Merge pull request #30713 from charris/backport-30710

charris · web-flow · commit 18bdb2e675b6 · 2026-01-22T16:16:22.000-07:00
BUG: Fixup the quantile promotion fixup
diff --git a/numpy/lib/_function_base_impl.py b/numpy/lib/_function_base_impl.py
@@ -4576,7 +4576,7 @@ def _get_gamma(virtual_indexes, previous_indexes, method):
     gamma = method["fix_gamma"](gamma, virtual_indexes)
     # Ensure both that we have an array, and that we keep the dtype
     # (which may have been matched to the input array).
-    return np.asanyarray(gamma)
+    return np.asanyarray(gamma, dtype=virtual_indexes.dtype)
 
 
 def _lerp(a, b, t, out=None):
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
@@ -3941,6 +3941,9 @@ def test_q_strong_promotion(self, method):
         a = np.array([1, 2, 3, 4, 5], dtype=np.float32)
         value = np.percentile(a, np.float64(50), method=method)
         assert value.dtype == np.float64
+        # Check that we don't do accidental promotion either:
+        value = np.percentile(a, np.float32(50), method=method)
+        assert value.dtype == np.float32
 
 
 class TestQuantile:
@@ -4379,6 +4382,9 @@ def test_q_strong_promotion(self, method):
         a = np.array([1, 2, 3, 4, 5], dtype=np.float32)
         value = np.quantile(a, np.float64(0.5), method=method)
         assert value.dtype == np.float64
+        # Check that we don't do accidental promotion either:
+        value = np.quantile(a, np.float32(0.5), method=method)
+        assert value.dtype == np.float32
 
 
 class TestLerp:
