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Those clusters are made by PCA and t-SNE, and drawn by matplotlib. The code has not been organized for release, but I can put the core code here for temporal usage:
fromsklearn.decompositionimportPCAfromsklearn.manifoldimportTSNEdeftsne_on_pca(arr):
""" visualize through t-sne on pca reduced data :param arr: ndarray, (nr_examples, nr_features) :return: ndarray, (nr_examples, 2) """pca_50=PCA(n_components=50)
res=pca_50.fit_transform(arr)
tsne_2=TSNE(n_components=2)
res=tsne_2.fit_transform(res)
returnres# apply this function on latent vectors
Is the code to cluster the motions into the latent space also available?
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