doMC, doParallel, knitr, rmarkdown, testthat

Modeling Framework for Cellular Communities in their
Environments
c( person("Eugen", "Bauer", , "eugen.bauer@uni.lu", role = c("aut")),
person("Johannes", "Zimmermann", , "j.zimmermann@iem.uni-kiel.de", role = c("aut", "cre")))
Eugen Bauer [aut],
Johannes Zimmermann [aut, cre]
Can be used for simulation of organisms living in
communities. Each organism is represented individually and genome scale
metabolic models determine the uptake and release of compounds. Biological
processes such as movement, diffusion, chemotaxis and kinetics are available
along with data analysis techniques.
igraph, methods, utils, stats, graphics, Rcpp

igraph, methods, utils, stats, graphics, ggplot2, reshape2,
glpkAPI, Rcpp

igraph, methods, utils, stats, graphics, ggplot2, reshape2,
glpkAPI, plyr, Rcpp

Can be used for simulation of organisms living in
communities (Bauer and Zimmermann (2017) <doi:10.1371/journal.pcbi.1005544>).
Each organism is represented individually and genome scale
metabolic models determine the uptake and release of compounds. Biological
processes such as movement, diffusion, chemotaxis and kinetics are available
along with data analysis techniques.
methods, utils, stats, graphics, ggplot2, reshape2, glpkAPI,
plyr, Rcpp, igraph, stringr, R.matlab

This is the companion package of a PhD thesis entitled "Bases Giving Distances. A new paradigm for investigating functional data with applications for spectroscopy" by Timmermans (2012). See references for details and related publications. The core of the BAGIDIS methodology is a functional wavelet based semi-distance that has been introduced by Timmermans and von Sachs (2010, 2015) and Timmermans, Delsol and von Sachs (2013). This semi-distance allows for comparing curves with sharp local patterns that might not be well aligned from one curve to another. It is data-driven and highly adaptive to the curves being studied.  Its main originality is its ability to consider simultaneously horizontal and vertical variations of patterns, which proofs highly useful when used together with clustering algorithms or visualization method. BAGIDIS is an acronym for BAsis GIving DIStances. The extension of BAGIDIS to image data relies on the same principles and has been described in Timmermans and Fryzlewicz (2012), Fryzlewicz and Timmermans (2015).