def test_direct_initializers(self):
np.testing.assert_equal(math.zeros([1, 16]), np.zeros([1, 16]))
self.assertEqual(math.zeros([1, 16]).dtype, np.float32)
np.testing.assert_equal(math.ones([1, 16, 1]), np.ones([1, 16, 1]))
np.testing.assert_equal(math.zeros_like(math.ones([1, 16, 1])), np.zeros([1, 16, 1]))
np.testing.assert_equal(math.randn([1, 4]).shape, [1, 4])
self.assertEqual(math.randn([1, 4]).dtype, np.float32)
def test_fluid_initializers(self):
def typetest(fluid):
self.assertIsInstance(fluid, Fluid)
self.assertIsInstance(fluid.velocity, StaggeredGrid)
numpy.testing.assert_equal(fluid.density.data.shape, [1, 4, 4, 1])
numpy.testing.assert_equal(fluid.velocity.resolution, [4, 4])
numpy.testing.assert_equal(fluid.velocity.data[0].resolution,
[5, 4])
typetest(Fluid(Domain([4, 4]), density=0.0, velocity=0.0))
typetest(Fluid(Domain([4, 4]), density=1.0, velocity=1.0))
typetest(Fluid(Domain([4, 4]), density=0, velocity=math.zeros))
typetest(
Fluid(Domain([4, 4]),
density=lambda s: math.randn(s),
velocity=lambda s: math.randn(s)))
typetest(
Fluid(Domain([4, 4]),
density=numpy.zeros([1, 4, 4, 1]),
velocity=numpy.zeros([1, 5, 5, 2])))
typetest(
Fluid(Domain([4, 4]),
density=numpy.zeros([1, 4, 4, 1]),
velocity=numpy.zeros([1, 5, 5, 2])))
typetest(Fluid(Domain([4, 4])))
def grid_sample(self, resolution, size, batch_size=1, dtype=np.float32):
shape = (batch_size,) + tuple(resolution) + (self.channels,)
rndj = math.randn(shape, dtype) + 1j * math.randn(shape, dtype)
k = math.fftfreq(resolution) * resolution / size * self.scale # in physical units
k = math.sum(k ** 2, axis=-1, keepdims=True)
lowest_frequency = 0.1
weight_mask = 1 / (1 + math.exp((lowest_frequency - k) * 1e3)) # High pass filter
# --- Compute 1/k ---
k[(0,) * len(k.shape)] = np.inf
inv_k = 1 / k
inv_k[(0,) * len(k.shape)] = 0
# --- Compute result ---
fft = rndj * inv_k ** self.smoothness * weight_mask
array = math.real(math.ifft(fft)).astype(dtype)
array /= math.std(array, axis=tuple(range(1, math.ndims(array))), keepdims=True)
array -= math.mean(array, axis=tuple(range(1, math.ndims(array))), keepdims=True)
return array
