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Author: agramfort

examples/plot_OT_1D.py

@@ -8,7 +8,7 @@
 """
 
 import numpy as np
-import matplotlib.pylab as plt
+import matplotlib.pylab as pl
 import ot
 from ot.datasets import get_1D_gauss as gauss
 
@@ -29,29 +29,29 @@
 
 #%% plot the distributions
 
-plt.figure(1)
-plt.plot(x, a, 'b', label='Source distribution')
-plt.plot(x, b, 'r', label='Target distribution')
-plt.legend()
+pl.figure(1, figsize=(6.4, 3))
+pl.plot(x, a, 'b', label='Source distribution')
+pl.plot(x, b, 'r', label='Target distribution')
+pl.legend()
 
 #%% plot distributions and loss matrix
 
-plt.figure(2, figsize=(5, 5))
+pl.figure(2, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, M, 'Cost matrix M')
 
 #%% EMD
 
 G0 = ot.emd(a, b, M)
 
-plt.figure(3, figsize=(5, 5))
+pl.figure(3, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
 
 #%% Sinkhorn
 
 lambd = 1e-3
 Gs = ot.sinkhorn(a, b, M, lambd, verbose=True)
 
-plt.figure(4, figsize=(5, 5))
+pl.figure(4, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, Gs, 'OT matrix Sinkhorn')
 
-plt.show()
+pl.show()

examples/plot_optim_OTreg.py

@@ -31,7 +31,7 @@
 
 G0 = ot.emd(a, b, M)
 
-pl.figure(3)
+pl.figure(3, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
 
 #%% Example with Frobenius norm regularization
@@ -64,7 +64,7 @@ def df(G):
 
 Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
 
-pl.figure(4)
+pl.figure(4, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, Ge, 'OT matrix Entrop. reg')
 
 #%% Example with Frobenius norm + entropic regularization with gcg
@@ -82,6 +82,6 @@ def df(G):
 
 Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)
 
-pl.figure(5)
+pl.figure(5, figsize=(5, 5))
 ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')
 pl.show()