ivis.models.lrsb

Classes

LRSB(basis[, lambda_r, lambda_pos, ...])	Low-rank spectral basis model driven by a user-supplied basis matrix.
LRSBMemory(basis[, lambda_r, lambda_pos, ...])	Memory-streaming LRSB variant.
LRSB_C(basis[, continuum_basis, ...])	LRSB variant with explicit continuum basis functions.
LRSB_CMemory(basis[, continuum_basis, ...])	Memory-streaming LRSB_C variant.

class ivis.models.lrsb.LRSB(basis, lambda_r=1.0, lambda_pos=0.0, conj_data=True, assume_channel_invariant_operator=False, reference_channel=0)

Bases: BaseModel

Low-rank spectral basis model driven by a user-supplied basis matrix.

The basis must have shape (nbasis, nchan).

forward(x, vis_data, device, primary_beam_list=None, primary_beam=None, pb_list=None, grid_list=None, pb=None, grid_array=None, cell_size=None, fill_flagged='zero')

loss(x, shape, device, vis_data, **kwargs)

Compute scalar loss and gradient for optimization.

Parameters:

x (np.ndarray) – Flattened parameter vector.

Returns:

• loss (float) – Scalar loss.

• grad (np.ndarray) – Flattened gradient.

property nbasis

property nchan

objective(x, vis_data, device, primary_beam_list=None, primary_beam=None, pb_list=None, grid_list=None, pb=None, grid_array=None, cell_size=None, fftsd=None, fftbeam=None, tapper=None, lambda_sd=0.0, lambda_pos=None, fftkernel=None, beam_workers=4, verbose=False, **_)

reconstruct_cube(x, device=None, return_numpy=False)

reconstruct_cube_from_coeffs(coeffs, device=None, return_numpy=True)

class ivis.models.lrsb.LRSBMemory(basis, lambda_r=1.0, lambda_pos=0.0, conj_data=True, assume_channel_invariant_operator=False, reference_channel=0)

Bases: LRSB

Memory-streaming LRSB variant.

LRSB stores a smaller coefficient cube than Classic3D, but its objective still accumulates one large autograd graph by default. This variant backpropagates independent loss blocks as soon as they are computed.

objective(x, vis_data, device, primary_beam_list=None, primary_beam=None, pb_list=None, grid_list=None, pb=None, grid_array=None, cell_size=None, fftsd=None, fftbeam=None, tapper=None, lambda_sd=0.0, lambda_pos=None, fftkernel=None, beam_workers=4, verbose=False, **_)

class ivis.models.lrsb.LRSB_C(basis, continuum_basis=None, continuum_order=0, frequency=None, reference_frequency=None, continuum_only_channels=None, lambda_r_line_factor=1.0, lambda_r_cont_factor=1.0, **kwargs)

Bases: LRSB

LRSB variant with explicit continuum basis functions.

This augments the learned line basis with fixed smooth spectral modes. By default, it adds a single flat continuum mode psi_0(nu) = 1.

property continuum_basis

property continuum_nbasis

property continuum_only_channels

property continuum_order

property line_nbasis

reconstruct_continuum_cube(x, device=None, return_numpy=False)

reconstruct_line_cube(x, device=None, return_numpy=False)

property reference_frequency

split_coeffs(x)

class ivis.models.lrsb.LRSB_CMemory(basis, continuum_basis=None, continuum_order=0, frequency=None, reference_frequency=None, continuum_only_channels=None, lambda_r_line_factor=1.0, lambda_r_cont_factor=1.0, **kwargs)

Bases: LRSBMemory, LRSB_C

Memory-streaming LRSB_C variant.

This combines the hybrid line+continuum basis construction from LRSB_C with the blockwise backward pass from LRSBMemory.