stdpipe.photometry_iraf module

Aperture photometry using PyRAF DAOPHOT routines.

This module provides photometry functionality compatible with stdpipe.photometry but using IRAF/DAOPHOT tasks for aperture photometry measurements.

stdpipe.photometry_iraf.measure_objects(obj, image, aper=3, bkgann=None, fwhm=None, mask=None, bg=None, err=None, gain=None, bg_size=64, sn=None, centroid_iter=0, keep_negative=True, get_bg=False, _workdir=None, _tmpdir=None, verbose=False)

Aperture photometry at the positions of already detected objects using PyRAF DAOPHOT.

This function provides similar behavior to stdpipe.photometry.measure_objects() but uses IRAF DAOPHOT tasks for photometry measurements.

It will estimate and subtract the background unless external background estimation (bg) is provided, and use user-provided noise map (err) if requested.

If the mask is provided, it will set 0x200 bit in object flags if at least one of aperture pixels is masked.

The results may optionally be filtered to drop the detections with low signal to noise ratio if sn parameter is set and positive. It will also filter out the events with negative flux.

Note: Requires PyRAF and IRAF to be installed and properly configured.

Parameters:

objastropy.table.Table

Initial object detections to be measured. Must have ‘x’ and ‘y’ columns.

imagenumpy.ndarray

Input image as a 2D NumPy array.

aperfloat

Circular aperture radius in pixels for flux measurement.

bkganntuple of float or None

Background annulus as (inner_radius, outer_radius) for local background estimation. If not set, global background model is used instead.

fwhmfloat or None

If provided, aper and bkgann are measured in units of FWHM.

masknumpy.ndarray or None

Boolean image mask (True values will be masked).

bgnumpy.ndarray or None

Background image to subtract instead of automatically computed one.

errnumpy.ndarray or None

Image noise map to use instead of automatically computed one.

gainfloat or None

Image gain in e/ADU, used for photometry error estimation.

bg_sizeint

Background grid size in pixels for global background estimation.

snfloat or None

Minimal S/N ratio. If set, measurements with magnitude errors exceeding 1/sn will be discarded.

centroid_iterint

Number of centroiding iterations before photometry (not implemented for IRAF backend).

keep_negativebool

If False, measurements with negative fluxes will be discarded.

get_bgbool

If True, also return estimated background and background noise images.

_workdirstr or None

Directory for temporary files. If None, a temporary directory is created.

_tmpdirstr or None

Parent directory for temporary directory creation if _workdir is None.

verbosebool or callable

Whether to show verbose messages. May be boolean or a print-like function.

Returns:

astropy.table.Table

Copy of original table with flux, fluxerr, mag and magerr columns replaced with measured values. If get_bg=True, returns a tuple of (table, background, background_error).

Raises:

ImportError

If PyRAF is not available.

RuntimeError

If DAOPHOT task fails.

stdpipe.photometry_iraf.measure_objects_psf(obj, image, fwhm=None, psf_stars=None, n_psf_stars=20, mask=None, bg=None, err=None, gain=None, bg_size=64, sn=None, psfrad=None, fitrad=None, psf_function='auto', psf_varorder=0, keep_negative=True, get_bg=False, _workdir=None, _tmpdir=None, verbose=False)

PSF photometry using IRAF DAOPHOT (psf + allstar tasks).

This function performs PSF photometry using the full DAOPHOT workflow: 1. Select PSF stars (or use provided psf_stars) 2. Build PSF model using DAOPHOT psf task 3. Fit all sources using DAOPHOT allstar task 4. Return results in stdpipe format with quality metrics

The PSF model is built automatically from bright, isolated stars in the image. If psf_stars is provided, those specific stars will be used instead of automatic selection.

Note: Requires PyRAF and IRAF to be installed and properly configured.

Parameters:

objastropy.table.Table

Initial object detections. Must have ‘x’ and ‘y’ columns. Should also have ‘flux’ or ‘mag’ for PSF star selection.

imagenumpy.ndarray

Input image as a 2D NumPy array.

fwhmfloat

FWHM in pixels (required for PSF building and fitting).

psf_starsarray-like or None

Indices of objects to use as PSF stars. If None, stars are selected automatically.

n_psf_starsint

Number of PSF stars to select automatically.

masknumpy.ndarray or None

Boolean image mask (True values will be masked).

bgnumpy.ndarray or None

Background image to subtract instead of automatically computed one.

errnumpy.ndarray or None

Image noise map.

gainfloat or None

Image gain in e/ADU.

bg_sizeint

Background grid size in pixels.

snfloat or None

Minimal S/N ratio for output filtering.

psfradfloat or None

PSF radius in pixels (default: 3*fwhm). Sets how far the PSF extends.

fitradfloat or None

Fitting radius in pixels (default: fwhm). Sets how many pixels to use for fitting each star.

psf_functionstr

PSF function type: ‘auto’, ‘gauss’, ‘moffat15’, ‘moffat25’, ‘lorentz’, ‘penny1’, or ‘penny2’.

psf_varorderint

PSF variability order: 0=constant, 1=linear, 2=quadratic.

keep_negativebool

If False, discard measurements with negative fluxes.

get_bgbool

If True, also return background and error images.

_workdirstr or None

Working directory for temporary files.

_tmpdirstr or None

Parent directory for temporary directory creation.

verbosebool or callable

Verbose output.

Returns:

astropy.table.Table

Table with PSF photometry results including flux, mag, x_psf, y_psf, qfit_psf, cfit_psf, flags_psf columns. If get_bg=True, returns a tuple of (table, background, background_error).

Raises:

ImportError

If PyRAF is not available.

ValueError

If required parameters are missing.

RuntimeError

If DAOPHOT tasks fail.