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View Code? Open in Web Editor NEWA R package for Participatory Plant Breeding statisticial analyses
Home Page: https://priviere.github.io/PPBstats_web_site/
A R package for Participatory Plant Breeding statisticial analyses
Home Page: https://priviere.github.io/PPBstats_web_site/
one plot per cluster/group ?
label for one group + points ?
see shinemas2R::get.table
to get inspiration
cf old R code + vignette:
2.1. barplot_variation_repartition ----------
dtmp = data.frame()
for(i in 1:length(out_ammi)){
d = out_ammi[[i]]$ANOVA$variability_repartition$data
d = cbind.data.frame(names(out_ammi)[i], d)
dtmp = rbind.data.frame(dtmp, d)
}
colnames(dtmp)[1] = "var"
p = ggplot(dtmp, aes(x = var, y = percentage_Sum_sq)) + geom_bar(stat = "identity", aes(fill = factor))
p = p + ylab("pourcentage de variation") + theme(axis.text.x = element_text(angle = 90))
cbbPalette <- c("#000000", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
barplot_variation_repartition = p + scale_fill_manual(values = cbbPalette)
\subsubsection{Post AMMI analysis}
\paragraph{Repartition of the variation for each variable}
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$barplot_variation_repartition
@
\paragraph{Germplasm effects}
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_G_effect$variation_dim
@
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_G_effect$ind
@
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_G_effect$var
@
\paragraph{Variance intra germplasm effects}
<<message=TRUE,cache=FALSE>>=
p1 = ammi$Post_AMMI$PCA_intraG_effect$variation_dim
p2 = ammi$Post_AMMI$PCA_intraG_effect$ind
p3 = ammi$Post_AMMI$PCA_intraG_effect$var
grid.arrange(p1, p2, p3, ncol=3, nrow=1)
@
\paragraph{Location effects}
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_E_effect$variation_dim
@
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_E_effect$ind
@
<<message=TRUE,cache=FALSE>>=
ammi$Post_AMMI$PCA_E_effect$var
@
put color for estimated and non estimated => cf get_ggplot, it seems ok before
When I get.PPBsttats.data()
it downloads a bunch of 818-byte RData files, which are really plain text, all with the same HTML content:
<!DOCTYPE html>
<html>
<head><meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>Dropbox - 403</title>
<link href="https://cfl.dropboxstatic.com/static/css/error.css" rel="stylesheet" type="text/css"/>
<link rel="shortcut icon" href="https://cfl.dropboxstatic.com/static/images/favicon.ico"/>
</head>
<body>
<div class="figure">
<img src="https://cfl.dropboxstatic.com/static/images/lockbox.png" alt="Error: 403"/>
</div>
<div id="errorbox">
<h1>Error (403)</h1>It seems you don't belong here! You should probably <b><a href="https://www.dropbox.com/login">sign in</a></b>. Check out our <a href="https://www.dropbox.com/help">Help Center</a> and <a href="https://forums.dropbox.com">forums</a> for help, or head back to <a href="https://www.dropbox.com/home">home</a>.
</div>
</body>
</html>
Which is, on the other hand, the same thing I get when I manually try to download a file directly from the dropbox:
https://dl.dropboxusercontent.com/s/6qvl515k5484zg4/comp.mu.RData
Either the files are no longer there, or they are not anymore publicly available.
create a data set data_model_variance_intra
model_variance_intra.R
:
check_model.model_variance_intra.R
:
check_model.R
plot.check_model_model_variance_intra.R
check_model.model_variance_intra.R
is okplot.PPBstats
mean_comparisons.check_model_variance_intra.R
check_model.model_variance_intra.R
is okdata
per x
library(qdapRegex)
useful ?mean_comparisons
create a function plot.mean_comparisons_model_variance_intra.R
plot.PPBstats
check and update vignette
cf https://github.com/stefano-meschiari/latex2exp for more details
create a standard input format : look at shinemas2R::is.get.data.output.R and appendix D of the vignette of shinemas2R
reformat code from shinemas2R functions
shinemas2R::get.ggplot.R & shinemas2R::get.ggplot_hide.labels.part.R that may be useful if we keep the format of the seed lots GERMPLASM_LOCATION_YEAR_DIGIT
shinemas2R::get.ggplot_plot.network.R and shinemas2R::get.ggplot_ggnet.custom.R
But see https://briatte.github.io/ggnetwork/ => maybe better to go from here and
forget shinemas2R::get.ggplot_plot.network.R and shinemas2R::get.ggplot_ggnet.custom.R functions ?
shinemas2R::get.ggplot_network.relation.barplot.R
shinemas2R::get.ggplot_network.relation.map.R
pie on network or map : reformat code from shinemas2R function shinemas2R::get.ggplot_pie.on.ggplot
But maybe forgot it and look at other solutions :
http://stackoverflow.com/questions/10368180/plotting-pie-graphs-on-map-in-ggplot
http://rgraphgallery.blogspot.fr/2013/04/rg-plot-pie-over-google-map.html
https://qdrsite.wordpress.com/2016/06/26/pies-on-a-map/
it is correct ? because it is not possible to compare entry that are not on the same plot => put one color per group ?
shinemas2R
:
translate.data()
encrypt.data()
data_agro_version
to dop_out_check_model_1_bis = plot(out_check_model_1_bis)
, bug in the titleSome elements to start :
https://stackoverflow.com/questions/15875786/dynamically-add-plots-to-web-page-using-shiny
https://stackoverflow.com/questions/32968119/r-shiny-build-links-between-apps
https://shiny.rstudio.com/articles/persistent-data-storage.html
https://shiny.rstudio.com/reference/shiny/latest/downloadButton.html
https://stackoverflow.com/questions/31686773/shiny-dynamic-number-of-output-elements-plots
https://stackoverflow.com/questions/21465411/r-shiny-passing-reactive-to-selectinput-choices
How to implement workflow step by step ?
1 tab set or nav list per step of analysis
ecovalence add that is on gxe + résiduals
in appendices : example with apply and a vector of variables for GxE for example
add decision tree from Isabelle
differenciate memory needed for the different analyses
add function for AMMI and GGE analysis
This is useful for balanced data
Therefore change the vignette with two part: balanced and not balanced (make a function that say is it is balanced or not and advice an analysis? cf experimental_design in analysis.output
make it on rank
cf SpATS package
create sub-function that are called into PPBstats::describe_data, maybe go throught get_ggplot directly as it is only plot ? With the data in argument
describe_data_network :
create a standard input format : look at shinemas2R::is.get.data.output.R and appendix D of the vignette of shinemas2R
reformat code from shinemas2R functions
shinemas2R::get.ggplot.R & shinemas2R::get.ggplot_hide.labels.part.R that may be useful if we keep the format of the seed lots GERMPLASM_LOCATION_YEAR_DIGIT
shinemas2R::get.ggplot_plot.network.R and shinemas2R::get.ggplot_ggnet.custom.R
But see https://briatte.github.io/ggnetwork/ => maybe better to go from here and
forget shinemas2R::get.ggplot_plot.network.R and shinemas2R::get.ggplot_ggnet.custom.R functions ?
shinemas2R::get.ggplot_network.relation.barplot.R
shinemas2R::get.ggplot_network.relation.map.R
pie on network or map : reformat code from shinemas2R function shinemas2R::get.ggplot_pie.on.ggplot
But maybe forgot it and look at other solutions :
http://stackoverflow.com/questions/10368180/plotting-pie-graphs-on-map-in-ggplot
http://rgraphgallery.blogspot.fr/2013/04/rg-plot-pie-over-google-map.html
https://qdrsite.wordpress.com/2016/06/26/pies-on-a-map/
describe_data_agro :
nb iteration = 100 000 with speed ?
get.PPBsttats.data()
: use GitHub's releases (or pages) to download the RData instead of dropbox
update 3.1.1 Workflow and function relations in PPBstats regarding agronomic analysis
update 3.2.1 Analysis carry out in PPBstats
fill 3.7.1 Family of analysis 3 : effects from family 1 and 2 in a network of farms model 3
calculate it with the sum of the two first dim of PCA to avoid residuals : update code + vignette
write Rd
delete library(qdapRegex) and update DESCRIPTION and NAMESPACE files
get_ggplot()
could be turned into a plot()
method if classes were used
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