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212
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9dae9e1cb02e03ac83133c64c0010ed526601e15
|
bd9c74247381121f71f3dde6b55c67856f58e124
|
/编程题/第4章-6 输出前 n 个Fibonacci数 (15分).py
|
d9428ceda6a9128e079ff4764f63ec641e09169e
|
[] |
no_license
|
Redomeliu/Python
|
302cd5abd89f7040911c8afb1db6faee6d43de64
|
9f5568ec59d30ce0f7d572d072b86088e933abc8
|
refs/heads/master
| 2023-01-05T19:51:00.795864 | 2020-10-29T02:42:36 | 2020-10-29T02:42:36 | 308,293,416 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 332 |
py
|
def Fibonacci(i):
lis = [1,1]
n = 1
while(i>n):
lis.append(lis[n]+lis[n-1])
n +=1
return lis[i]
x = int(input())
count = 0
for i in range(x):
count +=1
print(f'{Fibonacci(i):>11d}',end="")
if count == 5 or i==x-1:
print('\n')
count=0
if x < 1:
print('Invalid.')
|
[
"1258995373@qq.com"
] |
1258995373@qq.com
|
5fbc95af27e8f02dbba38eac2683c62ebb6d0c35
|
3a6ab03da2f7ec1069c80f23c2ed6e2108ecb0ff
|
/urllib_urlopen.py
|
a8567af89b4f9558c14308f49467b82ed5562da0
|
[] |
no_license
|
lyletzzzw/pyAPIExample
|
01604c0bc0f3df2b20b229873d25493d191d3e99
|
3760789f5d485774d86c469aa221ca6d8c2dba2c
|
refs/heads/master
| 2021-01-17T17:06:33.730266 | 2012-08-05T13:06:18 | 2012-08-05T13:06:18 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 387 |
py
|
#! /usr/bin/env python
#coding=utf-8
import urllib
'''
sock = urllib.urlopen('http://diveintopython.org')
html1 = sock.info()
html2 = sock.read()
sock.close()
print html1
print html2
'''
print '--------------------------------------------'
data=urllib.urlencode({'wd':'AAA'})
print data
sock = urllib.urlopen('http://www.baidu.com',data)
html = sock.read()
sock.close()
print html
|
[
"lyletzzzw@sina.com"
] |
lyletzzzw@sina.com
|
da9bfaca059b92580491b71e850ef87666555b90
|
9baa968c71efebb42c70c130de930cb4810ded31
|
/OS_IMUDataConversion.py
|
05e2d59dff4bb385de0ff7c99c81dc6fa852ff76
|
[] |
no_license
|
jravenhorst909/MoveShelf_IMU_analyser
|
02cdc0e7f54f9120611106314ad8c055dfb7ad22
|
cadc3c405b4f61f4d44a29783824889e1f204360
|
refs/heads/main
| 2023-02-12T20:46:16.826991 | 2021-01-06T10:21:20 | 2021-01-06T10:21:20 | 311,619,156 | 8 | 1 | null | 2021-01-06T10:21:21 | 2020-11-10T10:12:03 |
Python
|
UTF-8
|
Python
| false | false | 1,582 |
py
|
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 8 13:28:40 2020
@author: Joris Ravenhorst
"""
import opensim as osim
def IMUdata_conversion(trial_dir_path,TrialName):
# Build an Xsens Settings Object.
# Instantiate the Reader Settings Class
xsensSettings = osim.XsensDataReaderSettings('myIMUMappings.xml')
# Instantiate an XsensDataReader
xsens = osim.XsensDataReader(xsensSettings)
# Read in seprate tables of data from the specified IMU file(s)
tables = xsens.read(trial_dir_path)
# get the trial name from the settings
trialID = xsensSettings.get_trial_prefix()
# Get Orientation Data as quaternions
quatTable = xsens.getOrientationsTable(tables)
# Write to file
osim.STOFileAdapterQuaternion.write(quatTable, trial_dir_path +'/'+ trialID + '_orientations.sto')
# OPTIONAL:
# # Get Acceleration Data
# accelTable = xsens.getLinearAccelerationsTable(tables)
# # Write to file
# osim.STOFileAdapterVec3.write(accelTable, trial_dir_path +'/'+ trialID + '_linearAccelerations.sto')
# # Get Magnetic (North) Heading Data
# magTable = xsens.getMagneticHeadingTable(tables)
# # Write to file
# osim.STOFileAdapterVec3.write(magTable, trial_dir_path +'/'+ trialID + '_magneticNorthHeadings.sto')
# # Get Angular Velocity Data
# angVelTable = xsens.getAngularVelocityTable(tables)
# # Write to file
# osim.STOFileAdapterVec3.write(angVelTable, trial_dir_path +'/'+ trialID + '_angularVelocities.sto')
return trialID
|
[
"noreply@github.com"
] |
jravenhorst909.noreply@github.com
|
74be8d4d0984d5ac6a6f034cc22a1d68d58228f7
|
369e4a831387a477a1e37b995b264504e6ed91bd
|
/nomadiq_app/run.py
|
66275b06c174c1dd71971b802216f699235dbd0b
|
[] |
no_license
|
geneahn/nomadiq_repo
|
2544762c507e0121c284b979240c52fca36a4f68
|
baba67426f940f9de5f3b7cb0519a496467cd087
|
refs/heads/master
| 2020-04-21T22:38:43.380259 | 2019-04-16T07:08:21 | 2019-04-16T07:08:21 | 169,919,167 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 103 |
py
|
from nomadiq_app import app as application
if __name__ == '__main__':
application.run(debug=True)
|
[
"linhmtran@berkeley.edu"
] |
linhmtran@berkeley.edu
|
47cb81c305f5950abd06d4b86fb817c6ec52f5fa
|
1d9ad7aa473191dad19a64b8a72a4677db221e93
|
/main.py
|
62666cef8f1456cdbb69389b0e988ba4da7db633
|
[] |
no_license
|
ethicalhacker7217/PyStudio
|
1884329209ec487f95300ee30521a51761d5bc3c
|
176756fa396d3156803b400ffac2c5ac658a27cc
|
refs/heads/main
| 2023-04-25T07:00:09.446229 | 2021-05-15T05:20:09 | 2021-05-15T05:20:09 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,752 |
py
|
from tkinter import *
from tkinter.filedialog import asksaveasfile,askopenfilename
import subprocess
compiler = Tk()
compiler.title('PyStudio')
File_path = ''
def set_file_path(path):
global File_path()
File_path = path
def run():
if File_path == '':
save_prompt = Toplevel()
text = Label(save_prompt, text='Please save your code')
text.pack()
command = f'python{File_path}'
process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True )
output, error = process.communicate()
code_output.insert('1.0', output)
code_output.insert('1.0', error)
def Save_as():
if File_path == '':
path = asksaveasfile(filetypes=['Python Files','*.py'])
else:
path = File_path
with open(path,'w') as file:
code = editor.get('1.0',END)
file.write(code)
set_file_path(path)
def Open():
path = askopenfilename(filetypes=['Python Files','*.py'])
with open(path,'r') as file:
code = editor.get('1.0',END)
file.read()
editor.delete('1.0',END)
editor.insert('1.0', code)
set_file_path(path)
menu_bar = Menu(compiler)
file_menu = Menu(menu_bar, tearoff=0)
file_menu.add_command(label='Open', command=Open)
file_menu.add_command(label='Save', command=Save_as)
file_menu.add_command(label='Save As', command=Save_as)
file_menu.add_command(label='Exit', command=exit)
menu_bar.add_cascade(label = 'File', menu=file_menu)
run_bar = Menu(menu_bar, tearoff=0)
run_bar.add_command(label='Run', command=run)
menu_bar.add_cascade(label='Run', menu=run_bar)
compiler.config(menu=menu_bar)
editor = Text()
editor.pack()
code_output = Text(height=7)
code_output.pack
compiler.mainloop()
|
[
"noreply@github.com"
] |
ethicalhacker7217.noreply@github.com
|
bec5d5fbb09b6260d514209bc438f344d215832b
|
ac5e52a3fc52dde58d208746cddabef2e378119e
|
/exps-sblp/sblp_ut=3.5_rd=1_rw=0.04_rn=4_u=0.075-0.325_p=harmonic-2/sched=RUN_trial=30/sched.py
|
a85202e958d39e172c17afa700742b708255c6d6
|
[] |
no_license
|
ricardobtxr/experiment-scripts
|
1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1
|
7bcebff7ac2f2822423f211f1162cd017a18babb
|
refs/heads/master
| 2023-04-09T02:37:41.466794 | 2021-04-25T03:27:16 | 2021-04-25T03:27:16 | 358,926,457 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 495 |
py
|
-S 0 -X RUN -Q 0 -L 2 84 250
-S 1 -X RUN -Q 0 -L 2 80 250
-S 0 -X RUN -Q 0 -L 2 74 250
-S 0 -X RUN -Q 0 -L 2 59 250
-S 2 -X RUN -Q 1 -L 1 57 200
-S 2 -X RUN -Q 1 -L 1 48 175
-S 2 -X RUN -Q 1 -L 1 40 125
-S 2 -X RUN -Q 1 -L 1 33 300
-S 3 -X RUN -Q 2 -L 1 29 100
-S 3 -X RUN -Q 2 -L 1 27 125
-S 3 -X RUN -Q 2 -L 1 21 100
-S 3 -X RUN -Q 2 -L 1 19 150
-S 4 -X RUN -Q 3 -L 1 19 100
-S 4 -X RUN -Q 3 -L 1 15 100
-S 4 -X RUN -Q 3 -L 1 14 100
|
[
"ricardo.btxr@gmail.com"
] |
ricardo.btxr@gmail.com
|
5893049dfab4f9e7702c5a3117f4468d5c72a98f
|
27bd7769798502bccbbc4b1bbc34e22d17f17d98
|
/regressao_linear.py
|
6dd8db7e2851e9a8717ad91bfc2f4b32d1eb00d7
|
[] |
no_license
|
jcclark/regressao_linear
|
03f3bfd759de3e629788d7ba6891f081ae41a667
|
bcf27dd810eb3916809b3683098ae2c3bd4dc619
|
refs/heads/master
| 2020-08-01T09:29:57.254610 | 2019-10-05T22:35:14 | 2019-10-05T22:35:14 | 210,948,723 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,757 |
py
|
import csv
import math
from random import randint
import matplotlib.pyplot as plt
def modelo( data, tipo, i):
dados = dv_dados(data, tipo)
b_treino, b_teste = dv_bases(dados, i)
b_0, b_1 = regressao_linear(b_treino, tipo)
x = [d[0] for d in dados]
y = [(b_0 + (d[0] * b_1)) for d in dados]
desvio = desvio_padrao(b_teste, b_0, b_1)
print("Desvio padrão: " + str( round(desvio, 2) ))
plt.title('Média Provas x ' + tipo )
plt.xlabel(tipo.title())
plt.ylabel('Média provas')
plt.scatter(x, y)
plt.plot(x, y)
plt.show()
def desvio_padrao( b_teste, b_0, b_1):
desvio = 0
for d in b_teste:
y = d[1]
fx = (b_0 + (d[0] * b_1))
desvio += (y - fx) ** 2
return desvio
def regressao_linear( b_treino, type):
N = len(b_treino)
x = somatorio(b_treino, 'x')
y = somatorio(b_treino, 'y')
xy = somatorio(b_treino, 'xy')
x1 = somatorio(b_treino, 'x2')
b_1 = ((x * y) - (N * xy)) / ((x ** 2) - (N * x1))
b_0 = (y - (b_1 * x))/ N
return b_0, b_1
def somatorio( l_n, tipo):
numeros = []
for t in l_n:
if tipo == 'x':
a = t[0]
elif tipo == 'y':
a = t[1]
elif tipo == 'xy':
a = t[0] * t[1]
elif tipo == 'x2':
a = t[0] ** 2
else:
a = 1
print('Erro')
numeros.append(a)
return sum(numeros)
def dv_dados( data, tipo):
res = []
for item in data:
if tipo == "Idade":
x = item.get("Idade")
elif tipo == "Tempo de Estudo":
x = item.get("Tempo de Estudo")
elif tipo == "Faltas":
x = item.get("Faltas")
y = item.get("MediaProvas")
res.append((int(x), int(y)))
return res
def dv_bases(dados, i):
p_treino = []
while (len(p_treino) < round(i * 0.7)):
posicao = randint(0, i - 1)
if posicao not in p_treino:
p_treino.append(posicao)
d_treino = [dados[p] for p in p_treino]
d_treino = [dados[p] for p in range(len(dados)) if p not in p_treino]
return d_treino, d_treino
def excutar():
data = []
with open("AnaliseEstudo.csv") as csv_file:
csv_reader = csv.reader(csv_file, delimiter=";")
for row in csv_reader:
if row[0] != "Idade":
media = (int(row[3]) + int(row[4]) + int(row[5])) / 3
aux = {
"Idade": row[0],
"Tempo de Estudo": row[1],
"Faltas":row[2],
"MediaProvas": media
}
data.append(aux)
for tipo in ["Idade", "Tempo de Estudo", "Faltas"]:
modelo(data, tipo, len(data))
excutar()
|
[
"juniorclark@gmail.com"
] |
juniorclark@gmail.com
|
c2abb820a33634fbd4d2baa8cc40894fd5ffc9db
|
afea9757be324c8def68955a12be11d71ce6ad35
|
/willyanealves/customer_service/migrations/0018_remove_customerservice_serviceitem.py
|
5389c0887e5e5598bfdb43884190c5126c6d8681
|
[] |
no_license
|
bergpb/willyane-alves
|
c713cac3ec3a68005f3b8145985693d2477ba706
|
8b2b9922ba35bf2043f2345228f03d80dbd01098
|
refs/heads/master
| 2023-02-10T19:57:50.893172 | 2021-01-11T16:17:14 | 2021-01-11T16:17:14 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 368 |
py
|
# Generated by Django 3.1.2 on 2020-11-16 14:18
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('customer_service', '0017_auto_20201116_1115'),
]
operations = [
migrations.RemoveField(
model_name='customerservice',
name='serviceitem',
),
]
|
[
"jocsadm@gmail.com"
] |
jocsadm@gmail.com
|
6dcb83acc4bf4107889ebbe1f7af8432518e95eb
|
3a022998c1fa28408e6d38845f29730579d22a20
|
/rootsofcube.py
|
88f22babfd0f3217b9e57c2e5a715534a2a49d56
|
[] |
no_license
|
nandishaivalli/APS2020
|
1cd69fbade6fd2069f6b72dc5e8815d905c73836
|
57bcbe919c92692c61093e01304815c0f29222dc
|
refs/heads/master
| 2020-12-20T20:58:23.523106 | 2020-05-16T07:44:33 | 2020-05-16T07:44:33 | 236,208,138 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 252 |
py
|
#using formula find the roots of cubic eqn
a = 3
b = 4
c = 4
d = 3
#ax3+bx2+cx+d=0
p = (-1*b)/(3*a)
q = p**3 + (b*c-3*a*d)/(6*a**2)
r = c/(3*a)
x = (q+(q**2 + (r-p**2)**3)**0.5)**(1/3) + (q-(q**2 + (r-p**2)**3)**0.5)**(1/3) + p
print(x)
|
[
"noreply@github.com"
] |
nandishaivalli.noreply@github.com
|
563f625c719041548b3b0dee923cd3f05db82e19
|
498328d283bbcfa2aed7780cc2ccd1ab1435998c
|
/validation.py
|
7edbc1a87dd4a75e441e312bb3351b880ee9201b
|
[] |
no_license
|
ktan8/AM205-Project
|
51a336921314b5e977dd9682a60f8c73adc64598
|
e697afe74f0b9fb8d2b177191e7d8472a3167031
|
refs/heads/master
| 2020-04-11T01:01:34.481178 | 2018-12-16T15:01:19 | 2018-12-16T15:01:19 | 161,403,438 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 6,987 |
py
|
'''Reads suppulemeal data'''
import pandas as pd
import os
import network_matrices
import numpy as np
import scipy.stats
import matplotlib.pyplot as plt
def label_active(row):
'''Label whether a given knockout was higher express - huristic is to see
if it's above 20% points above/below baseline'''
if(row['RNA1_percent'] >1.2 and row["RNA2_percent"] > 1.2):
return(1)
elif(row["RNA1_percent"] < 0.8 and row["RNA2_percent"] < 0.8):
return(-1)
return(0)
def get_data_jak2():
'''Read the expression data for jak2'''
path = os.path.join("data", "data_jak2_knockdown.txt")
data = pd.read_csv(path, sep = '\t')
data["RNA1_percent"] = data["sh-JAK2-shRNA1"] / data["shRNA-control"]
data["RNA2_percent"] = data["sh-JAK2-shRNA2"] / data["shRNA-control"]
data['mat_val'] = data.apply(label_active, axis = 1)
return(data)
def get_data_stat5():
'''Get stat5 expression data'''
path3 = os.path.join("data", "data_stat5_knockdown.txt")
d4 = pd.read_csv(path3, sep = '\t')
d4['percent_change' ] = d4['data.expr.anno.ctl'] / d4['data.expr.anno.kdSTAT5']
return(d4)
def get_pathway(path):
'''Read in hand currated network'''
pathway = pd.read_csv(path)
pathway = pathway.set_index("Unnamed: 0")
pathway.index.name = "Gene"
conversion_path = os.path.join("data", "convertModelToExprNames.txt")
conversions = pd.read_table(conversion_path)
return(pathway, conversions)
def compute_expressions(conversions, df, gene_col = "Gene Symbol", control_col = "shRNA-control", experiment_col = "sh-JAK2-shRNA1"):
'''Create a dictionary of the expresison data percent change per gene'''
expression_levels_change = {}
for elem in conversions:
model_name = elem[0]
targets = elem[1].split(',')
total_control = 0
total_expression = 0
for gene in targets:
avg_df = df[df[gene_col] == gene].mean() # We may have multiple expression
total_control += avg_df[experiment_col]
total_expression += avg_df[control_col]
change = total_control / total_expression - 1
if(not np.isnan(change)):
expression_levels_change[model_name] = change
return(expression_levels_change)
def get_val(df, index, gene_names):
a = (df[df["Gene Symbol"] == gene_names[index]]['mat_val']).sum()
return(np.sign(a))
def quick_correlation(jak2_index, indicies, mat1, exp):
'''Compute the correlation at a given index pair in mat1'''
l1 = np.squeeze(np.asarray(mat1[jak2_index, indicies]))
return(scipy.stats.spearmanr(np.abs(l1), np.abs(exp)))
def wrapper_corr(jak2_index, indicies, exp):
'''Dummy wrapper for syntax'''
return(lambda x : quick_correlation(jak2_index, indicies, x, exp))
def run_example(data, pathway, conversions, elc, knockdown_gene ):
path2 = os.path.join("data", "PDL1_pathway", "PDL1_pathway.matrix.csv")
tran = True
rem = True
'''Get the models'''
(prop, dist, neighbors) = network_matrices.run_many(path2, tran, rem)
(_, gene_names, _) = network_matrices.get_data(path2, tran, rem)
genes_have_all = list(elc.items())
genes_have = [x[0] for x in genes_have_all]
genes_have_val = [x[1] for x in genes_have_all]
indicies = []
jak2_index = -1
pdl1_index = pathway.index.get_loc("PD-L1")
for i in range(0, len(gene_names)):
if(gene_names[i] == knockdown_gene):
jak2_index = i
if(gene_names[i] in genes_have):
indicies.append(i)
genes_have_val = np.array(genes_have_val)
f = wrapper_corr(jak2_index, indicies, genes_have_val)
#Correlation data
corr_data = [f(prop[0]), f(prop[1]), f(prop[2]), f(dist[0]), f(dist[1]) ]
'''Plotting code'''
blues = [plt.cm.Blues(300), plt.cm.Blues(200), plt.cm.Blues(100)]
oranges= [plt.cm.Oranges(200), plt.cm.Oranges(100)]
greys= [plt.cm.Greys(300), plt.cm.Greys(200), plt.cm.Greys(100)]
reds= [
plt.cm.Reds(200), plt.cm.Reds(175), plt.cm.Reds(150),
plt.cm.Reds(125), plt.cm.Reds(100)
]
colors = blues + oranges + greys + reds
objects = ('Propogation (d+s)', 'Propogation (d)',
'Propogation (u)', 'Distance (d)',
'Adjacency (d+s)')
y_pos = np.arange(len(objects))
blues = [plt.cm.Blues(300), plt.cm.Blues(200), plt.cm.Blues(100)]
oranges= [plt.cm.Oranges(200), plt.cm.Oranges(100)]
greys= [plt.cm.Greys(300)]
colors = blues + oranges + greys + reds
corr_data = [x[0] for x in corr_data]
plt.bar(y_pos, corr_data, align='center', alpha=0.5, color = colors)
plt.xticks(y_pos, objects, rotation='vertical')
plt.ylabel('Correlation')
plt.title('Strength with experiment')
plt.show()
def isactive(val):
'''Look at the direction. Up is more than 10%, down is < 10%'''
if(val > 0.1):
return(1)
elif(val < -0.1):
return(-1)
return(0)
vfunc = np.vectorize(isactive)
genes_have_val_ind = vfunc(genes_have_val)
'''Get the precent sign match'''
q = lambda inp : np.sum(np.sign(inp[jak2_index, indicies]) == np.sign(genes_have_val_ind)) / (len(indicies))
sign_match = [q(prop[0]), q(prop[1]), q(prop[2]), q(dist[0]), q(dist[1]),
]
plt.bar(y_pos, sign_match, align='center', alpha=0.5, color = colors)
plt.xticks(y_pos, objects, rotation='vertical')
plt.ylabel('Percent agreement')
plt.title('Percent agrement in sign with different models')
plt.show()
all_data_names = ["Propogation (d+s)", "Progation (d)", "Propogation (u)", "Distance (d)", "Distance (u)", "neighbors (signed)"]
all_data_models = [prop[0], prop[1], prop[0], dist[0], dist[1], neighbors[0]]
def write_data(index, all_data, all_data_names, pathway):
list_arr = []
for model in all_data:
list_arr.append((np.squeeze(np.asarray(model[:, index]))))
df_res = pd.DataFrame(list_arr, index = all_data_names, columns = pathway.columns[1:])
df_res.index.name = "method"
return(df_res)
'''Can write this data to a csv if needed'''
d = write_data(pdl1_index , all_data_models, all_data_names, pathway)
return(d)
(pathway, conversions) = get_pathway(os.path.join("data", "PDL1_pathway", "PDL1_pathway.matrix.csv"))
elc = compute_expressions(conversions.values, jak_2)
knockdown_gene = "JAK2"
run_example(jak_2, pathway, conversions, elc, knockdown_gene)
#stat5 = get_data_stat5()
#elc2 = compute_expressions(conversions.values, stat5, 'data.expr.anno.GENE_SYMBOL','data.expr.anno.ctl', 'data.expr.anno.kdSTAT5')
#knockdown_gene = "STAT5"
#run_example(stat5, pathway, conversions, elc2, knockdown_gene)
#
#
#f(neighbors[2].T)
|
[
"akaran@caltech.edu"
] |
akaran@caltech.edu
|
e5473522c26a9ba7d2654c9fa7a954d97bb4ed88
|
f855be082bd55159cf6f77be034a78ecf2020232
|
/actions/actions.py
|
9501206f8fdb9634b4fe7561bdb7409868ff48ea
|
[] |
no_license
|
athenasaurav/venkat
|
64e3b9522bbcceb141d87f4b04498dcfd7f10969
|
bfb7a767793483a6a8663e1e112a20c03433b2df
|
refs/heads/main
| 2023-03-27T11:32:52.246192 | 2021-03-16T18:01:55 | 2021-03-16T18:01:55 | 348,443,833 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 12,129 |
py
|
# This files contains your custom actions which can be used to run
# custom Python code.
#
# See this guide on how to implement these action:
# https://rasa.com/docs/rasa/custom-actions
# This is a simple example for a custom action which utters "Hello World!"
from typing import Any, Text, Dict, List
from rasa_sdk import Action, Tracker
from rasa_sdk.executor import CollectingDispatcher
from rasa_sdk.events import Form, AllSlotsReset, Restarted
class ActionHelloWorld(Action):
def name(self) -> Text:
return "action_greet"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Hi human, I'm sure you want something 😃 I'm sure you are gonna ask me something")
return []
class ActionPostAccommodationServicesHotel(Action):
def name(self) -> Text:
return "action_post_Accommodation_Services_Hotel"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Hotel")
return []
class ActionPostCityAttractionSpa(Action):
def name(self) -> Text:
return "action_post_city_attraction_spa"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Spa")
return []
class ActionPostEducationalSuppliesDealers(Action):
def name(self) -> Text:
return "action_post_Educational_Supplies_Dealers"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Education supplies dealers")
return []
class ActionPostEducationalSuppliesDealersBookShop(Action):
def name(self) -> Text:
return "action_post_Educational_Supplies_Dealers_book_shop"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Book Services")
return []
class ActionPostAccountant(Action):
def name(self) -> Text:
return "action_post_Accountant"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Accountant")
return []
class ActionPostInsurance(Action):
def name(self) -> Text:
return "action_post_Insurance"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Insurance")
return []
class ActionPostATM(Action):
def name(self) -> Text:
return "action_post_ATM"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="ATM")
return []
class ActionPostGovernmentOffices(Action):
def name(self) -> Text:
return "action_post_Government_Offices"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="GOVT OFFICE")
return []
class ActionPostNightlife(Action):
def name(self) -> Text:
return "action_post_Nightlife"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Nightlife")
return []
class ActionPostNightlifeHookah(Action):
def name(self) -> Text:
return "action_post_Nightlife_Hookah"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Nightlife Hookah")
return []
class ActionPostSchools(Action):
def name(self) -> Text:
return "action_post_Schools"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Schools")
return []
class ActionPostSchoolsRetakers(Action):
def name(self) -> Text:
return "action_post_Schools_Retakers"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Schools Retakers")
return []
class ActionPostGamesCenters(Action):
def name(self) -> Text:
return "action_post_Games_Centers"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Game Centers")
return []
class ActionPostFoodandDininglocation(Action):
def name(self) -> Text:
return "action_post_Food_and_Dining_location"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Food_and_Dining_location")
return []
class ActionPostFoodandDiningFoodProductSuppliers(Action):
def name(self) -> Text:
return "action_post_Food_and_Dining_Food_Product_Suppliers"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Food_and_Dining_Food_Product_Suppliers")
return []
class ActionPostFoodandDiningRestaurant(Action):
def name(self) -> Text:
return "action_post_Food_and_Dining_Restaurant"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Food_and_Dining_Restaurant")
return []
class ActionPostFoodandDiningSeafood(Action):
def name(self) -> Text:
return "action_post_Food_and_Dining_Seafood"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Food_and_Dining_Seafood")
return []
class ActionPostFoodandDiningSweet(Action):
def name(self) -> Text:
return "action_post_Food_and_Dining_Sweet"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Food_and_Dining_Sweet")
return []
class ActionPostGrocery(Action):
def name(self) -> Text:
return "action_post_Grocery"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="Grocery")
return []
class ActionPostClinicsAndDoctorsType(Action):
def name(self) -> Text:
return "action_post_Clinics_and_Doctors_type"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Clinics_and_Doctors_type")
return []
class ActionPostClinicsandDoctorstypeChiropractors(Action):
def name(self) -> Text:
return "action_post_Clinics_and_Doctors_type_Chiropractors"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Clinics_and_Doctors_type_Chiropractors")
return []
class ActionPostClinicsandDoctorstypeDentists(Action):
def name(self) -> Text:
return "action_post_Clinics_and_Doctors_type_Dentists"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Clinics_and_Doctors_type_Dentists")
return []
class ActionPostEmergencyServices(Action):
def name(self) -> Text:
return "action_post_Emergency_Services"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Emergency_Services")
return []
class ActionPostLegalService(Action):
def name(self) -> Text:
return "action_post_Legal_Service"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Legal_Service")
return []
class ActionPostLegalServiceAdvocates(Action):
def name(self) -> Text:
return "action_post_Legal_Service_Advocates"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Legal_Service_Advocates")
return []
class ActionPostLegalServiceImmigration(Action):
def name(self) -> Text:
return "action_post_Legal_Service_Immigration"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Legal_Service_Immigration")
return []
class ActionPostLegalServicePassport(Action):
def name(self) -> Text:
return "action_post_Legal_Service_Passport"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Legal_Service_Passport")
return []
class ActionPostFuneralsandMemorials(Action):
def name(self) -> Text:
return "action_post_Funerals_and_Memorials"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Funerals_and_Memorials")
return []
class ActionPostGardenandLawn(Action):
def name(self) -> Text:
return "action_post_Garden_and_Lawn"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Garden_and_Lawn")
return []
class ActionPostGardenandLawnGarden(Action):
def name(self) -> Text:
return "action_post_Garden_and_Lawn_Garden"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Garden_and_Lawn_Garden")
return []
class ActionPostGardenandLawnIrrigation(Action):
def name(self) -> Text:
return "action_post_Garden_and_Lawn_Irrigation"
def run(self, dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
dispatcher.utter_message(text="action_post_Garden_and_Lawn_Irrigation")
return []
class ActionRestarted(Action):
def name(self):
return "action_restart"
def run(self, dispatcher, tracker, domain):
dispatcher.utter_template("utter_reset_full", tracker)
return [Form(None), AllSlotsReset(None), Restarted(None)]
|
[
"noreply@github.com"
] |
athenasaurav.noreply@github.com
|
e97a029febec768754bf9e0c325316f93500cf73
|
8025929108bb70599cc5079b0f32d35c556dfe33
|
/font_batch_subset.py
|
4166574af64597447c4f5d871beec315011070c0
|
[] |
no_license
|
waivek/website
|
1b0a0c49c3d28f6736362251a184cf48db4063b7
|
82a5f91ef9335de2dde86af934e5305895cd160d
|
refs/heads/master
| 2023-07-11T08:10:32.109086 | 2023-07-02T06:47:19 | 2023-07-02T06:47:19 | 113,569,477 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,715 |
py
|
from columnar import columnar
import argparse
import subprocess
import os.path
import re
parser = argparse.ArgumentParser(description='Batch subsets a font to an accepted unicode range')
parser.add_argument("directory")
parser.add_argument("unicode_range")
args = parser.parse_args()
headers = [ "Input", "Output", "Input Size", "Output Size"]
data = []
# correct - fonts\Vollkorn\Vollkorn.400italic.ttf
filenames = os.listdir(args.directory)
layout_features="lnum,tnum"
directory_save = os.getcwd()
os.chdir(args.directory)
selected_filenames = [ filename for filename in filenames if re.match(r"(\w+)\.(\d)00(italic)?\.ttf", filename) ]
total_selected_filenames = len(selected_filenames)
padding_length = len(str(total_selected_filenames))
for i, filename in enumerate(selected_filenames, start=1):
status_message = "[%s/%s] %s" % (str(i).rjust(padding_length), total_selected_filenames)
print(status_message)
m = re.match(r"(\w+)\.(\d)00(italic)?\.ttf", filename)
font_name_with_underscores, font_weight, font_style = m.groups()
font_style = font_style if font_style else "normal"
input_filename_root, extension = os.path.splitext(filename)
output_filename = input_filename_root + "-subset"
ttf_subset_command = 'pyftsubset {input_filename} --unicodes={unicode_range} --output-file={output_filename}.ttf --layout-features={layout_features}'.format(
input_filename=filename, unicode_range=args.unicode_range, output_filename=output_filename, layout_features=layout_features)
woff_subset_command = 'pyftsubset {input_filename} --unicodes={unicode_range} --output-file={output_filename}.woff --layout-features={layout_features} --flavor=woff'.format(
input_filename=filename, unicode_range=args.unicode_range, output_filename=output_filename, layout_features=layout_features)
woff2_subset_command = 'pyftsubset {input_filename} --unicodes={unicode_range} --output-file={output_filename}.woff2 --layout-features={layout_features} --flavor=woff2'.format(
input_filename=filename, unicode_range=args.unicode_range, output_filename=output_filename, layout_features=layout_features)
subprocess.run(ttf_subset_command)
input_byte_size = os.path.getsize(filename)
input_kilobyte_size_string = str(round(input_byte_size / 1024, 2)) + " KB"
# Subsetting fonts/Vollkorn/Vollkorn.400.ttf to Vollkorn.400-subset.ttf (was 313.88 KB, now 5.72 KB)
# Subsetting fonts/Vollkorn/Vollkorn.400.ttf to Vollkorn.400-subset.zopfli.woff (was 313.88 KB, now 3.44 KB)
# Subsetting fonts/Vollkorn/Vollkorn.400.ttf to Vollkorn.400-subset.woff2 (was 313.88 KB, now 2.8 KB)
output_ttf_byte_size = os.path.getsize("%s.ttf" % output_filename)
output_ttf_kilboyte_size_string = str(round(output_ttf_byte_size / 1024, 2)) + " KB"
data.append([ filename, "%s.ttf" % output_filename, input_kilobyte_size_string, output_ttf_kilboyte_size_string ])
subprocess.run(woff_subset_command)
output_woff_byte_size = os.path.getsize("%s.woff" % output_filename)
output_woff_kilboyte_size_string = str(round(output_woff_byte_size / 1024, 2)) + " KB"
data.append([ filename, "%s.woff" % output_filename, input_kilobyte_size_string, output_woff_kilboyte_size_string ])
subprocess.run(woff2_subset_command)
output_woff2_byte_size = os.path.getsize("%s.woff2" % output_filename)
output_woff2_kilboyte_size_string = str(round(output_woff2_byte_size / 1024, 2)) + " KB"
data.append([ filename, "%s.woff2" % output_filename, input_kilobyte_size_string, output_woff2_kilboyte_size_string ])
os.chdir(directory_save)
print()
table = columnar(data, headers, no_borders=True, justify=["l", "l", "r", "r"] )
print(table)
|
[
"waivek@gmail.com"
] |
waivek@gmail.com
|
4968c79739666e8ad2edd13f77a4d5034eea9c2e
|
649bd422025e421d86025743eac324c9b882a2e8
|
/exam/1_three-dimensional_atomic_system/dump/phasetrans/temp45_9000.py
|
4d4f26e616aa9b6ced1b2bb6742aa541c91b1e07
|
[] |
no_license
|
scheuclu/atom_class
|
36ddee1f6a5995872e858add151c5942c109847c
|
0c9a8c63d9b38898c1869fe8983126cef17662cd
|
refs/heads/master
| 2021-01-21T10:52:28.448221 | 2017-03-07T23:04:41 | 2017-03-07T23:04:41 | 83,489,471 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 68,965 |
py
|
ITEM: TIMESTEP
9000
ITEM: NUMBER OF ATOMS
2048
ITEM: BOX BOUNDS pp pp pp
7.1778912625688207e-01 4.6482210873740115e+01
7.1778912625688207e-01 4.6482210873740115e+01
7.1778912625688207e-01 4.6482210873740115e+01
ITEM: ATOMS id type xs ys zs
8 1 0.128064 0.0616737 0.0601487
35 1 0.0656057 0.120012 0.0619676
130 1 0.0685266 0.0608412 0.125938
165 1 0.131318 0.120832 0.125956
1268 1 0.497119 0.93268 0.182308
1361 1 0.496588 0.750478 0.240454
133 1 0.126633 1.00601 0.124891
1460 1 0.500803 0.688928 0.435722
12 1 0.250297 0.0562202 0.0614448
39 1 0.192212 0.12316 0.0614049
43 1 0.310904 0.126252 0.0601463
134 1 0.189034 0.058369 0.123643
138 1 0.309645 0.0635839 0.120587
169 1 0.251645 0.126535 0.118547
137 1 0.247687 0.998671 0.125268
1505 1 -0.00176351 0.879562 0.375917
1090 1 0.0589042 0.812625 -0.00200376
16 1 0.373189 0.060716 0.0622224
47 1 0.438316 0.126239 0.0610428
142 1 0.437451 0.0601493 0.122661
173 1 0.378996 0.12285 0.11939
141 1 0.372617 1.00299 0.12081
15 1 0.439286 0.00251552 0.0601038
1124 1 0.000200366 0.942055 0.0542765
40 1 0.123702 0.18568 0.0616187
67 1 0.0646421 0.253388 0.0630245
72 1 0.12164 0.314239 0.0652134
162 1 0.0610812 0.179524 0.12545
194 1 0.0576994 0.309699 0.127795
197 1 0.123288 0.249691 0.120972
1641 1 0.243923 0.878471 0.504706
353 1 -4.25247e-05 0.36814 0.246475
42 1 0.312772 0.188421 -0.000934665
44 1 0.251675 0.196724 0.0615479
71 1 0.188218 0.252487 0.0601214
75 1 0.317639 0.248913 0.0683485
76 1 0.249202 0.315718 0.0597648
166 1 0.186483 0.190151 0.118945
170 1 0.318594 0.185733 0.127466
198 1 0.185731 0.312591 0.120281
201 1 0.248152 0.254854 0.127487
202 1 0.31761 0.313972 0.119253
340 1 0.49425 0.316618 0.314526
48 1 0.378232 0.186003 0.0651367
79 1 0.438053 0.251286 0.0629577
80 1 0.37839 0.312127 0.0577043
174 1 0.440193 0.18599 0.127182
205 1 0.380049 0.250952 0.125125
206 1 0.437785 0.319056 0.121805
1473 1 0.00366176 0.754869 0.374141
1169 1 0.501797 0.496945 0.123152
99 1 0.0652059 0.377204 0.0671047
104 1 0.130785 0.437832 0.0599418
226 1 0.0653255 0.431762 0.124595
229 1 0.130258 0.376473 0.121647
1157 1 0.125964 0.494957 0.124186
1645 1 0.372234 0.871195 0.501377
1281 1 -0.00107149 0.500479 0.250666
180 1 0.503362 0.186886 0.188477
103 1 0.186807 0.373728 0.0608981
107 1 0.317603 0.377198 0.0633315
108 1 0.252165 0.438418 0.061388
230 1 0.188993 0.439229 0.120675
233 1 0.247896 0.378781 0.126012
234 1 0.312021 0.441367 0.124453
1035 1 0.312601 0.505172 0.0603768
1236 1 0.495387 0.816815 0.186807
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642 1 0.0695546 0.0614315 0.62409
677 1 0.124684 0.123272 0.622116
1700 1 0.00101246 0.686352 0.689902
2032 1 0.382164 0.938479 0.932941
2030 1 0.438879 0.93587 0.870083
772 1 0.000769592 0.0639141 0.80914
524 1 0.249243 0.0578783 0.564704
551 1 0.186384 0.121689 0.562887
555 1 0.309132 0.119411 0.56206
646 1 0.185935 0.0632394 0.628386
650 1 0.316229 0.0577595 0.627406
681 1 0.248625 0.11828 0.624511
523 1 0.31149 0.999273 0.561799
516 1 0.00543394 0.0619777 0.558973
649 1 0.256109 0.998104 0.622261
528 1 0.370896 0.0623663 0.558815
559 1 0.439948 0.120926 0.564551
654 1 0.437496 0.060425 0.626761
685 1 0.37294 0.121981 0.62437
653 1 0.373905 0.996316 0.623087
552 1 0.128424 0.188985 0.558243
579 1 0.0658063 0.254733 0.562862
584 1 0.123058 0.315951 0.563262
674 1 0.069042 0.184711 0.617286
706 1 0.0632727 0.309538 0.627352
709 1 0.126787 0.247377 0.623286
2029 1 0.373736 0.871884 0.878657
1668 1 -0.00322596 0.556349 0.687148
556 1 0.248287 0.182616 0.565385
583 1 0.191475 0.250634 0.562061
587 1 0.312262 0.254455 0.563499
588 1 0.25086 0.319155 0.559572
678 1 0.182991 0.185403 0.626886
682 1 0.310511 0.190577 0.624665
710 1 0.183807 0.310926 0.629449
713 1 0.246675 0.252406 0.626801
714 1 0.30826 0.312735 0.626267
721 1 0.499692 0.251525 0.627053
1602 1 0.0634611 0.815875 0.501439
560 1 0.374148 0.182946 0.561241
591 1 0.438979 0.251241 0.564756
592 1 0.37642 0.314363 0.564962
686 1 0.43576 0.189289 0.628774
717 1 0.377889 0.248524 0.625526
718 1 0.438718 0.311342 0.625345
2031 1 0.437497 0.873803 0.934551
1972 1 0.5019 0.691596 0.935257
1542 1 0.190403 0.560185 0.501972
1122 1 0.0643881 0.938714 0.995185
1577 1 0.249501 0.622202 0.493308
611 1 0.0647631 0.381704 0.563061
616 1 0.124809 0.44203 0.564227
738 1 0.067576 0.435805 0.624297
741 1 0.120532 0.369286 0.626147
1539 1 0.0614148 0.496667 0.5546
785 1 0.496098 0.00729805 0.755923
615 1 0.183843 0.369891 0.562052
619 1 0.31387 0.375183 0.560677
620 1 0.246567 0.434126 0.561779
742 1 0.187952 0.435324 0.62375
745 1 0.250269 0.375017 0.62337
746 1 0.307137 0.437961 0.625603
1547 1 0.310666 0.493485 0.564088
1637 1 0.120413 0.877746 0.498637
1841 1 0.500554 0.617498 0.74947
1034 1 0.315394 0.565924 1.00062
586 1 0.313461 0.314567 0.500037
623 1 0.439689 0.3762 0.554473
624 1 0.378293 0.433515 0.562361
749 1 0.376815 0.37412 0.625711
750 1 0.441483 0.433155 0.623068
1551 1 0.440196 0.497052 0.562824
1545 1 0.247598 0.500915 0.503279
1677 1 0.377979 0.496442 0.618921
5 1 0.125092 -0.00122863 0.999796
2001 1 0.500095 0.751921 0.868954
2028 1 0.253593 0.938916 0.939473
1620 1 0.498964 0.808977 0.564461
2033 1 0.49929 0.87612 0.874744
1669 1 0.126548 0.49681 0.625604
1544 1 0.121288 0.558284 0.565014
1571 1 0.0649863 0.622401 0.559259
1666 1 0.066144 0.566567 0.626786
1701 1 0.127124 0.63037 0.621908
529 1 0.496955 0.99654 0.500628
1921 1 0.00747398 0.495076 0.87411
2022 1 0.191032 0.94071 0.881071
2023 1 0.185459 0.8737 0.931692
1543 1 0.18956 0.496925 0.564153
1673 1 0.246998 0.496656 0.625166
1548 1 0.246164 0.563319 0.567943
1575 1 0.189166 0.627398 0.555903
1579 1 0.311763 0.625529 0.56077
1670 1 0.183615 0.564274 0.625936
1674 1 0.313972 0.562675 0.62347
1705 1 0.253001 0.631474 0.623704
913 1 0.502791 -0.000818464 0.873867
1101 1 0.372137 0.745685 0.998709
2026 1 0.315568 0.938672 0.876853
1552 1 0.373497 0.56169 0.563755
1583 1 0.442366 0.622568 0.557136
1678 1 0.440243 0.558172 0.628136
1709 1 0.38304 0.619133 0.62553
69 1 0.125565 0.250724 0.999599
1956 1 -0.000383628 0.682693 0.942352
1576 1 0.121276 0.686595 0.554888
1603 1 0.0612514 0.75145 0.56451
1608 1 0.119952 0.815358 0.562637
1698 1 0.0618077 0.685391 0.621662
1730 1 0.0621077 0.813463 0.627909
1733 1 0.12351 0.746574 0.624574
2025 1 0.254117 0.872117 0.881552
1889 1 0.00289885 0.8733 0.749938
1580 1 0.246303 0.686729 0.560345
1607 1 0.182497 0.749602 0.561968
1611 1 0.312015 0.747644 0.561952
1612 1 0.249163 0.811222 0.561529
1702 1 0.18781 0.684923 0.62066
1706 1 0.315301 0.684025 0.619984
1734 1 0.191343 0.812623 0.623524
1737 1 0.250353 0.748512 0.619576
1738 1 0.313558 0.810855 0.625193
38 1 0.188321 0.181934 0.998308
1828 1 -0.000513273 0.685702 0.819317
618 1 0.306673 0.436612 0.497459
2036 1 0.495081 0.938197 0.934182
2027 1 0.314586 0.873128 0.941012
903 1 0.190126 0.00398837 0.936317
1584 1 0.376808 0.688728 0.564426
1615 1 0.435037 0.755162 0.5658
1616 1 0.371832 0.81082 0.564382
1710 1 0.439745 0.682303 0.631958
1741 1 0.376171 0.745633 0.628114
1742 1 0.432461 0.812463 0.625196
1745 1 0.496975 0.752634 0.625064
549 1 0.123384 0.12405 0.497774
515 1 0.0658499 0.00152715 0.558977
645 1 0.126165 -0.00134032 0.624454
1635 1 0.0614402 0.873821 0.56618
1640 1 0.123325 0.933014 0.564167
1762 1 0.0631879 0.936491 0.62538
1765 1 0.127916 0.879116 0.625718
899 1 0.0641856 0.00329544 0.932782
1844 1 0.496915 0.687471 0.812969
78 1 0.439879 0.31461 0.997363
519 1 0.179943 0.996041 0.56107
1639 1 0.19275 0.875621 0.56564
1643 1 0.312943 0.872063 0.565332
1644 1 0.251443 0.939321 0.563903
1766 1 0.189092 0.94488 0.63143
1769 1 0.25143 0.871309 0.628565
1770 1 0.311967 0.933079 0.622045
1609 1 0.247552 0.747915 0.497445
2021 1 0.120144 0.88256 0.874696
527 1 0.434637 1.00254 0.560988
1647 1 0.435411 0.871619 0.561278
1648 1 0.371687 0.933975 0.55749
1773 1 0.372113 0.869834 0.626625
1774 1 0.437131 0.937785 0.622254
648 1 0.128144 0.060344 0.689507
675 1 0.0658383 0.123003 0.687604
770 1 0.0649177 0.0584914 0.749177
776 1 0.129528 0.0639422 0.814545
803 1 0.0627353 0.123328 0.813568
805 1 0.124035 0.122701 0.756365
2004 1 0.500024 0.806016 0.935548
652 1 0.252486 0.0627011 0.693495
679 1 0.189165 0.124869 0.687546
683 1 0.311096 0.12053 0.685537
774 1 0.185466 0.0635735 0.751981
778 1 0.318642 0.0637514 0.747924
780 1 0.251565 0.0682328 0.804002
807 1 0.187824 0.127145 0.818492
809 1 0.256308 0.132971 0.75025
811 1 0.313425 0.128423 0.812978
651 1 0.311877 1.00376 0.689711
775 1 0.188251 1.00088 0.812737
656 1 0.374677 0.0598313 0.684786
687 1 0.43767 0.129643 0.685866
782 1 0.434758 0.0684076 0.748523
784 1 0.374975 0.0638139 0.809596
813 1 0.379181 0.129412 0.749224
815 1 0.437811 0.131277 0.813431
655 1 0.438101 0.999534 0.683654
781 1 0.378789 0.000257986 0.753879
2024 1 0.122624 0.94071 0.936278
2018 1 0.0634879 0.941297 0.874987
2019 1 0.0635621 0.876498 0.934276
680 1 0.125075 0.183995 0.68791
707 1 0.0617235 0.245558 0.68734
712 1 0.124222 0.30845 0.687831
802 1 0.058063 0.187908 0.754036
808 1 0.120604 0.185896 0.815781
834 1 0.0655173 0.310641 0.751144
835 1 0.0638357 0.250911 0.812259
837 1 0.124285 0.245025 0.751237
840 1 0.128938 0.310005 0.811305
74 1 0.314128 0.31754 0.998792
684 1 0.24331 0.185909 0.688476
711 1 0.177855 0.247423 0.691821
715 1 0.314849 0.251358 0.685957
716 1 0.248559 0.314482 0.688561
806 1 0.182076 0.18509 0.756064
810 1 0.314632 0.194219 0.751943
812 1 0.251294 0.19536 0.808977
838 1 0.193888 0.310782 0.75041
839 1 0.186394 0.250827 0.813107
841 1 0.250045 0.24792 0.746821
842 1 0.310415 0.318716 0.749517
843 1 0.310144 0.253408 0.814508
844 1 0.25293 0.312187 0.81184
688 1 0.371408 0.185408 0.686972
719 1 0.441456 0.252327 0.687947
720 1 0.377403 0.312806 0.687223
814 1 0.437544 0.191535 0.749737
816 1 0.379531 0.191721 0.809123
845 1 0.373657 0.257614 0.746037
846 1 0.437825 0.316792 0.748212
847 1 0.440331 0.250742 0.8137
848 1 0.380056 0.309283 0.812902
901 1 0.128005 1.002 0.87877
689 1 0.502466 0.127875 0.629971
739 1 0.0590572 0.372999 0.685292
744 1 0.125998 0.435789 0.686343
866 1 0.0630369 0.435272 0.744382
867 1 0.0661926 0.370599 0.816054
869 1 0.126378 0.375738 0.749024
872 1 0.125712 0.435658 0.816784
1795 1 0.0673327 0.493409 0.813619
1667 1 0.0658716 0.497613 0.686039
1797 1 0.125086 0.501089 0.752967
788 1 0.494573 0.0655753 0.815541
743 1 0.185363 0.369822 0.685931
747 1 0.311593 0.373152 0.685958
748 1 0.248053 0.438257 0.6876
870 1 0.186172 0.440431 0.752426
871 1 0.190672 0.374886 0.811558
873 1 0.246638 0.377787 0.744758
874 1 0.311009 0.433426 0.747932
875 1 0.313853 0.372448 0.812982
876 1 0.249846 0.441052 0.814486
1671 1 0.18509 0.49641 0.690037
1968 1 0.376138 0.689756 0.932822
751 1 0.435219 0.37501 0.685503
752 1 0.373261 0.433558 0.682414
877 1 0.376586 0.378119 0.750996
878 1 0.442056 0.440662 0.749711
879 1 0.434425 0.378142 0.812494
880 1 0.37375 0.436949 0.812714
1679 1 0.441082 0.497717 0.683315
1805 1 0.380133 0.49615 0.742611
1966 1 0.439915 0.683673 0.875231
1672 1 0.129863 0.556937 0.687069
1699 1 0.0679603 0.626171 0.684144
1794 1 0.0608389 0.559489 0.747781
1800 1 0.124687 0.565789 0.815442
1827 1 0.0611083 0.626375 0.814135
1829 1 0.124351 0.622965 0.75111
1803 1 0.313956 0.499045 0.805342
1675 1 0.315422 0.499847 0.679389
1801 1 0.24954 0.498486 0.745632
1799 1 0.183453 0.50165 0.814458
1676 1 0.24704 0.560233 0.682967
1703 1 0.182789 0.624701 0.683993
1707 1 0.310272 0.621649 0.680478
1798 1 0.192547 0.561008 0.747299
1802 1 0.313432 0.559943 0.736448
1804 1 0.255885 0.559547 0.804673
1831 1 0.188803 0.620465 0.812385
1833 1 0.252584 0.621464 0.744144
1835 1 0.31339 0.623473 0.808585
1807 1 0.444045 0.496419 0.812799
1680 1 0.375743 0.557727 0.687213
1711 1 0.434572 0.618982 0.692617
1806 1 0.438702 0.556047 0.752676
1808 1 0.374728 0.558782 0.811723
1837 1 0.369941 0.623853 0.749582
1839 1 0.442174 0.625764 0.813109
1098 1 0.311401 0.810499 1.00112
2000 1 0.370608 0.807447 0.937775
1998 1 0.439687 0.810809 0.873357
1997 1 0.372108 0.74922 0.873494
1704 1 0.124216 0.688792 0.689716
1731 1 0.0610832 0.74718 0.68525
1736 1 0.127672 0.816897 0.687367
1826 1 0.0660012 0.686859 0.748803
1832 1 0.120691 0.686161 0.812593
1858 1 0.06687 0.815638 0.749184
1859 1 0.060878 0.755193 0.811528
1861 1 0.123573 0.750358 0.751073
1864 1 0.125723 0.814094 0.815879
1708 1 0.249107 0.687188 0.689129
1735 1 0.18336 0.75312 0.687098
1739 1 0.308805 0.749167 0.684725
1740 1 0.25103 0.812255 0.688481
1830 1 0.183798 0.679317 0.749402
1834 1 0.311282 0.683835 0.744492
1836 1 0.246313 0.685096 0.807236
1862 1 0.185159 0.815209 0.751692
1863 1 0.184277 0.746929 0.812556
1865 1 0.256086 0.753628 0.753478
1866 1 0.315212 0.812857 0.749824
1867 1 0.316363 0.754449 0.818707
1868 1 0.24399 0.812049 0.812279
1999 1 0.438136 0.749902 0.936928
1712 1 0.376723 0.678836 0.686753
1743 1 0.437488 0.752592 0.686741
1744 1 0.377647 0.807766 0.690475
1838 1 0.443063 0.683938 0.748302
1840 1 0.378601 0.687034 0.810061
1869 1 0.374412 0.748409 0.749611
1870 1 0.43531 0.810878 0.751591
1871 1 0.436487 0.749059 0.813649
1872 1 0.374771 0.816162 0.811894
1094 1 0.184275 0.813751 1.00006
1037 1 0.377651 0.500212 1.0059
643 1 0.0627477 0.999088 0.684968
771 1 0.0622834 0.00176828 0.81241
773 1 0.128141 1.00016 0.749953
1763 1 0.064928 0.876625 0.689129
1768 1 0.128783 0.940735 0.688995
1890 1 0.0643719 0.94109 0.748633
1891 1 0.0636711 0.875622 0.81075
1893 1 0.124011 0.875721 0.751191
1896 1 0.122063 0.940665 0.812498
1924 1 -9.15941e-05 0.558299 0.938115
777 1 0.253906 1.00259 0.751776
779 1 0.315163 -4.91504e-05 0.81568
647 1 0.192497 -0.0018102 0.690699
1767 1 0.186667 0.874582 0.686758
1771 1 0.315797 0.872878 0.683573
1772 1 0.255723 0.937383 0.691268
1894 1 0.186952 0.93287 0.753131
1895 1 0.188184 0.878345 0.822254
1897 1 0.248833 0.874148 0.751524
1898 1 0.309811 0.934713 0.757969
1899 1 0.311599 0.871811 0.814511
1900 1 0.252106 0.93861 0.816369
783 1 0.439167 0.00265187 0.812783
1775 1 0.439821 0.87562 0.684281
1776 1 0.375032 0.936154 0.688809
1901 1 0.377669 0.876218 0.753351
1902 1 0.443638 0.936719 0.745094
1903 1 0.442777 0.875933 0.810228
1904 1 0.375997 0.935555 0.811775
1652 1 0.496284 0.942102 0.567092
641 1 0.00583405 -0.000729188 0.626502
898 1 0.0656409 0.0613879 0.872653
904 1 0.128965 0.0615661 0.936436
931 1 0.0646859 0.125792 0.939081
933 1 0.123158 0.1227 0.877064
66 1 0.0667541 0.318446 1.00308
1553 1 0.496333 0.497818 0.495367
905 1 0.252212 -0.000515712 0.873837
907 1 0.316797 0.00256747 0.937643
902 1 0.192867 0.0579331 0.87141
906 1 0.30993 0.0578507 0.873908
908 1 0.255848 0.0661966 0.941086
935 1 0.188536 0.126679 0.934543
937 1 0.255764 0.12635 0.869793
939 1 0.313528 0.128651 0.935081
817 1 0.49848 0.122159 0.747947
1954 1 0.0628528 0.686256 0.880316
911 1 0.44012 -0.00062172 0.936532
1992 1 0.128489 0.803033 0.940007
909 1 0.377323 -0.000555195 0.880394
910 1 0.435144 0.0662903 0.872931
912 1 0.374392 0.0644014 0.932288
941 1 0.373501 0.120075 0.868099
943 1 0.43519 0.121372 0.937937
1989 1 0.122644 0.746169 0.872713
1987 1 0.0566181 0.751223 0.936875
993 1 0.002283 0.375032 0.873466
1825 1 0.00831613 0.621926 0.74935
930 1 0.057479 0.186685 0.875131
936 1 0.124741 0.197046 0.937448
962 1 0.0625304 0.309159 0.87567
963 1 0.0634229 0.253453 0.939809
965 1 0.122379 0.252331 0.875638
968 1 0.125329 0.312801 0.938262
1962 1 0.313662 0.683625 0.869927
596 1 0.50317 0.310605 0.557573
1777 1 0.500341 0.874694 0.619993
1990 1 0.190841 0.803354 0.879944
545 1 0.000210539 0.125893 0.500407
934 1 0.182126 0.191902 0.875103
938 1 0.31078 0.191278 0.87352
940 1 0.252625 0.193488 0.93802
966 1 0.186174 0.310545 0.876022
967 1 0.186962 0.248848 0.942272
969 1 0.248885 0.253433 0.872793
970 1 0.311417 0.310923 0.876214
971 1 0.318257 0.253325 0.933843
972 1 0.249684 0.313198 0.933435
628 1 0.499814 0.43959 0.563793
1986 1 0.0679391 0.817274 0.881029
644 1 -0.00413542 0.059809 0.685675
1764 1 -0.00239757 0.935258 0.689887
564 1 0.496008 0.188126 0.560233
973 1 0.37734 0.246656 0.872191
944 1 0.379304 0.187944 0.939822
942 1 0.437963 0.189432 0.876325
976 1 0.377693 0.317216 0.939963
975 1 0.445605 0.251 0.935826
974 1 0.43981 0.315061 0.876877
1933 1 0.376676 0.493609 0.872272
1964 1 0.251253 0.684854 0.930565
995 1 0.065405 0.372423 0.933533
1000 1 0.131195 0.440757 0.937235
994 1 0.0623419 0.437682 0.876508
997 1 0.129821 0.376075 0.877737
1070 1 0.439844 0.685526 1.00024
1996 1 0.244597 0.810608 0.942471
998 1 0.188776 0.438275 0.875176
1001 1 0.247382 0.373357 0.869666
999 1 0.190468 0.374702 0.932058
1004 1 0.251272 0.438337 0.932547
1002 1 0.313205 0.432893 0.875032
1003 1 0.311337 0.377111 0.938028
1927 1 0.195429 0.499868 0.934253
1960 1 0.126727 0.691984 0.939132
1 1 0.00436475 -0.00241054 0.995194
1935 1 0.442247 0.498514 0.940102
1934 1 0.441526 0.557328 0.87553
1993 1 0.252614 0.743656 0.872804
1965 1 0.37562 0.620681 0.877935
1991 1 0.191553 0.745422 0.93741
109 1 0.380828 0.378579 0.998134
1008 1 0.38016 0.436389 0.938704
1007 1 0.441756 0.374978 0.937109
1005 1 0.374192 0.375073 0.87169
1006 1 0.439812 0.434921 0.874401
1995 1 0.311004 0.746776 0.936522
1925 1 0.1211 0.500347 0.877627
1923 1 0.0637427 0.497157 0.940242
1922 1 0.0625044 0.559499 0.876071
1928 1 0.123482 0.558739 0.940673
1955 1 0.0644578 0.617384 0.941844
1957 1 0.127067 0.627237 0.871958
1994 1 0.306606 0.811408 0.883031
1963 1 0.316981 0.62152 0.934884
1961 1 0.254675 0.622994 0.869286
1932 1 0.257294 0.56127 0.934142
1931 1 0.315863 0.493316 0.93957
1959 1 0.185295 0.627024 0.93562
1929 1 0.248636 0.498787 0.871531
1926 1 0.187637 0.563845 0.882306
1930 1 0.312421 0.554027 0.870825
1967 1 0.443323 0.624893 0.932696
1936 1 0.370298 0.558216 0.938878
1958 1 0.186658 0.683648 0.874892
1713 1 0.49757 0.616914 0.624328
1892 1 -0.00184886 0.938747 0.809186
532 1 0.500031 0.0575155 0.558523
945 1 0.500772 0.125648 0.878398
868 1 0.0040553 0.43254 0.80903
580 1 0.000708972 0.313294 0.563444
1684 1 0.501952 0.557779 0.687804
1572 1 -0.000500131 0.691335 0.562045
1860 1 0.00188093 0.816538 0.812663
1988 1 0.00372531 0.813429 0.935963
1953 1 0.00363215 0.624622 0.877699
961 1 -0.00342324 0.24952 0.878047
820 1 0.503476 0.182313 0.817508
929 1 -0.00448578 0.127354 0.876885
900 1 -0.00396885 0.0639565 0.935706
1857 1 0.0077197 0.753349 0.747233
660 1 0.493946 0.0625243 0.686755
1793 1 0.0047145 0.495927 0.746367
1646 1 0.435662 0.937587 0.497279
1062 1 0.191883 0.685639 0.998671
1133 1 0.374119 0.875547 0.996237
561 1 0.497688 0.124364 0.50119
98 1 0.0642239 0.436234 1.00015
1029 1 0.128821 0.500517 1.00361
1065 1 0.250203 0.618174 0.995509
105 1 0.249247 0.37787 0.999124
1069 1 0.379797 0.623686 0.992217
550 1 0.194661 0.186846 0.501945
1038 1 0.441785 0.563918 0.997964
1026 1 0.0671187 0.557065 1.0065
34 1 0.0665448 0.188376 1.00363
102 1 0.190836 0.439952 1.00093
70 1 0.184921 0.313895 0.996719
2 1 0.0637328 0.0622296 0.997802
1610 1 0.309213 0.812236 0.500618
610 1 0.0617435 0.438763 0.497906
1634 1 0.0625082 0.941941 0.503477
546 1 0.0644266 0.186581 0.506098
1126 1 0.186882 0.933918 0.994815
1614 1 0.441367 0.812064 0.49812
1582 1 0.4429 0.690711 0.501556
1025 1 0.00243718 0.496597 0.999772
1642 1 0.306481 0.932868 0.499309
14 1 0.437802 0.0577394 0.997652
1066 1 0.310036 0.681924 0.995108
1578 1 0.312167 0.685176 0.494693
1550 1 0.433493 0.558617 0.503146
37 1 0.127922 0.121828 0.99816
101 1 0.129734 0.375202 0.997699
1030 1 0.184218 0.563112 1.00199
577 1 -0.00212934 0.244826 0.502702
1137 1 0.496396 0.875431 0.999107
1102 1 0.440556 0.815455 0.99997
609 1 -0.00116001 0.379188 0.501298
1125 1 0.124189 0.873875 0.995099
1549 1 0.375342 0.499072 0.503484
6 1 0.19694 0.0674476 0.996059
517 1 0.125504 0.00435885 0.49665
1546 1 0.31015 0.561599 0.507038
24 1 0.626399 0.0573837 0.0620094
51 1 0.569128 0.123393 0.0632087
146 1 0.561952 0.0651107 0.127877
181 1 0.626327 0.122176 0.122112
121 1 0.747134 0.375143 -0.00464349
18 1 0.560791 0.0655138 0.00158793
19 1 0.567621 0.997209 0.0621821
28 1 0.75148 0.0641966 0.0647518
55 1 0.692542 0.120706 0.0623231
59 1 0.810665 0.126596 0.063853
150 1 0.690125 0.0594092 0.128109
154 1 0.809862 0.0581578 0.125649
185 1 0.747725 0.127995 0.131601
153 1 0.751709 0.998759 0.133326
23 1 0.687474 1.00078 0.0638551
260 1 1.00127 0.0647922 0.314466
36 1 1.00096 0.182041 0.0592992
32 1 0.872741 0.0637825 0.0606589
63 1 0.935846 0.124073 0.0650631
158 1 0.935715 0.0623437 0.124332
189 1 0.870769 0.123871 0.126185
157 1 0.874158 -0.00109471 0.119846
1492 1 0.504118 0.812252 0.436539
31 1 0.941162 0.998157 0.0582881
56 1 0.625941 0.190568 0.0675596
83 1 0.560225 0.249685 0.0709225
88 1 0.626287 0.316939 0.0644042
178 1 0.566142 0.189259 0.133365
210 1 0.564529 0.314105 0.127352
213 1 0.626413 0.253021 0.132879
1536 1 0.872164 0.939144 0.441238
449 1 0.998967 0.2439 0.371248
20 1 0.500967 0.0603355 0.0611252
1535 1 0.938574 0.873295 0.43828
60 1 0.75152 0.191677 0.067389
87 1 0.686276 0.252742 0.0679084
91 1 0.811584 0.252902 0.0645685
92 1 0.747356 0.308827 0.0662207
182 1 0.68967 0.192822 0.129438
186 1 0.808864 0.187231 0.123336
214 1 0.686486 0.319176 0.132663
217 1 0.749654 0.250111 0.132529
218 1 0.812716 0.313058 0.129589
116 1 0.498315 0.437946 0.0670291
289 1 1.0012 0.122863 0.252484
1049 1 0.750592 0.494831 -0.000278839
64 1 0.871194 0.182681 0.068798
95 1 0.936523 0.242788 0.0708239
96 1 0.87915 0.315597 0.0640727
190 1 0.940601 0.179758 0.129022
221 1 0.874443 0.247053 0.127375
222 1 0.938344 0.314722 0.124155
126 1 0.940549 0.440688 -0.00584294
337 1 0.499266 0.259721 0.255032
53 1 0.626557 0.123389 0.00283229
115 1 0.564066 0.38222 0.061024
120 1 0.627999 0.44224 0.0637311
242 1 0.56656 0.438885 0.128978
245 1 0.625999 0.374625 0.128706
1173 1 0.62977 0.502677 0.125671
119 1 0.687136 0.379375 0.063297
123 1 0.811731 0.370608 0.0596388
124 1 0.751973 0.439314 0.0664706
246 1 0.691414 0.435713 0.126975
249 1 0.753198 0.371848 0.125352
250 1 0.812756 0.431806 0.125983
1047 1 0.689587 0.500318 0.0689718
1561 1 0.750699 0.499362 0.5044
127 1 0.936279 0.376923 0.0558252
128 1 0.872876 0.436011 0.060464
253 1 0.873533 0.374079 0.127734
254 1 0.935464 0.435373 0.12306
1534 1 0.938435 0.947133 0.378054
1043 1 0.560857 0.502843 0.0616467
1048 1 0.624805 0.561807 0.0650246
1075 1 0.56369 0.620688 0.0650105
1170 1 0.561483 0.561674 0.128812
1205 1 0.632945 0.627039 0.122394
89 1 0.752108 0.248007 0.00119117
1051 1 0.815899 0.499205 0.0699382
1177 1 0.753016 0.49875 0.12346
1052 1 0.746027 0.562174 0.0632045
1079 1 0.687681 0.626921 0.0642752
1083 1 0.812019 0.625144 0.0619209
1174 1 0.688241 0.564369 0.124893
1178 1 0.812419 0.561752 0.128513
1209 1 0.7495 0.626379 0.12455
1105 1 0.500748 0.748029 -0.000474966
598 1 0.688593 0.311383 0.502429
30 1 0.941167 0.0630112 -6.47857e-05
1181 1 0.882246 0.499666 0.123565
1055 1 0.939488 0.494432 0.0609133
1056 1 0.876927 0.558049 0.0627759
1087 1 0.941936 0.626067 0.0633304
1182 1 0.938323 0.554363 0.127973
1213 1 0.876933 0.621234 0.123099
1533 1 0.875767 0.878181 0.376209
1053 1 0.87603 0.503417 0.00284468
1149 1 0.876159 0.876313 0.00210626
22 1 0.685798 0.0655557 -0.000597379
1364 1 0.498441 0.812949 0.309874
1080 1 0.627009 0.687896 0.0668721
1107 1 0.564198 0.749335 0.0661631
1112 1 0.624278 0.813019 0.0635718
1202 1 0.562684 0.691889 0.128063
1234 1 0.562453 0.820092 0.129344
1237 1 0.62981 0.753055 0.126427
465 1 0.503834 0.250517 0.377166
84 1 0.499112 0.312148 0.0631002
1537 1 0.995842 0.49859 0.493157
1084 1 0.751238 0.684951 0.057661
1111 1 0.686711 0.75061 0.0671969
1115 1 0.815331 0.749606 0.0657126
1116 1 0.753793 0.805134 0.0645913
1206 1 0.68759 0.688848 0.12561
1210 1 0.809828 0.685595 0.121423
1238 1 0.691506 0.815457 0.122813
1241 1 0.750402 0.746865 0.126272
1242 1 0.816504 0.809113 0.130981
212 1 0.504838 0.31512 0.183909
637 1 0.878332 0.376708 0.498344
90 1 0.814058 0.310888 0.00203436
1088 1 0.875141 0.685287 0.0659761
1119 1 0.942222 0.751437 0.0601177
1120 1 0.875243 0.815143 0.0679469
1214 1 0.936526 0.689404 0.124881
1245 1 0.876961 0.75139 0.124961
1246 1 0.937681 0.812435 0.125173
407 1 0.690365 0.00416773 0.43904
149 1 0.627509 0.999859 0.125985
1139 1 0.555724 0.876777 0.0587742
1144 1 0.626344 0.934276 0.0630045
1266 1 0.565858 0.934227 0.123201
1269 1 0.625854 0.873164 0.127484
420 1 0.997661 0.189904 0.438993
177 1 0.499892 0.124136 0.121665
50 1 0.558885 0.188503 -0.00183613
1532 1 0.749237 0.942934 0.438125
468 1 0.503894 0.316023 0.435197
1412 1 0.995999 0.562911 0.435046
27 1 0.805684 0.0020473 0.0579308
1143 1 0.6862 0.873127 0.0624444
1147 1 0.811813 0.87246 0.0636943
1148 1 0.748896 0.936742 0.0598553
1270 1 0.689207 0.937451 0.124815
1273 1 0.75261 0.876919 0.124818
1274 1 0.816338 0.93598 0.124011
62 1 0.929887 0.184326 0.00225384
436 1 0.498285 0.190925 0.440001
1089 1 1.0043 0.750887 0.00110582
225 1 0.998286 0.373808 0.124073
1151 1 0.939448 0.877288 0.0647018
1152 1 0.874055 0.938479 0.0574861
1277 1 0.877001 0.876588 0.130924
1278 1 0.939212 0.937828 0.123423
1531 1 0.811773 0.872399 0.442003
1530 1 0.815692 0.935998 0.370798
152 1 0.626527 0.0646744 0.185552
179 1 0.562604 0.127133 0.184483
274 1 0.55994 0.0607368 0.24737
280 1 0.624229 0.0641817 0.315419
307 1 0.558075 0.124656 0.31255
309 1 0.619585 0.125554 0.248222
277 1 0.623903 0.00155706 0.251003
147 1 0.566657 -0.00708448 0.18413
156 1 0.747393 0.0650819 0.187682
183 1 0.681318 0.125598 0.189112
187 1 0.812724 0.12481 0.187469
278 1 0.681987 0.0578485 0.25069
282 1 0.810175 0.0570482 0.244455
284 1 0.743005 0.064281 0.313457
311 1 0.683918 0.121742 0.31048
313 1 0.746081 0.125577 0.25012
315 1 0.813855 0.124746 0.312645
281 1 0.743419 -0.00163245 0.249864
283 1 0.811966 0.00988793 0.31442
151 1 0.686569 0.994615 0.187699
1529 1 0.752064 0.885585 0.378473
160 1 0.873094 0.0583237 0.183269
191 1 0.940276 0.120001 0.188919
286 1 0.935403 0.0609867 0.250638
288 1 0.871732 0.0636187 0.314754
317 1 0.878297 0.117543 0.247656
319 1 0.94055 0.124761 0.312327
285 1 0.875682 1.00398 0.250372
159 1 0.936573 0.998677 0.188263
1527 1 0.687548 0.8803 0.439749
184 1 0.623357 0.19094 0.190932
211 1 0.557477 0.254581 0.191985
216 1 0.62441 0.313523 0.192085
306 1 0.562656 0.192125 0.250491
312 1 0.617915 0.189762 0.310203
338 1 0.567204 0.313978 0.25679
339 1 0.562825 0.252283 0.31273
341 1 0.626044 0.251465 0.25013
344 1 0.634351 0.313854 0.310816
1526 1 0.683496 0.943375 0.37458
209 1 0.495059 0.245963 0.124139
188 1 0.749056 0.188543 0.18898
215 1 0.68662 0.250302 0.193292
219 1 0.813533 0.249404 0.187642
220 1 0.754578 0.314291 0.189746
310 1 0.687238 0.185585 0.255127
314 1 0.811393 0.186446 0.249862
316 1 0.750716 0.191159 0.313574
342 1 0.695194 0.3167 0.247933
343 1 0.687677 0.249811 0.314641
345 1 0.749955 0.24828 0.247321
346 1 0.816086 0.314364 0.24951
347 1 0.813691 0.252189 0.309905
348 1 0.750108 0.312268 0.310734
1566 1 0.937206 0.5645 0.497417
192 1 0.872576 0.184583 0.185538
223 1 0.930222 0.247659 0.184436
224 1 0.873957 0.315106 0.18587
318 1 0.93404 0.184579 0.246518
320 1 0.872808 0.18723 0.312327
349 1 0.871422 0.245333 0.246785
350 1 0.932937 0.307128 0.249369
351 1 0.932197 0.249593 0.310561
352 1 0.873114 0.312677 0.313165
500 1 0.49818 0.438073 0.433481
405 1 0.618308 1.00107 0.376128
403 1 0.56116 1.00065 0.436654
243 1 0.565488 0.370796 0.194017
248 1 0.623906 0.435321 0.194627
370 1 0.561381 0.442843 0.250657
371 1 0.562229 0.376432 0.314919
373 1 0.630369 0.376981 0.253648
376 1 0.627152 0.440744 0.312374
1299 1 0.56074 0.503584 0.309368
1301 1 0.627739 0.500863 0.249164
1525 1 0.626846 0.875706 0.374005
247 1 0.687605 0.378971 0.188348
251 1 0.816702 0.374796 0.191324
252 1 0.751907 0.438688 0.190764
374 1 0.687907 0.441711 0.247966
375 1 0.691284 0.377807 0.31381
377 1 0.756052 0.373455 0.250226
378 1 0.812192 0.435866 0.254067
379 1 0.811052 0.379165 0.311514
380 1 0.746239 0.439716 0.309231
1303 1 0.687375 0.502855 0.310039
255 1 0.938987 0.372358 0.186859
256 1 0.874585 0.434938 0.190311
381 1 0.876132 0.373183 0.24982
382 1 0.939547 0.435715 0.249803
383 1 0.940315 0.374917 0.309483
384 1 0.877112 0.432247 0.313713
1528 1 0.626326 0.941703 0.437469
1171 1 0.560198 0.503369 0.190573
1176 1 0.629624 0.569354 0.183701
1203 1 0.564167 0.625842 0.187202
1298 1 0.565303 0.566679 0.248547
1304 1 0.625224 0.560892 0.312594
1331 1 0.563836 0.624798 0.308937
1333 1 0.6295 0.621272 0.251887
1307 1 0.813554 0.494678 0.315562
1175 1 0.690326 0.500886 0.184464
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1305 1 0.754885 0.503189 0.250601
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1207 1 0.690935 0.625492 0.187462
1211 1 0.80858 0.627457 0.186713
1302 1 0.689262 0.556031 0.247502
1306 1 0.809424 0.563652 0.252903
1308 1 0.746103 0.561675 0.307773
1335 1 0.687871 0.6278 0.316868
1337 1 0.748447 0.624246 0.250279
1339 1 0.811867 0.624245 0.313207
1183 1 0.942947 0.497219 0.190815
1311 1 0.935515 0.499938 0.313956
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1312 1 0.874764 0.565642 0.31578
1341 1 0.866591 0.620323 0.248564
1343 1 0.932963 0.626077 0.316859
1522 1 0.5613 0.933637 0.37552
1523 1 0.56598 0.878902 0.439201
530 1 0.558157 0.0635147 0.497017
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1363 1 0.568586 0.752848 0.316687
1365 1 0.627499 0.748197 0.249301
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25 1 0.743762 0.00530171 -0.00434486
1332 1 0.504929 0.694435 0.307064
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1340 1 0.753326 0.692242 0.314621
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279 1 0.685421 0.99602 0.313104
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1041 1 0.501524 0.497927 -0.00452964
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445 1 0.872332 0.127983 0.373344
447 1 0.933267 0.131241 0.439119
601 1 0.751013 0.250811 0.50185
1653 1 0.623233 0.879187 0.504394
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434 1 0.564443 0.189482 0.376455
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1436 1 0.751012 0.564175 0.435274
1434 1 0.810591 0.562142 0.374977
1430 1 0.688389 0.55918 0.375962
1467 1 0.806719 0.626823 0.441497
1465 1 0.749899 0.627537 0.374793
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1233 1 0.503187 0.755399 0.126017
1437 1 0.875349 0.50203 0.374693
1438 1 0.934309 0.560364 0.37365
1440 1 0.871699 0.560766 0.436652
1469 1 0.870525 0.620823 0.378926
1471 1 0.938264 0.627157 0.434858
1524 1 0.496185 0.940243 0.439518
1633 1 1.00172 0.878616 0.504525
61 1 0.871642 0.119607 0.0011204
308 1 0.499633 0.188804 0.313705
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117 1 0.62515 0.376624 -0.000608342
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638 1 0.939468 0.435891 0.492934
1593 1 0.747953 0.625482 0.502839
602 1 0.812945 0.310314 0.496508
1521 1 0.49993 0.87722 0.369943
1618 1 0.562803 0.817464 0.500522
630 1 0.687523 0.438248 0.500669
1113 1 0.753883 0.744308 -0.00149954
1185 1 0.994837 0.621112 0.129289
52 1 0.504674 0.185094 0.0658266
1081 1 0.745937 0.623211 -0.00339365
1045 1 0.620626 0.501386 0.00174516
1489 1 0.501104 0.750688 0.369697
1076 1 0.504736 0.684138 0.0665576
1444 1 0.996142 0.690878 0.436632
193 1 1.00331 0.238795 0.130464
305 1 0.499736 0.12483 0.249097
1284 1 0.998863 0.561875 0.317813
68 1 0.997609 0.315429 0.0636683
1201 1 0.502786 0.622181 0.123368
1217 1 0.999789 0.756978 0.133099
356 1 0.999547 0.439591 0.311844
634 1 0.81745 0.438837 0.498112
565 1 0.616012 0.126036 0.500062
1313 1 0.994137 0.625911 0.250877
1562 1 0.807679 0.559778 0.501099
1300 1 0.498344 0.566131 0.308456
1220 1 1.00136 0.82078 0.189322
1204 1 0.501695 0.686336 0.181146
1409 1 0.999563 0.501652 0.380515
321 1 0.993202 0.245019 0.249001
324 1 0.992403 0.309718 0.313357
273 1 0.500007 0.00198396 0.243554
369 1 0.498232 0.377285 0.25234
417 1 1.00032 0.129007 0.379843
1188 1 0.992419 0.691663 0.186962
241 1 0.502051 0.37949 0.127642
542 1 0.937185 0.0660915 0.500223
65 1 0.995246 0.243345 0.00801298
1597 1 0.876699 0.629893 0.495671
1558 1 0.690422 0.559202 0.499397
570 1 0.809431 0.191819 0.504315
114 1 0.566464 0.439002 0.000394092
541 1 0.871073 0.00384553 0.500574
86 1 0.68729 0.312034 0.00363204
122 1 0.812474 0.438638 -0.000130935
629 1 0.629611 0.378429 0.497702
626 1 0.559494 0.441416 0.494976
1086 1 0.935866 0.683333 0.00237814
1054 1 0.941694 0.558137 0.00338406
29 1 0.870304 0.00348507 0.000223778
93 1 0.875994 0.249718 0.0049311
534 1 0.681723 0.0633942 0.498693
57 1 0.751511 0.127965 0.00476684
593 1 0.505982 0.253682 0.497061
1077 1 0.625851 0.621929 -0.00332039
1662 1 0.935855 0.937067 0.499988
1085 1 0.873431 0.621288 0.00138137
54 1 0.68633 0.183964 0.00610228
1046 1 0.685568 0.559875 0.00519794
85 1 0.624662 0.248726 0.00791486
82 1 0.565603 0.31359 0.00707315
1050 1 0.80921 0.560008 0.00321695
94 1 0.940609 0.308038 0.00391409
536 1 0.625322 0.062472 0.558766
563 1 0.556949 0.125799 0.563134
658 1 0.556974 0.0651907 0.625805
693 1 0.623279 0.121473 0.626061
1716 1 0.502676 0.68355 0.687987
964 1 0.997863 0.313622 0.937494
612 1 0.99744 0.437776 0.563421
605 1 0.871862 0.248038 0.499288
540 1 0.749348 0.0676328 0.56802
567 1 0.682601 0.124021 0.560771
571 1 0.811639 0.130597 0.558475
662 1 0.686986 0.0596153 0.625566
666 1 0.812254 0.0704029 0.624109
697 1 0.745141 0.128796 0.626354
539 1 0.813371 0.00516001 0.565823
535 1 0.684509 0.00879617 0.558864
665 1 0.747587 -0.000768396 0.622979
573 1 0.869875 0.130677 0.5004
544 1 0.870994 0.0698446 0.559107
575 1 0.934832 0.12301 0.563343
670 1 0.941061 0.058981 0.620028
701 1 0.877958 0.129353 0.622136
865 1 0.998904 0.37032 0.746496
2017 1 1.00193 0.872715 0.870714
568 1 0.62191 0.186143 0.559143
595 1 0.559993 0.246587 0.558802
600 1 0.624292 0.315724 0.560503
690 1 0.561991 0.190172 0.618902
722 1 0.5643 0.312528 0.619067
725 1 0.624324 0.252563 0.621387
1630 1 0.934644 0.814651 0.501791
708 1 0.995448 0.310251 0.685878
916 1 0.501195 0.0620524 0.937784
1556 1 0.50485 0.560217 0.554625
572 1 0.745244 0.185298 0.560453
599 1 0.687589 0.251222 0.560771
603 1 0.808188 0.249005 0.562985
604 1 0.75041 0.320739 0.56141
694 1 0.68279 0.183606 0.621421
698 1 0.810656 0.189816 0.624987
726 1 0.692483 0.310118 0.623854
729 1 0.747327 0.247687 0.621291
730 1 0.811239 0.31678 0.620938
594 1 0.564511 0.319748 0.494181
1009 1 0.500801 0.372506 0.874704
576 1 0.87617 0.189442 0.564486
607 1 0.938401 0.255454 0.562257
608 1 0.87255 0.311964 0.563538
702 1 0.934881 0.194001 0.622701
733 1 0.872414 0.250092 0.626786
734 1 0.940491 0.311363 0.623376
657 1 0.501465 -8.35426e-06 0.62827
1626 1 0.810919 0.810424 0.504714
1748 1 0.498836 0.808089 0.684966
627 1 0.560569 0.377551 0.557422
632 1 0.621339 0.43656 0.559066
754 1 0.566227 0.435943 0.623454
757 1 0.62872 0.375508 0.624749
1685 1 0.627772 0.499044 0.618845
948 1 0.502606 0.188208 0.941444
631 1 0.68434 0.379782 0.564112
635 1 0.815663 0.377107 0.556827
636 1 0.753588 0.439804 0.562911
758 1 0.689017 0.444568 0.617908
761 1 0.747615 0.380071 0.623627
762 1 0.816019 0.436476 0.619469
1563 1 0.813404 0.50218 0.558655
1940 1 0.500806 0.558225 0.938726
639 1 0.932937 0.374114 0.565059
640 1 0.878583 0.433338 0.56324
765 1 0.875328 0.375627 0.626322
766 1 0.938332 0.435913 0.625389
1969 1 0.499989 0.626589 0.873156
1812 1 0.501469 0.563651 0.811574
996 1 0.997996 0.43519 0.93533
1555 1 0.564437 0.50315 0.56559
1560 1 0.627349 0.564549 0.564105
1587 1 0.563104 0.628817 0.559946
1682 1 0.564776 0.566266 0.62483
1717 1 0.626337 0.624624 0.624624
2048 1 0.871762 0.938841 0.939904
1078 1 0.683879 0.690427 1.00457
2047 1 0.944842 0.880436 0.933027
1697 1 1.00031 0.623375 0.626068
1559 1 0.689595 0.505491 0.56136
1689 1 0.748269 0.500969 0.622262
1564 1 0.746978 0.563856 0.565633
1591 1 0.686047 0.624792 0.563861
1595 1 0.814867 0.62293 0.557879
1686 1 0.688904 0.566735 0.628971
1690 1 0.817024 0.559547 0.624429
1721 1 0.756174 0.624915 0.628337
1109 1 0.622291 0.751406 1.00274
897 1 0.999246 -0.000199348 0.87137
1636 1 0.99962 0.945255 0.564407
1567 1 0.938298 0.497593 0.555053
1693 1 0.87871 0.499384 0.620143
1568 1 0.878825 0.565272 0.557921
1599 1 0.93702 0.624369 0.558547
1694 1 0.938108 0.560984 0.623898
1725 1 0.878455 0.620249 0.622291
538 1 0.806525 0.0659754 0.498967
801 1 1.00328 0.118854 0.747926
2046 1 0.938885 0.936418 0.872195
1592 1 0.627181 0.687899 0.564434
1619 1 0.56711 0.748129 0.563199
1624 1 0.620577 0.812764 0.564626
1714 1 0.558512 0.686243 0.622796
1746 1 0.558114 0.817806 0.624538
1749 1 0.622949 0.752937 0.623957
1985 1 0.995786 0.750227 0.871195
932 1 0.999549 0.187425 0.938107
1596 1 0.752931 0.68556 0.565132
1623 1 0.692979 0.744269 0.568313
1627 1 0.811505 0.752953 0.569103
1628 1 0.750011 0.811748 0.562083
1718 1 0.685374 0.683351 0.631438
1722 1 0.811315 0.684821 0.62996
1750 1 0.684378 0.812834 0.624209
1753 1 0.748827 0.748821 0.631811
1754 1 0.811281 0.813537 0.620341
769 1 0.999109 1.00139 0.749438
2045 1 0.875785 0.876496 0.875492
1600 1 0.876891 0.685602 0.567467
1631 1 0.940018 0.754874 0.564231
1632 1 0.879106 0.814098 0.56508
1726 1 0.940999 0.687491 0.623961
1757 1 0.883496 0.749336 0.626381
1758 1 0.939541 0.812969 0.629241
692 1 0.500266 0.186378 0.688749
1629 1 0.874021 0.750915 0.506283
661 1 0.622158 0.00449964 0.619363
531 1 0.560233 1.00567 0.56513
1651 1 0.559258 0.879336 0.562622
1656 1 0.62419 0.942147 0.560284
1778 1 0.565557 0.938511 0.624277
1781 1 0.623855 0.874624 0.626736
1665 1 1.00748 0.498998 0.620336
1655 1 0.684187 0.875369 0.564893
1659 1 0.814426 0.871892 0.56137
1660 1 0.742218 0.940053 0.565675
1782 1 0.685652 0.941839 0.623132
1785 1 0.747062 0.869051 0.623618
1786 1 0.80971 0.930268 0.624084
1876 1 0.496342 0.816999 0.810411
543 1 0.932523 1.00281 0.557369
1908 1 0.499746 0.941596 0.811795
705 1 1.00212 0.251947 0.622211
669 1 0.871775 0.00361138 0.623722
1663 1 0.939148 0.874875 0.561579
1664 1 0.875997 0.93799 0.568577
1789 1 0.872542 0.874506 0.626179
1790 1 0.939192 0.932791 0.630551
1681 1 0.503629 0.497027 0.62483
1780 1 0.498765 0.934745 0.679071
804 1 0.997422 0.184158 0.813409
664 1 0.627271 0.0601409 0.685426
691 1 0.565941 0.128575 0.690841
786 1 0.559622 0.0658013 0.748491
792 1 0.627584 0.064903 0.813809
819 1 0.560589 0.125 0.808166
821 1 0.620769 0.130373 0.75405
1589 1 0.623839 0.626579 0.501788
1121 1 0.998939 0.875463 0.999492
533 1 0.618971 0.00292298 0.497034
668 1 0.742139 0.0584481 0.687584
695 1 0.682224 0.12257 0.694772
699 1 0.81052 0.121399 0.693913
790 1 0.689454 0.0626318 0.752552
794 1 0.811836 0.0634171 0.755254
796 1 0.747585 0.0624971 0.819465
823 1 0.688556 0.127147 0.816757
825 1 0.749392 0.122334 0.752643
827 1 0.811429 0.127344 0.813882
667 1 0.812364 1.00063 0.685275
795 1 0.816004 0.999431 0.818825
663 1 0.682667 0.99898 0.689761
2044 1 0.746812 0.941721 0.937823
672 1 0.871814 0.0624039 0.689467
703 1 0.936911 0.12361 0.68494
798 1 0.934803 0.0630345 0.752354
800 1 0.874098 0.0629309 0.807341
829 1 0.874331 0.127244 0.749442
831 1 0.934905 0.123984 0.809759
797 1 0.87674 -0.00247329 0.744326
799 1 0.936047 1.00162 0.813415
671 1 0.939969 0.999533 0.681244
2043 1 0.806757 0.876815 0.940463
562 1 0.56055 0.190649 0.499631
1905 1 0.503122 0.872178 0.74862
696 1 0.61906 0.189812 0.686182
723 1 0.563554 0.251978 0.683638
728 1 0.623487 0.311416 0.687015
818 1 0.565543 0.190244 0.753721
824 1 0.624495 0.186816 0.81336
850 1 0.563858 0.31271 0.748633
851 1 0.562415 0.251142 0.814918
853 1 0.624037 0.250433 0.747587
856 1 0.627397 0.314262 0.8071
1106 1 0.557646 0.816034 1.00007
537 1 0.747764 0.00397396 0.507671
881 1 0.501367 0.378589 0.752078
700 1 0.748854 0.181919 0.691497
727 1 0.688633 0.249179 0.684047
731 1 0.812315 0.245172 0.68564
732 1 0.750013 0.311632 0.688534
822 1 0.682909 0.18638 0.750714
826 1 0.812937 0.187746 0.74981
828 1 0.747349 0.189095 0.814274
854 1 0.684612 0.310711 0.747626
855 1 0.682596 0.254286 0.812538
857 1 0.743739 0.248992 0.752974
858 1 0.812493 0.312174 0.754229
859 1 0.813311 0.247397 0.815295
860 1 0.751907 0.30934 0.818567
2042 1 0.809775 0.931431 0.878068
704 1 0.875345 0.183001 0.685343
735 1 0.935888 0.249331 0.689062
736 1 0.874943 0.312578 0.686174
830 1 0.938798 0.184145 0.748192
832 1 0.877421 0.189836 0.810633
861 1 0.873203 0.251209 0.751017
862 1 0.933223 0.311169 0.753581
863 1 0.937261 0.246006 0.818539
864 1 0.875986 0.311697 0.817803
2041 1 0.753224 0.87313 0.880036
755 1 0.568413 0.377973 0.682617
760 1 0.630767 0.439139 0.679265
882 1 0.570177 0.437219 0.744051
883 1 0.570915 0.375776 0.808601
885 1 0.63012 0.375877 0.742863
888 1 0.633499 0.435155 0.809437
1683 1 0.558615 0.499968 0.687144
1813 1 0.621802 0.498097 0.74813
2039 1 0.693006 0.877149 0.937045
759 1 0.693425 0.370259 0.690498
763 1 0.812873 0.371135 0.683095
764 1 0.756854 0.437174 0.688998
886 1 0.692636 0.438108 0.749422
887 1 0.689366 0.368 0.809596
889 1 0.757108 0.376778 0.75229
890 1 0.816451 0.438146 0.758123
891 1 0.816428 0.374932 0.814084
892 1 0.749291 0.438011 0.815293
1691 1 0.817056 0.500862 0.685414
1687 1 0.693493 0.496023 0.684844
1815 1 0.688592 0.501278 0.806312
1601 1 0.998189 0.754268 0.502528
767 1 0.933847 0.369134 0.68879
768 1 0.871057 0.436601 0.688753
893 1 0.870529 0.378615 0.753002
894 1 0.943409 0.436824 0.743745
895 1 0.937449 0.373579 0.80945
896 1 0.874899 0.441281 0.81802
1823 1 0.942449 0.494705 0.81412
1695 1 0.938484 0.498794 0.68575
2038 1 0.691888 0.937276 0.873613
1811 1 0.559121 0.50428 0.817591
1688 1 0.62612 0.560816 0.694434
1715 1 0.564187 0.622806 0.687051
1810 1 0.562691 0.560746 0.7513
1816 1 0.627087 0.560966 0.810439
1843 1 0.559977 0.621766 0.814617
1845 1 0.623712 0.623612 0.751228
1729 1 1.00013 0.747548 0.630251
1819 1 0.81315 0.49982 0.818719
1817 1 0.758853 0.494661 0.754225
1692 1 0.752753 0.559629 0.688283
1719 1 0.687413 0.622474 0.688208
1723 1 0.813085 0.621628 0.688465
1814 1 0.692384 0.557774 0.747116
1818 1 0.812081 0.559051 0.752692
1820 1 0.753566 0.56161 0.815999
1847 1 0.685996 0.624265 0.814222
1849 1 0.751825 0.622149 0.751699
1851 1 0.806525 0.629769 0.814625
980 1 0.505173 0.309955 0.938578
1821 1 0.877986 0.496722 0.755167
1696 1 0.878416 0.561154 0.691421
1727 1 0.943979 0.623766 0.690566
1822 1 0.938179 0.557336 0.749561
1824 1 0.875555 0.557864 0.813673
1853 1 0.878844 0.620584 0.753113
1855 1 0.940516 0.621467 0.812577
1970 1 0.562234 0.683599 0.874746
2003 1 0.565206 0.751521 0.931953
919 1 0.684777 -0.000733749 0.937477
915 1 0.56012 0.00314353 0.938457
1720 1 0.620777 0.687804 0.685316
1747 1 0.560711 0.750954 0.685767
1752 1 0.623764 0.80684 0.686901
1842 1 0.564344 0.684536 0.75137
1848 1 0.620227 0.695391 0.818099
1874 1 0.562116 0.809047 0.747475
1875 1 0.557328 0.751046 0.808235
1877 1 0.626192 0.749637 0.750225
1880 1 0.621461 0.814826 0.807445
1657 1 0.748273 0.877904 0.506938
1724 1 0.74805 0.683513 0.69098
1751 1 0.687248 0.747585 0.685905
1755 1 0.809384 0.748575 0.687537
1756 1 0.750784 0.810564 0.684731
1846 1 0.680453 0.684082 0.747696
1850 1 0.810418 0.68499 0.752482
1852 1 0.74561 0.689966 0.80796
1878 1 0.689452 0.808681 0.751353
1879 1 0.686631 0.754991 0.816165
1881 1 0.748396 0.747956 0.751364
1882 1 0.811778 0.807653 0.749222
1883 1 0.807825 0.74864 0.815081
1884 1 0.750378 0.810323 0.814202
1873 1 0.497291 0.750275 0.748411
1728 1 0.876274 0.684836 0.688409
1759 1 0.940906 0.749516 0.687253
1760 1 0.872447 0.815215 0.685213
1854 1 0.939587 0.689197 0.7534
1856 1 0.873771 0.683549 0.818779
1885 1 0.875026 0.748425 0.744299
1886 1 0.93935 0.808856 0.749772
1887 1 0.940536 0.750408 0.805916
1888 1 0.875129 0.805023 0.810404
2035 1 0.556951 0.875988 0.935812
2005 1 0.625805 0.757625 0.872902
2034 1 0.559633 0.939547 0.881616
849 1 0.505127 0.250352 0.750096
787 1 0.558821 0.00642062 0.813555
789 1 0.622831 1.00284 0.751289
659 1 0.562421 0.00203701 0.68384
1779 1 0.561884 0.873383 0.688255
1784 1 0.622887 0.941366 0.686612
1906 1 0.55966 0.940337 0.744563
1907 1 0.565816 0.875564 0.817619
1909 1 0.622652 0.876514 0.748345
1912 1 0.617159 0.944797 0.813923
597 1 0.62102 0.252387 0.500119
791 1 0.688918 0.000783335 0.812899
793 1 0.750694 0.997785 0.747805
1783 1 0.686848 0.871823 0.684479
1787 1 0.811307 0.874835 0.685088
1788 1 0.748542 0.938221 0.682997
1910 1 0.691385 0.936201 0.755806
1911 1 0.688208 0.866743 0.81146
1913 1 0.751226 0.877366 0.749807
1914 1 0.811462 0.937178 0.748253
1915 1 0.812733 0.869273 0.814524
1916 1 0.757647 0.936847 0.811652
676 1 0.999854 0.182777 0.685994
1791 1 0.936226 0.870022 0.688916
1792 1 0.874802 0.940387 0.685478
1917 1 0.870605 0.870524 0.748474
1918 1 0.933182 0.937886 0.750115
1919 1 0.936879 0.874111 0.810951
1920 1 0.871283 0.933245 0.813103
2037 1 0.628068 0.879637 0.873067
569 1 0.743699 0.122476 0.501843
2040 1 0.621598 0.93978 0.937904
914 1 0.560943 0.0674181 0.878163
920 1 0.625091 0.0611309 0.939245
947 1 0.568297 0.128436 0.942293
949 1 0.622393 0.128463 0.877283
2002 1 0.563369 0.814542 0.875334
1604 1 0.99996 0.813945 0.563422
923 1 0.805848 0.0017076 0.938255
921 1 0.744716 1.00342 0.877845
918 1 0.684697 0.0644241 0.878342
922 1 0.814268 0.0646317 0.874942
924 1 0.749963 0.0645557 0.938535
951 1 0.688286 0.12416 0.944795
953 1 0.74636 0.128287 0.875295
955 1 0.810841 0.12852 0.94104
2008 1 0.629585 0.814612 0.940006
925 1 0.870467 1.00266 0.877614
927 1 0.937247 0.00326639 0.93371
926 1 0.939468 0.0634824 0.87061
928 1 0.87102 0.0642136 0.936497
957 1 0.875367 0.120898 0.87383
959 1 0.934677 0.120527 0.936538
1978 1 0.809506 0.682327 0.879261
724 1 0.503809 0.318288 0.689616
2007 1 0.683377 0.744481 0.939626
2012 1 0.747433 0.80837 0.938459
917 1 0.624562 0.00574954 0.874169
2011 1 0.81626 0.745914 0.935858
1974 1 0.685672 0.686945 0.87286
1732 1 1.003 0.811539 0.690171
981 1 0.629624 0.252615 0.877941
984 1 0.626765 0.316597 0.939235
946 1 0.566239 0.186211 0.876354
952 1 0.627737 0.186192 0.941404
978 1 0.570169 0.317655 0.873013
979 1 0.567208 0.252272 0.940322
2009 1 0.745983 0.746627 0.877851
753 1 0.501764 0.375525 0.624536
986 1 0.813331 0.3068 0.875724
982 1 0.687458 0.312745 0.875132
987 1 0.810207 0.24842 0.939045
988 1 0.749635 0.31242 0.937339
983 1 0.68818 0.24945 0.950164
954 1 0.809998 0.186491 0.876473
985 1 0.748975 0.252041 0.875545
956 1 0.748851 0.183594 0.941937
950 1 0.68887 0.187529 0.878488
1949 1 0.87815 0.497724 0.880476
960 1 0.876985 0.187249 0.940719
991 1 0.936117 0.250267 0.941917
990 1 0.939163 0.316104 0.871925
992 1 0.877545 0.312238 0.940899
989 1 0.87271 0.247128 0.882044
958 1 0.936924 0.183863 0.878661
2006 1 0.688937 0.808202 0.877927
1980 1 0.744133 0.686892 0.938205
1141 1 0.626704 0.876756 1.0024
1016 1 0.62572 0.437293 0.937641
1013 1 0.631051 0.371723 0.87399
1011 1 0.562207 0.376738 0.938612
1010 1 0.56888 0.439529 0.872285
1941 1 0.625402 0.500207 0.875065
2010 1 0.814097 0.807761 0.876261
1982 1 0.940689 0.684629 0.88008
1020 1 0.748326 0.437711 0.937416
1019 1 0.810363 0.371185 0.935978
1018 1 0.814029 0.439091 0.875558
1017 1 0.750213 0.374236 0.873206
1014 1 0.689296 0.44098 0.875965
1015 1 0.688852 0.376123 0.937827
1943 1 0.686868 0.501243 0.937859
2015 1 0.937968 0.749522 0.939175
1984 1 0.877805 0.680759 0.938687
1761 1 1.00206 0.875274 0.629442
1024 1 0.87215 0.437322 0.938089
1023 1 0.934393 0.370703 0.941714
1022 1 0.942514 0.435539 0.874602
1021 1 0.8746 0.375117 0.877044
1951 1 0.941059 0.498927 0.936765
1950 1 0.940629 0.560551 0.872508
1796 1 1.00021 0.560498 0.814115
1976 1 0.624748 0.679174 0.934401
2013 1 0.878327 0.746568 0.876442
1625 1 0.750481 0.755356 0.501492
1939 1 0.563477 0.498332 0.939609
1938 1 0.560713 0.563156 0.87779
1944 1 0.627556 0.559827 0.942673
1971 1 0.563215 0.626392 0.937767
1973 1 0.62268 0.625045 0.87347
2016 1 0.872151 0.813186 0.938218
2014 1 0.938355 0.812786 0.876374
1947 1 0.81307 0.499735 0.939189
1945 1 0.747324 0.497183 0.873345
1979 1 0.810351 0.622731 0.940126
1942 1 0.68228 0.564514 0.872138
1946 1 0.815006 0.563061 0.877181
1948 1 0.747778 0.559284 0.941944
1975 1 0.685148 0.620222 0.937031
1977 1 0.751177 0.624491 0.874837
1983 1 0.938361 0.617133 0.936982
1981 1 0.879137 0.620079 0.874074
1952 1 0.874636 0.562907 0.93847
737 1 0.997941 0.373913 0.621445
1117 1 0.879044 0.744647 1.00546
1012 1 0.503286 0.436653 0.935444
884 1 0.505884 0.434705 0.816171
1118 1 0.93839 0.809876 0.997263
1588 1 0.499899 0.688481 0.563406
977 1 0.505543 0.25315 0.876481
833 1 0.998674 0.251342 0.750867
756 1 0.502317 0.436516 0.688344
1937 1 0.502036 0.499138 0.877494
1661 1 0.877441 0.878671 0.500302
1586 1 0.566439 0.688273 0.496768
1809 1 0.505914 0.493486 0.752876
2020 1 1.0002 0.940374 0.935096
836 1 1.00101 0.311922 0.811263
1554 1 0.564346 0.562004 0.498796
852 1 0.506821 0.310508 0.808788
1074 1 0.563563 0.687265 1.00346
1540 1 0.998003 0.558044 0.558027
673 1 1.00738 0.124951 0.623239
740 1 1.00124 0.43656 0.682158
548 1 0.998463 0.185125 0.564347
1654 1 0.689232 0.939878 0.499937
1658 1 0.808957 0.938682 0.507323
1585 1 0.504732 0.628264 0.496457
1082 1 0.814379 0.684687 1.00247
21 1 0.61988 0.000150999 1.00165
1110 1 0.690073 0.809348 1.00194
118 1 0.688528 0.438766 0.996812
1146 1 0.8104 0.939979 1.00041
1114 1 0.816671 0.81506 1.00052
113 1 0.4993 0.371679 0.998608
125 1 0.87007 0.371168 1.0022
1650 1 0.558143 0.937179 0.504975
1150 1 0.94005 0.938008 0.996478
1617 1 0.501506 0.753439 0.504246
606 1 0.935426 0.313179 0.50003
633 1 0.744173 0.381078 0.49725
1590 1 0.683331 0.692264 0.502539
1557 1 0.623861 0.500824 0.50135
26 1 0.808787 0.068226 1.00226
1622 1 0.685959 0.813626 0.507248
1594 1 0.815898 0.692924 0.504871
33 1 0.998463 0.122122 0.998915
574 1 0.935994 0.188305 0.502992
1598 1 0.93674 0.691651 0.503403
1138 1 0.561145 0.937173 0.995046
1142 1 0.684473 0.937888 1.00198
|
[
"scheuclu@gmail.com"
] |
scheuclu@gmail.com
|
74c6e22e10d24f80e71b7232533ed388186eeff9
|
6ecbf084f558b37f0cee51c7226c1e116b5aa7bf
|
/scratch/bnn.py
|
aac4b4b2e7b7f9d26c1dc0798692c2967766ade1
|
[] |
no_license
|
reichlab/bayesian_non_parametric
|
364b12ad07b09e9a4386572bd47c709ad7629497
|
c8d7eb7493addb919b8f7159768dc732ce1a1f35
|
refs/heads/master
| 2021-01-01T06:43:10.176687 | 2018-03-25T14:33:32 | 2018-03-25T14:33:32 | 97,492,688 | 2 | 0 | null | 2018-01-02T15:23:21 | 2017-07-17T15:38:01 |
Python
|
UTF-8
|
Python
| false | false | 8,338 |
py
|
from __future__ import absolute_import
from __future__ import print_function
import matplotlib.pyplot as plt
import autograd.numpy as np
import autograd.numpy.random as npr
from autograd import grad
from sklearn.preprocessing import scale
from autograd.optimizers import adam
def black_box_variational_inference(logprob, D, num_samples):
"""Implements http://arxiv.org/abs/1401.0118, and uses the
local reparameterization trick from http://arxiv.org/abs/1506.02557"""
def unpack_params(params):
# Variational dist is a diagonal Gaussian.
mean, log_std = params[:D], params[D:]
return mean, log_std
def gaussian_entropy(log_std):
return 0.5 * D * (1.0 + np.log(2*np.pi)) + np.sum(log_std)
rs = npr.RandomState(0)
def variational_objective(params, t):
"""Provides a stochastic estimate of the variational lower bound."""
mean, log_std = unpack_params(params)
samples = rs.randn(num_samples, D) * np.exp(log_std) + mean
lower_bound = gaussian_entropy(log_std) + np.mean(logprob(samples, t))
return -lower_bound
gradient = grad(variational_objective)
return variational_objective, gradient, unpack_params
def make_nn_funs(layer_sizes, L2_reg, noise_variance, nonlinearity=np.tanh):
"""These functions implement a standard multi-layer perceptron,
vectorized over both training examples and weight samples."""
shapes = list(zip(layer_sizes[:-1], layer_sizes[1:]))
num_weights = sum((m+1)*n for m, n in shapes)
def unpack_layers(weights):
num_weight_sets = len(weights)
for m, n in shapes:
yield weights[:, :m*n] .reshape((num_weight_sets, m, n)),\
weights[:, m*n:m*n+n].reshape((num_weight_sets, 1, n))
weights = weights[:, (m+1)*n:]
def predictions(weights, inputs):
"""weights is shape (num_weight_samples x num_weights)
inputs is shape (num_datapoints x D)"""
inputs = np.expand_dims(inputs, 0)
for W, b in unpack_layers(weights):
outputs = np.einsum('mnd,mdo->mno', inputs, W) + b
inputs = nonlinearity(outputs)
return outputs
def logprob(weights, inputs, targets):
log_prior = -L2_reg * np.sum(weights**2, axis=1)
preds = predictions(weights, inputs)
log_lik = -np.sum((preds - targets)**2, axis=1)[:, 0] / noise_variance
return log_prior + log_lik
return num_weights, predictions, logprob
def build_toy_dataset(n_data=40, noise_std=0.1):
D = 1
rs = npr.RandomState(0)
inputs = np.concatenate([np.linspace(0, 2, num=n_data/2),
np.linspace(6, 8, num=n_data/2)])
targets = np.cos(inputs) + rs.randn(n_data) * noise_std
inputs = (inputs - 4.0) / 4.0
inputs = inputs.reshape((len(inputs), D))
targets = targets.reshape((len(targets), D))
return inputs, targets
if __name__ == '__main__':
# Specify inference problem by its unnormalized log-posterior.
rbf = lambda x: np.exp(-x**2)
relu = lambda x: np.maximum(x, 0.)
num_weights, predictions, logprob = \
make_nn_funs(layer_sizes=[1, 20, 20, 1], L2_reg=0.001,
noise_variance=0.01, nonlinearity=rbf)
inputs, targets = build_toy_dataset()
data__full = [4,5,4,3,6,2,4,5,10,6,8,2,6,17,23,13,21,28,24,20,40,27,42,33,43,37,57,71,44,56,53,52,47,26,27,21,21,26,34,37,17,19,25,18,21,17,17,16,16,15,23,16,17,12,17,10,15,19,21,14,18,13,14,18,23,25,62,60,76,66,64,68,89,92,140,116,142,129,140,140,127,129,169,141,108,78,70,81,104,90,85,55,53,65,33,38,59,40,37,29,30,30,28,23,24,29,26,23,20,19,20,26,29,31,28,26,32,35,33,30,52,59,67,65,74,70,61,53,76,61,57,44,34,47,60,60,53,36,31,30,32,28,33,33,35,22,13,13,21,17,11,8,8,6,6,7,12,17,10,10,18,19,12,22,12,21,18,16,16,22,17,25,23,12,25,28,27,18,23,23,29,38,36,43,46,31,25,40,31,38,30,22,31,26,35,36,39,25,31,37,33,25,24,18,23,13,18,14,17,22,13,24,31,34,31,31,38,49,42,49,55,80,84,72,89,115,179,202,272,302,395,426,461,381,333,353,410,364,359,288,221,149,112,154,91,72,56,46,37,26,17,17,20,11,7,16,14,16,5,2,6,5,4,3,4,16,8,7,10,14,7,9,11,23,17,19,24,17,28,40,33,31,33,29,30,36,48,40,28,36,19,34,23,17,17,23,14,20,13,23,20,16,16,23,14,15,4,5,5,11,11,7,4,6,5,2,4,2,4,6,6,4,6,11,16,9,12,13,27,21,19,17,24,27,30,29,25,35,33,30,29,31,29,22,27,24,26,29,22,33,24,30,20,17,24,28,18,13,9,14,11,11,19,10,8,8,9,3,7,14,4,9,14,7,9,3,3,14,12,10,21,26,47,42,31,34,33,52,56,70,112,70,47,48,49,66,56,61,67,64,68,49,50,56,75,63,62,41,50,34,31,38,30,32,26,30,36,35,46,48,44,51,59,71,102,128,127,150,191,256,329,263,220,204,181,99,54,80,102,127,73,68,64,55,67,84,85,67,73,89,68,59,56,77,75,47,50,42,28,37,37,27,12,15,22,8,15,17,10,9,11,20,13,11,16,11,7,17,14,13,15,30,25,40,44,25,21,48,56,60,45,55,32,46,61,42,37,43,34,40,25,16,17,17,16,23,18,18,9,7,7,4,3,2,8,3,1,1,2,3,3,2,0,0,2,2,0,6,3,6,2,3,2,4,5,2,9,2,4,8,6,3,11,14,15,20,9,20,28,38,30,30,23,16,22,28,14,17,20,17,10,13,20,9,18,9,8,19,11,4,6,6,8,13,8,8,5,16,12,11,18,10,22,14,16,18,27,38,35,41,51,65,55,54,62,64,56,65,71,75,71,72,47,27,35,25,19,37,38,34,26,19,18,22,16,18,6,12,6,6,3,7,6,1,3,2,2,1,10,3,3,1,1,2,6,3,3,5,4,7,6,5,7,6,4,4,7,9,5,5,10,6,13,6,5,5,9,3,6,11,7,7,15,9,6,6,6,7,10,8,7,12,3,2,7,5,5,7,7,7,7,10,13,10,14,11,20,25,17,18,25,21,31,32,26,35,28,37,41,34,30,39,39,39,34,30,37,29,26,15,22,15,20,14,10,21,14,14,9,11,5,6,7,11,4,3,2,6,10,7,5,3,12,13,10,13,13,8,21,18,8,7,20,14,14,7,14,10,13,27,13,18,16,16,20,17,4,15,8,6,12,15,11,10,15,17,7,7,8,9,12,12,5,4,11,4,5,7,1,1,4,2,6,3,4,10,12,21,26,21,30,45,56,75,83,82,126,119,137,131,112,82,73,43,55,55,53,46,43,29,22,26,13,17,8,13,10,17,19,9,9,9,3,7,7,0,2,3,3,1,3,3,3,7,3,5,11,5,5,6,6,4,4,8,14,12,16,10,16,18,15,23,17,33,15,13,11,14,17,19,20,12,21,7,19,10,13,10,8,21,11,9,14,14,15,18,16,12,20,8,3,13,4,1,10,8,13,10,21,18,21,34,25,34,33,40,42,36,72,75,76,92,71,112,106,101,170,135,106,68,48,48,26,33,29,17,12,13,17,15,14,15,10,9,2,6,8,5,1,2,3,4,3,1,3,5,2,3,2,3,2,2,3,4,3,4,4,4,7,6,15,11,9,9,12,13,13,13,20,28,45,28,34,41,36,38,48,27,23,28,42,30,18,38,28,36,44,41,35,28,28,22,26,24,9,21,10,15]
#data__full = np.array(data__full)/np.max(data__full).tolist()
from sklearn.cluster import KMeans
data__full = scale(data__full)
data__ = data__full[:50]
m = 1
train_target = []
train_data = []
test_data = []
test_target = []
for i in range(1,len(data__)):
train_data.append(data__[i-1])
train_target.append(data__[i])
print (np.array(train_data).shape)
X_train = X_test = np.array(train_data,dtype=np.float32).reshape((-1,1))
y_train = y_test = np.array(train_target,dtype=np.float32).reshape((-1))
inputs = X_train
targets = y_train
log_posterior = lambda weights, t: logprob(weights, X_train, y_train)
# Build variational objective.
objective, gradient, unpack_params = \
black_box_variational_inference(log_posterior, num_weights,
num_samples=20)
# Set up figure.
fig = plt.figure(figsize=(12, 8), facecolor='white')
ax = fig.add_subplot(111, frameon=False)
plt.ion()
plt.show(block=False)
def callback(params, t, g):
print("Iteration {} lower bound {}".format(t, -objective(params, t)))
# Sample functions from posterior.
rs = npr.RandomState(0)
mean, log_std = unpack_params(params)
#rs = npr.RandomState(0)
sample_weights = rs.randn(10, num_weights) * np.exp(log_std) + mean
plot_inputs = data__full[49:60]
plot_inputs = np.linspace(0, 100, num=400)
outputs = predictions(sample_weights, np.expand_dims(inputs.ravel(), 1))
plt.cla()
ax.plot(inputs.ravel(), targets.ravel(), 'bx')
ax.plot(inputs.ravel(), outputs[:, :, 0].T)
ax.set_ylim([-2, 2])
ax.set_xlim([-2, 2])
plt.draw()
plt.pause(1.0/60.0)
# Plot data and functions.
# Initialize variational parameters
rs = npr.RandomState(0)
init_mean = rs.randn(num_weights)
init_log_std = -5 * np.ones(num_weights)
init_var_params = np.concatenate([init_mean, init_log_std])
print("Optimizing variational parameters...")
variational_params = adam(gradient, init_var_params,
step_size=0.1, num_iters=1000, callback=callback)
|
[
"gcgibson@us.ibm.com"
] |
gcgibson@us.ibm.com
|
dfa355b0aa14dd76ed80003014bdb0d64e25c20b
|
84fe91caa2209022b8300a7f42dea0b78db41e12
|
/action/test/test_watermark.py
|
acb7ae6abfbc2f7e2d4e76c4d1d2bf2991c3c0c8
|
[
"MIT"
] |
permissive
|
mshemanskyi/image-batch-processor
|
6b579f1e3442262a9abb5a0cd8f6731a23ebf13b
|
dd7e0d9bc77fd06fe0f94c4f4fd025323633d9f7
|
refs/heads/master
| 2023-01-10T10:03:52.523962 | 2020-11-07T21:18:47 | 2020-11-07T21:18:47 | 303,668,070 | 0 | 0 |
MIT
| 2020-11-07T20:27:36 | 2020-10-13T10:33:10 |
Python
|
UTF-8
|
Python
| false | false | 677 |
py
|
import unittest
from action.watermark import watermarkImage, watermarkText
import cv2 as cv
import numpy as np
class WatermarkTest((unittest.TestCase)):
@classmethod
def setUpClass(self):
self.testImage = cv.imread('examples/img1.jpg')
self.watermarkLogo = cv.imread('examples/wm-logo.png')
def setUp(self):
pass
def test_watermak__image_action(self):
wmi = watermarkImage(self.testImage, self.watermarkLogo)
self.assertTrue(np.any(self.testImage != wmi))
def test_watarmark_text_action(self):
wmi = watermarkText(self.testImage, 'watermarkLogo')
self.assertTrue(np.any(self.testImage != wmi))
|
[
"noreply@github.com"
] |
mshemanskyi.noreply@github.com
|
ba55baa802dc3a6b2fe5b7b479d00888a5eec426
|
728be4e1d3ab5a63e2d6900637fdfb822d965a43
|
/blobing_photo.py
|
a41716f876d2c4ec077f3e39a3870d46e285f6db
|
[] |
no_license
|
Reveta/openCV_Python
|
7ea7aeb5da5243b4359cb75ed9e14489051d917f
|
6b88a9c1ba459f2810c54b91da77e0f0914da894
|
refs/heads/master
| 2023-07-16T00:26:17.752429 | 2021-08-23T19:33:10 | 2021-08-23T19:33:10 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,054 |
py
|
# !/usr/bin/python
# Standard imports
import cv2
import numpy as np
# Read image
# image_original = cv2.imread("media/blobs/blob.jpg", cv2.IMREAD_GRAYSCALE)
image_original = cv2.imread("media/blobs/microchips_1.png", cv2.IMREAD_COLOR)
# image_original = cv2.imread("media/blobs/microchips_2.png", cv2.IMREAD_COLOR)
th, image = cv2.threshold(image_original, 150, 255, cv2.THRESH_BINARY)
image = cv2.medianBlur(src=image, ksize=3)
image = cv2.bitwise_not(image)
# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()
# Change thresholds
params.minThreshold = 150
params.maxThreshold = 255
# params.filterByColor = True
# params.blobColor = 203
# Filter by Area.
# params.filterByArea = True
# params.minArea = 100
#
# Filter by Circularity
# params.filterByCircularity = True
# params.minCircularity = 0.7
# Filter by Convexity
params.filterByConvexity = True
params.minConvexity = 0
# Filter by Inertia
params.filterByInertia = True
params.minInertiaRatio = 0
# Create a detector with the parameters
ver = (cv2.__version__).split('.')
if int(ver[0]) < 3:
detector = cv2.SimpleBlobDetector(params)
else:
detector = cv2.SimpleBlobDetector_create(params)
# Detect blobs.
keypoints = detector.detect(image)
# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures
# the size of the circle corresponds to the size of blob
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
th, image = cv2.threshold(image, 150, 255, cv2.THRESH_BINARY_INV)
im_with_keypoints = cv2.drawKeypoints(image_original, keypoints, np.array([]), (0, 0, 255),
cv2.DrawMatchesFlags_DRAW_RICH_KEYPOINTS)
down_width = 800
down_height = 800
down_points = (down_width, down_height)
image_original = cv2.resize(image_original, down_points, interpolation= cv2.INTER_LINEAR)
im_with_keypoints = cv2.resize(im_with_keypoints, down_points, interpolation= cv2.INTER_LINEAR)
# Show blobs
cv2.imshow("original", image_original)
cv2.imshow("Keypoints", im_with_keypoints)
cv2.waitKey(0)
|
[
"gfdsre1999@gmail.com"
] |
gfdsre1999@gmail.com
|
c5764734108e5118eb033f9417b70073be8ac9a0
|
28541d61368a14a0d5003db4cc07fed21b40c41f
|
/Chapter-4/maze3.py
|
2a2bcf9a00c029002b258874bd88cd10f9fc123a
|
[] |
no_license
|
eizin6389/python_algorithm
|
390861f9342ce907f2cda0b45b84d364bcba7541
|
abf3588ed97a343b6559eb5d69156708d42bc243
|
refs/heads/master
| 2022-12-06T20:48:49.470312 | 2020-08-14T13:29:26 | 2020-08-14T13:29:26 | 282,905,077 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 796 |
py
|
maze = [
[9,9,9,9,9,9,9,9,9,9,9,9],
[9,0,0,0,9,0,0,0,0,0,0,9],
[9,0,9,0,0,0,9,9,0,9,9,9],
[9,0,9,9,0,9,0,0,0,9,0,9],
[9,0,0,0,9,0,0,9,9,0,9,9],
[9,9,9,0,0,9,0,9,0,0,0,9],
[9,0,0,0,9,0,9,0,0,9,1,9],
[9,0,9,0,0,0,0,9,0,0,9,9],
[9,0,0,9,0,9,0,0,9,0,0,9],
[9,0,9,0,9,0,9,0,0,9,0,9],
[9,0,0,0,0,0,0,9,0,0,0,9],
[9,9,9,9,9,9,9,9,9,9,9,9]
]
dir = [[1,0],[0,1],[-1,0],[0,-1]]
x, y, depth, d = 1, 1, 0, 0
while maze[x][y] != 1:
maze[x][y] = 2
for i in range(len(dir)):
j = (d + i - 1) % len(dir)
if maze[x + dir[j][0]][y + dir[j][1]] < 2:
x += dir[j][0]
y += dir[j][1]
d = j
depth += 1
break
elif maze[x + dir[j][0]][y + dir[j][1]] == 2:
x += dir[j][0]
y += dir[j][1]
d = j
depth -= 1
break
print(depth)
|
[
"hide@matsumotohideto-no-MacBook-Pro.local"
] |
hide@matsumotohideto-no-MacBook-Pro.local
|
3eaa1551407f554655a52f1b22c4d721669fa579
|
3e6e18edfe81bb19e298ae4e1831cb76c2c6069d
|
/src/lpcshop/models/bottles.py
|
a4dba719454dd661eebe4d48daada55e5b64e9f8
|
[] |
no_license
|
libertalia/lpc
|
2e72de7eee36cd92d62e4d250186bda2353c179a
|
972343abdcffffc2bec0cac4e2057c91edfa1716
|
refs/heads/master
| 2023-01-07T08:13:02.708844 | 2016-05-13T01:34:57 | 2016-05-13T01:34:57 | 58,680,165 | 0 | 1 | null | 2022-12-26T19:59:29 | 2016-05-12T22:02:24 |
JavaScript
|
UTF-8
|
Python
| false | false | 2,117 |
py
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
from django.utils.translation import ugettext_lazy as _
from django.utils.six.moves.urllib.parse import urljoin
from django.utils.encoding import python_2_unicode_compatible
from djangocms_text_ckeditor.fields import HTMLField
from shop.money.fields import MoneyField
from shop.models.product import BaseProduct, BaseProductManager
from shop.models.defaults.mapping import ProductPage, ProductImage
@python_2_unicode_compatible
class Bottle(BaseProduct):
# common product fields
product_name = models.CharField(max_length=255, verbose_name=_("Product Name"))
slug = models.SlugField(verbose_name=_("Slug"))
unit_price = MoneyField(_("Unit price"), decimal_places=3,
help_text=_("Net price for this product"))
description = HTMLField(verbose_name=_("Description"),
help_text=_("Description for the list view of products."))
# controlling the catalog
order = models.PositiveIntegerField(verbose_name=_("Sort by"), db_index=True)
cms_pages = models.ManyToManyField('cms.Page', through=ProductPage,
help_text=_("Choose list view this product shall appear on."))
images = models.ManyToManyField('filer.Image', through=ProductImage)
objects = BaseProductManager()
# filter expression used to search for a product item using the Select2 widget
lookup_fields = ('product_name__icontains',)
class Meta:
verbose_name = _("Bottle")
ordering = ('order',)
def __str__(self):
return self.product_name
@property
def sample_image(self):
return self.images.first()
def get_price(self, request):
return self.unit_price
def get_absolute_url(self):
# sorting by highest level, so that the canonical URL associates with the
# most generic category
cms_page = self.cms_pages.order_by('depth').last()
if cms_page is None:
return urljoin('category-not-assigned', self.slug)
return urljoin(cms_page.get_absolute_url(), self.slug)
|
[
"jamespic@gmail.com"
] |
jamespic@gmail.com
|
c16c35fcddd7c0a797b27db56f807ce47716da1a
|
7bc03c4f3fc28a9cebc9ebd3581060129a112416
|
/ogb/ogbn-products/mlp.py
|
3a6a307fffdcbe5fdff3be599899997a804eddba
|
[
"BSD-3-Clause"
] |
permissive
|
cornell-zhang/GraphZoom
|
468f6a03cf8009d133345f267425933421054e6a
|
5156f86fa22efa853e864553de4225a9122d8062
|
refs/heads/master
| 2023-04-04T19:06:33.155239 | 2021-04-20T23:21:35 | 2021-04-20T23:21:35 | 238,811,116 | 106 | 16 |
BSD-3-Clause
| 2023-03-24T23:42:18 | 2020-02-07T00:10:40 |
Python
|
UTF-8
|
Python
| false | false | 4,345 |
py
|
import argparse
import numpy as np
import torch
import torch.nn.functional as F
from ogb.nodeproppred import PygNodePropPredDataset, Evaluator
from logger import Logger
from csv import writer
class MLP(torch.nn.Module):
def __init__(self, in_channels, hidden_channels, out_channels, num_layers,
dropout):
super(MLP, self).__init__()
self.lins = torch.nn.ModuleList()
self.lins.append(torch.nn.Linear(in_channels, hidden_channels))
for _ in range(num_layers - 2):
self.lins.append(torch.nn.Linear(hidden_channels, hidden_channels))
self.lins.append(torch.nn.Linear(hidden_channels, out_channels))
self.dropout = dropout
def reset_parameters(self):
for lin in self.lins:
lin.reset_parameters()
def forward(self, x):
for lin in self.lins[:-1]:
x = lin(x)
x = F.relu(x)
x = F.dropout(x, p=self.dropout, training=self.training)
x = self.lins[-1](x)
return torch.log_softmax(x, dim=-1)
def train(model, x, y_true, train_idx, optimizer):
model.train()
optimizer.zero_grad()
out = model(x[train_idx])
loss = F.nll_loss(out, y_true.squeeze(1)[train_idx])
loss.backward()
optimizer.step()
return loss.item()
@torch.no_grad()
def test(model, x, y_true, split_idx, evaluator):
model.eval()
out = model(x)
y_pred = out.argmax(dim=-1, keepdim=True)
train_acc = evaluator.eval({
'y_true': y_true[split_idx['train']],
'y_pred': y_pred[split_idx['train']],
})['acc']
valid_acc = evaluator.eval({
'y_true': y_true[split_idx['valid']],
'y_pred': y_pred[split_idx['valid']],
})['acc']
test_acc = evaluator.eval({
'y_true': y_true[split_idx['test']],
'y_pred': y_pred[split_idx['test']],
})['acc']
return train_acc, valid_acc, test_acc
def main():
parser = argparse.ArgumentParser(description='OGBN-Products (MLP)')
parser.add_argument('--device', type=int, default=0)
parser.add_argument('--log_steps', type=int, default=1)
parser.add_argument('--use_node_embedding', action='store_true')
parser.add_argument('--num_layers', type=int, default=3)
parser.add_argument('--hidden_channels', type=int, default=256)
parser.add_argument('--dropout', type=float, default=0.0)
parser.add_argument('--lr', type=float, default=0.01)
parser.add_argument('--epochs', type=int, default=300)
parser.add_argument('--runs', type=int, default=10)
args = parser.parse_args()
print(args)
device = f'cuda:{args.device}' if torch.cuda.is_available() else 'cpu'
device = torch.device(device)
dataset = PygNodePropPredDataset(name='ogbn-products')
split_idx = dataset.get_idx_split()
data = dataset[0]
x = data.x
if args.use_node_embedding:
embedding = np.load('./embed_results/embeddings.npy')
embedding = torch.from_numpy(embedding).float()
x = torch.cat([x, embedding], dim=-1)
x = x.to(device)
y_true = data.y.to(device)
train_idx = split_idx['train'].to(device)
model = MLP(x.size(-1), args.hidden_channels, dataset.num_classes, args.num_layers,
args.dropout).to(device)
evaluator = Evaluator(name='ogbn-products')
logger = Logger(args.runs, args)
for run in range(args.runs):
model.reset_parameters()
optimizer = torch.optim.Adam(model.parameters(), lr=args.lr)
for epoch in range(1, 1 + args.epochs):
loss = train(model, x, y_true, train_idx, optimizer)
result = test(model, x, y_true, split_idx, evaluator)
logger.add_result(run, result)
if epoch % args.log_steps == 0:
train_acc, valid_acc, test_acc = result
print(f'Run: {run + 1:02d}, '
f'Epoch: {epoch:02d}, '
f'Loss: {loss:.4f}, '
f'Train: {100 * train_acc:.2f}%, '
f'Valid: {100 * valid_acc:.2f}%, '
f'Test: {100 * test_acc:.2f}%')
logger.print_statistics(run)
logger.print_statistics()
total_params = sum(p.numel() for p in model.parameters())
print(f'mlp total params are {total_params}')
if __name__ == "__main__":
main()
|
[
"xl289@cornell.edu"
] |
xl289@cornell.edu
|
4ac2e03f18c59c4cf2e602bb3b261c600978f096
|
c7575775b41d1435f33131eb5fdb1b5ec9066bba
|
/heyapp/settings.py
|
e259df91898c04a481dccc46c69e0c51a5722d51
|
[] |
no_license
|
Wambuilucy/nostalgia
|
12a5c951769b2d4dc0e4e68fce65bb53d360e0e7
|
5daf50d9e37e263a40c948ffcb155d85e03bd5b2
|
refs/heads/master
| 2023-01-06T08:00:33.547694 | 2020-11-03T17:00:44 | 2020-11-03T17:00:44 | 309,750,279 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,094 |
py
|
"""
Django settings for heyapp project.
Generated by 'django-admin startproject' using Django 1.11.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.11/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'x5a(^4i%79m302-_w6^0&v*pa--xyf&=&=dr8j#2v5lu1%-^l-'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'heyapp.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'heyapp.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
|
[
"wambuilucie99@gmail.com"
] |
wambuilucie99@gmail.com
|
bfed24c5b9f51dc5e88f33ea662a3f1e253a3474
|
39c7137821880e504608a4508299ed5883e3ebe3
|
/website/run.py
|
d10df72b10721b85de47d5e8500058bead40b612
|
[] |
no_license
|
tharrington923/rCheckUp
|
081a6b806e41f2b0d2a1b82e35f402b0ed9c932d
|
80e13d9b79b069f01dc83cb43d282557d5f78787
|
refs/heads/master
| 2020-12-10T03:27:05.944264 | 2017-06-29T16:02:15 | 2017-06-29T16:02:15 | 95,575,694 | 2 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 82 |
py
|
#!/usr/bin/env python
from rcheckup import app
app.run(host='0.0.0.0', port=5000)
|
[
"tharrington923@gmail.com"
] |
tharrington923@gmail.com
|
07030cbb64db6488b93f8e7f03c975d1d39c099d
|
df5cd640098a10e754a9552187fc5ad8c50df90c
|
/colour/examples/algebra/examples_interpolation.py
|
4acf509db6a9fd00459d7e4bce455a3a20c6b8ca
|
[
"BSD-3-Clause"
] |
permissive
|
ofek/colour
|
d4963c9b77b0d119cf3ef3296dbf5369167472df
|
04f4863ef49093a93244c1fedafd1d5e2b1b76da
|
refs/heads/develop
| 2021-07-08T05:33:14.220392 | 2017-09-29T22:34:14 | 2017-09-29T22:34:14 | 105,406,461 | 0 | 0 | null | 2017-09-30T23:06:18 | 2017-09-30T23:06:18 | null |
UTF-8
|
Python
| false | false | 3,265 |
py
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Showcases interpolation computations.
"""
import pylab
import colour
from colour.plotting import * # noqa
from colour.utilities.verbose import message_box
message_box('Interpolation Computations')
message_box(('Comparing "Sprague (1880)" and "Cubic Spline" recommended '
'interpolation methods to "Pchip" method.'))
uniform_spd_data = {
340: 0.0000,
360: 0.0000,
380: 0.0000,
400: 0.0641,
420: 0.0645,
440: 0.0562,
460: 0.0537,
480: 0.0559,
500: 0.0651,
520: 0.0705,
540: 0.0772,
560: 0.0870,
580: 0.1128,
600: 0.1360,
620: 0.1511,
640: 0.1688,
660: 0.1996,
680: 0.2397,
700: 0.2852,
720: 0.0000,
740: 0.0000,
760: 0.0000,
780: 0.0000,
800: 0.0000,
820: 0.0000
}
non_uniform_spd_data = {
340.1: 0.0000,
360: 0.0000,
380: 0.0000,
400: 0.0641,
420: 0.0645,
440: 0.0562,
460: 0.0537,
480: 0.0559,
500: 0.0651,
520: 0.0705,
540: 0.0772,
560: 0.0870,
580: 0.1128,
600: 0.1360,
620: 0.1511,
640: 0.1688,
660: 0.1996,
680: 0.2397,
700: 0.2852,
720: 0.0000,
740: 0.0000,
760: 0.0000,
780: 0.0000,
800: 0.0000,
820.9: 0.0000
}
base_spd = colour.SpectralPowerDistribution('Reference', uniform_spd_data)
uniform_interpolated_spd = colour.SpectralPowerDistribution(
'Uniform - Sprague Interpolation', uniform_spd_data)
uniform_pchip_interpolated_spd = colour.SpectralPowerDistribution(
'Uniform - Pchip Interpolation', uniform_spd_data)
non_uniform_interpolated_spd = colour.SpectralPowerDistribution(
'Non Uniform - Cubic Spline Interpolation', non_uniform_spd_data)
uniform_interpolated_spd.interpolate(colour.SpectralShape(interval=1))
uniform_pchip_interpolated_spd.interpolate(
colour.SpectralShape(interval=1), method='Pchip')
non_uniform_interpolated_spd.interpolate(colour.SpectralShape(interval=1))
shape = base_spd.shape
x_limit_min, x_limit_max, y_limit_min, y_limit_max = [], [], [], []
pylab.plot(
base_spd.wavelengths,
base_spd.values,
'ro-',
label=base_spd.name,
linewidth=2)
pylab.plot(
uniform_interpolated_spd.wavelengths,
uniform_interpolated_spd.values,
label=uniform_interpolated_spd.name,
linewidth=2)
pylab.plot(
uniform_pchip_interpolated_spd.wavelengths,
uniform_pchip_interpolated_spd.values,
label=uniform_pchip_interpolated_spd.name,
linewidth=2)
pylab.plot(
non_uniform_interpolated_spd.wavelengths,
non_uniform_interpolated_spd.values,
label=non_uniform_interpolated_spd.name,
linewidth=2)
x_limit_min.append(shape.start)
x_limit_max.append(shape.end)
y_limit_min.append(min(base_spd.values))
y_limit_max.append(max(base_spd.values))
settings = {
'x_label':
'Wavelength $\\lambda$ (nm)',
'y_label':
'Spectral Power Distribution',
'x_tighten':
True,
'legend':
True,
'legend_location':
'upper left',
'x_ticker':
True,
'y_ticker':
True,
'limits': (min(x_limit_min), max(x_limit_max), min(y_limit_min),
max(y_limit_max))
}
boundaries(**settings)
decorate(**settings)
display(**settings)
|
[
"thomas.mansencal@gmail.com"
] |
thomas.mansencal@gmail.com
|
aea1aef16acb0e35be9835c1de7d957ef061384a
|
a55bf36b8c58cb5b430734a9e5c35fec3a757b46
|
/Pygame/Maps/Attempts/Map01/app.py
|
4eab769097b0c2c65af739eb60bbae8eaf628217
|
[] |
no_license
|
alexetsnyder/OuroborosPython
|
5547a6f925263430f024b5fd1d1d797600ec5f9d
|
3c5e93fb90368c30c2748218a56a4d184e144caa
|
refs/heads/master
| 2021-06-28T22:37:07.555035 | 2021-03-01T23:45:10 | 2021-03-01T23:45:10 | 225,740,980 | 1 | 0 | null | 2021-03-01T23:45:10 | 2019-12-04T00:03:14 |
Python
|
UTF-8
|
Python
| false | false | 1,680 |
py
|
#app.py
import pygame, island_map
import imp, go, events, config
from pygame import freetype
from structs import *
class Screen:
def __init__(self, size):
self.set_size(size)
self.surface = pygame.display.set_mode(self.size, pygame.RESIZABLE)
def wire_events(self):
imp.IMP().add_listener(events.WindowResizedEvent().listen(self.on_resize))
def on_resize(self, event):
self.surface = pygame.display.set_mode((event.w, event.h), pygame.RESIZABLE)
def set_size(self, size):
self.w, self.h = self.size = size
def set_title(self, title):
pygame.display.set_caption(title)
def fill(self, color=Color.BLACK):
self.surface.fill(color)
def flip(self):
pygame.display.flip()
class App:
def __init__(self):
pygame.init()
self.island_map = island_map.IslandMap((0, 0), imp.IMP().screen.size, 320, 200)
self.wire_events()
def wire_events(self):
imp.IMP().add_listener(events.WindowResizedEvent().listen(self.on_resize))
def on_resize(self, event):
self.island_map.refresh((0, 0), (event.w, event.h))
def update(self):
pass
def draw(self):
imp.IMP().screen.fill(Color.BLACK)
imp.IMP().draw(self.island_map)
imp.IMP().screen.flip()
def free(self):
pygame.quit()
def run(self):
while imp.IMP().running:
for event in pygame.event.get():
imp.IMP().dispatch(event)
self.update()
self.draw()
self.free()
if __name__=='__main__':
data = config.Config('data/config_data.txt')
screen = Screen((640, 400))
event_dispatcher = events.EventDispatcher()
imp.IMP().init(screen, data, event_dispatcher, data.try_get('DEBUG', False))
app = App()
app.run()
|
[
"alexetsnyder@gmail.com"
] |
alexetsnyder@gmail.com
|
a3686500cf1b87f08d8a3d467cb0f56dead33719
|
44cfc32ae35487314cbf2ea83fbc96de9ac3e693
|
/Trees/post_iterative.py
|
f989a9dbf228047512a35fb120c7ca73c34c63c3
|
[] |
no_license
|
Imonymous/Practice
|
738fdf2099a74127460a647fee8db97c95f322fc
|
ff6138d858777e6a669a5a387cd2f775c60c9aff
|
refs/heads/master
| 2020-03-18T16:53:15.029553 | 2019-11-09T23:29:27 | 2019-11-09T23:29:27 | 134,991,515 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,237 |
py
|
#!/usr/bin/env python
from isBST import TreeNode, BinaryTree, readBinaryTree
# Using one stack
def build_stack(node, s):
while node:
if node.right_ptr:
s.append(node.right_ptr)
s.append(node)
node = node.left_ptr
def peek(s):
if len(s) > 0:
return s[-1]
return None
def post_iterative_1_stack(root):
s = []
build_stack(root, s)
while s:
curr = s.pop()
if curr.right_ptr == peek(s):
temp = s.pop()
s.append(curr)
build_stack(temp, s)
else:
print(curr.val)
# Using two stacks
def dfs(node):
if node is None:
return
print(node.val)
dfs(node.left_ptr)
dfs(node.right_ptr)
def post_iterative_2_stack(root):
# dfs(root)
s1 = []
s2 = []
s1.append(root)
while s1:
curr = s1.pop()
s2.append(curr)
if curr.right_ptr:
s1.append(curr.right_ptr)
if curr.left_ptr:
s1.append(curr.left_ptr)
while s2:
curr = s2.pop()
print(curr.val)
def main():
root = readBinaryTree()
post_iterative_2_stack(root)
post_iterative_1_stack(root)
if __name__ == '__main__':
main()
|
[
"iman.mukherjee@gmail.com"
] |
iman.mukherjee@gmail.com
|
467775b4bd0bdc529f7af369a772db9776c3f4d4
|
0b793bce2da8c3d09b7956c0672ddbffd46feaed
|
/atcoder/corp/dwacon6_a.py
|
0f60c706492fb0f7e55329255dd53fcbe06cb6d9
|
[
"MIT"
] |
permissive
|
knuu/competitive-programming
|
c6c4e08fb231937d988bdc5a60a8ad6b31b97616
|
16bc68fdaedd6f96ae24310d697585ca8836ab6e
|
refs/heads/master
| 2021-01-17T09:39:02.647688 | 2020-11-07T03:17:22 | 2020-11-07T03:17:22 | 27,886,732 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 225 |
py
|
N = int(input())
titles, times = [], []
for _ in range(N):
s, t = input().split()
titles.append(s)
times.append(int(t))
idx = titles.index(input())
ans = 0
for i in range(idx+1, N):
ans += times[i]
print(ans)
|
[
"premier3next@gmail.com"
] |
premier3next@gmail.com
|
7bd8c0b70b4ffef14ae6fc96a939fd776a871a5f
|
c4b852ce48ddef75f8c57bd2e70cc8ae7dc10693
|
/ToDo/console/migrations/0006_auto_20150309_1629.py
|
cbad7de01caa9cfa4fe39921f022ec9d123245ed
|
[] |
no_license
|
MMX13/todo
|
a2d063b3872579faa4b2ac4e1df4dfab74fe6788
|
b303fcec6e44f93223e6dab0de5a6d359c72cc70
|
refs/heads/master
| 2020-06-07T11:36:13.255423 | 2015-03-20T05:00:11 | 2015-03-20T05:00:11 | 31,998,487 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 450 |
py
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('console', '0005_auto_20150309_1627'),
]
operations = [
migrations.AlterField(
model_name='task',
name='scheduledDate',
field=models.DateField(null=True, blank=True),
preserve_default=True,
),
]
|
[
"bgaramy@hotmail.com"
] |
bgaramy@hotmail.com
|
396451adf046ae9a1e9a93d08c731002c02b4a78
|
5a52ccea88f90dd4f1acc2819997fce0dd5ffb7d
|
/alipay/aop/api/response/AntMerchantExpandIndirectOnlineModifyResponse.py
|
deb575d50e426359ce6993ae14225946249fa464
|
[
"Apache-2.0"
] |
permissive
|
alipay/alipay-sdk-python-all
|
8bd20882852ffeb70a6e929038bf88ff1d1eff1c
|
1fad300587c9e7e099747305ba9077d4cd7afde9
|
refs/heads/master
| 2023-08-27T21:35:01.778771 | 2023-08-23T07:12:26 | 2023-08-23T07:12:26 | 133,338,689 | 247 | 70 |
Apache-2.0
| 2023-04-25T04:54:02 | 2018-05-14T09:40:54 |
Python
|
UTF-8
|
Python
| false | false | 805 |
py
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.response.AlipayResponse import AlipayResponse
class AntMerchantExpandIndirectOnlineModifyResponse(AlipayResponse):
def __init__(self):
super(AntMerchantExpandIndirectOnlineModifyResponse, self).__init__()
self._sub_merchant_id = None
@property
def sub_merchant_id(self):
return self._sub_merchant_id
@sub_merchant_id.setter
def sub_merchant_id(self, value):
self._sub_merchant_id = value
def parse_response_content(self, response_content):
response = super(AntMerchantExpandIndirectOnlineModifyResponse, self).parse_response_content(response_content)
if 'sub_merchant_id' in response:
self.sub_merchant_id = response['sub_merchant_id']
|
[
"liuqun.lq@alibaba-inc.com"
] |
liuqun.lq@alibaba-inc.com
|
4b664002f3b91925204f95cf5afde92db89ca9f4
|
154e563104144721865a90987db0332bef08a4c3
|
/rh_aligner/plotting/__init__.py
|
8187d6023c6db7b60a29f9fbf00456387099c256
|
[
"MIT"
] |
permissive
|
Rhoana/rh_aligner
|
565572d645769053c74a36ddf0f53ecc20d997fe
|
baab698f6520b9b999bccf423dc510b0c8f4b9bb
|
refs/heads/master
| 2021-01-01T05:29:25.406459 | 2016-05-09T15:34:58 | 2016-05-09T15:34:58 | 56,165,015 | 3 | 3 | null | 2016-05-05T20:00:26 | 2016-04-13T15:43:33 |
Python
|
UTF-8
|
Python
| false | false | 281 |
py
|
"""
Plotting of the stitching and alignment steps library
- to deubg the steps
"""
from .view_pre_pmcc_mfov import view_pre_pmcc_mfov
from .view_post_pmcc_mfov import view_post_pmcc_mfov
__all__ = [
'view_pre_pmcc_mfov',
'view_post_pmcc_mfov'
]
|
[
"adisuis@seas.harvard.edu"
] |
adisuis@seas.harvard.edu
|
39b251cf54d0848c796c624fffa0a173acf39360
|
8d5ff31efba68cfc3e833d74ee2e1baa20c2ae87
|
/example/petstore/apis/pet/updatePet.py
|
905f31823115094929116457528d605abd007d7b
|
[] |
no_license
|
avanov/swagger_codegen
|
8fd3f08f0e0d7aff5beb5602e755836009b0494f
|
b0fcc84cfd12091ef443fc000d4ff6a547a48d86
|
refs/heads/master
| 2022-12-11T04:21:24.066731 | 2020-08-28T13:56:34 | 2020-08-28T13:56:34 | 292,118,282 | 0 | 0 | null | 2020-09-01T22:10:54 | 2020-09-01T22:10:53 | null |
UTF-8
|
Python
| false | false | 1,585 |
py
|
from __future__ import annotations
import pydantic
import datetime
import asyncio
import typing
from pydantic import BaseModel
from swagger_codegen.api.base import BaseApi
from swagger_codegen.api.request import ApiRequest
class Tag(BaseModel):
id: typing.Optional[int] = None
name: typing.Optional[str] = None
class Category(BaseModel):
id: typing.Optional[int] = None
name: typing.Optional[str] = None
class Pet(BaseModel):
category: typing.Optional[Category] = None
id: typing.Optional[int] = None
name: str
photoUrls: typing.List[str]
status: typing.Optional[str] = None
tags: typing.Optional[typing.List[Tag]] = None
def make_request(self: BaseApi, __request__: Pet,) -> Pet:
"""Update an existing pet"""
def serialize_item(item):
if isinstance(item, pydantic.BaseModel):
return item.dict()
return item
if isinstance(__request__, (list, tuple, set)):
body = [serialize_item(item) for item in __request__]
else:
body = __request__.dict()
m = ApiRequest(
method="PUT",
path="/api/v3/pet".format(),
content_type="application/json",
body=body,
headers=self._only_provided({}),
query_params=self._only_provided({}),
cookies=self._only_provided({}),
)
return self.make_request(
{
"200": {"application/json": Pet, "application/xml": Pet,},
"400": {"default": None,},
"404": {"default": None,},
"405": {"default": None,},
},
m,
)
|
[
"asyncee@users.noreply.github.com"
] |
asyncee@users.noreply.github.com
|
97550ee9088bd44771d6985a9fa127e9f57fd623
|
9fb8221849511024fa74a7a9f40c89075e06d7b1
|
/node_modules/bcrypt/build/config.gypi
|
e53b910c93cae2e01ae79dba6454d5dd5ee46d45
|
[
"MIT"
] |
permissive
|
ericajlittle/tinyURL
|
d94f6598ef49c95177bc84fa52351672dd9b9c86
|
b1f167da5a5665ab93598594389ac7f3a665b534
|
refs/heads/master
| 2021-01-11T21:13:21.703523 | 2017-01-31T21:51:28 | 2017-01-31T21:51:28 | 79,271,946 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 4,489 |
gypi
|
# Do not edit. File was generated by node-gyp's "configure" step
{
"target_defaults": {
"cflags": [],
"default_configuration": "Release",
"defines": [],
"include_dirs": [],
"libraries": []
},
"variables": {
"asan": 0,
"debug_devtools": "node",
"gas_version": "2.23",
"host_arch": "x64",
"icu_data_file": "icudt57l.dat",
"icu_data_in": "../../deps/icu-small/source/data/in/icudt57l.dat",
"icu_endianness": "l",
"icu_gyp_path": "tools/icu/icu-generic.gyp",
"icu_locales": "en,root",
"icu_path": "deps/icu-small",
"icu_small": "true",
"icu_ver_major": "57",
"node_byteorder": "little",
"node_enable_d8": "false",
"node_enable_v8_vtunejit": "false",
"node_install_npm": "true",
"node_module_version": 48,
"node_no_browser_globals": "false",
"node_prefix": "/",
"node_release_urlbase": "https://nodejs.org/download/release/",
"node_shared": "false",
"node_shared_cares": "false",
"node_shared_http_parser": "false",
"node_shared_libuv": "false",
"node_shared_openssl": "false",
"node_shared_zlib": "false",
"node_tag": "",
"node_use_bundled_v8": "true",
"node_use_dtrace": "false",
"node_use_etw": "false",
"node_use_lttng": "false",
"node_use_openssl": "true",
"node_use_perfctr": "false",
"node_use_v8_platform": "true",
"openssl_fips": "",
"openssl_no_asm": 0,
"target_arch": "x64",
"uv_parent_path": "/deps/uv/",
"uv_use_dtrace": "false",
"v8_enable_gdbjit": 0,
"v8_enable_i18n_support": 1,
"v8_inspector": "true",
"v8_no_strict_aliasing": 1,
"v8_optimized_debug": 0,
"v8_random_seed": 0,
"v8_use_snapshot": "true",
"want_separate_host_toolset": 0,
"nodedir": "/home/vagrant/.node-gyp/6.3.1",
"copy_dev_lib": "true",
"standalone_static_library": 1,
"fallback_to_build": "true",
"module": "/vagrant/week2day2/express_tinyURL/node_modules/bcrypt/lib/binding/bcrypt_lib.node",
"module_name": "bcrypt_lib",
"module_path": "/vagrant/week2day2/express_tinyURL/node_modules/bcrypt/lib/binding",
"cache_lock_stale": "60000",
"legacy_bundling": "",
"sign_git_tag": "",
"user_agent": "npm/3.10.3 node/v6.3.1 linux x64",
"always_auth": "",
"bin_links": "true",
"key": "",
"description": "true",
"fetch_retries": "2",
"heading": "npm",
"if_present": "",
"init_version": "1.0.0",
"user": "1000",
"force": "",
"only": "",
"cache_min": "10",
"init_license": "ISC",
"editor": "vi",
"rollback": "true",
"tag_version_prefix": "v",
"cache_max": "Infinity",
"userconfig": "/home/vagrant/.npmrc",
"engine_strict": "",
"init_author_name": "",
"init_author_url": "",
"tmp": "/tmp",
"depth": "Infinity",
"save_dev": "",
"usage": "",
"progress": "true",
"https_proxy": "",
"onload_script": "",
"rebuild_bundle": "true",
"save_bundle": "",
"shell": "/bin/bash",
"dry_run": "",
"prefix": "/home/vagrant/.nvm/versions/node/v6.3.1",
"browser": "",
"cache_lock_wait": "10000",
"registry": "https://registry.npmjs.org/",
"save_optional": "",
"scope": "",
"searchopts": "",
"versions": "",
"cache": "/home/vagrant/.npm",
"global_style": "",
"ignore_scripts": "",
"searchsort": "name",
"version": "",
"local_address": "",
"viewer": "man",
"color": "true",
"fetch_retry_mintimeout": "10000",
"maxsockets": "50",
"umask": "0002",
"fetch_retry_maxtimeout": "60000",
"message": "%s",
"ca": "",
"cert": "",
"global": "",
"link": "",
"save": "true",
"access": "",
"also": "",
"unicode": "",
"long": "",
"production": "",
"unsafe_perm": "true",
"node_version": "6.3.1",
"tag": "latest",
"git_tag_version": "true",
"shrinkwrap": "true",
"fetch_retry_factor": "10",
"npat": "",
"proprietary_attribs": "true",
"save_exact": "",
"strict_ssl": "true",
"dev": "",
"globalconfig": "/home/vagrant/.nvm/versions/node/v6.3.1/etc/npmrc",
"init_module": "/home/vagrant/.npm-init.js",
"parseable": "",
"globalignorefile": "/home/vagrant/.nvm/versions/node/v6.3.1/etc/npmignore",
"cache_lock_retries": "10",
"save_prefix": "^",
"group": "1000",
"init_author_email": "",
"searchexclude": "",
"git": "git",
"optional": "true",
"json": ""
}
}
|
[
"ericalittle123@gmail.com"
] |
ericalittle123@gmail.com
|
0486cb46bc1ae6e72dae5915d07ace26bbe31c92
|
ebc478ba6921afc9a3f613eda29942e3434512c6
|
/snpfc/snpCompare.py
|
4b454241b380e1545d7cabec6d16716f95c013b5
|
[
"Python-2.0"
] |
permissive
|
TeamMacLean/snpFC
|
704c24947bf13a476c733845324061a7e12e4b2f
|
6f3f90ebba4aa527bca80381d7d0002438011d22
|
refs/heads/master
| 2020-04-28T02:28:44.062833 | 2019-04-26T11:36:11 | 2019-04-26T11:36:11 | 174,899,809 | 4 | 3 | null | null | null | null |
UTF-8
|
Python
| false | false | 14,318 |
py
|
import os
import vcf
class SnpCompare:
"class to compare SNPs from multiple VCFs."
def __init__(self, vcffiles):
"""Initializes the object with vcf files and data structure variables to compare snps."""
self.vcffilenames = vcffiles
self.snpsites = {}
self.snp_positions = {}
def _record_all_snp_positions(self, chromosome, position):
"""
creates datastructure to store snp positions.
Records all chromosome and positions in global variable (dictionary data structure) and initializes with an array of False boolean values for each vcf input file
Each boolean value is a positional value of a snp in input vcf files in an array.
E.g. if input vcf files are ["test1.vcf", "test2.vcf", "test3.vcf"]
snpsites["chr1"]["1"] = [False, False, False]
snpsites["chr1"]["10"] = [False, False, False]
snpsites["chr2"]["1"] = [False, False, False]
:type chromosome: string
:param chromosome: name of the chromosome
:type position: int
:param position: position of SNP call in the chromosome
return:
None
"""
if chromosome in self.snpsites.keys():
if str(position) in self.snpsites[chromosome].keys():
return
else:
self.snpsites[chromosome][str(position)] = [False] * len(
self.vcffilenames
)
else:
self.snpsites.update(
{chromosome: {str(position): [False] * len(self.vcffilenames)}}
)
def _record_all_snps(self, filename, chromosome, position, ref, alt):
"""
creates datastructure to store all snps and it's relevant information.
append the snp records to the dictionary data structure once they passed the filter
:type filename: string
:param filename: vcf filename
:type chromosome: string
:param chromosome: chromosome name on which SNP was call
:type position: int
:param position: base position in the chromosome
:type ref: String
:param ref: reference base in SNP call
:type alt: String
:param alt: alternate base in SNP call
return:
None
"""
if filename in self.snp_positions.keys():
if chromosome in self.snp_positions[filename].keys():
self.snp_positions[filename][chromosome].update(
{
str(position): {
"ref": ref,
"alt": str(alt)
.replace("[", "")
.replace("]", "")
.replace(" ", ""),
}
}
)
else:
self.snp_positions[filename].update(
{
chromosome: {
str(position): {
"ref": ref,
"alt": str(alt)
.replace("[", "")
.replace("]", "")
.replace(" ", ""),
}
}
}
)
else:
self.snp_positions.update(
{
filename: {
chromosome: {
str(position): {
"ref": ref,
"alt": str(alt)
.replace("[", "")
.replace("]", "")
.replace(" ", ""),
}
}
}
}
)
def _get_snp_data(self):
""" reads chromosome, position, reference and alternative columns for SNPs and store in dict data structure."""
vcf_counter = 0
for filename in self.vcffilenames:
vcf_reader = vcf.Reader(open(filename), "rb")
samplename = vcf_reader.samples[0]
for record in vcf_reader:
chromosome, position, ref, alt = (
record.CHROM,
record.POS,
record.REF,
record.ALT,
)
position = str(position)
## code to build all snps position
self._record_all_snp_positions(chromosome, position)
self._record_all_snps(filename, chromosome, position, ref, alt)
# self.snp_positions.update({str(vcf_counter) + "_" + chromosome + "_" + str(position):{"ref": str(ref), "alt":str(alt).replace("[","").replace("]", "")}})
self.snpsites[chromosome][str(position)][vcf_counter] = True
vcf_counter += 1
def count_list_elements_occurrences(self, alt_bases):
"""
counts number of each element of input array.
:type alt_bases: Array
:param alt_bases: alternate bases from all VCF files for same chromosome and position. e.g. ["A", "T", "A", "T,C"]
return:
array with count of each element in the input array. e.g for above array it retuns [2, 1, 2, 1]
"""
counts = []
for x in alt_bases:
counts.append(alt_bases.count(x))
return counts
def get_unique_snps(self):
""" records a unique snps in a vcf file """
for chromosome in self.snpsites.keys():
for position in self.snpsites[chromosome].keys():
for filenumber in range(len(self.vcffilenames)):
if (
self.snpsites[chromosome][position][filenumber] == True
and sum(self.snpsites[chromosome][position]) == 1
): # First any(array) finds
self.snp_positions[self.vcffilenames[filenumber]][chromosome][
position
].update({"unique": True})
elif (
sum(self.snpsites[chromosome][position]) >= 2
): # there might be snp at same position but with different alt base
snp_index = [
i
for i, j in enumerate(self.snpsites[chromosome][position])
if j == True
]
totalindex = len(snp_index)
# Lets check the alt base in these vcf files using index
# lets get array of alt bases from each file
alt_snps = []
for index in snp_index:
alt_snps.append(
self.snp_positions[self.vcffilenames[index]][
chromosome
][position]["alt"]
)
# get the counts of the elements
counts = self.count_list_elements_occurrences(alt_snps)
for index in range(len(counts)):
if counts[index] == 1:
# this is unique, so occurred once
self.snp_positions[self.vcffilenames[snp_index[index]]][
chromosome
][position].update(
{"unique": True}
) # vcffilenames[snp_index[index]] = this will be the filename
# print("this is unique", vcffilenames[snp_index[index]], chromosome, position, self.snp_positions[vcffilenames[snp_index[index]]][chromosome][position])
# else:
# vcf_database["self.snp_positions"][chromosome + "_" + position].update({"unique":False})
return
def get_common_snps(self):
""" records SNPs common to all VCF input files. """
for chromosome in self.snpsites.keys():
for position in self.snpsites[chromosome].keys():
if all(self.snpsites[chromosome][position]) == True:
# lets check if all alt bases are same
alt_snps = []
for index in range(len(self.snpsites[chromosome][position])):
alt_snps.append(
self.snp_positions[self.vcffilenames[index]][chromosome][
position
]["alt"]
)
counts = self.count_list_elements_occurrences(alt_snps)
for countindex in range(len(counts)):
if counts[countindex] == len(self.vcffilenames):
self.snp_positions[self.vcffilenames[countindex]][
chromosome
][position].update({"common": True})
def compare(self, outdir, save=True, display=False):
"""
save the common/unique snps to files and/or display the results.
:type outdir: string
:param outdir: output directory to save the output files
:type save: boolean
:param save: save the results to output files. Default True
:type display: boolean
:param display: display the results on the screen. Default False
returns:
None
"""
self._get_snp_data()
self.get_unique_snps()
self.get_common_snps()
outfiles = []
for filename in self.vcffilenames:
outfile = (
outdir
+ "/"
+ os.path.basename(filename).replace(".vcf", "")
+ "_snpcompare.txt"
)
outfh = open(outfile, "w")
outfiles.append(outfile)
if display == True:
print("Common and Unique SNPS in vcf File : ", filename)
else:
print(
"Common and Unique SNPs from file ",
filename,
" are saved in :",
outfile,
)
for chromosome in self.snp_positions[filename].keys():
for position in self.snp_positions[filename][chromosome].keys():
if (
"common"
in self.snp_positions[filename][chromosome][position].keys()
and self.snp_positions[filename][chromosome][position]["common"]
== True
):
if save == True:
outfh.write(
" ".join(
[
chromosome,
position,
self.snp_positions[filename][chromosome][
position
]["ref"],
self.snp_positions[filename][chromosome][
position
]["alt"],
"common",
]
)
+ "\n"
)
if display == True:
print(
" ".join(
[
chromosome,
position,
self.snp_positions[filename][chromosome][
position
]["ref"],
self.snp_positions[filename][chromosome][
position
]["alt"],
"common",
]
)
)
elif (
"unique"
in self.snp_positions[filename][chromosome][position].keys()
and self.snp_positions[filename][chromosome][position]["unique"]
== True
):
if save == True:
outfh.write(
" ".join(
[
chromosome,
position,
self.snp_positions[filename][chromosome][
position
]["ref"],
self.snp_positions[filename][chromosome][
position
]["alt"],
"unique",
]
)
+ "\n"
)
if display == True:
print(
" ".join(
[
chromosome,
position,
self.snp_positions[filename][chromosome][
position
]["ref"],
self.snp_positions[filename][chromosome][
position
]["alt"],
"unique",
]
)
)
outfh.close()
if display == True:
print("The outputs are saved in these files :", " ".join(outfiles))
return
|
[
"ram_krishna.shrestha@tsl.ac.uk"
] |
ram_krishna.shrestha@tsl.ac.uk
|
47cf0fd8aeef98b4cf379b295d0c198188f4b2da
|
22a671da954e3c6ecc83f7d24bb4a7c6c22cdeb9
|
/flask/lib/python3.6/io.py
|
153ad1e1b39a6a6b1fc5224983d5dbaa58d11d97
|
[] |
no_license
|
areibman/Kaggle-Renthop
|
62b7b0066bd6e980f10447681d749f183e8552b9
|
553aadca9ba1faa1696df048fb46e3843dda0113
|
refs/heads/master
| 2021-09-03T14:22:09.400118 | 2018-01-09T18:50:13 | 2018-01-09T18:50:13 | 116,855,697 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 41 |
py
|
/Users/alex/anaconda3/lib/python3.6/io.py
|
[
"alex@Alexs-MBP.fios-router.home"
] |
alex@Alexs-MBP.fios-router.home
|
1f20faa1db5d79da116d4b083125c2a17a098fc2
|
2485df18e7584efc0652ab5693ca299a29bf315a
|
/Finance/Monte-Carlo/Python/Pricing.py
|
443d07a10067c4ceebbe99b11a406d8ee136e2d2
|
[] |
no_license
|
lesibius/Programming-For-Fun
|
c16a576dcb91ff12e7ae8116386d4ac89c5e40c0
|
ae7e19e6ba78f4f95bbbf64f0d222f16d6b22b1d
|
refs/heads/master
| 2020-05-29T08:41:19.938610 | 2017-02-17T10:50:23 | 2017-02-17T10:50:23 | 69,820,991 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 9,485 |
py
|
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 18 10:28:21 2017
@author: clem
"""
import math
import numpy.random
import scipy.stats
import matplotlib.pyplot as plt
import sklearn.utils as sku
class Path:
"""
Class to represent the path of a random variable following a Brownian motion (e.g. stock price)
"""
def __init__(self,s0,nPeriod,deltaT):
"""
Parameters
----------
s0: float
Initial value of the random variable
nPeriod: int
Number of period to generate
deltaT: float
Inter-period time interval
Returns
-------
None
"""
self.NPeriod = nPeriod
self.DeltaT = deltaT
self.Values = [s0 for i in range(nPeriod)]
def GetLastItem(self):
"""
Returns the last value of the Path instance
Parameters
----------
None
Returns
-------
type: float
Last value of the Path instance
"""
return self.Values[self.NPeriod-1]
def __setitem__(self,ind,item):
"""
Set the value of an item in the Path value list
Parameters
----------
ind: int
Index in the random variable path list
item:
Value to set
Returns
-------
None
"""
self.Values[ind] = item
def __getitem__(self,ind):
"""
Returns a value of an item from the Path value list with the index provided
Parameters
----------
ind: int
Index of the item to return
Returns
-------
type: float
Value of the random variable at the given index
"""
return self.Values[ind]
def GetItemByDate(self,date):
"""
Return the value of the random variable at a given date
Parameters
----------
date: float
Date for which the random variable value should be returned
Returns
-------
type: float
Value of the random variable at the selected date
"""
frac, ind = math.modf(date / self.DeltaT)
ind=int(ind)
if frac < 0.000001:
return self[ind]
else:
return frac*self[ind]+(1-frac)*self[ind+1]
def Plot(self):
"""
Plot a graph of the path
Parameters
----------
None
Returns
-------
None
"""
plt.plot([self.DeltaT * period for period in range(self.NPeriod)],self.Values)
class PathGenerator:
"""
Class generating Path instances to price derivatives
"""
def __init__(self,nPath,totaltime,deltaT,model, drift, vol,**kwargs):
"""
Parameters
----------
nPath: int
Number of path to generate
totaltime: float
Total time of each path
deltaT: float
Time interval between two periods
drift: float/function
Drift of the Brownian motion
model: str
Name of the model to use. Currently, only "black-scholes" supported
vol: float/function
Volatility of the Brownian motion
**kwargs: optional arguments to provide for certain model
"""
self.TotalTime = totaltime
self.NPath = nPath
self.NPeriod = int(totaltime/deltaT)
self.DeltaT = deltaT
self.Drift = drift
self.Vol = vol
if model.lower() in ['bs','black-scholes','black scholes','merton','black-scholes-merton','black scholes merton']:
self.DriftFun = self._BSDriftFun
self.VolFun = self._BSVolFun
def _BSDriftFun(self,S,t,rt,sigmat):
"""
Drift function used by the Black-Scholes-Merton model
"""
return self.Drift * S
def _BSVolFun(self,S,t,r,sigmat):
"""
Volatility function used by the Black-Scholes-Merton model
"""
return self.Vol * S * numpy.random.normal(0.0,1.0)
def _initPaths(self,s0):
"""
Init the attribute Paths as a list of Path instance
Parameters
----------
s0: float
Initial value of the random variable
Returns
-------
None
"""
self.Paths = [Path(s0,self.NPeriod,self.DeltaT) for i in range(self.NPath)]
def GeneratePaths(self,s0):
"""
Generate the Path instance to price derivatives
Parameters
----------
s0: float
Initial value of the random variable
Returns
-------
None
"""
self._initPaths(s0)
for i in range(self.NPath):
S = s0
for j in range(self.NPeriod-1):
t = (j+1)*self.DeltaT
S = S + self.DriftFun(S,t,0.01,0) * self.DeltaT + self.VolFun(S,t,0.01,0) * math.sqrt(self.DeltaT)
self.Paths[i][j+1] = S
def Discount(self,date):
"""
Returns the discount factor for a given date
Warnings
--------
Only provide the discount factor, and do not implement r=f(t) yet
Parameters
----------
date: float
Date of the cash flow
Returns
-------
type: float
Discount factor for the selected date
"""
return math.exp(-date * 0.01)
def __getitem__(self,ind):
"""
Return a Path instance from the path list
Parameters
----------
ind: int
Index of the Path instance
Returns
-------
type: Path
Path at the ind index
"""
return self.Paths[ind]
def __iter__(self):
"""
Returns an iterable list of the Path instance
Parameters
----------
None
Returns
-------
type: list
List of Path instance
"""
for path in self.Paths:
yield path
class Option:
"""
Option class
"""
def __init__(self,payoff,underlying,expiry=None):
"""
Parameters
----------
payoff: function(Path -> float)
Payoff function
underlying: PathGenerator
Underlying PathGenerator instance
expiry: float (optional)
Expiry date (or last expirty date) of the derivative
"""
self.Underlying = underlying
self.Payoff = payoff
if expiry is None:
self.Expiry = underlying.TotalTime
else:
self.Expiry = expiry
def _GetValue(self,path):
"""
Compute the value at expiry date of the option"
Parameters
----------
path: Path
Path for which the value should be computed
Returns
-------
type: float
Value at expiry
"""
return self.Payoff(path) * self.Underlying.Discount(self.Expiry)
def Price(self,nbootstrap = 1000):
"""
Compute the option price using simulations
Parameters
----------
None
Returns
-------
type: float
Option price at t = 0
"""
tmpval = []
for path in self.Underlying:
tmpval.append(self._GetValue(path))
#av = mean(tmpval)
#st = (1.0/sqrt(self.Underlying.NPath))*numpy.std(tmpval)
#Dirty bootstrap procedure. Fall far from the closed form solution for OTM put
#But still better than without actually
bootstrap = [mean(sku.resample(tmpval)) for i in range(nbootstrap)]
av = mean(bootstrap)
st = numpy.std(bootstrap)
return [av - 1.96 * st, av ,av + 1.96 * st]
#Filled with some data ~ today
libor = 0.76944/100.0
S0 = 2267.89
r = 12.0 * math.log(1+libor/12.0)
sigma =0.06 #0.1177
K = 2250.0
t=1.0/12.0
nperiod = 1000
npath = 2000
pg = PathGenerator(npath,t,t/nperiod,'bs',r,sigma)
pg.GeneratePaths(S0)
plainvanillacall = Option(lambda x: max(x.GetLastItem() - K,0),pg)
plainvanillaput = Option(lambda x: max(K - x.GetLastItem(),0),pg)
print("Call price data: {}".format(plainvanillacall.Price()))
print("Put price data: {}".format(plainvanillaput.Price()))
N = lambda x: scipy.stats.norm.cdf(x)
d1 = (1.0/(sigma *math.sqrt(t))) * (math.log(S0/K)+(r+(sigma**2.0)/2.0)*t)
d2 = d1 - sigma * math.sqrt(t)
print("Closed form call: {}".format(S0 * N(d1) - K * math.exp(-r*t) * N(d2)))
print("Closed form put: {}".format(-S0 * N(-d1) + K * math.exp(-r*t) * N(-d2)))
from matplotlib.ticker import FuncFormatter
"""
plt.hist([p.GetLastItem() for p in pg.Paths],bins=10)
def to_percent(y,position):
return str(100*y/npath) + '%'
formatter = FuncFormatter(to_percent)
plt.gca().yaxis.set_major_formatter(formatter)
"""
print(mean([p.GetLastItem() for p in pg.Paths]))
print(S0 * math.exp(r * plainvanillacall.Expiry))
pg.Paths[0].Plot()
#plt.gca().set_ylim([0,2500])
|
[
"noreply@github.com"
] |
lesibius.noreply@github.com
|
1517524505fa74f594aa60a8d208dff423017646
|
2ce15189f888f9823469d7eaca69c7c1e06d9a01
|
/apps/login_app/migrations/0001_initial.py
|
0d97fff9e69a4eec96bb77b7913c10519bb3f726
|
[] |
no_license
|
paulfranco/cards
|
6cbcbe3e71b889cb8fbbbbc0fe9a3a4b229087d0
|
5250b2526d37b9993355fc2f5afed3df778a2812
|
refs/heads/master
| 2021-07-04T16:49:41.182133 | 2017-09-27T06:20:44 | 2017-09-27T06:20:44 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 745 |
py
|
# -*- coding: utf-8 -*-
# Generated by Django 1.11.4 on 2017-09-27 01:35
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='User',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('first_name', models.CharField(max_length=200)),
('last_name', models.CharField(max_length=200)),
('email', models.CharField(max_length=200)),
('password', models.CharField(max_length=200)),
],
),
]
|
[
"paulfranco@Pauls-MacBook-Pro.local"
] |
paulfranco@Pauls-MacBook-Pro.local
|
25824908e100267109197ad1c04cca8d349a6f10
|
8cf0cf9b71b7c5fbaa150e9893bf461ef661045e
|
/ownblock/ownblock/apps/parking/models.py
|
84c75498d4e8e94365b81a282ee43d877a925a7d
|
[
"MIT"
] |
permissive
|
danjac/ownblock
|
676b27a5aa0d4ce2ac2cd924a632489cd6fc21ee
|
ac662fb7efb2f04567e2f85638c1250286452611
|
refs/heads/master
| 2016-08-02T21:51:56.055598 | 2015-05-02T12:54:47 | 2015-05-02T12:54:47 | 34,940,828 | 3 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 875 |
py
|
from django.conf import settings
from django.db import models
from django_countries.fields import CountryField
class Vehicle(models.Model):
description = models.CharField(max_length=100)
registration_number = models.CharField(max_length=12)
country = CountryField(default="FI")
resident = models.ForeignKey(settings.AUTH_USER_MODEL)
reserved_place = models.CharField(max_length=12, blank=True)
def __str__(self):
return self.registration_number
def get_groups(self):
return [self.resident,
self.resident.apartment.building.site.group]
def has_permission(self, user, perm):
if user.role == 'resident':
return user == self.resident
if user.role == 'manager':
return (self.resident.apartment.building.site_id ==
user.site_id)
return False
|
[
"danjac354@gmail.com"
] |
danjac354@gmail.com
|
fd6eb4ffc23f7389f26fd2d60442434609b29286
|
5f814192b19721dc9c06e0e9595738b0f8561233
|
/OCR/east_text_detection.py
|
f8bee5a5e3d5d1b813617866d1b192837295a2ef
|
[] |
no_license
|
irischo/civil_translation
|
7b3c5c58e201f74547d5ae21123fdfd9d4bc5e64
|
240638a434957ea25cfac262da93fc23e292f6f2
|
refs/heads/master
| 2022-11-23T15:32:50.503095 | 2020-07-29T00:40:06 | 2020-07-29T00:40:06 | 283,387,321 | 0 | 0 | null | 2020-07-29T03:21:50 | 2020-07-29T03:21:49 | null |
UTF-8
|
Python
| false | false | 2,829 |
py
|
from imutils.object_detection import non_max_suppression
import numpy as np
import argparse
import time
import cv2
# argument parse
ap = argparse.ArgumentParser()
ap.add_argument('-i', '--image', type=str, help='path to input image')
ap.add_argument('-east', '--east', type=str, help='path to input EAST text detector')
ap.add_argument('-c', '--min-confidence', type=float, default=0.5, help='minimum probability required to inspect a region')
ap.add_argument('-w', '--width', type=int, default=320, help='resized image width (should be multiple of 32)')
ap.add_argument('-e', '--height', type=int, default=320, help='resized image height (should be multiple of 32)')
args = vars(ap.parse_args())
# load image
image = cv2.imread(args['image'])
orig = image.copy()
(H, W) = image.shape[:2]
# set new width & height
(newW, newH) = (args['width'], args['height'])
rW = W / float(newW)
rH = H / float(newH)
# resize image
image = cv2.resize(image, (newW, newH))
(H, W) = image.shape[:2]
layerNames = [
'feature_fusion/Conv_7/Sigmoid', # text or not check
'feature_fusion/concat_3' # image geometry
]
# load pre-trained EAST text decorator (from frozen_east_text_detection.pb)
print('[INFO] loading EAST text detector ...')
net = cv2.dnn.readNet(args['east'])
blob = cv2.dnn.blobFromImage(image, 1.0, (W, H), (123.68, 116.78, 103.94), swapPB=True, crop=False)
start = time.time()
net.setInput(blob)
(scores, geometry) = net.forward(layerNames)
end = time.time()
# show timing information on text prediction
print("[INFO] text detection took {:.6f} seconds".format(end - start))
(numRows, numCols) = scores.shape[2:4]
rects = []
confidences = []
for y in range(0, numRows):
scoresData = scores[0, 0, y]
xData0 = geometry[0, 0, y]
xData1 = geometry[0, 1, y]
xData2 = geometry[0, 2, y]
xData3 = geometry[0, 3, y]
anglesData = geometry[0, 4, y]
for x in range(0, numCols):
if scoresData[x] < args['min_confidence']:
continue
(offsetX, offsetY) = (x * 4.0, y * 4.0)
angle = anglesData[x]
cos = np.cos(angle)
sin = np.sin(angle)
h = xData0[x] + xData2[x]
w = xData1[x] + xData3[x]
endX = int(offsetX + (cos * xData1[x]) + (sin * xData2[x]))
endY = int(offsetY - (sin * xData1[x]) + (cos * xData2[x]))
startX = int(endX - w)
startY = int(endY - h)
rects.append((startX, startY, endX, endY))
confidences.append(scoresData[x])
boxes = non_max_suppression(np.array(rects), probs=confidences)
for (startX, startY, endX, endY) in boxes:
startX = int(startX * rW)
startY = int(startY * rH)
endX = int(endX * rW)
endY = int(endY * rH)
cv2.rectangle(orig, (startX, startY), (endX, endY), (0, 255, 0), 2)
cv2.imshow('Text Detection', orig)
cv2.waitKey(0)
|
[
"korea7030@naver.com"
] |
korea7030@naver.com
|
564f224574f406c1a966ab5582a316627e5a9ae1
|
2cfa657fd119a23de2a5c2ae6d55e6d2516bae2d
|
/test/functional/wallet_keypool_topup.py
|
1c1aa4fe3a776fdc70d840768a3b9deacdbccf53
|
[
"MIT"
] |
permissive
|
vivuscoin/vivuscoin
|
640b10ae3a72c03b501e03b07caae09ce6c87c81
|
ba0db89712234bf68b2d6b63ef2c420d65c7c25d
|
refs/heads/master
| 2023-05-07T06:26:26.241247 | 2021-05-25T03:54:32 | 2021-05-25T03:54:32 | 362,198,076 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,779 |
py
|
#!/usr/bin/env python3
# Copyright (c) 2017-2018 The Bitcoin Core developers
# Copyright (c) 2021 The Vivuscoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test HD Wallet keypool restore function.
Two nodes. Node1 is under test. Node0 is providing transactions and generating blocks.
- Start node1, shutdown and backup wallet.
- Generate 110 keys (enough to drain the keypool). Store key 90 (in the initial keypool) and key 110 (beyond the initial keypool). Send funds to key 90 and key 110.
- Stop node1, clear the datadir, move wallet file back into the datadir and restart node1.
- connect node1 to node0. Verify that they sync and node1 receives its funds."""
import os
import shutil
from test_framework.test_framework import VivuscoinTestFramework
from test_framework.util import (
assert_equal,
connect_nodes_bi,
sync_blocks,
)
class KeypoolRestoreTest(VivuscoinTestFramework):
def set_test_params(self):
self.setup_clean_chain = True
self.num_nodes = 4
self.extra_args = [[], ['-keypool=100'], ['-keypool=100'], ['-keypool=100']]
def skip_test_if_missing_module(self):
self.skip_if_no_wallet()
def run_test(self):
wallet_path = os.path.join(self.nodes[1].datadir, "regtest", "wallets", "wallet.dat")
wallet_backup_path = os.path.join(self.nodes[1].datadir, "wallet.bak")
self.nodes[0].generate(101)
self.log.info("Make backup of wallet")
self.stop_node(1)
shutil.copyfile(wallet_path, wallet_backup_path)
self.start_node(1, self.extra_args[1])
connect_nodes_bi(self.nodes, 0, 1)
connect_nodes_bi(self.nodes, 0, 2)
connect_nodes_bi(self.nodes, 0, 3)
for i, output_type in enumerate(["legacy", "p2sh-segwit", "bech32"]):
self.log.info("Generate keys for wallet with address type: {}".format(output_type))
idx = i+1
for _ in range(90):
addr_oldpool = self.nodes[idx].getnewaddress(address_type=output_type)
for _ in range(20):
addr_extpool = self.nodes[idx].getnewaddress(address_type=output_type)
# Make sure we're creating the outputs we expect
address_details = self.nodes[idx].validateaddress(addr_extpool)
if i == 0:
assert(not address_details["isscript"] and not address_details["iswitness"])
elif i == 1:
assert(address_details["isscript"] and not address_details["iswitness"])
else:
assert(not address_details["isscript"] and address_details["iswitness"])
self.log.info("Send funds to wallet")
self.nodes[0].sendtoaddress(addr_oldpool, 10)
self.nodes[0].generate(1)
self.nodes[0].sendtoaddress(addr_extpool, 5)
self.nodes[0].generate(1)
sync_blocks(self.nodes)
self.log.info("Restart node with wallet backup")
self.stop_node(idx)
shutil.copyfile(wallet_backup_path, wallet_path)
self.start_node(idx, self.extra_args[idx])
connect_nodes_bi(self.nodes, 0, idx)
self.sync_all()
self.log.info("Verify keypool is restored and balance is correct")
assert_equal(self.nodes[idx].getbalance(), 15)
assert_equal(self.nodes[idx].listtransactions()[0]['category'], "receive")
# Check that we have marked all keys up to the used keypool key as used
assert_equal(self.nodes[idx].getaddressinfo(self.nodes[idx].getnewaddress())['hdkeypath'], "m/0'/0'/110'")
if __name__ == '__main__':
KeypoolRestoreTest().main()
|
[
"support@vivuscoin.com"
] |
support@vivuscoin.com
|
36ef3a599bd8eeffa53ece08e08283a8b626e2f6
|
29a0ce2e17aa6a092d3c5bae2da9a3a4fcd7fd22
|
/pandas_practice/basic5.5_clean.py
|
0b15b414ec7a4ed81aeffe658385351a63fed922
|
[] |
no_license
|
varun0308/python_practice
|
0a94c7c5789665e6f930166a424499647b83ba55
|
6badc59b871b610ef407054128bc1ed482ec148f
|
refs/heads/main
| 2023-08-25T12:56:22.404006 | 2021-10-02T13:59:47 | 2021-10-02T13:59:47 | 330,429,476 | 0 | 0 | null | 2021-01-20T09:22:17 | 2021-01-17T16:02:00 |
Python
|
UTF-8
|
Python
| false | false | 380 |
py
|
import pandas as pd
df = pd.read_csv('D:\Varun\python_practice\pandas_practice\dirtydata.csv')
print(df.head())
# We can drop any unwanted column as
df1 = df.drop(['Calories'], axis = 1) # Or axis = 1
print(df.head())
# We can concatinate 2 dataframe, column-wise or row-wise
df2 = pd.concat([df1,df['Calories']], axis = 1) # Or axis = 0 for row concatination
print(df2.head())
|
[
"varunsathish038@gmail.com"
] |
varunsathish038@gmail.com
|
12554a6f358810f3d7bcf732d99807639d1b65bf
|
22ebdd6881730a9474ede8e8167c615990c4e275
|
/prob17a.py
|
e5cae5301008b8a21864cb95ac76154a72222942
|
[] |
no_license
|
MMohan1/eueler
|
a96a465b265334b03645f2e2bb66c85395c54e75
|
05a88f1c9b41fbc3d6bcd95b38b83a6510b3b50a
|
refs/heads/master
| 2021-01-18T15:14:35.320214 | 2015-02-02T11:02:06 | 2015-02-02T11:02:06 | 15,935,991 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 840 |
py
|
def prob17():
list1=[]
total_char=0
dict1={0:'',1:'one',2:'two',3:'three',4:'four',5:'five',6:'six',7:'seven',8:'eight',9:'nine',10:'ten'}
dict2={11:'eleven',12:'twelve',13:'thirteen',14:'fourteen',15:'fifteen',16:'sixteen',17:'seventeen',18:'eighteen',19:'nineteen'}
dict3={0:'',1:'ten',2:'twenty',3:'thirty',4:'fourty',5:'fifty',6:'sixty',7:'seventy',8:'eighty',9:'ninty'}
for i in range(1,100):
x=str(i)
if len(x) == 1:
list1.append(dict1[i])
elif len(x) == 2 and x[1] == '0':
list1.append(dict3[int(x[0])])
elif len(x) == 2 and x[0] == '1':
list1.append(dict2[i])
elif len(x) == 2:
list1.append(dict3[int(x[0])]+dict1[int(x[1])])
p = sum([len(i) for i in list1])
print list1,p
k = 3*((13*99)+p) + 3*((14*99)+p) + 3*((15*99)+p) + len('onethousand') + p + 99
print k
if __name__ == '__main__':
prob17()
|
[
"manmohansharma987@gmail.com"
] |
manmohansharma987@gmail.com
|
caef2901988d4c4ef7134aa4f7bd5d6bc5e027cf
|
e180e68c468557b186d083869c005c98abdf539a
|
/Testing Hardcoded format/test12.py
|
45c8d0b0c94ebea29eb0ddab7264b94cf3c404aa
|
[] |
no_license
|
singhalshubh/Notification-system-Testing-using-selenium
|
8a58977d7d63c1216e420363f408826e9bfccf7a
|
e460e7ceeb63e5eea9a914be0ed84febaebe47c7
|
refs/heads/master
| 2020-03-21T21:33:03.046748 | 2020-01-17T09:53:24 | 2020-01-17T09:53:24 | 139,069,652 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,514 |
py
|
__author__= 'shubh'
import unittest
from selenium import webdriver
class signup(unittest.TestCase):
def setUp(self):
self.driver = webdriver.Firefox()
def test_unsubscribe_community(self):
user ="raghav"
pwd= "sha123#56su"
driver = webdriver.Firefox()
driver.maximize_window() #For maximizing window
driver.implicitly_wait(20) #gives an implicit wait for 20 seconds
driver.get("http://127.0.0.1:8000/")
driver.find_element_by_xpath('//a [@href="/login/?next=/"]').click()
driver.get("http://localhost:8000/login/?next=/")
elem = driver.find_element_by_id("id_username")
elem.send_keys(user)
elem = driver.find_element_by_id("id_password")
elem.send_keys(pwd)
driver.find_element_by_class_name('btn-block').click()
driver.find_element_by_xpath('//a [@href="/communities/"]').click()
driver.find_element_by_xpath('//a [@href="/community-view/1/"]').click()
driver.find_element_by_id("join-us").click()
driver.find_element_by_xpath('//a [@href="/logout/"]').click()
driver.get("http://127.0.0.1:8000/")
user ="shubh"
pwd= "sha123#56su"
driver.find_element_by_xpath('//a [@href="/login/?next=/"]').click()
driver.get("http://localhost:8000/login/?next=/")
elem = driver.find_element_by_id("id_username")
elem.send_keys(user)
elem = driver.find_element_by_id("id_password")
elem.send_keys(pwd)
driver.find_element_by_class_name('btn-block').click()
driver.find_element_by_xpath('//a [@href="/communities/"]').click()
driver.find_element_by_xpath('//a [@href="/community-view/2/"]').click()
driver.find_element_by_xpath('//a [@href="/manage_community/2/"]').click()
name = "raghav"
Role = "author"
elem = driver.find_element_by_id("username")
elem.send_keys(name)
elem = driver.find_element_by_id("role")
elem.send_keys(Role)
#specify the class
driver.find_element_by_class_name('btn-block').click()
driver.find_element_by_xpath('//a [@href="/logout/"]').click()
driver.get("http://127.0.0.1:8000/")
user ="raghav"
pwd= "sha123#56su"
driver.find_element_by_xpath('//a [@href="/login/?next=/"]').click()
driver.get("http://localhost:8000/login/?next=/")
elem = driver.find_element_by_id("id_username")
elem.send_keys(user)
elem = driver.find_element_by_id("id_password")
elem.send_keys(pwd)
driver.find_element_by_class_name('btn-block').click()
driver.find_element_by_xpath('//a [@href="/notifications/"]').click()
def tearDown(self):
self.driver.quit()
if __name__ == '__main__':
unittest.main()
|
[
"noreply@github.com"
] |
singhalshubh.noreply@github.com
|
dada702324b30a4d4a00d067c7b3c97d8b05129b
|
b8ef1a5cd3856a8e9134c3313a4e23522f199df7
|
/Baekjoon/1966_프린터 큐/1966_프린터 큐.py
|
73d38dbd9d6bdf4902738765108954a7e7151128
|
[] |
no_license
|
scl2589/Algorithm_problem_solving
|
910623d9675ae0219320abfd1fefc7d576027544
|
80db697cdd0180a7d4dbcfae4944d4a54191bddf
|
refs/heads/master
| 2023-07-29T10:56:38.225206 | 2021-09-11T13:50:46 | 2021-09-11T13:50:46 | 235,363,353 | 0 | 0 | null | 2021-03-04T15:39:41 | 2020-01-21T14:36:41 |
Python
|
UTF-8
|
Python
| false | false | 548 |
py
|
from collections import deque
tc = int(input())
for _ in range(tc):
N, M = map(int, input().split())
impt = list(map(int, input().split()))
q = deque()
for idx, value in enumerate(impt):
q.append([idx, value])
count = 0
while True:
max_num = sorted(q, key = lambda x: x[1], reverse=True)[0][1]
num = q.popleft()
if num[0] == M and num[1] == max_num:
break
elif num[1] == max_num:
count += 1
else:
q.append(num)
print(count + 1)
|
[
"chaelinshin96@gmail.com"
] |
chaelinshin96@gmail.com
|
eabdc4dfe6fbd29641364cd7beabe54e1c5611c7
|
49facbcd74c2ca6adbca447a45e30a4190b35bc7
|
/EMAN2/2.06/lib/emitem3d.py
|
4fb979d45e44e783786926fe49428f77efc44768
|
[] |
no_license
|
CVL-dev/StructuralBiology
|
801c37bfa5664e74c36f9f97478d59016f1f61fc
|
1f1eaa42ae565c2032e245c6a874c8439d2719b9
|
refs/heads/master
| 2023-02-25T10:28:00.700774 | 2013-03-02T08:29:43 | 2013-03-02T08:29:43 | 5,609,380 | 2 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 39,273 |
py
|
#!/usr/local/eman/2.06/Python/bin/python
# Copyright (c) 2011- Baylor College of Medicine
#
# This software is issued under a joint BSD/GNU license. You may use the
# source code in this file under either license. However, note that the
# complete EMAN2 and SPARX software packages have some GPL dependencies,
# so you are responsible for compliance with the licenses of these packages
# if you opt to use BSD licensing. The warranty disclaimer below holds
# in either instance.
#
# This complete copyright notice must be included in any revised version of the
# source code. Additional authorship citations may be added, but existing
# author citations must be preserved.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston MA 02111-1307 USA
#
#
from OpenGL import GL
from PyQt4 import QtCore, QtGui
from EMAN2 import Transform, Vec4f, Vec3f
from libpyGLUtils2 import GLUtil
from valslider import ValSlider, EMSpinWidget
import weakref
import math
import numpy
class EMVertexBuffers(object):
""" Class to hold vertex buffers """
vbuffers = []
numbuffers = 2
@staticmethod
def getBuffers():
if not len(EMVertexBuffers.vbuffers):
EMVertexBuffers.vbuffers = GL.glGenBuffers(EMVertexBuffers.numbuffers)
return EMVertexBuffers.vbuffers
def drawBoundingBox(width, height, depth):
""" Draw bounding box use C side for easy of vertex arrays """
GL.glPushAttrib(GL.GL_LIGHTING_BIT)
GL.glMaterialfv(GL.GL_FRONT, GL.GL_EMISSION, [1.0,1.0,1.0,1.0])
GLUtil.glDrawBoundingBox(width, height, depth)
GL.glPopAttrib()
class EMItem3D(object): #inherit object for new-style class (new-stype classes required for super() and Python properties)
"""
The base class for nodes in our scene graph, which is used in our 3D scene viewer.
In our case, the scene graph is a tree data structure.
"""
# Class attrib to connect openGL int identifiers to class instances
vbuffers = 0
selection_idx_dict = {}
selection_recycle = []
selection_intname = -1
name = "General 3D Item"
nodetype = "BaseNode"
@staticmethod
def get_transformlayout(layout, idx, attribdict):
"""
Adds a transform layout to a dialog
@param layout, the layout to append to
@param idx, the row to being appnding to
"""
font = QtGui.QFont()
font.setBold(True)
translatelabel = QtGui.QLabel("Translation")
translatelabel.setFont(font)
translatelabel.setAlignment(QtCore.Qt.AlignCenter)
layout.addWidget(translatelabel, idx, 0, 1, 4)
txlabel = QtGui.QLabel("Tx")
tylabel = QtGui.QLabel("Ty")
txlabel.setAlignment(QtCore.Qt.AlignRight)
tylabel.setAlignment(QtCore.Qt.AlignRight)
attribdict["tx"] = QtGui.QLineEdit("0.0")
attribdict["ty"] = QtGui.QLineEdit("0.0")
attribdict["tx"].setMinimumWidth(100.0)
attribdict["ty"].setMinimumWidth(100.0)
layout.addWidget(txlabel, idx+1, 0, 1, 1)
layout.addWidget(attribdict["tx"], idx+1, 1, 1, 1)
layout.addWidget(tylabel, idx+1, 2, 1, 1)
layout.addWidget(attribdict["ty"], idx+1, 3, 1, 1)
tzlabel = QtGui.QLabel("Tz")
zoomlabel = QtGui.QLabel("Zm")
tylabel.setAlignment(QtCore.Qt.AlignRight)
zoomlabel.setAlignment(QtCore.Qt.AlignRight)
attribdict["tz"] = QtGui.QLineEdit("0.0")
attribdict["zoom"] = QtGui.QLineEdit("1.0")
attribdict["tz"].setMinimumWidth(100.0)
attribdict["zoom"].setMinimumWidth(100.0)
layout.addWidget(tzlabel, idx+2, 0, 1, 1)
layout.addWidget(attribdict["tz"], idx+2, 1, 1, 1)
layout.addWidget(zoomlabel, idx+2, 2, 1, 1)
layout.addWidget(attribdict["zoom"], idx+2, 3, 1, 1)
rotatelabel = QtGui.QLabel("EMAN Rotation")
rotatelabel.setFont(font)
rotatelabel.setAlignment(QtCore.Qt.AlignCenter)
layout.addWidget(rotatelabel, idx+3, 0, 1, 4)
azlabel = QtGui.QLabel("Az")
azlabel.setAlignment(QtCore.Qt.AlignRight)
attribdict["az"] = QtGui.QLineEdit("0.0")
altlabel = QtGui.QLabel("Alt")
altlabel.setAlignment(QtCore.Qt.AlignRight)
attribdict["alt"] = QtGui.QLineEdit("0.0")
attribdict["az"] .setMinimumWidth(100.0)
attribdict["alt"].setMinimumWidth(100.0)
layout.addWidget(azlabel, idx+4, 0, 1, 1)
layout.addWidget(attribdict["az"], idx+4, 1, 1, 1)
layout.addWidget(altlabel, idx+4, 2, 1, 1)
layout.addWidget(attribdict["alt"], idx+4, 3, 1, 1)
philabel = QtGui.QLabel("Phi")
philabel.setAlignment(QtCore.Qt.AlignRight)
attribdict["phi"] = QtGui.QLineEdit("0.0")
layout.addWidget(philabel, idx+5, 0, 1, 1)
layout.addWidget(attribdict["phi"], idx+5, 1, 1, 1)
@staticmethod
def getTransformFromDict(attribdict):
""" Return a transform using a dict created using the above function"""
return Transform({"type":"eman","az":float(attribdict["az"].text()),"alt":float(attribdict["alt"].text()),"phi":float(attribdict["phi"].text()),"tx":float(attribdict["tx"].text()),"ty":float(attribdict["ty"].text()),"tz":float(attribdict["tz"].text()),"scale":float(attribdict["zoom"].text())})
@staticmethod
def getNodeDialogWidget(attribdict):
"""
Get Data Widget
"""
nodewidget = QtGui.QWidget()
grid = QtGui.QGridLayout()
node_name_label = QtGui.QLabel("Node Name")
attribdict["node_name"] = QtGui.QLineEdit()
grid.addWidget(node_name_label , 0, 0, 1, 2)
grid.addWidget(attribdict["node_name"], 0, 2, 1, 2)
EMItem3D.get_transformlayout(grid, 2, attribdict)
nodewidget.setLayout(grid)
return nodewidget
@staticmethod
def getNodeForDialog(attribdict):
"""
Create a new node using a attribdict
"""
return EMItem3D(attribdict["parent"], transform=EMItem3D.getTransformFromDict(attribdict))
def __init__(self, parent = None, children = [], transform=None):
"""
@type parent: EMItem3D
@param parent: the parent node to the current node or None for the root node
@type children: list
@param children: the child nodes
@type transform: Transform or None
@param transform: The transformation (rotation, scaling, translation) that should be applied before rendering this node and its children
"""
self.label = None # Customisabl label, used to label the inspector in the tree
self.setParent(parent)
self.setChildren(children)
if not transform: transform = Transform()
self.transform = transform
self.is_visible = True
self.is_selected = False
self.hide_selection = False
self.item_inspector = None # This is an inspector widget
self.EMQTreeWidgetItem = None # This is an inspector tree item
self.boundingboxsize = None
self.getAndSetUniqueInteger()
def getChildren(self): return self.children
def setChildren(self, children):
self.children = list(children)
for child in children:
child.parent = self
def getParent(self): return self.parent
def setParent(self, parent):
self.parent = parent
#if parent: # Why is this here is causes chaos b/c things get added twice. You can only implment this if you check to ensure self is not already a child of parent!
#parent.addChild(self)
def isSelectedItem(self): return self.is_selected
def setSelectedItem(self, is_selected): self.is_selected = is_selected
def isSelectionHidded(self): return self.hide_selection
def getHiddenSelected(self): return self.hide_selection
def setHiddenSelected(self, hide_selection): self.hide_selection = hide_selection
def getTransform(self): return self.transform
def setTransform(self, transform): self.transform = transform
def isVisibleItem(self): return self.is_visible
def setVisibleItem(self, is_visible): self.is_visible = is_visible
def setLabel(self, label): self.label = label
def getLabel(self): return self.label
def __del__(self):
EMItem3D.selection_recycle.append(self.intname)
def getEvalString(self):
"""
Retrun a string that after eval can reinstatiate the object
"""
return "EMItem3D()"
def getAndSetUniqueInteger(self):
"""
Stuff for the selection mechanism, return a unique int for each instance of EMItem3D
"""
if len(EMItem3D.selection_recycle) > 0:
self.intname = EMItem3D.selection_recycle.pop()
else:
EMItem3D.selection_intname += 1
self.intname = EMItem3D.selection_intname
EMItem3D.selection_idx_dict[self.intname] = weakref.ref(self)
def addChild(self, node):
"""
Adds a child node, if not already in the list of child nodes.
@type node: EMItem3D
@param node: the child node to add
"""
self.children.append(node)
node.parent = self
def insertChild(self, node, nodeindex):
"""
Inserts a child node, if not already in the list of child nodes.
@type node: EMItem3D
@param node: the child node to add
@param nodeindex: the index for insertion
"""
self.children.insert(nodeindex, node)
node.parent = self
def addChildren(self, nodes):
"""
Adds all the provided child nodes which are not already in the list of child nodes.
@type nodes: an iterable collection of EMItem3D (or subclass) objects
@param nodes: the nodes which will be added as child nodes
"""
for node in nodes:
if not node in self.children:
self.children.append(node)
node.parent = self
def hasChild(self, node):
"""
Tests whether the supplied node is a child of the current node.
@type node: EMItem3D
@param node: test whether this node is a child node of self
"""
return node in self.children
def getChildIndex(self, node):
"""
Returns the index of child in the list of children. Raises an execption if not found
"""
return self.children.index(node)
def displayTree(self, level = 1):
"""
This prints a representation of the subtree rooted at this node to standard output. Useful for debugging.
"""
indent = "\t"*(level-1)
marker = "<-->" if self.parent else "-->"
print indent, marker, self.intname
for child in self.children:
child.displayTree(level+1)
def addParentReferences(self):
"""
For the subtree rooted at self, give each child node a reference to its parent node.
"""
for child in self.children:
child.parent = self
child.addParentReferences()
def removeParentReferences(self):
"""
For the subtree rooted at self, break reference cycles by setting self.parent to None.
"""
self.parent = None
for child in self.children:
child.removeParentReferences()
def removeChild(self, node):
"""
Remove the supplied node from the list of child nodes This also removes all its descendant nodes.
@type node: EMItem3D
@param node: the node to remove
"""
if node in self.children:
node.removeParentReferences()
while node in self.children: #In case a duplicate got in, somehow
self.children.remove(node)
def getSelectedAncestorNodes(self):
"""
Return a list of selected node ancestors
"""
selected_ancestors = []
node = self
while node.parent:
if node.parent.is_selected:
selected_ancestors.append(node.parent)
node = node.parent
return selected_ancestors
def getRootNode(self):
"""
Returns the root node
"""
node = self
while node.parent:
node = node.parent
return node
def getAllSelectedNodes(self):
"""
For the tree rooted at self, this recursive method returns a list of all the selected nodes.
@return: a list of selected nodes
"""
selected_list = []
if self.is_selected:
selected_list.append(self)
for child in self.children: #Recursion ends on leaf nodes here
selected_list.extend(child.getAllSelectedNodes()) #Recursion
return selected_list
def getAllNodes(self):
"""
For the tree rooted at self, this recursive method returns a list of all the nodes.
@return: a list of selected nodes
"""
nodelist = []
nodelist.append(self)
for child in self.children: #Recursion ends on leaf nodes here
nodelist.extend(child.getAllNodes()) #Recursion
return nodelist
def getNearbySelectedNodes(self):
"""
For the tree rooted at self, this recursive method returns a list of the selected nodes that are near self.
A selected node will not be in the returned list if one of its ancestor nodes is also selected.
@return: a list of selected nodes
"""
selected_list = []
if self.is_selected:
return [self]
else:
for child in self.children:
selected_list.extend(child.getNearbySelectedNodes())
return selected_list
def getDistantSelectedNodes(self):
"""
For the tree rooted at self, this recursive method returns a list of the selected nodes that are distant from self.
A selected node will not be in the returned list if one of its descendant nodes is also selected.
@return: a list of selected nodes
"""
selected_list = []
for child in self.children:
selected_list.extend(child.getDistantSelectedNodes())
if not selected_list: #either this is a leaf node, or there are no selected nodes in the child subtrees
if self.is_selected:
selected_list.append(self)
return selected_list
def getItemInspector(self):
"""
Return a Qt widget that controls the scene item
"""
if not self.item_inspector: self.item_inspector = EMItem3DInspector("Node", self)
return self.item_inspector
def setEMQTreeWidgetItem(self, node):
"""
Relate a QtreeItem to this node
"""
self.EMQTreeWidgetItem = node
def getTransformStdCoord(self):
"""
This returns the transform in standard coordinate system, not one changed by7 parent matrices
"""
tt = t = self.transform
tp = self.getParentMatrixProduct()
if tp: tt = tp*t
return tt
def getParentMatrixProduct(self):
"""
Get the product of all parent matrices
This is a recursive function
"""
if self.parent:
if self.parent.getParentMatrixProduct():
return self.parent.getParentMatrixProduct()*self.parent.getTransform()
else:
return self.parent.getTransform()
else:
return None
def updateMatrices(self, params, xformtype):
"""
The matrcies are updated in such a way that each is done in the standard cooridnate system and the std coord system is not perturbed by the others
@type params: List
@param params: A list defining how the transform in each active node is modified
@type xfromtype: sting
@param xformtype: The sort of transform we wish to do
"""
if self.is_selected:
if xformtype == "rotate":
if self.parent:
self.transform.rotate_origin_newbasis(self.getParentMatrixProduct(), params[0], params[1], params[2], params[3])
else:
self.transform.rotate_origin(Transform({"type":"spin","Omega":params[0],"n1":params[1],"n2":params[2],"n3":params[3]}))
elif xformtype == "translate":
if self.parent:
self.transform.translate_newbasis(self.getParentMatrixProduct(), params[0], params[1], params[2])
else:
self.transform.translate(params[0], params[1], params[2])
elif xformtype == "scale":
self.transform.scale(params[0])
else:
raise Exception,"Invalid transformation type"
# Now tell all children to update
# TODO: we MIGHT want to get rid of the recursive part of this algorithm
# instead, the calling function would get a list of all selected nodes, and apply transformations to each
for child in self.children:
child.updateMatrices(params, xformtype) #Note: the transformation is only applied to SELECTED nodes
def getItemDictionary(self):
"""
Return a dictionary of item parameters (used for restoring sessions
"""
return {"TRANSFORMATION":self.transform.get_params("eman"),"CONSTRUCTOR":self.getEvalString(),"NAME":str(self.getLabel()),"VISIBLE":self.isVisibleItem(),"SELECTED":self.isSelectedItem(),"NODETYPE":self.nodetype,"HIDDENSEL":self.getHiddenSelected()}
def setUsingDictionary(self, dictionary):
"""
Set item attributes using a dictionary, used in session restoration
"""
self.setTransform(Transform(dictionary["TRANSFORMATION"]))
self.setVisibleItem(dictionary["VISIBLE"])
self.setSelectedItem(dictionary["SELECTED"])
try:
self.setHiddenSelected(dictionary["HIDDENSEL"])
except:
pass
self.setLabel(dictionary["NAME"])
def render(self):
"""
This is the method to call to render the node and its child nodes.
It calls self.renderNode() to render the current node.
Usually, this method is unchanged in subclasses.
"""
if not self.is_visible:
return #Also applies to subtree rooted at this node
if self.transform.is_identity():
GL.glPushName(self.intname)
self.renderNode()
for child in self.children:
child.render()
GL.glPopName()
else:
GL.glPushMatrix()
GL.glPushName(self.intname)
GLUtil.glMultMatrix(self.transform) #apply the transformation
self.renderNode()
for child in self.children:
child.render()
GL.glPopName()
GL.glPopMatrix()
if self.item_inspector != None and self.is_selected:
self.item_inspector.updateItemControls()
def renderNode(self):
"""
This method, which is called by self.render(), renders the current node.
It should be implemented in subclasses that represent visible objects.
"""
pass
def keyPressEvent(self, event): pass
def keyReleaseEvent(self, event): pass
def mouseDoubleClickEvent(self, event): pass
def mouseMoveEvent(self, event): pass
def mousePressEvent(self, event): pass
def mouseReleaseEvent(self, event): pass
def wheelEvent(self, event): pass
class EMItem3DInspector(QtGui.QTabWidget):
"""
Class to make the EMItem GUI controls
"""
def __init__(self, name, item3d):
QtGui.QTabWidget.__init__(self)
self.item3d = weakref.ref(item3d)
self.name = name
self.inspector = None
self.transfromboxmaxheight = 400 # This might be problematic
self.addTabs()
def setInspector(self, inspector):
""" This is a reference back to the main inspector, which holds all the item inspectors"""
self.inspector = weakref.ref(inspector)
def addTabs(self):
""" Add a tab for each 'column' """
tabwidget = QtGui.QWidget()
gridbox = QtGui.QGridLayout()
EMItem3DInspector.addControls(self, gridbox)
tabwidget.setLayout(gridbox)
self.addTab(tabwidget, "basic")
def addControls(self, gridbox):
""" Construct all the widgets in this Item Inspector """
# selection box and label
font = QtGui.QFont()
font.setBold(True)
label = QtGui.QLabel(self.name,self)
label.setFont(font)
label.setAlignment(QtCore.Qt.AlignCenter)
gridbox.addWidget(label, 0, 0, 1, 1)
databox = QtGui.QHBoxLayout()
self.boundingbox = None
if self.item3d().boundingboxsize:
self.boundingbox = QtGui.QLabel("Size: "+self.item3d().boundingboxsize,self)
databox.addWidget(self.boundingbox)
gridbox.addLayout(databox, 1, 0, 1, 1)
# angluar controls
xformframe = QtGui.QFrame()
xformframe.setFrameShape(QtGui.QFrame.StyledPanel)
xformbox = QtGui.QGridLayout()
xformlabel = QtGui.QLabel("Transformation", xformframe)
xformlabel.setFont(font)
xformlabel.setAlignment(QtCore.Qt.AlignCenter)
xformbox.addWidget(xformlabel, 0, 0, 1, 2)
# Rotations
self.rotcombobox = QtGui.QComboBox()
xformbox.addWidget(self.rotcombobox, 1, 0, 1, 2)
self.rotstackedwidget = QtGui.QStackedWidget()
self.addRotationWidgets()
xformbox.addWidget(self.rotstackedwidget, 2, 0, 1, 2)
#translations
txlabel = QtGui.QLabel("TX",xformframe)
txlabel.setAlignment(QtCore.Qt.AlignCenter)
xformbox.addWidget(txlabel, 3, 0, 1, 1)
tylabel = QtGui.QLabel("TY",xformframe)
tylabel.setAlignment(QtCore.Qt.AlignCenter)
xformbox.addWidget(tylabel, 3, 1, 1, 1)
self.tx = EMSpinWidget(0.0, 1.0)
self.ty = EMSpinWidget(0.0, 1.0)
xformbox.addWidget(self.tx, 4, 0, 1, 1)
xformbox.addWidget(self.ty, 4, 1, 1, 1)
tzlabel = QtGui.QLabel("TZ",xformframe)
tzlabel.setAlignment(QtCore.Qt.AlignCenter)
xformbox.addWidget(tzlabel, 5, 0, 1, 1)
zoomlabel = QtGui.QLabel("Zoom",xformframe)
zoomlabel.setAlignment(QtCore.Qt.AlignCenter)
xformbox.addWidget(zoomlabel, 5, 1, 1, 1)
self.tz = EMSpinWidget(0.0, 1.0)
self.zoom = EMSpinWidget(1.0, 0.1, postivemode=True, wheelstep=0.1)
xformbox.addWidget(self.tz, 6, 0, 1, 1)
xformbox.addWidget(self.zoom, 6, 1, 1, 1)
self.resetbuttontx = QtGui.QPushButton("Reset Tx")
self.resetbuttonrot = QtGui.QPushButton("Reset Rot")
xformbox.addWidget(self.resetbuttontx, 7, 0, 1, 1)
xformbox.addWidget(self.resetbuttonrot, 7, 1, 1, 1)
xformframe.setLayout(xformbox)
xformframe.setMaximumWidth(350)
xformframe.setMaximumHeight(self.transfromboxmaxheight)
xformframe.setLayout(xformbox)
gridbox.addWidget(xformframe, 2, 0, 1, 1)
# set to default, but run only as a base class
if type(self) == EMItem3DInspector: self.updateItemControls()
QtCore.QObject.connect(self.tx,QtCore.SIGNAL("valueChanged(int)"),self._on_translation)
QtCore.QObject.connect(self.ty,QtCore.SIGNAL("valueChanged(int)"),self._on_translation)
QtCore.QObject.connect(self.tz,QtCore.SIGNAL("valueChanged(int)"),self._on_translation)
QtCore.QObject.connect(self.zoom,QtCore.SIGNAL("valueChanged(int)"),self._on_scale)
QtCore.QObject.connect(self.resetbuttontx,QtCore.SIGNAL("clicked()"),self._on_resettx)
QtCore.QObject.connect(self.resetbuttonrot,QtCore.SIGNAL("clicked()"),self._on_resetrot)
def _on_translation(self, value):
"""
Need to contain the right coords. And do translation in the correct corrd system
"""
tt = t = Transform({"tx":self.tx.getValue(),"ty":self.ty.getValue(),"tz":self.tz.getValue()})
tp = self.item3d().getParentMatrixProduct()
if tp: tt = tp.inverse()*t
self.item3d().getTransform().set_trans(tt.get_trans())
self.inspector().updateSceneGraph()
def _on_scale(self, value):
self.item3d().getTransform().set_scale(self.zoom.getValue())
self.inspector().updateSceneGraph()
def _on_resettx(self):
self.item3d().getTransform().set_trans(0.0, 0.0, 0.0)
self.updateItemControls()
self.inspector().updateSceneGraph()
def _on_resetrot(self):
self.item3d().getTransform().set_rotation({"type":"eman","az":0.0,"alt":0.0,"phi":0.0})
self.updateItemControls()
self.inspector().updateSceneGraph()
def _isRotNaN(self, rot1, rot2, rot3):
""" Better check to make sure get_rotation did not return Nan, so to prevent a crash """
if rot1 != rot1: return True
if rot2 != rot2: return True
if rot3 != rot3: return True
return False
def updateItemControls(self):
""" Updates this item inspector. Function is called by the item it observes"""
# Translation update
stdtransfrom = self.item3d().getTransformStdCoord()
translation = stdtransfrom.get_trans()
self.tx.setValue(translation[0])
self.ty.setValue(translation[1])
self.tz.setValue(translation[2])
# Rotation update
rotation = stdtransfrom.get_rotation(str(self.rotcombobox.currentText()))
is_identity = stdtransfrom.is_rot_identity()
comboboxidx = self.rotcombobox.currentIndex()
if comboboxidx == 0:
if self._isRotNaN(rotation["az"],rotation["alt"],rotation["phi"]): return
self.emanazslider.setValue(rotation["az"], quiet=1)
self.emanaltslider.setValue(rotation["alt"], quiet=1)
self.emanphislider.setValue(rotation["phi"], quiet=1)
if comboboxidx == 1:
if self._isRotNaN(rotation["gamma"],rotation["beta"],rotation["alpha"]): return
self.imagicgammaslider.setValue(rotation["gamma"], quiet=1)
self.imagicbetaslider.setValue(rotation["beta"], quiet=1)
self.imagicalphaslider.setValue(rotation["alpha"], quiet=1)
if comboboxidx == 2:
if self._isRotNaN(rotation["psi"],rotation["theta"],rotation["phi"]): return
self.spiderpsislider.setValue(rotation["psi"], quiet=1)
self.spiderthetaslider.setValue(rotation["theta"], quiet=1)
self.spiderphislider.setValue(rotation["phi"], quiet=1)
if comboboxidx == 3:
if self._isRotNaN(rotation["phi"],rotation["theta"],rotation["omega"]): return
self.mrcpsislider.setValue(rotation["phi"], quiet=1)
self.mrcthetaslider.setValue(rotation["theta"], quiet=1)
self.mrcomegaslider.setValue(rotation["omega"], quiet=1)
if comboboxidx == 4:
if self._isRotNaN(rotation["ztilt"],rotation["ytilt"],rotation["xtilt"]): return
self.xyzzslider.setValue(rotation["ztilt"], quiet=1)
self.xyzyslider.setValue(rotation["ytilt"], quiet=1)
self.xyzxslider.setValue(rotation["xtilt"], quiet=1)
if comboboxidx == 5:
if self._isRotNaN(rotation["n1"],rotation["n2"],rotation["n3"]): return
if is_identity and self.spinn1slider.getValue() == 0.0 and self.spinn2slider.getValue() == 0.0 and self.spinn3slider.getValue() == 0.0:
self.spinomegaslider .setValue(0.0, quiet=1)
self.spinn1slider.setValue(0.0, quiet=1)
self.spinn2slider.setValue(0.0, quiet=1)
self.spinn3slider.setValue(1.0, quiet=1)
else:
self.spinomegaslider .setValue(rotation["Omega"], quiet=1)
# Don't change slider if reult is Nan
if rotation["n1"] == rotation["n1"]: self.spinn1slider.setValue(rotation["n1"], quiet=1)
if rotation["n2"] == rotation["n2"]: self.spinn2slider.setValue(rotation["n2"], quiet=1)
if rotation["n3"] == rotation["n3"]: self.spinn3slider.setValue(rotation["n3"], quiet=1)
if comboboxidx == 6:
if self._isRotNaN(rotation["n1"],rotation["n2"],rotation["n3"]): return
if is_identity and self.spinn1slider.getValue() == 0.0 and self.spinn2slider.getValue() == 0.0 and self.spinn3slider.getValue() == 0.0:
self.spinomegaslider.setValue(0.0, quiet=1)
self.sgirotn1slider.setValue(0.0, quiet=1)
self.sgirotn2slider.setValue(0.0, quiet=1)
self.sgirotn3slider.setValue(1.0, quiet=1)
else:
self.spinomegaslider.setValue(rotation["q"], quiet=1)
# Don't change slider if reult is Nan
if rotation["n1"] == rotation["n1"]: self.sgirotn1slider.setValue(rotation["n1"], quiet=1)
if rotation["n2"] == rotation["n2"]: self.sgirotn2slider.setValue(rotation["n2"], quiet=1)
if rotation["n3"] == rotation["n3"]: self.sgirotn3slider.setValue(rotation["n3"], quiet=1)
if comboboxidx == 7:
if self._isRotNaN(rotation["e1"],rotation["e2"],rotation["e3"]): return
if is_identity:
self.quaternione0slider.setValue(1.0, quiet=1)
self.quaternione1slider.setValue(0.0, quiet=1)
self.quaternione2slider.setValue(0.0, quiet=1)
self.quaternione3slider.setValue(0.0, quiet=1)
else:
self.quaternione0slider.setValue(rotation["e0"], quiet=1)
self.quaternione1slider.setValue(rotation["e1"], quiet=1)
self.quaternione2slider.setValue(rotation["e2"], quiet=1)
self.quaternione3slider.setValue(rotation["e3"], quiet=1)
# Scaling update
self.zoom.setValue(self.item3d().getTransform().get_scale())
def updateMetaData(self):
"""
I didn't want to put this in update b/c this data doesn't change very often, and I don't want to waste CPU
Its a judgement call really, less coupling vs. more efficiency
"""
if self.boundingbox: self.boundingbox.setText("Size: "+self.item3d().boundingboxsize)
def addRotationWidgets(self):
""" Add alll the widgets for the various EMAN2 rotation conventions """
EMANwidget = QtGui.QWidget()
Imagicwidget = QtGui.QWidget()
Spiderwidget = QtGui.QWidget()
MRCwidget = QtGui.QWidget()
XYZwidget = QtGui.QWidget()
spinwidget = QtGui.QWidget()
sgirotwidget = QtGui.QWidget()
quaternionwidget = QtGui.QWidget()
# EMAN
emanbox = QtGui.QVBoxLayout()
self.emanazslider = ValSlider(EMANwidget, (0.0, 360.0), " Az", rounding = 1)
self.emanaltslider = ValSlider(EMANwidget, (0.0, 180.0), "Alt", rounding = 1)
self.emanphislider = ValSlider(EMANwidget, (0.0, 360.0), "Phi", rounding = 1)
emanbox.addWidget(self.emanazslider)
emanbox.addWidget(self.emanaltslider)
emanbox.addWidget(self.emanphislider)
EMANwidget.setLayout(emanbox)
# Imagic
imagicbox = QtGui.QVBoxLayout()
self.imagicgammaslider = ValSlider(Imagicwidget, (0.0, 360.0), "Gamma", rounding = 1)
self.imagicbetaslider = ValSlider(Imagicwidget, (0.0, 180.0), " Beta", rounding = 1)
self.imagicalphaslider = ValSlider(Imagicwidget, (0.0, 360.0), " Alpha", rounding = 1)
imagicbox.addWidget(self.imagicgammaslider)
imagicbox.addWidget(self.imagicbetaslider)
imagicbox.addWidget(self.imagicalphaslider)
Imagicwidget.setLayout(imagicbox)
# Spider
spiderbox = QtGui.QVBoxLayout()
self.spiderpsislider = ValSlider(Spiderwidget, (0.0, 360.0), " Psi", rounding = 1)
self.spiderthetaslider = ValSlider(Spiderwidget, (0.0, 180.0), "Theta", rounding = 1)
self.spiderphislider = ValSlider(Spiderwidget, (0.0, 360.0), " Phi", rounding = 1)
spiderbox.addWidget(self.spiderpsislider)
spiderbox.addWidget(self.spiderthetaslider)
spiderbox.addWidget(self.spiderphislider)
Spiderwidget.setLayout(spiderbox)
# MRC
mrcbox = QtGui.QVBoxLayout()
self.mrcpsislider = ValSlider(MRCwidget, (0.0, 360.0), " Psi", rounding = 1)
self.mrcthetaslider = ValSlider(MRCwidget, (0.0, 180.0), " Theta", rounding = 1)
self.mrcomegaslider = ValSlider(MRCwidget, (0.0, 360.0), "Omega", rounding = 1)
mrcbox.addWidget(self.mrcpsislider)
mrcbox.addWidget(self.mrcthetaslider)
mrcbox.addWidget(self.mrcomegaslider)
MRCwidget.setLayout(mrcbox)
# XYZ
xyzbox = QtGui.QVBoxLayout()
self.xyzzslider = ValSlider(XYZwidget, (0.0, 360.0), "Z", rounding = 1)
self.xyzyslider = ValSlider(XYZwidget, (0.0, 180.0), "Y", rounding = 1)
self.xyzxslider = ValSlider(XYZwidget, (0.0, 360.0), "X", rounding = 1)
xyzbox.addWidget(self.xyzzslider)
xyzbox.addWidget(self.xyzyslider)
xyzbox.addWidget(self.xyzxslider)
XYZwidget.setLayout(xyzbox)
# spin
spinbox = QtGui.QVBoxLayout()
self.spinomegaslider = ValSlider(spinwidget, (0.0, 180.0), "Omega", rounding = 1)
self.spinn1slider = ValSlider(spinwidget, (0.0, 1.0), " N1", rounding = 4)
self.spinn2slider = ValSlider(spinwidget, (0.0, 1.0), " N2", rounding = 4)
self.spinn3slider = ValSlider(spinwidget, (0.0, 1.0), " N3", rounding = 4)
spinbox.addWidget(self.spinomegaslider)
spinbox.addWidget(self.spinn1slider)
spinbox.addWidget(self.spinn2slider)
spinbox.addWidget(self.spinn3slider)
spinwidget.setLayout(spinbox)
# sgirot
sgirotbox = QtGui.QVBoxLayout()
self.sgirotqslider = ValSlider(sgirotwidget, (0.0, 180.0), " Q", rounding = 1)
self.sgirotn1slider = ValSlider(sgirotwidget, (0.0, 1.0), "N1", rounding = 4)
self.sgirotn2slider = ValSlider(sgirotwidget, (0.0, 1.0), "N2", rounding = 4)
self.sgirotn3slider = ValSlider(sgirotwidget, (0.0, 1.0), "N3", rounding = 4)
sgirotbox.addWidget(self.sgirotqslider)
sgirotbox.addWidget(self.sgirotn1slider)
sgirotbox.addWidget(self.sgirotn2slider)
sgirotbox.addWidget(self.sgirotn3slider)
sgirotwidget.setLayout(sgirotbox)
# quaternion
quaternionbox = QtGui.QVBoxLayout()
self.quaternione0slider = ValSlider(quaternionwidget, (0.0, 1.0), "E0", rounding = 4)
self.quaternione1slider = ValSlider(quaternionwidget, (0.0, 1.0), "E1", rounding = 4)
self.quaternione2slider = ValSlider(quaternionwidget, (0.0, 1.0), "E2", rounding = 4)
self.quaternione3slider = ValSlider(quaternionwidget, (0.0, 1.0), "E3", rounding = 4)
quaternionbox.addWidget(self.quaternione0slider)
quaternionbox.addWidget(self.quaternione1slider)
quaternionbox.addWidget(self.quaternione2slider)
quaternionbox.addWidget(self.quaternione3slider)
quaternionwidget.setLayout(quaternionbox)
# Add widgets to the stack
self.rotstackedwidget.addWidget(EMANwidget)
self.rotstackedwidget.addWidget(Imagicwidget)
self.rotstackedwidget.addWidget(Spiderwidget)
self.rotstackedwidget.addWidget(MRCwidget)
self.rotstackedwidget.addWidget(XYZwidget)
self.rotstackedwidget.addWidget(spinwidget)
self.rotstackedwidget.addWidget(sgirotwidget)
self.rotstackedwidget.addWidget(quaternionwidget)
# add choices to combobox
self.rotcombobox.addItem("EMAN")
self.rotcombobox.addItem("Imagic")
self.rotcombobox.addItem("Spider")
self.rotcombobox.addItem("MRC")
self.rotcombobox.addItem("XYZ")
self.rotcombobox.addItem("spin")
self.rotcombobox.addItem("sgirot")
self.rotcombobox.addItem("quaternion")
# Signal for all sliders
QtCore.QObject.connect(self.rotcombobox, QtCore.SIGNAL("activated(int)"), self._rotcombobox_changed)
QtCore.QObject.connect(self.emanazslider,QtCore.SIGNAL("valueChanged"),self._on_EMAN_rotation)
QtCore.QObject.connect(self.emanaltslider,QtCore.SIGNAL("valueChanged"),self._on_EMAN_rotation)
QtCore.QObject.connect(self.emanphislider,QtCore.SIGNAL("valueChanged"),self._on_EMAN_rotation)
QtCore.QObject.connect(self.imagicgammaslider,QtCore.SIGNAL("valueChanged"),self._on_Imagic_rotation)
QtCore.QObject.connect(self.imagicbetaslider,QtCore.SIGNAL("valueChanged"),self._on_Imagic_rotation)
QtCore.QObject.connect(self.imagicalphaslider,QtCore.SIGNAL("valueChanged"),self._on_Imagic_rotation)
QtCore.QObject.connect(self.spiderpsislider,QtCore.SIGNAL("valueChanged"),self._on_Spider_rotation)
QtCore.QObject.connect(self.spiderthetaslider,QtCore.SIGNAL("valueChanged"),self._on_Spider_rotation)
QtCore.QObject.connect(self.spiderphislider,QtCore.SIGNAL("valueChanged"),self._on_Spider_rotation)
QtCore.QObject.connect(self.mrcpsislider,QtCore.SIGNAL("valueChanged"),self._on_MRC_rotation)
QtCore.QObject.connect(self.mrcthetaslider,QtCore.SIGNAL("valueChanged"),self._on_MRC_rotation)
QtCore.QObject.connect(self.mrcomegaslider,QtCore.SIGNAL("valueChanged"),self._on_MRC_rotation)
QtCore.QObject.connect(self.xyzzslider,QtCore.SIGNAL("valueChanged"),self._on_XYZ_rotation)
QtCore.QObject.connect(self.xyzyslider,QtCore.SIGNAL("valueChanged"),self._on_XYZ_rotation)
QtCore.QObject.connect(self.xyzxslider,QtCore.SIGNAL("valueChanged"),self._on_XYZ_rotation)
QtCore.QObject.connect(self.spinomegaslider,QtCore.SIGNAL("valueChanged"),self._on_spin_rotation)
QtCore.QObject.connect(self.spinn1slider,QtCore.SIGNAL("valueChanged"),self._on_spin_rotation)
QtCore.QObject.connect(self.spinn2slider,QtCore.SIGNAL("valueChanged"),self._on_spin_rotation)
QtCore.QObject.connect(self.spinn3slider,QtCore.SIGNAL("valueChanged"),self._on_spin_rotation)
QtCore.QObject.connect(self.sgirotqslider,QtCore.SIGNAL("valueChanged"),self._on_sgirot_rotation)
QtCore.QObject.connect(self.sgirotn1slider,QtCore.SIGNAL("valueChanged"),self._on_sgirot_rotation)
QtCore.QObject.connect(self.sgirotn2slider,QtCore.SIGNAL("valueChanged"),self._on_sgirot_rotation)
QtCore.QObject.connect(self.sgirotn3slider,QtCore.SIGNAL("valueChanged"),self._on_sgirot_rotation)
QtCore.QObject.connect(self.quaternione0slider,QtCore.SIGNAL("valueChanged"),self._on_quaternion_rotation)
QtCore.QObject.connect(self.quaternione1slider,QtCore.SIGNAL("valueChanged"),self._on_quaternion_rotation)
QtCore.QObject.connect(self.quaternione2slider,QtCore.SIGNAL("valueChanged"),self._on_quaternion_rotation)
QtCore.QObject.connect(self.quaternione3slider,QtCore.SIGNAL("valueChanged"),self._on_quaternion_rotation)
def _rotcombobox_changed(self, idx):
self.rotstackedwidget.setCurrentIndex(idx)
self.updateItemControls()
def _on_EMAN_rotation(self, value):
self._set_rotation_std_coords(Transform({"type":"eman","az":self.emanazslider.getValue(),"alt":self.emanaltslider.getValue(),"phi":self.emanphislider.getValue()}))
self.inspector().updateSceneGraph()
def _on_Imagic_rotation(self, value):
self._set_rotation_std_coords(Transform({"type":"imagic","gamma":self.imagicgammaslider.getValue(),"beta":self.imagicbetaslider.getValue(),"alpha":self.imagicalphaslider.getValue()}))
self.inspector().updateSceneGraph()
def _on_Spider_rotation(self, value):
self._set_rotation_std_coords(Transform({"type":"spider","psi":self.spiderpsislider.getValue(),"theta":self.spiderthetaslider.getValue(),"phi":self.spiderphislider.getValue()}))
self.inspector().updateSceneGraph()
def _on_MRC_rotation(self, value):
self._set_rotation_std_coords(Transform({"type":"mrc","phi":self.mrcpsislider.getValue(),"theta":self.mrcthetaslider.getValue(),"omega":self.mrcomegaslider.getValue()}))
self.inspector().updateSceneGraph()
def _on_XYZ_rotation(self, value):
self._set_rotation_std_coords(Transform({"type":"xyz","ztilt":self.xyzzslider.getValue(),"ytilt":self.xyzyslider.getValue(),"xtilt":self.xyzxslider.getValue()}))
self.inspector().updateSceneGraph()
def _on_spin_rotation(self, value):
v = Vec3f(self.spinn1slider.getValue(), self.spinn2slider.getValue(), self.spinn3slider.getValue())
v.normalize()
self._set_rotation_std_coords(Transform({"type":"spin","Omega":self.spinomegaslider.getValue(),"n1":v[0],"n2":v[1],"n3":v[2]}))
self.inspector().updateSceneGraph()
def _on_sgirot_rotation(self, value):
v = Vec3f(self.sgirotn1slider.getValue(), self.sgirotn2slider.getValue(), self.sgirotn3slider.getValue())
v.normalize()
self._set_rotation_std_coords(Transform({"type":"sgirot","q":self.sgirotqslider.getValue(),"n1":v[0],"n2":v[1],"n3":v[2]}))
self.inspector().updateSceneGraph()
def _on_quaternion_rotation(self, value):
v = Vec4f(self.quaternione0slider.getValue(), self.quaternione1slider.getValue(), self.quaternione2slider.getValue(), self.quaternione3slider.getValue())
v.normalize()
self._set_rotation_std_coords(Transform({"type":"quaternion","e0":v[0],"e1":v[1],"e2":v[2],"e3":v[3]}))
self.inspector().updateSceneGraph()
def _set_rotation_std_coords(self, rotation):
""" This function sets the rotation as if there were no preceeding ones, otherwise a rot around Z could be arounf y,x, etc.
Works by transforming local coords into global corrds"""
tt = rotation
tp = self.item3d().getParentMatrixProduct()
if tp: tt = tp.inverse()*rotation
self.item3d().getTransform().set_rotation(tt.get_rotation())
if __name__ == '__main__':
#Test code
root = EMItem3D(0)
a = EMItem3D(root)
b = EMItem3D(root)
c = EMItem3D(root)
# root.addChildren([a,b,c])
aa = EMItem3D(a)
ab = EMItem3D(a)
ac = EMItem3D(a)
# a.addChildren([aa,ab,ac])
ba = EMItem3D(b)
bb = EMItem3D(b)
bc = EMItem3D(b)
# b.addChildren([ba,bb,bc])
ca = EMItem3D(c)
cb = EMItem3D(c)
cc = EMItem3D(c)
# c.addChildren([ca,cb,cc])
aaa = EMItem3D(aa)
aab = EMItem3D(aa)
aac = EMItem3D(aa)
# aa.addChildren([aaa,aab,aac])
a.is_selected = True
aab.is_selected = True
ba.is_selected = True
bc.is_selected = True
c.is_selected = True
cc.is_selected = True
print "getAllSelectedNodes() test: "
print "\tpassed? ", set(root.getAllSelectedNodes()) == set([a,aab,ba,bc,c,cc])
print "getNearbySelectedNodes() test: "
print "\tpassed? ", set(root.getNearbySelectedNodes()) == set([a,ba,bc,c])
print "getDistantSelectedNodes() test: "
print "\tpassed? ", set(root.getDistantSelectedNodes()) == set([aab,ba,bc,cc])
root.displayTree()
print "\n"
a.removeParentReferences()
root.displayTree()
print "\n"
root.addParentReferences()
root.displayTree()
print "\n"
print "removing child..."
root.removeChild(a)
root.displayTree()
del a, b, c, aa, ab, ac, ba, bb, bc, ca, cb, cc, aaa, aab, aac #Ensure instances are deleted before the class object is deleted, which is important in EMItem3D.__del__(self):
|
[
"jupiterh@vpac.org"
] |
jupiterh@vpac.org
|
68a88475ce22d1c7e3b750255bbf7cee712a0ee7
|
e8d927d593e2d8d08004e12ec11988062b9df8b3
|
/typeidea/blog/adminx.py
|
d5363e831143e4fac4e100c666967e13751ed032
|
[] |
no_license
|
choupihuan/typeidea
|
9c4f6a90dfb53f94dcaeb15e5e6e915f9f9e0ee6
|
f8e13b1e4afd0f67bf365bdbb04e35cc4f56a0da
|
refs/heads/master
| 2020-06-05T19:51:29.757681 | 2019-06-29T11:32:46 | 2019-06-29T11:32:46 | 192,530,809 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,567 |
py
|
import xadmin
from django.urls import reverse
from django.utils.html import format_html
from django.contrib.admin.models import LogEntry
from xadmin.layout import Row,Fieldset,Container
from xadmin.filters import manager
from xadmin.filters import RelatedFieldListFilter
from .models import Post,Category,Tag
from .adminforms import PostAdminForm
from typeidea.base_admin import BaseOwnerAdmin
class PostInline:
form_layout = (
Container(Row('title','desc')
)
)
extra = 1
model = Post
@xadmin.sites.register(Category)
class CategoryAdmin(BaseOwnerAdmin):
list_display = ('name','status','is_nav','owner','create_time','post_count')
fields = ('name','status','is_nav')
inlines = [PostInline,]
def post_count(self,obj):
return obj.post_set.count()
post_count.short_description = '文章数量'
@xadmin.sites.register(Tag)
class TagAdmin(BaseOwnerAdmin):
list_display = ('name','status','create_time')
fields = ('name','status')
class CategoryOwnerFilter(RelatedFieldListFilter):
""" 自定义过滤器只展示当前用户分类 """
@classmethod
def test(cls, field, request, params, model, admin_view, field_path):
return field.name == 'category'
def __init__(self,field,request,params,model,model_admin,field_path):
super().__init__(field,request,params,model,model_admin,field_path)
self.lookup_choices = Category.objects.filter(owner=request.user).values_list('id','name')
manager.register(CategoryOwnerFilter,take_priority=True)
@xadmin.sites.register(Post)
class PostAdmin(BaseOwnerAdmin):
form = PostAdminForm
list_display = [
'title','category','status',
'create_time','owner','operator'
]
list_display_links = []
exclude = ('owner',)
list_filter = ['category']
search_fields = ['title','category__name']
actions_on_top = True
actions_on_bottom = False
#编辑页面
save_on_top = False
filter_horizontal = ('tag',)
# fields = (
# ('category','title'),
# 'desc',
# 'status',
# 'content',
# 'tag',
# )
# fieldsets = (
# ('基础配置',{
# 'description':'基础配置',
# 'fields': (
# ('title','category','tag'),
# 'status',
# ),
# }),
# ('内容',{
# 'fields': (
# 'desc',
# 'content',
# ),
# }),
#
# )
# 使用xadmin修改的地方
form_layout = (
Fieldset(
'基础信息',
Row('title','category'),
'status',
'tag',
),
Fieldset(
'内容信息',
'desc',
'is_md',
'content_ck',
'content_md',
'content',
)
)
# @property
# def media(self):
# media = super().media
# media.add_js(['https://cdn.bootcss.com/bootstrap/4.0.0-beta.2/js/bootstrap.bundle.js'])
# media.add_css({
# 'all':('https://cdn.bootcss.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css')
# })
# return media
def operator(self,obj):
return format_html(
'<a href="{}">编辑</a>',
reverse('xadmin:blog_post_change',args=(obj.id,))
)
operator.short_description = '操作'
@xadmin.sites.register(LogEntry)
class LogEntryAdmin():
list_display = ['object_repr','object_id','action_flag','user','change_message']
|
[
"1193496683@qq.com"
] |
1193496683@qq.com
|
4f1cde96439f98545e5230a27a9a466a7284b8c1
|
2d39d2dbfc4d54c79899caf6fab83d23b1823b9a
|
/extract_info.py
|
f2316188355dc7286dc2172aa53a4455fba34d35
|
[] |
no_license
|
josephthurman/nyt-reviews
|
77db49ab131cbbb2664a45cf4d1625b2ea79f5c8
|
15067020ecb96acfc89a2b14c38ebd3e0dbf7841
|
refs/heads/master
| 2020-03-24T11:51:41.936973 | 2018-10-03T19:17:44 | 2018-10-03T19:17:44 | 142,697,014 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 6,327 |
py
|
from bs4 import BeautifulSoup
import re
import json
import os
# Some helper functions - mostly used in testing
def get_review(counter):
with open('./reviews/review' + str(counter) + '.html', 'r') as file:
parsed = BeautifulSoup(file, 'html.parser')
return(parsed)
# Extract the text of the review
def find_review(bs):
tag_searches = [('p', re.compile('story-body-text story-content')),
('p', re.compile('css-1i0edl6'))]
for (tag, regex) in tag_searches:
result = bs.find_all(tag, {'class': regex})
if len(result) > 0:
review_text = ''
for p in result:
review_text += p.get_text()
review_text = re.sub(r'\s+', ' ', review_text)
return(review_text)
# Return EMPTY if review text cannot be found
return("EMPTY")
# Extract the rating from the review
def find_stars(bs):
# Newer reviews have the rating set off from the story in special html tag. Find those first
tag_searches = [('span', re.compile('ReviewFooter-stars')),
('div', re.compile('ReviewFooter-rating')),
('li', re.compile('critic-star-rating')),
('li', re.compile('critic-word-rating'))]
stars = "NA"
for (tag, regex) in tag_searches:
result = bs.find_all(tag, {'class': regex})
if len(result) > 0:
text = result[0].get_text()
stars = re.sub(r'\s+', ' ', text).strip()
if stars in ['Satisfactory', 'Fair', 'Poor']:
return(stars)
else:
return(str(len(stars)))
# Older stories have the rating just sitting in a plain paragraph. We can also find those
if re.search('<p.*?>\s*[Ss]atisfactory\s*</p>', str(bs)):
return('Satisfactory')
if re.search('<p.*?>\s*[Ff]air\s*</p>', str(bs)):
return('Fair')
if re.search('<p.*?>\s*[Pp]oor\s*</p>', str(bs)):
return('Poor')
direct_search = re.search('<p.*?>\s*★+\s*</p>', str(bs))
if direct_search:
just_stars = re.search('★+', direct_search.group()).group()
return(str(len(just_stars)))
# If all else fails, return 'NA' to show we couldn't find a rating
return('NA')
# Extract the number of recommended dishes in the review
def find_rec_dishes(bs):
tag_searches = [('div', 'class', re.compile('ReviewFooter-recommendedDishes')),
('span', 'itemprop', re.compile('[Mm]enu'))]
rec_dish_text = ''
for (tag, property, regex) in tag_searches:
result = bs.find_all(tag, {property: regex})
if result:
if len(result) > 1:
rec_dish_text = result[1].get_text()
else:
rec_dish_text = result[0].get_text()
break
# Two reviews have the prices listed in a totally different format. We pick those up here
if rec_dish_text == '':
regex = re.compile(r'RECOMMENDED\s*</strong>(.*?)</p>', flags = re.DOTALL)
rec_dish_text = re.search(regex, str(bs)).group(1)
# Return the number of recommended dishes
rec_dish_list = re.split('; |\. ', rec_dish_text)
return(len(rec_dish_list))
# Convert numeric price to price category
# This is a best guess - they don't have a current key for this.
# But we're actually only doing this for 2 reviews anyway
def price_to_category(price):
if price < 25:
return(1)
elif price < 50:
return(2)
elif price < 100:
return(3)
else:
return(4)
# Extract the price rating in the review
def find_price(bs):
tag_searches = [('dd', 'class', 'price'),
('span', 'itemprop', re.compile('[Pp]rice[Rr]ange'))]
price_text = ''
for (tag, property, regex) in tag_searches:
result = bs.find_all(tag, {property: regex})
if len(result) > 0:
price_text = result[0].get_text()
break
# Two reviews have the prices listed in a totally different format. We pick those up here
if price_text == '':
regex = re.compile(r'PRICES\s*</strong>(.*?)</p>', flags = re.DOTALL)
price_text = re.search(regex, str(bs)).group(1)
# Read price description and get the dollar sign rating
dollar_regex = re.compile('(\$+)\s')
dollarsigns = re.search(dollar_regex, price_text)
if dollarsigns:
return(len(dollarsigns.group(1)))
else:
# Extract actual price numbers - finds numbers preceded by $, or by hyphens for ranges,
# e.g. return 5, 17 and 45 from somthing like "apps $5-17, entrees $45"
price_regex = re.compile('(?<=[-\$])[0-9]+')
list_of_prices = re.findall(price_regex, price_text)
if list_of_prices:
max_price = max(map(int,list_of_prices))
return(price_to_category(max_price))
else:
# Error - couldn't find the price category.
return(0)
if __name__ == '__main__':
with open('./reviews/url_list.txt', 'r') as url_file:
urls = json.load(url_file)
cleaned_reviews = []
unprocessed_URLS = []
for counter, review_url in enumerate(urls):
# progress counter for debugging
if counter % 10 == 0:
print(counter)
# Read review
parsed = get_review(counter)
rating = find_stars(parsed)
if rating != 'NA':
restaurant_info = {'id': counter,
'review_url': review_url,
'rating': rating,
'review_text': find_review(parsed),
'price': find_price(parsed),
'rec_dishes' : find_rec_dishes(parsed)}
cleaned_reviews.append(restaurant_info)
else:
unprocessed_URLS.append(review_url)
# There are still some articles for which we can't find a star rating. The list of such articles is saved here
# It ends up being short enough to inspect by hand and see that none of these articles are real reviews with stars
os.makedirs('data', exist_ok=True)
with open('./data/unprocessed_URLs.txt', 'w') as outfile:
json.dump(unprocessed_URLS, outfile)
# Save cleaned reviews for further analysis
with open('./data/cleaned_reviews.json', 'w') as outfile:
json.dump(cleaned_reviews, outfile)
|
[
"joethurman3@gmail.com"
] |
joethurman3@gmail.com
|
2054a0b722aa2fa72a01cff5884700470b6bbf49
|
edcccb46c663d7ef52b72c40c2b93c1f2b61c2d2
|
/Sample Work/Remove Char.py
|
f3ddb784e1ebb06aec5b34fd384a31d52f733336
|
[] |
no_license
|
mre9798/Python_Anlin
|
235292e80fe38181098706f733dba78614f38e7a
|
83c1e0c994fa55e9bb8cd5de1097b2de7345813e
|
refs/heads/master
| 2023-02-24T22:31:38.279969 | 2021-02-01T09:17:36 | 2021-02-01T09:17:36 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 146 |
py
|
# Remove nth character
s = input("Enter a string : ")
pos = int(input("Enter position of character to be removed : "))
print(s[:pos-1] + s[pos:])
|
[
"anlinalbert@gmail.com"
] |
anlinalbert@gmail.com
|
18369325e71e025ee816fd5e5d7ce741992af937
|
399765d71fbc931125fe75cc6c71eabdac4dc58f
|
/app-tornado.py
|
bced06bd7f1d0304a5654802440c2e6409be3fa6
|
[] |
no_license
|
G-Guillard/NEO
|
98e989952c7a15de630962c44d65998e979f7efd
|
3317b228fbeead14b1546290e9e7a7a7abbd7ff3
|
refs/heads/master
| 2020-12-10T09:16:47.845598 | 2020-01-16T15:29:19 | 2020-01-16T15:29:19 | 233,555,035 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 5,208 |
py
|
import os
from tornado.web import Application, RequestHandler
from tornado.ioloop import IOLoop
from pymongo import MongoClient
from bson import Code
import pandas as pd
from plotly.utils import PlotlyJSONEncoder
import plotly.graph_objects as go
import plotly.express as px
import json
from sklearn.cluster import KMeans
#Connect to Mongo client and DB
client = MongoClient('db', 27017)
db = client.nasadb
coll = db.neo
collname = "neo" # Near Earth Objects
def get_keys(collection, numeric=False):
"""Get all documents keys, or only numerical keys"""
if numeric:
mapper = Code("function() { for (var key in this) { if (typeof(this[key]) == 'number') emit(key, null); } }")
else:
mapper = Code("function() { for (var key in this) { emit(key, null); } }")
reducer = Code("function(key, stuff) { return null; }")
result = db[collection].map_reduce(mapper, reducer, collection + "_keys")
return result.distinct("_id")
def get_features(f1, f2=''):
"""Get features from Mongo DB"""
cursor = coll.find()
if f2:
return pd.DataFrame(list(cursor), columns=[f1, f2])
else:
return pd.DataFrame(list(cursor), columns=[f1])
class Index(RequestHandler):
def get(self):
"""Index page contains links to plots of single distributions"""
items = [key for key in get_keys(collname, numeric=True)]
self.render('templates/index-tornado.html', items = items)
class Plot1D(RequestHandler):
def get(self, feature):
"""Plot distribution of a feature"""
if not feature:
self.set_status(400)
return self.render('templates/error-tornado.html', code=400)
else:
feature = feature.split("/")[0]
if not feature in get_keys(collname):
self.set_status(404)
return self.render('templates/error-tornado.html', code=404, key=feature)
df = get_features(feature)
fig = go.Figure(data=[go.Histogram(x=df[feature])])
graphJSON = json.dumps(fig, cls=PlotlyJSONEncoder)
return self.render('templates/plot-tornado.html', plot=json.dumps(graphJSON))
class Plot2D(RequestHandler):
def get(self, query=''):
"""GET request for 2D plot"""
features = query.split("/")
if features[0] and features[1]:
self.plot(features[0], features[1])
else:
self.set_status(400)
return self.render('templates/error-tornado.html', code=400)
def post(self):
"""POST request for 2D plot"""
feature1 = self.get_argument('x')
feature2 = self.get_argument('y')
if feature1 and feature2:
self.plot(feature1, feature2)
else:
self.set_status(400)
return self.render('templates/error-tornado.html', code=400)
def plot(self, feature1, feature2):
"""Plot 2D distributions of two features"""
if not feature1 in get_keys(collname):
self.set_status(404)
return self.render('templates/error-tornado.html', code=404, key=feature1)
if not feature2 in get_keys(collname):
self.set_status(404)
return self.render('templates/error-tornado.html', code=404, key=feature2)
df = get_features(feature1, feature2)
fig = px.scatter(df, x=feature1, y=feature2)
graphJSON = json.dumps(fig, cls=PlotlyJSONEncoder)
return self.render('templates/plot-tornado.html', plot=json.dumps(graphJSON))
class KMeansClassifier(RequestHandler):
def get(self, n_clusters=2):
"""Unsupervised classification attempt"""
# Default argument value doesn't work, set to ''
if not n_clusters:
n_clusters = 2
cursor = coll.find()
df = pd.DataFrame(list(cursor), columns=[
'Absolute Magnitude',
'Est Dia in M(min)',
'Est Dia in M(max)',
'Relative Velocity km per hr',
# 'Miss Dist (Astronomical)',
'Minimum Orbit Intersection',
'Jupiter Tisserand Invariant',
'Epoch Osculation',
'Eccentricity',
'Semi Major Axis',
'Inclination',
'Asc Node Longitude',
'Orbital Period',
'Perihelion Distance',
'Perihelion Arg',
'Aphelion Dist',
'Perihelion Time',
'Mean Anomaly',
'Mean Motion'
])
normalized_df = (df - df.mean()) / df.std()
normalized_df = normalized_df.dropna()
pred = KMeans(n_clusters=int(n_clusters)).fit_predict(normalized_df)
df["pred"] = pred
fig = px.scatter(df, x="Mean Anomaly", y="Eccentricity", color="pred")
graphJSON = json.dumps(fig, cls=PlotlyJSONEncoder)
return self.render('templates/plot-tornado.html', plot=json.dumps(graphJSON))
# Launch the app
if __name__ == "__main__":
app = Application([
('/',Index),
(r'/plots/1D/(.*)',Plot1D),
(r'/plots/2D/',Plot2D),
(r'/plots/2D/(.*)',Plot2D),
(r'/classify/kmeans/(.*)',KMeansClassifier)
])
app.listen(5000)
IOLoop.current().start()
|
[
"5038620+G-Guillard@users.noreply.github.com"
] |
5038620+G-Guillard@users.noreply.github.com
|
2c04318b0b4fa9de6ab094de0b250b0fad83f7ad
|
3ee88f6e7c427eef6dd7bb177f4b3a727bccbcd2
|
/pbnh/conf.py
|
90a4b7dcbb4ef4decd192aada7dd76669fc36f77
|
[
"MIT"
] |
permissive
|
bhanderson/pbnh
|
67a4132adf366dafda3d01cfcfae92f14d84266c
|
59bcb27de1a2300f14476349f3182c651a8f88a1
|
refs/heads/master
| 2022-11-05T13:45:17.674023 | 2022-10-24T23:21:24 | 2022-10-24T23:21:24 | 55,452,403 | 17 | 10 |
MIT
| 2022-10-24T23:21:25 | 2016-04-04T23:21:09 |
JavaScript
|
UTF-8
|
Python
| false | false | 580 |
py
|
import yaml
import copy
DEFAULTS = {
"server": {
"bind_ip": "0.0.0.0",
"bind_port": 5001,
"debug": True,
},
"database": {
"dbname": "pastedb",
"dialect": "sqlite",
"driver": None,
"host": None,
"password": None,
"port": None,
"username": None
}
}
def get_config():
try:
with open('secrets.yml') as config:
return yaml.load(config)
except IOError:
return copy.copy(DEFAULTS)
|
[
"bryce.handerson@isilon.com"
] |
bryce.handerson@isilon.com
|
4e6dc77e570b5419eef0fc74fd16710afdfd3235
|
190d03cf370844548b9e8c89952dfbaec4d0c5c8
|
/p103.py
|
467aee99fa0ff340b0a00d481a047ab36a7d0d52
|
[] |
no_license
|
alainlou/leetcode
|
446d101a9fd2f9eaa2229252e5909e7df36b4a74
|
fe500bcb067be59aa048259e3860e9da6f98344d
|
refs/heads/master
| 2022-10-16T12:20:44.726963 | 2022-09-18T15:29:05 | 2022-09-18T15:29:05 | 178,775,702 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 623 |
py
|
from DS.TreeNode import TreeNode
class Solution:
def zigzagLevelOrder(self, root: TreeNode) -> List[List[int]]:
if root is None:
return []
ans = []
q = [(root, 0)]
while len(q) > 0:
curr = q.pop(0)
if len(ans) <= curr[1]:
ans.append([])
ans[-1].append(curr[0].val)
if curr[0].left:
q.append((curr[0].left, curr[1]+1))
if curr[0].right:
q.append((curr[0].right, curr[1]+1))
for i in range(1, len(ans), 2):
ans[i] = ans[i][::-1]
return ans
|
[
"az2lou@uwaterloo.ca"
] |
az2lou@uwaterloo.ca
|
55579000cd5ed23906233808f75b3a4fae18bda1
|
7e9e76ccb9a8132f875ff8e3279eeb95b4f9b424
|
/houseDjango/loggings/urls.py
|
fbc79cdd86349e0b486fc3cb7c5f10e4b586d14a
|
[] |
no_license
|
IPingStudio/houseDjango
|
9f282273beb80ab4ec2e741bcba28c10c59880c5
|
55aff03fb7febb106304f4555ecdce254539cfa6
|
refs/heads/master
| 2023-01-13T02:04:00.362837 | 2020-11-02T02:30:37 | 2020-11-02T02:30:37 | 302,852,093 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 816 |
py
|
"""houseDjango URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, re_path, include
from . import views
urlpatterns = [
re_path(r'^$', views.searchLoginByHouse, name='showLog'),
]
|
[
"haoran201314@126.com"
] |
haoran201314@126.com
|
552d7737321351084598b558d7543b946c890425
|
4f989b9e1e9c1caa70b5d013d95b95f3c3f0cb3c
|
/classbasedapiview/urls.py
|
e0fddc3de7513210995950c8b9d2832b0757ac90
|
[] |
no_license
|
vikashtiwary118/class-based-apiview
|
4cdb9bc786c16d51dbc5e80060c2b92579659bea
|
bccaa57a8c7ca07e17402b6d9a12e7f32ba2546f
|
refs/heads/main
| 2023-05-17T00:47:38.819526 | 2021-06-07T05:09:35 | 2021-06-07T05:09:35 | 374,537,483 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 254 |
py
|
from django.contrib import admin
from django.urls import path
from api import views
urlpatterns = [
path('admin/', admin.site.urls),
path('studentapi/', views.StudentAPI.as_view()),
path('studentapi/<int:pk>', views.StudentAPI.as_view()),
]
|
[
"tiwaryvikash118@gmail.com"
] |
tiwaryvikash118@gmail.com
|
5df906375ee0c7d24ede8dd570122ce0cbdd1251
|
9bdc5bd0b6195761fbceed17c0725bc48a5941a1
|
/testing/keras_taylor_1D.py
|
f24a460e11be29c65a55abbe497af20fe014f122
|
[] |
no_license
|
lapsintra/htt-ml
|
bc6bbb12eda4a3f0abbc5c0db13940a31b667a08
|
ce07cad6fcc8625b1595157de6486759b74f6d62
|
refs/heads/master
| 2020-04-05T16:29:29.858916 | 2018-12-04T19:32:10 | 2018-12-04T19:32:10 | 157,015,043 | 0 | 0 | null | 2018-11-10T19:38:56 | 2018-11-10T19:38:56 | null |
UTF-8
|
Python
| false | false | 7,871 |
py
|
#!/usr/bin/env python
import ROOT
ROOT.PyConfig.IgnoreCommandLineOptions = True # disable ROOT internal argument parser
import argparse
from array import array
import yaml
import pickle
import numpy as np
import os
import sys
import matplotlib as mpl
mpl.use('Agg')
mpl.rcParams['font.size'] = 16
import matplotlib.pyplot as plt
from matplotlib import cm
from keras.models import load_model
import tensorflow as tf
from tensorflow_derivative.inputs import Inputs
from tensorflow_derivative.outputs import Outputs
from tensorflow_derivative.derivatives import Derivatives
import logging
logger = logging.getLogger("keras_taylor_1D")
logger.setLevel(logging.DEBUG)
handler = logging.StreamHandler()
formatter = logging.Formatter("%(name)s - %(levelname)s - %(message)s")
handler.setFormatter(formatter)
logger.addHandler(handler)
def parse_arguments():
parser = argparse.ArgumentParser(description="Produce confusion matrice")
parser.add_argument("config_training", help="Path to training config file")
parser.add_argument("config_testing", help="Path to testing config file")
parser.add_argument("fold", type=int, help="Trained model to be tested.")
parser.add_argument(
"--no-abs",
action="store_true",
default=False,
help="Do not use abs for metric.")
parser.add_argument(
"--normalize",
action="store_true",
default=False,
help="Normalize rows.")
return parser.parse_args()
def parse_config(filename):
logger.debug("Load config %s.", filename)
return yaml.load(open(filename, "r"))
def main(args, config_test, config_train):
# Load preprocessing
path = os.path.join(config_train["output_path"],
config_test["preprocessing"][args.fold])
logger.info("Load preprocessing %s.", path)
preprocessing = pickle.load(open(path, "rb"))
# Load Keras model
path = os.path.join(config_train["output_path"],
config_test["model"][args.fold])
logger.info("Load keras model %s.", path)
model_keras = load_model(path)
# Get TensorFlow graph
inputs = Inputs(config_train["variables"])
try:
sys.path.append("htt-ml/training")
import keras_models
except:
logger.fatal("Failed to import Keras models.")
raise Exception
try:
name_keras_model = config_train["model"]["name"]
model_tensorflow_impl = getattr(
keras_models, config_train["model"]["name"] + "_tensorflow")
except:
logger.fatal(
"Failed to load TensorFlow version of Keras model {}.".format(
name_keras_model))
raise Exception
model_tensorflow = model_tensorflow_impl(inputs.placeholders, model_keras)
outputs = Outputs(model_tensorflow, config_train["classes"])
sess = tf.Session()
sess.run(tf.global_variables_initializer())
# Get operations for first-order derivatives
deriv_ops = {}
derivatives = Derivatives(inputs, outputs)
for class_ in config_train["classes"]:
deriv_ops[class_] = []
for variable in config_train["variables"]:
deriv_ops[class_].append(derivatives.get(class_, [variable]))
# Loop over testing dataset
path = os.path.join(config_train["datasets"][(1, 0)[args.fold]])
logger.info("Loop over test dataset %s to get model response.", path)
file_ = ROOT.TFile(path)
mean_abs_deriv = {}
for i_class, class_ in enumerate(config_train["classes"]):
logger.debug("Process class %s.", class_)
tree = file_.Get(class_)
if tree == None:
logger.fatal("Tree %s does not exist.", class_)
raise Exception
values = []
for variable in config_train["variables"]:
typename = tree.GetLeaf(variable).GetTypeName()
if typename == "Float_t":
values.append(array("f", [-999]))
elif typename == "Int_t":
values.append(array("i", [-999]))
else:
logger.fatal("Variable {} has unknown type {}.".format(variable, typename))
raise Exception
tree.SetBranchAddress(variable, values[-1])
if tree.GetLeaf(variable).GetTypeName() != "Float_t":
logger.fatal("Weight branch has unkown type.")
raise Exception
weight = array("f", [-999])
tree.SetBranchAddress(config_test["weight_branch"], weight)
deriv_class = np.zeros((tree.GetEntries(),
len(config_train["variables"])))
weights = np.zeros((tree.GetEntries()))
for i_event in range(tree.GetEntries()):
tree.GetEntry(i_event)
# Preprocessing
values_stacked = np.hstack(values).reshape(1, len(values))
values_preprocessed = preprocessing.transform(values_stacked)
# Keras inference
response = model_keras.predict(values_preprocessed)
response_keras = np.squeeze(response)
# Tensorflow inference
response = sess.run(
model_tensorflow,
feed_dict={
inputs.placeholders: values_preprocessed
})
response_tensorflow = np.squeeze(response)
# Check compatibility
mean_error = np.mean(np.abs(response_keras - response_tensorflow))
if mean_error > 1e-5:
logger.fatal(
"Found mean error of {} between Keras and TensorFlow output for event {}.".
format(mean_error, i_event))
raise Exception
# Calculate first-order derivatives
deriv_values = sess.run(
deriv_ops[class_],
feed_dict={
inputs.placeholders: values_preprocessed
})
deriv_values = np.squeeze(deriv_values)
deriv_class[i_event, :] = deriv_values
# Store weight
weights[i_event] = weight[0]
if args.no_abs:
mean_abs_deriv[class_] = np.average((deriv_class), weights=weights, axis=0)
else:
mean_abs_deriv[class_] = np.average(np.abs(deriv_class), weights=weights, axis=0)
# Normalize rows
classes = config_train["classes"]
matrix = np.vstack([mean_abs_deriv[class_] for class_ in classes])
if args.normalize:
for i_class, class_ in enumerate(classes):
matrix[i_class, :] = matrix[i_class, :] / np.sum(
matrix[i_class, :])
# Plotting
variables = config_train["variables"]
plt.figure(0, figsize=(len(variables), len(classes)))
axis = plt.gca()
for i in range(matrix.shape[0]):
for j in range(matrix.shape[1]):
axis.text(
j + 0.5,
i + 0.5,
'{:.2f}'.format(matrix[i, j]),
ha='center',
va='center')
q = plt.pcolormesh(matrix, cmap='Wistia')
#cbar = plt.colorbar(q)
#cbar.set_label("mean(abs(Taylor coefficients))", rotation=270, labelpad=20)
plt.xticks(
np.array(range(len(variables))) + 0.5, variables, rotation='vertical')
plt.yticks(
np.array(range(len(classes))) + 0.5, classes, rotation='horizontal')
plt.xlim(0, len(config_train["variables"]))
plt.ylim(0, len(config_train["classes"]))
output_path = os.path.join(config_train["output_path"],
"fold{}_keras_taylor_1D.png".format(args.fold))
logger.info("Save plot to {}.".format(output_path))
plt.savefig(output_path, bbox_inches='tight')
if __name__ == "__main__":
args = parse_arguments()
config_test = parse_config(args.config_testing)
config_train = parse_config(args.config_training)
main(args, config_test, config_train)
|
[
"stefan.wunsch@student.kit.edu"
] |
stefan.wunsch@student.kit.edu
|
fc07829f755d7e6cdcfbb45f1595dfd39618bdaa
|
6d69b249a81e076d79787dd08eb8957908052052
|
/libs/parse/sections/grouper_mixins/blocks.py
|
154423ab5e2c3ebe6544db079d4af4ebccbedda5
|
[] |
no_license
|
2vitalik/wiktionary
|
02ee1f1327c3b82fc7b4d7da12083b1431b1eb8b
|
8edae2f7dcf9089084c5ce7033c4fb0b454f4dfa
|
refs/heads/master
| 2023-02-06T11:28:41.554604 | 2023-02-05T22:49:01 | 2023-02-05T22:49:01 | 121,025,447 | 7 | 2 | null | 2021-10-13T17:36:32 | 2018-02-10T15:06:24 |
Lua
|
UTF-8
|
Python
| false | false | 486 |
py
|
from libs.parse.groupers.sections.blocks.any_blocks import AnyBlocksGrouper
from libs.parse.groupers.sections.blocks.blocks import BlocksGrouper
from libs.parse.sections.grouper_mixins.sub_blocks import SubBlocksGroupersMixin
from libs.parse.utils.decorators import parsed
class BlocksGroupersMixin(SubBlocksGroupersMixin):
@property
@parsed
def blocks(self):
return BlocksGrouper(self)
@parsed
def any_blocks(self):
return AnyBlocksGrouper(self)
|
[
"vitaliy.lyapota@anvileight.com"
] |
vitaliy.lyapota@anvileight.com
|
d3e48f69c086cadbd11c7ae49adb48301ab31324
|
62669fa98cfba28653f97adfaf169c166e02d69c
|
/yi_parser.py
|
b829e653e392286b80afb190dd2a9d2223f8e028
|
[] |
no_license
|
Kevin-Xi/Yi_Analysis_Tools
|
d8e7850275572bc00c59a46fe10c0ae2a584670d
|
2191948795f1c6df621ec1ab535d43c35b3067d7
|
refs/heads/master
| 2020-04-18T11:47:18.576014 | 2013-06-05T08:26:39 | 2013-06-05T08:26:39 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,719 |
py
|
# -- coding=utf-8 -- #
"""Parser of Yi
Analyse specified Yao of a Gua
Usage:
python yi_parser.py [options]
Options:
-s ... use specified xml file
-g ... specify a Gua, between 1 and 64
-y ... specify a Yao, between 1 and 6
-a analyse all
-h show help document
Examples:
yi_parser.py -s new_yi.xml use 'new_yi.xml' as source xml file
yi_parser.py -g 32 analyse all Yao of Gua no.32
yi_parser.py -y 5 analyse Yao no.5 of every Gua
yi_parser.py -g 16 -y 3 analyse the third Yao of Gua no.16
yi_parser.py -a analyse all
Visit https://github.com/Kevin-Xi/Yi_Analysis_Tools for the latest version.
"""
from xml.dom import minidom
import sys
import getopt
import time
class Yi_parser():
result = {}
def __init__(self, xmlfile, gflag, yflag):
xmldoc = minidom.parse(xmlfile)
self.xmlroot = xmldoc.childNodes[0]
target_gua = self.xmlroot.childNodes[gflag*2-1]
self.yao_bucket = target_gua.childNodes
self.target_yao = self.yao_bucket[yflag*2-1]
self.gflag = gflag
self.yflag = yflag
self.parse()
def parse(self):
self.target_p = int(self.target_yao.attributes['p'].value)
self.dangwei()
self.dezhong()
self.ying()
self.cheng_up() #乘
self.cheng_down() #承
def dangwei(self):
if self.yflag % 2 == self.target_p % 2:
self.result['当位'] = 1
else:
self.result['当位'] = 0
def dezhong(self):
if self.yflag == 2 or self.yflag == 5:
self.result['得中'] = 1
else:
self.result['得中'] = 0
def ying(self):
ying_no = self.yflag-3 > 0 and self.yflag-3 or self.yflag+3
ying_p = int(self.yao_bucket[ying_no*2-1].attributes['p'].value)
if self.target_p != ying_p:
self.result['应'] = 1
else:
self.result['应'] = 0
def cheng_up(self):
try:
cheng_p = int(self.yao_bucket[self.yflag*2-3].attributes['p'].value)
if self.target_p == 1 and cheng_p == 0:
self.result['乘'] = 1
else:
self.result['乘'] = 0
except:
self.result['乘'] = -1
def cheng_down(self):
try:
cheng_p = int(self.yao_bucket[self.yflag*2+1].attributes['p'].value)
if self.target_p == 0 and cheng_p == 1:
self.result['承'] = 1
else:
self.result['承'] = 0
except:
self.result['承'] = -1
def output(self):
return ', '.join(['%s = %s' % (k, v) for k, v in self.result.items() if self.result[k] != -1]) + '\n'
class ArgOutofRangeError(Exception): pass
def usage():
print __doc__
def main(argv):
xmlfile = 'yi.xml'
gflag = 0
yflag = 0
try:
opts, args = getopt.getopt(argv, 's:g:y:ah') #the args should be here to take the junk
for opt, arg in opts:
if opt == 'h':
usage()
sys.exit()
elif opt == '-s':
xmlfile = arg
elif opt == '-g':
gflag = int(arg)
if gflag > 64 or gflag < 1:
raise ArgOutofRangeError
elif opt == '-y':
yflag = int(arg)
if yflag > 6 or yflag < 1:
raise ArgOutofRangeError
elif opt == '-a':
(gflag, yflag) = (0, 0) #HOW TO PROCESS OVERWRITE CONFLICT BETWEEN g, y and a
except getopt.GetoptError:
usage()
sys.exit(2)
#except ArgOutofRangeError, ValueError: #WHY CANNOT???????
except:
usage()
sys.exit(3)
if gflag != 0 and yflag != 0:
run(xmlfile, gflag, yflag)
elif gflag == 0 and yflag != 0:
for i in range(64): # A big memory comsumer, but I think let the class only parse one yao is right. How to do? Cache?
run(xmlfile, i+1, yflag)
elif gflag != 0 and yflag == 0:
for i in range(6):
run(xmlfile, gflag, i+1)
else:
for i in range(64):
for j in range(6):
run(xmlfile, i+1, j+1)
def run(xmlfile, gflag, yflag):
y = Yi_parser(xmlfile, gflag, yflag)
print y.output()
if __name__ == '__main__':
if len(sys.argv) <= 1:
usage()
sys.exit()
main(sys.argv[1:])
|
[
"kevin.xgr@gmail.com"
] |
kevin.xgr@gmail.com
|
fcd899d0868ace0b83ecc9fb302a4fa7c51e35ea
|
a20707ab33beba0b0aac6401d7baf91c135af4c6
|
/Lab/Notes/Embed MatPlotLib in Tkinter.py
|
a5538e3c87caac7cdc899dbd0792cc75179dc895
|
[] |
no_license
|
ffarassati/Metherate-Lab
|
21fa34fadf165c6ba0d1862db5e4097fb047da4f
|
4f34d59d9168c150f7ae578a38e8b11674275c54
|
refs/heads/master
| 2020-05-17T05:17:13.318713 | 2019-06-17T09:37:41 | 2019-06-17T09:37:41 | 183,529,688 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,885 |
py
|
# The code for changing pages was derived from: http://stackoverflow.com/questions/7546050/switch-between-two-frames-in-tkinter
# License: http://creativecommons.org/licenses/by-sa/3.0/
# https://pythonprogramming.net/how-to-embed-matplotlib-graph-tkinter-gui/
import matplotlib
matplotlib.use("TkAgg")
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.figure import Figure
import tkinter as tk
from tkinter import ttk
LARGE_FONT= ("Verdana", 12)
class SeaofBTCapp(tk.Tk):
def __init__(self, *args, **kwargs):
tk.Tk.__init__(self, *args, **kwargs)
tk.Tk.iconbitmap(self, default="")
tk.Tk.wm_title(self, "Sea of BTC client")
container = tk.Frame(self)
container.pack(side="top", fill="both", expand = True)
container.grid_rowconfigure(0, weight=1)
container.grid_columnconfigure(0, weight=1)
self.frames = {}
for F in (StartPage, PageOne, PageTwo, PageThree):
frame = F(container, self)
self.frames[F] = frame
frame.grid(row=0, column=0, sticky="nsew")
self.show_frame(StartPage)
def show_frame(self, cont):
frame = self.frames[cont]
frame.tkraise()
class StartPage(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self,parent)
label = tk.Label(self, text="Start Page", font=LARGE_FONT)
label.pack(pady=10,padx=10)
button = ttk.Button(self, text="Visit Page 1",
command=lambda: controller.show_frame(PageOne))
button.pack()
button2 = ttk.Button(self, text="Visit Page 2",
command=lambda: controller.show_frame(PageTwo))
button2.pack()
button3 = ttk.Button(self, text="Graph Page",
command=lambda: controller.show_frame(PageThree))
button3.pack()
class PageOne(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self, parent)
label = tk.Label(self, text="Page One!!!", font=LARGE_FONT)
label.pack(pady=10,padx=10)
button1 = ttk.Button(self, text="Back to Home",
command=lambda: controller.show_frame(StartPage))
button1.pack()
button2 = ttk.Button(self, text="Page Two",
command=lambda: controller.show_frame(PageTwo))
button2.pack()
class PageTwo(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self, parent)
label = tk.Label(self, text="Page Two!!!", font=LARGE_FONT)
label.pack(pady=10,padx=10)
button1 = ttk.Button(self, text="Back to Home",
command=lambda: controller.show_frame(StartPage))
button1.pack()
button2 = ttk.Button(self, text="Page One",
command=lambda: controller.show_frame(PageOne))
button2.pack()
class PageThree(tk.Frame):
def __init__(self, parent, controller):
tk.Frame.__init__(self, parent)
label = tk.Label(self, text="Graph Page!", font=LARGE_FONT)
label.pack(pady=10,padx=10)
button1 = ttk.Button(self, text="Back to Home",
command=lambda: controller.show_frame(StartPage))
button1.pack()
f = Figure(figsize=(5,5), dpi=100)
a = f.add_subplot(111)
a.plot([1,2,3,4,5,6,7,8],[5,6,1,3,8,9,3,5])
canvas = FigureCanvasTkAgg(f, self)
canvas.draw()
canvas.get_tk_widget().pack(side=tk.BOTTOM, fill=tk.BOTH, expand=True)
toolbar = NavigationToolbar2Tk(canvas, self)
toolbar.update()
canvas._tkcanvas.pack(side=tk.TOP, fill=tk.BOTH, expand=True)
app = SeaofBTCapp()
app.mainloop()
|
[
"farshadfarassati@gmail.com"
] |
farshadfarassati@gmail.com
|
2e6669b326e3edda7be0bf7c377f290405bcf0c3
|
163bbb4e0920dedd5941e3edfb2d8706ba75627d
|
/Code/CodeRecords/2671/60590/241334.py
|
25e5fee553d7db62878bfa4165d65ebdfde7331c
|
[] |
no_license
|
AdamZhouSE/pythonHomework
|
a25c120b03a158d60aaa9fdc5fb203b1bb377a19
|
ffc5606817a666aa6241cfab27364326f5c066ff
|
refs/heads/master
| 2022-11-24T08:05:22.122011 | 2020-07-28T16:21:24 | 2020-07-28T16:21:24 | 259,576,640 | 2 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 314 |
py
|
def cal(w):
if w==1:
return 2
if w==2:
return 3
elif w==3:
return 5
else:
w2=2
w3=3
for i in range(w-2):
temp=w2+w3
w2=w3
w3=temp
return temp
t = int(input())
for i in range(t):
w=int(input())
print(2**w-cal(w))
|
[
"1069583789@qq.com"
] |
1069583789@qq.com
|
d078bea59e3fd25f0fb187ea727e6ef3f081d3f2
|
a6db31c3f9264c7b0ad5c3307dee4afd7ce689c1
|
/Python/MyPythonTest/zy/com/python3/Demo003.py
|
f0fcd0b4de6ffc722baa962d301009f4d34b9480
|
[] |
no_license
|
aJanefish/Work
|
2933fa5437b3c216ff1d76aa641af26226e5295c
|
96e585d6208e9d6bab5576a25853c0fdb54fbcd8
|
refs/heads/master
| 2021-06-29T15:53:28.458468 | 2020-02-23T08:23:44 | 2020-02-23T08:23:44 | 141,233,308 | 0 | 0 | null | 2020-10-13T10:42:43 | 2018-07-17T04:58:08 |
Python
|
UTF-8
|
Python
| false | false | 317 |
py
|
# -*- coding: UTF-8 -*-
# Filename : test.py
# author by : www.runoob.com
# 文件操作
# 写文件
print
with open("test.txt", "wt") as out_file:
out_file.write("该文本会写入到文件中\n看到我了吧！")
# Read a file
with open("test.txt", "rt") as in_file:
text = in_file.read()
print(text)
|
[
"36288075+aJanefish@users.noreply.github.com"
] |
36288075+aJanefish@users.noreply.github.com
|
866c1d3d680c6beedd8c74466cc4d708fc411925
|
58a392f4c4bae3fa1c99e3d081eda0701bb9c93f
|
/comment/migrations/0001_initial.py
|
02c7a01063db0d61442f5fc9a3fe66b88b72b2b4
|
[] |
no_license
|
KD233233/kd
|
84e6b60457c70b0eb603049762a3e17c808701f9
|
d0c298aefdc4b0712afa27604f832459b97a8edf
|
refs/heads/master
| 2020-05-19T07:21:08.312106 | 2019-05-05T06:03:42 | 2019-05-05T06:03:42 | 184,895,175 | 1 | 0 | null | 2019-05-04T13:09:01 | 2019-05-04T12:58:51 | null |
UTF-8
|
Python
| false | false | 864 |
py
|
# Generated by Django 2.1.7 on 2019-02-26 01:40
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('blog', '0006_auto_20190226_0940'),
]
operations = [
migrations.CreateModel(
name='Comment',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=52)),
('email', models.CharField(max_length=50)),
('content', models.CharField(max_length=1000)),
('time', models.DateTimeField(auto_now_add=True)),
('post', models.ForeignKey(on_delete=django.db.models.deletion.DO_NOTHING, to='blog.Post')),
],
),
]
|
[
"1769895221@qq.com"
] |
1769895221@qq.com
|
808c37dcb29ca35c6d9c2b58002ea569528d3997
|
f82728b6f868a2275e63848f936d2c22354dc024
|
/Data Structure/Array Or Vector/Search An Element in Sorted Array/SolutionByYashika.py
|
08248acbf202fda8812505c30c4bb5b29244da21
|
[
"MIT"
] |
permissive
|
shoaibrayeen/Programmers-Community
|
0b0fa4ba1427fa472126e640cda52dff3416b939
|
cd0855e604cfd54101aaa9118f01a3e3b4c48c1c
|
refs/heads/master
| 2023-03-16T03:13:48.980900 | 2023-03-12T00:25:37 | 2023-03-12T00:25:37 | 209,997,598 | 285 | 424 |
MIT
| 2023-03-12T00:25:38 | 2019-09-21T14:17:24 |
C++
|
UTF-8
|
Python
| false | false | 381 |
py
|
def search(array,ele):
if len(array)==0: #if array is empty
return False
if array[0]==ele: # if ele is found at 0th index
return True
return search(array[1:],ele) # recursively search for the element in the array
size=int(input())
array=[int(i) for i in input().split()]
ele=int(input())
if search(array,ele):
print("Yes")
else:
print("No")
|
[
"sharmayashika996@gmail.com"
] |
sharmayashika996@gmail.com
|
42912ac022fad380ab3b2d80fe7989268ffc6c88
|
a1858b1eeef112531b52f977b644a83fc3436688
|
/second/protos/train_pb2.py
|
d23b33889b3ebd11208cdc61c940a72a4d0ed2f7
|
[] |
no_license
|
NorthCross/CLOCs
|
2086ab2fe7fdce0c93ee7f181caf1b94774506a5
|
4cef59b23990a35656853bb16c4e897164b2ef02
|
refs/heads/master
| 2023-08-16T08:09:42.479641 | 2021-10-25T22:47:50 | 2021-10-25T22:47:50 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | true | 5,945 |
py
|
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: second/protos/train.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from second.protos import optimizer_pb2 as second_dot_protos_dot_optimizer__pb2
from second.protos import preprocess_pb2 as second_dot_protos_dot_preprocess__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='second/protos/train.proto',
package='second.protos',
syntax='proto3',
serialized_options=None,
serialized_pb=b'\n\x19second/protos/train.proto\x12\rsecond.protos\x1a\x1dsecond/protos/optimizer.proto\x1a\x1esecond/protos/preprocess.proto\"\x95\x02\n\x0bTrainConfig\x12+\n\toptimizer\x18\x01 \x01(\x0b\x32\x18.second.protos.Optimizer\x12\r\n\x05steps\x18\x02 \x01(\r\x12\x16\n\x0esteps_per_eval\x18\x03 \x01(\r\x12\x1d\n\x15save_checkpoints_secs\x18\x04 \x01(\r\x12\x1a\n\x12save_summary_steps\x18\x05 \x01(\r\x12\x1e\n\x16\x65nable_mixed_precision\x18\x06 \x01(\x08\x12\x19\n\x11loss_scale_factor\x18\x07 \x01(\x02\x12!\n\x19\x63lear_metrics_every_epoch\x18\x08 \x01(\x08\x12\x19\n\x11\x64\x65tection_2d_path\x18\t \x01(\tb\x06proto3'
,
dependencies=[second_dot_protos_dot_optimizer__pb2.DESCRIPTOR,second_dot_protos_dot_preprocess__pb2.DESCRIPTOR,])
_TRAINCONFIG = _descriptor.Descriptor(
name='TrainConfig',
full_name='second.protos.TrainConfig',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='optimizer', full_name='second.protos.TrainConfig.optimizer', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='steps', full_name='second.protos.TrainConfig.steps', index=1,
number=2, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='steps_per_eval', full_name='second.protos.TrainConfig.steps_per_eval', index=2,
number=3, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='save_checkpoints_secs', full_name='second.protos.TrainConfig.save_checkpoints_secs', index=3,
number=4, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='save_summary_steps', full_name='second.protos.TrainConfig.save_summary_steps', index=4,
number=5, type=13, cpp_type=3, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='enable_mixed_precision', full_name='second.protos.TrainConfig.enable_mixed_precision', index=5,
number=6, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='loss_scale_factor', full_name='second.protos.TrainConfig.loss_scale_factor', index=6,
number=7, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='clear_metrics_every_epoch', full_name='second.protos.TrainConfig.clear_metrics_every_epoch', index=7,
number=8, type=8, cpp_type=7, label=1,
has_default_value=False, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='detection_2d_path', full_name='second.protos.TrainConfig.detection_2d_path', index=8,
number=9, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=108,
serialized_end=385,
)
_TRAINCONFIG.fields_by_name['optimizer'].message_type = second_dot_protos_dot_optimizer__pb2._OPTIMIZER
DESCRIPTOR.message_types_by_name['TrainConfig'] = _TRAINCONFIG
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
TrainConfig = _reflection.GeneratedProtocolMessageType('TrainConfig', (_message.Message,), {
'DESCRIPTOR' : _TRAINCONFIG,
'__module__' : 'second.protos.train_pb2'
# @@protoc_insertion_point(class_scope:second.protos.TrainConfig)
})
_sym_db.RegisterMessage(TrainConfig)
# @@protoc_insertion_point(module_scope)
|
[
"pangsu0613@gmail.com"
] |
pangsu0613@gmail.com
|
9e81266bf495049477857e380675d6fdda9605c5
|
6d35c28f907b6ce999522ae53b98fa6ded98df6f
|
/server/corpsoftportal/corpsoftportal/wsgi.py
|
dee886c41e13032dd34908158d6bf79ad0948be8
|
[] |
no_license
|
Rassoliny/csp
|
7a5f22c0b6c969ef566b1871c097aad5fc5a38d1
|
815aa0abcf0796e67ac4a81d065d4d99243881f1
|
refs/heads/master
| 2020-04-18T06:54:56.747455 | 2019-03-11T12:24:02 | 2019-03-11T12:24:02 | 167,342,026 | 0 | 0 | null | 2019-02-11T10:14:42 | 2019-01-24T09:38:40 |
JavaScript
|
UTF-8
|
Python
| false | false | 405 |
py
|
"""
WSGI config for corpsoftportal project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/2.1/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'corpsoftportal.settings')
application = get_wsgi_application()
|
[
"dimo120@yandex.ru"
] |
dimo120@yandex.ru
|
3e7d7a968820733d5a77fff903a398968800b2e8
|
4dccaf218916f20294d2fb944c78244210636955
|
/wordladder/neighbors.py
|
2f39fc1064fad1452249909ac8e93418e46ab8bb
|
[] |
no_license
|
aaronli39/artificial_intel
|
750649495fde223fa22b83f3c82092cbb89001f4
|
3c284ac836972ec9ecc67ee10b3431bdccf4f2a3
|
refs/heads/master
| 2021-06-22T02:22:09.531412 | 2020-12-31T01:59:48 | 2020-12-31T01:59:48 | 168,211,566 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 6,231 |
py
|
#! /usr/bin/python3
import sys
def comp(a, b, end):
ac, bc = 0, 0
# print(a, b)
for i in range(4):
if a[1][i] == end[i]: ac += 1
for i in range(4):
if b[1][i] == end[i]: bc += 1
if (ac + a[0]) < (bc + b[0]): return 1
elif (ac + a[0]) == (bc + b[0]): return 0
return -1
# priority queue
class Pqueue:
# default comparison
# a and b are lists [steps, word]
def bad_cmp(self, a, b, end):
ac, bc = 0, 0
for i in range(self.len):
if a[1][i] == end[i]: ac += 1
for i in range(self.len):
if b[1][i] == end[i]: bc += 1
if (ac - a[0]) < (bc - b[0]): return -1
elif (ac - a[0]) == (bc - b[0]): return 0
return 1
def ord_cmp(self, a, b, end):
ac, bc = 0, 0
for i in range(self.len):
if a[1][i] == end[i]: ac += 1
for i in range(self.len):
if b[1][i] == end[i]: bc += 1
if (ac - a[0]) < (bc - b[0]): return 1
elif (ac - a[0]) == (bc - b[0]): return 0
return -1
# init initializes the array, size, and comparator obj
def __init__(self, length, start, result, comparator=ord_cmp):
self.data = []
self.size = 0
self.len = length
self.end = result
self.cmp_to = comparator
# push takes in 1 val, appends it, and bubbles the
# val to appropriate position
def push(self, val):
self.data.append(val)
self.size += 1
el = self.size - 1
par = int((self.size - 2) / 2)
while(self.cmp_to(self, self.data[el], self.data[par], self.end) == -1 and par >= 0):
self.data[el], self.data[par] = self.data[par], self.data[el]
el = par
par = int((par - 1) / 2)
# pushL takes in a list, appends each value in list to
# queue, and the bubbles them to their correct location
def push_all(self, data):
[self.push(i) for i in data]
return
# pop root, rearrange rest of array
def pop(self):
if self.size == 0: return None
ret = self.data[0]
# set new root as last element to bubble down
self.data[0] = self.data[self.size - 1]
self.data, self.size = self.data[:-1], self.size - 1
# starting indices with left and right children
cur = 0
left, right = 2 * cur + 1, 2 * cur + 2
# if it's just a one level tree, pop root and swap left and current if necessary
if self.size == 2 and self.cmp_to(self, self.data[cur], self.data[left], self.end) == 1:
self.data[cur], self.data[left] = self.data[left], self.data[cur]
while(left < self.size and right < self.size and
(self.cmp_to(self, self.data[cur], self.data[left], self.end) == 1 or self.cmp_to(self, self.data[cur], self.data[right], self.end) == 1)):
# if left smaller than right
if self.cmp_to(self, self.data[left], self.data[right], self.end) == 1:
# right smaller so swap right and current
self.data[cur], self.data[right] = self.data[right], self.data[cur]
cur = right
left, right = cur * 2 + 1, cur * 2 + 2
else:
# swap left and current
self.data[cur], self.data[left] = self.data[left], self.data[cur]
cur = left
left, right = cur * 2 + 1, cur * 2 + 2
return ret
# look at next root
def peek(self):
if self.size == 0: return None
return self.data[0][1]
# returns list representation of the queue
def toList(self):
ret = [self.pop() for i in self.data]
return ret
# returns the elements in the queue without popping
def internal_list(self):
return self.data
# do the actual ladder
def ladder(words, length, start, end):
queue = Pqueue(length, start, end)
neighbors, path, explored, steps = [start], [], set(), 0
while True:
steps += 1
for i in neighbors:
queue.push([steps, i, path])
# if no more elements there is no ladder
if len(queue.data) == 0: return [start, end]
val = queue.pop()
if val[1] == end: return val[2] + [val[1]]
else:
if val[1] not in explored:
explored.add(val[1])
path = val[2] + [val[1]]
neighbors = [word for word in words[val[1]] if word not in explored]
else:
path = []
neighbors = []
# general function
def do(inp, out, data, length):
# vars to use
alpha = "abcdefghijklmnopqrstuvwxyz"
words = {}
try:
with open(inp, "rU") as temp:
temp = temp.read().split("\n")
goal = []
for i in temp:
goal.append(i.split(","))
except:
print("error reading input file")
return
# create the dictionary of words of desired length
for i in data:
ind = 0
neighbors = set()
while ind < length:
for letter in alpha:
word = i[:ind] + letter + i[ind + 1:]
if word in data and word != i:
neighbors.add(word)
ind += 1
words[i] = list(neighbors)
# getting wordladder data
if goal[0][0] == "":
print("input file empty")
return
ret = []
print(goal)
for i in goal:
ret.append(ladder(words, length, i[0], i[1]))
# create write data
with open(out, "w") as temp:
for i in ret:
temp.write(",".join(i) + "\n")
return
# sys argv stuff
def main():
try:
with open(sys.argv[1], "rU") as temp:
length = len(temp.read().split("\n")[0].split(",")[0])
with open("dictall.txt", "rU") as temp:
data = set()
# create set of all 4 letter words to pass on
data = {word for word in temp.read().strip().split("\n") if len(word) == length}
except:
print("error getting input file")
do(sys.argv[1], sys.argv[2], data, length)
main()
|
[
"aaronli39@gmail.com"
] |
aaronli39@gmail.com
|
4c40cb98ca63c117e54ac2a813fc76d9104e8a5b
|
88ba7e002797738d2f7496a70158931f31992e57
|
/src/ANN/ANNTest.py
|
560f606b973aeb3685629e144e15a1a875e68462
|
[] |
no_license
|
HUbbm409/bbm406-project-what-is-this-books-genre
|
6a9464dda8ae80bf23017b2b3252cea1600ac674
|
541391f1fa11ba039374dec334161042c6315eef
|
refs/heads/master
| 2020-04-13T06:18:43.608987 | 2019-01-18T16:44:02 | 2019-01-18T16:44:02 | 163,016,881 | 0 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,822 |
py
|
from object_management.object_manager import ObjectManager
import keras
import gensim
import numpy as np
from sklearn.metrics import hamming_loss
from sklearn.metrics import zero_one_loss
import ast
import os
from pathlib import Path
def ConvertGenreListToVector(data):
genreTypes = {' Fiction': 0, ' Speculative fiction': 1, ' Science Fiction': 2, ' Novel': 3, ' Fantasy': 4,
" Children's literature": 5, ' Mystery': 6, ' Young adult literature': 7, ' Suspense': 8,
' Crime Fiction': 9, ' Historical novel': 10, ' Thriller': 11, ' Horror': 12, ' Romance novel': 13,
' Historical fiction': 14, ' Detective fiction': 15, ' Adventure novel': 16, ' Non-fiction': 17,
' Alternate history': 18, ' Spy fiction': 19, ' Comedy': 20, ' Dystopia': 21, ' Autobiography': 22,
' Satire': 23, ' Gothic fiction': 24, ' Comic novel': 25, ' Biography': 26}
labels = [] # represent books all genres as a vector
for genreList in data["GenreList"]:
vector = [0] * 27
genres = ast.literal_eval(genreList)
for genre in genres:
vector[genreTypes.get(genre)] = 1.0
labels.append(vector)
return np.array(labels)
def Word2Vec(model, data):
temp = []
for x in data:
count = 0
vector = np.zeros((300,))
for word in x.split(' '):
try:
vector += model.get_vector(word)
count += 1
except KeyError:
continue
if count == 0:
vector = np.zeros((300,))
count = 1
print(x)
temp.append(vector / count)
return temp
# -- Get data --
directory = Path().absolute()
modelFiles = os.listdir(str(directory) + "\\Model")
word2vecModel = gensim.models.KeyedVectors.load_word2vec_format('../2vecmodels/GoogleNews-vectors-negative300.bin', binary=True)
objManager = ObjectManager()
testData = objManager.ReadObject(str(directory)+"\\RecordedObject\\TestData")
file = open("log.txt","w")
for modelName in modelFiles:
file.write(str(modelName) + "\n")
model = keras.models.load_model(str(directory) + '\\Model\\' + str(modelName) )
# -- Test Data --
testSummary = testData["Summary"] # novel's summaries for test
testGenre = testData["Genre"] # novel's genres for test
tempTest = Word2Vec(word2vecModel, testSummary)
x_test = np.array(tempTest)
y_test = ConvertGenreListToVector(testData)
# Multilabel classifier
trasholdList = [0.1, 0.15, 0.175, 0.2, 0.225, 0.25, 0.275, 0.30, 0.35, 0.40, 0.45, 0.50]
# -My Prediction-
for th in trasholdList:
print("-- Trashold Value: ", th, " --")
file.write("-- Trashold Value: "+ str(th) + " --"+ "\n")
predict = model.predict(x_test, 32)
predict[predict >= th] = 1
predict[predict < th] = 0
predictionHit = 0
for i in range(predict.shape[0]):
pre = [i for i, e in enumerate(predict[i]) if e == 1]
acc = [i for i, e in enumerate(y_test[i]) if e == 1]
hitNum = 0
for j in pre:
if acc.__contains__(j):
hitNum += 1
hitRate = hitNum / len(acc)
if hitRate > 0.65:
predictionHit += 1
print('Test accuracy:', (predictionHit / predict.shape[0]))
file.write('Test accuracy:'+ str(predictionHit / predict.shape[0]) + "\n")
print("Hamming Loss:", hamming_loss(np.array(y_test),predict ))
print("Zero One Loss:", zero_one_loss(np.array(y_test),predict ))
file.write("Hamming Loss:" + str(hamming_loss(np.array(y_test),predict)) + "\n")
file.write("Zero One Loss:" + str(zero_one_loss(np.array(y_test),predict)) + "\n")
file.close()
print("Done")
|
[
"b21427559@cs.hacettepe.edu.tr"
] |
b21427559@cs.hacettepe.edu.tr
|
b5c26aa9fc4c568ff3effe6c26bb5dbcdedb889b
|
9d027df3b1295ecc49be75b2902c9e0f1089405b
|
/ingest/stuart_lab_remove_all.py
|
6594820647844b6aa97c529cc4ea3026d27fc4e6
|
[
"MIT"
] |
permissive
|
mrJeppard/clusterdb-ingest
|
5e3681f0712f830e3ffd34c802cc7221d463c0d6
|
f52f3ee03a1071ef15a63412e1e2085fdf74e584
|
refs/heads/master
| 2022-12-12T03:56:44.097278 | 2019-05-14T21:06:13 | 2019-05-14T21:06:13 | 174,733,533 | 0 | 0 |
MIT
| 2022-12-08T01:41:16 | 2019-03-09T18:49:35 |
Python
|
UTF-8
|
Python
| false | false | 2,222 |
py
|
"""
Works with a directory of anndata objects which are the result of the stuart lab
runs from October 2018
Update the data values common across the cluster solution, such as
cluster_description, method...
To run change the DATADIR and FULLPATHDB global run and run the script from the repos venv.
python stuart_lab_anndata_in.py
"""
import os, csv
import scanpy as sc
import pandas as pd
from sqlalchemy import create_engine, Table, MetaData, select
"""
# Full path to the sqllite db on bop
FULLDBPATH = "/soe/swat/cellAtlas/data/cluster.swat.db"
# Path to the data directory filled with anndata objects.
DATADIR = "/soe/swat/cellAtlas/data/cluster"
# Path to the dataset tsv file.
DATASETPATH = "/soe/swat/clusterdb-ingest/dataset.tsv"
"""
# Full path to the sqllite db for swat
FULLDBPATH = "/Users/swat/dev/cdb/cluster.db"
# Path to the data directory filled with anndata objects.
DATADIR = "/Users/swat/dev/cdbIngest/dataIn"
# Path to the dataset tsv file.
DATASETPATH = "/Users/swat/dev/cdbIngest/dataIn/dataset.tsv"
# Connection to the database.
dbstartstr = "sqlite:///%s" % FULLDBPATH
engine = create_engine(dbstartstr, echo=False)
metadata = MetaData()
conn = engine.connect()
# Accessor for each of the tables.
dataset = Table('dataset', metadata, autoload=True, autoload_with=engine)
cluster_solution_table = Table('cluster_solution', metadata, autoload=True, autoload_with=engine)
cluster = Table('cluster', metadata, autoload=True, autoload_with=engine)
cell_of_cluster = Table('cell_of_cluster', metadata, autoload=True, autoload_with=engine)
# Remove obsolete datasets from the db.
with open(DATASETPATH, 'rU') as fin:
fin = csv.DictReader(fin, delimiter='\t')
for row in fin:
dataset_delete = dataset.delete().where(dataset.c.name == row['name'])
result = conn.execute(dataset_delete)
print('deleted:', row['name'])
for name in [
'Tabula Muris facs',
'Tabula Muris droplet',
'Quake Brain',
'UCSC Human Cortex',
'Immune Bone',
'Immune Cord']:
dataset_delete = dataset.delete().where(dataset.c.name == name)
result = conn.execute(dataset_delete)
print('deleted:', name)
# Remove obsolete cluster solutions from the db
|
[
""
] | |
8c055cb19494e422d0d5bb1e656c1a374f646cbb
|
6da108db00c294a55410bde285fa7851358331df
|
/mobycity/carpooling/forms.py
|
78599ffb37b78a430fdc9db6e0e32a0c46f8eed0
|
[
"MIT"
] |
permissive
|
LucienD/Mobct
|
5639eb108922dc03dd88d62b93b8eaac0c989dae
|
1c8422b30c205bdb2dc21c988f74280194980ec4
|
refs/heads/master
| 2020-07-04T18:55:49.784534 | 2016-11-20T13:30:48 | 2016-11-20T13:30:48 | 74,147,433 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,259 |
py
|
from django import forms
from django.core.exceptions import ValidationError
from django.utils.translation import ugettext as _
from carpooling.models import Carpool
class OfferCarpoolForm(forms.ModelForm):
class Meta:
model = Carpool
fields = [
'departure_latitude',
'departure_longitude',
'arrival_latitude',
'arrival_longitude',
'frequency',
'occ_departure_datetime',
'occ_arrival_datetime',
'reg_departure_time',
'reg_arrival_time',
'seats_number',
'free',
'comment',
]
exclude = (
'organizer',
)
widgets = {
'frequency': forms.RadioSelect(),
'departure_latitude': forms.HiddenInput(),
'departure_longitude': forms.HiddenInput(),
'arrival_latitude': forms.HiddenInput(),
'arrival_longitude': forms.HiddenInput(),
'occ_departure_datetime': forms.SplitDateTimeWidget(),
'occ_arrival_datetime': forms.SplitDateTimeWidget(),
}
def clean_occ_departure_datetime(self):
if self.cleaned_data['frequency'] == 'REG':
return None
else:
if (self.cleaned_data['occ_departure_datetime']):
return self.cleaned_data['occ_departure_datetime']
else:
raise ValidationError(_('This field is required.'))
def clean_occ_arrival_datetime(self):
if self.cleaned_data['frequency'] == 'REG':
return None
else:
if (self.cleaned_data['occ_arrival_datetime']):
return self.cleaned_data['occ_arrival_datetime']
else:
raise ValidationError(_('This field is required.'))
def clean_reg_departure_time(self):
if self.cleaned_data['frequency'] == 'OCC':
return None
else:
if (self.cleaned_data['reg_departure_time']):
return self.cleaned_data['reg_departure_time']
else:
raise ValidationError(_('This field is required.'))
def clean_reg_arrival_time(self):
if self.cleaned_data['frequency'] == 'OCC':
return None
else:
if (self.cleaned_data['reg_arrival_time']):
return self.cleaned_data['reg_arrival_time']
else:
raise ValidationError(_('This field is required.'))
class SearchCarpoolForm(forms.ModelForm):
class Meta:
model = Carpool
fields = [
'departure_latitude',
'departure_longitude',
'arrival_latitude',
'arrival_longitude',
'frequency',
'occ_arrival_datetime',
'reg_arrival_time',
]
exclude = (
'organizer',
)
widgets = {
'frequency': forms.RadioSelect(),
'departure_latitude': forms.HiddenInput(),
'departure_longitude': forms.HiddenInput(),
'arrival_latitude': forms.HiddenInput(),
'arrival_longitude': forms.HiddenInput(),
'occ_arrival_datetime': forms.SplitDateTimeWidget(),
}
|
[
"luciendartois@gmail.com"
] |
luciendartois@gmail.com
|
b866f47bcedbd24a41b9e989c6316740d4e2d137
|
5b21e3b64083c5449f367a927a0f718af7a74491
|
/venv/Scripts/pip3-script.py
|
c91dffd6ff58842f226b6cdff66d4e17ad56d2ea
|
[] |
no_license
|
james-bogert/Lists_Project
|
ae257cd0005a081c0b89cad05c33d8f0f9fabbe6
|
abf81699f126f33d60cd87e19fd619c71a8042e7
|
refs/heads/master
| 2020-04-08T00:46:15.953431 | 2018-11-23T18:27:48 | 2018-11-23T18:27:48 | 158,258,045 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 403 |
py
|
#!C:\Users\jjbog\Lists_Project\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==10.0.1','console_scripts','pip3'
__requires__ = 'pip==10.0.1'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==10.0.1', 'console_scripts', 'pip3')()
)
|
[
"james.bogert@greenwoodcollege.com"
] |
james.bogert@greenwoodcollege.com
|
fc3b822caec378c8a3defbf7471bb237e7933eb6
|
bd8eb564710998df1f2d77650d357d1b3b02fbd4
|
/can/bt_plugin_can.py
|
ea56995dcbca5f67b055e7185b770431e790c486
|
[] |
no_license
|
gpollo/babeltrace-fun-plugins
|
43afd3c64004cebc6902e2f8713b3a23a980b1ea
|
7145f8647db7d9662fd37ecfe5b4265654e7b7fc
|
refs/heads/master
| 2022-02-25T17:43:51.193150 | 2019-08-16T04:34:55 | 2019-08-16T04:34:55 | 198,295,555 | 0 | 0 | null | 2019-07-22T20:14:43 | 2019-07-22T20:14:42 | null |
UTF-8
|
Python
| false | false | 9,344 |
py
|
import bt2
import cantools
class CANIterator(bt2._UserMessageIterator):
def __init__(self, port):
(self._events, self._trace_class, self._messages) = port.user_data
self._trace = self._trace_class()
self._stream_class = self._trace_class[0]
self._stream = self._trace.create_stream(self._stream_class)
self._init_msgs = [self._create_stream_beginning_message(self._stream)]
self._end_msgs = [self._create_stream_end_message(self._stream)]
self._iter = iter(self._events)
self._next = self._next_init
def _create_decoded_event(self, timestamp, frame_id, bytedata):
if len(self._messages[frame_id]) == 2:
(database, event_class) = self._messages[frame_id]
decoded_data = database.decode_message(frame_id, bytedata)
elif len(self._messages[frame_id]) == 3:
(database, event_classes, key) = self._messages[frame_id]
decoded_data = database.decode_message(frame_id, bytedata)
event_class = event_classes[decoded_data[key]]
else:
raise ValueError
event_msg = self._create_event_message(
event_class, self._stream, default_clock_snapshot=timestamp
)
for key in event_msg.event.payload_field.keys():
event_msg.event.payload_field[key] = decoded_data[key]
return event_msg
def _create_unknown_event(self, timestamp, frame_id, bytedata):
event_class = self._messages[None]
event_msg = self._create_event_message(
event_class, self._stream, default_clock_snapshot=timestamp
)
event_msg.event.payload_field["id"] = frame_id
for i in range(7):
event_msg.event.payload_field[f"byte {i}"] = bytedata[i]
return event_msg
def _next_init(self):
if len(self._init_msgs) > 0:
return self._init_msgs.pop(0)
else:
self._next = self._next_events
return self._next()
def _next_events(self):
try:
(timestamp, frame_id, bytedata) = next(self._iter)
if frame_id in self._messages:
event_msg = self._create_decoded_event(timestamp, frame_id, bytedata)
else:
event_msg = self._create_unknown_event(timestamp, frame_id, bytedata)
return event_msg
except StopIteration:
self._next = self._next_end
return self._next()
def _next_end(self):
if len(self._end_msgs) > 0:
return self._end_msgs.pop(0)
else:
raise StopIteration
def __next__(self):
return self._next()
@bt2.plugin_component_class
class CANSource(bt2._UserSourceComponent, message_iterator_class=CANIterator):
def __init__(self, params, obj):
inputs = CANSource._get_param_list(params, "inputs")
databases = CANSource._get_param_list(params, "databases")
(trace_class, messages) = self._create_trace_class_for_databases(databases)
for path in inputs:
self._create_port_for_can_trace(trace_class, messages, str(path))
def _create_trace_class_for_databases(self, databases):
messages = dict()
clock_class = self._create_clock_class(frequency=1000)
trace_class = self._create_trace_class()
stream_class = trace_class.create_stream_class(
name="can", default_clock_class=clock_class
)
print(f"created trace class {trace_class}")
event_class = CANSource._create_unknown_event_class(trace_class, stream_class)
messages[None] = event_class
print(f"created event class 'UNKNOWN' at {event_class}")
for path in databases:
CANSource._create_database_event_classes(
trace_class, stream_class, str(path), messages
)
return (trace_class, messages)
def _create_port_for_can_trace(self, trace_class, messages, path):
try:
file = open(path, "rb")
except FileNotFoundError as err:
raise ValueError(f"couldn't read {path}") from err
events = []
while True:
# Custom binary format parsing.
#
# [bytes 0 - 3] timestamp
# [bytes 4 - 7] frame ID (standard or extended)
# [bytes 8 - 15] up to 64 bits of data
msg = file.read(16)
if msg == b"":
break
timestamp = 0
timestamp += msg[0] << 0
timestamp += msg[1] << 8
timestamp += msg[2] << 16
timestamp += msg[3] << 32
frame_id = 0
frame_id += msg[4] << 0
frame_id += msg[5] << 8
data = msg[8:]
events.append((timestamp, frame_id, data))
self._add_output_port(path, (events, trace_class, messages))
@staticmethod
def _get_param_list(params, key):
if key not in params:
raise ValueError(f"missing `{key}` parameter")
param = params[key]
if type(param) != bt2.ArrayValue:
raise TypeError(
f"expecting `{key}` parameter to be a list, got a {type(param)}"
)
if len(param) == 0:
raise ValueError(f"expecting `{key}` to not be of length zero")
return param
@staticmethod
def _create_database_event_classes(trace_class, stream_class, path, messages):
try:
database = cantools.db.load_file(path)
except FileNotFoundError as err:
raise ValueError(f"database file `{path}` couldn't be read.") from err
for message in database.messages:
if message.frame_id in messages:
print(f"{message.name} already present in another database")
continue
multiplexed = False
for signal in message.signal_tree:
if isinstance(signal, str):
continue
multiplexed = True
break
if multiplexed:
(event_classes, key) = CANSource._create_multiplexed_message_classes(
trace_class, stream_class, message
)
messages[message.frame_id] = [database, event_classes, key]
print(f"created event class '{message.name}' at {event_class}")
else:
event_class = CANSource._create_message_class(
trace_class, stream_class, message
)
messages[message.frame_id] = [database, event_class]
print(f"created event class '{message.name}' at {event_class}")
@staticmethod
def _create_unknown_event_class(trace_class, stream_class):
field_class = trace_class.create_structure_field_class()
field_class.append_member("id", trace_class.create_real_field_class())
for i in range(8):
field_class.append_member(
f"byte {i}", trace_class.create_real_field_class()
)
event_class = stream_class.create_event_class(
name="UNKNOWN", payload_field_class=field_class
)
return event_class
@staticmethod
def _create_multiplexed_message_classes(trace_class, stream_class, message):
event_classes = dict()
multiplexer = None
signals = []
for signal in message.signal_tree:
if isinstance(signal, str):
signals.append(signal)
elif multiplexer is None:
multiplexer = signal
else:
raise ValueError(f"multiple multiplexer in message `{message.name}`")
if multiplexer is None or len(multiplexer) == 0:
raise ValueError(f"no multiplexer found in `{message.name}`")
if len(multiplexer) > 1:
raise ValueError(f"more than 1 multiplexer found in `{message.name}`")
key = list(multiplexer.keys())[0]
for value in multiplexer[key].keys():
field_class = trace_class.create_structure_field_class()
field_class.append_member(key, trace_class.create_real_field_class())
for signal in multiplexer[key][value]:
field_class.append_member(signal, trace_class.create_real_field_class())
for signal in signals:
field_class.append_member(signal, trace_class.create_real_field_class())
event_class = stream_class.create_event_class(
name=message.name, payload_field_class=field_class
)
event_classes[value] = event_class
return (event_classes, key)
@staticmethod
def _create_message_class(trace_class, stream_class, message):
field_class = trace_class.create_structure_field_class()
for signal in message.signals:
field_class.append_member(
signal.name, trace_class.create_real_field_class()
)
event_class = stream_class.create_event_class(
name=message.name, payload_field_class=field_class
)
return event_class
bt2.register_plugin(
module_name=__name__,
name="can",
description="CAN Format",
author="Gabriel-Andrew Pollo-Guilbert",
license="GPL",
version=(1, 0, 0),
)
|
[
"simon.marchi@polymtl.ca"
] |
simon.marchi@polymtl.ca
|
32e18a4664cd9782b3a51b71a5e8d6d18c54ee03
|
c8705c604e9dbc50c65d157f95c42f2529354bbb
|
/keras_layers/keras_layer_L2Normalization.py
|
3c5977e6a76ed021285bfd28c2762ba39cdd4fff
|
[] |
no_license
|
toschilt/object_detection_ic
|
e00b45c56865273f831b29c6017e89f92e545de6
|
bd2d8aa36c6734cdb21c517ff3bb47d174993663
|
refs/heads/main
| 2023-05-30T18:33:23.881966 | 2021-06-24T02:32:58 | 2021-06-24T02:32:58 | 342,574,861 | 0 | 0 | null | 2021-06-24T02:32:59 | 2021-02-26T12:52:28 | null |
UTF-8
|
Python
| false | false | 2,734 |
py
|
'''
A custom Keras layer to perform L2-normalization.
Copyright (C) 2018 Pierluigi Ferrari
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
from __future__ import division
import numpy as np
import keras.backend as K
import keras as keras
from keras.engine.topology import InputSpec
from keras.engine.topology import Layer
class L2Normalization(Layer):
'''
Performs L2 normalization on the input tensor with a learnable scaling parameter
as described in the paper "Parsenet: Looking Wider to See Better" (see references)
and as used in the original SSD model.
Arguments:
gamma_init (int): The initial scaling parameter. Defaults to 20 following the
SSD paper.
Input shape:
4D tensor of shape `(batch, channels, height, width)` if `dim_ordering = 'th'`
or `(batch, height, width, channels)` if `dim_ordering = 'tf'`.
Returns:
The scaled tensor. Same shape as the input tensor.
References:
http://cs.unc.edu/~wliu/papers/parsenet.pdf
'''
def __init__(self, gamma_init=20, **kwargs):
if K.image_data_format() == 'channels_last':
self.axis = 3
else:
self.axis = 1
self.gamma_init = gamma_init
super(L2Normalization, self).__init__(**kwargs)
def build(self, input_shape):
self.input_spec = [InputSpec(shape=input_shape)]
#gamma = self.gamma_init * np.ones((input_shape[self.axis],))
#self.gamma = K.variable(gamma, name='{}_gamma'.format(self.name))
#self.trainable_weights = [self.gamma]
self.gamma = self.add_weight(name='{}_gamma'.format(self.name),
shape=(input_shape[self.axis],),
initializer=keras.initializers.Constant(value=self.gamma_init),
trainable=True)
super(L2Normalization, self).build(input_shape)
def call(self, x, mask=None):
output = K.l2_normalize(x, self.axis)
return output * self.gamma
def get_config(self):
config = {
'gamma_init': self.gamma_init
}
base_config = super(L2Normalization, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
|
[
"lt.toschi@gmail.com"
] |
lt.toschi@gmail.com
|
e1267a54f015e66aaf57df060a0ebb302d36b67e
|
8d4f26bccc3b016cf45e8270df617cea73d1a741
|
/utils/transforms.py
|
4a3b38f5fe3802f8719e83a981a8f9c1740e3a2c
|
[] |
no_license
|
krylatov-pavel/aibolit-ECG
|
3b6e4fc8d87ada6a615038c7fb94048570af2d43
|
27bad875981547ea93ac0088518eb29149078988
|
refs/heads/master
| 2022-12-26T05:49:30.827061 | 2019-08-19T10:47:20 | 2019-08-19T10:47:20 | 191,343,111 | 1 | 0 | null | 2022-12-08T05:56:08 | 2019-06-11T09:53:21 |
Python
|
UTF-8
|
Python
| false | false | 631 |
py
|
import torch
from torchvision import transforms
def squeeze(x):
return torch.squeeze(x, dim=0)
def clip_fn(min, max):
def clip(x):
x = torch.clamp(x, min, max)
return x
return clip
def scale_fn(min, max, a, b):
def scale(x):
x = ((b - a) * (x - min) / (max - min)) + a
return x
return scale
def get_transform():
clip = clip_fn(-19, 21)
scale = scale_fn(-19, 21, 0, 5)
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Lambda(clip),
transforms.Lambda(scale),
transforms.Lambda(squeeze)
])
return transform
|
[
"krylatov.pavel@gmail.com"
] |
krylatov.pavel@gmail.com
|
6133612965233013406ba7cb943881799c725dd8
|
875c602f53b5775468e5a39161a0cf2bf3a4af53
|
/pipify/ShowProxy.py
|
1a8189c43ef62b8a1e97050d34e8aaa60c0641ea
|
[] |
no_license
|
cjsatuforc/fusion360-kaneka
|
87bf141e7e2a546a1a6b0a9e7260e51cb4a83c5b
|
d29037d7432be0be6fea86efabdaaf1faeb864f3
|
refs/heads/master
| 2020-05-03T12:29:24.776853 | 2018-02-09T19:18:26 | 2018-02-09T19:18:26 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 11,504 |
py
|
# (C) Copyright 2015 by Autodesk, Inc.
# Permission to use, copy, modify, and distribute this software in
# object code form for any purpose and without fee is hereby granted,
# provided that the above copyright notice appears in all copies and
# that both that copyright notice and the limited warranty and restricted
# rights notice below appear in all supporting documentation.
#
# AUTODESK PROVIDES THIS PROGRAM "AS IS" AND WITH ALL FAULTS.
# AUTODESK SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTY OF MERCHANTABILITY OR
# FITNESS FOR A PARTICULAR USE. AUTODESK, INC. DOES NOT WARRANT THAT THE
# OPERATION OF THE PROGRAM WILL BE UNINTERRUPTED OR ERROR FREE.
import adsk.core, adsk.fusion, traceback
# Global variable used to maintain a reference to all event handlers.
handlers = []
dim=0.09375
def getInputs(inputs):
try:
selection = inputs.itemById('selectEnt').selection(0)
face = selection.entity
evalType = inputs.itemById('evalType').selectedItem.name
density = int(inputs.itemById('number').value)
return(evalType, face, density)
except:
app = adsk.core.Application.get()
ui = app.userInterface
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
def add_pip(lines, ent, pip, sketchPoints):
p0 = ent.geometry.getData()[1]
# recLines = lines.addTwoPointRectangle(ent.geometry.getData()[1], ent.geometry.getData()[1])
sketchPoint = sketchPoints.add(p0)
# Move sketch point
translation = adsk.core.Vector3D.create(dim*pip*2, 0, 0)
sketchPoint.move(translation)
x = sketchPoint.geometry.x
y = sketchPoint.geometry.y
z = sketchPoint.geometry.z
p1 = adsk.core.Point3D.create(x + dim, y, z)
lines.addByTwoPoints(sketchPoint.geometry, p1)
p2 = adsk.core.Point3D.create(x + dim, y-dim, z)
lines.addByTwoPoints(p1, p2)
p3 = adsk.core.Point3D.create(x + dim*2, y-dim, z)
lines.addByTwoPoints(p2, p3)
p4 = adsk.core.Point3D.create(x + dim*2, y, z)
lines.addByTwoPoints(p3, p4)
# seg2 = lines.addByTwoPoints(ent.geometry.getData()[1], ent.geometry.getData()[1] + dim)
# seg3 = lines.addByTwoPoints(ent.geometry.getData()[1], ent.geometry.getData()[1] + dim)
# seg4 = lines.addByTwoPoints(ent.geometry.getData()[1], ent.geometry.getData()[1] + dim)
def draw(ent, num_pips):
app = adsk.core.Application.get()
ui = app.userInterface
# doc = app.documents.add(adsk.core.DocumentTypes.FusionDesignDocumentType)
design = adsk.fusion.Design.cast(app.activeProduct)
# Get the root component of the active design.
rootComp = design.rootComponent
# Create a new sketch on the xy plane.
sketches = rootComp.sketches
xyPlane = rootComp.xYConstructionPlane
sketch = sketches.add(xyPlane)
# Get sketch points
sketchPoints = sketch.sketchPoints
# Draw two connected lines.
lines = sketch.sketchCurves.sketchLines;
for x in range(num_pips):
add_pip(lines, ent, x, sketchPoints)
# ExecutePreview event handler class.
class MyExecutePreviewHandler(adsk.core.CommandEventHandler):
def __init__(self):
super().__init__()
def notify(self, args):
try:
cmdArgs = adsk.core.CommandEventArgs.cast(args)
# Get the current info from the dialog.
inputs = cmdArgs.command.commandInputs
(evalType, ent, num_pips) = getInputs(inputs)
draw(ent, num_pips)
# Set this property indicating that the preview is a good
# result and can be used as the final result when the command
# is executed.
cmdArgs.isValidResult = True
except:
app = adsk.core.Application.get()
ui = app.userInterface
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
# Called when the command is executed. However, because this command
# is using the ExecutePreview event and is setting the isValidResult property
# to true, the results created in the preview will be used as the final
# results and the Execute will not be called.
class MyExecuteHandler(adsk.core.CommandEventHandler):
def __init__(self):
super().__init__()
def notify(self, args):
try:
# Get the current info from the dialog.
inputs = args.command.commandInputs
(evalType, face, density) = getInputs(inputs)
draw(face)
except:
app = adsk.core.Application.get()
ui = app.userInterface
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
# CommandCreated event handler class.
class MyCommandCreatedHandler(adsk.core.CommandCreatedEventHandler):
def __init__(self):
super().__init__()
def notify(self, args):
try:
command = adsk.core.Command.cast(args.command)
inputs = command.commandInputs
# Create a selection input to get a selected entity from the user.
selectInput = inputs.addSelectionInput('selectEnt', 'Selection', 'Select an entity')
selectInput.addSelectionFilter('SketchLines')
selectInput.setSelectionLimits(1, 1)
# Create a text box that will be used to display the results.
textResult = inputs.addTextBoxCommandInput('textResult', '', '', 2, True)
# Create a text box that will be used to display the results.
varResult = inputs.addTextBoxCommandInput('varResult', '', '', 2, True)
# Add the selection input to get the points.
typeInput = inputs.addDropDownCommandInput('evalType', 'Huristic', adsk.core.DropDownStyles.LabeledIconDropDownStyle)
typeInput.listItems.add('Floor', True, '', -1)
typeInput.listItems.add('Ceiling', True, '', -1)
# Add the unitless value input to get the density.
densityInput = inputs.addValueInput('number', 'NumPips', '', adsk.core.ValueInput.createByString('10'))
baseDimInput = inputs.addDistanceValueCommandInput('baseDim', 'baseDimInput', adsk.core.ValueInput.createByString('3in/32'))
# Connect to the input changed event.
onInputChanged = MyInputChangedHandler()
command.inputChanged.add(onInputChanged)
handlers.append(onInputChanged)
# Connect to the execute preview and execute events.
onExecutePreview = MyExecutePreviewHandler()
command.executePreview.add(onExecutePreview)
handlers.append(onExecutePreview)
except:
app = adsk.core.Application.get()
ui = app.userInterface
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
# InputChanged event handler class.
class MyInputChangedHandler(adsk.core.InputChangedEventHandler):
def __init__(self):
super().__init__()
def notify(self, args):
try:
# Get the selection command input.
cmdInput = adsk.core.CommandInput.cast(args.input)
if cmdInput.id == 'selectEnt':
selInput = adsk.core.SelectionCommandInput.cast(cmdInput)
# Check that an entity is selected.
if selInput.selectionCount > 0:
ent = selInput.selection(0).entity
# Create a string showing the proxy path.
path = getPath(ent)
entType = ent.objectType
entType = entType.split(':')
entType = entType[len(entType)-1]
path += '/' + entType
# Get the text box command input and display the path string in it.
textResult = cmdInput.parentCommand.commandInputs.itemById('textResult')
textResult.text = path
# Get the text box command input and display the path string in it.
varResult = cmdInput.parentCommand.commandInputs.itemById('varResult')
# if It's a line then this is x, y of the first and second point.
varResult.text = "begin: (" + str(ent.geometry.getData()[1].x) + ", " + str(ent.geometry.getData()[1].y) + ")"
varResult.text += " end: (" + str(ent.geometry.getData()[2].x) + ", " + str(ent.geometry.getData()[2].y) + ")"
# If we were instpecting a point these are the x, y coords
# varResult.text = str(ent.geometry.getData()[1]) + ", " + str(ent.geometry.getData()[2])
except:
app = adsk.core.Application.get()
ui = app.userInterface
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
# Builds up the string showing the proxy path by stepping up the path from
# the proxy entity itself to each occurrence that defines its context.
def getPath(ent):
path = ''
if ent.assemblyContext:
occ = ent.assemblyContext
while occ:
if path == '':
path = occ.name
else:
path = occ.name + '/' + path
occ = occ.assemblyContext
path = 'Root/' + path
else:
path = 'Root'
return path
def run(context):
ui = None
try:
app = adsk.core.Application.get()
ui = app.userInterface
# Create a new command and connect to the command created event.
buttonDef = ui.commandDefinitions.addButtonDefinition('ekinsShowProxyPath', 'Show Proxy', 'Display the proxy path of the selected entity.', 'Resources/ShowProxy')
onCommandCreated = MyCommandCreatedHandler()
buttonDef.commandCreated.add(onCommandCreated)
handlers.append(onCommandCreated)
# Add a control for the command into the INSPECT panel.
inspectPanel = ui.allToolbarPanels.itemById('InspectPanel')
inspectPanel.controls.addCommand(buttonDef)
except:
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
def stop(context):
ui = None
try:
app = adsk.core.Application.get()
ui = app.userInterface
# Clean up all UI related to this command.
buttonDef = ui.commandDefinitions.itemById('ekinsShowProxyPath')
if buttonDef:
buttonDef.deleteMe()
inspectPanel = ui.allToolbarPanels.itemById('InspectPanel')
if inspectPanel.controls.itemById('ekinsShowProxyPath'):
inspectPanel.controls.itemById('ekinsShowProxyPath').deleteMe()
except:
if ui:
ui.messageBox('Failed:\n{}'.format(traceback.format_exc()))
|
[
"narget@umich.edu"
] |
narget@umich.edu
|
67c5c82a547f0328a5f2785a7f49e1a9f8b45785
|
1050b277f6cb4bf4535c913dcf699c51fc705dd1
|
/pysp/projects/shield/metahumans/migrations/0004_metahuman_last_update.py
|
e6025ee3ee97df1d184e5429f1ccd7eb01954743
|
[] |
no_license
|
joserequenaidv/my-eoi
|
7d680d6a48f688867eae37c1af103a54d8cf57b9
|
019d0fffbee95372eb63c378d0c93b66b6e6fedf
|
refs/heads/master
| 2022-12-06T19:52:29.703696 | 2020-08-12T14:27:38 | 2020-08-12T14:27:38 | 267,091,694 | 4 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 390 |
py
|
# Generated by Django 3.0.5 on 2020-05-04 10:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('metahumans', '0003_metahuman'),
]
operations = [
migrations.AddField(
model_name='metahuman',
name='last_update',
field=models.DateTimeField(auto_now=True),
),
]
|
[
"joserequenaidv@gmail.com"
] |
joserequenaidv@gmail.com
|
53de45efc62f9e11b91f03a858fe16a54ff85139
|
bc105a7586ed67a352430563d36770078f2b3a29
|
/most-recent-seasonal-spotify-playlist-generator.py
|
201c6dca176ea15c06ff02e4be8530bd6769e48f
|
[] |
no_license
|
neasatang/seasonal-spotify-playlist-generator
|
1692957deccb56fa49c85cfe05d4416a3ce79a64
|
843a8175bf8f62294656d1da30e86f300bfd34d4
|
refs/heads/master
| 2023-02-08T00:55:18.594188 | 2020-12-29T16:01:11 | 2020-12-29T16:01:11 | 239,403,536 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,688 |
py
|
import os
import datetime
import spotipy
from spotipy.oauth2 import SpotifyOAuth
spring_months = ("02", "03", "04")
summer_months = ("05", "06", "07")
autumn_months = ("08", "09", "10")
winter_months = ("01", "11", "12")
seasons = {
"01": winter_months,
"04": spring_months,
"07": summer_months,
"10": autumn_months
}
def get_season(month):
if month in ("01","11","12"):
return " Winter '", "❄"
elif month in ("02","03","04"):
return " Spring '", "🌸"
elif month in ("05", "06", "07"):
return " Summer '", "🌞"
else:
return " Autumn '", "🍂"
def add_to_specific_season_playlist(year, month, track, months):
season = get_season(month)
if month == "01":
change_year = int(year) - 1
year = str(change_year)
playlist_name = season[0] + year[-2:] + " " + season[1]
playlist_exists = False
playlist_id = ""
user_playlists = sp.current_user_playlists()
for item in user_playlists["items"]:
if playlist_name == item['name']:
playlist_id = item["id"]
playlist_exists = True
if playlist_exists is False:
newly_created_playlist = sp.user_playlist_create(os.environ["USER_ID"], playlist_name, description= "Automatically generated playlist for" + season[0] + year[-2:] + season[1] + " https://github.com/neasatang/monthly-spotify-playlist-generator" )
playlist_id = newly_created_playlist["id"]
sp.playlist_add_items(playlist_id, {track})
scope = "playlist-modify-public"
sp = spotipy.Spotify(auth_manager=SpotifyOAuth(scope=scope))
results = sp.current_user_playlists()
playlist = sp.playlist(os.environ["PLAYLIST_ID"])
total = playlist["tracks"]["total"]
offset = 0
temp_offset = 0
while offset != total:
playlist_tracks = sp.playlist_items(os.environ["PLAYLIST_ID"], offset=offset)
for item in playlist_tracks["items"]:
date = item["added_at"].split("-")
now = datetime.datetime.now()
previous_month = str(now.month-1)
# edge case
if previous_month == "0":
previous_month = "12"
if len(previous_month) < 2:
previous_month = "0" + previous_month
if previous_month in seasons and str(now.year) == date[0] and \
date[1] in seasons.get(previous_month):
if item["track"] is not None:
track_id = item["track"]["id"]
if track_id is not None:
add_to_specific_season_playlist(date[0], date[1], track_id, seasons.get(previous_month))
new_track_id = sp.track(track_id)
temp_offset += 1
offset = temp_offset
|
[
"tangn@tcd.ie"
] |
tangn@tcd.ie
|
033a0c1772872da6d3ec1735dadf3faddd9151e8
|
9fe8442df6f27791f8798d5905969a85ae705dd4
|
/Python_Stack/Django/Django_Orm/Users_Shell/Shell_App/models.py
|
f638bb1644c0850de0525c46a0966d2155c451dc
|
[] |
no_license
|
cpugao/Python
|
225493da5d1c8f146680182cd2951d81c5a087ff
|
77a8d6f884543ae6679d9635a1eb96d6dda3bc10
|
refs/heads/master
| 2022-12-21T11:23:22.624304 | 2020-09-08T07:34:58 | 2020-09-08T07:34:58 | 293,735,920 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 380 |
py
|
from django.db import models
class User(models.Model):
first_name = models.CharField(max_length=255)
last_name = models.CharField(max_length=255)
email_address = models.EmailField(max_length=255)
age = models.IntegerField()
created_at = models.DateTimeField(auto_now_add=True)
updated_at = models.DateTimeField(auto_now=True)
# Create your models here.
|
[
"cpugao@yahoo.com"
] |
cpugao@yahoo.com
|
df87989ac6e9817600210b00a6107f9f117640db
|
40dc0e7a24ff1ef5fb932b44cb663acd71df31fe
|
/AlphaZero_Gomoku-master/human_play.py
|
b617f0dea3383b34bdde3cf7c28d37ce05809a08
|
[
"MIT"
] |
permissive
|
channerduan01/gomoku
|
42e558528fb93bd50b585e32538e822c4a3279a9
|
0b759ab8b6633190fc205f00e34d6947ef8871bd
|
refs/heads/master
| 2021-01-10T13:31:55.148620 | 2019-05-05T03:08:28 | 2019-05-05T03:08:28 | 50,356,694 | 0 | 1 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,043 |
py
|
# -*- coding: utf-8 -*-
"""
human VS AI models
Input your move in the format: 2,3
@author: Junxiao Song
"""
from __future__ import print_function
import pickle
from game import Board, Game
from mcts_pure import MCTSPlayer as MCTS_Pure
from mcts_alphaZero import MCTSPlayer
from policy_value_net_numpy import PolicyValueNetNumpy
# from policy_value_net import PolicyValueNet # Theano and Lasagne
# from policy_value_net_pytorch import PolicyValueNet # Pytorch
# from policy_value_net_tensorflow import PolicyValueNet # Tensorflow
# from policy_value_net_keras import PolicyValueNet # Keras
class Human(object):
"""
human player
"""
def __init__(self):
self.player = None
def set_player_ind(self, p):
self.player = p
def get_action(self, board):
try:
location = input("Your move: ")
if isinstance(location, str): # for python3
location = [int(n, 10) for n in location.split(",")]
move = board.location_to_move(location)
except Exception as e:
move = -1
if move == -1 or move not in board.availables:
print("invalid move")
move = self.get_action(board)
return move
def __str__(self):
return "Human {}".format(self.player)
def run():
# print("!!!!!!!!!!")
n = 5
width, height = 8, 8
model_file = 'best_policy_8_8_5.model'
try:
board = Board(width=width, height=height, n_in_row=n)
game = Game(board)
# ############### human VS AI ###################
# load the trained policy_value_net in either Theano/Lasagne, PyTorch or TensorFlow
# best_policy = PolicyValueNet(width, height, model_file = model_file)
# mcts_player = MCTSPlayer(best_policy.policy_value_fn, c_puct=5, n_playout=400)
# load the provided model (trained in Theano/Lasagne) into a MCTS player written in pure numpy
try:
policy_param = pickle.load(open(model_file, 'rb'))
except:
policy_param = pickle.load(open(model_file, 'rb'),
encoding='bytes') # To support python3
best_policy = PolicyValueNetNumpy(width, height, policy_param)
# best_policy = PolicyValueNet(width, height, model_file)
mcts_player = MCTSPlayer(best_policy.policy_value_fn,
c_puct=5,
n_playout=400) # set larger n_playout for better performance
# uncomment the following line to play with pure MCTS (it's much weaker even with a larger n_playout)
# mcts_player = MCTS_Pure(c_puct=5, n_playout=1000)
# human player, input your move in the format: 2,3
human = Human()
# set start_player=0 for human first
game.start_play(human, mcts_player, start_player=1, is_shown=1)
# game.start_self_play(mcts_player, is_shown=1)
except KeyboardInterrupt:
print('\n\rquit')
if __name__ == '__main__':
run()
|
[
"xiuchan.dc@antfin.com"
] |
xiuchan.dc@antfin.com
|
1b6973b7da92004e47d0485666a2fa1e91eead94
|
310bfe2d33786fb4af8ef9c74149649a6c735d34
|
/cnn_processor.py
|
434a6cb36151f9ca71d57f3afd22659a222e3e4a
|
[] |
no_license
|
hanayashiki/FindEmotionalWords
|
472e62351b86db34ffcfd8c880b2703da4f96f8b
|
333affee5c61fcc074cfa2727e7616974a9aac35
|
refs/heads/master
| 2021-08-11T19:18:47.166614 | 2017-11-14T02:55:45 | 2017-11-14T02:55:45 | 109,950,597 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 764 |
py
|
import tensorflow as tf
from settings_cnn import *
import test_cnn
optimizer, losses, sigmoid_output, accuracy, one_zero = test_cnn.build()
def process(x_data):
sess = tf.Session()
saver = tf.train.Saver()
sess.run(tf.global_variables_initializer())
saver.restore(sess, model_path)
y = sess.run(one_zero, feed_dict={test_cnn.xs: x_data})
to_ret = []
for y_line in y:
emotion_obj_list = []
for idx in range(len(y_line)):
if y_line[idx] == 1:
emotion_obj_list.append((idx // sequence_length + 1, idx % sequence_length + 1))
to_ret.append(emotion_obj_list)
print(emotion_obj_list)
#print(y)
#print(to_ret)
return to_ret
if __name__ == '__main__':
process()
|
[
"494450105@qq.com"
] |
494450105@qq.com
|
8abbdd180f33166add8aa0e2afc8656a3e61eb68
|
198dd2fd5b2aa27b950bd5844c97a1ebdbd3af17
|
/dephell/repositories/_local.py
|
90ceb7d1f9c1045a3bc1c9a026ebe0a9eea2cb71
|
[
"MIT"
] |
permissive
|
espdev/dephell
|
68411b20c1830836dcea0eec96a8bd15e95171d5
|
17d5604e7b443b4d58bffc635a139adb49431efc
|
refs/heads/master
| 2020-11-26T01:05:07.580285 | 2019-12-20T14:29:07 | 2019-12-20T14:29:07 | 228,915,765 | 0 | 0 |
MIT
| 2019-12-18T20:24:21 | 2019-12-18T20:24:20 | null |
UTF-8
|
Python
| false | false | 4,172 |
py
|
# built-in
from datetime import datetime
from pathlib import Path
from typing import Optional, Tuple, Union
# app
from ..cache import RequirementsCache
from ..config import Config
from ..constants import FILES
from ..models.release import Release
from ._warehouse import WarehouseLocalRepo
from .base import Interface
class LocalRepo(Interface):
def __init__(self, path: Union[Path, str]):
if type(path) is str:
path = Path(path)
self.path = path
def get_releases(self, dep) -> Tuple[Release, ...]:
releases = []
dist_path = (self.path / 'dist')
if dist_path.exists():
repo = WarehouseLocalRepo(name='tmp', path=dist_path)
releases = list(repo.get_releases(dep=dep))
root = self.get_root(name=dep.name, version='0.0.0')
self.update_dep_from_root(dep=dep, root=root)
releases.append(Release(
raw_name=root.raw_name,
version=root.version,
time=datetime.fromtimestamp(self.path.stat().st_mtime),
))
return tuple(reversed(releases))
async def get_dependencies(self, name: str, version: str, extra: Optional[str] = None) -> tuple:
cache = RequirementsCache('local', 'deps', name, str(version))
deps = cache.load()
if deps:
return deps
root = self.get_root(name=name, version=version)
deps = root.dependencies
if extra:
deps = tuple(dep for dep in deps if extra in dep.envs)
cache.dump(root=root)
return deps
def get_root(self, name: str, version: str):
from ..converters import EggInfoConverter, SDistConverter, WheelConverter, CONVERTERS
if not self.path.exists():
raise FileNotFoundError(str(self.path))
# load from file
if self.path.is_file():
for converter in CONVERTERS.values():
if converter.can_parse(path=self.path):
return converter.load(path=self.path)
raise LookupError('cannot find loader for file ' + str(self.path))
# get from wheel or sdist
patterns = (
('-*-*-*.whl', WheelConverter()),
('.tar.gz', SDistConverter()),
('.tgz', SDistConverter()),
)
for suffix, converter in patterns:
paths = tuple(self.path.glob('**/{name}-{version}{suffix}'.format(
name=name.replace('-', '_'),
version=str(version),
suffix=suffix,
)))
if paths:
path = min(paths, key=lambda path: len(path.parts))
return converter.load(path=path)
# read from egg-info
path = self.path / (name + '.egg-info')
if path.exists():
return EggInfoConverter().load(path=path)
# read from dephell config
path = self.path / 'pyproject.toml'
if path.exists():
config = Config().attach_file(path=path, env='main')
if config is not None:
section = config.get('to') or config.get('from')
if section and 'path' in section and 'format' in section:
converter = CONVERTERS[section['format']]
path = self.path.joinpath(section['path'])
return converter.load(path)
# get from dependencies file
for fname in FILES:
path = self.path / fname
if not path.exists():
continue
for converter in CONVERTERS.values():
if converter.can_parse(path=path):
return converter.load(path=path)
raise LookupError('cannot find dependencies in ' + str(self.path))
@staticmethod
def update_dep_from_root(dep, root) -> None:
if not dep.description:
dep.description = root.description
if not dep.authors:
dep.authors = root.authors
if not dep.links:
dep.links = root.links
if not dep.classifiers:
dep.classifiers = root.classifiers
if not dep.license:
dep.license = root.license
|
[
"master_fess@mail.ru"
] |
master_fess@mail.ru
|
635ba9cef3c47552319481c624406b556a3d4b17
|
ac5e52a3fc52dde58d208746cddabef2e378119e
|
/exps-sblp-obt/sblp_ut=3.5_rd=1_rw=0.04_rn=4_u=0.075-0.325_p=harmonic-2/sched=RUN_trial=0/params.py
|
aff20aa8732740d3ec888ec12ac9538f67a70364
|
[] |
no_license
|
ricardobtxr/experiment-scripts
|
1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1
|
7bcebff7ac2f2822423f211f1162cd017a18babb
|
refs/heads/master
| 2023-04-09T02:37:41.466794 | 2021-04-25T03:27:16 | 2021-04-25T03:27:16 | 358,926,457 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 247 |
py
|
{'cpus': 4,
'duration': 30,
'final_util': '3.570619',
'max_util': '3.5',
'periods': 'harmonic-2',
'release_master': False,
'res_distr': '1',
'res_nmb': '4',
'res_weight': '0.04',
'scheduler': 'RUN',
'trial': 0,
'utils': 'uni-medium-3'}
|
[
"ricardo.btxr@gmail.com"
] |
ricardo.btxr@gmail.com
|
0e056bd4bb9433bc9d9431ddbca1ea8006b3f319
|
dcb57598b4b7f9fb7a25f847574b227824b5420c
|
/tests/integration_tests/test_features.py
|
53172ef02b0bf7875a94cad0a5af4b9fa26394f8
|
[
"MIT"
] |
permissive
|
netor27/features-webapp
|
473a0f393bea5d30d654d1880869fe8daebe4c5b
|
801d582975de7734c90bf0a4c95f404cbf305e86
|
refs/heads/master
| 2021-05-11T07:36:06.494569 | 2018-05-08T17:54:15 | 2018-05-08T17:54:15 | 118,023,763 | 0 | 2 |
MIT
| 2018-05-08T17:54:16 | 2018-01-18T18:48:42 |
Python
|
UTF-8
|
Python
| false | false | 17,571 |
py
|
import pytest
from unittest import TestCase
from flask import url_for, json
from datetime import date
from web.server import create_app
from web.db import db
from web.status import status
from web.models import Feature
from tests.integration_tests.post_helpers import PostHelper
class FeaturesTests(TestCase):
@pytest.fixture(autouse=True)
def transact(self, request, configfile, waitForDb):
self.app = create_app(configfile, waitForDb)
self.test_client = self.app.test_client()
self.app_context = self.app.app_context()
self.app_context.push()
self.test_user_name = 'testuserusers'
self.test_user_password = 'T3s!p4s5w0RDd12#'
self.ph = PostHelper(self.test_client, self.test_user_name, self.test_user_password)
db.create_all()
yield
db.session.remove()
db.drop_all()
self.app_context.pop()
def test_create_and_retrieve_feature(self):
"""
Ensure we can create a new Feature and then retrieve it
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create a new feature, assert we receive a 201 http code and and assert there's only one Feature in the db
title = 'New Feature Title'
description = 'Description ' * 10
target_date = date(2018, 6, 15)
priority = 1
client = 'Client 1'
area = 'Billing'
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
self.assertEqual(Feature.query.count(), 1)
# check that the returned values in the post response are correct
post_res_data = json.loads(post_res.get_data(as_text=True))
self.assertEqual(post_res_data['title'], title)
self.assertEqual(post_res_data['description'], description)
self.assertEqual(post_res_data['target_date'], target_date.isoformat())
self.assertEqual(post_res_data['client_priority'], priority)
self.assertEqual(post_res_data['client']['name'], client)
self.assertEqual(post_res_data['area']['name'], area)
# get the new feature url, retrieve it and assert the correct values
feature_url = post_res_data['url']
res = self.test_client.get(
feature_url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['title'], title)
self.assertEqual(res_data['description'], description)
self.assertEqual(res_data['target_date'], target_date.isoformat())
self.assertEqual(res_data['client_priority'], priority)
self.assertEqual(res_data['client']['name'], client)
self.assertEqual(res_data['area']['name'], area)
def test_retrieve_features_list(self):
"""
Ensure we can retrieve the features list
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create 4 features and assert the response
for i in range(1, 5):
title = 'New Feature Title {}'.format(i)
description = 'Description {}'.format(i)
target_date = date(2018, 6, i)
priority = i
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# assert we only have this 4
self.assertEqual(Feature.query.count(), 4)
# retrieve the complete list of features, it should return only the 4 we created
url = url_for('api.featurelistresource', _external=True)
res = self.test_client.get(
url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['count'], 4)
def test_update_feature(self):
"""
Ensure we can update the name for an existing feature
"""
# create our user so we can authenticate and create the feature
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create a new feature, assert we receive a 201 http code and and assert there's only one Feature in the db
title = 'New Feature Title'
description = 'Description ' * 10
target_date = date(2018, 6, 15)
priority = 1
client = 'Client 1'
area = 'Billing'
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
self.assertEqual(Feature.query.count(), 1)
post_res_data = json.loads(post_res.get_data(as_text=True))
# Create a new area and a new client, so we test we can update those too
area = "New Area"
res = self.ph.create_area(area)
self.assertEqual(res.status_code, status.HTTP_201_CREATED, res.get_data(as_text=True))
client = "New Client"
res = self.ph.create_client(client)
self.assertEqual(res.status_code, status.HTTP_201_CREATED, res.get_data(as_text=True))
# Create the patch request with the updated values
feature_url = post_res_data['url']
title = 'Updated Title'
description = 'Updated Description ' * 10
target_date = date(2018, 5, 19)
priority = 15
data = {'title': title, 'description': description, 'target_date': target_date.isoformat(),
'client_priority': priority, 'client': client, 'area': area}
patch_response = self.test_client.patch(
feature_url,
headers=self.ph.get_authentication_headers(),
data=json.dumps(data))
self.assertEqual(patch_response.status_code,
status.HTTP_200_OK, patch_response.get_data(as_text=True))
# retrieve the updated feature and validate the name is the same as the updated value
res = self.test_client.get(
feature_url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK, res.get_data(as_text=True))
self.assertEqual(res_data['title'], title)
self.assertEqual(res_data['description'], description)
self.assertEqual(res_data['target_date'], target_date.isoformat())
self.assertEqual(res_data['client_priority'], priority)
self.assertEqual(res_data['area']['name'], area)
self.assertEqual(res_data['client']['name'], client)
def test_features_priority_adjustment_when_adding_a_new_feature(self):
"""
Ensure that when creating a new feature that has the same priority as another one it should adjust the priorities
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create 4 features and assert the response
for i in range(10):
title = 'Title {}'.format(i+1)
description = 'Description {}'.format(i+1)
target_date = date(2018, 6, 1)
priority = i+1
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(title, description, target_date, priority, client, area)
self.assertEqual(post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# assert we only have this 10 features (with priorities from 1 to 10)
self.assertEqual(Feature.query.count(), 10)
# create a new one with priority 5, so the service must update all the priorities that are higher than 5
title = 'New Feature'
description = 'Description'
target_date = date(2018, 6, i)
priority = 5
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(title, description, target_date, priority, client, area)
self.assertEqual(post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# Query all the priorities and verify they are updated correctly
url = url_for('api.featurelistresource', _external=True, page=1, size=11)
res = self.test_client.get(
url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['count'], 11)
# because it's a new db for this test, the id should be the same as the priority before we updated them
features = res_data['results']
for i in range(11):
id = features[i]['id']
priority = features[i]['client_priority']
if id <= 4:
self.assertEqual(priority, id)
elif id == 11:
self.assertEqual(priority, 5)
else:
self.assertEqual(priority, id + 1)
def test_features_priority_adjustment_when_updating_an_existing_feature(self):
"""
Ensure that when updating a feature that has the same priority as another one it should adjust the priorities
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create the first feature, that we will update later
title = 'Title 1'
description = 'Description 1'
target_date = date(2018, 6, 1)
priority = 1
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(title, description, target_date, priority, client, area)
res_data = json.loads(post_res.get_data(as_text=True))
self.assertEqual(post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
feature_url = res_data['url']
# create other 9 features and assert the response
for i in range(1,10):
title = 'Title {}'.format(i+1)
description = 'Description {}'.format(i+1)
target_date = date(2018, 6, 1)
priority = i+1
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(title, description, target_date, priority, client, area)
res_data = json.loads(post_res.get_data(as_text=True))
self.assertEqual(post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# assert we only have this 10 features (with priorities from 1 to 10)
self.assertEqual(Feature.query.count(), 10)
# update a feature with priority 1 to priority 2, so the service must update all the priorities that are higher or equal than 2
priority = 2
data = {'client_priority': priority}
patch_response = self.test_client.patch(
feature_url,
headers=self.ph.get_authentication_headers(),
data=json.dumps(data))
self.assertEqual(patch_response.status_code,
status.HTTP_200_OK, patch_response.get_data(as_text=True))
# Query all the priorities and verify they are updated correctly
url = url_for('api.featurelistresource', _external=True, page=1, size=10)
res = self.test_client.get(
url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['count'], 10)
# because it's a new db for this test, the id should be the same as the priority before we updated them
features = res_data['results']
for i in range(10):
id = features[i]['id']
priority = features[i]['client_priority']
self.assertEqual(priority, id+1)
def test_retrieve_features_list_by_area(self):
"""
Ensure we can retrieve the features list for an area
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create 4 features and assert the response
for i in range(1, 5):
title = 'New Feature Title {}'.format(i)
description = 'Description {}'.format(i)
target_date = date(2018, 6, i)
priority = i
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# create another 4 features but for another area
for i in range(1, 5):
title = 'New Feature Title {}'.format(i)
description = 'Description {}'.format(i)
target_date = date(2018, 6, i)
priority = i
client = "Client"
area = "Claims"
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# assert we only have this 8
self.assertEqual(Feature.query.count(), 8)
# retrieve the complete list of features for the first client, it should return only the 4 we created
url = url_for('api.featurelistbyarearesource', id = 1, _external=True)
res = self.test_client.get(
url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['count'], 4)
def test_retrieve_features_list_by_client(self):
"""
Ensure we can retrieve the features list for a client
"""
# create our user so we can authenticate
res = self.ph.create_user(self.test_user_name, self.test_user_password)
self.assertEqual(res.status_code, status.HTTP_201_CREATED,
res.get_data(as_text=True))
# create 4 features and assert the response
for i in range(1, 5):
title = 'New Feature Title {}'.format(i)
description = 'Description {}'.format(i)
target_date = date(2018, 6, i)
priority = i
client = "Client"
area = "Billing"
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# create another 4 features but for another area
for i in range(1, 5):
title = 'New Feature Title {}'.format(i)
description = 'Description {}'.format(i)
target_date = date(2018, 6, i)
priority = i
client = "Client 2"
area = "Billing"
post_res = self.ph.create_feature(
title, description, target_date, priority, client, area)
self.assertEqual(
post_res.status_code, status.HTTP_201_CREATED, post_res.get_data(as_text=True))
# assert we only have this 8
self.assertEqual(Feature.query.count(), 8)
# retrieve the complete list of features for the first client, it should return only the 4 we created
url = url_for('api.featurelistbyclientresource', id = 1, _external=True)
res = self.test_client.get(
url,
headers=self.ph.get_authentication_headers())
res_data = json.loads(res.get_data(as_text=True))
self.assertEqual(res.status_code, status.HTTP_200_OK,
res.get_data(as_text=True))
self.assertEqual(res_data['count'], 4)
|
[
"neto.r27@gmail.com"
] |
neto.r27@gmail.com
|
8a5e173f87c878730e0dfa0966878e78abf3d25e
|
3e5d04efc67876ddd3cc490f4254b43d81287c69
|
/task_list/urls.py
|
adea6b8465672d6033e912421b32e4fc5eebe08d
|
[] |
no_license
|
asattelmaier/django_task_list
|
f7208b94fda5b5fd30e84bc175f030acea43eb78
|
0bd949a12d63e191ac097c4dd0d05115ecc478c8
|
refs/heads/master
| 2021-09-13T11:52:14.475084 | 2018-04-29T13:56:50 | 2018-04-29T13:56:50 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 837 |
py
|
"""task_list URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from tasks.views import get_task_list
from django.contrib import admin
from django.urls import path
urlpatterns = [
path('admin/', admin.site.urls),
path('', get_task_list, name='task_list'),
]
|
[
"alexander@sattelmaier.info"
] |
alexander@sattelmaier.info
|
654213eace46387f5fd43bd5e09a377bfc08c864
|
916d152cef8955d68465e963e131e10db02e431c
|
/bin/count_lines.py
|
f3a76cbaeaa78a9165926a99eb4a4e83d20122c4
|
[] |
no_license
|
camgunz/profile
|
fa57f44f2f94eaee90e99249440435bbaa0f0b15
|
7ab9e02b3750096c6a46ff83a28dd9413d8a8d28
|
refs/heads/master
| 2021-09-26T14:12:55.968071 | 2021-09-16T15:10:44 | 2021-09-16T15:10:44 | 31,148,797 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 460 |
py
|
#!/usr/bin/env python
import sys
import os.path
def main():
total = 0
for file_name in sys.argv[1:]:
if not os.path.isfile(file_name):
continue
with open(file_name, 'r') as fobj:
line_count = len([ln for ln in fobj.readlines() if ln.strip()])
print('%s: %s' % (file_name, line_count))
total += line_count
print('------------------------------')
print(f'Total: {total}')
main()
|
[
"charles.gunyon@gmail.com"
] |
charles.gunyon@gmail.com
|
81ead41af15f2e458481b49604b4fc00b30f8ecc
|
9cbd22ce203ab7f40d6e02a7ee2b565461369b45
|
/bagbankde/items.py
|
768a82202c55a20a6a785aed852583aebad99500
|
[] |
no_license
|
hristo-grudev/bagbankde
|
a506ed6af28db7ad4c609d7fbd922d5a699b64d6
|
1afcb0454b9e498c4b4eccb233b7d2aa15823513
|
refs/heads/main
| 2023-03-26T14:09:08.641400 | 2021-03-18T14:16:31 | 2021-03-18T14:16:31 | 349,100,217 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 136 |
py
|
import scrapy
class BagbankdeItem(scrapy.Item):
title = scrapy.Field()
description = scrapy.Field()
date = scrapy.Field()
|
[
"hr.grudev@gmail.com"
] |
hr.grudev@gmail.com
|
bcc5720fc4cdcc6f82c6aabd3852ce15ab77b4e0
|
d886d3a2c1c9e117a817d60d4d29122fe49afef5
|
/test/lexTests.py
|
4d5cde4ff3ceea8ae499d385a879634d350fa9f5
|
[
"LicenseRef-scancode-scintilla"
] |
permissive
|
missdeer/Scintilla-iOS
|
e70012012af9c2a500871d59d6b52386f083983a
|
956d4fb53c2ffa135648f86b0b395f51e4136448
|
refs/heads/master
| 2022-05-16T12:28:45.315261 | 2022-04-03T08:57:27 | 2022-04-03T08:57:27 | 178,977,537 | 0 | 0 |
NOASSERTION
| 2020-01-08T01:39:51 | 2019-04-02T01:47:01 |
C++
|
UTF-8
|
Python
| false | false | 3,424 |
py
|
# -*- coding: utf-8 -*-
from __future__ import with_statement
import io, os, sys, unittest
if sys.platform == "win32":
import XiteWin as Xite
else:
import XiteQt as Xite
keywordsHTML = [
b"b body content head href html link meta "
b"name rel script strong title type xmlns",
b"function",
b"sub"
]
class TestLexers(unittest.TestCase):
def setUp(self):
self.xite = Xite.xiteFrame
self.ed = self.xite.ed
self.ed.ClearAll()
self.ed.EmptyUndoBuffer()
def AsStyled(self):
text = self.ed.Contents()
data = io.BytesIO()
prevStyle = -1
for o in range(self.ed.Length):
styleNow = self.ed.GetStyleAt(o)
if styleNow != prevStyle:
styleBuf = "{%0d}" % styleNow
data.write(styleBuf.encode('utf-8'))
prevStyle = styleNow
data.write(text[o:o+1])
return data.getvalue()
def LexExample(self, name, lexerName, keywords=None):
if keywords is None:
keywords = []
self.ed.SetCodePage(65001)
self.ed.LexerLanguage = lexerName
bits = self.ed.StyleBitsNeeded
mask = 2 << bits - 1
self.ed.StyleBits = bits
for i in range(len(keywords)):
self.ed.SetKeyWords(i, keywords[i])
nameExample = os.path.join("examples", name)
namePrevious = nameExample +".styled"
nameNew = nameExample +".new"
with open(nameExample, "rb") as f:
prog = f.read()
BOM = b"\xEF\xBB\xBF"
if prog.startswith(BOM):
prog = prog[len(BOM):]
lenDocument = len(prog)
self.ed.AddText(lenDocument, prog)
self.ed.Colourise(0, lenDocument)
self.assertEquals(self.ed.EndStyled, lenDocument)
try:
with open(namePrevious, "rb") as f:
prevStyled = f.read()
except FileNotFoundError:
prevStyled = ""
progStyled = self.AsStyled()
if progStyled != prevStyled:
with open(nameNew, "wb") as f:
f.write(progStyled)
print(progStyled)
print(prevStyled)
self.assertEquals(progStyled, prevStyled)
# The whole file doesn't parse like it did before so don't try line by line
# as that is likely to fail many times.
return
# Try partial lexes from the start of every line which should all be identical.
for line in range(self.ed.LineCount):
lineStart = self.ed.PositionFromLine(line)
self.ed.StartStyling(lineStart, mask)
self.assertEquals(self.ed.EndStyled, lineStart)
self.ed.Colourise(lineStart, lenDocument)
progStyled = self.AsStyled()
if progStyled != prevStyled:
with open(nameNew, "wb") as f:
f.write(progStyled)
self.assertEquals(progStyled, prevStyled)
# Give up after one failure
return
def testCXX(self):
self.LexExample("x.cxx", b"cpp", [b"int"])
def testPython(self):
self.LexExample("x.py", b"python",
[b"class def else for if import in print return while"])
def testHTML(self):
self.LexExample("x.html", b"hypertext", keywordsHTML)
def testASP(self):
self.LexExample("x.asp", b"hypertext", keywordsHTML)
def testPHP(self):
self.LexExample("x.php", b"hypertext", keywordsHTML)
def testVB(self):
self.LexExample("x.vb", b"vb", [b"as dim or string"])
def testLua(self):
self.LexExample("x.lua", b"lua", [b"function end"])
def testRuby(self):
self.LexExample("x.rb", b"ruby", [b"class def end"])
def testPerl(self):
self.LexExample("x.pl", b"perl", [b"printf sleep use while"])
def testD(self):
self.LexExample("x.d", b"d",
[b"keyword1", b"keyword2", b"", b"keyword4", b"keyword5",
b"keyword6", b"keyword7"])
if __name__ == '__main__':
Xite.main("lexTests")
|
[
"semyonc@iMac.local"
] |
semyonc@iMac.local
|
b8e64eea9a8b89c992011677975679292443dff5
|
259bf472d38d05ea86f23932789f5fb7f264df89
|
/projectApps/consumers.py
|
ed362646e24bf9f2b8800ab761743d1a1ce6b81f
|
[] |
no_license
|
andrewryan/ClassCollabs
|
0fc3416e5f5fed59aae6aa2fad8a2e8373a7c74b
|
e73bb0164ce8e8f64f794b4fbd1509adfa09cf96
|
refs/heads/master
| 2021-01-20T18:04:13.536089 | 2017-07-18T22:35:27 | 2017-07-18T22:35:27 | 90,900,824 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,222 |
py
|
import json
from channels import Group
from channels.auth import channel_session_user, channel_session_user_from_http
# When a user logs in, add them to the 'users' group,
# with their username and the value of 'is_logged_in',
# websockets have to be passed a JSON serializable message
@channel_session_user_from_http
def ws_connect(message):
Group('users').add(message.reply_channel)
Group('chat').add(message.reply_channel)
Group('users').send({
'text': json.dumps({
'username': message.user.username,
'is_logged_in': True
})
})
# When the user logs out remove them from the 'users' group,
# and change the is_logged_in value to false
@channel_session_user
def ws_disconnect(message):
Group('users').send({
'text': json.dumps({
'username': message.user.username,
'is_logged_in': False
})
})
Group('users').discard(message.reply_channel)
Group("chat").discard(message.reply_channel)
# Trying to send messages through websockets for chat,
# 'text' represents the data of the message being sent
def ws_message(message):
Group('chat').send({
"text": "[user] %s" % message.content['text'],
})
|
[
"aryan17@mail.csuchico.edu"
] |
aryan17@mail.csuchico.edu
|
f7eacb3ff42e16ef6d307a110f5e395dc4aaec5a
|
829dc287dbdbd1b73a65035d3be67a22ea37a140
|
/test.py
|
8411f87c1d6b22e3dd4402e562b56f07cf1916b7
|
[] |
no_license
|
JesseE/flask-prototype-sqldata
|
24a3ef0f35dc1639b10dba1eb9ef20b9b3507f5a
|
e14874eea4773893b9a5130b4fd4b643ce3212e6
|
refs/heads/master
| 2021-01-09T20:32:47.744412 | 2016-05-31T14:59:36 | 2016-05-31T14:59:36 | 60,099,240 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,437 |
py
|
from app import app
import unittest
class FlaskTestCase(unittest.TestCase):
# Ensure that flask was set up correctly
def test_index(self):
#isolated test client like selenium
tester = app.test_client(self)
response = tester.get('/login', content_type='html/text')
self.assertEqual(response.status_code, 200)
# Ensure that login page load correctly
def test_login_page_loads(self):
#isolated test client like selenium
tester = app.test_client(self)
response = tester.get('/login', content_type='html/text')
self.assertTrue(b'Please login' in response.data)
# Ensure that login page load correctly with correct credentials
def test_correct_login(self):
tester = app.test_client()
response = tester.post(
'/login',
data=dict(username="admin", password="admin"),
follow_redirects=True
)
self.assertIn(b'you were just logged in', response.data)
# Ensure that login page load correctly with incorrect credentials
def test_incorrect_login(self):
tester = app.test_client()
response = tester.post(
'/login',
data=dict(username="wrong", password="wrong"),
follow_redirects=True
)
self.assertIn(b'Invalid credentilals. please try again.', response.data)
# Ensure that login out page load correctly
def test_logout(self):
tester = app.test_client()
tester.post(
'/logout',
data=dict(username="admin", password="admin"),
follow_redirects=True
)
response = tester.get('/logout', follow_redirects=True)
self.assertIn(b'You need to login first.', response.data)
# Ensure that the main page requires login
def test_main_route_requires_login(self):
tester = app.test_client(self)
response = tester.get('/', follow_redirects=True)
self.assertTrue(b'You need to login first.' in response.data)
# Ensure that post show up on the main page
def test_post_show_up(self):
tester = app.test_client(self)
response = tester.post(
'/login',
data=dict(username="admin",password="admin"),
follow_redirects=True
)
self.assertIn(b'name:',response.data)
if __name__ == '__main__':
unittest.main()
|
[
"jesse@voorhoede.nl"
] |
jesse@voorhoede.nl
|
5b7a76806a2d1052d41fbce4748ec2feec0badda
|
3873dadd6e60a426439fbfefcff084590cd39670
|
/solver.py
|
04f717bfbda2274a9b02cda05635305feab94052
|
[] |
no_license
|
adam-urbanczyk/Eigenvalues
|
52e7a0f25501f24ee8d76f4ce2d6a49e17565813
|
5484b0be5fac95ef0a0f1f2ab9d19ddffe128e6c
|
refs/heads/master
| 2021-01-11T21:23:49.372225 | 2016-03-22T04:46:44 | 2016-03-22T04:46:44 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 14,571 |
py
|
"""
Provides Solver class and other tools for solving eigenvalue problems.
Handles all adaptive cases.
"""
from dolfin import refine, CellFunction, Constant, Measure, FunctionSpace, \
TrialFunction, TestFunction, dot, assemble, dx, DirichletBC, \
grad, SLEPcEigenSolver, Function, FacetFunction, PETScMatrix, Mesh, \
project, interpolate, ds, \
Expression, DomainBoundary
from boundary import get_bc_parts
from transforms import transform_mesh
from domains import build_mesh
import numpy as np
import time
USE_EIGEN = False
# FIXME finish EIGEN implementation
class Solver:
""" Main eigenvalue solver class. """
def __init__(self, mesh, bcList, transformList, deg=2,
bcLast=False, method='CG',
wTop='1', wBottom='1'):
"""
Initialize basic data.
Method should be either CG or CR.
"""
self.pickleMesh = None
self.mesh = mesh
self.deg = deg
self.dim = mesh.topology().dim()
self.size = self.mesh.size(self.dim)
self.exit = False
self.bcList = bcList
self.transformList = transformList
self.bcLast = bcLast
if method in {'nonconforming', 'lower bound'}:
self.method = 'CR'
self.deg = 1
else:
self.method = 'CG'
self.CGbound = (method == 'lower bound')
self.monitor = None
self.adaptive = self.upTo = self.edge = False
self.number = 10
self.target = None
self.wTop = wTop
self.wBottom = wBottom
self.space = None
def refineTo(self, size, upTo=False, edge=False):
"""
Save arguments.
Procedure is done while solving.
"""
self.upTo = upTo
self.size = size
self.edge = edge
def refineMesh(self):
""" Perform mesh refinement. """
if self.upTo:
mesh = refine_mesh_upto(self.mesh, self.size, self.edge)
else:
mesh = refine_mesh(self.mesh, self.size, self.edge)
return mesh
def __call__(self, monitor):
""" Call solvers and return eigenvalues/eigenfunctions. """
self.monitor = monitor
self.mesh = build_mesh(*self.pickleMesh)
results = list(self.solve())
results.extend(self.getGeometry())
return results
def progress(self, s):
"""
Send progress report.
Assumes monitor is a queue (as in multiprocessing), or a function.
"""
try:
self.monitor.put(s)
except:
try:
self.monitor(s)
except:
pass
time.sleep(0.01)
def newFunction(self):
""" Create a function in the appropriate FEM space. """
if not self.mesh:
self.addMesh()
if not self.space:
# space takes a long time to construct
self.space = FunctionSpace(self.mesh, 'CG', 1)
return Function(self.space)
def addMesh(self, mesh=None):
"""
Keep fully transformed mesh.
This breaks pickling.
"""
if mesh is None:
self.mesh = build_mesh(*self.pickleMesh)
self.mesh = self.refineMesh()
self.mesh = transform_mesh(self.mesh, self.transformList)
self.finalsize = self.mesh.size(self.dim)
else:
self.mesh = mesh
self.extraRefine = self.deg > 1
if self.extraRefine:
self.mesh = refine(self.mesh)
def removeMesh(self):
""" Remove mesh to restore pickling ability. """
if self.pickleMesh is None:
self.pickleMesh = [self.mesh.cells(), self.mesh.coordinates()]
self.mesh = None
def solveFor(self, number=10, target=None, exit=False):
""" Save parameters related to number of eigenvalues. """
self.number = number
self.target = target
self.exit = exit
def solve(self):
""" Find eigenvalues for transformed mesh. """
self.progress("Building mesh.")
# build transformed mesh
mesh = self.refineMesh()
# dim = mesh.topology().dim()
if self.bcLast:
mesh = transform_mesh(mesh, self.transformList)
Robin, Steklov, shift, bcs = get_bc_parts(mesh, self.bcList)
else:
Robin, Steklov, shift, bcs = get_bc_parts(mesh, self.bcList)
mesh = transform_mesh(mesh, self.transformList)
# boundary conditions computed on non-transformed mesh
# copy the values to transformed mesh
fun = FacetFunction("size_t", mesh, shift)
fun.array()[:] = bcs.array()[:]
bcs = fun
ds = Measure('ds', domain=mesh, subdomain_data=bcs)
V = FunctionSpace(mesh, self.method, self.deg)
u = TrialFunction(V)
v = TestFunction(V)
self.progress("Assembling matrices.")
wTop = Expression(self.wTop)
wBottom = Expression(self.wBottom)
#
# build stiffness matrix form
#
s = dot(grad(u), grad(v))*wTop*dx
# add Robin parts
for bc in Robin:
s += Constant(bc.parValue)*u*v*wTop*ds(bc.value+shift)
#
# build mass matrix form
#
if len(Steklov) > 0:
m = 0
for bc in Steklov:
m += Constant(bc.parValue)*u*v*wBottom*ds(bc.value+shift)
else:
m = u*v*wBottom*dx
# assemble
# if USE_EIGEN:
# S, M = EigenMatrix(), EigenMatrix()
# tempv = EigenVector()
# else:
S, M = PETScMatrix(), PETScMatrix()
# tempv = PETScVector()
if not np.any(bcs.array() == shift+1):
# no Dirichlet parts
assemble(s, tensor=S)
assemble(m, tensor=M)
else:
#
# with EIGEN we could
# apply Dirichlet condition symmetrically
# completely remove rows and columns
#
# Dirichlet parts are marked with shift+1
#
# temp = Constant(0)*v*dx
bc = DirichletBC(V, Constant(0.0), bcs, shift+1)
# assemble_system(s, temp, bc, A_tensor=S, b_tensor=tempv)
# assemble_system(m, temp, bc, A_tensor=M, b_tensor=tempv)
assemble(s, tensor=S)
bc.apply(S)
assemble(m, tensor=M)
# bc.zero(M)
# if USE_EIGEN:
# M = M.sparray()
# M.eliminate_zeros()
# print M.shape
# indices = M.indptr[:-1] - M.indptr[1:] < 0
# M = M[indices, :].tocsc()[:, indices]
# S = S.sparray()[indices, :].tocsc()[:, indices]
# print M.shape
#
# solve the eigenvalue problem
#
self.progress("Solving eigenvalue problem.")
eigensolver = SLEPcEigenSolver(S, M)
eigensolver.parameters["problem_type"] = "gen_hermitian"
eigensolver.parameters["solver"] = "krylov-schur"
if self.target is not None:
eigensolver.parameters["spectrum"] = "target real"
eigensolver.parameters["spectral_shift"] = self.target
else:
eigensolver.parameters["spectrum"] = "smallest magnitude"
eigensolver.parameters["spectral_shift"] = -0.01
eigensolver.parameters["spectral_transform"] = "shift-and-invert"
eigensolver.solve(self.number)
self.progress("Generating eigenfunctions.")
if eigensolver.get_number_converged() == 0:
return None
eigf = []
eigv = []
if self.deg > 1:
mesh = refine(mesh)
W = FunctionSpace(mesh, 'CG', 1)
for i in range(eigensolver.get_number_converged()):
pair = eigensolver.get_eigenpair(i)[::2]
eigv.append(pair[0])
u = Function(V)
u.vector()[:] = pair[1]
eigf.append(interpolate(u, W))
return eigv, eigf
def SolveExit(self):
""" Find expected exit time/torsion function. """
pass
def getGeometry(self):
""" Compute geometric factors. """
self.progress("Computing geometric factors.")
# build transformed mesh
mesh = self.refineMesh()
mesh = transform_mesh(mesh, self.transformList)
V = FunctionSpace(mesh, 'CG', 1)
u = Function(V)
u.vector()[:] = 1
# area/volume
# weight from denominator of Rayleigh
w = Expression(self.wBottom)
geometry = {}
A = geometry['A'] = assemble(u*w*dx)
# perimeter/surface area
geometry['P'] = assemble(u*w*ds)
# center of mass
x = Expression('x[0]')
y = Expression('x[1]')
cx = assemble(u*x*w*dx)/A
cy = assemble(u*y*w*dx)/A
c = [cx, cy]
if self.dim == 3:
z = Expression('x[2]')
cz = assemble(u*z*w*dx)/A
c.append(cz)
geometry['c'] = c
# moment of inertia
if self.dim == 2:
f = Expression(
"(x[0]-cx)*(x[0]-cx)+(x[1]-cy)*(x[1]-cy)",
cx=cx, cy=cy)
else:
f = Expression(
"(x[0]-cx)*(x[0]-cx)+(x[1]-cy)*(x[1]-cy)+(x[2]-cz)*(x[2]-cz)",
cx=cx, cy=cy, cz=cz)
geometry['I'] = assemble(u*f*w*dx)
# TODO: implement Gs
# TODO: implement diameter and inradius
geometry['D'] = None
geometry['R'] = None
return [geometry]
def AdaptiveSolve(self):
""" Adaptive refine and solve. """
pass
def refine_mesh(mesh, size, edge=False):
""" Refine mesh to at least given size, using one of two methods. """
dim = mesh.topology().dim()
if not edge:
# FEniCS 1.5 and 1.6 have a bug which prevents uniform refinement
while mesh.size(dim) < size:
mesh = refine(mesh)
else:
# Refine based on MeshFunction
while mesh.size(dim) < size:
print refine(mesh).size(dim)
full = CellFunction("bool", mesh, True)
print refine(mesh, full).size(dim)
mesh = refine(mesh, full)
return mesh
def refine_mesh_upto(mesh, size, edge=False):
""" Refine mesh to at most given size, using one of two methods. """
dim = mesh.topology().dim()
if mesh.size(dim) > size:
return mesh
if not edge:
while True:
# FEniCS 1.5 and 1.6 have a bug which prevents uniform refinement
mesh2 = refine(mesh)
if mesh2.size(dim) > size:
return mesh
mesh = mesh2
else:
# Refine based on MeshFunction
while True:
all = CellFunction("bool", mesh, True)
mesh2 = refine(mesh, all)
if mesh2.size(dim) > size:
return mesh
mesh = mesh2
def shiftMesh(mesh, vector):
""" Shift mesh by vector. """
mesh.coordinates()[:, :] += np.array(vector)[None, :]
def symmetrize(u, d, sym):
""" Symmetrize function u. """
if len(d) == 3:
# three dimensions -> cycle XYZ
return cyclic3D(u)
elif len(d) >= 4:
# four dimensions -> rotations in 2D
return rotational(u, d[-1])
nrm = np.linalg.norm(u.vector())
V = u.function_space()
mesh = Mesh(V.mesh())
# test if domain is symmetric using function equal 0 inside, 1 on boundary
# extrapolation will force large values if not symmetric since the flipped
# domain is different
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
if len(d) == 2:
# two dimensions given: swap dimensions
mesh.coordinates()[:, d] = mesh.coordinates()[:, d[::-1]]
else:
# one dimension given: reflect
mesh.coordinates()[:, d[0]] *= -1
# FIXME functionspace takes a long time to construct, maybe copy?
W = FunctionSpace(mesh, 'CG', 1)
try:
# testing
test = interpolate(Function(W, test.vector()), V)
# max-min should be around 1 if domain was symmetric
# may be slightly above due to boundary approximation
assert max(test.vector()) - min(test.vector()) < 1.1
v = interpolate(Function(W, u.vector()), V)
if sym:
# symmetric
pr = project(u+v)
else:
# antisymmetric
pr = project(u-v)
# small solution norm most likely means that symmetrization gives
# trivial function
assert np.linalg.norm(pr.vector())/nrm > 0.01
return pr
except:
# symmetrization failed for some reason
print "Symmetrization " + str(d) + " failed!"
return u
def cyclic3D(u):
""" Symmetrize with respect to (xyz) cycle. """
try:
nrm = np.linalg.norm(u.vector())
V = u.function_space()
assert V.mesh().topology().dim() == 3
mesh1 = Mesh(V.mesh())
mesh1.coordinates()[:, :] = mesh1.coordinates()[:, [1, 2, 0]]
W1 = FunctionSpace(mesh1, 'CG', 1)
# testing if symmetric
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
test = interpolate(Function(W1, test.vector()), V)
assert max(test.vector()) - min(test.vector()) < 1.1
v1 = interpolate(Function(W1, u.vector()), V)
mesh2 = Mesh(mesh1)
mesh2.coordinates()[:, :] = mesh2.coordinates()[:, [1, 2, 0]]
W2 = FunctionSpace(mesh2, 'CG', 1)
v2 = interpolate(Function(W2, u.vector()), V)
pr = project(u+v1+v2)
assert np.linalg.norm(pr.vector())/nrm > 0.01
return pr
except:
print "Cyclic symmetrization failed!"
return u
def rotational(u, n):
""" Symmetrize with respect to n-fold symmetry. """
# TODO: test one rotation only
V = u.function_space()
if V.mesh().topology().dim() > 2 or n < 2:
return u
mesh = V.mesh()
sum = u
nrm = np.linalg.norm(u.vector())
rotation = np.array([[np.cos(2*np.pi/n), np.sin(2*np.pi/n)],
[-np.sin(2*np.pi/n), np.cos(2*np.pi/n)]])
for i in range(1, n):
mesh = Mesh(mesh)
mesh.coordinates()[:, :] = np.dot(mesh.coordinates(), rotation)
W = FunctionSpace(mesh, 'CG', 1)
v = interpolate(Function(W, u.vector()), V)
sum += v
pr = project(sum)
if np.linalg.norm(pr.vector())/nrm > 0.01:
return pr
else:
return u
|
[
"siudej@gmail.com"
] |
siudej@gmail.com
|
526d68e7367544fddb75b1feac1d125516d58c15
|
2eca0111818adce7454e76197436fa567a0ab6bd
|
/storefront/themed_products/migrations/0003_auto_20210114_1449.py
|
c47334bfb5dc7db3481a78f5d8fa49cd1326dfff
|
[] |
no_license
|
jbar173/Storefront
|
336eedc9b75e31e8f2f1fd0015fdcbdc10bd7467
|
0a7a9cf3fd6267fb828b1b5d2f99b8ad0794db32
|
refs/heads/main
| 2023-03-28T19:08:25.633081 | 2021-03-29T16:07:07 | 2021-03-29T16:07:07 | 321,958,485 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 848 |
py
|
# Generated by Django 3.1.2 on 2021-01-14 14:49
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('orders', '0003_auto_20210113_2056'),
('themed_products', '0002_themedbouquet_theme_name'),
]
operations = [
migrations.AddField(
model_name='themedbouquet',
name='order',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='t_bouquet', to='orders.order'),
),
migrations.AlterField(
model_name='themedbouquet',
name='theme_name',
field=models.CharField(choices=[('Type', 'Type'), ('Colour', 'Colour'), ('Type and Colour', 'Type and Colour')], max_length=50, null=True),
),
]
|
[
"jb316700@gmail.com"
] |
jb316700@gmail.com
|
61f49f427b666427264c788d37ae7c6625a6b4c8
|
cc3aa2b5a08416b96cc0633647f9567864c0de58
|
/test/test3.py
|
4904b3d4897d02086ce0982afb38c6f431168874
|
[] |
no_license
|
piixeltree/testcase_generator
|
2c31be02061b3d52d729c20dce13b90d071629f9
|
d1694b5799a92b2a66f6ae5423d9881c3c45dfa4
|
refs/heads/master
| 2020-03-10T03:23:46.548505 | 2018-04-12T11:49:08 | 2018-04-12T11:49:08 | 129,163,656 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 33 |
py
|
def sub(a,b):
return (a-b,4)
|
[
"rlawodnr1203@gmail.com"
] |
rlawodnr1203@gmail.com
|
01b32f0e13acf20a01c271a146bc3a109c71506a
|
0533cdcaa13edd15d60523be1c806985f2a27be3
|
/life/addRestaurants.py
|
523f72ba7849fd028b5157a5be5b00d20fa7c69f
|
[] |
no_license
|
cs160su18/p5-junseoky21
|
bfcebb141ea9501d866707939c6435506f49664c
|
27a39c4cbc795e2f2e6805d9f3ae9fc78b2013c1
|
refs/heads/master
| 2020-03-23T11:08:27.179003 | 2018-07-22T23:19:57 | 2018-07-22T23:19:57 | 141,485,743 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 287 |
py
|
from life.models import *
Mc = Restaurant(name="McDonalds", latitude=37.8716, longitude=-122.2727)
Mc.save()
Mc = Restaurant(name="Bongo Burger", latitude=37.8653, longitude=-122.2582)
Mc.save()
Mc = Restaurant(name="Taco Bell", latitude=37.8678, longitude=-122.2576)
Mc.save()
|
[
"junseoky21@gmail.com"
] |
junseoky21@gmail.com
|
16e773d0dc3490478889f1eef2ab3f40c45177bc
|
68f119bc8d30e106df37b56993df7909ec0c95fc
|
/readbacks/apps/common/utils.py
|
8a772b631c0e4f6fa7b0e4a540cf30b524185fed
|
[
"MIT"
] |
permissive
|
argybarg/readbacks
|
7b580d8a2a733b89cd03d7eb9803fbea8ce3a585
|
6b78bc3f33e53dd0850ed40d1412e355b7cd7cd6
|
refs/heads/master
| 2020-01-22T15:16:28.978295 | 2014-05-22T22:01:26 | 2014-05-22T22:01:26 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 797 |
py
|
# https://djangosnippets.org/snippets/1259/
def truncatesmart(value, limit=80):
"""
Truncates a string after a given number of chars keeping whole words.
Usage:
{{ string|truncatesmart }}
{{ string|truncatesmart:50 }}
"""
try:
limit = int(limit)
# invalid literal for int()
except ValueError:
# Fail silently.
return value
# Make sure it's unicode
value = unicode(value)
# Return the string itself if length is smaller or equal to the limit
if len(value) <= limit:
return value
# Cut the string
value = value[:limit]
# Break into words and remove the last
words = value.split(' ')[:-1]
# Join the words and return
return ' '.join(words) + '...'
|
[
"sunstance@gmail.com"
] |
sunstance@gmail.com
|
b70b6252b5bca3bad1bd930541510f86d3f7360e
|
167c6b1238c0e3f8f17e3659ae4e34a8dff3908d
|
/task1.py
|
bbb51409030000b6d4014178effcd77099474735
|
[] |
no_license
|
Pajke123/ORS-PA-18-Homework07
|
8345ae8758601e9b42e76f0ac324adb005802727
|
fdd7c0c853f0fd70616295145e8ebef04677808f
|
refs/heads/master
| 2020-05-21T01:02:13.703392 | 2019-04-30T12:53:10 | 2019-04-30T12:53:10 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 549 |
py
|
"""
=================== TASK 1 ====================
* Name: Roll The Dice
*
* Write a script that will simulate rolling the
* dice. The script should fetch the number of times
* the dice should be "rolled" as user input.
* At the end, the script should print how many times
* each number appeared (1 - 6).
*
* Note: Please describe in details possible cases
* in which your solution might not work.
*
* Note: You can use `rand` module to simulate dice
* rolling.
===================================================
"""
# Write your script here
|
[
"noreply@github.com"
] |
Pajke123.noreply@github.com
|
7d42995cc032265dc1da6c26ba81455cc32bcebd
|
c60c199410289c1d7ec4aea00833b461e1f08f88
|
/.history/older-than/older/source-example/day2/user-list.py
|
a923e529b041db39bfa93f7bc43cb926236f86e4
|
[] |
no_license
|
ver007/pythonjumpstart
|
66fb111e6af197fad3e853b2c2d712a1b57a7d59
|
5b1f52479abd07456e2da494149e491d398f3b7d
|
refs/heads/master
| 2021-01-21T01:34:35.501870 | 2015-05-13T14:10:13 | 2015-05-13T14:10:13 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 189 |
py
|
#!/usr/bin/env python
users = [ line.split(':')[0] for line in open('/etc/passwd') if '#' not in line and '!' in line ]
users.sort()
for (i, n) in enumerate(users):
print i, ":", n
|
[
"ravi@rootcap.in"
] |
ravi@rootcap.in
|
550ed41dde0be83f539c8f99ae6123610cd360c3
|
c424cc8b499d61da10dba06cc582d271be481b5b
|
/bin/pscp
|
c6d17e566eba1c8dfd5752cbae05cfa0e8957c5f
|
[] |
no_license
|
westfly/mssh
|
c908e7a369bcb4f8c48975e4ae92f9a8b341df98
|
4cece9eb08c5d03a238fd55754b12e1551514bd1
|
refs/heads/master
| 2021-01-10T02:16:42.130330 | 2015-12-27T10:37:32 | 2015-12-27T10:37:32 | 48,640,888 | 2 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,905 |
#!/usr/bin/env python
# -*- Mode: python -*-
# Copyright (c) 2009, Andrew McNabb
# Copyright (c) 2003-2008, Brent N. Chun
"""Parallel scp to the set of nodes in hosts.txt.
For each node, we essentially do a scp [-r] local user@host:remote. This
program also uses the -q (quiet) and -C (compression) options. Note that
remote must be an absolute path.
"""
import os
import re
import sys
parent, bindir = os.path.split(os.path.dirname(os.path.abspath(sys.argv[0])))
if os.path.exists(os.path.join(parent, 'psshlib')):
sys.path.insert(0, parent)
from psshlib import psshutil
from psshlib.task import Task
from psshlib.manager import Manager
from psshlib.cli import common_parser, common_defaults
def option_parser():
parser = common_parser()
parser.usage = "%prog [OPTIONS] -h hosts.txt local remote"
parser.epilog = ("Example: pscp -h hosts.txt -l irb2 foo.txt " +
"/home/irb2/foo.txt")
parser.add_option('-r', '--recursive', dest='recursive',
action='store_true', help='recusively copy directories (OPTIONAL)')
return parser
def parse_args():
parser = option_parser()
defaults = common_defaults()
parser.set_defaults(**defaults)
opts, args = parser.parse_args()
if len(args) < 1:
parser.error('Paths not specified.')
if len(args) < 2:
parser.error('Remote path not specified.')
if not opts.host_files and not opts.host_entries:
parser.error('Hosts not specified.')
return opts, args
def do_pscp(hosts, localargs, remote, opts):
if opts.outdir and not os.path.exists(opts.outdir):
os.makedirs(opts.outdir)
if opts.errdir and not os.path.exists(opts.errdir):
os.makedirs(opts.errdir)
manager = Manager(opts)
for host, port, user in hosts:
cmd = []
if opts.common_password:
cmd += ['sshpass', '-p', opts.common_password]
cmd += ['scp', '-qC']
if opts.options:
cmd += ['-o', opts.options]
if port:
cmd += ['-P', port]
if opts.recursive:
cmd.append('-r')
if opts.extra:
cmd.extend(opts.extra)
cmd.extend(localargs)
if user:
cmd.append('%s@%s:%s' % (user, host, remote))
else:
cmd.append('%s:%s' % (host, remote))
t = Task(host, port, user, cmd, opts)
manager.add_task(t)
manager.run()
if __name__ == "__main__":
opts, args = parse_args()
localargs = args[0:-1]
remote = args[-1]
if not re.match("^/", remote):
print("Remote path %s must be an absolute path" % remote)
sys.exit(3)
hosts = psshutil.read_hosts(opts.host_files, default_user=opts.user)
if opts.host_entries:
for entry in opts.host_entries:
hosts.append(psshutil.parse_host(entry, default_user=opts.user))
do_pscp(hosts, localargs, remote, opts)
|
[
"yweiyun@gmail.com"
] |
yweiyun@gmail.com
|
|
0933da67fd790e5811ce8b580f16a0ab1a3f6a75
|
32bbbd6dbd100bbb9a2282f69ac3b7b34516347f
|
/Study/keras/keras44_cifar100_2_cnn.py
|
88e3f8742ac013b4f6a6c64966e550971666ddae
|
[] |
no_license
|
kimjh1753/AIA_Academy_Study
|
2162d4d4f1a6b8ca1870f86d540df45a8742f359
|
6022718ae7f9e5170a19c4786d096c8042894ead
|
refs/heads/master
| 2023-05-07T12:29:12.920693 | 2021-06-05T01:09:33 | 2021-06-05T01:09:33 | 324,136,796 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 1,971 |
py
|
# 1. 데이터
from tensorflow.keras.datasets import cifar100
(x_train, y_train), (x_test, y_test) = cifar100.load_data()
print(x_train.shape, y_train.shape) # (50000, 32, 32, 3) (50000, 1)
print(x_test.shape, y_test.shape) # (10000, 32, 32, 3) (10000, 1)
x_train = x_train.reshape(x_train.shape[0], x_train.shape[1], x_train.shape[2], x_train.shape[3])/255.
x_test = x_test.reshape(x_test.shape[0], x_test.shape[1], x_test.shape[2], x_test.shape[3])/255.
# OneHotEncoding
from tensorflow.keras.utils import to_categorical
y_train = to_categorical(y_train)
y_test = to_categorical(y_test)
print(y_train.shape, y_test.shape) # (50000, 100) (10000, 100)
# 2. 모델 구성
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout
model = Sequential()
model.add(Conv2D(filters=10, kernel_size=(2,2), padding='same',
strides=1, input_shape=(32, 32, 3)))
model.add(Dropout(0.2))
model.add(Conv2D(9, (2,2), padding='valid'))
model.add(Flatten())
model.add(Dense(1000, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1000, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1000, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1000, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1000, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(1000, activation='relu'))
model.add(Dense(100, activation='softmax'))
# 3. 컴파일, 훈련
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['acc'])
from tensorflow.keras.callbacks import EarlyStopping
es = EarlyStopping(monitor='loss', patience=30, mode='auto')
model.fit(x_train, y_train, epochs=2000, batch_size=2000, validation_split=0.2, verbose=1, callbacks=[es])
# 4. 평가, 예측
loss, acc = model.evaluate(x_test, y_test, batch_size=1)
print("loss : ", loss)
print("loss : ", acc)
# keras cifar100 cnn
# loss : 5.992544174194336
# loss : 0.23280000686645508
|
[
"kimjh1753@naver.com"
] |
kimjh1753@naver.com
|
ca62342c43c23dfc47000c1aae015fc88579da3b
|
f0194c40b3e5c8b9e06eb1d70af862b6e465c9ef
|
/448-Find All Numbers Disappeared in an Array.py
|
616ae2c65c2c73616b35eff000b90511868fd712
|
[] |
no_license
|
ElijahYG/Leetcode_Python
|
842ae9db71e7f70f7398aeec427ba51706fc2b26
|
79148047b27b19f1b581dd350fb9de849877bf73
|
refs/heads/master
| 2021-01-11T17:59:45.779227 | 2017-03-21T16:07:18 | 2017-03-21T16:07:18 | 79,895,401 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,019 |
py
|
'''
Given an array of integers where 1 ≤ a[i] ≤ n (n = size of array), some elements appear twice and others appear once.
Find all the elements of [1, n] inclusive that do not appear in this array.
Could you do it without extra space and in O(n) runtime? You may assume the returned list does not count as extra space.
Example:
Input:
[4,3,2,7,8,2,3,1]
Output:
[5,6]
'''
# ------------------------------------------------------------------------------
#Best Result ：此题自己没有AC，标记
# ------------------------------------------------------------------------------
class Solution(object):
def findDisappearedNumbers(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
ret = set(range(1, len(nums)+1))
ret = ret - set(nums)
return list(ret)
S = Solution()
print(S.findDisappearedNumbers([1,2,2,9,4,7,6,6,5]))
print(S.findDisappearedNumbers([]))
print(S.findDisappearedNumbers([1,1]))
# ------------------------------------------------------------------------------
# ------------------------------------------------------------------------------
#以下方法可以正常执行，但是时间不合要求TLE(Time Limit Exceeded),
# ------------------------------------------------------------------------------
# class Solution(object):
# def findDisappearedNumbers(self, nums):
# """
# :type nums: List[int]
# :rtype: List[int]
# """
# res = []
# for x in range(len(nums)):
# if (x+1) not in nums:
# res.append(x+1)
# return res
# S = Solution()
# print(S.findDisappearedNumbers([1,2,2,9,4,7,6,6,5]))
# print(S.findDisappearedNumbers([]))
# print(S.findDisappearedNumbers([1,1]))
# ------------------------------------------------------------------------------
# array = [1,2,3,2]
# print(min(array))
# for x in range(max(array)):
# print('x=%s'%x)
# else:
# print('NO')
# print(array.index(2))
|
[
"627471266@qq.com"
] |
627471266@qq.com
|
973325cd65d92a99bb447908d6527aa29d2f230e
|
b9cb9229b042be70e5c7918b9e89006bfb01d506
|
/uniforms.py
|
b142a544242f109a0ca9fc1dd063e9b507f3c877
|
[] |
no_license
|
adibenc/sentimen-aa
|
d2defbc38ab785ba4b254b8b1f3aab4af9d1f887
|
eb4d145fe51ec9baa59703dd643e5b432c97c7f2
|
refs/heads/main
| 2023-05-13T07:49:43.295866 | 2021-05-28T10:20:40 | 2021-05-28T10:20:40 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 2,724 |
py
|
import pandas as pd
import numpy as np
class BaseIO:
datas = {
"csv": None,
"xls": None,
"dataframe": None,
}
def __init__(self):
pass
def fromCsv(self, filename):
pass
def toCsv(self, filename):
pass
def toXls(self, filename):
pass
def inputFmt(self, name, filename):
return {
"name": name,
"filename": filename,
}
baseio = BaseIO()
"""
https://stackabuse com/how-to-merge-dataframes-in-pandas/#mergedataframesusingappend
pd.concat(dataframes, axis=0, join='outer', ignore_index=False, keys=None,
levels=None, names=None, verify_integrity=False, sort=False, copy=True)
Here are the most commonly used parameters for the concat() function:
objs is the list of DataFrame objects ([df1, df2, ...]) to be concatenated
axis defines the direction of the concatenation, 0 for row-wise and 1 for column-wise
join can either be inner (intersection) or outer (union)
ignore_index by default set to False which allows the index values to remain as they were in the original DataFrames, can cause duplicate index values. If set to True, it will ignore the original values and re-assign index values in sequential order
keys allows us to construct a hierarchical index. Think of it as another level of the index that appended on the outer left of the DataFrame that helps us to distinguish indices when values are not unique
"""
def concatDataframeRows(dataframes):
return pd.concat(dataframes, axis=0, join='outer')
def initialize():
crawled = [
baseio.inputFmt("ruu.minol", 'ruu.minol.csv'),
baseio.inputFmt("ruu.minol2", 'ruu.minol2.csv'),
baseio.inputFmt("ruu.minuman.beralkohol", 'ruu.minuman.beralkohol.csv'),
baseio.inputFmt("ruu.minuman.beralkohol2", 'ruu.minuman.beralkohol2.csv'),
baseio.inputFmt("ruu.miras", 'ruu.miras.csv'),
baseio.inputFmt("ruu.miras2", 'ruu.miras2.csv'),
]
useCols = [
'status_id',
'created_at',
'screen_name',
'text',
'preprocessed',
'classify_data',
'classified'
]
dataframes = []
# print(crawled)
for c in crawled:
# get classified
filen = './' + c['name'] + '.classified.csv'
print(filen)
df = pd.read_csv(filen, header=0, lineterminator='\n', usecols=useCols)
dataframes.append(df)
# preprocessor.results['sentimen.y1'][c['name']] = c
concated = concatDataframeRows(dataframes)
concated.to_csv("ruu.all.classified.csv")
initialize()
"""
'status_id', 'created_at', 'screen_name', 'text', 'preprocessed', 'classify_data', 'classified'
"""
|
[
"adib35785@gmail.com"
] |
adib35785@gmail.com
|
84cc0587d07c1b8dd4cdaa6a6736f3482679e698
|
aec4dc0c6780e1dc63fb1a840541771b2931198f
|
/app/models/follow.py
|
7a7d81cd0bdd0513286e51112a7feab36650310e
|
[] |
no_license
|
dunnjm814/mySampler
|
e1864fa8e7407eaa31a32ceec5252840d7ad5dde
|
a272ed13e19a2d6593ef6a7ae6d20441d16e9546
|
refs/heads/main
| 2023-06-14T22:50:30.477166 | 2021-07-14T00:35:03 | 2021-07-14T00:35:03 | 343,591,654 | 8 | 0 | null | 2021-07-14T00:35:04 | 2021-03-01T23:59:18 |
Python
|
UTF-8
|
Python
| false | false | 195 |
py
|
from .db import db
follows = db.Table(
"follows",
db.Column("follower_id", db.Integer, db.ForeignKey("users.id")),
db.Column("followed_id", db.Integer, db.ForeignKey("users.id"))
)
|
[
"dunnjm814@gmail.com"
] |
dunnjm814@gmail.com
|
5398a563c0de1db0f5989219d0edd118e020b7df
|
c1e4c88f57baf3b316fcf9379c318347fea63c33
|
/working files/win64/setup.py
|
b17bed60bad4a1ae1e8abcb40dd7002092b436dd
|
[] |
no_license
|
finmonster-research/midasmlpy
|
7bee72e23f964f173a7876cd0355276966349e7d
|
80c1e69eb5e6e3667afe899228df64f0c9e13bb4
|
refs/heads/master
| 2023-02-07T08:07:20.049709 | 2020-12-23T15:25:20 | 2020-12-23T15:25:20 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 570 |
py
|
from setuptools import Extension,setup
from Cython.Build import cythonize
import numpy as np
setup(
ext_modules=cythonize(Extension(
name="midasml2",
sources=[
'pyx/midasml2.pyx',
'src/wrapper1.cpp',
'src/wrapper2.cpp',
'src/fit_sgl.cpp',
'src/ld_estim.cpp'
],
language='c++',
extra_objects=["win64/lib_win64/blas_win64_MT.lib","win64/lib_win64/lapack_win64_MT.lib"],
extra_compile_args=['-w']
)
),
language='c++',
include_dirs=[np.get_include(),'include/'],
)
|
[
"jonas.striaukas@gmail.com"
] |
jonas.striaukas@gmail.com
|
12a717c45c8c69c635adf443185ebd07138871b6
|
aa39aa66215492d85c254116045e5516c40d4b80
|
/Brilliant/toy_lstm.py
|
f39f6268252c2b6b7ecd30b862929c8bbe6ff758
|
[] |
no_license
|
JoaoAreias/Artificial-intelligence
|
f7a2260ceba9a6c0bbd7d9c5db4a347c2d3a965f
|
37c99d7cb094f7e084dd4a52fac2e54e02bf1473
|
refs/heads/master
| 2021-08-02T16:16:10.380044 | 2021-07-30T14:24:06 | 2021-07-30T14:24:06 | 152,242,702 | 1 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 802 |
py
|
"""A toy LSTM to solve
brilliant.org's challanges
[INCOMPLETE]
"""
from scipy.special import expit
import numpy as np
class LSTM(object):
def __init__(self):
self.C = None
self.h = None
def _forget_gate(self):
"""Models the output of a forget gate"""
ft = np.array([1, 0, 0.5])
return self.C*ft
def _input_gate(self, X):
"""Models the output of an input gate"""
Wi = None
X = np.concatenate(self.h, X)
b = None
return expit(np.matmul(Wi, X) + b)
def _tanh_gate(self, X):
"""Creates possible new additions to the cell
state"""
Wc = None
X = np.concatenate(self.h, X)
b = None
return np.tanh(np.matmul(Wc, X) + b)
def _update_cell_state(self, X):
self.C = self._forget_gate() + self._input_gate(X)* self._tanh_gate(X)
|
[
"joaoareiasmoraes@gmail.com"
] |
joaoareiasmoraes@gmail.com
|
ea3e3e20813dd7c814e974b5e7d3ee59754282cd
|
80c315a21e1b1edeab236a6f19ec06cdfc81873d
|
/scripts/download_mggg.py
|
639054e3239bf0cb2579796c344a17b9ed819a88
|
[
"MIT"
] |
permissive
|
mcullan-redistricting/redistricting-postgis
|
0bf99787decf66d19a6d41cf26f3896c4da5f62d
|
7adef1c1e2060122004ad050eea3b1e89565ef45
|
refs/heads/master
| 2022-04-06T03:19:52.730698 | 2020-02-17T11:11:16 | 2020-02-17T11:11:16 | null | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 3,306 |
py
|
from io import BytesIO
from bs4 import BeautifulSoup
import requests
import os
import pandas as pd
from constants import STATES
from zipfile import ZipFile
data_path = os.environ.get('DATA_PATH', '../data')
def download_mggg_state_zip(state_abbreviation, filepath, overwrite = False):
url = f'https://github.com/mggg-states/{state_abbreviation}-shapefiles/archive/master.zip'
response = requests.get(url)
if response.ok:
full_path = filepath + f'/precincts-elections/'
if not os.path.exists(full_path):
os.mkdir(full_path)
zip_name = f'{state_abbreviation}-shapefiles-master.zip'
full_filepath = f'{full_path}/{zip_name}'
if overwrite or not os.path.exists(full_filepath):
with open(full_filepath, 'wb') as file:
file.write(response.content)
print(f'Extracting {state_abbreviation} zip file.')
with ZipFile(full_filepath) as file:
file.extractall(full_path)
os.remove(full_filepath)
if response.status_code == 404:
print(f'404 returned for {state_abbreviation}.')
return
def get_mggg_states_metadata(state_abbreviation):
url = f'https://github.com/mggg-states/{state_abbreviation}-shapefiles/blob/master/README.md'
response = requests.get(url)
if response.ok:
print(f'Downloaded {state_abbreviation} metadata.')
soup = BeautifulSoup(response.text, 'lxml')
metadata = soup.select('li:has(code)')
data_dict = {}
for line in metadata:
k,v = line.text.split(': ')
data_dict[k] = v
return data_dict
if response.status_code == 404:
print('Could not complete request due to 404 error.')
def download_mggg_shapefile(state_abbreviation, filepath):
url = f'https://github.com/mggg-states/{state_abbreviation}-shapefiles/raw/master/{state_abbreviation}_VTD.zip'
response = requests.get(url)
if response.ok:
print(f'Downloaded {state_abbreviation} zip file.')
full_path = filepath + f'/{state_abbreviation}_VTD'
zip_name = f'{state_abbreviation}_VTD.zip'
with open(f'{full_path}/{zip_name}', 'wb') as file:
file.write(response.content)
with ZipFile(f'{full_path}/{zip_name}') as file:
file.extractall(filepath + '/NC_VTD')
os.remove(f'{full_path}/{zip_name}')
if response.status_code == 404:
print(f'404 returned for {state_abbreviation}.')
return
def download_mggg_state(state_abbreviation, filepath):
# If directory doesn't exist, create it
full_path = filepath + f'/precincts-elections/{state_abbreviation}_VTD'
if not os.path.exists(full_path):
os.mkdir(full_path)
# Download metadata and save to constants.py
data_dict = get_mggg_states_metadata(state_abbreviation)
with open(f'{full_path}/metadata.py', 'w') as file:
file.write(f'DATA_DICT = {data_dict}')
# Download shapefile and election data
download_mggg_shapefile(state_abbreviation, filepath)
if __name__ == '__main__':
state_abbvreviations = STATES.values()
for abbreviation in list(state_abbvreviations):
download_mggg_state_zip(abbreviation, data_path)
|
[
"mjcullan@gmail.com"
] |
mjcullan@gmail.com
|
066606616f939cd8455b4c5eaeb8039be54a8ed4
|
c4e872fc1cbfd78006cfd6826f57b7db3d94c622
|
/web/pack.py
|
458c0ab36b94e98bed1c68ccfe455611c09bcad6
|
[
"Apache-2.0"
] |
permissive
|
rajeshpandit107/AccDNN
|
7049eb3e14193f59f03d61fbf7d3ed7fbfb8d22b
|
e250a0c020d0ba84f4c4ec098d58b5d1c5fb6d10
|
refs/heads/master
| 2023-03-29T22:56:08.042630 | 2021-04-09T14:58:28 | 2021-04-09T14:58:28 | 255,531,572 | 0 | 1 |
Apache-2.0
| 2020-04-14T06:45:03 | 2020-04-14T06:45:02 | null |
UTF-8
|
Python
| false | false | 910 |
py
|
#!/usr/bin/env python
from settings import *
def pack_layer_profile(layer_name, layer_type, cpf, kpf, macs, dsps, weights_num, delay, bandwidth, blks):
return {'name':layer_name, 'type':layer_type, 'cpf':cpf, 'kpf':kpf, 'macs':macs, \
'dsps':dsps, 'weights':weights_num, 'delay':delay, 'bandwidth':bandwidth, 'blks':blks}
def pack_model_profile(layer_info, batch_size, total_macs, total_dsps, \
total_weights_num, total_blks, total_ddr_bandwidth, throughput, utilization):
return {'layer_info':layer_info, 'batch_size':batch_size, 'total_macs':total_macs, \
'total_dsps': total_dsps, 'total_weights_num':total_weights_num, 'total_blks':total_blks,
'total_ddr_bandwidth':total_ddr_bandwidth, 'throughput':throughput, 'utilization':utilization}
def pack_optim_info(layer_name, cpf, kpf):
return {'name':layer_name, 'cpf':cpf, 'kpf':kpf}
|
[
"junsongw@cn.ibm.com"
] |
junsongw@cn.ibm.com
|
af26b2e4c69d706a2290188dd72518c77b79a727
|
8c6c5daf87e7335ea2450f117c8dbb20cd586b04
|
/blog/migrations/0003_auto_20190717_1433.py
|
2f5c89a127022a175d0a3dd638d17224df5fb4df
|
[] |
no_license
|
lucifer0508/demoblog
|
62cef204ee6278371e215952a6d7a641bda43e05
|
f45b0fce32e6b8a999ab68da74fe3790eb6f8fba
|
refs/heads/master
| 2020-06-21T13:50:48.224315 | 2019-07-17T22:22:54 | 2019-07-17T22:22:54 | 197,471,529 | 0 | 0 | null | null | null | null |
UTF-8
|
Python
| false | false | 400 |
py
|
# Generated by Django 2.2.3 on 2019-07-17 09:03
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('blog', '0002_blogdata_email'),
]
operations = [
migrations.AlterField(
model_name='blogdata',
name='email',
field=models.CharField(default='Empty...', max_length=40),
),
]
|
[
"markevans005@gmail.com"
] |
markevans005@gmail.com
|
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