GridData

class pyvisgrid.core.gridder.GridData(vis_data: ndarray, fov: float | None = None, mask: ndarray | None = None, mask_real: ndarray | None = None, mask_imag: ndarray | None = None, dirty_image: ndarray | None = None)

Bases: object

DataClass to save the gridded and non-gridded visibilities for a specific Stokes component.

Attributes:

vis_datanumpy.ndarray

The ungridded visibilities of shape (N_MEASUREMENTS * N_CHANNELS,).

fovfloat

The size of the Field Of View of the gridded data in arcseconds.

masknumpy.ndarray, optional

The mask created from the given (u,v) coordinates. The mask contains the number of (u,v) coordinates per pixel.

mask_realnumpy.ndarray, optional

The gridded real part of the visibilites.

mask_imagnumpy.ndarray, optional

The gridded imaginary part of the visibilities.

dirty_imgnumpy.ndarray, optional

The complex Dirty Image. This is the 2-dimensional Fourier transform of the gridded visibilities.

Attributes Summary

dirty_image
fov
mask
mask_imag
mask_real

Methods Summary

copy()
get_mask_abs_phase()	Returns the gridded mask as amplitude and phase.
get_mask_complex()	Returns the gridded mask as a complex array with the form mask.real + 1j * mask.imag.
get_mask_real_imag()	Returns the gridded mask as real and imaginary parts.

Attributes Documentation

dirty_image: ndarray | None = None

fov: float | None = None

mask: ndarray | None = None

mask_imag: ndarray | None = None

mask_real: ndarray | None = None

Methods Documentation

copy() → GridData

get_mask_abs_phase() → tuple[ndarray]

Returns the gridded mask as amplitude and phase.

Returns:

tuple[numpy.ndarray]

Amplitude and phase of the complex mask.

get_mask_complex() → ndarray

Returns the gridded mask as a complex array with the form mask.real + 1j * mask.imag.

Returns:

numpy.ndarray

Complex mask

get_mask_real_imag() → tuple[ndarray]

Returns the gridded mask as real and imaginary parts.

Returns:

tuple[numpy.ndarray]

Real and parts of the complex mask.