/*
* Creates a result for reducing 'operand' along the axes specified
* in 'axis_flags'. If 'dtype' isn't NULL, this function steals a
* reference to 'dtype'.
*
* If 'out' isn't NULL, this function creates a view conforming
* to the number of dimensions of 'operand', adding a singleton dimension
* for each reduction axis specified. In this case, 'dtype' is ignored
* (but its reference is still stolen), and the caller must handle any
* type conversion/validity check for 'out'
*
* If 'subok' is true, creates a result with the subtype of 'operand',
* otherwise creates on with the base ndarray class.
*
* If 'out' is NULL, it allocates a new array whose shape matches that of
* 'operand', except for at the reduction axes. If 'dtype' is NULL, the dtype
* of 'operand' is used for the result.
*/
NPY_NO_EXPORT PyArrayObject *
PyArray_CreateReduceResult(PyArrayObject *operand, PyArrayObject *out,
PyArray_Descr *dtype, npy_bool *axis_flags,
int keepdims, int subok,
const char *funcname)
{
PyArrayObject *result;
if (out == NULL) {
/* This function steals the reference to 'dtype' */
result = allocate_reduce_result(operand, axis_flags, dtype, subok);
}
else {
int need_copy = 0;
if (solve_may_share_memory(operand, out, 1) != 0) {
need_copy = 1;
}
/* Steal the dtype reference */
Py_XDECREF(dtype);
result = conform_reduce_result(PyArray_NDIM(operand), axis_flags,
out, keepdims, funcname, need_copy);
}
return result;
}
/* Returns 1 if the arrays have overlapping data, 0 otherwise */
NPY_NO_EXPORT int
arrays_overlap(PyArrayObject *arr1, PyArrayObject *arr2)
{
mem_overlap_t result;
result = solve_may_share_memory(arr1, arr2, NPY_MAY_SHARE_BOUNDS);
if (result == MEM_OVERLAP_NO) {
return 0;
}
else {
return 1;
}
}
