def test_io(self):
# Write PsfExModel to disk, then read and check consistency.
import tempfile
f, tmpfn = tempfile.mkstemp(suffix='.fits')
os.close(f)
self.psf.psfex.writeto(tmpfn)
print('Wrote', tmpfn)
# Read
mod = PsfExModel(fn=tmpfn)
psf = PixelizedPsfEx(None, psfex=mod)
orig_im = self.psf.getImage(0., 0.)
im = psf.getImage(0., 0.)
self.assertEqual(np.max(np.abs(orig_im - im)), 0.)
os.unlink(tmpfn)
def read_psf_model(self,
x0,
y0,
gaussPsf=False,
pixPsf=False,
const2psf=False,
psf_sigma=1.,
cx=0,
cy=0):
psffn = None
if gaussPsf:
from tractor.basics import GaussianMixturePSF
v = psf_sigma**2
psf = GaussianMixturePSF(1., 0., 0., v, v, 0.)
print('WARNING: using mock PSF:', psf)
psf.version = '0'
psf.plver = ''
elif pixPsf:
# spatially varying pixelized PsfEx
from tractor.psfex import PixelizedPsfEx
print('Reading PsfEx model from', self.psffn)
psf = PixelizedPsfEx(self.psffn)
psf.shift(x0, y0)
psffn = self.psffn
elif const2psf:
from tractor.psfex import PsfExModel
from tractor.basics import GaussianMixtureEllipsePSF
# 2-component constant MoG.
print('Reading PsfEx model from', self.psffn)
psffn = self.psffn
psfex = PsfExModel(self.psffn)
psfim = psfex.at(cx, cy)
psfim = psfim[5:-5, 5:-5]
print('Fitting PsfEx model as 2-component Gaussian...')
psf = GaussianMixtureEllipsePSF.fromStamp(psfim, N=2)
del psfim
del psfex
else:
assert (False)
print('Using PSF model', psf)
if psffn is not None:
hdr = fitsio.read_header(psffn)
psf.version = hdr.get('LEGSURV', None)
if psf.version is None:
psf.version = str(os.stat(psffn).st_mtime)
psf.plver = hdr.get('PLVER', '').strip()
return psf
def read_psf_model(self,
x0,
y0,
gaussPsf=False,
pixPsf=False,
hybridPsf=False,
psf_sigma=1.,
cx=0,
cy=0):
assert (gaussPsf or pixPsf or hybridPsf)
psffn = None
if gaussPsf:
from tractor.basics import GaussianMixturePSF
v = psf_sigma**2
psf = GaussianMixturePSF(1., 0., 0., v, v, 0.)
print('WARNING: using mock PSF:', psf)
psf.version = '0'
psf.plver = ''
else:
# spatially varying pixelized PsfEx
from tractor.psfex import PixelizedPsfEx
print('Reading PsfEx model from', self.psffn)
psf = PixelizedPsfEx(self.psffn)
psf.shift(x0, y0)
psffn = self.psffn
if hybridPsf:
from tractor.psf import HybridPixelizedPSF
psf = HybridPixelizedPSF(psf)
print('Using PSF model', psf)
if psffn is not None:
hdr = fitsio.read_header(psffn)
psf.version = hdr.get('LEGSURV', None)
if psf.version is None:
psf.version = str(os.stat(psffn).st_mtime)
psf.plver = hdr.get('PLVER', '').strip()
return psf
def psf_residuals(expnum,
ccdname,
stampsize=35,
nstar=30,
magrange=(13, 17),
verbose=0,
splinesky=False):
# Set the debugging level.
if verbose == 0:
lvl = logging.INFO
else:
lvl = logging.DEBUG
logging.basicConfig(level=lvl, format='%(message)s', stream=sys.stdout)
pngprefix = 'qapsf-{}-{}'.format(expnum, ccdname)
# Gather all the info we need about this CCD.
decals = Decals()
ccd = decals.find_ccds(expnum=expnum, ccdname=ccdname)[0]
band = ccd.filter
ps1band = dict(g=0, r=1, i=2, z=3, Y=4)
print('Band {}'.format(band))
#scales = dict(g=0.0066, r=0.01, z=0.025)
#vmin, vmax = np.arcsinh(-1), np.arcsinh(100)
#print(scales[band])
im = decals.get_image_object(ccd)
iminfo = im.get_image_info()
H, W = iminfo['dims']
wcs = im.get_wcs()
# Choose a uniformly selected subset of PS1 stars on this CCD.
ps1 = ps1cat(ccdwcs=wcs)
cat = ps1.get_stars(band=band, magrange=magrange)
rand = np.random.RandomState(seed=expnum * ccd.ccdnum)
these = rand.choice(len(cat) - 1, nstar, replace=False)
#these = rand.random_integers(0,len(cat)-1,nstar)
cat = cat[these]
cat = cat[np.argsort(cat.median[:, ps1band[band]])] # sort by magnitude
#print(cat.nmag_ok)
get_tim_kwargs = dict(const2psf=True, splinesky=splinesky)
# Make a QAplot of the positions of all the stars.
tim = im.get_tractor_image(**get_tim_kwargs)
img = tim.getImage()
#img = tim.getImage()/scales[band]
fig = plt.figure(figsize=(5, 10))
ax = fig.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
#ax.imshow(np.arcsinh(img),cmap='gray',interpolation='nearest',
# origin='lower',vmin=vmax,vmax=vmax)
ax.imshow(img, **tim.ima)
ax.axis('off')
ax.set_title('{}: {}/{} AM={:.2f} Seeing={:.3f}"'.format(
band, expnum, ccdname, ccd.airmass, ccd.seeing))
for istar, ps1star in enumerate(cat):
ra, dec = (ps1star.ra, ps1star.dec)
ok, xpos, ypos = wcs.radec2pixelxy(ra, dec)
ax.text(xpos,
ypos,
'{:2d}'.format(istar + 1),
color='red',
horizontalalignment='left')
circ = plt.Circle((xpos, ypos), radius=30, color='g', fill=False, lw=1)
ax.add_patch(circ)
#radec = wcs.radec_bounds()
#ax.scatter(cat.ra,cat.dec)
#ax.set_xlim([radec[1],radec[0]])#*[1.0002,0.9998])
#ax.set_ylim([radec[2],radec[3]])#*[0.985,1.015])
#ax.set_xlabel('$RA\ (deg)$',fontsize=18)
#ax.set_ylabel('$Dec\ (deg)$',fontsize=18)
fig.savefig(pngprefix + '-ccd.png', bbox_inches='tight')
# Initialize the many-stamp QAplot
ncols = 3
nrows = np.ceil(nstar / ncols).astype('int')
inchperstamp = 2.0
fig = plt.figure(figsize=(inchperstamp * 3 * ncols, inchperstamp * nrows))
irow = 0
icol = 0
for istar, ps1star in enumerate(cat):
ra, dec = (ps1star.ra, ps1star.dec)
mag = ps1star.median[ps1band[band]] # r-band
ok, xpos, ypos = wcs.radec2pixelxy(ra, dec)
ix, iy = int(xpos), int(ypos)
# create a little tractor Image object around the star
slc = (slice(max(iy - stampsize, 0), min(iy + stampsize + 1, H)),
slice(max(ix - stampsize, 0), min(ix + stampsize + 1, W)))
# The PSF model 'const2Psf' is the one used in DR1: a 2-component
# Gaussian fit to PsfEx instantiated in the image center.
tim = im.get_tractor_image(slc=slc, **get_tim_kwargs)
stamp = tim.getImage()
ivarstamp = tim.getInvvar()
# Initialize a tractor PointSource from PS1 measurements
flux = NanoMaggies.magToNanomaggies(mag)
star = PointSource(RaDecPos(ra, dec), NanoMaggies(**{band: flux}))
# Fit just the source RA,Dec,flux.
tractor = Tractor([tim], [star])
tractor.freezeParam('images')
print('2-component MOG:', tim.psf)
tractor.printThawedParams()
for step in range(50):
dlnp, X, alpha = tractor.optimize()
if dlnp < 0.1:
break
print('Fit:', star)
model_mog = tractor.getModelImage(0)
chi2_mog = -2.0 * tractor.getLogLikelihood()
mag_mog = NanoMaggies.nanomaggiesToMag(star.brightness)[0]
# Now change the PSF model to a pixelized PSF model from PsfEx instantiated
# at this place in the image.
psf = PixelizedPsfEx(im.psffn)
tim.psf = psf.constantPsfAt(xpos, ypos)
#print('PSF model:', tim.psf)
#tractor.printThawedParams()
for step in range(50):
dlnp, X, alpha = tractor.optimize()
if dlnp < 0.1:
break
print('Fit:', star)
model_psfex = tractor.getModelImage(0)
chi2_psfex = -2.0 * tractor.getLogLikelihood()
mag_psfex = NanoMaggies.nanomaggiesToMag(star.brightness)[0]
#mn, mx = np.percentile((stamp-model_psfex)[ivarstamp>0],[1,95])
sig = np.std((stamp - model_psfex)[ivarstamp > 0])
mn, mx = [-2.0 * sig, 5 * sig]
# Generate a QAplot.
if (istar > 0) and (istar % (ncols) == 0):
irow = irow + 1
icol = 3 * istar - 3 * ncols * irow
#print(istar, irow, icol, icol+1, icol+2)
ax1 = plt.subplot2grid((nrows, 3 * ncols), (irow, icol),
aspect='equal')
ax1.axis('off')
#ax1.imshow(stamp, **tim.ima)
ax1.imshow(stamp,
cmap='gray',
interpolation='nearest',
origin='lower',
vmin=mn,
vmax=mx)
ax1.text(0.1,
0.9,
'{:2d}'.format(istar + 1),
color='white',
horizontalalignment='left',
verticalalignment='top',
transform=ax1.transAxes)
ax2 = plt.subplot2grid((nrows, 3 * ncols), (irow, icol + 1),
aspect='equal')
ax2.axis('off')
#ax2.imshow(stamp-model_mog, **tim.ima)
ax2.imshow(stamp - model_mog,
cmap='gray',
interpolation='nearest',
origin='lower',
vmin=mn,
vmax=mx)
ax2.text(0.1,
0.9,
'MoG',
color='white',
horizontalalignment='left',
verticalalignment='top',
transform=ax2.transAxes)
ax2.text(0.08,
0.08,
'{:.3f}'.format(mag_mog),
color='white',
horizontalalignment='left',
verticalalignment='bottom',
transform=ax2.transAxes)
#ax2.set_title('{:.3f}, {:.2f}'.format(mag_psfex,chi2_psfex),fontsize=14)
#ax2.set_title('{:.3f}, $\chi^{2}$={:.2f}'.format(mag_psfex,chi2_psfex))
ax3 = plt.subplot2grid((nrows, 3 * ncols), (irow, icol + 2),
aspect='equal')
ax3.axis('off')
#ax3.imshow(stamp-model_psfex, **tim.ima)
ax3.imshow(stamp - model_psfex,
cmap='gray',
interpolation='nearest',
origin='lower',
vmin=mn,
vmax=mx)
ax3.text(0.1,
0.9,
'PSFEx',
color='white',
horizontalalignment='left',
verticalalignment='top',
transform=ax3.transAxes)
ax3.text(0.08,
0.08,
'{:.3f}'.format(mag_psfex),
color='white',
horizontalalignment='left',
verticalalignment='bottom',
transform=ax3.transAxes)
if istar == (nstar - 1):
break
fig.savefig(pngprefix + '-stargrid.png', bbox_inches='tight')
def main():
# Where are the data?
datadir = os.path.join(os.path.dirname(__file__), 'data-decam')
name = 'decam-520206-S16'
imagefn = os.path.join(datadir, '%s-image-sub.fits' % name)
invvarfn = os.path.join(datadir, '%s-invvar-sub.fits' % name)
psfexfn = os.path.join(datadir, '%s-psfex.fits' % name)
catfn = os.path.join(datadir, 'tractor-1816p325-sub.fits')
# Read the image and inverse-variance maps.
image = fitsio.read(imagefn)
invvar = fitsio.read(invvarfn)
# The DECam inverse-variance maps are unfortunately corrupted
# by fpack, causing zeros to become negative. Fix those.
invvar[invvar < np.median(invvar) * 0.1] = 0.
H, W = image.shape
print('Subimage size:', image.shape)
# For the PSF model, we need to know what subimage region this is:
subimage_offset = (35, 1465)
# We also need the calibrated zeropoint.
zeropoint = 24.7787
# What filter was this image taken in? (z)
prim_header = fitsio.read_header(imagefn)
band = prim_header['FILTER'].strip()[0]
print('Band:', band)
# These DECam images were calibrated so that the zeropoints need
# an exposure-time factor, so add that in.
exptime = prim_header['EXPTIME']
zeropoint += 2.5 * np.log10(exptime)
# Read the PsfEx model file
psf = PixelizedPsfEx(psfexfn)
# Instantiate a constant pixelized PSF at the image center
# (of the subimage)
x0, y0 = subimage_offset
psf = psf.constantPsfAt(x0 + W / 2., y0 + H / 2.)
# Load the WCS model from the header
# We convert from the RA---TPV type to RA---SIP
header = fitsio.read_header(imagefn, ext=1)
wcsobj = wcs_pv2sip_hdr(header, stepsize=10)
# We'll just use a rough sky estimate...
skyval = np.median(image)
# Create the Tractor Image (tim).
tim = Image(data=image,
invvar=invvar,
psf=psf,
wcs=ConstantFitsWcs(wcsobj),
sky=ConstantSky(skyval),
photocal=LinearPhotoCal(
NanoMaggies.zeropointToScale(zeropoint), band=band))
# Read the official DECaLS DR3 catalog -- it has only two sources in this subimage.
catalog = fits_table(catfn)
print('Read', len(catalog), 'sources')
print('Source types:', catalog.type)
# Create Tractor sources corresponding to these two catalog
# entries.
# In DECaLS, the "SIMP" type is a round Exponential galaxy with a
# fixed 0.45" radius, but we'll treat it as a general Exp galaxy.
sources = []
for c in catalog:
# Create a "position" object given the catalog RA,Dec
position = RaDecPos(c.ra, c.dec)
# Create a "brightness" object; in the catalog, the fluxes are
# stored in a [ugrizY] array, so pull out the right index
band_index = 'ugrizY'.index(band)
flux = c.decam_flux[band_index]
brightness = NanoMaggies(**{band: flux})
# Depending on the source classification in the catalog, pull
# out different fields for the galaxy shape, and for the
# galaxy type. The DECaLS catalogs, conveniently, store
# galaxy shapes as (radius, e1, e2) ellipses.
if c.type.strip() == 'DEV':
shape = EllipseE(c.shapedev_r, c.shapedev_e1, c.shapedev_e2)
galclass = DevGalaxy
elif c.type.strip() == 'SIMP':
shape = EllipseE(c.shapeexp_r, c.shapeexp_e1, c.shapeexp_e2)
galclass = ExpGalaxy
else:
assert (False)
# Create the tractor galaxy object
source = galclass(position, brightness, shape)
print('Created', source)
sources.append(source)
# Create the Tractor object -- a list of tractor Images and a list of tractor sources.
tractor = Tractor([tim], sources)
# Render the initial model image.
print('Getting initial model...')
mod = tractor.getModelImage(0)
make_plot(tim, mod, 'Initial Scene', 'mod0.png')
# Instantiate a new source at the location of the unmodelled peak.
print('Adding new source...')
# Find the peak very naively...
ipeak = np.argmax((image - mod) * tim.inverr)
iy, ix = np.unravel_index(ipeak, tim.shape)
print('Residual peak at', ix, iy)
# Compute the RA,Dec location of the peak...
radec = tim.getWcs().pixelToPosition(ix, iy)
print('RA,Dec', radec)
# Try modelling it as a point source.
# We'll initialize the brightness arbitrarily to 1 nanomaggy (= mag 22.5)
brightness = NanoMaggies(**{band: 1.})
source = PointSource(radec, brightness)
# Add it to the catalog!
tractor.catalog.append(source)
# Render the new model image with this source added.
mod = tractor.getModelImage(0)
make_plot(tim, mod, 'New Source (Before Fit)', 'mod1.png')
print('Fitting new source...')
# Now we're going to fit for the properties of the new source we
# added.
# We don't want to fit for any of the image calibration properties:
tractor.freezeParam('images')
# And we don't (yet) want to fit the existing sources. The new
# source is index number 2, so freeze everything else in the catalog.
tractor.catalog.freezeAllBut(2)
print('Fitting parameters:')
tractor.printThawedParams()
# Do the actual optimization:
tractor.optimize_loop()
mod = tractor.getModelImage(0)
make_plot(tim, mod, 'New Source Fit', 'mod2.png')
print('Fitting sources simultaneously...')
# Now let's unfreeze all the sources and fit them simultaneously.
tractor.catalog.thawAllParams()
tractor.printThawedParams()
tractor.optimize_loop()
mod = tractor.getModelImage(0)
make_plot(tim, mod, 'Simultaneous Fit', 'mod3.png')
def psf(self, ext):
path = os.path.join(self.sxdir, self.psf_name)
return PixelizedPsfEx(path)
def psf_residuals(expnum,ccdname,stampsize=35,nstar=30,
magrange=(13,17),verbose=0):
# Set the debugging level.
if verbose==0:
lvl = logging.INFO
else:
lvl = logging.DEBUG
logging.basicConfig(level=lvl,format='%(message)s',stream=sys.stdout)
pngprefix = 'qapsf-{}-{}'.format(expnum,ccdname)
# Gather all the info we need about this CCD.
decals = Decals()
ccd = decals.find_ccds(expnum=expnum,ccdname=ccdname)[0]
band = ccd.filter
ps1band = dict(g=0,r=1,i=2,z=3,Y=4)
print('Band {}'.format(band))
#scales = dict(g=0.0066, r=0.01, z=0.025)
#vmin, vmax = np.arcsinh(-1), np.arcsinh(100)
#print(scales[band])
im = DecamImage(decals,ccd)
iminfo = im.get_image_info()
H,W = iminfo['dims']
wcs = im.get_wcs()
# Choose a uniformly selected subset of PS1 stars on this CCD.
ps1 = ps1cat(ccdwcs=wcs)
cat = ps1.get_stars(band=band,magrange=magrange)
rand = np.random.RandomState(seed=expnum*ccd.ccdnum)
these = rand.choice(len(cat)-1,nstar,replace=False)
#these = rand.random_integers(0,len(cat)-1,nstar)
cat = cat[these]
cat = cat[np.argsort(cat.median[:,ps1band[band]])] # sort by magnitude
#print(cat.nmag_ok)
# Make a QAplot of the positions of all the stars.
tim = im.get_tractor_image(const2psf=True)
img = tim.getImage()
#img = tim.getImage()/scales[band]
fig = plt.figure(figsize=(5,10))
ax = fig.gca()
ax.get_xaxis().get_major_formatter().set_useOffset(False)
#ax.imshow(np.arcsinh(img),cmap='gray',interpolation='nearest',
# origin='lower',vmin=vmax,vmax=vmax)
ax.imshow(img, **tim.ima)
ax.axis('off')
ax.set_title('{}: {}/{} AM={:.2f} Seeing={:.3f}"'.
format(band,expnum,ccdname,ccd.airmass,ccd.seeing))
for istar, ps1star in enumerate(cat):
ra, dec = (ps1star.ra, ps1star.dec)
ok, xpos, ypos = wcs.radec2pixelxy(ra, dec)
ax.text(xpos,ypos,'{:2d}'.format(istar+1),color='red',
horizontalalignment='left')
circ = plt.Circle((xpos,ypos),radius=30,color='g',fill=False,lw=1)
ax.add_patch(circ)
#radec = wcs.radec_bounds()
#ax.scatter(cat.ra,cat.dec)
#ax.set_xlim([radec[1],radec[0]])#*[1.0002,0.9998])
#ax.set_ylim([radec[2],radec[3]])#*[0.985,1.015])
#ax.set_xlabel('$RA\ (deg)$',fontsize=18)
#ax.set_ylabel('$Dec\ (deg)$',fontsize=18)
fig.savefig(pngprefix+'-ccd.png',bbox_inches='tight')
# Initialize the many-stamp QAplot
ncols = 3
nrows = np.ceil(nstar/ncols).astype('int')
inchperstamp = 2.0
fig = plt.figure(figsize=(inchperstamp*3*ncols,inchperstamp*nrows))
irow = 0
icol = 0
for istar, ps1star in enumerate(cat):
ra, dec = (ps1star.ra, ps1star.dec)
mag = ps1star.median[ps1band[band]] # r-band
ok, xpos, ypos = wcs.radec2pixelxy(ra, dec)
ix,iy = int(xpos), int(ypos)
# create a little tractor Image object around the star
slc = (slice(max(iy-stampsize, 0), min(iy+stampsize+1, H)),
slice(max(ix-stampsize, 0), min(ix+stampsize+1, W)))
# The PSF model 'const2Psf' is the one used in DR1: a 2-component
# Gaussian fit to PsfEx instantiated in the image center.
tim = im.get_tractor_image(slc=slc, const2psf=True)
stamp = tim.getImage()
ivarstamp = tim.getInvvar()
# Initialize a tractor PointSource from PS1 measurements
flux = NanoMaggies.magToNanomaggies(mag)
star = PointSource(RaDecPos(ra,dec), NanoMaggies(**{band: flux}))
# Fit just the source RA,Dec,flux.
tractor = Tractor([tim], [star])
tractor.freezeParam('images')
print('2-component MOG:', tim.psf)
tractor.printThawedParams()
for step in range(50):
dlnp,X,alpha = tractor.optimize()
if dlnp < 0.1:
break
print('Fit:', star)
model_mog = tractor.getModelImage(0)
chi2_mog = -2.0*tractor.getLogLikelihood()
mag_mog = NanoMaggies.nanomaggiesToMag(star.brightness)[0]
# Now change the PSF model to a pixelized PSF model from PsfEx instantiated
# at this place in the image.
psf = PixelizedPsfEx(im.psffn)
tim.psf = psf.constantPsfAt(xpos, ypos)
#print('PSF model:', tim.psf)
#tractor.printThawedParams()
for step in range(50):
dlnp,X,alpha = tractor.optimize()
if dlnp < 0.1:
break
print('Fit:', star)
model_psfex = tractor.getModelImage(0)
chi2_psfex = -2.0*tractor.getLogLikelihood()
mag_psfex = NanoMaggies.nanomaggiesToMag(star.brightness)[0]
#mn, mx = np.percentile((stamp-model_psfex)[ivarstamp>0],[1,95])
sig = np.std((stamp-model_psfex)[ivarstamp>0])
mn, mx = [-2.0*sig,5*sig]
# Generate a QAplot.
if (istar>0) and (istar%(ncols)==0):
irow = irow+1
icol = 3*istar - 3*ncols*irow
#print(istar, irow, icol, icol+1, icol+2)
ax1 = plt.subplot2grid((nrows,3*ncols), (irow,icol), aspect='equal')
ax1.axis('off')
#ax1.imshow(stamp, **tim.ima)
ax1.imshow(stamp,cmap='gray',interpolation='nearest',
origin='lower',vmin=mn,vmax=mx)
ax1.text(0.1,0.9,'{:2d}'.format(istar+1),color='white',
horizontalalignment='left',verticalalignment='top',
transform=ax1.transAxes)
ax2 = plt.subplot2grid((nrows,3*ncols), (irow,icol+1), aspect='equal')
ax2.axis('off')
#ax2.imshow(stamp-model_mog, **tim.ima)
ax2.imshow(stamp-model_mog,cmap='gray',interpolation='nearest',
origin='lower',vmin=mn,vmax=mx)
ax2.text(0.1,0.9,'MoG',color='white',
horizontalalignment='left',verticalalignment='top',
transform=ax2.transAxes)
ax2.text(0.08,0.08,'{:.3f}'.format(mag_mog),color='white',
horizontalalignment='left',verticalalignment='bottom',
transform=ax2.transAxes)
#ax2.set_title('{:.3f}, {:.2f}'.format(mag_psfex,chi2_psfex),fontsize=14)
#ax2.set_title('{:.3f}, $\chi^{2}$={:.2f}'.format(mag_psfex,chi2_psfex))
ax3 = plt.subplot2grid((nrows,3*ncols), (irow,icol+2), aspect='equal')
ax3.axis('off')
#ax3.imshow(stamp-model_psfex, **tim.ima)
ax3.imshow(stamp-model_psfex,cmap='gray',interpolation='nearest',
origin='lower',vmin=mn,vmax=mx)
ax3.text(0.1,0.9,'PSFEx',color='white',
horizontalalignment='left',verticalalignment='top',
transform=ax3.transAxes)
ax3.text(0.08,0.08,'{:.3f}'.format(mag_psfex),color='white',
horizontalalignment='left',verticalalignment='bottom',
transform=ax3.transAxes)
if istar==(nstar-1):
break
fig.savefig(pngprefix+'-stargrid.png',bbox_inches='tight')
def setUp(self):
fn = os.path.join(os.path.dirname(__file__),
'psfex-decam-00392360-S31.fits')
self.psf = PixelizedPsfEx(fn)
class PsfExTest(unittest.TestCase):
def setUp(self):
fn = os.path.join(os.path.dirname(__file__),
'psfex-decam-00392360-S31.fits')
self.psf = PixelizedPsfEx(fn)
def test_tiny_image(self):
from tractor.patch import ModelMask
H, W = 1, 1
tim = Image(data=np.zeros((H, W)),
invvar=np.ones((H, W)),
psf=self.psf)
src = PointSource(PixPos(2.3, 2.4), Flux(100.))
tr = Tractor([tim], [src])
mod = tr.getModelImage(0)
assert (mod.shape == (H, W))
#
mm = ModelMask(0, 0, W, H)
#patch = src.getModelPatch(tim, modelMask=mm)
#upatch = src.getUnitFluxModelPatch(img, modelMask=mm)
psfpatch = self.psf.getPointSourcePatch(-3.1, 2.4, modelMask=mm)
# psf.getImage(px,py)
def test_shifted(self):
# Test that the PsfEx model varies spatially
# Test that the PixelizedPsfEx.getShifted() method works
# (shifted model's model at 0.,0. equals the original at dx,dy)
dx, dy = 50., 100.
psfim0 = self.psf.getImage(0., 0.)
psfim = self.psf.getImage(dx, dy)
# spatial variation
rms = np.sqrt(np.mean((psfim0 - psfim)**2))
self.assertTrue((rms > 0) * (rms < 1e-4))
# getShifted()
subpsf = self.psf.getShifted(dx, dy)
subim = subpsf.getImage(0., 0.)
rms = np.sqrt(np.mean((subim - psfim)**2))
self.assertEqual(rms, 0.)
def test_io(self):
# Write PsfExModel to disk, then read and check consistency.
import tempfile
f, tmpfn = tempfile.mkstemp(suffix='.fits')
os.close(f)
self.psf.psfex.writeto(tmpfn)
print('Wrote', tmpfn)
# Read
mod = PsfExModel(fn=tmpfn)
psf = PixelizedPsfEx(None, psfex=mod)
orig_im = self.psf.getImage(0., 0.)
im = psf.getImage(0., 0.)
self.assertEqual(np.max(np.abs(orig_im - im)), 0.)
os.unlink(tmpfn)
def test_fourier(self):
F, (cx, cy), shape, (v,
w) = self.psf.getFourierTransform(100., 100., 32)
print('F', F)
print('cx,cy', cx, cy)
print('shape', shape)
print('v, w', v, w)
if ps is not None:
import pylab as plt
from astrometry.util.plotutils import dimshow
plt.clf()
plt.subplot(1, 2, 1)
dimshow(F.real)
plt.subplot(1, 2, 2)
dimshow(F.imag)
ps.savefig()
def test_psfex(self):
if ps is not None:
from astrometry.util.plotutils import dimshow
import pylab as plt
H, W = 100, 100
cx, cy = W / 2., H / 2.
pixpsf = self.psf.constantPsfAt(cx, cy)
ph, pw = pixpsf.shape
xx, yy = np.meshgrid(np.arange(pw), np.arange(ph))
im = pixpsf.img.copy()
im /= np.sum(im)
cenx, ceny = np.sum(im * xx), np.sum(im * yy)
print('Pixpsf centroid:', cenx, ceny)
print('shape:', ph, pw)
dx, dy = cenx - pw // 2, ceny - ph // 2
print('dx,dy', dx, dy)
# gpsf = GaussianMixturePSF.fromStamp(im, N=1)
# print('Fit gpsf:', gpsf)
# self.assertTrue(np.abs(gpsf.mog.mean[0,0] - dx) < 0.1)
# self.assertTrue(np.abs(gpsf.mog.mean[0,1] - dy) < 0.1)
# self.assertTrue(np.abs(gpsf.mog.var[0,0,0] - 15.5) < 1.)
# self.assertTrue(np.abs(gpsf.mog.var[0,1,1] - 13.5) < 1.)
# self.assertTrue(np.abs(gpsf.mog.var[0,1,0] - -1) < 1.)
gpsf = GaussianMixturePSF.fromStamp(im, N=2)
print('Fit gpsf:', gpsf)
print('Params:', ', '.join(['%.1f' % p for p in gpsf.getParams()]))
pp = np.array(
[0.8, 0.2, 0.1, -0.0, 1.2, 0.2, 7.6, 6.0, -1.0, 51.6, 49.1, -1.3])
self.assertTrue(np.all(np.abs(np.array(gpsf.getParams()) - pp) < 0.1))
tim = Image(data=np.zeros((H, W)),
invvar=np.ones((H, W)),
psf=self.psf)
xx, yy = np.meshgrid(np.arange(W), np.arange(H))
star = PointSource(PixPos(cx, cy), Flux(100.))
gal = ExpGalaxy(PixPos(cx, cy), Flux(100.), EllipseE(1., 0., 0.))
tr1 = Tractor([tim], [star])
tr2 = Tractor([tim], [gal])
disable_galaxy_cache()
tim.psf = self.psf
mod = tr1.getModelImage(0)
mod1 = mod
im = mod.copy()
im /= im.sum()
cenx, ceny = np.sum(im * xx), np.sum(im * yy)
print('Star model + PsfEx centroid', cenx, ceny)
self.assertTrue(np.abs(cenx - (cx + dx)) < 0.1)
self.assertTrue(np.abs(ceny - (cy + dy)) < 0.1)
if ps is not None:
plt.clf()
dimshow(mod)
plt.title('Star model, PsfEx')
ps.savefig()
tim.psf = pixpsf
mod = tr1.getModelImage(0)
if ps is not None:
plt.clf()
dimshow(mod)
plt.title('Star model, pixpsf')
ps.savefig()
tim.psf = gpsf
mod = tr1.getModelImage(0)
mod2 = mod
if ps is not None:
plt.clf()
dimshow(mod)
plt.title('Star model, gpsf')
plt.colorbar()
ps.savefig()
plt.clf()
dimshow(mod1 - mod2)
plt.title('Star model, PsfEx - gpsf')
plt.colorbar()
ps.savefig()
# range ~ -0.15 to +0.25
self.assertTrue(np.all(np.abs(mod1 - mod2) < 0.25))
tim.psf = self.psf
mod = tr2.getModelImage(0)
mod1 = mod
im = mod.copy()
im /= im.sum()
cenx, ceny = np.sum(im * xx), np.sum(im * yy)
print('Gal model + PsfEx centroid', cenx, ceny)
self.assertTrue(np.abs(cenx - (cx + dx)) < 0.1)
self.assertTrue(np.abs(ceny - (cy + dy)) < 0.1)
if ps is not None:
plt.clf()
dimshow(mod)
plt.title('Gal model, PsfEx')
ps.savefig()
# tim.psf = pixpsf
# mod = tr2.getModelImage(0)
# plt.clf()
# dimshow(mod)
# plt.title('Gal model, pixpsf')
# ps.savefig()
tim.psf = gpsf
mod = tr2.getModelImage(0)
mod2 = mod
# range ~ -0.1 to +0.2
self.assertTrue(np.all(np.abs(mod1 - mod2) < 0.2))
if ps is not None:
plt.clf()
dimshow(mod)
plt.title('Gal model, gpsf')
ps.savefig()
plt.clf()
dimshow(mod1 - mod2)
plt.title('Gal model, PsfEx - gpsf')
plt.colorbar()
ps.savefig()