Source code for openTSNE.sklearn

import openTSNE
import numpy as np


[docs]class TSNE(openTSNE.TSNE): __doc__ = openTSNE.TSNE.__doc__
[docs] def fit(self, X, y=None): """Fit X into an embedded space. Parameters ---------- X: np.ndarray The data matrix to be embedded. y : ignored """ self.fit_transform(X, y) return self
[docs] def fit_transform(self, X, y=None): """Fit X into an embedded space and return that transformed output. Parameters ---------- X: np.ndarray The data matrix to be embedded. y : ignored Returns ------- np.ndarray Embedding of the training data in low-dimensional space. """ embedding = super().fit(X) self.embedding_ = embedding return self.embedding_.view(np.ndarray)
[docs] def transform(self, X, *args, **kwargs): """Apply dimensionality reduction to X. See :meth:`openTSNE.TSNEEmbedding.transform` for additional parameters. Parameters ---------- X: np.ndarray The data matrix to be embedded. Returns ------- np.ndarray Embedding of the training data in low-dimensional space. """ embedding = self.embedding_.transform(X, *args, **kwargs) return embedding.view(np.ndarray)