Update to be a complete identity operation - preserving the original dtype, not converting real to complex

Author: antonwolfy

mkl_fft/_fft_utils.py

@@ -415,13 +415,13 @@ def _c2c_fftnd_impl(
     else:
         x = np.asarray(x)
 
-        # Fast path: FFT over no axes is identity (just type conversion, no scaling)
+        # Fast path: FFT over no axes is complete identity (preserve dtype)
         _, xa = _cook_nd_args(x, s, axes)
         if len(xa) == 0:
             if out is None:
-                out = x.astype(dtype=_output_dtype(x.dtype), copy=True)
+                out = x.copy()
             else:
-                _validate_out_array(out, x, _output_dtype(x.dtype))
+                _validate_out_array(out, x, x.dtype)
                 np.copyto(out, x)
             # No scaling applied - identity transform has no normalization
             return out

mkl_fft/tests/test_fftnd.py

@@ -353,8 +353,8 @@ def test_empty_axes_with_out(dtype, func):
     else:
         x = rnd.random((3, 4)).astype(dtype)
 
-    out_dtype = np.dtype(dtype).char.upper()
-    out = np.empty_like(x, dtype=out_dtype)
+    # For axes=(), output dtype should match input dtype (identity transform)
+    out = np.empty_like(x, dtype=dtype)
     result = getattr(mkl_fft, func)(x, axes=(), out=out)
     expected = getattr(np.fft, func)(x, axes=())