import sys
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.axislines import Subplot


c = np.loadtxt('ipecamera2.1024.gpu.txt')
g = np.loadtxt('ipedirectgma.1024.gpu.txt')
cpu_data = c[:,1]
gpu_data = g[:,1]

cpu_data = cpu_data[cpu_data < 5]
gpu_data = gpu_data[gpu_data < 5]



#plt.rc('font', **dict(family='serif'))

fig = plt.figure(1, (4,3.2))
ax = Subplot(fig, 111)
fig.add_subplot(ax)

cpu_weights = np.ones_like(cpu_data)/float(len(cpu_data))
gpu_weights = np.ones_like(gpu_data)/float(len(gpu_data))

# divide by 2 for one-way latency
# plt.ylim(0.1, 10000)
# plt.hist(gpu_data, bins=200, label='GPU', log=True)
# plt.hist(cpu_data, bins=200, label='CPU', log=True)
ax.hist(gpu_data, weights=gpu_weights, bins=50, color='#3b5b92', label='Setup 1', linewidth=0)
ax.hist(cpu_data, weights=cpu_weights, bins=50, color='#aec6cf', label='Setup 2', linewidth=0)
plt.xticks([2.0, 3.0, 4.0, 5.0])
plt.yticks([0,0.25,0.5])
ax.axis["right"].set_visible(False)
ax.axis["top"].set_visible(False)
# plt.semilogy()

plt.xlabel(u'Latency in \u00b5s')
plt.ylabel('Frequency')
plt.legend(loc='upper right',frameon=False)
plt.savefig('latency-hist-gpu.pdf', dpi=300, bbox_inches='tight')