# User Guide: 0 The R for Photobiology Suite

### Photobiology-related computations in R

#### Pedro J. Aphalo

#### Built: 2024-03-31

The citation for the suite is given by

    print(citation('photobiology'), style = "textVersion")

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

## 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).

## Packages in the suite

The core package in this suite is called ‘photobiology’ and all other packages in the suite depend on it. 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’. Two additional packages (‘rOmniDriver’) and (‘ooacquire’) make it possible to acquire spectral data by controlling Ocean Insight/Ocean Optics spectrometers from within R.

Package | Provides
--- | ---
‘photobiology’ | Core classes, methods and functions
‘photobiologyWavebands’ | Definitions of standardized and frequently used wavelength band definitions and spectral weighting functions.
‘photobiologyPlants’ | Methods, functions and data for plants and vegetation.
‘photobiologyInOut’ | Exchange of data within R and using different proprietary and standard-based formats.
‘photobiologyLamps’ | Spectral emission and other data for various lamp types.
‘photobiologyLEDs’ | Spectral emission and other data for various LEDs and LED arrays.
‘photobiologySensors’ | Spectral response and other data for various UV, VIS and NIR sensors.
‘photobiologySun’ | Spectral irradiance and other data for sunlight. Both measured and standard definitions for ground level and top of the atmosphere.
‘photobiologyFilters’ | Spectral transmittance and spectral reflectance data for different materials including optical filters. Spectral data on refractive index.
‘ggspectra’ | Extensions to package ‘ggplot2’ for easier plotting of spectral data, including `autoplot()` and `ggplot()` methods for the classes defined in package ‘photobiology’ and scales, geoms and statistics.
‘oocquire’ (Not in CRAN) | Data acquision and control of Ocean Optics (now Ocean Insight) spectrometers.
‘rOmniDriver’ (Not in CRAN) | Interface to OmniDriver drivers for communication with spectrometers from Ocean Optics (now Ocean Insight)

For additional information on these and other packages by the author please visit (https://www.r4photobiology.info) for news, and check the menue entry R Packages > Checks and Issues for current status and links to on-line documentation and public Git repositories. Each package has its own public Git repository at my GitHub account from where the source code of the current and earlier versions can be cloned or forked.

## 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.