def test_velocity_assignment(mpicomm=None, verbose=True):
"""
Test Maxwell-Boltzmann velocity assignment subtroutine produces correct distribution, raising an exception if this test fails.
"""
# Stop here if not root node.
if mpicomm and (mpicomm.rank != 0): return
if verbose: print "Testing Maxwell-Boltzmann velocity assignment: ",
# Make a list of all test system constructors.
import testsystems
# Test parameters
temperature = 298.0 * units.kelvin # test temperature
kT = kB * temperature # thermal energy
ntrials = 1000 # number of test trials
systems_to_test = ['HarmonicOscillator', 'HarmonicOscillatorArray', 'AlanineDipeptideImplicit'] # systems to test
for system_name in systems_to_test:
#print '*' * 80
#print system_name
# Create system.
constructor = getattr(testsystems, system_name)
[system, coordinates] = constructor()
# Create temporary filename.
import tempfile # use a temporary file for testing
file = tempfile.NamedTemporaryFile()
store_filename = file.name
# Create repex instance.
from repex import ReplicaExchange
from thermodynamics import ThermodynamicState
states = [ ThermodynamicState(system, temperature=temperature) ]
simulation = ReplicaExchange(states=states, coordinates=coordinates, store_filename=store_filename)
# Create integrator and context.
natoms = system.getNumParticles()
velocity_trials = numpy.zeros([ntrials, natoms, 3])
kinetic_energy_trials = numpy.zeros([ntrials])
for trial in range(ntrials):
velocities = simulation._assign_Maxwell_Boltzmann_velocities(system, temperature)
kinetic_energy = 0.5 * units.sum(units.sum(system.masses * velocities**2))
velocity_trials[trial,:,:] = velocities / (units.nanometers / units.picosecond)
kinetic_energy_trials[trial] = kinetic_energy / units.kilocalories_per_mole
velocity_mean = velocity_trials.mean(0)
velocity_stderr = velocity_trials.std(0) / numpy.sqrt(ntrials)
kinetic_analytical = (3.0/2.0) * natoms * kT / units.kilocalories_per_mole
kinetic_mean = kinetic_energy_trials.mean()
kinetic_error = kinetic_mean - kinetic_analytical
kinetic_stderr = kinetic_energy_trials.std() / numpy.sqrt(ntrials)
# Test if violations exceed tolerance.
MAX_SIGMA = 6.0 # maximum number of standard errors allowed
if numpy.any(numpy.abs(kinetic_error / kinetic_stderr) > MAX_SIGMA):
print "analytical kinetic energy"
print kinetic_analytical
print "mean kinetic energy (kcal/mol)"
print kinetic_mean
print "difference (kcal/mol)"
print kinetic_mean - kinetic_analytical
print "stderr (kcal/mol)"
print kinetic_stderr
print "nsigma"
print (kinetic_mean - kinetic_analytical) / kinetic_stderr
raise Exception("Mean kinetic energy exceeds error tolerance of %.1f standard errors." % MAX_SIGMA)
if numpy.any(numpy.abs(velocity_mean / velocity_stderr) > MAX_SIGMA):
print "mean velocity (nm/ps)"
print velocity_mean
print "stderr (nm/ps)"
print velocity_stderr
print "nsigma"
print velocity_mean / velocity_stderr
raise Exception("Mean velocity exceeds error tolerance of %.1f standard errors." % MAX_SIGMA)
if verbose: print "PASSED"
return
