"""MIT License Copyright (c) 2019 David Luevano Alvarado Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import os import time import numpy as np import random from misc import printc # 'periodic_table_of_elements.txt' retrieved from # https://gist.github.com/GoodmanSciences/c2dd862cd38f21b0ad36b8f96b4bf1ee def read_nc_data(data_path): """ Reads nuclear charge data from file and returns a dictionary. data_path: path to the data directory. """ fname = 'periodic_table_of_elements.txt' with open(''.join([data_path, '\\', fname]), 'r') as infile: temp_lines = infile.readlines() del temp_lines[0] lines = [] for temp_line in temp_lines: new_line = temp_line.split(sep=',') lines.append(new_line) # Dictionary of nuclear charge. return {line[2]: int(line[0]) for line in lines} # 'hof_qm7.txt.txt' retrieved from # https://github.com/qmlcode/tutorial def reas_db_data(zi_data, data_path, r_seed=111): """ Reads molecule database and extracts its contents as usable variables. zi_data: dictionary containing nuclear charge data. data_path: path to the data directory. r_seed: random seed. """ os.chdir(data_path) fname = 'hof_qm7.txt' with open(fname, 'r') as infile: lines = infile.readlines() # Temporary energy dictionary. energy_temp = dict() for line in lines: xyz_data = line.split() xyz_name = xyz_data[0] hof = float(xyz_data[1]) dftb = float(xyz_data[2]) # print(xyz_name, hof, dftb) energy_temp[xyz_name] = np.array([hof, hof - dftb]) # Use a random seed. random.seed(r_seed) et_keys = list(energy_temp.keys()) random.shuffle(et_keys) # Temporary energy dictionary, shuffled. energy_temp_shuffled = dict() for key in et_keys: energy_temp_shuffled.update({key: energy_temp[key]}) mol_data = [] mol_nc_data = [] # Actual reading of the xyz files. for i, k in enumerate(energy_temp_shuffled.keys()): with open(k, 'r') as xyz_file: lines = xyz_file.readlines() len_lines = len(lines) mol_temp_data = [] mol_nc_temp_data = np.array(np.zeros(len_lines-2)) for j, line in enumerate(lines[2:len_lines]): line_list = line.split() mol_nc_temp_data[j] = float(zi_data[line_list[0]]) line_data = np.array(np.asarray(line_list[1:4], dtype=float)) mol_temp_data.append(line_data) mol_data.append(mol_temp_data) mol_nc_data.append(mol_nc_temp_data) # Convert everything to a numpy array. molecules = np.array([np.array(mol) for mol in mol_data]) nuclear_charge = np.array([nc_d for nc_d in mol_nc_data]) energy_pbe0 = np.array([energy_temp_shuffled[k][0] for k in energy_temp_shuffled.keys()]) energy_delta = np.array([energy_temp_shuffled[k][1] for k in energy_temp_shuffled.keys()]) return molecules, nuclear_charge, energy_pbe0, energy_delta def read_qm7_data(): """ Reads all the qm7 data. """ tic = time.perf_counter() printc('Data reading started.', 'CYAN') init_path = os.getcwd() os.chdir('data') data_path = os.getcwd() zi_data = read_nc_data(data_path) molecules, nuclear_charge, energy_pbe0, energy_delta = \ reas_db_data(zi_data, data_path) os.chdir(init_path) toc = time.perf_counter() printc('\tData reading took {:.4f} seconds.'.format(toc-tic), 'GREEN') return zi_data, molecules, nuclear_charge, energy_pbe0, energy_delta