Source code for jwst.tweakreg.tweakreg_step

JWST pipeline step for image alignment.

:Authors: Mihai Cara

from os import path

from astropy.table import Table
from tweakwcs.imalign import align_wcs
from tweakwcs.tpwcs import JWSTgWCS
from tweakwcs.matchutils import TPMatch

from ..stpipe import Step
from .. import datamodels

from . import astrometric_utils as amutils
from .tweakreg_catalog import make_tweakreg_catalog

__all__ = ['TweakRegStep']

[docs]class TweakRegStep(Step): """ TweakRegStep: Image alignment based on catalogs of sources detected in input images. """ spec = """ save_catalogs = boolean(default=False) # Write out catalogs? catalog_format = string(default='ecsv') # Catalog output file format kernel_fwhm = float(default=2.5) # Gaussian kernel FWHM in pixels snr_threshold = float(default=10.0) # SNR threshold above the bkg brightest = integer(default=1000) # Keep top ``brightest`` objects peakmax = float(default=None) # Filter out objects with pixel values >= ``peakmax`` enforce_user_order = boolean(default=False) # Align images in user specified order? expand_refcat = boolean(default=False) # Expand reference catalog with new sources? minobj = integer(default=15) # Minimum number of objects acceptable for matching searchrad = float(default=1.0) # The search radius in arcsec for a match use2dhist = boolean(default=True) # Use 2d histogram to find initial offset? separation = float(default=0.5) # Minimum object separation in arcsec tolerance = float(default=1.0) # Matching tolerance for xyxymatch in arcsec xoffset = float(default=0.0), # Initial guess for X offset in arcsec yoffset = float(default=0.0) # Initial guess for Y offset in arcsec fitgeometry = option('shift', 'rscale', 'general', default='general') # Fitting geometry nclip = integer(min=0, default=3) # Number of clipping iterations in fit sigma = float(min=0.0, default=3.0) # Clipping limit in sigma units align_to_gaia = boolean(default=False) # Align to GAIA catalog gaia_catalog = option('GAIADR2', 'GAIADR1', default='GAIADR2') min_gaia = integer(min=0, default=5) # Min number of GAIA sources needed save_gaia_catalog = boolean(default=False) # Write out GAIA catalog as a separate product """ reference_file_types = []
[docs] def process(self, input): try: images = datamodels.ModelContainer(input) except TypeError as e: e.args = ("Input to tweakreg must be a list of DataModels, an " "association, or an already open ModelContainer " "containing one or more DataModels.", ) + e.args[1:] raise e if self.align_to_gaia: # Set expand_refcat to True to eliminate possibility of duplicate # entries when aligning to GAIA self.expand_refcat=True # Build the catalogs for input images for image_model in images: catalog = make_tweakreg_catalog( image_model, self.kernel_fwhm, self.snr_threshold, brightest=self.brightest, peakmax=self.peakmax ) # filter out sources outside the image array if WCS validity # region is provided: wcs_bounds = image_model.meta.wcs.pixel_bounds if wcs_bounds is not None: ((xmin, xmax), (ymin, ymax)) = wcs_bounds xname = 'xcentroid' if 'xcentroid' in catalog.colnames else 'x' yname = 'ycentroid' if 'ycentroid' in catalog.colnames else 'y' x = catalog[xname] y = catalog[yname] mask = (x > xmin) & (x < xmax) & (y > ymin) & (y < ymax) catalog = catalog[mask] filename = image_model.meta.filename nsources = len(catalog) if nsources == 0: self.log.warning('No sources found in {}.'.format(filename)) else:'Detected {} sources in {}.' .format(len(catalog), filename)) if self.save_catalogs: catalog_filename = filename.replace( '.fits', '_cat.{}'.format(self.catalog_format) ) if self.catalog_format == 'ecsv': fmt = 'ascii.ecsv' elif self.catalog_format == 'fits': # NOTE: The catalog must not contain any 'None' values. # FITS will also not clobber existing files. fmt = 'fits' else: raise ValueError( '\'catalog_format\' must be "ecsv" or "fits".' ) catalog.write(catalog_filename, format=fmt, overwrite=True)'Wrote source catalog: {}' .format(catalog_filename)) image_model.meta.tweakreg_catalog = catalog_filename image_model.catalog = catalog # Now use the catalogs for tweakreg if len(images) == 0: raise ValueError("Input must contain at least one image model.") # group images by their "group id": grp_img = images.models_grouped'')"Number of image groups to be aligned: {:d}." .format(len(grp_img)))"Image groups:") if len(grp_img) == 1:"* Images in GROUP 1:") for im in grp_img[0]:" {}".format(im.meta.filename))'') # we need at least two exposures to perform image alignment self.log.warning("At least two exposures are required for image " "alignment.") self.log.warning("Nothing to do. Skipping 'TweakRegStep'...") self.skip = True for model in images: model.meta.cal_step.tweakreg = "SKIPPED" return input # create a list of WCS-Catalog-Images Info and/or their Groups: imcats = [] for g in grp_img: if len(g) == 0: raise AssertionError("Logical error in the pipeline code.") else: group_name = _common_name(g) wcsimlist = list(map(self._imodel2wcsim, g))"* Images in GROUP '{}':".format(group_name)) for im in wcsimlist: im.meta['group_id'] = group_name" {}".format(im.meta['name'])) imcats.extend(wcsimlist)'') # align images: tpmatch = TPMatch( searchrad=self.searchrad, separation=self.separation, use2dhist=self.use2dhist, tolerance=self.tolerance, xoffset=self.xoffset, yoffset=self.yoffset ) try: align_wcs( imcats, refcat=None, enforce_user_order=self.enforce_user_order, expand_refcat=self.expand_refcat, minobj=self.minobj, match=tpmatch, fitgeom=self.fitgeometry, nclip=self.nclip, sigma=(self.sigma, 'rmse') ) except ValueError as e: msg = e.args[0] if (msg == "Too few input images (or groups of images) with " "non-empty catalogs."): # we need at least two exposures to perform image alignment self.log.warning(msg) self.log.warning("At least two exposures are required for " "image alignment.") self.log.warning("Nothing to do. Skipping 'TweakRegStep'...") self.skip = True for model in images: model.meta.cal_step.tweakreg = "SKIPPED" return images else: raise e if self.align_to_gaia: # Get catalog of GAIA sources for the field # # NOTE: If desired, the pipeline can write out the reference # catalog as a separate product with a name based on # whatever convention is determined by the JWST Cal Working # Group. if self.save_gaia_catalog: output_name = 'fit_{}_ref.ecsv'.format(self.gaia_catalog.lower()) else: output_name = None ref_cat = amutils.create_astrometric_catalog(images, self.gaia_catalog, output=output_name) # Check that there are enough GAIA sources for a reliable/valid fit num_ref = len(ref_cat) if num_ref < self.min_gaia: msg = "Not enough GAIA sources for a fit: {}\n".format(num_ref) msg += "Skipping alignment to {} astrometric catalog!\n".format(self.gaia_catalog) # Raise Exception here to avoid rest of code in this try block self.log.warning(msg) else: # align images: # Update to separation needed to prevent confusion of sources # from overlapping images where centering is not consistent or # for the possibility that errors still exist in relative overlap. tpmatch_gaia = TPMatch( searchrad=self.searchrad * 3.0, separation=self.separation / 10.0, use2dhist=self.use2dhist, tolerance=self.tolerance, xoffset=0.0, yoffset=0.0 ) # Set group_id to same value so all get fit as one observation # The assigned value, 987654, has been hard-coded to make it # easy to recognize when alignment to GAIA was being performed # as opposed to the group_id values used for relative alignment # earlier in this step. for imcat in imcats: imcat.meta['group_id'] = 987654 if 'REFERENCE' in imcat.meta['fit_info']['status']: del imcat.meta['fit_info'] # Perform fit align_wcs( imcats, refcat=ref_cat, enforce_user_order=True, expand_refcat=False, minobj=self.minobj, match=tpmatch_gaia, fitgeom=self.fitgeometry, nclip=self.nclip, sigma=(self.sigma, 'rmse') ) for imcat in imcats: imcat.meta['image_model'].meta.cal_step.tweakreg = 'COMPLETE' # retrieve fit status and update wcs if fit is successful: if 'SUCCESS' in imcat.meta.get('fit_info')['status']: # Update/create the WCS .name attribute with information # on this astrometric fit as the only record that it was # successful: if self.align_to_gaia: # NOTE: This .name attrib agreed upon by the JWST Cal # Working Group. # Current value is merely a place-holder based # on HST conventions. This value should also be # translated to the FITS WCSNAME keyword # IF that is what gets recorded in the archive # for end-user searches. = "FIT-LVL3-{}".format(self.gaia_catalog) imcat.meta['image_model'].meta.wcs = imcat.wcs """ # Also update FITS representation in input exposures for # subsequent reprocessing by the end-user. # Not currently enabled, but may be requested later... gwcs_header = imcat.wcs.to_fits_sip(max_pix_error=0.1, max_inv_pix_error=0.1, degree=3, npoints=128) imcat.meta['image_model'].wcs = wcs.WCS(header=gwcs_header) """ return images
def _imodel2wcsim(self, image_model): # make sure that we have a catalog: if hasattr(image_model, 'catalog'): catalog = image_model.catalog else: catalog = image_model.meta.tweakreg_catalog model_name = path.splitext(image_model.meta.filename)[0].strip('_- ') if isinstance(catalog, Table): if not catalog.meta.get('name', None): catalog.meta['name'] = model_name else: try: cat_name = str(catalog) catalog =, format='ascii.ecsv') catalog.meta['name'] = cat_name except IOError: self.log.error("Cannot read catalog {}".format(catalog)) if 'xcentroid' in catalog.colnames: catalog.rename_column('xcentroid', 'x') catalog.rename_column('ycentroid', 'y') # create WCSImageCatalog object: refang = image_model.meta.wcsinfo.instance im = JWSTgWCS( wcs=image_model.meta.wcs, wcsinfo={'roll_ref': refang['roll_ref'], 'v2_ref': refang['v2_ref'], 'v3_ref': refang['v3_ref']}, meta={'image_model': image_model, 'catalog': catalog, 'name': model_name} ) return im
def _common_name(group): file_names = [path.splitext(im.meta.filename)[0].strip('_- ') for im in group] fname_len = list(map(len, file_names)) assert all(fname_len[0] == l for l in fname_len) cn = path.commonprefix(file_names) assert cn return cn