MolHandling Translation - Most

In this commit most of the work about Molecules and the Quantum Mechanical System has been finished, the only part still missing if a method that populates de ASSEC, but this method requires the Classes: Dice, Player and Gaussian

Signed-off-by: Vitor Hideyoshi <vitor.h.n.batista@gmail.com>
This commit is contained in:
2021-07-12 16:00:09 -03:00
committed by Vitor Hideyoshi
parent 6768012cc0
commit ec08e05614
2 changed files with 345 additions and 146 deletions

View File

@@ -53,6 +53,133 @@ class System:
return min(distances)
def rmsd_fit(self, index_p, index_r):
projecting_mol = self.molecule[index_p]
reference_mol = self.molecule[index_r]
if len(projecting_mol.atom) != len(reference_mol.atom):
sys.exit("Error in RMSD fit procedure: molecules have different number of atoms")
dim = len(projecting_mol.atom)
new_projecting_mol = deepcopy(projecting_mol)
new_reference_mol = deepcopy(reference_mol)
new_projecting_mol.center_of_mass_to_origin()
new_reference_mol.center_of_mass_to_origin()
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.atom[i].rx = x[i,0]
new_projecting_mol.atom[i].ry = x[i,1]
new_projecting_mol.atom[i].rz = x[i,2]
tr_vector = reference_mol.center_of_mass()
projected_mol = new_projecting_mol.translate(tr_vector)
return rmsd, projected_mol
def update_molecule(self, position, fh):
position_in_ang = (position * bohr2ang).tolist()
self.add_molecule(deepcopy(self.molecule[0]))
for atom in self.molecule[-1].atom:
atom.rx = position_in_ang.pop(0)
atom.ry = position_in_ang.pop(0)
atom.rz = position_in_ang.pop(0)
rmsd, self.molecule[0] = self.rmsd_fit(-1, 0)
self.molecule.pop(-1)
fh.write("\nProjected new conformation of reference molecule with RMSD fit\n")
fh.write("RMSD = {:>8.5f} Angstrom\n".format(rmsd))
def nearest_image(self, index_r, index_m, lx, ly, lz, criterium=None):
if criterium in None:
criterium = "com"
if criterium != "com" and criterium != "min":
sys.exit("Error in value passed to function nearest_image")
min_dist = 1e20
for i in range(-1, 2):
for j in range(-1, 2):
for k in range(-1, 2):
tr_vector = [i * lx, j * ly, k * lz]
self.add_molecule(self.molecule[index_m].translate(tr_vector))
if criterium == "com":
dist = self.center_of_mass_distance(index_r, -1)
else:
dist = self.minimum_distance(index_r, -1)
if dist < min_dist:
min_dist = dist
nearestmol = deepcopy(self.molecule[-1])
self.molecule.pop(-1)
return min_dist, nearestmol
def print_geom(self, cycle, fh):
fh.write("{}\n".format(len(self.molecule[0])))
fh.write("Cycle # {}\n".format(cycle))
for atom in self.molecule[0].atoms:
symbol = atomsymb[atom.na]
fh.write("{:<2s} {:>10.6f} {:>10.6f} {:>10.6f}\n".format(symbol,
atom.rx, atom.ry, atom.rz))
# Classe que conterá toda informação e funções relacionadas a uma unica molecula
class Molecule:
@@ -262,6 +389,81 @@ class Molecule:
return new_molecule
def print_mol_info(self, fh):
com = self.center_of_mass()
fh.write(" Center of mass = ( {:>10.4f} , {:>10.4f} , {:>10.4f} )\n".format(com[0],
com[1], com[2]))
inertia = self.inertia_tensor()
evals, evecs = self.principal_axes()
fh.write(" Moments of inertia = {:>9E} {:>9E} {:>9E}\n".format(evals[0],
evals[1], evals[2]))
fh.write(" Major principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
evecs[0,0], evecs[1,0], evecs[2,0]))
fh.write(" Inter principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
evecs[0,1], evecs[1,1], evecs[2,1]))
fh.write(" Minor principal axis = ( {:>10.6f} , {:>10.6f} , {:>10.6f} )\n".format(
evecs[0,2], evecs[1,2], evecs[2,2]))
sizes = self.sizes_of_molecule()
fh.write(" Characteristic lengths = ( {:>6.2f} , {:>6.2f} , {:>6.2f} )\n".format(
sizes[0], sizes[1], sizes[2]))
mol_mass = self.total_mass()
fh.write(" Total mass = {:>8.2f} au\n".format(mol_mass))
chg_dip = self.charges_and_dipole()
fh.write(" Total charge = {:>8.4f} e\n".format(chg_dip[0]))
fh.write(" Dipole moment = ( {:>9.4f} , {:>9.4f} , {:>9.4f} ) Total = {:>9.4f} Debye\n\n".format(
chg_dip[1], chg_dip[2], chg_dip[3], chg_dip[4]))
def calculate_step(self, fh):
invhessian = linalg.inv(self.hessian)
pre_step = -1 * np.matmul(invhessian, self.gradient.T).T
maxstep = np.amax(np.absolute(pre_step))
factor = min(1, player['maxstep']/maxstep)
step = factor * pre_step
fh.write("\nCalculated step:\n")
pre_step_list = pre_step.tolist()
fh.write("-----------------------------------------------------------------------\n"
"Center Atomic Step (Bohr)\n"
"Number Number X Y Z\n"
"-----------------------------------------------------------------------\n")
for i in range(len(molecules[0])):
fh.write(" {:>5d} {:>3d} {:>14.9f} {:>14.9f} {:>14.9f}\n".format(
i + 1, molecules[0][i]['na'],
pre_step_list.pop(0), pre_step_list.pop(0), pre_step_list.pop(0)))
fh.write("-----------------------------------------------------------------------\n")
fh.write("Maximum step is {:>11.6}\n".format(maxstep))
fh.write("Scaling factor = {:>6.4f}\n".format(factor))
fh.write("\nFinal step (Bohr):\n")
step_list = step.tolist()
fh.write("-----------------------------------------------------------------------\n"
"Center Atomic Step (Bohr)\n"
"Number Number X Y Z\n"
"-----------------------------------------------------------------------\n")
for i in range(len(molecules[0])):
fh.write(" {:>5d} {:>3d} {:>14.9f} {:>14.9f} {:>14.9f}\n".format(
i + 1, molecules[0][i]['na'],
step_list.pop(0), step_list.pop(0), step_list.pop(0)))
fh.write("-----------------------------------------------------------------------\n")
step_max = np.amax(np.absolute(step))
step_rms = np.sqrt(np.mean(np.square(step)))
fh.write(" Max Step = {:>14.9f} RMS Step = {:>14.9f}\n\n".format(
step_max, step_rms))
return step
class Atom:
def __init__(self, lbl,na,rx,ry,rz,chg,eps,sig):