How to use drizzlepac - 10 common examples
To help you get started, we’ve selected a few drizzlepac examples, based on popular ways it is used in public projects.
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gbrammer / grizli / grizli / multifit.py View on Github 
pixel variances.
ds9: `pyds9.DS9`
Show intermediate steps of the drizzling
Returns
-------
hdu : `~astropy.io.fits.HDUList`
FITS HDUList with the drizzled 2D spectrum and weight arrays
"""
from drizzlepac.astrodrizzle import adrizzle
from astropy import log
log.setLevel('ERROR')
#log.disable_warnings_logging()
adrizzle.log.setLevel('ERROR')
NX = int(np.round(np.diff(wlimit)[0]*1.e4/dlam)) // 2
center = np.mean(wlimit[:2])*1.e4
out_header, output_wcs = utils.make_spectrum_wcsheader(center_wave=center,
dlam=dlam, NX=NX,
spatial_scale=spatial_scale, NY=NY)
sh = (out_header['NAXIS2'], out_header['NAXIS1'])
outsci = np.zeros(sh, dtype=np.float32)
outwht = np.zeros(sh, dtype=np.float32)
outctx = np.zeros(sh, dtype=np.int32)
outvar = np.zeros(sh, dtype=np.float32)
outwv = np.zeros(sh, dtype=np.float32)
outcv = np.zeros(sh, dtype=np.int32)def apply_tweak_shifts(wcs_ref, shift_dict, grism_matches={}, verbose=True):
"""
"""
from drizzlepac import updatehdr
hdu = wcs_ref.to_fits(relax=True)
file0 = list(shift_dict.keys())[0].split('.fits')[0]
tweak_file = '{0}_tweak_wcs.fits'.format(file0)
hdu.writeto(tweak_file, clobber=True)
for file in shift_dict:
updatehdr.updatewcs_with_shift(file, tweak_file,
xsh=shift_dict[file][0],
ysh=shift_dict[file][1],
rot=0., scale=1.,
wcsname='SHIFT', force=True,
reusename=True, verbose=verbose,
sciext='SCI')
### Bug in astrodrizzle? Dies if the FLT files don't have MJD-OBS
### keywords
im = pyfits.open(file, mode='update')
im[0].header['MJD-OBS'] = im[0].header['EXPSTART']
im.flush()
# Update paired grism exposures
if file in grism_matches:
for grism_file in grism_matches[file]:for drz_file in drz_files[1:]:
root = drz_file.split('_drz')[0]
result = align_drizzled_image(root=root, mag_limits=mag_limits,
radec=rd_ref,
NITER=5, clip=20)
orig_wcs, drz_wcs, out_shift, out_rot, out_scale = result
im = pyfits.open(drz_file)
files = []
for i in range(im[0].header['NDRIZIM']):
files.append(im[0].header['D{0:03d}DATA'.format(i+1)].split('[')[0])
for file in files:
updatehdr.updatewcs_with_shift(file, drz_files[0],
xsh=out_shift[0], ysh=out_shift[1],
rot=out_rot, scale=out_scale,
wcsname=ref_catalog, force=True,
reusename=True, verbose=True,
sciext='SCI')
im = pyfits.open(file, mode='update')
im[0].header['MJD-OBS'] = im[0].header['EXPSTART']
im.flush()
### Second drizzle
if len(files) > 1:
AstroDrizzle(files, output=root, clean=True, context=False, preserve=False, skysub=True, driz_separate=False, driz_sep_wcs=False, median=False, blot=False, driz_cr=False, driz_cr_corr=False, driz_combine=True, final_bits=576, coeffs=True, resetbits=0, build=False, final_wht_type='IVM')
else:
AstroDrizzle(files, output=root, clean=True, final_scale=None, final_pixfrac=1, context=False, final_bits=576, preserve=False, driz_separate=False, driz_sep_wcs=False, median=False, blot=False, driz_cr=False, driz_cr_corr=False, driz_combine=True, build=False, final_wht_type='IVM')### Contamination-cleaned
adrizzle.do_driz(beam_data, beam_wcs, wht, output_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Continuum
adrizzle.do_driz(beam_continuum, beam_wcs, wht, output_wcs,
coutsci, coutwht, coutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Contamination
adrizzle.do_driz(beam.contam, beam_wcs, wht, output_wcs,
xoutsci, xoutwht, xoutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Direct thumbnail
if direct_extension == 'REF':
if beam.direct['REF'] is None:
direct_extension = 'SCI'
if direct_extension == 'REF':
thumb = beam.direct['REF']
thumb_wht = np.cast[np.float32]((thumb != 0)*1)
else:
thumb = beam.direct[direct_extension]#/beam.direct.photflam
thumb_wht = 1./(beam.direct.data['ERR']/beam.direct.photflam)**2wht = 1./im['ERR'].data**2
wht[(im['ERR'].data == 0) | (dq > 0) | (~np.isfinite(wht))] = 0
wht[im['SCI'].data < -3*im['ERR'].data] = 0
wht = np.cast[np.float32](wht)
exp_wcs = pywcs.WCS(im[1].header, relax=True)
exp_wcs.pscale = utils.get_wcs_pscale(exp_wcs)
#pf = 0.5
# import drizzlepac.wcs_functions as dwcs
# xx = out_wcs.deepcopy()
# #xx.all_pix2world = xx.wcs_world2pix
# map = dwcs.WCSMap(exp_wcs, xx)
astrodrizzle.adrizzle.do_driz(im['SCI'].data, exp_wcs, wht,
inter_wcs, outsci, outwht, outctx,
1., 'cps', 1,
wcslin_pscale=exp_wcs.pscale,
uniqid=1,
pixfrac=pixfrac, kernel=kernel,
fillval=0, stepsize=10,
wcsmap=SIP_WCSMap)
if ds9 is not None:
ds9.view(outsci, header=outh)
#outsci /= out_wcs.pscale**2
rms = 1/np.sqrt(outwht)
mask = (outwht == 0) | (rms > 100)
rms[mask] = 0
outsci[mask] = 0.line_wcs = pywcs.WCS(h, relax=True)
line_wcs.pscale = utils.get_wcs_pscale(line_wcs)
# Science and wht arrays
sci = flt.grism['SCI'] - flt.model
wht = 1/(flt.grism['ERR']**2)
scl = np.exp(-(fcontam*np.abs(flt.model)/flt.grism['ERR']))
wht *= scl
wht[~np.isfinite(wht)] = 0
# Drizzle it
if verbose:
print('Drizzle {0} to wavelength {1:.2f}'.format(flt.grism.parent_file, wave))
adrizzle.do_driz(sci, line_wcs, wht, out_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=line_wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
# Done!
return outsci, outwhtwht[~np.isfinite(data_i+scl)] = 0
contam_weight[~np.isfinite(data_i+scl)] = 0
data_i[~np.isfinite(data_i+scl)] = 0
###### Go drizzle
### Contamination-cleaned
adrizzle.do_driz(data_i, beam_wcs, wht, output_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=1.0, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
# For variance
adrizzle.do_driz(contam_weight, beam_wcs, wht, output_wcs,
outvar, outwv, outcv, 1., 'cps', 1,
wcslin_pscale=1.0, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
if ds9 is not None:
ds9.view(outsci/output_wcs.pscale**2, header=out_header)
### Correct for drizzle scaling
outsci /= output_wcs.pscale**2
# variance
outvar /= outwv*output_wcs.pscale**2
outwht = 1/outvar
outwht[(outvar == 0) | (~np.isfinite(outwht))] = 0else:
wht *= sens**2
beam_data /= sens
beam_continuum /= sens
###### Go drizzle
### Contamination-cleaned
adrizzle.do_driz(beam_data, beam_wcs, wht, output_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Continuum
adrizzle.do_driz(beam_continuum, beam_wcs, wht, output_wcs,
coutsci, coutwht, coutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Contamination
adrizzle.do_driz(beam.contam, beam_wcs, wht, output_wcs,
xoutsci, xoutwht, xoutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Direct thumbnail
if direct_extension == 'REF':
if beam.direct['REF'] is None:
direct_extension = 'SCI'dlam = np.interp(wave, beam.beam.lam[1:], np.diff(beam.beam.lam))
# 1e-17 erg/s/cm2 #, scaling closer to e-/s
sens *= 1./dlam
if sens == 0:
continue
else:
wht *= sens**2
beam_data /= sens
beam_continuum /= sens
###### Go drizzle
### Contamination-cleaned
adrizzle.do_driz(beam_data, beam_wcs, wht, output_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Continuum
adrizzle.do_driz(beam_continuum, beam_wcs, wht, output_wcs,
coutsci, coutwht, coutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
### Contamination
adrizzle.do_driz(beam.contam, beam_wcs, wht, output_wcs,
xoutsci, xoutwht, xoutctx, 1., 'cps', 1,
wcslin_pscale=beam.grism.wcs.pscale, uniqid=1,scl = convert_to_flambda*beam.beam.total_flux/1.e-17
scl *= 1./beam.flat_flam.reshape(beam.beam.sh_beam).sum(axis=0)
#scl = convert_to_flambda/beam.beam.sensitivity
data_i *= scl
wht *= (1/scl)**2
#contam_weight *= scl
wht[~np.isfinite(data_i+scl)] = 0
contam_weight[~np.isfinite(data_i+scl)] = 0
data_i[~np.isfinite(data_i+scl)] = 0
###### Go drizzle
### Contamination-cleaned
adrizzle.do_driz(data_i, beam_wcs, wht, output_wcs,
outsci, outwht, outctx, 1., 'cps', 1,
wcslin_pscale=1.0, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
# For variance
adrizzle.do_driz(contam_weight, beam_wcs, wht, output_wcs,
outvar, outwv, outcv, 1., 'cps', 1,
wcslin_pscale=1.0, uniqid=1,
pixfrac=pixfrac, kernel=kernel, fillval=0,
stepsize=10, wcsmap=None)
if ds9 is not None:
ds9.view(outsci/output_wcs.pscale**2, header=out_header)
### Correct for drizzle scalingdrizzlepac
HST image combination using the drizzle algorithm to combine astronomical images, to model image distortion, to remove cosmic rays, and generally to improve the fidelity of data in the final image.
Package Health Score
84 / 100Popular drizzlepac functions
- drizzlepac.adrizzle
- drizzlepac.adrizzle.do_driz.__class__
- drizzlepac.astrodrizzle
- drizzlepac.astrodrizzle.ablot
- drizzlepac.astrodrizzle.adrizzle
- drizzlepac.astrodrizzle.adrizzle.do_driz
- drizzlepac.astrodrizzle.adrizzle.log
- drizzlepac.astrodrizzle.adrizzle.log.setLevel
- drizzlepac.astrodrizzle.AstroDrizzle
- drizzlepac.updatehdr
- drizzlepac.updatehdr.updatewcs_with_shift