def main(train_file, test_file, force):
global train
global test
train = pd.read_feather(train_file)
test = pd.read_feather(test_file)
features = list(get_features(globals()))
generate_features(features, force)
molecule_name_list = []
for molecule_name in molecule_name_array:
atom_size = np.amax(structures[structures["molecule_name"] == molecule_name]["atom_index"])
atom_size_list.append(atom_size)
molecule_name_list.append(molecule_name)
molecule_df = pd.DataFrame()
molecule_df["molecule_name"] = molecule_name_list
molecule_df["atom_size"] = atom_size_list
self.train = merge_df(train, molecule_df, "molecule_name", "molecule_name")
self.test = merge_df(test, molecule_df, "molecule_name", "molecule_name")
def merge_df(df1, df2, column1, column2):
df = pd.merge(df1, df2, how="left",
left_on=column1,
right_on=column2)
return df
if __name__ == '__main__':
args = get_arguments()
train = pd.read_feather('../data/input/train.feather')
test = pd.read_feather('../data/input/test.feather')
structures = pd.read_feather('../data/input/structures.feather')
generate_features(globals(), args.force)
