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ENH: show warning when np.maximum receives more than 2 inputs
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3 files changed

+41
-11
lines changed

3 files changed

+41
-11
lines changed

‎numpy/_core/src/umath/ufunc_object.c

Lines changed: 19 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -4289,6 +4289,14 @@ ufunc_generic_fastcall(PyUFuncObject *ufunc,
42894289
{
42904290
int errval;
42914291
int nin = ufunc->nin, nout = ufunc->nout, nop = ufunc->nargs;
4292+
if (strcmp(ufunc->name, "maximum") == 0 &&
4293+
len_args > 2 &&
4294+
(kwnames == NULL || PyTuple_Size(kwnames) == 0)) {
4295+
PyErr_Format(PyExc_TypeError,
4296+
"np.maximum() takes exactly 2 input arguments (%zd given). ",
4297+
len_args);
4298+
return NULL;
4299+
}
42924300

42934301
/* All following variables are cleared in the `fail` error path */
42944302
ufunc_full_args full_args = {NULL, NULL};
@@ -4598,6 +4606,17 @@ static PyObject *
45984606
ufunc_generic_vectorcall(PyObject *ufunc,
45994607
PyObject *const *args, size_t len_args, PyObject *kwnames)
46004608
{
4609+
// Only do this for the maximum ufunc
4610+
if (strcmp(((PyUFuncObject *)ufunc)->name, "maximum") == 0 &&
4611+
len_args < 128 &&
4612+
len_args > 2 &&
4613+
(kwnames == NULL || PyTuple_Size(kwnames)==0)) {
4614+
4615+
PyErr_Format(PyExc_TypeError,
4616+
"np.maximum() takes exactly 2 input arguments (%zd given). ",
4617+
len_args);
4618+
return NULL;
4619+
}
46014620
/*
46024621
* Unlike METH_FASTCALL, `len_args` may have a flag to signal that
46034622
* args[-1] may be (temporarily) used. So normalize it here.

‎numpy/_core/tests/test_umath.py

Lines changed: 17 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -2383,7 +2383,7 @@ def test_float_nans(self):
23832383
arg1 = np.array([0, nan, nan])
23842384
arg2 = np.array([nan, 0, nan])
23852385
out = np.array([nan, nan, nan])
2386-
assert_equal(np.maximum(arg1, arg2), out)
2386+
assert_equal(np.maximum(arg1, arg2, out=out), out)
23872387

23882388
def test_object_nans(self):
23892389
# Multiple checks to give this a chance to
@@ -2393,21 +2393,24 @@ def test_object_nans(self):
23932393
x = np.array(float('nan'), object)
23942394
y = 1.0
23952395
z = np.array(float('nan'), object)
2396-
assert_(np.maximum(x, y) == 1.0)
2397-
assert_(np.maximum(z, y) == 1.0)
2396+
out1 = np.empty((), dtype=object)
2397+
out2 = np.empty((), dtype=object)
2398+
assert_(np.maximum(x, y, out=out1) == 1.0)
2399+
assert_(np.maximum(z, y, out=out2) == 1.0)
23982400

23992401
def test_complex_nans(self):
24002402
nan = np.nan
24012403
for cnan in [complex(nan, 0), complex(0, nan), complex(nan, nan)]:
24022404
arg1 = np.array([0, cnan, cnan], dtype=complex)
24032405
arg2 = np.array([cnan, 0, cnan], dtype=complex)
24042406
out = np.array([nan, nan, nan], dtype=complex)
2405-
assert_equal(np.maximum(arg1, arg2), out)
2407+
assert_equal(np.maximum(arg1, arg2, out=out), out)
24062408

24072409
def test_object_array(self):
24082410
arg1 = np.arange(5, dtype=object)
24092411
arg2 = arg1 + 1
2410-
assert_equal(np.maximum(arg1, arg2), arg2)
2412+
out = np.empty_like(arg1)
2413+
assert_equal(np.maximum(arg1, arg2, out=out), arg2)
24112414

24122415
def test_strided_array(self):
24132416
arr1 = np.array([-4.0, 1.0, 10.0, 0.0, np.nan, -np.nan, np.inf, -np.inf])
@@ -2419,7 +2422,12 @@ def test_strided_array(self):
24192422
assert_equal(np.maximum(arr1[::2], arr2[::2]), maxtrue[::2])
24202423
assert_equal(np.maximum(arr1[:4:], arr2[::2]), np.array([-2.0, np.nan, 10.0, 1.0]))
24212424
assert_equal(np.maximum(arr1[::3], arr2[:3:]), np.array([-2.0, 0.0, np.nan]))
2422-
assert_equal(np.maximum(arr1[:6:2], arr2[::3], out=out[::3]), np.array([-2.0, 10., np.nan]))
2425+
2426+
result = np.empty_like(arr1[:6:2])
2427+
np.maximum(arr1[:6:2], arr2[::3], out=result)
2428+
assert_equal(result, np.array([-2.0, 10., np.nan]))
2429+
2430+
np.maximum( arr1[:6:2], arr2[::3], out=out[::3])
24232431
assert_equal(out, out_maxtrue)
24242432

24252433
def test_precision(self):
@@ -2443,6 +2451,9 @@ def test_precision(self):
24432451
assert_equal(np.maximum([v1], [v2]), [expected])
24442452
assert_equal(np.maximum.reduce([v1, v2]), expected)
24452453

2454+
def test_maximum_too_many_args(self):
2455+
with pytest.raises(TypeError, match=r"np\.maximum\(\) takes exactly 2 input arguments \(3 given\)"):
2456+
np.maximum(1, 2, 3)
24462457

24472458
class TestMinimum(_FilterInvalids):
24482459
def test_reduce(self):

‎numpy/_typing/_ufunc.pyi

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -176,8 +176,8 @@ class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: i
176176
x1: _ScalarLike_co,
177177
x2: _ScalarLike_co,
178178
/,
179-
out: None = None,
180179
*,
180+
out: None = None,
181181
dtype: DTypeLike | None = None,
182182
**kwds: Unpack[_UFunc3Kwargs],
183183
) -> Any: ...
@@ -187,8 +187,8 @@ class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: i
187187
x1: ArrayLike,
188188
x2: NDArray[np.generic],
189189
/,
190-
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
191190
*,
191+
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
192192
dtype: DTypeLike | None = None,
193193
**kwds: Unpack[_UFunc3Kwargs],
194194
) -> NDArray[Any]: ...
@@ -198,8 +198,8 @@ class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: i
198198
x1: NDArray[np.generic],
199199
x2: ArrayLike,
200200
/,
201-
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
202201
*,
202+
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
203203
dtype: DTypeLike | None = None,
204204
**kwds: Unpack[_UFunc3Kwargs],
205205
) -> NDArray[Any]: ...
@@ -209,8 +209,8 @@ class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: i
209209
x1: ArrayLike,
210210
x2: ArrayLike,
211211
/,
212-
out: NDArray[np.generic] | tuple[NDArray[np.generic]],
213212
*,
213+
out: NDArray[np.generic] | tuple[NDArray[np.generic]],
214214
dtype: DTypeLike | None = None,
215215
**kwds: Unpack[_UFunc3Kwargs],
216216
) -> NDArray[Any]: ...
@@ -220,8 +220,8 @@ class _UFunc_Nin2_Nout1(ufunc, Generic[_NameType, _NTypes, _IDType]): # type: i
220220
x1: ArrayLike,
221221
x2: ArrayLike,
222222
/,
223-
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
224223
*,
224+
out: NDArray[np.generic] | tuple[NDArray[np.generic]] | None = None,
225225
dtype: DTypeLike | None = None,
226226
**kwds: Unpack[_UFunc3Kwargs],
227227
) -> NDArray[Any] | Any: ...

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