Created
April 21, 2017 15:59
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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)) | |
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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))