pyodide/benchmark/benchmarks/periodic_dist.py

41 lines
1.2 KiB
Python

# setup: import numpy as np ; N = 20 ; x = y = z = np.arange(0., N, 0.1) ; L = 4 ; periodic = True # noqa
# run: periodic_dist(x, x, x, L,periodic, periodic, periodic)
# pythran export periodic_dist(float [], float[], float[], int, bool,
# bool, bool)
import numpy as np
def periodic_dist(x, y, z, L, periodicX, periodicY, periodicZ):
"""Computes distances between all particles and places the result
in a matrix such that the ij th matrix entry corresponds to the
distance between particle i and j"""
N = len(x)
xtemp = np.tile(x, (N, 1))
dx = xtemp - xtemp.T
ytemp = np.tile(y, (N, 1))
dy = ytemp - ytemp.T
ztemp = np.tile(z, (N, 1))
dz = ztemp - ztemp.T
# Particles 'feel' each other across the periodic boundaries
if periodicX:
dx[dx > L / 2] = dx[dx > L / 2] - L
dx[dx < -L / 2] = dx[dx < -L / 2] + L
if periodicY:
dy[dy > L / 2] = dy[dy > L / 2] - L
dy[dy < -L / 2] = dy[dy < -L / 2] + L
if periodicZ:
dz[dz > L / 2] = dz[dz > L / 2] - L
dz[dz < -L / 2] = dz[dz < -L / 2] + L
# Total Distances
d = np.sqrt(dx ** 2 + dy ** 2 + dz ** 2)
# Mark zero entries with negative 1 to avoid divergences
d[d == 0] = -1
return d, dx, dy, dz