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author | RĂ©mi Flamary <remi.flamary@gmail.com> | 2020-04-21 08:18:34 +0200 |
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committer | GitHub <noreply@github.com> | 2020-04-21 08:18:34 +0200 |
commit | 3ade772179eb0405ae6bc70cfc5e701b70d70e89 (patch) | |
tree | 1cd567393e5687f44b65157b8a9a7b7614392493 /docs/source/auto_examples/plot_screenkhorn_1D.py | |
parent | 43b2190db71b1ccbeec8fddaae23ca6af220e1b5 (diff) | |
parent | e106537ee2fd5c3b2dac87789ed9f2dc40766a55 (diff) |
Merge pull request #143 from PythonOT/doc_travis
[WIP] Update travis test and documentation (examples)
Diffstat (limited to 'docs/source/auto_examples/plot_screenkhorn_1D.py')
-rw-r--r-- | docs/source/auto_examples/plot_screenkhorn_1D.py | 68 |
1 files changed, 68 insertions, 0 deletions
diff --git a/docs/source/auto_examples/plot_screenkhorn_1D.py b/docs/source/auto_examples/plot_screenkhorn_1D.py new file mode 100644 index 0000000..840ead8 --- /dev/null +++ b/docs/source/auto_examples/plot_screenkhorn_1D.py @@ -0,0 +1,68 @@ +# -*- coding: utf-8 -*- +""" +=============================== +1D Screened optimal transport +=============================== + +This example illustrates the computation of Screenkhorn: +Screening Sinkhorn Algorithm for Optimal transport. +""" + +# Author: Mokhtar Z. Alaya <mokhtarzahdi.alaya@gmail.com> +# +# License: MIT License + +import numpy as np +import matplotlib.pylab as pl +import ot.plot +from ot.datasets import make_1D_gauss as gauss +from ot.bregman import screenkhorn + +############################################################################## +# 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) + +# 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 Screenkhorn +# ----------------------- + +# Screenkhorn +lambd = 2e-03 # entropy parameter +ns_budget = 30 # budget number of points to be keeped in the source distribution +nt_budget = 30 # budget number of points to be keeped in the target distribution + +G_screen = screenkhorn(a, b, M, lambd, ns_budget, nt_budget, uniform=False, restricted=True, verbose=True) +pl.figure(4, figsize=(5, 5)) +ot.plot.plot1D_mat(a, b, G_screen, 'OT matrix Screenkhorn') +pl.show() |