Module sleplet.slepian_methods
Methods to work with Slepian coefficients.
Functions
def choose_slepian_method(L: int,
region: Region) ‑> SlepianFunctions-
Initialise Slepian object depending on input.
Args
L- The spherical harmonic bandlimit.
region- The Slepian region.
Raises
ValueError- Invalid
region_type, likely cause is invalidmask_name.
Returns
The given Slepian object.
def compute_s_p_omega(L: int,
slepian: SlepianFunctions) ‑> numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128]]-
Compute S_{p}(\omega) for a given region.
Args
L- The spherical harmonic bandlimit.
slepian- The given Slepian object.
Returns
The complex S_{p}(\omega) values.
def slepian_forward(L: int,
slepian: SlepianFunctions,
*,
f: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128]] | None = None,
flm: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]] | None = None,
mask: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.float64]] | None = None,
n_coeffs: int | None = None) ‑> numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128]]-
Compute the Slepian forward transform for all coefficients.
Args
L- The spherical harmonic bandlimit.
slepian- The given Slepian object.
f- The field value.
flm- The spherical harmonic coefficients.
mask- A boolean mask of the Slepian region.
n_coeffs- The number of Slepian coefficients to use.
Returns
The Slepian coefficients of the inputs.
def slepian_inverse(f_p: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]],
L: int,
slepian: SlepianFunctions) ‑> numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128]]-
Compute the Slepian inverse transform up to the Shannon number.
Args
f_p- The Slepian coefficients.
L- The spherical harmonic bandlimit.
slepian- The given Slepian object.
Returns
The values on the sphere in pixel space.
def slepian_mesh_forward(mesh_slepian: MeshSlepian,
*,
u: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]] | None = None,
u_i: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]] | None = None,
mask: bool = False,
n_coeffs: int | None = None) ‑> numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.float64]]-
Compute the Slepian forward transform for all coefficients on the mesh.
Args
mesh_slepian- The Slepian mesh object containing the eigensolutions.
u- The signal field value on the mesh.
u_i- The Fourier coefficients of the mesh.
mask- Whether to use the mask to compute the coefficients.
n_coeffs- The number of Slepian coefficients to use.
Returns
The Slepian coefficients on the mesh.
def slepian_mesh_inverse(mesh_slepian: MeshSlepian,
f_p: numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]]) ‑> numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[numpy.complex128 | numpy.float64]]-
Compute the Slepian inverse transform on the mesh up to the Shannon number.
Args
mesh_slepian- The Slepian mesh object containing the eigensolutions.
f_p- The Slepian wavelet coefficients.
Returns
The value of a function on the mesh in pixel space.