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1 | 1 | import numpy as np
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2 | 2 | from snmf_class import SNMFOptimizer
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3 | 3 |
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4 |
| -X0 = np.loadtxt("input/X0.txt", dtype=float) |
5 |
| -MM = np.loadtxt("input/MM.txt", dtype=float) |
6 |
| -A0 = np.loadtxt("input/A0.txt", dtype=float) |
7 |
| -Y0 = np.loadtxt("input/W0.txt", dtype=float) |
8 |
| -N, M = MM.shape |
| 4 | +init_comps_file = np.loadtxt("input/X0.txt", dtype=float) |
| 5 | +source_matrix_file = np.loadtxt("input/MM.txt", dtype=float) |
| 6 | +init_stretch_file = np.loadtxt("input/A0.txt", dtype=float) |
| 7 | +init_weights_file = np.loadtxt("input/W0.txt", dtype=float) |
| 8 | + |
| 9 | +my_model = SNMFOptimizer( |
| 10 | + source_matrix=source_matrix_file, |
| 11 | + init_weights=init_weights_file, |
| 12 | + init_comps=init_comps_file, |
| 13 | + init_stretch=init_stretch_file, |
| 14 | +) |
9 | 15 |
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10 |
| -my_model = SNMFOptimizer(MM=MM, Y0=Y0, X0=X0, A0=A0) |
11 | 16 | print("Done")
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12 |
| -np.savetxt("my_norm_X.txt", my_model.X, fmt="%.6g", delimiter=" ") |
13 |
| -np.savetxt("my_norm_Y.txt", my_model.Y, fmt="%.6g", delimiter=" ") |
14 |
| -np.savetxt("my_norm_A.txt", my_model.A, fmt="%.6g", delimiter=" ") |
| 17 | +np.savetxt("my_norm_comps.txt", my_model.comps, fmt="%.6g", delimiter=" ") |
| 18 | +np.savetxt("my_norm_weights.txt", my_model.weights, fmt="%.6g", delimiter=" ") |
| 19 | +np.savetxt("my_norm_stretch.txt", my_model.stretch, fmt="%.6g", delimiter=" ") |
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