switch.rate.timecourse: Plot population distribution of switch.rate over time
In jessicaaudreylee/PhenoEvoR: Tools for analysis of NetLogo Pheno-Evo model results
Description
Usage
Arguments
Details
Value
Examples
View source: R/PlotNetLogoData.R
Description
Generates a heatmap displaying how the genotypic switch rate changes over the
course of a Pheno-Evo experiment. Time is displayed on the x-axis, the range
of possible switch rate values on the y-axis, and relative abundance given by
color. To reduce plot size and complexity, if the input dataframe contains
more than 1,000 timepoints, only every 10th timepoint is plotted.
Usage
1
switch.rate.timecourse(NLdata, runnum)
Arguments
NLdata
The full dataframe containing data from all BehaviorSpace
experiments at all timepoints, imported from NetLogo.
runnum
The run number of the experiment of interest.
Details
#' See also [degrade.rate.timecourse()] and [response.error.timecourse()].
Value
A ggplot object using geom_tile. This can be modified in the typical
ggplot way by adding layers, scales, etc.
Examples
1
2
data(PhenoEvoData_4)
switch.rate.timecourse(PhenoEvoData_run4, 4)
jessicaaudreylee/PhenoEvoR documentation built on Sept. 7, 2020, 3:50 a.m.
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Description Usage Arguments Details Value Examples
View source: R/PlotNetLogoData.R
Description
Generates a heatmap displaying how the genotypic switch rate changes over the course of a Pheno-Evo experiment. Time is displayed on the x-axis, the range of possible switch rate values on the y-axis, and relative abundance given by color. To reduce plot size and complexity, if the input dataframe contains more than 1,000 timepoints, only every 10th timepoint is plotted.
Usage
1 | switch.rate.timecourse(NLdata, runnum)
|
Arguments
NLdata |
The full dataframe containing data from all BehaviorSpace experiments at all timepoints, imported from NetLogo. |
runnum |
The run number of the experiment of interest. |
Details
#' See also [degrade.rate.timecourse()] and [response.error.timecourse()].
Value
A ggplot object using geom_tile. This can be modified in the typical ggplot way by adding layers, scales, etc.
Examples
1 2 | data(PhenoEvoData_4)
switch.rate.timecourse(PhenoEvoData_run4, 4)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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