1 files changed, 26 insertions, 16 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index fb37801b9..d9a539f18 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -4284,8 +4284,17 @@ def percentile(a, q, axis=None, out=None,
     >>> assert not np.all(a == b)
 
     """
-    q = array(q, dtype=np.float64, copy=True)
-    r, k = _ureduce(a, func=_percentile, q=q, axis=axis, out=out,
+    q = np.true_divide(q, 100.0)  # handles the asarray for us too
+    if not _quantile_is_valid(q):
+        raise ValueError("Percentiles must be in the range [0, 100]")
+    return _quantile_unchecked(
+        a, q, axis, out, overwrite_input, interpolation, keepdims)
+
+
+def _quantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
+                        interpolation='linear', keepdims=False):
+    """Assumes that q is in [0, 1], and is an ndarray"""
+    r, k = _ureduce(a, func=_quantile_ureduce_func, q=q, axis=axis, out=out,
                     overwrite_input=overwrite_input,
                     interpolation=interpolation)
     if keepdims:
@@ -4294,8 +4303,21 @@ def percentile(a, q, axis=None, out=None,
         return r
 
 
-def _percentile(a, q, axis=None, out=None,
-                overwrite_input=False, interpolation='linear', keepdims=False):
+def _quantile_is_valid(q):
+    # avoid expensive reductions, relevant for arrays with < O(1000) elements
+    if q.ndim == 1 and q.size < 10:
+        for i in range(q.size):
+            if q[i] < 0.0 or q[i] > 1.0:
+                return False
+    else:
+        # faster than any()
+        if np.count_nonzero(q < 0.0) or np.count_nonzero(q > 1.0):
+            return False
+    return True
+
+
+def _quantile_ureduce_func(a, q, axis=None, out=None, overwrite_input=False,
+                           interpolation='linear', keepdims=False):
     a = asarray(a)
     if q.ndim == 0:
         # Do not allow 0-d arrays because following code fails for scalar
@@ -4304,18 +4326,6 @@ def _percentile(a, q, axis=None, out=None,
     else:
         zerod = False
 
-    # avoid expensive reductions, relevant for arrays with < O(1000) elements
-    if q.size < 10:
-        for i in range(q.size):
-            if q[i] < 0. or q[i] > 100.:
-                raise ValueError("Percentiles must be in the range [0,100]")
-            q[i] /= 100.
-    else:
-        # faster than any()
-        if np.count_nonzero(q < 0.) or np.count_nonzero(q > 100.):
-            raise ValueError("Percentiles must be in the range [0,100]")
-        q /= 100.
-
     # prepare a for partioning
     if overwrite_input:
         if axis is None: