def mcint(a, b, f, sample_count=100000):
rng = m.PCG32()
i = m.UInt32(0)
result = m.Float(0)
l = m.Loop(i, rng, result)
while l.cond(i < sample_count):
result += f(ek.lerp(a, b, rng.next_float32()))
i += 1
return result * (b - a) / sample_count
def test04_chi2(variant_packet_rgb, warp, attempt):
# Chi^2 test to make sure that the warping schemes are producing
# the right distribution. Test for all supported variants of
# N-dimensional warps (N = 0..3)
from mitsuba.core import ScalarBoundingBox2f
from mitsuba.python.chi2 import ChiSquareTest, PlanarDomain
cls = getattr(mitsuba.core, warp)
ndim = int(warp[-1]) + 2
np.random.seed(all_warps.index(warp) * 10 + attempt)
shape = np.random.randint(2, 8, ndim)
param_res = [sorted(np.random.rand(s)) for s in shape[:-2]]
if attempt == 9:
values = np.ones(shape)
else:
values = np.random.rand(*shape) * 10
instance = cls(values, param_res)
for j in range(10 if ndim > 2 else 1):
param = [
ek.lerp(param_res[i][0], param_res[i][-1], np.random.rand())
for i in range(0, ndim - 2)
]
chi2 = ChiSquareTest(
domain=PlanarDomain(ScalarBoundingBox2f(0, 1)),
sample_func=lambda p: instance.sample(p, param=param)[0],
pdf_func=lambda p: instance.eval(p, param=param),
sample_dim=2,
res=31,
sample_count=100000)
assert chi2.run(test_count=11 * len(all_warps))