def test_coverage_hv_quadrants1c():
grid = np.zeros([1, 2, 2, 1])
gsize = np.array([1, 2, 2])
gmin = -gsize / 2.0
theta, h, v = [-np.pi / 2], [0], [-0.5]
cov_map = coverage(grid, gmin, gsize, pgrid, psize, theta, v, h)[0, ..., 0]
truth = np.array([[0., 0.], [1., 1.]])
np.testing.assert_equal(truth, cov_map)
def test_coverage_hv_quadrants4():
grid = np.zeros([2, 2, 2, 1])
gsize = np.array([2, 2, 2])
gmin = -gsize / 2.0
obj = np.zeros((2, 2, 2))
theta, h, v = [0], [0], [-1]
cov_map = coverage(grid, gmin, gsize, pgrid, psize, theta, v, h)[..., 0]
obj[0, :, 1] = 1
np.testing.assert_equal(obj, cov_map)
def test_coverage_hv_quadrants1_crop():
theta, h, v = [0], [-0.5], [0]
gmin = np.array([-2, 0, -1])
gsize = np.array([5, 1, 3])
grid = np.zeros((5, 1, 3, 1))
cov_map = coverage(grid, gmin, gsize, pgrid, psize, theta, v, h)[:, 0, :,
0]
truth = np.array([[0, 0, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 0, 0]])
truth = np.moveaxis(truth, 1, 0)
np.testing.assert_equal(truth, cov_map)
def test_theta_coverage():
probe_grid, probe_size, \
region, region_corner, region_size = init_coverage()
theta, v, h, dwell, times = discrete_trajectory(theta_move,
tmin=0,
tmax=1,
tstep=0.5,
xstep=1 / 32)
region = np.zeros([4, 16, 16, 1])
region_corner = [-2 / 16, -8 / 16, -8 / 16]
region_size = [4 / 16, 16 / 16, 16 / 16]
cov_map = coverage(region, region_corner, region_size, probe_grid,
probe_size, theta, v, h, dwell)[..., 0]
# np.save('tests/theta_coverage.npy', cov_map)
truth = np.load('tests/theta_coverage.npy')
# show_coverage(cov_map)
print("Computed map\n{}\n".format(cov_map))
print("True map\n{}\n".format(truth))
def test_stationary_coverage():
"""A beam of magnitude 10 at (:, 10, 8)."""
probe_grid, probe_size, \
region, region_corner, region_size = init_coverage()
theta, v, h, dwell, times = discrete_trajectory(stationary,
tmin=0,
tmax=10,
tstep=1,
xstep=1 / 32)
cov_map = coverage(region, region_corner, region_size, probe_grid,
probe_size, theta, v, h, dwell)[..., 0]
# show_coverage(cov_map)
key = cov_map[:, 8, :]
truth = np.zeros([16, 16])
truth[8, 10] = 10
# plt.figure()
# plt.plot(key[8, :], 'o')
np.testing.assert_equal(key, truth)
def test_vertical_coverage():
probe_grid, probe_size, \
region, region_corner, region_size = init_coverage()
theta, v, h, dwell, times = discrete_trajectory(vertical_move,
tmin=0,
tmax=40,
tstep=1,
xstep=1 / 32)
cov_map = coverage(region, region_corner, region_size, probe_grid,
probe_size, theta, v, h, dwell)[..., 0]
# show_coverage(cov_map)
key = cov_map[:, 4, :]
truth = np.zeros([16, 16])
truth[9:12, 8] = 10
truth[(8, 12), 8] = 5
# plt.figure()
# plt.plot(key[:, 8], 'o')
# print(key[8, :])
# assert_array_equal(key, truth)
assert key[8, 8] >= 5 and key[8, 8] < 6
assert key[12, 8] > 4 and key[12, 8] <= 5
assert np.all(key[9:12, 8] == 10)
def test_horizontal_coverage():
# NOTE: The forward edge of the smear will be slightly larger. The two
# edges even out as the time step approaches zero.
probe_grid, probe_size, \
region, region_corner, region_size = init_coverage()
theta, v, h, dwell, times = discrete_trajectory(horizontal_move,
tmin=0,
tmax=40,
tstep=1,
xstep=1 / 32)
cov_map = coverage(region, region_corner, region_size, probe_grid,
probe_size, theta, v, h, dwell)[..., 0]
# show_coverage(cov_map)
key = cov_map[:, 10, :]
truth = np.zeros([16, 16])
truth[10, 5:18] = 10
truth[10, (4, 8)] = 5
# plt.figure()
# plt.plot(key[10, :], 'o')
print(key[10, :])
# np.testing.assert_equal(key, truth)
assert key[10, 8] >= 5 and key[10, 8] < 6
assert key[10, 4] > 4 and key[10, 4] <= 5
assert np.all(key[10, 5:8] == 10)