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Diffstat (limited to 'wcsutil/wcscorr.py')
| -rw-r--r-- | wcsutil/wcscorr.py | 458 |
1 files changed, 0 insertions, 458 deletions
diff --git a/wcsutil/wcscorr.py b/wcsutil/wcscorr.py deleted file mode 100644 index bab0964..0000000 --- a/wcsutil/wcscorr.py +++ /dev/null @@ -1,458 +0,0 @@ -import os,copy -import pyfits -import numpy as np - -from pytools import fileutil -import stwcs -from stwcs.wcsutil import altwcs -import convertwcs - - -DEFAULT_WCS_KEYS = ['CRVAL1','CRVAL2','CRPIX1','CRPIX2', - 'CD1_1','CD1_2','CD2_1','CD2_2', - 'CTYPE1','CTYPE2'] -DEFAULT_PRI_KEYS = ['PA_V3'] -### -### WCSEXT table related keyword archive functions -### -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, pyfits.HDUList): - # input must be a filename, so open as PyFITS object - fimg = pyfits.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 - if len(fimg) == 1: - return - - # Verify that a WCSCORR extension does not already exist... - for extn in fimg: - if extn.header.has_key('extname') and \ - extn.header['extname'] == 'WCSCORR': - if not force: - return - else: - del fimg['WCSCORR'] - # define the primary columns of the WCSEXT table with initial rows for each - # SCI extension for the original OPUS solution - numsci = fileutil.countExtn(fimg) - - # create new table with more rows than needed initially to make it easier to - # add new rows later - wcsext = create_wcscorr(numrows=numsci, padding=numsci * 4) - # Assign the correct EXTNAME value to this table extension - wcsext.header.update('TROWS', numsci * 2, - comment='Number of updated rows in table') - wcsext.header.update('EXTNAME', 'WCSCORR', - comment='Table with WCS Update history') - wcsext.header.update('EXTVER', 1) - - used_wcskeys = None - wcs1 = stwcs.wcsutil.HSTWCS(fimg,ext=('SCI',1)) - idc2header = True - if wcs1.idcscale is None: - idc2header = False - wcs_keywords = wcs1.wcs2header(idc2hdr=idc2header).keys() - - # Now copy original OPUS values into table - for extver in xrange(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.archiveWCS(fimg,('SCI',extver),wcskey='O', wcsname='OPUS') - wkey = 'O' - - wcs = stwcs.wcsutil.HSTWCS(fimg, ext=('SCI', extver), wcskey=wkey) - wcshdr = wcs.wcs2header(idc2hdr=idc2header) - - for key in DEFAULT_PRI_KEYS: - prihdr_keys = [] - if not hdr.has_key(key): - prihdr_keys.append(key) - - 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 key in wcs_keywords: - if key in wcsext.data.names: - wcsext.data.field(key)[rownum] = wcshdr[(key+wkey)[:8]] - # Now get any keywords from PRIMARY header needed for WCS updates - for key in prihdr_keys: - wcsext.data.field(key)[rownum] = fimg[0].header[key] - - # 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: - if wkey == ' ': - break - for extver in xrange(1, numsci + 1): - hdr = fimg['SCI', extver].header - wcs = stwcs.wcsutil.HSTWCS(fimg, ext=('SCI', extver), - wcskey=uwkey) - wcshdr = wcs.wcs2header() - if 'WCSNAME' + uwkey not in wcshdr: - idctab = fileutil.osfn(fimg[0].header['idctab']) - idcname = os.path.split(idctab)[-1] - idcname = idcname[:idcname.find('_')] - wcsid = 'IDC_' + idcname - else: - wcsid = wcshdr['WCSNAME' + uwkey] - - # identify next empty row - rowind = find_wcscorr_row(wcsext.data, selections={'wcs_id': ''}) - rows = np.where(rowind) - if len(rows[0]) > 0: - rownum = np.where(rowind)[0][0] - else: - print 'No available rows found for updating. ' - #print 'Archiving current WCS row number ',rownum,' in WCSCORR table for SCI,',extver - - # 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: - wcsext.data.field(key)[rownum] = fimg[0].header[key] - - # 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 - fimg.flush('warn') - - if need_to_close: - fimg.close() - - -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() - bmask = (icol == selections[i]) - if mask is None: - mask = bmask.copy() - else: - mask = np.logical_and(mask,bmask) - del bmask - return mask - - -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, pyfits.HDUList): - fimg = pyfits.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() - - -def update_wcscorr(dest, source=None, extname='SCI', wcs_id=None): - """ - 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. - """ - - if source is None: - source = dest - - numext = fileutil.countExtn(source, extname) - if numext == 0: - raise ValueError('No %s extensions found in the source HDU list.' - % extname) - - # 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) - wcs_keys = filter(None, wcs_keys) - wcshdr = stwcs.wcsutil.HSTWCS(source, ext=(extname, 1)).wcs2header() - wcs_keywords = wcshdr.keys() - - if 'O' in wcs_keys: - wcs_keys.remove('O') # 'O' is reserved for original OPUS WCS - - # If we're looking for a particular wcs_id, test ahead of time that it's - # actually present in the specified extension headers - if wcs_id: - wcs_key = '' - for wcs_key in wcs_keys: - wcsname = source[(extname, 1)].header['WCSNAME' + wcs_key] - if wcs_id == wcsname: - break - else: - raise ValueError('A WCS with name %s was not found in the %s ' - 'extension headers in the source HDU list.' - % (wcs_id, extname)) - wcs_keys = [wcs_key] # We're only interested in this one - - # create new table for hdr and populate it with the newly updated values - new_table = create_wcscorr(numrows=0, padding=len(wcs_keys)*numext) - old_table = dest['WCSCORR'] - - idx = -1 - for wcs_key in wcs_keys: - for extver in range(1, numext + 1): - extn = (extname, extver) - hdr = source[extn].header - wcsname = hdr['WCSNAME' + wcs_key] - selection = {'WCS_ID': wcsname, 'EXTVER': extver, - 'WCS_key': wcs_key} - - # 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 = stwcs.wcsutil.HSTWCS(source, ext=extn, wcskey=wcs_key) - wcshdr = wcs.wcs2header() - - # Update selection column values - for key, val in selection.iteritems(): - 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] - - prihdr = source[0].header - for key in DEFAULT_PRI_KEYS: - if key in new_table.data.names and prihdr.has_key(key): - new_table.data.field(key)[idx] = prihdr[key] - - # 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':''}) - 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 = pyfits.new_table(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: - # 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.update('TROWS', old_nrows + new_nrows) - - # replace old extension with newly updated table extension - dest['WCSCORR'] = upd_table - - -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. - """ - - if not isinstance(image, pyfits.HDUList): - fimg = pyfits.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 = stwcs.wcsutil.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.update(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.update(pkey,wcs_table.data.field(key)[erow]) - - # close the image now that the update has been completed. - if close_image: - fimg.close() - - -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 = [('CRVAL1', def_float_col), ('CRVAL2', def_float_col), - ('CRPIX1', def_float_col), ('CRPIX2', def_float_col), - ('CD1_1', def_float_col), ('CD1_2', def_float_col), - ('CD2_1', def_float_col), ('CD2_2', def_float_col), - ('CTYPE1', def_str24_col), ('CTYPE2', def_str24_col), - ('ORIENTAT', def_float_col), ('PA_V3', def_float_col), - ('Delta_RA', def_float_col), ('Delta_Dec', def_float_col), - ('RMS_RA', def_float_col), ('RMS_Dec', def_float_col), - ('Delta_Orientat', def_float_col), - ('Delta_Scale', def_float1_col), - ('NMatch', def_int32_col), ('Catalog', def_str40_col)] - - # Define selector columns - id_col = pyfits.Column(name='WCS_ID', format='40A', - array=np.array(['OPUS'] * numrows + [''] * padding, - dtype='S24')) - extver_col = pyfits.Column(name='EXTVER', format='I', - array=np.array(range(1, numrows + 1), - dtype=np.int16)) - wcskey_col = pyfits.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(pyfits.Column(name=c[0], format=cdef['format'], - array=cdef['array'])) - - if descrip: - col_list.append( - pyfits.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 = pyfits.new_table(pyfits.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 - |