library (hypervolume)

datos <- read.csv("/Data_Hypervolumen.csv")
head (datos)
datos <-datos[2:5] 
#data <-datos[3:5] 

tucuquere = as.data.frame(na.omit(datos))
tucuquere_Season = tucuquere[tucuquere$Season=="Autumn",
                                 c("Weight","length","Width")]

hv = hypervolume_box(datos,name='Autumn')

new_points = data.frame(bill_length_mm=c(0,38), bill_depth_mm=c(0,18),flipper_length_mm=c(0,190))

probs <- hypervolume_estimate_probability(hv, points=new_points)
probs

head (datos)

hv = hypervolume_gaussian(data=subset(tucuquere, Season=="Summer")[2:4],name='Summer')
summary(hv)


varimp = hypervolume_variable_importance(hv,verbose=FALSE)
barplot(varimp,ylab='Importance',xlab='Variable')

## 2D
plot(hv, show.3d=FALSE)

## 3D

plot(hv, show.3d=TRUE)


#### hypervolume_overlap_statistics

hv1 = hypervolume_gaussian(subset(tucuquere, Season=="Autumn")[,2:4])
hv2 = hypervolume_gaussian(subset(tucuquere, Season=="Winter")[,2:4])
hv3 = hypervolume_gaussian(subset(tucuquere, Season=="Spring")[,2:4])
hv4 = hypervolume_gaussian(subset(tucuquere, Season=="Summer")[,2:4])

hv_set <- hypervolume_set(hv1,hv2, check.memory=FALSE)
hypervolume_overlap_statistics(hv_set)

hv_set2 <- hypervolume_set(hv3,hv4, check.memory=FALSE)
hypervolume_overlap_statistics(hv_set2)

hv_set3 <- hypervolume_set(hv2,hv4, check.memory=FALSE)
hypervolume_overlap_statistics(hv_set3)