import math import numpy as np from numpy.linalg import eig def c_matrix(mol_data, nc_data, max_len=25, as_eig=False, bohr_radius_units=False): """ Creates the coulomb matrix from the molecule data given. mol_data: molecule data, matrix of atom coordinates. nc_data: nuclear charge data, array of atom data. max_len: maximum amount of atoms in molecule. as_eig: if data should be returned as matrix or array of eigenvalues. bohr_radius_units: if units should be in bohr's radius units. """ if bohr_radius_units: conversion_rate = 0.52917721067 else: conversion_rate = 1 mol_n = len(mol_data) mol_nr = range(mol_n) if not mol_n == len(nc_data): print(''.join(['Error. Molecule matrix dimension is different ', 'than the nuclear charge array dimension.'])) else: if max_len < mol_n: print(''.join(['Error. Molecule matrix dimension (mol_n) is ', 'greater than max_len. Using mol_n.'])) max_len = None if max_len: cm = np.zeros((max_len, max_len)) ml_r = range(max_len) # Actual calculation of the coulomb matrix. for i in ml_r: if i < mol_n: x_i = mol_data[i, 0] y_i = mol_data[i, 1] z_i = mol_data[i, 2] Z_i = nc_data[i] else: break for j in ml_r: if j < mol_n: x_j = mol_data[j, 0] y_j = mol_data[j, 1] z_j = mol_data[j, 2] Z_j = nc_data[j] x = (x_i-x_j)**2 y = (y_i-y_j)**2 z = (z_i-z_j)**2 if i == j: cm[i, j] = (0.5*Z_i**2.4) else: cm[i, j] = (conversion_rate*Z_i*Z_j/math.sqrt(x + y + z)) else: break # Now the value will be returned. if as_eig: cm_sorted = np.sort(eig(cm)[0])[::-1] # Thanks to SO for the following lines of code. # https://stackoverflow.com/a/43011036 # Keep zeros at the end. mask = cm_sorted != 0. f_mask = mask.sum(0, keepdims=1) >\ np.arange(cm_sorted.shape[0]-1, -1, -1) f_mask = f_mask[::-1] cm_sorted[f_mask] = cm_sorted[mask] cm_sorted[~f_mask] = 0. return cm_sorted else: return cm else: cm_temp = [] # Actual calculation of the coulomb matrix. for i in mol_nr: x_i = mol_data[i, 0] y_i = mol_data[i, 1] z_i = mol_data[i, 2] Z_i = nc_data[i] cm_row = [] for j in mol_nr: x_j = mol_data[j, 0] y_j = mol_data[j, 1] z_j = mol_data[j, 2] Z_j = nc_data[j] x = (x_i-x_j)**2 y = (y_i-y_j)**2 z = (z_i-z_j)**2 if i == j: cm_row.append(0.5*Z_i**2.4) else: cm_row.append(conversion_rate*Z_i*Z_j/math.sqrt(x + y + z)) cm_temp.append(np.array(cm_row)) cm = np.array(cm_temp) # Now the value will be returned. if as_eig: return np.sort(eig(cm)[0])[::-1] else: return cm