index int64 | repo_name string | branch_name string | path string | content string | import_graph string |
|---|---|---|---|---|---|
15,674 | ohwani/molla | refs/heads/main | /post/models.py | from django.db import models
# Create your models here.
# class Post(models.Model):
# user = models.ForeignKey(settings.AUTH_USER_MODEL)
# title = models.CharField(max_length=120)
# slug = models.SlugField(unique=True)
# image = models.ImageField()
# content = models.TextField()
# create_at = m... | {"/accounts/views.py": ["/accounts/serializers.py", "/accounts/models.py"], "/accounts/serializers.py": ["/accounts/models.py"], "/accounts/models.py": ["/accounts/regex.py"]} |
15,675 | ohwani/molla | refs/heads/main | /accounts/serializers.py | # from django.contrib.auth import authenticate
from rest_framework import serializers
from rest_framework.validators import UniqueTogetherValidator
# from rest_framework_simplejwt.serializers import TokenObtainSerializer
# from rest_framework_simplejwt.tokens import RefreshToken
from .models import User
import re
c... | {"/accounts/views.py": ["/accounts/serializers.py", "/accounts/models.py"], "/accounts/serializers.py": ["/accounts/models.py"], "/accounts/models.py": ["/accounts/regex.py"]} |
15,728 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/training/__init__.py | """
The :mod:'llstring.training' module implements a trainer
which builds an IDF from raw text input (either from file or list)
"""
from .idf_trainer import IDFTrainer
__all__ = ['IDFTrainer']
| {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,729 | escap-data-hub/LLString | refs/heads/master | /examples/norm.py | #! /usr/bin/env python
# levenshtein_example.py
#
# Example script to demonstrate Levenshtein string-match classifier
#
# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "License... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,730 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/training/idf_trainer.py | #!/usr/bin/env python
# idf_trainer.py
#
# Class to learn IDF weighting from training data
#
# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie K. Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not u... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,731 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/matching/__init__.py | """
The :mod:'llstring.matching' module implements classifiers
based on basic string matching algorithms: Levenshtein Distance,
Jaro-Winkler Similarity and Soft TF-IDF Similarity.
"""
from .mitll_string_matcher import MITLLStringMatcher
from .softtfidf import Softtfidf
__all__ = ['MITLLStringMatcher','Softtfidf']
| {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,732 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/matching/mitll_string_matcher.py | #!/usr/bin/env python
# mitll_string_matcher.py
#
# MITLLSTringMatcher:
# SKLEARN compatable classifier implementing string matching techniques:
# - Levenshtein Distance
# - Jaro-Winkler
# - Soft TF-IDF
#
# Copyright 2015 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,733 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/utilities/sampling/reservoir_sampler.py | #!/usr/bin/env python
# reservoir_sampler.py
#
# Perform uniform sampling from an (possibly infinite) input stream
#
# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie K. Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "Li... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,734 | escap-data-hub/LLString | refs/heads/master | /llstring/setup.py | #! /usr/bin/env python
# setup.py
#
# Setup and Install of llstring
#
# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in complian... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,735 | escap-data-hub/LLString | refs/heads/master | /examples/soft_tfidf_example.py | #! /usr/bin/env python
# soft_tfidf_example.py
#
# Example script to demonstrate Soft TF-IDF string-match classifier
#
# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "License"... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,736 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/utilities/normalization/text_normalization.py | #!/usr/bin/env python
# text_normalization.py
#
# Generic Text Normalization Routines
#
# Copyright 2013-2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli & William M. Cambpell
# {dagli,wcampbell}@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,737 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/__init__.py | """
The :mod:'llstring' module implements classifiers
based on basic string matching algorithms (Levenshtein Distance,
Jaro-Winkler Similarity and Soft TF-IDF Similarity) as well
as provides a variety of basic string processing/normalization
tools.
"""
from pkgutil import extend_path as __extend_path
__path__ = __ext... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,738 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/utilities/normalization/__init__.py | """
The :mod:'llstring.normalization' sub-package implements
generic and latin script text normalization. Included
as well are functions for web and social media normalization.
"""
from .text_normalization import MITLLTextNormalizer
from .latin_normalization import MITLLLatinNormalizer
__all__ = ['MITLLTextNormalizer',... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,739 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/utilities/sampling/__init__.py | """
The :mod:'llstring.sampling' sub-package implements
basic reservoir sampling: one-pass uniform sampling of
a large dataset.
"""
from .reservoir_sampler import ReservoirSampler
__all__ = ['ReservoirSampler']
| {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,740 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/utilities/normalization/latin_normalization.py | #!/usr/bin/env python
# latin_normalization.py
#
# Text Normalization Routines for Latin Script Text (including for Twitter data)
#
# Copyright 2013-2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: William M. Campbell and Charlie Dagli
# {wcampbell,dagli}@ll.mit.edu
#
# License... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,741 | escap-data-hub/LLString | refs/heads/master | /llstring/llstring/matching/softtfidf.py | #!/usr/bin/env python
# softtfidf.py
#
# Soft TF-IDF String Comparison Algorithm
#
# Copyright 2015-2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli
# dagli@ll.mit.edu
#
# Original logic written by @drangons for the entity_resolution_spark repository:
# https://gi... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,742 | escap-data-hub/LLString | refs/heads/master | /examples/idf_training_example.py | #! /usr/bin/env python
# idf_training_example.py
#
# Example script to learn IDF from a training corpus
#
# Copyright 2016 Massachusetts Institute of Technology, Lincoln Laboratory
# version 0.1
#
# author: Charlie Dagli
# dagli@ll.mit.edu
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may ... | {"/llstring/llstring/training/__init__.py": ["/llstring/llstring/training/idf_trainer.py"], "/llstring/llstring/matching/__init__.py": ["/llstring/llstring/matching/mitll_string_matcher.py", "/llstring/llstring/matching/softtfidf.py"], "/llstring/llstring/matching/mitll_string_matcher.py": ["/llstring/llstring/matching... |
15,757 | pg815/Fake_News_Prediction_And_Summarization | refs/heads/main | /summa/preprocessing/util.py |
def suffix_replace(original, old, new):
"""
Replaces the old suffix of the original string by a new suffix
"""
return original[: -len(old)] + new
def prefix_replace(original, old, new):
"""
Replaces the old prefix of the original string by a new suffix
:param original: string
:param... | {"/app.py": ["/newsscraper.py"], "/newsscraper.py": ["/model.py"]} |
15,758 | pg815/Fake_News_Prediction_And_Summarization | refs/heads/main | /app.py | from flask import Flask,render_template
from newsscraper import get_news,get_titles
app = Flask("__WorldTime__")
@app.route("/")
def root():
channels = get_news()
titles = get_titles()
return render_template("index.html",channels = channels,titles = titles)
app.run(host='0.0.0.0') | {"/app.py": ["/newsscraper.py"], "/newsscraper.py": ["/model.py"]} |
15,759 | pg815/Fake_News_Prediction_And_Summarization | refs/heads/main | /model.py | from getEmbeddings import getEmbeddings
from sklearn.naive_bayes import GaussianNB
import scikitplot.plotters as skplt
from sklearn.svm import SVC
import numpy as np
import pickle
import os
class Models:
def __init__(self):
if not os.path.isfile('./xtr.npy') or \
not os.path.isfile('./xte.... | {"/app.py": ["/newsscraper.py"], "/newsscraper.py": ["/model.py"]} |
15,760 | pg815/Fake_News_Prediction_And_Summarization | refs/heads/main | /newsscraper.py | import sys
import json
from time import mktime
from datetime import datetime
import feedparser as fp
import newspaper
from newspaper import Article
from model import Models
from summarizers import summarize_textrank,summarize_tfidf,summarize_wf
data = {}
data["newspapers"] = {}
model = Models()
def parse_config(fname... | {"/app.py": ["/newsscraper.py"], "/newsscraper.py": ["/model.py"]} |
15,763 | pcaravelli-sr/milestone-2-challenge | refs/heads/master | /milestone2/merge_sort.py | def merge_sort(items):
"""
Uses merge sort algorithm to sort items from input list and return new list in sorted order
:param items: list of comparable items, e.g. [3, 1, 2] or ['z', 'x', 'y']
:return: a sorted list containing every item from the input list
"""
return []
| {"/milestone2/benchmarks/benchmarks.py": ["/milestone2/merge_sort.py"]} |
15,764 | pcaravelli-sr/milestone-2-challenge | refs/heads/master | /milestone2/benchmarks/benchmarks.py | from random import randint
from time import time
from milestone2.merge_sort import merge_sort
from milestone2.insertion_sort import insertion_sort
# Dictionary of labeled sort functions. If you decide to try writing a more optimized sort
# function, you can add it in an entry in this dictionary to see how it... | {"/milestone2/benchmarks/benchmarks.py": ["/milestone2/merge_sort.py"]} |
15,777 | jonberliner/jordan_e | refs/heads/master | /rotationExperiment.py | from numpy import sum, concatenate, repeat, linspace, abs, ndarray, arange, mean
from numpy.random import RandomState, permutation
from numpy import array as npa
def rotationExperiment(domainbounds, rotmag, nPerXOpt,\
mindegArcPool, maxdegArcPool, nEpicycle, radwrtxArc,\
m... | {"/custom.py": ["/rotationExperiment.py"]} |
15,778 | jonberliner/jordan_e | refs/heads/master | /custom.py | # this file imports custom routes into the experiment server
from flask import Blueprint, render_template, request, jsonify, Response, abort, current_app
from jinja2 import TemplateNotFound
from functools import wraps
from sqlalchemy import or_
from psiturk.psiturk_config import PsiturkConfig
from psiturk.experiment_e... | {"/custom.py": ["/rotationExperiment.py"]} |
15,789 | hemengf/my_python_lib | refs/heads/master | /door_position/batch_doorposition.py | import matplotlib.pyplot as plt
import processbar
import os
import subprocess
import time
from door_position.disks import *
for batchiter in range(8):
print 'processing iteration {:d}'.format(batchiter)
start = time.time()
env = Environment(boxsize=(0.6,0.4), \
lower_doorbnd=np.array([0,batchiter*0.02... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,790 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/findroot.py | import scipy.optimize
def F(x):
return x[0], x[1]
def g(x):
return x-1
if __name__ == "__main__":
import numpy as np
sol = scipy.optimize.fsolve(F, np.array([1,1]))
x0 = scipy.optimize.root(g, 0)
print sol
print x0.x[0]
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,791 | hemengf/my_python_lib | refs/heads/master | /door_position/passnumber_door_position_v5cm/data_analysis.py | import matplotlib.pyplot as plt
import numpy as np
if __name__ == '__main__':
iternum = 8
p = [0]*iternum
fig, ax = plt.subplots()
for i in range(iternum):
s = np.load('passnumber_list {:d}.npy'.format(i))
#ax.plot(range(len(s)), s)
pp = np.polyfit(range(len(s)),s, 1)
p[i] = pp[0]
plt.plot(rang... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,792 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/stripes_counting.py | #!/usr/bin/env python
import cookb_signalsmooth
import numpy as np
import matplotlib.pyplot as plt
import sys
from find_peaks import exact_local_maxima1D, exact_local_minima1D
def stripes_counting(datafile_name):
"""
Given a 1-D array of grayscale data, find the peak number
and the valley number.
Data ... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,793 | hemengf/my_python_lib | refs/heads/master | /Utape.py | from __future__ import division
import numpy as np
import sys
dt = sys.argv[1] #0.005
while 1:
try:
intv = input('intervels(pix): ')
s = np.mean(intv)
percenterr = np.std(intv)/s
break
except Exception as e:
print e
while 1:
try:
R = input('mm/pix rat... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,794 | hemengf/my_python_lib | refs/heads/master | /easyprompt.py | import sys
from colorama import init, Fore, Style
class easyprompt:
def __init__(self):
init()
self.count = 0
def __str__(self):
self.count += 1
print(Fore.GREEN + '(%d)>>>>>>>>>>>>>>>' % self.count)
print(Style.RESET_ALL)
sys.ps1 = easyprompt()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,795 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/basinhopping_mask_foodfill_wpreprocess_bot.py | #!/usr/bin/env python
from __future__ import division
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
from scipy.optimize import basinhopping
from scipy import fftpack
from... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,796 | hemengf/my_python_lib | refs/heads/master | /saffman_taylor.py | from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
w = 236/519
y = np.arange(-w+0.0005,w-0.0005,0.001)
plt.plot(y, ((1-w)/np.pi)*np.log((1+np.cos(np.pi*y/w))/2))
plt.axes().set_aspect('equal')
plt.xlim(-1,1)
plt.show()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,797 | hemengf/my_python_lib | refs/heads/master | /concatenate.py | from __future__ import division
import numpy as np
import sys
def split_concatenate(img1, img2, angle, sp):
"""
Takes two pictures of (e.g. red and green) interference patterns and
concatenate them in a split screen fashion for easy comparison.
The split line is the line that passes sp===split_poi... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,798 | hemengf/my_python_lib | refs/heads/master | /contrast.py | from __future__ import division
import sys
contrast='uncalculated'
if len(sys.argv)>1:
contrast = (float(sys.argv[1])-float(sys.argv[2]))/(float(sys.argv[1])+float(sys.argv[2]))
print contrast
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,799 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/check.py | import numpy as np
d = np.load('goodness.npy').item()
print d
print min(d, key=d.get)
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,800 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/red_amber.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
cmap = plt.get_cmap('tab10')
x = np.arange(0,20, 0.001)
red = 1+np.cos(4*np.pi*(x+0.630/4)/0.630)
amber = 1+ np.cos(4*np.pi*(x+0.59/4)/0.590)
#plt.plot(x, red+amber)
plt.title('red and amber')
plt.plot(x, red,color=cmap(3))
plt.plot(x, ... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,801 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/pattern_shift1D.py | from __future__ import division
import scipy.optimize
import scipy.spatial.distance
#from scipy.misc import derivative
import partial_derivative
import math
import sys
#@profile
def shape_function(x):
#return np.exp(-0.00002*((x+250)**2))
#return -0.000008*(x**2)+ float(sys.argv[1])
return 0.00000001*x + ... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,802 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/ffttest2.py | import numpy as np
import cv2
import matplotlib.pyplot as plt
image = cv2.imread('ideal.tif',0)
print image.shape
nrows = np.shape(image)[0]
ncols = np.shape(image)[1]
ftimage = np.fft.fft2(image)
ftimage = np.fft.fftshift(ftimage)
logftimage = np.log(ftimage)
plt.imshow(np.abs(logftimage))
sigmax, sigmay = 10, 50
cy,... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,803 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/plotheight_interp_whole_grayscale.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib as mpl
from scipy import interpolate
import os
data_img = cv2.imread('sample4.tif',0)
data_img = data_img.asty... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,804 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/basinhopping_abcheck.py | #!/usr/bin/env python
from __future__ import division
import sys
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib as mpl
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
from mpl_toolkits.axes_grid1.colorbar import colorbar
import nump... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,805 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/basinhopping_2steps_onepiece.py | #!/usr/bin/env python
from __future__ import division
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
from scipy.optimize import basinhopping
from scipy import fftpack
from... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,806 | hemengf/my_python_lib | refs/heads/master | /crosscenter.py | from __future__ import division
import numpy as np
import cv2
import matplotlib.pyplot as plt
import time
import statsmodels.api as sm
from collections import namedtuple
def roughcenter(img,ilwindow,jlwindow,i0,j0):
""" Returns icenter, jcenter only using 4 tips of the cross shape.
img needs to be blurred... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,807 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/basinhopping_2steps.py | #!/usr/bin/env python
from __future__ import division, print_function
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
from scipy.optimize import basinhopping
def normalize... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,808 | hemengf/my_python_lib | refs/heads/master | /door_position/try.py | class trythis:
""" Don't have to initialize data attributes; they can be defined directly in method attributes.
"""
attr_directly_under_class_def = 30
def seeattr(self):
self.attr = 20
def seeagain(self):
self.attr = 200
if __name__ == "__main__":
print trythis.__doc__
x = trythis()
x.s... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,809 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/plotheight_interp.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from scipy import interpolate
data_img = cv2.imread('sample4.tif',0)
data_img = data_img.astype('float64')
xstore = np.load('./x... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,810 | hemengf/my_python_lib | refs/heads/master | /left_partial.py | from __future__ import division
def derivative(f, x, dx=1e-2):
return (f(x+dx)-f(x-dx))/(2*dx)
if __name__ == "__main__":
from mpmath import *
mp.dps =2
def f(x):
return x**4
print derivative(f, 1, dx=1e-8)-4
print derivative(f, 1, dx=-1e-8)-4
print diff(f,1.)
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,811 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/normalization_test.py | import cv2
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import gaussian_kde
from skimage import exposure
ideal_img = cv2.imread('ideal.tif', 0)
crop_img = cv2.imread('crop.tif',0)
crop_eq = exposure.equalize_hist(crop_img)
crop_eq2 = exposure.equalize_hist(crop_eq)
crop_adapteq = expos... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,812 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/plotheight.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
data_img = cv2.imread('sample5.tif')
xstore = np.load('xoptstore_sample5.npy').item()
print xstore
#xstore_badtiles=np.load('xopt... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,813 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/OPDcorrection/plotcorrection.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
theta = np.arange(0,0.02,0.001)
n1 = 1.5
n2 = 1
a1= np.pi/2
OB =500*1000
a2 = np.arccos((n2/n1)*np.sin(np.arcsin((n1/n2)*np.cos(a1)+2*theta)))
s = (np.sin((a1-a2)/2))**2
dL = -2*n1*OB*s
fig, ax = p... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,814 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/basinhopping_2steps_version1.py | #!/usr/bin/env python
from __future__ import division
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
from scipy.optimize import basinhopping
def equalize(img_array):
... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,815 | hemengf/my_python_lib | refs/heads/master | /boundaryv/brownian_gas.py | from __future__ import division
import progressbar
import matplotlib.pyplot as plt
import numpy as np
class gas:
def __init__(self):
pass
class Dimer(gas):
def __init__(self, mass, radius, restlength):
self.position1 = np.zeros(2)
self.position2 = np.zeros(2)
self.positionCOM = (self.position1 + s... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,816 | hemengf/my_python_lib | refs/heads/master | /leastsq.py | from __future__ import division
from scipy import stats
import numpy as np
def leastsq_unweighted(x,y):
"""
y = A + Bx
all inputs are np arrays
"""
N = len(x)
delta_unweighted = N*((x**2).sum())-(x.sum())**2
A_unweighted = ((x*x).sum()*(y.sum())-x.sum()*((x*y).sum()))/delta_unweighted
B... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,817 | hemengf/my_python_lib | refs/heads/master | /intensity2height.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
colorimg = cv2.imread('DSC_5311.jpg').astype(float)
#colorimg = cv2.imread('crop.tif').astype(float)
blue, green, red = cv2.split(colorimg)
#red = red*90/80
cutoff = 100
ratio = green/(red+1e-6) #prevent diverging
ratio[ratio<... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,818 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/printtime.py | #import os
#if os.getenv("TZ"):
# os.unsetenv("TZ")
from time import strftime, localtime,gmtime,timezone
print strftime("%H_%M_%S",localtime())
print timezone/3600.
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,819 | hemengf/my_python_lib | refs/heads/master | /trythisfromlabcomputer.py | print 'try this from the lab computer'
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,820 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/thin/readthin.py | from __future__ import division
import numpy as np
import cv2
from scipy import interpolate
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
left0_img = cv2.imread('left0.tif',0)
left1_img = cv2.imread('left1.tif',0)
left2_img = cv2.imread('left2.tif',0)
left3_img = cv2.imread('left3.tif',0)
lef... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,821 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/pattern_shift1D_vectorized.py | from __future__ import division
from scipy.misc import derivative
import scipy.optimize
import scipy.spatial.distance
def shape_function(x):
return 0.000005*(x**2)+68
#return 0.00000001*x + 68
#@profile
def find_k_refracting(k_incident, x1, n1,n2):
#n = np.array([[-derivative(shape_function, x, dx=1e-6), ... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,822 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/amber_green.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
cmap = plt.get_cmap('tab10')
x = np.arange(0,20, 0.001)
red = 1+np.cos(4*np.pi*(x+0.630/4)/0.630)
amber = 1+ np.cos(4*np.pi*(x+0.59/4)/0.590)
green = 1+ np.cos(4*np.pi*(x+0.534/4)/0.534)
#plt.plot(x, red+amber)
#plt.plot(x, amber+green)... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,823 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/red_amber_8bit.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0,20, 0.001)
red = 1+np.cos(4*np.pi*(x+0.630/4)/0.630)
amber = 1+ np.cos(4*np.pi*(x+0*0.59/4)/0.590)
plt.plot(x, red+amber)
plt.title('red and amber 8bit')
plt.plot(x, red, 'r')
plt.plot(x, amber, 'y')
plt.show()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,824 | hemengf/my_python_lib | refs/heads/master | /door_position/disks.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from boundaryv.brownian_gas import findnearest
class Particle:
def __init__(self):
self.position = np.array([0.,0.])
self.velocity = np.array([0.,0.])
self.repelforce = np.zeros(2)
def accelerate(self, acceleration... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,825 | hemengf/my_python_lib | refs/heads/master | /door_position/fluid/data_plot.py | import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()
x1,y1 = np.loadtxt('data_center.txt', delimiter=',', unpack = True)
ax.plot(x1, y1, 'x', color = 'r')
x2,y2 = np.loadtxt('data_wall.txt', delimiter=',', unpack=True)
ax.plot(x2, y2, '+', color = 'g')
plt.axis([0,4, 20, 70])
plt.show()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,826 | hemengf/my_python_lib | refs/heads/master | /partial_derivative.py | from __future__ import division
import scipy.misc
import numpy as np
def partial_derivative_wrapper(func, var, point):
"""
Returns the partial derivative of a function 'func' with
respect to 'var'-th variable at point 'point'
Scipy hasn't provided a partial derivative function.
This is a simple wrap... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,827 | hemengf/my_python_lib | refs/heads/master | /water_glycerol.py | from __future__ import division
import numpy as np
from scipy.optimize import fsolve
def mu(Cm,T):
a = 0.705-0.0017*T
b = (4.9+0.036*T)*np.power(a,2.5)
alpha = 1-Cm+(a*b*Cm*(1-Cm))/(a*Cm+b*(1-Cm))
mu_water = 1.790*np.exp((-1230-T)*T/(36100+360*T))
mu_gly = 12100*np.exp((-1233+T)*T/(9900+70*T))
... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,828 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/ffttest.py | from scipy import fftpack
import cv2
import matplotlib.pyplot as plt
import numpy as np
img = cv2.imread('ideal.tif',0)
absfft2 = np.abs(fftpack.fft2(img))[2:-2,2:-2]
absfft2 /= absfft2.max()
print absfft2.max()
plt.imshow(absfft2)
plt.show()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,829 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/test_peak.py | import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
import cookb_signalsmooth
intensity = np.load("intensity.npy")
intensity = -intensity
coordinates = np.linspace(-500,500,300)
plt.plot(coordinates, intensity)
#intensity = cookb_signalsmooth.smooth(intensity, 10)
#plt.plot(coordinates, intensi... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,830 | hemengf/my_python_lib | refs/heads/master | /cursor.py | import ctypes
import time
start_time = time.time()
# see http://msdn.microsoft.com/en-us/library/ms646260(VS.85).aspx for details
ctypes.windll.user32.SetCursorPos(100, 40)
ctypes.windll.user32.mouse_event(2, 0, 0, 0,0) # left down
ctypes.windll.user32.mouse_event(4, 0, 0, 0,0) # left up
ctypes.windll.user32.m... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,831 | hemengf/my_python_lib | refs/heads/master | /removeholes.py | from skimage import morphology
import mahotas as mh
import matplotlib.pyplot as plt
import numpy as np
#label original image, im=uint8(0 and 255), labeled=uint8
im = plt.imread('../../Downloads/image.tif')
labeled, nr_objects = mh.label(im,np.ones((3,3),bool))
print nr_objects
#an example of removing holes.... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,832 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/warptest.py | import cv2
import numpy as np
from skimage import transform as tf
import matplotlib.pyplot as plt
img = cv2.imread('sample6.tif',0)
pointset1 = np.genfromtxt('pointset1.csv', delimiter=',', names=True)
pointset2 = np.genfromtxt('pointset2.csv', delimiter=',', names=True)
pointset1 = np.vstack((pointset1['BX'],pointset1... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,833 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/plotheight.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from scipy import interpolate
from scipy.signal import savgol_filter as sg
data_img = cv2.imread('sample4.tif',0)
data_img = dat... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,834 | hemengf/my_python_lib | refs/heads/master | /convertcygpath.py | import subprocess
filename = "/cygdrive/c/Lib/site-packages/matplotlib"
cmd = ['cygpath','-w',filename]
proc = subprocess.Popen(cmd, stdout=subprocess.PIPE)
output = proc.stdout.read()
#output = output.replace('\\','/')[0:-1] #strip \n and replace \\
print output
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,835 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/cannytest.py | import cv2
from scipy import ndimage as ndi
from skimage import feature
import numpy as np
from matplotlib import pyplot as plt
from skimage import exposure
def equalize(img_array):
"""
returns array with float 0-1
"""
equalized = exposure.equalize_hist(img_array)
return equalized
img = cv2.imread... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,836 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/whitespacetest.py | import numpy as np
import cv2
img = cv2.imread('test.tif',0)
img = img.astype('float')
img /= 255.
#print img.sum()/(img.shape[0]*img.shape[1])
print img.sum()/len(img.flat)
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,837 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/plotheight_interp_whole_1d.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib as mpl
from scipy.signal import savgol_filter as sg
from scipy import interpolate
import os
from progressbar im... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,838 | hemengf/my_python_lib | refs/heads/master | /plotwithsliders.py | import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
from matplotlib.widgets import Button
def sliders_buttons(pararange,parainit,height = 0.08,incremental=0.001):
xslider = plt.axes([0.25,height,0.65,0.03])
slider = Slider(xslider,'para',pararange[0],pararange[1],valinit=parainit,valfmt='%1.3... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,839 | hemengf/my_python_lib | refs/heads/master | /find_peaks.py | from __future__ import division
import numpy as np
import warnings
def exact_local_maxima1D(a):
"""
Compare adjacent elements of a 1D array.
Returns a np array of true values for each element not counting
the first and last element.
Modified from http://stackoverflow.com/questions/4624970/finding... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,840 | hemengf/my_python_lib | refs/heads/master | /oseen.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
Rmin = 1
Rmax = 5
R = np.arange(Rmin,Rmax,0.01)
for U in np.arange(0.09,0.136,0.01):
v = 438*1e-6
rhs = np.sqrt(1e6*v*U/9.8)*np.sqrt(2/np.log(7.4*v/(2*R*1e-3*U)))
plt.plot(R, rhs)
plt.plot(R, R)
plt.ylim(Rmin,Rmax)
plt.ylim(R... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,841 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/failed_pattern_shift2D.py | from __future__ import division
import scipy.optimize
import scipy.spatial.distance
import partial_derivative
def shape_function(x,y):
return 0.000005*(x**2+y**2)+68
#return 0.00000001*x + 68
def find_k_refracting(k_incident, x1, n1,n2):
#x1 = [[xa,ya],
# [xb,yb],
# [xc,yc]]
... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,842 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/plotheight_whole.py | from __future__ import division
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
data_img = cv2.imread('sample4.tif',0)
fitimg_whole = np.copy(data_img)
xstorebot = np.load('./xoptstore_bot.npy').item()
xstorer... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,843 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/basinhopping_2steps_version0.py | #!/usr/bin/env python
from __future__ import division
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
from scipy.optimize import basinhopping
def equalize(img_array):
... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,844 | hemengf/my_python_lib | refs/heads/master | /elephantfeet/elephantfeet_generation.py | from boundaryv.brownian_gas import touch, findnearest
from door_position.disks import tchbnd
import numpy as np
import matplotlib.pyplot as plt
import os
import progressbar
class Elephant_foot():
def __init__(self, radius, velocity):
self.position = np.array([0.,0.])
self.radius = radius
... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,845 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/pattern_shift2D.py | from __future__ import division
import scipy.optimize
import scipy.spatial.distance
import partial_derivative
import math
#@profile
def shape_function(x,y):
#return np.exp(-0.00002*((x+250)**2+y**2)) + np.exp(-0.00002*((x-250)**2+y**2))+100
return 0.000005*(x**2+y**2)+68.1
#return 0.00000001*x + 68
#@prof... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,846 | hemengf/my_python_lib | refs/heads/master | /progressbar.py | from __future__ import division
from ctypes import windll, create_string_buffer
import time
import sys
import struct
import subprocess
def progressbar_win_console(cur_iter, tot_iter, deci_dig):
"""
Presents the percentage and draws a progress bar.
Import at the begining of a file. Call at the end... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,847 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/simulated_annealing_bak.py | #!/usr/bin/env python
from __future__ import division, print_function
import sys
from scipy import interpolate
import time
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import cv2
from skimage import exposure
def normalize(img_array,normrange):
#elementmax = np... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,848 | hemengf/my_python_lib | refs/heads/master | /envelope.py | from __future__ import division
import numpy as np
from scipy.signal import savgol_filter as sg
from scipy.interpolate import interp1d
from skimage.measure import profile_line as pl
from find_peaks import left_find_indices_min as minindices
from find_peaks import left_find_indices_max as maxindices
import sys
import ti... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,849 | hemengf/my_python_lib | refs/heads/master | /boundaryv/draft.py | import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import numpy as np
import random
boxsize = 1000
class Particle:
def __init__(self, particle_pos, size):
self.x = particle_pos[0]
self.y = particle_pos[1]
self.orientation = random.uniform(0,2*np.pi)
self.size = size
def touch(... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,850 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/shape_fitting/whole/piecewise/checkconnectivity.py | from scipy.ndimage import label as lb
import cv2
import matplotlib.pyplot as plt
img = cv2.imread('cl.tif',0)
labeled_array,num =lb(img,structure=[[1,1,1],[1,1,1],[1,1,1]])
plt.imshow(labeled_array)
plt.show()
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,851 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/red_amber_green_button632.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import CheckButtons
from find_peaks import find_indices_max as fimax
from find_peaks import find_indices_min as fimin
cmap = plt.get_cmap('tab10')
am = cmap(1)
gr = cmap(2)
rd = cmap(3)
amwvlg = 0.590
rdwvlg = 0.... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,852 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/green_slider_8bit.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from plotwithsliders import plotwithsliders as ps
from plotwithsliders import sliders_buttons as sb
from find_peaks import find_indices_max as fimax
from find_peaks import find_indices_min as fimin
cmap = plt.get_cmap('tab10')
am = cma... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,853 | hemengf/my_python_lib | refs/heads/master | /error_boxes.py | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import PatchCollection
from matplotlib.patches import Rectangle
def make_error_boxes(ax, xdata, ydata, xerror, yerror, facecolor='r',
edgecolor='#1f77b4', errorcolor='k',alpha=1):
"""
Call function to create er... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,854 | hemengf/my_python_lib | refs/heads/master | /webscraping/t66y.py | # -*- encoding: utf-8 -*-
import urllib
import cfscrape
from bs4 import BeautifulSoup
import re
n = 1
f = open('result.html','w+')
f.write('<!DOCTYPE html>')
f.write('<html>')
f.write('<body>')
for page in range(1,50):
site15 ="http://t66y.com/thread0806.php?fid=15&search=&page=%d"%page
site2 ="http://t66y.com/... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,855 | hemengf/my_python_lib | refs/heads/master | /boundaryv/trycircle.py | import matplotlib.pyplot as plt
circle1=plt.Circle((0,0),.2,color='r')
circle2=plt.Circle((.5,.5),.2,color='b')
circle3=plt.Circle((1,1),.2,color='g',clip_on=False)
fig = plt.gcf()
fig.gca().add_artist(circle1)
fig.gca().add_artist(circle2)
fig.gca().add_artist(circle3)
plt.axis([0,2,0,2])
plt.axes().set_aspec... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,856 | hemengf/my_python_lib | refs/heads/master | /trans_circulation/plot_lambda1vsanglefunction.py | import matplotlib.pyplot as plt
import numpy as np
data = np.loadtxt('data_lambda1vsangle')
lambda1 = 0.5*(data[:,2]+data[:,3])
angle = 0.5*(180-data[:,0]+data[:,1])*np.pi/180.
cosangle = np.cos(angle)
sinangle = np.sin(angle)
anglefunction = sinangle/np.power(cosangle,0.33)
plt.scatter(anglefunction, lambda1, ... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,857 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/find_center.py | from __future__ import division
import find_peaks
import numpy as np
def center_position(intensity, x, center):
left_indices = find_peaks.left_find_indices_all(intensity)
left_x_position = x[left_indices]
left_center_idx = np.abs(left_x_position-center).argmin()
right_indices = find_peaks.right_find_ind... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,858 | hemengf/my_python_lib | refs/heads/master | /trystatus.py | import time
import progressbar
for i in range(400):
# work
time.sleep(0.01)
progressbar.progressbar_tty(i,399,3)
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,859 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/red_amber_green/green_slider.py | from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import CheckButtons
from plotwithsliders import plotwithsliders as ps
from plotwithsliders import sliders_buttons as sb
from find_peaks import find_indices_max as fimax
from find_peaks import find_indices_min as... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,860 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/dataplot.py | import matplotlib.pyplot as plt
import numpy as np
framenumber = 50
fig = plt.figure()
ax = fig.add_subplot(111)
d = {}
height_range = range(0,2000,100)
for i in height_range:
d["data%d"%i] = np.load("./output_test/center_array_%d.npy"%i)
d["data%d"%i] = d["data%d"%i][::1]
angles = np.linspace(0,0.06, frame... | {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,861 | hemengf/my_python_lib | refs/heads/master | /interference_pattern/callable_test.py | def perform(args):
x = args[0]
return x, shape_function(args)
def shape_function(x):
return np.sin(x[0])+x[1]
if __name__ == "__main__":
import numpy as np
print perform((1,0,3))
| {"/interference_pattern/red_amber_green/red_amber_green_button632.py": ["/find_peaks.py"], "/interference_pattern/red_amber_green/green_slider_8bit.py": ["/plotwithsliders.py", "/find_peaks.py"], "/interference_pattern/find_center.py": ["/find_peaks.py"], "/trystatus.py": ["/progressbar.py"], "/interference_pattern/red... |
15,915 | prudhvikumar22/proper_modern_webui_automation | refs/heads/master | /webui/webui.py | try:
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.action_chains import ActionChains
import os
import time
exce... | {"/tests/test_youtube_site.py": ["/tests/conftest.py"], "/tests/conftest.py": ["/webui/webui.py"]} |
15,916 | prudhvikumar22/proper_modern_webui_automation | refs/heads/master | /tests/test_youtube_site.py | from tests.conftest import browser
def test_youtube_site_load(driver, browser):
browser.open("http://www.youtube.com")
assert driver.title == "YouTube"
| {"/tests/test_youtube_site.py": ["/tests/conftest.py"], "/tests/conftest.py": ["/webui/webui.py"]} |
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