C++ refactoring: ak.argsort

src/awkward/_v2/contents/listoffsetarray.py

@@ -1084,7 +1084,7 @@ def _argsort_next(
                         self_stops.data,
                         stable,
                         ascending,
-                        False,
+                        True,
                     )
                 )
                 return ak._v2.contents.NumpyArray(nextcarry, None, None, self._nplike)

src/awkward/_v2/operations/structure/ak_argsort.py

@@ -7,46 +7,44 @@
 
 # @ak._v2._connect.numpy.implements("argsort")
 def argsort(array, axis=-1, ascending=True, stable=True, highlevel=True, behavior=None):
-    raise NotImplementedError
-
-
-#     """
-#     Args:
-#         array: Data for which to get a sorting index, possibly within nested
-#             lists.
-#         axis (int): The dimension at which this operation is applied. The
-#             outermost dimension is `0`, followed by `1`, etc., and negative
-#             values count backward from the innermost: `-1` is the innermost
-#             dimension, `-2` is the next level up, etc.
-#         ascending (bool): If True, the first value in each sorted group
-#             will be smallest, the last value largest; if False, the order
-#             is from largest to smallest.
-#         stable (bool): If True, use a stable sorting algorithm (introsort:
-#             a hybrid of quicksort, heapsort, and insertion sort); if False,
-#             use a sorting algorithm that is not guaranteed to be stable
-#             (heapsort).
-#         highlevel (bool): If True, return an #ak.Array; otherwise, return
-#             a low-level #ak.layout.Content subclass.
-#         behavior (None or dict): Custom #ak.behavior for the output array, if
-#             high-level.
-
-#     For example,
-
-#         >>> ak.argsort(ak.Array([[7.7, 5.5, 7.7], [], [2.2], [8.8, 2.2]]))
-#         <Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>
-
-#     The result of this function can be used to index other arrays with the
-#     same shape:
-
-#         >>> data = ak.Array([[7, 5, 7], [], [2], [8, 2]])
-#         >>> index = ak.argsort(index)
-#         >>> index
-#         <Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>
-#         >>> data[index]
-#         <Array [[5, 7, 7], [], [2], [2, 8]] type='4 * var * int64'>
-#     """
-#     layout = ak._v2.operations.convert.to_layout(
-#         array, allow_record=False, allow_other=False
-#     )
-#     out = layout.argsort(axis, ascending, stable)
-#     return ak._v2._util.maybe_wrap_like(out, array, behavior, highlevel)
+
+    """
+    Args:
+        array: Data for which to get a sorting index, possibly within nested
+            lists.
+        axis (int): The dimension at which this operation is applied. The
+            outermost dimension is `0`, followed by `1`, etc., and negative
+            values count backward from the innermost: `-1` is the innermost
+            dimension, `-2` is the next level up, etc.
+        ascending (bool): If True, the first value in each sorted group
+            will be smallest, the last value largest; if False, the order
+            is from largest to smallest.
+        stable (bool): If True, use a stable sorting algorithm (introsort:
+            a hybrid of quicksort, heapsort, and insertion sort); if False,
+            use a sorting algorithm that is not guaranteed to be stable
+            (heapsort).
+        highlevel (bool): If True, return an #ak.Array; otherwise, return
+            a low-level #ak.layout.Content subclass.
+        behavior (None or dict): Custom #ak.behavior for the output array, if
+            high-level.
+
+    For example,
+
+        >>> ak.argsort(ak.Array([[7.7, 5.5, 7.7], [], [2.2], [8.8, 2.2]]))
+        <Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>
+
+    The result of this function can be used to index other arrays with the
+    same shape:
+
+        >>> data = ak.Array([[7, 5, 7], [], [2], [8, 2]])
+        >>> index = ak.argsort(index)
+        >>> index
+        <Array [[1, 0, 2], [], [0], [1, 0]] type='4 * var * int64'>
+        >>> data[index]
+        <Array [[5, 7, 7], [], [2], [2, 8]] type='4 * var * int64'>
+    """
+    layout = ak._v2.operations.convert.to_layout(
+        array, allow_record=False, allow_other=False
+    )
+    out = layout.argsort(axis, ascending, stable)
+    return ak._v2._util.wrap(out, behavior, highlevel)