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pavo

An R package for the spectral and spatial analysis of color patterns

Currently maintained by Rafael Maia, Thomas White, and Hugo Gruson.

About

pavo is an R package developed with the goal of establishing a flexible and integrated workflow for working with spectral and spatial colour data. It includes functions that take advantage of new data classes to work seamlessly from importing raw spectra and images, to visualisation and analysis. It provides flexible ways to input spectral data from a variety of equipment manufacturers, process these data, extract variables, and produce publication-quality figures.

pavo was written with the following workflow in mind:

  • Organise data by importing and processing spectra and images (e.g., to remove noise, negative values, smooth curves, etc.).
  • Analyse the resulting files, using spectral analyses of shape (hue, saturation, brightness), visual models based on perceptual data, and/or spatial adjacency and boundary strength analyses.
  • Visualise the output, with multiple options provided for exploration, presentation, and analysis.

Need more information, or help with the package?

Citing pavo

The manuscripts describing the package has been published and are free to access:

> v. 2.0

Maia R., Gruson H., Endler J.A. and White T.E. 2018 pavo 2: new tools for the spectral and spatial analysis of colour in R. bioRxiv. doi: 10.1101/427658

< v. 2.0

Maia R., Eliason C.M., Bitton P.-P., Doucet S.M. and Shawkey M.D. 2013. pavo: an R Package for the analysis, visualization and organization of spectral data. Methods in Ecology and Evolution 4(10):609-613. doi: 10.1111/2041-210X.12069

Install

This is the development page for pavo. The stable release is available from CRAN. Simply use install.packages('pavo') to install.

If you want to install the bleeding edge version of pavo, you can:

# install.packages('remotes')
remotes::install_github('rmaia/pavo')
  • download files from GitHub and install using $R CMD INSTALL or, from within R:
install.packages(path, type='source', repos=NULL)

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Version

Install

install.packages('pavo')

Monthly Downloads

765

Version

2.1.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Rafael Maia

Last Published

March 6th, 2019

Functions in pavo (2.1.0)

is.colspace

Test is object is of class 'colspace'
coldist2mat

Convert coldist to distance matrix
hexagon

Colour hexagon
coldist

Colour distances
img_conversion

Convert images between class rimg and cimg
getspec

Import spectra files
procspec

Process spectra
spec2rgb

Spectrum to rgb colour conversion
voloverlap

Color volume overlap
cie

CIE colour spaces
explorespec

Plot spectral curves
hexplot

Plot a colour hexagon
sensdata

Retrieve or plot in-built spectral sensitivity data
cocplot

Plot the colour opponent coding diagram
jnd2xyz

Convert JND distances into perceptually-corrected Cartesian coordinates
peakshape

Peak shape descriptors
as.rspec

Convert data to an rspec object
axistetra

Plot reference axes in a static tetrahedral colourspace
tcspace

Tetrahedral colourspace
points.colspace

Plot points in a colourspace
plotsmooth

Plot loess smoothed curves
transmissiondata

Default ocular transmission data
irrad2flux

Converts between irradiance and photon (quantum) flux
jndplot

Perceptually-corrected chromaticity diagrams
tcsplot

Interactive plot of a tetrahedral colourspace
plot.colspace

Plot spectra in a colourspace
catplot

Plot the categorical colour vision model
procimg

Process images
bootcoldist

Bootstrap colour distance confidence intervals
bgandilum

Default background and illuminant data
colspace

Model spectra in a colorspace
subset.rspec

Subset rspec, vismodel, and colspace objects
summary.vismodel

Visual model summary
plot.rimg

Plot unprocessed or colour-classified images
jndrot

Rotate Cartesian coordinates obtained from jnd2xyz
getimg

Import image data
aggplot

Plot aggregated reflectance spectra
triplot

Plot a Maxwell triangle
plot.rspec

Plot spectra
summary.rspec

Colourimetric variables
classify

Identify colour classes in an image for adjacency analyses
sensmodel

Modeling spectral sensitivity
merge.rspec

Merge two rspec objects
categorical

Categorical fly-visual model
cieplot

CIE plot
coc

Color opponent coding model
sicalis

Spectral curves from three body regions of stripe-tailed yellow finch (Sicalis citrina) males
segspace

Segment classification
vismodel

Visual models
vol

Plot a tetrahedral color space
flowers

Reflectance spectra from a suite of native Australian flowers, collected around Cairns, Queensland.
trispace

Trichromatic colour space
vissyst

Animal visual systems data
parse_avantes

Import Avantes binary file
adjacent

Run an adjacency and boundary strength analysis
is.vismodel

Test is object is of class 'vismodel'
ttvertex

vertex for the tetrahedral color space
legendtetra

Add legend to a static tetrahedral colourspace
projplot

2D projection of a tetrahedral colourspace
pavo-package

pavo: Perceptual Analysis, Visualization and Organization of Spectral Color Data in R
aggspec

Aggregate reflectance spectra
summary.colspace

Colourspace data summary
diplot

Plot a dichromat segment
parse_procspec

Import ProcSpec spectra file
as.rimg

Convert data to an rimg object
dispace

Dichromatic colour space
teal

Angle-resolved reflectance data for the iridescent wing patch of a male green-winged teal (Anas carolinensis)
segplot

Plot the segment-analysis model
summary.rimg

Image summary
tetraplot

Plot a static tetrahedral colorspace