Further refinements to the WCSCORR code in STWCS to reduce the number of new rows that gets added each time, and to maintain the same header information from one update to the next.

git-svn-id: http://svn.stsci.edu/svn/ssb/stsci_python/stsci_python/trunk/stwcs@12715 fe389314-cf27-0410-b35b-8c050e845b92

1 files changed, 10 insertions, 6 deletions

diff --git a/wcsutil/wcscorr.py b/wcsutil/wcscorr.py
index 054626b..c344851 100644
--- a/wcsutil/wcscorr.py
+++ b/wcsutil/wcscorr.py
@@ -263,7 +263,7 @@ def update_wcscorr(dest, source=None, extname='SCI', wcs_id=None):
         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=numext, padding=numext)
+    new_table = create_wcscorr(numrows=0, padding=len(wcs_keys)*numext)
     old_table = dest['WCSCORR']
 
     idx = -1
@@ -308,18 +308,22 @@ def update_wcscorr(dest, source=None, extname='SCI', wcs_id=None):
     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]:
-        pad_rows = 5 * new_nrows
+        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,
-                                     nrows=old_table.data.shape[0] + pad_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)