Merge pull request #2787 from bfroehle/unique_argsortmaintenance/1.6.x

np.unique: TypeError: requested sort not available for type

2 files changed, 15 insertions, 15 deletions

diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index 7952cbb37..efc055b84 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -1611,19 +1611,22 @@ class TestRegression(TestCase):
         a[...] = [[1,2]]
         assert_equal(a, [[1,2], [1,2]])
 
-    def test_unique_stable(self):
-        # Ticket #2063 must always choose stable sort for argsort to
-        # get consistent results
-        v=np.array([0,0,0,0,0,1,1,1,1,1,1,2,2,2,2,2,2]*4)
-        w=np.array([0,0,0,0,0,1,1,1,1,1,1,2,2,2,2])
-        resv = np.unique(v,return_index=True)
-        resw = np.unique(w,return_index=True)
-        assert_equal(resv, resw)
-
     def test_search_sorted_invalid_arguments(self):
         # Ticket #2021, should not segfault.
         x = np.arange(0, 4, dtype='datetime64[D]')
         assert_raises(TypeError, x.searchsorted, 1)
 
+    def test_unique_special_comparators(self):
+        # gh-2785
+        # np.unique should not raise an exception for dtypes with
+        # special comparators.
+
+        # Extract the unique rows of the matrix
+        A = np.array([[1, 2], [1, 3], [1, 2]], dtype='i')
+        B, I, J = np.unique(A.view([('', A.dtype)]*A.shape[1]), True, True)
+        B = B.view(A.dtype).reshape((-1, A.shape[1]))
+        assert_equal(A, B[J])
+        assert_equal(A[I], B)
+
 if __name__ == "__main__":
     run_module_suite()
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index 47e94bc4d..721039238 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -112,8 +112,8 @@ def unique(ar, return_index=False, return_inverse=False):
     unique : ndarray
         The sorted unique values.
     unique_indices : ndarray, optional
-        The indices of the first occurrences of the unique values in the
-        (flattened) original array. Only provided if `return_index` is True.
+        The indices of the unique values in the (flattened) original array.
+        Only provided if `return_index` is True.
     unique_inverse : ndarray, optional
         The indices to reconstruct the (flattened) original array from the
         unique array. Only provided if `return_inverse` is True.
@@ -174,10 +174,7 @@ def unique(ar, return_index=False, return_inverse=False):
             return ar
 
     if return_inverse or return_index:
-        if return_index:
-            perm = ar.argsort(kind='mergesort')
-        else:
-            perm = ar.argsort()
+        perm = ar.argsort()
         aux = ar[perm]
         flag = np.concatenate(([True], aux[1:] != aux[:-1]))
         if return_inverse: