[racket] Math library ready for testing

I've bumped Dirichlet to the top of the "unordered distributions" list.

I should make that list and some others on my to-do list public, like 
the "planned special functions" list. Where's a good place for that?

Neil ⊥

On 12/07/2012 01:58 PM, Ray Racine wrote:
> Amazing.  Tons of hard work.  Thank you.  I'm going to use it asap.
> Grab a beer and if you're making a list, please add Dirichlet
> Distribution to the Phase 2 list.
>
>
> On Fri, Dec 7, 2012 at 3:33 PM, Neil Toronto <neil.toronto at gmail.com
> <mailto:neil.toronto at gmail.com>> wrote:
>
>     I've just pushed the last commits that make the new math library
>     ready for wider testing. Almost everything ready for use is
>     documented, the tests keep passing, and everything *seems* to work.
>
>     We (the Racket development team) need people to use the heck out of
>     it, to find the majority of the remaining logic and design errors
>     before the next release. This is a big chunk of new code - ~20k
>     lines in ~100 nontrivial files - so the more eyes, the better.
>
>     If all you have time for is checking documentation, we'll take it.
>     The latest docs are here:
>
>     http://pre.racket-lang.org/__docs/html/math/
>     <http://pre.racket-lang.org/docs/html/math/>
>
>     The nightly builds are here:
>
>     http://pre.racket-lang.org/__installers/
>     <http://pre.racket-lang.org/installers/>
>
>     For Windows and Mac, the nightlies should include two new libraries
>     used by `math/bigfloat': libgmp and libmpfr. Linux users almost
>     certainly already have them; many packages (e.g. gcc) depend on libmpfr.
>
>     If you prefer to build from source, clone the git repository here:
>
>     https://github.com/plt/racket
>
>     If you're building on Windows or Mac, you can download pre-built
>     libgmp and libmpfr from here:
>
>     http://download.racket-lang.__org/libs/10/
>     <http://download.racket-lang.org/libs/10/>
>
>     ************
>
>     Once you have a pre-release build, do (require math), and away you go!
>
>     Well, it's probably not obvious where to start. The following are
>     the modules that `math' re-exports, and for some, what needs
>     testing. Please feel free to skim. In decreasing order of attention
>     they need:
>
>     (require math/array)
>
>        NumPy/SciPy/Repa-like arrays, Typed-Racket-style. Provides a
>        covariant `Array' type and several mutable subtypes, array literals,
>        functional constructors, pointwise operations with automatic
>        broadcasting in SciPy/NumPy or permissive mode, slicing, indexing
>        tricks, folds, easy arbitrary transformations, and parallel FFT.
>
>        This one needs a lot of usability testing. In particular...
>
>        We're trying something that's been done only once before, in
>        Haskell's Repa: by default, arrays' elements are *non-strict*,
>        meaning that they're recomputed when referenced. Cool things about
>        this: pretty much everything can in principle be parallelized, and
>        most intermediate arrays use almost no memory. But it requires more
>        thought from users about when arrays should be made strict (computed
>        and stored all at once). If it totally sucks, we can change it. If
>        it's a worthwhile imposition, we'll leave it. If it's a wash, we
>        could parameterize the default behavior.
>
>        Also, I've been considering allowing negative axis numbers and row
>        indexes. Need feedback on how helpful it would be vs. confusing and
>        error-hiding.
>
>        Lastly, I'm looking for a dual of `array-axis-reduce' (a kind of
>        fold) that makes it easy to write `list-array->array', the inverse of
>        the existing `array->list-array'. If you're into functional design
>        puzzles, give this one a shot.
>
>     (require math/bigfloat)
>
>        Floating-point numbers with arbitrarily large precision and
>        large exponents. Also elementary and special functions, whose results
>        are proved to be correct in many theses and dissertations. This is a
>        Racket interface to MPFR (www.mpfr.org <http://www.mpfr.org>).
>
>        This module needs platform-specific testing.
>
>        I think we've verified that `math/bigfloat' works on all the
>        supported 64-bit platforms, but not whether it works on supported
>        32-bit platforms. It should. ;)
>
>        There's an error in the current nightly build, which causes an
>        infinite loop when libmpfr isn't installed and a bigfloat function is
>        applied. I just pushed a fix; it should fail properly tomorrow.
>
>     (require math/distributions)
>
>        Probability distributions: discrete, integer-valued and real-valued.
>        Distribution objects can compute pdfs, cdfs and inverse cdfs,
>        optionally in log space, and for cdfs and inverse cdfs, optionally
>        for upper tails. They can also generate samples.
>
>        Design ideas are welcome. More distributions are planned. Let me know
>        which you need, and I'll concentrate on those first.
>
>        Watch out, R. Our gamma cdf is more accurate.
>
>     (require math/special-functions)
>
>        Non-elementary functions like gamma, erf, zeta, Lambert W, and
>        incomplete gamma and beta integrals. Most of these should be fairly
>        accurate; i.e. they compute answers with apparently < 5 ulps error
>        for the majority of their domains. But floating-point domains are
>        huge, so the more use, the better.
>
>     (require math/number-theory)
>
>        Number theory! Chinese Remainder solutions, coprimality and primality
>        testing, factorization, congruence arithmetic parameterized on a
>        current modulus, integer nth roots, multiplicative functions, common
>        number sequences (Bernoulli, Eulerian, tangent, etc.), combinatorics,
>        primitive roots, and more.
>
>        Please thank Jens Axel Søgaard, who wrote this module, for his
>        excellent work.
>
>     (require math/statistics)
>
>        Functions to compute summary values for collections of data, and to
>        manage weighted samples. Every function for which it makes sense
>        accepts weighted values, including the O(1)-space running statistics
>        update.
>
>        I'm in the middle of documenting this. I'll get around to documenting
>        correlation, kth-value order statistics (via quickselect), and
>        counting/binning at least by Dec. 18.
>
>     (require math/flonum)
>
>        Re-exports `racket/flonum' along with many more floating-point
>        goodies. If you're a floating-point nut, you'll love it. If you're
>        not, at least check out `flsum'. If you're doing statistics, look
>        into log-space arithmetic (`lg+' and friends).
>
>     (require math/base)
>
>        Re-exports `racket/math'; also exports some more constants like
>        gamma.0 (Euler-Mascheroni), a bit more float-complex support, inverse
>        hyperbolic functions, large random numbers, error measurement.
>
>     Lastly, there's `math/matrix', which is currently not re-exported by
>     `math' because I haven't reviewed it yet. This is more from Jens
>     Axel, and if it's like his other fine work, it's correct and
>     well-tested. I'll probably get to it by Christmas.
>
>     To sum up, there are 8 modules that need pounding on, and we need
>     YOU to do some pounding. If you're not terribly busy, please pick
>     one that looks interesting/fun/useful, and try it out.
>
>     Thanks!
>
>     Neil ⊥
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