# tests/testthat/test-smooth.R In pROC: Display and Analyze ROC Curves

```library(pROC)
data(aSAH)

context("smooth")

# Define some density functions

unif.density <- function(x, n, from, to, bw, kernel, ...) {
smooth.x <- seq(from = from, to = to, length.out = n)
smooth.y <- dunif(smooth.x, min = min(x), max = max(x))
return(smooth.y)
}

norm.density <- function(x, n, from, to, bw, kernel, ...) {
smooth.x <- seq(from = from, to = to, length.out = n)
smooth.y <- dnorm(smooth.x, mean = mean(x), sd = sd(x))
return(smooth.y)
}

lnorm.density <- function(x, n, from, to, bw, kernel, ...) {
smooth.x <- seq(from = from, to = to, length.out = n)
smooth.y <- dlnorm(smooth.x, meanlog = mean(x), sdlog = sd(x))
return(smooth.y)
}

test_that("We fall back to the standard smooth", {
tukey <- smooth(c(4, 1, 3, 6, 6, 4, 1, 6, 2, 4, 2))
expect_is(tukey, "tukeysmooth")
expect_equal(as.numeric(tukey), c(3, 3, 3, 3, 4, 4, 4, 4, 2, 2, 2))
})

test_that("smooth with a density function works", {
smoothed <- smooth(r.ndka, method="density", density = unif.density, n = 10)
expect_is(smoothed, "smooth.roc")
expect_equal(smoothed\$sensitivities, c(1, 1, 1, 0.875, 0.75, 0.625, 0.5, 0.375, 0.25, 0.125, 0, 0))
expect_equal(smoothed\$specificities, c(0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1))
expect_equal(as.numeric(smoothed\$auc), 0.9375)
})

test_that("smooth with two density functions works", {
smoothed <- smooth(r.ndka, method="density", density.controls = norm.density, density.cases = lnorm.density, n = 10)
expect_is(smoothed, "smooth.roc")
expect_equal(smoothed\$sensitivities, c(1, 1, 1, 0.635948942024884, 0.460070154191559, 0.344004532431686,
0.25735248652959, 0.188201024566009, 0.130658598389315, 0.0813814489619488,
0.0382893349015216, 0))
expect_equal(smoothed\$specificities, c(0, 0, 0.832138478872629, 0.99999996787709, 1, 1, 1, 1, 1, 1, 1, 1))
expect_equal(as.numeric(smoothed\$auc), 0.9694449)
})

test_that("smooth with fitdistr works", {
smoothed <- smooth(r.ndka, method="fitdistr", n = 10)
expect_is(smoothed, "smooth.roc")
expect_equal(smoothed\$sensitivities, c(1, 1, 0.65584212882921, 0.303849532306639, 0.0922807400203477,
0.017547821937714, 0.00203415264061833, 0.000141550295211778,
5.86072275643637e-06, 1.43622216786009e-07, 2.05997195401133e-09,
0))
expect_equal(smoothed\$specificities, c(0, 0, 0.961731211013412, 0.999999997253703, 1, 1, 1, 1, 1,
1, 1, 1))
expect_equal(as.numeric(smoothed\$auc), 0.814600645965216)
})

test_that("smooth with fitdistr different densities works", {
smoothed <- smooth(r.ndka, method="fitdistr", density.controls="normal", density.cases="lognormal", n = 10)
expect_is(smoothed, "smooth.roc")
expect_equal(smoothed\$sensitivities, c(1, 1, 0.174065394158716, 0.0241224684680268, 0.00565556180305715,
0.0017644346804079, 0.000654794610631603, 0.000269912354252342,
0.000116632088037343, 4.89426737202444e-05, 1.6544031070368e-05,
0))
expect_equal(smoothed\$specificities, c(0, 0, 0.961731211013412, 0.999999997253703, 1, 1, 1, 1, 1,
1, 1, 1))
expect_equal(as.numeric(smoothed\$auc), 0.568359871182632)
})

test_that("smooth with fitdistr with a density function works", {
smoothed <- smooth(r.ndka, method="fitdistr", n = 10,
density.controls = dnorm, start.controls = list(mean = 10, sd = 10),
density.cases = dlnorm, start = list(meanlog=2.7, sdlog=.822))
expect_is(smoothed, "smooth.roc")
expect_equal(smoothed\$sensitivities, c(1, 1, 0.174065542189585, 0.0241224212514905, 0.00565553823693818,
0.00176442417351747, 0.000654789746505889, 0.000269910020195159,
0.000116630962648119, 4.8942161699917e-05, 1.65438472509127e-05,
0))
expect_equal(smoothed\$specificities, c(0, 0, 0.961730914432089, 0.999999997253745, 1, 1, 1, 1, 1,
1, 1, 1))
expect_equal(as.numeric(smoothed\$auc), 0.568359799581078)
})
```

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pROC documentation built on Nov. 2, 2023, 6:05 p.m.