Merge pull request #44 from tardyb/addLog

Using log parameter, fixes #43 

Thank you @tardyb

Author: rflamary

ot/da.py

@@ -1332,13 +1332,14 @@ class EMDTransport(BaseTransport):
            on Pattern Analysis and Machine Intelligence , vol.PP, no.99, pp.1-1
     """
 
-    def __init__(self, metric="sqeuclidean", norm=None,
+    def __init__(self, metric="sqeuclidean", norm=None, log=False,
                  distribution_estimation=distribution_estimation_uniform,
                  out_of_sample_map='ferradans', limit_max=10,
                  max_iter=100000):
 
         self.metric = metric
         self.norm = norm
+        self.log = log
         self.limit_max = limit_max
         self.distribution_estimation = distribution_estimation
         self.out_of_sample_map = out_of_sample_map
@@ -1371,11 +1372,16 @@ class label
 
         super(EMDTransport, self).fit(Xs, ys, Xt, yt)
 
-        # coupling estimation
-        self.coupling_ = emd(
-            a=self.mu_s, b=self.mu_t, M=self.cost_, numItermax=self.max_iter
-        )
+        returned_ = emd(
+            a=self.mu_s, b=self.mu_t, M=self.cost_, numItermax=self.max_iter,
+            log=self.log)
 
+        # coupling estimation
+        if self.log:
+            self.coupling_, self.log_ = returned_
+        else:
+            self.coupling_ = returned_
+            self.log_ = dict()
         return self
 
 
@@ -1432,7 +1438,7 @@ class SinkhornLpl1Transport(BaseTransport):
     """
 
     def __init__(self, reg_e=1., reg_cl=0.1,
-                 max_iter=10, max_inner_iter=200,
+                 max_iter=10, max_inner_iter=200, log=False,
                  tol=10e-9, verbose=False,
                  metric="sqeuclidean", norm=None,
                  distribution_estimation=distribution_estimation_uniform,
@@ -1443,6 +1449,7 @@ def __init__(self, reg_e=1., reg_cl=0.1,
         self.max_iter = max_iter
         self.max_inner_iter = max_inner_iter
         self.tol = tol
+        self.log = log
         self.verbose = verbose
         self.metric = metric
         self.norm = norm
@@ -1480,12 +1487,18 @@ class label
 
             super(SinkhornLpl1Transport, self).fit(Xs, ys, Xt, yt)
 
-            self.coupling_ = sinkhorn_lpl1_mm(
+            returned_ = sinkhorn_lpl1_mm(
                 a=self.mu_s, labels_a=ys, b=self.mu_t, M=self.cost_,
                 reg=self.reg_e, eta=self.reg_cl, numItermax=self.max_iter,
                 numInnerItermax=self.max_inner_iter, stopInnerThr=self.tol,
-                verbose=self.verbose)
+                verbose=self.verbose, log=self.log)
 
+        # deal with the value of log
+        if self.log:
+            self.coupling_, self.log_ = returned_
+        else:
+            self.coupling_ = returned_
+            self.log_ = dict()
         return self