1 files changed, 0 insertions, 76 deletions
diff --git a/docs/source/auto_examples/plot_UOT_1D.py b/docs/source/auto_examples/plot_UOT_1D.py
deleted file mode 100644
index 2ea8b05..0000000
--- a/docs/source/auto_examples/plot_UOT_1D.py
+++ /dev/null
@@ -1,76 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-===============================
-1D Unbalanced optimal transport
-===============================
-
-This example illustrates the computation of Unbalanced Optimal transport
-using a Kullback-Leibler relaxation.
-"""
-
-# Author: Hicham Janati <hicham.janati@inria.fr>
-#
-# License: MIT License
-
-import numpy as np
-import matplotlib.pylab as pl
-import ot
-import ot.plot
-from ot.datasets import make_1D_gauss as gauss
-
-##############################################################################
-# Generate data
-# -------------
-
-
-#%% parameters
-
-n = 100  # nb bins
-
-# bin positions
-x = np.arange(n, dtype=np.float64)
-
-# Gaussian distributions
-a = gauss(n, m=20, s=5)  # m= mean, s= std
-b = gauss(n, m=60, s=10)
-
-# make distributions unbalanced
-b *= 5.
-
-# loss matrix
-M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
-M /= M.max()
-
-
-##############################################################################
-# Plot distributions and loss matrix
-# ----------------------------------
-
-#%% plot the distributions
-
-pl.figure(1, figsize=(6.4, 3))
-pl.plot(x, a, 'b', label='Source distribution')
-pl.plot(x, b, 'r', label='Target distribution')
-pl.legend()
-
-# plot distributions and loss matrix
-
-pl.figure(2, figsize=(5, 5))
-ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
-
-
-##############################################################################
-# Solve Unbalanced Sinkhorn
-# --------------
-
-
-# Sinkhorn
-
-epsilon = 0.1  # entropy parameter
-alpha = 1.  # Unbalanced KL relaxation parameter
-Gs = ot.unbalanced.sinkhorn_unbalanced(a, b, M, epsilon, alpha, verbose=True)
-
-pl.figure(4, figsize=(5, 5))
-ot.plot.plot1D_mat(a, b, Gs, 'UOT matrix Sinkhorn')
-
-pl.show()