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28 lines
1.1 KiB
28 lines
1.1 KiB
2 weeks ago
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try:
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for i in range(1, 3):
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k = i
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model = pca_train_k.pca(train_data, k)
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if al_type == "SPE":
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limit = model["QCUL_95"]
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elif al_type == "FAI":
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limit = model["Kesi_95"]
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else:
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limit = model["T2CUL_95"]
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_, test_data, f_m = get_test_data_1(train_data, samples, amplitudes, fault_index, 1)
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data = (test_data - model["Train_X_mean"]) / model["Train_X_std"]
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t_r = get_rb_pca(data, model, limit, al_type, f_m)
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result.append(t_r)
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except Exception as e:
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with open('log.log', "a") as f:
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f.write(f"{str(datetime.datetime.now())}{traceback.format_exc()}")
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# for index in range(data.shape[0]):
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# line = data[index] @ m @ data[index].T
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# lines.append(line)
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# x = list(range(data.shape[0]))
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# limits_line = list(repeat(limit, data.shape[0]))
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# plt.plot(x, lines)
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# plt.plot(x, limits_line)
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# plt.title(f'k={k},limit={limit}')
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