Combinatorial substitutions and sofic tilings

A combinatorial substitution is a map over tilings which allows to define sets of tilings with a strong hierarchical structure. In this paper, we show that such sets of tilings are sofic, that is, can be enforced by finitely many local constraints. This extends some similar previous results (Mozes'90, Goodman-Strauss'98) in a much shorter presentation.Comment: 17 pages, 16 figures. In proceedings of JAC 201

Stochastic Flips on Two-letter Words

This paper introduces a simple Markov process inspired by the problem of quasicrystal growth. It acts over two-letter words by randomly performing \emph{flips}, a local transformation which exchanges two consecutive different letters. More precisely, only the flips which do not increase the number of pairs of consecutive identical letters are allowed. Fixed-points of such a process thus perfectly alternate different letters. We show that the expected number of flips to converge towards a fixed-point is bounded by $O(n^3)$ in the worst-case and by $O(n^{5/2}\ln{n})$ in the average-case, where $n$ denotes the length of the initial word.Comment: ANALCO'1

AutoWIG : automatisation de l'encapsulation de librairies C++ en Python et en R

National audiencePython and R programming languages are two of the most popular languages in scientific computing. However, most scientific packages incorporates C and C++ libraries. While several semi-automatic solutions and tools exist to wrap C++ libraries (RCPP, Boost.Python), the process of wrapping a large C++ library is cumbersome and time consuming. Some solutions have been developed in the past (e.g. Py++ or XDress) but require to write complex code to automate the process, and rely on technologies that are not maintained. AutoWIG relies on the LLVM/Clang technology for parsing C/C++ code and the Mako templating engine for generating Boost.Python wrappers. We will illustrate the usage of AutoWIG on a complex collection of C++ libraries for statistical analysis.Les langages de programmation Python et R sont deux des langages les plus populaires pour le calcul scientifique. Cependant, la plupart des logiciels scientifiques incorporent des biblioth eques C ou C++. Bien qu'il existe plusieurs solutions et des outils semi-automatiques pour encapsuler des biblioth eques C++ (RCPP, Boost.Python), le processus d'encapsulation d'une grande biblioth eque C++ est long et fastidieux. Certaines solutions pour Python ont eté développées dans le passé (par exemple Py++ ou XDress) mais nécessitent d'´ ecrire du code complexe pour automatiser le processus, et de compter sur des technologies qui ne sont pas entretenues. Le logiciel AutoWIG fait appeì a la technologie LLVM/Clang pour l'analyse syntaxique de code C/C++ et a l'outil Mako pour générer l'encapsulation des biblioth eques C++ avec Boost.Python et RCPP. Nous illustrerons l'utilisation d'AutoWIG sur un ensemble complexe de biblioth eques C++ pour l'analyse statistique. Mots-clés. C++, Python, R, calcul scientifique Abstract. Python and R programming languages are two of the most popular languages in scientific computing. However, most scientific packages incorporates C and C++ libraries. While several semi-automatic solutions and tools exist to wrap C++ libraries (RCPP, Boost.Python), the process of wrapping a large C++ library is cumbersome and time consuming. Some solutions have been developed in the past (e.g. Py++ or XDress) but require to write complex code to automate the process, and rely on technologies that are not maintained. AutoWIG relies on the LLVM/Clang technology for parsing C/C++ code and the Mako templating engine for generating Boost.Python wrappers. We will illustrate the usage of AutoWIG on a complex collection of C++ libraries for statistical analysis

Parametric Modelling of Multivariate Count Data Using Probabilistic Graphical Models

Multivariate count data are defined as the number of items of different categories issued from sampling within a population, which individuals are grouped into categories. The analysis of multivariate count data is a recurrent and crucial issue in numerous modelling problems, particularly in the fields of biology and ecology (where the data can represent, for example, children counts associated with multitype branching processes), sociology and econometrics. We focus on I) Identifying categories that appear simultaneously, or on the contrary that are mutually exclusive. This is achieved by identifying conditional independence relationships between the variables; II)Building parsimonious parametric models consistent with these relationships; III) Characterising and testing the effects of covariates on the joint distribution of the counts. To achieve these goals, we propose an approach based on graphical probabilistic models, and more specifically partially directed acyclic graphs

Local Rules for Computable Planar Tilings

Aperiodic tilings are non-periodic tilings characterized by local constraints. They play a key role in the proof of the undecidability of the domino problem (1964) and naturally model quasicrystals (discovered in 1982). A central question is to characterize, among a class of non-periodic tilings, the aperiodic ones. In this paper, we answer this question for the well-studied class of non-periodic tilings obtained by digitizing irrational vector spaces. Namely, we prove that such tilings are aperiodic if and only if the digitized vector spaces are computable.Comment: In Proceedings AUTOMATA&JAC 2012, arXiv:1208.249

Approche graphique pour la modélisation statistique de la dépendance entre activités journalières

http://mistis.inrialpes.fr/workshop-statistique-transport.html Transparents disponibles sur http://mistis.inrialpes.fr/docs/workshop-statistique-transport/slidesDurand.pdfInternational audienceIn this presentation, we introduce a new family of statistical models for the analysis of multivariate count data. We propose an application in modelling daily activity programs at the scale of individuals or families