gistfile1.txt

import matplotlib
import videocapture
import pandas as pd
import numpy
import scipy.stats
import requests
import math

%matplotlib inline

# Make graphs prettier
pd.set_option('display.max_columns', 15)
pd.set_option('display.line_width', 400)
pd.set_option('display.mpl_style', 'default')


def get_entropy_pvalues(entropies, window_size=10):
    pvalues = []
    for i in range(window_size, len(entropies)-window_size):
        previousrange = entropies[i-window_size:i]
        nextrange = entropies[i:i+window_size]
        # use welch's ttest, which does not assume equal variance between
        # populations
        pvalue = scipy.stats.ttest_ind(nextrange, previousrange, equal_var=False)[1]
        pvalues.append(pvalue)
    
    return pvalues


hash = '7c5e49eac4a111e3851df0def1767b24'
def get_metadata(hash):
    baseurl = 'http://eideticker.mozilla.org/b2g'
    url = baseurl + '/metadata/%s.json' % hash
    r = requests.get(url)
    return r.json()

metadata = get_metadata(hash)
pvalues = get_entropy_pvalues(metadata['framesobelentropies'])
for (i, pvalue) in enumerate(pvalues):
    print "%s,%s" % (i/60.0,-math.log10(pvalue))
pd.Series(pvalues).plot()