def test_getitem():
"""Test getitem with different parameters."""
# test without weights
coords = Coordinates([1, 2], 0, 0)
new = coords[0]
assert isinstance(new, Coordinates)
npt.assert_allclose(new.get_cart(), np.atleast_2d([1, 0, 0]))
# test with weights
coords = Coordinates([1, 2], 0, 0, weights=[.1, .9])
new = coords[0]
assert isinstance(new, Coordinates)
npt.assert_allclose(new.get_cart(), np.atleast_2d([1, 0, 0]))
assert new.weights == np.array(.1)
# test with 3D array
coords = Coordinates([[1, 2, 3, 4, 5], [2, 3, 4, 5, 6]], 0, 0)
new = coords[0:1]
assert isinstance(new, Coordinates)
assert new.cshape == (1, 5)
# test if sliced object stays untouched
coords = Coordinates([0, 1], [0, 1], [0, 1])
new = coords[0]
new.set_cart(2, 2, 2)
assert coords.cshape == (2, )
npt.assert_allclose(coords.get_cart()[0], np.array([0, 0, 0]))
def test_orientations_from_view_up_show_coordinate_system_change(
views, ups, positions):
"""
Create `Orientations` from view and up vectors in the spherical domain
as well as in the carteesian domain, and visualize both to compare them
manually by eye.
"""
# Carteesian: Visualize to manually validate orientations
views = np.asarray(views)
ups = np.asarray(ups)
views = Coordinates(views[:, 0], views[:, 1], views[:, 2])
ups = Coordinates(ups[:, 0], ups[:, 1], ups[:, 2])
positions = np.asarray(positions)
positions = Coordinates(positions[:, 0], positions[:, 1], positions[:, 2])
orient_from_cart = Orientations.from_view_up(views, ups)
orient_from_cart.show(positions)
# Convert to spherical: And again visualize to manually validate
views.get_sph(convert=True)
ups.get_sph(convert=True)
positions.get_sph(convert=True)
orient_from_sph = Orientations.from_view_up(views, ups)
orient_from_sph.show(positions)
# Check if coordinate system has not been changed by orientations
assert views._system['domain'] == 'sph', (
"Coordinate system has been changed by Orientations.")
assert ups._system['domain'] == 'sph', (
"Coordinate system has been changed by Orientations.")
assert positions._system['domain'] == 'sph', (
"Coordinate system has been changed by Orientations.show().")
def test_orientations_from_view_up():
"""Create `Orientations` from view and up vectors."""
# test with single view and up vectors
view = [1, 0, 0]
up = [0, 1, 0]
Orientations.from_view_up(view, up)
# test with multiple view and up vectors
views = [[1, 0, 0], [0, 0, 1]]
ups = [[0, 1, 0], [0, 1, 0]]
Orientations.from_view_up(views, ups)
# provided as numpy ndarrays
views = np.atleast_2d(views).astype(np.float64)
ups = np.atleast_2d(ups).astype(np.float64)
Orientations.from_view_up(views, ups)
# provided as Coordinates
views = Coordinates(views[:, 0], views[:, 1], views[:, 2])
ups = Coordinates(ups[:, 0], ups[:, 1], ups[:, 2])
Orientations.from_view_up(views, ups)
# number of views to ups N:1
views = [[1, 0, 0], [0, 0, 1]]
ups = [[0, 1, 0]]
Orientations.from_view_up(views, ups)
# number of views to ups 1:N
views = [[1, 0, 0]]
ups = [[0, 1, 0], [0, 1, 0]]
Orientations.from_view_up(views, ups)
# number of views to ups M:N
with raises(ValueError):
views = [[1, 0, 0], [0, 0, 1], [0, 0, 1]]
ups = [[0, 1, 0], [0, 1, 0]]
Orientations.from_view_up(views, ups)
def test_coordinates_init_default_convention_and_unit():
"""Test initialization with the default convention and untit."""
# get list of available coordinate systems
coords = Coordinates()
systems = coords._systems()
# test constructor with all systems, units, and convention=None
for domain in systems:
Coordinates(0, 0, 0, domain)
def test_coordinates_init_val_and_weights():
"""Test initialization with weights."""
# correct number of weights
coords = Coordinates([1, 2], 0, 0, weights=[.5, .5])
assert isinstance(coords, Coordinates)
npt.assert_allclose(coords.weights, [.5, .5])
# incorrect number of weights
with raises(AssertionError):
Coordinates([1, 2], 0, 0, weights=.5)
def test_cdim():
"""Test the csim attribute."""
# empty
coords = Coordinates()
assert coords.cdim == 0
# 2D points
coords = Coordinates([1, 0], 1, 1)
assert coords.cdim == 1
# 3D points
coords = Coordinates([[1, 2, 3], [4, 5, 6]], 1, 1)
assert coords.cdim == 2
def test___eq___differInUnit_notEqual():
coordinates = Coordinates([1, 1], [1, 1], [1, 1],
convention='top_colat',
domain='sph',
unit='rad')
actual = Coordinates([1, 1], [1, 1], [1, 1],
convention='top_colat',
domain='sph',
unit='deg')
is_equal = coordinates == actual
assert not is_equal
def test_coordinates_init_default_convention():
"""Test initialization with the default convention."""
# get list of available coordinate systems
coords = Coordinates()
systems = coords._systems()
# test constructor with all systems, units, and convention=None
for domain in systems:
convention = list(systems[domain])[0]
for unit in systems[domain][convention]['units']:
Coordinates(0, 0, 0, domain, unit=unit[0][0:3])
def test_coordinates_init_val_and_system():
"""Test initialization with all available coordinate systems."""
# get list of available coordinate systems
coords = Coordinates()
systems = coords._systems()
# test constructor with all systems
for domain in systems:
for convention in systems[domain]:
for unit in systems[domain][convention]['units']:
Coordinates(0, 0, 0, domain, convention, unit[0][0:3])
def test_cshape():
"""Test the cshape attribute."""
# empty
coords = Coordinates()
assert coords.cshape == (0, )
# 2D points
coords = Coordinates([1, 0], [1, 1], [0, 1])
assert coords.cshape == (2, )
# 3D points
coords = Coordinates([[1, 2, 3], [4, 5, 6]], 1, 1)
assert coords.cshape == (2, 3)
def test_csize():
"""Test the csize attribute."""
# 0 points
coords = Coordinates()
assert coords.csize == 0
# two points
coords = Coordinates([1, 0], 1, 1)
assert coords.csize == 2
# 6 points in two dimensions
coords = Coordinates([[1, 2, 3], [4, 5, 6]], 1, 1)
assert coords.csize == 6
def test_setter_and_getter_with_conversion():
"""Test conversion between coordinate systems using the default unit."""
# get list of available coordinate systems
coords = Coordinates()
systems = coords._systems()
# test points contained in system definitions
points = [
'positive_x', 'positive_y', 'positive_z', 'negative_x', 'negative_y',
'negative_z'
]
# test setter and getter with all systems and default unit
for domain_in in list(systems):
for convention_in in list(systems[domain_in]):
for domain_out in list(systems):
for convention_out in list(systems[domain_out]):
for point in points:
# for debugging
print(f"{domain_in}({convention_in}) -> "
f"{domain_out}({convention_out}): {point}")
# in and out points
p_in = systems[domain_in][convention_in][point]
p_out = systems[domain_out][convention_out][point]
# empty object
c = Coordinates()
# --- set point ---
eval(f"c.set_{domain_in}(p_in[0], p_in[1], p_in[2], \
'{convention_in}')")
# check point
p = c._points
npt.assert_allclose(p.flatten(), p_in, atol=1e-15)
# --- test without conversion ---
p = eval(f"c.get_{domain_out}('{convention_out}')")
# check internal and returned point
npt.assert_allclose(c._points.flatten(),
p_in,
atol=1e-15)
npt.assert_allclose(p.flatten(), p_out, atol=1e-15)
# check if system was converted
assert c._system["domain"] == domain_in
assert c._system["convention"] == convention_in
# --- test with conversion ---
p = eval(f"c.get_{domain_out}('{convention_out}', \
convert=True)")
# check point
npt.assert_allclose(p.flatten(), p_out, atol=1e-15)
# check if system was converted
assert c._system["domain"] == domain_out
assert c._system["convention"] == convention_out
def test_get_nearest_k():
"""Test returns of get_nearest_k"""
# 1D cartesian, nearest point
x = np.arange(6)
coords = Coordinates(x, 0, 0)
d, i, m = coords.get_nearest_k(1, 0, 0)
assert d == 0.
assert i == 1
npt.assert_allclose(m, np.array([0, 1, 0, 0, 0, 0]))
# 1D spherical, nearest point
d, i, m = coords.get_nearest_k(0, 0, 1, 1, 'sph', 'top_elev', 'deg')
assert d == 0.
assert i == 1
npt.assert_allclose(m, np.array([0, 1, 0, 0, 0, 0]))
# 1D cartesian, two nearest points
d, i, m = coords.get_nearest_k(1.2, 0, 0, 2)
npt.assert_allclose(d, [.2, .8], atol=1e-15)
npt.assert_allclose(i, np.array([1, 2]))
npt.assert_allclose(m, np.array([0, 1, 1, 0, 0, 0]))
# 1D cartesian query two points
d, i, m = coords.get_nearest_k([1, 2], 0, 0)
npt.assert_allclose(d, [0, 0], atol=1e-15)
npt.assert_allclose(i, [1, 2])
npt.assert_allclose(m, np.array([0, 1, 1, 0, 0, 0]))
# 2D cartesian, nearest point
coords = Coordinates(x.reshape(2, 3), 0, 0)
d, i, m = coords.get_nearest_k(1, 0, 0)
assert d == 0.
assert i == 1
npt.assert_allclose(m, np.array([[0, 1, 0], [0, 0, 0]]))
# test with plot
coords = Coordinates(x, 0, 0)
coords.get_nearest_k(1, 0, 0, show=True)
# test object with a single point
coords = Coordinates(1, 0, 0)
coords.get_nearest_k(1, 0, 0, show=True)
# test out of range parameters
with raises(AssertionError):
coords.get_nearest_k(1, 0, 0, -1)
plt.close("all")
def _decode(cls, obj_dict):
"""Decode object based on its respective `_encode` counterpart."""
sampling = Coordinates(obj_dict['points'][:, 0],
obj_dict['points'][:, 1],
obj_dict['points'][:, 2],
domain='cart')
return cls(sampling, center=obj_dict['center'])
def sphericalvoronoi():
""" SphericalVoronoi object.
"""
points = np.array([[0, 0, 1], [0, 0, -1], [1, 0, 0], [0, 1, 0], [0, -1, 0],
[-1, 0, 0]])
sampling = Coordinates(points[:, 0], points[:, 1], points[:, 2])
return SphericalVoronoi(sampling)
def test_get_slice():
"""Test different queries for get slice."""
# test only for self.cdim = 1.
# self.get_slice uses KDTree, which is tested with N-dimensional arrays
# in test_get_nearest_k()
# cartesian grid
d = np.linspace(-2, 2, 5)
c = Coordinates(d, 0, 0)
npt.assert_allclose(c.get_slice('x', 'met', 0, 1),
np.array([0, 1, 1, 1, 0]))
c = Coordinates(0, d, 0)
npt.assert_allclose(c.get_slice('y', 'met', 0, 1),
np.array([0, 1, 1, 1, 0]))
c = Coordinates(0, 0, d)
npt.assert_allclose(c.get_slice('z', 'met', 0, 1),
np.array([0, 1, 1, 1, 0]))
# spherical grid
d = [358, 359, 0, 1, 2]
c = Coordinates(d, 0, 1, 'sph', 'top_elev', 'deg')
# cyclic query for lower bound
npt.assert_allclose(c.get_slice('azimuth', 'deg', 0, 1),
np.array([0, 1, 1, 1, 0]))
# cyclic query for upper bound
npt.assert_allclose(c.get_slice('azimuth', 'deg', 359, 2),
np.array([1, 1, 1, 1, 0]))
# non-cyclic query
npt.assert_allclose(c.get_slice('azimuth', 'deg', 1, 1),
np.array([0, 0, 1, 1, 1]))
# out of range query
with raises(AssertionError):
c.get_slice('azimuth', 'deg', -1, 1)
# non existing coordinate query
with raises(ValueError, match="'elevation' in 'ged' does not exist"):
c.get_slice('elevation', 'ged', 1, 1)
# test with show
c.get_slice('azimuth', 'deg', 1, 1, show=True)
# there is no unique processing for cylindrical coordinates - they are thus
# not tested here.
plt.close("all")
def test_inverse_rotation():
"""Test the inverse rotation."""
xyz = np.concatenate((np.ones((2, 4, 1)), np.zeros(
(2, 4, 1)), np.zeros((2, 4, 1))), -1)
c = Coordinates(xyz[..., 0].copy(), xyz[..., 1].copy(), xyz[..., 2].copy())
c.rotate('z', 90)
c.rotate('z', 90, inverse=True)
npt.assert_allclose(c.get_cart(), xyz, atol=1e-15)
def test_getter_with_degrees():
"""Test if getter return correct values also in degrees"""
coords = Coordinates(0, 1, 0)
sph = coords.get_sph(unit="deg")
npt.assert_allclose(sph, np.atleast_2d([90, 90, 1]))
cyl = coords.get_cyl(unit="deg")
npt.assert_allclose(cyl, np.atleast_2d([90, 0, 1]))
def test_assertion_for_getter():
"""Test assertion for empty Coordinates objects"""
coords = Coordinates()
with raises(ValueError, match="Object is empty"):
coords.get_cart()
with raises(ValueError, match="Object is empty"):
coords.get_sph()
with raises(ValueError, match="Object is empty"):
coords.get_cyl()
def test_coordinates_init_val():
"""Test initializing Coordinates with values of different type and size."""
# test input: scalar
c1 = 1
# test input: 2 element vectors
c2 = [1, 2] # list
c3 = np.asarray(c2) # flat np.array
c4 = np.atleast_2d(c2) # row vector np.array
c5 = np.transpose(c4) # column vector np.array
# test input: 3 element vector
c6 = [1, 2, 3]
# test input: 2D matrix
c7 = np.array([[1, 2, 3], [1, 2, 3]])
# test input: 3D matrix
c8 = np.array([[[1, 2, 3], [1, 2, 3]], [[1, 2, 3], [1, 2, 3]]])
# tests that have to path
# input scalar coordinate
Coordinates(c1, c1, c1)
# input list of coordinates
Coordinates(c2, c2, c2)
# input scalar and lists
Coordinates(c1, c2, c2)
# input flat np.arrays
Coordinates(c3, c3, c3)
# input non flat vectors
Coordinates(c3, c4, c5)
# input 2D data
Coordinates(c1, c1, c7)
# input 3D data
Coordinates(c1, c1, c8)
# tests that have to fail
with raises(AssertionError):
Coordinates(c2, c2, c6)
with raises(AssertionError):
Coordinates(c6, c6, c7)
with raises(AssertionError):
Coordinates(c2, c2, c8)
def test_orientations_show(views, ups, positions, orientations):
"""
Visualize orientations via `Orientations.show()`
with and without `positions`.
"""
# default orientation
Orientations().show()
# single vectors no position
view = [1, 0, 0]
up = [0, 1, 0]
orientation_single = Orientations.from_view_up(view, up)
orientation_single.show()
# with position
position = Coordinates(0, 1, 0)
orientation_single.show(position)
# multiple vectors no position
orientations.show()
# with matching number of positions
orientations.show(positions)
# select what to show
orientations.show(show_views=False)
orientations.show(show_ups=False)
orientations.show(show_rights=False)
orientations.show(show_views=False, show_ups=False)
orientations.show(show_views=False, show_rights=False)
orientations.show(show_ups=False, show_rights=False)
orientations.show(positions=positions, show_views=False, show_ups=False)
# with positions provided as Coordinates
positions = np.asarray(positions)
positions = Coordinates(positions[:, 0], positions[:, 1], positions[:, 2])
orientations.show(positions)
# with non-matching positions
positions = Coordinates(0, 1, 0)
with raises(ValueError):
orientations.show(positions)
def test_show():
"""Test if possible calls of show() pass."""
coords = Coordinates([-1, 0, 1], 0, 0)
# show without mask
coords.show()
# show with mask as list
coords.show([1, 0, 1])
# show with mask as ndarray
coords.show(np.array([1, 0, 1], dtype=bool))
# test assertion
with raises(AssertionError):
coords.show(np.array([1, 0], dtype=bool))
plt.close("all")
def test_get_nearest_sph():
"""Tests returns of get_nearest_sph."""
# test only 1D case since most of the code from self.get_nearest_k is used
az = np.linspace(0, 40, 5)
coords = Coordinates(az, 0, 1, 'sph', 'top_elev', 'deg')
i, m = coords.get_nearest_sph(25, 0, 1, 5, 'sph', 'top_elev', 'deg')
npt.assert_allclose(i, np.array([2, 3]))
npt.assert_allclose(m, np.array([0, 0, 1, 1, 0]))
# test search with empty results
i, m = coords.get_nearest_sph(25, 0, 1, 1, 'sph', 'top_elev', 'deg')
assert len(i) == 0
npt.assert_allclose(m, np.array([0, 0, 0, 0, 0]))
# test out of range parameters
with raises(AssertionError):
coords.get_nearest_sph(1, 0, 0, -1)
with raises(AssertionError):
coords.get_nearest_sph(1, 0, 0, 181)
# test assertion for multiple radii
coords = Coordinates([1, 2], 0, 0)
with raises(ValueError, match="get_nearest_sph only works if"):
coords.get_nearest_sph(0, 0, 1, 1)
def test_systems():
"""Test if all possible function calls of Coordinates.systems() pass."""
# get class instance
coords = Coordinates()
# test all four possible calls
coords.systems()
coords.systems(brief=True)
coords.systems('all')
coords.systems('all', brief=True)
coords.systems('current')
coords.systems('current', brief=True)
with raises(ValueError, match="show must be 'current' or 'all'."):
coords.systems('what')
def test_coordinate_names():
"""Test if units agree across coordinates that appear more than once"""
# get all coordinate systems
c = Coordinates()
systems = c._systems()
# get unique list of coordinates and their properties
coords = {}
# loop across domains and conventions
for domain in systems:
for convention in systems[domain]:
# loop across coordinates
for cc, coord in enumerate(
systems[domain][convention]['coordinates']):
# units of the current coordinate
cur_units = [
u[cc] for u in systems[domain][convention]['units']
]
# add coordinate to coords
if coord not in coords:
coords[coord] = {}
coords[coord]['domain'] = [domain]
coords[coord]['convention'] = [convention]
coords[coord]['units'] = [cur_units]
else:
coords[coord]['domain'].append(domain)
coords[coord]['convention'].append(convention)
coords[coord]['units'].append(cur_units)
# check if units agree across coordinates that appear more than once
for coord in coords:
# get unique first entry
units = coords[coord]['units'].copy()
units_ref, idx = np.unique(units[0], True)
units_ref = units_ref[idx]
for cc in range(1, len(units)):
# get next entry for comparison
units_test, idx = np.unique(units[cc], True)
units_test = units_test[idx]
# compare
assert all(units_ref == units_test), \
f"'{coord}' has units {units_ref} in "\
f"{coords[coord]['domain'][0]} "\
f"({coords[coord]['convention'][0]}) but units {units_test} "\
f"in {coords[coord]['domain'][cc]} "\
f"({coords[coord]['convention'][cc]})"
def test_get_nearest_cart():
"""Tests returns of get_nearest_cart."""
# test only 1D case since most of the code from self.get_nearest_k is used
x = np.arange(6)
coords = Coordinates(x, 0, 0)
i, m = coords.get_nearest_cart(2.5, 0, 0, 1.5)
npt.assert_allclose(i, np.array([1, 2, 3, 4]))
npt.assert_allclose(m, np.array([0, 1, 1, 1, 1, 0]))
# test search with empty results
i, m = coords.get_nearest_cart(2.5, 0, 0, .1)
assert len(i) == 0
npt.assert_allclose(m, np.array([0, 0, 0, 0, 0, 0]))
# test out of range parameters
with raises(AssertionError):
coords.get_nearest_cart(1, 0, 0, -1)
def test__systems():
"""Test completeness of internal representation of coordinate systems."""
# get all coordinate systems
coords = Coordinates()
systems = coords._systems()
# check object type
assert isinstance(systems, dict)
# check completeness of systems
for domain in systems:
for convention in systems[domain]:
assert "description_short" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'description_short'"
assert "coordinates" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'coordinates'"
assert "units" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'units'"
assert "description" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'description'"
assert "positive_x" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'positive_x'"
assert "positive_y" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'positive_y'"
assert "negative_x" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'negative_'"
assert "negative_y" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'negative_y'"
assert "positive_z" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'positive_z'"
assert "negative_z" in systems[domain][convention], \
f"{domain} ({convention}) is missing entry 'negative_z'"
for coord in systems[domain][convention]['coordinates']:
assert coord in systems[domain][convention], \
f"{domain} ({convention}) is missing entry '{coord}'"
assert systems[domain][convention][coord][0] in \
["unbound", "bound", "cyclic"], \
f"{domain} ({convention}), {coord}[0] must be 'unbound', "\
"'bound', or 'cyclic'."
def test_exist_systems():
"""Test internal function for checking if a coordinate system exists."""
# get class instance
coords = Coordinates()
# tests that have to pass
coords._exist_system('sph')
coords._exist_system('sph', 'side')
coords._exist_system('sph', 'side', 'rad')
coords._exist_system('sph', unit='rad')
# tests that have to fail
with raises(ValueError):
coords._exist_system()
with raises(AssertionError):
coords._exist_system('shp')
with raises(ValueError):
coords._exist_system(None, 'side')
with raises(AssertionError):
coords._exist_system('sph', 'tight')
with raises(AssertionError):
coords._exist_system('sph', 'side', 'met')
with raises(ValueError):
coords._exist_system(None, None, 'met')
def test_multiple_getter_with_conversion():
"""Test output of 500 random sequential conversions."""
# test N successive coordinate conversions
N = 500
# get list of available coordinate systems
coords = Coordinates()
systems = coords._systems()
# get reference points in cartesian coordinate system
points = [
'positive_x', 'positive_y', 'positive_z', 'negative_x', 'negative_y',
'negative_z'
]
pts = np.array([systems['cart']['right'][point] for point in points])
# init the system
coords.set_cart(pts[:, 0], pts[:, 1], pts[:, 2])
# list of domains
domains = list(systems)
for ii in range(N):
# randomly select a coordinate system
domain = domains[np.random.randint(len(domains))]
conventions = list(systems[domain])
convention = conventions[np.random.randint(len(conventions))]
# convert points to selected system
pts = eval(f"coords.get_{domain}('{convention}', convert=True)")
# get the reference
ref = np.array(
[systems[domain][convention][point] for point in points])
# check
npt.assert_allclose(pts, ref, atol=1e-15)
# print
print(f"Tolerance met in iteration {ii}")
def coordinates():
""" Coordinates object.
"""
return Coordinates([0, 1], [2, 3], [4, 5])