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23 lines
653 B
Python
23 lines
653 B
Python
from sklearn.decomposition import PCA
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from matplotlib import pyplot as plt
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from simulation_list import SimulationList
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from mpl_toolkits.mplot3d import Axes3D
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import numpy as np
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simulations = SimulationList.jsonlines_load()
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np.set_printoptions(linewidth=1000,edgeitems=4)
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data = simulations.as_matrix
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simpledata=data[:, 4:]
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pca = PCA(n_components=3)
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pca.fit(simpledata)
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print(pca.components_)
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X_pca = pca.transform(simpledata)
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X_new = pca.inverse_transform(X_pca)
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print(X_pca)
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fig = plt.figure()
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ax = Axes3D(fig)
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# ax.scatter(simpledata[:, 0],simpledata[:, 1], simpledata[:, 2])
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# plt.show()
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ax.scatter(X_new[:, 0],X_new[:, 1], X_new[:, 2])
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plt.show()
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