content
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1.04M
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|---|---|---|---|
import numpy as np
import matplotlib.pyplot as plt
import Graphic
import Core
if __name__ == "__main__":
# Set xy grid
y0 = np.linspace(-0.5, 0.5, 30)
x0 = np.linspace(-0.5, 0.5, 30)
grid = np.meshgrid(x0, y0, indexing='ij')
grid_array = np.stack(grid, axis=-1)
Domain = Core.RectangularDomain(grid_array, wrapped=True)
X, Y = grid # X and Y are matrices, while x0 and y0 are vectors
# Set initial psi and V w
d = 0.0
S = 0.1
psi0 = (angular(X, Y, 1, 1) + angular(X, Y, 1, -1)) * gaussian(X, S, 0) * gaussian(Y, S, 0)
V = 16 * (X ** 2 + Y ** 2) ** 0.5
hbar = 0.05
mass = 0.5
schrodinger_eq = [-hbar / mass * 0.5j, 0, -hbar / mass * 0.5j, 0, 1j / hbar * V.flatten()]
# build and run simulator
simulator = Calculator_legacy(Domain, schrodinger_eq, 0.005, psi0, dtype='complex')
simulator.run()
plt.show()
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if __name__=='__main__':
main() | [
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import pandas as pd
import numpy as np
import scipy.sparse as sparse
from implicit.nearest_neighbours import bm25_weight, tfidf_weight, normalize
def make_matrix(df, count=False):
"""
Args:
plu_column: string. Name of column which contains PLU
card_column: string. Name of column which contains Card numbers
Returns:
df: dataframe
"""
if count:
return df \
.pivot_table(index=['user_id'], columns=['item_id'], values='feedback', aggfunc='count') \
.reset_index(drop=True) \
.fillna(0)
else:
return df \
.pivot_table(index=['user_id'], columns=['item_id'], values='feedback') \
.reset_index(drop=True) \
.fillna(0)
def transform(matrix, method='no', clip_upper_value=100):
"""
Function transforms every single value in matrix with specified rules
Args:
matrix: Matrix to transform
method: Transformation method (no, clip)
clip_upper_value: clip upper value
Returns:
Transformed matrix
"""
if method == 'no':
return matrix
elif method == 'clip':
return matrix.clip(upper=clip_upper_value)
elif method == 'log':
return matrix.apply(np.log).clip(0, clip_upper_value)
def apply_weights(df, weight='bm25'):
"""
Function apply weights to user-item matrix
Args:
df: Matrix user-item
weight: (bm25, tf-idf, normalize) - weight method
Returns:
Weighted user-item matrix
"""
if weight == 'bm25':
crd_list = list(df.index.values)
plu_list = list(df.columns)
matrix = pd.DataFrame(bm25_weight(sparse.csr_matrix(df.to_numpy(), dtype='float16'), B=0.9).toarray())
matrix.columns = plu_list
matrix.index = crd_list
return matrix
if weight == 'tf-idf':
crd_list = list(df.index.values)
plu_list = list(df.columns)
matrix = pd.DataFrame(tfidf_weight(sparse.csr_matrix(df.to_numpy(), dtype='float16')).toarray())
matrix.columns = plu_list
matrix.index = crd_list
return matrix
if weight == 'normalize':
crd_list = list(df.index.values)
plu_list = list(df.columns)
matrix = pd.DataFrame(normalize(sparse.csr_matrix(df.to_numpy(), dtype='float16')).toarray())
matrix.columns = plu_list
matrix.index = crd_list
return matrix
def precision_at_k(preds, df_test, matrix, k=5, warm=True):
"""Calculates Precision@k, x%"""
precision_list = []
for user in matrix.index:
if warm == True:
if (user in df_test['user_id'].unique()):
pred = preds[user].tolist()
pred = pred[:k] # @k
true = df_test.loc[df_test['user_id'] == user, 'item_id'].values.tolist()
guessed = [p in true for p in pred]
precision = sum(guessed) / min(sum(true), k)
precision_list.append(precision)
else:
pred = preds[user].tolist()
pred = pred[:k] # @k
true = df_test.loc[df_test['user_id'] == user, 'item_id'].values.tolist()
guessed = [p in true for p in pred]
precision = sum(guessed) / sum(true)
precision_list.append(precision)
return np.round(np.mean(precision_list) * 100, 2) | [
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] | 2.168489 | 1,555 |
import stripe
from django.utils.encoding import smart_str
from ..models import InvoiceItem
def create(customer, amount, description, currency="usd", discountable=False, invoice=None, metadata=None, subscription=None):
"""
Creates a Stripe invoice item
Args:
customer: the customer to create the invoice for (Customer)
amount: The integer amount in cents of the charge to be applied to the upcoming invoice.
description: An arbitrary string which you can attach to the invoice item.
currency: Three-letter ISO currency code, in lowercase. Must be a supported currency.
discountable: Controls whether discounts apply to this invoice item.
invoice: The ID of an existing invoice to add this invoice item to. When left blank,
the invoice item will be added to the next upcoming scheduled invoice.
metadata: A set of key/value pairs that you can attach to an invoice item object.
subscription: The ID of a subscription to add this invoice item to. When left blank,
the invoice item will be be added to the next upcoming scheduled invoice.
Returns:
the data from the Stripe API that represents the invoice item object that
was created
"""
return stripe.InvoiceItem.create(
amount=amount,
customer=customer.stripe_id,
description=description,
currency=currency,
discountable=discountable,
invoice=invoice,
metadata=metadata,
subscription=subscription
)
def retrieve(invoiceitem_id):
"""
Retrieve an invoiceitem object from Stripe's API
Stripe throws an exception if the invoiceitem was not found, we are failing this exception
silently and raising any other exception so the developer can know what went wrong.
Args:
invoiceitem_id: the Stripe ID of the invoiceitem you are fetching
Returns:
the data for a order object from the Stripe API
"""
if not invoiceitem_id:
return
try:
return stripe.InvoiceItem.retrieve(invoiceitem_id)
except stripe.InvalidRequestError as e:
if smart_str(e).find("No such invoiceitem") == -1:
raise
else:
# Not Found
return None
def delete(invoiceitem):
"""
delete an invoiceitem
Args:
invoiceitem: the invoiceitem to delete
"""
invoice_item_id = invoiceitem.id
invoiceitem = retrieve(invoice_item_id)
if invoiceitem:
invoiceitem.delete()
try:
ii = InvoiceItem.objects.get(sttipe_id=invoice_item_id)
ii.delete()
except InvoiceItem.DoesNotExist:
pass | [
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1208
] | 2.762437 | 985 |
from PyQt5 import QtWidgets, QtCore
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
import numpy as np
from . artists import TemplateSourcePlotManual
| [
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] | 3.064103 | 78 |
# Generated by Django 2.2.2 on 2019-07-01 16:00
from django.db import migrations
import django.db.models.manager
import rdmo.views.managers
| [
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] | 2.84 | 50 |
import argparse
import sys
from emeki.project_setup import setup_project_UI
def emeki_main():
"""The main function.
It may be called directly from the command line when
typing `emeki`."""
print("Hoi! This is my personal python library.")
# Define argument parser
parser = argparse.ArgumentParser()
parser.add_argument("--init_pro", help="initialize project", action="store_true")
# Parse arguments
args = parser.parse_args(sys.argv[1:])
# Setup base project
if args.init_pro:
setup_project_UI()
def execute():
"""Calls `emeki_main` if module is called directly."""
if __name__ == "__main__":
sys.exit(emeki_main())
execute()
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] | 2.82 | 250 |
from thstatuses import STATUS, getTextFromStatus
from PyQt5.QtWidgets import QApplication
from PyQt5.QtGui import QPixmap
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from pynput.keyboard import Key, Controller
from multiprocessing.pool import ThreadPool
from thgui import Ui_MainWindow
import pygetwindow as gw
import sys, time
import requests
import pyperclip
# Define a trade class which represents one individual trade
# Setup main window and links all functions
# Start Button clicked
# Stop Button clicked
# Resume Button clicked
# Function to change the current status
# Main Loop for status
if __name__ == "__main__":
# Thread pool
pool = ThreadPool(processes=4)
# Local app and webdriver
app = QApplication(sys.argv)
driverThread = pool.apply_async(openWebDriver)
# Variables
appStatus = STATUS.LOADING
window = setupWindow()
numberOfTrades = 0
reloadTime = 3
startedAtLeastOneTrade = False
# Trades that are currently displayed on the GUI
tradeList = []
# List of all current session trades
allTradesList = []
# Initialise keyboard
keyboard = Controller()
# Status bar thread
statusThread = pool.apply_async(updateStatus)
# Terminate the program when window is closed
sys.exit(app.exec_())
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###################Calculating state average of a variable and plotting using shape file#######
##############The shapefile and data file are read; Regions are defined and masked#############
###########Zonal statistics for first state is calculated and plotted##########################
##############Zonal statistics and plot of other states are done inside a loop#################
############Give necessary plot settings, colorbar and save figure#############################
import geopandas as gpd
import regionmask
import numpy as np
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import matplotlib.patheffects as pe
import xarray as xr
import netCDF4 as nc
############### Read the data file###########################
file_name ='/mnt/d/DATA/ERA5/Wind/ERA5_Wind_2019.nc'
f = xr.open_dataset(file_name)
u10=f.u10.values
lat=f.latitude.values
lon=f.longitude.values
lat_size=len(lat)
lon_size=len(lon)
################Read the shape file##########################
fname='/mnt/e/Python_DEMO_Scripts/plotting/shpfile/Admin2.shp'
shp=gpd.read_file(fname)
#print(shp.head())
state_name=list(shp['ST_NM'])
state_1=list(shp['ST_NM'])
indexes=[state_name.index(x) for x in state_1] # Obtain state indexes
state1=regionmask.Regions(outlines=list(shp.geometry.values[i] for i in range(0, shp.shape[0])), names=shp.ST_NM[indexes],abbrevs=shp.ST_NM[indexes],name='state', ) ##Obtaining region boundaries
state1_mask=state1.mask(lon,lat) ##### State mask variable
###################Calculating first state average################
time_ind=10 ####Any time step as per need
u10_all=np.full([lat_size,lon_size],np.nan,order='C') ##Create a variable to store state averagein whole lat-lon range
result=np.where(state1_mask==0) ###Obtain indices for first state
lat_ind=result[0] # latitude index for state1
lon_ind=result[1] # longitude index for state1
u10_state=np.mean((u10[time_ind,:,:][lat_ind,:][:,lon_ind]),axis=(0,1))##Calculate state mean (single value)
u10_all[result]=u10_state ##Store state mean in the whole lat-lon range
del u10_state # delete variables for future use
del result
del lat_ind
del lon_ind
#####################Plotting Settings#############################
###############Plotting state 1 average############################
lev_min=-5 #Setting contour min,max levels and divisions
lev_max=5
lev_n=30
plt.figure(figsize=(18,8)) # Plot settings
ax=plt.axes()
x,y=np.meshgrid(lon,lat)
c=ax.contourf(x,y,u10_all,cmap='tab20b',levels=np.linspace(lev_min,lev_max,lev_n)) #Contour plot
shp.plot(ax=ax,alpha=0.8,facecolor='None',lw=1) # Shape file plot
##################Calculating and plotting remaining state average in a loop##############
for i in range(1,shp.shape[0]): ## Remaining states in a loop
result=np.where(state1_mask==i)
lat_ind=result[0]
lon_ind=result[1]
u10_state=np.mean((u10[time_ind,:,:][lat_ind,:][:,lon_ind]),axis=(0,1))
u10_all[result]=u10_state
del u10_state
ax.contourf(x,y,u10_all,cmap='tab20b',alpha=0.8,levels=np.linspace(lev_min,lev_max,lev_n))
shp.plot(ax=ax,alpha=0.8,facecolor='None',lw=1)
cbar=plt.colorbar(c) ## Give colorbar
cbar.set_label('U at 10m', rotation=270) ##Colorbar label
plt.suptitle('State Average of U Wind at 10m/s at 01/01/2019 09 UTC')
plt.title('Wind (m/s)', loc='left')
plt.xlabel('Lon')
plt.ylabel('Lat')
plt.savefig('zonal_stat_final.png')
#plt.show()
exit()
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83,
13,
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457,
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82,
379,
5534,
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8,
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87,
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43,
261,
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83,
13,
2645,
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198,
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83,
13,
21928,
5647,
10786,
89,
20996,
62,
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62,
20311,
13,
11134,
11537,
198,
2,
489,
83,
13,
12860,
3419,
198,
37023,
3419,
198
] | 2.688138 | 1,273 |
# the contents of this file will be executed when the module is run with -m.
from .xc import xc
xc()
| [
2,
262,
10154,
286,
428,
2393,
481,
307,
10945,
618,
262,
8265,
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13,
198,
198,
6738,
764,
25306,
1330,
2124,
66,
628,
198,
25306,
3419,
198
] | 3.354839 | 31 |
"""Script for data visualization.
"""
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def plot_data(data, path, ylabel="y"):
"""Plot data.
"""
fig, ax = plt.subplots()
im = ax.imshow(
data.transpose((-1, 0)),
aspect='auto',
cmap='hot',
origin='lower',
interpolation='none')
fig.colorbar(im, ax=ax)
xlabel = 'frame'
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.tight_layout()
plt.savefig(path, format='png')
plt.close("all")
| [
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220,
458,
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7,
87,
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8,
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220,
220,
220,
458,
83,
13,
2645,
9608,
7,
2645,
9608,
8,
198,
220,
220,
220,
458,
83,
13,
33464,
62,
39786,
3419,
198,
220,
220,
220,
458,
83,
13,
21928,
5647,
7,
6978,
11,
5794,
11639,
11134,
11537,
198,
220,
220,
220,
458,
83,
13,
19836,
7203,
439,
4943,
198
] | 2.145161 | 248 |
from TemporaryStorage import TemporaryStorageInstance
if __name__ == '__main__':
main()
| [
6738,
46042,
31425,
1330,
46042,
31425,
33384,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 3.518519 | 27 |
import sys
import pymongo
import projectmemcached
import time
if __name__ == "__main__":
argv = sys.argv
if len(argv) < 2:
print("Usage: python3.6 reviewapi.py mongodb_uri <listing_id>")
exit(-1)
mongodb_uri = argv[1]
listing_id = int(argv[2])
db = pymongo.MongoClient(mongodb_uri)['client_database']
print(get_review_with_listing_id(listing_id, db))
| [
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62,
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220,
220,
220,
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7,
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62,
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62,
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62,
4868,
278,
62,
312,
7,
4868,
278,
62,
312,
11,
20613,
4008,
198
] | 2.211111 | 180 |
import sys
from typing import List
from enum import Enum, auto
from parse_ctl import Parse, CmdType, DatType, BinOp, CmdValue
import logging
logging.basicConfig()
logging.root.setLevel(logging.WARNING)
logger = logging.getLogger("TCL_Machine")
from tokenizer.Tokenizer import Tokenizer, TT
print("Tcl/Forth inspired language")
# give some information about how to use from the cli
if __name__ == '__main__':
if len(sys.argv) < 3:
cli_reference()
raise Exception("Please give the right amount of parameters to the program")
machine = TCL_machine()
# give the cli args to the machine
machine.run(sys.argv[1:])
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4943,
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796,
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62,
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220,
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262,
537,
72,
26498,
284,
262,
4572,
198,
220,
220,
220,
4572,
13,
5143,
7,
17597,
13,
853,
85,
58,
16,
25,
12962,
198
] | 2.96789 | 218 |
#!/usr/bin/env python
# coding=utf-8
debugEnable = False
| [
2,
48443,
14629,
14,
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21015,
198,
2,
19617,
28,
40477,
12,
23,
198,
198,
24442,
36695,
796,
10352,
198
] | 2.636364 | 22 |
import sys
sys.path.append('../')
import bz2, os
import random, string
import importlib
import _pickle as pickle
from datetime import datetime, timedelta
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# OS & list MANAGEMENT FUNCTIONS <~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
def getFilepaths(directory):
"""
This function will generate the file names in a directory
tree by walking the tree either top-down or bottom-up. For each
directory in the tree rooted at directory top (including top itself),
it yields a 3-tuple (dirpath, dirnames, filenames).
"""
file_paths = [] # List which will store all of the full filepaths.
# Walk the tree.
for root, directories, files in os.walk(directory):
for filename in files:
# Join the two strings in order to form the full filepath.
filepath = os.path.join(root, filename)
file_paths.append(filepath) # Add it to the list.
return file_paths # Self-explanatory.
def absoluteFilePaths(directory):
'''Get the absolute file path for every file in the given directory'''
for dirpath,_,filenames in os.walk(directory):
for f in filenames:
yield os.path.abspath(os.path.join(dirpath, f))
def import_package_string(package_string):
'''Submit a string argument to be imported as a package (i.e. day_trader.models.LU01_A3). No need to include the .py'''
return importlib.import_module(package_string)
def genrs(length=10):
'''Generate random string'''
return ''.join(random.choices(string.ascii_letters + string.digits, k=length))
def remove_values_from_list(the_list, val):
'''Remove a specific value from a list'''
return [value for value in the_list if value != val]
def chunks(l,n):
'''Break list l up into chunks of size n'''
for i in range(0, len(l), n):
yield l[i:i+n]
def sizeFirstBin(data, col, minimum_bin_size, vals=None):
'''Bin the data based on the vals, iterates through each val assigning the corresponding rows to a bin while that bin size has not reached the minimum_bin_size
__________
parameters
- data : pd.DataFrame
- col : the columns to bin based on
- minimum_bin_size : int. Each bin must have at least this size
- vals : list. Will only bin the values in this list. The default is all the unique values of "col"
'''
if vals is None:
values = sorted(data[col].unique())
else:
values = vals
bins = {}
bin_number = 1
bin_total = 0
vc = dict(data[col].value_counts())
for val in values:
if bin_total<minimum_bin_size:
if bin_number not in bins:
bins[bin_number] = []
bins[bin_number].append(val)
bin_total += vc[val]
else:
bins[bin_number].append(val)
bin_total += vc[val]
else:
bin_number+=1
bins[bin_number] = []
bins[bin_number].append(val)
bin_total = vc[val]
return bins
def nondups(items : list):
'''Return True if list has no duplicate items'''
print('List length:',len(items))
print('Unique items:',len(set(items)))
return len(items) == len(set(items))
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# Storage & COMPRESSION FUNCTIONS <~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# Article on pickling and compressed pickling functions
# https://betterprogramming.pub/load-fast-load-big-with-compressed-pickles-5f311584507e
def full_pickle(title, data):
'''pickles the submited data and titles it'''
pikd = open(title + '.pickle', 'wb')
pickle.dump(data, pikd)
pikd.close()
def loosen(file):
'''loads and returns a pickled objects'''
pikd = open(file, 'rb')
data = pickle.load(pikd)
pikd.close()
return data
def compressed_pickle(title, data):
'''
Pickle a file and then compress it into a file with extension .pbz2
__________
parameters
- title : title of the file you want to save (will be saved with .pbz2 extension automatically)
- data : object you want to save
'''
with bz2.BZ2File(title + '.pbz2', 'w') as f:
pickle.dump(data, f)
def decompress_pickle(filename):
'''filename - file name including .pbz2 extension'''
data = bz2.BZ2File(filename, 'rb')
data = pickle.load(data)
return data
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# Time Management FUNCTIONS <~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~
# ~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<~<
# Time Stuff
def cuttomin(x):
'''Cut a time stamp at the minutes (exclude seconds or more precise)'''
return datetime.strftime(x, '%m-%d %H:%M')
def cuttohrs(x):
'''Cut a time stamp at the hours (exclude minutes or more precise)'''
return datetime.strftime(x, '%m-%d %H')
def cuttodays(x):
'''Cut a time stamp at the date (exclude hour or more precise)'''
return datetime.strftime(x, '%y-%m-%d')
def datetime_range(start, end, delta):
'''Returns the times between start and end in steps of delta'''
current = start
while current < end:
yield current
current += delta
def prev_weekday(adate):
'''Returns the date of the last weekday before the given date'''
adate -= timedelta(days=1)
while adate.weekday() > 4: # Mon-Fri are 0-4
adate -= timedelta(days=1)
return adate
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] | 2.086165 | 2,855 |
import click
from deploy_tools.cli import (
auto_nonce_option,
connect_to_json_rpc,
gas_option,
gas_price_option,
get_nonce,
jsonrpc_option,
keystore_option,
nonce_option,
retrieve_private_key,
)
from deploy_tools.deploy import build_transaction_options
from deploy_tools.files import (
InvalidAddressException,
read_addresses_in_csv,
validate_and_format_address,
)
from web3 import EthereumTesterProvider, Web3
from validator_set_deploy.core import (
deploy_validator_proxy_contract,
deploy_validator_set_contract,
get_validator_contract,
initialize_validator_set_contract,
)
# we need test_provider and test_json_rpc for running the tests in test_cli
# they need to persist between multiple calls to runner.invoke and are
# therefore initialized on the module level.
test_provider = EthereumTesterProvider()
test_json_rpc = Web3(test_provider)
def validate_address(
ctx, param, value
): # TODO: take this from deploy_tools once new version is available
"""This function must be at the top of click commands using it"""
try:
return validate_and_format_address(value)
except InvalidAddressException as e:
raise click.BadParameter(
f"The address parameter is not recognized to be an address: {value}"
) from e
validator_set_address_option = click.option(
"--address",
"validator_contract_address",
help='The address of the validator set contract, "0x" prefixed string',
type=str,
required=True,
callback=validate_address,
metavar="ADDRESS",
envvar="VALIDATOR_CONTRACT_ADDRESS",
)
validator_file_option = click.option(
"--validators",
"validators_file",
help="Path to the csv file containing the addresses of the validators",
type=click.Path(exists=True, dir_okay=False),
required=True,
)
@click.group()
@main.command(
short_help="Deploys the validator set and initializes with the validator addresses."
)
@keystore_option
@validator_file_option
@click.option(
"--address",
"validator_proxy_address",
help='The address of the validator proxy contract, "0x" prefixed string',
type=str,
required=True,
callback=validate_address,
metavar="ADDRESS",
envvar="VALIDATOR_PROXY_ADDRESS",
)
@gas_option
@gas_price_option
@nonce_option
@auto_nonce_option
@jsonrpc_option
@main.command(
short_help="Deploys the validator proxy and initializes with the validator addresses "
"within the given validator csv file."
)
@keystore_option
@click.option(
"--validators",
"validators_file",
help="Path to the csv file containing the addresses of the validators",
type=click.Path(),
required=False,
)
@gas_option
@gas_price_option
@nonce_option
@auto_nonce_option
@jsonrpc_option
@main.command(
short_help="Check that the current validators of the contract are matching the one in the given file."
)
@validator_set_address_option
@validator_file_option
@jsonrpc_option
@main.command(short_help="Prints the current validators.")
@validator_set_address_option
@jsonrpc_option
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# -*- coding: utf-8 -*-
"""
Unit Test: orchard.system_status.formatters.temperature
"""
import unittest
import flask_babel
import orchard
import orchard.system_status.formatters.temperature as formatter
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from typing import Dict, List, Tuple
from collections import defaultdict
from django.db import models
from django.db.models.fields.related_descriptors import ManyToManyDescriptor
from dotdict import DotDict
from .sorter import Sorter
from .model_importer import ModelImporter
from .importer_manager import ImporterManager
#: TODO: delete the commented delimiter for the following reasons, AFTER documenting how to specify multiple fields
# (TODO) for an object referenced in a m2m relationship
# I think this is unnecesary, if you want multiple fields to be specifiable,
# you need to put them in separate chuncks of 'a;a;a;a , b;b;b;b'
# M2M_FIELD_DELIMITER = '|'
#: TODO: Move to a settings file, which can be overridden
M2M_DELIMITER = ';'
DEFAULT_DELIMITER = ',' | [
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] | 3.19917 | 241 |
# author: Bartlomiej "furas" Burek (https://blog.furas.pl)
# date: 2021.05.30
#
# title: How to add text in a “textbox” to an image?
# url: https://stackoverflow.com/questions/67760340/how-to-add-text-in-a-textbox-to-an-image/67762111#67762111
import PIL
print('PIL version:', PIL.__version__)
from PIL import Image, ImageDraw, ImageFont
# create empty image
img = Image.new(size=(400, 300), mode='RGB')
draw = ImageDraw.Draw(img)
# draw white rectangle 200x100 with center in 200,150
draw.rectangle((200-100, 150-50, 200+100, 150+50), fill='white')
draw.line(((0, 150), (400, 150)), 'gray')
draw.line(((200, 0), (200, 300)), 'gray')
# find font size for text `"Hello World"` to fit in rectangle 200x100
selected_size = 1
for size in range(1, 150):
arial = ImageFont.FreeTypeFont('/home/furas/.wine/drive_c/windows/Fonts/arial.ttf', size=size)
w, h = arial.getsize("Hello World") # older versions
left, top, right, bottom = arial.getbbox("Hello World") # needs PIL 8.0.0
#w = right - left
#h = bottom - top
print(w, h)
if w > 200 or h > 100:
break
selected_size = size
print(arial.size)
# draw text in center of rectangle 200x100
arial = ImageFont.FreeTypeFont('/home/furas/.wine/drive_c/windows/Fonts/arial.ttf', size=selected_size)
draw.text((200-w//2, 150-h//2), "Hello World", fill='black', font=arial) # older versions
img.save('center-older-getsize.png')
#draw.text((200, 150), "Hello World", fill='black', anchor='mm', font=arial)
#img.save('center-newer.png')
img.show()
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] | 2.521739 | 621 |
from configs.Config import Config
| [
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] | 4.375 | 8 |
import sys
import pathlib
import argparse
import gzip
import json
import requests
import datadiff
import pysmata.loader as loader
import pysmata.files
if __name__ == "__main__":
main()
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from rx import AnonymousObservable, Observable
from rx.internal import extensionmethod
@extensionmethod(Observable)
def default_if_empty(self, default_value=None):
"""Returns the elements of the specified sequence or the specified value
in a singleton sequence if the sequence is empty.
res = obs = xs.defaultIfEmpty()
obs = xs.defaultIfEmpty(False
Keyword arguments:
default_value -- The value to return if the sequence is empty. If not
provided, this defaults to None.
Returns an observable {Observable} sequence that contains the specified
default value if the source is empty otherwise, the elements of the
source itself.
"""
source = self
return AnonymousObservable(subscribe)
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220,
220,
220,
1441,
19200,
31310,
712,
540,
7,
7266,
12522,
8,
198
] | 3.428571 | 217 |
# coding: utf-8
"""
CONS3RT Web API
A CONS3RT ReSTful API # noqa: E501
The version of the OpenAPI document: 1.0.0
Contact: [email protected]
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import unittest
import cons3rt
from cons3rt.api.test_assets_api import TestAssetsApi # noqa: E501
from cons3rt.rest import ApiException
class TestTestAssetsApi(unittest.TestCase):
"""TestAssetsApi unit test stubs"""
def test_add_test_asset_trusted_project(self):
"""Test case for add_test_asset_trusted_project
"""
pass
def test_get_test_asset(self):
"""Test case for get_test_asset
Retrieve test asset # noqa: E501
"""
pass
def test_get_test_assets(self):
"""Test case for get_test_assets
List test assets # noqa: E501
"""
pass
def test_get_test_assets_expanded(self):
"""Test case for get_test_assets_expanded
List all test assets, including project assets # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
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10354,
198,
220,
220,
220,
555,
715,
395,
13,
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3419,
198
] | 2.376033 | 484 |
from qtpy import QtCore
from qtpy.QtGui import *
from qtpy.QtWidgets import *
from cidan.GUI.ListWidgets.ClassItemModule import ClassItemModule
from cidan.GUI.ListWidgets.ClassItemWidget import ClassItemWidget
class ClassListModule(QFrame):
"""
Its the class list in the Class modification tab
"""
# def set_current_select(self, num):
# self.list.setCurrentIndex(self.model.index(int(num - 1), 0))
# self.class_time_check_list[num - 1] = not self.class_time_check_list[num - 1]
# self.class_item_list[num - 1].select_check_box()
# # self.class_module_list[num-1].
# if self.display_time:
# self.class_item_list[num - 1].select_time_check_box()
# def change(self):
# # This is a way of running the select class function when a checkbox is clicked there
# # needed to be a work around because can't just connect a signal to it
# for num, item, check_val in zip(range(1,len(self.class_time_check_list)+1),self.class_item_list,self.class_time_check_list):
# if item.checkState() != check_val:
# self.class_time_check_list[num-1] = item.checkState()
# if item.checkState():
# self.classifier_tab.selectRoi(num)
# else:
# self.classifier_tab.deselectRoi(num)
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2771,
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] | 2.332759 | 580 |
"""Implementation of the replaceitem command."""
from mcipc.rcon.be.types import EntityEquipmentSlot, ReplaceMode
from mcipc.rcon.client import Client
from mcipc.rcon.proxy import CommandProxy
from mcipc.rcon.types import Vec3
__all__ = ['ReplaceitemProxy', 'replaceitem']
class ReplaceitemProxy(CommandProxy):
"""Proxy for replaceitem related commands."""
# pylint: disable=R0913
def block(self, position: Vec3, slot_id: int, item_name: str,
amount: int = None, data: int = None, components: dict = None,
*, old_item_handling: ReplaceMode = None) -> str:
"""Replaces a block."""
command = ['block', position, 'slot.container', slot_id]
if old_item_handling is not None:
command.append(old_item_handling)
return self._run(*command, item_name, amount, data, components)
def entity(self, target: str, slot_type: EntityEquipmentSlot, slot_id: int,
item_name: str, amount: int = None, data: int = None,
components: dict = None, *,
old_item_handling: ReplaceMode = None) -> str:
"""Replaces an item."""
command = ['entity', target, slot_type, slot_id]
if old_item_handling is not None:
command.append(old_item_handling)
return self._run(*command, item_name, amount, data, components)
def replaceitem(self: Client) -> ReplaceitemProxy:
"""Delegates to a
:py:class:`mcipc.rcon.be.commands.replaceitem.ReplaceitemProxy`
"""
return ReplaceitemProxy(self, 'replaceitem')
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8,
628,
220,
220,
220,
220,
220,
220,
220,
1441,
2116,
13557,
5143,
46491,
21812,
11,
2378,
62,
3672,
11,
2033,
11,
1366,
11,
6805,
8,
628,
198,
4299,
6330,
9186,
7,
944,
25,
20985,
8,
4613,
40177,
9186,
44148,
25,
198,
220,
220,
220,
37227,
5005,
37061,
284,
257,
198,
220,
220,
220,
1058,
9078,
25,
4871,
25,
63,
23209,
541,
66,
13,
81,
1102,
13,
1350,
13,
9503,
1746,
13,
33491,
9186,
13,
3041,
5372,
9186,
44148,
63,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1441,
40177,
9186,
44148,
7,
944,
11,
705,
33491,
9186,
11537,
198
] | 2.566285 | 611 |
if __name__ == '__main__':
fun_while()
| [
198,
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361,
11593,
3672,
834,
6624,
705,
834,
12417,
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220,
220,
220,
1257,
62,
4514,
3419,
198,
220,
220,
220,
220
] | 1.96 | 25 |
print(df.groupby('station').temperature.min())
print(df.groupby('station').temperature.max())
print(df.groupby('station').temperature.std())
| [
4798,
7,
7568,
13,
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] | 3.133333 | 45 |
import pytest
import dependencies
import sys
sys.path.insert(0, dependencies.program_path)
from src import RoomObject as rObject
from src import Room as r
| [
11748,
12972,
9288,
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10267,
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6738,
12351,
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] | 3.651163 | 43 |
from django.db import models
| [
6738,
42625,
14208,
13,
9945,
1330,
4981,
628,
628,
628,
628,
628
] | 3.166667 | 12 |
r"""
Given a positive integer num, write a function which returns True if num is a perfect square else False.
Follow up: Do not use any built-in library function such as sqrt.
Example 1:
Input: num = 16
Output: true
Example 2:
Input: num = 14
Output: false
Constraints:
1 <= num <= 2^31 - 1
"""
# Submitted:
# https://leetcode.com/submissions/detail/341903032/?from=/explore/challenge/card/may-leetcoding-challenge/535/week-2-may-8th-may-14th/3324/
# https://leetcode.com/submissions/detail/341905412/?from=/explore/challenge/card/may-leetcoding-challenge/535/week-2-may-8th-may-14th/3324/
from collections import defaultdict
from typing import Iterator, DefaultDict, Callable
# ceil(sqrt(2**31 - 1))
max_sqrt = 46341
squares = squares_gen()
| [
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14,
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14,
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4277,
11600,
198,
6738,
19720,
1330,
40806,
1352,
11,
15161,
35,
713,
11,
4889,
540,
198,
198,
2,
2906,
346,
7,
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7,
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532,
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628,
198,
198,
16485,
3565,
796,
24438,
62,
5235,
3419,
628
] | 2.801471 | 272 |
from django.db import models
from ckeditor.fields import RichTextField
# Create your models here.
| [
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from __future__ import absolute_import
from .number import randomPN
from .gid import calcAge
from .passwd import randomPW | [
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# -*- coding: utf-8 -*-
import django
from django.conf import settings
from django.utils.functional import keep_lazy
if django.VERSION >= (1, 5):
from django.contrib.auth import get_user_model
AUTH_USER_MODEL = settings.AUTH_USER_MODEL
get_user_model = keep_lazy(AUTH_USER_MODEL)(get_user_model)
get_username_field = keep_lazy(str)(lambda: get_user_model().USERNAME_FIELD)
else:
from django.contrib.auth.models import User
AUTH_USER_MODEL = 'auth.User'
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220,
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62,
29904,
62,
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6,
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] | 2.603261 | 184 |
from Membership import sad,memberships
import defuzzify
import rule
import itertools
if __name__ == "__main__":
x = FLC(70, 15, 30)
x.evaluate()
| [
6738,
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] | 2.736842 | 57 |
import argparse
from FCNetwork import FCNetwork
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--sizes",
default=[
# 3*28*28,
# 2*28*28,
14*28],
type=list)
parser.add_argument(
"--labels_path",
default='5_classes/labels',
type=str)
parser.add_argument(
"--pretrained_path",
default='5_classes/checkpoints_fc_3/pass_25.ckpt',
type=str)
parser.add_argument(
"--test_data_path",
default='5_classes/test',
type=str)
parser.add_argument(
"--output_path",
default='./',
type=str)
parser.add_argument(
"--use_gpu",
default=True,
type=bool)
parser.add_argument(
"--img_size",
default=28,
type=int)
args = parser.parse_args()
nn = FCNetwork(label_path=args.labels_path,
pretrained_path=args.pretrained_path,
use_gpu=args.use_gpu,
img_size=args.img_size)
nn.create(args.sizes)
statisctic_report = nn.get_statistics(args.test_data_path)
print(statisctic_report)
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220,
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220,
220,
220,
779,
62,
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13,
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62,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
33705,
62,
7857,
28,
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13,
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62,
7857,
8,
198,
220,
220,
220,
299,
77,
13,
17953,
7,
22046,
13,
82,
4340,
8,
198,
220,
220,
220,
1185,
271,
11048,
62,
13116,
796,
299,
77,
13,
1136,
62,
14269,
3969,
7,
22046,
13,
9288,
62,
7890,
62,
6978,
8,
198,
220,
220,
220,
3601,
7,
14269,
271,
11048,
62,
13116,
8,
198
] | 1.895801 | 643 |
'''
Copyright 2022 Airbus SAS
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 unittest
import numpy as np
import pandas as pd
from os.path import join, dirname
from pandas import read_csv
from sos_trades_core.execution_engine.execution_engine import ExecutionEngine
# for graph in graph_list:
# graph.to_plotly().show()
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] | 3.401639 | 244 |
#!/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.
#
"""Tests for google.apphosting.tools.devappserver2.inotify_file_watcher."""
import logging
import os
import os.path
import shutil
import sys
import tempfile
import unittest
from google.appengine.tools.devappserver2 import inotify_file_watcher
@unittest.skipUnless(sys.platform.startswith('linux'), 'requires linux')
class TestInotifyFileWatcher(unittest.TestCase):
"""Tests for inotify_file_watcher.InotifyFileWatcher."""
def _create_directory_tree(self, path, num_directories):
"""Create exactly num_directories subdirectories in path."""
assert num_directories >= 0
if not num_directories:
return
self._create_directory(path)
num_directories -= 1
# Divide the remaining number of directories to create among 4
# subdirectories in an approximate even fashion.
for i in range(4, 0, -1):
sub_dir_size = num_directories/i
self._create_directory_tree(os.path.join(path, 'dir%d' % i), sub_dir_size)
num_directories -= sub_dir_size
def test_subdirectory_deleted(self):
"""Tests that internal _directory_to_subdirs is updated on delete."""
path = self._create_directory('test')
sub_path = self._create_directory('test/test2')
self._watcher.start()
self.assertEqual(
set([sub_path]),
self._watcher._directory_to_subdirs[path])
os.rmdir(sub_path)
self.assertEqual(
set([sub_path]),
self._watcher._get_changed_paths())
self.assertEqual(
set(),
self._watcher._directory_to_subdirs[path])
os.rmdir(path)
self.assertEqual(
set([path]),
self._watcher._get_changed_paths())
if __name__ == '__main__':
unittest.main()
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] | 2.818519 | 810 |
#
# Copyright 2016 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.
DATASTORE_USER = 'User'
DATASTORE_PHOTO = 'Photo'
DATASTORE_MOVIE = 'Movie'
DATASTORE_ORIENTED_IMAGE = 'ProcessedImage'
# Movie daemon properties
TOTALITY_IMAGE_TYPE = "totality"
TOTALITY_ORDERING_PROPERTY = "adj_timestamp"
ALLOWED_ENTITIES = {
DATASTORE_USER: {
'deleted': {'restricted': True},
'deleted_date': {'restricted': True},
'geolat': {'restricted': False},
'geolng': {'restricted': False},
'badges': {'restricted': True}
},
DATASTORE_PHOTO: {
'gcs_upload_failed': {'restricted': False},
'in_gcs': {'restricted': False},
'processed': {'restricted': False},
'uploaded_date': {'restricted': False},
'user': {'restricted': True},
'image_type': {'restricted': True},
'width': {'restricted': True},
'height': {'restricted': True},
'image_datetime': {'restricted': True},
'lat': {'restricted': True},
'lon': {'restricted': True},
'exif_json': {'restricted': True},
'reviews': {'restricted': True},
'num_reviews': {'restricted': True},
'upload_session_id': {'restricted': True},
'image_bucket': {'restricted': True},
'original_filename': {'restricted': True},
'confirmed_by_user': {'restricted': True},
'is_adult_content': {'restricted': True},
'public_agree': {'restricted': True},
'cc0_agree': {'restricted': True},
'anonymous_photo': {'restricted': True},
'equatorial_mount': { 'restricted': True},
'camera_datetime': { 'restricted': True},
'datetime_repaired': { 'restricted': True},
},
DATASTORE_ORIENTED_IMAGE: {
'upload_date': {'restricted': False},
'original_photo': {'restricted': True},
'img_type': {'restricted': False},
TOTALITY_ORDERING_PROPERTY: {'restricted': False},
},
DATASTORE_MOVIE: {
'contributors': {'restricted': False},
},
}
JSON_MAPPINGS = {
DATASTORE_USER: (
('geolat', 'v', float),
('geolng', 'h', float),
),
}
def validate_data(data, allow_restricted_fields, kind):
"""
Check that all the fields in `data` correspond to fields in
`ALLOWED_ENTITIES[kind]`. `data` is a dictionary/dictionary subclass, `kind`
is the datastore entity kind. `allow_restricted_fields` is a bool.
"""
if kind not in ALLOWED_ENTITIES:
print "invalid kind:", kind
return False
for key in data:
if key not in ALLOWED_ENTITIES[kind]:
print "invalid key:", key
return False
if (ALLOWED_ENTITIES[kind][key]['restricted']
and not allow_restricted_fields):
print "invalid restricted", kind, key, allow_restricted_fields
return False
return True
| [
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220,
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] | 2.473338 | 1,369 |
from Hackdavis.ab_recipes import Recipes
# name, type, ingredients, url
if __name__ == "__main__":
s = Simplyrecipes('https://www.simplyrecipes.com/recipes/mexican_red_chili_sauce/')
print(s.find_ingredients()) | [
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# -*- coding: utf-8 -*-
from zope.interface import alsoProvides
from collective.transmogrifier.transmogrifier import Transmogrifier
from plone.protect.interfaces import IDisableCSRFProtection
from Products.Five.browser import BrowserView
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] | 3.333333 | 72 |
import logging
import re
import hashlib
from appAux import loadFile, toHex
logger = logging.getLogger(__name__) | [
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] | 3.111111 | 36 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Feb 13 22:07:00 2021
@authors: Ali Kamali
Sara Baradaran
Mahdi Heidari
"""
import angr,claripy
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] | 2.141176 | 85 |
from flask import Flask, request, abort
from datetime import datetime
import pytz
app = Flask(__name__)
@app.route('/')
if __name__ == '__main__':
app.run(ssl_context=("/etc/demo/ssl/blueapron.crt",
"/etc/demo/ssl/blueapron.key"), host='0.0.0.0')
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] | 2.20155 | 129 |
from probability import with_probability
import random
| [
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] | 4.666667 | 12 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""The setup script."""
import os
import re
from setuptools import find_packages, setup
REQUIREMENTS = []
SETUP_REQUIREMENTS = []
TEST_REQUIREMENTS = []
DEV_REQUIREMENTS = ["bumpversion", "pre-commit", "tox"]
with open("README.rst") as readme_file:
README = readme_file.read()
with open(os.path.join("{{ cookiecutter.project_name }}", '__version__.py'), 'rt') as f:
VERSION = re.search(r"""__version__\s=\s['"](.+)['"]""", f.read()).group(1)
{%- set license_classifiers = {
"MIT": "License :: OSI Approved :: MIT License",
"BSD": "License :: OSI Approved :: BSD License",
"ISC": "License :: OSI Approved :: ISC License (ISCL)"
} %}
setup(
author="{{ cookiecutter.full_name.replace('\"', '\\\"') }}",
author_email="{{ cookiecutter.email }}",
classifiers=[
"Development Status :: 2 - Pre-Alpha",
"Intended Audience :: Developers",
{%- if cookiecutter.open_source_license in license_classifiers %}
"{{ license_classifiers[cookiecutter.open_source_license] }}",
{%- endif %}
{%- if cookiecutter.support_python2 != "n" %}
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.7",
{%- endif %}
"Programming Language :: Python :: 3",
{%- if cookiecutter.minimum_python_version|float <= 3.6 %}
"Programming Language :: Python :: 3.6",
{%- endif %}
{%- if cookiecutter.minimum_python_version|float <= 3.7 %}
"Programming Language :: Python :: 3.7",
{%- endif %}
],
description="{{ cookiecutter.project_short_description }}",
{%- if cookiecutter.command_line_interface|lower == 'y' %}
entry_points={"console_scripts": ["{{ cookiecutter.project_name }}={{ cookiecutter.project_name }}.__main__:main"]},
{%- endif %}
install_requires=REQUIREMENTS,
{%- if cookiecutter.open_source_license in license_classifiers %}
license="{{ cookiecutter.open_source_license }}",
{%- endif %}
long_description=README,
include_package_data=True,
keywords="{{ cookiecutter.project_name }}",
name="{{ cookiecutter.project_name }}",
packages=find_packages(),
setup_requires=SETUP_REQUIREMENTS,
tests_require=TEST_REQUIREMENTS,
extras_require={"dev": DEV_REQUIREMENTS},
url="https://github.com/{{ cookiecutter.github_username }}/{{ cookiecutter.project_name }}",
version=VERSION,
)
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] | 2.687289 | 889 |
import torch, cv2
from PIL import Image, ImageDraw
import numpy as np
from shapely.geometry import Polygon, MultiPoint, MultiPolygon
from .boxes import dists_pt2line_numpy, dists2corners_numpy
# ref: https://github.com/MhLiao/TextBoxes_plusplus/blob/master/examples/text/nms.py
def quads_iou(a, b):
"""
:param a: Box Tensor, shape is (nums, 8)
:param b: Box Tensor, shape is (nums, 8)
IMPORTANT: Note that 8 means (topleft=(x1, y1), x2, y2,..clockwise)
:return:
iou: Tensor, shape is (a_num, b_num)
formula is
iou = intersection / union
"""
# convert Tensor to numpy for using shapely
a_numpy, b_numpy = a.cpu().numpy(), b.cpu().numpy()
a_number, b_number = a_numpy.shape[0], b_numpy.shape[0]
ret = np.zeros(shape=(a_number, b_number), dtype=np.float32)
a_numpy, b_numpy = a_numpy.reshape((-1, 4, 2)), b_numpy.reshape((-1, 4, 2))
for i in range(a_number):
a_polygon = Polygon(a_numpy[i]).convex_hull
for j in range(b_number):
b_polygon = Polygon(b_numpy[j]).convex_hull
if not a_polygon.intersects(b_polygon):
continue
intersectionArea = a_polygon.intersection(b_polygon).area
unionArea = MultiPoint(np.concatenate((a_numpy[i], b_numpy[j]))).convex_hull.area
if unionArea == 0:
continue
ret[i, j] = intersectionArea / unionArea
return torch.from_numpy(ret)
def sort_clockwise_topleft(a):
"""
Sort corners points (xmin, ymin, xmax, ymax)
:param a: Quads Tensor, shape is ([nums, ]*, 4=(x1,y1,x2,y2))
:return a: Quads Tensor, shape is ([nums, ]*, 4=(xmin, ymin, xmax, ymax))
"""
return torch.from_numpy(sort_clockwise_topleft_numpy(a.numpy()))
def sort_clockwise_topleft_numpy(a):
"""
Sort corners points (x1, y1, x2, y2, ... clockwise from topleft)
:ref https://gist.github.com/flashlib/e8261539915426866ae910d55a3f9959
:param a: Quads ndarray, shape is (box nums, 8=(x1,y1,x2,y2,...))
:return a: Quads ndarray, shape is (box nums, 8=(x1,y1,x2,y2,... clockwise from topleft))
"""
reshaped_a = a.reshape((-1, 4, 2))
# sort the points based on their x-coordinates
# shape = (box_nums, 4=points_nums, 1), the indices about 4 points
x_ascend_indices = np.argsort(reshaped_a[..., 0:1], axis=1)
# that's why take_along_axis's argument: axis is 1
# shape = (box_nums, 4=(x_ascending), 2=(x,y))
x_ascend = np.take_along_axis(reshaped_a, x_ascend_indices, axis=1)
# grab the left-most and right-most points from the sorted
# x-roodinate points
# shape = (box_nums, 2, 2=(x,y))
leftMost = x_ascend[:, :2]
rightMost = x_ascend[:, 2:]
# now, sort the left-most coordinates according to their
# y-coordinates so we can grab the top-left and bottom-left
# points, respectively
# shape = (box_nums, 2=points_nums), the indices about 2 points
leftMost_y_ascend_indices = np.argsort(leftMost[..., 1:2], axis=1)
# shape = (box_nums, 2, 2=(x,y))
leftMost_y_ascend = np.take_along_axis(leftMost, leftMost_y_ascend_indices, axis=1)
# shape = (box_nums, 1, 2=(x,y))
tl, bl = leftMost_y_ascend[:, 0:1], leftMost_y_ascend[:, 1:2]
# if use Euclidean distance, it will run in error when the object
# is trapezoid. So we should use the same simple y-coordinates order method.
# now, sort the right-most coordinates according to their
# y-coordinates so we can grab the top-right and bottom-right
# points, respectively
# shape = (box_nums, 2=points_nums), the indices about 2 points
rightMost_y_ascend_indices = np.argsort(rightMost[..., 1:2], axis=1)
# shape = (box_nums, 2, 2=(x,y))
rightMost_y_ascend = np.take_along_axis(rightMost, rightMost_y_ascend_indices, axis=1)
# shape = (box_nums, 1, 2=(x,y))
tr, br = rightMost_y_ascend[:, 0:1], rightMost_y_ascend[:, 1:2]
# return the coordinates in top-left, top-right,
# bottom-right, and bottom-left order
sorted_a = np.concatenate([tl, tr, br, bl], axis=1).reshape((-1, 8))
"""
# :ref https://stackoverflow.com/questions/10846431/ordering-shuffled-points-that-can-be-joined-to-form-a-polygon-in-python
# below code is using arctan from centroids, but this method is not applicable for image-coordinates system?
box_nums = a.shape[0]
centroids = np.concatenate((a[:, ::2].mean(axis=-1, keepdims=True),
a[:, 1::2].mean(axis=-1, keepdims=True)), axis=-1)
sorted_a = np.zeros_like(a, dtype=np.float32)
reshaped_a = a.reshape((-1, 4, 2))
for b in range(box_nums):
sorted_a[b] = np.array(sorted(reshaped_a[b], key=lambda pt: np.arctan2(pt[1]-centroids[b,1], pt[0]-centroids[b,0])))
"""
return sorted_a
def quad2mask(quad, w, h, device):
"""
:param quad: Tensor, shape = (8=(x1,y1,...)), percent style
:param w: int
:param h: int
:param device: device
:return: mask_per_rect: Bool Tensor, shape = (h, w)
"""
return torch.from_numpy(quad2mask_numpy(quad.numpy(), w, h)).to(device=device)
def quad2mask_numpy(quad, w, h):
"""
:param quad: ndarray, shape = (8=(x1,y1,...)), percent style
:param w: int
:param h: int
:return: mask_per_rect: Bool ndarray, shape = (h, w)
"""
_quad = quad.copy()
_quad[::2] *= w
_quad[1::2] *= h
img = Image.new('L', (w, h), 0)
ImageDraw.Draw(img).polygon(_quad, outline=255, fill=255)
# img.show()
return np.array(img, dtype=np.bool)
def quads2allmask(quads, w, h, device):
"""
:param quads: Tensor, shape = (box num, 8=(x1,y1,...)), percent style
:param w: int
:param h: int
:param device: device
:return: mask_per_rect: Bool Tensor, shape = (h, w)
"""
return torch.from_numpy(quads2allmask_numpy(quads.numpy(), w, h)).to(device=device)
def quads2allmask_numpy(quads, w, h):
"""
:param quads: ndarray, shape = (box num, 8=(x1,y1,...)), percent style
:param w: int
:param h: int
:return: mask_per_rect: Bool ndarray, shape = (h, w)
"""
box_nums = quads.shape[0]
ret = np.zeros((h, w), dtype=np.bool)
for b in range(box_nums):
ret = np.logical_or(ret, quad2mask_numpy(quads[b], w, h))
return ret
def angles_from_quads_numpy(quads):
"""
:param quads: ndarray, shape = (box nums, 8=(x1,y1,... clockwose from top-left))
:return angles: ndarray, shape = (box nums, 1)
Note that angle range is [-pi/4, pi/4)
"""
box_nums = quads.shape[0]
angles = np.zeros((box_nums, 1))
reshaped_quads = quads.reshape((-1, 4, 2))
for b in range(box_nums):
rect = cv2.minAreaRect(reshaped_quads[b])
# note that angle range is (0, 90]
angle = -rect[-1]
if angle == 90:
angle = 0
angles[b, 0] = angle if angle < 45 else -(90 - angle)
return np.deg2rad(angles)
def shrink_quads_numpy(quads, scale=0.3):
"""
convert quads into rbox, see fig4 in EAST paper
Brief summary of rbox creation from quads
1. compute reference lengths (ref_lengths) by getting shorter edge adjacent one point
2. shrink longer edge pair* with scale value
*: longer pair is got by comparing between two opposing edges following;
(vertical edge1 + 2)ave <=> (horizontal edge1 + 2)ave
Note that shrinking way is different between vertical edges pair and horizontal one
horizontal: (x_i, y_i) += scale*(ref_lengths_i*cos + ref_lengths_(i mod 4 + 1)*sin)
vertical: (x_i, y_i) += scale*(ref_lengths_i*sin + ref_lengths_(i mod 4 + 1)*cos)
:param quads: ndarray, shape = (box nums, 8=(x1,y1,...clockwise order))
:param scale: int, shrink scale
:return: shrinked_quads: ndarray, shape = (box nums, 8=(x1,y1,...clockwise order))
"""
reshaped_quads = quads.reshape((-1, 4, 2))
# reference lengths, clockwise from horizontal top edge
# shape = (box nums, 4)
ref_lengths = np.minimum(np.linalg.norm(reshaped_quads - np.roll(reshaped_quads, 1, axis=1), axis=-1),
np.linalg.norm(reshaped_quads - np.roll(reshaped_quads, -1, axis=1), axis=-1))
def _shrink_h(quad, ref_len):
"""
:param quad: ndarray, shape = (4, 2)
:param ref_len: ndarray, shape = (4,)
"""
# get angle
adj_quad = np.roll(quad[::-1], 2, axis=0) # adjacent points
# shape = (4,)
angles = np.arctan2(adj_quad[:, 1] - quad[:, 1], adj_quad[:, 0] - quad[:, 0])
# shape = (4,2)
trigonometric = np.array([np.cos(angles),
np.sin(angles)]).T
quad += np.expand_dims(ref_len, axis=-1) * trigonometric * scale
return quad
def _shrink_v(quad, ref_len):
"""
:param quad: ndarray, shape = (4, 2)
:param ref_len: ndarray, shape = (4,)
"""
# get angle
adj_quad = quad[::-1] # adjacent points
# shape = (4,)
angles = np.arctan2(adj_quad[:, 0] - quad[:, 0], adj_quad[:, 1] - quad[:, 1])
# shape = (4,2)
trigonometric = np.array([np.sin(angles),
np.cos(angles)]).T
quad += np.expand_dims(ref_len, axis=-1) * trigonometric * scale
return quad
def _shrink(quad, ref_len, horizontal_first):
"""
:param quad: ndarray, shape = (4, 2)
:param ref_len: ndarray, shape = (4,)
:param horizontal_first: boolean, if True, horizontal edges will be shrunk first, otherwise vertical ones will be shrunk first
:return:
"""
if horizontal_first:
quad = _shrink_h(quad, ref_len)
quad = _shrink_v(quad, ref_len)
else:
quad = _shrink_v(quad, ref_len)
quad = _shrink_h(quad, ref_len)
return quad
box_nums = reshaped_quads.shape[0]
# lengths, clockwise from horizontal top edge
# shape = (box nums, 4)
lengths = np.linalg.norm(reshaped_quads - np.roll(reshaped_quads, 1, axis=1), axis=-1)
h_lens, v_lens = np.mean(lengths[:, ::2], axis=-1), np.mean(lengths[:, 1::2], axis=-1)
horizontal_firsts = h_lens > v_lens
shrinked_quads = np.array([_shrink(reshaped_quads[b], ref_lengths[b], horizontal_firsts[b]) for b in range(box_nums)])
return shrinked_quads.reshape((-1, 8))
def quads2rboxes_numpy(quads, w, h, shrink_scale=0.3):
"""
convert quads into rbox, see fig4 in EAST paper
https://github.com/Masao-Taketani/FOTS_OCR/blob/5c214bf2e3d815d6f826f7771da92ba4d899d08b/data_provider/data_utils.py#L575
1. create minimum rectangle surrounding quads points and angle. these values are created by opencv's minAreaRect
:param quads: ndarray, shape = (box nums, 8)
:param w: int
:param h: int
:param shrink_scale: None or int, use raw quads to calculate dists if None or 1, use shrinked ones otherwise
:returns:
pos: ndarray, shape = (h, w)
rbox: ndarray, shape=(h, w, 5=(4=(t, r, b, l)+1=(angle))
Note that angle is between [-pi/4, pi/4)
"""
reshaped_quads = quads.reshape((-1, 4, 2)).copy()
reshaped_quads[:, :, 0] *= w
reshaped_quads[:, :, 1] *= h
box_nums, _, _ = reshaped_quads.shape
# initialization
rbox = np.zeros((h, w, 5), dtype=np.float32) # shape=(h, w, 5=(4=(t, r, b, l)+1=(angle))
pos = np.zeros((h, w), dtype=np.bool)
# shrink
if shrink_scale and shrink_scale != 1:
shrunk_quads = shrink_quads_numpy(reshaped_quads.reshape(-1, 8).copy(), shrink_scale)
else:
shrunk_quads = reshaped_quads.reshape(-1, 8).copy()
shrunk_quads[:, ::2] /= w
shrunk_quads[:, 1::2] /= h
for b in range(box_nums):
rect = cv2.minAreaRect(reshaped_quads[b])
# note that angle range is (0, 90]
angle = -rect[-1]
# shape = (4, 2)
# clockwise from ymax point: https://stackoverflow.com/questions/29739411/what-does-cv2-cv-boxpointsrect-return/51952289
box_4pts = cv2.boxPoints(rect)
# shift box_4pts for clockwise order from top-left
# and convert angle range into [0, 90)
if angle == 90:
angle = 0
# horizontal and vertical lines are parallel to x-axis and y-axis respectively
# box is clockwise order from bottom-right, i.e. index 0 is bottom-right
shift = -2
elif angle < 45:
# box is clockwise order from bottom-left, i.e. index 0 is bottom-left
shift = -1
else:
# box is clockwise order from bottom-right, i.e. index 0 is bottom-right
shift = -2
box_4pts = np.roll(box_4pts, shift, axis=0)
# compute distance from each point
# >>> widths, heights = np.meshgrid(np.arange(3), np.arange(7))
# >>> heights.shape
# (7, 3)
# >>> k=np.concatenate((np.expand_dims(widths, -1), np.expand_dims(heights, -1)), axis=-1)
# >>> k[0,1,:]
# array([1, 0])
widths, heights = np.meshgrid(np.arange(w), np.arange(h))
# shape = (h, w, 2)
origins = np.concatenate((np.expand_dims(widths, -1), np.expand_dims(heights, -1)), axis=-1)
# shape = (h, w, 4=(t,r,b,l))
dists = dists_pt2line_numpy(box_4pts, np.roll(box_4pts, -1, axis=0), origins)
# compute pos
shrunk_quad = shrunk_quads[b]
mask = quad2mask_numpy(shrunk_quad, w, h)
pos = np.logical_or(pos, mask)
# assign dists
rbox[mask, :4] = dists[mask]
# assign angle
# the reason of below process is https://github.com/argman/EAST/issues/210
angle = angle if angle < 45 else -(90 - angle)
rbox[mask, -1] = np.deg2rad(angle)
return pos, rbox
#ref https://github.com/Masao-Taketani/FOTS_OCR/blob/5c214bf2e3d815d6f826f7771da92ba4d899d08b/data_provider/data_utils.py#L498
def rboxes2quads_numpy(rboxes):
"""
:param rboxes: ndarray, shape = (*, h, w, 5=(4=(t,r,b,l) + 1=angle))
Note that angle is between [-pi/4, pi/4)
:return: quads: ndarray, shape = (*, h, w, 8=(x1, y1,... clockwise order from top-left))
"""
# dists, shape = (*, h, w, 4=(t,r,b,l))
# angles, shape = (*, h, w)
h, w, _ = rboxes.shape[-3:]
dists, angles = rboxes[..., :4], rboxes[..., 4]
# shape = (*, h, w, 5=(t,r,b,l,offset), 2=(x,y))
pts = np.zeros(list(dists.shape[:-1]) + [5, 2], dtype=np.float32)
# assign pts for angle >= 0
dists_pos = dists[angles >= 0]
if dists_pos.size > 0:
# shape = (*, h, w)
tops, rights, bottoms, lefts = np.rollaxis(dists_pos, axis=-1)
shape = tops.shape
pts[angles >= 0] = np.moveaxis(np.array([[np.zeros(shape), -(tops+bottoms)],
[lefts+rights, -(tops+bottoms)],
[lefts+rights, np.zeros(shape)],
[np.zeros(shape), np.zeros(shape)],
[lefts, -bottoms]]), [0, 1], [-2, -1])
# assign pts for angle < 0
dists_neg = dists[angles < 0]
if dists_neg.size > 0:
# shape = (*, h, w)
tops, rights, bottoms, lefts = np.rollaxis(dists_neg, axis=-1)
shape = tops.shape
pts[angles < 0] = np.moveaxis(np.array([[-(lefts+rights), -(tops+bottoms)],
[np.zeros(shape), -(tops+bottoms)],
[np.zeros(shape), np.zeros(shape)],
[-(lefts+rights), np.zeros(shape)],
[-rights, -bottoms]]), [0, 1], [-2, -1])
# note that rotate clockwise is positive, otherwise, negative
angles *= -1
# rotate
# shape = (*, h, w, 2, 2)
R = np.moveaxis(np.array([[np.cos(angles), -np.sin(angles)],
[np.sin(angles), np.cos(angles)]]), [0, 1], [-2, -1])
# shape = (*, h, w, 2=(x, y), 5=(t,r,b,l,offset))
pts = np.swapaxes(pts, -1, -2)
# shape = (*, h, w, 2=(x, y), 5=(t,r,b,l,offset))
rotated_pts = R @ pts
# quads, shape = (*, h, w, 2=(x, y), 4=(t,r,b,l))
# offsets, shape = (*, h, w, 2=(x, y), 1=(offset))
quads, offsets = rotated_pts[..., :4], rotated_pts[..., 4:5]
# align
widths, heights = np.meshgrid(np.arange(w), np.arange(h))
# shape = (h, w, 2)
origins = np.concatenate((np.expand_dims(widths, -1), np.expand_dims(heights, -1)), axis=-1)
# shape = (*, h, w, 2=(x,y), 1)
origins = np.expand_dims(origins, axis=tuple(i for i in range(-1, rboxes.ndim - 3)))
quads += origins - offsets
quads[..., 0, :] = np.clip(quads[..., 0, :], 0, w)
quads[..., 1, :] = np.clip(quads[..., 1, :], 0, h)
# reshape
quads = np.swapaxes(quads, -1, -2).reshape(list(rboxes.shape[:-1]) + [8])
return quads | [
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] | 2.106269 | 8,055 |
import re
# optional dot, word characters, hyphens allowed
tag_regex = "^\.?[-\w]+$"
# same but repeated and joined by +
multitag_regex = "^(\+?\.?[-\w]+)+$"
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import numpy as np
import torch
from torch.utils.data import Dataset, Sampler
from torch_geometric.data import Data
from rorlkit.torch.data_management import rosbag_data
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import copy
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import argparse
import math
import sys
import tqdm
sys.path.append('/relnet')
from relnet.evaluation.experiment_conditions import get_conditions_for_experiment
from relnet.evaluation.file_paths import FilePaths
from multiprocessing.pool import Pool
from psutil import cpu_count
if __name__ == "__main__":
main()
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__all__ = ["composition", "crystal"] | [
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] | 3 | 12 |
import sys
from unittest import mock
import py
import pytest
FIX_PROJECT = py.path.local(__file__).dirpath("fixture-project")
@pytest.fixture
@pytest.fixture
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import typing
import colors
palette: typing.Mapping[str, typing.Mapping[int, typing.Tuple[int, int, int]]] = {
"blueGray": {
50: (248, 250, 252),
100: (241, 245, 249),
200: (226, 232, 240),
300: (203, 213, 225),
400: (148, 163, 184),
500: (100, 116, 139),
600: (71, 85, 105),
700: (51, 65, 85),
800: (30, 41, 59),
900: (15, 23, 42),
},
"coolGray": {
50: (249, 250, 251),
100: (243, 244, 246),
200: (229, 231, 235),
300: (209, 213, 219),
400: (156, 163, 175),
500: (107, 114, 128),
600: (75, 85, 99),
700: (55, 65, 81),
800: (31, 41, 55),
900: (17, 24, 39),
},
"gray": {
50: (250, 250, 250),
100: (244, 244, 245),
200: (228, 228, 231),
300: (212, 212, 216),
400: (161, 161, 170),
500: (113, 113, 122),
600: (82, 82, 91),
700: (63, 63, 70),
800: (39, 39, 42),
900: (24, 24, 27),
},
"trueGray": {
50: (250, 250, 250),
100: (245, 245, 245),
200: (229, 229, 229),
300: (212, 212, 212),
400: (163, 163, 163),
500: (115, 115, 115),
600: (82, 82, 82),
700: (64, 64, 64),
800: (38, 38, 38),
900: (23, 23, 23),
},
"warmGray": {
50: (250, 250, 249),
100: (245, 245, 244),
200: (231, 229, 228),
300: (214, 211, 209),
400: (168, 162, 158),
500: (120, 113, 108),
600: (87, 83, 78),
700: (68, 64, 60),
800: (41, 37, 36),
900: (28, 25, 23),
},
"red": {
50: (254, 242, 242),
100: (254, 226, 226),
200: (254, 202, 202),
300: (252, 165, 165),
400: (248, 113, 113),
500: (239, 68, 68),
600: (220, 38, 38),
700: (185, 28, 28),
800: (153, 27, 27),
900: (127, 29, 29),
},
"orange": {
50: (255, 247, 237),
100: (255, 237, 213),
200: (254, 215, 170),
300: (253, 186, 116),
400: (251, 146, 60),
500: (249, 115, 22),
600: (234, 88, 12),
700: (194, 65, 12),
800: (154, 52, 18),
900: (124, 45, 18),
},
"amber": {
50: (255, 251, 235),
100: (254, 243, 199),
200: (253, 230, 138),
300: (252, 211, 77),
400: (251, 191, 36),
500: (245, 158, 11),
600: (217, 119, 6),
700: (180, 83, 9),
800: (146, 64, 14),
900: (120, 53, 15),
},
"yellow": {
50: (254, 252, 232),
100: (254, 249, 195),
200: (254, 240, 138),
300: (253, 224, 71),
400: (250, 204, 21),
500: (234, 179, 8),
600: (202, 138, 4),
700: (161, 98, 7),
800: (133, 77, 14),
900: (113, 63, 18),
},
"lime": {
50: (247, 254, 231),
100: (236, 252, 203),
200: (217, 249, 157),
300: (190, 242, 100),
400: (163, 230, 53),
500: (132, 204, 22),
600: (101, 163, 13),
700: (77, 124, 15),
800: (63, 98, 18),
900: (54, 83, 20),
},
"green": {
50: (240, 253, 244),
100: (220, 252, 231),
200: (187, 247, 208),
300: (134, 239, 172),
400: (74, 222, 128),
500: (34, 197, 94),
600: (22, 163, 74),
700: (21, 128, 61),
800: (22, 101, 52),
900: (20, 83, 45),
},
"emerald": {
50: (236, 253, 245),
100: (209, 250, 229),
200: (167, 243, 208),
300: (110, 231, 183),
400: (52, 211, 153),
500: (16, 185, 129),
600: (5, 150, 105),
700: (4, 120, 87),
800: (6, 95, 70),
900: (6, 78, 59),
},
"teal": {
50: (240, 253, 250),
100: (204, 251, 241),
200: (153, 246, 228),
300: (94, 234, 212),
400: (45, 212, 191),
500: (20, 184, 166),
600: (13, 148, 136),
700: (15, 118, 110),
800: (17, 94, 89),
900: (19, 78, 74),
},
"cyan": {
50: (236, 254, 255),
100: (207, 250, 254),
200: (165, 243, 252),
300: (103, 232, 249),
400: (34, 211, 238),
500: (6, 182, 212),
600: (8, 145, 178),
700: (14, 116, 144),
800: (21, 94, 117),
900: (22, 78, 99),
},
"sky": {
50: (240, 249, 255),
100: (224, 242, 254),
200: (186, 230, 253),
300: (125, 211, 252),
400: (56, 189, 248),
500: (14, 165, 233),
600: (2, 132, 199),
700: (3, 105, 161),
800: (7, 89, 133),
900: (12, 74, 110),
},
"blue": {
50: (239, 246, 255),
100: (219, 234, 254),
200: (191, 219, 254),
300: (147, 197, 253),
400: (96, 165, 250),
500: (59, 130, 246),
600: (37, 99, 235),
700: (29, 78, 216),
800: (30, 64, 175),
900: (30, 58, 138),
},
"indigo": {
50: (238, 242, 255),
100: (224, 231, 255),
200: (199, 210, 254),
300: (165, 180, 252),
400: (129, 140, 248),
500: (99, 102, 241),
600: (79, 70, 229),
700: (67, 56, 202),
800: (55, 48, 163),
900: (49, 46, 129),
},
"violet": {
50: (245, 243, 255),
100: (237, 233, 254),
200: (221, 214, 254),
300: (196, 181, 253),
400: (167, 139, 250),
500: (139, 92, 246),
600: (124, 58, 237),
700: (109, 40, 217),
800: (91, 33, 182),
900: (76, 29, 149),
},
"purple": {
50: (250, 245, 255),
100: (243, 232, 255),
200: (233, 213, 255),
300: (216, 180, 254),
400: (192, 132, 252),
500: (168, 85, 247),
600: (147, 51, 234),
700: (126, 34, 206),
800: (107, 33, 168),
900: (88, 28, 135),
},
"fuchsia": {
50: (253, 244, 255),
100: (250, 232, 255),
200: (245, 208, 254),
300: (240, 171, 252),
400: (232, 121, 249),
500: (217, 70, 239),
600: (192, 38, 211),
700: (162, 28, 175),
800: (134, 25, 143),
900: (112, 26, 117),
},
"pink": {
50: (253, 242, 248),
100: (252, 231, 243),
200: (251, 207, 232),
300: (249, 168, 212),
400: (244, 114, 182),
500: (236, 72, 153),
600: (219, 39, 119),
700: (190, 24, 93),
800: (157, 23, 77),
900: (131, 24, 67),
},
"rose": {
50: (255, 241, 242),
100: (255, 228, 230),
200: (254, 205, 211),
300: (253, 164, 175),
400: (251, 113, 133),
500: (244, 63, 94),
600: (225, 29, 72),
700: (190, 18, 60),
800: (159, 18, 57),
900: (136, 19, 55),
},
}
engine = make_color("cyan", 500)
wagon = make_color("teal", 500)
train = make_color("blue", 600)
era = make_color("gray", 500)
good = make_color("green", 500)
bad = make_color("red", 500)
neutral = make_color("gray", 500)
money = make_color("green", 500)
timber = make_color("yellow", 700)
coal = make_color("gray", 700)
iron = make_color("gray", 400)
diesel = make_color("magenta", 500)
steel = make_color("gray", 100)
electric = make_color("yellow", 400)
quest = make_color("pink", 500)
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6138,
796,
787,
62,
8043,
7203,
79,
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1600,
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198
] | 1.750763 | 4,257 |
from random import shuffle
alunoI = input('Digite o aluno I: ')
alunoII = input('Digite o aluno II: ')
alunoIII = input('Digite o aluno III: ')
alunoIV = input('Digite o aluno IV: ')
ordem = [alunoI,alunoII,alunoIII, alunoIV]
shuffle(ordem)
print('A ordem de apresentação será')
print(ordem)
| [
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282,
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40,
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198
] | 2.45 | 120 |
"""
Module for various checkers.
"""
import re
import logging
from functools import lru_cache
from abc import ABCMeta, abstractmethod
from .parser import compile_regex
from .exceptions import InvalidPatternError
log = logging.getLogger(__name__)
class Checker(metaclass=ABCMeta):
"""
Abstract class for Checker typing.
"""
@abstractmethod
def fits(self, policy, field, what, inquiry=None):
"""
Check if fields from Inquiry fit some Policies
"""
pass
class RegexChecker(Checker):
"""
Checker that uses regular expressions.
E.g. 'Dog', 'Doge', 'Dogs' fit <Dog[se]?>
'Dogger' doesn't fit <Dog[se]?>
"""
def __init__(self, cache_size=1024):
"""Set up LRU-cache size for compiled regular expressions."""
self.compile = lru_cache(maxsize=cache_size)(compile_regex)
def fits(self, policy, field, what, inquiry=None):
"""Does Policy fit the given 'what' value by its 'field' property"""
where = getattr(policy, field, [])
for i in where:
# We are not meant to handle non-string values if they accidentally got here
if type(i) != str:
continue
# check if 'where' item is not written in a policy-defined-regex syntax.
if policy.start_tag not in i and policy.end_tag not in i:
if i != what:
continue # continue if it's not a string match
else:
return True # we've found a string match - policy fits by simple string value
try:
pattern = self.compile(i, policy.start_tag, policy.end_tag)
except InvalidPatternError:
log.exception('Error matching policy, because of failed regex %s compilation', i)
return False
if re.match(pattern, what):
return True
return False
class StringChecker(Checker):
"""
Checker that uses string equality.
You have to redefine `compare` method.
"""
def fits(self, policy, field, what, inquiry=None):
"""Does Policy fit the given 'what' value by its 'field' property"""
where = getattr(policy, field, [])
for item in where:
# We are not meant to handle non-string values if they accidentally got here
if type(item) != str:
continue
if policy.start_tag == item[0] and policy.end_tag == item[-1]:
item = item[1:-1]
if self.compare(what, item):
return True
return False
@abstractmethod
def compare(self, needle, haystack):
"""Compares two string values. Override it in a subclass"""
pass
class StringExactChecker(StringChecker):
"""
Checker that uses exact string equality. Case-sensitive.
E.g. 'sun' in 'sunny' - False
'sun' in 'sun' - True
"""
class StringFuzzyChecker(StringChecker):
"""
Checker that uses fuzzy substring equality. Case-sensitive.
E.g. 'sun' in 'sunny' - True
'sun' in 'unsung' - True
'sun' in 'sun' - True
"""
class RulesChecker(Checker):
"""
Checker that uses Rules defined inside dictionaries to determine match.
"""
def fits(self, policy, field, what, inquiry=None):
"""Does Policy fit the given 'what' value by its 'field' property"""
where_list = getattr(policy, field, [])
is_what_dict = isinstance(what, dict)
for i in where_list:
item_result = False
# If not dict or Rule, skip it - we are not meant to handle it.
# Do not use isinstance for higher execution speed
if type(i) == dict:
for key, rule in i.items():
if not is_what_dict:
log.debug('Error matching Policy: data %r in Inquiry is not `dict`', what)
item_result = False
# at least one missing key in inquiry's data means no match for this item
elif key not in what:
log.debug('Error matching Policy: data %r has no key "%r" required by Policy', what, key)
item_result = False
else:
what_value = what[key]
item_result = self._check_satisfied(rule, what_value, inquiry)
# at least one item's key didn't satisfy -> fail fast: policy doesn't fit anyway
if not item_result:
break
elif callable(getattr(i, 'satisfied', '')):
item_result = self._check_satisfied(i, what, inquiry)
# If at least one item fits -> policy fits for this field
if item_result:
return True
return False
@staticmethod
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] | 2.267253 | 2,159 |
# -*- coding: utf-8 -*-
import os
import sys
import urllib,urllib2,cookielib
import datetime,time
import re
import random
from bs4 import BeautifulSoup as soup
import io
text_file = open("amazonreviewlinks.txt", "r")
lines = text_file.read().split(',')
no = len(lines)
#opening product link
print no
for hij in lines :
Review_link_len = 0
hdr1 = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
hdr2 = {'User-Agent': 'Mozilla/5.0 (Windows; U; MSIE 9.0; Windows NT 9.0; en-US)',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
hdr3 = {'User-Agent': 'Mozilla/5.0 (compatible; MSIE 10.0; Macintosh; Intel Mac OS X 10_7_3; Trident/6.0)',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
hdr4 = {'User-Agent': 'Opera/9.80 (X11; Linux i686; U; ru) Presto/2.8.131 Version/11.11',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
hdr5 = {'User-Agent': 'Mozilla/5.0 (iPad; CPU OS 6_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/6.0 Mobile/10A5355d Safari/8536.25',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
while Review_link_len == 0 :
try :
hdr = random.choice([hdr1,hdr2,hdr3,hdr4,hdr5])
req = urllib2.Request(hij, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout=10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
site1 = page_soup.findAll("a",{"id" : "acrCustomerReviewLink"})
Review_link_len = len(site1)
print Review_link_len
except :
hdr = random.choice([hdr1,hdr2,hdr3,hdr4,hdr5])
req = urllib2.Request(hij, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout=10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
site1 = page_soup.findAll("a",{"id" : "acrCustomerReviewLink"})
Review_link_len = len(site1)
print Review_link_len
site2 = site1[0]['href']
amazon_homepage = "https://www.amazon.in"
site = amazon_homepage + site2
print site
#openinig review link
hdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
len_captcha = 0
while len_captcha == 0 :
try :
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
except :
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
next_button1 = page_soup.findAll("li",{"class" : "a-last"})[0]
next_button = next_button1.findAll("a")
next_button_len = len(next_button)
if next_button_len == 0 :
next_button_len = 50
else :
next_button = next_button1.findAll("a")[0]['href']
print len(next_button)
try :
filename = page_soup.findAll("a",{"class" : "a-link-normal"})[0].text.strip()
#filename = filename.replace('\'', "!")
filename = filename + '.csv'
f = io.open(filename,"w",encoding="utf-8")
headers = "Customer name,Customer ratings out of 5.0,Review date,Review word count,Customer review\n"
f.write(unicode(headers,"utf-8"))
except :
filename = page_soup.findAll("a",{"class" : "a-link-normal"})[0].text.strip()[:10]
#filename = filename.replace('\'', "!")
filename = filename + '.csv'
f = io.open(filename,"w",encoding="utf-8")
headers = "Customer name,Customer ratings out of 5.0,Review date,Review word count,Customer review\n"
f.write(unicode(headers,"utf-8"))
#loop for content extraction
while next_button_len != 50 :
for single in review_element :
try :
review007 = single.findAll("span",{"data-hook" : "review-body"})[0].getText()
review007 = review007.replace(",", "|")
review007 = len(review007.split())
review = single.findAll("span",{"data-hook" : "review-body"})[0].getText()
review = (review.encode('utf-8', 'ignore')).encode("utf-8",errors='ignore')
review = unicode(review,"utf-8",errors='ignore')
review = review.replace(",", "|")
print review
except :
review = "can not extract review"
try :
ratings = single.findAll("a",{"class" : "a-link-normal"})[0]['title'][:3]
ratings = (ratings.encode('utf-8', 'ignore')).encode("utf-8",errors='ignore')
ratings = unicode(ratings,"utf-8",errors='ignore')
ratings = ratings.replace(",", "|")
print ratings
except :
ratings = "can not extract ratings"
try :
review_date = single.findAll("span",{"class" : "a-size-base a-color-secondary review-date"})[0].getText()[3:]
review_date = (review_date.encode('utf-8', 'ignore')).encode("utf-8",errors='ignore')
review_date = unicode(review_date,"utf-8",errors='ignore')
review_date = review_date.replace(",", "|")
print review_date
except :
ratings = "can not extract review date"
try :
review_length = unicode(review007)
print review_length
except :
review_length = "can not extract review length"
try :
customer_name = single.findAll("a",{"data-hook" : "review-author"})[0].getText().strip()
customer_name = (customer_name.encode('utf-8', 'ignore')).encode("utf-8",errors='ignore')
customer_name = unicode(customer_name,"utf-8",errors='ignore')
customer_name = customer_name.replace(",", "|")
print customer_name
except :
customer_name = "can not extract customer name"
data1 = [customer_name , ratings, review_date, review_length, review]
data1 = customer_name + "," + ratings + "," + review_date + "," + review_length + "," + review + "\n"
try :
f.write(data1)
except :
data1 = unicode("can not find customr name") + "," + unicode("can not extract review") + "\n"
f.write(data1)
next_button1 = page_soup.findAll("li",{"class" : "a-last"})[0]
next_button = next_button1.findAll("a")
next_button_len = len(next_button)
if next_button_len == 0 :
next_button_len = 50
else :
next_button = next_button1.findAll("a")[0]['href']
try :
amazon_homepage = "https://www.amazon.in"
site = amazon_homepage + next_button
except :
site = 0
print site
if site == 0 :
next_button_len = 50
else :
try :
try :
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
cj.clear_session_cookies()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
while len_captcha == 0 :
cj.clear_session_cookies()
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
except :
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
cj.clear_session_cookies()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
while len_captcha == 0 :
cj.clear_session_cookies()
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
except :
print "sleeping due to connection errors"
try :
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
cj.clear_session_cookies()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
while len_captcha == 0 :
cj.clear_session_cookies()
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
except :
print "sleeping due to connection error"
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
cj.clear_session_cookies()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
while len_captcha == 0 :
cj.clear_session_cookies()
req = urllib2.Request(site, headers=hdr)
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
response = opener.open(req,timeout = 10)
content = response.read()
response.close()
page_soup = soup(content,"html.parser")
review_element = page_soup.findAll("div",{"class" : "a-section celwidget"})
captcha = page_soup.findAll("li",{"class" : "a-last"})
len_captcha = len(captcha)
f.close()
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] | 2.122518 | 6,195 |
# spectral_cluster.py
import torch
import torch.nn.functional as F
import numpy as np
import random
import time
import datetime
import os
import sklearn
from sklearn import metrics
from multi_kmeans_pp import MultiKMeans
from logger import Logger
from scipy.sparse.csgraph import laplacian as csgraph_laplacian
DEBUG = 0
def spectral_cluster(attn_maps,K=10,neighbor_mask=None,use_gpu=True,pre_labels=None):
"""
Parameters
attn_maps: Tensor (*,n_samples,n_samples)
Attention map from Transfomrer as similarity matrix
K: int
Number of clusters, default: 10
neighbor_mask: Tensor (n_samples,n_samples)
Mask to reserve neighbors only
pre_labels: Tensor (*,n_samples_pre)
Label(Index of cluster) of data points of last module
Returns
labels:
['normal'] - Tensor (*,n_samples)
['debug'] - Tensor (len(K_trials),*,n_samples)
Label(Index of cluster) of data points
"""
batched = False
if attn_maps.ndim == 3: # Batched data
B,N,_ = attn_maps.shape
batched = True
else:
B = 1
N,_ = attn_maps.shape
K_1 = K
# 1. Generate similarity matrix -- only neighbor patches considered
if neighbor_mask is None:
if pre_labels is not None: # (*,2N)
pre_mask = get_neighbor_mask_old(N*2,use_gpu=use_gpu) # (2N,2N) / (784,784)
neighbor_mask = neighbor_mask_reduce(pre_mask,pre_labels,N,use_gpu=use_gpu) # (*,N,N)
else:
neighbor_mask = get_neighbor_mask_old(N,use_gpu=use_gpu) # (N,N)
sim_mat = attn_maps*neighbor_mask # Reserve only neighbors (*,N,N)
sim_mat = torch.softmax(sim_mat, dim=-1)
sim_mat = 0.5 * (sim_mat + sim_mat.transpose(-2,-1)) # symmetrize (*,N,N)
# 2. Compute degree matrix
# 3. Laplacian Matrix and Normalized Laplacian Matrix
normalized_laplacian_mat, diag_term = graph_laplacian(sim_mat) # (*,N,N), (*,N)
# 4. Top K_1 eigen vector with respect to eigen values
eig_values,eig_vectors = torch.linalg.eigh(normalized_laplacian_mat) # Eigen value decomposition of of a complex Hermitian or real symmetric matrix.
# eigenvalues will always be real-valued, even when A is complex. It will also be ordered in ascending order.
if batched:
feat_mat = eig_vectors[:,:,:K_1] # (B,N,K_1)
else:
feat_mat = eig_vectors[:,:K_1] # (N,K_1)
if diag_term is not None:
feat_mat /= diag_term.unsqueeze(-1)
# 5. KMeans Cluster
if batched:
kmeans = MultiKMeans(n_clusters=K,n_kmeans=B,max_iter=100)
labels = kmeans.fit_predict(feat_mat) # (B,N)
return labels # (B,N)
else:
kmeans = MultiKMeans(n_clusters=K,n_kmeans=1,max_iter=100)
labels = kmeans.fit_predict(feat_mat.unsqueeze(0)) # (N,) -> (1,N)
return labels[0] # (B,N) -> (N,)
def calinski_harabasz_score(X,labels,centroids=None):
"""
Borrowed from https://github.com/scikit-learn/scikit-learn/blob/844b4be24/sklearn/metrics/cluster/_unsupervised.py#L251
Implementation of https://scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabasz_score.html#sklearn.metrics.calinski_harabasz_score
"""
assert X.ndim == 2
N,_ = X.shape
classes_,counuts_ = torch.unique(labels,sorted=True,return_counts=True)
K = len(classes_)
if DEBUG:
print(f"[DEBUG] calinski_harabasz_score: K = {K}")
print(f"[DEBUG] calinski_harabasz_score: counuts_ = {counuts_}")
extra_disp, intra_disp = 0.0, 0.0
center = torch.mean(X,dim=0)
for q in range(K):
cluster_q = X[labels==q]
center_q = torch.mean(cluster_q,dim=0)
if centroids is not None:
center_q = centroids[q]
extra_disp += len(cluster_q) * torch.sum((center_q-center)**2)
intra_disp += torch.sum((cluster_q-center_q)**2)
return (
1.0
if intra_disp == 0.0
else (extra_disp*(N-K)) / (intra_disp*(K-1))
)
def get_neighbor_mask_old(N,use_gpu=True):
"""
neighbor: 8
"""
P = int(N**(0.5))
A = torch.zeros((N,N))
ind = torch.arange(N)
row = torch.div(ind,P,rounding_mode='floor')
# Same row
# ind + 1
neigbor_ind = ind+1
neighbor_row = torch.div(neigbor_ind,P,rounding_mode='floor')
mask = (neigbor_ind<N) & (row==neighbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# ind - 1
neigbor_ind = ind-1
neighbor_row = torch.div(neigbor_ind,P,rounding_mode='floor')
mask = (neigbor_ind>=0) & (row==neighbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# exit()
# stride = [-(P+1),-P,-(P-1),-1]
strides = [P-1,P,P+1]
for s in strides:
# ind + s
neigbor_ind = ind+s
neigbor_row = torch.div(neigbor_ind,P,rounding_mode='floor') - 1
mask = (neigbor_ind<N) & (row==neigbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# ind - s
neigbor_ind = ind-s
neigbor_row = torch.div(neigbor_ind,P,rounding_mode='floor') + 1
mask = (neigbor_ind>=0) & (row==neigbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
if use_gpu:
A = A.cuda()
return A
def get_neighbor_mask(N,use_gpu=True):
"""
neighbor: 4 (w/o diagonals)
"""
P = int(N**(0.5))
A = torch.zeros((N,N))
ind = torch.arange(N)
row = torch.div(ind,P,rounding_mode='floor')
# Same row
# ind + 1
neigbor_ind = ind+1
neighbor_row = torch.div(neigbor_ind,P,rounding_mode='floor')
mask = (neigbor_ind<N) & (row==neighbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# ind - 1
neigbor_ind = ind-1
neighbor_row = torch.div(neigbor_ind,P,rounding_mode='floor')
mask = (neigbor_ind>=0) & (row==neighbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# exit()
# stride = [-(P+1),-P,-(P-1),-1]
strides = [P]
for s in strides:
# ind + s
neigbor_ind = ind+s
neigbor_row = torch.div(neigbor_ind,P,rounding_mode='floor') - 1
mask = (neigbor_ind<N) & (row==neigbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
# ind - s
neigbor_ind = ind-s
neigbor_row = torch.div(neigbor_ind,P,rounding_mode='floor') + 1
mask = (neigbor_ind>=0) & (row==neigbor_row)
A[ind[mask],neigbor_ind[mask]] = 1
if use_gpu:
A = A.cuda()
return A
if __name__ == '__main__':
seed = 99
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
random.seed(seed)
# Logger
time_info = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
log_dir = './log_sc/'
if not os.path.exists(log_dir):
os.makedirs(log_dir)
print(f"Create {log_dir}")
log = Logger(log_dir+f'test_sc-{time_info}.log',level='debug')
# Data preparation
# Just for DEBUG
B,N,D,K = 5,784,384,10
# data = torch.Tensor([[0,1,0,0],
# [2,1,0,0],
# [0,0,3,0],
# [1,2,0,0],
# [0,1,1,1]])
# data = torch.rand(B,N,D)
file_dir = '/home/heyj/data/feature/train/n01910747/'
file_list = os.listdir(file_dir)
load_start_t = datetime.datetime.now()
data = []
for file_name in file_list[:100]: # Less images
data.append(torch.load(os.path.join(file_dir,file_name))[1:])
data = torch.stack(data).cuda() # torch.Size([3, 49, 384])
# data = torch.load('/home/heyj/data/feature_50/train/n01910747/n0191074700000003.pth')[1:] # torch.Size([49, 384])
load_t = (datetime.datetime.now() - load_start_t).total_seconds()
print(f"data.shape: {data.shape} [{data.device}]")
# print(torch.cuda.device_count())
# exit(1)
print(f"load {len(data)} images time: {load_t:.4f}s")
# Test for sigma and K
B,N,D = data.shape
neighbor_mask = get_neighbor_mask(N)
neighbor_mask = neighbor_mask.cuda()
do_our = True
do_sklearn = False
#--------------------------------------------------------------------------------------------------------
# Our spectral_cluster
#--------------------------------------------------------------------------------------------------------
if do_our:
mini_batch_size = 16
scores = []
scores_skl = []
configs = []
sigma_trials = [31,40,50,75]
gamma_trials = [0.0002,0.0003125,0.0005,0.0006,0.0008]
K_trials = [10,15,20,25,28]
log.logger.debug(f"\nOur spectral_cluster:")
# for sigma in sigma_trials:
for gamma in gamma_trials:
# log.logger.debug(f"sigma:{sigma}")
log.logger.debug(f"gamma:{gamma}")
pred_labels = spectral_cluster(data,K,gamma=gamma,neighbor_mask=neighbor_mask,
mode="debug",K_trials=K_trials) # (len(K_trials),B,N)
for K_ind,K in enumerate(K_trials):
mini_batch_indices = random.sample(range(B), mini_batch_size)
# mini_batch_indices = [0] # DEBUG
score = 0.0
score_skl = 0.0
for i in mini_batch_indices:
score += calinski_harabasz_score(data[i],pred_labels[K_ind,i])
score_skl += metrics.calinski_harabasz_score(
data[i].cpu().numpy(),pred_labels[K_ind,i].cpu().numpy())
# print(type(score))
# print(type(score_skl))
# exit(1)
score /= mini_batch_size
score_skl /= mini_batch_size
scores.append(score)
scores_skl.append(score_skl)
# configs.append(dict(sigma=sigma,K=K,labels=pred_labels[K_ind]))
configs.append(dict(gamma=gamma,K=K))
log.logger.debug(f" - K:{K} score:{score:.4f} score_skl:{score_skl:.4f}")
# Print result
max_ind = torch.argmax(torch.Tensor(scores))
max_score = scores[max_ind]
log.logger.debug(f"Max Score: {max_score}")
log.logger.debug(f"Configurations: gamma:{configs[max_ind]['gamma']} K:{configs[max_ind]['K']}")
#--------------------------------------------------------------------------------------------------------
# Sklearn's SpectralClustering
#--------------------------------------------------------------------------------------------------------
if do_sklearn:
log.logger.debug(f"\nSklearn SpectralClustering:")
scores_skl = []
configs = []
gamma_trials = [0.0003125,0.0005,0.0008]
# sigma [100.0000, 70.7107, 50.0000, 31.6228, 25.0000]
K_trials = [10,15,20]
for gamma in gamma_trials:
log.logger.debug(f"gamma:{gamma}")
for K in K_trials:
score_skl = 0.0
for X in data:
X_ = X.cpu().numpy() # (784, 384)
y_pred = SpectralClustering(n_clusters=K, gamma=gamma).fit_predict(X_)
# score_skl += metrics.calinski_harabasz_score(X_,y_pred)
score_skl += calinski_harabasz_score(X,torch.from_numpy(y_pred))
exit(1)
score_skl /= len(data)
scores_skl.append(score_skl)
configs.append(dict(gamma=gamma,K=K))
log.logger.debug(f" - K:{K} score_skl:{score_skl:.4f}")
# Print result
max_ind = torch.argmax(torch.Tensor(scores_skl))
max_score = score_skl[max_ind]
log.logger.debug(f"Max Score: {max_score}")
log.logger.debug(f"Configurations: gamma:{configs[max_ind]['gamma']} K:{configs[max_ind]['K']}")
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220,
220,
220,
220,
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220,
2604,
13,
6404,
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13,
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7,
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1,
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25,
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62,
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92,
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220,
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220,
220,
2604,
13,
6404,
1362,
13,
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7,
69,
1,
16934,
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25,
34236,
29164,
11250,
82,
58,
9806,
62,
521,
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6,
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2611,
20520,
92,
220,
509,
29164,
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82,
58,
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62,
521,
7131,
6,
42,
20520,
92,
4943,
201,
198,
201,
198,
220,
220,
220,
220
] | 1.932276 | 6,305 |
from timeit import default_timer as timer
import revkit
| [
6738,
640,
270,
1330,
4277,
62,
45016,
355,
19781,
198,
198,
11748,
2710,
15813,
198
] | 3.8 | 15 |
# Time: O(n^2)
# Space: O(1)
#
# Given an array S of n integers,
# are there elements a, b, c in S such that a + b + c = 0?
# Find all unique triplets in the array which gives the sum of zero.
#
# Note:
# Elements in a triplet (a,b,c) must be in non-descending order. (ie, a <= b <= c)
# The solution set must not contain duplicate triplets.
# For example, given array S = {-1 0 1 2 -1 -4},
#
# A solution set is:
# (-1, 0, 1)
# (-1, -1, 2)
#
# @return a list of lists of length 3, [[val1,val2,val3]]
if __name__ == '__main__':
result = Solution().threeSum([-1, 0, 1, 2, -1, -4])
print result | [
2,
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532,
16,
11,
532,
19,
12962,
198,
220,
220,
220,
3601,
1255
] | 2.472 | 250 |
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
from .core import Word, Meaning, ReviewPlan, AddCounter, ReviewPlanType, ReviewStatus, ReviewStage
| [
6738,
44161,
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] | 3.519231 | 52 |
# This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
from __future__ import absolute_import, division, print_function
import six
from cryptography import utils
from cryptography.hazmat.primitives import interfaces
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
@utils.register_interface(interfaces.EllipticCurve)
_CURVE_TYPES = {
"prime192v1": SECP192R1,
"prime256v1": SECP256R1,
"secp192r1": SECP192R1,
"secp224r1": SECP224R1,
"secp256r1": SECP256R1,
"secp384r1": SECP384R1,
"secp521r1": SECP521R1,
"sect163k1": SECT163K1,
"sect233k1": SECT233K1,
"sect283k1": SECT283K1,
"sect409k1": SECT409K1,
"sect571k1": SECT571K1,
"sect163r2": SECT163R2,
"sect233r1": SECT233R1,
"sect283r1": SECT283R1,
"sect409r1": SECT409R1,
"sect571r1": SECT571R1,
}
@utils.register_interface(interfaces.EllipticCurveSignatureAlgorithm)
| [
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291,
26628,
303,
11712,
1300,
2348,
42289,
8,
628,
628
] | 2.583582 | 670 |
""" This module loads all the classes from the VTK Chemistry library into
its namespace. This is an optional module."""
from vtkChemistryPython import *
| [
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] | 4.189189 | 37 |
from .spotify import Spotify
from .cache import Cache
from . import croapi
from . import matcher
__all__ = [Spotify, Cache, croapi, matcher]
| [
6738,
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60,
198
] | 3.302326 | 43 |
import json
from fastapi.testclient import TestClient
from main import my_awesome_api
client = TestClient(my_awesome_api)
with open("openapi.json", "w") as f:
json.dump(client.get("/openapi.json").json(), f, indent=4)
| [
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] | 2.8125 | 80 |
import numpy as np
# x = np.array([0.1, 0.8, 0.05, 0.05])
# t = np.array([0.0, 0.1, 0.0, 0.0]) # target probability distribution
# x = np.array([0.2, 0.5, 0.2, 0.1])
# t = np.array([0.0, 0.0, 0.1, 0.0]) # target probability distribution
# x = np.array([0.05, 0.05, 0.8, 0.1])
# t = np.array([0.0, 0.0, 0.0, 0.1]) # target probability distribution
x = np.array([0.5, 0.1, 0.1, 0.3])
# target probability distribution
t = np.array([0.1, 0.0, 0.0, 0.0])
# Function definitions
# [0.10650698, 0.10650698, 0.78698604]
soft = softmax(x)
print(soft)
print(cross_entropy(soft, t)) # 2.2395447662218846
# [-0. , -9.3890561, -0. ]
cross_der = cross_entropy_derivatives(soft, t)
print(cross_der)
# [0.09516324, 0.09516324, 0.16763901]
soft_der = softmax_derivatives(soft)
print(soft_der)
print(cross_der * soft_der)
print(soft - t)
# ## Derivative using chain rule
# cross_der * soft_der # [-0. , -0.89349302, -0. ]
#
#
# ## Derivative using analytical derivation
#
# soft - t # [ 0.10650698, -0.89349302, 0.78698604]
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7,
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1303,
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220,
220,
220,
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15,
13,
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220,
220,
220,
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220,
220,
837,
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15,
13,
4531,
27371,
22709,
11,
532,
15,
13,
220,
220,
220,
220,
220,
220,
220,
2361,
198,
2,
198,
2,
198,
2,
22492,
9626,
452,
876,
1262,
30063,
16124,
341,
198,
2,
198,
2,
2705,
532,
256,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
685,
657,
13,
15801,
1120,
39357,
11,
532,
15,
13,
4531,
27371,
22709,
11,
220,
657,
13,
3695,
39357,
31916,
60,
198
] | 1.982363 | 567 |
import io
import pickle
import pprint
data = []
data.append(SimpleObject('pickle'))
data.append(SimpleObject('preserve'))
data.append(SimpleObject('last'))
# Simulate a file.
out_s = io.BytesIO()
# Write to the stream
for o in data:
print('WRITING : {} ({})'.format(o.name, o.name_backwards))
pickle.dump(o, out_s)
out_s.flush()
# Set up a read-able stream
in_s = io.BytesIO(out_s.getvalue())
# Read the data
while True:
try:
o = pickle.load(in_s)
except EOFError:
break
else:
print('READ : {} ({})'.format(
o.name, o.name_backwards))
| [
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220,
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7,
198,
220,
220,
220,
220,
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220,
220,
220,
220,
220,
220,
267,
13,
3672,
11,
267,
13,
3672,
62,
1891,
2017,
4008,
198
] | 2.283019 | 265 |
#!/usr/bin/env python
# This script has been taken from https://github.com/miguelgrinberg/flasky-with-celery.
# The github repo above also provided the starting guidelines to
# have celery work in factory mode with Flask: I recommend you also look at the repo above!
import os
from app import celery, create_app
app = create_app()
app.app_context().push()
| [
2,
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62,
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14689,
3419,
198
] | 3.419048 | 105 |
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import time
from pytoion import *
if len(sys.argv) == 1:
print("Usage: python %s [BLE_DEVICE_ADDRESS]" %(sys.argv[0]))
sys.exit()
cube = Toio(sys.argv[1])
# sound
# see https://toio.github.io/toio-spec/docs/ble_sound
try:
# [note, octave, time(time*10msec),volume(0:off/1-255:on)]
music= [
[cube.NOTE.D,5,100],
[cube.NOTE.C,5,100],
[cube.NOTE.D,5,100],
[cube.NOTE.E,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.E,5,100],
[cube.NOTE.D,5,150],
[cube.NOTE.C,5,80,0], # volume off
[cube.NOTE.E,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.A,5,100],
[cube.NOTE.G,5,50],
[cube.NOTE.A,5,50],
[cube.NOTE.D,6,100],
[cube.NOTE.B,5,100],
[cube.NOTE.A,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.C,5,60,0],
[cube.NOTE.E,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.A,5,150],
[cube.NOTE.C,5,80,0],
[cube.NOTE.D,6,100],
[cube.NOTE.C,6,100],
[cube.NOTE.D,6,150],
[cube.NOTE.C,5,80,0],
[cube.NOTE.E,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.A,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.E,5,200],
[cube.NOTE.G,5,50],
[cube.NOTE.D,5,150],
[cube.NOTE.C,5,80,0],
[cube.NOTE.A,5,100],
[cube.NOTE.C,6,100],
[cube.NOTE.D,6,150],
[cube.NOTE.C,5,80,0],
[cube.NOTE.C,6,100],
[cube.NOTE.D,6,100],
[cube.NOTE.A,5,100],
[cube.NOTE.G,5,100],
[cube.NOTE.A,5,100],
[cube.NOTE.G,5,50],
[cube.NOTE.E,5,50],
[cube.NOTE.D,5,150]
]
for note in music:
cube.sound(*note)
time.sleep(note[2]/100)
finally:
cube.disconnect()
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] | 1.649293 | 1,132 |
from django.shortcuts import render
from django.http import HttpResponse, Http404
from rest_framework import status
from rest_framework.decorators import api_view
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.parsers import JSONParser
from models import Task
from serializers import TaskSerializer
from rest_framework.request import Request
| [
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] | 4.112245 | 98 |
#!/usr/local/bin/python3
#
# stochastic_hill_climbing.py
# src
#
# Created by Illya Starikov on 10/13/18.
# Copyright 2018. Illya Starikov. MIT License.
#
from random import choice
from hill_climber import HillClimber
class StochasticHillClimber(HillClimber):
"""A stochastic steepest-ascent hill-climbing algorithm."""
def _get_random_uphill_move(self, current_node, neighbors):
"""Find a random uphill move relative to `current_node` in `neighbors`.
Args:
current_node (Node): The current node in the search.
neighbors (list<Node>): The neighbors of `current_node`.
Returns:
Node: A random, uphill move.
"""
uphill_nodes = []
for point in neighbors:
if self._value_at_node(point) > self._value_at_node(current_node):
uphill_nodes.append(point)
return current_node if len(uphill_nodes) == 0 else choice(uphill_nodes)
def climb(self):
"""Run the steepest-ascent hill-climbing algorithm, finding a local optimum in a function.
Returns:
Node: The local optimum discovered.
"""
current_node = self._initial_node()
while True:
print("Exploring Node({}, {})".format(current_node.x, current_node.y))
neighbors = self._generate_all_neighbors(current_node)
successor = self._get_random_uphill_move(current_node, neighbors)
if self._value_at_node(successor) <= self._value_at_node(current_node):
return current_node
current_node = successor | [
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] | 2.408683 | 668 |
for _ in range(int(input())):
n=int(input())
l=list(map(int,input().split()))
l=sorted(l)
r=l[::-1]
if(n==1 or n==2):
print("first")
else:
p1=r[1]+sum(r[2::2])
p2=sum(l)-p1
if(p1>p2):
print("second")
elif(p2>p1):
print("first")
else:
print("draw") | [
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] | 1.566524 | 233 |
#!/usr/bin/python
import os
import sys
import signal
import json
import time
from urllib.request import urlopen
'''
5130315
https://www.funder.co.il/wsfund.asmx/GetFundTickerm?callback=jQuery111306779790886268987_1621159388408&id=5130315&startDate=2018-05-16&endDate=2021-05-17&_=1621159388411
https://www.funder.co.il/wsfund.asmx/GetFundTickerm?callback=jQuery&id=[FUND_NUMBER]&startDate=2018-05-16&endDate=2021-05-17&_=[SIMPLE_NUMBER]
'''
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] | 2.376344 | 186 |
# @param s, a string
# @return an integer
s = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
solution = Solution()
print(solution.minCut(s))
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7252,
1,
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] | 3.819951 | 411 |
from flask import Flask
from shellshocker_server.saferproxyfix import SaferProxyFix
from raven.contrib.flask import Sentry
import os
app = Flask(__name__)
app.config['SECRET_KEY'] = os.environ['SECRET_KEY']
try:
if os.environ['SECRET_KEY'] is not None:
app.config['USE_SENTRY'] = True
app.config['SENTRY_DSN'] = os.environ['SENTRY_DSN']
except KeyError:
app.config['USE_SENTRY'] = False
sentry = Sentry(app)
app.wsgi_app = SaferProxyFix(app.wsgi_app)
import shellshocker_server.views
| [
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] | 2.592784 | 194 |
"""
NYT Download articles
"""
from nytimesarticle import articleAPI
import pandas as pd
import time
import re
api = articleAPI("<PASTE_YOUR_API_KEY>")
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Artificial Intelligence",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Artificial Intelligence",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Artificial Intelligence",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_ArtificialIntelligence.csv')
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Machine Learning",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Machine Learning",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Machine Learning",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_MachineLearning.csv')
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Deep Learning",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Deep Learning",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Deep Learning",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_DeepLearning.csv')
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Self Driving Car",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Self Driving Car",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Self Driving Car",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_SelfDrivingCar.csv')
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Neural Network",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Neural Network",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Neural Network",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_NeuralNetwork.csv')
df = pd.DataFrame()
for i in range(1,10):
articles = api.search(q="Reinforcement Learning",
begin_date=int("20180"+str(i)+"01"), end_date=int("20180"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(10,13):
articles = api.search(q="Reinforcement Learning",
begin_date=int("2018"+str(i)+"01"), end_date=int("2018"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
for i in range(1,4):
articles = api.search(q="Reinforcement Learning",
begin_date=int("20190"+str(i)+"01"), end_date=int("20190"+str(i)+"28"))
df = df.append(pd.DataFrame.from_dict(articles))
time.sleep(60)
df.to_csv('NYT_ReinforcementLearning.csv')
"""
NYT clean articles and store each paragraph in line
"""
from bs4 import BeautifulSoup
import requests
import os
# Collect nyt URLs from nyt sourcing
#
url_list = []
for filename in os.listdir("nyt"):
ls = 0
if filename.endswith(".csv"):
print(filename)
cnt=0
with open(os.path.join("nyt",filename), 'r',encoding="utf8") as file:
for line in file.readlines():
for url in line.split("'"):
if "https://www.nytimes" in url:
url_list.append(url)
cnt += 1
url_list = (set(url_list))
# Visit all urls and write content in paratags
#
with open("nyt_paras.txt", "w") as nyt:
for url in url_list:
page = requests.get(str(url))
soup = BeautifulSoup(page.text, 'html.parser')
anchor_tags = soup.find_all('a')
for tag in anchor_tags:
para_tag = soup.find_all('p')
for tag in para_tag:
nyt.write(str(tag.prettify().encode("utf8"))+"\n")
# Clean data from paratags
#
with open("nyt_paras.txt","r") as nyt:
with open("nyt_clean.txt","w") as clean:
for line in nyt.readlines():
s = ""
line=line.lower()
flag = False
for ch in line:
if ch == '<':
flag=True
elif ch == '>':
flag=False
if not flag and (ord('a')<=ord(ch)<=ord('z') or ch is ' '):
s += ch
s = (re.sub(' +', ' ', s)).strip()
if len(s)>0:
clean.write(s+"\n")
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220,
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220,
220,
220,
220,
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220,
220,
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220,
220,
220,
220,
220,
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220,
220,
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220,
220,
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220,
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220,
220,
220,
220,
220,
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220,
220,
220,
220,
611,
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7,
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29,
15,
25,
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220,
220,
220,
220,
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220,
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220,
220,
220,
220,
220,
220,
220,
220,
3424,
13,
13564,
7,
82,
10,
1,
59,
77,
4943,
198
] | 2.111223 | 2,976 |
import math
from collections import Counter
from fractions import Fraction
from datatypes import Chord
import json
| [
11748,
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17268,
1330,
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4818,
265,
9497,
1330,
609,
585,
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11748,
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] | 4.5 | 26 |
from nlpia.loaders import * # noqa | [
6738,
299,
34431,
544,
13,
2220,
364,
1330,
1635,
220,
1303,
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20402
] | 2.692308 | 13 |
import collections
from enum import Enum
from vtypes import (
VString,
VInt,
VBool,
VUnsignedInt,
VDict,
VValidatorDict,
VList,
VDate,
VDateTime,
VTime,
VEnum,
Validator,
)
class RecordingType(Enum):
"""From https://github.com/MythTV/mythtv/blob/master/mythtv/libs/libmyth/recordingtypes.cpp#L76
The `toRawString` method converts to a string. I believe this are
always returned untranslated.
"""
single_record = 'Single Record'
all_record = 'Record All'
record_one = 'Record One'
record_daily = 'Record Daily'
record_weekly = 'Record Weekly'
override_recording = 'Override Recording'
recording_template = 'Recording Template'
not_recording = 'Not Recording'
@property
@property
@classmethod
@classmethod
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24396,
628,
220,
220,
220,
2488,
4871,
24396,
628,
628,
628,
628
] | 2.547401 | 327 |
import sublime
from sublime_plugin import WindowCommand
from ..git_command import GitCommand
from ..ui_mixins.quick_panel import show_paginated_panel
| [
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] | 3.731707 | 41 |
# -- Description ----------------------------------------------------------------------------- #
# Given a function , that returns two random values between 0..1 , calculate the value of Pi
# Credits to YT channel Joma Tech
# -------------------------------------------------------------------------------------------- #
import random
while(True):
precision = int(input("How precise ?"))
print(near_pi(precision)) | [
2,
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] | 5.234568 | 81 |
from __future__ import division
import abc
import numpy as np
from .utils import psnr
class metric(object):
"""Represents an metric for measuring reconstruction quality
"""
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
def _eval(self, v):
"""Evaluate the metric
"""
return NotImplemented
def eval(self, v):
"""Evaluate the metric
"""
if self.decimals is None:
return self._eval(v)
else:
return np.round(self._eval(v), decimals=self.decimals)
def message(self, v):
"""Evaluate the metric
"""
mval = self.eval(v)
message = "{0}: {1} {2}".format(self.desc, mval, self.unit)
return message
class psnr_metric(metric):
"""PSNR metric
"""
def _eval(self, v):
"""Evaluate PSNR metric
"""
return psnr(np.reshape(v, self.ref.shape),
self.ref,
pad=self.pad, maxval=self.maxval)
| [
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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13,
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11,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
14841,
28,
944,
13,
15636,
11,
3509,
2100,
28,
944,
13,
9806,
2100,
8,
198
] | 2.102941 | 476 |
from pythagoras import *
| [
6738,
279,
5272,
363,
41043,
1330,
1635,
628
] | 3.25 | 8 |
Desc = cellDescClass("NAND2BXL")
Desc.properties["cell_footprint"] = "nand2b"
Desc.properties["area"] = "13.305600"
Desc.properties["cell_leakage_power"] = "540.512676"
Desc.pinOrder = ['AN', 'B', 'Y']
Desc.add_arc("AN","Y","combi")
Desc.add_arc("B","Y","combi")
Desc.add_param("area",13.305600);
Desc.add_pin("AN","input")
Desc.add_pin("B","input")
Desc.add_pin("Y","output")
Desc.add_pin_func("Y","unknown")
CellLib["NAND2BXL"]=Desc
| [
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28780,
25835,
14692,
45,
6981,
17,
33,
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8973,
28,
24564,
198
] | 2.403315 | 181 |
# -*- coding: utf-8 -*-
"""
cherry.exceptions
~~~~~~~~~~~~~~~~~~~
This module contains the set of cheery' exceptions.
:copyright: (c) 2018-2019 by Windson Yang
:license: MIT License, see LICENSE for more details.
"""
class CacheNotFoundError(IOError):
'''Cache files not found'''
class FilesNotFoundError(IOError):
'''Files not found'''
class MethodNotFoundError(AttributeError):
'''Method not found'''
class DataMismatchError(AttributeError):
'''Data mismatch'''
class UnicodeFileEncodeError(UnicodeEncodeError):
'''Unicode File Encode Error'''
| [
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] | 3.026455 | 189 |
# -*- coding: utf-8 -*-
@bot.message_handler(commands=['setlang' , 'Setlang'])
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from abc import ABCMeta, abstractmethod
import inspect
import warnings
import re
import types
class ExecutionNode(object):
"""Abstract Superclass for all nodes in an execution flow,
e.g. parts, molecules
Parts are the atomistic instructions in the genetic circuit execution flow
| *Attributes:*
| before : [ExecutionNode]
| A list of ExecutionNode objects that precede this node
| after : [ExeuctionNode]
| A list of ExecutionNode objects that follow this node
| scope : class(WeaverOutput)
| What woven system is this node part of
| additionStack : [Circuit or Aspect]
| stack of Aspects and Circuits which are executing to add
| this node
"""
__metaclass__ = ABCMeta
def getBeforeNodes(self, filterType=object):
"""Returns all nodes immediately before this node in the execution flow, with the option to filter by node type
| *Args:*
| filterType: Filters the list to only include nodes of a given (super)type
"""
result = []
for executionNode in self.before:
if isinstance(executionNode, filterType):
result.append(executionNode)
return result
def getAfterNodes(self, filterType):
"""Returns all nodes immediately after this node in the execution flow, with the option to filter by node type
| *Args:*
| filterType: Filters the list to only include nodes of a given (super)type
"""
result = []
for executionNode in self.after:
if isinstance(executionNode, filterType):
result.append(executionNode)
return result
# Parts are always used as objects
class Part(ExecutionNode):
"""Abstract Superclass for all Parts
Parts are the atomistic instructions in the genetic circuit execution flow,
e.g. Promoters, RBSs, Terminators, Coding Regions
They inherit their functionality as nodes in the execution flow from their
superclass ExecutionNode
"""
__metaclass__ = ABCMeta
def setBeforePart(self, part):
"""Inserts a part before this part in the execution flow. If there's already a part in front of this part,
the part to be inserted will be inserted between the two parts presently connected
| *Args:*
| part: the Part to be inserted
"""
oldPart = self.getBeforePart()
if oldPart != None:
self.before.remove(oldPart)
self.before.append(part)
def setAfterPart(self, part):
"""Inserts a part after this part in the execution flow. If there's already a part behind this part,
the part to be inserted will be inserted between the two parts presently connected
| *Args:*
| part: the Part to be inserted
"""
oldPart = self.getAfterPart()
if oldPart != None:
self.after.remove(oldPart)
self.after.append(part)
def getBeforePart(self):
"""Returns the part just before this part in the execution flow
"""
for executionNode in self.before:
if isinstance(executionNode, Part):
return executionNode
return None
def getAfterPart(self):
"""Returns the part just after this part in the execution flow
"""
for executionNode in self.after:
if isinstance(executionNode, Part):
return executionNode
return None
def weave(self, weaver):
"""Internal method used during the weaving process:
Facilitates molecule scope checking
"""
for beforeMol in self.precompileMoleculesBefore:
mol = weaver.getMoleculeObject(self.scope, beforeMol)
self.before.append(mol)
mol.after.append(self)
for afterMol in self.precompileMoleculesAfter:
mol = weaver.getMoleculeObject(self.scope, afterMol, True)
self.after.append(mol)
mol.before.append(self)
class Molecule(ExecutionNode):
"""Abstract Superclass for all Molecules
Molecules are the nodes in the execution flow, for example:
reactions: (MoleculeA+MoleculeB -> MoleculeC),
translation: CodingRegion->MoleculeA,
inducing: MoleculeA -> RegulatdPromoter,
membrane transfer: MoleculeA (Compartment) -> MoleculeA (Outside Compartment)
These nodes in the execution flow don't mean an existence of an element, but rather
describe the information flow within the system.
"""
class Protein(Molecule):
"""Class for Molecules that are Proteins"""
pass
class Promoter(Part):
"""Class for Parts that are Promoters"""
pass
class ConstitutivePromoter(Promoter):
"""Class for Promoters that are Constitutive Promoters"""
pass
def checkIfTypeReturnInstance(possibleType):
"""if the parameter is a type, try to return an instance
| *Args:*
| possibleType - a parameter which may be an instance or a type
| *Raises:*
| PartInitializationError - if the parameter is a type which can not be constructed
| *Returns:*
| An instance of the type of possibleType
"""
if isinstance(possibleType, type):
try:
return possibleType()
except:
raise PartInitializationError(str(possibleType) + " can not be initialized without Parameters.")
return possibleType
def checkAndSetMolecule(molecule):
"""checks if parameter is a class of type Molecule and returns it
| *Args:*
| molecule - A potential Molecule
| *Raises:*
| MoleculeValue - If molecule is not a class of type Molecule
| *Returns:*
| A class of type Molecule
"""
if inspect.isclass(molecule) and issubclass(molecule, Molecule):
return molecule
else:
raise MoleculeValueError("molecule must be a class of (sub)type Molecule")
class NegativePromoter(Promoter):
"""Class for Promoters that are Negative Promoters"""
def __init__(self, regulatedBy):
"""NegativePromoter Constructor
| *Args:*
| regulatedBy: sets moleculeConnection
"""
super(NegativePromoter, self).__init__()
self.precompileMoleculesBefore.append(checkAndSetMolecule(regulatedBy))
def getRegulatedBy(self):
"""Returns a list of Molecules regulating this Promoter"""
result = self.getBeforeNodes(Molecule)
if len(result) > 0:
return result
# else: not compiled yet
return self.precompileMoleculesBefore
class PositivePromoter(Promoter):
"""Class for Promoters that are Positive Promoters"""
def __init__(self, regulatedBy):
"""PositivePromoter Constructor
| *Args:*
| regulatedBy: sets moleculeConnection
"""
super(PositivePromoter, self).__init__()
self.precompileMoleculesBefore.append(checkAndSetMolecule(regulatedBy))
def getRegulatedBy(self):
"""Returns a list of Molecules regulating this Promoter"""
result = self.getBeforeNodes(Molecule)
if len(result) > 0:
return result
# else: not compiled yet
return self.precompileMoleculesBefore
class HybridPromoter(Promoter):
"""Class for Promoters that are Hybrid Promoters, i.e. with several repressing / inducing operator sites
like other regulated Promoters (NegativePromoter, PostiivePromoter), its regulators are accessible by
getRegulatedBy(). Additionally, getInducers(), getRepressors(), and isInducer(molecule), isRepressor(molecule)
give information about the functionality of the Promoter."""
def __init__(self, regulatedBy, regulatorInfo):
"""PositivePromoter Constructor
| *Args:*
| regulatedBy: [] list of regulator Molecules
| regulatorInfo: Dictionary of the form {Molecule: Boolean}, where True: Induce, False: Repress
"""
cleanRegulatorInfo = {}
if not type(regulatorInfo) is dict:
raise ValueError("regulatorInfo must be a dictionary in the form of {Molecule: Boolean}")
super(HybridPromoter, self).__init__()
for mol in regulatedBy:
self.precompileMoleculesBefore.append(checkAndSetMolecule(mol))
# todo try catch / raise exception if mol not in regulatorInfo
cleanRegulatorInfo[mol] = regulatorInfo[mol]
self.regulatorInfo = cleanRegulatorInfo
def getRegulatedBy(self):
"""Returns a list of Molecules regulating this Promoter"""
result = self.getBeforeNodes(Molecule)
if len(result) > 0:
return result
# else: not compiled yet
return self.precompileMoleculesBefore
def getInducers(self):
"""Returns a list of positively regulating Molecules """
regulators = self.getRegulatedBy()
ret = []
for mol in regulators:
if self.regulatorInfo[mol.__class__] is True:
ret.append(mol)
return ret
def getRepressors(self):
"""Returns a list of negatively regulating Molecules """
regulators = self.getRegulatedBy()
ret = []
for mol in regulators:
if self.regulatorInfo[mol.__class__] is False:
ret.append(mol)
return ret
class CodingRegion(Part):
"""Class for parts that are Coding Regions"""
def __init__(self, codesFor):
"""Constructor for a Coding Region Part
| *Args:*
| codesFor: sets moleculeConnection
"""
super(CodingRegion, self).__init__()
self.precompileMoleculesAfter.append(checkAndSetMolecule(codesFor))
# todo : is this necessary?
# def __del__(self):
# self.codesFor.before.remove(self)
class RBS(Part):
"""Class for parts that are Ribosome BindingSites"""
class Terminator(Part):
"""Class for parts that are Terminators"""
class Circuit(Part):
"""Abstract class for a genetic part circuit.
| Will generally be used to represent a design's core concerns
| Additionally, a circuit can be used to represent composite parts
| *Attributes:*
| weaver: Weaver
| The weaver which compiles the circuit
"""
__metaclass__ = ABCMeta
@abstractmethod
def mainCircuit(self):
"""Entry point for a circuit, analogous to "main" in a program
| Needs to be implemented by any sub class.
| mainCircuit will be called by the AOSB Weaver."""
pass
def importMolecule(self, molecule):
"""Import a particular molecule from the outer compartment to this compartment
| *Args:*
| molecule
"""
self.weaver.importMolecule(self, molecule)
def exportMolecule(self, molecule):
"""Export a particular molecule from this compartment to the outer compartment
| *Args:*
| molecule
"""
self.weaver.exportMolecule(self, molecule)
def createMolecule(self, molecule):
"""Declare that a particular molecule exists in the current scope
| *Args:*
| molecule
"""
self.weaver.createMolecule(self, molecule)
def addCircuit(self, circuit):
"""Add a circuit as a sub-compartment in the current compartment
| *Args:*
| circuit: Circuit to be added as a sub-compartment
"""
self.weaver.addCircuit(self, circuit)
def addPart(self, part):
"""Used to add parts to the circuit by passing them on to the AOSB Weaver
| *Args:*
| part: The part to be added to the circuit
"""
self.weaver.addPart(self, part)
def reactionFrom(self, *molecules):
"""Used to add a reaction to the circuit by passing the reactions left side on to the AOSB Weaver
| *Args:*
| *molecules: a list of one or more molecules on the lhs of the reaction
"""
return self.weaver.reactionFrom(self, molecules)
def reactionTo(self, *molecules):
"""Used to add a reaction to the circuit by passing the reactions right side on to the AOSB Weaver
| *Args:*
| *molecules: a list of one or more molecules on the rhs of the reaction
"""
return self.weaver.reactionTo(self, molecules)
def setWeaver(self, weaver):
"""Internal - Should not be used outside of the framework.
Sets the Weaver Object of this Circuit
| *Args:*
| weaver: A weaver object that will be used
"""
self.weaver = weaver
def declareNewPart(classname, parent=Part, moleculesBefore=[], moleculesAfter=[], regulatorInfoMap={}):
''' Returns a new Part type and exports it to the caller's namespace
| *Args*
| classname : string
| The name for the new type
| parent : Part
| super class for the new type
| moleculesBefore : [Molecule]
| optional, if the new Part type should have Molecule node(s) before it, e.g. regulators of a Promoter
| moleculesAfter : [Molecule]
| optional, if the new Part type should have Molecule node(s) after it, e.g. Proteins created by CodingRegions
| regulatorInfoMap : Dictionary
| optional, if a parent part needs additional regulator information.
| Necessary for HybridPromoters, who need a map in the form of {Molecule: Boolean}
| *Returns*
| The new Part type
| *Raises*
| PartValueError -If the parent is not a Part
| InvalidSymbolNameError - If classname is not a valid name for a symbol
| *Warnings*
| SymbolExistsWarning - If classname already exists in the namespace'''
if not issubclass(parent, Part):
raise PartValueError("parent must be of type Part")
validnameregex = re.compile('[a-zA-Z_][a-zA-Z0-9_]*')
if not isinstance(classname, str) or not validnameregex.match(classname) or not validnameregex.match(
classname).span() == (0, len(classname)):
raise InvalidSymbolNameError('name is not a valid symbold name')
if not isinstance(moleculesBefore, list):
raise ValueError("moleculesBefore must be of type list")
if not isinstance(moleculesAfter, list):
raise ValueError("moleculesAfter must be of type list")
for mol in moleculesBefore:
checkAndSetMolecule(mol)
for mol in moleculesAfter:
checkAndSetMolecule(mol)
basestuple = parent,
result = None
currentframe = inspect.currentframe()
# Create warning if name already exists
if currentframe.f_back.f_globals.has_key(classname):
line = currentframe.f_back.f_lineno
warnings.warn(
"Line " + str(line) + ": Part " + classname + " already defined. Existing definition will be used",
SymbolExistsWarning, 2) # 2 = one stack level above this
result = currentframe.f_back.f_globals.get(classname)
else:
result = type(classname, basestuple, {})
# this means that parent does not take a moleculeConnection parameter,
#but the new subtype should have one.
result = type(classname, basestuple, {'__init__': newTypeInit})
currentframe.f_back.f_globals[classname] = result
return result
def declareNewMolecule(classname, *parents):
"""Returns a new Molecule type and exports it to the caller's namespace
| *Args:*
| classname: The name for the new type
| \*parents: 0 or more Molecule super classes
| *Returns:*
| The new Part type
| *Raises:*
| MoleculeValueError: If any parent is not a Molecule
| InvalidSymbolNameError: If classname is not a valid name for a symbol
| *Warnings:*
| SymbolExistsWarning: If classname already exists in the namespace
"""
validnameregex = re.compile('[a-zA-Z_][a-zA-Z0-9_]*')
if not isinstance(classname, str) or not validnameregex.match(classname) or not validnameregex.match(
classname).span() == (0, len(classname)):
raise InvalidSymbolNameError('name is not a valid symbold name')
if len(parents) == 0:
parents = Molecule,
else:
for parent in parents:
if not issubclass(parent, Molecule):
raise MoleculeValueError("All parents must be of type Molecule")
currentframe = inspect.currentframe()
result = None
# Check if classname already exists
if currentframe.f_back.f_globals.has_key(classname):
line = currentframe.f_back.f_lineno
warnings.warn(
"Line " + str(line) + ": Molecule " + classname + " already defined. Existing definition will be used",
SymbolExistsWarning, 2) # 2 = one stack level above this
result = currentframe.f_back.f_globals.get(classname)
else:
result = type(classname, parents, {})
currentframe.f_back.f_globals[classname] = result
return result
class PointCutExpressionNode(object):
"""Abstract superclass for all Nodes in a Point Cut Expression Tree
| A complex expression for a Point Cut, using operators such as & (and),
| \| (or) or % (concatenation) is represented as a tree of nodes
"""
__metaclass__ = ABCMeta
def __mod__(self, other):
"""% - concatenates two PointCutExpressionNodes
| *Args:*
| other - the node on the right of self
| *Returns:*
| a new PointCutExpressionConcatenate node
"""
return PointCutExpressionConcatenate(self, other)
def __and__(self, other):
"""& - boolean and evaluation of two PointCutExpressionNodes
| *Args:*
| other - the node on the right of self
| *Returns:*
| a new PointCutExpressionNodeAnd node
"""
return PointCutExpressionAnd(self, other)
def __or__(self, other):
"""| - boolean or evaluation of two PointCutExpressionNodes
| *Args:*
| other - the node on the right of self
| *Returns:*
| a new PointCutExpressionOr node
"""
return PointCutExpressionOr(self, other)
def numberOfMatchingParts(self, part):
"""returns the number of parts the expression matches
| If an expression uses concatenation, then it might match the current part and a number of preceding parts.
| *Args:*
| part - The part at which matching starts
| *Returns:*
| integer - how many parts were matched
"""
if self.match(part):
return 1
else:
return 0
@abstractmethod
def match(self, part):
"""Does a part match this (sub)-expression? An abstract method, must be implemented by each child
| *Args:*
| part - The part to be matched
| *Returns:*
| boolean - Whether or not the part was matched
"""
pass
class PointCutExpressionOperator(PointCutExpressionNode):
"""Abstract superclass of an PointCutExpression Node which is an operator
| *Attributes:*
| left - The first child of the operator
| right - The second child of the operator
"""
__metaclass__ = ABCMeta
left = None
right = None
def __init__(self, left, right):
"""Constructs a new PointCutExpresionOperator
| *Args:*
| left - Sets the left child node
| right - Sets the right child node
| *Raises:*
| InvalidPointCutExpressionError -
| If either child is not an instance of PointCutExpressionNode
"""
if isinstance(left, PointCutExpressionNode) and isinstance(right, PointCutExpressionNode):
self.left = left
self.right = right
else:
raise InvalidPointCutExpressionError("Invalid type used in a PointCut formula.")
def expressionUses(self, nodeType):
"""Confirms if a certain type of node is used in the expression
| *Args:*
| nodeType: The type of the node whose existence is to be confirmed
| *Returns:*
| boolean - Whether or not the node exists in the formula
"""
if isinstance(self, nodeType) or isinstance(self.left, nodeType) or isinstance(self.right, nodeType):
return True
else:
leftresult = False
rightresult = False
try:
leftresult = self.left.expressionUses(nodeType)
except:
pass
try:
rightresult = self.right.expressionUses(nodeType)
except:
pass
return leftresult or rightresult
class PointCutExpressionNot(PointCutExpressionOperator):
"""A PointCutExpressionOperator which is a Not
A special case, only uses one child, acts as the inverse operator
"""
def __init__(self, pointcutexpression):
"""Constructs a new PointCutExprresionNot
| *Args:*
| pointcutexpression - The expression to be negated
"""
self.right = pointcutexpression
def match(self, part, within=None):
"""see PointCutExpressionNode definition"""
return not self.right.match(part, within)
class PointCutExpressionOr(PointCutExpressionOperator):
"""A PointCutExpressionOperator which is an Or"""
def match(self, part, within=None):
"""see PointCutExpressionNode definition"""
return self.left.match(part) or self.right.match(part)
class PointCutExpressionAnd(PointCutExpressionOperator):
"""A PointCutExpressionOperator which is an And"""
def match(self, part):
"""see PointCutExpressionNode definition"""
return self.left.match(part) and self.right.match(part)
class PointCutExpressionConcatenate(PointCutExpressionOperator):
"""A PointCutExpressionOperator which is an Concatenation"""
def numberOfMatchingParts(self, part):
"""see PointCutExpressionNode definition
This child overrides it, since a concatenation operator is
a node in the expression at which more than one part can be
matched.
"""
if self.match(part):
return self.left.numberOfMatchingParts(part.getBeforePart()) + self.right.numberOfMatchingParts(part)
else:
return 0
def match(self, part):
"""see PointCutExpressionNode definition"""
try:
return self.left.match(part.getBeforePart()) and self.right.match(part)
except:
return False
def checkBaseClassesMatch(bases, typename):
"""Recursively check if the name of the types in bases (or parents) are equal to typename
| *Args:*
| bases - A tuple of types
| typename : str - A name of a type
| *Returns:*
| True if any of the names of types in bases or any of their parent bases equals typename,
| False otherwise
"""
for baseClass in bases:
if (typename == baseClass.__name__):
return True
else:
if checkBaseClassesMatch(baseClass.__bases__, typename):
return True
class PartSignatureElement(object):
"""A building block of a Part Signature
| *Attributes:*
| qualifier : ANY / SUBCLASS / CLASSONLY
| Whether the element should match precisely, all subclasses or uses a wildcard
| element : str - The string of the element (without a qualifier)
| inverse : boolean - Whether the element has been negated
"""
ANY = 1
SUBCLASS = 2
CLASSONLY = 3
def __init__(self, signature):
"""Constructs a new PartSignatureElement
| Analyzes signature and sets internal attributes
| *Args:*
| signature - the part of the Part signature for this element
"""
self.inverse = False
self.qualifier = None
self.element = ''
if signature[0] == '!':
self.inverse = True
signature = signature[1:]
if signature[-1] == '*':
self.qualifier = PartSignatureElement.ANY
self.element = signature[:-1]
elif signature[-1] == '+':
self.qualifier = PartSignatureElement.SUBCLASS
self.element = signature[:-1]
else:
self.qualifier = PartSignatureElement.CLASSONLY
self.element = signature
def match(self, obj):
"""see PointCutExpressionNode definition"""
if self.inverse:
return not self.__match(obj)
else:
return self.__match(obj)
def __match(self, obj):
"""internal match method, matching without inverse"""
objectName = obj.__class__.__name__
if (isinstance(obj, str)):
objectName = obj
if (inspect.isclass(obj)):
objectName = obj.__name__
if ((self.qualifier == self.CLASSONLY) or (self.qualifier == self.SUBCLASS)) and (objectName == self.element):
return True
if (self.qualifier == self.ANY) and (objectName.startswith(self.element)):
return True
if (self.qualifier == self.SUBCLASS):
if (inspect.isclass(obj)):
return checkBaseClassesMatch(obj.__bases__, self.element)
else:
return checkBaseClassesMatch(obj.__class__.__bases__, self.element)
return False
class MoleculeSignatureElement(PartSignatureElement):
"""A PartSignatureElement that is a Molecule Signature
| Overloads some methods, since MoleculeSignature is used by the user for
| Molecule Type Advice - unlike PartSignatureElement, which is internal
"""
def __init__(self, signature):
"""Constructs a new MoleculeSignature
| *Args:*
| signature : str - The string signature to be cast to a MoleculeSignature
| *Raises:*
| InvalidSignatureError - If signature does not adhere to the format
"""
signatureRE = re.compile('!?([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?|\*)')
try:
if not signatureRE.match(signature).span() == (0, len(signature)):
raise InvalidSignatureError()
except:
raise InvalidSignatureError()
return super(MoleculeSignatureElement, self).__init__(signature)
def match(self, obj):
"""see PointCutExpressionNode definition"""
if self.qualifier == self.ANY and obj == None:
if self.inverse:
return False
return True
return super(MoleculeSignatureElement, self).match(obj)
class MoleculeSignature():
"""A MoleculeSignature, used for Type Advice of Molecules
| *Attributes:*
| namespace : [PartSignatureElement] - List of signature parts of the signature
| molecule : MoleculeSignatureElement - The "part" part of the signature
"""
def __init__(self, signature):
"""Constructs a new PartSignature
| Analyzes signature and sets internal attributes
| *Args:*
| signature : str - The string signature to be cast to a PartSignature
| *Raises:*
| InvalidSignatureError - If signature does not adhere to the format
"""
self.namespace = []
self.molecule = None
# should be of format: Circuit.Part(Molecule)" (Molecule) is optional#
typeErrorMessage = "signature must be of type String and adhere to PointCut / PartSignature Format"
if not isinstance(signature, str):
raise InvalidSignatureError(typeErrorMessage)
# using a regular expression to make sure the signature is of a valid format
signatureRE = re.compile(
'(!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)\.)+!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)')
# regular expression has to match entire length of string
try:
if not signatureRE.match(signature).span() == (0, len(signature)):
raise InvalidSignatureError(typeErrorMessage)
except:
raise InvalidSignatureError(typeErrorMessage)
# split signature into components
signaturePartRE = re.compile('!?[a-zA-Z_][a-zA-Z0-9_]*[\+\*]?|\*')
splitSignature = signaturePartRE.findall(signature)
numOfCircuitElements = len(splitSignature) - 1;
self.molecule = MoleculeSignatureElement(splitSignature[numOfCircuitElements])
# #Circuit Part
# self.namespace = PartSignatureElement(splitSignature[0])
# Part ... Part
for i in range(0, numOfCircuitElements):
self.namespace.append(PartSignatureElement(splitSignature[i]))
def match(self, molecule):
"""see PointCutExpressionNode definition"""
if not isinstance(molecule, Molecule):
raise MoleculeValueError("Molecule to match must be instance of type Molecule")
result = self.molecule.match(molecule) and self.matchNamespaces(self.namespace, molecule.scope)
return result
class PartSignature(PointCutExpressionNode):
"""A PartSignature, used in PointCut expressions or directly for Type Advice
| *Attributes:*
| namespace : [PartSignatureElement] - List of signature parts of the signature
| part : PartSignatureElement - The "part" part of the signature
| molcule : PartSignatureElement - The molecule part of the signature
| nomolecule : Boolean -
| If the PartSignature explicitly should not match parts with molecules
"""
def __init__(self, signature):
"""Constructs a new PartSignature
| Analyzes signature and sets internal attributes
| *Args:*
| signature : str - The string signature to be cast to a PartSignature
| *Raises:*
| InvalidSignatureError - If signature does not adhere to the format
"""
self.namespace = []
self.part = None
self.molecule = None
self.nomolecule = False
# should be of format: Circuit.Part(Molecule)" (Molecule) is optional#
typeErrorMessage = "signature must be of type String and adhere to PointCut / PartSignature Format"
if not isinstance(signature, str):
raise InvalidSignatureError(typeErrorMessage)
# using a regular expression to make sure the signature is of a valid format
signatureRE = re.compile(
'(!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)\.)+!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)(\(!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)?\))?')
# regular expression has to match entire length of string
try:
if not signatureRE.match(signature).span() == (0, len(signature)):
raise InvalidSignatureError(typeErrorMessage)
except:
raise InvalidSignatureError(typeErrorMessage)
# split signature into components
signaturePartRE = re.compile('!?[a-zA-Z_][a-zA-Z0-9_]*[\+\*]?|\*')
splitSignature = signaturePartRE.findall(signature)
numOfCircuitElements = len(splitSignature) - 1;
signatureMoleculePartRE = re.compile('\(!?(([a-zA-Z_][a-zA-Z0-9_]*[\+\*]?)|\*)?\)')
moleculePartMatch = signatureMoleculePartRE.search(signature)
if moleculePartMatch != None:
moleculePart = moleculePartMatch.group(0)
if len(moleculePart) == 2:
self.nomolecule = True
else:
numOfCircuitElements -= 1
self.molecule = MoleculeSignatureElement(moleculePart[1:-1])
self.nomolecule = False
else:
self.nomolecule = False
self.molecule = MoleculeSignatureElement('*')
self.part = PartSignatureElement(splitSignature[numOfCircuitElements])
# #Circuit Part
# self.namespace = PartSignatureElement(splitSignature[0])
# Part ... Part
for i in range(0, numOfCircuitElements):
self.namespace.append(PartSignatureElement(splitSignature[i]))
def match(self, part):
"""see PointCutExpressionNode definition"""
if not isinstance(part, Part):
raise PartValueError("Part to match must be instance of type Part")
result = self.part.match(part) and self.matchNamespaces(self.namespace, part.additionStack) # or scope
if not self.nomolecule:
# I.E. THERE IS A MOLECULE
# this needs to be refined / TODO
if len(part.precompileMoleculesAfter) == 0 and len(part.precompileMoleculesBefore) == 0:
if self.molecule.qualifier == self.molecule.ANY and self.molecule.element == '':
result = result and True
else:
result = result and False
for mol in part.precompileMoleculesAfter:
result = result and self.molecule.match(mol)
for mol in part.precompileMoleculesBefore:
result = result and self.molecule.match(mol)
if self.nomolecule:
if len(part.getBeforeNodes(Molecule)) != 0 or len(part.getAfterNodes(Molecule)) != 0 or \
len(part.precompileMoleculesAfter) != 0 or len(part.precompileMoleculesBefore) != 0:
result = result and False
# todo this means we could also do more than one molecule, e.g. Promoter(AB || A) or bool and...
return result
class PointCut(object):
"""A PointCut to select Join Points in the genetic parts execution flow
| *Attributes:*
| operator : BEFORE / AFTER / REPLACE
| - The operator for this PointCut
| signature : PartSignature
"""
BEFORE = 11
AFTER = 22
REPLACE = 33
def __init__(self, signature, operator):
"""Construct a new PointCut
| *Args:*
| signature - A PointCutSignature or a string that will be cast to PointCutSignature
| operator - The operator
"""
self.operator = None
self.signature = None
if isinstance(signature, PointCutExpressionNode):
self.signature = signature
else:
self.signature = PartSignature(signature)
self.checkAndSetOperator(operator)
def match(self, part):
"""see PointCutExpressionNode definition"""
return self.signature.match(part)
def checkAndSetOperator(self, operator):
"""Set the internal operator attribute, if the parameter is a valid operator
| *Args:*
| operator - The operator to be confirmed
| *Raises:*
| InvalidPointCutOperatorError - if the operator is invalid
| (can be dependent on the signature)
"""
if (operator == self.BEFORE) or (operator == self.AFTER) or (operator == self.REPLACE):
self.operator = operator
if (operator == self.BEFORE and isinstance(self.signature,
PointCutExpressionOperator) and self.signature.expressionUses(
PointCutExpressionConcatenate)):
raise InvalidPointCutOperatorError(
'PointCut Operator can not be BEFORE if PartSignature uses concatenation.')
else:
raise InvalidPointCutOperatorError("operator must be of type PointCut.BEFORE / AFTER / REPLACE")
class PointCutContext(object):
"""Container for context at a PointCut
| *Attributes:*
| within - A stack of the circuits / aspects that within which the PointCut was matched
| part - The part matched by the PointCut"""
def isWithin(self, obj):
"""Checks if the parameter (a circuit or aspect) is on the within stack
| *Args:*
| obj : Circuit / Aspect - The object that is to be found on the stack
| *Returns:*
| Boolean - true if obj is on the within stack
"""
return self.__isWithinRecursive(obj, len(self.within))
class Advice(object):
"""Container for Advice
| *Attributes:*
| precedence : int - High precedence advice have execution priority over low precedence
| - MINPRECEDENCE <= precedence <= MAXPRECEDENCE is the valid range
| pointcut : PointCut
| adviceMethod : method - The method to be executed at the advice
| - must have 2 parameters: self and PointCutContext
"""
MINPRECEDENCE = 0
MAXPRECEDENCE = 100
def __init__(self, pointcut, adviceMethod, precedence=MINPRECEDENCE):
"""Constructs a new Advice object, setting internal state
| *Args:*
| pointcut - The PointCut to be set
| adviceMethod - The adviceMethod to be set
| precedence - The precedence to be set
| *Raises:*
| InvalidPointCutError
| InvalidAdviceMethodError - If argument is not a method or takes wrong
| number of parameters (must take self and PointCutContext object)
| PrecedenceOutOfRangeError - If precedence > MAXPRECEDENCE or
| precedence < MINPRECEDENCE
"""
self.pointcut = None
self.adviceMethod = None
self.precedence = self.MINPRECEDENCE
if not isinstance(pointcut, PointCut):
raise InvalidPointCutError("pointcut must be of type PointCut")
self.pointcut = pointcut
if not inspect.ismethod(adviceMethod) or len(inspect.getargspec(adviceMethod)[0]) != 2:
raise InvalidAdviceMethodError("adviceMethod must be a method with 2 parameters (self, PointCutContext)")
self.adviceMethod = adviceMethod
if precedence < (self.MINPRECEDENCE) or (precedence > self.MAXPRECEDENCE):
raise PrecedenceOutOfRangeError(
"Advice Precedence must be between " + str(self.MINPRECEDENCE) + " and " + str(self.MAXPRECEDENCE))
self.precedence = precedence
class TypeAdvice(object):
"""Container for TypeAdvice
| *Attributes:*
| signature : PartSignature or MoleculeSignature
| typeaddition : method or attribute to be added to the type
| name : The name the new typeaddition should have in the new type
| aspect : Aspect which declares this TypeAdvice
"""
def __init__(self, signature, typeaddition, name, aspect):
"""Constructs a new TypeAdvice
| *Args:*
| signature - PartSignature / MoleculeSignature to be set
| typeaddition - attribute to be set
| name : str - attribute to be set
| aspect : Aspect - attribute to be set
| *Raises:*
| InvalidSignatureError -
| If signature not instance of PartSignature or MoleculeSignature
| InvalidSymbolNameError -
| If name is not a valid name for a symbol
"""
self.signature = None
self.typeaddition = None
self.aspect = None
self.name = ''
if isinstance(signature, PartSignature) or isinstance(signature, MoleculeSignature):
self.signature = signature;
else:
raise InvalidSignatureError(
'Signature parameter for TypeAdvice must be of type PartSignature or MoleculeSignature')
self.typeaddition = typeaddition;
self.aspect = aspect
validnameregex = re.compile('[a-zA-Z_][a-zA-Z0-9_]*')
if not isinstance(name, str) or not validnameregex.match(name) or not validnameregex.match(name).span() == (
0, len(name)):
raise InvalidSymbolNameError('name is not a valid symbold name')
self.name = name
def isPartAdvice(self):
"""Returns True if TypeAdvice is for Part, False otherwise"""
return isinstance(self.signature, PartSignature)
def isMoleculeAdvice(self):
"""Returns True if TypeAdvice is for Molecule, False otherwise"""
return isinstance(self.signature, MoleculeSignature)
class Aspect(object):
"""Abstract class for an Aspect
| Will generally be used to represent a design's cross-cutting concerns
| *Notes:*
| Any child must implement mainAspect method
| *Attributes*
| weaver: Weaver
| The weaver which compiles the aspect
| adviceList - A list of all advice this aspect declares
| typeAdviceList - A list of all type advice this aspect declares
| weaverOutputList - A list of all type advice for the WeaverOutput
"""
__metaclass__ = ABCMeta
def importMolecule(self, molecule):
"""Import a particular molecule from the outer compartment to this compartment
| *Args:*
| molecule
"""
self.weaver.importMolecule(self, molecule)
def exportMolecule(self, molecule):
"""Export a particular molecule from this compartment to the outer compartment
| *Args:*
| molecule
"""
self.weaver.exportMolecule(self, molecule)
def createMolecule(self, molecule):
"""Declare that a particular molecule exists in the current scope
| *Args:*
| molecule
"""
self.weaver.createMolecule(self, molecule)
def addCircuit(self, circuit):
"""Add a circuit as a sub-compartment in the current compartment
| *Args:*
| circuit: Circuit to be added as a sub-compartment
"""
self.weaver.addCircuit(self, circuit)
def addPart(self, part):
"""Used to add parts to the design by passing them on to the AOSB Weaver
| *Args:*
| part: The part to be added to the circuit
"""
self.weaver.addPart(self, part)
def reactionFrom(self, *molecules):
"""Used to add a reaction to the aspect by passing the reactions left side on to the AOSB Weaver
| *Args:*
| *molecules: a list of one or more molecules on the lhs of the reaction
"""
return self.weaver.reactionFrom(self, molecules)
def reactionTo(self, *molecules):
"""Used to add a reaction to the aspect by passing the reactions right side on to the AOSB Weaver
| *Args:*
| *molecules: a list of one or more molecules on the rhs of the reaction
"""
return self.weaver.reactionTo(self, molecules)
return self.weaver.reactionTo(self, molecules)
def setWeaver(self, weaver):
"""Internal - Should not be used outside of the framework.
Sets the Weaver Object of this Circuit
| *Args:*
| weaver: A weaver object that will be used
"""
self.weaver = weaver
def addAdvice(self, pointcut, adviceMethod, precedence=Advice.MINPRECEDENCE):
"""Declare a new advice in the aspect
| *Args:*
| pointcut - The pointcut for the advice
| adviceMethod - The method to be executed at the pointcut
| should be a method bound to this aspect, with second parameter
| expecting a PointCutContext object
| precedence : integer (optional) - set precedence of advice,
| see notes on Advice.precedence
| *Notes:*
| addAdvice constructs an Advice object. Further information thus
| can be found there.
"""
self.adviceList.append(Advice(pointcut, adviceMethod, precedence))
def addTypeAdvice(self, signature, typeaddition, name):
"""Declare a type advice in the aspect
| *Args:*
| signature - The signature for the type advice
| typeaddition - The attribute / method to be added to the type
| name: str - The name for the typeaddition in the new type
| *Notes:*
| addTypeAdvice constructs an TypeAdvice object.
| Further information thus can be found there.
"""
self.typeAdviceList.append(TypeAdvice(signature, typeaddition, name, self))
def addWeaverOutput(self, outputmethod):
"""Declare a new weaver output target
| *Args:*
| outputMethod - The method to be added to the WeaverOutput
| *Raises:*
| InvalidWeaverOutputMethodError -
| If outputmethod is not a method or has wrong number of parameters
| (needs to accept self and a WeaverOutput reference)
"""
if not inspect.ismethod(outputmethod) or len(inspect.getargspec(outputmethod)[0]) != 2:
raise InvalidWeaverOutputMethodError("outputmethod must be a method with 2 parameters (self, WeaverOutput)")
self.weaverOutputList.append(outputmethod)
def getAdviceList(self):
"""Returns adviceList"""
return self.adviceList
def getTypeAdviceList(self):
"""Returns typeAdviceList"""
return self.typeAdviceList
def getWeaverOutputList(self):
"""Returns weaverOutputList"""
return self.weaverOutputList
@abstractmethod
def mainAspect(self):
"""Entry point for an aspect, analogous to "main" in a program
| Needs to be implemented by any sub class.
| mainAspect will be called by the AOSB Weaver."""
pass
class Weaver(object):
"""The "compiler" that weaves core concerns (circuits) and cross-cutting
concerns (aspects) and creates a woven execution flow of parts
| *Attributes:*
| partList - The current list of parts
| moleculeList - The current list of molecules
| beforeAndReplaceAdviceList - List of all before and replace advice to be woven
| afterAdviceList - List of all after advice to be woven
| partTypeAdviceList - List of all part type advice
| moleculeTypeAdviceList - List of all molecule type advice
| circuit - The main circuit
| aspects - The list of all aspects to be woven
| weaverOutput : WeaverOutput - The "compiled" result
"""
class WeaverOutput(object):
"""Container for the woven result of the Weaver
| *Attributes:*
| circuitName - the name of the circuit that was woven
| partList - finished ordered list of parts in the design
| moleculeList - list of all molecules in the design
| subcircuitList - list of all subcircuits (itself weaver outputs) (??)
|
"""
def __init__(self, circuit, *aspects):
"""Sets of the weaver and compiles the design
| *Attributes:*
| circuit : Circuit - The main circuit to be set
| *aspects : Aspect - list of aspects to be set
| *Raises:*
| CircuitValueError - If circuit is invalid
| AspectValueError - If any aspect is invalid"""
self.beforeAndReplaceAdviceList = []
self.afterAdviceList = []
self.partTypeAdviceList = []
self.moleculeTypeAdviceList = []
self.circuit = None
self.aspects = []
self.withinStack = []
self.weaverOutput = None
if not issubclass(circuit, Circuit) and not isinstance(circuit, Circuit):
raise CircuitValueError("circuit must be a class or instance of type Circuit.")
if inspect.isclass(circuit):
try:
self.circuit = circuit()
except:
raise CircuitValueError("Can not initialize Circuit " + circuit + " without parameters")
else:
self.circuit = circuit
self.circuit.setWeaver(self)
for aspect in aspects:
if not issubclass(aspect, Aspect) and not isinstance(aspect, Aspect):
raise AspectValueError("all aspects must be classes or instances of type Aspect.")
if inspect.isclass(aspect):
try:
self.aspects.append(aspect())
except:
raise AspectValueError("Can not initialize Aspect " + aspect + " without parameters")
else:
self.aspects.append(aspect)
self.weaverOutput = self.WeaverOutput(self.circuit.__class__.__name__)
self.readAspectsConstructAdviceLists()
self.sortAdviceList()
# weaving is kicked off here
self.currentWeaverOutput = self.weaverOutput
self.circuit.mainCircuit()
self.constructMoleculeListAndAddTypeAdvice()
def sortAdviceList(self):
"""Internal - sorts the advice lists by precedence"""
self.beforeAndReplaceAdviceList = sorted(self.beforeAndReplaceAdviceList, key=sortKey, reverse=True)
self.afterAdviceList = sorted(self.afterAdviceList, key=sortKey)
''' """Internal - constructs list of Molecules in design and adds their type advice"""
# construct moleculeList - this should probably be done during weaving?
for part in self.partList:
if part.moleculeConnection:
if not part.moleculeConnection in self.moleculeList:
self.moleculeList.append(part.moleculeConnection)
# add type advice to molecules
for molecule in self.moleculeList:
for typeAdvice in self.moleculeTypeAdviceList:
if typeAdvice.signature.match(molecule):
setattr(molecule,typeAdvice.name,typeAdvice.typeaddition)'''
def readAspectsConstructAdviceLists(self):
"""Internal - initializes aspects and constructs all advice lists"""
for aspect in self.aspects:
aspect.setWeaver(self)
aspect.mainAspect()
for advice in aspect.getAdviceList():
if advice.pointcut.operator == PointCut.AFTER:
self.afterAdviceList.append(advice)
else:
self.beforeAndReplaceAdviceList.append(advice)
for typeAdvice in aspect.getTypeAdviceList():
if typeAdvice.isPartAdvice():
self.partTypeAdviceList.append(typeAdvice)
else:
self.moleculeTypeAdviceList.append(typeAdvice)
weaverOutput = self.weaverOutput # to make weaverOutput visible to closure scope
if len(aspect.getWeaverOutputList()) > 0:
# this aspect wants to add a new weaver output target
# TODO check if a similarly named output target already exists and raise
# useful exception (containing name of clashed method, name of advice)
for outputMethod in aspect.getWeaverOutputList():
setattr(self.weaverOutput, outputMethod.__name__,
types.MethodType(outputMethodWrapper(outputMethod), aspect))
# todo clean up, possible split lookup and creation
def addElemTypeAdvice(self, elem):
"""Internal - adds type advice to a part"""
list = self.partTypeAdviceList
if isinstance(elem, Molecule):
list = self.moleculeTypeAdviceList
for typeAdvice in list:
if typeAdvice.signature.match(elem):
# TODO check for name clashes...
if inspect.ismethod(typeAdvice.typeaddition):
setattr(elem, typeAdvice.name,
types.MethodType(adviceMethodWrapper(typeAdvice.typeaddition), typeAdvice.aspect))
else:
setattr(elem, typeAdvice.name, typeAdvice.typeaddition)
def runBeforeAndReplaceAdvice(self, callingObject, part):
"""Internal - runs Before and Replace Advice of a part
| *Args:*
| part - The part for which the advice matches
| callingObject - the circuit or advice which added the part
| *Returns:*
| "continue"
| True - If part should still be added
| False - If part has been replaced and remaining after advice executed
"""
for advice in self.beforeAndReplaceAdviceList:
if len(self.currentWeaverOutput.partList) > 0:
part.setBeforePart(self.currentWeaverOutput.partList[-1])
if advice.pointcut.match(part):
if (advice.pointcut.operator == PointCut.REPLACE):
numberOfMatchingParts = advice.pointcut.signature.numberOfMatchingParts(part)
while numberOfMatchingParts > 1:
self.currentWeaverOutput.partList.pop()
numberOfMatchingParts -= 1
# Advice should return False if not replaced, True if Replaced
AdviceResult = advice.adviceMethod(PointCutContext(self.withinStack, part))
self.runAfterAdvice(callingObject, part, advice.precedence)
return not AdviceResult
advice.adviceMethod(PointCutContext(self.withinStack, part))
return True
def runAfterAdvice(self, callingObject, part, precedence=Advice.MINPRECEDENCE):
"""Internal - runs After Advice of a part
| *Args:*
| part - The part for which the advice matches
| callingObject - the circuit or advice which added the part
| precedence - Only run advice with a precedence greater or equal this
| Used if replacement advice has been executed
"""
# after advice are ordered by ascending precedence
# the one with the lowest priority is executed
#if precedenceLevel is set by a replacement advice, we will only
#execute those advice with >= precedence
for advice in self.afterAdviceList:
if (advice.precedence >= precedence) and (advice.pointcut.match(part)):
advice.adviceMethod(PointCutContext(self.withinStack, part))
class MoleculeReactionTo:
"""Class to represent the right hand side of a molecule reaction
"""
class MoleculeReactionFrom:
"""Class to represent the left hand side of a molecule reaction
and enable convenient syntax by overloading the >> (rshift) operator
| *Attributes:*
| before : [ExecutionNode]
| A list of ExecutionNode objects that precede this node
| after : [ExeuctionNode]
| A list of ExecutionNode objects that follow this node
| scope : class(WeaverOutput)
| What woven system is this node part of
| additionStack : [Circuit or Aspect]
| stack of Aspects and Circuits which are executing to add
| this node
"""
def reactionFrom(self, callingObject, molecules):
"""Used to add the left hand side of a molecule reaction to the design,
called by either a circuit or aspect
| *Args:*
| callingObject - the circuit or aspect calling this
| molecules - the list of molecules on the lhs of the reaction
"""
return self.MoleculeReactionFrom(self, callingObject, molecules)
def reactionTo(self, callingObject, molecules):
"""Used to add the right hand side of a molecule reaction to the design,
called by either a circuit or aspect
| *Args:*
| callingObject - the circuit or aspect calling this
| molecules - the list of molecules on the rhs of the reaction
"""
return self.MoleculeReactionTo(molecules)
def importMolecule(self, callingObject, molecule):
"""Indicates that a molecule should be "imported" by the current compartment from
the outer compartment
| *Args:*
| callingObject - the circuit or aspect calling this
| molecule - the molecule to be imported
"""
# means that we are getting a molecule from the next larger scope
# todo check that we are not in outest scope
# todo rethink - why should getMOlecule... take an object?? it's creating them afterall... should take class name?
# todo no? maybe?
importedMoleculeParent = self.getMoleculeObject(self.currentWeaverOutput.parentCircuit, molecule)
# case 1: molecule already exists in scope and needs to be merged
for mol in self.currentWeaverOutput.moleculeList:
if isinstance(mol, molecule):
mol.before.append(importedMoleculeParent)
importedMoleculeParent.after.append(mol)
return
# otherwise:
#case 2: molecule doesn't exist yet
self.createMolecule(callingObject, molecule)
# now we can add it via case 1:
self.importMolecule(callingObject, molecule)
def exportMolecule(self, callingObject, molecule):
"""Indicates that a molecule should be "exported" by the current compartment to
the outer compartment
| *Args:*
| callingObject - the circuit or aspect calling this
| molecule - the molecule to be exported
"""
# todo error checking
# e.g. if molecule already exists (but possible differnet instances?? warn of clash?
# if parent doesn't exist
exportMolecule = self.getMoleculeObject(self.currentWeaverOutput, molecule)
# case 1: the molecule already exists in the outer scope and needs to be added to its graph
for mol in self.currentWeaverOutput.parentCircuit.moleculeList:
if isinstance(mol, molecule):
mol.before.append(exportMolecule)
exportMolecule.after.append(mol)
return
# otherwise:
#case 2: molecule doens't exist yet in outer scope
self.getMoleculeObject(self.currentWeaverOutput.parentCircuit, molecule, True)
self.exportMolecule(callingObject, molecule)
def createMolecule(self, callingObject, molecule):
"""Indicates that a molecule is potentially present in the current compartment,
i.e. it does not necessarily need to be created by a Coding Region, by an import, etc.
| *Args:*
| callingObject - the circuit or aspect calling this
| molecule - the molecule to be present
"""
self.getMoleculeObject(self.currentWeaverOutput, molecule, True)
# todo, if create is set to true, should actually report an error if molecule already exists.
def addCircuit(self, callingObject, circuit):
"""Called by circuit or aspect to add a circuit as a sub-compartment in the current compartment
| *Args:*
| callingObject - the circuit or aspect calling this
| circuit - The circuit to be added as a sub-compartment
"""
# todo check circuit
circuitObject = circuit()
newCircuit = self.WeaverOutput(circuitObject.__class__.__name__, self.currentWeaverOutput)
self.currentWeaverOutput.wovenCircuitList.append(newCircuit)
self.currentWeaverOutput = newCircuit
# new sub circuit is set up. no we'll weave it
circuitObject.setWeaver(self)
circuitObject.mainCircuit()
self.currentWeaverOutput = self.currentWeaverOutput.parentCircuit
def addPart(self, callingObject, part):
"""Called by circuit or aspect to add a part in the execution flow
| *Args:*
| callingObject - the circuit or aspect calling this
| part - The part supposed to be added
"""
part = checkIfTypeReturnInstance(part)
# part.namespace = self.currentWeaverOutput
part.scope = self.currentWeaverOutput
self.withinStack.append(callingObject)
part.additionStack = self.withinStack[:]
continueAddingPart = self.runBeforeAndReplaceAdvice(callingObject, part)
# before adding the part, add any type advice
if continueAddingPart:
part.weave(self)
# TODO clean this up, the namespace issue...
self.addElemTypeAdvice(part)
# If the part is a composite, we unpack it here. otherwise we finally add the part
if isinstance(part, Circuit) == False:
# add before / after information
if len(self.currentWeaverOutput.partList) > 0:
self.currentWeaverOutput.partList[-1].setAfterPart(part)
part.setBeforePart(self.currentWeaverOutput.partList[-1])
self.currentWeaverOutput.partList.append(part)
else:
# the circuit is not initialized with a weaver
part.setWeaver(self)
part.mainCircuit()
self.runAfterAdvice(callingObject, part)
self.withinStack.pop()
def output(self):
"""Returns the weaverOutput Element"""
return self.weaverOutput
class MoleculeValueError(ValueError):
"""Molecule was expected, but something else was given"""
pass
class PartInitializationError(Exception):
"""Part was expected, but something else was given"""
class PartValueError(ValueError):
"""Part was expected, but something else was given"""
class InvalidSymbolNameError(ValueError):
"""A symbol name (string) was not correctly formatted"""
pass
class SymbolExistsWarning(UserWarning):
"""A Part or Molecule declaration uses an existing name"""
pass
class InvalidSignatureError(ValueError):
"""A signature (PointCut / Part / Molecule) is incorrectly formatted or typed"""
pass
class InvalidPointCutExpressionError(ValueError):
"""There is an error in a Point Cut expression"""
pass
class InvalidPointCutOperatorError(ValueError):
"""An unknown or illegal operator was used for the point cut"""
pass
class InvalidPointCutError(ValueError):
"""object of type PointCut expected, but something else given"""
pass
class InvalidAdviceMethodError(ValueError):
"""method with 2 parameters expected, but something else given"""
pass
class InvalidWeaverOutputMethodError(ValueError):
""" with 2 parameters expected, but something else given"""
pass
class PrecedenceOutOfRangeError(ValueError):
"""An unknown or illegal operator was used for the point cut"""
pass
class AspectValueError(ValueError):
"""An Aspect class was expected, but something else given"""
class CircuitValueError(ValueError):
"""A Circuit class was expected, but something else given"""
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2073,
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37811,
198
] | 2.468112 | 25,684 |
from setuptools import setup, Extension
import re
description = 'A python library to evolve binary star systems in time.'
try:
with open('README.md', 'r') as f:
long_description = f.read()
except FileNotFoundError:
long_description = description
metadata = {"version": "",
"author": "",
"email": ""
}
metadata_file = open("takahe/_metadata.py", "rt").read()
for item in metadata.keys():
version_regex = rf"^__{item}__ = ['\"]([^'\"]*)['\"]"
match = re.search(version_regex, metadata_file, re.M)
if match:
metadata[item] = match.group(1)
setup(name='takahe',
license = 'MIT License',
version = metadata['version'],
description = description,
long_description = long_description,
author = metadata['author'],
author_email = metadata['email'],
packages = ['takahe'],
zip_safe = False,
homepage = 'https://github.com/Krytic/Takahe',
install_requires = ['numpy',
'matplotlib',
'numba',
'pandas==1.0.1',
'diffeqpy'
]
)
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220,
220,
220,
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198,
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] | 1.988959 | 634 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from sklearn.preprocessing import Normalizer
from SharedFunctions import get_current_time, fmt, find_accuracy
from datetime import datetime
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from ReadPreprocessData import read_preprocess
from Tokenize import tokenize
import numpy as np
import tensorflow as tf
import scipy.sparse as ss
tf.logging.set_verbosity(tf.logging.INFO)
vectorizer = TfidfVectorizer(tokenizer=tokenize, stop_words='english')
if __name__ == "__main__":
tf.app.run() | [
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] | 3.397849 | 186 |
from __future__ import absolute_import, division, print_function
import boost_adaptbx.boost.python as bp
bp.import_ext("cctbx_covariance_ext")
from cctbx_covariance_ext import *
| [
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] | 2.825397 | 63 |
# coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# 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.
"""Base class for evaluation metrics."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import abc
class Scorer(object):
"""Abstract base class for computing evaluation metrics."""
__metaclass__ = abc.ABCMeta
@abc.abstractmethod
@abc.abstractmethod
@abc.abstractmethod
# def get_results(self, prefix=""):
# results = self._get_results() if self._updated else self._cached_results
# self._cached_results = results
# self._updated = False
# return [(prefix + k, v) for k, v in results]
| [
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66,
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220,
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220,
220,
220,
220,
2116,
13557,
66,
2317,
62,
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2482,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
2116,
13557,
43162,
796,
10352,
198,
220,
220,
220,
1303,
220,
220,
220,
220,
1441,
47527,
40290,
1343,
479,
11,
410,
8,
329,
479,
11,
410,
287,
2482,
60,
198
] | 3.348901 | 364 |
from pico_code.host.talker import Talker
import turtle
talker = Talker()
turtle = turtle.Turtle()
while True:
text = talker.receive()
x,y = [convert(text) for text in text.split()]
turtle.setx(x)
turtle.sety(y)
| [
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198
] | 2.391753 | 97 |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.16 on 2018-10-29 18:33
from __future__ import unicode_literals
from django.db import migrations
from django_airavata.apps.auth.models import (
NEW_USER_EMAIL_TEMPLATE,
VERIFY_EMAIL_TEMPLATE
)
| [
2,
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] | 2.40566 | 106 |
from sleekxmpp.plugins.base import register_plugin as _register_plugin
from sleekpromises.scheduler import sleekpromises_scheduler as _scheduler
def register_sleek_promises():
"""
Register the sleek promises components for the sleek xmpp framework.
:return:
"""
_register_plugin(_scheduler)
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] | 3.14 | 100 |
# git clone https://github.com/GoogleCloudPlatform/microservices-demo.git
# cd microservices-demo/src/loadgenerator
# export FRONTEND_ADDR=localhost
# rename : sock shop locustfile.py to locustfile.py
# ./loadgen.sh
# sock shop locustfile.py file
# loadgen.sh is using test steps in : locustfile.py for steps
import random
from locust import HttpUser, TaskSet, between
from random import randint, choice
| [
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220,
220,
220,
220,
201,
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] | 2.75625 | 160 |
import ansible.inventory.manager
import ansible.constants
import ansible.parsing.dataloader
| [
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] | 3.241379 | 29 |
# ===============================================================
# Author: Rodolfo Ferro
# Email: [email protected]
# Twitter: @FerroRodolfo
#
# ABOUT COPYING OR USING PARTIAL INFORMATION:
# This script was originally created by Rodolfo Ferro, for
# his workshop in PythonDay Mexico 2018 at CUCEA in Gdl, Mx.
# Any explicit usage of this script or its contents is granted
# according to the license provided and its conditions.
# ===============================================================
# -*- coding: utf-8 -*-
from keras.datasets import mnist
from random import randint
import cv2
def digit_downloader(number_of_digits, path):
"""
Utility funciton to download random digits.
"""
# Load data:
(X_train, y_train), (X_test, y_test) = mnist.load_data()
# Generate random indices:
digits = [randint(0, 59000) for i in range(number_of_digits)]
# Save images:
for digit in digits:
cv2.imwrite(path + '{}.png'.format(digit), X_train[digit])
return
if __name__ == "__main__":
digit_downloader(3, "../assets/")
| [
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7,
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7,
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62,
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628,
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198,
361,
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366,
834,
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220,
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220,
16839,
62,
15002,
263,
7,
18,
11,
366,
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19668,
14,
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198
] | 3.036932 | 352 |
from __future__ import print_function
import argparse
import gzip
import io
import os
import sys
from collections import defaultdict
from consplice.constraint.utils import get_alternative_gene_symbols
from interlap import InterLap
# ------------------------------------------------------------------------------------------------------------------------------------------------------
## Argument Parser
# ------------------------------------------------------------------------------------------------------------------------------------------------------
# ------------------------------------------------------------------------------------------------------------------------------------------------------
## Functions
# ------------------------------------------------------------------------------------------------------------------------------------------------------
def create_hexevent_interlap(file_path, zero_based):
"""
create_hexevent_interlap
========================
This method is used to create interlap objects of HEXEvent features. (Constitutive or cassette exons). It will iterate through
each feature in the file and add it to the chromosome specific interlap object in the dictionary. It uses the names of the columns
from the HEXEvent files. This function will not work if the column names have been changed. Removes any chr prefix if it exists.
The start position is set to 1-based if it is designated as a 0-based start position.
Parameters:
-----------
1) file_path: (str) Path to the HEXEvent txt file (of constitutive or cassette exon features).
2) zero_based: (bool) True if zero-based start position else False
Returns:
++++++++
1) (dict) A dict of interlap objects. Each interlap object contains of tuple of:
(1-based start pos, end-pos, {strand, constitLevel, inclLevel, genename})
"""
interlap_dict = defaultdict(InterLap)
try:
fh = (
gzip.open(file_path, "rt", encoding="utf-8")
if file_path.endswith(".gz")
else io.open(file_path, "rt", encoding="utf-8")
)
except IOError as e:
print("\n!!ERROR!! unable to open file: '{}'".format(file_path))
print(str(e))
sys.exit(1)
header = fh.readline().strip().split("\t")
for line in fh:
line_dict = dict(zip(header, line.strip().split("\t")))
## Skip any lines that are missing data
if "start" not in line_dict:
continue
start = int(line_dict["start"]) + 1 if zero_based else int(line_dict["start"])
end = int(line_dict["end"])
## create interlap object
interlap_dict[line_dict["chromo"].replace("chr", "")].add(
(
start,
end,
{
"strand": line_dict["strand"],
"constitLevel": line_dict["constitLevel"],
"inclLevel": line_dict["inclLevel"],
"genename": line_dict["genename"],
},
)
)
fh.close()
return interlap_dict
def overlapping_exon(
feature_chrom,
feature_start,
feature_end,
feature_strand,
feature_gene,
alt_gene_dict,
interlap_object,
):
"""
overlapping_exon
================
This method is used to identify exons from a gtf file that overlap a feature from an interlap object. This method assumes
that the start positions of the interlap object are 1-based, and that the chromosome name does not have a 'chr' prefix.
It also will only identify if an overlap if the exon has the same start, end, strand, and gene name.
This method expects that the interlap object is based on the HEXEvent data file and that it contains a dictionary with the 'strand',
'constitLevel', 'inclLevel', 'strand' feature values.
Parameters:
-----------
1) feature_chrom: (str) The gtf chromosome name
2) feature_start: (int) The start position of the gtf feature
3) feature_end: (int) The end position of the gtf feature
4) feature_strand: (str) The strand of the gtf feature
5) feature_gene: (str) The name of the gene for the gtf feature
6) alt_gene_dict: (dict) A dictionary of alt gene symbols
7) interlap_object: (dict) A dictionary of interlap object features to identify overlaps from
Returns:
++++++++
1) (bool) True or False whether a matching overlap feature was found
2) (str) The constitLevel value from the overlapping feature or an empty string
3) (str) The inclLevel value from the overlapping feature or an empty string
"""
for exon in interlap_object[feature_chrom.replace("chr", "")].find(
(int(feature_start), int(feature_end))
):
same_start = int(exon[0]) == int(feature_start)
same_end = int(exon[1]) == int(feature_end)
same_strand = exon[2]["strand"] == feature_strand
same_gene = any(
True if x == feature_gene or x in alt_gene_dict[feature_gene] else False
for x in exon[2]["genename"].strip().split(",")
)
return (
True if same_start and same_end and same_strand and same_gene else False,
exon[2]["constitLevel"],
exon[2]["inclLevel"],
)
return (False, "", "")
# ------------------------------------------------------------------------------------------------------------------------------------------------------
## Main
# ------------------------------------------------------------------------------------------------------------------------------------------------------
if __name__ == "__main__":
sys.exit(main() or 0)
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198,
220,
220,
220,
25064,
13,
37023,
7,
12417,
3419,
393,
657,
8,
198
] | 2.956835 | 1,946 |
print(interversion("Marc Barthet"))
| [
198,
198,
4798,
7,
3849,
9641,
7203,
22697,
13167,
3202,
48774,
198
] | 3.166667 | 12 |
import re
from setuptools import find_packages, setup
install_requires = [
'Django>=1.11.28',
'Wagtail>=2.2',
'django-otp>=0.8.1',
'six>=1.14.0',
'qrcode>=6.1',
]
docs_require = [
'sphinx>=1.4.1',
'sphinx_rtd_theme>=0.4.3',
]
tests_require = [
'coverage==5.0.3',
'pytest==5.3.5',
'pytest-cov==2.8.1',
'pytest-django==3.8.0',
# Linting
'isort==4.3.21',
'flake8==3.7.9', # 3.7.9
'flake8-blind-except==0.1.1',
'flake8-debugger==3.2.1',
]
with open('README.rst') as fh:
long_description = re.sub(
'^.. start-no-pypi.*^.. end-no-pypi', '', fh.read(), flags=re.M | re.S)
setup(
name='wagtail-2fa',
version='1.4.2',
description="Two factor authentication for Wagtail",
long_description=long_description,
url='https://github.com/LabD/wagtail-2fa',
author="Lab Digital",
author_email="[email protected]",
install_requires=install_requires,
tests_require=tests_require,
extras_require={
'docs': docs_require,
'test': tests_require,
},
python_requires='>=3.6',
use_scm_version=True,
entry_points={},
package_dir={'': 'src'},
packages=find_packages('src'),
include_package_data=True,
license='MIT',
classifiers=[
'Development Status :: 4 - Beta',
'Environment :: Web Environment',
'Framework :: Django',
'Framework :: Django :: 1.11',
'Framework :: Django :: 2.2',
'Framework :: Django :: 3.0',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
],
zip_safe=False,
)
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] | 2.145783 | 830 |
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