Remove unnecessary casts (#9825)

Co-authored-by: Tyler Pauly <[email protected]>

Author: braingram

changes/9825.group_scale.rst

@@ -0,0 +1 @@
+Remove cast (which consumed 3x the data array size) to improve memory usage.

changes/9825.linearity.rst

@@ -0,0 +1 @@
+Remove cast (which consumed 3x the data array size) to reduce memory usage.

changes/9825.superbias.rst

@@ -0,0 +1 @@
+Remove cast (which used 3x the data array size) to reduce memory usage.

jwst/group_scale/group_scale.py

@@ -40,8 +40,6 @@ def do_correction(model):
 
     # Apply the rescaling to the entire data array
     scale = float(frame_divisor) / nframes
-    if not isinstance(type(model.data), float):
-        model.data = (model.data).astype(float)
     model.data *= scale
     model.meta.cal_step.group_scale = "COMPLETE"
 

jwst/linearity/linearity.py

@@ -38,7 +38,7 @@ def do_correction(output_model, lin_model):
     gdq = output_model.groupdq
     # If the input data does not have an expanded DQ array, create one
     if len(output_model.groupdq) == 0:
-        gdq = (output_model.data * 0).astype(np.uint32)
+        gdq = np.zeros(output_model.data.shape, dtype=np.uint32)
 
     # Obtain linearity coefficients and dq array from reference file
     if reffile_utils.ref_matches_sci(output_model, lin_model):

jwst/superbias/bias_sub.py

@@ -63,12 +63,10 @@ def subtract_bias(output, bias):
         Bias-subtracted science data
     """
     # combine the science and superbias DQ arrays
-    output.pixeldq = np.bitwise_or(output.pixeldq, bias.dq)
+    output.pixeldq |= bias.dq
 
     # Subtract the superbias image from all groups and integrations
     # of the science data
-    if not isinstance(type(output.data), float):
-        output.data = (output.data).astype(float)
     output.data -= bias.data
 
     # If ZEROFRAME is present, subtract the super bias.  Zero values