arim.scat.Scattering2d#

class arim.scat.Scattering2d[source]#

Bases: ABC

Base object for computing the scattering functions in 2D.

Examples

>>> material = arim.Material(6300., 3120., 2700., 'solid', metadata={'long_name': 'Aluminium'})
>>> scat_obj = scat_factory('sdh', material, radius=0.5e-3)

A Scattering2d can be used a function of the incident angles, the scattered angles and the frequency:

>>> inc_theta = np.deg2rad([0., 0., 0.])
>>> out_theta = np.deg2rad([0., 10., 20])
>>> frequency = 5e6  # Hz
>>> result = scat_obj(inc_theta, out_theta, frequency)

result is a dict with keys ‘LL’, ‘LT’, ‘TL’, ‘TT’. Each value of the dict is an array of shape (3, ).

>>> result2 = scat_obj(inc_theta, out_theta, frequency, to_compute=['LL'])

result2 is a dict which contains the key ‘LL’. Use this feature to reduce the amount of computation. Depending on how the function is written, other keys may be returned.

To generate scattering matrices:

>>> numangles = 10  # number of angles between -pi (included) and +pi (excluded)
>>> single_freq_matrices = scat_obj.as_single_freq_matrices(numangles, frequency)

single_freq_matrices['LL'] is here a 2d array of shape (10, 10).

>>> frequencies = [1e6, 2e6, 3e6, 4e6, 5e6]  # Hz
>>> multi_freq_matrices = scat_obj.as_multi_freq_matrices(numangles, frequencies)

multi_freq_matrices['LL'] is here a 3d array of shape (5, 10, 10).

For convenience, functions that return an array instead of a dict of array are provided.

>>> func_dict = scat_obj.as_freq_angles_funcs()
>>> scat_LL_func = func_dict['LL']
>>> scat_LL_func(phi_in, phi_out, frequency)
...  # return an array
as_angles_funcs(frequency)[source]#

Returns a dict of scattering functions that take as input the incident angle and the outgoing angle.

as_freq_angles_funcs()[source]#

Returns a dict of scattering functions that take as input the incident angle, the outgoing angle and the frequency.

as_multi_freq_matrices(frequencies, numangles, to_compute=frozenset({'LL', 'LT', 'TL', 'TT'}))[source]#

Returns scattering matrices at different frequencies.

Parameters:

  • frequency (ndarray) – Shape: (numfreq, )

  • numangles (int)

  • to_compute – See SCAT_KEYS

Returns:

Shape of each matrix: (numfreq, numpoints, numpoints)

Return type:

dict[str, ndarray]

as_multi_freq_matrices_obj(frequencies, numangles, to_compute=frozenset({'LL', 'LT', 'TL', 'TT'}))[source]#

Returns scattering matrices at different frequencies as a ScatFromData object.

Parameters:

  • frequencies (ndarray)

  • numangles (int)

  • to_compute (set[str])

Return type:

ScatFromData

as_single_freq_matrices(frequency, numangles, to_compute=frozenset({'LL', 'LT', 'TL', 'TT'}))[source]#

Returns scattering matrices at a given frequency.

Parameters:

  • frequency (float)

  • numangles (int)

  • to_compute (set[str])

Returns:

Shape of each matrix: (numpoints, numpoints)

Return type:

dict[str, ndarray]