pyodide/benchmark/benchmarks/fdtd.py

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2018-04-05 22:07:33 +00:00
#from: http://stackoverflow.com/questions/19367488/converting-function-to-numbapro-cuda
#setup: N = 10 ; import numpy ; a = numpy.random.rand(N,N)
#run: fdtd(a,10)
#pythran export fdtd(float[][], int)
import numpy as np
def fdtd(input_grid, steps):
grid = input_grid.copy()
old_grid = np.zeros_like(input_grid)
previous_grid = np.zeros_like(input_grid)
l_x = grid.shape[0]
l_y = grid.shape[1]
for i in range(steps):
np.copyto(previous_grid, old_grid)
np.copyto(old_grid, grid)
for x in range(l_x):
for y in range(l_y):
grid[x,y] = 0.0
if 0 < x+1 < l_x:
grid[x,y] += old_grid[x+1,y]
if 0 < x-1 < l_x:
grid[x,y] += old_grid[x-1,y]
if 0 < y+1 < l_y:
grid[x,y] += old_grid[x,y+1]
if 0 < y-1 < l_y:
grid[x,y] += old_grid[x,y-1]
grid[x,y] /= 2.0
grid[x,y] -= previous_grid[x,y]
return grid