BUG: Fix __array__(None) to preserve dtype (numpy#28806)

This PR fixes a bug in the __array__ method where calling __array__(None) would return an array with the default dtype float64, regardless of the original array's dtype.

Author: MatthewGoldsberry

numpy/_core/src/multiarray/methods.c

@@ -928,7 +928,7 @@ array_getarray(PyArrayObject *self, PyObject *args, PyObject *kwds)
     PyObject *ret;
 
     if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&$O&:__array__", kwlist,
-                                     PyArray_DescrConverter, &newtype,
+                                     PyArray_DescrConverter2, &newtype,
                                      PyArray_CopyConverter, &copy)) {
         Py_XDECREF(newtype);
         return NULL;

numpy/_core/tests/test_multiarray.py

@@ -10459,3 +10459,13 @@ def __init__(self, interface):
     # Now, using np.asanyarray on this dummy should trigger a ValueError (not segfault)
     with pytest.raises(ValueError, match="dimensions must be within"):
         np.asanyarray(dummy)
+
+@pytest.mark.parametrize("dtype", [np.float32, np.float64, np.uint32, np.complex128])
+def test_array_dunder_array_preserves_dtype_on_none(dtype):
+    """
+    Regression test for: https://github.com/numpy/numpy/issues/27407
+    Ensure that __array__(None) returns an array of the same dtype.
+    """
+    a = np.array([1], dtype=dtype)
+    b = a.__array__(None)
+    assert_array_equal(a, b, strict=True)