#' cdensplot
#'
#' \code{cdensplot} function dedicated for quick single-region data obs.
#'
#'\usage{cdensplot(x)}
#' @param x .csv file exported from Excel, see details below
#' @return
#'\describe{
#'\item{value}{ggplot showing results for each method for considered species}}
#' @details Here will be described how it works TBA
#' @export
#'
cdensplot<-function(cdens){
wyk2<- ggplot2:::ggplot(cdens, ggplot2:::aes(x=reorder(distribution,se), y=mean))+ggplot2:::geom_point(size=3)+ggplot2:::geom_segment(ggplot2:::aes(x=distribution,xend=distribution, y=mean-se, yend=mean+se))+ggplot2:::coord_flip()+ggplot2:::theme_bw()
wyk2+ggplot2:::labs(x='Method', y='Density [ind. per 1000 ha]')+ggplot2:::ylim(0,NA) }
#' dplotall
#'
#' \code{dplotall} function dedicated for plotting all species
#'
#'\usage{dplotall(x)}
#' @param x data frame containing game densities, e.g. result of \code{game.load}
#' @param name name for .pdf file which will be saved
#' @return
#'\describe{
#'\item{value}{ggplot showing results for each method for considered species}}
#' @details Here will be described how it works TBA
#' @export
#'
dplotall<-function(x, name){
ryswyk<-function(i){
dupa<-cdensplot(compdens(x[,i],x[,2]))+ggplot2:::ggtitle(colnames(x)[i])
print(dupa)
}
filnam<-paste(name, '.pdf')
pdf(filnam, paper = 'a4r')
sapply(3:ncol(x), ryswyk)
dev.off()
}
#' rysuj
#'
#' \code{rysuj} polish wrapper for plotting all species
#'
#'\usage{rysuj(x)}
#' @param file name
#' @return
#'\describe{
#'\item{value}{ggplot showing results for each method for considered species}}
#' @details Here will be described how it works TBA
#' @export
#'
rysuj<-function(x, spe=';',long=TRUE){
#load data, depndly on format
if(long==TRUE) dfram<-game.load.pl(x, sep=';') else #jak długa
dfram<- game.load(x, sep=';')
#
ryswyk<-function(i){
#wwrrite basic functions for drawing
ryswyk<-function(i){
dupa<-cdensplot(compdens(dfram[,i],dfram[,2]))+ggplot2:::ggtitle(colnames(dfram)[i])
}
pl1<-ryswyk(i)
duppa<-data.frame(obs=dfram[,i]*10)
pl2<-ggplot2:::ggplot(duppa,ggplot2:::aes(x=obs))+ggplot2:::geom_histogram(fill='gray',col='black',binwidth =50)+ggplot2:::theme_bw()+ggplot2:::labs(x='Density', y='Number of observations')
pl3<-ggplot2:::ggplot(duppa,ggplot2:::aes(x=obs))+ggplot2:::geom_density(fill='gray',col='black',adjust=2)+ggplot2:::theme_bw()+ggplot2:::labs(x='Density [ind. / 1000 ha]', y='Density function response')
library(grid)
# Move to a new page
grid:::grid.newpage()
# Create layout : nrow = 2, ncol = 2
grid:::pushViewport(grid:::viewport(layout = grid.layout(2, 2)))
# A helper function to define a region on the layout
define_region <- function(row, col){
grid:::viewport(layout.pos.row = row, layout.pos.col = col)
}
# Arrange the plots
print(pl1, vp=define_region(1, 1:2))
print(pl2, vp = define_region(2, 1))
print(pl3, vp = define_region(2, 2))
}
name<-paste('wykres_',x)
filnam<-paste(name, '.pdf')
pdf(filnam, paper = 'a4')
sapply(3:ncol(dfram), ryswyk)
dev.off()
}
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