def test_iproject(self):
"""Projecting Gnomonic coordinates to cartesian coordinates
yields expected result.
"""
xy = np.array([
[1.4254, 2.0385],
[0.7819, 1.1650],
[1.5892, 1.3915],
[1.0372, 1.3397],
[0.7721, 0.0656],
[1.0743, 0.7245],
[0.7072, 1.0928],
[1.4103, 0.8177],
[2.7529, 15.1496],
[2.8328, 0.7039],
])
assert np.allclose(
GnomonicProjection.xy2vector(xy).data,
np.array([
[0.5316, 0.7603, 0.3729],
[0.4538, 0.6761, 0.5803],
[0.6800, 0.5954, 0.4278],
[0.5272, 0.6809, 0.5082],
[0.6103, 0.0519, 0.7904],
[0.6563, 0.4426, 0.6109],
[0.4308, 0.6657, 0.6091],
[0.7374, 0.4275, 0.5228],
[0.1784, 0.9818, 0.06480],
[0.9181, 0.2281, 0.3240],
]),
atol=1e-2,
)
def gnomonic_to_lambert(xy: np.ndarray) -> np.ndarray:
"""Convert (n,2) array from Gnomonic via Cartesian coordinates to
Lambert."""
# These two functions could probably be combined into 1 to decrease
# runtime
v = GnomonicProjection.xy2vector(xy)
return LambertProjection.vector2xy(v)
def lambert_to_gnomonic(xy: np.ndarray) -> np.ndarray:
"""Convert (n,2) array from Lambert via Cartesian coordinates to
Gnomonic."""
# These two functions could probably be combined into 1 to decrease
# runtime
vec = LambertProjection.iproject(xy)
xy = GnomonicProjection.project(vec)
return xy
def test_project(self):
"""Projecting cartesian coordinates to Gnomonic coordinates
yields expected result.
"""
v = np.array([
[0.5901, 0.8439, 0.4139],
[0.4994, 0.744, 0.6386],
[0.8895, 0.7788, 0.5597],
[0.6673, 0.8619, 0.6433],
[0.7605, 0.0647, 0.9849],
[0.5852, 0.3946, 0.5447],
[0.4647, 0.7181, 0.6571],
[0.8806, 0.5106, 0.6244],
[0.0816, 0.4489, 0.0296],
[0.7585, 0.1885, 0.2678],
])
xy = GnomonicProjection.vector2xy(v)
# Desired project result?
assert np.allclose(
xy,
np.array([
[1.42, 2.03],
[0.78, 1.16],
[1.58, 1.39],
[1.03, 1.33],
[0.77, 0.06],
[1.07, 0.72],
[0.70, 1.09],
[1.41, 0.81],
[2.75, 15.14],
[2.83, 0.70],
]),
atol=1e-1,
)
# Same result passing Vector3d
assert np.allclose(xy, GnomonicProjection.vector2xy(Vector3d(v)))