Made weight vectors optional to match scipy's wass1d API

Author: rtavenar

ot/lp/__init__.py

@@ -313,7 +313,7 @@ def free_support_barycenter(measures_locations, measures_weights, X_init, b=None
         return X
 
 
-def emd_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
+def emd_1d(x_a, x_b, a=None, b=None, metric='sqeuclidean', dense=True, log=False):
     """Solves the Earth Movers distance problem between 1d measures and returns
     the OT matrix
 
@@ -338,10 +338,10 @@ def emd_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
         Source dirac locations (on the real line)
     x_b : (nt,) or (ns, 1) ndarray, float64
         Target dirac locations (on the real line)
-    a : (ns,) ndarray, float64
-        Source histogram (uniform weight if empty list)
-    b : (nt,) ndarray, float64
-        Target histogram (uniform weight if empty list)
+    a : (ns,) ndarray, float64, optional
+        Source histogram (default is uniform weight)
+    b : (nt,) ndarray, float64, optional
+        Target histogram (default is uniform weight)
     metric: str, optional (default='sqeuclidean')
         Metric to be used. Only strings listed in :func:`ot.dist` are accepted.
         Due to implementation details, this function runs faster when
@@ -375,6 +375,9 @@ def emd_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
     >>> x_a = [2., 0.]
     >>> x_b = [0., 3.]
     >>> ot.emd_1d(x_a, x_b, a, b)
+    array([[0. ,  0.5],
+           [0.5,  0. ]])
+    >>> ot.emd_1d(x_a, x_b)
     array([[0. ,  0.5],
            [0.5,  0. ]])
 
@@ -401,9 +404,9 @@ def emd_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
         "emd_1d should only be used with monodimensional data"
 
     # if empty array given then use uniform distributions
-    if len(a) == 0:
+    if a.ndim == 0 or len(a) == 0:
         a = np.ones((x_a.shape[0],), dtype=np.float64) / x_a.shape[0]
-    if len(b) == 0:
+    if b.ndim == 0 or len(b) == 0:
         b = np.ones((x_b.shape[0],), dtype=np.float64) / x_b.shape[0]
 
     x_a_1d = x_a.reshape((-1, ))
@@ -424,7 +427,7 @@ def emd_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
     return G
 
 
-def emd2_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
+def emd2_1d(x_a, x_b, a=None, b=None, metric='sqeuclidean', dense=True, log=False):
     """Solves the Earth Movers distance problem between 1d measures and returns
     the loss
 
@@ -449,10 +452,10 @@ def emd2_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
         Source dirac locations (on the real line)
     x_b : (nt,) or (ns, 1) ndarray, float64
         Target dirac locations (on the real line)
-    a : (ns,) ndarray, float64
-        Source histogram (uniform weight if empty list)
-    b : (nt,) ndarray, float64
-        Target histogram (uniform weight if empty list)
+    a : (ns,) ndarray, float64, optional
+        Source histogram (default is uniform weight)
+    b : (nt,) ndarray, float64, optional
+        Target histogram (default is uniform weight)
     metric: str, optional (default='sqeuclidean')
         Metric to be used. Only strings listed in :func:`ot.dist` are accepted.
         Due to implementation details, this function runs faster when
@@ -488,6 +491,8 @@ def emd2_1d(x_a, x_b, a, b, metric='sqeuclidean', dense=True, log=False):
     >>> x_b = [0., 3.]
     >>> ot.emd2_1d(x_a, x_b, a, b)
     0.5
+    >>> ot.emd2_1d(x_a, x_b)
+    0.5
 
     References
     ----------