Rephrase NaN Inf section for integral and floating point types
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(see the [CppReference dedicated page](https://en.cppreference.com/w/cpp/types/numeric_limits) for more details about `std::numeric_limits`).
Other languages such as Python (but not its numeric modules such as _numpy_ which are using C or C++ under the hood) gets a underlying integer model that is resilient to this kind of issue but there is a performance cost behind it; types such as those used in C++ are tailored to favor optimization on your hardware.
Other languages such as Python (but not its numeric modules such as _numpy_ which are using C or C++ under the hood) gets a underlying integer model that is resilient to this kind of issue but there is a performance cost behind it; types such as those used in C++ are tailored to favor optimization on your hardware.
There are subtleties about NaN (see [Cppreference](https://en.cppreference.com/w/cpp/numeric/math/nan)) but in most cases you don't need to bother much with either `inf` or `nan`, except if you have reasons to think your computation may produce either of them. In that case, you may want to check your value is correct with `std::isfinite` ([Cppreference](https://en.cppreference.com/w/cpp/numeric/math/isfinite)).