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| Error_from_formula.NSPS = np.arange(10, 101, 10, dtype=int) |
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list | Error_from_formula.scores = [] |
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| Error_from_formula.Learn |
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| Error_from_formula.momLabels |
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| Error_from_formula.momData |
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| Error_from_formula.NDatasets |
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| Error_from_formula.DataString = SpaceString(inp.momData) |
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| Error_from_formula.LabelString = SpaceString(inp.momLabels) |
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string | Error_from_formula.fname = 'Errors_'+inp.Learn+'_in_'+LabelString+'_from_SSS_in_'+DataString+'_from_formula_'+str(inp.NDatasets)+'_datasets' |
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| Error_from_formula.NShotsPerSample |
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| Error_from_formula.NShots |
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| Error_from_formula.training_generator |
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| Error_from_formula.validation_generator |
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| Error_from_formula.X_train |
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| Error_from_formula.y_train |
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| Error_from_formula.X_val |
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| Error_from_formula.y_val = np.array(y_val) |
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| Error_from_formula.x_data = np.reshape(np.concatenate((np.array(X_train),np.array(X_val))),(inp.NDatasets,256,i)) |
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| Error_from_formula.y_data = np.reshape(np.concatenate((np.array(y_train),np.array(y_val))),(inp.NDatasets,256*256)) |
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list | Error_from_formula.thiserr = [] |
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list | Error_from_formula.rho2 = [] |
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float | Error_from_formula.local_err = y_data[j,:]/83.0-np.reshape(rho2,inp.Npoints*inp.Npoints) |
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list | Error_from_formula.rho = [] |
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list | Error_from_formula.legend = [] |
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| Error_from_formula.fig |
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| Error_from_formula.ax |
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| Error_from_formula.yerr |
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| Error_from_formula.fmt |
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| Error_from_formula.ecolor |
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| Error_from_formula.loc |
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| Error_from_formula.xlabel |
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| Error_from_formula.ylabel |
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