jorisvandenbossche commented on a change in pull request #9841:
URL: https://github.com/apache/arrow/pull/9841#discussion_r606633215
##########
File path: cpp/src/arrow/compute/kernels/scalar_arithmetic.cc
##########
@@ -233,6 +235,184 @@ struct DivideChecked {
}
};
+struct Power {
+ template <typename T, typename Arg0, typename Arg1>
+ static enable_if_signed_integer<T> Call(KernelContext* ctx, Arg0 left, Arg1
right) {
+ if (right < 0) {
+ ctx->SetStatus(
+ Status::Invalid("integers to negative integer powers are not
allowed"));
+ }
+ if (left == 0 && right != 0) {
+ return 0;
+ }
+ Arg0 result = 1;
+ for (Arg1 i = 0; i < right; i++) {
+ MultiplyWithOverflow(result, left, &result);
+ }
+ return result;
+ }
+
+ template <typename T, typename Arg0, typename Arg1>
+ static enable_if_unsigned_integer<T> Call(KernelContext* ctx, Arg0 left,
Arg1 right) {
+ if (left == 0 && right != 0) {
+ return 0;
+ }
+ Arg0 result = 1;
+ for (Arg1 i = 0; i < right; i++) {
+ MultiplyWithOverflow(result, left, &result);
+ }
+ return result;
+ }
+
+ template <typename T, typename Arg0, typename Arg1>
+ static enable_if_floating_point<T> Call(KernelContext* ctx, Arg0 left, Arg1
right) {
+ if (std::isnan(left) || std::isnan(right)) {
+ return NAN;
+ }
Review comment:
NumPy returns 1 by default in those cases as well:
```
In [20]: np.power(1.0, np.nan)
Out[20]: 1.0
In [21]: np.power(np.nan, 0.0)
Out[21]: 1.0
```
So we could maybe do that as well? (for NaN, not necessarily for Null)
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