phenoevo.heatmap: Heatmap showing population average of custom variable in many...

In jessicaaudreylee/PhenoEvoR: Tools for analysis of NetLogo Pheno-Evo model results

Description

This plot shows three dimensions of data: two experimental parameters (for instance, toxin concentration and diffusion rate) as axes, and the population average of any trait of choice as color gradient from white to black. It is a snapshot of several experiments from a parameter sweep, at a single timepoint.

Usage

phenoevo.heatmap(ends.df, xvar, yvar, gradientvar)

Arguments

ends.df	Dataframe of endpoint data, generated by extract.endpoint().
xvar	Experimental parameter for plotting on x-axis. Must be a column name of ends.df, with no quotation marks.
yvar	Experimental parameter for plotting on y-axis. Must be a column name of ends.df, with no quotation marks.
gradientvar	Variable to be expressed as color gradient in heat map fill. Must be the name of a column in ends.df containing population-mean data.

Details

To calculate the population mean for your trait of choice, use [summarize.endpoint()] As with other endpoint-summary plots, this function can be used with data from any timepoint, as long as the ends.df dataframe contains data from only one timepoint per run number. For functions designed for specific variables with pre-designated color schemes, see also [degrade.rate.heatmap()], [switch.rate.heatmap()], [response.error.heatmap()], [generation.heatmap()], and [survival.heatmap()].

Value

A ggplot object using geom_tile. This can be modified in the typical ggplot way by adding layers, scales, etc.

Examples

data(PE.ends)
phenoevo.heatmap(PE.ends, toxin.conc, env.noise, mean.response.error)

jessicaaudreylee/PhenoEvoR documentation built on Sept. 7, 2020, 3:50 a.m.