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diff --git a/docs/source/auto_examples/demo_OT_2D_sampleslarge.py b/docs/source/auto_examples/demo_OT_2D_sampleslarge.py
deleted file mode 100644
index ee3e8f7..0000000
--- a/docs/source/auto_examples/demo_OT_2D_sampleslarge.py
+++ /dev/null
@@ -1,78 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Demo for 2D Optimal transport between empirical distributions
-
-@author: rflamary
-"""
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-
-#%% parameters and data generation
-
-n=5000 # nb samples
-
-mu_s=np.array([0,0])
-cov_s=np.array([[1,0],[0,1]])
-
-mu_t=np.array([4,4])
-cov_t=np.array([[1,-.8],[-.8,1]])
-
-xs=ot.datasets.get_2D_samples_gauss(n,mu_s,cov_s)
-xt=ot.datasets.get_2D_samples_gauss(n,mu_t,cov_t)
-
-a,b = ot.unif(n),ot.unif(n) # uniform distribution on samples
-
-# loss matrix
-M=ot.dist(xs,xt)
-M/=M.max()
-
-#%% plot samples
-
-#pl.figure(1)
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('Source and traget distributions')
-#
-#pl.figure(2)
-#pl.imshow(M,interpolation='nearest')
-#pl.title('Cost matrix M')
-#
-
-#%% EMD
-
-G0=ot.emd(a,b,M)
-
-#pl.figure(3)
-#pl.imshow(G0,interpolation='nearest')
-#pl.title('OT matrix G0')
-#
-#pl.figure(4)
-#ot.plot.plot2D_samples_mat(xs,xt,G0,c=[.5,.5,1])
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('OT matrix with samples')
-
-
-#%% sinkhorn
-
-# reg term
-lambd=5e-3
-
-Gs=ot.sinkhorn(a,b,M,lambd)
-
-#pl.figure(5)
-#pl.imshow(Gs,interpolation='nearest')
-#pl.title('OT matrix sinkhorn')
-#
-#pl.figure(6)
-#ot.plot.plot2D_samples_mat(xs,xt,Gs,color=[.5,.5,1])
-#pl.plot(xs[:,0],xs[:,1],'+b',label='Source samples')
-#pl.plot(xt[:,0],xt[:,1],'xr',label='Target samples')
-#pl.legend(loc=0)
-#pl.title('OT matrix Sinkhorn with samples')
-#
-