Here is the latest Caml Weekly News, for the week of May 26 to June 02, 2009.
Archive: http://caml.inria.fr/pub/ml-archives/caml-list/2009/05/f3b3b8dfd837f6b039a44258ab59c99a.en.htmlRichard Jones announced:
There hasn't been a release of OCaml Ancient for two and a half years, and it stopped working with OCaml 3.11 because of a change in the way the heap was managed. So I'm pleased to announce a new release which fixes that and some other things: Home page: http://merjis.com/developers/ancient Download: http://merjis.com/_file/ancient-0.9.0.tar.gz (New) Git repository: http://git.et.redhat.com/?p=ocaml-ancient.git
Archive: http://groups.google.com/group/fa.caml/browse_thread/thread/57738498a2510adc#Continuing the thread from last week, Richard Jones said and Stéphane Glondu announced:
We finished upgrading the library packages in Fedora 12, and the only remaining problem is with ocamlduce which hasn't been ported yet. I've merged changes from 3.11.1+rc0, and tagged it 18.104.22.168rc0 on ocamlcore: http://git.ocamlcore.org/cgi-bin/gitweb.cgi?p=ocamlduce/ocamlduce.git I won't make a release (with tarball) before the final 3.11.1, but you can still try it if you want (have a look at README.ocamlduce first to know how to deal with git checkouts).
Archive: http://groups.google.com/group/fa.caml/browse_thread/thread/f8eb4c1d6648a1eb#Xavier Clerc announced:
This post announces the 1.0-beta release of the following projects: - Bisect: coverage tool - Bolt: logging tool - Kaputt: testing tool === Bisect === Home page: http://bisect.x9c.fr Main changes since 1.0-alpha: - switch to OCaml 3.11.0 - bug #30: incorrect detection of ocamljava - bug #31: default make target - bug #32: incorrect source rendering under Firefox - bug #33: information about global coverage missing - bug #34: bare text mode added - bug #35: introduction of navigation bar and code folding - bug #36: instrumentation with -unsafe switch - bug #37: incorrect handling of array literals - unreported bug regarding the handling of if/then construct with no else - introduction of CSV, XML modes - major code refactoring and improvement === Bolt === Home page: http://bolt.x9c.fr First public release, main features: - inspired by and modeled after the Apache log4j framework - camlp4 syntax extension to remove logging statements at compile time - configuration of logging at runtime through property file - predefined output formats: text, CSV, HTML, XML - fully customizable === Kaputt === Home page: http://kaputt.x9c.fr Main changes since 1.0-alpha: - 'Assert.assert_xyz' functions renamed to 'Assert.xyz' (old functions are temporary kept as 'deprecated') - support for Big_int, Num, Map, Set, Hashtbl, Queue, Stack, Weak, and Bigarray - support for shell-based tests - new output modes (HTML, XML, and CSV)
Archive: http://groups.google.com/group/fa.caml/browse_thread/thread/09b5dea11fd1ceb9#Oleg announced:
Chung-chieh Shan and I would like to announce the OCaml library HANSEI, to express probabilistic models and perform probabilistic inference. OCaml thus becomes a probabilistic programming language. The canonical example of Bayesian net, the grass model, looks as follows open ProbM;; let grass_model () = (* unit -> bool *) let rain = flip 0.3 and sprinkler = flip 0.5 in let grass_is_wet = (flip 0.9 && rain) || (flip 0.8 && sprinkler) || flip 0.1 in if not grass_is_wet then fail (); rain;; The model first defines the prior distributions of two events: of raining and of the sprinkler being on. We then specify the Bayesian: grass may be wet because it rained or because the sprinkler was on, or -- with the probability 10% -- for some other reason. We also consider that there is 10% chance rain did not wet the grass. We observe that the grass is wet. What are the chances it rained? To find out, we execute exact_reify grass_model;; - : bool pV = [(0.322, V false); (0.2838, V true)] which after normalization tells the posterior probability of raining, about 7/15. The probabilistic model is the regular OCaml function; the independent random variables rain and sprinkler and the dependent random variable grass_is_wet are regular OCaml boolean variables. We can pass the values of these random variables (which are just booleans) to regular OCaml functions such as 'not' and use the result in the regular if statement. HANSEI can handle models that are far more complex than the grass model, supporting variable (or bucket) elimination, on-demand evaluation of probabilistic expressions, memoization of stochastic functions, and importance sampling. Here is an example of on-demand evaluation: let lazy_pair () = let x = letlazy (fun () -> flip 0.5) in (x (), x ());; exact_reify lazy_pair;; - : (bool * bool) pV = [(0.5, V (true, true)); (0.5, V (false, false))] We do not observe the pair (true, false). Evaluating the expression x () several times gives the same result -- in the same possible world. That result may be different in another possible world. For that reason, we cannot use OCaml's own 'lazy' evaluation: OCaml's lazy is not thread-safe. A particular feature of HANSEI is that it permits calls to inference procedures (e.g., exact_reify) appear in models. After all, both are OCaml expressions. Distributions thus can be parameterized over distributions and inference procedures can reason about their own accuracy. The HANSEI code is available at http://okmij.org/ftp/kakuritu/ The web page also presents HANSEI code for sample probabilistic models and standard benchmarks (HMM, noisy-or, population estimation, belief networks). The current documentation includes two complementary papers http://okmij.org/ftp/kakuritu/dsl-paper.pdf to be presented at the IFIP working conference on domain-specific languages and http://okmij.org/ftp/kakuritu/embedpp.pdf to be presented at `Uncertainty in AI'. The papers are written for different audiences. The first paper explains the implementation of probabilistic primitives whereas the second describes the applications of the library.
Thanks to Alp Mestan, we now include in the Caml Weekly News the links to the recent posts from the ocamlcore planet blog at http://planet.ocamlcore.org/. OCaml Metrics beta (0.51) released: http://forge.ocamlcore.org/forum/forum.php?forum_id=370 Making mutable state faster: optimizing the caml_modify write barrier: http://eigenclass.org/R2/writings/optimizing-caml_modify simple expat based xml parser: https://mancoosi.org/~abate/simple-expat-based-xml-parser Mathematically Structured but not Necessarily Functional Programming: http://math.andrej.com/2009/05/29/mathematically-structured-but-not-necessarily-functional-programming/ Une nouvelle application demexp en web avec web2py: https://bentobako.org/david/blog/index.php?post/2009/05/28/une-nouvelle-application-demexp-en-web-avec-web2py When immutable data is faster: write barrier costs: http://eigenclass.org/R2/writings/write-barrier-cost Lwt and Concurrent ML: http://ambassadortothecomputers.blogspot.com/2009/05/lwt-and-concurrent-ml.html OCaml Metrics: http://forge.ocamlcore.org/projects/ocaml-metrics/
If you happen to miss a CWN, you can send me a message and I'll mail it to you, or go take a look at the archive or the RSS feed of the archives.
If you also wish to receive it every week by mail, you may subscribe online.