Merge pull request #15037 from tirthasheshpatel/patch-1

BUG: `np.resize` negative shape and subclasses edge case fixes

2 files changed, 46 insertions, 12 deletions

diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 7193af839..0c63bcf73 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1374,10 +1374,17 @@ def resize(a, new_shape):
 
     See Also
     --------
+    np.reshape : Reshape an array without changing the total size.
+    np.pad : Enlarge and pad an array.
+    np.repeat: Repeat elements of an array.
     ndarray.resize : resize an array in-place.
 
     Notes
     -----
+    When the total size of the array does not change `~numpy.reshape` should
+    be used.  In most other cases either indexing (to reduce the size)
+    or padding (to increase the size) may be a more appropriate solution.
+
     Warning: This functionality does **not** consider axes separately,
     i.e. it does not apply interpolation/extrapolation.
     It fills the return array with the required number of elements, taken
@@ -1401,22 +1408,21 @@ def resize(a, new_shape):
     """
     if isinstance(new_shape, (int, nt.integer)):
         new_shape = (new_shape,)
+
     a = ravel(a)
-    Na = len(a)
-    total_size = um.multiply.reduce(new_shape)
-    if Na == 0 or total_size == 0:
-        return mu.zeros(new_shape, a.dtype)
 
-    n_copies = int(total_size / Na)
-    extra = total_size % Na
+    new_size = 1
+    for dim_length in new_shape:
+        new_size *= dim_length
+        if dim_length < 0:
+            raise ValueError('all elements of `new_shape` must be non-negative')
 
-    if extra != 0:
-        n_copies = n_copies + 1
-        extra = Na - extra
+    if a.size == 0 or new_size == 0:
+        # First case must zero fill. The second would have repeats == 0.
+        return np.zeros_like(a, shape=new_shape)
 
-    a = concatenate((a,) * n_copies)
-    if extra > 0:
-        a = a[:-extra]
+    repeats = -(-new_size // a.size)  # ceil division
+    a = concatenate((a,) * repeats)[:new_size]
 
     return reshape(a, new_shape)
 
diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py
index acd442e2f..2a87ffaf8 100644
--- a/numpy/core/tests/test_numeric.py
+++ b/numpy/core/tests/test_numeric.py
@@ -31,6 +31,17 @@ class TestResize:
         Ar3 = np.array([[1, 2, 3], [4, 1, 2], [3, 4, 1], [2, 3, 4]])
         assert_equal(np.resize(A, (4, 3)), Ar3)
 
+    def test_repeats(self):
+        A = np.array([1, 2, 3])
+        Ar1 = np.array([[1, 2, 3, 1], [2, 3, 1, 2]])
+        assert_equal(np.resize(A, (2, 4)), Ar1)
+
+        Ar2 = np.array([[1, 2], [3, 1], [2, 3], [1, 2]])
+        assert_equal(np.resize(A, (4, 2)), Ar2)
+
+        Ar3 = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])
+        assert_equal(np.resize(A, (4, 3)), Ar3)
+
     def test_zeroresize(self):
         A = np.array([[1, 2], [3, 4]])
         Ar = np.resize(A, (0,))
@@ -50,6 +61,23 @@ class TestResize:
         assert_array_equal(Ar, np.zeros((2, 1), Ar.dtype))
         assert_equal(A.dtype, Ar.dtype)
 
+    def test_negative_resize(self):
+        A = np.arange(0, 10, dtype=np.float32)
+        new_shape = (-10, -1)
+        with pytest.raises(ValueError, match=r"negative"):
+            np.resize(A, new_shape=new_shape)
+
+    def test_subclass(self):
+        class MyArray(np.ndarray):
+            __array_priority__ = 1.
+
+        my_arr = np.array([1]).view(MyArray)
+        assert type(np.resize(my_arr, 5)) is MyArray
+        assert type(np.resize(my_arr, 0)) is MyArray
+
+        my_arr = np.array([]).view(MyArray)
+        assert type(np.resize(my_arr, 5)) is MyArray
+
 
 class TestNonarrayArgs:
     # check that non-array arguments to functions wrap them in arrays