Improve type matching to make tests pass

Author: svank

reproject/adaptive/core.py

@@ -117,10 +117,15 @@ def _reproject_adaptive_2d(
     "broadcast" across those images.
     """
 
-    # Make sure image is floating point, but preserve the floating-point precision if it's floating point already
+    # Make sure the input is floating point, and that it matches the output array type if specified. (Cython makes 32
+    # and 64-bit versions of the inner function, but it's either everything is 32-bit, or everything is 64-bit). In
+    # case of a disagreement between the input and output types, it's best to apply the output's type to the
+    # input---the input is more likely to have weirdness (e.g. the wrong endianness, which Cython can't handle), and
+    # the output type is either a safe default, if the user didn't provide an output array, or it has a user-specified
+    # type.
     array_in = np.asarray(array)
-    if not np.issubdtype(array.dtype, np.floating):
-        array_in = np.asarray(array, dtype=float)
+    if array_out is not None and array_in.dtype != array_out.dtype:
+        array_in = np.asarray(array, dtype=array_out.dtype)
     shape_out = tuple(shape_out)
 
     # Check dimensionality of WCS and shape_out
@@ -141,7 +146,9 @@ def _reproject_adaptive_2d(
         raise ValueError("Dimensions to be looped over must match exactly")
 
     if array_out is None:
-        array_out = np.empty(shape_out)
+        # n.b. in the normal calling sequence, array_out is always generated by `_reproject_dispatcher` and passed into
+        # this function.
+        array_out = np.empty(shape_out, dtype=array_in.dtype)
 
     if output_footprint is None:
         output_footprint = np.empty(shape_out)