[MRG] Crash when computing weightless Hamming distance & Doc build

RELEASES.md

@@ -23,6 +23,8 @@ incomplete transport plan above a certain size (slightly above 46k, its square b
 roughly 2^31) (PR #381)
 - Error raised when mass mismatch in emd2 (PR #386)
 - Fixed an issue where a pytorch example would throw an error if executed on a GPU (Issue #389, PR #391)
+- Added a work-around for scipy's bug, where you cannot compute the Hamming distance with a "None" weight attribute. (Issue #400, PR #402)
+- Fixed an issue where the doc could not be built due to some changes in matplotlib's API (Issue #403, PR #402)
 
 
 ## 0.8.2

examples/barycenters/plot_barycenter_1D.py

@@ -106,7 +106,7 @@
     ys = B_l2[:, i]
     verts.append(list(zip(x, ys)))
 
-ax = plt.gcf().gca(projection='3d')
+ax = plt.gcf().add_subplot(projection='3d')
 
 poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
 poly.set_alpha(0.7)
@@ -128,7 +128,7 @@
     ys = B_wass[:, i]
     verts.append(list(zip(x, ys)))
 
-ax = plt.gcf().gca(projection='3d')
+ax = plt.gcf().add_subplot(projection='3d')
 
 poly = PolyCollection(verts, facecolors=[cmap(a) for a in alpha_list])
 poly.set_alpha(0.7)

examples/unbalanced-partial/plot_UOT_barycenter_1D.py

@@ -127,7 +127,7 @@
     ys = B_l2[:, i]
     verts.append(list(zip(x, ys)))
 
-ax = pl.gcf().gca(projection='3d')
+ax = pl.gcf().add_subplot(projection='3d')
 
 poly = PolyCollection(verts, facecolors=[cmap(a) for a in weight_list])
 poly.set_alpha(0.7)
@@ -149,7 +149,7 @@
     ys = B_wass[:, i]
     verts.append(list(zip(x, ys)))
 
-ax = pl.gcf().gca(projection='3d')
+ax = pl.gcf().add_subplot(projection='3d')
 
 poly = PolyCollection(verts, facecolors=[cmap(a) for a in weight_list])
 poly.set_alpha(0.7)

ot/utils.py

@@ -234,7 +234,9 @@ def dist(x1, x2=None, metric='sqeuclidean', p=2, w=None):
         else:
             if isinstance(metric, str) and metric.endswith("minkowski"):
                 return cdist(x1, x2, metric=metric, p=p, w=w)
-            return cdist(x1, x2, metric=metric, w=w)
+            if w is not None:
+                return cdist(x1, x2, metric=metric, w=w)
+            return cdist(x1, x2, metric=metric)
 
 
 def dist0(n, method='lin_square'):

test/test_utils.py

@@ -143,6 +143,7 @@ def test_dist():
     for metric in metrics_w:
         print(metric)
         ot.dist(x, x, metric=metric, p=3, w=np.random.random((2, )))
+        ot.dist(x, x, metric=metric, p=3, w=None)  # check that not having any weight does not cause issues
     for metric in metrics:
         print(metric)
         ot.dist(x, x, metric=metric, p=3)