diff options
Diffstat (limited to 'examples/domain-adaptation/plot_otda_linear_mapping.py')
| -rw-r--r-- | examples/domain-adaptation/plot_otda_linear_mapping.py | 81 |
1 files changed, 44 insertions, 37 deletions
diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py index dbf16b8..a44096a 100644 --- a/examples/domain-adaptation/plot_otda_linear_mapping.py +++ b/examples/domain-adaptation/plot_otda_linear_mapping.py @@ -13,9 +13,11 @@ Linear OT mapping estimation # License: MIT License # sphinx_gallery_thumbnail_number = 2 +import os +from pathlib import Path import numpy as np -import pylab as pl +from matplotlib import pyplot as plt import ot ############################################################################## @@ -26,17 +28,19 @@ n = 1000 d = 2 sigma = .1 +rng = np.random.RandomState(42) + # source samples -angles = np.random.rand(n, 1) * 2 * np.pi +angles = rng.rand(n, 1) * 2 * np.pi xs = np.concatenate((np.sin(angles), np.cos(angles)), - axis=1) + sigma * np.random.randn(n, 2) + axis=1) + sigma * rng.randn(n, 2) xs[:n // 2, 1] += 2 # target samples -anglet = np.random.rand(n, 1) * 2 * np.pi +anglet = rng.rand(n, 1) * 2 * np.pi xt = np.concatenate((np.sin(anglet), np.cos(anglet)), - axis=1) + sigma * np.random.randn(n, 2) + axis=1) + sigma * rng.randn(n, 2) xt[:n // 2, 1] += 2 @@ -48,9 +52,9 @@ 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') +plt.figure(1, (5, 5)) +plt.plot(xs[:, 0], xs[:, 1], '+') +plt.plot(xt[:, 0], xt[:, 1], 'o') ############################################################################## @@ -66,22 +70,22 @@ 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], '+') +plt.figure(1, (5, 5)) +plt.clf() +plt.plot(xs[:, 0], xs[:, 1], '+') +plt.plot(xt[:, 0], xt[:, 1], 'o') +plt.plot(xst[:, 0], xst[:, 1], '+') -pl.show() +plt.show() ############################################################################## # Load image data # --------------- -def im2mat(I): +def im2mat(img): """Converts and image to matrix (one pixel per line)""" - return I.reshape((I.shape[0] * I.shape[1], I.shape[2])) + return img.reshape((img.shape[0] * img.shape[1], img.shape[2])) def mat2im(X, shape): @@ -89,13 +93,16 @@ def mat2im(X, shape): return X.reshape(shape) -def minmax(I): - return np.clip(I, 0, 1) +def minmax(img): + return np.clip(img, 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 +this_file = os.path.realpath('__file__') +data_path = os.path.join(Path(this_file).parent.parent.parent, 'data') + +I1 = plt.imread(os.path.join(data_path, 'ocean_day.jpg')).astype(np.float64) / 256 +I2 = plt.imread(os.path.join(data_path, 'ocean_sunset.jpg')).astype(np.float64) / 256 X1 = im2mat(I1) @@ -123,24 +130,24 @@ I2t = minmax(mat2im(xts, I2.shape)) # Plot transformed images # ----------------------- -pl.figure(2, figsize=(10, 7)) +plt.figure(2, figsize=(10, 7)) -pl.subplot(2, 2, 1) -pl.imshow(I1) -pl.axis('off') -pl.title('Im. 1') +plt.subplot(2, 2, 1) +plt.imshow(I1) +plt.axis('off') +plt.title('Im. 1') -pl.subplot(2, 2, 2) -pl.imshow(I2) -pl.axis('off') -pl.title('Im. 2') +plt.subplot(2, 2, 2) +plt.imshow(I2) +plt.axis('off') +plt.title('Im. 2') -pl.subplot(2, 2, 3) -pl.imshow(I1t) -pl.axis('off') -pl.title('Mapping Im. 1') +plt.subplot(2, 2, 3) +plt.imshow(I1t) +plt.axis('off') +plt.title('Mapping Im. 1') -pl.subplot(2, 2, 4) -pl.imshow(I2t) -pl.axis('off') -pl.title('Inverse mapping Im. 2') +plt.subplot(2, 2, 4) +plt.imshow(I2t) +plt.axis('off') +plt.title('Inverse mapping Im. 2') |