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 --- .../domain-adaptation/plot_otda_linear_mapping.py | 146 +++++++++++++++++++++ 1 file changed, 146 insertions(+) create mode 100644 examples/domain-adaptation/plot_otda_linear_mapping.py (limited to 'examples/domain-adaptation/plot_otda_linear_mapping.py') diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py new file mode 100644 index 0000000..36ccb56 --- /dev/null +++ b/examples/domain-adaptation/plot_otda_linear_mapping.py @@ -0,0 +1,146 @@ +#!/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 From 956df7af113d62eab1d65f6db5fbb81897dc49c6 Mon Sep 17 00:00:00 2001 From: Rémi Flamary Date: Fri, 24 Apr 2020 17:45:13 +0200 Subject: vchange path in examples --- examples/barycenters/plot_convolutional_barycenter.py | 8 ++++---- examples/domain-adaptation/plot_otda_linear_mapping.py | 4 ++-- 2 files changed, 6 insertions(+), 6 deletions(-) (limited to 'examples/domain-adaptation/plot_otda_linear_mapping.py') diff --git a/examples/barycenters/plot_convolutional_barycenter.py b/examples/barycenters/plot_convolutional_barycenter.py index e74db04..cbcd4a1 100644 --- a/examples/barycenters/plot_convolutional_barycenter.py +++ b/examples/barycenters/plot_convolutional_barycenter.py @@ -26,10 +26,10 @@ import ot # The four distributions are constructed from 4 simple images -f1 = 1 - pl.imread('../data/redcross.png')[:, :, 2] -f2 = 1 - pl.imread('../data/duck.png')[:, :, 2] -f3 = 1 - pl.imread('../data/heart.png')[:, :, 2] -f4 = 1 - pl.imread('../data/tooth.png')[:, :, 2] +f1 = 1 - pl.imread('../../data/redcross.png')[:, :, 2] +f2 = 1 - pl.imread('../../data/duck.png')[:, :, 2] +f3 = 1 - pl.imread('../../data/heart.png')[:, :, 2] +f4 = 1 - pl.imread('../../data/tooth.png')[:, :, 2] A = [] f1 = f1 / np.sum(f1) diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py index 36ccb56..dbf16b8 100644 --- a/examples/domain-adaptation/plot_otda_linear_mapping.py +++ b/examples/domain-adaptation/plot_otda_linear_mapping.py @@ -94,8 +94,8 @@ def minmax(I): # Loading images -I1 = pl.imread('../data/ocean_day.jpg').astype(np.float64) / 256 -I2 = pl.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256 +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) -- cgit v1.2.3