inst/tests/test-getpibootstrap.r

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

context("get.pi.bootstrap")

test_that("get.pi.boostrap runs and returns 1 when it should", {

    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.pi.bootstrap(x, test, seq(10,100,10), seq(0,90,10), 20)[,-(1:2)]
    expect_that(sum(res!=1),equals(0))
    expect_that(ncol(res),equals(20))

})


test_that("get.pi.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.pi.bootstrap(x, test, seq(15,45,15), seq(0,30,15), 20)[,-(1:2)]

    set.seed(787)
    ci1 <- get.pi.ci(x, test, seq(15,45,15), seq(0,30,15), 20)[,4:5]

    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.pi.bootstrap(x, test, 1.5, 0.1, 500)[,-(1:2)]
    res2 <- get.pi.typed.bootstrap(x, 1,2, 1.5, 0.1, 500)[,-(1:2)]

    #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(0,1)))
    expect_that(as.numeric(quantile(res2[1,], probs=c(.025,.975), na.rm=T)),
                equals(c(0,1)))


})

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 2,1,0
    res <- get.pi.bootstrap(x, test, c(1.5,2.5,3.5), c(0,1.5,2.5), 500)[,-(1:2)]
    res2 <- get.pi.typed.bootstrap(x, 1, 2, c(1.5,2.5,3.5), c(0,1.5,2.5), 500)[,-(1:2)]

    expect_that(median(as.numeric(res[1,]), na.rm=T), equals(1))
    expect_that(median(as.numeric(res[2,]), na.rm=T), equals(0.5))
    expect_that(median(as.numeric(res[3,]), na.rm=T), equals(0))

    expect_that(median(as.numeric(res2[1,]), na.rm=T), equals(1))
    expect_that(median(as.numeric(res2[2,]), na.rm=T), equals(0.5))
    expect_that(median(as.numeric(res2[3,]), na.rm=T), equals(0))


    #FIRST RANGE
    #deterministically 1
    expect_that(as.numeric(quantile(res[1,], probs=c(.025,.975), na.rm=T)),
                equals(c(1,1)))
    expect_that(as.numeric(quantile(res2[1,], probs=c(.025,.975), na.rm=T)),
                equals(c(1,1)))

    #SECOND RANGE...should be 0 and 1 respectively a fairly large % of the time
    expect_that(as.numeric(quantile(res[2,], probs=c(0.025,.975), na.rm=T)),
                equals(c(0,1)))
    expect_that(as.numeric(quantile(res2[2,], probs=c(.025,.975), na.rm=T)),
                equals(c(0,1)))

    #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.pi.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.pi.ci(x,test,seq(10,50,10), seq(0,40,10),100),
                throws_error("unique x and y columns must be defined"))
})


##################DEPRECATED TESTS...TAKE TO LONG...NOW USING SMALLER CANONICAL
##################TESTS THAT HAVE VALUES THAT CAN BE WORKED OUT BY HAND



## test_that("CIs calculated from get.pi.bootstrap include the true value", {
##     set.seed(787)

##     x<-cbind(rep(c(1,2),250), x=runif(500,0,100), y=runif(500,0,100))

##     colnames(x) <-c("type","x","y")

##     test <- function(a,b) {
##         if (a[1] != 1) return(3)
##         if (b[1] == 1) return(1)
##         return(2)
##     }

##     res <- get.pi.ci(x, test, seq(10,100,10), seq(0,90,10), 100)

##     expect_that(sum(!(res[1,]<res[2,])),equals(0))
##     expect_that(sum(!(res[1,]<.5)),equals(0))
##     expect_that(sum(!(res[2,]>.5)),equals(0))
## })