Merge pull request #23314 from rgommers/depr-product-and-co

DEP: deprecate `product`, `cumproduct`, `sometrue`, `alltrue`

18 files changed, 100 insertions, 54 deletions

diff --git a/doc/release/upcoming_changes/23314.deprecation.rst b/doc/release/upcoming_changes/23314.deprecation.rst
new file mode 100644
index 000000000..8bed1aef8
--- /dev/null
+++ b/doc/release/upcoming_changes/23314.deprecation.rst
@@ -0,0 +1,4 @@
+* ``np.product`` is deprecated. Use `np.prod` instead.
+* ``np.cumproduct`` is deprecated. Use `np.cumprod` instead.
+* ``np.sometrue`` is deprecated. Use `np.any` instead.
+* ``np.alltrue`` is deprecated. Use `np.all` instead.
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index ed8b68ecd..7ea2313d1 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -3821,6 +3821,7 @@ def round_(a, decimals=0, out=None):
     --------
     around : equivalent function; see for details.
     """
+    # 2023-02-28, 1.25.0
     warnings.warn("`round_` is deprecated as of NumPy 1.25.0, and will be "
                   "removed in NumPy 2.0. Please use `round` instead.",
                   DeprecationWarning, stacklevel=2)
@@ -3832,10 +3833,18 @@ def product(*args, **kwargs):
     """
     Return the product of array elements over a given axis.
 
+    .. deprecated:: 1.25.0
+        ``product`` is deprecated as of NumPy 1.25.0, and will be
+        removed in NumPy 2.0. Please use `prod` instead.
+
     See Also
     --------
     prod : equivalent function; see for details.
     """
+    # 2023-03-02, 1.25.0
+    warnings.warn("`product` is deprecated as of NumPy 1.25.0, and will be "
+                  "removed in NumPy 2.0. Please use `prod` instead.",
+                  DeprecationWarning, stacklevel=2)
     return prod(*args, **kwargs)
 
 
@@ -3844,10 +3853,18 @@ def cumproduct(*args, **kwargs):
     """
     Return the cumulative product over the given axis.
 
+    .. deprecated:: 1.25.0
+        ``cumproduct`` is deprecated as of NumPy 1.25.0, and will be
+        removed in NumPy 2.0. Please use `cumprod` instead.
+
     See Also
     --------
     cumprod : equivalent function; see for details.
     """
+    # 2023-03-02, 1.25.0
+    warnings.warn("`cumproduct` is deprecated as of NumPy 1.25.0, and will be "
+                  "removed in NumPy 2.0. Please use `cumprod` instead.",
+                  DeprecationWarning, stacklevel=2)
     return cumprod(*args, **kwargs)
 
 
@@ -3858,10 +3875,18 @@ def sometrue(*args, **kwargs):
 
     Refer to `any` for full documentation.
 
+    .. deprecated:: 1.25.0
+        ``sometrue`` is deprecated as of NumPy 1.25.0, and will be
+        removed in NumPy 2.0. Please use `any` instead.
+
     See Also
     --------
     any : equivalent function; see for details.
     """
+    # 2023-03-02, 1.25.0
+    warnings.warn("`sometrue` is deprecated as of NumPy 1.25.0, and will be "
+                  "removed in NumPy 2.0. Please use `any` instead.",
+                  DeprecationWarning, stacklevel=2)
     return any(*args, **kwargs)
 
 
@@ -3870,8 +3895,16 @@ def alltrue(*args, **kwargs):
     """
     Check if all elements of input array are true.
 
+    .. deprecated:: 1.25.0
+        ``alltrue`` is deprecated as of NumPy 1.25.0, and will be
+        removed in NumPy 2.0. Please use `all` instead.
+
     See Also
     --------
     numpy.all : Equivalent function; see for details.
     """
+    # 2023-03-02, 1.25.0
+    warnings.warn("`alltrue` is deprecated as of NumPy 1.25.0, and will be "
+                  "removed in NumPy 2.0. Please use `all` instead.",
+                  DeprecationWarning, stacklevel=2)
     return all(*args, **kwargs)
diff --git a/numpy/core/tests/test_deprecations.py b/numpy/core/tests/test_deprecations.py
index 8ff52c885..96ae4b2a8 100644
--- a/numpy/core/tests/test_deprecations.py
+++ b/numpy/core/tests/test_deprecations.py
@@ -902,8 +902,23 @@ class TestDeprecatedFinfo(_DeprecationTestCase):
     def test_deprecated_none(self):
         self.assert_deprecated(np.finfo, args=(None,))
 
-
-class TestRound_(_DeprecationTestCase):
+class TestFromnumeric(_DeprecationTestCase):
     # 2023-02-28, 1.25.0
     def test_round_(self):
         self.assert_deprecated(lambda: np.round_(np.array([1.5, 2.5, 3.5])))
+
+    # 2023-03-02, 1.25.0
+    def test_cumproduct(self):
+        self.assert_deprecated(lambda: np.cumproduct(np.array([1, 2, 3])))
+
+    # 2023-03-02, 1.25.0
+    def test_product(self):
+        self.assert_deprecated(lambda: np.product(np.array([1, 2, 3])))
+
+    # 2023-03-02, 1.25.0
+    def test_sometrue(self):
+        self.assert_deprecated(lambda: np.sometrue(np.array([True, False])))
+
+    # 2023-03-02, 1.25.0
+    def test_alltrue(self):
+        self.assert_deprecated(lambda: np.alltrue(np.array([True, False])))
diff --git a/numpy/core/tests/test_indexing.py b/numpy/core/tests/test_indexing.py
index 74075639c..042936702 100644
--- a/numpy/core/tests/test_indexing.py
+++ b/numpy/core/tests/test_indexing.py
@@ -1062,7 +1062,7 @@ class TestMultiIndexingAutomated:
                         if np.any(_indx >= _size) or np.any(_indx < -_size):
                                 raise IndexError
                 if len(indx[1:]) == len(orig_slice):
-                    if np.product(orig_slice) == 0:
+                    if np.prod(orig_slice) == 0:
                         # Work around for a crash or IndexError with 'wrap'
                         # in some 0-sized cases.
                         try:
diff --git a/numpy/core/tests/test_mem_overlap.py b/numpy/core/tests/test_mem_overlap.py
index d66decfda..1fd4c4d41 100644
--- a/numpy/core/tests/test_mem_overlap.py
+++ b/numpy/core/tests/test_mem_overlap.py
@@ -55,7 +55,7 @@ def _indices(ndims):
 def _check_assignment(srcidx, dstidx):
     """Check assignment arr[dstidx] = arr[srcidx] works."""
 
-    arr = np.arange(np.product(shape)).reshape(shape)
+    arr = np.arange(np.prod(shape)).reshape(shape)
 
     cpy = arr.copy()
 
diff --git a/numpy/core/tests/test_memmap.py b/numpy/core/tests/test_memmap.py
index 914f86f14..ad074b312 100644
--- a/numpy/core/tests/test_memmap.py
+++ b/numpy/core/tests/test_memmap.py
@@ -6,7 +6,7 @@ from pathlib import Path
 from tempfile import NamedTemporaryFile, TemporaryFile
 
 from numpy import (
-    memmap, sum, average, product, ndarray, isscalar, add, subtract, multiply)
+    memmap, sum, average, prod, ndarray, isscalar, add, subtract, multiply)
 
 from numpy import arange, allclose, asarray
 from numpy.testing import (
@@ -153,7 +153,7 @@ class TestMemmap:
 
         with suppress_warnings() as sup:
             sup.filter(FutureWarning, "np.average currently does not preserve")
-            for unary_op in [sum, average, product]:
+            for unary_op in [sum, average, prod]:
                 result = unary_op(fp)
                 assert_(isscalar(result))
                 assert_(result.__class__ is self.data[0, 0].__class__)
diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py
index 3cc168b34..f81f563cd 100644
--- a/numpy/core/tests/test_numeric.py
+++ b/numpy/core/tests/test_numeric.py
@@ -114,7 +114,9 @@ class TestNonarrayArgs:
 
     def test_cumproduct(self):
         A = [[1, 2, 3], [4, 5, 6]]
-        assert_(np.all(np.cumproduct(A) == np.array([1, 2, 6, 24, 120, 720])))
+        with assert_warns(DeprecationWarning):
+            expected = np.array([1, 2, 6, 24, 120, 720])
+            assert_(np.all(np.cumproduct(A) == expected))
 
     def test_diagonal(self):
         a = [[0, 1, 2, 3],
@@ -1193,8 +1195,8 @@ class TestFromiter:
         expected = np.array(list(self.makegen()))
         a = np.fromiter(self.makegen(), int)
         a20 = np.fromiter(self.makegen(), int, 20)
-        assert_(np.alltrue(a == expected, axis=0))
-        assert_(np.alltrue(a20 == expected[:20], axis=0))
+        assert_(np.all(a == expected, axis=0))
+        assert_(np.all(a20 == expected[:20], axis=0))
 
     def load_data(self, n, eindex):
         # Utility method for the issue 2592 tests.
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index 413ece045..fdd536bb9 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -516,22 +516,15 @@ class TestRegression:
     def test_method_args(self):
         # Make sure methods and functions have same default axis
         # keyword and arguments
-        funcs1 = ['argmax', 'argmin', 'sum', ('product', 'prod'),
-                 ('sometrue', 'any'),
-                 ('alltrue', 'all'), 'cumsum', ('cumproduct', 'cumprod'),
-                 'ptp', 'cumprod', 'prod', 'std', 'var', 'mean',
-                 'round', 'min', 'max', 'argsort', 'sort']
+        funcs1 = ['argmax', 'argmin', 'sum', 'any', 'all', 'cumsum',
+                  'ptp', 'cumprod', 'prod', 'std', 'var', 'mean',
+                  'round', 'min', 'max', 'argsort', 'sort']
         funcs2 = ['compress', 'take', 'repeat']
 
         for func in funcs1:
             arr = np.random.rand(8, 7)
             arr2 = arr.copy()
-            if isinstance(func, tuple):
-                func_meth = func[1]
-                func = func[0]
-            else:
-                func_meth = func
-            res1 = getattr(arr, func_meth)()
+            res1 = getattr(arr, func)()
             res2 = getattr(np, func)(arr2)
             if res1 is None:
                 res1 = arr
@@ -1336,8 +1329,8 @@ class TestRegression:
         # Ticket #1058
         a = np.fromiter(list(range(10)), dtype='b')
         b = np.fromiter(list(range(10)), dtype='B')
-        assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
-        assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
+        assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
+        assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
 
     def test_array_from_sequence_scalar_array(self):
         # Ticket #1078: segfaults when creating an array with a sequence of
@@ -1515,8 +1508,8 @@ class TestRegression:
     def test_fromiter_comparison(self):
         a = np.fromiter(list(range(10)), dtype='b')
         b = np.fromiter(list(range(10)), dtype='B')
-        assert_(np.alltrue(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
-        assert_(np.alltrue(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
+        assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
+        assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])))
 
     def test_fromstring_crash(self):
         # Ticket #1345: the following should not cause a crash
diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index fa3a90e4f..abf9e1090 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -3,11 +3,10 @@ import sys
 import math
 import warnings
 
+import numpy as np
 from .._utils import set_module
 import numpy.core.numeric as _nx
-from numpy.core.numeric import (
-    asarray, ScalarType, array, alltrue, cumprod, arange, ndim
-)
+from numpy.core.numeric import ScalarType, array
 from numpy.core.numerictypes import find_common_type, issubdtype
 
 import numpy.matrixlib as matrixlib
@@ -94,7 +93,7 @@ def ix_(*args):
     nd = len(args)
     for k, new in enumerate(args):
         if not isinstance(new, _nx.ndarray):
-            new = asarray(new)
+            new = np.asarray(new)
             if new.size == 0:
                 # Explicitly type empty arrays to avoid float default
                 new = new.astype(_nx.intp)
@@ -396,7 +395,7 @@ class AxisConcatenator:
                 scalar = True
                 scalartypes.append(newobj.dtype)
             else:
-                item_ndim = ndim(item)
+                item_ndim = np.ndim(item)
                 newobj = array(item, copy=False, subok=True, ndmin=ndmin)
                 if trans1d != -1 and item_ndim < ndmin:
                     k2 = ndmin - item_ndim
@@ -596,7 +595,7 @@ class ndenumerate:
     """
 
     def __init__(self, arr):
-        self.iter = asarray(arr).flat
+        self.iter = np.asarray(arr).flat
 
     def __next__(self):
         """
@@ -909,9 +908,9 @@ def fill_diagonal(a, val, wrap=False):
     else:
         # For more than d=2, the strided formula is only valid for arrays with
         # all dimensions equal, so we check first.
-        if not alltrue(diff(a.shape) == 0):
+        if not np.all(diff(a.shape) == 0):
             raise ValueError("All dimensions of input must be of equal length")
-        step = 1 + (cumprod(a.shape[:-1])).sum()
+        step = 1 + (np.cumprod(a.shape[:-1])).sum()
 
     # Write the value out into the diagonal.
     a.flat[:end:step] = val
@@ -982,7 +981,7 @@ def diag_indices(n, ndim=2):
             [0, 1]]])
 
     """
-    idx = arange(n)
+    idx = np.arange(n)
     return (idx,) * ndim
 
 
@@ -1041,7 +1040,7 @@ def diag_indices_from(arr):
         raise ValueError("input array must be at least 2-d")
     # For more than d=2, the strided formula is only valid for arrays with
     # all dimensions equal, so we check first.
-    if not alltrue(diff(arr.shape) == 0):
+    if not np.all(diff(arr.shape) == 0):
         raise ValueError("All dimensions of input must be of equal length")
 
     return diag_indices(arr.shape[0], arr.ndim)
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index cc8003f61..3ec46735c 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -229,8 +229,8 @@ class TestAny:
     def test_nd(self):
         y1 = [[0, 0, 0], [0, 1, 0], [1, 1, 0]]
         assert_(np.any(y1))
-        assert_array_equal(np.sometrue(y1, axis=0), [1, 1, 0])
-        assert_array_equal(np.sometrue(y1, axis=1), [0, 1, 1])
+        assert_array_equal(np.any(y1, axis=0), [1, 1, 0])
+        assert_array_equal(np.any(y1, axis=1), [0, 1, 1])
 
 
 class TestAll:
@@ -247,8 +247,8 @@ class TestAll:
     def test_nd(self):
         y1 = [[0, 0, 1], [0, 1, 1], [1, 1, 1]]
         assert_(not np.all(y1))
-        assert_array_equal(np.alltrue(y1, axis=0), [0, 0, 1])
-        assert_array_equal(np.alltrue(y1, axis=1), [0, 0, 1])
+        assert_array_equal(np.all(y1, axis=0), [0, 0, 1])
+        assert_array_equal(np.all(y1, axis=1), [0, 0, 1])
 
 
 class TestCopy:
diff --git a/numpy/lib/tests/test_type_check.py b/numpy/lib/tests/test_type_check.py
index 3f4ca6309..ea0326139 100644
--- a/numpy/lib/tests/test_type_check.py
+++ b/numpy/lib/tests/test_type_check.py
@@ -155,7 +155,7 @@ class TestIscomplex:
     def test_fail(self):
         z = np.array([-1, 0, 1])
         res = iscomplex(z)
-        assert_(not np.sometrue(res, axis=0))
+        assert_(not np.any(res, axis=0))
 
     def test_pass(self):
         z = np.array([-1j, 1, 0])
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py
index 255de94e5..78927d1ae 100644
--- a/numpy/linalg/linalg.py
+++ b/numpy/linalg/linalg.py
@@ -23,7 +23,7 @@ from numpy.core import (
     array, asarray, zeros, empty, empty_like, intc, single, double,
     csingle, cdouble, inexact, complexfloating, newaxis, all, Inf, dot,
     add, multiply, sqrt, sum, isfinite,
-    finfo, errstate, geterrobj, moveaxis, amin, amax, product, abs,
+    finfo, errstate, geterrobj, moveaxis, amin, amax, prod, abs,
     atleast_2d, intp, asanyarray, object_, matmul,
     swapaxes, divide, count_nonzero, isnan, sign, argsort, sort,
     reciprocal
@@ -196,7 +196,7 @@ def _assert_finite(*arrays):
 
 def _is_empty_2d(arr):
     # check size first for efficiency
-    return arr.size == 0 and product(arr.shape[-2:]) == 0
+    return arr.size == 0 and prod(arr.shape[-2:]) == 0
 
 
 def transpose(a):
diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py
index 41bce0f22..4abe2107a 100644
--- a/numpy/ma/extras.py
+++ b/numpy/ma/extras.py
@@ -398,7 +398,7 @@ def apply_along_axis(func1d, axis, arr, *args, **kwargs):
         dtypes.append(np.asarray(res).dtype)
         outarr = zeros(outshape, object)
         outarr[tuple(ind)] = res
-        Ntot = np.product(outshape)
+        Ntot = np.prod(outshape)
         k = 1
         while k < Ntot:
             # increment the index
@@ -418,7 +418,7 @@ def apply_along_axis(func1d, axis, arr, *args, **kwargs):
         j = i.copy()
         j[axis] = ([slice(None, None)] * res.ndim)
         j.put(indlist, ind)
-        Ntot = np.product(outshape)
+        Ntot = np.prod(outshape)
         holdshape = outshape
         outshape = list(arr.shape)
         outshape[axis] = res.shape
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index 172a1ee8d..5db01b74a 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -1336,16 +1336,16 @@ class TestMaskedArrayArithmetic:
         assert_equal(np.sum(x, axis=0), sum(x, axis=0))
         assert_equal(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0))
         assert_equal(np.sum(x, 0), sum(x, 0))
-        assert_equal(np.product(x, axis=0), product(x, axis=0))
-        assert_equal(np.product(x, 0), product(x, 0))
-        assert_equal(np.product(filled(xm, 1), axis=0), product(xm, axis=0))
+        assert_equal(np.prod(x, axis=0), product(x, axis=0))
+        assert_equal(np.prod(x, 0), product(x, 0))
+        assert_equal(np.prod(filled(xm, 1), axis=0), product(xm, axis=0))
         s = (3, 4)
         x.shape = y.shape = xm.shape = ym.shape = s
         if len(s) > 1:
             assert_equal(np.concatenate((x, y), 1), concatenate((xm, ym), 1))
             assert_equal(np.add.reduce(x, 1), add.reduce(x, 1))
             assert_equal(np.sum(x, 1), sum(x, 1))
-            assert_equal(np.product(x, 1), product(x, 1))
+            assert_equal(np.prod(x, 1), product(x, 1))
 
     def test_binops_d2D(self):
         # Test binary operations on 2D data
diff --git a/numpy/ma/tests/test_old_ma.py b/numpy/ma/tests/test_old_ma.py
index 8465b1153..7b892ad23 100644
--- a/numpy/ma/tests/test_old_ma.py
+++ b/numpy/ma/tests/test_old_ma.py
@@ -194,16 +194,16 @@ class TestMa:
         assert_(eq(np.sum(x, axis=0), sum(x, axis=0)))
         assert_(eq(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0)))
         assert_(eq(np.sum(x, 0), sum(x, 0)))
-        assert_(eq(np.product(x, axis=0), product(x, axis=0)))
-        assert_(eq(np.product(x, 0), product(x, 0)))
-        assert_(eq(np.product(filled(xm, 1), axis=0),
+        assert_(eq(np.prod(x, axis=0), product(x, axis=0)))
+        assert_(eq(np.prod(x, 0), product(x, 0)))
+        assert_(eq(np.prod(filled(xm, 1), axis=0),
                            product(xm, axis=0)))
         if len(s) > 1:
             assert_(eq(np.concatenate((x, y), 1),
                                concatenate((xm, ym), 1)))
             assert_(eq(np.add.reduce(x, 1), add.reduce(x, 1)))
             assert_(eq(np.sum(x, 1), sum(x, 1)))
-            assert_(eq(np.product(x, 1), product(x, 1)))
+            assert_(eq(np.prod(x, 1), product(x, 1)))
 
     def test_testCI(self):
         # Test of conversions and indexing
diff --git a/numpy/ma/testutils.py b/numpy/ma/testutils.py
index 2dd479abe..7a633906b 100644
--- a/numpy/ma/testutils.py
+++ b/numpy/ma/testutils.py
@@ -233,7 +233,7 @@ def fail_if_array_equal(x, y, err_msg='', verbose=True):
 
     """
     def compare(x, y):
-        return (not np.alltrue(approx(x, y)))
+        return (not np.all(approx(x, y)))
     assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
                          header='Arrays are not equal')
 
diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx
index faf19eaf2..4cc8d42f5 100644
--- a/numpy/random/_generator.pyx
+++ b/numpy/random/_generator.pyx
@@ -2628,7 +2628,7 @@ cdef class Generator:
         >>> b = []
         >>> for i in range(1000):
         ...    a = 10. + rng.standard_normal(100)
-        ...    b.append(np.product(a))
+        ...    b.append(np.prod(a))
 
         >>> b = np.array(b) / np.min(b) # scale values to be positive
         >>> count, bins, ignored = plt.hist(b, 100, density=True, align='mid')
diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx
index ca6ba9de8..dfa553ee4 100644
--- a/numpy/random/mtrand.pyx
+++ b/numpy/random/mtrand.pyx
@@ -3066,7 +3066,7 @@ cdef class RandomState:
         >>> b = []
         >>> for i in range(1000):
         ...    a = 10. + np.random.standard_normal(100)
-        ...    b.append(np.product(a))
+        ...    b.append(np.prod(a))
 
         >>> b = np.array(b) / np.min(b) # scale values to be positive
         >>> count, bins, ignored = plt.hist(b, 100, density=True, align='mid')