Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ---- eval=FALSE--------------------------------------------------------------
# # Install from CRAN
# install.packages('toolStability', dependencies=TRUE)
#
# # Install development version from Github
# devtools::install_github("Illustratien/toolStability")
#
## -----------------------------------------------------------------------------
library(toolStability)
## ----plot, fig.cap = 'Example of environmental effects on wheat yield.', echo = FALSE, fig.height=4, fig.width=8, message=FALSE----
ggplot2::ggplot(Data,ggplot2::aes(x=Sites,y=Yield,col=Genotype))+
ggplot2::geom_boxplot()+
ggplot2::facet_grid(Sowing~Nitrogen,labeller =ggplot2::label_both)+
ggplot2::ylab(bquote('Wheat yield (kg' %.%'ha'^'-1'*')'))+
ggplot2::theme_test()
## -----------------------------------------------------------------------------
rm(list=ls())
library(toolStability)
### load data
data("Data")
### check the structure of sample dataset
### be sure that the trait is numeric!!!
dplyr::glimpse(Data)
### calculate ecovalence for all genotypes
single.index.ecovalence <- ecovalence(data = Data,
trait = 'Yield',
genotype = 'Genotype',
environment = 'Environment',
unit.correct = FALSE,
modify = FALSE)
### check the structure of result
dplyr::glimpse(single.index.ecovalence)
### calculate modified ecovalence for all genotypes
single.index.ecovalence.modified <- ecovalence(data = Data,
trait = 'Yield',
genotype = 'Genotype',
environment = 'Environment',
unit.correct = FALSE,
modify = TRUE)
### check the structure of result
dplyr::glimpse(single.index.ecovalence.modified)
## -----------------------------------------------------------------------------
### calculate all stability indices for all genotypes
summary.table <- table_stability(data = Data,
trait = 'Yield',
genotype = 'Genotype',
environment = 'Environment',
lambda = median(Data$Yield),
normalize = FALSE,
unit.correct = FALSE)
#### warning message means your data structure is not distributed as normal distribution
#### check the structure of result
dplyr::glimpse(summary.table)
### calculate all stability indices for all genotypes
normalized.summary.table <- table_stability(data = Data,
trait = 'Yield',
genotype = 'Genotype',
environment = 'Environment',
lambda = median(Data$Yield),
normalize = TRUE,
unit.correct = FALSE)
#### warning message means your data structure is not distributed as normal distribution
#### check the structure of result
dplyr::glimpse(normalized.summary.table)
### compare the result from summary.table and normalized.summary.table
### calculate the stability indices only based only on CO2 and Nitrogen environments
summary.table2 <- table_stability(data = Data,
trait = 'Yield',
genotype = 'Genotype',
environment = c('CO2','Nitrogen'),
lambda = median(Data$Yield),
normalize = FALSE,
unit.correct = FALSE)
#### check the structure of result
dplyr::glimpse(summary.table2)
### compare the result from summary.table and summary.table2
### see how the choice of environments affect the data
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