R for Photobiology: Theory and recipes for common calculations

Contents
List of Tables
List of Figures
Preface
	Typographical conventions
	Acknowledgements
Theory behind calculations
	Radiation properties
		Packages used in this chapter
		Ultraviolet and visible radiation
		Solar radiation
		Artificial radiation
	Radiation interactions
		Radiation and molecules
			Absorption
			Fluorescence
			Phosphorescence
		Radiation and simple objects
			Angle of incidence
			Refraction
			Difraction
			Scatering
		Radiation in tissues and cells
		Radiation interactions in plant canopies
		Radiation interactions in water bodies
		Physical quantities
			Specular and total reflectance
			Internal and total transmittance
			Absorbance and absorptance
	Photochemistry and photobiology
		Light driven reactions
		Silver salts and photographic films
		Bleaching by UV radiation
		Chlorophyll
		Plant photoreceptors
		Animal photoreceptors
		Action spectroscopy
		Photoreception tuning
	Algorithms
		Integration
			Area under a spectral curve
		Discontinuous functions
		Scaling
		Normalization
		Interpolation
		Astronomy
			Times to events
			Position of the sun
		Array-detector spectrometers
			Measurements—problems and solutions
			Data processing steps for irradiance
Tools used for calculations
	Software
		Introduction
		The different pieces
			R
			RStudio
			Revision control: Git and Subversion
			C++ compiler
			LaTeX
			Markdown
	R for Photobiology packages
		Expected use and users
		The design of the framework
		The suite
		The r4photobiology repository
Cookbook of calculations
	Storing data
		Packages used in this chapter
		Introduction
		Spectra
			How are spectra stored?
			Spectral data assumptions
			Task: Create a spectral object from numeric vectors
			Task: Create a spectral object from a data frame
			Task: Convert a data frame into a spectral object
			Task: trimming a spectrum
			Task: interpolating a spectrum
			Task: Row binding spectra
			Task: Merging spectra
		Collections of multiple spectra
			Task: Constructing Scale = 0.89 0.05ptcolor push gray 0color pop_mspctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects from Scale = 0.89 0.05ptcolor push gray 0color pop_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: Retrieving Scale = 0.89 0.05ptcolor push gray 0color pop_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects from Scale = 0.89 0.05ptcolor push gray 0color pop_mspctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: Subsetting Scale = 0.89 0.05ptcolor push gray 0color pop_mspctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: Combining Scale = 0.89 0.05ptcolor push gray 0color pop_mspctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
		Internal-use functions
		Wavebands
			How are wavebands stored?
			Task: Create waveband objects
			Task: trimming wavebands
	Arithmetic operators and mathematical functions
		Packages used in this chapter
		Introduction
		Conversion between units of expression
			Task: conversion of irradiance from energy to photon base
			Task: conversion of responsivity from energy to photon base
			Task: conversion irradiance from photon to energy base
			Task: conversion of responsivity from photon to energy base
			Task: conversion of transmittance into absorptance
			Task: conversion of transmittance into absorbance
			Task: conversion of absorptance into transmittance
			Task: conversion of absorbance into transmittance
		Arithmetic operators and mathematical functions for spectra
		Operators and operations between a spectrum and a numeric vector
		Math functions taking a spectrum as argument
		Comparison operators
		Task: Simulating spectral irradiance under a filter
		Task: Uniform scaling of a spectrum
			Task: Arithmetic operations within one spectrum
			Task: Using operators on underlying vectors
			Task: Using options to change default behaviour of maths operators and functions
		Wavebands
			Mathematical operators
			Task: Compute weighted spectral quantities
	Spectra: simple summaries and features
		Packages used in this chapter
		Task: Printing spectra
		Task: Summaries related to object properties
		Task: Integrating spectral data
		Task: Averaging spectral data
		Task: Summaries related to wavelength
		Task: Finding the class of an object
		Task: Querying other attributes
		Task: Query how spectral data contained is expressed
		Task: Querying about `origin\' of data
		Task: Plotting a spectrum
		Task: Other R\'s methods
		Task: Extract peaks and valleys
			Task: finding the location of peaks as an index into vectors with spectral data
			Task: Extracting peaks and valleys using vectors
		Task: Refining the location of peaks and valleys
			Bell-shaped function
			Spline with a single node
			Spline with three nodes
	Wavebands: simple summaries and features
		Packages used in this chapter
		Task: Printing wavebands
		Task: Summaries related to object properties
		Task: Summaries related to wavelength
		Task: Querying other properties
		Task: R\'s methods
		Task: Plotting a waveband
	Irradiance (not weighted)
		Packages used in this chapter
		Introduction
		Task: use simple predefined wavebands
		Task: define simple wavebands
		Task: define lists of simple wavebands
		Task: (energy) irradiance from spectral irradiance
		Task: photon irradiance from spectral irradiance
		Task: irradiance for more than one waveband
		Task: calculate fluence for an irradiation event
		Task: photon ratios
		Task: energy ratios
		Task: calculate average number of photons per unit energy
		Task: split energy irradiance into regions
		Task: calculate overlap between spectra
		Collections of spectra
	Irradiance (weighted or effective)
		Packages used in this chapter
		Introduction
		Task: specifying the normalization wavelength
		Task: use of weighted wavebands
		Task: define wavebands that use weighting functions
		Task: calculate effective energy irradiance
		Task: calculate effective photon irradiance
		Task: calculate daily effective energy exposure
			From spectral daily exposure
			From spectral irradiance
	Transmission and reflection
		Packages used in this chapter
		Introduction
		Task: absorbance, absorptance and transmittance
		Task: spectral absorbance from spectral transmittance
		Task: spectral transmittance from spectral absorbance
		Task: transmitted spectrum from spectral transmittance and spectral irradiance
		Task: reflected spectrum from spectral reflectance and spectral irradiance
		Task: total spectral transmittance from internal spectral transmittance and spectral reflectance
		Task: combined spectral transmittance of two or more filters
			Ignoring reflectance
			Considering reflectance
		Task: light scattering media (natural waters, plant and animal tissues)
		Task: simulating the spectral irradiance under a LED luminaire
	Astronomy
		Packages used in this chapter
		Introduction
			Time coordinates
			Geographic coordinates
			Algorithm and peculiarities of time data
		Task: calculating the length of the photoperiod
		Task: Calculating times of sunrise, solar noon and sunset
		Task: calculating the position of the sun
		Task: plotting sun elevation through a day
		Task: plotting day or night length through the year
		Task: plotting local time at sunrise
		Task: plotting solar time at sunrise
	Colour
		Packages used in this chapter
		Introduction
		Task: calculating an RGB colour from a single wavelength
		Task: calculating an RGB colour for a range of wavelengths
		Task: calculating an RGB colour for spectrum
		Standard CIE illuminants
		A sample of colours
	Colour based indexes
		Packages used in this chapter
		What are colour-based indexes?
		Task: Calculation of the value of a known index from spectral data
		Task: Estimation of an optimal index for discrimination
		Task: Fitting a simple optimal index for prediction of a continuous variable
		Task: PCA or PCoA applied to spectral data
		Task: Working with spectral images
	Plotting spectra and colours
		Packages used in this chapter
		Set up
		Introduction to plotting spectra
		Using autoplot() methods with spectra
			Task: plotting of Scale = 0.89 0.05ptcolor push gray 0color popsource_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting of normalized Scale = 0.89 0.05ptcolor push gray 0color popsource_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting of Scale = 0.89 0.05ptcolor push gray 0color popresponse_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting of Scale = 0.89 0.05ptcolor push gray 0color popfilter_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting of Scale = 0.89 0.05ptcolor push gray 0color popreflector_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting of Scale = 0.89 0.05ptcolor push gray 0color popobject_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: plotting collections of spectra
		Plotting spectra with ggplot
			Task: plotting Scale = 0.89 0.05ptcolor push gray 0color popsource_spctcodeshadecolorcolor push gray 0color poptowidthheightdepth objects
			Task: Saving axis-label definitions for re-use
			Task: plotting a spectrum as discrete columns
			Task: using a log scale
			Task: compare energy and photon spectral units
			Task: annotating peaks and valleys in spectra
		Annotating wavebands and wavelengths
			Task: annotate a plot with waveband names as labels
			Task: annotate a plot with waveband summary values as labels
		Using colour as data in plots
			Task: Plots using colour for the spectral data
			Task: Plots using waveband definitions
		Plotting the result of operations on spectral data
			Task: plotting effective spectral irradiance
			Task: making a bar plot of effective irradiance
			Task: plotting a spectrum using colour bars
		Task: plotting colours in Maxwell\'s triangle
			Human vision: RGB
	Radiation physics
		Packages used in this chapter
		Introduction
		Task: black body emission
Data acquisition and exchange
	Importing and exporting `R\' data
		Packages used in this chapter
		Base R
			Task: Import one spectrum from a Scale = 0.89 0.05ptcolor push gray 0color popdata.framecodeshadecolorcolor push gray 0color poptowidthheightdepth
			Task: Export one spectrum to a Scale = 0.89 0.05ptcolor push gray 0color popdata.framecodeshadecolorcolor push gray 0color poptowidthheightdepth
			Task: Import one spectrum from a Scale = 0.89 0.05ptcolor push gray 0color popmatrixcodeshadecolorcolor push gray 0color poptowidthheightdepth
			Task: Export one spectrum to Scale = 0.89 0.05ptcolor push gray 0color popmatrixcodeshadecolorcolor push gray 0color poptowidthheightdepth
			Task: Import a collection of spectra from a Scale = 0.89 0.05ptcolor push gray 0color popmatrixcodeshadecolorcolor push gray 0color poptowidthheightdepth
			Task: Export a collection of spectra to Scale = 0.89 0.05ptcolor push gray 0color popmatrixcodeshadecolorcolor push gray 0color poptowidthheightdepth
		Package `hyperSpec\'
			To `hyperSpec\'
			From `hyperSpec\'
		Package `colorSpec\'
			From `colorSpec\'
			To `colorSpec\'
		Package `pavo\'
			From `pavo\'
		Packages `fda\' and `fda.usc\'
	Importing and exporting `foreign\' data
		Introduction
		Packages used in this chapter
		Reading and writing common file formats
			Task: Read and write spectra from text files
			Task: Read a spectrum from an Excel workbook
		Reading instrument-output files
			Task: Import data from Ocean Optics instruments and software
			Task: Import data from Avantes instruments and software
			Task: Import data from Macam instruments and software
			Task: Import data from LI-COR instruments and software
			Task: Import data from Bentham instruments and software
	Data acquisition from within R
		Introduction
		Packages and other software used in this chapter
		Adcquiring spectra with Ocean Optics spectrometers
			Task: Acquiring raw-counts data from Ocean Optics spectrometers
			Task: Acquiring spectral irradiance with Ocean Optics spectrometers
			Task: Acquiring spectral transmittance with Ocean Optics spectrometers
			Task: Acquiring spectral reflectance with Ocean Optics spectrometers
			Task: Acquiring spectral absorptance with Ocean Optics spectrometers
		sglux spectrometers and sensors
			Task: Acquiring spectral data with sglux instrument
		YoctoPuce modules
			Task: Acquiring data with YoctoPuce modules and servers
	Calibration
		Task: Calibration of broadband sensors
		Task: Correcting for non-linearity of sensor response
		Task: Applying a spectral calibration to raw spectral data
		Task: Wavelength calibration and peak fitting
	Simulation
		Task: Running TUV in batch mode
		Task: Importing into R simulated spectral data from TUV
		Task: Running libRadtran in batch mode
		Task: Importing into R simulated spectral data from libRadtran
Catalogue of example data
	Radiation sources
		Packages used in this chapter
		Introduction
		Data: extraterrestrial solar radiation spectra
		Data: terrestrial solar radiation spectra
		Data: radiation within plant canopies
		Data: radiation in water bodies
		Data: lamps
		Data: LEDs
	Optical properties of inanimate objects
		Packages used in this chapter
		Introduction
		Data: spectral transmittance of filters, glass, plastic sheets and films
		Data: spectral reflectance of materials and objects
	Example data for organisms
		Packages used in this chapter
		Introduction
		Plants
			Data: Optical properties of organs
			Data: Photoreceptors
			Data: Photosynthesis
			Data: Mass pigments and other metabolites
		Animals, including humans
			Data: Surface properties of organs
			Data: Photoreceptors
			Data: Light driven synthesis
			Data: Damage
			Data: Metabolites
		Microbes
			Data: Photoreceptors
			Data: Light driven synthesis
			Data: Damage
			Data: Metabolites
	Further reading
		Radiation physics
		Photochemistry
		Photobiology
		Using R
		Programming in R
	Bibliography
Appendix
	Build information
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