SparseSpatialFluxComponent

class jolideco.models.SparseSpatialFluxComponent(flux, x_pos, y_pos, shape, use_log_flux=True, prior=None, frozen=False, wcs=None)

Bases: Module

Sparse flux component to represent a list of point sources

flux

Initial flux tensor

Type:

~torch.Tensor

x_pos

x position in pixel coordinates

Type:

~torch.Tensor

y_pos

y position in pixel coordinates

Type:

~torch.Tensor

shape

Image shape

Type:

tuple of int

use_log_flux

Use log scaling for flux

Type:

bool

prior

Prior for this flux component.

Type:

Prior

frozen

Whether to freeze component.

Type:

bool

wcs

World coordinate transform object

Type:

~astropy.wcs.WCS

Initialize internal Module state, shared by both nn.Module and ScriptModule.

Attributes Summary

flux	Flux (~torch.Tensor)
flux_numpy	Flux as numpy array
flux_upsampled	Upsampled flux
indices	Shape of the flux component
is_sparse
shape	Shape of the flux component
sky_coord	Positions as SkyCoord
upsampling_factor
use_log_flux	Use log flux
wcs	Flux error
x_pos_numpy	x pos as numpy array
y_pos_numpy	y pos as numpy array

Methods Summary

from_numpy(flux, x_pos, y_pos, **kwargs)	Create sparse flux component from numpy arrays
from_sky_coord(skycoord, wcs, **kwargs)	Create sparse flux component from sky coordinates
parameters([recurse])	Parameter list
plot([ax, kwargs_norm])	Plot flux component as sky image
read(filename[, format])	Read sparse flux component from file
to_dict(**kwargs)	Convert sparse flux component configuration to dict, with simple data types.
write(filename[, format, overwrite])	Write flux component to file

Attributes Documentation

flux

Flux (~torch.Tensor)

flux_numpy

Flux as numpy array

flux_upsampled

Upsampled flux

indices

Shape of the flux component

is_sparse = True

shape

Shape of the flux component

sky_coord

Positions as SkyCoord

upsampling_factor = 1

use_log_flux

Use log flux

wcs

Flux error

x_pos_numpy

x pos as numpy array

y_pos_numpy

y pos as numpy array

Methods Documentation

classmethod from_numpy(flux, x_pos, y_pos, **kwargs)

Create sparse flux component from numpy arrays

flux

Initial flux tensor

Type:

~numpy.ndarray

x_pos

x position in pixel coordinates

Type:

~numpy.ndarray

y_pos

y position in pixel coordinates

Type:

~numpy.ndarray

\*\*kwargs

Keyword arguments forwarded to SparseFluxComponent

Type:

dict

Returns:

sparse_flux_component – Sparse flux component

Return type:

SparseFluxComponent

classmethod from_sky_coord(skycoord, wcs, **kwargs)

Create sparse flux component from sky coordinates

Parameters:

• skycoord (~astropy.coordinates.SkyCoord) – Sky coordinates

• wcs (~astropy.wcs.WCS) – World coordinate transform object

Returns:

sparse_flux_component – Sparse flux component

Return type:

SparseFluxComponent

parameters(recurse=True)

Parameter list

plot(ax=None, kwargs_norm=None, **kwargs)

Plot flux component as sky image

Parameters:

• ax (~matplotlib.pyplot.Axes) – Plotting axes

• kwargs_norm (dict) – Keyword arguments passed to ~astropy.visualization.simple_norm

• **kwargs (dict) – Keywords forwarded to ~matplotlib.pyplot.imshow

Returns:

ax – Plotting axes

Return type:

~matplotlib.pyplot.Axes

classmethod read(filename, format=None)

Read sparse flux component from file

Parameters:

• filename (str or Path) – Output filename

• format ({'fits'}) – Format to use.

Returns:

flux_component – Flux component

Return type:

SparseFluxComponent

to_dict(**kwargs) → dict[str, Any]

Convert sparse flux component configuration to dict, with simple data types.

Returns:

data – Parameter dict.

Return type:

dict

write(filename, format=None, overwrite=False, **kwargs)

Write flux component to file

Parameters:

• filename (str or Path) – Output filename

• overwrite (bool) – Overwrite file.

• format ({'fits'}) – Format to use.