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Image: pixelised brightness

A pixel image is one more component of a System, for image reconstruction. Its visibilities are the exact Fourier transform of the pixels.

virgil.models.Image

Bases: Component

Pixelised brightness distribution, for image reconstruction.

Pixel fluxes are softmax(log_brightness) over the pixels in support: positive, summing to one, zero outside. Inside a System it has a flux weight and offset like any component, so unresolved sources stay analytic; visibilities are the exact Fourier transform of the pixels, each a point at its centre. A constant added to log_brightness changes nothing, so fit fixes it (a free array comes back as log of the pixel fluxes); a pixel whose optimum is zero flux can fit far below the rest (-1e3 or lower, set by rounding): read an image from brightness, not from those values.

Parameters:

Name Type Description Default
log_brightness array-like, shape (nrow, ncol), or GaussianField

Log pixel fluxes up to a constant, oriented as render (row 0 North, column 0 East), or an object with evaluate(pixel_scale_mas) such as a GaussianField.

 required
pixel_scale_mas float

Pixel size in mas; the image centre, index ((nrow - 1) / 2, (ncol - 1) / 2), is at (dra, ddec).

 required
support array-like of bool

Pixels allowed to carry flux, same shape as log_brightness (default all); see circular_support.

 None
flux optional

As for any Component.

 1.0
dra optional

As for any Component.

 1.0
ddec optional

As for any Component.

 1.0
rotation_deg float

Position angle (North to East) of the grid's "up" axis (default 0); matching data.uv_grid.rotation_deg gives a much faster exact two-sided matrix transform.

 0.0
ft (auto, dft, nufft)

Transform for irregular uv points (default "auto", whichever is faster; see set_ft_defaults).

 "auto"
blur_fwhm_mas float

FWHM in mas of a fixed (not fitted) Gaussian blurring kernel in the forward model: the data are compared with the blurred image, so the pixels are the unblurred sky. Default None, recommended; blur for display after the fit (smoothed() gives the blurred pixels). Compounds with CalibrationNuisance.blur_fwhm_mas. Source: MPoL's Gaussian base layer, Czekala et al. (2025), references.

 None
smooth_fwhm_mas float

Deprecated alias of blur_fwhm_mas.

 required

Examples:

>>> image = Image(np.zeros((32, 32)), pixel_scale_mas=2.0)
>>> envelope = Image.from_model(GaussianDisk(sigma=8.0), 32, 2.0, flux=0.3)

brightness property

Pixel fluxes: positive, unit sum, zero outside support.

eta property

The log-brightness array, evaluated if it is a field.

from_brightness(brightness, pixel_scale_mas, *, floor=1e-06, **kwargs) classmethod

Build an image from non-negative pixel fluxes.

Pixels fainter than floor times the brightest are raised to that level, so that their logarithm is finite. Other keyword arguments (support, flux, dra, ddec, rotation_deg) go to Image.

from_model(model, npix, pixel_scale_mas, **kwargs) classmethod

Pixelise a model, e.g. a parametric fit, as a starting image.

The pixels sample model on an npix x npix grid (rotated by rotation_deg, if given); see from_brightness for the keyword arguments.

virgil.models.circular_support(npix, pixel_scale_mas, radius_mas, inner_radius_mas=0.0)

Pixels of an npix x npix image within radius_mas of its centre.

Returns a boolean array for the support of an Image. With inner_radius_mas, pixels closer to the centre than that are left out too: a hole under an analytic star, so that the image cannot pile flux onto it.