Vitor Hideyoshi Nakazone Batista
2899031b71
Signed-off-by: Vitor Hideyoshi <vitor.h.n.batista@gmail.com>
604 lines
17 KiB
Python
604 lines
17 KiB
Python
import sys, math
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import textwrap
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from copy import deepcopy
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import numpy as np
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from numpy import linalg
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from DPpack.PTable import *
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from DPpack.SetGlobals import *
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####################################### functions ######################################
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def center_of_mass(molecule):
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com = np.zeros(3)
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total_mass = 0.0
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for atom in molecule:
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total_mass += atom['mass']
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position = np.array([atom['rx'], atom['ry'], atom['rz']])
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com += atom['mass'] * position
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com = com / total_mass
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return com
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def center_of_mass_distance(molecule1, molecule2):
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com1 = center_of_mass(molecule1)
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com2 = center_of_mass(molecule2)
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dx = com1[0] - com2[0]
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dy = com1[1] - com2[1]
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dz = com1[2] - com2[2]
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distance = math.sqrt(dx**2 + dy**2 + dz**2)
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return distance
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def center_of_mass_to_origin(molecule):
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com = center_of_mass(molecule)
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for atom in molecule:
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atom['rx'] -= com[0]
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atom['ry'] -= com[1]
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atom['rz'] -= com[2]
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return
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def charges_and_dipole(molecule):
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eA_to_Debye = 1/0.20819434
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charge = 0
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dipole = np.zeros(3)
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for atom in molecule:
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position = np.array([ atom['rx'], atom['ry'], atom['rz'] ])
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dipole += atom['chg'] * position
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charge += atom['chg']
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dipole *= eA_to_Debye
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total_dipole = math.sqrt(dipole[0]**2 + dipole[1]**2 + dipole[2]**2)
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return [charge, dipole[0], dipole[1], dipole[2], total_dipole]
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def distances_between_atoms(molecule):
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distances = []
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dim = len(molecule)
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for atom1 in molecule:
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if atom1['na'] != ghost_number:
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for atom2 in molecule:
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if atom2['na'] != ghost_number:
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dx = atom1['rx'] - atom2['rx']
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dy = atom1['ry'] - atom2['ry']
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dz = atom1['rz'] - atom2['rz']
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distances.append(math.sqrt(dx**2 + dy**2 + dz**2))
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return np.array(distances).reshape(dim, dim)
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def eixos(molecule):
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eixos = np.zeros(3)
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if len(molecule) == 2:
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position1 = np.array([ molecule[0]['rx'], molecule[0]['ry'], molecule[0]['rz'] ])
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position2 = np.array([ molecule[1]['rx'], molecule[1]['ry'], molecule[1]['rz'] ])
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eixos = position2 - position1
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eixos /= linalg.norm(eixos)
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elif len(molecule) > 2:
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position1 = np.array([ molecule[0]['rx'], molecule[0]['ry'], molecule[0]['rz'] ])
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position2 = np.array([ molecule[1]['rx'], molecule[1]['ry'], molecule[1]['rz'] ])
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position3 = np.array([ molecule[2]['rx'], molecule[2]['ry'], molecule[2]['rz'] ])
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v1 = position2 - position1
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v2 = position3 - position1
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v3 = np.cross(v1, v2)
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v2 = np.cross(v1, v3)
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v1 /= linalg.norm(v1)
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v2 /= linalg.norm(v2)
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v3 /= linalg.norm(v3)
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eixos = np.array([[v1[0], v1[1], v1[2]],
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[v2[0], v2[1], v2[2]],
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[v3[0], v3[1], v3[2]]])
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return eixos
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def inertia_tensor(molecule):
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com = center_of_mass(molecule)
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Ixx = Ixy = Ixz = Iyy = Iyz = Izz = 0.0
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for atom in molecule:
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#### Obtain the displacement from the center of mass
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dx = atom['rx'] - com[0]
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dy = atom['ry'] - com[1]
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dz = atom['rz'] - com[2]
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#### Update the diagonal components of the tensor
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Ixx += atom['mass'] * (dy**2 + dz**2)
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Iyy += atom['mass'] * (dz**2 + dx**2)
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Izz += atom['mass'] * (dx**2 + dy**2)
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#### Update the off-diagonal components of the tensor
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Ixy += atom['mass'] * dx * dy * -1
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Ixz += atom['mass'] * dx * dz * -1
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Iyz += atom['mass'] * dy * dz * -1
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return np.array([[Ixx, Ixy, Ixz],
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[Ixy, Iyy, Iyz],
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[Ixz, Iyz, Izz]])
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def minimum_distance(molecule1, molecule2):
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distances = []
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for atom1 in molecule1:
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if atom1['na'] != ghost_number:
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for atom2 in molecule2:
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if atom2['na'] != ghost_number:
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dx = atom1['rx'] - atom2['rx']
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dy = atom1['ry'] - atom2['ry']
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dz = atom1['rz'] - atom2['rz']
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distances.append(math.sqrt(dx**2 + dy**2 + dz**2))
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return min(distances)
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def nearest_image(refmol, molecule, lx, ly, lz, criterium="com"):
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if criterium != "com" and criterium != "min":
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sys.exit("Error in value passed to function nearest_image")
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min_dist = 1e20
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for i in range(-1, 2):
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for j in range(-1, 2):
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for k in range(-1, 2):
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tr_vector = [i * lx, j * ly, k * lz]
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new_molecule = translate(molecule, tr_vector)
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if criterium == "com":
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dist = center_of_mass_distance(refmol, new_molecule)
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else:
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dist = minimum_distance(refmol, new_molecule)
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if dist < min_dist:
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min_dist = dist
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nearestmol = deepcopy(new_molecule)
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return min_dist, nearestmol
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def calculate_step(gradient, hessian, fh):
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invhessian = linalg.inv(hessian)
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pre_step = -1 * np.matmul(invhessian, gradient.T).T
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maxstep = np.amax(np.absolute(pre_step))
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factor = min(1, player['maxstep']/maxstep)
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step = factor * pre_step
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fh.write("\nCalculated step:\n")
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pre_step_list = pre_step.tolist()
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fh.write("-----------------------------------------------------------------------\n"
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"Center Atomic Step (Bohr)\n"
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"Number Number X Y Z\n"
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"-----------------------------------------------------------------------\n")
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for i in range(len(molecules[0])):
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fh.write(" {:>5d} {:>3d} {:>14.9f} {:>14.9f} {:>14.9f}\n".format(
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i + 1, molecules[0][i]['na'],
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pre_step_list.pop(0), pre_step_list.pop(0), pre_step_list.pop(0)))
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fh.write("-----------------------------------------------------------------------\n")
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fh.write("Maximum step is {:>11.6}\n".format(maxstep))
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fh.write("Scaling factor = {:>6.4f}\n".format(factor))
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fh.write("\nFinal step (Bohr):\n")
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step_list = step.tolist()
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fh.write("-----------------------------------------------------------------------\n"
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"Center Atomic Step (Bohr)\n"
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"Number Number X Y Z\n"
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"-----------------------------------------------------------------------\n")
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for i in range(len(molecules[0])):
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fh.write(" {:>5d} {:>3d} {:>14.9f} {:>14.9f} {:>14.9f}\n".format(
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i + 1, molecules[0][i]['na'],
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step_list.pop(0), step_list.pop(0), step_list.pop(0)))
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fh.write("-----------------------------------------------------------------------\n")
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step_max = np.amax(np.absolute(step))
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step_rms = np.sqrt(np.mean(np.square(step)))
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fh.write(" Max Step = {:>14.9f} RMS Step = {:>14.9f}\n\n".format(
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step_max, step_rms))
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return step
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def read_position(molecule):
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position_list = []
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for atom in molecule:
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position_list.extend([ atom['rx'], atom['ry'], atom['rz'] ])
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position = np.array(position_list)
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position *= ang2bohr
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return position
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def update_molecule(position, fh):
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position_in_ang = (position * bohr2ang).tolist()
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new_molecule = deepcopy(molecules[0])
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for atom in new_molecule:
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atom['rx'] = position_in_ang.pop(0)
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atom['ry'] = position_in_ang.pop(0)
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atom['rz'] = position_in_ang.pop(0)
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rmsd, molecules[0] = rmsd_fit(new_molecule, molecules[0])
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fh.write("\nProjected new conformation of reference molecule with RMSD fit\n")
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fh.write("RMSD = {:>8.5f} Angstrom\n".format(rmsd))
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return
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def update_hessian(step, cur_gradient, old_gradient, hessian): ## According to the BFGS
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dif_gradient = cur_gradient - old_gradient
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mat1 = 1/np.dot(dif_gradient, step) * np.matmul(dif_gradient.T, dif_gradient)
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mat2 = 1/np.dot(step, np.matmul(hessian, step.T).T)
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mat2 *= np.matmul( np.matmul(hessian, step.T), np.matmul(step, hessian) )
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hessian += mat1 - mat2
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return hessian
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def populate_asec_vdw(cycle, fh):
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asec_charges = [] # (rx, ry, rz, chg)
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vdw_meanfield = [] # (rx, ry, rz, eps, sig)
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if dice['nstep'][-1] % dice['isave'] == 0:
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nconfigs = round(dice['nstep'][-1] / dice['isave'])
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else:
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nconfigs = int(dice['nstep'][-1] / dice['isave'])
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norm_factor = nconfigs * player['nprocs']
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nsitesref = len(molecules[0]) + len(ghost_atoms) + len(lp_atoms)
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nsites_total = dice['nmol'][0] * nsitesref
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for i in range(1, len(dice['nmol'])):
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nsites_total += dice['nmol'][i] * len(molecules[i])
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thickness = []
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picked_mols = []
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for proc in range(1, player['nprocs'] + 1): ## Run over folders
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path = "step{:02d}".format(cycle) + os.sep + "p{:02d}".format(proc)
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file = path + os.sep + dice['outname'] + ".xyz"
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if not os.path.isfile(file):
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sys.exit("Error: cannot find file {}".format(file))
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try:
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with open(file) as xyzfh:
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xyzfile = xyzfh.readlines()
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except:
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sys.exit("Error: cannot open file {}".format(file))
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for config in range(nconfigs): ## Run over configs in a folder
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if int( xyzfile.pop(0).split()[0] ) != nsites_total:
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sys.exit("Error: wrong number of sites in file {}".format(file))
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box = xyzfile.pop(0).split()[-3:]
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box = [ float(box[0]), float(box[1]), float(box[2]) ]
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sizes = sizes_of_molecule(molecules[0])
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thickness.append( min([ (box[0] - sizes[0])/2, (box[1] - sizes[1])/2,
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(box[2] - sizes[2])/2 ]) )
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xyzfile = xyzfile[nsitesref:] ## Skip the first (reference) molecule
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mol_count = 0
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for type in range(len(dice['nmol'])): ## Run over types of molecules
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if type == 0:
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nmols = dice['nmol'][0] - 1
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else:
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nmols = dice['nmol'][type]
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for mol in range(nmols): ## Run over molecules of each type
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new_molecule = []
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for site in range(len(molecules[type])): ## Run over sites of each molecule
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new_molecule.append({})
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line = xyzfile.pop(0).split()
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if line[0].title() != atomsymb[molecules[type][site]['na']].strip():
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sys.exit("Error reading file {}".format(file))
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new_molecule[site]['na'] = molecules[type][site]['na']
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new_molecule[site]['rx'] = float(line[1])
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new_molecule[site]['ry'] = float(line[2])
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new_molecule[site]['rz'] = float(line[3])
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new_molecule[site]['chg'] = molecules[type][site]['chg']
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new_molecule[site]['eps'] = molecules[type][site]['eps']
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new_molecule[site]['sig'] = molecules[type][site]['sig']
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dist = minimum_distance(molecules[0], new_molecule)
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if dist < thickness[-1]:
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mol_count += 1
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for atom in new_molecule:
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asec_charges.append({})
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vdw_meanfield.append({})
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asec_charges[-1]['rx'] = atom['rx']
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asec_charges[-1]['ry'] = atom['ry']
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asec_charges[-1]['rz'] = atom['rz']
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asec_charges[-1]['chg'] = atom['chg'] / norm_factor
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if player['vdwforces'] == "yes":
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vdw_meanfield[-1]['rx'] = atom['rx']
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vdw_meanfield[-1]['ry'] = atom['ry']
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vdw_meanfield[-1]['rz'] = atom['rz']
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vdw_meanfield[-1]['eps'] = atom['eps']
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vdw_meanfield[-1]['sig'] = atom['sig']
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#### Read lines with ghosts or lps in molecules of type 0 (reference)
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#### and, if dist < thickness, appends to asec
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if type == 0:
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for ghost in ghost_atoms:
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line = xyzfile.pop(0).split()
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if line[0] != dice_ghost_label:
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sys.exit("Error reading file {}".format(file))
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if dist < thickness[-1]:
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asec_charges.append({})
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asec_charges[-1]['rx'] = float(line[1])
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asec_charges[-1]['ry'] = float(line[2])
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asec_charges[-1]['rz'] = float(line[3])
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asec_charges[-1]['chg'] = ghost['chg'] / norm_factor
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for lp in lp_atoms:
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line = xyzfile.pop(0).split()
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if line[0] != dice_ghost_label:
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sys.exit("Error reading file {}".format(file))
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if dist < thickness[-1]:
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asec_charges.append({})
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asec_charges[-1]['rx'] = float(line[1])
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asec_charges[-1]['ry'] = float(line[2])
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asec_charges[-1]['rz'] = float(line[3])
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asec_charges[-1]['chg'] = lp['chg'] / norm_factor
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picked_mols.append(mol_count)
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fh.write("Done\n")
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string = "In average, {:^7.2f} molecules ".format(sum(picked_mols)/norm_factor)
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string += "were selected from each of the {} configurations ".format(len(picked_mols))
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string += "of the production simulations to form the ASEC, comprising a shell with "
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string += "minimum thickness of {:>6.2f} Angstrom\n".format(sum(thickness)/norm_factor)
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fh.write(textwrap.fill(string, 86))
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fh.write("\n")
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otherfh = open("ASEC.dat", "w")
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for charge in asec_charges:
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otherfh.write("{:>10.5f} {:>10.5f} {:>10.5f} {:>11.8f}\n".format(
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charge['rx'], charge['ry'], charge['rz'], charge['chg']))
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otherfh.close()
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return asec_charges
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def principal_axes(inertia_tensor):
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try:
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evals, evecs = linalg.eigh(inertia_tensor)
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except:
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sys.exit("Error: diagonalization of inertia tensor did not converge")
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return evals, evecs
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def print_geom(cycle, fh):
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fh.write("{}\n".format(len(molecules[0])))
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fh.write("Cycle # {}\n".format(cycle))
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for atom in molecules[0]:
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symbol = atomsymb[atom['na']]
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fh.write("{:<2s} {:>10.6f} {:>10.6f} {:>10.6f}\n".format(symbol,
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atom['rx'], atom['ry'], atom['rz']))
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return
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def print_mol_info(molecule, fh):
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com = center_of_mass(molecule)
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fh.write(" Center of mass = ( {:>10.4f} , {:>10.4f} , {:>10.4f} )\n".format(com[0],
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com[1], com[2]))
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inertia = inertia_tensor(molecule)
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evals, evecs = principal_axes(inertia)
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fh.write(" Moments of inertia = {:>9E} {:>9E} {:>9E}\n".format(evals[0],
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evals[1], evals[2]))
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fh.write(" Major principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
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evecs[0,0], evecs[1,0], evecs[2,0]))
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fh.write(" Inter principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
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evecs[0,1], evecs[1,1], evecs[2,1]))
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fh.write(" Minor principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
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evecs[0,2], evecs[1,2], evecs[2,2]))
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sizes = sizes_of_molecule(molecule)
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fh.write(" Characteristic lengths = ( {:>6.2f} , {:>6.2f} , {:>6.2f} )\n".format(
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sizes[0], sizes[1], sizes[2]))
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mol_mass = total_mass(molecule)
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fh.write(" Total mass = {:>8.2f} au\n".format(mol_mass))
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chg_dip = charges_and_dipole(molecule)
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fh.write(" Total charge = {:>8.4f} e\n".format(chg_dip[0]))
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fh.write(" Dipole moment = ( {:>9.4f} , {:>9.4f} , {:>9.4f} ) Total = {:>9.4f} Debye\n\n".format(
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chg_dip[1], chg_dip[2], chg_dip[3], chg_dip[4]))
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return
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def sizes_of_molecule(molecule):
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x_list = []
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y_list = []
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z_list = []
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for atom in molecule:
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if atom['na'] != ghost_number:
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x_list.append(atom['rx'])
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|
y_list.append(atom['ry'])
|
|
z_list.append(atom['rz'])
|
|
|
|
x_max = max(x_list)
|
|
x_min = min(x_list)
|
|
y_max = max(y_list)
|
|
y_min = min(y_list)
|
|
z_max = max(z_list)
|
|
z_min = min(z_list)
|
|
|
|
sizes = [x_max - x_min, y_max - y_min, z_max - z_min]
|
|
|
|
return sizes
|
|
|
|
|
|
|
|
def standard_orientation(molecule):
|
|
|
|
center_of_mass_to_origin(molecule)
|
|
tensor = inertia_tensor(molecule)
|
|
evals, evecs = principal_axes(tensor)
|
|
if round(linalg.det(evecs)) == -1:
|
|
evecs[0,2] *= -1
|
|
evecs[1,2] *= -1
|
|
evecs[2,2] *= -1
|
|
if round(linalg.det(evecs)) != 1:
|
|
sys.exit("Error: could not make a rotation matrix while adopting the standard orientation")
|
|
|
|
rot_matrix = evecs.T
|
|
for atom in molecule:
|
|
position = np.array([ atom['rx'], atom['ry'], atom['rz'] ])
|
|
new_position = np.matmul(rot_matrix, position.T).T
|
|
atom['rx'] = new_position[0]
|
|
atom['ry'] = new_position[1]
|
|
atom['rz'] = new_position[2]
|
|
|
|
return
|
|
|
|
|
|
|
|
def total_mass(molecule):
|
|
|
|
mass = 0
|
|
for atom in molecule:
|
|
mass += atom['mass']
|
|
|
|
return mass
|
|
|
|
|
|
|
|
def translate(molecule, vector):
|
|
|
|
new_molecule = deepcopy(molecule)
|
|
for atom in new_molecule:
|
|
atom['rx'] += vector[0]
|
|
atom['ry'] += vector[1]
|
|
atom['rz'] += vector[2]
|
|
|
|
return new_molecule
|
|
|
|
|
|
|
|
def rmsd_fit(projecting_mol, reference_mol):
|
|
|
|
if len(projecting_mol) != len(reference_mol):
|
|
sys.exit("Error in RMSD fit procedure: molecules have different number of atoms")
|
|
dim = len(projecting_mol)
|
|
|
|
new_projecting_mol = deepcopy(projecting_mol)
|
|
new_reference_mol = deepcopy(reference_mol)
|
|
|
|
center_of_mass_to_origin(new_projecting_mol)
|
|
center_of_mass_to_origin(new_reference_mol)
|
|
|
|
x = []
|
|
y = []
|
|
|
|
for atom in new_projecting_mol:
|
|
x.extend([ atom['rx'], atom['ry'], atom['rz'] ])
|
|
|
|
for atom in new_reference_mol:
|
|
y.extend([ atom['rx'], atom['ry'], atom['rz'] ])
|
|
|
|
x = np.array(x).reshape(dim, 3)
|
|
y = np.array(y).reshape(dim, 3)
|
|
|
|
r = np.matmul(y.T, x)
|
|
rr = np.matmul(r.T, r)
|
|
|
|
try:
|
|
evals, evecs = linalg.eigh(rr)
|
|
except:
|
|
sys.exit("Error: diagonalization of RR matrix did not converge")
|
|
|
|
a1 = evecs[:,2].T
|
|
a2 = evecs[:,1].T
|
|
a3 = np.cross(a1, a2)
|
|
|
|
A = np.array([ a1[0], a1[1], a1[2], a2[0], a2[1], a2[2], a3[0], a3[1], a3[2] ])
|
|
A = A.reshape(3,3)
|
|
|
|
b1 = np.matmul(r, a1.T).T # or np.dot(r, a1)
|
|
b1 /= linalg.norm(b1)
|
|
b2 = np.matmul(r, a2.T).T # or np.dot(r, a2)
|
|
b2 /= linalg.norm(b2)
|
|
b3 = np.cross(b1, b2)
|
|
|
|
B = np.array([ b1[0], b1[1], b1[2], b2[0], b2[1], b2[2], b3[0], b3[1], b3[2] ])
|
|
B = B.reshape(3,3).T
|
|
|
|
rot_matrix = np.matmul(B, A)
|
|
x = np.matmul(rot_matrix, x.T).T
|
|
|
|
rmsd = 0
|
|
for i in range(dim):
|
|
rmsd += (x[i,0] - y[i,0])**2 + (x[i,1] - y[i,1])**2 + (x[i,2] - y[i,2])**2
|
|
rmsd = math.sqrt(rmsd/dim)
|
|
|
|
for i in range(dim):
|
|
new_projecting_mol[i]['rx'] = x[i,0]
|
|
new_projecting_mol[i]['ry'] = x[i,1]
|
|
new_projecting_mol[i]['rz'] = x[i,2]
|
|
|
|
tr_vector = center_of_mass(reference_mol)
|
|
projected_mol = translate(new_projecting_mol, tr_vector)
|
|
|
|
return rmsd, projected_mol
|
|
|
|
|
|
|