def test_all_keys(self):
input_dict = {'x': [0], 'y': [1], 'z': [0, 1, 2]}
output_dict = {
'x': np.array([0, 0, 0]),
'y': np.array([1, 1, 1]),
'z': [0, 1, 2]
}
np.testing.assert_equal(repeat_sing_dims(input_dict), output_dict)
def to_cartesian(r, theta, phi):
x, y, z = transform_spherical_to_cartesian([r, theta, phi])
return repeat_sing_dims({'x': x, 'y': y, 'z': z})
def detector_points(coords={}, x=None, y=None, z=None, r=None, theta=None,
phi=None, normals=None, name=None):
"""
Returns a one-dimensional set of detector coordinates at which scattering
calculations are to be done.
Parameters
----------
coords : dict, optional
Dictionary of detector coordinates. Default: empty dictionary.
Typical usage should not pass this argument, giving other parameters
(Cartesian `x`, `y`, and `z` or polar `r`, `theta`, and `phi`
coordinates) instead.
x, y : int or array_like, optional
Cartesian x and y coordinates of detectors.
z : int or array_like, optional
Cartesian z coordinates of detectors. If not specified, assume `z` = 0.
r : int or array_like, optional
Spherical polar radial coordinates of detectors. If not specified,
assume `r` = infinity (far-field).
theta : int or array_like, optional
Spherical polar coordinates (polar angle from z axis) of detectors.
phi : int or array_like, optional
Spherical polar azimuthal coodinates of detectors.
name : string
Returns
-------
grid : DataArray object
DataArray of zeros with calculated coordinates.
Notes
-----
Specify either the Cartesian or the polar coordinates of your detector.
This may be helpful for modeling static light scattering calculations.
Use detector_grid() to specify coordinates of a grid of pixels (e.g.,
a digital camera.)
"""
if normals is not None:
raise ValueError(NORMALS_DEPRECATION_MESSAGE)
updatelist = {'x': x, 'y': y, 'z': z, 'r': r, 'theta': theta, 'phi': phi}
coords = updated(coords, updatelist)
if 'x' in coords and 'y' in coords:
keys = ['x', 'y', 'z']
if coords.get('z') is None:
coords['z'] = 0
elif 'theta' in coords and 'phi' in coords:
keys = ['r', 'theta', 'phi']
if coords.get('r') is None:
coords['r'] = np.inf
else:
raise CoordSysError()
if name is None:
name = 'data'
coords = repeat_sing_dims(coords, keys)
coords = updated(coords, {key: ('point', coords[key]) for key in keys})
return xr.DataArray(np.zeros(len(coords[keys[0]][1])), dims=['point'],
coords=coords, name=name)
def test_nothing_to_repeat(self):
input_dict = {'x': [0], 'y': [1], 'z': [0, 1, 2]}
repeated = repeat_sing_dims(input_dict, ['x', 'y'])
self.assertEqual(repeated, input_dict)
def test_repeat_some_keys(self):
input_dict = {'x': [0], 'y': [1], 'z': [0, 1, 2]}
output_dict = {'x': np.array([0, 0, 0]), 'y': [1], 'z': [0, 1, 2]}
repeated = repeat_sing_dims(input_dict, ['x', 'z'])
np.testing.assert_equal(repeated, output_dict)
def test_input_isnt_modified(self):
input_dict = {'x': [0], 'y': [1], 'z': [0, 1, 2]}
repeat_sing_dims(input_dict)
self.assertEqual(input_dict, {'x': [0], 'y': [1], 'z': [0, 1, 2]})