47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
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import numpy as np
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import matplotlib.pyplot as plt
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data = np.load("data_log_cnn_20_True_0.001_0.01_True_True_True_True.npy")
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plt.loglog(data[:, 0], 100.0 * (1.0 - data[:, 1] / 10000.0), "k", label="CNN + CNN Top")
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data = np.load("data_log_cnn_20_False_0.001_0.01_True_True_True_True.npy")
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plt.loglog(data[:, 0], 100.0 * (1.0 - data[:, 1] / 10000.0), "k--", label="CNN")
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data = np.load("data_log_nnmf_20_True_0.001_0.01_True_True_True_True.npy")
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plt.loglog(
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data[:, 0],
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100.0 * (1.0 - data[:, 1] / 10000.0),
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"r",
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label="NNMF + CNN Top (Iter 20, KL)",
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)
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data = np.load("data_log_nnmf_20_False_0.001_0.01_True_True_True_True.npy")
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plt.loglog(
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data[:, 0],
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100.0 * (1.0 - data[:, 1] / 10000.0),
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"r--",
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label="NNMF (Iter 20, KL)",
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)
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data = np.load("data_log_nnmf_20_True_0.001_0.01_True_True_True_False.npy")
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plt.loglog(
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data[:, 0],
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100.0 * (1.0 - data[:, 1] / 10000.0),
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"b",
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label="NNMF + CNN Top (Iter 20, MSE)",
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)
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data = np.load("data_log_nnmf_20_False_0.001_0.01_True_True_True_False.npy")
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plt.loglog(
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data[:, 0],
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100.0 * (1.0 - data[:, 1] / 10000.0),
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"b--",
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label="NNMF (Iter 20, MSE)",
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)
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plt.legend()
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plt.xlabel("Epoch")
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plt.ylabel("Error [%]")
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plt.show()
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