inst/cec_tests/energy.calculation.test.various.data.sets.R

In CEC: Cross-Entropy Clustering

testname <- "energy calculation (various data sets)"
setup <- function()
{
    two.gausses.4d = as.matrix(read.table(system.file("cec_tests", "two.gausses.4d.data", package="CEC")))
    
    mouse3d <- as.matrix(read.table(system.file("cec_tests", "mouse3d.data", package="CEC")))
    C <- as.matrix(read.table(system.file("cec_tests", "centers3d.data", package="CEC")))
    C4 <- as.matrix(read.table(system.file("cec_tests", "centers43d.data", package="CEC")))
}

test.type.covariance <- function()
{
    given.cov = matrix(c(0.770118878, 0.005481129, -0.005991149, 0.005481129, 0.766972716, 0.008996509, -0.005991149, 0.008996509,  0.821481768), 3, 3)
    
    expected.energy <-  4.365855156
    
    CE <- cec(mouse3d, centers=C, type="cov", param = given.cov, iter.max=20)

    CEC:::checkNumericVectorEquals(expected.energy, CE$cost, msg="Energy")
}

test.type.fixedr.mixture <- function()
{
    r <- c(0.2, 0.3, 0.4) 

    expected.energy <- 4.853461033
    
    CE <- cec(mouse3d, centers=C, type=c("fi", "fi", "fi"), param = r)
    
    CEC:::checkNumericVectorEquals(expected.energy, CE$cost, msg="Energy")
}


test.type.spherical.one.cluster.removed <- function()
{  
    expected.energy <- 4.179257781
    expected.number.of.clusters <- 3
     
    CE <- cec(mouse3d, C4, type="sp")
    
    CEC:::checkNumericVectorEquals(expected.number.of.clusters, CE$nclusters, msg="Number of clusters")
    CEC:::checkNumericVectorEquals(expected.energy, CE$cost, msg="Energy")
}

test.type.diagonal.spherical.mixture <- function()
{  
    expected.energy <- 4.177793598
    expected.number.of.clusters <- 3
    
    CE <- cec(mouse3d, C, type=c("diag", "diag", "sp"))  

    CEC:::checkNumericVectorEquals(expected.number.of.clusters, CE$nclusters, msg="Number of clusters")
    CEC:::checkNumericVectorEquals(expected.energy, CE$cost, msg="Energy")
}

test.type.eigenvalues.all.fixedr.mixture <- function()
{ 
    evals1 <- c(0.8240634, 0.7739987, 0.7595220)
    evals2 <- c(0.7240634, 0.5739987, 0.3595220)
    r <- 1.0
    
    expected.energy <- 4.323007035
    expected.number.of.clusters <- 3
    
    CE <- cec(mouse3d, C4, type=c("all", "eigen", "fixedr", "eigen"), param=list(evals1, r, evals2))
    
    CEC:::checkNumericVectorEquals(expected.number.of.clusters, CE$nclusters, msg="Number of clusters")
    CEC:::checkNumericVectorEquals(expected.energy, CE$cost, msg="Energy")
}

test.type.mean.two.gaussians <- function()
{
    centers = matrix(c(2, 4, 2, 4, 2, 4, 2, 4), 2, 4)
    means.param = list(c(0, 0, 0, 0), c(5, 5, 5, 5))
    
    expected.energy = 6.142651451
    
    cec = cec(two.gausses.4d, centers, c("mean", "mean"), param=means.param)
    
    CEC:::checkNumericVectorEquals(expected.energy, cec$cost, msg="Energy")
}