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
