def test_turbo_with_image(self):
"""
Test do_driz turbo kernel
"""
input = os.path.basename(self.get_input_file('input', 'j8bt06nyq_unit.fits'))
output = 'output_turbo_image.fits'
output_template = os.path.basename(self.get_data('truth',
'reference_turbo_image.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
inwht = np.ones(insci.shape,dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1 = output_wcs._naxis1
naxis2 = output_wcs._naxis2
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs],undistort=False)
adrizzle.do_driz(insci, input_wcs, inwht, output_wcs, outsci,
outwht, outcon, expin, in_units, wt_scl,
kernel='turbo', wcslin_pscale=wcslin.pscale)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
self.ignore_keywords += ['rootname']
self.compare_outputs([(output, output_template)])
def test_square_with_point(self):
"""
Test do_driz square kernel with point
"""
input = os.path.basename(
self.get_input_file('input', 'j8bt06nyq_flt.fits'))
output = 'output_square_point.fits'
output_difference = os.path.basename(
self.get_data('truth', 'difference_square_point.txt'))
output_template = os.path.basename(
self.get_data('truth', 'reference_square_point.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
insci = self.make_point_image(insci, (500, 200), 100.0)
inwht = np.ones(insci.shape, dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1 = output_wcs._naxis1
naxis2 = output_wcs._naxis2
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs], undistort=False)
adrizzle.do_driz(insci,
input_wcs,
inwht,
output_wcs,
outsci,
outwht,
outcon,
expin,
in_units,
wt_scl,
wcslin_pscale=wcslin.pscale)
output_bounds = self.bound_image(outsci)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
template_bounds = self.bound_image(template_data)
(min_diff, med_diff,
max_diff) = self.centroid_statistics("square with point",
output_difference, outsci,
template_data, 20.0, 8)
assert (med_diff < 1.0e-6)
assert (max_diff < 1.0e-5)
def test_tophat_with_grid(self):
"""
Test do_driz tophat kernel with grid
"""
input = os.path.basename(
self.get_input_file('input', 'j8bt06nyq_unit.fits'))
output = 'output_tophat_grid.fits'
output_difference = os.path.basename(
self.get_data('truth', 'difference_tophat_grid.txt'))
output_template = os.path.basename(
self.get_data('truth', 'reference_tophat_grid.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
insci = self.make_grid_image(insci, 64, 100.0)
inwht = np.ones(insci.shape, dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1, naxis2 = output_wcs.pixel_shape
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs], undistort=False)
adrizzle.do_driz(insci,
input_wcs,
inwht,
output_wcs,
outsci,
outwht,
outcon,
expin,
in_units,
wt_scl,
kernel='tophat',
wcslin_pscale=wcslin.pscale)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
(min_diff, med_diff,
max_diff) = self.centroid_statistics("tophat with grid",
output_difference, outsci,
template_data, 20.0, 8)
assert (med_diff < 1.0e-6)
assert (max_diff < 1.0e-5)
def not_test_turbo_with_image(self):
"""
Test do_driz turbo kernel
"""
input = os.path.basename(
self.get_input_file('input', 'j8bt06nyq_flt.fits'))
output = 'output_turbo_image.fits'
output_difference = os.path.basename(
self.get_data('truth', 'difference_turbo_image.txt'))
output_template = os.path.basename(
self.get_data('truth', 'reference_turbo_image.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
inwht = np.ones(insci.shape, dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1 = output_wcs._naxis1
naxis2 = output_wcs._naxis2
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs], undistort=False)
adrizzle.do_driz(insci,
input_wcs,
inwht,
output_wcs,
outsci,
outwht,
outcon,
expin,
in_units,
wt_scl,
kernel='turbo',
wcslin_pscale=wcslin.pscale)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
self.compare_outputs([(output, output_template)])
def test_square_with_image(self):
"""
Test do_driz square kernel
"""
input = os.path.basename(
self.get_input_file('input', 'j8bt06nyq_unit.fits'))
output = 'output_square_image.fits'
output_template = os.path.basename(
self.get_data('truth', 'reference_square_image.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
inwht = np.ones(insci.shape, dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1, naxis2 = output_wcs.pixel_shape
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs], undistort=False)
adrizzle.do_driz(insci,
input_wcs,
inwht,
output_wcs,
outsci,
outwht,
outcon,
expin,
in_units,
wt_scl,
wcslin_pscale=wcslin.pscale)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
self.ignore_keywords += ['rootname']
self.compare_outputs([(output, output_template)])
def test_turbo_with_grid(self):
"""
Test do_driz turbo kernel with grid
"""
input = os.path.basename(self.get_input_file('input','j8bt06nyq_unit.fits'))
output = 'output_turbo_grid.fits'
output_difference = os.path.basename(self.get_data('truth',
'difference_turbo_grid.txt'))
output_template = os.path.basename(self.get_data('truth',
'reference_turbo_grid.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
insci = self.make_grid_image(insci, 64, 100.0)
inwht = np.ones(insci.shape,dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1 = output_wcs._naxis1
naxis2 = output_wcs._naxis2
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs],undistort=False)
adrizzle.do_driz(insci, input_wcs, inwht,
output_wcs, outsci, outwht, outcon,
expin, in_units, wt_scl,
kernel='turbo', wcslin_pscale=wcslin.pscale)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
(min_diff, med_diff, max_diff) = self.centroid_statistics("turbo with grid", output_difference,
outsci, template_data, 20.0, 8)
assert(med_diff < 1.0e-6)
assert(max_diff < 1.0e-5)
def test_square_with_point(self):
"""
Test do_driz square kernel with point
"""
input = os.path.basename(self.get_input_file('input','j8bt06nyq_unit.fits'))
output = 'output_square_point.fits'
output_difference = 'difference_square_point.txt'
output_template = os.path.basename(self.get_data('truth',
'reference_square_point.fits'))
insci = self.read_image(input)
input_wcs = self.read_wcs(input)
insci = self.make_point_image(insci, (500, 200), 100.0)
inwht = np.ones(insci.shape,dtype=insci.dtype)
output_wcs = self.read_wcs(output_template)
naxis1, naxis2 = output_wcs.pixel_shape
outsci = np.zeros((naxis2, naxis1), dtype='float32')
outwht = np.zeros((naxis2, naxis1), dtype='float32')
outcon = np.zeros((1, naxis2, naxis1), dtype='i4')
expin = 1.0
wt_scl = expin
in_units = 'cps'
wcslin = distortion.utils.output_wcs([input_wcs],undistort=False)
adrizzle.do_driz(insci, input_wcs, inwht,
output_wcs, outsci, outwht, outcon,
expin, in_units, wt_scl, wcslin_pscale=wcslin.pscale)
output_bounds = self.bound_image(outsci)
self.write_image(output, output_wcs, outsci, outwht, outcon[0])
template_data = self.read_image(output_template)
template_bounds = self.bound_image(template_data)
(min_diff, med_diff, max_diff) = self.centroid_statistics("square with point", output_difference,
outsci, template_data, 20.0, 8)
assert(med_diff < 1.0e-6)
assert(max_diff < 1.0e-5)
def get_psf(self,
ra=53.06967306,
dec=-27.72333015,
filter='F140W',
pixfrac=0.1,
kernel='point',
verbose=True,
wcs_slice=None,
get_extended=True,
get_weight=False):
from drizzlepac import adrizzle
from shapely.geometry import Polygon, Point
pix = np.arange(-13, 14)
#wcs_slice = self.get_driz_cutout(ra=ra, dec=dec)
if wcs_slice is None:
wcs_slice = self.driz_wcs.copy()
outsci, outwht, outctx = self._get_empty_driz(wcs_slice)
count = 1
for key in self.flt_keys:
if self.footprint[key].contains(Point(ra, dec)):
file, ext = key
if verbose:
print('{0}[SCI,{1}]'.format(file, ext))
xy = self.wcs[key].all_world2pix(np.array([[ra, dec]]), 0)[0]
xyp = np.cast[int](xy) # +1
dx = xy[0] - int(xy[0])
dy = xy[1] - int(xy[1])
if ext == 2:
# UVIS
# print('UVIS1!')
chip_offset = 2051
else:
chip_offset = 0
psf_xy = self.ePSF.get_at_position(xy[0],
xy[1] + chip_offset,
filter=filter)
yp, xp = np.meshgrid(pix - dy,
pix - dx,
sparse=False,
indexing='ij')
if get_extended:
extended_data = self.ePSF.extended_epsf[filter]
else:
extended_data = None
psf = self.ePSF.eval_ePSF(psf_xy,
xp,
yp,
extended_data=extended_data)
# if get_weight:
# fltim = pyfits.open(file)
# flt_weight = fltim[0].header['EXPTIME']
# else:
# flt_weight = 1
flt_weight = self.wcs[key].expweight
N = 13
psf_wcs = model.ImageData.get_slice_wcs(
self.wcs[key], slice(xyp[0] - N, xyp[0] + N + 1),
slice(xyp[1] - N, xyp[1] + N + 1))
psf_wcs.pscale = utils.get_wcs_pscale(self.wcs[key])
try:
adrizzle.do_driz(psf,
psf_wcs,
psf * 0 + flt_weight,
wcs_slice,
outsci,
outwht,
outctx,
1.,
'cps',
1,
wcslin_pscale=1.,
uniqid=1,
pixfrac=pixfrac,
kernel=kernel,
fillval=0,
stepsize=10,
wcsmap=None)
except:
psf_wcs._naxis1, psf_wcs._naxis2 = psf_wcs._naxis
adrizzle.do_driz(psf,
psf_wcs,
psf * 0 + flt_weight,
wcs_slice,
outsci,
outwht,
outctx,
1.,
'cps',
1,
wcslin_pscale=1.,
uniqid=1,
pixfrac=pixfrac,
kernel=kernel,
fillval=0,
stepsize=10,
wcsmap=None)
if False:
count += 1
hdu = pyfits.HDUList([
pyfits.PrimaryHDU(),
pyfits.ImageHDU(data=psf * 100,
header=utils.to_header(psf_wcs))
])
ds9.set('frame {0}'.format(count + 1))
ds9.set_pyfits(hdu)
#ss = 1000000/2
ss = 1. / outsci.sum()
hdu = pyfits.HDUList([
pyfits.PrimaryHDU(),
pyfits.ImageHDU(data=outsci * ss,
header=utils.to_header(wcs_slice))
])
if False:
ds9.set('frame 2')
ds9.set_pyfits(hdu)
return hdu
def get_psf(self, ra=53.06967306, dec=-27.72333015, filter='F140W', pixfrac=0.1, kernel='point', verbose=True, wcs_slice=None, get_extended=True, get_weight=False):
from drizzlepac import adrizzle
from shapely.geometry import Polygon, Point
pix = np.arange(-13,14)
#wcs_slice = self.get_driz_cutout(ra=ra, dec=dec)
outsci, outwht, outctx = self._get_empty_driz(wcs_slice)
count = 1
for key in self.flt_keys:
if self.footprint[key].contains(Point(ra, dec)):
file, ext = key
if verbose:
print('{0}[SCI,{1}]'.format(file, ext))
xy = self.wcs[key].all_world2pix(np.array([[ra,dec]]), 0)[0]
xyp = np.cast[int](xy)#+1
dx = xy[0]-int(xy[0])
dy = xy[1]-int(xy[1])
if ext == 2:
# UVIS
#print('UVIS1!')
chip_offset = 2051
else:
chip_offset = 0
psf_xy = self.ePSF.get_at_position(xy[0], xy[1]+chip_offset, filter=filter)
yp, xp = np.meshgrid(pix-dy, pix-dx, sparse=False, indexing='ij')
if get_extended:
extended_data = self.ePSF.extended_epsf[filter]
else:
extended_data = None
psf = self.ePSF.eval_ePSF(psf_xy, xp, yp, extended_data=extended_data)
if get_weight:
fltim = pyfits.open(file)
flt_weight = fltim[0].header['EXPTIME']
else:
flt_weight = 1
N = 13
psf_wcs = model.ImageData.get_slice_wcs(self.wcs[key], slice(xyp[0]-N, xyp[0]+N+1), slice(xyp[1]-N, xyp[1]+N+1))
psf_wcs.pscale = utils.get_wcs_pscale(self.wcs[key])
adrizzle.do_driz(psf, psf_wcs, psf*0+flt_weight, wcs_slice,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=1., uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
if False:
count += 1
hdu = pyfits.HDUList([pyfits.PrimaryHDU(), pyfits.ImageHDU(data=psf*100, header=utils.to_header(psf_wcs))])
ds9.set('frame {0}'.format(count+1))
ds9.set_pyfits(hdu)
#ss = 1000000/2
ss = 1./outsci.sum()
hdu = pyfits.HDUList([pyfits.PrimaryHDU(), pyfits.ImageHDU(data=outsci*ss, header=utils.to_header(wcs_slice))])
if False:
ds9.set('frame 2')
ds9.set_pyfits(hdu)
return hdu
