def test_cutcell(dim, order):
from random import randint
assert dim == 2 or dim == 3
N = 4 if dim == 2 else 6
# set an arbitrary number >0 of vertices to 1
S = randint(1, N)
# vertex_vals = np.arange(N, dtype=int)
vertex_vals = np.zeros(N, dtype=int)
while S > 0:
i = randint(0, N - 1)
if vertex_vals[i] == 0:
vertex_vals[i] = 1
S -= 1
print "TEST decompose in", dim, "dimensions with vertices", vertex_vals, "\n"
cell_data = np.arange(1000 * dim * order, dtype=np.float64)
facet_data = np.arange(1000 * dim * order, dtype=np.float64)
m, n = mc.decompose(dim, vertex_vals, order, cell_data, facet_data)
print "decompose returned %i volume quadrature points and %i facet quadrature points" % (m, n)
# parse data
size_pw = dim + 1
cell_pw = [(cell_data[i * size_pw:i * size_pw + dim], cell_data[i * size_pw + dim]) for i in range(m)]
facet_pw = [(facet_data[i * size_pw:i * size_pw + dim], cell_data[i * size_pw + dim]) for i in range(n)]
# print out
print "\nCELL QUADRATURE:"
for i, pw in enumerate(cell_pw):
p, w = pw
print "\t%i: point %s weight %f" % (i, str(p), w)
print "\nFACET QUADRATURE:"
for i, pw in enumerate(facet_pw):
p, w = pw
print "\t%i: point %s weight %f" % (i, str(p), w)
import marchingcube_py as mc
import numpy as np
def levelset_func(data):
dim = len(data)
print "\t levelset_func: ", dim, data
return 10*sum(data)
# callback test
print "\n", "*"*80, "\nTEST callback\n"
r = mc.test_callback(levelset_func)
print "result =", r
# data transfer test
data = np.arange(100, dtype=np.float64)
print "\n", "*"*80, "\nTEST decompose\n"
r = mc.decompose(data)
print "result =", r
print "DATA", data
