boostorg / boostorg/multiprecision

Update examples

Open
#725 0 comments 0 reactions 1 assignee Claimed by @ckormanyos View on GitHub
documentation enhancement quality
Dominant language
C++
Stars
265
Forks
128
Avg merge
4h 48m
Merged PRs (30d)
2

Description

We can upgrade some of the examples, as partially motivated by discussion in #718.

- [ ] Having one example that demonstrates the using trick when necessary, would be good.
- [ ] The [Jahnke-Emden-Lambda example](https://www.boost.org/doc/libs/latest/libs/multiprecision/doc/html/boost_multiprecision/tut/floats/fp_eg/jel.html) makes use of `using`. But we could emphasize it even more.
- [ ] The [Calculating a Derivative example](https://www.boost.org/doc/libs/latest/libs/multiprecision/doc/html/boost_multiprecision/tut/floats/fp_eg/nd.html) could make much better use of `using`, particularly in the calls of the derivative functor(s).
- [ ] The [Calculating an Integral example](https://www.boost.org/doc/libs/latest/libs/multiprecision/doc/html/boost_multiprecision/tut/floats/fp_eg/gi.html) could be made much more generic. It seems to already be relying on ADL and does not use `using`. I'm not even sure it is set up properly for `float`, `double` or `long double`?
- [ ] Looking at [Polynomial Evaluation](https://www.boost.org/doc/libs/latest/libs/multiprecision/doc/html/boost_multiprecision/tut/floats/fp_eg/poly_eg.html) I have evolved in the past 20 years or so. These days, I tend to prefer Pade-like expansions for these in order to reduce the coefficient list(s). These still require polynomial evaluation for the numerator and denominator in the Pade approximation.
- [x] In the [Gause-Laguerre example](https://www.boost.org/doc/libs/latest/libs/multiprecision/doc/html/boost_multiprecision/tut/floats/fp_eg/gauss_lagerre_quadrature.html), we could post the [full link](https://www.wolframalpha.com/input?i=Fit%5B%7B%7B21.0%2C+3.5%7D%2C+%7B51.0%2C+11.1%7D%2C+%7B101.0%2C+22.5%7D%2C+%7B201.0%2C+46.8%7D%7D%2C+%7B1%2C+d%2C+d%5E2%7D%2C+d%5D+FullSimplify%5B%25%5D) to the Wolfram alpha code for the guess at the numbers of coefficients.

Contributor guide

No contributing guide indexed for this repository

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.