utils.helper.plot_tSNE

utils.helper.plot_tSNE(latent, labels, cmap=<matplotlib.colors.ListedColormap object>, perform_tsne=True)[source]

Adoptd from:

Lopez R, Regier J, Cole MB, Jordan MI, Yosef N. Deep generative modeling for single-cell transcriptomics. Nat Methods. 2018 Dec;15(12):1053-1058. doi: 10.1038/s41592-018-0229-2.

Given a latent space and class labels, the function will calculate the tSNE of the latent space and make a graph of the tSNE latent space using the classes.

Parameters

latent_spacenumpy ndarray: The latent space matrix.
labelsa numpy array or a list: The batch (or cluster) number of each sample in the latent space matrix.
cmappylot instance: a colormap instance (see Matplotlib doc for more info).
perform_tsneBoolean: If True the function will perform the tSNE. Otherwise, tSNE will not be performed on the latent space.

Returns

latentnumpy ndarray: The latent space of the tSNE.