MolHandling Translation

In this commit were created a System class to manage the functions between two atoms and various new functions were translated

Signed-off-by: Vitor Hideyoshi <vitor.h.n.batista@gmail.com>
This commit is contained in:
2021-07-09 10:55:05 -03:00
committed by Vitor Hideyoshi
parent 292995d0ea
commit 6768012cc0
2 changed files with 400 additions and 172 deletions

View File

@@ -1,31 +1,83 @@
from DPpack.MolHandling import total_mass
import os, sys
import math
import shutil
import textwrap
import numpy as np
import sys, math
from copy import deepcopy
import numpy as np
from numpy import linalg
from DPpack.PTable import *
from DPpack.Misc import *
from DPpack.PTable import *
from DPpack.SetGlobals import *
# Usaremos uma nova classe que ira conter toda interação entre moleculas
class System:
def __init__(self):
self.molecule = []
def add_molecule(self, m):
self.molecule.append(m)
# Função que calcula a distância entre dois centros de massa
# e por se tratar de uma função de dois atomos não deve ser
# inserida dentro de Molecule
def center_of_mass_distance(self, a, b):
com1 = self.molecule[a].center_of_mass()
com2 = self.molecule[b].center_of_mass()
dx = com1[0] - com2[0]
dy = com1[1] - com2[1]
dz = com1[2] - com2[2]
distance = math.sqrt(dx**2 + dy**2 + dz**2)
return distance
def minimum_distance(self, index1, index2):
distances = []
for atom1 in self.molecule[index1]:
if atom1.na != ghost_number:
for atom2 in self.molecule[index2]:
if atom2.na != ghost_number:
dx = atom1.rx - atom2.rx
dy = atom1.ry - atom2.ry
dz = atom1.rz - atom2.rz
distances.append(math.sqrt(dx**2 + dy**2 + dz**2))
return min(distances)
# Classe que conterá toda informação e funções relacionadas a uma unica molecula
class Molecule:
def __init__(self):
self.atoms = [] # Lista de instancias de Atom
self.positions = None # Array Numpy
self.atom = [] # Lista de instancias de Atom
self.position = None # Array Numpy
self.energy = None # Array Numpy
self.gradient = None # Array Numpy
self.hessian = None # Array Numpy
self.total_mass = 0
def add_atom(self, a):
self.atoms.append(a) # Inserção de um novo atomo
self.atom.append(a) # Inserção de um novo atomo
self.total_mass += a.mass
def center_of_mass(self):
com = np.zeros(3)
total_mass = 0.0
for atom in self.atoms:
for atom in self.atom:
total_mass += atom.mass
com += atom.mass * np.array([atom.rx, atom.ry, atom.rz])
@@ -33,6 +85,182 @@ class Molecule:
return com
def center_of_mass_to_origin(self):
com = self.center_of_mass()
for atom in self.atom:
atom.rx -= com[0]
atom.ry -= com[1]
atom.rz -= com[2]
def charges_and_dipole(self):
eA_to_Debye = 1/0.20819434
charge = 0
dipole = np.zeros(3)
for atom in self.atom:
position = np.array([ atom.rx, atom.ry, atom.rz ])
dipole += atom.chg * position
charge += atom.chg
dipole *= eA_to_Debye
total_dipole = math.sqrt(dipole[0]**2 + dipole[1]**2 + dipole[2]**2)
return [charge, dipole[0], dipole[1], dipole[2], total_dipole]
def distances_between_atoms(self):
distances = []
dim = len(self.atom)
for atom1 in self.atom:
if atom1.na != ghost_number:
for atom2 in self.atom:
if atom2.na != ghost_number:
dx = atom1.rx - atom2.rx
dy = atom1.ry - atom2.ry
dz = atom1.rz - atom2.rz
distances.append(math.sqrt(dx**2 + dy**2 + dz**2))
return np.array(distances).reshape(dim, dim)
def eixos(self):
eixos = np.zeros(3)
if len(self.atom) == 2:
position1 = np.array([ self.atom[0].rx, self.atom[0].ry, self.atom[0].rz ])
position2 = np.array([ self.atom[1].rx, self.atom[1].ry, self.atom[1].rz ])
eixos = position2 - position1
eixos /= linalg.norm(eixos)
elif len(self.atom) > 2:
position1 = np.array([ self.atom[0].rx, self.atom[0].ry, self.atom[0].rz ])
position2 = np.array([ self.atom[1].rx, self.atom[1].ry, self.atom[1].rz ])
position3 = np.array([ self.atom[2].rx, self.atom[2].ry, self.atom[2].rz ])
v1 = position2 - position1
v2 = position3 - position1
v3 = np.cross(v1, v2)
v2 = np.cross(v1, v3)
v1 /= linalg.norm(v1)
v2 /= linalg.norm(v2)
v3 /= linalg.norm(v3)
eixos = np.array([[v1[0], v1[1], v1[2]],
[v2[0], v2[1], v2[2]],
[v3[0], v3[1], v3[2]]])
return eixos
def inertia_tensor(self):
com = self.center_of_mass()
Ixx = Ixy = Ixz = Iyy = Iyz = Izz = 0.0
for atom in self.atom:
#### Obtain the displacement from the center of mass
dx = atom.rx - com[0]
dy = atom.ry - com[1]
dz = atom.rz - com[2]
#### Update the diagonal components of the tensor
Ixx += atom.mass * (dy**2 + dz**2)
Iyy += atom.mass * (dz**2 + dx**2)
Izz += atom.mass * (dx**2 + dy**2)
#### Update the off-diagonal components of the tensor
Ixy += atom.mass * dx * dy * -1
Ixz += atom.mass * dx * dz * -1
Iyz += atom.mass * dy * dz * -1
return np.array([ [Ixx, Ixy, Ixz],
[Ixy, Iyy, Iyz],
[Ixz, Iyz, Izz] ])
def principal_axes(self):
try:
evals, evecs = linalg.eigh(self.inertia_tensor())
except:
sys.exit("Error: diagonalization of inertia tensor did not converge")
return evals, evecs
def read_position(self):
position_list = []
for atom in self.atom:
position_list.extend([ atom.rx, atom.ry, atom.rz ])
position = np.array(position_list)
position *= ang2bohr
return position
def update_hessian(self, step, cur_gradient): ## According to the BFGS
dif_gradient = cur_gradient - self.gradient
mat1 = 1/np.dot(dif_gradient, step) * np.matmul(dif_gradient.T, dif_gradient)
mat2 = 1/np.dot(step, np.matmul(self.hessian, step.T).T)
mat2 *= np.matmul( np.matmul(self.hessian, step.T), np.matmul(step, hessian) )
self.hessian += mat1 - mat2
def sizes_of_molecule(self):
x_list = []
y_list = []
z_list = []
for atom in self.atom:
if atom.na != ghost_number:
x_list.append(atom.rx)
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(self):
self.center_of_mass_to_origin()
tensor = self.inertia_tensor()
evals, evecs = self.principal_axes()
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 self.atom:
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]
def translate(self, vector):
new_molecule = deepcopy(self)
for atom in new_molecule.atom:
atom.rx += vector[0]
atom.ry += vector[1]
atom.rz += vector[2]
return new_molecule
class Atom: