Merge pull request #17921 from bashtage/uniform-high-low-check

BUG: Enforce high >= low on uniform number generators

3 files changed, 29 insertions, 11 deletions

diff --git a/doc/release/upcoming_changes/17921.compatibility.rst b/doc/release/upcoming_changes/17921.compatibility.rst
new file mode 100644
index 000000000..a1e2fb2d0
--- /dev/null
+++ b/doc/release/upcoming_changes/17921.compatibility.rst
@@ -0,0 +1,6 @@
+Validate input values in ``Generator.uniform``
+----------------------------------------------
+Checked that ``high - low >= 0`` in ``np.random.Generator.uniform``. Raises
+``ValueError`` if ``low > high``. Previously out-of-order inputs were accepted
+and silently swapped, so that if ``low > high``, the value generated was
+``high + (low - high) * random()``.
diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx
index 7ffa36775..e00bc4d98 100644
--- a/numpy/random/_generator.pyx
+++ b/numpy/random/_generator.pyx
@@ -859,7 +859,8 @@ cdef class Generator:
             greater than or equal to low.  The default value is 0.
         high : float or array_like of floats
             Upper boundary of the output interval.  All values generated will be
-            less than high.  The default value is 1.0.
+            less than high.  high - low must be non-negative.  The default value
+            is 1.0.
         size : int or tuple of ints, optional
             Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
             ``m * n * k`` samples are drawn.  If size is ``None`` (default),
@@ -885,10 +886,6 @@ cdef class Generator:
         anywhere within the interval ``[a, b)``, and zero elsewhere.
 
         When ``high`` == ``low``, values of ``low`` will be returned.
-        If ``high`` < ``low``, the results are officially undefined
-        and may eventually raise an error, i.e. do not rely on this
-        function to behave when passed arguments satisfying that
-        inequality condition.
 
         Examples
         --------
@@ -914,7 +911,7 @@ cdef class Generator:
         """
         cdef bint is_scalar = True
         cdef np.ndarray alow, ahigh, arange
-        cdef double _low, _high, range
+        cdef double _low, _high, rng
         cdef object temp
 
         alow = <np.ndarray>np.PyArray_FROM_OTF(low, np.NPY_DOUBLE, np.NPY_ALIGNED)
@@ -923,13 +920,13 @@ cdef class Generator:
         if np.PyArray_NDIM(alow) == np.PyArray_NDIM(ahigh) == 0:
             _low = PyFloat_AsDouble(low)
             _high = PyFloat_AsDouble(high)
-            range = _high - _low
-            if not np.isfinite(range):
-                raise OverflowError('Range exceeds valid bounds')
+            rng = _high - _low
+            if not np.isfinite(rng):
+                raise OverflowError('high - low range exceeds valid bounds')
 
             return cont(&random_uniform, &self._bitgen, size, self.lock, 2,
                         _low, '', CONS_NONE,
-                        range, '', CONS_NONE,
+                        rng, 'high - low', CONS_NON_NEGATIVE,
                         0.0, '', CONS_NONE,
                         None)
 
@@ -943,7 +940,7 @@ cdef class Generator:
             raise OverflowError('Range exceeds valid bounds')
         return cont(&random_uniform, &self._bitgen, size, self.lock, 2,
                     alow, '', CONS_NONE,
-                    arange, '', CONS_NONE,
+                    arange, 'high - low', CONS_NON_NEGATIVE,
                     0.0, '', CONS_NONE,
                     None)
 
diff --git a/numpy/random/tests/test_generator_mt19937.py b/numpy/random/tests/test_generator_mt19937.py
index b69cd38d4..c4fb5883c 100644
--- a/numpy/random/tests/test_generator_mt19937.py
+++ b/numpy/random/tests/test_generator_mt19937.py
@@ -1666,6 +1666,21 @@ class TestRandomDist:
         # DBL_MAX by increasing fmin a bit
         random.uniform(low=np.nextafter(fmin, 1), high=fmax / 1e17)
 
+    def test_uniform_zero_range(self):
+        func = random.uniform
+        result = func(1.5, 1.5)
+        assert_allclose(result, 1.5)
+        result = func([0.0, np.pi], [0.0, np.pi])
+        assert_allclose(result, [0.0, np.pi])
+        result = func([[2145.12], [2145.12]], [2145.12, 2145.12])
+        assert_allclose(result, 2145.12 + np.zeros((2, 2)))
+
+    def test_uniform_neg_range(self):
+        func = random.uniform
+        assert_raises(ValueError, func, 2, 1)
+        assert_raises(ValueError, func,  [1, 2], [1, 1])
+        assert_raises(ValueError, func,  [[0, 1],[2, 3]], 2)
+
     def test_scalar_exception_propagation(self):
         # Tests that exceptions are correctly propagated in distributions
         # when called with objects that throw exceptions when converted to