Fix factorizing some more.

flox/core.py

@@ -421,6 +421,7 @@ def factorize_(
     factorized = []
     found_groups = []
     for groupvar, expect in zip(by, expected_groups):
+        flat = groupvar.ravel()
         if isinstance(expect, pd.IntervalIndex):
             # when binning we change expected groups to integers marking the interval
             # this makes the reindexing logic simpler.
@@ -432,21 +433,19 @@ def factorize_(
             if groupvar.dtype.kind == "M":
                 expect = np.concatenate([expect.left.to_numpy(), [expect.right[-1].to_numpy()]])
             # code is -1 for values outside the bounds of all intervals
-            idx = pd.cut(groupvar.ravel(), bins=expect).codes.copy()
+            idx = pd.cut(flat, bins=expect).codes.copy()
         else:
             if expect is not None and reindex:
-                groups = expect
+                sorter = np.argsort(expect)
+                groups = expect[(sorter,)] if sort else expect
+                idx = np.searchsorted(expect, flat, sorter=sorter)
+                mask = ~np.isin(flat, expect) | isnull(flat) | (idx == len(expect))
                 if not sort:
-                    sorter = np.argsort(expect)
-                else:
-                    sorter = None
-                idx = np.searchsorted(expect, groupvar.ravel(), sorter=sorter)
-                mask = isnull(groupvar.ravel()) | (idx == len(expect))
-                # TODO: optimize?
+                    # idx is the index in to the sorted array.
+                    # if we didn't want sorting, unsort it back
+                    idx[(idx == len(expect),)] = -1
+                    idx = sorter[(idx,)]
                 idx[mask] = -1
-                if not sort:
-                    idx = sorter[idx]
-                    idx[mask] = -1
             else:
                 idx, groups = pd.factorize(groupvar.ravel(), sort=sort)
 

tests/test_core.py

@@ -905,3 +905,62 @@ def test_factorize_values_outside_bins():
     actual = vals[0]
     expected = np.array([[-1, -1], [-1, 0], [6, 12], [18, 24], [-1, -1]])
     assert_equal(expected, actual)
+
+
+def test_multiple_groupers():
+    actual, *_ = groupby_reduce(
+        np.ones((5, 2)),
+        np.arange(10).reshape(5, 2),
+        np.arange(10).reshape(5, 2),
+        axis=(0, 1),
+        expected_groups=(
+            pd.IntervalIndex.from_breaks(np.arange(2, 8, 1)),
+            pd.IntervalIndex.from_breaks(np.arange(2, 8, 1)),
+        ),
+        reindex=True,
+        func="count",
+    )
+    expected = np.eye(5, 5)
+    assert_equal(expected, actual)
+
+
+def test_factorize_reindex_sorting_strings():
+    kwargs = dict(
+        by=(np.array(["El-Nino", "La-Nina", "boo", "Neutral"]),),
+        axis=-1,
+        expected_groups=(np.array(["El-Nino", "Neutral", "foo", "La-Nina"]),),
+    )
+
+    expected = factorize_(**kwargs, reindex=True, sort=True)[0]
+    assert_equal(expected, [0, 1, 4, 2])
+
+    expected = factorize_(**kwargs, reindex=True, sort=False)[0]
+    assert_equal(expected, [0, 3, 4, 1])
+
+    expected = factorize_(**kwargs, reindex=False, sort=False)[0]
+    assert_equal(expected, [0, 1, 2, 3])
+
+    expected = factorize_(**kwargs, reindex=False, sort=True)[0]
+    assert_equal(expected, [0, 1, 3, 2])
+
+
+def test_factorize_reindex_sorting_ints():
+    kwargs = dict(
+        by=(np.array([-10, 1, 10, 2, 3, 5]),),
+        axis=-1,
+        expected_groups=(np.array([0, 1, 2, 3, 4, 5]),),
+    )
+
+    expected = factorize_(**kwargs, reindex=True, sort=True)[0]
+    assert_equal(expected, [6, 1, 6, 2, 3, 5])
+
+    expected = factorize_(**kwargs, reindex=True, sort=False)[0]
+    assert_equal(expected, [6, 1, 6, 2, 3, 5])
+
+    kwargs["expected_groups"] = (np.arange(5, -1, -1),)
+
+    expected = factorize_(**kwargs, reindex=True, sort=True)[0]
+    assert_equal(expected, [6, 1, 6, 2, 3, 5])
+
+    expected = factorize_(**kwargs, reindex=True, sort=False)[0]
+    assert_equal(expected, [6, 4, 6, 3, 2, 0])