Merge remote-tracking branch 'upstream/master' into ot_dual_variables

1 files changed, 55 insertions, 19 deletions

diff --git a/ot/da.py b/ot/da.py
index 564c7b7..1d3d0ba 100644
--- a/ot/da.py
+++ b/ot/da.py
@@ -966,8 +966,12 @@ class BaseTransport(BaseEstimator):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -989,7 +993,7 @@ class BaseTransport(BaseEstimator):
 
                 # assumes labeled source samples occupy the first rows
                 # and labeled target samples occupy the first columns
-                classes = np.unique(ys)
+                classes = [c for c in np.unique(ys) if c != -1]
                 for c in classes:
                     idx_s = np.where((ys != c) & (ys != -1))
                     idx_t = np.where(yt == c)
@@ -1023,8 +1027,12 @@ class BaseTransport(BaseEstimator):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -1045,8 +1053,12 @@ class BaseTransport(BaseEstimator):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
         batch_size : int, optional (default=128)
             The batch size for out of sample inverse transform
 
@@ -1110,8 +1122,12 @@ class BaseTransport(BaseEstimator):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
         batch_size : int, optional (default=128)
             The batch size for out of sample inverse transform
 
@@ -1241,8 +1257,12 @@ class SinkhornTransport(BaseTransport):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -1333,8 +1353,12 @@ class EMDTransport(BaseTransport):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -1434,8 +1458,12 @@ class SinkhornLpl1Transport(BaseTransport):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -1545,8 +1573,12 @@ class SinkhornL1l2Transport(BaseTransport):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------
@@ -1662,8 +1694,12 @@ class MappingTransport(BaseEstimator):
             The class labels
         Xt : array-like, shape (n_target_samples, n_features)
             The training input samples.
-        yt : array-like, shape (n_labeled_target_samples,)
-            The class labels
+        yt : array-like, shape (n_target_samples,)
+            The class labels. If some target samples are unlabeled, fill the
+            yt's elements with -1.
+
+            Warning: Note that, due to this convention -1 cannot be used as a
+            class label
 
         Returns
         -------