tSNE: Wrap fastTSNE initialization

biolab · Dec 21, 2018 · b55c4f5 · b55c4f5
1 parent 0aa6e51
commit b55c4f5
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Showing 2 changed files with 6 additions and 3 deletions.
diff --git a/Orange/projection/manifold.py b/Orange/projection/manifold.py
@@ -483,3 +483,8 @@ def __call__(self, data: Table) -> TSNEModel:
         model.name = self.name
 
         return model
+
+    @staticmethod
+    def default_initialization(data, n_components=2, random_state=None):
+        return fastTSNE.initialization.pca(
+            data, n_components, random_state=random_state)
diff --git a/Orange/widgets/unsupervised/owtsne.py b/Orange/widgets/unsupervised/owtsne.py
@@ -3,8 +3,6 @@
 from AnyQt.QtCore import Qt, QTimer
 from AnyQt.QtWidgets import QFormLayout
 
-import fastTSNE.initialization
-
 from Orange.data import Table, Domain
 from Orange.preprocess.preprocess import Preprocess, ApplyDomain
 from Orange.projection import PCA, TSNE, TruncatedSVD
@@ -208,7 +206,7 @@ def __start(self):
 
         # We call PCA through fastTSNE because it involves scaling. Instead of
         # worrying about this ourselves, we'll let the library worry for us.
-        initialization = fastTSNE.initialization.pca(
+        initialization = TSNE.default_initialization(
             self.pca_data.X, n_components=2, random_state=0)
 
         # Compute perplexity settings for multiscale