def test_rect_grid_2d():
"""test 2D grids"""
grid = CartesianGrid([[2], [2]], 4, periodic=True)
assert grid.get_image_data(np.zeros(grid.shape))["extent"] == [0, 2, 0, 2]
for _ in range(10):
p = np.random.randn(2)
assert np.all(grid.polar_coordinates_real(p) < np.sqrt(2))
periodic = random.choices([True, False], k=2)
grid = CartesianGrid([[4], [4]], 4, periodic=periodic)
assert grid.dim == 2
assert grid.volume == 16
np.testing.assert_array_equal(grid.discretization, np.ones(2))
assert grid.typical_discretization == 1
assert grid.polar_coordinates_real((1, 1)).shape == (4, 4)
grid = CartesianGrid([[-2, 2], [-2, 2]], [4, 8], periodic=periodic)
assert grid.dim == 2
assert grid.volume == 16
assert grid.typical_discretization == 0.75
assert grid.polar_coordinates_real((1, 1)).shape == (4, 8)
# test conversion between polar and Cartesian coordinates
c1 = grid.cell_coords
p = np.random.random(2) * grid.shape
d, a = grid.polar_coordinates_real(p, ret_angle=True)
c2 = grid.from_polar_coordinates(d, a, p)
assert np.allclose(grid.distance_real(c1, c2), 0)
def test_rect_grid_1d():
"""test 1D grids"""
grid = CartesianGrid([32], 16, periodic=False)
assert grid.dim == 1
assert grid.volume == 32
assert grid.typical_discretization == 2
np.testing.assert_array_equal(grid.discretization, np.full(1, 2))
assert grid.polar_coordinates_real(0).shape == (16, )
grid = CartesianGrid([[-16, 16]], 8, periodic=True)
assert grid.cuboid.pos == [-16]
assert grid.shape == (8, )
assert grid.dim == 1
assert grid.volume == 32
assert grid.typical_discretization == 4
assert grid.polar_coordinates_real(1).shape == (8, )
np.testing.assert_allclose(grid.normalize_point(-16 - 1e-10), 16 - 1e-10)
np.testing.assert_allclose(grid.normalize_point(-16 + 1e-10), -16 + 1e-10)
np.testing.assert_allclose(grid.normalize_point(16 - 1e-10), 16 - 1e-10)
np.testing.assert_allclose(grid.normalize_point(16 + 1e-10), -16 + 1e-10)
for periodic in [True, False]:
a, b = np.random.random(2)
grid = CartesianGrid([[a, a + b]], 8, periodic=periodic)
# test conversion between polar and Cartesian coordinates
c1 = grid.cell_coords
p = np.random.random(1) * grid.shape
d, a = grid.polar_coordinates_real(p, ret_angle=True)
c2 = grid.from_polar_coordinates(d, a, p)
assert np.allclose(grid.distance_real(c1, c2), 0)
