library(PPBstats)
data("data_model_GxE")
data_model_GxE = format_data_PPBstats(data_model_GxE, type = "data_agro")
## data has been formated for PPBstats functions.
vec_locations = levels(data_model_GxE$location)
list_hist_locations = lapply(
vec_locations, function(x){
p = plot(
data_model_GxE, plot_type = "histogramm",
vec_variables = c("y1")
)
p$y1
}
)
names(list_hist_locations) = vec_locations
Note that it is important that each element of the list refers to data of a given location in order to catch the right information in the next step when generating the report.
The function workflow_gxe()
is coming from the book here.
workflow_gxe = function(x, gxe){
out_gxe = model_GxE(data_model_GxE, variable = x, gxe_analysis = gxe)
out_check_gxe = check_model(out_gxe)
p_out_check_gxe = plot(out_check_gxe)
out_mean_comparisons_gxe = mean_comparisons(out_check_gxe, p.adj = "bonferroni")
p_out_mean_comparisons_gxe = plot(out_mean_comparisons_gxe)
out_biplot_gxe = biplot_data(out_check_gxe)
p_out_biplot_gxe = plot(out_biplot_gxe)
out = list(
"out_gxe" = out_gxe,
"out_check_gxe" = out_check_gxe,
"p_out_check_gxe" = p_out_check_gxe,
"out_mean_comparisons_gxe" = out_mean_comparisons_gxe,
"p_out_mean_comparisons_gxe" = p_out_mean_comparisons_gxe,
"out_biplot_gxe" = out_biplot_gxe,
"p_out_biplot_gxe" = p_out_biplot_gxe
)
return(out)
}
vec_variables = c("y1")
res_gge = lapply(vec_variables, workflow_gxe, "GGE")
## GGE model done for y1
names(res_gge) = vec_variables
res = list("hist_locations" = list_hist_locations,
"res_gge" = res_gge
)
To generate the report, you need the R
package rmarkdown
installed. In the following example, the output is .html
. You can choose .pdf
or .docx
. See ?rmarkdown::render
for more information.
Note that the template calls two objects:
params
which is list with parameter of the reportres
which is a list with all results coming from the analysisThe template used below can be download here.
library(rmarkdown)
vec_locations = names(res$hist_locations)
for (location in vec_locations){ # For each location, render a report
params = list("title" = paste("Agronomic analyses for", location))
rmarkdown::render("_example_1_template.Rmd",
output_file = paste("example_1_report_", location, ".html", sep = ""),
output_dir = "./"
)
}
The report generated can be visualized for loc-1, loc-2 and loc-3.