch.append(labels)
vids=[vid_name]*len(steps)
video_minibatch+=vids
if (i + 1) % files_per_shard == 0 or i == len(filenames) - 1:
# if shard_id==2:
output_filename = os.path.join(
output_path,
'%s-%s-of-%s.npy' % (name,
str(shard_id).zfill(len_num_shards),
str(num_shards).zfill(len_num_shards)))
image_minibatch=np.concatenate(image_minibatch,axis=0)
step_minibatch=np.concatenate(step_minibatch,axis=0)
label_minibatch=np.concatenate(label_minibatch,axis=0)
numpy_dict={
'images':image_minibatch, # np.array: B*H*W*3
'activity':label_minibatch, # np.array: B*1
'steps':step_minibatch, # np.array:B*1
'videos':video_minibatch,# list
}
with open(output_filename,'wb') as file:
np.save(file,numpy_dict)
shard_id += 1
image_minibatch=list()
step_minibatch=list()
label_minibatch=list()
video_minibatch=list()
# print('-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+')
# print('shard_id',shard_id)
if __name__ == '__main__':
app.run(main) | [
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8
] | 2.445607 | 3,153 |
#!/usr/bin/python3
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.asymmetric import padding
import sys
import os
keysdir = "./keys"
pubdir = keysdir + "/public"
pvtdir = keysdir + "/private"
pubkey = pubdir + "/mypub.pem"
pvtkey = pvtdir + "/mypvt.pem"
srvkey = pubdir + "/srvpub.pem"
public_key = ""
private_key = ""
server_public_key = ""
if __name__ == "__main__":
main()
| [
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] | 2.848341 | 211 |
# Generated by Django 3.0.7 on 2020-06-15 22:15
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
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] | 3.019231 | 52 |
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from fairseq.dataclass import ChoiceEnum, FairseqDataclass
STEP_MODE_CHOICE = ChoiceEnum(['epoch', 'subepoch'])
@dataclass
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] | 3.014706 | 68 |
n = int(input('Digite um numero: '))
a = n * 2
b = n * 3
c = n ** (1/2)
print('O dobro do numero seria {} \n O triplo seria {} \n A raiz quadrada seria {:.2f}'.format(a, b, c))
| [
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] | 2.130952 | 84 |
# FAST拐点检测，拐点检测Opencv有七种，且比skimage的方法快的多
from skimage import data, feature, img_as_float, io
import numpy as np
image = img_as_float(io.imread('/home/qiao/PythonProjects/Scikit-image_On_CT/Test_Img/10.jpg'))
gamma_corrected = feature.corner_fast(image)
points = feature.corner_peaks(gamma_corrected)
print(points)
io.imshow(image)
io.show()
| [
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12860,
7,
9060,
8,
198,
952,
13,
12860,
3419,
628
] | 1.965517 | 174 |
import socket
from .Packet import Packet
from .PacketIpHeader import PacketIpv4Header, PacketIpv6Header
from hpimdm.tree.hpim_globals import MSG_FORMAT
from hpimdm.utils import TYPE_CHECKING
if TYPE_CHECKING:
from hpimdm.Interface import Interface
if MSG_FORMAT == "BINARY":
from .PacketHPIMHeader import PacketHPIMHeader, PacketHPIMHeader_v6
else:
from .PacketHPIMHeader import PacketHPIMHeaderJson as PacketHPIMHeader
from .PacketHPIMHeader import PacketHPIMHeaderJson as PacketHPIMHeader_v6
| [
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198
] | 2.824176 | 182 |
import time
import RPi.GPIO as GPIO #Python Package Reference: https://pypi.org/project/RPi.GPIO/
# Code taken from https://learn.sparkfun.com/tutorials/raspberry-pi-safe-reboot-and-shutdown-button using the last example to minimize resources used (sleep function)
# Pin definition
reset_shutdown_pin = 17
# Suppress warnings
GPIO.setwarnings(False)
# Use "GPIO" pin numbering
GPIO.setmode(GPIO.BCM)
# Use built-in internal pullup resistor so the pin is not floating
# if using a momentary push button without a resistor.
#GPIO.setup(reset_shutdown_pin, GPIO.IN, pull_up_down=GPIO.PUD_UP)
# Use Qwiic pHAT's pullup resistor so that the pin is not floating
GPIO.setup(reset_shutdown_pin, GPIO.IN)
# modular function to restart Pi
# modular function to shutdown Pi
while True:
#short delay, otherwise this code will take up a lot of the Pi's processing power
time.sleep(1)
# wait for a button press with switch debounce on the falling edge so that this script
# is not taking up too many resources in order to shutdown/reboot the Pi safely
channel = GPIO.wait_for_edge(reset_shutdown_pin, GPIO.FALLING, bouncetime=200)
if channel is None:
print('Timeout occurred')
else:
print('Edge detected on channel', channel)
# For troubleshooting, uncomment this line to output button status on command line
#print('GPIO state is = ', GPIO.input(reset_shutdown_pin))
counter = 0
while GPIO.input(reset_shutdown_pin) == False:
# For troubleshooting, uncomment this line to view the counter. If it reaches a value above 4, we will restart.
#print(counter)
counter += 1
time.sleep(0.5)
# long button press
if counter > 4:
shut_down()
#if short button press, restart!
restart()
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220,
220,
220,
220,
220,
220,
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4936,
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11,
15765,
0,
198,
220,
220,
220,
220,
220,
220,
220,
15765,
3419,
198
] | 2.799699 | 664 |
import time
import board
import adafruit_thermistor
# these values work with the Adafruit CircuitPlayground Express.
# they may work with other thermistors as well, as they're fairly standard,
# though the pin will likely need to change (ie board.A1)
# pylint: disable=no-member
pin = board.TEMPERATURE
resistor = 10000
resistance = 10000
nominal_temp = 25
b_coefficient = 3950
thermistor = adafruit_thermistor.Thermistor(pin, resistor, resistance, nominal_temp, b_coefficient)
# print the temperature in C and F to the serial console every second
while True:
celsius = thermistor.temperature
fahrenheit = (celsius * 9 / 5) + 32
print('== Temperature ==\n{} *C\n{} *F\n'.format(celsius, fahrenheit))
time.sleep(1)
| [
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8,
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201,
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220,
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640,
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] | 2.89272 | 261 |
from distutils.core import setup
setup(
name = 'jellylanguage',
version = '0.1.31',
packages = [
'jelly'
],
scripts = [
'scripts/jelly'
],
install_requires = [
'sympy'
]
)
| [
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] | 2.174419 | 86 |
from distutils.core import setup, Extension
if __name__ == "__main__":
main() | [
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from typing import Optional, Dict, List, Tuple
from bxcommon.messages.abstract_block_message import AbstractBlockMessage
from bxcommon.network.ip_endpoint import IpEndpoint
from bxcommon.utils.expiring_dict import ExpiringDict
from bxcommon.utils.object_hash import Sha256Hash
from bxgateway import log_messages
from bxgateway.connections.abstract_gateway_blockchain_connection import AbstractGatewayBlockchainConnection
from bxgateway.services.abstract_block_queuing_service import AbstractBlockQueuingService
from bxutils import logging
logger = logging.get_logger(__name__)
| [
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1136,
62,
6404,
1362,
7,
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3672,
834,
8,
628
] | 3.473054 | 167 |
#!/usr/bin/python
#-*- mode: python; coding: utf-8 -*-
#import simpleaudio as sa # This need wav files
# avconv -i audio/d/dog.mp3 -acodec pcm_u8 -ar 8000 audio/d/dog.wav
import time
import os
from gtts import gTTS
import pyglet
from subprocess import call
| [
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] | 2.584158 | 101 |
import sys
sys.path.insert(0, '../models')
from get_data import GetData
# from python.ultilities.get_data import GetData
import unittest
import csv
if __name__ == '__main__':
unittest.main() | [
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# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from django.test import TestCase
from django.contrib import admin
from physical.admin.engine_type import EngineTypeAdmin
from physical.models import EngineType
SEARCH_FIELDS = ('name', )
LIST_FILTER = ('is_in_memory', )
LIST_FIELDS = ('name', 'is_in_memory', 'created_at')
SAVE_ON_TOP = True
| [
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] | 2.984127 | 126 |
# dbitem.py
import re
# Auto detect and split labels/cmd
# Return a string suitable for substring searching
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from django.template.base import Variable, VariableDoesNotExist
from django.test import SimpleTestCase
| [
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] | 3.888889 | 27 |
# Import the agent class
from .devicemanager import DeviceManager
| [
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def originalDigits(self, s: str) -> str:
"""
credit to ZitaoWang for being a beast (adapted sol.)
The key to this solution is in the set-up in identifying
that each number has its own unique character that defines
it. Some don't have this characteristic but they become
defined as the ones before it do
"""
char2word = {'z': 'zero', 'w': 'two', 'u': 'four', 'x': 'six', 'g': 'eight', 'o': 'one', 'r': 'three', 'f': 'five', 's': 'seven','i': 'nine'}
word2int = {'zero': '0', 'one': '1', 'two': '2', 'three': '3', \
'four': '4', 'five': '5', 'six': '6', 'seven': '7', \
'eight': '8', 'nine': '9'}
kei = list(char2word.keys())
arr = []
all = dict()
# fill dict with all letters
for letter in s:
if letter in all:
all[letter] += 1
else:
all[letter] = 1
#iterate through each key
for key in kei:
if key in all:
while all[key] != 0:
# take the key and output it to an array while subtracting the letters from all
for i in range(len(char2word[key])):
print(char2word[key][i])
all[char2word[key][i]] -= 1
arr.append(word2int[char2word[key]])
arr.sort()
return ''.join(arr) | [
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# coding=utf-8
# Django settings for bluebottle project.
import os, datetime
# Import global settings for overriding without throwing away defaults
from django.conf import global_settings
from django.utils.translation import ugettext as _
from admin_dashboard import *
from .payments import *
# Set PROJECT_ROOT to the dir of the current file
# Find the project's containing directory and normalize it to refer to
# the project's root more easily
PROJECT_ROOT = os.path.dirname(os.path.normpath(os.path.join(__file__, '..', '..')))
# DJANGO_PROJECT: the short project name
# (defaults to the basename of PROJECT_ROOT)
DJANGO_PROJECT = os.path.basename(PROJECT_ROOT.rstrip('/'))
DEBUG = True
TEST_MEMCACHE = False
TEMPLATE_DEBUG = True
COMPRESS_TEMPLATES = False
ADMINS = (
('Team Error', '[email protected]'),
)
CONTACT_EMAIL = '[email protected]'
MANAGERS = ADMINS
# Hosts/domain names that are valid for this site; required if DEBUG is False
# See https://docs.djangoproject.com/en/1.5/ref/settings/#allowed-hosts
ALLOWED_HOSTS = ['.onepercentclub.com', '.1procentclub.nl', 'localhost']
# Local time zone for this installation. Choices can be found here:
# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name
# although not all choices may be available on all operating systems.
# On Unix systems, a value of None will cause Django to use the same
# timezone as the operating system.
# If running in a Windows environment this must be set to the same as your
# system time zone.
TIME_ZONE = 'Europe/Amsterdam'
# Available user interface translations
# Ref: https://docs.djangoproject.com/en/1.4/ref/settings/#languages
#
# Default language code for this installation. All choices can be found here:
# http://www.i18nguy.com/unicode/language-identifiers.html
LANGUAGE_CODE = 'en'
# This is defined here as a do-nothing function because we can't import
# django.utils.translation -- that module depends on the settings.
gettext_noop = lambda s: s
LANGUAGES = (
('nl', gettext_noop('Dutch')),
('en', gettext_noop('English'))
)
SITE_ID = 1
# If you set this to False, Django will make some optimizations so as not
# to load the internationalization machinery.
USE_I18N = True
# If you set this to False, Django will not format dates, numbers and
# calendars according to the current locale.
USE_L10N = True
# First one is for apps the second for the main templates
LOCALE_PATHS = ('../locale', 'locale')
# If you set this to False, Django will not use timezone-aware datetimes.
# pytz is in requirements.txt because it's "highly recommended" when using
# timezone support.
# https://docs.djangoproject.com/en/1.4/topics/i18n/timezones/
USE_TZ = True
# Static Files and Media
# ======================
#
# For staticfiles and media, the following convention is used:
#
# * '/static/media/': Application media default path
# * '/static/global/': Global static media
# * '/static/assets/<app_name>/': Static assets after running `collectstatic`
#
# The respective URL's (available only when `DEBUG=True`) are in `urls.py`.
#
# More information:
# https://docs.djangoproject.com/en/1.4/ref/contrib/staticfiles/
# Absolute filesystem path to the directory that will hold user-uploaded files.
# Example: "/home/media/media.lawrence.com/media/"
MEDIA_ROOT = os.path.join(PROJECT_ROOT, 'static', 'media')
# Absolute filesystem path to the directory that will hold PRIVATE user-uploaded files.
PRIVATE_MEDIA_ROOT = os.path.join(PROJECT_ROOT, 'private', 'media')
# URL that handles the media served from MEDIA_ROOT. Make sure to use a
# trailing slash.
# Examples: "http://media.lawrence.com/media/", "http://example.com/media/"
MEDIA_URL = '/static/media/'
PRIVATE_MEDIA_URL = '/private/media/'
# Absolute path to the directory static files should be collected to.
# Don't put anything in this directory yourself; store your static files
# in apps' "static/" subdirectories and in STATICFILES_DIRS.
# Example: "/home/media/media.lawrence.com/static/"
STATIC_ROOT = os.path.join(PROJECT_ROOT, 'static', 'assets')
# URL prefix for static files.
# Example: "http://media.lawrence.com/static/"
STATIC_URL = '/static/assets/'
# Additional locations of static files
STATICFILES_DIRS = (
# Put strings here, like "/home/html/static" or "C:/www/django/static".
# Always use forward slashes, even on Windows.
# Don't forget to use absolute paths, not relative paths.
# You can also name this tuple like: ('css', '/path/to/css')
(os.path.join(PROJECT_ROOT, 'static', 'global')),
)
# List of finder classes that know how to find static files in
# various locations.
STATICFILES_FINDERS = [
'django.contrib.staticfiles.finders.FileSystemFinder',
'django.contrib.staticfiles.finders.AppDirectoriesFinder',
# 'django.contrib.staticfiles.finders.DefaultStorageFinder',
]
TEMPLATE_LOADERS = [
'django.template.loaders.filesystem.Loader',
'django.template.loaders.app_directories.Loader',
'apptemplates.Loader', # extend AND override templates
]
CACHES = {
'default': {
'BACKEND': 'django.core.cache.backends.dummy.DummyCache',
}
}
# These are basically the default values from the Django configuration, written
# as a list for easy manipulation. This way one can:
#
# 1. Easily add, remove or replace elements in the list, ie. overriding.
# 2. Know what the defaults are, if you want to change them right here. This
# way you won't have to look them up every time you want to change.
#
# Note: The first three middleware classes need to be in this order: Session, Locale, Common
# http://stackoverflow.com/questions/8092695/404-on-requests-without-trailing-slash-to-i18n-urls
MIDDLEWARE_CLASSES = [
'bluebottle.auth.middleware.UserJwtTokenMiddleware',
'apps.redirects.middleware.RedirectHashCompatMiddleware',
'bluebottle.auth.middleware.AdminOnlyCsrf',
# Have a middleware to make sure old cookies still work after we switch to domain-wide cookies.
'bluebottle.utils.middleware.SubDomainSessionMiddleware',
'django.middleware.locale.LocaleMiddleware',
'django.middleware.common.CommonMiddleware',
'bluebottle.auth.middleware.AdminOnlySessionMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'bluebottle.auth.middleware.AdminOnlyAuthenticationMiddleware',
'bluebottle.bb_accounts.middleware.LocaleMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
# https://docs.djangoproject.com/en/1.4/ref/clickjacking/
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'django.middleware.transaction.TransactionMiddleware',
'apps.redirects.middleware.RedirectFallbackMiddleware',
'apps.crawlable.middleware.HashbangMiddleware',
'django_tools.middlewares.ThreadLocal.ThreadLocalMiddleware',
'bluebottle.auth.middleware.SlidingJwtTokenMiddleware'
]
# Browsers will block our pages from loading in an iframe no matter which site
# made the request. This setting can be overridden on a per response or a per
# view basis with the @xframe decorators.
X_FRAME_OPTIONS = 'DENY'
TEMPLATE_CONTEXT_PROCESSORS = global_settings.TEMPLATE_CONTEXT_PROCESSORS + (
# Makes the 'request' variable (the current HttpRequest) available in templates.
'django.core.context_processors.request',
'django.core.context_processors.i18n',
'bluebottle.utils.context_processors.installed_apps_context_processor',
'bluebottle.utils.context_processors.git_commit',
'bluebottle.utils.context_processors.conf_settings',
'bluebottle.utils.context_processors.google_maps_api_key',
'bluebottle.utils.context_processors.google_analytics_code',
'bluebottle.utils.context_processors.sentry_dsn',
'bluebottle.utils.context_processors.facebook_auth_settings',
'bluebottle.utils.context_processors.mixpanel_settings',
'social.apps.django_app.context_processors.backends',
'social.apps.django_app.context_processors.login_redirect',
)
ROOT_URLCONF = 'onepercentclub.urls'
# Python dotted path to the WSGI application used by Django's runserver.
WSGI_APPLICATION = 'onepercentclub.wsgi.application'
TEMPLATE_DIRS = (
# Put strings here, like "/home/html/django_templates".
# Always use forward slashes, even on Windows.
# Don't forget to use absolute paths, not relative paths.
os.path.join(PROJECT_ROOT, 'templates')
)
INSTALLED_APPS = (
# Django apps
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.sites',
'django.contrib.messages',
'django.contrib.staticfiles',
# 3rd party apps
'django_extensions',
'django_extensions.tests',
'raven.contrib.django.raven_compat',
'djcelery',
'south',
# 'django_nose',
'compressor',
'sorl.thumbnail',
'taggit',
'taggit_autocomplete_modified',
'micawber.contrib.mcdjango', # Embedding videos
'templatetag_handlebars',
'rest_framework',
'rest_framework.authtoken',
'polymorphic',
'registration',
'filetransfers',
'loginas',
#'social_auth',
'social.apps.django_app.default',
# Onepercent app to send POST requests to AFOM
'onepercent_afom',
#Widget
'bluebottle.widget',
# CMS page contents
'fluent_contents',
'fluent_contents.plugins.text',
'fluent_contents.plugins.oembeditem',
'fluent_contents.plugins.rawhtml',
'django_wysiwyg',
'tinymce',
'statici18n',
'django.contrib.humanize',
'django_tools',
# FB Auth
'bluebottle.auth',
# Password auth from old PHP site.
'legacyauth',
# Plain Bluebottle apps
'bluebottle.wallposts',
'bluebottle.utils',
'bluebottle.common',
'bluebottle.contentplugins',
'bluebottle.contact',
'bluebottle.geo',
'bluebottle.pages',
'bluebottle.news',
'bluebottle.slides',
'bluebottle.quotes',
'bluebottle.payments',
'bluebottle.payments_docdata',
'bluebottle.payments_logger',
'bluebottle.payments_voucher',
'bluebottle.redirects',
# Apps extending Bluebottle base models
# These should be before there Bb parents so the templates are overridden
'apps.members',
'apps.tasks',
'apps.projects',
'apps.organizations',
'apps.payouts',
# apps overriding bluebottle functionality should come before the bluebottle entries
# (template loaders pick the first template they find)
'apps.core',
'apps.bluebottle_salesforce',
'apps.bluebottle_dashboard',
'apps.contentplugins',
'apps.campaigns',
'apps.hbtemplates',
'apps.statistics',
'apps.homepage',
'apps.partners',
'apps.crawlable',
'apps.mchanga',
'apps.recurring_donations',
# Bluebottle apps with abstract models
'bluebottle.bb_accounts',
'bluebottle.bb_organizations',
'bluebottle.bb_projects',
'bluebottle.bb_tasks',
'bluebottle.bb_fundraisers',
'bluebottle.bb_donations',
'bluebottle.bb_orders',
'bluebottle.bb_payouts',
# Basic Bb implementations
'bluebottle.fundraisers',
'bluebottle.donations',
'bluebottle.orders',
# FIXME: Keep these just for migrations
'apps.fund',
'apps.cowry',
'apps.cowry_docdata',
# FIXME: Reimplement these apps
'apps.vouchers',
# 'apps.sepa',
# 'apps.csvimport',
# 'apps.accounting',
# Custom dashboard
'fluent_dashboard',
'admin_tools',
'admin_tools.theming',
'admin_tools.menu',
'admin_tools.dashboard',
'django.contrib.admin',
'django.contrib.admindocs',
)
# Custom User model
AUTH_USER_MODEL = 'members.Member'
PROJECTS_PROJECT_MODEL = 'projects.Project'
PROJECTS_PHASELOG_MODEL = 'projects.ProjectPhaseLog'
FUNDRAISERS_FUNDRAISER_MODEL = 'fundraisers.FundRaiser'
TASKS_TASK_MODEL = 'tasks.Task'
TASKS_SKILL_MODEL = 'tasks.Skill'
TASKS_TASKMEMBER_MODEL = 'tasks.TaskMember'
TASKS_TASKFILE_MODEL = 'tasks.TaskFile'
ORGANIZATIONS_ORGANIZATION_MODEL = 'organizations.Organization'
ORGANIZATIONS_DOCUMENT_MODEL = 'organizations.OrganizationDocument'
ORGANIZATIONS_MEMBER_MODEL = 'organizations.OrganizationMember'
ORDERS_ORDER_MODEL = 'orders.Order'
DONATIONS_DONATION_MODEL = 'donations.Donation'
PAYOUTS_PROJECTPAYOUT_MODEL = 'payouts.ProjectPayout'
PAYOUTS_ORGANIZATIONPAYOUT_MODEL = 'payouts.OrganizationPayout'
SOCIAL_AUTH_USER_MODEL = 'members.Member'
SOCIAL_AUTH_FACEBOOK_SCOPE = ['email', 'user_friends', 'public_profile', 'user_birthday']
SOCIAL_AUTH_FACEBOOK_EXTRA_DATA = [('birthday', 'birthday')]
# A sample logging configuration. The only tangible logging
# performed by this configuration is to send an email to
# the site admins on every HTTP 500 error when DEBUG=False.
# See http://docs.djangoproject.com/en/dev/topics/logging for
# more details on how to customize your logging configuration.
LOGGING = {
'version': 1,
'disable_existing_loggers': False,
'formatters': {
'standard': {
'format': "[%(asctime)s] %(levelname)s [%(name)s:%(lineno)s] %(message)s",
'datefmt': "%d/%b/%Y %H:%M:%S"
},
},
'filters': {
'require_debug_false': {
'()': 'django.utils.log.RequireDebugFalse'
}
},
'handlers': {
'mail_admins': {
'level': 'ERROR',
'filters': ['require_debug_false'],
'class': 'django.utils.log.AdminEmailHandler'
},
'payment_logs': {
'level': 'INFO',
'class': 'bluebottle.payments_logger.handlers.PaymentLogHandler',
}
},
'loggers': {
'django.request': {
'handlers': ['mail_admins'],
'level': 'ERROR',
'propagate': True,
},
'bluebottle.salesforce': {
'handlers': ['mail_admins'],
'level': 'ERROR',
'propagate': True,
},
'payments.payment': {
'handlers': ['mail_admins', 'payment_logs'],
'level': 'INFO',
'propagate': True,
},
}
}
# log errors & warnings
import logging
logging.basicConfig(level=logging.WARNING, format='[%(asctime)s] %(levelname)-8s %(message)s', datefmt="%d/%b/%Y %H:%M:%S")
# Django Celery - asynchronous task server
import djcelery
djcelery.setup_loader()
SOCIAL_AUTH_STRATEGY = 'social.strategies.django_strategy.DjangoStrategy'
SOCIAL_AUTH_STORAGE = 'social.apps.django_app.default.models.DjangoStorage'
AUTHENTICATION_BACKENDS = (
'social.backends.facebook.FacebookAppOAuth2',
'social.backends.facebook.FacebookOAuth2',
'django.contrib.auth.backends.ModelBackend',
)
# We're using nose because it limits the tests to our apps (i.e. no Django and
# 3rd party app tests). We need this because tests in contrib.auth.user are
# failing in Django 1.4.1. Here's the ticket for the failing test:
# https://code.djangoproject.com/ticket/17966
# The new test runner in Django 1.5 will be more flexible:
#https://code.djangoproject.com/ticket/17365
TEST_RUNNER = 'django_nose.NoseTestSuiteRunner'
NOSE_ARGS = [
'--detailed-errors',
'--nologcapture',
]
SKIP_BB_FUNCTIONAL_TESTS = True
SOUTH_TESTS_MIGRATE = False # Make south shut up during tests
# django-compressor http://pypi.python.org/pypi/django_compressor
# Compressor is enabled whenever DEBUG is False.
STATICFILES_FINDERS += [
# django-compressor staticfiles
'compressor.finders.CompressorFinder',
]
# TODO Enable compass here.
COMPRESS_OUTPUT_DIR = 'compressed'
COMPRESS_CSS_FILTERS = [
'compressor.filters.css_default.CssAbsoluteFilter',
#'compressor.filters.datauri.DataUriFilter',
'compressor.filters.cssmin.CSSMinFilter'
]
# Automagic CSS precompilation
#COMPRESS_PRECOMPILERS = (
# ('text/coffeescript', 'coffee --compile --stdio'),
# ('text/less', 'lessc {infile} {outfile}'),
# ('text/x-sass', 'sass {infile} {outfile}'),
# ('text/x-scss', 'sass --scss {infile} {outfile}'),
#)
# The default URL to send users to after login. This will be used when the
# 'next' URL parameter hasn't been set.
LOGIN_REDIRECT_URL = '/'
# Blog/news content configuration
FLUENT_CONTENTS_CACHE_OUTPUT = True
FLUENT_TEXT_CLEAN_HTML = True
FLUENT_TEXT_SANITIZE_HTML = True
DJANGO_WYSIWYG_FLAVOR = 'tinymce_advanced'
# Required for handlebars_template to work properly
USE_EMBER_STYLE_ATTRS = True
# Sorl Thumbnail settings
# http://sorl-thumbnail.readthedocs.org/en/latest/reference/settings.html
THUMBNAIL_QUALITY = 85
# TODO: Configure Sorl with Redis.
REST_FRAMEWORK = {
'FILTER_BACKEND': 'rest_framework.filters.DjangoFilterBackend',
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework_jwt.authentication.JSONWebTokenAuthentication',
'rest_framework.authentication.SessionAuthentication',
'rest_framework.authentication.TokenAuthentication',
)
}
JWT_AUTH = {
'JWT_EXPIRATION_DELTA': datetime.timedelta(days=7),
'JWT_LEEWAY': 0,
'JWT_VERIFY': True,
'JWT_VERIFY_EXPIRATION': True,
'JWT_ALLOW_TOKEN_RENEWAL': True,
# After the renewal limit it isn't possible to request a token refresh
# => time token first created + renewal limit.
'JWT_TOKEN_RENEWAL_LIMIT': datetime.timedelta(days=90),
}
# Time between attempts to refresh the jwt token automatically on standard request
# TODO: move this setting into the JWT_AUTH settings.
JWT_TOKEN_RENEWAL_DELTA = datetime.timedelta(minutes=30)
COWRY_RETURN_URL_BASE = 'http://127.0.0.1:8000'
COWRY_PAYMENT_METHODS = {
'dd-webmenu': {
'profile': 'webmenu',
'name': 'DocData Web Menu',
'supports_recurring': False,
'supports_single': True,
},
'dd-webdirect': {
'profile': 'webdirect',
'name': 'DocData WebDirect Direct Debit',
'restricted_countries': ('NL',),
'supports_recurring': True,
'supports_single': False,
},
}
# Default VAT percentage as string (used in payouts)
VAT_RATE = '0.21'
# Settings for organization bank account. Please set this in secrets.py
# SEPA = {
# 'iban': '',
# 'bic': '',
# 'name': '',
# 'id': ''
# }
# Salesforce app settings
SALESFORCE_QUERY_TIMEOUT = 3
DATABASE_ROUTERS = [
"salesforce.router.ModelRouter"
]
# E-mail settings
DEFAULT_FROM_EMAIL = '<[email protected]> 1%Club'
# Django-registration settings
ACCOUNT_ACTIVATION_DAYS = 4
HTML_ACTIVATION_EMAIL = True # Note this setting is from our forked version.
# Functional testing
# Selenium and Splinter settings
SELENIUM_TESTS = True
SELENIUM_WEBDRIVER = 'phantomjs' # Can be any of chrome, firefox, phantomjs
FIXTURE_DIRS = [
os.path.join(DJANGO_PROJECT, 'fixtures')
]
# PhantomJS for flat page generation.
# NOTE: This has nothing to do with testing against phantomjs.
CRAWLABLE_PHANTOMJS_DEDICATED_MODE = True
# If dedicated mode is enabled, configure the port:
CRAWLABLE_PHANTOMJS_DEDICATED_PORT = 8910
# If dedicated mode is disabled, you can specify arguments to start phantomjs.
CRAWLABLE_PHANTOMJS_ARGS = []
# Use HTTPS for PhantomJS requests.
CRAWLABLE_FORCE_HTTPS = True
# Send email to console by default
EMAIL_BACKEND = 'django.core.mail.backends.console.EmailBackend'
STATICI18N_ROOT = os.path.join(PROJECT_ROOT, 'static', 'global')
SESSION_COOKIE_NAME = 'bb-session-id'
# Support legacy passwords
PASSWORD_HASHERS = global_settings.PASSWORD_HASHERS + (
'legacyauth.hashers.LegacyPasswordHasher',
)
# Twitter handles, per language
TWITTER_HANDLES = {
'nl': '1procentclub',
'en': '1percentclub',
}
DEFAULT_TWITTER_HANDLE = TWITTER_HANDLES['nl']
MINIMAL_PAYOUT_AMOUNT = 21.00
SOCIAL_AUTH_PIPELINE = (
'social.pipeline.social_auth.social_details',
'social.pipeline.social_auth.social_uid',
'social.pipeline.social_auth.auth_allowed',
'social.pipeline.social_auth.social_user',
'social.pipeline.user.get_username',
'social.pipeline.social_auth.associate_by_email',
'social.pipeline.user.create_user',
'social.pipeline.social_auth.associate_user',
'social.pipeline.social_auth.load_extra_data',
'social.pipeline.user.user_details',
'bluebottle.auth.utils.save_profile_picture',
'bluebottle.auth.utils.get_extra_facebook_data',
'bluebottle.auth.utils.send_welcome_mail_pipe'
)
AFOM_ENABLED = False
SOCIAL_AUTH_PROTECTED_USER_FIELDS = ['email', 'first_name', 'last_name', ]
SOCIAL_AUTH_USERNAME_IS_FULL_EMAIL = True
SEND_WELCOME_MAIL = True
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4146,
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198
] | 2.622068 | 7,758 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#Los valores reales eran
#La altura inicial es 0.5 [m]
#La gravedad es 9.8 [m/s^2]
#El ángulo es 25 [grados]
#La velocidad inicial es 5 [m/s]
#El Xmax es 2.724 [m]
#El Ymax es 0.728 [m]
import math, sys
#PARA REVISAR RÁPIDAMENTE
n=15
x=[0.100,0.250,0.400,0.550,0.700,0.850,1.000,1.150,1.300,1.450,1.600,1.750,1.900,2.050,2.200]
y=[0.553,0.605,0.657,0.693,0.711,0.733,0.734,0.724,0.710,0.676,0.639,0.594,0.525,0.462,0.380]
t=[0.029,0.064,0.091,0.130,0.158,0.193,0.225,0.262,0.288,0.326,0.353,0.392,0.421,0.458,0.494]
#POR ENTRADA POR CONSOLA
#n=int(input("¿Cuántos datos son?"))
#x=[]
#y=[]
#t=[]
#
#if n<=0:
# print("El número de datos debe ser mayor a cero")
# sys.exit()
#else:
# for i in range(0,n):
# print("Ingrese el dato x%d") % (i)
# x.append(float(input()))
# print("Ingrese el dato y%d") % (i)
# y.append(float(input()))
# print("Ingrese el dato t%d") % (i)
# t.append(float(input()))
sol1=reglineal(x,t,n)
sol2=regcuad(y,t,n)
print sol1
#sol1[0]-->m
#sol1[1]-->b
#sol2[0]-->cc
#sol2[1]-->bc
#sol2[2]-->ac
y0 = sol2[2]
g = -2.0*sol2[0]
theta = math.atan(sol2[1]/sol1[0]) #En radianes
V0 = sol1[0]/math.cos(theta)
if ((V0*math.sin(theta))**2.0+2.0*g*y0)==0:
print("Los datos arrojan tiempos complejos")
sys.exit()
else:
tmax1 = (-1.0*V0*math.sin(theta) + math.sqrt((V0*math.sin(theta))**2.0+2.0*g*y0))/(-1.0*g)
tmax2 = (-1.0*V0*math.sin(theta) - math.sqrt((V0*math.sin(theta))**2.0+2.0*g*y0))/(-1.0*g)
if tmax1>0:
xmax = V0*math.cos(theta)*tmax1
elif tmax2>0:
xmax = V0*math.cos(theta)*tmax2
else:
print("Tiempos negativos hay un error en sus datos")
sys.exit()
ts = V0*math.sin(theta)/g
if ts<0:
print("Tiempos negativos hay un error en sus datos")
else:
ymax = y0 - 0.5*g*ts**2 + V0*math.sin(theta)*ts
print ("La altura inicial es %.3f [m]\nLa gravedad es %.3f [m/s^2]\nEl ángulo es %.3f [grados] \nLa velocidad inicial es %.3f [m/s] \nEl Xmax es %.3f [m] \nEl Ymax es %.3f [m]") % (y0,g,math.degrees(theta),V0,xmax,ymax)
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] | 1.751494 | 1,171 |
# Copyright (c) 2020 Chris Richardson & Matthew Scroggs
# FEniCS Project
# SPDX-License-Identifier: MIT
import sympy
import basix
import numpy as np
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from enum import Enum
if __name__ == '__main__':
pass
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#!/usr/bin/env python3
"""
Visualize results of Gaussian process bootstrapping.
"""
import argparse
import math
import os
import pathlib
import pandas as pd
import matplotlib.pyplot as mpl
def parse_args():
"""
Parse command line arguments.
"""
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument("--dirpath", type=str, default="results", help="path to results directory")
parser.add_argument("--save", action="store_true", help="save figures under output directory")
parser.add_argument("--output", type=str, default="figures", help="output directory")
return parser.parse_args()
def read_result_tsv(path_tsv, length=300):
"""
Parse TSV file and returns basename of file and list of test accuracy.
"""
def is_test_row(line):
"""
Returns true if the given line is a row of test score.
"""
return line.startswith("Test: ")
def get_test_accuracy(line):
"""
Returns test accuracy based on the supposition that the given `line` is a test score row.
"""
return float(line.split("\t")[0].split("=")[-1].strip())
# Compute base name.
basename = path_tsv.name[:-len(path_tsv.suffix)]
# Read file and get test accuracy scores.
scores = [get_test_accuracy(line) for line in path_tsv.open() if is_test_row(line)]
# Normalize list length.
if len(scores) < length: scores += [0.0] * (length - len(scores))
else : scores = scores[:length]
return (basename, scores)
def read_result_txt(path_txt, apply_sqrt=True):
"""
Parse TXT file and returns a list of variance.
"""
def is_variance_row(line):
"""
Returns true if the given line is a row of test score.
"""
return all(char in ".0123456789e+-" for char in line.strip())
output = [float(line.strip()) for line in path_txt.open("rt") if is_variance_row(line)]
if apply_sqrt: return list(map(math.sqrt, output))
else : return output
def plot_trends(scores, keys, header, args):
"""
Plot test accuracy plotting for both with/without data augmentation.
"""
# Plot accuracies without data augmentation.
mpl.figure(figsize=(8, 5))
mpl.title(f"{header}: without data augmentation")
for key in keys:
mpl.plot(100 * scores[key], "-o", label=key, lw=1, markersize=2, alpha=0.8)
mpl.xlim(0, 150)
mpl.ylim(60, 75)
mpl.legend(loc="lower right", ncol=2)
mpl.grid(linestyle="dotted")
mpl.xlabel("Epoch")
mpl.ylabel("Accuracy on CIFAR10 [%]")
if args.save:
filepath = "trend_" + header.lower().replace(" ", "_") + ".png"
mpl.savefig(os.path.join(args.output, filepath))
# Plot accuracies with data augmentation.
mpl.figure(figsize=(8, 5))
mpl.title(f"{header}: with data augmentation")
for key in keys:
mpl.plot(100 * scores[key + "_da"], "-o", label=key, lw=1, markersize=2, alpha=0.8)
mpl.xlim(0, 300)
mpl.ylim(75, 85)
mpl.legend(loc="lower right", ncol=2)
mpl.grid(linestyle="dotted")
mpl.xlabel("Epoch")
mpl.ylabel("Accuracy on CIFAR10 [%]")
if args.save:
filepath = "trend_" + header.lower().replace(" ", "_") + "_da.png"
mpl.savefig(os.path.join(args.output, filepath))
def plot_topval(scores, keys, header, args):
"""
Plot top accuracy of test data for both with/without data augmentation.
"""
# Plot top accuracies without data augmentation.
ks = keys
xs = list(range(len(ks)))
ys = [100 * max(scores[key]) for key in ks]
mpl.figure(figsize=(8, 5))
mpl.title(f"{header}: top scores without data augmentation")
mpl.bar(xs, ys, color=[f"C{x}" for x in xs])
for x, y in enumerate(ys):
mpl.text(x - 0.25, y + 0.1, f"{y:.2f}", color=f"C{x}", fontweight="bold")
mpl.xticks(xs, ks, rotation=20)
mpl.ylim(70, 75)
mpl.grid(linestyle="dotted")
mpl.ylabel("Accuracy on CIFAR10 [%]")
if args.save:
filepath = "topscore_" + header.lower().replace(" ", "_") + ".png"
mpl.savefig(os.path.join(args.output, filepath))
# Plot top accuracies with data augmentation.
ks = [k + "_da" for k in keys]
xs = list(range(len(ks)))
ys = [100 * max(scores[key]) for key in ks]
mpl.figure(figsize=(8, 5))
mpl.title(f"{header}: top scores with data augmentation")
mpl.bar(xs, ys, color=[f"C{x}" for x in xs])
for x, y in enumerate(ys):
mpl.text(x - 0.25, y + 0.1, f"{y:.2f}", color=f"C{x}", fontweight="bold")
mpl.xticks(xs, ks, rotation=20)
mpl.ylim(80, 82.5)
mpl.grid(linestyle="dotted")
mpl.ylabel("Accuracy on CIFAR10 [%]")
if args.save:
filepath = "topscore_" + header.lower().replace(" ", "_") + "_da.png"
mpl.savefig(os.path.join(args.output, filepath))
def plot_stdhist(std_plain, std_gpb_b, args):
"""
Plot histogram of feature standard deviation.
"""
mpl.figure(figsize=(8, 5))
mpl.title("Histogram of feature standard deviation (N = 10,000)")
mpl.hist(std_plain, bins=101, histtype="step", label="plain")
mpl.hist(std_gpb_b, bins=101, histtype="step", label="gpb_b")
mpl.grid(linestyle="dotted")
mpl.xlabel("Standard deviation of features")
mpl.ylabel("Frequency")
mpl.legend()
if args.save:
filepath = "histogram_standard_deviation.png"
mpl.savefig(os.path.join(args.output, filepath))
def main(args):
"""
Main function.
"""
# Path to the result directory.
dirpath = pathlib.Path(args.dirpath)
# Read test accuracy scores.
scores = pd.DataFrame({name:score for name, score in map(read_result_tsv, sorted(dirpath.glob("*.tsv")))})
# Target base names.
keys1 = ["baseline", "gpb_tmx", "gpb_xmb", "gpb_tmb"]
keys2 = ["baseline", "gpb_txx", "gpb_xmx", "gpb_xxb", "gpb_xmb", "gpb_txb", "gpb_tmx", "gpb_tmb"]
# Plot figures and show them.
plot_trends(scores, keys1, "Main results", args)
plot_trends(scores, keys2, "Exhaustive results", args)
plot_topval(scores, keys2, "Exhaustive results", args)
# Read test accuracy scores.
std_plain = read_result_txt(dirpath / "variance_plain_da.txt", apply_sqrt=True)
std_gpb_b = read_result_txt(dirpath / "variance_gpb_b_da.txt", apply_sqrt=True)
# Plot figures and show them.
plot_stdhist(std_plain, std_gpb_b, args)
mpl.show()
if __name__ == "__main__":
main(parse_args())
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] | 2.363472 | 2,765 |
text = input('Enter a text: ')
character = input('Enter a character that you can search in "'+text+'": ')
result = text.count(character)
print('The character "'+character+'" appears '+str(result)+' times in "'+text+'".') | [
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] | 3.217391 | 69 |
import torch
torch.manual_seed(0)
# from _ext import th_fft
import pytorch_fft.fft as cfft
import pytorch_fft.fft.autograd as afft
import numpy as np
import numpy.fft as nfft
if __name__ == "__main__":
if torch.cuda.is_available():
nfft3 = lambda x: nfft.fftn(x,axes=(1,2,3))
nifft3 = lambda x: nfft.ifftn(x,axes=(1,2,3))
cfs = [cfft.fft, cfft.fft2, cfft.fft3]
nfs = [nfft.fft, nfft.fft2, nfft3]
cifs = [cfft.ifft, cfft.ifft2, cfft.ifft3]
nifs = [nfft.ifft, nfft.ifft2, nifft3]
for args in zip(cfs, nfs, cifs, nifs):
test_c2c(*args)
nrfft3 = lambda x: nfft.rfftn(x,axes=(1,2,3))
nirfft3 = lambda x: nfft.irfftn(x,axes=(1,2,3))
cfs = [cfft.rfft, cfft.rfft2, cfft.rfft3]
nfs = [nfft.rfft, nfft.rfft2, nrfft3]
cifs = [cfft.irfft, cfft.irfft2, cfft.irfft3]
nifs = [nfft.irfft, nfft.irfft2, nirfft3]
for args in zip(cfs, nfs, cifs, nifs):
test_r2c(*args)
test_expand()
test_fft_gradcheck()
test_ifft_gradcheck()
test_fft2d_gradcheck()
test_ifft2d_gradcheck()
test_fft3d_gradcheck()
test_ifft3d_gradcheck()
test_rfft_gradcheck()
test_irfft_gradcheck()
test_rfft2d_gradcheck()
test_irfft2d_gradcheck()
test_rfft3d_gradcheck()
test_irfft3d_gradcheck()
else:
print("Cuda not available, cannot test.")
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# -*- coding: utf-8 -*-
# Copyright (c) 2020, omar jaber and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe.model.document import Document
from frappe import _
| [
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] | 3.422535 | 71 |
import pdf2txt
#import time
import csv
from PySide import QtGui
import os
import os.path
# prove prove
my_dir = QtGui.QFileDialog.getExistingDirectory(None,'Scegli una cartella','\\srveuro\Ufficio_Tecnico\VALIDAZIONE\S10')
file_list = []
for dirpath, dirnames, filenames in os.walk(my_dir):
for filename in [f for f in filenames if f.endswith(".pdf")]:
file_list.append(os.path.join(dirpath, filename))
nome_file = raw_input('Nome del file CSV:')
#nome=[]
#nome.append('Ore')
#
#my_dir = QtGui.QFileDialog.getExistingDirectory(None,'Scegli una cartella','D:\Documenti\Lavoro\Eurocoating\Logs')
#
#
## Get folder path containing text files
#file_list = glob.glob(my_dir + '/*.csv')
#
#
#lunghezza = 5 #len(file_list)
lunghezza = len(file_list)
excel = [[0 for x in range(7)] for y in range(lunghezza)]
for f in range(0,lunghezza):
#for f in range(0,len(file_list)):
print f
reportpdf = file_list[f]
reporttxt = my_dir + '\\temp.txt'
pdf2txt.main(['', '-o', reporttxt, reportpdf])
data_raw = []
testo = open(reporttxt, 'r')
with testo as myfile:
for line in myfile:
data_raw.append(line)
#for i in range(0,len(data_raw)):
# print i, data_raw[i]
testo.close()
############## Data ##############
excel[f][0] = data_raw[2][:-1]
############## Nome #############
index = data_raw.index('[mm]\n')
excel[f][1] = data_raw[index+2][:-1]
############## Norma #############
index = data_raw.index('GAUSS\n')
if int(data_raw[index-3][:-1]) == 10:
excel[f][2] = 'EC'
if int(data_raw[index-3][:-1]) == 5:
excel[f][2] = 'NORMA'
############## Ra #############
index = data_raw.index('Ra\n')
excel[f][3] = float(data_raw[index+10][:-3])
############## Rz #############
excel[f][4] = float(data_raw[index+11][:-3])
############## Rt #############
excel[f][5] = float(data_raw[index+12][:-3])
############## Nome file #############
excel[f][6] = reportpdf
nome_csv = my_dir + "\\" + nome_file +".csv"
with open(nome_csv, "wb") as c:
writer = csv.writer(c, delimiter=";")
writer.writerows(excel)
print "Finito!" | [
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] | 1.94177 | 1,288 |
from typing import Any, Dict, List, Optional, Union
from .muxed_account import MuxedAccount
from .sep.ed25519_public_key_signer import Ed25519PublicKeySigner
from .type_checked import type_checked
__all__ = ["Account"]
@type_checked
class Account:
"""The :class:`Account` object represents a single
account on the Stellar network and its sequence number.
Account tracks the sequence number as it is used
by :class:`TransactionBuilder <stellar_sdk.transaction_builder.TransactionBuilder>`.
Normally, you can get an :class:`Account` instance through :func:`stellar_sdk.server.Server.load_account`
or :func:`stellar_sdk.server_async.ServerAsync.load_account`.
An example::
from stellar_sdk import Keypair, Server
server = Server(horizon_url="https://horizon-testnet.stellar.org")
source = Keypair.from_secret("SBFZCHU5645DOKRWYBXVOXY2ELGJKFRX6VGGPRYUWHQ7PMXXJNDZFMKD")
# `account` can also be a muxed account
source_account = server.load_account(account=source.public_key)
See `Accounts <https://developers.stellar.org/docs/glossary/accounts/>`__ for
more information.
:param account: Account Id of the
account (ex. ``"GB3KJPLFUYN5VL6R3GU3EGCGVCKFDSD7BEDX42HWG5BWFKB3KQGJJRMA"``)
or muxed account (ex. ``"MBZSQ3YZMZEWL5ZRCEQ5CCSOTXCFCMKDGFFP4IEQN2KN6LCHCLI46AAAAAAAAAAE2L2QE"``)
:param sequence: Current sequence number of the account.
:param raw_data: Raw horizon response data.
"""
@property
def universal_account_id(self) -> str:
"""Get the universal account id,
if `account` is ed25519 public key, it will return ed25519
public key (ex. ``"GDGQVOKHW4VEJRU2TETD6DBRKEO5ERCNF353LW5WBFW3JJWQ2BRQ6KDD"``),
otherwise it will return muxed
account (ex. ``"MAAAAAAAAAAAJURAAB2X52XFQP6FBXLGT6LWOOWMEXWHEWBDVRZ7V5WH34Y22MPFBHUHY"``)
.. note::
SEP-0023 support is not enabled by default, if you want to enable it,
please set `ENABLE_SEP_0023` to ``true`` in the environment variable,
on Linux and MacOS, generally you can use ``export ENABLE_SEP_0023=true`` to set it.
:raises: :exc:`FeatureNotEnabledError <stellar_sdk.exceptions.FeatureNotEnabledError>`:
if `account_id` is a muxed account and `ENABLE_SEP_0023` is not set to ``true``.
"""
return self.account.universal_account_id
def increment_sequence_number(self) -> None:
"""Increments sequence number in this object by one."""
self.sequence += 1
@property
def load_ed25519_public_key_signers(self) -> List[Ed25519PublicKeySigner]:
"""Load ed25519 public key signers."""
if self.raw_data is None:
raise ValueError('"raw_data" is None, unable to get signers from it.')
signers = self.raw_data["signers"]
ed25519_public_key_signers = []
for signer in signers:
if signer["type"] == "ed25519_public_key":
ed25519_public_key_signers.append(
Ed25519PublicKeySigner(signer["key"], signer["weight"])
)
return ed25519_public_key_signers
@type_checked
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] | 2.385075 | 1,340 |
# -*- coding: utf-8 -*-
from .apiserver import APIServer
from .apiresponse import APIResponse
__all__ = ['APIServer', 'APIResponse']
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#!/usr/bin/env python3
#
# fix_gpiov2_gds.py ---
#
# Special-purpose script that does the work of what ought to be a simple
# binary diff and patch. Except that no such thing exists as a standard
# offering on most Linux systems, so instead of adding another OS
# package requirement, I'm just writing a binary search-and-replace in
# python.
#
# The purpose of the patch is to correct the coordinates of the deep nwell
# and nwell layers in the cell amux_switch_1v2b, as the SkyWater cell
# contains DRC errors.
#
# Specifically, DNWELL coordinate (34.450, 0.035) is moved to (34.905, 0.035)
# and NWELL coordinate (35.055, -0.365) is moved to (35.390, -0.365)
import sys
if len(sys.argv) != 2:
print('Usage: fix_gpiov2_gds.py <filename>')
sys.exit(1)
else:
file_name = sys.argv[1]
orig_data_1 = b'\x00\x00\x86\x92\x00\x00\x00\x23\x00\x00\x86\x92'
replace_data_1 = b'\x00\x00\x88\x59\x00\x00\x00\x23\x00\x00\x88\x59'
orig_data_2 = b'\x00\x00\x88\xef\xff\xff\xff\x8d\x00\x00\x47\xef\xff\xff\xff\x8d'
replace_data_2 = b'\x00\x00\x8a\x3e\x00\x00\x00\x91\x00\x00\x47\xef\x00\x00\x00\x91'
orig_data_3 = b'\x00\x00\x88\xef\xff\xff\xfe\x93\x00\x00\x88\xef\xff\xff\xff\x8d'
replace_data_3 = b'\x00\x00\x8a\x3e\xff\xff\xfe\x93\x00\x00\x8a\x3e\x00\x00\x00\x91'
# This is not efficient, but only needs to be done once.
with open(file_name, 'rb') as ifile:
data = ifile.read()
data = data.replace(orig_data_1, replace_data_1)
data = data.replace(orig_data_2, replace_data_2)
data = data.replace(orig_data_3, replace_data_3)
# Write back into the same file
with open(file_name, 'wb') as ofile:
ofile.write(data)
print("Done!")
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8,
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198,
4798,
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45677,
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8,
198
] | 2.193421 | 760 |
import math
import os
from copy import copy
from functools import lru_cache
from functools import partial
from os.path import join
import igl
import numpy as np
from numpy.linalg import norm
#
@lru_cache(maxsize=None)
@lru_cache(maxsize=None)
@lru_cache(maxsize=None)
@lru_cache()
def distort_unfold_to_imgcoord(distort_unfold, drop_NE=True):
"""
Parameters
----------
distort_unfold :
distorted unfold
drop_NE : bool
drop north and east as in [1]
References
----------
[1] orientation-aware semantic segmentation on icosahedron spheres, ICCV2019
"""
vertex_num = len(distort_unfold)
level = round(math.log((vertex_num - 2) // 10, 4))
width = 2 ** level + 1
height = 2 * width - 1
unfold_pts_set = set() # (vertex_id, x, y)
# remove duplicate
for key, arr in distort_unfold.items():
for val in arr:
unfold_pts_set.add((key, val[0], val[1]))
# sort
unfold_pts_set = sorted(unfold_pts_set, key=lambda x: (x[1], x[2]))
# to image coorinate
img_coord = {}
for (vertex_id, x, y) in unfold_pts_set:
rect_idxs = get_rect_idxs(x, y)
for key in rect_idxs:
if key not in img_coord:
img_coord[key] = []
img_coord[key].append(vertex_id)
# to numpy
for key in img_coord:
img_coord[key] = np.array(img_coord[key]).reshape(width, height).T
if drop_NE:
# orientation-aware semantic segmentation on icosahedron spheres form
for key in img_coord:
img_coord[key] = img_coord[key][1:, :-1]
return img_coord
@lru_cache()
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628,
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] | 2.282967 | 728 |
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from configuration import DATABASE_FILE
import os
import sys
# custom module imports
from src.models import Base
if not os.path.exists(os.path.dirname(DATABASE_FILE)):
print(f"[initialize_database] Creating the database dir : {os.path.dirname(DATABASE_FILE)}")
os.makedirs(os.path.dirname(DATABASE_FILE))
engine = create_engine('sqlite:///{}'.format(DATABASE_FILE), echo=True)
Session = sessionmaker(bind=engine)
session = Session()
Base.metadata.create_all(engine)
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] | 2.989189 | 185 |
from Vertex import Vertex
INF = 10**9
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1268,
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] | 2.714286 | 14 |
VOWELS = ('a', 'e', 'i', 'o', 'u', 'yt', 'xr')
CONSONANTS = ('b', 'c', 'd', 'f', 'g',
'h', 'j', 'k', 'l', 'm',
'n', 'p', 'q', 'r', 's',
't', 'v', 'w', 'x', 'y',
'z', 'sh', 'sch', 'zz', 'gh',
'ch', 'th', 'qu', 'thr',
'squ')
| [
53,
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] | 1.478469 | 209 |
import os
KHAN_BASE_URL = "http://192.168.1.2:8080" # instance used by khan mini to access API
KHAN_MINI_BASE_URL = "http://192.168.1.2:8081"
KHAN_BASE_URL2 = "http://192.168.1.2" # excluding port, which will be randomly assigned from below
KHAN_INSTANCES = [8082,8083,8084,8085,8086]
khanconf = os.path.join(os.path.dirname(__file__), 'khanmini.conf')
enlishessayconf = os.path.join(os.path.dirname(__file__), 'englishessay.conf')
current_dir = os.path.dirname(os.path.abspath(__file__))
ESSAY_DB = "mysql://ase:asep4s5@localhost/ase"
| [
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292,
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19,
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198
] | 2.237903 | 248 |
from django.contrib import admin
from django.contrib.admin.actions import delete_selected
from .models import CustomUser
from djoser import signals, utils
from djoser.compat import get_user_email
from djoser.conf import settings
make_activate.short_description = "Ativar Usuarios"
send_confirmation_email.short_description = "Enviar Email de Confirmacao"
send_resend_activation_email.short_description = "Reenviar Email de Ativação"
send_reset_password_email.short_description = "Enviar link para Troca de Senha"
block_user.short_description = "Bloquear Usuário"
# Exclui globalmente a ação de apagar selecionados
# É necessário adicionar apenas nos que quiser conforme abaixo
admin.site.disable_action('delete_selected')
delete_selected.short_description = "Apagar Selecionados"
admin.site.site_header = 'Titulo do Topo'
admin.site.index_title = 'Titulo do Index'
admin.site.site_title = 'Titulo do Site(HTML)'
admin.site.register(CustomUser, CustomUserAdmin)
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] | 3.082803 | 314 |
from flask import Flask
from flask_restful import Api
from objects import Objects
from replicate import Replicate
from restore import Restore
from object import Object
app = Flask(__name__)
api = Api(app)
api.add_resource(Objects, "/api/objects/")
api.add_resource(Replicate, "/api/replicate/<action>")
api.add_resource(Restore, "/api/restore/<server>")
api.add_resource(Object, "/api/objects/<name>")
if __name__ == "__main__":
app.run("172.26.208.232", 5000)
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1600,
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198
] | 2.974522 | 157 |
pratos = ('bolinho de bacalhau',
'francesinha',
'caldo verde',
'pastel de belém',
'feijoada')
print('Cardápio principal:')
for prato in pratos:
print(f'\t{prato.title()}')
pratos = ('arroz de forno',
'farofa crocante',
'caldo verde',
'pastel de belém',
'feijoada')
print('\nCardápio revisado:')
for prato in pratos:
print(f'\t{prato.title()}')
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83,
90,
1050,
5549,
13,
7839,
3419,
92,
11537,
198
] | 1.842553 | 235 |
# Copyright 2020 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
import json
import argparse
import config.config as pconfig
from avalon_sdk.connector.blockchains.ethereum.ethereum_work_order \
import EthereumWorkOrderProxyImpl
from avalon_sdk.connector.blockchains.ethereum.ethereum_worker_registry \
import EthereumWorkerRegistryImpl
from avalon_sdk.connector.blockchains.ethereum.ethereum_wrapper \
import EthereumWrapper
from ethereum_connector.ethereum_connector \
import EthereumConnector
import logging
# -----------------------------------------------------------------
# -----------------------------------------------------------------
TCF_HOME = os.environ.get("TCF_HOME", "../../../")
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(message)s", level=logging.INFO)
# -----------------------------------------------------------------
# -----------------------------------------------------------------
# -----------------------------------------------------------------
# -----------------------------------------------------------------
# -----------------------------------------------------------------
# -----------------------------------------------------------------
main()
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82,
1600,
1241,
28,
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13,
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8,
198,
198,
2,
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2,
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2,
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2,
16529,
12,
198,
2,
16529,
12,
628,
198,
12417,
3419,
198
] | 4.331707 | 410 |
"""
https://adventofcode.com/2017/day/6
"""
import unittest
from _2017 import d06_memreallocation
if __name__ == '__main__':
unittest.main()
| [
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from random import randint
from typing import Optional
from harvester.zerg_action import ZergAction
from sc2 import UnitTypeId
from sc2.ids.upgrade_id import UpgradeId
from sharpy.interfaces import IGameAnalyzer, IEnemyUnitsManager
from sharpy.managers.extensions.game_states import AirArmy
from sharpy.managers.extensions.game_states.advantage import at_least_disadvantage, at_least_advantage
from tactics.ml.base_agent_manager import BaseAgentManager
from tactics.ml.ml_build import MlBuild
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] | 3.413793 | 145 |
# Django
from rest_framework import serializers
# Models
from sunnysouth.marketplace.models import Category
| [
2,
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] | 3.928571 | 28 |
# Copyright 2019 Open Source Robotics Foundation, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Test parsing an include action."""
import io
from pathlib import Path
import textwrap
from launch import LaunchService
from launch.actions import IncludeLaunchDescription
from launch.frontend import Parser
from launch.launch_description_sources import AnyLaunchDescriptionSource
def test_include():
"""Parse node xml example."""
# Always use posix style paths in launch XML files.
path = (Path(__file__).parent / 'executable.xml').as_posix()
xml_file = \
"""\
<launch>
<include file="{}"/>
</launch>
""".format(path) # noqa: E501
xml_file = textwrap.dedent(xml_file)
root_entity, parser = Parser.load(io.StringIO(xml_file))
ld = parser.parse_description(root_entity)
include = ld.entities[0]
assert isinstance(include, IncludeLaunchDescription)
assert isinstance(include.launch_description_source, AnyLaunchDescriptionSource)
ls = LaunchService(debug=True)
ls.include_launch_description(ld)
assert 0 == ls.run()
if __name__ == '__main__':
test_include()
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] | 3.173333 | 525 |
"""
scrapple.utils.dynamicdispatch
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Functions related to dynamic dispatch of objects
"""
def get_command_class(command):
"""
Called from runCLI() to select the command class for the selected command.
:param command: The command to be implemented
:return: The command class corresponding to the selected command
"""
from scrapple.commands import genconfig, generate, run, web
commandMapping = {
'genconfig': genconfig,
'generate': generate,
'run': run,
'web': web
}
cmdClass = getattr(commandMapping.get(command), command.title() + 'Command')
return cmdClass
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705,
21575,
11537,
198,
220,
220,
220,
1441,
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198
] | 3.056338 | 213 |
import tasks
from . import base
from jones import FixerAPI | [
11748,
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198,
198,
6738,
764,
1330,
2779,
198,
6738,
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] | 3.6875 | 16 |
from typing import Tuple
import jax.numpy as jnp
from ase import units
from jax_md import energy
from jax_md.energy import NeighborFn
from .calculator import Calculator
from .jax_utils import EnergyFn
class LennardJones(Calculator):
"""Lennard-Jones Potential"""
implemented_properties = ["energy", "energies", "forces", "stress"]
def __init__(
self,
epsilon=1.0,
sigma=1.0,
rc=None,
ro=None,
stress=False,
dr_threshold=1 * units.Angstrom,
**kwargs
):
"""
Parameters:
sigma: The potential minimum is at 2**(1/6) * sigma, default 1.0
epsilon: The potential depth, default 1.0
rc: Cut-off for the NeighborList is set to 3 * sigma if None, the default.
ro: Onset of the cutoff function. Set to 0.8*rc if None, the default.
stress: Compute stress tensor (periodic systems only)
"""
super().__init__(**kwargs, stress=stress)
self.epsilon = epsilon
self.sigma = sigma
if rc is None:
rc = 3 * self.sigma
self.rc = rc
if ro is None:
ro = 0.8 * self.rc
self.ro = ro
self.dr_threshold = dr_threshold
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] | 2.168111 | 577 |
import numpy as np
from typing import Tuple, Callable, List, Union, cast
from typing_extensions import Protocol
import types
import torch
import pydrake.symbolic as sym
import pdb
import sympy
from sympy import Symbol, sympify, simplify, trigsimp
from functools import reduce
import operator
from enum import Enum
# string formatting literals
TORCH_ARGS = 'torch_args'
INTERMEDIATE_VARIABLE_PREFIX = 'var'
SYMPY_SYMBOL_PREFIX = 's'
# simplification settings
_simplifier_map = {
Simplifier.ALL: simplify,
Simplifier.TRIGONLY: trigsimp,
Simplifier.QUICKTRIG: lambda x: trigsimp(x, quick=True),
Simplifier.NONE: lambda x: x
}
# Convert an expression to a function in pytorch. The arguments for the
# returned function are be `x[i]`, where index `i` is derived from the
# ordering in `sym_args`. Returns [func, func_string]
#
# @param expr Either a pydrake.symbolic.Expression, or a list of expressions
# @param *sym_args The arguments to the symbolic expression. Multiple arguments
# can be provided.
#
# @return func A function object, which can be evaluated on a pytorch Tensor
# The function takes a variable number of arguments, matching the list in
# sym_args
# @return A string expressing the entire python function
# # # # # # # # # # # # # # # # # # # # # # # #
# helper functions / data for drake -> sympy #
# # # # # # # # # # # # # # # # # # # # # # # #
_constant_dict = {1.0: "1", -1.0: "-1"}
sympy_ops = {
sym.ExpressionKind.Add: sympy.Add,
sym.ExpressionKind.Mul: sympy.Mul,
sym.ExpressionKind.Div: lambda x, y: x / y,
sym.ExpressionKind.Log: sympy.log,
sym.ExpressionKind.Abs: sympy.Abs,
sym.ExpressionKind.Exp: sympy.exp,
sym.ExpressionKind.Pow: _fastpow,
sym.ExpressionKind.Sin: sympy.sin,
sym.ExpressionKind.Cos: sympy.cos,
sym.ExpressionKind.Tan: sympy.tan,
sym.ExpressionKind.Asin: sympy.asin,
sym.ExpressionKind.Acos: sympy.acos,
sym.ExpressionKind.Atan: sympy.atan,
sym.ExpressionKind.Atan2: sympy.atan2,
sym.ExpressionKind.Sinh: sympy.sinh,
sym.ExpressionKind.Cosh: sympy.cosh,
sym.ExpressionKind.Tanh: sympy.tanh,
sym.ExpressionKind.Min: sympy.Min,
sym.ExpressionKind.Max: sympy.Max,
sym.ExpressionKind.Ceil: sympy.ceiling,
sym.ExpressionKind.Floor: sympy.floor
}
# # # # # # # # # # # # # # # # # # # # # # # #
# helper functions / data for sympy -> torch #
# # # # # # # # # # # # # # # # # # # # # # # #
_torch_ops = {
sympy.Add: _reduction('+'),
sympy.Mul: _reduction('*'),
sympy.div: sympy_to_pytorch_simple_fun('div'),
sympy.log: sympy_to_pytorch_simple_fun('log'),
sympy.Abs: sympy_to_pytorch_simple_fun('abs'),
sympy.exp: sympy_to_pytorch_simple_fun('exp'),
sympy.Pow: _fastpow_string,
sympy.sin: sympy_to_pytorch_simple_fun('sin'),
sympy.cos: sympy_to_pytorch_simple_fun('cos'),
sympy.tan: sympy_to_pytorch_simple_fun('tan'),
sympy.asin: sympy_to_pytorch_simple_fun('asin'),
sympy.acos: sympy_to_pytorch_simple_fun('acos'),
sympy.atan: sympy_to_pytorch_simple_fun('atan'),
sympy.atan2: sympy_to_pytorch_simple_fun('atan2'),
sympy.sinh: sympy_to_pytorch_simple_fun('sinh'),
sympy.cosh: sympy_to_pytorch_simple_fun('cosh'),
sympy.tanh: sympy_to_pytorch_simple_fun('tanh'),
sympy.Min: sympy_to_pytorch_simple_fun('min'),
sympy.Max: sympy_to_pytorch_simple_fun('max'),
sympy.ceiling: sympy_to_pytorch_simple_fun('ceil'),
sympy.floor: sympy_to_pytorch_simple_fun('floor'),
}
# Convert a drake symbolic expression to sympy
#
# @param expr The drake expression to convert
# @param vardict Dictionary which corresponds drake variables to sympy Symbols
# @return The sympy expression
# Convert a sympy expression to a string. The arguments for the returned
# string will be `x[i]`, where index `i` is derived from the ordering
# in `sym_args`
#
# @param expr The sympy to convert
# @param memos Memoization dictionary of previously-seen expressions
# @param lines python lines which calculated memoized expressions
# @param vardict Dictionary which corresponds sympy Symbols to drake variables
# @param sym_args An ordered list of drake symbolic variables
# @return The variable name the expression is stored in to
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287,
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] | 2.628942 | 1,617 |
from Mesh.System.Entity.Function import BaseFunction
from Mesh.System.Entity.Function.Tasked import TaskName
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#!/usr/bin/env python
#
# Created on 07/11/2014 Pat Cappelaere - Vightel Corporation
#
# Output: Landsat 8 browse image
#
import os, inspect, sys
import argparse
import numpy
import scipy
import math
from scipy import ndimage
from osgeo import gdal
from osgeo import osr
from osgeo import ogr
from which import *
import config
force = 0
verbose = 0
#
# execute with verbose option
#
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Generate Landsat8 Floodmap vectors')
apg_input = parser.add_argument_group('Input')
apg_input.add_argument("-f", "--force", action='store_true', help="Forces new product to be generated")
apg_input.add_argument("-v", "--verbose", action='store_true', help="Verbose on/off")
apg_input.add_argument("-s", "--scene", help="Landsat Scene")
options = parser.parse_args()
force = options.force
verbose = options.verbose
scene = options.scene
outdir = os.path.join(config.LANDSAT8_DIR,scene)
app = Landsat8(outdir, scene)
app.process() | [
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] | 2.693717 | 382 |
nome = input('Digite seu nome: ').upper()
print(f'Seu nome possui {nome.count("A")} letra A')
print(f'O primeiro A está na posição {nome.find("A")+1}')
print(f'O último A está na posição {nome.rfind("A")+1}') | [
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import asyncio
import datetime
import logging
import pykube
import requests
from kopf import config
from kopf.clients import auth
from kopf.structs import hierarchies
logger = logging.getLogger(__name__)
MAX_MESSAGE_LENGTH = 1024
CUT_MESSAGE_INFIX = '...'
async def post_event(*, obj=None, ref=None, type, reason, message=''):
"""
Issue an event for the object.
This is where they can also be accumulated, aggregated, grouped,
and where the rate-limits should be maintained. It can (and should)
be done by the client library, as it is done in the Go client.
"""
# Object reference - similar to the owner reference, but different.
if obj is not None and ref is not None:
raise TypeError("Only one of obj= and ref= is allowed for a posted event. Got both.")
if obj is None and ref is None:
raise TypeError("One of obj= and ref= is required for a posted event. Got none.")
if ref is None:
ref = hierarchies.build_object_reference(obj)
now = datetime.datetime.utcnow()
# See #164. For cluster-scoped objects, use the current namespace from the current context.
# It could be "default", but in some systems, we are limited to one specific namespace only.
namespace = ref.get('namespace') or auth.get_pykube_cfg().namespace
if not ref.get('namespace'):
ref = dict(ref, namespace=namespace)
# Prevent a common case of event posting errors but shortening the message.
if len(message) > MAX_MESSAGE_LENGTH:
infix = CUT_MESSAGE_INFIX
prefix = message[:MAX_MESSAGE_LENGTH // 2 - (len(infix) // 2)]
suffix = message[-MAX_MESSAGE_LENGTH // 2 + (len(infix) - len(infix) // 2):]
message = f'{prefix}{infix}{suffix}'
body = {
'metadata': {
'namespace': namespace,
'generateName': 'kopf-event-',
},
'action': 'Action?',
'type': type,
'reason': reason,
'message': message,
'reportingComponent': 'kopf',
'reportingInstance': 'dev',
'source' : {'component': 'kopf'}, # used in the "From" column in `kubectl describe`.
'involvedObject': ref,
'firstTimestamp': now.isoformat() + 'Z', # '2019-01-28T18:25:03.000000Z' -- seen in `kubectl describe ...`
'lastTimestamp': now.isoformat() + 'Z', # '2019-01-28T18:25:03.000000Z' - seen in `kubectl get events`
'eventTime': now.isoformat() + 'Z', # '2019-01-28T18:25:03.000000Z'
}
try:
api = auth.get_pykube_api()
obj = pykube.Event(api, body)
loop = asyncio.get_running_loop()
await loop.run_in_executor(config.WorkersConfig.get_syn_executor(), obj.create)
except (requests.exceptions.HTTPError, pykube.exceptions.HTTPError) as e:
# Events are helpful but auxiliary, they should not fail the handling cycle.
# Yet we want to notice that something went wrong (in logs).
logger.warning("Failed to post an event. Ignoring and continuing. "
f"Error: {e!r}. "
f"Event: type={type!r}, reason={reason!r}, message={message!r}.")
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277,
1,
9237,
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0,
81,
5512,
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20500,
0,
81,
92,
19570,
198
] | 2.522472 | 1,246 |
# coding: utf-8
from __future__ import division, print_function, absolute_import
import pkg_resources
__version__ = pkg_resources.get_distribution('pypcl').version
from pypcl.common import *
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from . import main
from flask import render_template,abort
from flask_login import login_required
from ..models import User,Blog
from app.request import get_quote
@main.route('/')
@main.route('/user/<jina>',methods=['GET','POST'])
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# lambda 는 1줄 함수.
# lambda argument: manipulate(argument)
# ex
add = lambda x, y: x + y
print(add(2,4))
# sort
a = [(1,2), (4,1), (9,10), (13,-3)]
a.sort(key = lambda x:x[1])
print(a)
# 병렬로 sort list
list1 = [1,2,3,4,5]
list2 = [9,8,5,3,1]
data = list(zip(list1, list2))
print(data)
data.sort()
list1, list2 = map(lambda t: list(t), zip(*data))
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import torch
import torch.nn as nn
import torch.nn.functional as F
class TripletLoss(object):
"""Modified from Tong Xiao's open-reid (https://github.com/Cysu/open-reid).
Related Triplet Loss theory can be found in paper 'In Defense of the Triplet
Loss for Person Re-Identification'."""
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628,
628
] | 3.122449 | 98 |
#!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Stub version of the Channel API, queues messages and writes them to a log."""
import hashlib
import logging
import random
import time
from google.appengine.api import apiproxy_stub
from google.appengine.api.channel import channel_service_pb
from google.appengine.runtime import apiproxy_errors
def _GenerateTokenHash(token):
"""Returns a MD5 hash of a token for integrity checking."""
return hashlib.md5(token).hexdigest()
class InvalidTokenError(Error):
"""A stub method was called with a syntactically invalid token."""
pass
class TokenTimedOutError(Error):
"""A stub method was called with a token that has expired or never existed."""
pass
class ChannelServiceStub(apiproxy_stub.APIProxyStub):
"""Python only channel service stub.
This stub does not use a browser channel to push messages to a client.
Instead it queues messages internally.
"""
THREADSAFE = True
CHANNEL_TIMEOUT_SECONDS = 2
XMPP_PUBLIC_IP = '0.1.0.10'
CHANNEL_TOKEN_DEFAULT_DURATION = 120
CHANNEL_TOKEN_IDENTIFIER = 'channel'
def __init__(self, log=logging.debug, service_name='channel',
time_func=time.time, request_data=None):
"""Initializer.
Args:
log: A logger, used for dependency injection.
service_name: Service name expected for all calls.
time_func: function to get the current time in seconds.
request_data: A request_info.RequestInfo instance. If None, a
request_info._LocalRequestInfo instance will be used.
"""
apiproxy_stub.APIProxyStub.__init__(self, service_name,
request_data=request_data)
self._log = log
self._time_func = time_func
self._connected_channel_messages = {}
def _Dynamic_CreateChannel(self, request, response):
"""Implementation of channel.create_channel.
Args:
request: A ChannelServiceRequest.
response: A ChannelServiceResponse
"""
client_id = request.application_key()
if not client_id:
raise apiproxy_errors.ApplicationError(
channel_service_pb.ChannelServiceError.INVALID_CHANNEL_KEY)
if request.has_duration_minutes():
duration = request.duration_minutes()
else:
duration = ChannelServiceStub.CHANNEL_TOKEN_DEFAULT_DURATION
expiration_sec = long(self._time_func() + duration * 60) + 1
raw_token = '-'.join([ChannelServiceStub.CHANNEL_TOKEN_IDENTIFIER,
str(random.randint(0, 2 ** 32)),
str(expiration_sec),
client_id])
token = '-'.join([_GenerateTokenHash(raw_token), raw_token])
self._log('Creating channel token %s with client id %s and duration %s',
token, request.application_key(), duration)
response.set_token(token)
@apiproxy_stub.Synchronized
def _Dynamic_SendChannelMessage(self, request, response):
"""Implementation of channel.send_message.
Queues a message to be retrieved by the client when it polls.
Args:
request: A SendMessageRequest.
response: A VoidProto.
"""
client_id = self.client_id_from_token(request.application_key())
if client_id is None:
client_id = request.application_key()
if not request.message():
raise apiproxy_errors.ApplicationError(
channel_service_pb.ChannelServiceError.BAD_MESSAGE)
if client_id in self._connected_channel_messages:
self._log('Sending a message (%s) to channel with key (%s)',
request.message(), client_id)
self._connected_channel_messages[client_id].append(request.message())
else:
self._log('SKIPPING message (%s) to channel with key (%s): '
'no clients connected',
request.message(), client_id)
def client_id_from_token(self, token):
"""Returns the client id from a given token.
Args:
token: A string representing an instance of a client connection to a
client id, returned by CreateChannel.
Returns:
A string representing the client id used to create this token,
or None if this token is incorrectly formed and doesn't map to a
client id.
"""
try:
return self.validate_token_and_extract_client_id(token)
except (InvalidTokenError, TokenTimedOutError):
return None
def validate_token_and_extract_client_id(self, token):
"""Ensures token is well-formed and hasn't expired, and extracts client_id.
Args:
token: a token returned by CreateChannel.
Returns:
A client_id, which is the value passed to CreateChannel.
Raises:
InvalidTokenError: The token is syntactically invalid.
TokenTimedOutError: The token expired or does not exist.
"""
pieces = token.split('-', 1)
if len(pieces) != 2 or _GenerateTokenHash(pieces[1]) != pieces[0]:
raise InvalidTokenError()
raw_token = pieces[1]
pieces = raw_token.split('-', 3)
if len(pieces) != 4:
raise InvalidTokenError()
constant_id, unused_random_id, expiration_sec, client_id = pieces
if (constant_id != ChannelServiceStub.CHANNEL_TOKEN_IDENTIFIER
or not expiration_sec.isdigit()):
raise InvalidTokenError()
if long(expiration_sec) <= self._time_func():
raise TokenTimedOutError()
return client_id
@apiproxy_stub.Synchronized
def get_channel_messages(self, token):
"""Returns the pending messages for a given channel.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
Returns:
List of messages, or None if the channel doesn't exist. The messages are
strings.
"""
self._log('Received request for messages for channel: ' + token)
client_id = self.client_id_from_token(token)
if client_id in self._connected_channel_messages:
return self._connected_channel_messages[client_id]
return None
@apiproxy_stub.Synchronized
def has_channel_messages(self, token):
"""Checks to see if the given channel has any pending messages.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
Returns:
True if the channel exists and has pending messages.
"""
client_id = self.client_id_from_token(token)
has_messages = (client_id in self._connected_channel_messages and
bool(self._connected_channel_messages[client_id]))
self._log('Checking for messages on channel (%s) (%s)',
token, has_messages)
return has_messages
@apiproxy_stub.Synchronized
def pop_first_message(self, token):
"""Returns and clears the first message from the message queue.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
Returns:
The first message in the queue (a string), or None if no messages.
"""
if self.has_channel_messages(token):
client_id = self.client_id_from_token(token)
self._log('Popping first message of queue for channel (%s)', token)
return self._connected_channel_messages[client_id].pop(0)
return None
@apiproxy_stub.Synchronized
def clear_channel_messages(self, token):
"""Clears all messages from the channel.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
"""
client_id = self.client_id_from_token(token)
if client_id:
self._log('Clearing messages on channel (' + client_id + ')')
if client_id in self._connected_channel_messages:
self._connected_channel_messages[client_id] = []
else:
self._log('Ignoring clear messages for nonexistent token (' +
token + ')')
def add_connect_event(self, client_id):
"""Tell the application that the client has connected."""
self.request_data.get_dispatcher().add_async_request(
'POST', '/_ah/channel/connected/',
[('Content-Type', 'application/x-www-form-urlencoded')],
'from=%s' % client_id,
ChannelServiceStub.XMPP_PUBLIC_IP)
@apiproxy_stub.Synchronized
def disconnect_channel_event(self, client_id):
"""Removes the channel from the list of connected channels."""
self._log('Removing channel %s', client_id)
if client_id in self._connected_channel_messages:
del self._connected_channel_messages[client_id]
self.request_data.get_dispatcher().add_async_request(
'POST', '/_ah/channel/disconnected/',
[('Content-Type', 'application/x-www-form-urlencoded')],
'from=%s' % client_id,
ChannelServiceStub.XMPP_PUBLIC_IP)
def add_disconnect_event(self, client_id):
"""Add an event to notify the app if a client has disconnected.
Args:
client_id: A client ID used for a particular channel.
"""
timeout = self._time_func() + ChannelServiceStub.CHANNEL_TIMEOUT_SECONDS
self.request_data.get_dispatcher().add_event(
DefineDisconnectCallback(client_id), timeout, 'channel-disconnect',
client_id)
@apiproxy_stub.Synchronized
def connect_channel(self, token):
"""Marks the channel identified by the token (token) as connected.
If the channel has not yet been connected, this triggers a connection event
to let the application know that the channel has been connected to.
If the channel has already been connected, this refreshes the channel's
timeout so that it will not disconnect. This should be done at regular
intervals to avoid automatic disconnection.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
Raises:
InvalidTokenError: The token is syntactically invalid.
TokenTimedOutError: The token expired or does not exist.
"""
client_id = self.validate_token_and_extract_client_id(token)
if client_id in self._connected_channel_messages:
timeout = self._time_func() + ChannelServiceStub.CHANNEL_TIMEOUT_SECONDS
self.request_data.get_dispatcher().update_event(
timeout, 'channel-disconnect', client_id)
return
self._connected_channel_messages[client_id] = []
self.add_connect_event(client_id)
self.add_disconnect_event(client_id)
@apiproxy_stub.Synchronized
def connect_and_pop_first_message(self, token):
"""Atomically performs a connect_channel and a pop_first_message.
This is designed to be called after the channel has already been connected,
so that it refreshes the channel's timeout, and retrieves a message, in a
single atomic operation.
Args:
token: A string representing the channel. Note that this is the token
returned by CreateChannel, not the client id.
Returns:
The first message in the queue (a string), or None if no messages.
Raises:
InvalidTokenError: The token is syntactically invalid.
TokenTimedOutError: The token expired or does not exist.
"""
self.connect_channel(token)
return self.pop_first_message(token)
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] | 2.819332 | 4,190 |
from eax import gf_double, xorstrings
# these classes simulate the way it could be done in C in online mode, byte by byte
# wrappers for the online stream api to test it
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import setuptools
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setuptools.setup(
name="body-mass-index",
version="1.0.1",
author="Romen Rodriguez-Gil",
author_email="[email protected]",
description="Utilities related to the Body Mass Index (BMI): Calculating it, calculating healthy weight, ranges, " +
"boundaries,...",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/romenrg/body-mass-index",
packages=setuptools.find_packages(),
include_package_data=True,
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
python_requires='>=3.6',
)
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] | 2.635484 | 310 |
from db.models import Trade, Asset
ass1 = Asset(name="Algo", asset_id="0", network="mainnet")
ass2 = Asset(name="Choice", asset_id="297995609", network="mainnet")
ass1.save()
ass2.save()
trade = Trade(
wallet_address="Replace With Address",
asset1=ass1,
asset2=ass2,
asset_in=ass2,
asset_in_amount=10,
slippage=0.5,
min_sell_price=0.003,
do_redeem=False,
network="mainnet"
)
trade.save() | [
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220,
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220,
1267,
198,
198,
25351,
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] | 2.317204 | 186 |
"""This example changes the fill, brightness, blink rates,
shows number and text printing, displays a counter
and then shows off the new marquee features."""
from time import sleep
from adafruit_featherwing import alphanum_featherwing
display = alphanum_featherwing.AlphaNumFeatherWing()
#Fill and empty all segments
for count in range(0, 3):
display.fill(True)
sleep(0.5)
display.fill(False)
sleep(0.5)
#Display a number and text
display.print(1234)
sleep(1)
display.print('Text')
#Change brightness
for brightness in range(0, 16):
display.brightness = brightness
sleep(0.1)
#Change blink rate
for blink_rate in range(3, 0, -1):
display.blink_rate = blink_rate
sleep(4)
display.blink_rate = 0
#Show a counter using decimals
count = 975.0
while count < 1025:
count += 1
display.print(count)
sleep(0.1)
#Show the Marquee
display.marquee('This is a really long message!!! ', 0.2)
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890,
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] | 2.855828 | 326 |
import argparse
import numpy as np
import os
import torch
from torch import nn
from torch.autograd import Variable
from torch.backends import cudnn
from torch.utils import data
from utils.mpnet import MPNet
from utils.plan_class import plan_dataset
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--path', type=str, default='/scratch/rkm350/mpnet/dataset',
help='location of dataset directory')
parser.add_argument('--num_epochs', type=int, default=100, help='number of epochs')
parser.add_argument('--batch_size', type=int, default=32, help='batch size')
parser.add_argument('--learning_rate', type=float, default=0.001, help='Learning rate')
parser.add_argument('--num_files', type=int, default=10000, help='num of files')
parser.add_argument('--num_workers', type=int, default=6, help='number of sub processes for loading data')
parser.add_argument('--lam', type=float, default=0.001, help='lambda value for the CAE network')
parser.add_argument('--cuda', type=str, default='cuda', help='Cuda for processing the network')
args = parser.parse_args()
main(args)
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] | 2.912935 | 402 |
from django.shortcuts import render, HttpResponse, HttpResponseRedirect
# importing calculators
from .calculatorDilution import DilutionForm
from .calculatorDilution import *
from .calculatorPCR import PCRForm
from .calculatorPCR import *
from .calculatorUnitConvert import ConversionForm
from .calculatorUnitConvert import *
from .calculatorCuttingReaction import CuttingEdgeForm
from .calculatorCuttingReaction import *
from .opentrons import RandomNumGenerator
from .opentrons import *
# from .models import Person
import time
# Create your views here.
# CALCULATORS
# DILUTION CALCULATOR
# GLOBAL VARIABLES
INPUTVOL = None
INPUTCONC = None
INPUTSOLUTE = None
FINALVOL = None
FINALCONC = None
ADDEDSOLUTE = None
ADDEDWATER = None
MOLARMASS = None
# PCR CALCULATOR
# GLOBAL VARIABLES
RESULTtotalVol = None
RESULTwaterVol = None
RESULTPCRBufferVol = None
RESULTPCRBufferInitConc = None
RESULTPCRBufferFinalConc = None
RESULTpolymeraseVol = None
RESULTpolymeraseConc = None
RESULTdNTPVol = None
RESULTdNTPConc = None
RESULTMgCl2Vol = None
RESULTMgCl2Conc = None
RESULTforwardPrimerVol = None
RESULTforwardPrimerConc = None
RESULTbackwardPrimerVol = None
RESULTbackwardPrimerConc = None
RESULTtemplateDNAVol = None
RESULTtemplateDNAConc = None
RESULTDMSOOptionalVol = None
RESULTDMSOOptionalConc = None
ERRORMSG = ""
# UNIT CONVERSION CALCULATOR
# GLOBAL VARIABLES
INPUTVALUE = None
INPUTUNIT = None
OUTPUTVALUE = None
OUTPUTUNIT = None
MOLARMASS = None
ERROR = False
######################################## CUTTING REACTION CALCULATOR #######################################
# GLOBAL VARIABLES
TOTALVOL = None
TEMPLATEDNAVOL = None
TEMPLATEDNAINITCONC = None
TEMPLATEDNAFINALMASS = None
BUFFERVOL = None
BUFFERCONC = None
RESTRICTIONENZYMEVOL = None
RESTRICTIONENZYMECONC = None
WATERVOL = None
ERRORMSG = ""
# totalVol = cuttingform.cleaned_data['TOTALVOL']
# templateDNAVol = cuttingform.cleaned_data['templateDNAVol']
# templateDNAInitConc = cuttingform.cleaned_data['templateDNAInitConc']
# templateDNAFinalMass = cuttingform.cleaned_data['templateDNAFinalMass']
# bufferVol = cuttingform.cleaned_data['bufferVol']
# bufferConc = cuttingform.cleaned_data['bufferConc']
# restrictionEnzymeVol = cuttingform.cleaned_data['restrictionEnzymeVol']
# restrictionEnzymeConc = cuttingform.cleaned_data['restrictionEnzymeConc']
# TODO: Define global variables --> Work on the results page
######################################## AR OPENTRONS CALCULATOR #######################################
# global variable
FLOOR = None
CEILING = None
OPENTRONS_RESULT = None
# ####### TRIAL DEPENDENT DROPDOWN AAA AAAA #########
# from django.views.generic import ListView, CreateView, UpdateView
# from django.urls import reverse_lazy
# class PersonListView(ListView):
# model = Person
# context_object_name = 'people'
# class PersonCreateView(CreateView):
# model = Person
# form_class = PersonForm
# success_url = reverse_lazy('person_changelist')
# class PersonUpdateView(UpdateView):
# model = Person
# form_class = PersonForm
# success_url = reverse_lazy('person_changelist')
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] | 2.854867 | 1,130 |
# scrapes Townes van Zandt lyrics
# sample code so I don't have to remember all of this stuff
# the next time I want to source some verses
from bs4 import BeautifulSoup as soup
import requests
import string
punctuation_trans_table = str.maketrans("", "", string.punctuation)
base_url = "http://ippc2.orst.edu/coopl/lyrics/"
index = requests.get(base_url + "albums.html")
parsed_index = soup(index.text)
all_links = parsed_index.find_all("a") # get all <a> tags
links = [l for l in all_links if l.text] # filter out image links
def to_filename(s, path="texts/townes_van_zandt/"):
'''Quick and dirty snake-casing'''
s = s.replace("&", "and") # special case, "Poncho & Lefty"
s = strip_punctuation(s)
s = s.lower()
s = s.replace(" ", "_")
s = path + s + ".txt"
return s
| [
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264,
1343,
27071,
14116,
1,
198,
220,
220,
220,
1441,
264,
628
] | 2.634304 | 309 |
from django.core import management
from django.core.management.base import BaseCommand
| [
6738,
42625,
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13,
7295,
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201,
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13,
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1330,
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198,
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] | 3.64 | 25 |
"""
Display all visible SSIDs
"""
import NetworkManager
for dev in NetworkManager.NetworkManager.GetDevices():
if dev.DeviceType != NetworkManager.NM_DEVICE_TYPE_WIFI:
continue
for ap in dev.GetAccessPoints():
print('%-30s %dMHz %d%%' % (ap.Ssid, ap.Frequency, ap.Strength))
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15457,
40710,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
33963,
1270,
82,
4064,
67,
25983,
4064,
67,
16626,
6,
4064,
357,
499,
13,
50,
30255,
11,
2471,
13,
37,
28707,
11,
2471,
13,
45027,
4008,
198
] | 2.6875 | 112 |
import requests
import time
import csv
import sys
from itertools import groupby
import Utils
# ====================================================================
# **Description**
# This script takes the list of train stations we found on wikipedia
# --> Extracts: train station number, train station name, train station category
# --> Calls the db-stations API to recieve:
# --> GeoJSON (Point) [longitude, latitude] for every train station
# --> Saves the successfull recieved data in a new .csv file
# --> Saves the train stations where the request failed in a new .csv file
# (Depending on the size of the failed request, repeat the steps)
# read train stations from csv file (where data begins in second row)
# function to handle the api call and save the data
#utility function to quickly check if all values of the array are equal
# function to handle the auth tokens
# array with the important station data
stations = read_station("/home/bigdata/db-ripper/misc/Mappe1.csv")
# the URL for db API requests regarding train station data
base_request_string = "https://api.deutschebahn.com/stada/v2/stations/"
# the array of successfull collected train station data
resultArr = []
# the array of unsuccessfull collected train station data
failArr = []
# the array of auth tokens that are subscribed to the db-api stations
tokenArr = Utils.tokens_timetable_parking
# the array of headers needed for the request containing the auth tokens
headers_arr = []
for token in tokenArr:
header = {'Accept': 'application/json', 'Authorization': token}
headers_arr.append(header)
# the array of counters for each auth token, to make sure every auth token is only used n-times before
# the next token has to be used, if all tokens have been used n-times the loop needs to sleep to garant access
counter_arr = []
for i in range(30):
counter_arr.append(0)
# work
compute_geo_data(stations, base_request_string, headers_arr,
resultArr, failArr, counter_arr=counter_arr)
#write successes data in a new file 'test_table_result.csv'
with open("/home/bigdata/db-ripper/misc/test_table_result.csv", "w", newline='', encoding='utf-8') as resultfile:
writer = csv.writer(resultfile)
for result in resultArr:
writer.writerow(result)
#write failures in a new file 'test_table_fail.csv'
with open("/home/bigdata/db-ripper/misc/test_table_fail.csv", "w", newline='', encoding='utf-8') as failfile:
writer = csv.writer(failfile)
for fail in failArr:
writer.writerow(fail)
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6260,
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322,
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198
] | 3.335535 | 757 |
#! /usr/bin/env python
import glob
import time
import torch
import click
import os.path
import random
import logging
import pathlib
import datetime
import numpy as np
import torchvision.transforms as tf
from PIL import Image, ImageDraw
from pathlib import Path
from rich.logging import RichHandler
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import ModelCheckpoint, StochasticWeightAveraging
from curt.models import CurtCurveModel, MaskedCurtCurveModel
from curt.dataset import CurveDataModule
from curt.progress import KrakenTrainProgressBar
from curt.util.misc import NestedTensor
from curt.transforms import BezierCoeff
# raise default max image size to 20k * 20k pixels
Image.MAX_IMAGE_PIXELS = 20000 ** 2
logging.captureWarnings(True)
logger = logging.getLogger()
torch.multiprocessing.set_sharing_strategy('file_system')
def _validate_merging(ctx, param, value):
"""
Maps baseline/region merging to a dict of merge structures.
"""
if not value:
return None
merge_dict = {}
try:
for m in value:
k, v = m.split(':')
merge_dict[v] = k # type: ignore
except Exception:
raise click.BadParameter('Mappings must be in format target:src')
return merge_dict
@click.group()
@click.pass_context
@click.option('-v', '--verbose', default=0, count=True)
@click.option('-s', '--seed', default=None, type=click.INT,
help='Seed for numpy\'s and torch\'s RNG. Set to a fixed value to '
'ensure reproducible random splits of data')
@cli.command('polytrain')
@click.pass_context
@click.option('--precision', default='32', type=click.Choice(['64', '32', '16', 'bf16']), help='set tensor precision')
@click.option('-lr', '--learning-rate', default=0.0006, help='Learning rate')
@click.option('-blr', '--backbone-learning-rate', default=0.00006, help='Learning rate')
@click.option('-B', '--batch-size', default=1, help='Batch size')
@click.option('-w', '--weight-decay', default=0.01, help='Weight decay in optimizer')
@click.option('-N', '--epochs', default=25, help='Number of epochs to train for')
@click.option('-F', '--freq', show_default=True, default=1.0, type=click.FLOAT,
help='Model saving and report generation frequency in epochs '
'during training. If frequency is >1 it must be an integer, '
'i.e. running validation every n-th epoch.')
@click.option('-lr-drop', '--lr-drop', default=15, help='Reduction factor of learning rate over time')
@click.option('--dropout', default=0.1, help='Dropout applied in the transformer')
@click.option('--match-cost-class', default=1.0, help='Class coefficient in the matching cost')
@click.option('--match-cost-curve', default=5.0, help='L1 curve coefficient in the matching cost')
@click.option('--curve-loss-coef', default=5.0, help='L1 curve coefficient in the loss')
@click.option('--eos-coef', default=0.1, help='Relative classification weight of the no-object class')
@click.option('--mask-loss-coef', default=1.0, help='Mask loss coefficient')
@click.option('--dice-loss-coef', default=1.0, help='Mask dice loss coefficient')
@click.option('-i', '--load', show_default=True, type=click.Path(exists=True, readable=True), help='Load existing file to continue training')
@click.option('-o', '--output', show_default=True, type=click.Path(), default='curt_model', help='Pytorch lightning output directory')
@click.option('-p', '--partition', show_default=True, default=0.9,
help='Ground truth data partition ratio between train/validation set')
@click.option('-t', '--training-files', show_default=True, default=None, multiple=True,
callback=_validate_manifests, type=click.File(mode='r', lazy=True),
help='File(s) with additional paths to training data')
@click.option('-e', '--evaluation-files', show_default=True, default=None, multiple=True,
callback=_validate_manifests, type=click.File(mode='r', lazy=True),
help='File(s) with paths to evaluation data. Overrides the `-p` parameter')
@click.option('-vb', '--valid-baselines', show_default=True, default=None, multiple=True,
help='Valid baseline types in training data. May be used multiple times.')
@click.option('-mb',
'--merge-baselines',
show_default=True,
default=None,
help='Baseline type merge mapping. Same syntax as `--merge-regions`',
multiple=True,
callback=_validate_merging)
@click.option('--merge-all-baselines/--no-merge-baselines',
show_default=True,
default=False,
help='Merge all baseline types into `default`')
@click.option('--workers', show_default=True, default=2, help='Number of data loader workers.')
@click.option('-d', '--device', show_default=True, default='1', help='Select device to use (1, ...)')
@click.argument('ground_truth', nargs=-1, callback=_expand_gt, type=click.Path(exists=False, dir_okay=False))
@cli.command('train')
@click.pass_context
@click.option('--precision', default='32', type=click.Choice(['64', '32', '16', 'bf16']), help='set tensor precision')
@click.option('-lr', '--learning-rate', default=1e-4, help='Learning rate')
@click.option('-blr', '--backbone-learning-rate', default=1e-4, help='Learning rate')
@click.option('-B', '--batch-size', default=1, help='Batch size')
@click.option('-w', '--weight-decay', default=1e-4, help='Weight decay in optimizer')
@click.option('-N', '--epochs', default=300, help='Number of epochs to train for')
@click.option('-F', '--freq', show_default=True, default=1.0, type=click.FLOAT,
help='Model saving and report generation frequency in epochs '
'during training. If frequency is >1 it must be an integer, '
'i.e. running validation every n-th epoch.')
@click.option('-lr-drop', '--lr-drop', default=200, help='Reduction factor of learning rate over time')
@click.option('--encoder', default='mit_b0', type=click.Choice(['mit_b0', 'mit_b1', 'mit_b2', 'mit_b3', 'mit_b4', 'mit_b5']), help='Encoding max transformers architecture')
@click.option('-dl', '--decoder-layers', default=3, help='Number of decoder layers in the transformer')
@click.option('-dff', '--dim-ff', default=2048, help='Intermediate size of the feedforward layers in the transformer block')
@click.option('-edd', '--embedding-dim', default=256, help='Size of the embeddings (dimension of the transformer')
@click.option('--dropout', default=0.1, help='Dropout applied in the transformer')
@click.option('-nh', '--num-heads', default=8, help="Number of attention heads inside the transformer's attentions")
@click.option('-nq', '--num-queries', default=500, help='Number of query slots (#lines + #regions detectable in an image)')
@click.option('--match-cost-class', default=1.0, help='Class coefficient in the matching cost')
@click.option('--match-cost-curve', default=5.0, help='L1 curve coefficient in the matching cost')
@click.option('--curve-loss-coef', default=5.0, help='L1 curve coefficient in the loss')
@click.option('--eos-coef', default=0.1, help='Relative classification weight of the no-object class')
@click.option('-i', '--load', show_default=True, type=click.Path(exists=True, readable=True), help='Load existing file to continue training')
@click.option('-o', '--output', show_default=True, type=click.Path(), default='curt_model', help='Pytorch lightning output directory')
@click.option('-p', '--partition', show_default=True, default=0.9,
help='Ground truth data partition ratio between train/validation set')
@click.option('-t', '--training-files', show_default=True, default=None, multiple=True,
callback=_validate_manifests, type=click.File(mode='r', lazy=True),
help='File(s) with additional paths to training data')
@click.option('-e', '--evaluation-files', show_default=True, default=None, multiple=True,
callback=_validate_manifests, type=click.File(mode='r', lazy=True),
help='File(s) with paths to evaluation data. Overrides the `-p` parameter')
@click.option('-vb', '--valid-baselines', show_default=True, default=None, multiple=True,
help='Valid baseline types in training data. May be used multiple times.')
@click.option('-mb',
'--merge-baselines',
show_default=True,
default=None,
help='Baseline type merge mapping. Same syntax as `--merge-regions`',
multiple=True,
callback=_validate_merging)
@click.option('--merge-all-baselines/--no-merge-baselines',
show_default=True,
default=False,
help='Merge all baseline types into `default`')
@click.option('--set-matcher/--dummy-matcher', show_default=True, default=True, help='Use the set criterion or dummy matching.')
@click.option('--aux-loss/--no-aux-loss', show_default=True, default=True, help='Enable auxiliary losses in decoder.')
@click.option('--workers', show_default=True, default=2, help='Number of data loader workers.')
@click.option('-d', '--device', show_default=True, default='1', help='Select device to use')
@click.argument('ground_truth', nargs=-1, callback=_expand_gt, type=click.Path(exists=False, dir_okay=False))
@cli.command('pred')
@click.pass_context
@click.option('-i', '--load', help='Input model')
@click.option('-o', '--suffix', default='.overlay.png', show_default=True, help='Suffix for output files')
@click.option('-t', '--threshold', default=0.9, show_default=True, help='Minimum score for objectness')
@click.option('-d', '--device', show_default=True, default='cpu', help='Select device to use (cpu, cuda:0, cuda:1, ...)')
@click.argument('input_files', nargs=-1, callback=_expand_gt, type=click.Path(exists=False, dir_okay=False))
if __name__ == '__main__':
cli()
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] | 2.740956 | 3,621 |
from django.db import models
# Create your models here.
| [
6738,
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14208,
13,
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4981,
198,
198,
2,
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534,
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] | 3.5625 | 16 |
# -*- coding: utf-8 -*-
import argparse
import os
import re
import shutil
import zipfile
parser = argparse.ArgumentParser()
parser.add_argument('directory', type=str, nargs=1)
group = parser.add_mutually_exclusive_group(required = True)
group.add_argument('--extract', action='store_true')
group.add_argument('--compress', action='store_true')
args = parser.parse_args()
for root, dirs, files in os.walk(args.directory[0]):
if args.extract:
for f in files:
if re.match(r".+\.(zip|stromx)", f):
path = os.path.join(root, f)
try:
with zipfile.ZipFile(path, 'r') as archive:
dirname = "{0}.extracted".format(f)
dirpath = os.path.join(root, dirname)
os.mkdir(dirpath)
archive.extractall(dirpath)
print "Created {0}".format(dirpath)
except zipfile.BadZipfile:
print "Failed to open {0}".format(path)
else:
for d in dirs:
if re.match(r".+\.(zip|stromx).extracted", d):
f = d[:-len(".extracted")]
filePath = os.path.join(root, f)
dirPath = os.path.join(root, d)
with zipfile.ZipFile(filePath, 'w') as archive:
for member in os.listdir(dirPath):
memberPath = os.path.join(root, d, member)
archive.write(memberPath, member)
shutil.rmtree(dirPath)
print "Created {0}".format(filePath) | [
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"""TESTING STRATEGY
Function: generate(self)
1. Ensure the correct # of problems are generated.
2. Generated problems are of proper type
3. Ensure prediction problems are generated in order of
Filter->Row->Transformation->Aggregation
"""
import unittest
import pandas as pd
from mock import MagicMock, call, patch
from trane.core.prediction_problem_generator import PredictionProblemGenerator
from trane.ops.aggregation_ops import * # noqa
from trane.ops.filter_ops import * # noqa
from trane.ops.row_ops import * # noqa
from trane.ops.transformation_ops import * # noqa
from trane.utils.table_meta import TableMeta
class TestPredictionProblemGeneratorValidation(unittest.TestCase):
'''
TestPredictionProblemGeneratorValidation has its own class, because unlike
other tests, the ensure_valid_inputs method cannot be mocked out.
'''
def create_patch(self, name, return_value=None):
'''helper method for creating patches'''
patcher = patch(name)
thing = patcher.start()
self.addCleanup(patcher.stop)
if return_value:
thing.return_value = return_value
return thing
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"""The |pydwf.core.api.digital_spi| module implements a single class: |DigitalSpi|."""
from typing import List
from pydwf.core.dwf_device_subapi import AbstractDwfDeviceSubApi
from pydwf.core.auxiliary.typespec_ctypes import typespec_ctypes
from pydwf.core.auxiliary.constants import RESULT_SUCCESS
from pydwf.core.auxiliary.enum_types import DwfDigitalOutIdle
class DigitalSpi(AbstractDwfDeviceSubApi):
"""The |DigitalSpi| class provides access to the SPI protocol functionality of a |DwfDevice:link|.
Attention:
Users of |pydwf| should not create instances of this class directly.
It is instantiated during initialization of a |DwfDevice| and subsequently assigned to its public
|digitalSpi:link| attribute for access by the user.
"""
def reset(self) -> None:
"""Reset the SPI protocol support.
Raises:
DwfLibraryError: An error occurred while executing the *reset* operation.
"""
result = self.lib.FDwfDigitalSpiReset(self.hdwf)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def frequencySet(self, frequency: float) -> None:
"""Set the SPI frequency, in Hz.
Parameters:
frequency (float): SPI frequency, in Hz.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiFrequencySet(self.hdwf, frequency)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def clockSet(self, channel_index: int) -> None:
"""Set the digital channel (pin) for the SPI clock signal.
Parameters:
channel_index (int):
The digital channel (pin) where the SPI clock signal will be generated.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiClockSet(self.hdwf, channel_index)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def dataSet(self, spi_data_bit: int, channel_index: int) -> None:
"""Set the digital channel (pin) for an SPI data bit.
Parameters:
spi_data_bit (int):
The data bit to configure:
* 0 — DQ0 / MOSI / SISO
* 1 — DQ1 / MISO
* 2 — DQ2
* 3 — DQ3
channel_index (int):
The digital channel (pin) for this data bit.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiDataSet(self.hdwf, spi_data_bit, channel_index)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def idleSet(self, spi_data_bit: int, idle_mode: DwfDigitalOutIdle) -> None:
"""Set the idle behavior for an SPI data bit.
Parameters:
spi_data_bit (int):
The data bit to configure:
* 0 — DQ0 / MOSI / SISO
* 1 — DQ1 / MISO
* 2 — DQ2
* 3 — DQ3
idle_mode (DwfDigitalOutIdle):
The idle behavior of this bit.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiIdleSet(self.hdwf, spi_data_bit, idle_mode.value)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def modeSet(self, spi_mode: int) -> None:
"""Set the SPI mode.
Parameters:
spi_mode (int):
The values for CPOL (polarity) and CPHA (phase) to use with the attached slave device:
* 0 — CPOL = 0, CPHA = 0
* 1 — CPOL = 0, CPHA = 1
* 2 — CPOL = 1, CPHA = 0
* 3 — CPOL = 1, CPHA = 1
Refer to the slave device's datasheet to select the correct value.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiModeSet(self.hdwf, spi_mode)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def orderSet(self, bit_order: int) -> None:
"""Set the SPI data bit order.
Parameters:
bit_order (int):
Select the bit order of each word sent out:
* 1 — MSB first, LSB last
* 0 — LSB first, MSB last
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiOrderSet(self.hdwf, bit_order)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def select(self, channel_index: int, level: int) -> None:
"""Set the chip select (CS) status.
Parameters:
channel_index (int):
The digital channel (pin) for the Chip Select signal.
level (int):
The Chip Select level to configure.
* 0 — low
* 1 — high
* -1 — Z (high impedance)
The CS (chip select) is usually an active-low signal, from the
SPI bus master to a specific SPI slave device. Before starting a bus
request, the master should set CS to 0 for the chip it wants to talk to.
Usually, each slave on an SPI bus has its own CS line. At most one of them
should be selected at any time.
Raises:
DwfLibraryError: An error occurred while executing the operation.
"""
result = self.lib.FDwfDigitalSpiSelect(self.hdwf, channel_index, level)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def writeRead(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> List[int]:
"""Write and read multiple SPI data-words, with up to 8 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…8).
tx (List[int]):
The data-words to write.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the write/read operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_char * number_of_words
tx_buffer = buffer_type(*tx_list)
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiWriteRead(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer,
number_of_words,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def writeRead16(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> List[int]:
"""Write and read multiple SPI data-words, with up to 16 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…16).
tx (List[int]):
The data-words to write.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the write/read operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_short * number_of_words
tx_buffer = buffer_type(*tx_list)
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiWriteRead16(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer,
number_of_words,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def writeRead32(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> List[int]:
"""Write and read multiple SPI data-words, with up to 32 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…32).
tx (List[int]):
The data-words to write.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the write/read operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_int * number_of_words
tx_buffer = buffer_type(*tx_list)
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiWriteRead32(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer,
number_of_words,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def read(self, transfer_type: int, bits_per_word: int, number_of_words: int) -> List[int]:
"""Read multiple SPI data-words, with up to 8 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…8).
number_of_words (int):
The number of data-words to read.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the read operation.
"""
buffer_type = typespec_ctypes.c_unsigned_char * number_of_words
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiRead(
self.hdwf,
transfer_type,
bits_per_word,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def read16(self, transfer_type: int, bits_per_word: int, number_of_words: int) -> List[int]:
"""Read multiple SPI data-words, with up to 16 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…16).
number_of_words (int):
The number of data-words to read.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the read operation.
"""
buffer_type = typespec_ctypes.c_unsigned_short * number_of_words
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiRead16(
self.hdwf,
transfer_type,
bits_per_word,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def read32(self, transfer_type: int, bits_per_word: int, number_of_words: int) -> List[int]:
"""Read multiple SPI data-words, with up to 32 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…32).
number_of_words (int):
The number of data-words to read.
Returns:
List[int]: The data-words received.
Raises:
DwfLibraryError: An error occurred while executing the read operation.
"""
buffer_type = typespec_ctypes.c_unsigned_int * number_of_words
rx_buffer = buffer_type()
result = self.lib.FDwfDigitalSpiRead32(
self.hdwf,
transfer_type,
bits_per_word,
rx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx_list = list(rx_buffer)
return rx_list
def readOne(self, transfer_type: int, bits_per_word: int) -> int:
"""Read a single SPI data-word, with up to 32 bits.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits of the data-word (1…32).
Returns:
int: The data-word received.
Raises:
DwfLibraryError: An error occurred while executing the read operation.
"""
c_rx = typespec_ctypes.c_unsigned_int()
result = self.lib.FDwfDigitalSpiReadOne(self.hdwf, transfer_type, bits_per_word, c_rx)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
rx = c_rx.value
return rx
def write(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> None:
"""Write multiple SPI data-words, with up to 32 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…32).
tx (List[int]):
The data-words to write.
Raises:
DwfLibraryError: An error occurred while executing the write operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_char * number_of_words
tx_buffer = buffer_type(*tx_list)
result = self.lib.FDwfDigitalSpiWrite(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def write16(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> None:
"""Write multiple SPI data-words, with up to 16 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…16).
tx (List[int]):
The data-words to write.
Raises:
DwfLibraryError: An error occurred while executing the write operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_short * number_of_words
tx_buffer = buffer_type(*tx_list)
result = self.lib.FDwfDigitalSpiWrite16(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer,
number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def write32(self, transfer_type: int, bits_per_word: int, tx: List[int]) -> None:
"""Write multiple SPI data-words, with up to 32 bits per data-word.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits per data-word (1…32).
tx (List[int]):
The data-words to write.
Raises:
DwfLibraryError: An error occurred while executing the write operation.
"""
tx_list = list(tx)
number_of_words = len(tx_list)
buffer_type = typespec_ctypes.c_unsigned_int * number_of_words
tx_buffer = buffer_type(*tx_list)
result = self.lib.FDwfDigitalSpiWrite32(
self.hdwf,
transfer_type,
bits_per_word,
tx_buffer, number_of_words)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
def writeOne(self, transfer_type: int, bits_per_word: int, tx: int) -> None:
"""Write a single SPI data-word, with up to 32 bits.
Parameters:
transfer_type (int):
* 0 — SISO
* 1 — MOSI/MISO
* 2 — dual
* 4 — quad
bits_per_word (int):
The number of bits of the data-word (1…32).
tx (int):
The data-word to write.
Raises:
DwfLibraryError: An error occurred while executing the write operation.
"""
result = self.lib.FDwfDigitalSpiWriteOne(self.hdwf, transfer_type, bits_per_word, tx)
if result != RESULT_SUCCESS:
raise self.dwf.exception()
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] | 2.004766 | 8,813 |
#created [email protected]
#created: May 2015
#Based on twitter bootstrap
import os
import sys
import re
import time
import datetime
# set an include path
sys.path.append("./_bootstrap/_scripts")
import zBMS
import scan
import whatsNew
# import repairMenu
outputFileName = "index.html"
ignoreFolders = ['trash', '_trash', '_bootstrap', '__pychache__', 'aspnet_client', '.vscode', '.git']
print("Starting to compile the Project Documentation...")
print("compiling static parts..")
projectconfig = scan.loadCSVFile('config.txt')
fin = open("./_bootstrap/_parts/1head.html", "r")
document = fin.read()
fin.close()
fout = open(outputFileName, "w")
fout.write(document)
fout.close()
scan.mergeFile(outputFileName, "./_bootstrap/_parts/2bodyStart.html")
# build the menu system
scan.mergeFile(outputFileName,"./_bootstrap/_parts/34menuHeader.html")
scan.buildDropDownMenu("dropdownmenu.txt", "./", ignoreFolders)
scan.mergeFile(outputFileName, "dropdownmenu.txt")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/35menuSideBarHeader.html")
scan.buildSideBarMenu("sidebarmenu.txt", "./", ignoreFolders)
scan.mergeFile(outputFileName, "sidebarmenu.txt")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/5title.html")
#create the whatsnew section
whatsNew.whatsnew("tmp.txt", "./", ignoreFolders)
# scan folders and sub folders and build all links...
scan.scanFolders("tmp.txt", "./", ignoreFolders)
now = datetime.datetime.now()
compileStr = projectconfig['projectid'] + " Updated: " + now.strftime("%d/%m/%y %H:%M")
print(compileStr)
scan.wordSearchReplace(outputFileName, "compileInfo", compileStr )
scan.wordSearchReplace(outputFileName, "projectname", projectconfig['projectname'] )
scan.wordSearchReplace(outputFileName, "projectsummary", projectconfig['projectsummary'] )
scan.wordSearchReplace(outputFileName, "browsertabname", projectconfig['browsertabname'] )
scan.mergeFile(outputFileName,"tmp.txt")
os.remove("tmp.txt")
#Overview pages...
scan.mergeFile(outputFileName,"./_bootstrap/_parts/about.html")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/contact.html")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/overview.html")
os.remove("dropdownmenu.txt")
os.remove("sidebarmenu.txt")
#readme section with 2 boxes
print("Adding readme...")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/readme.html")
print("Adding the closing tags to the page...")
scan.mergeFile(outputFileName,"./_bootstrap/_parts/99lastPart.html")
# print("Zipping the entire Portal into a all-in-one so users can self serve...")
# zBMS.zipEntireBMS(".")
print("Complete;-)")
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] | 2.937642 | 882 |
import abc
from abc import ABC
from typing import Any
import numpy as np
| [
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] | 3.409091 | 22 |
from srcs.environments.MazeEnv import MazeEnv
from srcs.agent.POMCP import POMCP
import time
import math
if __name__ == "__main__":
# Create the environment
MAZE_FILE_NAME = "5.maze"
env = MazeEnv("./mazes/" + MAZE_FILE_NAME)
LOCAL_MINIMA = env.get_local_minima(MAZE_FILE_NAME)
S = env.states_list()
A = env.actions_list()
O = env.observations_list()
# Hyper-parameters
NB_SIMULATIONS = 100
NB_ACTION_PERCEPTION_CYCLES = 20
GAMMA = 0.9
TIMEOUT = 500
NO_PARTICLES = 100
EXP_CONST = 5
# Performance tracking variables
exec_times = []
perf = [0 for i in range(0, len(LOCAL_MINIMA) + 2)]
# Run the simulations
for j in range(0, NB_SIMULATIONS):
# Create the agent
agent = POMCP(S, A, O, env, c=EXP_CONST, gamma=GAMMA, timeout=TIMEOUT, no_particles=NO_PARTICLES)
# Action-perception cycles
start = time.time()
# env.render() # TODO
for t in range(0, NB_ACTION_PERCEPTION_CYCLES):
action = agent.search()
obs, _, done = env.step(action)
# env.render() # TODO
if done:
break
agent.update_belief(action, obs)
agent.tree.prune_after_action(action, obs)
# Track execution time and performance
exec_times.append(time.time() - start)
perf = env.track(perf, LOCAL_MINIMA)
# Reset the environment to its initial state
env.reset()
# Display hyperparameters setting
print("MAZE_FILE_NAME={}".format(MAZE_FILE_NAME))
print("NB_SIMULATIONS={}".format(NB_SIMULATIONS))
print("NB_ACTION_PERCEPTION_CYCLES={}".format(NB_ACTION_PERCEPTION_CYCLES))
print("GAMMA={}".format(GAMMA))
print("TIMEOUT={}".format(TIMEOUT))
print("NO_PARTICLES={}".format(NO_PARTICLES))
print("EXP_CONST={}".format(EXP_CONST))
print()
# Display execution time and performance of the POMCP agent
avg = sum(exec_times) / len(exec_times)
var = sum((x - avg)**2 for x in exec_times) / (len(exec_times) - 1)
print("Time: {} +/- {}\n".format(avg, math.sqrt(var)))
total = sum(perf)
print("P(global): {}".format(perf[len(perf) - 1] / total))
for i in range(0, len(LOCAL_MINIMA)):
print("P(local {}): {}".format(i + 1, perf[i + 1] / total))
print("P(other): {}".format(perf[0] / total))
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] | 2.248106 | 1,056 |
import numpy as np
from os import getcwd, path
from cv2 import imread, IMREAD_COLOR
def read_image(path=None):
'''
Read an image from a path
Path is relative path or full path
'''
base_path = getcwd()
full_path = path.join(base_path,path)
if base_path in path:
full_path = path
if not(path.exists(full_path)):
print('The path \" {}\"does not exist. Make just that the file exist').fromat(full_path)
return None
else:
image = imread(full_path,IMREAD_COLOR)
return image
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] | 2.35865 | 237 |
# Copyright 2018-2020 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Unit tests for the autograd interface"""
import pytest
from pennylane import numpy as np
import pennylane as qml
from pennylane.tape import JacobianTape
from pennylane.tape.interfaces.autograd import AutogradInterface
class TestAutogradQuantumTape:
"""Test the autograd interface applied to a tape"""
def test_interface_str(self):
"""Test that the interface string is correctly identified as autograd"""
with AutogradInterface.apply(JacobianTape()) as tape:
qml.RX(0.5, wires=0)
qml.expval(qml.PauliX(0))
assert tape.interface == "autograd"
assert isinstance(tape, AutogradInterface)
def test_get_parameters(self):
"""Test that the get_parameters function correctly gets the trainable parameters and all
parameters, depending on the trainable_only argument"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=False)
c = np.array(0.3, requires_grad=True)
d = np.array(0.4, requires_grad=False)
with AutogradInterface.apply(JacobianTape()) as tape:
qml.Rot(a, b, c, wires=0)
qml.RX(d, wires=1)
qml.CNOT(wires=[0, 1])
qml.expval(qml.PauliX(0))
assert tape.trainable_params == {0, 2}
assert np.all(tape.get_parameters(trainable_only=True) == [a, c])
assert np.all(tape.get_parameters(trainable_only=False) == [a, b, c, d])
def test_execution(self):
"""Test execution"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=False)
dev = qml.device("default.qubit", wires=1)
res = cost(a, b, device=dev)
assert res.shape == (1,)
def test_scalar_jacobian(self, tol):
"""Test scalar jacobian calculation"""
a = np.array(0.1, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
res = qml.jacobian(cost)(a, device=dev)
assert res.shape == (1,)
# compare to standard tape jacobian
with JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
tape.trainable_params = {0}
expected = tape.jacobian(dev)
assert expected.shape == (1, 1)
assert np.allclose(res, np.squeeze(expected), atol=tol, rtol=0)
def test_jacobian(self, tol):
"""Test jacobian calculation"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
res = cost(a, b, device=dev)
expected = [np.cos(a), -np.cos(a) * np.sin(b)]
assert np.allclose(res, expected, atol=tol, rtol=0)
res = qml.jacobian(cost)(a, b, device=dev)
assert res.shape == (2, 2)
expected = [[-np.sin(a), 0], [np.sin(a) * np.sin(b), -np.cos(a) * np.cos(b)]]
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_jacobian_options(self, mocker, tol):
"""Test setting jacobian options"""
spy = mocker.spy(JacobianTape, "numeric_pd")
a = np.array([0.1, 0.2], requires_grad=True)
dev = qml.device("default.qubit", wires=1)
res = qml.jacobian(cost)(a, device=dev)
for args in spy.call_args_list:
assert args[1]["order"] == 2
assert args[1]["h"] == 1e-8
def test_reusing_quantum_tape(self, tol):
"""Test re-using a quantum tape by passing new parameters"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
with AutogradInterface.apply(JacobianTape()) as tape:
qml.RY(a, wires=0)
qml.RX(b, wires=1)
qml.CNOT(wires=[0, 1])
qml.expval(qml.PauliZ(0))
qml.expval(qml.PauliY(1))
assert tape.trainable_params == {0, 1}
jac_fn = qml.jacobian(cost)
jac = jac_fn(a, b)
a = np.array(0.54, requires_grad=True)
b = np.array(0.8, requires_grad=True)
res2 = cost(2 * a, b)
expected = [np.cos(2 * a), -np.cos(2 * a) * np.sin(b)]
assert np.allclose(res2, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(lambda a, b: cost(2 * a, b))
jac = jac_fn(a, b)
expected = [
[-2 * np.sin(2 * a), 0],
[2 * np.sin(2 * a) * np.sin(b), -np.cos(2 * a) * np.cos(b)],
]
assert np.allclose(jac, expected, atol=tol, rtol=0)
def test_classical_processing(self, tol):
"""Test classical processing within the quantum tape"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=False)
c = np.array(0.3, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
res = qml.jacobian(cost)(a, b, c, device=dev)
assert res.shape == (1, 2)
def test_no_trainable_parameters(self, tol):
"""Test evaluation and Jacobian if there are no trainable parameters"""
a = np.array(0.1, requires_grad=False)
b = np.array(0.2, requires_grad=False)
dev = qml.device("default.qubit", wires=2)
res = cost(a, b, device=dev)
assert res.shape == (2,)
res = qml.jacobian(cost)(a, b, device=dev)
assert not res
with pytest.warns(UserWarning, match="Output seems independent"):
res = qml.grad(loss)(a, b)
assert not res
def test_matrix_parameter(self, tol):
"""Test that the autograd interface works correctly
with a matrix parameter"""
U = np.array([[0, 1], [1, 0]], requires_grad=False)
a = np.array(0.1, requires_grad=True)
dev = qml.device("default.qubit", wires=2)
res = cost(a, U, device=dev)
assert np.allclose(res, -np.cos(a), atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(a, U, device=dev)
assert np.allclose(res, np.sin(a), atol=tol, rtol=0)
def test_differentiable_expand(self, mocker, tol):
"""Test that operation and nested tapes expansion
is differentiable"""
mock = mocker.patch.object(qml.operation.Operation, "do_check_domain", False)
a = np.array(0.1, requires_grad=False)
p = np.array([0.1, 0.2, 0.3], requires_grad=True)
dev = qml.device("default.qubit", wires=1)
res = cost_fn(a, p, device=dev)
expected = np.cos(a) * np.cos(p[1]) * np.sin(p[0]) + np.sin(a) * (
np.cos(p[2]) * np.sin(p[1]) + np.cos(p[0]) * np.cos(p[1]) * np.sin(p[2])
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost_fn)
res = jac_fn(a, p, device=dev)
expected = np.array(
[
np.cos(p[1]) * (np.cos(a) * np.cos(p[0]) - np.sin(a) * np.sin(p[0]) * np.sin(p[2])),
np.cos(p[1]) * np.cos(p[2]) * np.sin(a)
- np.sin(p[1])
* (np.cos(a) * np.sin(p[0]) + np.cos(p[0]) * np.sin(a) * np.sin(p[2])),
np.sin(a)
* (np.cos(p[0]) * np.cos(p[1]) * np.cos(p[2]) - np.sin(p[1]) * np.sin(p[2])),
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_probability_differentiation(self, tol):
"""Tests correct output shape and evaluation for a tape
with prob outputs"""
dev = qml.device("default.qubit", wires=2)
x = np.array(0.543, requires_grad=True)
y = np.array(-0.654, requires_grad=True)
res = cost(x, y, device=dev)
expected = np.array(
[
[np.cos(x / 2) ** 2, np.sin(x / 2) ** 2],
[(1 + np.cos(x) * np.cos(y)) / 2, (1 - np.cos(x) * np.cos(y)) / 2],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(x, y, device=dev)
assert res.shape == (2, 2, 2)
expected = np.array(
[
[[-np.sin(x) / 2, 0], [-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2]],
[
[np.sin(x) / 2, 0],
[np.cos(y) * np.sin(x) / 2, np.cos(x) * np.sin(y) / 2],
],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_ragged_differentiation(self, tol):
"""Tests correct output shape and evaluation for a tape
with prob and expval outputs"""
dev = qml.device("default.qubit", wires=2)
x = np.array(0.543, requires_grad=True)
y = np.array(-0.654, requires_grad=True)
res = cost(x, y, device=dev)
expected = np.array(
[np.cos(x), (1 + np.cos(x) * np.cos(y)) / 2, (1 - np.cos(x) * np.cos(y)) / 2]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(x, y, device=dev)
expected = np.array(
[
[-np.sin(x), 0],
[-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2],
[np.cos(y) * np.sin(x) / 2, np.cos(x) * np.sin(y) / 2],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_sampling(self):
"""Test sampling works as expected"""
dev = qml.device("default.qubit", wires=2, shots=10)
x = np.array(0.543, requires_grad=True)
res = cost(x, device=dev)
assert res.shape == (2, 10)
class TestAutogradPassthru:
"""Test that the quantum tape works with an autograd passthru
device.
These tests are very similar to the tests above, with three key differences:
* We do **not** apply the autograd interface. These tapes simply use passthru
backprop, no custom gradient registration needed.
* We do not test the trainable_params attribute. Since these tapes have no
autograd interface, the tape does not need to bookkeep which parameters
are trainable; this is done by autograd internally.
* We use mock.spy to ensure that the tape's Jacobian method is not being called.
"""
def test_execution(self):
"""Test execution"""
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=False)
dev = qml.device("default.qubit.autograd", wires=1)
res = cost(a, b, device=dev)
assert res.shape == (1,)
def test_scalar_jacobian(self, tol, mocker):
"""Test scalar jacobian calculation"""
spy = mocker.spy(JacobianTape, "jacobian")
a = np.array(0.1, requires_grad=True)
dev = qml.device("default.qubit.autograd", wires=2)
res = qml.jacobian(cost)(a, device=dev)
spy.assert_not_called()
assert res.shape == (1,)
# compare to standard tape jacobian
with JacobianTape() as tape:
qml.RY(a, wires=0)
qml.expval(qml.PauliZ(0))
expected = tape.jacobian(dev)
assert expected.shape == (1, 1)
assert np.allclose(res, np.squeeze(expected), atol=tol, rtol=0)
def test_jacobian(self, mocker, tol):
"""Test jacobian calculation"""
spy = mocker.spy(JacobianTape, "jacobian")
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=True)
dev = qml.device("default.qubit.autograd", wires=2)
res = qml.jacobian(cost)(a, b, device=dev)
spy.assert_not_called()
assert res.shape == (2, 2)
# compare to standard tape jacobian
with JacobianTape() as tape:
qml.RY(a, wires=0)
qml.RX(b, wires=0)
qml.expval(qml.PauliZ(0))
qml.expval(qml.PauliY(0))
expected = tape.jacobian(dev)
assert expected.shape == (2, 2)
assert np.allclose(res, expected, atol=tol, rtol=0)
def test_classical_processing(self, mocker, tol):
"""Test classical processing within the quantum tape"""
spy = mocker.spy(JacobianTape, "jacobian")
a = np.array(0.1, requires_grad=True)
b = np.array(0.2, requires_grad=False)
c = np.array(0.3, requires_grad=True)
dev = qml.device("default.qubit.autograd", wires=2)
res = qml.jacobian(cost)(a, b, c, device=dev)
assert res.shape == (1, 2)
spy.assert_not_called()
def test_no_trainable_parameters(self, mocker, tol):
"""Test evaluation and Jacobian if there are no trainable parameters"""
spy = mocker.spy(JacobianTape, "jacobian")
a = np.array(0.1, requires_grad=False)
b = np.array(0.2, requires_grad=False)
dev = qml.device("default.qubit.autograd", wires=2)
res = cost(a, b, device=dev)
assert res.shape == (2,)
spy.assert_not_called()
res = qml.jacobian(cost)(a, b, device=dev)
assert not res
with pytest.warns(UserWarning, match="Output seems independent"):
res = qml.grad(loss)(a, b)
assert not res
def test_matrix_parameter(self, mocker, tol):
"""Test jacobian computation when the tape includes a matrix parameter"""
spy = mocker.spy(JacobianTape, "jacobian")
U = np.array([[0, 1], [1, 0]], requires_grad=False)
a = np.array(0.1, requires_grad=True)
dev = qml.device("default.qubit.autograd", wires=2)
res = cost(a, U, device=dev)
assert np.allclose(res, -np.cos(a), atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(a, U, device=dev)
assert np.allclose(res, np.sin(a), atol=tol, rtol=0)
spy.assert_not_called()
def test_differentiable_expand(self, mocker, tol):
"""Test that operation and nested tapes expansion
is differentiable"""
spy = mocker.spy(JacobianTape, "jacobian")
mock = mocker.patch.object(qml.operation.Operation, "do_check_domain", False)
a = np.array(0.1, requires_grad=False)
p = np.array([0.1, 0.2, 0.3], requires_grad=True)
dev = qml.device("default.qubit.autograd", wires=1)
res = cost_fn(a, p, device=dev)
expected = np.cos(a) * np.cos(p[1]) * np.sin(p[0]) + np.sin(a) * (
np.cos(p[2]) * np.sin(p[1]) + np.cos(p[0]) * np.cos(p[1]) * np.sin(p[2])
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost_fn)
res = jac_fn(a, p, device=dev)
expected = np.array(
[
np.cos(p[1]) * (np.cos(a) * np.cos(p[0]) - np.sin(a) * np.sin(p[0]) * np.sin(p[2])),
np.cos(p[1]) * np.cos(p[2]) * np.sin(a)
- np.sin(p[1])
* (np.cos(a) * np.sin(p[0]) + np.cos(p[0]) * np.sin(a) * np.sin(p[2])),
np.sin(a)
* (np.cos(p[0]) * np.cos(p[1]) * np.cos(p[2]) - np.sin(p[1]) * np.sin(p[2])),
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
spy.assert_not_called()
def test_probability_differentiation(self, mocker, tol):
"""Tests correct output shape and evaluation for a tape
with prob and expval outputs"""
spy = mocker.spy(JacobianTape, "jacobian")
dev = qml.device("default.qubit.autograd", wires=2)
x = np.array(0.543, requires_grad=True)
y = np.array(-0.654, requires_grad=True)
res = cost(x, y, device=dev)
expected = np.array(
[
[np.cos(x / 2) ** 2, np.sin(x / 2) ** 2],
[(1 + np.cos(x) * np.cos(y)) / 2, (1 - np.cos(x) * np.cos(y)) / 2],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(x, y, device=dev)
assert res.shape == (2, 2, 2)
expected = np.array(
[
[[-np.sin(x) / 2, 0], [-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2]],
[
[np.sin(x) / 2, 0],
[np.cos(y) * np.sin(x) / 2, np.cos(x) * np.sin(y) / 2],
],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
spy.assert_not_called()
def test_ragged_differentiation(self, mocker, monkeypatch, tol):
"""Tests correct output shape and evaluation for a tape
with prob and expval outputs"""
spy = mocker.spy(JacobianTape, "jacobian")
dev = qml.device("default.qubit.autograd", wires=2)
# The current DefaultQubitAutograd device provides an _asarray method that does
# not work correctly for ragged arrays. For ragged arrays, we would like _asarray to
# flatten the array. Here, we patch the _asarray method on the device to achieve this
# behaviour; once the tape has moved from the beta folder, we should implement
# this change directly in the device.
monkeypatch.setattr(dev, "_asarray", _asarray)
x = np.array(0.543, requires_grad=True)
y = np.array(-0.654, requires_grad=True)
res = cost(x, y, device=dev)
expected = np.array(
[np.cos(x), (1 + np.cos(x) * np.cos(y)) / 2, (1 - np.cos(x) * np.cos(y)) / 2]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
jac_fn = qml.jacobian(cost)
res = jac_fn(x, y, device=dev)
expected = np.array(
[
[-np.sin(x), 0],
[-np.sin(x) * np.cos(y) / 2, -np.cos(x) * np.sin(y) / 2],
[np.cos(y) * np.sin(x) / 2, np.cos(x) * np.sin(y) / 2],
]
)
assert np.allclose(res, expected, atol=tol, rtol=0)
spy.assert_not_called()
def test_sampling(self):
"""Test sampling works as expected"""
dev = qml.device("default.qubit.autograd", wires=2, shots=10)
x = np.array(0.543, requires_grad=True)
res = cost(x, device=dev)
assert res.shape == (2, 10)
| [
2,
15069,
2864,
12,
42334,
47482,
324,
84,
29082,
21852,
3457,
13,
201,
198,
201,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
201,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
13,
201,
198,
2,
921,
743,
7330,
257,
4866,
286,
262,
13789,
379,
201,
198,
201,
198,
2,
220,
220,
220,
220,
2638,
1378,
2503,
13,
43073,
13,
2398,
14,
677,
4541,
14,
43,
2149,
24290,
12,
17,
13,
15,
201,
198,
201,
198,
2,
17486,
2672,
416,
9723,
1099,
393,
4987,
284,
287,
3597,
11,
3788,
201,
198,
2,
9387,
739,
262,
13789,
318,
9387,
319,
281,
366,
1921,
3180,
1,
29809,
1797,
11,
201,
198,
2,
42881,
34764,
11015,
6375,
7102,
49828,
11053,
3963,
15529,
509,
12115,
11,
2035,
4911,
393,
17142,
13,
201,
198,
2,
4091,
262,
13789,
329,
262,
2176,
3303,
15030,
21627,
290,
201,
198,
2,
11247,
739,
262,
13789,
13,
201,
198,
37811,
26453,
5254,
329,
262,
1960,
519,
6335,
7071,
37811,
201,
198,
11748,
12972,
9288,
201,
198,
6738,
22429,
2645,
1531,
1330,
299,
32152,
355,
45941,
201,
198,
201,
198,
11748,
22429,
2645,
1531,
355,
10662,
4029,
201,
198,
6738,
22429,
2645,
1531,
13,
83,
1758,
1330,
12806,
666,
51,
1758,
201,
198,
6738,
22429,
2645,
1531,
13,
83,
1758,
13,
3849,
32186,
13,
2306,
519,
6335,
1330,
5231,
519,
6335,
39317,
201,
198,
201,
198,
201,
198,
4871,
6208,
16541,
519,
6335,
24915,
388,
51,
1758,
25,
201,
198,
220,
220,
220,
37227,
14402,
262,
1960,
519,
6335,
7071,
5625,
284,
257,
9154,
37811,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
39994,
62,
2536,
7,
944,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
326,
262,
7071,
4731,
318,
9380,
5174,
355,
1960,
519,
6335,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
351,
5231,
519,
6335,
39317,
13,
39014,
7,
46751,
666,
51,
1758,
28955,
355,
9154,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
49,
55,
7,
15,
13,
20,
11,
19474,
28,
15,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
11201,
2100,
7,
80,
4029,
13,
12041,
72,
55,
7,
15,
4008,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
9154,
13,
39994,
6624,
366,
2306,
519,
6335,
1,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
318,
39098,
7,
83,
1758,
11,
5231,
519,
6335,
39317,
8,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
1136,
62,
17143,
7307,
7,
944,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
326,
262,
651,
62,
17143,
7307,
2163,
9380,
3011,
262,
4512,
540,
10007,
290,
477,
201,
198,
220,
220,
220,
220,
220,
220,
220,
10007,
11,
6906,
319,
262,
4512,
540,
62,
8807,
4578,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
18747,
7,
15,
13,
16,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
275,
796,
45941,
13,
18747,
7,
15,
13,
17,
11,
4433,
62,
9744,
28,
25101,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
269,
796,
45941,
13,
18747,
7,
15,
13,
18,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
288,
796,
45941,
13,
18747,
7,
15,
13,
19,
11,
4433,
62,
9744,
28,
25101,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
351,
5231,
519,
6335,
39317,
13,
39014,
7,
46751,
666,
51,
1758,
28955,
355,
9154,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
24864,
7,
64,
11,
275,
11,
269,
11,
19474,
28,
15,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
49,
55,
7,
67,
11,
19474,
28,
16,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
34,
11929,
7,
86,
2387,
41888,
15,
11,
352,
12962,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
11201,
2100,
7,
80,
4029,
13,
12041,
72,
55,
7,
15,
4008,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
9154,
13,
27432,
540,
62,
37266,
6624,
1391,
15,
11,
362,
92,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
45941,
13,
439,
7,
83,
1758,
13,
1136,
62,
17143,
7307,
7,
27432,
540,
62,
8807,
28,
17821,
8,
6624,
685,
64,
11,
269,
12962,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
45941,
13,
439,
7,
83,
1758,
13,
1136,
62,
17143,
7307,
7,
27432,
540,
62,
8807,
28,
25101,
8,
6624,
685,
64,
11,
275,
11,
269,
11,
288,
12962,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
18558,
1009,
7,
944,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
9706,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
18747,
7,
15,
13,
16,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
275,
796,
45941,
13,
18747,
7,
15,
13,
17,
11,
4433,
62,
9744,
28,
25101,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
796,
10662,
4029,
13,
25202,
7203,
12286,
13,
421,
2545,
1600,
19474,
28,
16,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
1575,
7,
64,
11,
275,
11,
3335,
28,
7959,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
581,
13,
43358,
6624,
357,
16,
35751,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
1416,
282,
283,
62,
30482,
672,
666,
7,
944,
11,
284,
75,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
16578,
283,
474,
330,
672,
666,
17952,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
18747,
7,
15,
13,
16,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
796,
10662,
4029,
13,
25202,
7203,
12286,
13,
421,
2545,
1600,
19474,
28,
17,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
10662,
4029,
13,
30482,
672,
666,
7,
15805,
5769,
64,
11,
3335,
28,
7959,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
581,
13,
43358,
6624,
357,
16,
35751,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
8996,
284,
3210,
9154,
474,
330,
672,
666,
201,
198,
220,
220,
220,
220,
220,
220,
220,
351,
12806,
666,
51,
1758,
3419,
355,
9154,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
18276,
7,
64,
11,
19474,
28,
15,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10662,
4029,
13,
11201,
2100,
7,
80,
4029,
13,
12041,
72,
57,
7,
15,
4008,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
9154,
13,
27432,
540,
62,
37266,
796,
1391,
15,
92,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2938,
796,
9154,
13,
30482,
672,
666,
7,
7959,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
2938,
13,
43358,
6624,
357,
16,
11,
352,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
45941,
13,
439,
19836,
7,
411,
11,
45941,
13,
16485,
1453,
2736,
7,
40319,
828,
379,
349,
28,
83,
349,
11,
374,
83,
349,
28,
15,
8,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
30482,
672,
666,
7,
944,
11,
284,
75,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
474,
330,
672,
666,
17952,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
18747,
7,
15,
13,
16,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
275,
796,
45941,
13,
18747,
7,
15,
13,
17,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
796,
10662,
4029,
13,
25202,
7203,
12286,
13,
421,
2545,
1600,
19474,
28,
17,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
1575,
7,
64,
11,
275,
11,
3335,
28,
7959,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2938,
796,
685,
37659,
13,
6966,
7,
64,
828,
532,
37659,
13,
6966,
7,
64,
8,
1635,
45941,
13,
31369,
7,
65,
15437,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
45941,
13,
439,
19836,
7,
411,
11,
2938,
11,
379,
349,
28,
83,
349,
11,
374,
83,
349,
28,
15,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
10662,
4029,
13,
30482,
672,
666,
7,
15805,
5769,
64,
11,
275,
11,
3335,
28,
7959,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
581,
13,
43358,
6624,
357,
17,
11,
362,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2938,
796,
16410,
12,
37659,
13,
31369,
7,
64,
828,
657,
4357,
685,
37659,
13,
31369,
7,
64,
8,
1635,
45941,
13,
31369,
7,
65,
828,
532,
37659,
13,
6966,
7,
64,
8,
1635,
45941,
13,
6966,
7,
65,
8,
11907,
201,
198,
220,
220,
220,
220,
220,
220,
220,
6818,
45941,
13,
439,
19836,
7,
411,
11,
2938,
11,
379,
349,
28,
83,
349,
11,
374,
83,
349,
28,
15,
8,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
30482,
672,
666,
62,
25811,
7,
944,
11,
285,
12721,
11,
284,
75,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
4634,
474,
330,
672,
666,
3689,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
13997,
796,
285,
12721,
13,
2777,
88,
7,
46751,
666,
51,
1758,
11,
366,
77,
39223,
62,
30094,
4943,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
18747,
26933,
15,
13,
16,
11,
657,
13,
17,
4357,
4433,
62,
9744,
28,
17821,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
1614,
796,
10662,
4029,
13,
25202,
7203,
12286,
13,
421,
2545,
1600,
19474,
28,
16,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
10662,
4029,
13,
30482,
672,
666,
7,
15805,
5769,
64,
11,
3335,
28,
7959,
8,
201,
198,
201,
198,
220,
220,
220,
220,
220,
220,
220,
329,
26498,
287,
13997,
13,
13345,
62,
22046,
62,
4868,
25,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6818,
26498,
58,
16,
7131,
1,
2875,
8973,
6624,
362,
201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6818,
26498,
58,
16,
7131,
1,
71,
8973,
6624,
352,
68,
12,
23,
201,
198,
201,
198,
220,
220,
220,
825,
1332,
62,
260,
3500,
62,
40972,
388,
62,
83,
1758,
7,
944,
11,
284,
75,
2599,
201,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
14402,
302,
12,
3500,
257,
14821,
9154,
416,
6427,
649,
10007,
37811,
201,
198,
220,
220,
220,
220,
220,
220,
220,
257,
796,
45941,
13,
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220,
220,
220,
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37227,
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201,
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220,
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220,
220,
220,
220,
220,
1614,
796,
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13,
421,
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13,
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519,
6335,
1600,
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17,
11,
6934,
28,
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8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
2124,
796,
45941,
13,
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7,
15,
13,
20,
3559,
11,
4433,
62,
9744,
28,
17821,
8,
201,
198,
220,
220,
220,
220,
220,
220,
220,
581,
796,
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7,
87,
11,
3335,
28,
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8,
201,
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220,
220,
220,
220,
220,
220,
220,
6818,
581,
13,
43358,
6624,
357,
17,
11,
838,
8,
201,
198
] | 1.94377 | 9,799 |
import requests_html
from pytest import fixture
from requests_html import HTMLResponse
from wsgiadapter import WSGIAdapter
from tests.endpoints import login
from warehouse14 import create_app
@fixture
@fixture
| [
11748,
7007,
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31,
69,
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628,
198,
31,
69,
9602,
628,
628,
198
] | 3.711864 | 59 |
l=input("CANDIES: ").lstrip("[").rstrip("]")
t=l.split(",")
boolist=[]
n= int(input("EXTRA CANDIES: "))
for i in range(len(t)):
if int(t[i])+n>=int(max(t)):
boolist.append("True")
else:
boolist.append("False")
print(boolist)
| [
75,
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33295,
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25101,
4943,
220,
220,
220,
198,
4798,
7,
30388,
396,
8,
198
] | 1.96875 | 128 |
import pandas as pd
from mock import MagicMock
from ..plotlygraphs.graphbase import GraphBase
from ..plotlygraphs.piegraph import PieGraph
from ..plotlygraphs.datagraph import DataGraph
from ..widget.encoding import Encoding
from ..widget.invalidencodingerror import InvalidEncodingError
| [
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1472,
1330,
17665,
27195,
7656,
12331,
628,
628,
628,
198
] | 3.511905 | 84 |
# NOTE(cutwater): This migration is replaced by v2_4_0 and should be
# deleted once superseding migration is merged into master.
from django.db import migrations
| [
2,
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7,
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6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
628
] | 3.75 | 44 |
# todo: handle cases where the boundary crosses the dateline
# usage:
# python landgrab.py [osm id] [zoom level] [optional list-only flag]
import requests, json, math, sys, os
import xml.etree.ElementTree as ET
import pprint
if len(sys.argv) < 3:
print "At least 2 arguments needed - please enter an OSM ID and zoom level."
sys.exit()
# get the OpenStreetMap ID
OSMID=sys.argv[1]
zoom=[]
# handle multi-part ranges, eg "3-4, 5, 6-7"
for part in sys.argv[2].split(','):
if '-' in part:
a, b = part.split('-')
a, b = int(a), int(b)
zoom.extend(range(a, b + 1))
else:
a = int(part)
zoom.append(a)
coordsonly=0
if len(sys.argv) > 3:
coordsonly=int(sys.argv[3])
print coordsonly
success = False
try:
INFILE = 'http://www.openstreetmap.org/api/0.6/relation/'+OSMID+'/full'
print "Downloading", INFILE
r = requests.get(INFILE)
r.raise_for_status()
success = True
except Exception, e:
print e
if not success:
try:
INFILE = 'http://www.openstreetmap.org/api/0.6/way/'+OSMID+'/full'
print "Downloading", INFILE
r = requests.get(INFILE)
r.raise_for_status()
success = True
except Exception, e:
print e
if not success:
try:
INFILE = 'http://www.openstreetmap.org/api/0.6/node/'+OSMID
print "Downloading", INFILE
r = requests.get(INFILE)
r.raise_for_status()
success = True
except Exception, e:
print e
print "Element not found, exiting"
sys.exit()
# print r.encoding
open('outfile.xml', 'w').close() # clear existing OUTFILE
with open('outfile.xml', 'w') as fd:
fd.write(r.text.encode("UTF-8"))
fd.close()
try:
tree = ET.parse('outfile.xml')
except Exception, e:
print e
print "XML parse failed, please check outfile.xml"
sys.exit()
root = tree.getroot()
##
## HELPER FUNCTIONS
##
tile_size = 256
half_circumference_meters = 20037508.342789244;
# Convert lat-lng to mercator meters
# convert from tile-space coords to meters, depending on zoom
# Given a point in mercator meters and a zoom level, return the tile X/Y/Z that the point lies in
# Convert tile location to mercator meters - multiply by pixels per tile, then by meters per pixel, adjust for map origin
##
## PROCESSING points
##
print "Processing:"
points = []
for node in root:
if node.tag == "node":
lat = float(node.attrib["lat"])
lon = float(node.attrib["lon"])
points.append({'y':lat, 'x':lon})
##
## GET TILES for all zoom levels
##
for z in zoom:
getTiles(points,z)
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198,
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366,
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278,
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198,
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220,
220,
611,
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220,
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300,
261,
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287,
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25,
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220,
220,
220,
651,
51,
2915,
7,
13033,
11,
89,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220
] | 2.380563 | 1,101 |
import tweepy
from keys import keys
CONSUMER_KEY = keys['consumer_key']
CONSUMER_SECRET = keys['consumer_secret']
ACCESS_TOKEN = keys['access_token']
ACCESS_TOKEN_SECRET = keys['access_token_secret']
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
api = tweepy.API(auth)
while 1:
twt = api.search(q="Jyo_Test_1")
#list of specific strings we want to check for in Tweets
t = ['Jyo_Test_1']
for s in twt:
for i in t:
if i == s.text:
sn = s.user.screen_name
m = "@%s Hello! We will resolve your complaint" % (sn)
s = api.update_status(m, s.id)
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0,
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264,
796,
40391,
13,
19119,
62,
13376,
7,
76,
11,
264,
13,
312,
8,
198
] | 2.125 | 336 |
from constants import *
from polytropes import *
from potentials import *
| [
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6738,
7514,
48385,
274,
1330,
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198,
6738,
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1635,
198
] | 4.111111 | 18 |
from webApp.utils.app.routes import *
from webApp.utils.app.forms import auth | [
6738,
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] | 3.08 | 25 |
# This file is Copyright (c) 2020 Gregory Davill <[email protected]>
# License: BSD
from migen import *
from litex.soc.interconnect.stream import Endpoint
from rtl.edge_detect import EdgeDetect
from litex.soc.interconnect.csr import AutoCSR, CSR, CSRStatus, CSRStorage
from litex.soc.interconnect.stream import Endpoint, EndpointDescription, AsyncFIFO | [
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] | 3.051282 | 117 |
from globals import *
import life as lfe
import historygen
import judgement
import survival
import speech
import groups
import combat
import camps
import sight
import brain
import zones
import bad_numbers
import logging
import random
MAX_INFLUENCE_FROM = 80
MAX_INTROVERSION = 10
MAX_CHARISMA = 9 | [
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] | 3.409091 | 88 |
from qgis.core import QgsProcessing
from qgis.core import QgsProcessingAlgorithm
from qgis.core import QgsProcessingMultiStepFeedback
from qgis.core import QgsProcessingParameterRasterLayer
from qgis.core import QgsProcessingParameterRasterDestination
import processing
| [
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] | 3.474359 | 78 |
import torch.nn as nn
import torch.nn.functional as F
import torch
from sklearn.cluster import KMeans
from sklearn.metrics.pairwise import pairwise_distances
import numpy as np
def initialize_bof_layers(model, data_loader, n_samples=100, n_feature_samples=5000, batch_size=32, k_means_max_iters=300,
k_means_n_init=4):
"""
Initializes the BoF layers of a model
:param model: the model
:param data: data to be used for initializing the model
:param n_samples: number of data samples used for the initializes
:param n_feature_samples: number of feature vectors to be used for the clustering process
:param batch_size:
:param k_means_max_iters: the maximum number of iterations for the clustering algorithm (k-means)
:param k_means_n_init: defines how many times to run the k-means algorithm
:return:
"""
features = {}
iternum = int(n_samples / batch_size + 0.5)
for name, layer in model.named_modules():
if isinstance(layer, BoF_Pooling):
print("Found BoF layer (layer %s), initializing..." % name)
# Compile a function for getting the feature vectors
# get_features = K.function([model.input] + [model.training], [model.layers[i - 1].output])
features[name] = []
handler = layer.register_forward_pre_hook(get_features(name))
# iterate dataset to trigger hook to get features
for i in range(iternum):
data, labels = data_loader.__iter__().next()
if len(list(data.shape)) == 5:
data = data[:, 0]
if torch.cuda.is_available():
data = data.cuda()
output = model(data)
handler.remove()
layer_features = np.concatenate(features[name])
np.random.shuffle(layer_features)
layer_features = layer_features[:n_feature_samples]
# Cluster the features
kmeans = KMeans(n_clusters=layer.N_k, n_init=k_means_n_init, max_iter=k_means_max_iters)
kmeans.fit(layer_features)
# V of BoF pooling layer
V = kmeans.cluster_centers_
V = V.reshape((V.shape[0], V.shape[1], 1, 1))
# Set the value for the codebook
layer.V.data = torch.tensor(np.float32(V)).cuda() if torch.cuda.is_available() else \
torch.tensor(np.float32(V))
# Get the mean distance for initializing the sigmas
mean_dist = np.mean(pairwise_distances(layer_features[:100]))
# Set the value for sigmas
sigmas = np.ones((1, layer.N_k, 1, 1)) * (mean_dist ** 2)
layer.sigmas.data = torch.tensor(np.float32(sigmas)).cuda() if torch.cuda.is_available() else \
torch.tensor(np.float32(sigmas))
if __name__ == '__main__':
x = torch.ones(size=(32, 32, 11, 11)) * 0.5
model = BoF_Pooling(64, features=32, spatial_level=1)
y = model(x)
print(y.mean())
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] | 2.226804 | 1,358 |
#!/usr/bin/env python3
from gevent import monkey; monkey.patch_all()
from arago.actors import Actor, Root
import arago.actors.pattern_matching as matching
from arago.common.logging import getCustomLogger
logger = getCustomLogger(level="WARNING")
players = [PingPong(name="Player One"), PingPong(name="Player Two")]
players[0].serve(opponent=players[1])
Root(name="root", children=players)
| [
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7,
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1600,
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28,
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8,
198
] | 3.070313 | 128 |
import pyspark
import random
if __name__ == "__main__":
sc_conf = pyspark.SparkConf()
sc_conf.setAppName("pi-app")
sc_conf.setMaster('spark://spark-master-01:7077')
sc_conf.set('spark.executor.cores','1')
sc_conf.set("spark.executor.memory", '1g')
sc = pyspark.SparkContext(conf=sc_conf)
num_samples = 1000000000
count = sc.parallelize(range(0, num_samples)).filter(inside).count()
pi = 4 * count / num_samples
print(pi)
sc.stop()
| [
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7,
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3419,
628
] | 2.478495 | 186 |
from Products.CMFPlone.utils import safe_unicode
from bika.lims import logger, to_utf8
from bika.lims.interfaces import IJSONReadExtender
from bika.lims.jsonapi import get_include_fields
from plone.jsonapi.core import router
from plone.jsonapi.core.interfaces import IRouteProvider
from plone.protect.authenticator import AuthenticatorView
from bika.lims.jsonapi import load_brain_metadata
from bika.lims.jsonapi import load_field_values
from Products.CMFCore.utils import getToolByName
from zope import interface
from zope.component import getAdapters
import re
import App
| [
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651,
2782,
12126,
198,
11748,
302,
198,
11748,
2034,
628,
198
] | 3.388235 | 170 |
'''
Function:
关卡切换界面
Author:
Charles
微信公众号:
Charles的皮卡丘
'''
import pygame
from .....utils import QuitGame
'''关卡切换界面''' | [
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] | 1.450549 | 91 |
# -*- coding: utf-8 -*-
"""
Reads in the raw data fetched from ENTSO-E Transparency Platform, refactors the
data and fills in missing data
"""
import pandas as pd
import numpy as np
from datetime import datetime, date, time, timezone, timedelta
import pickle
import os
import logging
#%%
def aggregate_entso(dictionary, start=None, end=None, start2=None):
""" Receives dictionary of raw data queried from ENTSO-E Transparency Portal
and start and end of sub-annual period desired (optional)
Calculates the size in timesteps between samples (rows) and checks
if they are identical (i.e., even timesteps throughout time series)
"""
new_dict = {}
summed_dict = {}
no_trade = []
for key, value in dictionary.items():
timestep_list = []
if (start is not None) and (end is not None) and (not isinstance(value, float)):
try:
value_tmp = value.loc[start:end]
if value_tmp.empty and (start2 is not None):
print(f'{key} does not have an entry for {start}. Sampling closest hour instead')
value_tmp = value.loc[start2:start2 + timedelta(minutes=1)]
# entsotime = value.index
except KeyError:
if isinstance(key, tuple):
print(f'No trade for {key} at {start}')
except AttributeError:
if isinstance(key, tuple):
no_trade.append(key)
else:
print(f'No dataframe for {key}, cannot take slice!')
raise
except Exception as e:
print('Ran into a problem!')
print(e)
raise
value = value_tmp
# try:
if isinstance(value, pd.DataFrame) or isinstance(value, pd.Series):
# we don't need timesteps if we have a single time period (i.e., footprint analysis)
for i in range(0, value.shape[0]-1):
try:
timestep = (value.index[i+1] - value.index[i]).total_seconds() / 3600 # get timestep in hours
timestep_list.append(timestep)
except IndexError:
print(f'IndexError {i}')
except Exception as e:
print('Could not perform!')
print(e)
# Make sure timesteps are all equal length before calculating
# NB: this is made obsolete by using bentso's fullyear=True
if checkEqual(timestep_list):
if (isinstance(value, pd.DataFrame)):
# ENTSO-E data from 2020 introduces MultiIndex headers
if type(value.columns) == pd.MultiIndex:
value = value.loc(axis=1)[:, 'Actual Aggregated'] # drop "Actual Consumption"
value.columns = value.columns.droplevel(1)
if (value.columns.str.contains('Hydro Pumped Storage').sum() == 1):
# check if value is the production matrix and if so, if the country has pumped storage
logging.info(f'Correcting for negative pumped hydropower in {key}')
value = value.apply(distribute_neg_hydro, axis=1) # correct for negative pumped hydro
if value.shape[0] -1 > 0:
summed_dict[key] = (value * timestep_list[0] / 1e6).sum() # To calculate electricity generated; take power per timestep and multiply by length of time period. Sum over whole year
elif value.shape[0] - 1 == 0:
summed_dict[key] = (value / 1e6).sum()
new_dict[key] = value
else:
print(f'warning: unequal time steps for {key}')
logging.warning(f'unequal time steps for %s', key)
if min(timestep_list) == 1:
logging.info(f'resampling data to 1 hour increments in {key}')
new_dict[key] = value.resample('1H').interpolate()
summed_dict[key] = (new_dict[key] * timestep_list[0] / 1e6).sum()
print('1 hour')
elif min(timestep_list) == 0.25:
logging.info(f'resampling data to 15 minute increments in {key}')
new_dict[key] = value.resample('15T').interpolate()
summed_dict[key] = (new_dict[key] * timestep_list[0] / 1e6).sum()
print('15 minutes')
else:
print('very uneven timesteps')
#value = (value*timestep_list[0]/1000).sum()
# except Exception as e:
# print(f'something went wrong in {key}')
# print(e)
return summed_dict, new_dict #, entsotime
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220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
62,
22065,
13,
28920,
290,
357,
9688,
17,
318,
407,
6045,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
6,
90,
2539,
92,
857,
407,
423,
281,
5726,
329,
1391,
9688,
27422,
3409,
11347,
11706,
1711,
2427,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
62,
22065,
796,
1988,
13,
17946,
58,
9688,
17,
25,
9688,
17,
1343,
28805,
12514,
7,
1084,
1769,
28,
16,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
220,
658,
313,
524,
796,
1988,
13,
9630,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
7383,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
2539,
11,
46545,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
6,
2949,
3292,
329,
1391,
2539,
92,
379,
1391,
9688,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
3460,
4163,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
2539,
11,
46545,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
645,
62,
25351,
13,
33295,
7,
2539,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
6,
2949,
1366,
14535,
329,
1391,
2539,
5512,
2314,
1011,
16416,
0,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
49,
272,
656,
257,
1917,
0,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
68,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
1988,
62,
22065,
198,
2,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
279,
67,
13,
6601,
19778,
8,
393,
318,
39098,
7,
8367,
11,
279,
67,
13,
27996,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
356,
836,
470,
761,
4628,
395,
25386,
611,
356,
423,
257,
2060,
640,
2278,
357,
72,
13,
68,
1539,
24713,
3781,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
15,
11,
1988,
13,
43358,
58,
15,
45297,
16,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4628,
395,
538,
796,
357,
8367,
13,
9630,
58,
72,
10,
16,
60,
532,
1988,
13,
9630,
58,
72,
35944,
23350,
62,
43012,
3419,
1220,
4570,
405,
220,
1303,
651,
4628,
395,
538,
287,
2250,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4628,
395,
538,
62,
4868,
13,
33295,
7,
16514,
395,
538,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
12901,
12331,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
6,
15732,
12331,
1391,
72,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
23722,
407,
1620,
0,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
68,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6889,
1654,
4628,
395,
25386,
389,
477,
4961,
4129,
878,
26019,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
41354,
25,
428,
318,
925,
26533,
416,
1262,
17157,
568,
338,
1336,
1941,
28,
17821,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2198,
36,
13255,
7,
16514,
395,
538,
62,
4868,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
271,
39098,
7,
8367,
11,
279,
67,
13,
6601,
19778,
8,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
12964,
4694,
46,
12,
36,
1366,
422,
12131,
20718,
15237,
15732,
24697,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2099,
7,
8367,
13,
28665,
82,
8,
6624,
279,
67,
13,
29800,
15732,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
1988,
13,
17946,
7,
22704,
28,
16,
38381,
45299,
705,
6398,
723,
19015,
2301,
515,
20520,
220,
1303,
4268,
366,
6398,
723,
42158,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
13,
28665,
82,
796,
1988,
13,
28665,
82,
13,
22285,
1154,
626,
7,
16,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
357,
8367,
13,
28665,
82,
13,
2536,
13,
3642,
1299,
10786,
40436,
305,
23220,
276,
20514,
27691,
16345,
3419,
6624,
352,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
2198,
611,
1988,
318,
262,
3227,
17593,
290,
611,
523,
11,
611,
262,
1499,
468,
29104,
6143,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
10951,
7,
69,
6,
42779,
278,
329,
4633,
29104,
7409,
1773,
789,
287,
1391,
2539,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
1988,
13,
39014,
7,
17080,
4163,
62,
12480,
62,
15511,
305,
11,
16488,
28,
16,
8,
220,
1303,
3376,
329,
4633,
29104,
17173,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
1988,
13,
43358,
58,
15,
60,
532,
16,
1875,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32794,
62,
11600,
58,
2539,
60,
796,
357,
8367,
1635,
4628,
395,
538,
62,
4868,
58,
15,
60,
1220,
352,
68,
21,
737,
16345,
3419,
1303,
1675,
15284,
8744,
7560,
26,
1011,
1176,
583,
4628,
395,
538,
290,
29162,
416,
4129,
286,
640,
2278,
13,
5060,
625,
2187,
614,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
1988,
13,
43358,
58,
15,
60,
532,
352,
6624,
657,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32794,
62,
11600,
58,
2539,
60,
796,
357,
8367,
1220,
352,
68,
21,
737,
16345,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
11600,
58,
2539,
60,
796,
1988,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
6,
43917,
25,
37334,
640,
4831,
329,
1391,
2539,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
43917,
7,
69,
6,
1726,
13255,
640,
4831,
329,
4064,
82,
3256,
1994,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
949,
7,
16514,
395,
538,
62,
4868,
8,
6624,
352,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
10951,
7,
69,
821,
37687,
11347,
1366,
284,
352,
1711,
41867,
287,
1391,
2539,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
11600,
58,
2539,
60,
796,
1988,
13,
411,
1403,
10786,
16,
39,
27691,
3849,
16104,
378,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32794,
62,
11600,
58,
2539,
60,
796,
357,
3605,
62,
11600,
58,
2539,
60,
1635,
4628,
395,
538,
62,
4868,
58,
15,
60,
1220,
352,
68,
21,
737,
16345,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
16,
1711,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
949,
7,
16514,
395,
538,
62,
4868,
8,
6624,
657,
13,
1495,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
18931,
13,
10951,
7,
69,
821,
37687,
11347,
1366,
284,
1315,
5664,
41867,
287,
1391,
2539,
92,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
649,
62,
11600,
58,
2539,
60,
796,
1988,
13,
411,
1403,
10786,
1314,
51,
27691,
3849,
16104,
378,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
32794,
62,
11600,
58,
2539,
60,
796,
357,
3605,
62,
11600,
58,
2539,
60,
1635,
4628,
395,
538,
62,
4868,
58,
15,
60,
1220,
352,
68,
21,
737,
16345,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
1314,
2431,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
10786,
548,
30690,
4628,
395,
25386,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
8367,
796,
357,
8367,
9,
16514,
395,
538,
62,
4868,
58,
15,
60,
14,
12825,
737,
16345,
3419,
198,
2,
220,
220,
220,
220,
220,
220,
220,
2845,
35528,
355,
304,
25,
198,
2,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7,
69,
338,
8370,
1816,
2642,
287,
1391,
2539,
92,
11537,
198,
2,
220,
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3601,
7,
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11,
649,
62,
11600,
1303,
11,
220,
658,
313,
524,
198
] | 2.049061 | 2,344 |
"""
A dictionary of words.
:Author: Maded Batara III
:Version: v20181010
"""
from collections import Counter
from .dictionary_query import DictionaryQuery
class Dictionary(DictionaryQuery):
"""A dictionary of words.
As this is a subclass of DictionaryQuery, this class supports all its
methods."""
def __init__(self, filename):
"""
Initializes a new dictionary.
Args:
filename (str): Filename of the dictionary to be loaded in.
"""
with open(filename) as dictionary_file:
self.words = {
word: Counter(word)
for word in dictionary_file.read().splitlines()
}
def __repr__(self):
"""Implements repr(Dictionary)."""
return "Dictionary(words={0})".format(len(self))
def __str__(self):
"""Implements str(Dictionary)."""
return "Dictionary with {0} entries".format(len(self))
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] | 2.477807 | 383 |
from myhdl import *
@block
def cr(pc_next,branch_offset,r6_r7_data,cr_data,clk,rst,int0,int1,int2,int3,mem_read,mem_write,mem_ok,branch,selector,cr_write,ret,apc,jmp,bra
,main_state):
'''
:param clk: 1 in clk
:param rst: 1 in rst
:param int0: 1 in interrupt
:param int1: 1 in interrupt
:param int2: 1 in interrupt
:param int3: 1 in interrupt
:param mem_read: 1 in memory read
:param mem_write: 1 in memory write
:param mem_ok: 1 in memory ok
:param branch: 1 in branch
:param selector: 3 in selectors
:param cr_write:1 in cr write
:param ret: 1 in return
:param apc: 1 in apc
:param jmp: 1 in jmp
:param bra: 1 in branch if
:param main_state: 1 out main state
:param pc_next: 16 out program counter next
:param branch_offset: 16 in branch offset
:param r6_r7_data: 16 in data from r6 and r7 (pointer
:param cr_data: 16 out cr register data
:return:
'''
states = enum ('status','ie','epc','cpc','tvec0','tvec1','tvec2','tvec3')
CPC = Signal(intbv(0)[16:])
#TEMP = Signal(intbv(0)[16:])
TVEC0 = Signal(intbv(0)[16:])
TVEC1 = Signal(intbv(0)[16:])
TVEC2 = Signal(intbv(0)[16:])
TVEC3 = Signal(intbv(0)[16:])
EPC = Signal(intbv(0)[16:])
PC = Signal(intbv(0)[16:])
GIE = Signal(bool(0))
PGIE = Signal(bool(0))
IE0 = Signal(bool(0))
IE1 = Signal(bool(0))
IE2 = Signal(bool(0))
IE3 = Signal(bool(0))
int_acc = Signal(bool(0))
tvec = Signal(intbv(0)[16:])
int0_acc = Signal(bool(0))
int1_acc = Signal(bool(0))
int2_acc = Signal(bool(0))
int3_acc = Signal(bool(0))
@always_comb
@always_comb
'''
@always_comb
def comb_logic3():
if selector=='000000001':
cr_data[16:2].next = intbv(0)[14:]
cr_data[1].next = PGIE
cr_data[0].next = GIE
elif selector=='000000010':
cr_data[16:4].next = intbv(0)[12:]
cr_data[3].next = IE3
cr_data[2].next = IE2
cr_data[1].next = IE1
cr_data[0].next = IE0
elif selector=='000000100':
cr_data.next = EPC
elif selector=='000001000':
cr_data.next = CPC
elif selector == '000010000':
cr_data.next = TVEC0
elif selector == '000100000':
cr_data.next = TVEC1
elif selector == '001000000':
cr_data.next = TVEC2
elif selector == '010000000':
cr_data.next = TVEC3
else:
cr_data.next = 0
'''
@always_comb
@always_seq(clk.posedge,reset = rst)
@always_seq(clk.posedge, reset=rst)
@always_seq(clk.posedge, reset=rst)
@always_seq(clk.posedge, reset=rst)
@always_seq(clk.posedge, reset=rst)
@always_seq(clk.posedge, reset=rst)
@always_seq(clk.posedge, reset=rst)
@always_comb
@always_comb
return instances()
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3419,
198
] | 2.029026 | 1,447 |
import sys
from os import path
import inspect
from keystoneauth1 import identity
from keystoneauth1 import session
from cinderclient import client
import re
METRIC_NAME_PREFIX = "openstack."
CINDER_LIMIT_PREFIX = "cinder.limit."
CINDER_VOLUME_PREFIX = "cinder.volume."
CINDER_SNAPSHOT_PREFIX = "cinder.snapshot."
DEFAULT_CINDER_CLIENT_VERSION = "2.0"
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628
] | 2.744186 | 129 |
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