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profiler.py
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import numpy as np
import sys
import matplotlib.pyplot as plt
a = sys.argv
f = open('result.txt')
beta_range_min = 0
beta_range_max = 200
contrast_range_min = 120
contrast_range_max = 201
contrast_number = int((contrast_range_max - contrast_range_min)/5 + 1)
lines = f.readlines()
beta = []
contrast = []
AAE = []
EPE = []
for b in range(len(lines)):
line = lines[b]
words = line.split()
if b % 2 == 0:
beta.append(int(words[2]))
contrast.append(int(words[3]))
else:
AAE.append(float(words[1]))
EPE.append(float(words[4]))
for b in range(len(lines)):
line = lines[b]
words = line.split()
beta.append(int(words[1]))
contrast.append(int(words[3]))
EPE.append(float(words[5]))
# Show AAE error according to beta value
xt = range(0, 195, 5)
plt.figure()
x = []
y = []
value = []
for c in range(17):
x = []
y = []
for b in range(195/5 + 1):
x.append(beta[b * 17 + c])
y.append(AAE[b * 17 + c])
value.append(contrast[b * 17 + c])
plt.plot(x, y, label='haze = ' + str(value[c * (195/5+1)]))
print x
print y
print value
plt.xticks(xt)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=-2)
# Show EPE error according to beta value
# Show error according to beta value
xt = range(0, 195, 5)
plt.figure()
x = []
y = []
value = []
for c in range(17):
x = []
y = []
for b in range(195/5 + 1):
x.append(beta[b * 17 + c])
y.append(EPE[b * 17 + c])
value.append(contrast[b * 17 + c])
plt.plot(x, y, label='haze = ' + str(value[c * (195/5+1)]))
print x
print y
print value
plt.xticks(xt)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=-2)
# Show EPE error according to beta value
# Show error according to beta value
xt = range(120, 201, 5)
plt.figure()
x = []
y = []
value = []
for b in range(beta_range_min, beta_range_max, 5):
x = []
y = []
for c in range((contrast_range_max-contrast_range_min)/5 + 1):
x.append(contrast[b/5 * contrast_number + c])
y.append(EPE[b/5 * contrast_number + c])
value.append(beta[b/5 * contrast_number + c])
plt.plot(x, y, label='beta = ' + str(value[b/5 * contrast_number]))
print x
print y
print value
plt.xticks(xt)
plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=-2)
plt.show()