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author | Nicolas Courty <ncourty@irisa.fr> | 2017-09-13 10:12:36 +0200 |
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committer | GitHub <noreply@github.com> | 2017-09-13 10:12:36 +0200 |
commit | c86cc4feb4003e90c7c3dddba237190b360fc514 (patch) | |
tree | f11601b6b1d7ef821a0ae3233960f6f29a1ac0f7 /ot/da.py | |
parent | 7e5df4cc25e6500ec6f3e85f1c80a7db94863ace (diff) | |
parent | a53ede95f916a11e2150ab7917820d813c0034bc (diff) |
Merge branch 'master' into gromov
Diffstat (limited to 'ot/da.py')
-rw-r--r-- | ot/da.py | 74 |
1 files changed, 55 insertions, 19 deletions
@@ -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 ------- |