Spectral Irradiance Data for Lamps

Spectral emission data for some frequently used lamps including bulbs and flashlights based on led emitting diodes (LEDs) but excluding LEDs available as electronic components. Original spectral irradiance data for incandescent-, LED- and discharge lamps are included. They are complemented by data on the effect of temperature on the emission by fluorescent tubes. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) .

Spectral Transmittance and Spectral Reflectance Data

Spectral 'transmittance' data for frequently used filters and similar materials. Plastic sheets and films; photography filters; theatrical gels; machine-vision filters; various types of window glass; optical glass and some laboratory plastics and glassware. Spectral reflectance data for frequently encountered materials. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) .

Read Spectral and Logged Data from Foreign Files

Functions for reading, and in some cases writing, foreign files containing spectral data from spectrometers and their associated software, output from daylight simulation models in common use, and some spectral data repositories. As well as functions for exchange of spectral data with other R packages. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) .

Response Data for Light Sensors

Spectral response data for broadband ultraviolet and visible radiation sensors. Angular response data for broadband ultraviolet and visible radiation sensors and diffusers used as entrance optics. Data obtained from multiple sources were used: author-supplied data from scientific research papers, sensor-manufacturer supplied data, and published sensor specifications. Part of the 'r4photobiology' suite Aphalo P. J. (2015) .

Miscellaneous Extensions to 'ggplot2'

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Statistics to locate and tag peaks and valleys and to label plots with the equation of a fitted polynomial model by ordinary least squares, major axis, quantile and robust and resistant regression approaches. Line and model equation for Normal mixture models. Labels for P-value, R^2 or adjusted R^2 or information criteria for fitted models; parametric and non-parametric correlation; ANOVA table or summary table for fitted models as plot insets; annotations for multiple pairwise comparisons with adjusted P-values. Model fit classes for which suitable methods are provided by package 'broom' and 'broom.mixed' are supported as well as user-defined wrappers on model fit functions, allowing model selection and conditional labelling. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.

Grammar Extensions to 'ggplot2'

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Geometries: geom_table(), geom_plot() and geom_grob() add insets to plots using native data coordinates, while geom_table_npc(), geom_plot_npc() and geom_grob_npc() do the same using "npc" coordinates through new aesthetics "npcx" and "npcy". Statistics: select observations based on 2D density. Positions: radial nudging away from a center point and nudging away from a line or curve; combined stacking and nudging; combined dodging and nudging.

Selected Utilities Extending 'ggplot2'

Selected utilities, in particular 'geoms' and 'stats' functions, extending the 'ggplot2' package. This package imports functions from 'EnvStats' by Millard (2013), 'ggpp' < https://CRAN.R-project.org/package=ggpp> by Aphalo et al. (2023) and 'ggstats' by Larmarange (2023), and then exports them. This package also contains modified code from 'ggquickeda' < https://CRAN.R-project.org/package=ggquickeda> by Mouksassi et al. (2023) for Kaplan-Meier lines and ticks additions to plots. All functions are tested to make sure that they work reliably.

General Modules for 'teal' Applications

Prebuilt 'shiny' modules containing tools for viewing data, visualizing data, understanding missing and outlier values within your data and performing simple data analysis. This extends 'teal' framework that supports reproducible research and analysis.