MonteCarlo simulation¶

Prepare the simulation¶

Calculation method¶

The calculation method define the software to use to calculate the atomic interactions. Two software are implemented: Gaussian09 and Tinker. To use these calculators, Gaussian and/or Tinker should be installed in your system and the binaries (or hard links to them) should be placed in a directory included in the $PATH environment variable with the name g09 and tinker, respectively. Note that setting up an alias in .profile or .bashrc for these software will not work.

Gaussian 09

from montecarlo.functions.method import gaussian
calculator = gaussian(methodology='pm6' [String],
                      internal=False [Boolean],
                      processors=None [Integer])

methodology: Method label to use in Gaussian09. This argument should contain the basis set if it is necessary (Ex: B3LYP/6-31G).
Internal: Use internal coordinates (z-matrix).
Set number of processors to use in the :program:Gaussian09` calculation.

Tinker

from montecarlo.functions.method import tinker
calculator = tinker(parameter_set='mm3.prm' [String]):

parameter_set: name of the force field file to use. This file should be placed in the work directory or full path should be specified

Conditions¶

Conditions object contains the parameters of the Monte Carlo simulation

from montecarlo.classes.results import Conditions
conditions = Conditions(temperature=None [Float],
                        number_of_cycles=100000 [Integer],
                        kb=0.0019872041, # kcal/mol
                        initial_expansion_factor=0.05 [Float],
                        acceptation_regulator=1.0 [Float],
                        number_of_values_for_average=2000 [Integer],
                        energy_method=calculator [Method object])

temperature: Temperature at which the MonteCarlo simulation is calcuculated.
number_of_cycles: Number of simulation steps
energy_method: Calculation method object
initial_expansion_factor: Initial factor of acceptance
acceptation_regulator: Ratio of alteration of the factor of acceptance as a function of acceptance.
number_of_values_for_average: Number of last simulation steps used to calculate the averaged properties.
kb: Boltzmann constant according to the units of energy and temperature

Run the simulation¶

Montecarlo object contains all the information concerting to the simulation. This object is generated from a structure object tha contains the initial structure

from montecarlo.classes.results import MonteCarlo
simulation = MonteCarlo(structure)

To Run the simulation the calculate_MonteCarlo() is used. This function returns a MonteCarlo object that contains the results

from montecarlo.functions.montecarlo import calculate_MonteCarlo
simulation = calculate_MonteCarlo(simulation [Montecarlo type],
                                  conditions [Conditions type],
                                  show_text=True [Boolean],
                                  alteration_type='cartesian' [String])
  Return result [Montecarlo type]

simulation: Initial Montecarlo object. If this object already contains information of a previous simulation, the simulation will continue adding the data of the new simulation.
conditions: Conditions object.
show_text: If True writes montecarlo information on screen during the simulation calculation. If False the calculation is carried out silently.
alteration_type: Defines the way the structures are altered during each simulation step. The possible options are ‘cartesian’ ‘internal’ or ‘modes’.

The returned Montecarlo object can be used again in the calculate_MonteCarlo() function to continue the simulation.

Save results to data files¶

To save the MonteCarlo data into files some helper functions are available in

montemodes.functions.reading

Save the energy, acceptation of each simulation

write_result_to_file(result, 'test.out')

Save the trajectory into a file in xyz format

write_result_trajectory(result.trajectory, 'trajectory.xyz')

Save the full simulation objects into a file

save_to_dump(conditions, result, filename='full.obj')

Load the simulation objects from a file

load_from_dump(filename='full.obj')

Example¶

import montemodes.functions.reading as io_monte
import montemodes.functions.montecarlo as monte
import montemodes.functions.methods as method
import montemodes.classes.results as res


gaussian_calc = method.gaussian(methodology='pm6',
                                internal=False)

conditions = res.Conditions(temperature=500,
                            number_of_cycles=1000,
                            initial_expansion_factor=0.05,
                            acceptation_regulator=0.1,
                            number_of_values_for_average=20,
                            energy_method=gaussian_calc)

initial_structure = io_monte.reading_from_xyz_file('molecule.xyz')
initial_structure.charge = 0
initial_structure.multiplicity = 1

simulation = res.MonteCarlo(initial_structure)

result = monte.calculate_MonteCarlo(simulation,
                                    conditions,
                                    show_text=True,
                                    alteration_type='cartesian')

io_monte.write_result_to_file(result, 'montecarlo.out')
io_monte.write_result_trajectory(result.trajectory, 'trajectory.xyz')