if len(sys.argv) != 2: print( 'Usage: \n"python3 KRR_script.py method"\nwhere method is one of linear polynomial gaussian laplacian' ) sys.exit(1) method = sys.argv[1] path = "Saved matrices/04-01-2019 21.56/sorted_Cutoff25_noSingleElementKrystals/" #%% Load training data featureMatrixFile = "train_featureMatrix.npy" atomicSymbolsListFile = "train_pickledAtomicSymbolsList.txt" energiesFile = "train_pickledEnergies.txt" largeFeatureMatrix, mappedAtomicNumber = simpleLargeMatrix( path, featureMatrixFile, atomicSymbolsListFile) with open(path + energiesFile, "rb") as pickleFile: energies = pickle.load(pickleFile) largeFeatureMatrix.shape = (largeFeatureMatrix.shape[0], -1) X = largeFeatureMatrix Y = np.array(energies) #%% Load validation data """ featureMatrixFileValidate = "validate_featureMatrix.npy" atomicSymbolsListFileValidate = "validate_pickledAtomicSymbolsList.txt" energiesFileValidate = "validate_pickledEnergies.txt"
if prdf == "default": path = "Saved matrices/03-01-2019 11.04/sorted_Cutoff25_noSingleElementKrystals/" elif prdf == "faulty": path = "Saved matrices/11-10-2018 11.36/sorted_Cutoff25_noSingleElementKrystals/" elif prdf == "newest": path = "Saved matrices/04-01-2019 21.56/sorted_Cutoff25_noSingleElementKrystals/" elif prdf == "deep": path = "Saved matrices/09-01-2019 16.03/sorted_Cutoff25_noSingleElementKrystals/" #%% Load training data featureMatrixFile = "train_featureMatrix.npy" atomicSymbolsListFile = "train_pickledAtomicSymbolsList.txt" energiesFile = "train_pickledEnergies.txt" if Feature == "SimpleLarge": largeFeatureMatrix = simpleLargeMatrix(path, featureMatrixFile, atomicSymbolsListFile) folder = folder + "SimpleLarge/" elif Feature == "GP": largeFeatureMatrix = advanced_large_matrix(path, featureMatrixFile, atomicSymbolsListFile) folder = folder + "GP/" with open(path + energiesFile, "rb") as pickleFile: energies = pickle.load(pickleFile) largeFeatureMatrix.shape = (largeFeatureMatrix.shape[0], -1) X = largeFeatureMatrix Y = np.array(energies) #%% Load Validation data