brownian_statistics.py

## \example atom/brownian_statistics.py
# This example prints out various statistics about a prospective Brownian
# dynamics simulation. You can use the statistics to determine if the time
# step is likely to be sufficiently short given the forces and particle
# sizes involved.

from __future__ import print_function
import IMP.atom
import sys

IMP.setup_from_argv(sys.argv, "brownian statistics")

# fs
time_step = 1000
# angstrom
minimum_particle_radius = 10
# kCal/mol/A
maximum_spring_constant = 1

maximum_diffusion_coefficient =\
    IMP.atom.get_einstein_diffusion_coefficient(minimum_particle_radius)
expected_delta = IMP.atom.get_diffusion_length(maximum_diffusion_coefficient,
                                               time_step)

expected_rotational_delta =\
    IMP.atom.get_diffusion_angle(maximum_diffusion_coefficient,
                                 time_step) * minimum_particle_radius

expected_spring_diffusion_length =\
    IMP.atom.get_diffusion_length(maximum_diffusion_coefficient,
                                  .5 * maximum_spring_constant *
                                  4 * expected_delta ** 2, time_step)

print("with a time step of", time_step, "fs")
print("an object of radius", minimum_particle_radius, "A will move",
      expected_delta, "A and a point on its surface will move",
      expected_rotational_delta, "A more")
print("the motion from fluctuations in the spring compression will be",
      expected_spring_diffusion_length, "A")
print("and a compression of 10% of the radius will induce a motion of",
      IMP.atom.get_diffusion_length(maximum_diffusion_coefficient,
                                    .5 * maximum_spring_constant *
                                    (.1 * minimum_particle_radius) ** 2,
                                    time_step), "A")