Source code for stwcs.wcsutil.wcscorr

import copy
import numpy as np
from astropy.io import fits

from . import altwcs
from .hstwcs import HSTWCS
from ..updatewcs import utils
from stsci.tools import fileutil

DEFAULT_WCS_KEYS = ['CRVAL1', 'CRVAL2', 'CRPIX1', 'CRPIX2',
                    'CD1_1', 'CD1_2', 'CD2_1', 'CD2_2',
                    'CTYPE1', 'CTYPE2', 'ORIENTAT']
DEFAULT_PRI_KEYS = ['HDRNAME', 'SIPNAME', 'NPOLNAME', 'D2IMNAME', 'DESCRIP']
COL_FITSKW_DICT = {'RMS_RA': 'sci.crder1', 'RMS_DEC': 'sci.crder2',
                   'NMatch': 'sci.nmatch', 'Catalog': 'sci.catalog'}

###
### WCSEXT table related keyword archive functions
###
[docs]def init_wcscorr(input, force=False): """ This function will initialize the WCSCORR table if it is not already present, and look for WCS keywords with a prefix of 'O' as the original OPUS generated WCS as the initial row for the table or use the current WCS keywords as initial row if no 'O' prefix keywords are found. This function will NOT overwrite any rows already present. This function works on all SCI extensions at one time. """ # TODO: Create some sort of decorator or (for Python2.5) context for # opening a FITS file and closing it when done, if necessary if not isinstance(input, fits.HDUList): # input must be a filename, so open as `astropy.io.fits.HDUList` object fimg = fits.open(input, mode='update') need_to_close = True else: fimg = input need_to_close = False # Do not try to generate a WCSCORR table for a simple FITS file numsci = fileutil.countExtn(fimg) if len(fimg) == 1 or numsci == 0 or 'NDRIZIM' in fimg[0].header or 'D001DATA' in fimg[0].header: if need_to_close: fimg.close() return enames = [] for e in fimg: enames.append(e.name) if 'WCSCORR' in enames: if not force: if need_to_close: fimg.close() return else: del fimg['wcscorr'] print('Initializing new WCSCORR table for ', fimg.filename()) used_wcskeys = altwcs.wcskeys(fimg['SCI', 1].header) # define the primary columns of the WCSEXT table with initial rows for each # SCI extension for the original OPUS solution numwcs = max(1, len(used_wcskeys)) # create new table with more rows than needed initially to make it easier to # add new rows later wcsext = create_wcscorr(descrip=True, numrows=numsci, padding=(numsci * numwcs) + numsci * 4) # Assign the correct EXTNAME value to this table extension wcsext.header['TROWS'] = (numsci * 2, 'Number of updated rows in table') wcsext.header['EXTNAME'] = ('WCSCORR', 'Table with WCS Update history') wcsext.header['EXTVER'] = 1 # define set of WCS keywords which need to be managed and copied to the table wcs1 = HSTWCS(fimg, ext=('SCI', 1)) idc2header = wcs1.idcscale is not None wcs_keywords = list(wcs1.wcs2header(idc2hdr=idc2header).keys()) prihdr = fimg[0].header prihdr_keys = DEFAULT_PRI_KEYS pri_funcs = {'SIPNAME': utils.build_sipname, 'NPOLNAME': utils.build_npolname, 'D2IMNAME': utils.build_d2imname} # Now copy original OPUS values into table for extver in range(1, numsci + 1): rowind = find_wcscorr_row(wcsext.data, {'WCS_ID': 'OPUS', 'EXTVER': extver, 'WCS_key': 'O'}) # There should only EVER be a single row for each extension with OPUS values rownum = np.where(rowind)[0][0] # print 'Archiving OPUS WCS in row number ',rownum,' in WCSCORR table for SCI,',extver hdr = fimg['SCI', extver].header # define set of WCS keywords which need to be managed and copied to the table if used_wcskeys is None: used_wcskeys = altwcs.wcskeys(hdr) # Check to see whether or not there is an OPUS alternate WCS present, # if so, get its values directly, otherwise, archive the PRIMARY WCS # as the OPUS values in the WCSCORR table if 'O' not in used_wcskeys: altwcs.archive_wcs(fimg, ('SCI', extver), wcskey='O', wcsname='OPUS') wkey = 'O' wcs = HSTWCS(fimg, ext=('SCI', extver), wcskey=wkey) wcshdr = wcs.wcs2header(idc2hdr=idc2header) if wcsext.data.field('CRVAL1')[rownum] != 0: # If we find values for these keywords already in the table, do not # overwrite them again print('WCS keywords already updated...') break for kwd in wcs_keywords: alt_kwd = (kwd + wkey)[:8] if kwd in wcsext.data.names and alt_kwd in wcshdr: wcsext.data.field(kwd)[rownum] = wcshdr[alt_kwd] # Now get any keywords from PRIMARY header needed for WCS updates for kwd in prihdr_keys: wcsext.data.field(kwd)[rownum] = prihdr.get(kwd, '') # Now that we have archived the OPUS alternate WCS, remove it from the list # of used_wcskeys if 'O' in used_wcskeys: used_wcskeys.remove('O') # Now copy remaining alternate WCSs into table # TODO: Much of this appears to be redundant with update_wcscorr; consider # merging them... for uwkey in used_wcskeys: for extver in range(1, numsci + 1): hdr = fimg['SCI', extver].header wcs = HSTWCS(fimg, ext=('SCI', extver), wcskey=uwkey) wcshdr = wcs.wcs2header() if 'WCSNAME' + uwkey not in wcshdr: wcsid = utils.build_default_wcsname(fimg[0].header['idctab']) else: wcsid = wcshdr['WCSNAME' + uwkey] # identify next empty row rowind = find_wcscorr_row(wcsext.data, selections={'wcs_id': ['', '0.0']}) rows = np.where(rowind) if len(rows[0]) > 0: rownum = np.where(rowind)[0][0] else: print('No available rows found for updating. ') # Update selection columns for this row with relevant values wcsext.data.field('WCS_ID')[rownum] = wcsid wcsext.data.field('EXTVER')[rownum] = extver wcsext.data.field('WCS_key')[rownum] = uwkey # Look for standard WCS keyword values for key in wcs_keywords: if key in wcsext.data.names: wcsext.data.field(key)[rownum] = wcshdr[key + uwkey] # Now get any keywords from PRIMARY header needed for WCS updates for key in prihdr_keys: if key in pri_funcs: val = pri_funcs[key](fimg)[0] else: val = prihdr.get(key, '') wcsext.data.field(key)[rownum] = val # Append this table to the image FITS file fimg.append(wcsext) # force an update now # set the verify flag to 'warn' so that it will always succeed, but still # tell the user if PyFITS detects any problems with the file as a whole utils.updateNEXTENDKw(fimg) fimg.flush('warn') if need_to_close: fimg.close()
[docs]def find_wcscorr_row(wcstab, selections): """ Return an array of indices from the table (NOT HDU) 'wcstab' that matches the selections specified by the user. The row selection criteria must be specified as a dictionary with column name as key and value(s) representing the valid desired row values. For example, {'wcs_id':'OPUS','extver':2}. """ mask = None for i in selections: icol = wcstab.field(i) if isinstance(icol, np.chararray): icol = icol.rstrip() selecti = selections[i] if not isinstance(selecti, list): if isinstance(selecti, str): selecti = selecti.rstrip() bmask = (icol == selecti) if mask is None: mask = bmask.copy() else: mask = np.logical_and(mask, bmask) del bmask else: for si in selecti: if isinstance(si, str): si = si.rstrip() bmask = (icol == si) if mask is None: mask = bmask.copy() else: mask = np.logical_or(mask, bmask) del bmask return mask
[docs]def archive_wcs_file(image, wcs_id=None): """ Update WCSCORR table with rows for each SCI extension to record the newly updated WCS keyword values. """ if not isinstance(image, fits.HDUList): fimg = fits.open(image, mode='update') close_image = True else: fimg = image close_image = False update_wcscorr(fimg, wcs_id=wcs_id) if close_image: fimg.close()
[docs]def update_wcscorr(dest, source=None, extname='SCI', wcs_id=None, active=True): """ Update WCSCORR table with a new row or rows for this extension header. It copies the current set of WCS keywords as a new row of the table based on keyed WCSs as per Paper I Multiple WCS standard). Parameters ---------- dest : HDUList The HDU list whose WCSCORR table should be appended to (the WCSCORR HDU must already exist) source : HDUList, optional The HDU list containing the extension from which to extract the WCS keywords to add to the WCSCORR table. If None, the dest is also used as the source. extname : str, optional The extension name from which to take new WCS keywords. If there are multiple extensions with that name, rows are added for each extension version. wcs_id : str, optional The name of the WCS to add, as in the WCSNAMEa keyword. If unspecified, all the WCSs in the specified extensions are added. active: bool, optional When True, indicates that the update should reflect an update of the active WCS information, not just appending the WCS to the file as a headerlet """ if not isinstance(dest, fits.HDUList): dest = fits.open(dest, mode='update') fname = dest.filename() if source is None: source = dest if extname == 'PRIMARY': return numext = fileutil.countExtn(source, extname) if numext == 0: raise ValueError('No %s extensions found in the source HDU list.' % extname) # Initialize the WCSCORR table extension in dest if not already present init_wcscorr(dest) try: dest.index_of('WCSCORR') except KeyError: return # check to see whether or not this is an up-to-date table # replace with newly initialized table with current format old_table = dest['WCSCORR'] wcscorr_cols = ['WCS_ID', 'EXTVER', 'SIPNAME', 'HDRNAME', 'NPOLNAME', 'D2IMNAME'] for colname in wcscorr_cols: if colname not in old_table.data.columns.names: print("WARNING: Replacing outdated WCSCORR table...") #outdated_table = old_table.copy() del dest['WCSCORR'] init_wcscorr(dest) old_table = dest['WCSCORR'] break # Current implementation assumes the same WCS keywords are in each # extension version; if this should not be assumed then this can be # modified... wcs_keys = altwcs.wcskeys(source[(extname, 1)].header) if 'O' in wcs_keys: wcs_keys.remove('O') # 'O' is reserved for original OPUS WCS if ' ' not in wcs_keys: wcs_keys.append(' ') # Insure that primary WCS gets used # apply logic for only updating WCSCORR table with specified keywords # corresponding to the WCS with WCSNAME=wcs_id if wcs_id is not None: wcs_id_up = wcs_id.upper() wnames = altwcs._alt_wcs_names(source[(extname, 1)].header) wkeys = [key for key, name in wnames.items() if name.upper() == wcs_id_up] if len(wkeys) > 1 and ' ' in wkeys: wkeys.remove(' ') wcs_keys = wkeys wcshdr = HSTWCS(source, ext=(extname, 1)).wcs2header() wcs_keywords = list(wcshdr.keys()) # create new table for hdr and populate it with the newly updated values new_table = create_wcscorr(descrip=True, numrows=0, padding=len(wcs_keys) * numext) prihdr = source[0].header # Get headerlet related keywords here sipname, idctab = utils.build_sipname(source, fname, "None") npolname, npolfile = utils.build_npolname(source, None) d2imname, d2imfile = utils.build_d2imname(source, None) hdrname = prihdr.get('hdrname', '') idx = -1 for wcs_key in wcs_keys: wcs_key_hdr = wcs_key.strip() for extver in range(1, numext + 1): extn = (extname, extver) if 'SIPWCS' in extname and not active: tab_extver = 0 # Since it has not been added to the SCI header yet else: tab_extver = extver hdr = source[extn].header wcsname_kwd = 'WCSNAME' + wcs_key_hdr if wcsname_kwd in hdr: wcsname = hdr[wcsname_kwd] else: wcsname = utils.build_default_wcsname(hdr['idctab']) selection = {'WCS_ID': wcsname, 'EXTVER': tab_extver, 'SIPNAME': sipname, 'HDRNAME': hdrname, 'NPOLNAME': npolname, 'D2IMNAME': d2imname } # Ensure that an entry for this WCS is not already in the dest # table; if so just skip it rowind = find_wcscorr_row(old_table.data, selection) if np.any(rowind): continue idx += 1 wcs = HSTWCS(source, ext=extn, wcskey=wcs_key) wcshdr = wcs.wcs2header() # Update selection column values for key, val in selection.items(): if key in new_table.data.names: new_table.data.field(key)[idx] = val for key in wcs_keywords: if key in new_table.data.names: new_table.data.field(key)[idx] = wcshdr[key + wcs_key_hdr] for key in DEFAULT_PRI_KEYS: if key in new_table.data.names and key in prihdr: new_table.data.field(key)[idx] = prihdr[key] # Now look for additional, non-WCS-keyword table column data for key, fitkw in COL_FITSKW_DICT.items(): # Interpret any 'pri.hdrname' or # 'sci.crpix1' formatted keyword names if '.' in fitkw: srchdr, fitkw = fitkw.split('.') if 'pri' in srchdr.lower(): srchdr = prihdr else: srchdr = source[extn].header else: srchdr = source[extn].header if fitkw + wcs_key_hdr in srchdr: new_table.data.field(key)[idx] = srchdr[fitkw + wcs_key_hdr] # If idx was never incremented, no rows were added, so there's nothing else # to do... if idx < 0: return # Now, we need to merge this into the existing table rowind = find_wcscorr_row(old_table.data, {'wcs_id': ['', '0.0']}) old_nrows = np.where(rowind)[0][0] new_nrows = new_table.data.shape[0] # check to see if there is room for the new row if (old_nrows + new_nrows) > old_table.data.shape[0] - 1: pad_rows = 2 * new_nrows # if not, create a new table with 'pad_rows' new empty rows upd_table = fits.BinTableHDU.from_columns(old_table.columns, header=old_table.header, nrows=old_table.data.shape[0] + pad_rows) else: upd_table = old_table pad_rows = 0 # Now, add for name in old_table.columns.names: if name in new_table.data.names: # reset the default values to ones specific to the row definitions for i in range(pad_rows): upd_table.data.field(name)[old_nrows + i] = old_table.data.field(name)[-1] # Now populate with values from new table upd_table.data.field(name)[old_nrows:old_nrows + new_nrows] = \ new_table.data.field(name) upd_table.header['TROWS'] = old_nrows + new_nrows # replace old extension with newly updated table extension dest['WCSCORR'] = upd_table
[docs]def restore_file_from_wcscorr(image, id='OPUS', wcskey=''): """ Copies the values of the WCS from the WCSCORR based on ID specified by user. The default will be to restore the original OPUS-derived values to the Primary WCS. If wcskey is specified, the WCS with that key will be updated instead. """ wcskey = wcskey.strip() if not isinstance(image, fits.HDUList): fimg = fits.open(image, mode='update') close_image = True else: fimg = image close_image = False numsci = fileutil.countExtn(fimg) wcs_table = fimg['WCSCORR'] orig_rows = (wcs_table.data.field('WCS_ID') == 'OPUS') # create an HSTWCS object to figure out what WCS keywords need to be updated wcsobj = HSTWCS(fimg, ext=('sci', 1)) wcshdr = wcsobj.wcs2header() for extn in range(1, numsci + 1): # find corresponding row from table ext_rows = (wcs_table.data.field('EXTVER') == extn) erow = np.where(np.logical_and(ext_rows, orig_rows))[0][0] for key in wcshdr: if key in wcs_table.data.names: # insure that keyword is column in table tkey = key if 'orient' in key.lower(): key = 'ORIENT' if wcskey == '': skey = key else: skey = key[:7] + wcskey fimg['sci', extn].header[skey] = wcs_table.data.field(tkey)[erow] for key in DEFAULT_PRI_KEYS: if key in wcs_table.data.names: if wcskey == '': pkey = key else: pkey = key[:7] + wcskey fimg[0].header[pkey] = wcs_table.data.field(key)[erow] utils.updateNEXTENDKw(fimg) # close the image now that the update has been completed. if close_image: fimg.close()
[docs]def create_wcscorr(descrip=False, numrows=1, padding=0): """ Return the basic definitions for a WCSCORR table. The dtype definitions for the string columns are set to the maximum allowed so that all new elements will have the same max size which will be automatically truncated to this limit upon updating (if needed). The table is initialized with rows corresponding to the OPUS solution for all the 'SCI' extensions. """ trows = numrows + padding # define initialized arrays as placeholders for column data # TODO: I'm certain there's an easier way to do this... for example, simply # define the column names and formats, then create an empty array using # them as a dtype, then create the new table from that array. def_float64_zeros = np.array([0.0] * trows, dtype=np.float64) def_float64_ones = def_float64_zeros + 1.0 def_float_col = {'format': 'D', 'array': def_float64_zeros.copy()} def_float1_col = {'format': 'D', 'array': def_float64_ones.copy()} def_str40_col = {'format': '40A', 'array': np.array([''] * trows, dtype='S40')} def_str24_col = {'format': '24A', 'array': np.array([''] * trows, dtype='S24')} def_int32_col = {'format': 'J', 'array': np.array([0] * trows, dtype=np.int32)} # If more columns are needed, simply add their definitions to this list col_names = [('HDRNAME', def_str24_col), ('SIPNAME', def_str24_col), ('NPOLNAME', def_str24_col), ('D2IMNAME', def_str24_col), ('CRVAL1', def_float_col), ('CRVAL2', def_float_col), ('CRPIX1', def_float_col), ('CRPIX2', def_float_col), ('CD1_1', def_float1_col), ('CD1_2', def_float_col), ('CD2_1', def_float_col), ('CD2_2', def_float1_col), ('CTYPE1', def_str24_col), ('CTYPE2', def_str24_col), ('ORIENTAT', def_float_col), ('PA_V3', def_float_col), ('RMS_RA', def_float_col), ('RMS_Dec', def_float_col), ('NMatch', def_int32_col), ('Catalog', def_str40_col)] # Define selector columns id_col = fits.Column(name='WCS_ID', format='40A', array=np.array(['OPUS'] * numrows + [''] * padding, dtype='S24')) extver_col = fits.Column(name='EXTVER', format='I', array=np.array(list(range(1, numrows + 1)), dtype=np.int16)) wcskey_col = fits.Column(name='WCS_key', format='A', array=np.array(['O'] * numrows + [''] * padding, dtype='S')) # create list of remaining columns to be added to table col_list = [id_col, extver_col, wcskey_col] # start with selector columns for c in col_names: cdef = copy.deepcopy(c[1]) col_list.append(fits.Column(name=c[0], format=cdef['format'], array=cdef['array'])) if descrip: col_list.append( fits.Column(name='DESCRIP', format='128A', array=np.array( ['Original WCS computed by OPUS'] * numrows, dtype='S128'))) # Now create the new table from the column definitions newtab = fits.BinTableHDU.from_columns(fits.ColDefs(col_list), nrows=trows) # The fact that setting .name is necessary should be considered a bug in # pyfits. # TODO: Make sure this is fixed in pyfits, then remove this newtab.name = 'WCSCORR' return newtab
[docs]def delete_wcscorr_row(wcstab, selections=None, rows=None): """ Sets all values in a specified row or set of rows to default values This function will essentially erase the specified row from the table without actually removing the row from the table. This avoids the problems with trying to resize the number of rows in the table while preserving the ability to update the table with new rows again without resizing the table. Parameters ---------- wcstab: object PyFITS binTable object for WCSCORR table selections: dict Dictionary of wcscorr column names and values to be used to select the row or set of rows to erase rows: int, list If specified, will specify what rows from the table to erase regardless of the value of 'selections' """ if selections is None and rows is None: print('ERROR: Some row selection information must be provided!') print(' Either a row numbers or "selections" must be provided.') raise ValueError delete_rows = None if rows is None: if 'wcs_id' in selections and selections['wcs_id'] == 'OPUS': delete_rows = None print('WARNING: OPUS WCS information can not be deleted from WCSCORR table.') print(' This row will not be deleted!') else: rowind = find_wcscorr_row(wcstab, selections=selections) delete_rows = np.where(rowind)[0].tolist() else: if not isinstance(rows, list): rows = [rows] delete_rows = rows # Insure that rows pointing to OPUS WCS do not get deleted, even by accident for row in delete_rows: if wcstab['WCS_key'][row] == 'O' or wcstab['WCS_ID'][row] == 'OPUS': del delete_rows[delete_rows.index(row)] if delete_rows is None: return # identify next empty row rowind = find_wcscorr_row(wcstab, selections={'wcs_id': ['', '0.0']}) last_blank_row = np.where(rowind)[0][-1] # copy values from blank row into user-specified rows for colname in wcstab.names: wcstab[colname][delete_rows] = wcstab[colname][last_blank_row]
[docs]def update_wcscorr_column(wcstab, column, values, selections=None, rows=None): """ Update the values in 'column' with 'values' for selected rows Parameters ---------- wcstab: object PyFITS binTable object for WCSCORR table column: string Name of table column with values that need to be updated values: string, int, or list Value or set of values to copy into the selected rows for the column selections: dict Dictionary of wcscorr column names and values to be used to select the row or set of rows to erase rows: int, list If specified, will specify what rows from the table to erase regardless of the value of 'selections' """ if selections is None and rows is None: print('ERROR: Some row selection information must be provided!') print(' Either a row numbers or "selections" must be provided.') raise ValueError if not isinstance(values, list): values = [values] update_rows = None if rows is None: if 'wcs_id' in selections and selections['wcs_id'] == 'OPUS': update_rows = None print('WARNING: OPUS WCS information can not be deleted from WCSCORR table.') print(' This row will not be deleted!') else: rowind = find_wcscorr_row(wcstab, selections=selections) update_rows = np.where(rowind)[0].tolist() else: if not isinstance(rows, list): rows = [rows] update_rows = rows if update_rows is None: return # Expand single input value to apply to all selected rows if len(values) > 1 and len(values) < len(update_rows): print('ERROR: Number of new values', len(values)) print(' does not match number of rows', len(update_rows), ' to be updated!') print(' Please enter either 1 value or the same number of values') print(' as there are rows to be updated.') print(' Table will not be updated...') raise ValueError if len(values) == 1 and len(values) < len(update_rows): values = values * len(update_rows) # copy values from blank row into user-specified rows for row in update_rows: wcstab[column][row] = values[row]