From a54775103541ea37f54269de1ba1e1396a6d7b30 Mon Sep 17 00:00:00 2001 From: Rémi Flamary Date: Fri, 24 Apr 2020 17:32:57 +0200 Subject: exmaples in sections --- examples/plot_otda_linear_mapping.py | 146 ----------------------------------- 1 file changed, 146 deletions(-) delete mode 100644 examples/plot_otda_linear_mapping.py (limited to 'examples/plot_otda_linear_mapping.py') diff --git a/examples/plot_otda_linear_mapping.py b/examples/plot_otda_linear_mapping.py deleted file mode 100644 index 36ccb56..0000000 --- a/examples/plot_otda_linear_mapping.py +++ /dev/null @@ -1,146 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- -""" -============================ -Linear OT mapping estimation -============================ - - -""" - -# Author: Remi Flamary -# -# License: MIT License - -# sphinx_gallery_thumbnail_number = 2 - -import numpy as np -import pylab as pl -import ot - -############################################################################## -# Generate data -# ------------- - -n = 1000 -d = 2 -sigma = .1 - -# source samples -angles = np.random.rand(n, 1) * 2 * np.pi -xs = np.concatenate((np.sin(angles), np.cos(angles)), - axis=1) + sigma * np.random.randn(n, 2) -xs[:n // 2, 1] += 2 - - -# target samples -anglet = np.random.rand(n, 1) * 2 * np.pi -xt = np.concatenate((np.sin(anglet), np.cos(anglet)), - axis=1) + sigma * np.random.randn(n, 2) -xt[:n // 2, 1] += 2 - - -A = np.array([[1.5, .7], [.7, 1.5]]) -b = np.array([[4, 2]]) -xt = xt.dot(A) + b - -############################################################################## -# Plot data -# --------- - -pl.figure(1, (5, 5)) -pl.plot(xs[:, 0], xs[:, 1], '+') -pl.plot(xt[:, 0], xt[:, 1], 'o') - - -############################################################################## -# Estimate linear mapping and transport -# ------------------------------------- - -Ae, be = ot.da.OT_mapping_linear(xs, xt) - -xst = xs.dot(Ae) + be - - -############################################################################## -# Plot transported samples -# ------------------------ - -pl.figure(1, (5, 5)) -pl.clf() -pl.plot(xs[:, 0], xs[:, 1], '+') -pl.plot(xt[:, 0], xt[:, 1], 'o') -pl.plot(xst[:, 0], xst[:, 1], '+') - -pl.show() - -############################################################################## -# Load image data -# --------------- - - -def im2mat(I): - """Converts and image to matrix (one pixel per line)""" - return I.reshape((I.shape[0] * I.shape[1], I.shape[2])) - - -def mat2im(X, shape): - """Converts back a matrix to an image""" - return X.reshape(shape) - - -def minmax(I): - return np.clip(I, 0, 1) - - -# Loading images -I1 = pl.imread('../data/ocean_day.jpg').astype(np.float64) / 256 -I2 = pl.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256 - - -X1 = im2mat(I1) -X2 = im2mat(I2) - -############################################################################## -# Estimate mapping and adapt -# ---------------------------- - -mapping = ot.da.LinearTransport() - -mapping.fit(Xs=X1, Xt=X2) - - -xst = mapping.transform(Xs=X1) -xts = mapping.inverse_transform(Xt=X2) - -I1t = minmax(mat2im(xst, I1.shape)) -I2t = minmax(mat2im(xts, I2.shape)) - -# %% - - -############################################################################## -# Plot transformed images -# ----------------------- - -pl.figure(2, figsize=(10, 7)) - -pl.subplot(2, 2, 1) -pl.imshow(I1) -pl.axis('off') -pl.title('Im. 1') - -pl.subplot(2, 2, 2) -pl.imshow(I2) -pl.axis('off') -pl.title('Im. 2') - -pl.subplot(2, 2, 3) -pl.imshow(I1t) -pl.axis('off') -pl.title('Mapping Im. 1') - -pl.subplot(2, 2, 4) -pl.imshow(I2t) -pl.axis('off') -pl.title('Inverse mapping Im. 2') -- cgit v1.2.3