Merge branch 'betereTabellen' into 'master'

Changed and added tables.

See merge request !14

Dockerfile

-FROM ubuntu:22.10 AS base
+FROM ubuntu:22.04 AS base
 RUN apt-get update && DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt-get install -y --no-install-recommends r-base-core && apt-get clean
 
 FROM base AS libraries

code.R

@@ -24,6 +24,17 @@ doId <- function(input) {
   appendPlot <- function(item) {
     appendPlotly(ggplotly(item))
   }
+  lettergrootte=18
+  regelhoogte=23
+  plot_tabel<-function(input_tabel){
+    kolombreedte=unname(sapply(input_tabel, function(x) max(nchar(as.character(x)))))
+    kolombreedte2=nchar(colnames(input_tabel))
+    kolombreedte_totaal=pmax(kolombreedte, kolombreedte2)
+    tabel_als_plot<-plot_ly(type = 'table', columnwidth=kolombreedte_totaal,
+                            header = list(values=colnames(input_tabel),font=list(size=lettergrootte)),
+                            cells = list(values =t(input_tabel),font=list(size=lettergrootte), height=regelhoogte))
+  return(tabel_als_plot)}
+
   dates_to_drop=as.list(strsplit(dates_to_drop, ","))[[1]]
   dates_to_drop=strptime(dates_to_drop, format="%Y-%m-%d")
   dates_to_drop=ymd(dates_to_drop)
@@ -75,27 +86,29 @@ doId <- function(input) {
   bron <-bron[order(bron$date),]
   bron$city=trimws(gsub('\\s+', ' ',gsub("-|'", ' ', str_replace_all(bron$city, "\\s", " "))))
   bron$city<-paste(toupper(substr(bron$city, 1, 1)), substr(bron$city, 2, nchar(bron$city)), sep="")
-  zonder_split <- bron[bron$ranking != "Split",]
+  zonder_split <- bron[bron$ranking != "Split",]#So even if your splittime is a Pb, it is not displayed by this application.
   bovennul<-zonder_split[zonder_split$points !=0,]
 
   DateAndPool<-bron %>%select('city', 'MeetId', 'date') %>%unique() %>% select('city', 'date')
   DateAndPool<-DateAndPool[order(DateAndPool$date),]
-  freqtabel=as.data.frame(table(DateAndPool$city))
-  freqtabel=freqtabel[order(freqtabel$Freq, decreasing=TRUE),]
-  kolombreedte=unname(sapply(freqtabel, function(x) max(nchar(as.character(x)))+5))
-  freqtabel_plot<-plot_ly(type = 'table', columnwidth=kolombreedte,
-                          cells = list(values =t(as.matrix(unname(freqtabel))), align='left',
-                                       font=list(size=16))) %>%
-        layout(title = 'Number of meets par city')
-  appendPlotly(freqtabel_plot)
-
   plotfreq=DateAndPool %>% group_by(city) %>% mutate(count=row_number())
+  tussentabel=plotfreq %>% group_by(city) %>% filter(count==max(count))
+  tussentabel$date=max(plotfreq$date)
+  plotfreq=rbind(plotfreq, tussentabel)
   CountsParPool_dates=ggplot(plotfreq, aes(x=date, y=count, color=city))+geom_step()+
     labs(title='Cumulative number of meets par city')
   CountsParPool_dates<-ggplotly(CountsParPool_dates, dynamicTicks=TRUE)
   appendPlotly(CountsParPool_dates)
 
+  freqtabel=tussentabel%>%select(c('city', 'count'))
+  freqtabel=freqtabel[order(freqtabel$count, decreasing=TRUE),]
+  freqtabel_plot=plot_tabel(freqtabel)%>% layout(title = 'Number of meets par city')
+  appendPlotly(freqtabel_plot)
+
   CountsParAfstandSlag_dates=bron %>% group_by(AfstandSlag) %>% mutate(count=row_number())
+  tussentabel=CountsParAfstandSlag_dates%>%group_by(AfstandSlag)%>%filter(count==max(count))
+  tussentabel$date=max(CountsParAfstandSlag_dates$date)
+  CountsParAfstandSlag_dates=rbind(CountsParAfstandSlag_dates, tussentabel)
   Plot_CountsParAfstandSlag_dates=ggplot(CountsParAfstandSlag_dates, aes(x=date, y=count, text=AfstandSlag,
                                                         color=interaction(distance, stroke, sep="m ")))+
     geom_step()+labs(color='Afstand & Slag', title='Cumulative count par distance/stroke')
@@ -135,19 +148,41 @@ doId <- function(input) {
   appendPlotly(heatmap_prs)
 
   tabel_LastEntrys<-zonder_split%>%
-    group_by(distance, stroke, poolType, Lap) %>%
+   filter(Lap==FALSE)%>%
+   group_by(distance, stroke, poolType) %>%
     filter(date == max(date, na.rm=TRUE))
 
-  tabel_lastswam=tabel_LastEntrys%>%select(c('distance', 'stroke', 'poolType', 'date', 'Lap'))
-  kolombreedte=unname(sapply(tabel_lastswam, function(x) max(nchar(as.character(x)))+5))
-  plottabel_LastSwam=plot_ly(type='table', columnwidth=kolombreedte,
-                             header = list(values=colnames(tabel_lastswam),font=list(size=16)),
-                             cells=list(values=t(tabel_lastswam[order(tabel_lastswam$date),]),
+  for (pooltype_loop in unique(tabel_LastEntrys$poolType)){
+    title_plot=paste("Last date swam - ", pooltype_loop, 'pool')
+    heatmap_lastswam=ggplot(tabel_LastEntrys[tabel_LastEntrys$poolType==pooltype_loop,],
+                            aes(distance, stroke, text=date)) +
+    geom_tile(aes(fill = date)) + geom_text(aes(label = format(date, format="%e %b\n%Y")), size=4) +
+      labs(title = title_plot)+  theme_bw()
+    heatmap_lastswam=ggplotly(heatmap_lastswam, tooltip=FALSE)%>%
+      layout(dragmode=FALSE)
+  appendPlotly(heatmap_lastswam)
+  }
+  tabel_lastswam=tabel_LastEntrys%>%select(c('distance', 'stroke', 'poolType', 'date'))
+  kolombreedte=unname(sapply(tabel_lastswam, function(x) max(nchar(as.character(x)))))
+  kolombreedte2=nchar(colnames(tabel_lastswam))
+  kolombreedte_totaal=pmax(kolombreedte, kolombreedte2)
+  plottabel_LastSwam=plot_ly(type='table', columnwidth=kolombreedte_totaal,
+                             header = list(values=colnames(tabel_lastswam),font=list(size=lettergrootte)),
+                             cells=list(values=t(tabel_lastswam),
                                         fill= list(color = list(kleurenset_pooltypes[tabel_lastswam$poolType])),
-                                        align='left',
-                                        font=list(size=16)))
-  plottabel_LastSwam<-plottabel_LastSwam %>% layout(title='Last swam par distance and pooltype')
+                                        align=c('right', 'middle', 'middle', 'middle'),
+                                        height=regelhoogte,
+                                        font=list(size=lettergrootte)))
+  plottabel_LastSwam<-plottabel_LastSwam%>% layout(title='Last swam par distance and pooltype - no Laptimes')
+  appendPlotly(plottabel_LastSwam)
+
+  for (pooltype_loop in unique(tabel_LastEntrys$poolType)){
+    title_plot=paste("Last swam par distance and stroke - no Laptimes' - ", pooltype_loop, 'pool')
+    tabel_lastswam=tabel_LastEntrys[tabel_LastEntrys$poolType==pooltype_loop,]%>%ungroup()
+    tabel_lastswam=tabel_lastswam%>%select(c('distance', 'stroke', 'date'))
+    plottabel_LastSwam<-plot_tabel(tabel_lastswam)%>% layout(title=title_plot)
   appendPlotly(plottabel_LastSwam)
+  }
 
   breedte_perslag=unique(tabel_Prs_metpooltype[, c('distance', 'stroke')]) %>% group_by(stroke) %>%count()
   breedte_perslag=breedte_perslag$n
@@ -171,7 +206,7 @@ doId <- function(input) {
   tabel_lasts=tabel_LastEntrys[order(tabel_LastEntrys$poolType),]%>%filter(points!=0)
   facetwrap_lasts=tabel_lasts %>% split(.$stroke) %>%map(barplot_facets)
   facetwrap_lasts=facetwrap_lasts %>% subplot(widths=breedte_perslag, margin=0.01, shareY=TRUE) %>%
-    layout(showlegend=FALSE, dragmode=FALSE, title='Last entrys. Points >0, so no laptimes, 25m-times, disqualifiactions etc.')
+    layout(showlegend=FALSE, dragmode=FALSE, title='Last entrys. Only points >0, and no laptimes.')
   appendPlotly(facetwrap_lasts)
 
   stippenplot_sizes<-ggplot(bovennul, aes(x=date, y=points, color=stroke, size=distance, group=AfstandSlag))+