Switch resample to the new drizzle package API

jwst/resample/gwcs_drizzle.py

@@ -1,7 +1,6 @@
 import numpy as np
 
-from drizzle import util
-from drizzle import cdrizzle
+from drizzle import cdrizzle, utils
 from . import resample_utils
 
 import logging
@@ -338,7 +337,7 @@ def dodrizzle(insci, input_wcs, inwht, output_wcs, outsci, outwht, outcon,
     """
 
     # Insure that the fillval parameter gets properly interpreted for use with tdriz
-    if util.is_blank(str(fillval)):
+    if str(fillval).strip() == '':
         fillval = 'NAN'
     else:
         fillval = str(fillval)
@@ -381,9 +380,13 @@ def dodrizzle(insci, input_wcs, inwht, output_wcs, outsci, outwht, outcon,
 
     # Compute the mapping between the input and output pixel coordinates
     # for use in drizzle.cdrizzle.tdriz
+
+    # pixmap = utils.calc_pixmap(input_wcs, output_wcs)
     pixmap = resample_utils.calc_gwcs_pixmap(input_wcs, output_wcs, insci.shape)
+
     # inwht[np.isnan(pixmap[:,:,0])] = 0.
 
+    print(f"Pixmap shape: {pixmap.shape}")
     log.debug(f"Pixmap shape: {pixmap[:,:,0].shape}")
     log.debug(f"Input Sci shape: {insci.shape}")
     log.debug(f"Output Sci shape: {outsci.shape}")

jwst/resample/resample.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 import psutil
-from drizzle import cdrizzle, util
+from drizzle import cdrizzle
 from spherical_geometry.polygon import SphericalPolygon
 
 from stdatamodels.jwst import datamodels
@@ -251,10 +251,10 @@ def _get_intensity_scale(self, img):
         else:
             iscale = 1.0
         return iscale
-    
+
     def resample_group(self, input_models, indices):
         """Apply resample_many_to_many for one group
-        
+
         Parameters
         ----------
         input_models : ModelLibrary
@@ -290,7 +290,7 @@ def resample_group(self, input_models, indices):
                 if isinstance(img, datamodels.SlitModel):
                     # must call this explicitly to populate area extension
                     # although the existence of this extension may not be necessary
-                    img.area = img.area 
+                    img.area = img.area
                 iscale = self._get_intensity_scale(img)
                 log.debug(f'Using intensity scale iscale={iscale}')
 
@@ -339,7 +339,7 @@ def resample_many_to_many(self, input_models):
         """
         output_models = []
         for group_id, indices in input_models.group_indices.items():
-            
+
             output_model = self.resample_group(input_models, indices)
 
             if not self.in_memory:
@@ -522,7 +522,7 @@ def resample_variance_arrays(self, output_model, input_models):
                         axis=0
                     )
                     total_weight_flat_var[mask] += weight[mask]
-                
+
                 del model.meta.iscale
                 del weight
                 input_models.shelve(model, i)
@@ -753,7 +753,7 @@ def drizzle_arrays(insci, inwht, input_wcs, output_wcs, outsci, outwht,
         """
 
         # Insure that the fillval parameter gets properly interpreted for use with tdriz
-        if util.is_blank(str(fillval)):
+        if str(fillval).strip() == '':
             fillval = 'NAN'
         else:
             fillval = str(fillval)

jwst/resample/resample_utils.py

@@ -5,6 +5,7 @@
 import numpy as np
 from astropy import units as u
 import gwcs
+from drizzle.utils import calc_pixmap
 
 from stdatamodels.dqflags import interpret_bit_flags
 from stdatamodels.jwst.datamodels.dqflags import pixel
@@ -124,17 +125,11 @@ def shape_from_bounding_box(bounding_box):
 def calc_gwcs_pixmap(in_wcs, out_wcs, shape=None):
     """ Return a pixel grid map from input frame to output frame.
     """
-    if shape:
-        bb = wcs_bbox_from_shape(shape)
-        log.debug("Bounding box from data shape: {}".format(bb))
-    else:
-        bb = in_wcs.bounding_box
-        log.debug("Bounding box from WCS: {}".format(in_wcs.bounding_box))
-
-    grid = gwcs.wcstools.grid_from_bounding_box(bb)
-    pixmap = np.dstack(reproject(in_wcs, out_wcs)(grid[0], grid[1]))
+    if shape and not np.array_equiv(shape, in_wcs.array_shape):
+        in_wcs = deepcopy(in_wcs)
+        in_wcs.array_shape = shape
 
-    return pixmap
+    return calc_pixmap(wcs_from=in_wcs, wcs_to=out_wcs)
 
 
 def reproject(wcs1, wcs2):

pyproject.toml

@@ -22,7 +22,7 @@ dependencies = [
     "astropy>=5.3",
     "BayesicFitting>=3.0.1",
     "crds>=11.17.14",
-    "drizzle>=1.15.0",
+    "drizzle @ git+https://github.com/mcara/drizzle.git@redesign-api",
     "gwcs>=0.21.0,<0.23.0",
     "numpy>=1.22,<2.0",
     "opencv-python-headless>=4.6.0.66",