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Lennard-Jones with Numba and NumPy
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import numpy | |
from numba import double, jit | |
rc2 = 6.25 | |
rc2i=1.0/rc2 | |
rc6i=rc2i*rc2i*rc2i | |
ecut=rc6i*(rc6i-1.0) | |
@jit(argtypes=[double[:,:], double[:]]) | |
def lennardjones(U, box): | |
# Can't use (ndim, npart) = numpy.shape(U) | |
# with Numba. No unpacking of tuples. | |
ndim = len(U) | |
npart = len(U[0]) | |
F = numpy.zeros((ndim, npart)) | |
Epot = 0.0 | |
Vir = 0.0 | |
for i in range(npart): | |
for j in range(npart): | |
if i > j: | |
X = U[0, j] - U[0, i] | |
Y = U[1, j] - U[1, i] | |
Z = U[2, j] - U[2, i] | |
# Periodic boundary condition | |
X -= box[0] * numpy.rint(X/box[0]) | |
Y -= box[1] * numpy.rint(Y/box[1]) | |
Z -= box[2] * numpy.rint(Z/box[2]) | |
# Distance squared | |
r2 = X*X + Y*Y + Z*Z | |
if(r2 < rc2): | |
r2i = 1.0 / r2 | |
r6i = r2i*r2i*r2i | |
Epot = Epot + r6i*(r6i-1.0) - ecut | |
ftmp = 48. * r6i*(r6i- 0.5) * r2i | |
F[0, i] -= ftmp * X | |
F[1, i] -= ftmp * Y | |
F[2, i] -= ftmp * Z | |
F[0, j] += ftmp * X | |
F[1, j] += ftmp * Y | |
F[2, j] += ftmp * Z | |
Vir += ftmp | |
Epot = Epot * 4.0 | |
return Epot, F, Vir |
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