1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
import numpy as np
import matplotlib.pylab as pl
from matplotlib import gridspec
def otplot1D(a,b,M,title=''):
""" Plot matrix M with the source and target 1D distribution """
na=M.shape[0]
nb=M.shape[1]
gs = gridspec.GridSpec(3, 3)
xa=np.arange(na)
xb=np.arange(nb)
ax1=pl.subplot(gs[0,1:])
pl.plot(xb,b,'r',label='Target distribution')
pl.yticks(())
pl.title(title)
#pl.axis('off')
ax2=pl.subplot(gs[1:,0])
pl.plot(a,xa,'b',label='Source distribution')
pl.gca().invert_xaxis()
pl.gca().invert_yaxis()
pl.xticks(())
#pl.ylim((0,n))
#pl.axis('off')
pl.subplot(gs[1:,1:],sharex=ax1,sharey=ax2)
pl.imshow(M,interpolation='nearest')
pl.xlim((0,nb))
def otplot2D_samples(xs,xt,G,thr=1e-8,**kwargs):
""" Plot matrix M in 2D with lines using alpha values"""
if ('color' not in kwargs) and ('c' not in kwargs):
kwargs['color']='k'
mx=G.max()
for i in range(xs.shape[0]):
for j in range(xt.shape[0]):
if G[i,j]/mx>thr:
pl.plot([xs[i,0],xt[j,0]],[xs[i,1],xt[j,1]],alpha=G[i,j]/mx,**kwargs)
|
