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Optimal transport with factored couplings — POT Python Optimal Transport 0.9.5 documentation

Illustration of the factored coupling OT between 2D empirical distributions

# Author: Remi Flamary <remi.flamary@polytechnique.edu>
#
# License: MIT License

# sphinx_gallery_thumbnail_number = 2

import numpy as np
import matplotlib.pylab as pl
import ot
import ot.plot

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 target distributions")

Text(0.5, 1.0, 'Source and target distributions')

pl.figure(2, (14, 4))

pl.subplot(1, 3, 1)
ot.plot.plot2D_samples_mat(xs, xt, G0, c=[0.2, 0.2, 0.2], alpha=0.1)
pl.plot(xs[:, 0], xs[:, 1], "+b", label="Source samples")
pl.plot(xt[:, 0], xt[:, 1], "xr", label="Target samples")
pl.title("Exact OT with samples")

pl.subplot(1, 3, 2)
ot.plot.plot2D_samples_mat(xs, xb, Ga, c=[0.6, 0.6, 0.9], alpha=0.5)
ot.plot.plot2D_samples_mat(xb, xt, Gb, c=[0.9, 0.6, 0.6], alpha=0.5)
pl.plot(xs[:, 0], xs[:, 1], "+b", label="Source samples")
pl.plot(xt[:, 0], xt[:, 1], "xr", label="Target samples")
pl.plot(xb[:, 0], xb[:, 1], "og", label="Template samples")
pl.title("Factored OT with template samples")

pl.subplot(1, 3, 3)
ot.plot.plot2D_samples_mat(xs, xt, Ga.dot(Gb), c=[0.2, 0.2, 0.2], alpha=0.1)
pl.plot(xs[:, 0], xs[:, 1], "+b", label="Source samples")
pl.plot(xt[:, 0], xt[:, 1], "xr", label="Target samples")
pl.title("Factored OT low rank OT plan")

Text(0.5, 1.0, 'Factored OT low rank OT plan')

Total running time of the script: (0 minutes 1.894 seconds)

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