diff --git a/docs/source/python.rst b/docs/source/python.rst
index 28b5519e8..0806ff10d 100644
--- a/docs/source/python.rst
+++ b/docs/source/python.rst
@@ -112,4 +112,8 @@ can be a numpy array or a pointer to memory large enough to hold the
 decompressed data.  Regardless if ``out`` is provided or its type,
 ``_decompress`` always returns a numpy array.  If ``out`` is not provided, the
 array is allocated for the user, and if ``out`` is provided, then the returned
-numpy is just a pointer to or wrapper around the user-supplied ``out``.
+numpy is just a pointer to or wrapper around the user-supplied ``out``.  If
+``out`` is a numpy array, then the shape and type of the numpy array must match
+the required arguments ``shape`` and ``ztype``.  If you want to avoid this
+constraint check, use ``out=ndarray.data`` rather than ``out=ndarray`` when
+calling ``_decompress``.
diff --git a/python/zfp.pyx b/python/zfp.pyx
index e673f6ec5..d0e4f3305 100644
--- a/python/zfp.pyx
+++ b/python/zfp.pyx
@@ -286,15 +286,38 @@ cpdef np.ndarray _decompress(
         if out is None:
             output = np.asarray(_decompress_with_view(field, stream))
         else:
+            dtype = zfp.ztype_to_dtype(ztype)
             if isinstance(out, np.ndarray):
                 output = out
-            else:
-                header_dtype = ztype_to_dtype(field[0]._type)
-                header_shape = (field[0].nw, field[0].nz, field[0].ny, field[0].nx)
-                header_shape = [x for x in header_shape if x > 0]
 
-                output = np.frombuffer(out, dtype=header_dtype)
-                output = output.reshape(header_shape)
+                # check that numpy and user-provided types match
+                if out.dtype != dtype:
+                    raise ValueError(
+                        "Out ndarray has dtype {} but decompression is using "
+                        "{}. Use out=ndarray.data to avoid this check.".format(
+                            out.dtype,
+                            dtype
+                        )
+                    )
+
+                # check that numpy and user-provided shape match
+                numpy_shape = out.shape
+                user_shape = [x for x in shape if x > 0]
+                if not all(
+                        [x == y for x, y in
+                         zip_longest(numpy_shape, user_shape)
+                        ]
+                ):
+                    raise ValueError(
+                        "Out ndarray has shape {} but decompression is using "
+                        "{}.  Use out=ndarray.data to avoid this check.".format(
+                            numpy_shape,
+                            user_shape
+                        )
+                    )
+            else:
+                output = np.frombuffer(out, dtype=dtype)
+                output = output.reshape(shape)
 
             _decompress_with_user_array(field, stream, <void *>output.data)