PythonPhot PSF Fitting Photometry Tutorial
getpsf.py : Generates a point-spread function (PSF) from observed stars atspecified locations. Uses the family of "peak fit" modules(pkfit, pkfit_noise, pkfit_norecent, etc) to fit a gaussian to eachstar and define an array of non-gaussian psf residuals.Returns a 5-element vector defining the gaussian, a 2-d array ofpsf residuals, and the magnitude of the psf. Also writes out thepsf model to a fits file with the gaussian parameters in the headerand the residuals in the data array.
rdpsf.py : Read the .fits file created by getpsf.py that contains thepsf model gaussian parameters and 2-d array of residuals.
pkfit.py : fit a psf model to an isolated point sourcepkfit_noise : fitting with an input noise imagepkfit_norecent : forced photometry (fitting a peak without recentering)pkfit_norecent_noise : forced photometry with an input noise image
EXAMPLE A : Make a psf model
import getpsf import aper import numpy as np # load FITS image and specify PSF star coordinates image = pyfits.getdata(fits_filename) xpos,ypos = np.array([1450,1400]),np.array([1550,1600]) # run aper to get mags and sky values for specified coords mag,magerr,flux,fluxerr,sky,skyerr,badflag,outstr = \ aper.aper(image,xpos,ypos,phpadu=1,apr=5,zeropoint=25, skyrad=[40,50],badpix=[-12000,60000],exact=True) # use the stars at those coords to generate a PSF model gauss,psf,psfmag = \ getpsf.getpsf(image,xpos,ypos, mag,sky,1,1,np.arange(len(xpos)), 5,'output_psf.fits')EXAMPLE B : fit a psf to isolated stars
import pyfits from PythonPhot import pkfit # read in the fits images containing the target sources image = pyfits.getdata(fits_filename) noiseim = pyfits.getdata(fits_noise_filename) maskim = pyfits.getdata(fits_mask_filename) # read in the fits image containing the PSF (gaussian model # parameters and 2-d residuals array. psf = pyfits.getdata(psf_filename) hpsf = pyfits.getheader(psf_filename) gauss = [hpsf['GAUSS1'],hpsf['GAUSS2'],hpsf['GAUSS3'],hpsf['GAUSS4'],hpsf['GAUSS5']] # x and y points for PSF fitting xpos,ypos = np.array([1450,1400]),np.array([1550,1600]) # run 'aper' on x,y coords to get sky values mag,magerr,flux,fluxerr,sky,skyerr,badflag,outstr = \ aper.aper(image,xpos,ypos,phpadu=1,apr=5,zeropoint=25, skyrad=[40,50],badpix=[-12000,60000],exact=True) # load the pkfit class pk = pkfit.pkfit_class(image,gauss,psf,1,1,noiseim,maskim) # do the PSF fitting for x,y,s in zip(xpos,ypos,sky): errmag,chi,sharp,niter,scale = \ pk.pkfit_norecent_noise(1,x,y,s,5) flux = scale*10**(0.4*(25.-hpsf['PSFMAG'])) dflux = errmag*10**(0.4*(25.-hpsf['PSFMAG'])) print('PSF fit to coords %.2f,%.2f gives flux %s +/- %s'%(x,y,flux,dflux))
