gistfile1.txt

import os, sys, csv
from os import listdir
from os.path import join, isdir
from operator import itemgetter
from ast import literal_eval
import re
import matplotlib.pyplot as plt
import shutil

def retrieve_var(var_name, file_path):
    _file = open(file_path)
    dummy_coefficients = None

    while True:
        string = _file.readline()
        match = re.match(var_name, string)

        if match:
            splits = string.split(":")
            coefficients = splits[1]
            coefficients = coefficients.strip()

            dummy_coefficients = literal_eval(coefficients)
            _file.close()
            break

    return dummy_coefficients

start_dir = sys.argv[1]
coeffs_amount = 5

test_no = 1
xs = []
ys = []
for c in range(coeffs_amount):
    #generate graph object and use it to build a graph for each coefficient
    test_no = c + 1
    xs.append(test_no)

    #grab the cth test from each directory and it's highest fit
    file_name = 'general_info.txt'
    file_path = join(start_dir,  '14-dimensions', 'test-{0}'.format(test_no), file_name)
    best_fit  = retrieve_var('best_fit', file_path)
    print 'best_fit: {0}'.format(best_fit)
    ys.append(best_fit)
    #build a graph with the fit as the y axis and elb as the x-axis
    test_no += 1
    
print 'ys: {0}'.format(ys)
print 'xs: {0}'.format(xs)
plt.plot(xs, ys)

png_file_name = '{0}-graph'.format(start_dir)
plt.savefig(png_file_name)

os.system("open {0}.png".format(png_file_name))

import matplotlib.pyplot as plt

test_no = 1
xs = []
ys = []

print 'ys: {0}'.format(ys)
print 'xs: {0}'.format(xs)
plt.plot(xs, ys)

png_file_name = '{0}-graph'.format(start_dir)
plt.savefig(png_file_name)

os.system("open {0}.png".format(png_file_name))