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import numpy as np
from math import pi
import time
from compyle.config import get_config
from compyle.api import declare, annotate
from compyle.parallel import Elementwise, Reduction
from compyle.array import get_backend, wrap
import compyle.array as carr
from nnps import NNPSCountingSort, NNPSRadixSort
from md_simple import integrate_step1, integrate_step2, \
boundary_condition, MDSolverBase
@annotate
def calculate_force(i, x, y, z, fx, fy, fz, pe, nbr_starts, nbr_lengths, nbrs):
start_idx = nbr_starts[i]
length = nbr_lengths[i]
for k in range(start_idx, start_idx + length):
j = nbrs[k]
if i == j:
continue
xij = x[i] - x[j]
yij = y[i] - y[j]
zij = z[i] - z[j]
rij2 = xij * xij + yij * yij + zij * zij
irij2 = 1.0 / rij2
irij6 = irij2 * irij2 * irij2
irij12 = irij6 * irij6
pe[i] += (2 * (irij12 - irij6))
f_base = 24 * irij2 * (2 * irij12 - irij6)
fx[i] += f_base * xij
fy[i] += f_base * yij
fz[i] += f_base * zij
@annotate
def step_method1(i, x, y, z, vx, vy, vz, fx, fy, fz, pe, xmin, xmax,
ymin, ymax, zmin, zmax, m, dt, nbr_starts, nbr_lengths,
nbrs):
integrate_step1(i, m, dt, x, y, z, vx, vy, vz, fx, fy, fz)
boundary_condition(i, x, y, z, vx, vy, vz, fx, fy, fz, pe, xmin, xmax,
ymin, ymax, zmin, zmax)
@annotate
def step_method2(i, x, y, z, vx, vy, vz, fx, fy, fz, pe, xmin, xmax,
ymin, ymax, zmin, zmax, m, dt, nbr_starts, nbr_lengths,
nbrs):
calculate_force(i, x, y, z, fx, fy, fz, pe, nbr_starts, nbr_lengths, nbrs)
integrate_step2(i, m, dt, x, y, z, vx, vy, vz, fx, fy, fz)
class MDNNPSSolver(MDSolverBase):
def __init__(self, num_particles, x=None, y=None, z=None,
vx=None, vy=None, vz=None,
xmax=100., ymax=100., zmax=100., dx=2., init_T=0.,
backend=None, use_count_sort=False):
super().__init__(num_particles, x=x, y=y, z=z, vx=vx, vy=vy, vz=vz,
xmax=xmax, ymax=ymax, zmax=zmax, dx=dx, init_T=init_T,
backend=backend)
self.nnps_algorithm = NNPSCountingSort \
if use_count_sort else NNPSRadixSort
self.nnps = self.nnps_algorithm(self.x, self.y, self.z, 3., 0.01,
self.xmax, self.ymax, self.zmax,
backend=self.backend)
self.init_forces = Elementwise(calculate_force, backend=self.backend)
self.step1 = Elementwise(step_method1, backend=self.backend)
self.step2 = Elementwise(step_method2, backend=self.backend)
def solve(self, t, dt, log_output=False):
num_steps = int(t // dt)
self.nnps.build()
self.nnps.get_neighbors()
self.init_forces(self.x, self.y, self.z, self.fx, self.fy, self.fz,
self.pe, self.nnps.nbr_starts,
self.nnps.nbr_lengths, self.nnps.nbrs)
for i in range(num_steps):
self.step1(self.x, self.y, self.z, self.vx, self.vy, self.vz,
self.fx, self.fy, self.fz,
self.pe, self.xmin, self.xmax, self.ymin, self.ymax,
self.zmin, self.zmax, self.m, dt, self.nnps.nbr_starts,
self.nnps.nbr_lengths, self.nnps.nbrs)
self.nnps.build()
self.nnps.get_neighbors()
self.step2(self.x, self.y, self.z, self.vx, self.vy, self.vz,
self.fx, self.fy, self.fz,
self.pe, self.xmin, self.xmax, self.ymin, self.ymax,
self.zmin, self.zmax, self.m, dt, self.nnps.nbr_starts,
self.nnps.nbr_lengths, self.nnps.nbrs)
if i % 100 == 0:
self.post_step(i, log_output=log_output)
if __name__ == '__main__':
from compyle.utils import ArgumentParser
p = ArgumentParser()
p.add_argument(
'--use-count-sort', action='store_true', dest='use_count_sort',
default=False, help='Use count sort instead of radix sort'
)
p.add_argument(
'--show', action='store_true', dest='show',
default=False, help='Show plot'
)
p.add_argument(
'--log-output', action='store_true', dest='log_output',
default=False, help='Log output'
)
p.add_argument('-n', action='store', type=int, dest='n',
default=100, help='Number of particles')
p.add_argument('--tf', action='store', type=float, dest='t',
default=40., help='Final time')
p.add_argument('--dt', action='store', type=float, dest='dt',
default=0.02, help='Time step')
o = p.parse_args()
solver = MDNNPSSolver(
o.n,
backend=o.backend,
use_count_sort=o.use_count_sort)
start = time.time()
solver.solve(o.t, o.dt, log_output=o.log_output)
end = time.time()
print("Time taken for N = %i is %g secs" % (o.n, (end - start)))
if o.log_output:
solver.write_log('nnps_log.log')
if o.show:
solver.pull()
solver.plot()
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