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spacetelescope/drizzlepac | drizzlepac/alignimages.py | generate_source_catalogs | def generate_source_catalogs(imglist, **pars):
"""Generates a dictionary of source catalogs keyed by image name.
Parameters
----------
imglist : list
List of one or more calibrated fits images that will be used for source detection.
Returns
-------
sourcecatalogdict : dictionary
a dictionary (keyed by image name) of two element dictionaries which in tern contain 1) a dictionary of the
detector-specific processing parameters and 2) an astropy table of position and photometry information of all
detected sources
"""
output = pars.get('output', False)
sourcecatalogdict = {}
for imgname in imglist:
log.info("Image name: {}".format(imgname))
sourcecatalogdict[imgname] = {}
# open image
imghdu = fits.open(imgname)
imgprimaryheader = imghdu[0].header
instrument = imgprimaryheader['INSTRUME'].lower()
detector = imgprimaryheader['DETECTOR'].lower()
# get instrument/detector-specific image alignment parameters
if instrument in detector_specific_params.keys():
if detector in detector_specific_params[instrument].keys():
detector_pars = detector_specific_params[instrument][detector]
# to allow generate_source_catalog to get detector specific parameters
detector_pars.update(pars)
sourcecatalogdict[imgname]["params"] = detector_pars
else:
sys.exit("ERROR! Unrecognized detector '{}'. Exiting...".format(detector))
log.error("ERROR! Unrecognized detector '{}'. Exiting...".format(detector))
else:
sys.exit("ERROR! Unrecognized instrument '{}'. Exiting...".format(instrument))
log.error("ERROR! Unrecognized instrument '{}'. Exiting...".format(instrument))
# Identify sources in image, convert coords from chip x, y form to reference WCS sky RA, Dec form.
imgwcs = HSTWCS(imghdu, 1)
fwhmpsf_pix = sourcecatalogdict[imgname]["params"]['fwhmpsf']/imgwcs.pscale #Convert fwhmpsf from arsec to pixels
sourcecatalogdict[imgname]["catalog_table"] = amutils.generate_source_catalog(imghdu, fwhm=fwhmpsf_pix, **detector_pars)
# write out coord lists to files for diagnostic purposes. Protip: To display the sources in these files in DS9,
# set the "Coordinate System" option to "Physical" when loading the region file.
imgroot = os.path.basename(imgname).split('_')[0]
numSci = amutils.countExtn(imghdu)
# Allow user to decide when and how to write out catalogs to files
if output:
for chip in range(1,numSci+1):
chip_cat = sourcecatalogdict[imgname]["catalog_table"][chip]
if chip_cat and len(chip_cat) > 0:
regfilename = "{}_sci{}_src.reg".format(imgroot, chip)
out_table = Table(chip_cat)
out_table.write(regfilename, include_names=["xcentroid", "ycentroid"], format="ascii.fast_commented_header")
log.info("Wrote region file {}\n".format(regfilename))
imghdu.close()
return(sourcecatalogdict) | python | def generate_source_catalogs(imglist, **pars):
"""Generates a dictionary of source catalogs keyed by image name.
Parameters
----------
imglist : list
List of one or more calibrated fits images that will be used for source detection.
Returns
-------
sourcecatalogdict : dictionary
a dictionary (keyed by image name) of two element dictionaries which in tern contain 1) a dictionary of the
detector-specific processing parameters and 2) an astropy table of position and photometry information of all
detected sources
"""
output = pars.get('output', False)
sourcecatalogdict = {}
for imgname in imglist:
log.info("Image name: {}".format(imgname))
sourcecatalogdict[imgname] = {}
# open image
imghdu = fits.open(imgname)
imgprimaryheader = imghdu[0].header
instrument = imgprimaryheader['INSTRUME'].lower()
detector = imgprimaryheader['DETECTOR'].lower()
# get instrument/detector-specific image alignment parameters
if instrument in detector_specific_params.keys():
if detector in detector_specific_params[instrument].keys():
detector_pars = detector_specific_params[instrument][detector]
# to allow generate_source_catalog to get detector specific parameters
detector_pars.update(pars)
sourcecatalogdict[imgname]["params"] = detector_pars
else:
sys.exit("ERROR! Unrecognized detector '{}'. Exiting...".format(detector))
log.error("ERROR! Unrecognized detector '{}'. Exiting...".format(detector))
else:
sys.exit("ERROR! Unrecognized instrument '{}'. Exiting...".format(instrument))
log.error("ERROR! Unrecognized instrument '{}'. Exiting...".format(instrument))
# Identify sources in image, convert coords from chip x, y form to reference WCS sky RA, Dec form.
imgwcs = HSTWCS(imghdu, 1)
fwhmpsf_pix = sourcecatalogdict[imgname]["params"]['fwhmpsf']/imgwcs.pscale #Convert fwhmpsf from arsec to pixels
sourcecatalogdict[imgname]["catalog_table"] = amutils.generate_source_catalog(imghdu, fwhm=fwhmpsf_pix, **detector_pars)
# write out coord lists to files for diagnostic purposes. Protip: To display the sources in these files in DS9,
# set the "Coordinate System" option to "Physical" when loading the region file.
imgroot = os.path.basename(imgname).split('_')[0]
numSci = amutils.countExtn(imghdu)
# Allow user to decide when and how to write out catalogs to files
if output:
for chip in range(1,numSci+1):
chip_cat = sourcecatalogdict[imgname]["catalog_table"][chip]
if chip_cat and len(chip_cat) > 0:
regfilename = "{}_sci{}_src.reg".format(imgroot, chip)
out_table = Table(chip_cat)
out_table.write(regfilename, include_names=["xcentroid", "ycentroid"], format="ascii.fast_commented_header")
log.info("Wrote region file {}\n".format(regfilename))
imghdu.close()
return(sourcecatalogdict) | [
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List of one or more calibrated fits images that will be used for source detection.
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spacetelescope/drizzlepac | drizzlepac/alignimages.py | update_image_wcs_info | def update_image_wcs_info(tweakwcs_output):
"""Write newly computed WCS information to image headers and write headerlet files
Parameters
----------
tweakwcs_output : list
output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image.
Returns
-------
out_headerlet_list : dictionary
a dictionary of the headerlet files created by this subroutine, keyed by flt/flc fits filename.
"""
out_headerlet_dict = {}
for item in tweakwcs_output:
imageName = item.meta['filename']
chipnum = item.meta['chip']
if chipnum == 1:
chipctr = 1
hdulist = fits.open(imageName, mode='update')
num_sci_ext = amutils.countExtn(hdulist)
# generate wcs name for updated image header, headerlet
if not hdulist['SCI',1].header['WCSNAME'] or hdulist['SCI',1].header['WCSNAME'] =="": #Just in case header value 'wcsname' is empty.
wcsName = "FIT_{}".format(item.meta['catalog_name'])
else:
wname = hdulist['sci', 1].header['wcsname']
if "-" in wname:
wcsName = '{}-FIT_{}'.format(wname[:wname.index('-')], item.meta['fit_info']['catalog'])
else:
wcsName = '{}-FIT_{}'.format(wname, item.meta['fit_info']['catalog'])
# establish correct mapping to the science extensions
sciExtDict = {}
for sciExtCtr in range(1, num_sci_ext + 1):
sciExtDict["{}".format(sciExtCtr)] = fileutil.findExtname(hdulist,'sci',extver=sciExtCtr)
# update header with new WCS info
updatehdr.update_wcs(hdulist, sciExtDict["{}".format(item.meta['chip'])], item.wcs, wcsname=wcsName,
reusename=True, verbose=True)
if chipctr == num_sci_ext:
# Close updated flc.fits or flt.fits file
#log.info("CLOSE {}\n".format(imageName)) # TODO: Remove before deployment
hdulist.flush()
hdulist.close()
# Create headerlet
out_headerlet = headerlet.create_headerlet(imageName, hdrname=wcsName, wcsname=wcsName)
# Update headerlet
update_headerlet_phdu(item, out_headerlet)
# Write headerlet
if imageName.endswith("flc.fits"):
headerlet_filename = imageName.replace("flc", "flt_hlet")
if imageName.endswith("flt.fits"):
headerlet_filename = imageName.replace("flt", "flt_hlet")
out_headerlet.writeto(headerlet_filename, clobber=True)
log.info("Wrote headerlet file {}.\n\n".format(headerlet_filename))
out_headerlet_dict[imageName] = headerlet_filename
# Attach headerlet as HDRLET extension
headerlet.attach_headerlet(imageName, headerlet_filename)
chipctr +=1
return (out_headerlet_dict) | python | def update_image_wcs_info(tweakwcs_output):
"""Write newly computed WCS information to image headers and write headerlet files
Parameters
----------
tweakwcs_output : list
output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image.
Returns
-------
out_headerlet_list : dictionary
a dictionary of the headerlet files created by this subroutine, keyed by flt/flc fits filename.
"""
out_headerlet_dict = {}
for item in tweakwcs_output:
imageName = item.meta['filename']
chipnum = item.meta['chip']
if chipnum == 1:
chipctr = 1
hdulist = fits.open(imageName, mode='update')
num_sci_ext = amutils.countExtn(hdulist)
# generate wcs name for updated image header, headerlet
if not hdulist['SCI',1].header['WCSNAME'] or hdulist['SCI',1].header['WCSNAME'] =="": #Just in case header value 'wcsname' is empty.
wcsName = "FIT_{}".format(item.meta['catalog_name'])
else:
wname = hdulist['sci', 1].header['wcsname']
if "-" in wname:
wcsName = '{}-FIT_{}'.format(wname[:wname.index('-')], item.meta['fit_info']['catalog'])
else:
wcsName = '{}-FIT_{}'.format(wname, item.meta['fit_info']['catalog'])
# establish correct mapping to the science extensions
sciExtDict = {}
for sciExtCtr in range(1, num_sci_ext + 1):
sciExtDict["{}".format(sciExtCtr)] = fileutil.findExtname(hdulist,'sci',extver=sciExtCtr)
# update header with new WCS info
updatehdr.update_wcs(hdulist, sciExtDict["{}".format(item.meta['chip'])], item.wcs, wcsname=wcsName,
reusename=True, verbose=True)
if chipctr == num_sci_ext:
# Close updated flc.fits or flt.fits file
#log.info("CLOSE {}\n".format(imageName)) # TODO: Remove before deployment
hdulist.flush()
hdulist.close()
# Create headerlet
out_headerlet = headerlet.create_headerlet(imageName, hdrname=wcsName, wcsname=wcsName)
# Update headerlet
update_headerlet_phdu(item, out_headerlet)
# Write headerlet
if imageName.endswith("flc.fits"):
headerlet_filename = imageName.replace("flc", "flt_hlet")
if imageName.endswith("flt.fits"):
headerlet_filename = imageName.replace("flt", "flt_hlet")
out_headerlet.writeto(headerlet_filename, clobber=True)
log.info("Wrote headerlet file {}.\n\n".format(headerlet_filename))
out_headerlet_dict[imageName] = headerlet_filename
# Attach headerlet as HDRLET extension
headerlet.attach_headerlet(imageName, headerlet_filename)
chipctr +=1
return (out_headerlet_dict) | [
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output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image.
Returns
-------
out_headerlet_list : dictionary
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spacetelescope/drizzlepac | drizzlepac/alignimages.py | update_headerlet_phdu | def update_headerlet_phdu(tweakwcs_item, headerlet):
"""Update the primary header data unit keywords of a headerlet object in-place
Parameters
==========
tweakwc_item :
Basically the output from tweakwcs which contains the cross match and fit
information for every chip of every valid input image.
headerlet :
object containing WCS information
"""
# Get the data to be used as values for FITS keywords
rms_ra = tweakwcs_item.meta['fit_info']['RMS_RA'].value
rms_dec = tweakwcs_item.meta['fit_info']['RMS_DEC'].value
fit_rms = tweakwcs_item.meta['fit_info']['FIT_RMS']
nmatch = tweakwcs_item.meta['fit_info']['nmatches']
catalog = tweakwcs_item.meta['fit_info']['catalog']
x_shift = (tweakwcs_item.meta['fit_info']['shift'])[0]
y_shift = (tweakwcs_item.meta['fit_info']['shift'])[1]
rot = tweakwcs_item.meta['fit_info']['rot']
scale = tweakwcs_item.meta['fit_info']['scale'][0]
skew = tweakwcs_item.meta['fit_info']['skew']
# Update the existing FITS keywords
primary_header = headerlet[0].header
primary_header['RMS_RA'] = rms_ra
primary_header['RMS_DEC'] = rms_dec
primary_header['NMATCH'] = nmatch
primary_header['CATALOG'] = catalog
# Create a new FITS keyword
primary_header['FIT_RMS'] = (fit_rms, 'RMS (mas) of the 2D fit of the headerlet solution')
# Create the set of HISTORY keywords
primary_header['HISTORY'] = '~~~~~ FIT PARAMETERS ~~~~~'
primary_header['HISTORY'] = '{:>15} : {:9.4f} "/pixels'.format('platescale', tweakwcs_item.wcs.pscale)
primary_header['HISTORY'] = '{:>15} : {:9.4f} pixels'.format('x_shift', x_shift)
primary_header['HISTORY'] = '{:>15} : {:9.4f} pixels'.format('y_shift', y_shift)
primary_header['HISTORY'] = '{:>15} : {:9.4f} degrees'.format('rotation', rot)
primary_header['HISTORY'] = '{:>15} : {:9.4f}'.format('scale', scale)
primary_header['HISTORY'] = '{:>15} : {:9.4f}'.format('skew', skew) | python | def update_headerlet_phdu(tweakwcs_item, headerlet):
"""Update the primary header data unit keywords of a headerlet object in-place
Parameters
==========
tweakwc_item :
Basically the output from tweakwcs which contains the cross match and fit
information for every chip of every valid input image.
headerlet :
object containing WCS information
"""
# Get the data to be used as values for FITS keywords
rms_ra = tweakwcs_item.meta['fit_info']['RMS_RA'].value
rms_dec = tweakwcs_item.meta['fit_info']['RMS_DEC'].value
fit_rms = tweakwcs_item.meta['fit_info']['FIT_RMS']
nmatch = tweakwcs_item.meta['fit_info']['nmatches']
catalog = tweakwcs_item.meta['fit_info']['catalog']
x_shift = (tweakwcs_item.meta['fit_info']['shift'])[0]
y_shift = (tweakwcs_item.meta['fit_info']['shift'])[1]
rot = tweakwcs_item.meta['fit_info']['rot']
scale = tweakwcs_item.meta['fit_info']['scale'][0]
skew = tweakwcs_item.meta['fit_info']['skew']
# Update the existing FITS keywords
primary_header = headerlet[0].header
primary_header['RMS_RA'] = rms_ra
primary_header['RMS_DEC'] = rms_dec
primary_header['NMATCH'] = nmatch
primary_header['CATALOG'] = catalog
# Create a new FITS keyword
primary_header['FIT_RMS'] = (fit_rms, 'RMS (mas) of the 2D fit of the headerlet solution')
# Create the set of HISTORY keywords
primary_header['HISTORY'] = '~~~~~ FIT PARAMETERS ~~~~~'
primary_header['HISTORY'] = '{:>15} : {:9.4f} "/pixels'.format('platescale', tweakwcs_item.wcs.pscale)
primary_header['HISTORY'] = '{:>15} : {:9.4f} pixels'.format('x_shift', x_shift)
primary_header['HISTORY'] = '{:>15} : {:9.4f} pixels'.format('y_shift', y_shift)
primary_header['HISTORY'] = '{:>15} : {:9.4f} degrees'.format('rotation', rot)
primary_header['HISTORY'] = '{:>15} : {:9.4f}'.format('scale', scale)
primary_header['HISTORY'] = '{:>15} : {:9.4f}'.format('skew', skew) | [
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headerlet :
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spacetelescope/drizzlepac | drizzlepac/alignimages.py | interpret_fit_rms | def interpret_fit_rms(tweakwcs_output, reference_catalog):
"""Interpret the FIT information to convert RMS to physical units
Parameters
----------
tweakwcs_output : list
output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image. This list gets updated, in-place, with the new RMS values;
specifically,
* 'FIT_RMS': RMS of the separations between fitted image positions and reference positions
* 'TOTAL_RMS': mean of the FIT_RMS values for all observations
* 'NUM_FITS': number of images/group_id's with successful fits included in the TOTAL_RMS
These entries are added to the 'fit_info' dictionary.
reference_catalog : astropy.Table
Table of reference source positions used for the fit
Returns
-------
Nothing
"""
# Start by collecting information by group_id
group_ids = [info.meta['group_id'] for info in tweakwcs_output]
# Compress the list to have only unique group_id values to avoid some unnecessary iterations
group_ids = list(set(group_ids))
group_dict = {'avg_RMS':None}
obs_rms = []
for group_id in group_ids:
for item in tweakwcs_output:
# When status = FAILED (fit failed) or REFERENCE (relative alignment done with first image
# as the reference), skip to the beginning of the loop as there is no 'fit_info'.
if item.meta['fit_info']['status'] != 'SUCCESS':
continue
# Make sure to store data for any particular group_id only once.
if item.meta['group_id'] == group_id and \
group_id not in group_dict:
group_dict[group_id] = {'ref_idx':None, 'FIT_RMS':None}
log.info("fit_info: {}".format(item.meta['fit_info']))
tinfo = item.meta['fit_info']
ref_idx = tinfo['matched_ref_idx']
fitmask = tinfo['fitmask']
group_dict[group_id]['ref_idx'] = ref_idx
ref_RA = reference_catalog[ref_idx]['RA'][fitmask]
ref_DEC = reference_catalog[ref_idx]['DEC'][fitmask]
input_RA = tinfo['fit_RA']
input_DEC = tinfo['fit_DEC']
img_coords = SkyCoord(input_RA, input_DEC,
unit='deg',frame='icrs')
ref_coords = SkyCoord(ref_RA, ref_DEC, unit='deg',frame='icrs')
dra, ddec = img_coords.spherical_offsets_to(ref_coords)
ra_rms = np.std(dra.to(u.mas))
dec_rms = np.std(ddec.to(u.mas))
fit_rms = np.std(Angle(img_coords.separation(ref_coords), unit=u.mas)).value
group_dict[group_id]['FIT_RMS'] = fit_rms
group_dict[group_id]['RMS_RA'] = ra_rms
group_dict[group_id]['RMS_DEC'] = dec_rms
obs_rms.append(fit_rms)
# Compute RMS for entire ASN/observation set
total_rms = np.mean(obs_rms)
#total_rms = np.sqrt(np.sum(np.array(obs_rms)**2))
# Now, append computed results to tweakwcs_output
for item in tweakwcs_output:
group_id = item.meta['group_id']
if group_id in group_dict:
fit_rms = group_dict[group_id]['FIT_RMS']
ra_rms = group_dict[group_id]['RMS_RA']
dec_rms = group_dict[group_id]['RMS_DEC']
else:
fit_rms = None
ra_rms = None
dec_rms = None
item.meta['fit_info']['FIT_RMS'] = fit_rms
item.meta['fit_info']['TOTAL_RMS'] = total_rms
item.meta['fit_info']['NUM_FITS'] = len(group_ids)
item.meta['fit_info']['RMS_RA'] = ra_rms
item.meta['fit_info']['RMS_DEC'] = dec_rms
item.meta['fit_info']['catalog'] = reference_catalog.meta['catalog'] | python | def interpret_fit_rms(tweakwcs_output, reference_catalog):
"""Interpret the FIT information to convert RMS to physical units
Parameters
----------
tweakwcs_output : list
output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image. This list gets updated, in-place, with the new RMS values;
specifically,
* 'FIT_RMS': RMS of the separations between fitted image positions and reference positions
* 'TOTAL_RMS': mean of the FIT_RMS values for all observations
* 'NUM_FITS': number of images/group_id's with successful fits included in the TOTAL_RMS
These entries are added to the 'fit_info' dictionary.
reference_catalog : astropy.Table
Table of reference source positions used for the fit
Returns
-------
Nothing
"""
# Start by collecting information by group_id
group_ids = [info.meta['group_id'] for info in tweakwcs_output]
# Compress the list to have only unique group_id values to avoid some unnecessary iterations
group_ids = list(set(group_ids))
group_dict = {'avg_RMS':None}
obs_rms = []
for group_id in group_ids:
for item in tweakwcs_output:
# When status = FAILED (fit failed) or REFERENCE (relative alignment done with first image
# as the reference), skip to the beginning of the loop as there is no 'fit_info'.
if item.meta['fit_info']['status'] != 'SUCCESS':
continue
# Make sure to store data for any particular group_id only once.
if item.meta['group_id'] == group_id and \
group_id not in group_dict:
group_dict[group_id] = {'ref_idx':None, 'FIT_RMS':None}
log.info("fit_info: {}".format(item.meta['fit_info']))
tinfo = item.meta['fit_info']
ref_idx = tinfo['matched_ref_idx']
fitmask = tinfo['fitmask']
group_dict[group_id]['ref_idx'] = ref_idx
ref_RA = reference_catalog[ref_idx]['RA'][fitmask]
ref_DEC = reference_catalog[ref_idx]['DEC'][fitmask]
input_RA = tinfo['fit_RA']
input_DEC = tinfo['fit_DEC']
img_coords = SkyCoord(input_RA, input_DEC,
unit='deg',frame='icrs')
ref_coords = SkyCoord(ref_RA, ref_DEC, unit='deg',frame='icrs')
dra, ddec = img_coords.spherical_offsets_to(ref_coords)
ra_rms = np.std(dra.to(u.mas))
dec_rms = np.std(ddec.to(u.mas))
fit_rms = np.std(Angle(img_coords.separation(ref_coords), unit=u.mas)).value
group_dict[group_id]['FIT_RMS'] = fit_rms
group_dict[group_id]['RMS_RA'] = ra_rms
group_dict[group_id]['RMS_DEC'] = dec_rms
obs_rms.append(fit_rms)
# Compute RMS for entire ASN/observation set
total_rms = np.mean(obs_rms)
#total_rms = np.sqrt(np.sum(np.array(obs_rms)**2))
# Now, append computed results to tweakwcs_output
for item in tweakwcs_output:
group_id = item.meta['group_id']
if group_id in group_dict:
fit_rms = group_dict[group_id]['FIT_RMS']
ra_rms = group_dict[group_id]['RMS_RA']
dec_rms = group_dict[group_id]['RMS_DEC']
else:
fit_rms = None
ra_rms = None
dec_rms = None
item.meta['fit_info']['FIT_RMS'] = fit_rms
item.meta['fit_info']['TOTAL_RMS'] = total_rms
item.meta['fit_info']['NUM_FITS'] = len(group_ids)
item.meta['fit_info']['RMS_RA'] = ra_rms
item.meta['fit_info']['RMS_DEC'] = dec_rms
item.meta['fit_info']['catalog'] = reference_catalog.meta['catalog'] | [
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Parameters
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tweakwcs_output : list
output of tweakwcs. Contains sourcelist tables, newly computed WCS info, etc. for every chip of every valid
input image. This list gets updated, in-place, with the new RMS values;
specifically,
* 'FIT_RMS': RMS of the separations between fitted image positions and reference positions
* 'TOTAL_RMS': mean of the FIT_RMS values for all observations
* 'NUM_FITS': number of images/group_id's with successful fits included in the TOTAL_RMS
These entries are added to the 'fit_info' dictionary.
reference_catalog : astropy.Table
Table of reference source positions used for the fit
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-------
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spacetelescope/drizzlepac | drizzlepac/sky.py | sky | def sky(input=None,outExt=None,configObj=None, group=None, editpars=False, **inputDict):
"""
Perform sky subtraction on input list of images
Parameters
----------
input : str or list of str
a python list of image filenames, or just a single filename
configObj : configObject
an instance of configObject
inputDict : dict, optional
an optional list of parameters specified by the user
outExt : str
The extension of the output image. If the output already exists
then the input image is overwritten
Notes
-----
These are parameters that the configObj should contain by default,
they can be altered on the fly using the inputDict
Parameters that should be in configobj:
========== ===================================================================
Name Definition
========== ===================================================================
skymethod 'Sky computation method'
skysub 'Perform sky subtraction?'
skywidth 'Bin width of histogram for sampling sky statistics (in sigma)'
skystat 'Sky correction statistics parameter'
skylower 'Lower limit of usable data for sky (always in electrons)'
skyupper 'Upper limit of usable data for sky (always in electrons)'
skyclip 'Number of clipping iterations'
skylsigma 'Lower side clipping factor (in sigma)'
skyusigma 'Upper side clipping factor (in sigma)'
skymask_cat 'Catalog file listing image masks'
use_static 'Use static mask for skymatch computations?'
sky_bits 'Integer mask bit values considered good pixels in DQ array'
skyfile 'Name of file with user-computed sky values'
skyuser 'KEYWORD indicating a sky subtraction value if done by user'
in_memory 'Optimize for speed or for memory use'
========== ===================================================================
The output from sky subtraction is a copy of the original input file
where all the science data extensions have been sky subtracted.
"""
if input is not None:
inputDict['input']=input
inputDict['output']=None
inputDict['updatewcs']=False
inputDict['group']=group
else:
print("Please supply an input image", file=sys.stderr)
raise ValueError
configObj = util.getDefaultConfigObj(__taskname__,configObj,inputDict,loadOnly=(not editpars))
if configObj is None:
return
if not editpars:
run(configObj,outExt=outExt) | python | def sky(input=None,outExt=None,configObj=None, group=None, editpars=False, **inputDict):
"""
Perform sky subtraction on input list of images
Parameters
----------
input : str or list of str
a python list of image filenames, or just a single filename
configObj : configObject
an instance of configObject
inputDict : dict, optional
an optional list of parameters specified by the user
outExt : str
The extension of the output image. If the output already exists
then the input image is overwritten
Notes
-----
These are parameters that the configObj should contain by default,
they can be altered on the fly using the inputDict
Parameters that should be in configobj:
========== ===================================================================
Name Definition
========== ===================================================================
skymethod 'Sky computation method'
skysub 'Perform sky subtraction?'
skywidth 'Bin width of histogram for sampling sky statistics (in sigma)'
skystat 'Sky correction statistics parameter'
skylower 'Lower limit of usable data for sky (always in electrons)'
skyupper 'Upper limit of usable data for sky (always in electrons)'
skyclip 'Number of clipping iterations'
skylsigma 'Lower side clipping factor (in sigma)'
skyusigma 'Upper side clipping factor (in sigma)'
skymask_cat 'Catalog file listing image masks'
use_static 'Use static mask for skymatch computations?'
sky_bits 'Integer mask bit values considered good pixels in DQ array'
skyfile 'Name of file with user-computed sky values'
skyuser 'KEYWORD indicating a sky subtraction value if done by user'
in_memory 'Optimize for speed or for memory use'
========== ===================================================================
The output from sky subtraction is a copy of the original input file
where all the science data extensions have been sky subtracted.
"""
if input is not None:
inputDict['input']=input
inputDict['output']=None
inputDict['updatewcs']=False
inputDict['group']=group
else:
print("Please supply an input image", file=sys.stderr)
raise ValueError
configObj = util.getDefaultConfigObj(__taskname__,configObj,inputDict,loadOnly=(not editpars))
if configObj is None:
return
if not editpars:
run(configObj,outExt=outExt) | [
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a python list of image filenames, or just a single filename
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an instance of configObject
inputDict : dict, optional
an optional list of parameters specified by the user
outExt : str
The extension of the output image. If the output already exists
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Notes
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These are parameters that the configObj should contain by default,
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Parameters that should be in configobj:
========== ===================================================================
Name Definition
========== ===================================================================
skymethod 'Sky computation method'
skysub 'Perform sky subtraction?'
skywidth 'Bin width of histogram for sampling sky statistics (in sigma)'
skystat 'Sky correction statistics parameter'
skylower 'Lower limit of usable data for sky (always in electrons)'
skyupper 'Upper limit of usable data for sky (always in electrons)'
skyclip 'Number of clipping iterations'
skylsigma 'Lower side clipping factor (in sigma)'
skyusigma 'Upper side clipping factor (in sigma)'
skymask_cat 'Catalog file listing image masks'
use_static 'Use static mask for skymatch computations?'
sky_bits 'Integer mask bit values considered good pixels in DQ array'
skyfile 'Name of file with user-computed sky values'
skyuser 'KEYWORD indicating a sky subtraction value if done by user'
in_memory 'Optimize for speed or for memory use'
========== ===================================================================
The output from sky subtraction is a copy of the original input file
where all the science data extensions have been sky subtracted. | [
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spacetelescope/drizzlepac | drizzlepac/sky.py | _skyUserFromFile | def _skyUserFromFile(imageObjList, skyFile, apply_sky=None):
"""
Apply sky value as read in from a user-supplied input file.
"""
skyKW="MDRIZSKY" #header keyword that contains the sky that's been subtracted
# create dict of fname=sky pairs
skyvals = {}
if apply_sky is None:
skyapplied = False # flag whether sky has already been applied to images
else:
skyapplied = apply_sky
for line in open(skyFile):
if apply_sky is None and line[0] == '#' and 'applied' in line:
if '=' in line: linesep = '='
if ':' in line: linesep = ':'
appliedstr = line.split(linesep)[1].strip()
if appliedstr.lower() in ['yes','true','y','t']:
skyapplied = True
print('...Sky values already applied by user...')
if not util.is_blank(line) and line[0] != '#':
lspl = line.split()
svals = []
for lvals in lspl[1:]:
svals.append(float(lvals))
skyvals[lspl[0]] = svals
# Apply user values to appropriate input images
for imageSet in imageObjList:
fname = imageSet._filename
numchips=imageSet._numchips
sciExt=imageSet.scienceExt
if fname in skyvals:
print(" ...updating MDRIZSKY with user-supplied value.")
for chip in range(1,numchips+1,1):
if len(skyvals[fname]) == 1:
_skyValue = skyvals[fname][0]
else:
_skyValue = skyvals[fname][chip-1]
chipext = '%s,%d'%(sciExt,chip)
_updateKW(imageSet[chipext],fname,(sciExt,chip),skyKW,_skyValue)
# Update internal record with subtracted sky value
#
# .computedSky: value to be applied by the
# adrizzle/ablot steps.
# .subtractedSky: value already (or will be by adrizzle/ablot)
# subtracted from the image
if skyapplied:
imageSet[chipext].computedSky = None # used by adrizzle/ablot
else:
imageSet[chipext].computedSky = _skyValue
imageSet[chipext].subtractedSky = _skyValue
print("Setting ",skyKW,"=",_skyValue)
else:
print("*"*40)
print("*")
print("WARNING:")
print(" .... NO user-supplied sky value found for ",fname)
print(" .... Setting sky to a value of 0.0! ")
print("*")
print("*"*40) | python | def _skyUserFromFile(imageObjList, skyFile, apply_sky=None):
"""
Apply sky value as read in from a user-supplied input file.
"""
skyKW="MDRIZSKY" #header keyword that contains the sky that's been subtracted
# create dict of fname=sky pairs
skyvals = {}
if apply_sky is None:
skyapplied = False # flag whether sky has already been applied to images
else:
skyapplied = apply_sky
for line in open(skyFile):
if apply_sky is None and line[0] == '#' and 'applied' in line:
if '=' in line: linesep = '='
if ':' in line: linesep = ':'
appliedstr = line.split(linesep)[1].strip()
if appliedstr.lower() in ['yes','true','y','t']:
skyapplied = True
print('...Sky values already applied by user...')
if not util.is_blank(line) and line[0] != '#':
lspl = line.split()
svals = []
for lvals in lspl[1:]:
svals.append(float(lvals))
skyvals[lspl[0]] = svals
# Apply user values to appropriate input images
for imageSet in imageObjList:
fname = imageSet._filename
numchips=imageSet._numchips
sciExt=imageSet.scienceExt
if fname in skyvals:
print(" ...updating MDRIZSKY with user-supplied value.")
for chip in range(1,numchips+1,1):
if len(skyvals[fname]) == 1:
_skyValue = skyvals[fname][0]
else:
_skyValue = skyvals[fname][chip-1]
chipext = '%s,%d'%(sciExt,chip)
_updateKW(imageSet[chipext],fname,(sciExt,chip),skyKW,_skyValue)
# Update internal record with subtracted sky value
#
# .computedSky: value to be applied by the
# adrizzle/ablot steps.
# .subtractedSky: value already (or will be by adrizzle/ablot)
# subtracted from the image
if skyapplied:
imageSet[chipext].computedSky = None # used by adrizzle/ablot
else:
imageSet[chipext].computedSky = _skyValue
imageSet[chipext].subtractedSky = _skyValue
print("Setting ",skyKW,"=",_skyValue)
else:
print("*"*40)
print("*")
print("WARNING:")
print(" .... NO user-supplied sky value found for ",fname)
print(" .... Setting sky to a value of 0.0! ")
print("*")
print("*"*40) | [
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spacetelescope/drizzlepac | drizzlepac/sky.py | _computeSky | def _computeSky(image, skypars, memmap=False):
"""
Compute the sky value for the data array passed to the function
image is a fits object which contains the data and the header
for one image extension
skypars is passed in as paramDict
"""
#this object contains the returned values from the image stats routine
_tmp = imagestats.ImageStats(image.data,
fields = skypars['skystat'],
lower = skypars['skylower'],
upper = skypars['skyupper'],
nclip = skypars['skyclip'],
lsig = skypars['skylsigma'],
usig = skypars['skyusigma'],
binwidth = skypars['skywidth']
)
_skyValue = _extractSkyValue(_tmp,skypars['skystat'].lower())
log.info(" Computed sky value/pixel for %s: %s "%
(image.rootname, _skyValue))
del _tmp
return _skyValue | python | def _computeSky(image, skypars, memmap=False):
"""
Compute the sky value for the data array passed to the function
image is a fits object which contains the data and the header
for one image extension
skypars is passed in as paramDict
"""
#this object contains the returned values from the image stats routine
_tmp = imagestats.ImageStats(image.data,
fields = skypars['skystat'],
lower = skypars['skylower'],
upper = skypars['skyupper'],
nclip = skypars['skyclip'],
lsig = skypars['skylsigma'],
usig = skypars['skyusigma'],
binwidth = skypars['skywidth']
)
_skyValue = _extractSkyValue(_tmp,skypars['skystat'].lower())
log.info(" Computed sky value/pixel for %s: %s "%
(image.rootname, _skyValue))
del _tmp
return _skyValue | [
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spacetelescope/drizzlepac | drizzlepac/sky.py | _subtractSky | def _subtractSky(image,skyValue,memmap=False):
"""
subtract the given sky value from each the data array
that has been passed. image is a fits object that
contains the data and header for one image extension
"""
try:
np.subtract(image.data,skyValue,image.data)
except IOError:
print("Unable to perform sky subtraction on data array")
raise IOError | python | def _subtractSky(image,skyValue,memmap=False):
"""
subtract the given sky value from each the data array
that has been passed. image is a fits object that
contains the data and header for one image extension
"""
try:
np.subtract(image.data,skyValue,image.data)
except IOError:
print("Unable to perform sky subtraction on data array")
raise IOError | [
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spacetelescope/drizzlepac | drizzlepac/sky.py | _updateKW | def _updateKW(image, filename, exten, skyKW, Value):
"""update the header with the kw,value"""
# Update the value in memory
image.header[skyKW] = Value
# Now update the value on disk
if isinstance(exten,tuple):
strexten = '[%s,%s]'%(exten[0],str(exten[1]))
else:
strexten = '[%s]'%(exten)
log.info('Updating keyword %s in %s' % (skyKW, filename + strexten))
fobj = fileutil.openImage(filename, mode='update', memmap=False)
fobj[exten].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle')
fobj.close() | python | def _updateKW(image, filename, exten, skyKW, Value):
"""update the header with the kw,value"""
# Update the value in memory
image.header[skyKW] = Value
# Now update the value on disk
if isinstance(exten,tuple):
strexten = '[%s,%s]'%(exten[0],str(exten[1]))
else:
strexten = '[%s]'%(exten)
log.info('Updating keyword %s in %s' % (skyKW, filename + strexten))
fobj = fileutil.openImage(filename, mode='update', memmap=False)
fobj[exten].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle')
fobj.close() | [
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spacetelescope/drizzlepac | drizzlepac/sky.py | _addDefaultSkyKW | def _addDefaultSkyKW(imageObjList):
"""Add MDRIZSKY keyword to "commanded" SCI headers of all input images,
if that keyword does not already exist.
"""
skyKW = "MDRIZSKY"
Value = 0.0
for imageSet in imageObjList:
fname = imageSet._filename
numchips=imageSet._numchips
sciExt=imageSet.scienceExt
fobj = fileutil.openImage(fname, mode='update', memmap=False)
for chip in range(1,numchips+1,1):
ext = (sciExt,chip)
if not imageSet[ext].group_member:
# skip over extensions not used in processing
continue
if skyKW not in fobj[ext].header:
fobj[ext].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle')
log.info("MDRIZSKY keyword not found in the %s[%s,%d] header."%(
fname,sciExt,chip))
log.info(" Adding MDRIZSKY to header with default value of 0.")
fobj.close() | python | def _addDefaultSkyKW(imageObjList):
"""Add MDRIZSKY keyword to "commanded" SCI headers of all input images,
if that keyword does not already exist.
"""
skyKW = "MDRIZSKY"
Value = 0.0
for imageSet in imageObjList:
fname = imageSet._filename
numchips=imageSet._numchips
sciExt=imageSet.scienceExt
fobj = fileutil.openImage(fname, mode='update', memmap=False)
for chip in range(1,numchips+1,1):
ext = (sciExt,chip)
if not imageSet[ext].group_member:
# skip over extensions not used in processing
continue
if skyKW not in fobj[ext].header:
fobj[ext].header[skyKW] = (Value, 'Sky value computed by AstroDrizzle')
log.info("MDRIZSKY keyword not found in the %s[%s,%d] header."%(
fname,sciExt,chip))
log.info(" Adding MDRIZSKY to header with default value of 0.")
fobj.close() | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | create_astrometric_catalog | def create_astrometric_catalog(inputs, **pars):
"""Create an astrometric catalog that covers the inputs' field-of-view.
Parameters
----------
input : str, list
Filenames of images to be aligned to astrometric catalog
catalog : str, optional
Name of catalog to extract astrometric positions for sources in the
input images' field-of-view. Default: GAIADR2. Options available are
documented on the catalog web page.
output : str, optional
Filename to give to the astrometric catalog read in from the master
catalog web service. If None, no file will be written out.
gaia_only : bool, optional
Specify whether or not to only use sources from GAIA in output catalog
Default: False
existing_wcs : ~stwcs.wcsutils.HSTWCS`
existing WCS object specified by the user
Notes
-----
This function will point to astrometric catalog web service defined
through the use of the ASTROMETRIC_CATALOG_URL environment variable.
Returns
-------
ref_table : ~.astropy.table.Table`
Astropy Table object of the catalog
"""
# interpret input parameters
catalog = pars.get("catalog", 'GAIADR2')
output = pars.get("output", 'ref_cat.ecsv')
gaia_only = pars.get("gaia_only", False)
table_format = pars.get("table_format", 'ascii.ecsv')
existing_wcs = pars.get("existing_wcs", None)
inputs, _ = parseinput.parseinput(inputs)
# start by creating a composite field-of-view for all inputs
# This default output WCS will have the same plate-scale and orientation
# as the first chip in the list, which for WFPC2 data means the PC.
# Fortunately, for alignment, this doesn't matter since no resampling of
# data will be performed
if existing_wcs:
outwcs = existing_wcs
else:
outwcs = build_reference_wcs(inputs)
radius = compute_radius(outwcs)
ra, dec = outwcs.wcs.crval
# perform query for this field-of-view
ref_dict = get_catalog(ra, dec, sr=radius, catalog=catalog)
colnames = ('ra', 'dec', 'mag', 'objID', 'GaiaID')
col_types = ('f8', 'f8', 'f4', 'U25', 'U25')
ref_table = Table(names=colnames, dtype=col_types)
# Add catalog name as meta data
ref_table.meta['catalog'] = catalog
ref_table.meta['gaia_only'] = gaia_only
# rename coordinate columns to be consistent with tweakwcs
ref_table.rename_column('ra', 'RA')
ref_table.rename_column('dec', 'DEC')
# extract just the columns we want...
num_sources = 0
for source in ref_dict:
if 'GAIAsourceID' in source:
g = source['GAIAsourceID']
if gaia_only and g.strip() == '':
continue
else:
g = "-1" # indicator for no source ID extracted
r = float(source['ra'])
d = float(source['dec'])
m = -999.9 # float(source['mag'])
o = source['objID']
num_sources += 1
ref_table.add_row((r, d, m, o, g))
# Write out table to a file, if specified
if output:
ref_table.write(output, format=table_format)
log.info("Created catalog '{}' with {} sources".format(output, num_sources))
return ref_table | python | def create_astrometric_catalog(inputs, **pars):
"""Create an astrometric catalog that covers the inputs' field-of-view.
Parameters
----------
input : str, list
Filenames of images to be aligned to astrometric catalog
catalog : str, optional
Name of catalog to extract astrometric positions for sources in the
input images' field-of-view. Default: GAIADR2. Options available are
documented on the catalog web page.
output : str, optional
Filename to give to the astrometric catalog read in from the master
catalog web service. If None, no file will be written out.
gaia_only : bool, optional
Specify whether or not to only use sources from GAIA in output catalog
Default: False
existing_wcs : ~stwcs.wcsutils.HSTWCS`
existing WCS object specified by the user
Notes
-----
This function will point to astrometric catalog web service defined
through the use of the ASTROMETRIC_CATALOG_URL environment variable.
Returns
-------
ref_table : ~.astropy.table.Table`
Astropy Table object of the catalog
"""
# interpret input parameters
catalog = pars.get("catalog", 'GAIADR2')
output = pars.get("output", 'ref_cat.ecsv')
gaia_only = pars.get("gaia_only", False)
table_format = pars.get("table_format", 'ascii.ecsv')
existing_wcs = pars.get("existing_wcs", None)
inputs, _ = parseinput.parseinput(inputs)
# start by creating a composite field-of-view for all inputs
# This default output WCS will have the same plate-scale and orientation
# as the first chip in the list, which for WFPC2 data means the PC.
# Fortunately, for alignment, this doesn't matter since no resampling of
# data will be performed
if existing_wcs:
outwcs = existing_wcs
else:
outwcs = build_reference_wcs(inputs)
radius = compute_radius(outwcs)
ra, dec = outwcs.wcs.crval
# perform query for this field-of-view
ref_dict = get_catalog(ra, dec, sr=radius, catalog=catalog)
colnames = ('ra', 'dec', 'mag', 'objID', 'GaiaID')
col_types = ('f8', 'f8', 'f4', 'U25', 'U25')
ref_table = Table(names=colnames, dtype=col_types)
# Add catalog name as meta data
ref_table.meta['catalog'] = catalog
ref_table.meta['gaia_only'] = gaia_only
# rename coordinate columns to be consistent with tweakwcs
ref_table.rename_column('ra', 'RA')
ref_table.rename_column('dec', 'DEC')
# extract just the columns we want...
num_sources = 0
for source in ref_dict:
if 'GAIAsourceID' in source:
g = source['GAIAsourceID']
if gaia_only and g.strip() == '':
continue
else:
g = "-1" # indicator for no source ID extracted
r = float(source['ra'])
d = float(source['dec'])
m = -999.9 # float(source['mag'])
o = source['objID']
num_sources += 1
ref_table.add_row((r, d, m, o, g))
# Write out table to a file, if specified
if output:
ref_table.write(output, format=table_format)
log.info("Created catalog '{}' with {} sources".format(output, num_sources))
return ref_table | [
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Filenames of images to be aligned to astrometric catalog
catalog : str, optional
Name of catalog to extract astrometric positions for sources in the
input images' field-of-view. Default: GAIADR2. Options available are
documented on the catalog web page.
output : str, optional
Filename to give to the astrometric catalog read in from the master
catalog web service. If None, no file will be written out.
gaia_only : bool, optional
Specify whether or not to only use sources from GAIA in output catalog
Default: False
existing_wcs : ~stwcs.wcsutils.HSTWCS`
existing WCS object specified by the user
Notes
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This function will point to astrometric catalog web service defined
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Returns
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ref_table : ~.astropy.table.Table`
Astropy Table object of the catalog | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | build_reference_wcs | def build_reference_wcs(inputs, sciname='sci'):
"""Create the reference WCS based on all the inputs for a field"""
# start by creating a composite field-of-view for all inputs
wcslist = []
for img in inputs:
nsci = countExtn(img)
for num in range(nsci):
extname = (sciname, num + 1)
if sciname == 'sci':
extwcs = wcsutil.HSTWCS(img, ext=extname)
else:
# Working with HDRLET as input and do the best we can...
extwcs = read_hlet_wcs(img, ext=extname)
wcslist.append(extwcs)
# This default output WCS will have the same plate-scale and orientation
# as the first chip in the list, which for WFPC2 data means the PC.
# Fortunately, for alignment, this doesn't matter since no resampling of
# data will be performed
outwcs = utils.output_wcs(wcslist)
return outwcs | python | def build_reference_wcs(inputs, sciname='sci'):
"""Create the reference WCS based on all the inputs for a field"""
# start by creating a composite field-of-view for all inputs
wcslist = []
for img in inputs:
nsci = countExtn(img)
for num in range(nsci):
extname = (sciname, num + 1)
if sciname == 'sci':
extwcs = wcsutil.HSTWCS(img, ext=extname)
else:
# Working with HDRLET as input and do the best we can...
extwcs = read_hlet_wcs(img, ext=extname)
wcslist.append(extwcs)
# This default output WCS will have the same plate-scale and orientation
# as the first chip in the list, which for WFPC2 data means the PC.
# Fortunately, for alignment, this doesn't matter since no resampling of
# data will be performed
outwcs = utils.output_wcs(wcslist)
return outwcs | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | get_catalog | def get_catalog(ra, dec, sr=0.1, fmt='CSV', catalog='GSC241'):
""" Extract catalog from VO web service.
Parameters
----------
ra : float
Right Ascension (RA) of center of field-of-view (in decimal degrees)
dec : float
Declination (Dec) of center of field-of-view (in decimal degrees)
sr : float, optional
Search radius (in decimal degrees) from field-of-view center to use
for sources from catalog. Default: 0.1 degrees
fmt : str, optional
Format of output catalog to be returned. Options are determined by
web-service, and currently include (Default: CSV):
VOTABLE(default) | HTML | KML | CSV | TSV | JSON | TEXT
catalog : str, optional
Name of catalog to query, as defined by web-service. Default: 'GSC241'
Returns
-------
csv : CSV object
CSV object of returned sources with all columns as provided by catalog
"""
serviceType = 'vo/CatalogSearch.aspx'
spec_str = 'RA={}&DEC={}&SR={}&FORMAT={}&CAT={}&MINDET=5'
headers = {'Content-Type': 'text/csv'}
spec = spec_str.format(ra, dec, sr, fmt, catalog)
serviceUrl = '{}/{}?{}'.format(SERVICELOCATION, serviceType, spec)
rawcat = requests.get(serviceUrl, headers=headers)
r_contents = rawcat.content.decode() # convert from bytes to a String
rstr = r_contents.split('\r\n')
# remove initial line describing the number of sources returned
# CRITICAL to proper interpretation of CSV data
del rstr[0]
r_csv = csv.DictReader(rstr)
return r_csv | python | def get_catalog(ra, dec, sr=0.1, fmt='CSV', catalog='GSC241'):
""" Extract catalog from VO web service.
Parameters
----------
ra : float
Right Ascension (RA) of center of field-of-view (in decimal degrees)
dec : float
Declination (Dec) of center of field-of-view (in decimal degrees)
sr : float, optional
Search radius (in decimal degrees) from field-of-view center to use
for sources from catalog. Default: 0.1 degrees
fmt : str, optional
Format of output catalog to be returned. Options are determined by
web-service, and currently include (Default: CSV):
VOTABLE(default) | HTML | KML | CSV | TSV | JSON | TEXT
catalog : str, optional
Name of catalog to query, as defined by web-service. Default: 'GSC241'
Returns
-------
csv : CSV object
CSV object of returned sources with all columns as provided by catalog
"""
serviceType = 'vo/CatalogSearch.aspx'
spec_str = 'RA={}&DEC={}&SR={}&FORMAT={}&CAT={}&MINDET=5'
headers = {'Content-Type': 'text/csv'}
spec = spec_str.format(ra, dec, sr, fmt, catalog)
serviceUrl = '{}/{}?{}'.format(SERVICELOCATION, serviceType, spec)
rawcat = requests.get(serviceUrl, headers=headers)
r_contents = rawcat.content.decode() # convert from bytes to a String
rstr = r_contents.split('\r\n')
# remove initial line describing the number of sources returned
# CRITICAL to proper interpretation of CSV data
del rstr[0]
r_csv = csv.DictReader(rstr)
return r_csv | [
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Right Ascension (RA) of center of field-of-view (in decimal degrees)
dec : float
Declination (Dec) of center of field-of-view (in decimal degrees)
sr : float, optional
Search radius (in decimal degrees) from field-of-view center to use
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fmt : str, optional
Format of output catalog to be returned. Options are determined by
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Name of catalog to query, as defined by web-service. Default: 'GSC241'
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | compute_radius | def compute_radius(wcs):
"""Compute the radius from the center to the furthest edge of the WCS."""
ra, dec = wcs.wcs.crval
img_center = SkyCoord(ra=ra * u.degree, dec=dec * u.degree)
wcs_foot = wcs.calc_footprint()
img_corners = SkyCoord(ra=wcs_foot[:, 0] * u.degree,
dec=wcs_foot[:, 1] * u.degree)
radius = img_center.separation(img_corners).max().value
return radius | python | def compute_radius(wcs):
"""Compute the radius from the center to the furthest edge of the WCS."""
ra, dec = wcs.wcs.crval
img_center = SkyCoord(ra=ra * u.degree, dec=dec * u.degree)
wcs_foot = wcs.calc_footprint()
img_corners = SkyCoord(ra=wcs_foot[:, 0] * u.degree,
dec=wcs_foot[:, 1] * u.degree)
radius = img_center.separation(img_corners).max().value
return radius | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | find_gsc_offset | def find_gsc_offset(image, input_catalog='GSC1', output_catalog='GAIA'):
"""Find the GSC to GAIA offset based on guide star coordinates
Parameters
----------
image : str
Filename of image to be processed.
Returns
-------
delta_ra, delta_dec : tuple of floats
Offset in decimal degrees of image based on correction to guide star
coordinates relative to GAIA.
"""
serviceType = "GSCConvert/GSCconvert.aspx"
spec_str = "TRANSFORM={}-{}&IPPPSSOOT={}"
if 'rootname' in pf.getheader(image):
ippssoot = pf.getval(image, 'rootname').upper()
else:
ippssoot = fu.buildNewRootname(image).upper()
spec = spec_str.format(input_catalog, output_catalog, ippssoot)
serviceUrl = "{}/{}?{}".format(SERVICELOCATION, serviceType, spec)
rawcat = requests.get(serviceUrl)
if not rawcat.ok:
log.info("Problem accessing service with:\n{{}".format(serviceUrl))
raise ValueError
delta_ra = delta_dec = None
tree = BytesIO(rawcat.content)
for _, element in etree.iterparse(tree):
if element.tag == 'deltaRA':
delta_ra = float(element.text)
elif element.tag == 'deltaDEC':
delta_dec = float(element.text)
return delta_ra, delta_dec | python | def find_gsc_offset(image, input_catalog='GSC1', output_catalog='GAIA'):
"""Find the GSC to GAIA offset based on guide star coordinates
Parameters
----------
image : str
Filename of image to be processed.
Returns
-------
delta_ra, delta_dec : tuple of floats
Offset in decimal degrees of image based on correction to guide star
coordinates relative to GAIA.
"""
serviceType = "GSCConvert/GSCconvert.aspx"
spec_str = "TRANSFORM={}-{}&IPPPSSOOT={}"
if 'rootname' in pf.getheader(image):
ippssoot = pf.getval(image, 'rootname').upper()
else:
ippssoot = fu.buildNewRootname(image).upper()
spec = spec_str.format(input_catalog, output_catalog, ippssoot)
serviceUrl = "{}/{}?{}".format(SERVICELOCATION, serviceType, spec)
rawcat = requests.get(serviceUrl)
if not rawcat.ok:
log.info("Problem accessing service with:\n{{}".format(serviceUrl))
raise ValueError
delta_ra = delta_dec = None
tree = BytesIO(rawcat.content)
for _, element in etree.iterparse(tree):
if element.tag == 'deltaRA':
delta_ra = float(element.text)
elif element.tag == 'deltaDEC':
delta_dec = float(element.text)
return delta_ra, delta_dec | [
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image : str
Filename of image to be processed.
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Offset in decimal degrees of image based on correction to guide star
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | generate_source_catalog | def generate_source_catalog(image, **kwargs):
""" Build source catalogs for each chip using photutils.
The catalog returned by this function includes sources found in all chips
of the input image with the positions translated to the coordinate frame
defined by the reference WCS `refwcs`. The sources will be
- identified using photutils segmentation-based source finding code
- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : `~astropy.io.fits.HDUList`
Input image as an astropy.io.fits HDUList.
dqname : str
EXTNAME for the DQ array, if present, in the input image HDUList.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the threshold used for identifying sources in
the image relative to the background RMS.
If None, compute a default value of (background+3*rms(background)).
If threshold < 0.0, use absolute value as scaling factor for default value.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
-------
source_cats : dict
Dict of astropy Tables identified by chip number with
each table containing sources from image extension ``('sci', chip)``.
"""
if not isinstance(image, pf.HDUList):
raise ValueError("Input {} not fits.HDUList object".format(image))
dqname = kwargs.get('dqname', 'DQ')
output = kwargs.get('output', None)
# Build source catalog for entire image
source_cats = {}
numSci = countExtn(image, extname='SCI')
for chip in range(numSci):
chip += 1
# find sources in image
if output:
rootname = image[0].header['rootname']
outroot = '{}_sci{}_src'.format(rootname, chip)
kwargs['output'] = outroot
imgarr = image['sci', chip].data
# apply any DQ array, if available
dqmask = None
if image.index_of(dqname):
dqarr = image[dqname, chip].data
# "grow out" regions in DQ mask flagged as saturated by several
# pixels in every direction to prevent the
# source match algorithm from trying to match multiple sources
# from one image to a single source in the
# other or vice-versa.
# Create temp DQ mask containing all pixels flagged with any value EXCEPT 256
non_sat_mask = bitfield_to_boolean_mask(dqarr, ignore_flags=256)
# Create temp DQ mask containing saturated pixels ONLY
sat_mask = bitfield_to_boolean_mask(dqarr, ignore_flags=~256)
# Grow out saturated pixels by a few pixels in every direction
grown_sat_mask = ndimage.binary_dilation(sat_mask, iterations=5)
# combine the two temporary DQ masks into a single composite DQ mask.
dqmask = np.bitwise_or(non_sat_mask, grown_sat_mask)
# dqmask = bitfield_to_boolean_mask(dqarr, good_mask_value=False)
# TODO: <---Remove this old no-sat bit grow line once this
# thing works
seg_tab, segmap = extract_sources(imgarr, dqmask=dqmask, **kwargs)
seg_tab_phot = seg_tab
source_cats[chip] = seg_tab_phot
return source_cats | python | def generate_source_catalog(image, **kwargs):
""" Build source catalogs for each chip using photutils.
The catalog returned by this function includes sources found in all chips
of the input image with the positions translated to the coordinate frame
defined by the reference WCS `refwcs`. The sources will be
- identified using photutils segmentation-based source finding code
- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : `~astropy.io.fits.HDUList`
Input image as an astropy.io.fits HDUList.
dqname : str
EXTNAME for the DQ array, if present, in the input image HDUList.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the threshold used for identifying sources in
the image relative to the background RMS.
If None, compute a default value of (background+3*rms(background)).
If threshold < 0.0, use absolute value as scaling factor for default value.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
-------
source_cats : dict
Dict of astropy Tables identified by chip number with
each table containing sources from image extension ``('sci', chip)``.
"""
if not isinstance(image, pf.HDUList):
raise ValueError("Input {} not fits.HDUList object".format(image))
dqname = kwargs.get('dqname', 'DQ')
output = kwargs.get('output', None)
# Build source catalog for entire image
source_cats = {}
numSci = countExtn(image, extname='SCI')
for chip in range(numSci):
chip += 1
# find sources in image
if output:
rootname = image[0].header['rootname']
outroot = '{}_sci{}_src'.format(rootname, chip)
kwargs['output'] = outroot
imgarr = image['sci', chip].data
# apply any DQ array, if available
dqmask = None
if image.index_of(dqname):
dqarr = image[dqname, chip].data
# "grow out" regions in DQ mask flagged as saturated by several
# pixels in every direction to prevent the
# source match algorithm from trying to match multiple sources
# from one image to a single source in the
# other or vice-versa.
# Create temp DQ mask containing all pixels flagged with any value EXCEPT 256
non_sat_mask = bitfield_to_boolean_mask(dqarr, ignore_flags=256)
# Create temp DQ mask containing saturated pixels ONLY
sat_mask = bitfield_to_boolean_mask(dqarr, ignore_flags=~256)
# Grow out saturated pixels by a few pixels in every direction
grown_sat_mask = ndimage.binary_dilation(sat_mask, iterations=5)
# combine the two temporary DQ masks into a single composite DQ mask.
dqmask = np.bitwise_or(non_sat_mask, grown_sat_mask)
# dqmask = bitfield_to_boolean_mask(dqarr, good_mask_value=False)
# TODO: <---Remove this old no-sat bit grow line once this
# thing works
seg_tab, segmap = extract_sources(imgarr, dqmask=dqmask, **kwargs)
seg_tab_phot = seg_tab
source_cats[chip] = seg_tab_phot
return source_cats | [
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- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : `~astropy.io.fits.HDUList`
Input image as an astropy.io.fits HDUList.
dqname : str
EXTNAME for the DQ array, if present, in the input image HDUList.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the threshold used for identifying sources in
the image relative to the background RMS.
If None, compute a default value of (background+3*rms(background)).
If threshold < 0.0, use absolute value as scaling factor for default value.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
-------
source_cats : dict
Dict of astropy Tables identified by chip number with
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | generate_sky_catalog | def generate_sky_catalog(image, refwcs, **kwargs):
"""Build source catalog from input image using photutils.
This script borrows heavily from build_source_catalog.
The catalog returned by this function includes sources found in all chips
of the input image with the positions translated to the coordinate frame
defined by the reference WCS `refwcs`. The sources will be
- identified using photutils segmentation-based source finding code
- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : ~astropy.io.fits.HDUList`
Input image.
refwcs : `~stwcs.wcsutils.HSTWCS`
Definition of the reference frame WCS.
dqname : str
EXTNAME for the DQ array, if present, in the input image.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the S/N threshold used for identifying sources in
the image relative to the background RMS in much the same way that
the 'threshold' parameter in 'tweakreg' works.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
--------
master_cat : `~astropy.table.Table`
Source catalog for all 'valid' sources identified from all chips of the
input image with positions translated to the reference WCS coordinate
frame.
"""
# Extract source catalogs for each chip
source_cats = generate_source_catalog(image, **kwargs)
# Build source catalog for entire image
master_cat = None
numSci = countExtn(image, extname='SCI')
# if no refwcs specified, build one now...
if refwcs is None:
refwcs = build_reference_wcs([image])
for chip in range(numSci):
chip += 1
# work with sources identified from this specific chip
seg_tab_phot = source_cats[chip]
if seg_tab_phot is None:
continue
# Convert pixel coordinates from this chip to sky coordinates
chip_wcs = wcsutil.HSTWCS(image, ext=('sci', chip))
seg_ra, seg_dec = chip_wcs.all_pix2world(seg_tab_phot['xcentroid'], seg_tab_phot['ycentroid'], 1)
# Convert sky positions to pixel positions in the reference WCS frame
seg_xy_out = refwcs.all_world2pix(seg_ra, seg_dec, 1)
seg_tab_phot['xcentroid'] = seg_xy_out[0]
seg_tab_phot['ycentroid'] = seg_xy_out[1]
if master_cat is None:
master_cat = seg_tab_phot
else:
master_cat = vstack([master_cat, seg_tab_phot])
return master_cat | python | def generate_sky_catalog(image, refwcs, **kwargs):
"""Build source catalog from input image using photutils.
This script borrows heavily from build_source_catalog.
The catalog returned by this function includes sources found in all chips
of the input image with the positions translated to the coordinate frame
defined by the reference WCS `refwcs`. The sources will be
- identified using photutils segmentation-based source finding code
- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : ~astropy.io.fits.HDUList`
Input image.
refwcs : `~stwcs.wcsutils.HSTWCS`
Definition of the reference frame WCS.
dqname : str
EXTNAME for the DQ array, if present, in the input image.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the S/N threshold used for identifying sources in
the image relative to the background RMS in much the same way that
the 'threshold' parameter in 'tweakreg' works.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
--------
master_cat : `~astropy.table.Table`
Source catalog for all 'valid' sources identified from all chips of the
input image with positions translated to the reference WCS coordinate
frame.
"""
# Extract source catalogs for each chip
source_cats = generate_source_catalog(image, **kwargs)
# Build source catalog for entire image
master_cat = None
numSci = countExtn(image, extname='SCI')
# if no refwcs specified, build one now...
if refwcs is None:
refwcs = build_reference_wcs([image])
for chip in range(numSci):
chip += 1
# work with sources identified from this specific chip
seg_tab_phot = source_cats[chip]
if seg_tab_phot is None:
continue
# Convert pixel coordinates from this chip to sky coordinates
chip_wcs = wcsutil.HSTWCS(image, ext=('sci', chip))
seg_ra, seg_dec = chip_wcs.all_pix2world(seg_tab_phot['xcentroid'], seg_tab_phot['ycentroid'], 1)
# Convert sky positions to pixel positions in the reference WCS frame
seg_xy_out = refwcs.all_world2pix(seg_ra, seg_dec, 1)
seg_tab_phot['xcentroid'] = seg_xy_out[0]
seg_tab_phot['ycentroid'] = seg_xy_out[1]
if master_cat is None:
master_cat = seg_tab_phot
else:
master_cat = vstack([master_cat, seg_tab_phot])
return master_cat | [
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defined by the reference WCS `refwcs`. The sources will be
- identified using photutils segmentation-based source finding code
- ignore any input pixel which has been flagged as 'bad' in the DQ
array, should a DQ array be found in the input HDUList.
- classified as probable cosmic-rays (if enabled) using central_moments
properties of each source, with these sources being removed from the
catalog.
Parameters
----------
image : ~astropy.io.fits.HDUList`
Input image.
refwcs : `~stwcs.wcsutils.HSTWCS`
Definition of the reference frame WCS.
dqname : str
EXTNAME for the DQ array, if present, in the input image.
output : bool
Specify whether or not to write out a separate catalog file for all the
sources found in each chip. Default: None (False)
threshold : float, optional
This parameter controls the S/N threshold used for identifying sources in
the image relative to the background RMS in much the same way that
the 'threshold' parameter in 'tweakreg' works.
fwhm : float, optional
FWHM (in pixels) of the expected sources from the image, comparable to the
'conv_width' parameter from 'tweakreg'. Objects with FWHM closest to
this value will be identified as sources in the catalog.
Returns
--------
master_cat : `~astropy.table.Table`
Source catalog for all 'valid' sources identified from all chips of the
input image with positions translated to the reference WCS coordinate
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | compute_photometry | def compute_photometry(catalog, photmode):
""" Compute magnitudes for sources from catalog based on observations photmode.
Parameters
----------
catalog : `~astropy.table.Table`
Astropy Table with 'source_sum' column for the measured flux for each source.
photmode : str
Specification of the observation filter configuration used for the exposure
as reported by the 'PHOTMODE' keyword from the PRIMARY header.
Returns
-------
phot_cat : `~astropy.table.Table`
Astropy Table object of input source catalog with added column for
VEGAMAG photometry (in magnitudes).
"""
# Determine VEGAMAG zero-point using pysynphot for this photmode
photmode = photmode.replace(' ', ', ')
vega = S.FileSpectrum(VEGASPEC)
bp = S.ObsBandpass(photmode)
vegauvis = S.Observation(vega, bp)
vegazpt = 2.5 * np.log10(vegauvis.countrate())
# Use zero-point to convert flux values from catalog into magnitudes
# source_phot = vegazpt - 2.5*np.log10(catalog['source_sum'])
source_phot = vegazpt - 2.5 * np.log10(catalog['flux'])
source_phot.name = 'vegamag'
# Now add this new column to the catalog table
catalog.add_column(source_phot)
return catalog | python | def compute_photometry(catalog, photmode):
""" Compute magnitudes for sources from catalog based on observations photmode.
Parameters
----------
catalog : `~astropy.table.Table`
Astropy Table with 'source_sum' column for the measured flux for each source.
photmode : str
Specification of the observation filter configuration used for the exposure
as reported by the 'PHOTMODE' keyword from the PRIMARY header.
Returns
-------
phot_cat : `~astropy.table.Table`
Astropy Table object of input source catalog with added column for
VEGAMAG photometry (in magnitudes).
"""
# Determine VEGAMAG zero-point using pysynphot for this photmode
photmode = photmode.replace(' ', ', ')
vega = S.FileSpectrum(VEGASPEC)
bp = S.ObsBandpass(photmode)
vegauvis = S.Observation(vega, bp)
vegazpt = 2.5 * np.log10(vegauvis.countrate())
# Use zero-point to convert flux values from catalog into magnitudes
# source_phot = vegazpt - 2.5*np.log10(catalog['source_sum'])
source_phot = vegazpt - 2.5 * np.log10(catalog['flux'])
source_phot.name = 'vegamag'
# Now add this new column to the catalog table
catalog.add_column(source_phot)
return catalog | [
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catalog : `~astropy.table.Table`
Astropy Table with 'source_sum' column for the measured flux for each source.
photmode : str
Specification of the observation filter configuration used for the exposure
as reported by the 'PHOTMODE' keyword from the PRIMARY header.
Returns
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phot_cat : `~astropy.table.Table`
Astropy Table object of input source catalog with added column for
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | filter_catalog | def filter_catalog(catalog, **kwargs):
""" Create a new catalog selected from input based on photometry.
Parameters
----------
bright_limit : float
Fraction of catalog based on brightness that should be retained.
Value of 1.00 means full catalog.
max_bright : int
Maximum number of sources to keep regardless of `bright_limit`.
min_bright : int
Minimum number of sources to keep regardless of `bright_limit`.
colname : str
Name of column to use for selection/sorting.
Returns
-------
new_catalog : `~astropy.table.Table`
New table which only has the sources that meet the selection criteria.
"""
# interpret input pars
bright_limit = kwargs.get('bright_limit', 1.00)
max_bright = kwargs.get('max_bright', None)
min_bright = kwargs.get('min_bright', 20)
colname = kwargs.get('colname', 'vegamag')
# sort by magnitude
phot_column = catalog[colname]
num_sources = len(phot_column)
sort_indx = np.argsort(phot_column)
if max_bright is None:
max_bright = num_sources
# apply limits, insuring no more than full catalog gets selected
limit_num = max(int(num_sources * bright_limit), min_bright)
limit_num = min(max_bright, limit_num, num_sources)
# Extract sources identified by selection
new_catalog = catalog[sort_indx[:limit_num]]
return new_catalog | python | def filter_catalog(catalog, **kwargs):
""" Create a new catalog selected from input based on photometry.
Parameters
----------
bright_limit : float
Fraction of catalog based on brightness that should be retained.
Value of 1.00 means full catalog.
max_bright : int
Maximum number of sources to keep regardless of `bright_limit`.
min_bright : int
Minimum number of sources to keep regardless of `bright_limit`.
colname : str
Name of column to use for selection/sorting.
Returns
-------
new_catalog : `~astropy.table.Table`
New table which only has the sources that meet the selection criteria.
"""
# interpret input pars
bright_limit = kwargs.get('bright_limit', 1.00)
max_bright = kwargs.get('max_bright', None)
min_bright = kwargs.get('min_bright', 20)
colname = kwargs.get('colname', 'vegamag')
# sort by magnitude
phot_column = catalog[colname]
num_sources = len(phot_column)
sort_indx = np.argsort(phot_column)
if max_bright is None:
max_bright = num_sources
# apply limits, insuring no more than full catalog gets selected
limit_num = max(int(num_sources * bright_limit), min_bright)
limit_num = min(max_bright, limit_num, num_sources)
# Extract sources identified by selection
new_catalog = catalog[sort_indx[:limit_num]]
return new_catalog | [
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Fraction of catalog based on brightness that should be retained.
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max_bright : int
Maximum number of sources to keep regardless of `bright_limit`.
min_bright : int
Minimum number of sources to keep regardless of `bright_limit`.
colname : str
Name of column to use for selection/sorting.
Returns
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | build_self_reference | def build_self_reference(filename, clean_wcs=False):
""" This function creates a reference, undistorted WCS that can be used to
apply a correction to the WCS of the input file.
Parameters
----------
filename : str
Filename of image which will be corrected, and which will form the basis
of the undistorted WCS.
clean_wcs : bool
Specify whether or not to return the WCS object without any distortion
information, or any history of the original input image. This converts
the output from `utils.output_wcs()` into a pristine `~stwcs.wcsutils.HSTWCS` object.
Returns
-------
customwcs : `stwcs.wcsutils.HSTWCS`
HSTWCS object which contains the undistorted WCS representing the entire
field-of-view for the input image.
Examples
--------
This function can be used with the following syntax to apply a shift/rot/scale
change to the same image:
>>> import buildref
>>> from drizzlepac import updatehdr
>>> filename = "jce501erq_flc.fits"
>>> wcslin = buildref.build_self_reference(filename)
>>> updatehdr.updatewcs_with_shift(filename, wcslin, xsh=49.5694,
... ysh=19.2203, rot = 359.998, scale = 0.9999964)
"""
if 'sipwcs' in filename:
sciname = 'sipwcs'
else:
sciname = 'sci'
wcslin = build_reference_wcs([filename], sciname=sciname)
if clean_wcs:
wcsbase = wcslin.wcs
customwcs = build_hstwcs(wcsbase.crval[0], wcsbase.crval[1], wcsbase.crpix[0],
wcsbase.crpix[1], wcslin._naxis1, wcslin._naxis2,
wcslin.pscale, wcslin.orientat)
else:
customwcs = wcslin
return customwcs | python | def build_self_reference(filename, clean_wcs=False):
""" This function creates a reference, undistorted WCS that can be used to
apply a correction to the WCS of the input file.
Parameters
----------
filename : str
Filename of image which will be corrected, and which will form the basis
of the undistorted WCS.
clean_wcs : bool
Specify whether or not to return the WCS object without any distortion
information, or any history of the original input image. This converts
the output from `utils.output_wcs()` into a pristine `~stwcs.wcsutils.HSTWCS` object.
Returns
-------
customwcs : `stwcs.wcsutils.HSTWCS`
HSTWCS object which contains the undistorted WCS representing the entire
field-of-view for the input image.
Examples
--------
This function can be used with the following syntax to apply a shift/rot/scale
change to the same image:
>>> import buildref
>>> from drizzlepac import updatehdr
>>> filename = "jce501erq_flc.fits"
>>> wcslin = buildref.build_self_reference(filename)
>>> updatehdr.updatewcs_with_shift(filename, wcslin, xsh=49.5694,
... ysh=19.2203, rot = 359.998, scale = 0.9999964)
"""
if 'sipwcs' in filename:
sciname = 'sipwcs'
else:
sciname = 'sci'
wcslin = build_reference_wcs([filename], sciname=sciname)
if clean_wcs:
wcsbase = wcslin.wcs
customwcs = build_hstwcs(wcsbase.crval[0], wcsbase.crval[1], wcsbase.crpix[0],
wcsbase.crpix[1], wcslin._naxis1, wcslin._naxis2,
wcslin.pscale, wcslin.orientat)
else:
customwcs = wcslin
return customwcs | [
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filename : str
Filename of image which will be corrected, and which will form the basis
of the undistorted WCS.
clean_wcs : bool
Specify whether or not to return the WCS object without any distortion
information, or any history of the original input image. This converts
the output from `utils.output_wcs()` into a pristine `~stwcs.wcsutils.HSTWCS` object.
Returns
-------
customwcs : `stwcs.wcsutils.HSTWCS`
HSTWCS object which contains the undistorted WCS representing the entire
field-of-view for the input image.
Examples
--------
This function can be used with the following syntax to apply a shift/rot/scale
change to the same image:
>>> import buildref
>>> from drizzlepac import updatehdr
>>> filename = "jce501erq_flc.fits"
>>> wcslin = buildref.build_self_reference(filename)
>>> updatehdr.updatewcs_with_shift(filename, wcslin, xsh=49.5694,
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] | 15bec3c929a6a869d9e71b9398ced43ede0620f1 | https://github.com/spacetelescope/drizzlepac/blob/15bec3c929a6a869d9e71b9398ced43ede0620f1/drizzlepac/hlautils/astrometric_utils.py#L807-L855 | train | 35,519 |
spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | read_hlet_wcs | def read_hlet_wcs(filename, ext):
"""Insure `stwcs.wcsutil.HSTWCS` includes all attributes of a full image WCS.
For headerlets, the WCS does not contain information about the size of the
image, as the image array is not present in the headerlet.
"""
hstwcs = wcsutil.HSTWCS(filename, ext=ext)
if hstwcs.naxis1 is None:
hstwcs.naxis1 = int(hstwcs.wcs.crpix[0] * 2.) # Assume crpix is center of chip
hstwcs.naxis2 = int(hstwcs.wcs.crpix[1] * 2.)
return hstwcs | python | def read_hlet_wcs(filename, ext):
"""Insure `stwcs.wcsutil.HSTWCS` includes all attributes of a full image WCS.
For headerlets, the WCS does not contain information about the size of the
image, as the image array is not present in the headerlet.
"""
hstwcs = wcsutil.HSTWCS(filename, ext=ext)
if hstwcs.naxis1 is None:
hstwcs.naxis1 = int(hstwcs.wcs.crpix[0] * 2.) # Assume crpix is center of chip
hstwcs.naxis2 = int(hstwcs.wcs.crpix[1] * 2.)
return hstwcs | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | build_hstwcs | def build_hstwcs(crval1, crval2, crpix1, crpix2, naxis1, naxis2, pscale, orientat):
""" Create an `stwcs.wcsutil.HSTWCS` object for a default instrument without
distortion based on user provided parameter values.
"""
wcsout = wcsutil.HSTWCS()
wcsout.wcs.crval = np.array([crval1, crval2])
wcsout.wcs.crpix = np.array([crpix1, crpix2])
wcsout.naxis1 = naxis1
wcsout.naxis2 = naxis2
wcsout.wcs.cd = buildRotMatrix(orientat) * [-1, 1] * pscale / 3600.0
# Synchronize updates with astropy.wcs objects
wcsout.wcs.set()
wcsout.setPscale()
wcsout.setOrient()
wcsout.wcs.ctype = ['RA---TAN', 'DEC--TAN']
return wcsout | python | def build_hstwcs(crval1, crval2, crpix1, crpix2, naxis1, naxis2, pscale, orientat):
""" Create an `stwcs.wcsutil.HSTWCS` object for a default instrument without
distortion based on user provided parameter values.
"""
wcsout = wcsutil.HSTWCS()
wcsout.wcs.crval = np.array([crval1, crval2])
wcsout.wcs.crpix = np.array([crpix1, crpix2])
wcsout.naxis1 = naxis1
wcsout.naxis2 = naxis2
wcsout.wcs.cd = buildRotMatrix(orientat) * [-1, 1] * pscale / 3600.0
# Synchronize updates with astropy.wcs objects
wcsout.wcs.set()
wcsout.setPscale()
wcsout.setOrient()
wcsout.wcs.ctype = ['RA---TAN', 'DEC--TAN']
return wcsout | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | within_footprint | def within_footprint(img, wcs, x, y):
"""Determine whether input x, y fall in the science area of the image.
Parameters
----------
img : ndarray
ndarray of image where non-science areas are marked with value of NaN.
wcs : `stwcs.wcsutil.HSTWCS`
HSTWCS or WCS object with naxis terms defined.
x, y : ndarray
arrays of x, y positions for sources to be checked.
Returns
-------
x, y : ndarray
New arrays which have been trimmed of all sources that fall outside
the science areas of the image
"""
# start with limits of WCS shape
if hasattr(wcs, 'naxis1'):
naxis1 = wcs.naxis1
naxis2 = wcs.naxis2
elif hasattr(wcs, 'pixel_shape'):
naxis1, naxis2 = wcs.pixel_shape
else:
naxis1 = wcs._naxis1
naxis2 = wcs._naxis2
maskx = np.bitwise_or(x < 0, x > naxis1)
masky = np.bitwise_or(y < 0, y > naxis2)
mask = ~np.bitwise_or(maskx, masky)
x = x[mask]
y = y[mask]
# Now, confirm that these points fall within actual science area of WCS
img_mask = create_image_footprint(img, wcs, border=1.0)
inmask = np.where(img_mask[y.astype(np.int32), x.astype(np.int32)])[0]
x = x[inmask]
y = y[inmask]
return x, y | python | def within_footprint(img, wcs, x, y):
"""Determine whether input x, y fall in the science area of the image.
Parameters
----------
img : ndarray
ndarray of image where non-science areas are marked with value of NaN.
wcs : `stwcs.wcsutil.HSTWCS`
HSTWCS or WCS object with naxis terms defined.
x, y : ndarray
arrays of x, y positions for sources to be checked.
Returns
-------
x, y : ndarray
New arrays which have been trimmed of all sources that fall outside
the science areas of the image
"""
# start with limits of WCS shape
if hasattr(wcs, 'naxis1'):
naxis1 = wcs.naxis1
naxis2 = wcs.naxis2
elif hasattr(wcs, 'pixel_shape'):
naxis1, naxis2 = wcs.pixel_shape
else:
naxis1 = wcs._naxis1
naxis2 = wcs._naxis2
maskx = np.bitwise_or(x < 0, x > naxis1)
masky = np.bitwise_or(y < 0, y > naxis2)
mask = ~np.bitwise_or(maskx, masky)
x = x[mask]
y = y[mask]
# Now, confirm that these points fall within actual science area of WCS
img_mask = create_image_footprint(img, wcs, border=1.0)
inmask = np.where(img_mask[y.astype(np.int32), x.astype(np.int32)])[0]
x = x[inmask]
y = y[inmask]
return x, y | [
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HSTWCS or WCS object with naxis terms defined.
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arrays of x, y positions for sources to be checked.
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | create_image_footprint | def create_image_footprint(image, refwcs, border=0.):
""" Create the footprint of the image in the reference WCS frame.
Parameters
----------
image : `astropy.io.fits.HDUList` or str
Image to extract sources for matching to
the external astrometric catalog.
refwcs : `stwcs.wcsutil.HSTWCS`
Reference WCS for coordinate frame of image.
border : float
Buffer (in arcseconds) around edge of image to exclude astrometric
sources.
"""
# Interpret input image to generate initial source catalog and WCS
if isinstance(image, str):
image = pf.open(image)
numSci = countExtn(image, extname='SCI')
ref_x = refwcs._naxis1
ref_y = refwcs._naxis2
# convert border value into pixels
border_pixels = int(border / refwcs.pscale)
mask_arr = np.zeros((ref_y, ref_x), dtype=int)
for chip in range(numSci):
chip += 1
# Build arrays of pixel positions for all edges of chip
chip_y, chip_x = image['sci', chip].data.shape
chipwcs = wcsutil.HSTWCS(image, ext=('sci', chip))
xpix = np.arange(chip_x) + 1
ypix = np.arange(chip_y) + 1
edge_x = np.hstack([[1] * chip_y, xpix, [chip_x] * chip_y, xpix])
edge_y = np.hstack([ypix, [1] * chip_x, ypix, [chip_y] * chip_x])
edge_ra, edge_dec = chipwcs.all_pix2world(edge_x, edge_y, 1)
edge_x_out, edge_y_out = refwcs.all_world2pix(edge_ra, edge_dec, 0)
edge_x_out = np.clip(edge_x_out.astype(np.int32), 0, ref_x - 1)
edge_y_out = np.clip(edge_y_out.astype(np.int32), 0, ref_y - 1)
mask_arr[edge_y_out, edge_x_out] = 1
# Fill in outline of each chip
mask_arr = ndimage.binary_fill_holes(ndimage.binary_dilation(mask_arr, iterations=2))
if border > 0.:
mask_arr = ndimage.binary_erosion(mask_arr, iterations=border_pixels)
return mask_arr | python | def create_image_footprint(image, refwcs, border=0.):
""" Create the footprint of the image in the reference WCS frame.
Parameters
----------
image : `astropy.io.fits.HDUList` or str
Image to extract sources for matching to
the external astrometric catalog.
refwcs : `stwcs.wcsutil.HSTWCS`
Reference WCS for coordinate frame of image.
border : float
Buffer (in arcseconds) around edge of image to exclude astrometric
sources.
"""
# Interpret input image to generate initial source catalog and WCS
if isinstance(image, str):
image = pf.open(image)
numSci = countExtn(image, extname='SCI')
ref_x = refwcs._naxis1
ref_y = refwcs._naxis2
# convert border value into pixels
border_pixels = int(border / refwcs.pscale)
mask_arr = np.zeros((ref_y, ref_x), dtype=int)
for chip in range(numSci):
chip += 1
# Build arrays of pixel positions for all edges of chip
chip_y, chip_x = image['sci', chip].data.shape
chipwcs = wcsutil.HSTWCS(image, ext=('sci', chip))
xpix = np.arange(chip_x) + 1
ypix = np.arange(chip_y) + 1
edge_x = np.hstack([[1] * chip_y, xpix, [chip_x] * chip_y, xpix])
edge_y = np.hstack([ypix, [1] * chip_x, ypix, [chip_y] * chip_x])
edge_ra, edge_dec = chipwcs.all_pix2world(edge_x, edge_y, 1)
edge_x_out, edge_y_out = refwcs.all_world2pix(edge_ra, edge_dec, 0)
edge_x_out = np.clip(edge_x_out.astype(np.int32), 0, ref_x - 1)
edge_y_out = np.clip(edge_y_out.astype(np.int32), 0, ref_y - 1)
mask_arr[edge_y_out, edge_x_out] = 1
# Fill in outline of each chip
mask_arr = ndimage.binary_fill_holes(ndimage.binary_dilation(mask_arr, iterations=2))
if border > 0.:
mask_arr = ndimage.binary_erosion(mask_arr, iterations=border_pixels)
return mask_arr | [
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Reference WCS for coordinate frame of image.
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | find_hist2d_offset | def find_hist2d_offset(filename, reference, refwcs=None, refnames=['ra', 'dec'],
match_tolerance=5., chip_catalog=True, search_radius=15.0,
min_match=10, classify=True):
"""Iteratively look for the best cross-match between the catalog and ref.
Parameters
----------
filename : `~astropy.io.fits.HDUList` or str
Single image to extract sources for matching to
the external astrometric catalog.
reference : str or `~astropy.table.Table`
Reference catalog, either as a filename or ``astropy.Table``
containing astrometrically accurate sky coordinates for astrometric
standard sources.
refwcs : `~stwcs.wcsutil.HSTWCS`
This WCS will define the coordinate frame which will
be used to determine the offset. If None is specified, use the
WCS from the input image `filename` to build this WCS using
`build_self_reference()`.
refnames : list
List of table column names for sky coordinates of astrometric
standard sources from reference catalog.
match_tolerance : float
Tolerance (in pixels) for recognizing that a source position matches
an astrometric catalog position. Larger values allow for lower
accuracy source positions to be compared to astrometric catalog
chip_catalog : bool
Specify whether or not to write out individual source catalog for
each chip in the image.
search_radius : float
Maximum separation (in arcseconds) from source positions to look
for valid cross-matches with reference source positions.
min_match : int
Minimum number of cross-matches for an acceptable determination of
the offset.
classify : bool
Specify whether or not to use central_moments classification to
ignore likely cosmic-rays/bad-pixels when generating the source
catalog.
Returns
-------
best_offset : tuple
Offset in input image pixels between image source positions and
astrometric catalog positions that results in largest number of
matches of astrometric sources with image sources
seg_xy, ref_xy : astropy.Table
Source catalog and reference catalog, respectively, used for
determining the offset. Each catalog includes sources for the entire
field-of-view, not just a single chip.
"""
# Interpret input image to generate initial source catalog and WCS
if isinstance(filename, str):
image = pf.open(filename)
rootname = filename.split("_")[0]
else:
image = filename
rootname = image[0].header['rootname']
# check to see whether reference catalog can be found
if not os.path.exists(reference):
log.info("Could not find input reference catalog: {}".format(reference))
raise FileNotFoundError
# Extract reference WCS from image
if refwcs is None:
refwcs = build_self_reference(image, clean_wcs=True)
log.info("Computing offset for field-of-view defined by:")
log.info(refwcs)
# read in reference catalog
if isinstance(reference, str):
refcat = ascii.read(reference)
else:
refcat = reference
log.info("\nRead in reference catalog with {} sources.".format(len(refcat)))
ref_ra = refcat[refnames[0]]
ref_dec = refcat[refnames[1]]
# Build source catalog for entire image
img_cat = generate_source_catalog(image, refwcs, output=chip_catalog, classify=classify)
img_cat.write(filename.replace(".fits", "_xy.cat"), format='ascii.no_header',
overwrite=True)
# Retrieve source XY positions in reference frame
seg_xy = np.column_stack((img_cat['xcentroid'], img_cat['ycentroid']))
seg_xy = seg_xy[~np.isnan(seg_xy[:, 0])]
# Translate reference catalog positions into input image coordinate frame
xref, yref = refwcs.all_world2pix(ref_ra, ref_dec, 1)
# look for only sources within the viewable area of the exposure to
# determine the offset
xref, yref = within_footprint(image, refwcs, xref, yref)
ref_xy = np.column_stack((xref, yref))
log.info("\nWorking with {} astrometric sources for this field".format(len(ref_xy)))
# write out astrometric reference catalog that was actually used
ref_ra_img, ref_dec_img = refwcs.all_pix2world(xref, yref, 1)
ref_tab = Table([ref_ra_img, ref_dec_img, xref, yref], names=['ra', 'dec', 'x', 'y'])
ref_tab.write(reference.replace('.cat', '_{}.cat'.format(rootname)),
format='ascii.fast_commented_header', overwrite=True)
searchrad = search_radius / refwcs.pscale
# Use 2d-Histogram builder from drizzlepac.tweakreg -- for demo only...
xp, yp, nmatches, zpqual = build_xy_zeropoint(seg_xy, ref_xy,
searchrad=searchrad,
histplot=False, figure_id=1,
plotname=None, interactive=False)
hist2d_offset = (xp, yp)
log.info('best offset {} based on {} cross-matches'.format(hist2d_offset, nmatches))
return hist2d_offset, seg_xy, ref_xy | python | def find_hist2d_offset(filename, reference, refwcs=None, refnames=['ra', 'dec'],
match_tolerance=5., chip_catalog=True, search_radius=15.0,
min_match=10, classify=True):
"""Iteratively look for the best cross-match between the catalog and ref.
Parameters
----------
filename : `~astropy.io.fits.HDUList` or str
Single image to extract sources for matching to
the external astrometric catalog.
reference : str or `~astropy.table.Table`
Reference catalog, either as a filename or ``astropy.Table``
containing astrometrically accurate sky coordinates for astrometric
standard sources.
refwcs : `~stwcs.wcsutil.HSTWCS`
This WCS will define the coordinate frame which will
be used to determine the offset. If None is specified, use the
WCS from the input image `filename` to build this WCS using
`build_self_reference()`.
refnames : list
List of table column names for sky coordinates of astrometric
standard sources from reference catalog.
match_tolerance : float
Tolerance (in pixels) for recognizing that a source position matches
an astrometric catalog position. Larger values allow for lower
accuracy source positions to be compared to astrometric catalog
chip_catalog : bool
Specify whether or not to write out individual source catalog for
each chip in the image.
search_radius : float
Maximum separation (in arcseconds) from source positions to look
for valid cross-matches with reference source positions.
min_match : int
Minimum number of cross-matches for an acceptable determination of
the offset.
classify : bool
Specify whether or not to use central_moments classification to
ignore likely cosmic-rays/bad-pixels when generating the source
catalog.
Returns
-------
best_offset : tuple
Offset in input image pixels between image source positions and
astrometric catalog positions that results in largest number of
matches of astrometric sources with image sources
seg_xy, ref_xy : astropy.Table
Source catalog and reference catalog, respectively, used for
determining the offset. Each catalog includes sources for the entire
field-of-view, not just a single chip.
"""
# Interpret input image to generate initial source catalog and WCS
if isinstance(filename, str):
image = pf.open(filename)
rootname = filename.split("_")[0]
else:
image = filename
rootname = image[0].header['rootname']
# check to see whether reference catalog can be found
if not os.path.exists(reference):
log.info("Could not find input reference catalog: {}".format(reference))
raise FileNotFoundError
# Extract reference WCS from image
if refwcs is None:
refwcs = build_self_reference(image, clean_wcs=True)
log.info("Computing offset for field-of-view defined by:")
log.info(refwcs)
# read in reference catalog
if isinstance(reference, str):
refcat = ascii.read(reference)
else:
refcat = reference
log.info("\nRead in reference catalog with {} sources.".format(len(refcat)))
ref_ra = refcat[refnames[0]]
ref_dec = refcat[refnames[1]]
# Build source catalog for entire image
img_cat = generate_source_catalog(image, refwcs, output=chip_catalog, classify=classify)
img_cat.write(filename.replace(".fits", "_xy.cat"), format='ascii.no_header',
overwrite=True)
# Retrieve source XY positions in reference frame
seg_xy = np.column_stack((img_cat['xcentroid'], img_cat['ycentroid']))
seg_xy = seg_xy[~np.isnan(seg_xy[:, 0])]
# Translate reference catalog positions into input image coordinate frame
xref, yref = refwcs.all_world2pix(ref_ra, ref_dec, 1)
# look for only sources within the viewable area of the exposure to
# determine the offset
xref, yref = within_footprint(image, refwcs, xref, yref)
ref_xy = np.column_stack((xref, yref))
log.info("\nWorking with {} astrometric sources for this field".format(len(ref_xy)))
# write out astrometric reference catalog that was actually used
ref_ra_img, ref_dec_img = refwcs.all_pix2world(xref, yref, 1)
ref_tab = Table([ref_ra_img, ref_dec_img, xref, yref], names=['ra', 'dec', 'x', 'y'])
ref_tab.write(reference.replace('.cat', '_{}.cat'.format(rootname)),
format='ascii.fast_commented_header', overwrite=True)
searchrad = search_radius / refwcs.pscale
# Use 2d-Histogram builder from drizzlepac.tweakreg -- for demo only...
xp, yp, nmatches, zpqual = build_xy_zeropoint(seg_xy, ref_xy,
searchrad=searchrad,
histplot=False, figure_id=1,
plotname=None, interactive=False)
hist2d_offset = (xp, yp)
log.info('best offset {} based on {} cross-matches'.format(hist2d_offset, nmatches))
return hist2d_offset, seg_xy, ref_xy | [
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... | Iteratively look for the best cross-match between the catalog and ref.
Parameters
----------
filename : `~astropy.io.fits.HDUList` or str
Single image to extract sources for matching to
the external astrometric catalog.
reference : str or `~astropy.table.Table`
Reference catalog, either as a filename or ``astropy.Table``
containing astrometrically accurate sky coordinates for astrometric
standard sources.
refwcs : `~stwcs.wcsutil.HSTWCS`
This WCS will define the coordinate frame which will
be used to determine the offset. If None is specified, use the
WCS from the input image `filename` to build this WCS using
`build_self_reference()`.
refnames : list
List of table column names for sky coordinates of astrometric
standard sources from reference catalog.
match_tolerance : float
Tolerance (in pixels) for recognizing that a source position matches
an astrometric catalog position. Larger values allow for lower
accuracy source positions to be compared to astrometric catalog
chip_catalog : bool
Specify whether or not to write out individual source catalog for
each chip in the image.
search_radius : float
Maximum separation (in arcseconds) from source positions to look
for valid cross-matches with reference source positions.
min_match : int
Minimum number of cross-matches for an acceptable determination of
the offset.
classify : bool
Specify whether or not to use central_moments classification to
ignore likely cosmic-rays/bad-pixels when generating the source
catalog.
Returns
-------
best_offset : tuple
Offset in input image pixels between image source positions and
astrometric catalog positions that results in largest number of
matches of astrometric sources with image sources
seg_xy, ref_xy : astropy.Table
Source catalog and reference catalog, respectively, used for
determining the offset. Each catalog includes sources for the entire
field-of-view, not just a single chip. | [
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spacetelescope/drizzlepac | drizzlepac/hlautils/astrometric_utils.py | build_wcscat | def build_wcscat(image, group_id, source_catalog):
""" Return a list of `~tweakwcs.tpwcs.FITSWCS` objects for all chips in an image.
Parameters
----------
image : str, ~astropy.io.fits.HDUList`
Either filename or HDUList of a single HST observation.
group_id : int
Integer ID for group this image should be associated with; primarily
used when separate chips are in separate files to treat them all as one
exposure.
source_catalog : dict
If provided, these catalogs will be attached as `catalog`
entries in each chip's ``FITSWCS`` object. It should be provided as a
dict of astropy Tables identified by chip number with
each table containing sources from image extension ``('sci', chip)`` as
generated by `generate_source_catalog()`.
Returns
-------
wcs_catalogs : list of `~tweakwcs.tpwcs.FITSWCS`
List of `~tweakwcs.tpwcs.FITSWCS` objects defined for all chips in input image.
"""
open_file = False
if isinstance(image, str):
hdulist = pf.open(image)
open_file = True
elif isinstance(image, pf.HDUList):
hdulist = image
else:
log.info("Wrong type of input, {}, for build_wcscat...".format(type(image)))
raise ValueError
wcs_catalogs = []
numsci = countExtn(hdulist)
for chip in range(1, numsci + 1):
w = wcsutil.HSTWCS(hdulist, ('SCI', chip))
imcat = source_catalog[chip]
# rename xcentroid/ycentroid columns, if necessary, to be consistent with tweakwcs
if 'xcentroid' in imcat.colnames:
imcat.rename_column('xcentroid', 'x')
imcat.rename_column('ycentroid', 'y')
wcscat = FITSWCS(
w,
meta={
'chip': chip,
'group_id': group_id,
'filename': image,
'catalog': imcat,
'name': image
}
)
wcs_catalogs.append(wcscat)
if open_file:
hdulist.close()
return wcs_catalogs | python | def build_wcscat(image, group_id, source_catalog):
""" Return a list of `~tweakwcs.tpwcs.FITSWCS` objects for all chips in an image.
Parameters
----------
image : str, ~astropy.io.fits.HDUList`
Either filename or HDUList of a single HST observation.
group_id : int
Integer ID for group this image should be associated with; primarily
used when separate chips are in separate files to treat them all as one
exposure.
source_catalog : dict
If provided, these catalogs will be attached as `catalog`
entries in each chip's ``FITSWCS`` object. It should be provided as a
dict of astropy Tables identified by chip number with
each table containing sources from image extension ``('sci', chip)`` as
generated by `generate_source_catalog()`.
Returns
-------
wcs_catalogs : list of `~tweakwcs.tpwcs.FITSWCS`
List of `~tweakwcs.tpwcs.FITSWCS` objects defined for all chips in input image.
"""
open_file = False
if isinstance(image, str):
hdulist = pf.open(image)
open_file = True
elif isinstance(image, pf.HDUList):
hdulist = image
else:
log.info("Wrong type of input, {}, for build_wcscat...".format(type(image)))
raise ValueError
wcs_catalogs = []
numsci = countExtn(hdulist)
for chip in range(1, numsci + 1):
w = wcsutil.HSTWCS(hdulist, ('SCI', chip))
imcat = source_catalog[chip]
# rename xcentroid/ycentroid columns, if necessary, to be consistent with tweakwcs
if 'xcentroid' in imcat.colnames:
imcat.rename_column('xcentroid', 'x')
imcat.rename_column('ycentroid', 'y')
wcscat = FITSWCS(
w,
meta={
'chip': chip,
'group_id': group_id,
'filename': image,
'catalog': imcat,
'name': image
}
)
wcs_catalogs.append(wcscat)
if open_file:
hdulist.close()
return wcs_catalogs | [
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Either filename or HDUList of a single HST observation.
group_id : int
Integer ID for group this image should be associated with; primarily
used when separate chips are in separate files to treat them all as one
exposure.
source_catalog : dict
If provided, these catalogs will be attached as `catalog`
entries in each chip's ``FITSWCS`` object. It should be provided as a
dict of astropy Tables identified by chip number with
each table containing sources from image extension ``('sci', chip)`` as
generated by `generate_source_catalog()`.
Returns
-------
wcs_catalogs : list of `~tweakwcs.tpwcs.FITSWCS`
List of `~tweakwcs.tpwcs.FITSWCS` objects defined for all chips in input image. | [
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spacetelescope/drizzlepac | drizzlepac/updatehdr.py | update_from_shiftfile | def update_from_shiftfile(shiftfile,wcsname=None,force=False):
"""
Update headers of all images specified in shiftfile with shifts
from shiftfile.
Parameters
----------
shiftfile : str
Filename of shiftfile.
wcsname : str
Label to give to new WCS solution being created by this fit. If
a value of None is given, it will automatically use 'TWEAK' as the
label. [Default =None]
force : bool
Update header even though WCS already exists with this solution or
wcsname? [Default=False]
"""
f = open(fileutil.osfn(shiftfile))
shift_lines = [x.strip() for x in f.readlines()]
f.close()
# interpret header of shift file
for line in shift_lines:
if 'refimage' in line or 'reference' in line:
refimage = line.split(':')[-1]
refimage = refimage[:refimage.find('[wcs]')].lstrip()
break
# Determine the max length in the first column (filenames)
fnames = []
for row in shift_lines:
if row[0] == '#': continue
fnames.append(len(row.split(' ')[0]))
fname_fmt = 'S{0}'.format(max(fnames))
# Now read in numerical values from shiftfile
type_list = {'names':('fnames','xsh','ysh','rot','scale','xrms','yrms'),
'formats':(fname_fmt,'f4','f4','f4','f4','f4','f4')}
try:
sdict = np.loadtxt(shiftfile,dtype=type_list,unpack=False)
except IndexError:
tlist = {'names':('fnames','xsh','ysh','rot','scale'),
'formats':(fname_fmt,'f4','f4','f4','f4')}
s = np.loadtxt(shiftfile,dtype=tlist,unpack=False)
sdict = np.zeros([s['fnames'].shape[0],],dtype=type_list)
for sname in s.dtype.names:
sdict[sname] = s[sname]
for img in sdict:
updatewcs_with_shift(img['fnames'], refimage, wcsname=wcsname,
rot=img['rot'], scale=img['scale'],
xsh=img['xsh'], ysh=img['ysh'],
xrms=img['xrms'], yrms=img['yrms'],
force=force) | python | def update_from_shiftfile(shiftfile,wcsname=None,force=False):
"""
Update headers of all images specified in shiftfile with shifts
from shiftfile.
Parameters
----------
shiftfile : str
Filename of shiftfile.
wcsname : str
Label to give to new WCS solution being created by this fit. If
a value of None is given, it will automatically use 'TWEAK' as the
label. [Default =None]
force : bool
Update header even though WCS already exists with this solution or
wcsname? [Default=False]
"""
f = open(fileutil.osfn(shiftfile))
shift_lines = [x.strip() for x in f.readlines()]
f.close()
# interpret header of shift file
for line in shift_lines:
if 'refimage' in line or 'reference' in line:
refimage = line.split(':')[-1]
refimage = refimage[:refimage.find('[wcs]')].lstrip()
break
# Determine the max length in the first column (filenames)
fnames = []
for row in shift_lines:
if row[0] == '#': continue
fnames.append(len(row.split(' ')[0]))
fname_fmt = 'S{0}'.format(max(fnames))
# Now read in numerical values from shiftfile
type_list = {'names':('fnames','xsh','ysh','rot','scale','xrms','yrms'),
'formats':(fname_fmt,'f4','f4','f4','f4','f4','f4')}
try:
sdict = np.loadtxt(shiftfile,dtype=type_list,unpack=False)
except IndexError:
tlist = {'names':('fnames','xsh','ysh','rot','scale'),
'formats':(fname_fmt,'f4','f4','f4','f4')}
s = np.loadtxt(shiftfile,dtype=tlist,unpack=False)
sdict = np.zeros([s['fnames'].shape[0],],dtype=type_list)
for sname in s.dtype.names:
sdict[sname] = s[sname]
for img in sdict:
updatewcs_with_shift(img['fnames'], refimage, wcsname=wcsname,
rot=img['rot'], scale=img['scale'],
xsh=img['xsh'], ysh=img['ysh'],
xrms=img['xrms'], yrms=img['yrms'],
force=force) | [
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Filename of shiftfile.
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Label to give to new WCS solution being created by this fit. If
a value of None is given, it will automatically use 'TWEAK' as the
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force : bool
Update header even though WCS already exists with this solution or
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spacetelescope/drizzlepac | drizzlepac/updatehdr.py | linearize | def linearize(wcsim, wcsima, wcsref, imcrpix, f, shift, hx=1.0, hy=1.0):
""" linearization using 5-point formula for first order derivative
"""
x0 = imcrpix[0]
y0 = imcrpix[1]
p = np.asarray([[x0, y0],
[x0 - hx, y0],
[x0 - hx * 0.5, y0],
[x0 + hx * 0.5, y0],
[x0 + hx, y0],
[x0, y0 - hy],
[x0, y0 - hy * 0.5],
[x0, y0 + hy * 0.5],
[x0, y0 + hy]],
dtype=np.float64)
# convert image coordinates to reference image coordinates:
p = wcsref.wcs_world2pix(wcsim.wcs_pix2world(p, 1), 1).astype(ndfloat128)
# apply linear fit transformation:
p = np.dot(f, (p - shift).T).T
# convert back to image coordinate system:
p = wcsima.wcs_world2pix(
wcsref.wcs_pix2world(p.astype(np.float64), 1), 1).astype(ndfloat128)
# derivative with regard to x:
u1 = ((p[1] - p[4]) + 8 * (p[3] - p[2])) / (6*hx)
# derivative with regard to y:
u2 = ((p[5] - p[8]) + 8 * (p[7] - p[6])) / (6*hy)
return (np.asarray([u1, u2]).T, p[0]) | python | def linearize(wcsim, wcsima, wcsref, imcrpix, f, shift, hx=1.0, hy=1.0):
""" linearization using 5-point formula for first order derivative
"""
x0 = imcrpix[0]
y0 = imcrpix[1]
p = np.asarray([[x0, y0],
[x0 - hx, y0],
[x0 - hx * 0.5, y0],
[x0 + hx * 0.5, y0],
[x0 + hx, y0],
[x0, y0 - hy],
[x0, y0 - hy * 0.5],
[x0, y0 + hy * 0.5],
[x0, y0 + hy]],
dtype=np.float64)
# convert image coordinates to reference image coordinates:
p = wcsref.wcs_world2pix(wcsim.wcs_pix2world(p, 1), 1).astype(ndfloat128)
# apply linear fit transformation:
p = np.dot(f, (p - shift).T).T
# convert back to image coordinate system:
p = wcsima.wcs_world2pix(
wcsref.wcs_pix2world(p.astype(np.float64), 1), 1).astype(ndfloat128)
# derivative with regard to x:
u1 = ((p[1] - p[4]) + 8 * (p[3] - p[2])) / (6*hx)
# derivative with regard to y:
u2 = ((p[5] - p[8]) + 8 * (p[7] - p[6])) / (6*hy)
return (np.asarray([u1, u2]).T, p[0]) | [
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spacetelescope/drizzlepac | drizzlepac/updatehdr.py | update_wcs | def update_wcs(image,extnum,new_wcs,wcsname="",reusename=False,verbose=False):
"""
Updates the WCS of the specified extension number with the new WCS
after archiving the original WCS.
The value of 'new_wcs' needs to be the full
HSTWCS object.
Parameters
----------
image : str
Filename of image with WCS that needs to be updated
extnum : int
Extension number for extension with WCS to be updated/replaced
new_wcs : object
Full HSTWCS object which will replace/update the existing WCS
wcsname : str
Label to give newly updated WCS
reusename : bool
User can choose whether to over-write WCS with same name or not.
[Default: False]
verbose : bool, int
Print extra messages during processing? [Default: False]
"""
# Start by insuring that the correct value of 'orientat' has been computed
new_wcs.setOrient()
fimg_open=False
if not isinstance(image, fits.HDUList):
fimg = fits.open(image, mode='update', memmap=False)
fimg_open = True
fimg_update = True
else:
fimg = image
if fimg.fileinfo(0)['filemode'] is 'update':
fimg_update = True
else:
fimg_update = False
# Determine final (unique) WCSNAME value, either based on the default or
# user-provided name
if util.is_blank(wcsname):
wcsname = 'TWEAK'
if not reusename:
wcsname = create_unique_wcsname(fimg, extnum, wcsname)
idchdr = True
if new_wcs.idcscale is None:
idchdr = False
# Open the file for updating the WCS
try:
logstr = 'Updating header for %s[%s]'%(fimg.filename(),str(extnum))
if verbose:
print(logstr)
else:
log.info(logstr)
hdr = fimg[extnum].header
if verbose:
log.info(' with WCS of')
new_wcs.printwcs()
print("WCSNAME : ",wcsname)
# Insure that if a copy of the WCS has not been created yet, it will be now
wcs_hdr = new_wcs.wcs2header(idc2hdr=idchdr, relax=True)
for key in wcs_hdr:
hdr[key] = wcs_hdr[key]
hdr['ORIENTAT'] = new_wcs.orientat
hdr['WCSNAME'] = wcsname
util.updateNEXTENDKw(fimg)
# Only if this image was opened in update mode should this
# newly updated WCS be archived, as it will never be written out
# to a file otherwise.
if fimg_update:
if not reusename:
# Save the newly updated WCS as an alternate WCS as well
wkey = wcsutil.altwcs.next_wcskey(fimg,ext=extnum)
else:
wkey = wcsutil.altwcs.getKeyFromName(hdr,wcsname)
# wcskey needs to be specified so that archiveWCS will create a
# duplicate WCS with the same WCSNAME as the Primary WCS
wcsutil.altwcs.archiveWCS(fimg,[extnum],wcsname=wcsname,
wcskey=wkey, reusekey=reusename)
finally:
if fimg_open:
# finish up by closing the file now
fimg.close() | python | def update_wcs(image,extnum,new_wcs,wcsname="",reusename=False,verbose=False):
"""
Updates the WCS of the specified extension number with the new WCS
after archiving the original WCS.
The value of 'new_wcs' needs to be the full
HSTWCS object.
Parameters
----------
image : str
Filename of image with WCS that needs to be updated
extnum : int
Extension number for extension with WCS to be updated/replaced
new_wcs : object
Full HSTWCS object which will replace/update the existing WCS
wcsname : str
Label to give newly updated WCS
reusename : bool
User can choose whether to over-write WCS with same name or not.
[Default: False]
verbose : bool, int
Print extra messages during processing? [Default: False]
"""
# Start by insuring that the correct value of 'orientat' has been computed
new_wcs.setOrient()
fimg_open=False
if not isinstance(image, fits.HDUList):
fimg = fits.open(image, mode='update', memmap=False)
fimg_open = True
fimg_update = True
else:
fimg = image
if fimg.fileinfo(0)['filemode'] is 'update':
fimg_update = True
else:
fimg_update = False
# Determine final (unique) WCSNAME value, either based on the default or
# user-provided name
if util.is_blank(wcsname):
wcsname = 'TWEAK'
if not reusename:
wcsname = create_unique_wcsname(fimg, extnum, wcsname)
idchdr = True
if new_wcs.idcscale is None:
idchdr = False
# Open the file for updating the WCS
try:
logstr = 'Updating header for %s[%s]'%(fimg.filename(),str(extnum))
if verbose:
print(logstr)
else:
log.info(logstr)
hdr = fimg[extnum].header
if verbose:
log.info(' with WCS of')
new_wcs.printwcs()
print("WCSNAME : ",wcsname)
# Insure that if a copy of the WCS has not been created yet, it will be now
wcs_hdr = new_wcs.wcs2header(idc2hdr=idchdr, relax=True)
for key in wcs_hdr:
hdr[key] = wcs_hdr[key]
hdr['ORIENTAT'] = new_wcs.orientat
hdr['WCSNAME'] = wcsname
util.updateNEXTENDKw(fimg)
# Only if this image was opened in update mode should this
# newly updated WCS be archived, as it will never be written out
# to a file otherwise.
if fimg_update:
if not reusename:
# Save the newly updated WCS as an alternate WCS as well
wkey = wcsutil.altwcs.next_wcskey(fimg,ext=extnum)
else:
wkey = wcsutil.altwcs.getKeyFromName(hdr,wcsname)
# wcskey needs to be specified so that archiveWCS will create a
# duplicate WCS with the same WCSNAME as the Primary WCS
wcsutil.altwcs.archiveWCS(fimg,[extnum],wcsname=wcsname,
wcskey=wkey, reusekey=reusename)
finally:
if fimg_open:
# finish up by closing the file now
fimg.close() | [
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The value of 'new_wcs' needs to be the full
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----------
image : str
Filename of image with WCS that needs to be updated
extnum : int
Extension number for extension with WCS to be updated/replaced
new_wcs : object
Full HSTWCS object which will replace/update the existing WCS
wcsname : str
Label to give newly updated WCS
reusename : bool
User can choose whether to over-write WCS with same name or not.
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verbose : bool, int
Print extra messages during processing? [Default: False] | [
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spacetelescope/drizzlepac | drizzlepac/updatehdr.py | create_unique_wcsname | def create_unique_wcsname(fimg, extnum, wcsname):
"""
This function evaluates whether the specified wcsname value has
already been used in this image. If so, it automatically modifies
the name with a simple version ID using wcsname_NNN format.
Parameters
----------
fimg : obj
PyFITS object of image with WCS information to be updated
extnum : int
Index of extension with WCS information to be updated
wcsname : str
Value of WCSNAME specified by user for labelling the new WCS
Returns
-------
uniqname : str
Unique WCSNAME value
"""
wnames = list(wcsutil.altwcs.wcsnames(fimg, ext=extnum).values())
if wcsname not in wnames:
uniqname = wcsname
else:
# setup pattern to match
rpatt = re.compile(wcsname+'_\d')
index = 0
for wname in wnames:
rmatch = rpatt.match(wname)
if rmatch:
# get index
n = int(wname[wname.rfind('_')+1:])
if n > index: index = 1
index += 1 # for use with new name
uniqname = "%s_%d"%(wcsname,index)
return uniqname | python | def create_unique_wcsname(fimg, extnum, wcsname):
"""
This function evaluates whether the specified wcsname value has
already been used in this image. If so, it automatically modifies
the name with a simple version ID using wcsname_NNN format.
Parameters
----------
fimg : obj
PyFITS object of image with WCS information to be updated
extnum : int
Index of extension with WCS information to be updated
wcsname : str
Value of WCSNAME specified by user for labelling the new WCS
Returns
-------
uniqname : str
Unique WCSNAME value
"""
wnames = list(wcsutil.altwcs.wcsnames(fimg, ext=extnum).values())
if wcsname not in wnames:
uniqname = wcsname
else:
# setup pattern to match
rpatt = re.compile(wcsname+'_\d')
index = 0
for wname in wnames:
rmatch = rpatt.match(wname)
if rmatch:
# get index
n = int(wname[wname.rfind('_')+1:])
if n > index: index = 1
index += 1 # for use with new name
uniqname = "%s_%d"%(wcsname,index)
return uniqname | [
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fimg : obj
PyFITS object of image with WCS information to be updated
extnum : int
Index of extension with WCS information to be updated
wcsname : str
Value of WCSNAME specified by user for labelling the new WCS
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uniqname : str
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spacetelescope/drizzlepac | drizzlepac/util.py | end_logging | def end_logging(filename=None):
"""
Close log file and restore system defaults.
"""
if logutil.global_logging_started:
if filename:
print('Trailer file written to: ', filename)
else:
# This generally shouldn't happen if logging was started with
# init_logging and a filename was given...
print('No trailer file saved...')
logutil.teardown_global_logging()
else:
print('No trailer file saved...') | python | def end_logging(filename=None):
"""
Close log file and restore system defaults.
"""
if logutil.global_logging_started:
if filename:
print('Trailer file written to: ', filename)
else:
# This generally shouldn't happen if logging was started with
# init_logging and a filename was given...
print('No trailer file saved...')
logutil.teardown_global_logging()
else:
print('No trailer file saved...') | [
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spacetelescope/drizzlepac | drizzlepac/util.py | findrootname | def findrootname(filename):
"""
Return the rootname of the given file.
"""
puncloc = [filename.find(char) for char in string.punctuation]
if sys.version_info[0] >= 3:
val = sys.maxsize
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for num in puncloc:
if num !=-1 and num < val:
val = num
return filename[0:val] | python | def findrootname(filename):
"""
Return the rootname of the given file.
"""
puncloc = [filename.find(char) for char in string.punctuation]
if sys.version_info[0] >= 3:
val = sys.maxsize
else:
val = sys.maxint
for num in puncloc:
if num !=-1 and num < val:
val = num
return filename[0:val] | [
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spacetelescope/drizzlepac | drizzlepac/util.py | removeFileSafely | def removeFileSafely(filename,clobber=True):
""" Delete the file specified, but only if it exists and clobber is True.
"""
if filename is not None and filename.strip() != '':
if os.path.exists(filename) and clobber: os.remove(filename) | python | def removeFileSafely(filename,clobber=True):
""" Delete the file specified, but only if it exists and clobber is True.
"""
if filename is not None and filename.strip() != '':
if os.path.exists(filename) and clobber: os.remove(filename) | [
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spacetelescope/drizzlepac | drizzlepac/util.py | displayEmptyInputWarningBox | def displayEmptyInputWarningBox(display=True, parent=None):
""" Displays a warning box for the 'input' parameter.
"""
if sys.version_info[0] >= 3:
from tkinter.messagebox import showwarning
else:
from tkMessageBox import showwarning
if display:
msg = 'No valid input files found! '+\
'Please check the value for the "input" parameter.'
showwarning(parent=parent,message=msg, title="No valid inputs!")
return "yes" | python | def displayEmptyInputWarningBox(display=True, parent=None):
""" Displays a warning box for the 'input' parameter.
"""
if sys.version_info[0] >= 3:
from tkinter.messagebox import showwarning
else:
from tkMessageBox import showwarning
if display:
msg = 'No valid input files found! '+\
'Please check the value for the "input" parameter.'
showwarning(parent=parent,message=msg, title="No valid inputs!")
return "yes" | [
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spacetelescope/drizzlepac | drizzlepac/util.py | count_sci_extensions | def count_sci_extensions(filename):
""" Return the number of SCI extensions and the EXTNAME from a input MEF file.
"""
num_sci = 0
extname = 'SCI'
hdu_list = fileutil.openImage(filename, memmap=False)
for extn in hdu_list:
if 'extname' in extn.header and extn.header['extname'] == extname:
num_sci += 1
if num_sci == 0:
extname = 'PRIMARY'
num_sci = 1
hdu_list.close()
return num_sci,extname | python | def count_sci_extensions(filename):
""" Return the number of SCI extensions and the EXTNAME from a input MEF file.
"""
num_sci = 0
extname = 'SCI'
hdu_list = fileutil.openImage(filename, memmap=False)
for extn in hdu_list:
if 'extname' in extn.header and extn.header['extname'] == extname:
num_sci += 1
if num_sci == 0:
extname = 'PRIMARY'
num_sci = 1
hdu_list.close()
return num_sci,extname | [
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spacetelescope/drizzlepac | drizzlepac/util.py | verifyUniqueWcsname | def verifyUniqueWcsname(fname,wcsname):
"""
Report whether or not the specified WCSNAME already exists in the file
"""
uniq = True
numsci,extname = count_sci_extensions(fname)
wnames = altwcs.wcsnames(fname,ext=(extname,1))
if wcsname in wnames.values():
uniq = False
return uniq | python | def verifyUniqueWcsname(fname,wcsname):
"""
Report whether or not the specified WCSNAME already exists in the file
"""
uniq = True
numsci,extname = count_sci_extensions(fname)
wnames = altwcs.wcsnames(fname,ext=(extname,1))
if wcsname in wnames.values():
uniq = False
return uniq | [
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spacetelescope/drizzlepac | drizzlepac/util.py | verifyUpdatewcs | def verifyUpdatewcs(fname):
"""
Verify the existence of WCSNAME in the file. If it is not present,
report this to the user and raise an exception. Returns True if WCSNAME
was found in all SCI extensions.
"""
updated = True
numsci,extname = count_sci_extensions(fname)
for n in range(1,numsci+1):
hdr = fits.getheader(fname, extname=extname, extver=n, memmap=False)
if 'wcsname' not in hdr:
updated = False
break
return updated | python | def verifyUpdatewcs(fname):
"""
Verify the existence of WCSNAME in the file. If it is not present,
report this to the user and raise an exception. Returns True if WCSNAME
was found in all SCI extensions.
"""
updated = True
numsci,extname = count_sci_extensions(fname)
for n in range(1,numsci+1):
hdr = fits.getheader(fname, extname=extname, extver=n, memmap=False)
if 'wcsname' not in hdr:
updated = False
break
return updated | [
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spacetelescope/drizzlepac | drizzlepac/util.py | verifyRefimage | def verifyRefimage(refimage):
"""
Verify that the value of refimage specified by the user points to an
extension with a proper WCS defined. It starts by making sure an extension gets
specified by the user when using a MEF file. The final check comes by looking
for a CD matrix in the WCS object itself. If either test fails, it returns
a value of False.
"""
valid = True
# start by trying to see whether the code can even find the file
if is_blank(refimage):
valid=True
return valid
refroot,extroot = fileutil.parseFilename(refimage)
if not os.path.exists(refroot):
valid = False
return valid
# if a MEF has been specified, make sure extension contains a valid WCS
if valid:
if extroot is None:
extn = findWCSExtn(refimage)
if extn is None:
valid = False
else:
valid = True
else:
# check for CD matrix in WCS object
refwcs = wcsutil.HSTWCS(refimage)
if not refwcs.wcs.has_cd():
valid = False
else:
valid = True
del refwcs
return valid | python | def verifyRefimage(refimage):
"""
Verify that the value of refimage specified by the user points to an
extension with a proper WCS defined. It starts by making sure an extension gets
specified by the user when using a MEF file. The final check comes by looking
for a CD matrix in the WCS object itself. If either test fails, it returns
a value of False.
"""
valid = True
# start by trying to see whether the code can even find the file
if is_blank(refimage):
valid=True
return valid
refroot,extroot = fileutil.parseFilename(refimage)
if not os.path.exists(refroot):
valid = False
return valid
# if a MEF has been specified, make sure extension contains a valid WCS
if valid:
if extroot is None:
extn = findWCSExtn(refimage)
if extn is None:
valid = False
else:
valid = True
else:
# check for CD matrix in WCS object
refwcs = wcsutil.HSTWCS(refimage)
if not refwcs.wcs.has_cd():
valid = False
else:
valid = True
del refwcs
return valid | [
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spacetelescope/drizzlepac | drizzlepac/util.py | findWCSExtn | def findWCSExtn(filename):
""" Return new filename with extension that points to an extension with a
valid WCS.
Returns
=======
extnum : str, None
Value of extension name as a string either as provided by the user
or based on the extension number for the first extension which
contains a valid HSTWCS object. Returns None if no extension can be
found with a valid WCS.
Notes
=====
The return value from this function can be used as input to
create another HSTWCS with the syntax::
`HSTWCS('{}[{}]'.format(filename,extnum))
"""
rootname,extroot = fileutil.parseFilename(filename)
extnum = None
if extroot is None:
fimg = fits.open(rootname, memmap=False)
for i,extn in enumerate(fimg):
if 'crval1' in extn.header:
refwcs = wcsutil.HSTWCS('{}[{}]'.format(rootname,i))
if refwcs.wcs.has_cd():
extnum = '{}'.format(i)
break
fimg.close()
else:
try:
refwcs = wcsutil.HSTWCS(filename)
if refwcs.wcs.has_cd():
extnum = extroot
except:
extnum = None
return extnum | python | def findWCSExtn(filename):
""" Return new filename with extension that points to an extension with a
valid WCS.
Returns
=======
extnum : str, None
Value of extension name as a string either as provided by the user
or based on the extension number for the first extension which
contains a valid HSTWCS object. Returns None if no extension can be
found with a valid WCS.
Notes
=====
The return value from this function can be used as input to
create another HSTWCS with the syntax::
`HSTWCS('{}[{}]'.format(filename,extnum))
"""
rootname,extroot = fileutil.parseFilename(filename)
extnum = None
if extroot is None:
fimg = fits.open(rootname, memmap=False)
for i,extn in enumerate(fimg):
if 'crval1' in extn.header:
refwcs = wcsutil.HSTWCS('{}[{}]'.format(rootname,i))
if refwcs.wcs.has_cd():
extnum = '{}'.format(i)
break
fimg.close()
else:
try:
refwcs = wcsutil.HSTWCS(filename)
if refwcs.wcs.has_cd():
extnum = extroot
except:
extnum = None
return extnum | [
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The return value from this function can be used as input to
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spacetelescope/drizzlepac | drizzlepac/util.py | verifyFilePermissions | def verifyFilePermissions(filelist, chmod=True):
""" Verify that images specified in 'filelist' can be updated.
A message will be printed reporting the names of any images which
do not have write-permission, then quit.
"""
badfiles = []
archive_dir = False
for img in filelist:
fname = fileutil.osfn(img)
if 'OrIg_files' in os.path.split(fname)[0]:
archive_dir = True
try:
fp = open(fname,mode='a')
fp.close()
except IOError as e:
if e.errno == errno.EACCES:
badfiles.append(img)
# Not a permission error.
pass
num_bad = len(badfiles)
if num_bad > 0:
if archive_dir:
print('\n')
print('#'*40)
print(' Working in "OrIg_files" (archive) directory. ')
print(' This directory has been created to serve as an archive')
print(' for the original input images. ')
print('\n These files should be copied into another directory')
print(' for processing. ')
print('#'*40)
print('\n')
print('#'*40)
print('Found %d files which can not be updated!'%(num_bad))
for img in badfiles:
print(' %s'%(img))
print('\nPlease reset permissions for these files and restart...')
print('#'*40)
print('\n')
filelist = None
return filelist | python | def verifyFilePermissions(filelist, chmod=True):
""" Verify that images specified in 'filelist' can be updated.
A message will be printed reporting the names of any images which
do not have write-permission, then quit.
"""
badfiles = []
archive_dir = False
for img in filelist:
fname = fileutil.osfn(img)
if 'OrIg_files' in os.path.split(fname)[0]:
archive_dir = True
try:
fp = open(fname,mode='a')
fp.close()
except IOError as e:
if e.errno == errno.EACCES:
badfiles.append(img)
# Not a permission error.
pass
num_bad = len(badfiles)
if num_bad > 0:
if archive_dir:
print('\n')
print('#'*40)
print(' Working in "OrIg_files" (archive) directory. ')
print(' This directory has been created to serve as an archive')
print(' for the original input images. ')
print('\n These files should be copied into another directory')
print(' for processing. ')
print('#'*40)
print('\n')
print('#'*40)
print('Found %d files which can not be updated!'%(num_bad))
for img in badfiles:
print(' %s'%(img))
print('\nPlease reset permissions for these files and restart...')
print('#'*40)
print('\n')
filelist = None
return filelist | [
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spacetelescope/drizzlepac | drizzlepac/util.py | getFullParList | def getFullParList(configObj):
"""
Return a single list of all parameter names included in the configObj
regardless of which section the parameter was stored
"""
plist = []
for par in configObj.keys():
if isinstance(configObj[par],configobj.Section):
plist.extend(getFullParList(configObj[par]))
else:
plist.append(par)
return plist | python | def getFullParList(configObj):
"""
Return a single list of all parameter names included in the configObj
regardless of which section the parameter was stored
"""
plist = []
for par in configObj.keys():
if isinstance(configObj[par],configobj.Section):
plist.extend(getFullParList(configObj[par]))
else:
plist.append(par)
return plist | [
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spacetelescope/drizzlepac | drizzlepac/util.py | validateUserPars | def validateUserPars(configObj,input_dict):
""" Compares input parameter names specified by user with those already
recognized by the task.
Any parameters provided by the user that does not match a known
task parameter will be reported and a ValueError exception will be
raised.
"""
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
plist = getFullParList(configObj)
extra_pars = []
for kw in input_dict:
if kw not in plist:
extra_pars.append(kw)
if len(extra_pars) > 0:
print ('='*40)
print ('The following input parameters were not recognized as valid inputs:')
for p in extra_pars:
print(" %s"%(p))
print('\nPlease check the spelling of the parameter(s) and try again...')
print('='*40)
raise ValueError | python | def validateUserPars(configObj,input_dict):
""" Compares input parameter names specified by user with those already
recognized by the task.
Any parameters provided by the user that does not match a known
task parameter will be reported and a ValueError exception will be
raised.
"""
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
plist = getFullParList(configObj)
extra_pars = []
for kw in input_dict:
if kw not in plist:
extra_pars.append(kw)
if len(extra_pars) > 0:
print ('='*40)
print ('The following input parameters were not recognized as valid inputs:')
for p in extra_pars:
print(" %s"%(p))
print('\nPlease check the spelling of the parameter(s) and try again...')
print('='*40)
raise ValueError | [
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spacetelescope/drizzlepac | drizzlepac/util.py | applyUserPars_steps | def applyUserPars_steps(configObj, input_dict, step='3a'):
""" Apply logic to turn on use of user-specified output WCS if user provides
any parameter on command-line regardless of how final_wcs was set.
"""
step_kws = {'7a': 'final_wcs', '3a': 'driz_sep_wcs'}
stepname = getSectionName(configObj,step)
finalParDict = configObj[stepname].copy()
del finalParDict[step_kws[step]]
# interpret input_dict to find any parameters for this step specified by the user
user_pars = {}
for kw in finalParDict:
if kw in input_dict: user_pars[kw] = input_dict[kw]
if len(user_pars) > 0:
configObj[stepname][step_kws[step]] = True | python | def applyUserPars_steps(configObj, input_dict, step='3a'):
""" Apply logic to turn on use of user-specified output WCS if user provides
any parameter on command-line regardless of how final_wcs was set.
"""
step_kws = {'7a': 'final_wcs', '3a': 'driz_sep_wcs'}
stepname = getSectionName(configObj,step)
finalParDict = configObj[stepname].copy()
del finalParDict[step_kws[step]]
# interpret input_dict to find any parameters for this step specified by the user
user_pars = {}
for kw in finalParDict:
if kw in input_dict: user_pars[kw] = input_dict[kw]
if len(user_pars) > 0:
configObj[stepname][step_kws[step]] = True | [
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spacetelescope/drizzlepac | drizzlepac/util.py | getDefaultConfigObj | def getDefaultConfigObj(taskname,configObj,input_dict={},loadOnly=True):
""" Return default configObj instance for task updated
with user-specified values from input_dict.
Parameters
----------
taskname : string
Name of task to load into TEAL
configObj : string
The valid values for 'configObj' would be::
None - loads last saved user .cfg file
'defaults' - loads task default .cfg file
name of .cfg file (string)- loads user-specified .cfg file
input_dict : dict
Set of parameters and values specified by user to be different from
what gets loaded in from the .cfg file for the task
loadOnly : bool
Setting 'loadOnly' to False causes the TEAL GUI to start allowing the
user to edit the values further and then run the task if desired.
"""
if configObj is None:
# Start by grabbing the default values without using the GUI
# This insures that all subsequent use of the configObj includes
# all parameters and their last saved values
configObj = teal.load(taskname)
elif isinstance(configObj,str):
if configObj.lower().strip() == 'defaults':
# Load task default .cfg file with all default values
configObj = teal.load(taskname,defaults=True)
# define default filename for configObj
configObj.filename = taskname.lower()+'.cfg'
else:
# Load user-specified .cfg file with its special default values
# we need to call 'fileutil.osfn()' to insure all environment
# variables specified by the user in the configObj filename are
# expanded to the full path
configObj = teal.load(fileutil.osfn(configObj))
# merge in the user values for this run
# this, though, does not save the results for use later
if input_dict not in [None,{}]:# and configObj not in [None, {}]:
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
validateUserPars(configObj,input_dict)
# If everything looks good, merge user inputs with configObj and continue
cfgpars.mergeConfigObj(configObj, input_dict)
# Update the input .cfg file with the updated parameter values
#configObj.filename = os.path.join(cfgpars.getAppDir(),os.path.basename(configObj.filename))
#configObj.write()
if not loadOnly:
# We want to run the GUI AFTER merging in any parameters
# specified by the user on the command-line and provided in
# input_dict
configObj = teal.teal(configObj,loadOnly=False)
return configObj | python | def getDefaultConfigObj(taskname,configObj,input_dict={},loadOnly=True):
""" Return default configObj instance for task updated
with user-specified values from input_dict.
Parameters
----------
taskname : string
Name of task to load into TEAL
configObj : string
The valid values for 'configObj' would be::
None - loads last saved user .cfg file
'defaults' - loads task default .cfg file
name of .cfg file (string)- loads user-specified .cfg file
input_dict : dict
Set of parameters and values specified by user to be different from
what gets loaded in from the .cfg file for the task
loadOnly : bool
Setting 'loadOnly' to False causes the TEAL GUI to start allowing the
user to edit the values further and then run the task if desired.
"""
if configObj is None:
# Start by grabbing the default values without using the GUI
# This insures that all subsequent use of the configObj includes
# all parameters and their last saved values
configObj = teal.load(taskname)
elif isinstance(configObj,str):
if configObj.lower().strip() == 'defaults':
# Load task default .cfg file with all default values
configObj = teal.load(taskname,defaults=True)
# define default filename for configObj
configObj.filename = taskname.lower()+'.cfg'
else:
# Load user-specified .cfg file with its special default values
# we need to call 'fileutil.osfn()' to insure all environment
# variables specified by the user in the configObj filename are
# expanded to the full path
configObj = teal.load(fileutil.osfn(configObj))
# merge in the user values for this run
# this, though, does not save the results for use later
if input_dict not in [None,{}]:# and configObj not in [None, {}]:
# check to see whether any input parameters are unexpected.
# Any unexpected parameters provided on input should be reported and
# the code should stop
validateUserPars(configObj,input_dict)
# If everything looks good, merge user inputs with configObj and continue
cfgpars.mergeConfigObj(configObj, input_dict)
# Update the input .cfg file with the updated parameter values
#configObj.filename = os.path.join(cfgpars.getAppDir(),os.path.basename(configObj.filename))
#configObj.write()
if not loadOnly:
# We want to run the GUI AFTER merging in any parameters
# specified by the user on the command-line and provided in
# input_dict
configObj = teal.teal(configObj,loadOnly=False)
return configObj | [
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Name of task to load into TEAL
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'defaults' - loads task default .cfg file
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spacetelescope/drizzlepac | drizzlepac/util.py | getSectionName | def getSectionName(configObj,stepnum):
""" Return section label based on step number.
"""
for key in configObj.keys():
if key.find('STEP '+str(stepnum)+':') >= 0:
return key | python | def getSectionName(configObj,stepnum):
""" Return section label based on step number.
"""
for key in configObj.keys():
if key.find('STEP '+str(stepnum)+':') >= 0:
return key | [
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spacetelescope/drizzlepac | drizzlepac/util.py | displayMakewcsWarningBox | def displayMakewcsWarningBox(display=True, parent=None):
""" Displays a warning box for the 'makewcs' parameter.
"""
if sys.version_info[0] >= 3:
from tkinter.messagebox import showwarning
else:
from tkMessageBox import showwarning
ans = {'yes':True,'no':False}
if ans[display]:
msg = 'Setting "updatewcs=yes" will result '+ \
'in all input WCS values to be recomputed '+ \
'using the original distortion model and alignment.'
showwarning(parent=parent,message=msg, title="WCS will be overwritten!")
return True | python | def displayMakewcsWarningBox(display=True, parent=None):
""" Displays a warning box for the 'makewcs' parameter.
"""
if sys.version_info[0] >= 3:
from tkinter.messagebox import showwarning
else:
from tkMessageBox import showwarning
ans = {'yes':True,'no':False}
if ans[display]:
msg = 'Setting "updatewcs=yes" will result '+ \
'in all input WCS values to be recomputed '+ \
'using the original distortion model and alignment.'
showwarning(parent=parent,message=msg, title="WCS will be overwritten!")
return True | [
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spacetelescope/drizzlepac | drizzlepac/util.py | printParams | def printParams(paramDictionary, all=False, log=None):
"""
Print nicely the parameters from the dictionary.
"""
if log is not None:
def output(msg):
log.info(msg)
else:
def output(msg):
print(msg)
if not paramDictionary:
output('No parameters were supplied')
else:
for key in sorted(paramDictionary):
if all or (not isinstance(paramDictionary[key], dict)) \
and key[0] != '_':
output('\t' + '\t'.join([str(key) + ' :',
str(paramDictionary[key])]))
if log is None:
output('\n') | python | def printParams(paramDictionary, all=False, log=None):
"""
Print nicely the parameters from the dictionary.
"""
if log is not None:
def output(msg):
log.info(msg)
else:
def output(msg):
print(msg)
if not paramDictionary:
output('No parameters were supplied')
else:
for key in sorted(paramDictionary):
if all or (not isinstance(paramDictionary[key], dict)) \
and key[0] != '_':
output('\t' + '\t'.join([str(key) + ' :',
str(paramDictionary[key])]))
if log is None:
output('\n') | [
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spacetelescope/drizzlepac | drizzlepac/util.py | isCommaList | def isCommaList(inputFilelist):
"""Return True if the input is a comma separated list of names."""
if isinstance(inputFilelist, int) or isinstance(inputFilelist, np.int32):
ilist = str(inputFilelist)
else:
ilist = inputFilelist
if "," in ilist:
return True
return False | python | def isCommaList(inputFilelist):
"""Return True if the input is a comma separated list of names."""
if isinstance(inputFilelist, int) or isinstance(inputFilelist, np.int32):
ilist = str(inputFilelist)
else:
ilist = inputFilelist
if "," in ilist:
return True
return False | [
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spacetelescope/drizzlepac | drizzlepac/util.py | loadFileList | def loadFileList(inputFilelist):
"""Open up the '@ file' and read in the science and possible
ivm filenames from the first two columns.
"""
f = open(inputFilelist[1:])
# check the first line in order to determine whether
# IVM files have been specified in a second column...
lines = f.readline()
f.close()
# If there is a second column...
if len(line.split()) == 2:
# ...parse out the names of the IVM files as well
ivmlist = irafglob.irafglob(input, atfile=atfile_ivm)
# Parse the @-file with irafglob to extract the input filename
filelist = irafglob.irafglob(input, atfile=atfile_sci)
return filelist | python | def loadFileList(inputFilelist):
"""Open up the '@ file' and read in the science and possible
ivm filenames from the first two columns.
"""
f = open(inputFilelist[1:])
# check the first line in order to determine whether
# IVM files have been specified in a second column...
lines = f.readline()
f.close()
# If there is a second column...
if len(line.split()) == 2:
# ...parse out the names of the IVM files as well
ivmlist = irafglob.irafglob(input, atfile=atfile_ivm)
# Parse the @-file with irafglob to extract the input filename
filelist = irafglob.irafglob(input, atfile=atfile_sci)
return filelist | [
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spacetelescope/drizzlepac | drizzlepac/util.py | readCommaList | def readCommaList(fileList):
""" Return a list of the files with the commas removed. """
names=fileList.split(',')
fileList=[]
for item in names:
fileList.append(item)
return fileList | python | def readCommaList(fileList):
""" Return a list of the files with the commas removed. """
names=fileList.split(',')
fileList=[]
for item in names:
fileList.append(item)
return fileList | [
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spacetelescope/drizzlepac | drizzlepac/util.py | update_input | def update_input(filelist, ivmlist=None, removed_files=None):
"""
Removes files flagged to be removed from the input filelist.
Removes the corresponding ivm files if present.
"""
newfilelist = []
if removed_files == []:
return filelist, ivmlist
else:
sci_ivm = list(zip(filelist, ivmlist))
for f in removed_files:
result=[sci_ivm.remove(t) for t in sci_ivm if t[0] == f ]
ivmlist = [el[1] for el in sci_ivm]
newfilelist = [el[0] for el in sci_ivm]
return newfilelist, ivmlist | python | def update_input(filelist, ivmlist=None, removed_files=None):
"""
Removes files flagged to be removed from the input filelist.
Removes the corresponding ivm files if present.
"""
newfilelist = []
if removed_files == []:
return filelist, ivmlist
else:
sci_ivm = list(zip(filelist, ivmlist))
for f in removed_files:
result=[sci_ivm.remove(t) for t in sci_ivm if t[0] == f ]
ivmlist = [el[1] for el in sci_ivm]
newfilelist = [el[0] for el in sci_ivm]
return newfilelist, ivmlist | [
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spacetelescope/drizzlepac | drizzlepac/util.py | get_expstart | def get_expstart(header,primary_hdr):
"""shouldn't this just be defined in the instrument subclass of imageobject?"""
if 'expstart' in primary_hdr:
exphdr = primary_hdr
else:
exphdr = header
if 'EXPSTART' in exphdr:
expstart = float(exphdr['EXPSTART'])
expend = float(exphdr['EXPEND'])
else:
expstart = 0.
expend = 0.0
return (expstart,expend) | python | def get_expstart(header,primary_hdr):
"""shouldn't this just be defined in the instrument subclass of imageobject?"""
if 'expstart' in primary_hdr:
exphdr = primary_hdr
else:
exphdr = header
if 'EXPSTART' in exphdr:
expstart = float(exphdr['EXPSTART'])
expend = float(exphdr['EXPEND'])
else:
expstart = 0.
expend = 0.0
return (expstart,expend) | [
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spacetelescope/drizzlepac | drizzlepac/util.py | compute_texptime | def compute_texptime(imageObjectList):
"""
Add up the exposure time for all the members in
the pattern, since 'drizzle' doesn't have the necessary
information to correctly set this itself.
"""
expnames = []
exptimes = []
start = []
end = []
for img in imageObjectList:
expnames += img.getKeywordList('_expname')
exptimes += img.getKeywordList('_exptime')
start += img.getKeywordList('_expstart')
end += img.getKeywordList('_expend')
exptime = 0.
expstart = min(start)
expend = max(end)
exposure = None
for n in range(len(expnames)):
if expnames[n] != exposure:
exposure = expnames[n]
exptime += exptimes[n]
return (exptime,expstart,expend) | python | def compute_texptime(imageObjectList):
"""
Add up the exposure time for all the members in
the pattern, since 'drizzle' doesn't have the necessary
information to correctly set this itself.
"""
expnames = []
exptimes = []
start = []
end = []
for img in imageObjectList:
expnames += img.getKeywordList('_expname')
exptimes += img.getKeywordList('_exptime')
start += img.getKeywordList('_expstart')
end += img.getKeywordList('_expend')
exptime = 0.
expstart = min(start)
expend = max(end)
exposure = None
for n in range(len(expnames)):
if expnames[n] != exposure:
exposure = expnames[n]
exptime += exptimes[n]
return (exptime,expstart,expend) | [
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spacetelescope/drizzlepac | drizzlepac/util.py | computeRange | def computeRange(corners):
""" Determine the range spanned by an array of pixel positions. """
x = corners[:, 0]
y = corners[:, 1]
_xrange = (np.minimum.reduce(x), np.maximum.reduce(x))
_yrange = (np.minimum.reduce(y), np.maximum.reduce(y))
return _xrange, _yrange | python | def computeRange(corners):
""" Determine the range spanned by an array of pixel positions. """
x = corners[:, 0]
y = corners[:, 1]
_xrange = (np.minimum.reduce(x), np.maximum.reduce(x))
_yrange = (np.minimum.reduce(y), np.maximum.reduce(y))
return _xrange, _yrange | [
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spacetelescope/drizzlepac | drizzlepac/util.py | readcols | def readcols(infile, cols=[0, 1, 2, 3], hms=False):
"""
Read the columns from an ASCII file as numpy arrays.
Parameters
----------
infile : str
Filename of ASCII file with array data as columns.
cols : list of int
List of 0-indexed column numbers for columns to be turned into numpy arrays
(DEFAULT- [0,1,2,3]).
Returns
-------
outarr : list of numpy arrays
Simple list of numpy arrays in the order as specifed in the 'cols' parameter.
"""
fin = open(infile,'r')
outarr = []
for l in fin.readlines():
l = l.strip()
if len(l) == 0 or len(l.split()) < len(cols) or (len(l) > 0 and l[0] == '#' or (l.find("INDEF") > -1)): continue
for i in range(10):
lnew = l.replace(" "," ")
if lnew == l: break
else: l = lnew
lspl = lnew.split(" ")
if len(outarr) == 0:
for c in range(len(cols)): outarr.append([])
for c,n in zip(cols,list(range(len(cols)))):
if not hms:
val = float(lspl[c])
else:
val = lspl[c]
outarr[n].append(val)
fin.close()
for n in range(len(cols)):
outarr[n] = np.array(outarr[n])
return outarr | python | def readcols(infile, cols=[0, 1, 2, 3], hms=False):
"""
Read the columns from an ASCII file as numpy arrays.
Parameters
----------
infile : str
Filename of ASCII file with array data as columns.
cols : list of int
List of 0-indexed column numbers for columns to be turned into numpy arrays
(DEFAULT- [0,1,2,3]).
Returns
-------
outarr : list of numpy arrays
Simple list of numpy arrays in the order as specifed in the 'cols' parameter.
"""
fin = open(infile,'r')
outarr = []
for l in fin.readlines():
l = l.strip()
if len(l) == 0 or len(l.split()) < len(cols) or (len(l) > 0 and l[0] == '#' or (l.find("INDEF") > -1)): continue
for i in range(10):
lnew = l.replace(" "," ")
if lnew == l: break
else: l = lnew
lspl = lnew.split(" ")
if len(outarr) == 0:
for c in range(len(cols)): outarr.append([])
for c,n in zip(cols,list(range(len(cols)))):
if not hms:
val = float(lspl[c])
else:
val = lspl[c]
outarr[n].append(val)
fin.close()
for n in range(len(cols)):
outarr[n] = np.array(outarr[n])
return outarr | [
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spacetelescope/drizzlepac | drizzlepac/util.py | parse_colnames | def parse_colnames(colnames,coords=None):
""" Convert colnames input into list of column numbers.
"""
cols = []
if not isinstance(colnames,list):
colnames = colnames.split(',')
# parse column names from coords file and match to input values
if coords is not None and fileutil.isFits(coords)[0]:
# Open FITS file with table
ftab = fits.open(coords, memmap=False)
# determine which extension has the table
for extn in ftab:
if isinstance(extn, fits.BinTableHDU):
# parse column names from table and match to inputs
cnames = extn.columns.names
if colnames is not None:
for c in colnames:
for name,i in zip(cnames,list(range(len(cnames)))):
if c == name.lower(): cols.append(i)
if len(cols) < len(colnames):
errmsg = "Not all input columns found in table..."
ftab.close()
raise ValueError(errmsg)
else:
cols = cnames[:2]
break
ftab.close()
else:
for c in colnames:
if isinstance(c, str):
if c[0].lower() == 'c': cols.append(int(c[1:])-1)
else:
cols.append(int(c))
else:
if isinstance(c, int):
cols.append(c)
else:
errmsg = "Unsupported column names..."
raise ValueError(errmsg)
return cols | python | def parse_colnames(colnames,coords=None):
""" Convert colnames input into list of column numbers.
"""
cols = []
if not isinstance(colnames,list):
colnames = colnames.split(',')
# parse column names from coords file and match to input values
if coords is not None and fileutil.isFits(coords)[0]:
# Open FITS file with table
ftab = fits.open(coords, memmap=False)
# determine which extension has the table
for extn in ftab:
if isinstance(extn, fits.BinTableHDU):
# parse column names from table and match to inputs
cnames = extn.columns.names
if colnames is not None:
for c in colnames:
for name,i in zip(cnames,list(range(len(cnames)))):
if c == name.lower(): cols.append(i)
if len(cols) < len(colnames):
errmsg = "Not all input columns found in table..."
ftab.close()
raise ValueError(errmsg)
else:
cols = cnames[:2]
break
ftab.close()
else:
for c in colnames:
if isinstance(c, str):
if c[0].lower() == 'c': cols.append(int(c[1:])-1)
else:
cols.append(int(c))
else:
if isinstance(c, int):
cols.append(c)
else:
errmsg = "Unsupported column names..."
raise ValueError(errmsg)
return cols | [
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spacetelescope/drizzlepac | drizzlepac/util.py | createFile | def createFile(dataArray=None, outfile=None, header=None):
"""
Create a simple fits file for the given data array and header.
Returns either the FITS object in-membory when outfile==None or
None when the FITS file was written out to a file.
"""
# Insure that at least a data-array has been provided to create the file
assert(dataArray is not None), "Please supply a data array for createFiles"
try:
# Create the output file
fitsobj = fits.HDUList()
if header is not None:
try:
del(header['NAXIS1'])
del(header['NAXIS2'])
if 'XTENSION' in header:
del(header['XTENSION'])
if 'EXTNAME' in header:
del(header['EXTNAME'])
if 'EXTVER' in header:
del(header['EXTVER'])
except KeyError:
pass
if 'NEXTEND' in header:
header['NEXTEND'] = 0
hdu = fits.PrimaryHDU(data=dataArray, header=header)
try:
del hdu.header['PCOUNT']
del hdu.header['GCOUNT']
except KeyError:
pass
else:
hdu = fits.PrimaryHDU(data=dataArray)
fitsobj.append(hdu)
if outfile is not None:
fitsobj.writeto(outfile)
finally:
# CLOSE THE IMAGE FILES
fitsobj.close()
if outfile is not None:
del fitsobj
fitsobj = None
return fitsobj | python | def createFile(dataArray=None, outfile=None, header=None):
"""
Create a simple fits file for the given data array and header.
Returns either the FITS object in-membory when outfile==None or
None when the FITS file was written out to a file.
"""
# Insure that at least a data-array has been provided to create the file
assert(dataArray is not None), "Please supply a data array for createFiles"
try:
# Create the output file
fitsobj = fits.HDUList()
if header is not None:
try:
del(header['NAXIS1'])
del(header['NAXIS2'])
if 'XTENSION' in header:
del(header['XTENSION'])
if 'EXTNAME' in header:
del(header['EXTNAME'])
if 'EXTVER' in header:
del(header['EXTVER'])
except KeyError:
pass
if 'NEXTEND' in header:
header['NEXTEND'] = 0
hdu = fits.PrimaryHDU(data=dataArray, header=header)
try:
del hdu.header['PCOUNT']
del hdu.header['GCOUNT']
except KeyError:
pass
else:
hdu = fits.PrimaryHDU(data=dataArray)
fitsobj.append(hdu)
if outfile is not None:
fitsobj.writeto(outfile)
finally:
# CLOSE THE IMAGE FILES
fitsobj.close()
if outfile is not None:
del fitsobj
fitsobj = None
return fitsobj | [
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spacetelescope/drizzlepac | drizzlepac/util.py | base_taskname | def base_taskname(taskname, packagename=None):
"""
Extract the base name of the task.
Many tasks in the `drizzlepac` have "compound" names such as
'drizzlepac.sky'. This function will search for the presence of a dot
in the input `taskname` and if found, it will return the string
to the right of the right-most dot. If a dot is not found, it will return
the input string.
Parameters
----------
taskname : str, None
Full task name. If it is `None`, :py:func:`base_taskname` will
return `None`\ .
packagename : str, None (Default = None)
Package name. It is assumed that a compound task name is formed by
concatenating `packagename` + '.' + `taskname`\ . If `packagename`
is not `None`, :py:func:`base_taskname` will check that the string
to the left of the right-most dot matches `packagename` and will
raise an `AssertionError` if the package name derived from the
input `taskname` does not match the supplied `packagename`\ . This
is intended as a check for discrepancies that may arise
during the development of the tasks. If `packagename` is `None`,
no such check will be performed.
Raises
------
AssertionError
Raised when package name derived from the input `taskname` does not
match the supplied `packagename`
"""
if not isinstance(taskname, str):
return taskname
indx = taskname.rfind('.')
if indx >= 0:
base_taskname = taskname[(indx+1):]
pkg_name = taskname[:indx]
else:
base_taskname = taskname
pkg_name = ''
assert(True if packagename is None else (packagename == pkg_name))
return base_taskname | python | def base_taskname(taskname, packagename=None):
"""
Extract the base name of the task.
Many tasks in the `drizzlepac` have "compound" names such as
'drizzlepac.sky'. This function will search for the presence of a dot
in the input `taskname` and if found, it will return the string
to the right of the right-most dot. If a dot is not found, it will return
the input string.
Parameters
----------
taskname : str, None
Full task name. If it is `None`, :py:func:`base_taskname` will
return `None`\ .
packagename : str, None (Default = None)
Package name. It is assumed that a compound task name is formed by
concatenating `packagename` + '.' + `taskname`\ . If `packagename`
is not `None`, :py:func:`base_taskname` will check that the string
to the left of the right-most dot matches `packagename` and will
raise an `AssertionError` if the package name derived from the
input `taskname` does not match the supplied `packagename`\ . This
is intended as a check for discrepancies that may arise
during the development of the tasks. If `packagename` is `None`,
no such check will be performed.
Raises
------
AssertionError
Raised when package name derived from the input `taskname` does not
match the supplied `packagename`
"""
if not isinstance(taskname, str):
return taskname
indx = taskname.rfind('.')
if indx >= 0:
base_taskname = taskname[(indx+1):]
pkg_name = taskname[:indx]
else:
base_taskname = taskname
pkg_name = ''
assert(True if packagename is None else (packagename == pkg_name))
return base_taskname | [
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Raises
------
AssertionError
Raised when package name derived from the input `taskname` does not
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spacetelescope/drizzlepac | drizzlepac/util.py | ProcSteps.endStep | def endStep(self,key):
"""
Record the end time for the step.
If key==None, simply record ptime as end time for class to represent
the overall runtime since the initialization of the class.
"""
ptime = _ptime()
if key is not None:
self.steps[key]['end'] = ptime
self.steps[key]['elapsed'] = ptime[1] - self.steps[key]['start'][1]
self.end = ptime
print('==== Processing Step ',key,' finished at ',ptime[0])
print('') | python | def endStep(self,key):
"""
Record the end time for the step.
If key==None, simply record ptime as end time for class to represent
the overall runtime since the initialization of the class.
"""
ptime = _ptime()
if key is not None:
self.steps[key]['end'] = ptime
self.steps[key]['elapsed'] = ptime[1] - self.steps[key]['start'][1]
self.end = ptime
print('==== Processing Step ',key,' finished at ',ptime[0])
print('') | [
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spacetelescope/drizzlepac | drizzlepac/util.py | ProcSteps.reportTimes | def reportTimes(self):
"""
Print out a formatted summary of the elapsed times for all the
performed steps.
"""
self.end = _ptime()
total_time = 0
print(ProcSteps.__report_header)
for step in self.order:
if 'elapsed' in self.steps[step]:
_time = self.steps[step]['elapsed']
else:
_time = 0.0
total_time += _time
print(' %20s %0.4f sec.' % (step, _time))
print(' %20s %s' % ('=' * 20, '=' * 20))
print(' %20s %0.4f sec.' % ('Total', total_time)) | python | def reportTimes(self):
"""
Print out a formatted summary of the elapsed times for all the
performed steps.
"""
self.end = _ptime()
total_time = 0
print(ProcSteps.__report_header)
for step in self.order:
if 'elapsed' in self.steps[step]:
_time = self.steps[step]['elapsed']
else:
_time = 0.0
total_time += _time
print(' %20s %0.4f sec.' % (step, _time))
print(' %20s %s' % ('=' * 20, '=' * 20))
print(' %20s %0.4f sec.' % ('Total', total_time)) | [
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spacetelescope/drizzlepac | drizzlepac/buildmask.py | buildDQMasks | def buildDQMasks(imageObjectList,configObj):
""" Build DQ masks for all input images.
"""
# Insure that input imageObject is a list
if not isinstance(imageObjectList, list):
imageObjectList = [imageObjectList]
for img in imageObjectList:
img.buildMask(configObj['single'], configObj['bits']) | python | def buildDQMasks(imageObjectList,configObj):
""" Build DQ masks for all input images.
"""
# Insure that input imageObject is a list
if not isinstance(imageObjectList, list):
imageObjectList = [imageObjectList]
for img in imageObjectList:
img.buildMask(configObj['single'], configObj['bits']) | [
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spacetelescope/drizzlepac | drizzlepac/buildmask.py | buildMask | def buildMask(dqarr, bitvalue):
""" Builds a bit-mask from an input DQ array and a bitvalue flag """
return bitfield_to_boolean_mask(dqarr, bitvalue, good_mask_value=1,
dtype=np.uint8) | python | def buildMask(dqarr, bitvalue):
""" Builds a bit-mask from an input DQ array and a bitvalue flag """
return bitfield_to_boolean_mask(dqarr, bitvalue, good_mask_value=1,
dtype=np.uint8) | [
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spacetelescope/drizzlepac | drizzlepac/buildmask.py | buildMaskImage | def buildMaskImage(rootname, bitvalue, output, extname='DQ', extver=1):
""" Builds mask image from rootname's DQ array
If there is no valid 'DQ' array in image, then return
an empty string.
"""
# If no bitvalue is set or rootname given, assume no mask is desired
# However, this name would be useful as the output mask from
# other processing, such as MultiDrizzle, so return it anyway.
#if bitvalue == None or rootname == None:
# return None
# build output name
maskname = output
# If an old version of the maskfile was present, remove it and rebuild it.
if fileutil.findFile(maskname):
fileutil.removeFile(maskname)
# Open input file with DQ array
fdq = fileutil.openImage(rootname, mode='readonly', memmap=False)
try:
_extn = fileutil.findExtname(fdq, extname, extver=extver)
if _extn is not None:
# Read in DQ array
dqarr = fdq[_extn].data
else:
dqarr = None
# For the case where there is no DQ array,
# create a mask image of all ones.
if dqarr is None:
# We need to get the dimensions of the output DQ array
# Since the DQ array is non-existent, look for the SCI extension
_sci_extn = fileutil.findExtname(fdq,'SCI',extver=extver)
if _sci_extn is not None:
_shape = fdq[_sci_extn].data.shape
dqarr = np.zeros(_shape,dtype=np.uint16)
else:
raise Exception
# Build mask array from DQ array
maskarr = buildMask(dqarr,bitvalue)
#Write out the mask file as simple FITS file
fmask = fits.open(maskname, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data = maskarr)
fmask.append(maskhdu)
#Close files
fmask.close()
del fmask
fdq.close()
del fdq
except:
fdq.close()
del fdq
# Safeguard against leaving behind an incomplete file
if fileutil.findFile(maskname):
os.remove(maskname)
_errstr = "\nWarning: Problem creating MASK file for "+rootname+".\n"
#raise IOError, _errstr
print(_errstr)
return None
# Return the name of the mask image written out
return maskname | python | def buildMaskImage(rootname, bitvalue, output, extname='DQ', extver=1):
""" Builds mask image from rootname's DQ array
If there is no valid 'DQ' array in image, then return
an empty string.
"""
# If no bitvalue is set or rootname given, assume no mask is desired
# However, this name would be useful as the output mask from
# other processing, such as MultiDrizzle, so return it anyway.
#if bitvalue == None or rootname == None:
# return None
# build output name
maskname = output
# If an old version of the maskfile was present, remove it and rebuild it.
if fileutil.findFile(maskname):
fileutil.removeFile(maskname)
# Open input file with DQ array
fdq = fileutil.openImage(rootname, mode='readonly', memmap=False)
try:
_extn = fileutil.findExtname(fdq, extname, extver=extver)
if _extn is not None:
# Read in DQ array
dqarr = fdq[_extn].data
else:
dqarr = None
# For the case where there is no DQ array,
# create a mask image of all ones.
if dqarr is None:
# We need to get the dimensions of the output DQ array
# Since the DQ array is non-existent, look for the SCI extension
_sci_extn = fileutil.findExtname(fdq,'SCI',extver=extver)
if _sci_extn is not None:
_shape = fdq[_sci_extn].data.shape
dqarr = np.zeros(_shape,dtype=np.uint16)
else:
raise Exception
# Build mask array from DQ array
maskarr = buildMask(dqarr,bitvalue)
#Write out the mask file as simple FITS file
fmask = fits.open(maskname, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data = maskarr)
fmask.append(maskhdu)
#Close files
fmask.close()
del fmask
fdq.close()
del fdq
except:
fdq.close()
del fdq
# Safeguard against leaving behind an incomplete file
if fileutil.findFile(maskname):
os.remove(maskname)
_errstr = "\nWarning: Problem creating MASK file for "+rootname+".\n"
#raise IOError, _errstr
print(_errstr)
return None
# Return the name of the mask image written out
return maskname | [
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spacetelescope/drizzlepac | drizzlepac/buildmask.py | buildShadowMaskImage | def buildShadowMaskImage(dqfile,detnum,extnum,maskname,bitvalue=None,binned=1):
""" Builds mask image from WFPC2 shadow calibrations.
detnum - string value for 'DETECTOR' detector
"""
# insure detnum is a string
if type(detnum) != type(''):
detnum = repr(detnum)
_funcroot = '_func_Shadow_WF'
# build template shadow mask's filename
# If an old version of the maskfile was present, remove it and rebuild it.
if fileutil.findFile(maskname):
fileutil.removeFile(maskname)
_use_inmask = not fileutil.findFile(dqfile) or bitvalue is None
# Check for existance of input .c1h file for use in making inmask file
if _use_inmask:
#_mask = 'wfpc2_inmask'+detnum+'.fits'
_mask = maskname
# Check to see if file exists...
if not fileutil.findFile(_mask):
# If not, create the file.
# This takes a long time to run, so it should be done
# only when absolutely necessary...
try:
_funcx = _funcroot+detnum+'x'
_funcy = _funcroot+detnum+'y'
_xarr = np.clip(np.fromfunction(eval(_funcx),(800,800)),0.0,1.0).astype(np.uint8)
_yarr = np.clip(np.fromfunction(eval(_funcy),(800,800)),0.0,1.0).astype(np.uint8)
maskarr = _xarr * _yarr
if binned !=1:
bmaskarr = maskarr[::2,::2]
bmaskarr *= maskarr[1::2,::2]
bmaskarr *= maskarr[::2,1::2]
bmaskarr *= maskarr[1::2,1::2]
maskarr = bmaskarr.copy()
del bmaskarr
#Write out the mask file as simple FITS file
fmask = fits.open(_mask, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data=maskarr)
fmask.append(maskhdu)
#Close files
fmask.close()
del fmask
except:
return None
else:
#
# Build full mask based on .c1h and shadow mask
#
fdq = fileutil.openImage(dqfile, mode='readonly', memmap=False)
try:
# Read in DQ array from .c1h and from shadow mask files
dqarr = fdq[int(extnum)].data
#maskarr = fsmask[0].data
# Build mask array from DQ array
dqmaskarr = buildMask(dqarr,bitvalue)
#Write out the mask file as simple FITS file
fdqmask = fits.open(maskname, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data=dqmaskarr)
fdqmask.append(maskhdu)
#Close files
fdqmask.close()
del fdqmask
fdq.close()
del fdq
except:
fdq.close()
del fdq
# Safeguard against leaving behind an incomplete file
if fileutil.findFile(maskname):
os.remove(maskname)
_errstr = "\nWarning: Problem creating DQMASK file for "+rootname+".\n"
#raise IOError, _errstr
print(_errstr)
return None
# Return the name of the mask image written out
return maskname | python | def buildShadowMaskImage(dqfile,detnum,extnum,maskname,bitvalue=None,binned=1):
""" Builds mask image from WFPC2 shadow calibrations.
detnum - string value for 'DETECTOR' detector
"""
# insure detnum is a string
if type(detnum) != type(''):
detnum = repr(detnum)
_funcroot = '_func_Shadow_WF'
# build template shadow mask's filename
# If an old version of the maskfile was present, remove it and rebuild it.
if fileutil.findFile(maskname):
fileutil.removeFile(maskname)
_use_inmask = not fileutil.findFile(dqfile) or bitvalue is None
# Check for existance of input .c1h file for use in making inmask file
if _use_inmask:
#_mask = 'wfpc2_inmask'+detnum+'.fits'
_mask = maskname
# Check to see if file exists...
if not fileutil.findFile(_mask):
# If not, create the file.
# This takes a long time to run, so it should be done
# only when absolutely necessary...
try:
_funcx = _funcroot+detnum+'x'
_funcy = _funcroot+detnum+'y'
_xarr = np.clip(np.fromfunction(eval(_funcx),(800,800)),0.0,1.0).astype(np.uint8)
_yarr = np.clip(np.fromfunction(eval(_funcy),(800,800)),0.0,1.0).astype(np.uint8)
maskarr = _xarr * _yarr
if binned !=1:
bmaskarr = maskarr[::2,::2]
bmaskarr *= maskarr[1::2,::2]
bmaskarr *= maskarr[::2,1::2]
bmaskarr *= maskarr[1::2,1::2]
maskarr = bmaskarr.copy()
del bmaskarr
#Write out the mask file as simple FITS file
fmask = fits.open(_mask, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data=maskarr)
fmask.append(maskhdu)
#Close files
fmask.close()
del fmask
except:
return None
else:
#
# Build full mask based on .c1h and shadow mask
#
fdq = fileutil.openImage(dqfile, mode='readonly', memmap=False)
try:
# Read in DQ array from .c1h and from shadow mask files
dqarr = fdq[int(extnum)].data
#maskarr = fsmask[0].data
# Build mask array from DQ array
dqmaskarr = buildMask(dqarr,bitvalue)
#Write out the mask file as simple FITS file
fdqmask = fits.open(maskname, mode='append', memmap=False)
maskhdu = fits.PrimaryHDU(data=dqmaskarr)
fdqmask.append(maskhdu)
#Close files
fdqmask.close()
del fdqmask
fdq.close()
del fdq
except:
fdq.close()
del fdq
# Safeguard against leaving behind an incomplete file
if fileutil.findFile(maskname):
os.remove(maskname)
_errstr = "\nWarning: Problem creating DQMASK file for "+rootname+".\n"
#raise IOError, _errstr
print(_errstr)
return None
# Return the name of the mask image written out
return maskname | [
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spacetelescope/drizzlepac | drizzlepac/adrizzle.py | mergeDQarray | def mergeDQarray(maskname,dqarr):
""" Merge static or CR mask with mask created from DQ array on-the-fly here.
"""
maskarr = None
if maskname is not None:
if isinstance(maskname, str):
# working with file on disk (default case)
if os.path.exists(maskname):
mask = fileutil.openImage(maskname, memmap=False)
maskarr = mask[0].data.astype(np.bool)
mask.close()
else:
if isinstance(maskname, fits.HDUList):
# working with a virtual input file
maskarr = maskname[0].data.astype(np.bool)
else:
maskarr = maskname.data.astype(np.bool)
if maskarr is not None:
# merge array with dqarr now
np.bitwise_and(dqarr,maskarr,dqarr) | python | def mergeDQarray(maskname,dqarr):
""" Merge static or CR mask with mask created from DQ array on-the-fly here.
"""
maskarr = None
if maskname is not None:
if isinstance(maskname, str):
# working with file on disk (default case)
if os.path.exists(maskname):
mask = fileutil.openImage(maskname, memmap=False)
maskarr = mask[0].data.astype(np.bool)
mask.close()
else:
if isinstance(maskname, fits.HDUList):
# working with a virtual input file
maskarr = maskname[0].data.astype(np.bool)
else:
maskarr = maskname.data.astype(np.bool)
if maskarr is not None:
# merge array with dqarr now
np.bitwise_and(dqarr,maskarr,dqarr) | [
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spacetelescope/drizzlepac | drizzlepac/adrizzle.py | _setDefaults | def _setDefaults(configObj={}):
"""set up the default parameters to run drizzle
build,single,units,wt_scl,pixfrac,kernel,fillval,
rot,scale,xsh,ysh,blotnx,blotny,outnx,outny,data
Used exclusively for unit-testing, if any are defined.
"""
paramDict={"build":True,
"single":True,
"stepsize":10,
"in_units":"cps",
"wt_scl":1.,
"pixfrac":1.,
"kernel":"square",
"fillval":999.,
"maskval": None,
"rot":0.,
"scale":1.,
"xsh":0.,
"ysh":0.,
"blotnx":2048,
"blotny":2048,
"outnx":4096,
"outny":4096,
"data":None,
"driz_separate":True,
"driz_combine":False}
if(len(configObj) !=0):
for key in configObj.keys():
paramDict[key]=configObj[key]
return paramDict | python | def _setDefaults(configObj={}):
"""set up the default parameters to run drizzle
build,single,units,wt_scl,pixfrac,kernel,fillval,
rot,scale,xsh,ysh,blotnx,blotny,outnx,outny,data
Used exclusively for unit-testing, if any are defined.
"""
paramDict={"build":True,
"single":True,
"stepsize":10,
"in_units":"cps",
"wt_scl":1.,
"pixfrac":1.,
"kernel":"square",
"fillval":999.,
"maskval": None,
"rot":0.,
"scale":1.,
"xsh":0.,
"ysh":0.,
"blotnx":2048,
"blotny":2048,
"outnx":4096,
"outny":4096,
"data":None,
"driz_separate":True,
"driz_combine":False}
if(len(configObj) !=0):
for key in configObj.keys():
paramDict[key]=configObj[key]
return paramDict | [
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spacetelescope/drizzlepac | drizzlepac/adrizzle.py | interpret_maskval | def interpret_maskval(paramDict):
""" Apply logic for interpreting final_maskval value...
"""
# interpret user specified final_maskval value to use for initializing
# output SCI array...
if 'maskval' not in paramDict:
return 0
maskval = paramDict['maskval']
if maskval is None:
maskval = np.nan
else:
maskval = float(maskval) # just to be clear and absolutely sure...
return maskval | python | def interpret_maskval(paramDict):
""" Apply logic for interpreting final_maskval value...
"""
# interpret user specified final_maskval value to use for initializing
# output SCI array...
if 'maskval' not in paramDict:
return 0
maskval = paramDict['maskval']
if maskval is None:
maskval = np.nan
else:
maskval = float(maskval) # just to be clear and absolutely sure...
return maskval | [
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spacetelescope/drizzlepac | drizzlepac/mapreg.py | _regwrite | def _regwrite(shapelist,outfile):
""" Writes the current shape list out as a region file """
# This function corrects bugs and provides improvements over the pyregion's
# ShapeList.write method in the following:
#
# 1. ShapeList.write crashes if regions have no comments;
# 2. ShapeList.write converts 'exclude' ("-") regions to normal regions ("+");
# 3. ShapeList.write does not support mixed coordinate systems in a
# region list.
#
# NOTE: This function is provided as a temoprary workaround for the above
# listed problems of the ShapeList.write. We hope that a future version
# of pyregion will address all these issues.
#
#TODO: Push these changes to pyregion.
if len(shapelist) < 1:
_print_warning("The region list is empty. The region file \"%s\" "\
"will be empty." % outfile)
try:
outf = open(outfile,'w')
outf.close()
return
except IOError as e:
cmsg = "Unable to create region file \'%s\'." % outfile
if e.args:
e.args = (e.args[0] + "\n" + cmsg,) + e.args[1:]
else:
e.args=(cmsg,)
raise e
except:
raise
prev_cs = shapelist[0].coord_format
outf = None
try:
outf = open(outfile,'w')
attr0 = shapelist[0].attr[1]
defaultline = " ".join(["%s=%s" % (a,attr0[a]) for a in attr0 \
if a!='text'])
# first line is globals
print("global", defaultline, file=outf)
# second line must be a coordinate format
print(prev_cs, file=outf)
for shape in shapelist:
shape_attr = '' if prev_cs == shape.coord_format \
else shape.coord_format+"; "
shape_excl = '-' if shape.exclude else ''
text_coordlist = ["%f" % f for f in shape.coord_list]
shape_coords = "(" + ",".join(text_coordlist) + ")"
shape_comment = " # " + shape.comment if shape.comment else ''
shape_str = shape_attr + shape_excl + shape.name + shape_coords + \
shape_comment
print(shape_str, file=outf)
except IOError as e:
cmsg = "Unable to create region file \'%s\'." % outfile
if e.args:
e.args = (e.args[0] + "\n" + cmsg,) + e.args[1:]
else:
e.args=(cmsg,)
if outf: outf.close()
raise e
except:
if outf: outf.close()
raise
outf.close() | python | def _regwrite(shapelist,outfile):
""" Writes the current shape list out as a region file """
# This function corrects bugs and provides improvements over the pyregion's
# ShapeList.write method in the following:
#
# 1. ShapeList.write crashes if regions have no comments;
# 2. ShapeList.write converts 'exclude' ("-") regions to normal regions ("+");
# 3. ShapeList.write does not support mixed coordinate systems in a
# region list.
#
# NOTE: This function is provided as a temoprary workaround for the above
# listed problems of the ShapeList.write. We hope that a future version
# of pyregion will address all these issues.
#
#TODO: Push these changes to pyregion.
if len(shapelist) < 1:
_print_warning("The region list is empty. The region file \"%s\" "\
"will be empty." % outfile)
try:
outf = open(outfile,'w')
outf.close()
return
except IOError as e:
cmsg = "Unable to create region file \'%s\'." % outfile
if e.args:
e.args = (e.args[0] + "\n" + cmsg,) + e.args[1:]
else:
e.args=(cmsg,)
raise e
except:
raise
prev_cs = shapelist[0].coord_format
outf = None
try:
outf = open(outfile,'w')
attr0 = shapelist[0].attr[1]
defaultline = " ".join(["%s=%s" % (a,attr0[a]) for a in attr0 \
if a!='text'])
# first line is globals
print("global", defaultline, file=outf)
# second line must be a coordinate format
print(prev_cs, file=outf)
for shape in shapelist:
shape_attr = '' if prev_cs == shape.coord_format \
else shape.coord_format+"; "
shape_excl = '-' if shape.exclude else ''
text_coordlist = ["%f" % f for f in shape.coord_list]
shape_coords = "(" + ",".join(text_coordlist) + ")"
shape_comment = " # " + shape.comment if shape.comment else ''
shape_str = shape_attr + shape_excl + shape.name + shape_coords + \
shape_comment
print(shape_str, file=outf)
except IOError as e:
cmsg = "Unable to create region file \'%s\'." % outfile
if e.args:
e.args = (e.args[0] + "\n" + cmsg,) + e.args[1:]
else:
e.args=(cmsg,)
if outf: outf.close()
raise e
except:
if outf: outf.close()
raise
outf.close() | [
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spacetelescope/drizzlepac | drizzlepac/mapreg.py | _needs_ref_WCS | def _needs_ref_WCS(reglist):
""" Check if the region list contains shapes in image-like coordinates
"""
from pyregion.wcs_helper import image_like_coordformats
for r in reglist:
if r.coord_format in image_like_coordformats:
return True
return False | python | def _needs_ref_WCS(reglist):
""" Check if the region list contains shapes in image-like coordinates
"""
from pyregion.wcs_helper import image_like_coordformats
for r in reglist:
if r.coord_format in image_like_coordformats:
return True
return False | [
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spacetelescope/drizzlepac | drizzlepac/generate_final_product_filenames.py | run_generator | def run_generator(product_category,obs_info):
"""
This is the main calling subroutine. It decides which filename generation subroutine should be run based on the
input product_category, and then passes the information stored in input obs_info to the subroutine so that the
appropriate filenames can be generated.
Parameters
----------
product_category : string
The type of final output product which filenames will be generated for
obs_info : string
A string containing space-separated items that will be used to
generate the filenames.
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
category_generator_mapping = {'single exposure product': single_exposure_product_filename_generator,
'filter product': filter_product_filename_generator,
'total detection product': total_detection_product_filename_generator,
'multivisit mosaic product': multivisit_mosaic_product_filename_generator}
# Determine which name generator to use based on input product_category
for key in category_generator_mapping.keys():
if product_category.startswith(key):
generator_name = category_generator_mapping[key]
category_num = product_category.replace(key+" ","")
break
# parse out obs_info into a list
obs_info = obs_info.split(" ")
# pad 4-character proposal_id values with leading 0s so that proposal_id is
# a 5-character sting.
if key != "multivisit mosaic product": # pad
obs_info[0] = "{}{}".format("0"*(5-len(obs_info[0])),obs_info[0])
# generate and return filenames
product_filename_dict=generator_name(obs_info,category_num)
return(product_filename_dict) | python | def run_generator(product_category,obs_info):
"""
This is the main calling subroutine. It decides which filename generation subroutine should be run based on the
input product_category, and then passes the information stored in input obs_info to the subroutine so that the
appropriate filenames can be generated.
Parameters
----------
product_category : string
The type of final output product which filenames will be generated for
obs_info : string
A string containing space-separated items that will be used to
generate the filenames.
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
category_generator_mapping = {'single exposure product': single_exposure_product_filename_generator,
'filter product': filter_product_filename_generator,
'total detection product': total_detection_product_filename_generator,
'multivisit mosaic product': multivisit_mosaic_product_filename_generator}
# Determine which name generator to use based on input product_category
for key in category_generator_mapping.keys():
if product_category.startswith(key):
generator_name = category_generator_mapping[key]
category_num = product_category.replace(key+" ","")
break
# parse out obs_info into a list
obs_info = obs_info.split(" ")
# pad 4-character proposal_id values with leading 0s so that proposal_id is
# a 5-character sting.
if key != "multivisit mosaic product": # pad
obs_info[0] = "{}{}".format("0"*(5-len(obs_info[0])),obs_info[0])
# generate and return filenames
product_filename_dict=generator_name(obs_info,category_num)
return(product_filename_dict) | [
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Parameters
----------
product_category : string
The type of final output product which filenames will be generated for
obs_info : string
A string containing space-separated items that will be used to
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--------
product_filename_dict : dictionary
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spacetelescope/drizzlepac | drizzlepac/generate_final_product_filenames.py | single_exposure_product_filename_generator | def single_exposure_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for single-exposure products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, detector, filter, and ipppssoot
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
filter = obs_info[4]
ipppssoot = obs_info[5]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}_{}_{}_{}.fits".format(proposal_id,visit_id,instrument,detector,filter,ipppssoot,nn)
product_filename_dict["source catalog"]= product_filename_dict["image"].replace(".fits",".cat")
return(product_filename_dict) | python | def single_exposure_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for single-exposure products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, detector, filter, and ipppssoot
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
filter = obs_info[4]
ipppssoot = obs_info[5]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}_{}_{}_{}.fits".format(proposal_id,visit_id,instrument,detector,filter,ipppssoot,nn)
product_filename_dict["source catalog"]= product_filename_dict["image"].replace(".fits",".cat")
return(product_filename_dict) | [
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spacetelescope/drizzlepac | drizzlepac/generate_final_product_filenames.py | filter_product_filename_generator | def filter_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for filter products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, detector, and filter
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
filter = obs_info[4]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}_{}.fits".format(proposal_id,visit_id,instrument,detector,filter)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return(product_filename_dict) | python | def filter_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for filter products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, detector, and filter
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
filter = obs_info[4]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}_{}.fits".format(proposal_id,visit_id,instrument,detector,filter)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return(product_filename_dict) | [
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the single-exposure image number (NOTE: only used in
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spacetelescope/drizzlepac | drizzlepac/generate_final_product_filenames.py | total_detection_product_filename_generator | def total_detection_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for total detection products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, and detector
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}.fits".format(proposal_id, visit_id, instrument, detector)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return (product_filename_dict) | python | def total_detection_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for total detection products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, and detector
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
proposal_id = obs_info[0]
visit_id = obs_info[1]
instrument = obs_info[2]
detector = obs_info[3]
product_filename_dict = {}
product_filename_dict["image"] = "hst_{}_{}_{}_{}.fits".format(proposal_id, visit_id, instrument, detector)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return (product_filename_dict) | [
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"... | Generate image and sourcelist filenames for total detection products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: proposal_id,
visit_id, instrument, and detector
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames. | [
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"for",
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"products"
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spacetelescope/drizzlepac | drizzlepac/generate_final_product_filenames.py | multivisit_mosaic_product_filename_generator | def multivisit_mosaic_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for multi-visit mosaic products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: group_id,
instrument, detector, and filter
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
group_num = obs_info[0]
instrument = obs_info[1]
detector = obs_info[2]
filter = obs_info[3]
product_filename_dict = {}
product_filename_dict["image"] = "hst_mos_{}_{}_{}_{}.fits".format(group_num,instrument,detector,filter)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return (product_filename_dict) | python | def multivisit_mosaic_product_filename_generator(obs_info,nn):
"""
Generate image and sourcelist filenames for multi-visit mosaic products
Parameters
----------
obs_info : list
list of items that will be used to generate the filenames: group_id,
instrument, detector, and filter
nn : string
the single-exposure image number (NOTE: only used in
single_exposure_product_filename_generator())
Returns
--------
product_filename_dict : dictionary
A dictionary containing the generated filenames.
"""
group_num = obs_info[0]
instrument = obs_info[1]
detector = obs_info[2]
filter = obs_info[3]
product_filename_dict = {}
product_filename_dict["image"] = "hst_mos_{}_{}_{}_{}.fits".format(group_num,instrument,detector,filter)
product_filename_dict["source catalog"] = product_filename_dict["image"].replace(".fits",".cat")
return (product_filename_dict) | [
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list of items that will be used to generate the filenames: group_id,
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the single-exposure image number (NOTE: only used in
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | build_referenceWCS | def build_referenceWCS(catalog_list):
""" Compute default reference WCS from list of Catalog objects.
"""
wcslist = []
for catalog in catalog_list:
for scichip in catalog.catalogs:
wcslist.append(catalog.catalogs[scichip]['wcs'])
return utils.output_wcs(wcslist) | python | def build_referenceWCS(catalog_list):
""" Compute default reference WCS from list of Catalog objects.
"""
wcslist = []
for catalog in catalog_list:
for scichip in catalog.catalogs:
wcslist.append(catalog.catalogs[scichip]['wcs'])
return utils.output_wcs(wcslist) | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | convex_hull | def convex_hull(points):
"""Computes the convex hull of a set of 2D points.
Implements `Andrew's monotone chain algorithm <http://en.wikibooks.org/wiki/Algorithm_Implementation/Geometry/Convex_hull/Monotone_chain>`_.
The algorithm has O(n log n) complexity.
Credit: `<http://en.wikibooks.org/wiki/Algorithm_Implementation/Geometry/Convex_hull/Monotone_chain>`_
Parameters
----------
points : list of tuples
An iterable sequence of (x, y) pairs representing the points.
Returns
-------
Output : list
A list of vertices of the convex hull in counter-clockwise order,
starting from the vertex with the lexicographically smallest
coordinates.
"""
# Sort the points lexicographically (tuples are compared lexicographically).
# Remove duplicates to detect the case we have just one unique point.
points = sorted(set(points))
# Boring case: no points or a single point, possibly repeated multiple times.
if len(points) <= 1:
return points
# 2D cross product of OA and OB vectors, i.e. z-component of their 3D cross product.
# Returns a positive value, if OAB makes a counter-clockwise turn,
# negative for clockwise turn, and zero if the points are collinear.
def cross(o, a, b):
return (a[0] - o[0]) * (b[1] - o[1]) - (a[1] - o[1]) * (b[0] - o[0])
# Build lower hull
lower = []
for p in points:
while len(lower) >= 2 and cross(lower[-2], lower[-1], p) <= 0:
lower.pop()
lower.append(p)
# Build upper hull
upper = []
for p in reversed(points):
while len(upper) >= 2 and cross(upper[-2], upper[-1], p) <= 0:
upper.pop()
upper.append(p)
# Concatenation of the lower and upper hulls gives the convex hull.
# Last point of each list is omitted because it is repeated at the beginning of the other list.
return lower[:-1] + upper | python | def convex_hull(points):
"""Computes the convex hull of a set of 2D points.
Implements `Andrew's monotone chain algorithm <http://en.wikibooks.org/wiki/Algorithm_Implementation/Geometry/Convex_hull/Monotone_chain>`_.
The algorithm has O(n log n) complexity.
Credit: `<http://en.wikibooks.org/wiki/Algorithm_Implementation/Geometry/Convex_hull/Monotone_chain>`_
Parameters
----------
points : list of tuples
An iterable sequence of (x, y) pairs representing the points.
Returns
-------
Output : list
A list of vertices of the convex hull in counter-clockwise order,
starting from the vertex with the lexicographically smallest
coordinates.
"""
# Sort the points lexicographically (tuples are compared lexicographically).
# Remove duplicates to detect the case we have just one unique point.
points = sorted(set(points))
# Boring case: no points or a single point, possibly repeated multiple times.
if len(points) <= 1:
return points
# 2D cross product of OA and OB vectors, i.e. z-component of their 3D cross product.
# Returns a positive value, if OAB makes a counter-clockwise turn,
# negative for clockwise turn, and zero if the points are collinear.
def cross(o, a, b):
return (a[0] - o[0]) * (b[1] - o[1]) - (a[1] - o[1]) * (b[0] - o[0])
# Build lower hull
lower = []
for p in points:
while len(lower) >= 2 and cross(lower[-2], lower[-1], p) <= 0:
lower.pop()
lower.append(p)
# Build upper hull
upper = []
for p in reversed(points):
while len(upper) >= 2 and cross(upper[-2], upper[-1], p) <= 0:
upper.pop()
upper.append(p)
# Concatenation of the lower and upper hulls gives the convex hull.
# Last point of each list is omitted because it is repeated at the beginning of the other list.
return lower[:-1] + upper | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | _estimate_2dhist_shift | def _estimate_2dhist_shift(imgxy, refxy, searchrad=3.0):
""" Create a 2D matrix-histogram which contains the delta between each
XY position and each UV position. Then estimate initial offset
between catalogs.
"""
print("Computing initial guess for X and Y shifts...")
# create ZP matrix
zpmat = _xy_2dhist(imgxy, refxy, r=searchrad)
nonzeros = np.count_nonzero(zpmat)
if nonzeros == 0:
# no matches within search radius. Return (0, 0):
print("WARNING: No matches found within a search radius of {:g} "
"pixels.".format(searchrad))
return 0.0, 0.0, 0, 0, zpmat, False
elif nonzeros == 1:
# only one non-zero bin:
yp, xp = np.unravel_index(np.argmax(zpmat), zpmat.shape)
maxval = int(np.ceil(zpmat[yp, xp]))
xp -= searchrad
yp -= searchrad
print("Found initial X and Y shifts of {:.4g}, {:.4g} "
"based on a single non-zero bin and {} matches"
.format(xp, yp, maxval))
return xp, yp, maxval, maxval, zpmat, True
(xp, yp), fit_status, fit_sl = _find_peak(zpmat, peak_fit_box=5,
mask=zpmat > 0)
if fit_status.startswith('ERROR'):
print("WARNING: No valid shift found within a search radius of {:g} "
"pixels.".format(searchrad))
maxval = int(np.ceil(zpmat.max()))
return 0.0, 0.0, maxval, maxval, zpmat, False
xp -= searchrad
yp -= searchrad
if fit_status == 'WARNING:EDGE':
print(
"WARNING: Found peak in the 2D histogram lies at the edge of "
"the histogram. Try increasing 'searchrad' for improved results."
)
# Attempt to estimate "significance of detection":
maxval = zpmat.max()
zpmat_mask = (zpmat > 0) & (zpmat < maxval)
if np.any(zpmat_mask):
bkg = zpmat[zpmat_mask].mean()
sig = maxval / np.sqrt(bkg)
flux = int(zpmat[fit_sl].sum())
print("Found initial X and Y shifts of {:.4g}, {:.4g} "
"with significance of {:.4g} and {:d} matches"
.format(xp, yp, sig, flux))
return xp, yp, int(np.ceil(maxval)), flux, zpmat, True | python | def _estimate_2dhist_shift(imgxy, refxy, searchrad=3.0):
""" Create a 2D matrix-histogram which contains the delta between each
XY position and each UV position. Then estimate initial offset
between catalogs.
"""
print("Computing initial guess for X and Y shifts...")
# create ZP matrix
zpmat = _xy_2dhist(imgxy, refxy, r=searchrad)
nonzeros = np.count_nonzero(zpmat)
if nonzeros == 0:
# no matches within search radius. Return (0, 0):
print("WARNING: No matches found within a search radius of {:g} "
"pixels.".format(searchrad))
return 0.0, 0.0, 0, 0, zpmat, False
elif nonzeros == 1:
# only one non-zero bin:
yp, xp = np.unravel_index(np.argmax(zpmat), zpmat.shape)
maxval = int(np.ceil(zpmat[yp, xp]))
xp -= searchrad
yp -= searchrad
print("Found initial X and Y shifts of {:.4g}, {:.4g} "
"based on a single non-zero bin and {} matches"
.format(xp, yp, maxval))
return xp, yp, maxval, maxval, zpmat, True
(xp, yp), fit_status, fit_sl = _find_peak(zpmat, peak_fit_box=5,
mask=zpmat > 0)
if fit_status.startswith('ERROR'):
print("WARNING: No valid shift found within a search radius of {:g} "
"pixels.".format(searchrad))
maxval = int(np.ceil(zpmat.max()))
return 0.0, 0.0, maxval, maxval, zpmat, False
xp -= searchrad
yp -= searchrad
if fit_status == 'WARNING:EDGE':
print(
"WARNING: Found peak in the 2D histogram lies at the edge of "
"the histogram. Try increasing 'searchrad' for improved results."
)
# Attempt to estimate "significance of detection":
maxval = zpmat.max()
zpmat_mask = (zpmat > 0) & (zpmat < maxval)
if np.any(zpmat_mask):
bkg = zpmat[zpmat_mask].mean()
sig = maxval / np.sqrt(bkg)
flux = int(zpmat[fit_sl].sum())
print("Found initial X and Y shifts of {:.4g}, {:.4g} "
"with significance of {:.4g} and {:d} matches"
.format(xp, yp, sig, flux))
return xp, yp, int(np.ceil(maxval)), flux, zpmat, True | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.openFile | def openFile(self, openDQ=False):
""" Open file and set up filehandle for image file
"""
if self._im.closed:
if not self._dq.closed:
self._dq.release()
assert(self._dq.closed)
fi = FileExtMaskInfo(clobber=False,
doNotOpenDQ=not openDQ,
im_fmode=self.open_mode)
fi.image = self.name
self._im = fi.image
fi.append_ext(spu.get_ext_list(self._im, extname='SCI'))
fi.finalize()
self._im = fi.image
self._dq = fi.DQimage
self._imext = fi.fext
self._dqext = fi.dqext | python | def openFile(self, openDQ=False):
""" Open file and set up filehandle for image file
"""
if self._im.closed:
if not self._dq.closed:
self._dq.release()
assert(self._dq.closed)
fi = FileExtMaskInfo(clobber=False,
doNotOpenDQ=not openDQ,
im_fmode=self.open_mode)
fi.image = self.name
self._im = fi.image
fi.append_ext(spu.get_ext_list(self._im, extname='SCI'))
fi.finalize()
self._im = fi.image
self._dq = fi.DQimage
self._imext = fi.fext
self._dqext = fi.dqext | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.get_wcs | def get_wcs(self):
""" Helper method to return a list of all the input WCS objects associated
with this image.
"""
wcslist = []
for chip in self.chip_catalogs:
wcslist.append(self.chip_catalogs[chip]['wcs'])
return wcslist | python | def get_wcs(self):
""" Helper method to return a list of all the input WCS objects associated
with this image.
"""
wcslist = []
for chip in self.chip_catalogs:
wcslist.append(self.chip_catalogs[chip]['wcs'])
return wcslist | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.buildSkyCatalog | def buildSkyCatalog(self):
""" Convert sky catalog for all chips into a single catalog for
the entire field-of-view of this image.
"""
self.all_radec = None
self.all_radec_orig = None
ralist = []
declist = []
fluxlist = []
idlist = []
for scichip in self.chip_catalogs:
skycat = self.chip_catalogs[scichip]['catalog'].radec
xycat = self.chip_catalogs[scichip]['catalog'].xypos
if skycat is not None:
ralist.append(skycat[0])
declist.append(skycat[1])
if xycat is not None and len(xycat) > 2:
fluxlist.append(xycat[2])
idlist.append(xycat[3])
elif len(skycat) > 2:
fluxlist.append(skycat[2])
idlist.append(skycat[3])
else:
fluxlist.append([999.0]*len(skycat[0]))
idlist.append(np.arange(len(skycat[0])))
self.all_radec = [np.concatenate(ralist),np.concatenate(declist),
np.concatenate(fluxlist),np.concatenate(idlist)]
self.all_radec_orig = copy.deepcopy(self.all_radec) | python | def buildSkyCatalog(self):
""" Convert sky catalog for all chips into a single catalog for
the entire field-of-view of this image.
"""
self.all_radec = None
self.all_radec_orig = None
ralist = []
declist = []
fluxlist = []
idlist = []
for scichip in self.chip_catalogs:
skycat = self.chip_catalogs[scichip]['catalog'].radec
xycat = self.chip_catalogs[scichip]['catalog'].xypos
if skycat is not None:
ralist.append(skycat[0])
declist.append(skycat[1])
if xycat is not None and len(xycat) > 2:
fluxlist.append(xycat[2])
idlist.append(xycat[3])
elif len(skycat) > 2:
fluxlist.append(skycat[2])
idlist.append(skycat[3])
else:
fluxlist.append([999.0]*len(skycat[0]))
idlist.append(np.arange(len(skycat[0])))
self.all_radec = [np.concatenate(ralist),np.concatenate(declist),
np.concatenate(fluxlist),np.concatenate(idlist)]
self.all_radec_orig = copy.deepcopy(self.all_radec) | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.buildDefaultRefWCS | def buildDefaultRefWCS(self):
""" Generate a default reference WCS for this image. """
self.default_refWCS = None
if self.use_wcs:
wcslist = []
for scichip in self.chip_catalogs:
wcslist.append(self.chip_catalogs[scichip]['wcs'])
self.default_refWCS = utils.output_wcs(wcslist) | python | def buildDefaultRefWCS(self):
""" Generate a default reference WCS for this image. """
self.default_refWCS = None
if self.use_wcs:
wcslist = []
for scichip in self.chip_catalogs:
wcslist.append(self.chip_catalogs[scichip]['wcs'])
self.default_refWCS = utils.output_wcs(wcslist) | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.transformToRef | def transformToRef(self,ref_wcs,force=False):
""" Transform sky coords from ALL chips into X,Y coords in reference WCS.
"""
if not isinstance(ref_wcs, pywcs.WCS):
print(textutil.textbox('Reference WCS not a valid HSTWCS object'),
file=sys.stderr)
raise ValueError
# Need to concatenate catalogs from each input
if self.outxy is None or force:
outxy = ref_wcs.wcs_world2pix(self.all_radec[0],self.all_radec[1],self.origin)
# convert outxy list to a Nx2 array
self.outxy = np.column_stack([outxy[0][:,np.newaxis],outxy[1][:,np.newaxis]])
if self.pars['writecat']:
catname = self.rootname+"_refxy_catalog.coo"
self.write_outxy(catname)
self.catalog_names['ref_xy'] = catname | python | def transformToRef(self,ref_wcs,force=False):
""" Transform sky coords from ALL chips into X,Y coords in reference WCS.
"""
if not isinstance(ref_wcs, pywcs.WCS):
print(textutil.textbox('Reference WCS not a valid HSTWCS object'),
file=sys.stderr)
raise ValueError
# Need to concatenate catalogs from each input
if self.outxy is None or force:
outxy = ref_wcs.wcs_world2pix(self.all_radec[0],self.all_radec[1],self.origin)
# convert outxy list to a Nx2 array
self.outxy = np.column_stack([outxy[0][:,np.newaxis],outxy[1][:,np.newaxis]])
if self.pars['writecat']:
catname = self.rootname+"_refxy_catalog.coo"
self.write_outxy(catname)
self.catalog_names['ref_xy'] = catname | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.get_xy_catnames | def get_xy_catnames(self):
""" Return a string with the names of input_xy catalog names
"""
catstr = self.name+' '
if 'input_xy' in self.catalog_names:
for xycat in self.catalog_names['input_xy']:
catstr += ' '+xycat
return catstr + '\n' | python | def get_xy_catnames(self):
""" Return a string with the names of input_xy catalog names
"""
catstr = self.name+' '
if 'input_xy' in self.catalog_names:
for xycat in self.catalog_names['input_xy']:
catstr += ' '+xycat
return catstr + '\n' | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.get_shiftfile_row | def get_shiftfile_row(self):
""" Return the information for a shiftfile for this image to provide
compatability with the IRAF-based MultiDrizzle.
"""
if self.fit is not None:
rowstr = '%s %0.6f %0.6f %0.6f %0.6f %0.6f %0.6f\n'%(
self.name,self.fit['offset'][0],self.fit['offset'][1],
self.fit['rot'],self.fit['scale'][0],
self.fit['rms'][0],self.fit['rms'][1])
else:
rowstr = None
return rowstr | python | def get_shiftfile_row(self):
""" Return the information for a shiftfile for this image to provide
compatability with the IRAF-based MultiDrizzle.
"""
if self.fit is not None:
rowstr = '%s %0.6f %0.6f %0.6f %0.6f %0.6f %0.6f\n'%(
self.name,self.fit['offset'][0],self.fit['offset'][1],
self.fit['rot'],self.fit['scale'][0],
self.fit['rms'][0],self.fit['rms'][1])
else:
rowstr = None
return rowstr | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | Image.clean | def clean(self):
""" Remove intermediate files created.
"""
#TODO: add cleaning of mask files, *if* created ...
for f in self.catalog_names:
if 'match' in f:
if os.path.exists(self.catalog_names[f]):
log.info('Deleting intermediate match file: %s'%
self.catalog_names[f])
os.remove(self.catalog_names[f])
else:
for extn in f:
if os.path.exists(extn):
log.info('Deleting intermediate catalog: %d'%extn)
os.remove(extn) | python | def clean(self):
""" Remove intermediate files created.
"""
#TODO: add cleaning of mask files, *if* created ...
for f in self.catalog_names:
if 'match' in f:
if os.path.exists(self.catalog_names[f]):
log.info('Deleting intermediate match file: %s'%
self.catalog_names[f])
os.remove(self.catalog_names[f])
else:
for extn in f:
if os.path.exists(extn):
log.info('Deleting intermediate catalog: %d'%extn)
os.remove(extn) | [
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spacetelescope/drizzlepac | drizzlepac/imgclasses.py | RefImage.clean | def clean(self):
""" Remove intermediate files created
"""
if not util.is_blank(self.catalog.catname) and os.path.exists(self.catalog.catname):
os.remove(self.catalog.catname) | python | def clean(self):
""" Remove intermediate files created
"""
if not util.is_blank(self.catalog.catname) and os.path.exists(self.catalog.catname):
os.remove(self.catalog.catname) | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.close | def close(self):
""" Close the object nicely and release all the data
arrays from memory YOU CANT GET IT BACK, the pointers
and data are gone so use the getData method to get
the data array returned for future use. You can use
putData to reattach a new data array to the imageObject.
"""
if self._image is None:
return
# mcara: I think the code below is not necessary but in order to
# preserve the same functionality as the code removed below,
# I make an empty copy of the image object:
empty_image = fits.HDUList()
for u in self._image:
empty_image.append(u.__class__(data=None, header=None))
# mcara: END unnecessary code
self._image.close() #calls fits.close()
self._image = empty_image | python | def close(self):
""" Close the object nicely and release all the data
arrays from memory YOU CANT GET IT BACK, the pointers
and data are gone so use the getData method to get
the data array returned for future use. You can use
putData to reattach a new data array to the imageObject.
"""
if self._image is None:
return
# mcara: I think the code below is not necessary but in order to
# preserve the same functionality as the code removed below,
# I make an empty copy of the image object:
empty_image = fits.HDUList()
for u in self._image:
empty_image.append(u.__class__(data=None, header=None))
# mcara: END unnecessary code
self._image.close() #calls fits.close()
self._image = empty_image | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.clean | def clean(self):
""" Deletes intermediate products generated for this imageObject.
"""
clean_files = ['blotImage','crmaskImage','finalMask',
'staticMask','singleDrizMask','outSky',
'outSContext','outSWeight','outSingle',
'outMedian','dqmask','tmpmask',
'skyMatchMask']
log.info('Removing intermediate files for %s' % self._filename)
# We need to remove the combined products first; namely, median image
util.removeFileSafely(self.outputNames['outMedian'])
# Now remove chip-specific intermediate files, if any were created.
for chip in self.returnAllChips(extname='SCI'):
for fname in clean_files:
if fname in chip.outputNames:
util.removeFileSafely(chip.outputNames[fname]) | python | def clean(self):
""" Deletes intermediate products generated for this imageObject.
"""
clean_files = ['blotImage','crmaskImage','finalMask',
'staticMask','singleDrizMask','outSky',
'outSContext','outSWeight','outSingle',
'outMedian','dqmask','tmpmask',
'skyMatchMask']
log.info('Removing intermediate files for %s' % self._filename)
# We need to remove the combined products first; namely, median image
util.removeFileSafely(self.outputNames['outMedian'])
# Now remove chip-specific intermediate files, if any were created.
for chip in self.returnAllChips(extname='SCI'):
for fname in clean_files:
if fname in chip.outputNames:
util.removeFileSafely(chip.outputNames[fname]) | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.getData | def getData(self,exten=None):
""" Return just the data array from the specified extension
fileutil is used instead of fits to account for non-
FITS input images. openImage returns a fits object.
"""
if exten.lower().find('sci') > -1:
# For SCI extensions, the current file will have the data
fname = self._filename
else:
# otherwise, the data being requested may need to come from a
# separate file, as is the case with WFPC2 DQ data.
#
# convert exten to 'sci',extver to get the DQ info for that chip
extn = exten.split(',')
sci_chip = self._image[self.scienceExt,int(extn[1])]
fname = sci_chip.dqfile
extnum = self._interpretExten(exten)
if self._image[extnum].data is None:
if os.path.exists(fname):
_image=fileutil.openImage(fname, clobber=False, memmap=False)
_data=fileutil.getExtn(_image, extn=exten).data
_image.close()
del _image
self._image[extnum].data = _data
else:
_data = None
else:
_data = self._image[extnum].data
return _data | python | def getData(self,exten=None):
""" Return just the data array from the specified extension
fileutil is used instead of fits to account for non-
FITS input images. openImage returns a fits object.
"""
if exten.lower().find('sci') > -1:
# For SCI extensions, the current file will have the data
fname = self._filename
else:
# otherwise, the data being requested may need to come from a
# separate file, as is the case with WFPC2 DQ data.
#
# convert exten to 'sci',extver to get the DQ info for that chip
extn = exten.split(',')
sci_chip = self._image[self.scienceExt,int(extn[1])]
fname = sci_chip.dqfile
extnum = self._interpretExten(exten)
if self._image[extnum].data is None:
if os.path.exists(fname):
_image=fileutil.openImage(fname, clobber=False, memmap=False)
_data=fileutil.getExtn(_image, extn=exten).data
_image.close()
del _image
self._image[extnum].data = _data
else:
_data = None
else:
_data = self._image[extnum].data
return _data | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.getHeader | def getHeader(self,exten=None):
""" Return just the specified header extension fileutil
is used instead of fits to account for non-FITS
input images. openImage returns a fits object.
"""
_image=fileutil.openImage(self._filename, clobber=False, memmap=False)
_header=fileutil.getExtn(_image,extn=exten).header
_image.close()
del _image
return _header | python | def getHeader(self,exten=None):
""" Return just the specified header extension fileutil
is used instead of fits to account for non-FITS
input images. openImage returns a fits object.
"""
_image=fileutil.openImage(self._filename, clobber=False, memmap=False)
_header=fileutil.getExtn(_image,extn=exten).header
_image.close()
del _image
return _header | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.updateData | def updateData(self,exten,data):
""" Write out updated data and header to
the original input file for this object.
"""
_extnum=self._interpretExten(exten)
fimg = fileutil.openImage(self._filename, mode='update', memmap=False)
fimg[_extnum].data = data
fimg[_extnum].header = self._image[_extnum].header
fimg.close() | python | def updateData(self,exten,data):
""" Write out updated data and header to
the original input file for this object.
"""
_extnum=self._interpretExten(exten)
fimg = fileutil.openImage(self._filename, mode='update', memmap=False)
fimg[_extnum].data = data
fimg[_extnum].header = self._image[_extnum].header
fimg.close() | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.getAllData | def getAllData(self,extname=None,exclude=None):
""" This function is meant to make it easier to attach ALL the data
extensions of the image object so that we can write out copies of
the original image nicer.
If no extname is given, the it retrieves all data from the original
file and attaches it. Otherwise, give the name of the extensions
you want and all of those will be restored.
Ok, I added another option. If you want to get all the data
extensions EXCEPT a particular one, leave extname=NONE and
set exclude=EXTNAME. This is helpfull cause you might not know
all the extnames the image has, this will find out and exclude
the one you do not want overwritten.
"""
extensions = self._findExtnames(extname=extname,exclude=exclude)
for i in range(1,self._nextend+1,1):
if hasattr(self._image[i],'_extension') and \
"IMAGE" in self._image[i]._extension:
extver = self._image[i].header['extver']
if (self._image[i].extname in extensions) and self._image[self.scienceExt,extver].group_member:
self._image[i].data=self.getData(self._image[i].extname + ','+str(self._image[i].extver)) | python | def getAllData(self,extname=None,exclude=None):
""" This function is meant to make it easier to attach ALL the data
extensions of the image object so that we can write out copies of
the original image nicer.
If no extname is given, the it retrieves all data from the original
file and attaches it. Otherwise, give the name of the extensions
you want and all of those will be restored.
Ok, I added another option. If you want to get all the data
extensions EXCEPT a particular one, leave extname=NONE and
set exclude=EXTNAME. This is helpfull cause you might not know
all the extnames the image has, this will find out and exclude
the one you do not want overwritten.
"""
extensions = self._findExtnames(extname=extname,exclude=exclude)
for i in range(1,self._nextend+1,1):
if hasattr(self._image[i],'_extension') and \
"IMAGE" in self._image[i]._extension:
extver = self._image[i].header['extver']
if (self._image[i].extname in extensions) and self._image[self.scienceExt,extver].group_member:
self._image[i].data=self.getData(self._image[i].extname + ','+str(self._image[i].extver)) | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject._findExtnames | def _findExtnames(self, extname=None, exclude=None):
""" This method builds a list of all extensions which have 'EXTNAME'==extname
and do not include any extensions with 'EXTNAME'==exclude, if any are
specified for exclusion at all.
"""
#make a list of the available extension names for the object
extensions=[]
if extname is not None:
if not isinstance(extname,list): extname=[extname]
for extn in extname:
extensions.append(extn.upper())
else:
#restore all the extensions data from the original file, be careful here
#if you've altered data in memory you want to keep!
for i in range(1,self._nextend+1,1):
if hasattr(self._image[i],'_extension') and \
"IMAGE" in self._image[i]._extension:
if self._image[i].extname.upper() not in extensions:
extensions.append(self._image[i].extname)
#remove this extension from the list
if exclude is not None:
exclude.upper()
if exclude in extensions:
newExt=[]
for item in extensions:
if item != exclude:
newExt.append(item)
extensions=newExt
del newExt
return extensions | python | def _findExtnames(self, extname=None, exclude=None):
""" This method builds a list of all extensions which have 'EXTNAME'==extname
and do not include any extensions with 'EXTNAME'==exclude, if any are
specified for exclusion at all.
"""
#make a list of the available extension names for the object
extensions=[]
if extname is not None:
if not isinstance(extname,list): extname=[extname]
for extn in extname:
extensions.append(extn.upper())
else:
#restore all the extensions data from the original file, be careful here
#if you've altered data in memory you want to keep!
for i in range(1,self._nextend+1,1):
if hasattr(self._image[i],'_extension') and \
"IMAGE" in self._image[i]._extension:
if self._image[i].extname.upper() not in extensions:
extensions.append(self._image[i].extname)
#remove this extension from the list
if exclude is not None:
exclude.upper()
if exclude in extensions:
newExt=[]
for item in extensions:
if item != exclude:
newExt.append(item)
extensions=newExt
del newExt
return extensions | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.findExtNum | def findExtNum(self, extname=None, extver=1):
"""Find the extension number of the give extname and extver."""
extnum = None
extname = extname.upper()
if not self._isSimpleFits:
for ext in self._image:
if (hasattr(ext,'_extension') and 'IMAGE' in ext._extension and
(ext.extname == extname) and (ext.extver == extver)):
extnum = ext.extnum
else:
log.info("Image is simple fits")
return extnum | python | def findExtNum(self, extname=None, extver=1):
"""Find the extension number of the give extname and extver."""
extnum = None
extname = extname.upper()
if not self._isSimpleFits:
for ext in self._image:
if (hasattr(ext,'_extension') and 'IMAGE' in ext._extension and
(ext.extname == extname) and (ext.extver == extver)):
extnum = ext.extnum
else:
log.info("Image is simple fits")
return extnum | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject._assignRootname | def _assignRootname(self, chip):
""" Assign a unique rootname for the image based in the expname. """
extname=self._image[self.scienceExt,chip].header["EXTNAME"].lower()
extver=self._image[self.scienceExt,chip].header["EXTVER"]
expname = self._rootname
# record extension-based name to reflect what extension a mask file corresponds to
self._image[self.scienceExt,chip].rootname=expname + "_" + extname + str(extver)
self._image[self.scienceExt,chip].sciname=self._filename + "[" + extname +","+str(extver)+"]"
self._image[self.scienceExt,chip].dqrootname=self._rootname + "_" + extname + str(extver)
# Needed to keep EXPNAMEs associated properly (1 EXPNAME for all chips)
self._image[self.scienceExt,chip]._expname=expname
self._image[self.scienceExt,chip]._chip =chip | python | def _assignRootname(self, chip):
""" Assign a unique rootname for the image based in the expname. """
extname=self._image[self.scienceExt,chip].header["EXTNAME"].lower()
extver=self._image[self.scienceExt,chip].header["EXTVER"]
expname = self._rootname
# record extension-based name to reflect what extension a mask file corresponds to
self._image[self.scienceExt,chip].rootname=expname + "_" + extname + str(extver)
self._image[self.scienceExt,chip].sciname=self._filename + "[" + extname +","+str(extver)+"]"
self._image[self.scienceExt,chip].dqrootname=self._rootname + "_" + extname + str(extver)
# Needed to keep EXPNAMEs associated properly (1 EXPNAME for all chips)
self._image[self.scienceExt,chip]._expname=expname
self._image[self.scienceExt,chip]._chip =chip | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject._setOutputNames | def _setOutputNames(self,rootname,suffix='_drz'):
""" Define the default output filenames for drizzle products,
these are based on the original rootname of the image
filename should be just 1 filename, so call this in a loop
for chip names contained inside a file.
"""
# Define FITS output filenames for intermediate products
# Build names based on final DRIZZLE output name
# where 'output' normally would have been created
# by 'process_input()'
#
outFinal = rootname+suffix+'.fits'
outSci = rootname+suffix+'_sci.fits'
outWeight = rootname+suffix+'_wht.fits'
outContext = rootname+suffix+'_ctx.fits'
outMedian = rootname+'_med.fits'
# Build names based on input name
origFilename = self._filename.replace('.fits','_OrIg.fits')
outSky = rootname + '_sky.fits'
outSingle = rootname+'_single_sci.fits'
outSWeight = rootname+'_single_wht.fits'
crCorImage = rootname+'_crclean.fits'
# Build outputNames dictionary
fnames={
'origFilename': origFilename,
'outFinal': outFinal,
'outMedian': outMedian,
'outSci': outSci,
'outWeight': outWeight,
'outContext': outContext,
'outSingle': outSingle,
'outSWeight': outSWeight,
'outSContext': None,
'outSky': outSky,
'crcorImage': crCorImage,
'ivmFile': None
}
return fnames | python | def _setOutputNames(self,rootname,suffix='_drz'):
""" Define the default output filenames for drizzle products,
these are based on the original rootname of the image
filename should be just 1 filename, so call this in a loop
for chip names contained inside a file.
"""
# Define FITS output filenames for intermediate products
# Build names based on final DRIZZLE output name
# where 'output' normally would have been created
# by 'process_input()'
#
outFinal = rootname+suffix+'.fits'
outSci = rootname+suffix+'_sci.fits'
outWeight = rootname+suffix+'_wht.fits'
outContext = rootname+suffix+'_ctx.fits'
outMedian = rootname+'_med.fits'
# Build names based on input name
origFilename = self._filename.replace('.fits','_OrIg.fits')
outSky = rootname + '_sky.fits'
outSingle = rootname+'_single_sci.fits'
outSWeight = rootname+'_single_wht.fits'
crCorImage = rootname+'_crclean.fits'
# Build outputNames dictionary
fnames={
'origFilename': origFilename,
'outFinal': outFinal,
'outMedian': outMedian,
'outSci': outSci,
'outWeight': outWeight,
'outContext': outContext,
'outSingle': outSingle,
'outSWeight': outSWeight,
'outSContext': None,
'outSky': outSky,
'crcorImage': crCorImage,
'ivmFile': None
}
return fnames | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject._initVirtualOutputs | def _initVirtualOutputs(self):
""" Sets up the structure to hold all the output data arrays for
this image in memory.
"""
self.virtualOutputs = {}
for product in self.outputNames:
self.virtualOutputs[product] = None | python | def _initVirtualOutputs(self):
""" Sets up the structure to hold all the output data arrays for
this image in memory.
"""
self.virtualOutputs = {}
for product in self.outputNames:
self.virtualOutputs[product] = None | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.saveVirtualOutputs | def saveVirtualOutputs(self,outdict):
""" Assign in-memory versions of generated products for this
``imageObject`` based on dictionary 'outdict'.
"""
if not self.inmemory:
return
for outname in outdict:
self.virtualOutputs[outname] = outdict[outname] | python | def saveVirtualOutputs(self,outdict):
""" Assign in-memory versions of generated products for this
``imageObject`` based on dictionary 'outdict'.
"""
if not self.inmemory:
return
for outname in outdict:
self.virtualOutputs[outname] = outdict[outname] | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.getOutputName | def getOutputName(self,name):
""" Return the name of the file or PyFITS object associated with that
name, depending on the setting of self.inmemory.
"""
val = self.outputNames[name]
if self.inmemory: # if inmemory was turned on...
# return virtualOutput object saved with that name
val = self.virtualOutputs[val]
return val | python | def getOutputName(self,name):
""" Return the name of the file or PyFITS object associated with that
name, depending on the setting of self.inmemory.
"""
val = self.outputNames[name]
if self.inmemory: # if inmemory was turned on...
# return virtualOutput object saved with that name
val = self.virtualOutputs[val]
return val | [
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spacetelescope/drizzlepac | drizzlepac/imageObject.py | baseImageObject.updateOutputValues | def updateOutputValues(self,output_wcs):
""" Copy info from output WCSObject into outputnames for each chip
for use in creating outputimage object.
"""
outputvals = self.outputValues
outputvals['output'] = output_wcs.outputNames['outFinal']
outputvals['outnx'], outputvals['outny'] = output_wcs.wcs.pixel_shape
outputvals['texptime'] = output_wcs._exptime
outputvals['texpstart'] = output_wcs._expstart
outputvals['texpend'] = output_wcs._expend
outputvals['nimages'] = output_wcs.nimages
outputvals['scale'] = output_wcs.wcs.pscale #/ self._image[self.scienceExt,1].wcs.pscale
outputvals['exptime'] = self._exptime
outnames = self.outputNames
outnames['outMedian'] = output_wcs.outputNames['outMedian']
outnames['outFinal'] = output_wcs.outputNames['outFinal']
outnames['outSci'] = output_wcs.outputNames['outSci']
outnames['outWeight'] = output_wcs.outputNames['outWeight']
outnames['outContext'] = output_wcs.outputNames['outContext'] | python | def updateOutputValues(self,output_wcs):
""" Copy info from output WCSObject into outputnames for each chip
for use in creating outputimage object.
"""
outputvals = self.outputValues
outputvals['output'] = output_wcs.outputNames['outFinal']
outputvals['outnx'], outputvals['outny'] = output_wcs.wcs.pixel_shape
outputvals['texptime'] = output_wcs._exptime
outputvals['texpstart'] = output_wcs._expstart
outputvals['texpend'] = output_wcs._expend
outputvals['nimages'] = output_wcs.nimages
outputvals['scale'] = output_wcs.wcs.pscale #/ self._image[self.scienceExt,1].wcs.pscale
outputvals['exptime'] = self._exptime
outnames = self.outputNames
outnames['outMedian'] = output_wcs.outputNames['outMedian']
outnames['outFinal'] = output_wcs.outputNames['outFinal']
outnames['outSci'] = output_wcs.outputNames['outSci']
outnames['outWeight'] = output_wcs.outputNames['outWeight']
outnames['outContext'] = output_wcs.outputNames['outContext'] | [
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