1 files changed, 40 insertions, 33 deletions
diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py
index be47510..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')
 
 
 ##############################################################################
@@ -66,13 +70,13 @@ 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
@@ -94,8 +98,11 @@ def minmax(img):
 
 
 # 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')