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Introduction

Package ‘photobiology’ is at the core of a suite of packages for analysis and plotting of data relevant to photobiology (described at https://www.r4photobiology.info/). The accompanying packages provide data and definitions that are to a large extent application-area specific while the functions in the package ‘photobioloy’ are widely useful in photobiology and in radiation quantification in geophysics and meteorology. Package ‘photobiology’ has its main focus in the characterization of the light environment in a biologically relevant manner and in the manipulation of spectral data to simulate photo-physical, photo-chemical and photo-biological interactions and responses. In addition it implements the algorithms of Jean Meeus for the position of the sun, as this and derived quantities like day- and night length are important for most organisms.

Data exchange with packages ‘pavo’, ‘colorSpec’ and ‘hyperSpec’ is supported. The focus of package ‘pavo’ (Maia et al. 2003) is on color perception by animals and assessment of animal coloration. The focus of package ‘colorSpec’ (Davis 2019) is on color-related computations: “Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners.” The focus of package ‘hyperSpec’ (Beleites and Sergo) is the handling of hyperspectral data sets, such as spectral images and time series of spectra.

Because of their different focus, these packages mostly complement each other, in spite of some overlap and differences in approach or even, in philosophy about data handling.

References

Aphalo, P. J., Albert, A., Björn, L. O., McLeod, A. R., Robson, T. M., Rosenqvist, E. (Eds.). (2012). Beyond the Visible: A handbook of best practice in plant UV photobiology (1st ed., p. xx + 174). Helsinki: University of Helsinki, Department of Biosciences, Division of Plant Biology. ISBN 978-952-10-8363-1 (PDF), 978-952-10-8362-4 (paperback). Open access at https://doi.org/10.31885/9789521083631.

Aphalo, Pedro J. (2015) The r4photobiology suite. UV4Plants Bulletin, 2015:1, 21-29. (https://doi.org/10.19232/uv4pb.2015.1.14).

Davis G (2019). A Centroid for Sections of a Cube in a Function Space, with application to Colorimetry. ArXiv e-prints. 1811.00990, (https://arxiv.org/abs/1811.00990).

Maia, R., Eliason, C. M., Bitton, P. P., Doucet, S. M., Shawkey, M. D. (2013) pavo: an R package for the analysis, visualization and organization of spectral data. Methods in Ecology and Evolution, 4(10):906-913. (https://doi.org/10.1111/2041-210X.12069).

Acknowledgements

This work was funded in part by the Academy of Finland (decision 252548), and done when the author was employed at the University of Helsinki, Finland. COST Action FA9604 ‘UV4Growth’ facilitated discussions and exchanges of ideas that lead to the development of this package. The contributions of Andy McLeod, Lars Olof Björn, Nigel Paul, Lasse Ylianttila, Glen Davis, Agnese Fazio, T. Matthew Robson and Titta Kotilainen were specially significant. Other members of the UV4Plants Association (https://www.uv4plants.org/) and participants in workshops and training events contributed both problems in need of being solved and solutions to implement.

Tutorials by Hadley Wickham and comments on my presentation at UseR!2015 allowed me to significantly improve the coding and functionality. The generous on-line help by many members of the R community over more than 20 years is also warmly thanked.

The Packages

The core package in this suite is called photobiology. Other specialized packages for quantification of ultraviolet-, visible- and infra-red radiation (photobiologyWavebands), properties of plant photoreceptors and other plant photobiology related calculations (photobiologyPlants), example spectral data for filters and objects (photobiologyFilters), lamps (photobiologyLamps), LEDs (photobiologyLEDs), sunlight (photobiologySun), light sensors (photobiologySensors) and for exchange of data in foreign formats (photobiologyInOut) are part of the suite. One additional package, (ggspectra), implements facilities for plotting spectral data by extending package ‘ggplot2’, providing both ggplot statistics, geometries and scales in addition to specializations of ggplot() and autoplot(). For additional information on these and other packages by the author please visit (https://www.r4photobiology.info). Each package has its own public Git repository at my Bitbucket or GitHub account (https://bitbucket.org/aphalo/, https://github.com/aphalo/) from where the source code of the current and earlier versions can be cloned or forked.