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library("ggplot2")
library("extraDistr")
library("pracma")
rep = "Your repository for saving plots"
imb_coef = function(y, probfunc = 'density',bdw='SJ', n_map = 100000, distfunc = 'pdf', disttype = 'cont',plot=F, p=1,k=1, w = NULL,scale=T, quad=F, save=F){
if (disttype == 'cont'){
if (scale==T) {y=(y-min(y))/(max(y)-min(y))}
min_y=min(y)
max_y = max(y)
map = seq(min_y, max_y,length.out=n_map)
if (is.null(w)){
w = rep(1,n_map)
}
else{
w = approx(y,w,xout=map, yleft = min(w[y==min_y]), yright = min(w[y==max_y]))$y
}
if (distfunc == 'pdf'){
kde_y = density(y, from=min_y, to=max_y, bw=bdw,n=n_map)
y_map = kde_y$x
kde_map = kde_y$y
kde_map[is.na(kde_map)]=0
d_best = dunif(map,min_y,max_y)
kde_x = function(x){
return(approx(kde_y$x,kde_map,xout=x)$y)
}
weight = function(x){
return(approx(map,w,xout=x)$y)
}
if (is.null(w)){
imb_ratio = round(quad(function(x) pmax(0,1-kde_x(x)), min_y, max_y,tol=1e-5),4)*100
}
else{
imb_ratio = round(quad(function(x) pmax(0,1-kde_x(x))*weight(x), min_y, max_y,tol=1e-5)/quad(function(x) weight(x), min_y, max_y,tol=1e-5),4)*100
}
if (plot == TRUE) {
df_dens <- data.frame(map = map, kde_map = kde_map, d_best = d_best)
df_hist <- data.frame(y = y)
print(
ggplot() +
geom_histogram(data = df_hist, aes(x = y, y = ..density..),
bins = 100, fill = "gray", alpha = 0.8, col = "darkblue") +
geom_line(data = df_dens, aes(x = map, y = kde_map), color = "darkred", linewidth = 1) +
geom_line(data = df_dens, aes(x = map, y = d_best), color = "darkgreen", linewidth = 1) +
ggtitle(paste(imb_ratio, "%")) +
labs(x = "map", y = "Value") +
theme(plot.title = element_text(color = "darkred", size = 20, face = "bold"))
)
if (exists("save") && save == TRUE) {
ggsave(paste0(rep, "imbMtric_dens_", k, ".png"), width = 7.29, height = 4.5)
}
}
return(imb_ratio)
}
}
else if (disttype == 'dis'){
min_y=min(y)
max_y = max(y)
map = seq(min_y,max_y,1)
if (is.null(w)){
w = rep(1,max_y-min_y+1)
}
else{
w=data.frame(map=y,w1=w)
w = aggregate(w1~map,w,mean)
temp = data.frame(map=seq(min_y,max_y),w0=rep(0,max_y-min_y+1))
temp = merge(temp,w,by="map",all.x = T)
temp[is.na(temp$w1),'w1']=0
temp['w']=temp['w0']+temp['w1']
w = aggregate(w~map,temp, mean)$w
}
if (distfunc == 'pdf'){
kde_map = data.frame(prop.table(table(y)))
prop0 = data.frame(y=map, freq0=rep(0,length(map)))
kde_map = merge(prop0, kde_map,all.x=T)
kde_map[is.na(kde_map$Freq),'Freq']=0
kde_map$Freq = kde_map$Freq + kde_map$freq0
kde_map$freq0=NULL
d_best = ddunif(map,min_y,max_y)
if (plot==T){
df <- data.frame(map = map, freq = c(data.frame(kde_map)$Freq, d_best), dist=rep(c("Emp", "Uni"), each = length(map)))
error = abs(kde_map$Freq - d_best)^p * (kde_map$Freq < d_best) * w
imb_ratio <- round(sum(error[w>0])/sum(d_best*w),4)*100
if (is.na(imb_ratio)){imb_ratio=100}
print(ggplot(df, aes(x = factor(map), y = freq, fill = dist)) +
geom_bar(stat = "identity", position = "identity", alpha = 0.5) +
scale_fill_manual(values = c("darkred", "darkgreen"))+
ggtitle(paste(imb_ratio, "%")) +
labs(x = "y", y = "Fréquence", fill = "Type") +
theme(plot.title = element_text(color="darkred", size=20, face = "bold")))
if (save==T) {ggsave(paste0(rep,"imbMtric_mass_",k,".png"),width=7.29, height=4.5)}
}
return(imb_ratio)
}
}
}
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