Difference between revisions of "Diversity index"

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m (Answer)
Line 18: Line 18:
 
data <- opasnet.csv("5/54/Tigre-data.csv", wiki = "opasnet_en", sep = ",")
 
data <- opasnet.csv("5/54/Tigre-data.csv", wiki = "opasnet_en", sep = ",")
 
data <- data[data$Species != 1 & data$Individuals != 0, ]
 
data <- data[data$Species != 1 & data$Individuals != 0, ]
head(data)
+
#head(data)
 
species <- data$Species
 
species <- data$Species
 
amount <- data$Individuals
 
amount <- data$Individuals
Line 38: Line 38:
 
return(true(pi, c(0, 1, 2, 999)))
 
return(true(pi, c(0, 1, 2, 999)))
 
}
 
}
 
truelist(c(0.2, 0.2, 0.1, 0.4, 0.1))
 
  
 
true2 <- function(divj, wj){
 
true2 <- function(divj, wj){
q <- c(rep(0, length(wj)), rep(1, length(wj)), rep(2, length(wj)), rep(999, length(wj)))
+
q <- rep(c(0, 1, 2, 999), each = length(wj))
 
wj <- rep(wj, times = 4)
 
wj <- rep(wj, times = 4)
     qDa <- ifelse(q == 1, exp(sum(wj * log(divj))), (sum(wj * divj^(1-q)))^1/(1 - q))
+
#print(divj)
 +
#print(wj)
 +
#print(q)
 +
     qDa <- ifelse(q == 1, exp(sum(wj * log(divj))), (sum(wj * divj^(1-q)))^(1/(1 - q)))
 
minqDj <- tapply(qDa, q, min)
 
minqDj <- tapply(qDa, q, min)
 
qDa <- tapply(qDa, q, sum)
 
qDa <- tapply(qDa, q, sum)
Line 56: Line 57:
 
     pij <- as.data.frame(as.table(tapply(amount, data.frame(Transect = transect, Species = species), sum)))
 
     pij <- as.data.frame(as.table(tapply(amount, data.frame(Transect = transect, Species = species), sum)))
 
     pij[is.na(pij)] <- 0
 
     pij[is.na(pij)] <- 0
head(pij)
+
#head(pij)
 
colnames(pij)[3] <- "pij"
 
colnames(pij)[3] <- "pij"
  
Line 62: Line 63:
 
pij <- pij[pij$pij != 0, ]
 
pij <- pij[pij$pij != 0, ]
  
head(pij)
+
#head(pij)
 
wj <- as.data.frame(as.table(tapply(pij$pij, pij$Transect, sum)))
 
wj <- as.data.frame(as.table(tapply(pij$pij, pij$Transect, sum)))
head(wj)
+
#head(wj)
 
colnames(wj) <- c("Transect", "wj")
 
colnames(wj) <- c("Transect", "wj")
 
out <- merge(pij, wj)
 
out <- merge(pij, wj)
sum(out$pij)
+
#sum(out$pij)
sum(tapply(out$wj, out$Transect, max))
+
#sum(tapply(out$wj, out$Transect, max))
head(out)
+
#head(out)
 
out <- tapply(out$pij, out$Transect, truelist)
 
out <- tapply(out$pij, out$Transect, truelist)
  
# truelist WORKS NOW!
+
#head(out)
 
 
head(out)
 
 
qDj <- data.frame(Zero = 1:nrow(wj), One = NA, Two = NA, Infi = NA)
 
qDj <- data.frame(Zero = 1:nrow(wj), One = NA, Two = NA, Infi = NA)
 
for(i in 1:nrow(wj)){
 
for(i in 1:nrow(wj)){
 
qDj[i,] <- out[[i]][1:4]
 
qDj[i,] <- out[[i]][1:4]
 
}
 
}
 +
#qDj
 
qDj <- c(qDj$Zero, qDj$One, qDj$Two, qDj$Infi)  
 
qDj <- c(qDj$Zero, qDj$One, qDj$Two, qDj$Infi)  
 +
#qDj
 +
#wj
 +
qDa <- true2(qDj, wj$wj)
  
true2(qDj, wj$wj)
+
out <- data.frame(Name = c("Alpha diversity with q=0", "Alpha diversity with q=1", "Alpha diversity with q=2", "Alpha diversity with q=∞", "True diversity with q=0", "True diversity with q=1",  
 
 
out <- data.frame(Name = c("True diversity with q=0", "True diversity with q=1",  
 
 
     "True diversity with q=2", "True diversity with q=∞", "Richness", "Shannon index",  
 
     "True diversity with q=2", "True diversity with q=∞", "Richness", "Shannon index",  
 
     "Simpson index", "Inverse Simpson index", "Gini-Simpson index", "Berger-Parker index"),  
 
     "Simpson index", "Inverse Simpson index", "Gini-Simpson index", "Berger-Parker index"),  
     Symbol = c("0D", "1D", "2D", "∞D", "S", "H' or log(1D)", "λ or 1/(2D)", "1/λ or 2D",  
+
     Symbol = c("0Da", "1Da", "2Da", "∞Da", "0D", "1D", "2D", "∞D", "S", "H' or log(1D)", "λ or 1/(2D)", "1/λ or 2D",  
 
     "1-λ or 1-1/(2D)", "1/(∞D)"),
 
     "1-λ or 1-1/(2D)", "1/(∞D)"),
     Value = c(true(pi,0), true(pi,1), true(pi,2), 1/max(pi), length(pi), log(true(pi,1)),  
+
     Value = c(qDa, true(pi,0), true(pi,1), true(pi,2), 1/max(pi), length(pi), log(true(pi,1)),  
 
     1/true(pi,2), true(pi,2), 1-1/true(pi,2), max(pi)))
 
     1/true(pi,2), true(pi,2), 1-1/true(pi,2), max(pi)))
 
#return(out)
 
#return(out)

Revision as of 13:18, 8 January 2012



Question

How to calculate diversity indices?

Answer

Upload your data to Opasnet Base. Use the function diversity to calculate the most common indices.

Actual function diversity

+ Show code

Example to use function

Give your data in R format or leave empty for example data:

Is your data individual data or group abundancies?:

+ Show code

The data should be given in R format as a list of values in parenthesis, beginning with c:

c(3,5,3,5,2,1,3,3,4,2) or equivalently c(0.1,0.2,0.4,0.1,0.2)

where the values are either

  • identifiers of the species 1,2,3... in which the individuals belong (one entry per individual), or
  • abundancies of species, i.e. proportions of individuals belonging to each species among the whole population (one entry per species).

Rationale

Diversity indices are thoroughly described in Wikipedia.

See also

References


Related files

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