1 files changed, 0 insertions, 120 deletions
diff --git a/docs/source/auto_examples/plot_OTDA_2D.py b/docs/source/auto_examples/plot_OTDA_2D.py
deleted file mode 100644
index a1fb804..0000000
--- a/docs/source/auto_examples/plot_OTDA_2D.py
+++ /dev/null
@@ -1,120 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-==============================
-OT for empirical distributions
-==============================
-
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-
-
-
-#%% parameters
-
-n=150 # nb bins
-
-xs,ys=ot.datasets.get_data_classif('3gauss',n)
-xt,yt=ot.datasets.get_data_classif('3gauss2',n)
-
-a,b = ot.unif(n),ot.unif(n)
-# loss matrix
-M=ot.dist(xs,xt)
-#M/=M.max()
-
-#%% plot samples
-
-pl.figure(1)
-
-pl.subplot(2,2,1)
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.legend(loc=0)
-pl.title('Source  distributions')
-
-pl.subplot(2,2,2)
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-pl.legend(loc=0)
-pl.title('target  distributions')
-
-pl.figure(2)
-pl.imshow(M,interpolation='nearest')
-pl.title('Cost matrix M')
-
-
-#%% OT estimation
-
-# EMD
-G0=ot.emd(a,b,M)
-
-# sinkhorn
-lambd=1e-1
-Gs=ot.sinkhorn(a,b,M,lambd)
-
-
-# Group lasso regularization
-reg=1e-1
-eta=1e0
-Gg=ot.da.sinkhorn_lpl1_mm(a,ys.astype(np.int),b,M,reg,eta)
-
-
-#%% visu matrices
-
-pl.figure(3)
-
-pl.subplot(2,3,1)
-pl.imshow(G0,interpolation='nearest')
-pl.title('OT matrix ')
-
-pl.subplot(2,3,2)
-pl.imshow(Gs,interpolation='nearest')
-pl.title('OT matrix Sinkhorn')
-
-pl.subplot(2,3,3)
-pl.imshow(Gg,interpolation='nearest')
-pl.title('OT matrix Group lasso')
-
-pl.subplot(2,3,4)
-ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-
-pl.subplot(2,3,5)
-ot.plot.plot2D_samples_mat(xs,xt,Gs,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-pl.subplot(2,3,6)
-ot.plot.plot2D_samples_mat(xs,xt,Gg,c=[.5,.5,1])
-pl.scatter(xs[:,0],xs[:,1],c=ys,marker='+',label='Source samples')
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples')
-
-#%% sample interpolation
-
-xst0=n*G0.dot(xt)
-xsts=n*Gs.dot(xt)
-xstg=n*Gg.dot(xt)
-
-pl.figure(4)
-pl.subplot(2,3,1)
-
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xst0[:,0],xst0[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples')
-pl.legend(loc=0)
-
-pl.subplot(2,3,2)
-
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xsts[:,0],xsts[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Sinkhorn')
-
-pl.subplot(2,3,3)
-
-pl.scatter(xt[:,0],xt[:,1],c=yt,marker='o',label='Target samples',alpha=0.5)
-pl.scatter(xstg[:,0],xstg[:,1],c=ys,marker='+',label='Transp samples',s=30)
-pl.title('Interp samples Grouplasso')
-\ No newline at end of file