wroking make!

1 files changed, 47 insertions, 29 deletions

diff --git a/docs/source/auto_examples/plot_optim_OTreg.rst b/docs/source/auto_examples/plot_optim_OTreg.rst
index 70cd26c..f417158 100644
--- a/docs/source/auto_examples/plot_optim_OTreg.rst
+++ b/docs/source/auto_examples/plot_optim_OTreg.rst
@@ -503,67 +503,85 @@ Regularized OT with generic solver
     import ot
 
 
-
     #%% parameters
 
-    n=100 # nb bins
+    n = 100  # nb bins
 
     # bin positions
-    x=np.arange(n,dtype=np.float64)
+    x = np.arange(n, dtype=np.float64)
 
     # Gaussian distributions
-    a=ot.datasets.get_1D_gauss(n,m=20,s=5) # m= mean, s= std
-    b=ot.datasets.get_1D_gauss(n,m=60,s=10)
+    a = ot.datasets.get_1D_gauss(n, m=20, s=5)  # m= mean, s= std
+    b = ot.datasets.get_1D_gauss(n, m=60, s=10)
 
     # loss matrix
-    M=ot.dist(x.reshape((n,1)),x.reshape((n,1)))
-    M/=M.max()
+    M = ot.dist(x.reshape((n, 1)), x.reshape((n, 1)))
+    M /= M.max()
 
     #%% EMD
 
-    G0=ot.emd(a,b,M)
+    G0 = ot.emd(a, b, M)
 
-    pl.figure(3)
-    ot.plot.plot1D_mat(a,b,G0,'OT matrix G0')
+    pl.figure(3, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, G0, 'OT matrix G0')
 
     #%% Example with Frobenius norm regularization
 
-    def f(G): return 0.5*np.sum(G**2)
-    def df(G): return G
 
-    reg=1e-1
+    def f(G):
+        return 0.5 * np.sum(G**2)
+
+
+    def df(G):
+        return G
 
-    Gl2=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
+
+    reg = 1e-1
+
+    Gl2 = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
 
     pl.figure(3)
-    ot.plot.plot1D_mat(a,b,Gl2,'OT matrix Frob. reg')
+    ot.plot.plot1D_mat(a, b, Gl2, 'OT matrix Frob. reg')
 
     #%% Example with entropic regularization
 
-    def f(G): return np.sum(G*np.log(G))
-    def df(G): return np.log(G)+1
 
-    reg=1e-3
+    def f(G):
+        return np.sum(G * np.log(G))
+
+
+    def df(G):
+        return np.log(G) + 1.
 
-    Ge=ot.optim.cg(a,b,M,reg,f,df,verbose=True)
 
-    pl.figure(4)
-    ot.plot.plot1D_mat(a,b,Ge,'OT matrix Entrop. reg')
+    reg = 1e-3
+
+    Ge = ot.optim.cg(a, b, M, reg, f, df, verbose=True)
+
+    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
 
-    def f(G): return 0.5*np.sum(G**2)
-    def df(G): return G
 
-    reg1=1e-3
-    reg2=1e-1
+    def f(G):
+        return 0.5 * np.sum(G**2)
+
+
+    def df(G):
+        return G
 
-    Gel2=ot.optim.gcg(a,b,M,reg1,reg2,f,df,verbose=True)
 
-    pl.figure(5)
-    ot.plot.plot1D_mat(a,b,Gel2,'OT entropic + matrix Frob. reg')
+    reg1 = 1e-3
+    reg2 = 1e-1
+
+    Gel2 = ot.optim.gcg(a, b, M, reg1, reg2, f, df, verbose=True)
+
+    pl.figure(5, figsize=(5, 5))
+    ot.plot.plot1D_mat(a, b, Gel2, 'OT entropic + matrix Frob. reg')
     pl.show()
-**Total running time of the script:** ( 0 minutes  2.319 seconds)
+
+**Total running time of the script:** ( 0 minutes  2.720 seconds)