Initial Translation of SetGlobals

Initial work in the tradution of SetGlobals and Logistics in the use of classes for the management of processes and threaded works

Signed-off-by: Vitor Hideyoshi <vitor.h.n.batista@gmail.com>

DPpack/Molhandling.py

@@ -0,0 +1,480 @@
+from DPpack.MolHandling import total_mass
+import os, sys
+import math
+import shutil
+import textwrap
+import sys, math
+from copy import deepcopy
+
+import numpy as np
+from numpy import linalg
+
+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)
+
+	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:
+
+	def __init__(self):
+
+		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.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.atom:
+			
+			total_mass += atom.mass
+			com += atom.mass * np.array([atom.rx, atom.ry, atom.rz])
+		
+		com = com / total_mass
+		
+		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
+
+	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):
+		
+		self.lbl = lbl                  # Integer
+		self.na = na                    # Integer
+		self.rx = rx                    # Double
+		self.ry = ry                    # Double
+		self.rz = rz                    # Double
+		self.chg = chg                  # Double
+		self.eps = eps                  # Double
+		self.sig = sig                  # Double
+		self.mass = atommass[self.na]   # Double
+

DPpack/SetGlobalsClass.py

@@ -1,479 +1,94 @@
-from DPpack.MolHandling import total_mass
 import os, sys
-import math
 import shutil
 import textwrap
-import sys, math
-from copy import deepcopy
 
-import numpy as np
-from numpy import linalg
-
-from DPpack.Misc import *
 from DPpack.PTable import *
-from DPpack.SetGlobals import *
+from DPpack.Misc import *
 
-# Usaremos uma nova classe que ira conter toda interação entre moleculas
+class Internal:
-
-class System:
 
 	def __init__(self):
 
-		self.molecule = []
+		self.player = self.Player()
+		self.dice = self.Dice()
+		self.gaussian = self.Gaussian()
+		self.molca = self.Molca()
 
-	def add_molecule(self, m):
+		## Constanst that shall be set for global use
 
-		self.molecule.append(m)
+		self.tol_rms_force = 3e-4		# Hartree/Bohr
+		self.tol_max_force = 4.5e-4		# Hartree/Bohr
+		self.tol_rms_step = 1.2e-3		# Bohr
+		self.tol_max_step = 1.8e-3		# Bohr
+		self.trust_radius = None
 
-	# Função que calcula a distância entre dois centros de massa
+		## Dice:
-	# e por se tratar de uma função de dois atomos não deve ser
+		self.combrule = None
-	# inserida dentro de Molecule
+		self.randominit = None
-	def center_of_mass_distance(self, a, b):
 
-		com1 = self.molecule[a].center_of_mass()
+	class Player:
-		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)
-
-	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:
 
 		def __init__(self):
 
-		self.atom = []					# Lista de instancias de Atom
+			self.maxcyc = None
-		self.position = None			# Array Numpy
+			self.initcyc = 1
-		self.energy = None				# Array Numpy
+			self.nprocs = 1
-		self.gradient = None			# Array Numpy
+			self.switchcyc = 3
-		self.hessian = None				# Array Numpy
+			self.altsteps = 20000
-		self.total_mass = 0
+			self.maxstep = .3
+			self.qmprog = "g09"
+			self.opt = "yes"
+			self.freq = "no"
+			self.readhessian = "no"
+			self.lps = "no"
+			self.ghosts = "no"
+			self.vdwforces = "no"
+			self.tol_factor = 1.2
 		
-	def add_atom(self, a):
 
-		self.atom.append(a)			# Inserção de um novo atomo
-		self.total_mass += a.mass
 
-	def center_of_mass(self):
+	class Dice:
 
-		com = np.zeros(3)
+		def __init__(self):
-		total_mass = 0.0
 
-		for atom in self.atom:
+			self.title = "Diceplayer run"
+			self.progname = "dice"
+			self.temp = 300.0
+			self.press = 1.0
+			self.isave = 1000         # ASEC construction will take this into account
+			self.ncores = 1
 
-			total_mass += atom.mass
+			self.dens = None		# Investigate the possibility of using 'box = Lx Ly Lz' instead.
-			com += atom.mass * np.array([atom.rx, atom.ry, atom.rz])
+			#dice['box'] = None		# So 'geom' would be set by diceplayer and 'cutoff' would be
+									# switched off. One of them must be given.
+			self.ljname = None
+			self.outname = None
+			self.nmol = []     # Up to 4 integer values related to up to 4 molecule types
+			self.nstep = []    # 2 or 3 integer values related to 2 or 3 simulations
+								# (NVT th + NVT eq) or (NVT th + NPT th + NPT eq).
+								# This will control the 'nstep' keyword of Dice
 
-		com = com / total_mass
 
-		return com
+	class Gaussian:
 
-	def center_of_mass_to_origin(self):
+		def __init__(self):
 
-		com = self.center_of_mass()
+			self.mem = None
+			self.keywords = None
+			self.chgmult = [0, 1]
+			self.gmiddle = None   # In each case, if a filename is given, its content will be 
+			self.gbottom = None   # inserted in the gaussian input
+			self.pop = "chelpg"
+			self.chglevel = None
 
-		for atom in self.atom:
+			self.level = None
 
-			atom.rx -= com[0]
+	class Molcas:
-			atom.ry -= com[1]
-			atom.rz -= com[2]
 
-	def charges_and_dipole(self):
+		def __init(self):
 
-		eA_to_Debye = 1/0.20819434
+			self.orbfile = "input.exporb"
-		charge = 0
+			self.root = 1
-		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
+			self.mbottom = None
-		total_dipole = math.sqrt(dipole[0]**2 + dipole[1]**2 + dipole[2]**2)
+			self.basis = None
-		
-		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
-
-	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):
-		
-		self.lbl = lbl                  # Integer
-		self.na = na                    # Integer
-		self.rx = rx                    # Double
-		self.ry = ry                    # Double
-		self.rz = rz                    # Double
-		self.chg = chg                  # Double
-		self.eps = eps                  # Double
-		self.sig = sig                  # Double
-		self.mass = atommass[self.na]   # Double