Versatile Pie Charts, Bar Charts and Box Plots using Patterns,
Colors and Images
c( person("Chunqiao", "Luo", email = "chunqiaoluo@gmail.com", role = c("aut", "cre")),person("Shasha", "Bai", role = c("aut")) )
Creates aesthetically pleasing and informative pie charts, bar charts and box plots with colors, patterns, and images.

Versatile Pie Charts, Ring Charts, Bar Charts and Box Plots
using Patterns, Colors and Images
Rcpp (>= 0.11.0), R6 (>= 2.1.2), ggplot2 (>= 2.1.0), jpeg (>=
0.1-8), png (>= 0.1-7), grDevices, utils, RcppParallel, dplyr,
gtable, gridExtra
Creates aesthetically pleasing and informative pie charts, ring charts, bar charts and box plots with colors, patterns, and images.

Bayesian Experimental Design for Systems Biology.
Implementation of a Bayesian active learning strategy to carry out sequential experimental design in the context of biochemical network kinetic parameter estimation. This package gathers functions and pre-computed data sets to reproduce results presented in Pauwels E. et. al published in BMC Systems Biology, 2014. Scripts are given to compute all results from scratch or to draw pictures based on pre-computed data sets.

A cohesive framework for parsing, analyzing and organizing
color from spectral data
Perceptual analysis, visualization and organization of color
data
c(person("Rafael", "Maia", role = c("aut", "cre"), email =
"rm72@zips.uakron.edu"), person("Chad", "Eliason", role =
"aut", email = "cme16@zips.uakron.edu"), person("Pierre-Paul",
"Bitton", role = "aut", email = "bittonp@uwindsor.ca"))
'aggplot.R' 'aggspec.R' 'as.rspec.r' 'coldist.R'
'data-bgandilum.R' 'data-sicalis.R' 'data-teal.R'
'data-ttvertex.R' 'data-vissyst.R' 'explorespec.R' 'getspec.R'
'internal.R' 'pavo-package.R' 'peakshape.R' 'plot.rspec.r'
'plotsmooth.R' 'procspec.R' 'projplot.R' 'segclass.R'
'sensmodel.R' 'spec2rgb.R' 'summary.rspec.R' 'summary.tcs.R'
'tcs.R' 'tcsplot.R' 'tcspoints.R' 'tcsvol.R' 'vismodel.R'
'voloverlap.R'
Rafael Maia [aut, cre], Chad Eliason [aut], Pierre-Paul Bitton
[aut]