From 0d7df3b34b99a7578e7fbac68b40852dc6710524 Mon Sep 17 00:00:00 2001
From: Rémi Flamary <remi.flamary@gmail.com>
Date: Fri, 28 Oct 2016 13:35:53 +0200
Subject: doc plot.py

---
 ot/plot.py  | 42 ++++++++++++++++++++++++++++++++++++++++--
 ot/utils.py |  2 ++
 2 files changed, 42 insertions(+), 2 deletions(-)

(limited to 'ot')

diff --git a/ot/plot.py b/ot/plot.py
index d172c90..9737f8a 100644
--- a/ot/plot.py
+++ b/ot/plot.py
@@ -9,7 +9,25 @@ from matplotlib import gridspec
 
 
 def plot1D_mat(a,b,M,title=''):
-    """ Plot matrix M  with the source and target 1D distribution """
+    """ Plot matrix M  with the source and target 1D distribution 
+    
+    Creates a subplot with the source distribution a on the left and 
+    target distribution b on the tot. The matrix M is shown in between.
+    
+    
+    Parameters
+    ----------
+
+    a : np.array (na,)
+        Source distribution
+    b : np.array (nb,)
+        Target distribution  
+    M : np.array (na,nb)
+        Matrix to plot
+    
+    
+    
+    """
     
     na=M.shape[0]
     nb=M.shape[1]
@@ -43,7 +61,27 @@ def plot1D_mat(a,b,M,title=''):
 
 
 def plot2D_samples_mat(xs,xt,G,thr=1e-8,**kwargs):
-    """ Plot matrix M  in 2D with  lines using alpha values"""
+    """ Plot matrix M  in 2D with  lines using alpha values
+    
+    Plot lines between source and target 2D samples with a color 
+    proportional to the value of the matrix G between samples.
+    
+    
+    Parameters
+    ----------
+
+    xs : np.array (ns,2)
+        Source samples positions
+    b : np.array (nt,2)
+        Target samples positions
+    G : np.array (na,nb)
+        OT matrix
+    thr : float, optional
+        threshold above which the line is drawn
+    **kwargs : dict
+        paameters given to the plot functions (default color is black if nothing given)
+    
+    """
     if ('color' not in kwargs) and ('c' not  in kwargs):
         kwargs['color']='k'
     mx=G.max()
diff --git a/ot/utils.py b/ot/utils.py
index 2110c01..24f65a8 100644
--- a/ot/utils.py
+++ b/ot/utils.py
@@ -45,6 +45,7 @@ def dist(x1,x2=None,metric='sqeuclidean'):
   
     Returns
     -------
+    
     M : np.array (n1,n2)
         distance matrix computed with given metric
     
@@ -70,6 +71,7 @@ def dist0(n,method='lin_square'):
   
     Returns
     -------
+    
     M : np.array (n1,n2)
         distance matrix computed with given metric    
     
-- 
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