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"""
Functions for plotting OT matrices
"""
import numpy as np
import matplotlib.pylab as pl
from matplotlib import gridspec
def plot1D_mat(a,b,M,title=''):
""" Plot matrix M with the source and target 1D distribution
Creates a subplot with the source distribution a on the left and
target distribution b on the tot. The matrix M is shown in between.
Parameters
----------
a : np.array (na,)
Source distribution
b : np.array (nb,)
Target distribution
M : np.array (na,nb)
Matrix to plot
"""
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 plot2D_samples_mat(xs,xt,G,thr=1e-8,**kwargs):
""" Plot matrix M in 2D with lines using alpha values
Plot lines between source and target 2D samples with a color
proportional to the value of the matrix G between samples.
Parameters
----------
xs : np.array (ns,2)
Source samples positions
b : np.array (nt,2)
Target samples positions
G : np.array (na,nb)
OT matrix
thr : float, optional
threshold above which the line is drawn
**kwargs : dict
paameters given to the plot functions (default color is black if nothing given)
"""
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)
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