def test_numpy_wrappers():
a1 = YTArray([1, 2, 3], 'cm')
a2 = YTArray([2, 3, 4, 5, 6], 'cm')
a3 = YTArray([7, 8, 9, 10, 11], 'cm')
catenate_answer = [1, 2, 3, 2, 3, 4, 5, 6]
intersect_answer = [2, 3]
union_answer = [1, 2, 3, 4, 5, 6]
vstack_answer = [[2, 3, 4, 5, 6], [7, 8, 9, 10, 11]]
assert_array_equal(YTArray(catenate_answer, 'cm'), uconcatenate((a1, a2)))
assert_array_equal(catenate_answer, np.concatenate((a1, a2)))
assert_array_equal(YTArray(intersect_answer, 'cm'), uintersect1d(a1, a2))
assert_array_equal(intersect_answer, np.intersect1d(a1, a2))
assert_array_equal(YTArray(union_answer, 'cm'), uunion1d(a1, a2))
assert_array_equal(union_answer, np.union1d(a1, a2))
assert_array_equal(YTArray(catenate_answer, 'cm'), uhstack([a1, a2]))
assert_array_equal(catenate_answer, np.hstack([a1, a2]))
assert_array_equal(YTArray(vstack_answer, 'cm'), uvstack([a2, a3]))
assert_array_equal(vstack_answer, np.vstack([a2, a3]))
assert_array_equal(YTArray(vstack_answer, 'cm'), ustack([a2, a3]))
assert_array_equal(vstack_answer, np.stack([a2, a3]))
def _get_sampler_params(self, camera, render_source):
if self.disparity is None:
self.disparity = camera.width[0] / 1000.
single_resolution_y = int(np.floor(camera.resolution[1]) / 2)
px = np.linspace(-np.pi, np.pi, camera.resolution[0],
endpoint=True)[:, None]
py = np.linspace(-np.pi / 2.,
np.pi / 2.,
single_resolution_y,
endpoint=True)[None, :]
vectors = np.zeros((camera.resolution[0], single_resolution_y, 3),
dtype='float64',
order='C')
vectors[:, :, 0] = np.cos(px) * np.cos(py)
vectors[:, :, 1] = np.sin(px) * np.cos(py)
vectors[:, :, 2] = np.sin(py)
# The maximum possible length of ray
max_length = (unorm(camera.position - camera._domain_center) +
0.5 * unorm(camera._domain_width) +
np.abs(self.disparity))
# Rescale the ray to be long enough to cover the entire domain
vectors = vectors * max_length
R1 = get_rotation_matrix(0.5 * np.pi, [1, 0, 0])
R2 = get_rotation_matrix(0.5 * np.pi, [0, 0, 1])
uv = np.dot(R1, camera.unit_vectors)
uv = np.dot(R2, uv)
vectors.reshape((camera.resolution[0] * single_resolution_y, 3))
vectors = np.dot(vectors, uv)
vectors.reshape((camera.resolution[0], single_resolution_y, 3))
vectors2 = np.zeros((camera.resolution[0], single_resolution_y, 3),
dtype='float64',
order='C')
vectors2[:, :, 0] = -np.sin(px) * np.ones((1, single_resolution_y))
vectors2[:, :, 1] = np.cos(px) * np.ones((1, single_resolution_y))
vectors2[:, :, 2] = 0
vectors2.reshape((camera.resolution[0] * single_resolution_y, 3))
vectors2 = np.dot(vectors2, uv)
vectors2.reshape((camera.resolution[0], single_resolution_y, 3))
positions = np.tile(camera.position,
camera.resolution[0] * single_resolution_y)
positions = positions.reshape(camera.resolution[0],
single_resolution_y, 3)
# The left and right are switched here since VR is in LHS.
positions_left = positions + vectors2 * self.disparity
positions_right = positions + vectors2 * (-self.disparity)
if render_source.zbuffer is not None:
image = render_source.zbuffer.rgba
else:
image = self.new_image(camera)
dummy = np.ones(3, dtype='float64')
vectors_comb = uhstack([vectors, vectors])
positions_comb = uhstack([positions_left, positions_right])
image.shape = (camera.resolution[0], camera.resolution[1], 4)
vectors_comb.shape = (camera.resolution[0], camera.resolution[1], 3)
positions_comb.shape = (camera.resolution[0], camera.resolution[1], 3)
sampler_params = dict(vp_pos=positions_comb,
vp_dir=vectors_comb,
center=self.back_center,
bounds=(0.0, 1.0, 0.0, 1.0),
x_vec=dummy,
y_vec=dummy,
width=np.zeros(3, dtype="float64"),
image=image,
lens_type="stereo-spherical")
return sampler_params
