def get_view(self):
if self.view is None:
self.v = m.cross(self.w, self.u)
self.view = [[self.u[0], self.v[0], self.w[0], 0.0],
[self.u[1], self.v[1], self.w[1], 0.0],
[self.u[2], self.v[2], self.w[2], 0.0],
[
-m.dot(self.u, self.position),
-m.dot(self.v, self.position),
-m.dot(self.w, self.position), 1.0
]]
return to_tuple(self.view)
def find_leaf(self):
index = 0
while index > -1:
node = self.nodes[index]
plane = self.planes[node.plane]
distance = mymath.dot(plane.normal,
self.camera.position) - plane.dist
if distance >= 0:
index = node.children[0]
else:
index = node.children[1]
return self.leafs[-(index + 1)]
def test_known2x2(self):
# expected to fail because upsampled_idft2 doesn't handle the nyquist
# component properly
A = array([[1, 4], [0, 2]])
AA = fft2(A)
known_out = array([[4, 2.5], [3, 1.75]])
out = mm.upsampled_idft2(AA, 2, 2, 2, 0, 2)
self.assertArraysClose(known_out, out)
# code comparing the ideal fourier matrix approach with proper
# zero-padding, to the idft_upsampled
AAA = zpadf(AA, (2, 2))
F = array([[1, 1, 1, 1],[1, 1j, -1, -1j],[1,-1,1,-1],[1,-1j,-1,1j]])/4.0
out2 = mm.dot(F, AAA, F)*4.0
out = mm.upsampled_idft2(AA, 2, 4, 4, 0, 0)
def test_simple(self):
"""
Fourier transforms can be accomplished using matrices.
You need two of them (one for each dimension).
This test is a simple sanity check.
"""
a = fft2(
array([[0, 2, 2, 0], [0, 2, 2, 2], [0, 0, 0, 2], [10, 0, 0, 2]]))
ny, nx = a.shape
F = array([[1, 1, 1, 1], [1, 1j, -1, -1j], [1, -1, 1, -1],
[1, -1j, -1, 1j]])
self.assertArraysClose(ifft2(a), mm.dot(F, a, F) / nx / ny)
def test_known2x2(self):
# expected to fail because upsampled_idft2 doesn't handle the nyquist
# component properly
A = array([[1, 4], [0, 2]])
AA = fft2(A)
known_out = array([[4, 2.5], [3, 1.75]])
out = mm.upsampled_idft2(AA, 2, 2, 2, 0, 2)
self.assertArraysClose(known_out, out)
# code comparing the ideal fourier matrix approach with proper
# zero-padding, to the idft_upsampled
AAA = zpadf(AA, (2, 2))
F = array([[1, 1, 1, 1], [1, 1j, -1, -1j], [1, -1, 1, -1],
[1, -1j, -1, 1j]]) / 4.0
out2 = mm.dot(F, AAA, F) * 4.0
out = mm.upsampled_idft2(AA, 2, 4, 4, 0, 0)
def test_simple(self):
"""
Fourier transforms can be accomplished using matrices.
You need two of them (one for each dimension).
This test is a simple sanity check.
"""
a = fft2(array([[0, 2, 2, 0],
[0, 2, 2, 2],
[0, 0, 0, 2],
[10, 0, 0, 2]]))
ny, nx = a.shape
F = array([[1, 1, 1, 1],
[1, 1j, -1, -1j],
[1, -1, 1, -1],
[1, -1j, -1, 1j]])
self.assertArraysClose(ifft2(a), mm.dot(F, a, F)/nx/ny)
def network_error(activation, desired):
diff = mymath.vec_subtract(desired, activation)
return mymath.dot(diff, diff)
