doc sinkhorn

1 files changed, 22 insertions, 8 deletions

diff --git a/ot/lp/__init__.py b/ot/lp/__init__.py
index 568e370..72b4cb8 100644
--- a/ot/lp/__init__.py
+++ b/ot/lp/__init__.py
@@ -7,7 +7,6 @@ def emd(a,b,M):
     """
         Solves the Earth Movers distance problem and returns the optimal transport matrix
         
-        gamm=emd(a,b,M)
     
     .. math::
         \gamma = arg\min_\gamma <\gamma,M>_F 
@@ -21,6 +20,8 @@ def emd(a,b,M):
     
     - M is the metric cost matrix
     - a and b are the sample weights
+    
+    Uses the algorithm proposed in [1]_
              
     Parameters
     ----------
@@ -31,11 +32,17 @@ def emd(a,b,M):
     M : (ns,nt) ndarray, float64
         loss matrix        
         
+    Returns
+    -------
+    gamma: (ns x nt) ndarray
+        Optimal transportation matrix for the given parameters
+         
+        
     Examples
     --------
     
-    Simple example with obvious solution. The function :func:emd accepts lists and
-    perform automatic conversion tu numpy arrays 
+    Simple example with obvious solution. The function emd accepts lists and
+    perform automatic conversion to numpy arrays 
     
     >>> a=[.5,.5]
     >>> b=[.5,.5]
@@ -43,15 +50,22 @@ def emd(a,b,M):
     >>> ot.emd(a,b,M)
     array([[ 0.5,  0. ],
            [ 0. ,  0.5]])
+           
+    References
+    ----------
     
-    Returns
-    -------
-    gamma: (ns x nt) ndarray
-        Optimal transportation matrix for the given parameters
- 
+    .. [1] Bonneel, N., Van De Panne, M., Paris, S., & Heidrich, W. (2011, December).  Displacement interpolation using Lagrangian mass transport. In ACM Transactions on Graphics (TOG) (Vol. 30, No. 6, p. 158). ACM.
+        
+    See Also
+    --------
+    ot.bregman.sinkhorn : Entropic regularized OT
+    ot.optim.cg : General regularized OT           
+    
+
     """
     a=np.asarray(a,dtype=np.float64)
     b=np.asarray(b,dtype=np.float64)
+    M=np.asarray(M,dtype=np.float64)
     
     if len(a)==0:
         a=np.ones((M.shape[0],),dtype=np.float64)/M.shape[0]