31 lines
830 B
Python
31 lines
830 B
Python
import matplotlib.pyplot as plt
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import numpy as np
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import os.path as op
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import argparse
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LOG_DIR = "mnist_tsne_output"
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if __name__ == "__main__":
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parser = argparse.ArgumentParser('Plot benchmark results for t-SNE')
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parser.add_argument(
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'--labels', type=str,
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default=op.join(LOG_DIR, 'mnist_original_labels_10000.npy'),
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help='1D integer numpy array for labels')
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parser.add_argument(
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'--embedding', type=str,
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default=op.join(LOG_DIR, 'mnist_sklearn_TSNE_10000.npy'),
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help='2D float numpy array for embedded data')
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args = parser.parse_args()
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X = np.load(args.embedding)
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y = np.load(args.labels)
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for i in np.unique(y):
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mask = y == i
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plt.scatter(X[mask, 0], X[mask, 1], alpha=0.2, label=int(i))
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plt.legend(loc='best')
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plt.show()
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