library(PPBstats)
data("data_model_GxE") data_model_GxE = format_data_PPBstats(data_model_GxE, type = "data_agro")
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") 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.
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