mem_plot.py

import numpy as np
import matplotlib.pyplot as plt


N = 4

# Custom, nx , LIL , CSR
# First data set
construct_mem1 = (10.92,29.47,8.03,17.17)
merge_mem1 = (11.26,29.89,8.28,476.95)

# second data set
construct_mem2 = (110.99,272.55,39.78,225.19)
merge_mem2 = (123.12,284.69,40.07,257.37)

# 3rd data set
construct_mem3 = (150.08,370.51,53.66,286.27)
merge_mem3 = (165.41,386.41,53.78,378.78)



ind1 = np.arange(N)*4    # the x locations for the groups
ind2 = np.arange(N)*4 + 1
ind3 = np.arange(N)*4 + 2

width = 0.2       # the width of the bars: can also be len(x) sequence

pc1 = plt.bar(ind1, construct_mem1,   width, color='#953732')
pm1 = plt.bar(ind1 + 0.3, merge_mem1, width, color='#B5BB3E',)

pc2 = plt.bar(ind2, construct_mem2,   width, color='#953732')
pm2 = plt.bar(ind2 + 0.3, merge_mem2, width, color='#B5BB3E')

pc3 = plt.bar(ind3, construct_mem3,   width, color='#953732')
pm4 = plt.bar(ind3 + 0.3, merge_mem3, width, color='#B5BB3E')




plt.ylabel('Memory in MB')
plt.title('Memory Usage by Approach')

plt.xticks(ind1+width*6, ('CUSTOM','NX','LIL','CSR') )
#plt.xticks(ind2+width/2., ('CUSTOM-2','NX-2','LIL-2','CSR-2') )


plt.yticks(np.arange(0,200,40))
plt.legend( (pc1[0], pm1[0]), ('Construction', 'Merging'),loc = 2 )
plt.ylim((0,200))
#plt.xlim((0,5))
plt.show()