def setUp(self):
self.natoms = 4
self.k = 1
self.Emax = 2 #this choice is fundamentally arbitrary, it's only used to generate the initial configuration
#self.temperatures = [0.2,0.27,0.362,0.487,0.65,0.88,1.18,1.6]
self.temperatures = [0.2, 0.362, 0.65, 1.18]
self.stepsize = 1
self.niter = 2e6
self.adjustf = 0.9
self.adjust_niter = 0.3 * self.niter
self.radius = 1e10
self.tolerance = 2e-1
self.bdim = 3
self.ndim = self.natoms * self.bdim
self.origin = np.zeros(self.ndim)
self.seeds = dict(takestep=42, metropolis=44)
self.potential = Harmonic(self.origin,
self.k,
bdim=self.bdim,
com=False)
self.mcrunner = Metropolis_MCrunner(self.potential,
self.origin,
1,
self.stepsize,
self.niter,
hEmax=100,
adjustf=self.adjustf,
adjustf_niter=self.adjust_niter,
radius=self.radius,
bdim=self.bdim,
single=False,
seeds=self.seeds)
def test_heat_capacity_2D(self):
self.bdim = 2
self.ndim = self.natoms * self.bdim
self.origin = np.zeros(self.ndim)
self.potential = Harmonic(self.origin,
self.k,
bdim=self.bdim,
com=False)
print "2D"
for T in self.temperatures:
mcrunner = Metropolis_MCrunner(self.potential,
self.origin,
T,
self.stepsize,
self.niter,
hEmax=100,
adjustf=self.adjustf,
adjustf_niter=self.adjust_niter,
radius=self.radius,
bdim=self.bdim)
#MCMC
mcrunner.run()
#collect the results
binenergy, hist, mean, variance = mcrunner.get_histogram()
cv = variance / (T * T)
cv_true = self.natoms * self.bdim / 2.0
print cv, cv_true
self.assertLess(abs(cv - cv_true), self.tolerance,
'failed for temperature {}, cv = {}'.format(T, cv))
def test_heat_capacity_2D_com(self):
self.bdim = 2
self.ndim = self.natoms * self.bdim
self.origin = np.zeros(self.ndim)
potential = Harmonic(self.origin, self.k, bdim=self.bdim, com=True)
#self.start_coords = vector_random_uniform_hypersphere(self.ndim) * np.sqrt(2*self.Emax) #coordinates sampled from Pow(ndim)
print "2D com"
for T in self.temperatures:
mcrunner = Metropolis_MCrunner(potential,
self.origin,
T,
self.stepsize,
self.niter,
hEmax=100,
adjustf=self.adjustf,
adjustf_niter=self.adjust_niter,
radius=self.radius,
bdim=self.bdim)
#MCMC
mcrunner.run()
#collect the results
binenergy, hist, mean, variance = mcrunner.get_histogram()
cv = variance / (T * T)
cv_true = (self.natoms - 1) * self.bdim / 2.0
print cv, cv_true
self.assertLess(abs(cv - cv_true), self.tolerance,
'failed for temperature {}, cv = {}'.format(T, cv))
def test_composite_moves(self):
self.bdim = 2
self.ndim = self.natoms * self.bdim
self.origin = np.zeros(self.ndim)
self.potential = Harmonic(self.origin,
self.k,
bdim=self.bdim,
com=False)
res.nsteps = n
res.nhev = function_evaluate_pot.nhev
res.success = converged
# res.nhev = function_evaluate_pot.nhev
return res
# u0 = 0.5
# pot = potclass()
# tspan = (0, 1.0)
# print(pot.get_negative_grad(1, 1, 1))
# prob = de.ODEProblem(pot.get_negative_grad,u0, tspan)
# de.init(prob, de.Tsit5())
if __name__ == "__main__":
pot = Harmonic(np.zeros(3), 2)
res = ode_julia_naive([1.0, 1.0, 1.0], pot)
print(res.nfev)
print(res.coords)
print(res.nfev)
print(res.nhev)
print(res.niter)
# def initialize_ode(get_negative_grad, x0):
# tspan = (0, float('inf'))
# prob = de.ODEProblem(get_negative_grad,x0, tspan)
# return de.init(prob, de.Tsit5())
# def one_iteration(integrator):
# de.step_b(integrator)
# return (integrator.t, integrator.u, de.get_du(integrator))
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="do nested sampling on a Lennard Jones cluster")
parser.add_argument("base_directory",
type=str,
help="directory in which to save results")
#parser.add_argument("-K", "--nreplicas", type=int, help="number of replicas", default=300)
args = parser.parse_args()
natoms = 4
bdim = 3
k = 1
origin = np.zeros(natoms * bdim)
potential = Harmonic(origin, k, bdim=bdim, com=False)
path = args.base_directory
#Parallel Tempering
temperature = 1.0
stepsize = 1
niter = 1e4
mcrunner = Metropolis_MCrunner(potential,
origin,
temperature,
stepsize,
niter,
hEmax=100,
adjustf=0.9,
adjustf_niter=3000,
radius=100000,
from pele.potentials import Harmonic import numpy as np a = np.zeros(3) b = np.ones(3) pot = Harmonic(a, 2) print(pot.getEnergyGradientHessian(b))