more

1 files changed, 40 insertions, 40 deletions

diff --git a/examples/plot_OT_L1_vs_L2.py b/examples/plot_OT_L1_vs_L2.py
index e11d6ad..86d902b 100644
--- a/examples/plot_OT_L1_vs_L2.py
+++ b/examples/plot_OT_L1_vs_L2.py
@@ -12,7 +12,7 @@ https://arxiv.org/pdf/1706.07650.pdf
 """
 
 import numpy as np
-import matplotlib.pylab as plt
+import matplotlib.pylab as pl
 import ot
 
 #%% parameters and data generation
@@ -55,58 +55,58 @@ for data in range(2):
 
     #%% plot samples
 
-    plt.figure(1 + 3 * data, figsize=(7, 3))
-    plt.clf()
-    plt.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
-    plt.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
-    plt.axis('equal')
-    plt.title('Source and traget distributions')
+    pl.figure(1 + 3 * data, figsize=(7, 3))
+    pl.clf()
+    pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+    pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+    pl.axis('equal')
+    pl.title('Source and traget distributions')
 
-    plt.figure(2 + 3 * data, figsize=(7, 3))
+    pl.figure(2 + 3 * data, figsize=(7, 3))
 
-    plt.subplot(1, 3, 1)
-    plt.imshow(M1, interpolation='nearest')
-    plt.title('Euclidean cost')
+    pl.subplot(1, 3, 1)
+    pl.imshow(M1, interpolation='nearest')
+    pl.title('Euclidean cost')
 
-    plt.subplot(1, 3, 2)
-    plt.imshow(M2, interpolation='nearest')
-    plt.title('Squared Euclidean cost')
+    pl.subplot(1, 3, 2)
+    pl.imshow(M2, interpolation='nearest')
+    pl.title('Squared Euclidean cost')
 
-    plt.subplot(1, 3, 3)
-    plt.imshow(Mp, interpolation='nearest')
-    plt.title('Sqrt Euclidean cost')
-    plt.tight_layout()
+    pl.subplot(1, 3, 3)
+    pl.imshow(Mp, interpolation='nearest')
+    pl.title('Sqrt Euclidean cost')
+    pl.tight_layout()
 
     #%% EMD
     G1 = ot.emd(a, b, M1)
     G2 = ot.emd(a, b, M2)
     Gp = ot.emd(a, b, Mp)
 
-    plt.figure(3 + 3 * data, figsize=(7, 3))
+    pl.figure(3 + 3 * data, figsize=(7, 3))
 
-    plt.subplot(1, 3, 1)
+    pl.subplot(1, 3, 1)
     ot.plot.plot2D_samples_mat(xs, xt, G1, c=[.5, .5, 1])
-    plt.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
-    plt.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
-    plt.axis('equal')
-    # plt.legend(loc=0)
-    plt.title('OT Euclidean')
+    pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+    pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+    pl.axis('equal')
+    # pl.legend(loc=0)
+    pl.title('OT Euclidean')
 
-    plt.subplot(1, 3, 2)
+    pl.subplot(1, 3, 2)
     ot.plot.plot2D_samples_mat(xs, xt, G2, c=[.5, .5, 1])
-    plt.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
-    plt.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
-    plt.axis('equal')
-    # plt.legend(loc=0)
-    plt.title('OT squared Euclidean')
+    pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+    pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+    pl.axis('equal')
+    # pl.legend(loc=0)
+    pl.title('OT squared Euclidean')
 
-    plt.subplot(1, 3, 3)
+    pl.subplot(1, 3, 3)
     ot.plot.plot2D_samples_mat(xs, xt, Gp, c=[.5, .5, 1])
-    plt.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
-    plt.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
-    plt.axis('equal')
-    # plt.legend(loc=0)
-    plt.title('OT sqrt Euclidean')
-    plt.tight_layout()
-
-plt.show()
+    pl.plot(xs[:, 0], xs[:, 1], '+b', label='Source samples')
+    pl.plot(xt[:, 0], xt[:, 1], 'xr', label='Target samples')
+    pl.axis('equal')
+    # pl.legend(loc=0)
+    pl.title('OT sqrt Euclidean')
+    pl.tight_layout()
+
+pl.show()