Nothing
context("get.theta.bootstrap")
test_that("get.theta.boostrap runs and returns Inf when all relations are 1", {
x<-cbind(rep(c(1,2),50), x=runif(100,0,100), y=runif(100,0,100))
colnames(x) <-c("type","x","y")
test <- function(a,b) {return(1)}
#should return a matrix of all ones
res <- get.theta.bootstrap(x, test, seq(10,100,10), seq(0,90,10), 20)[,-(1:2)]
expect_that(sum(!is.infinite(as.matrix(res))), equals(0))
expect_that(ncol(res), equals(20))
})
test_that("get.theta.ci returns bootstrap cis when same seed", {
x<-cbind(rep(c(1,2),50), x=runif(100,0,100), y=runif(100,0,100))
colnames(x) <-c("type","x","y")
test <- function(a,b) {
if (a[1] != 1) return(3)
if (b[1] == 2) return(1)
return(2)
}
set.seed(787)
res <- get.theta.bootstrap(x, test, seq(15,45,15), seq(0,30,15), 20)[,-(1:2)]
set.seed(787)
ci1 <- get.theta.ci(x, test, seq(15,45,15), seq(0,30,15), 20)[,-(1:3)]
expect_that(as.numeric(ci1[1,]),
equals(as.numeric(quantile(res[1,],
probs=c(.025,.975),
na.rm=T))))
expect_that(as.numeric(ci1[2,]),
equals(as.numeric(quantile(res[2,],
probs=c(.025,.975),
na.rm=T))))
expect_that(as.numeric(ci1[3,]),
equals(as.numeric(quantile(res[3,],
probs=c(.025,.975),
na.rm=T))))
})
test_that("performs correctly for test case 1 (equilateral triangle)", {
x <- rbind(c(1,0,0), c(1,1,0),c(2,.5,sqrt(.75)))
colnames(x) <-c("type","x","y")
test <- function(a,b) {
if (a[1] != 1) return(3)
if (b[1] == 2) return(1)
return(2)
}
res <- get.theta.bootstrap(x, test, 1.5, 0.1, 500)[,-(1:3)]
res2 <- get.theta.typed.bootstrap(x, 1,2, 1.5, 0.1, 500)[,-(1:3)]
#should have 95% CI of 0,1 and mean/median of 0.5
expect_that(as.numeric(quantile(res[1,], probs=c(.025,.975), na.rm=T)),
equals(c(0,Inf)))
expect_that(as.numeric(quantile(res2[1,], probs=c(.025,.975), na.rm=T)),
equals(c(0,Inf)))
})
test_that("performs correctly for test case 2 (points on a line)", {
x<-rbind(c(1,0,0), c(2,1,0), c(2,-1,0), c(3,2,0),
c(2,-2,0), c(3,3,0),c(3,-3,0))
colnames(x) <-c("type","x","y")
test <- function(a,b) {
if (a[1] != 1) return(3)
if (b[1] == 2) return(1)
return(2)
}
#the medians for the null distribution should be 1,0.5,0
res <- get.theta.bootstrap(x, test, c(1.5,2.5,3.5), c(0,1.5,2.5), 500)[,-(1:3)]
res2 <- get.theta.typed.bootstrap(x, 1, 2, c(1.5,2.5,3.5), c(0,1.5,2.5), 500)[,-(1:3)]
expect_that(median(as.numeric(res[1,]), na.rm=T), equals(Inf))
expect_that(median(as.numeric(res[2,]), na.rm=T), equals(1))
expect_that(median(as.numeric(res[3,]), na.rm=T), equals(0))
expect_that(median(as.numeric(res2[1,]), na.rm=T), equals(Inf))
expect_that(median(as.numeric(res2[2,]), na.rm=T), equals(1))
expect_that(median(as.numeric(res2[3,]), na.rm=T), equals(0))
#FIRST RANGE
#deterministically Inf
expect_that(as.numeric(quantile(res[1,], probs=c(.025,.975), na.rm=T)),
equals(c(Inf,Inf)))
expect_that(as.numeric(quantile(res2[1,], probs=c(.025,.975), na.rm=T)),
equals(c(Inf,Inf)))
#SECOND RANGE...should be 0 and Inf respectively a fairly large % of the time
expect_that(as.numeric(quantile(res[2,], probs=c(0.025,.975), na.rm=T)),
equals(c(0,Inf)))
expect_that(as.numeric(quantile(res2[2,], probs=c(.025,.975), na.rm=T)),
equals(c(0,Inf)))
#THIRD RANGE
#deterministically 0
expect_that(as.numeric(quantile(res[3,], probs=c(.025,.975), na.rm=T)),
equals(c(0,0)))
expect_that(as.numeric(quantile(res2[3,], probs=c(.025,.975), na.rm=T)),
equals(c(0,0)))
})
test_that ("fails nicely if x and y column names are not provided", {
x<-cbind(rep(c(1,2),500), a=runif(1000,0,100), b=runif(1000,0,100))
test <- function(a,b) {
if (a[1] != 2) return(3)
if (b[1] == 3) return(1)
return(2)
}
expect_that(get.theta.bootstrap(x,test,seq(10,50,10), seq(0,40,10),100),
throws_error("unique x and y columns must be defined"))
expect_that(get.theta.ci(x,test,seq(10,50,10), seq(0,40,10),100),
throws_error("unique x and y columns must be defined"))
})
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