Nothing
data(flowers)
data(sicalis)
data(teal)
test_that("coldist", {
# JND transform
vis.flowers <- vismodel(flowers, visual = "apis")
cd.flowers <- coldist(vis.flowers, n = c(1, 1, 1))
jnd.flowers <- jnd2xyz(cd.flowers)
result1 <- jndrot(jnd2xyz(coldist(vismodel(flowers, achromatic = "bt.dc", relative = FALSE), achromatic = TRUE)))
expect_equal(dim(result1), c(36, 4))
expect_equal(round(mean(unlist(result1)^3), 3), -132.915)
# Output
result2 <- coldist(colspace(vismodel(flowers, visual = "canis", achromatic = "ml")), achromatic = TRUE)
expect_equal(dim(result2), c(630, 4))
expect_equal(round(mean(unlist(result2[,3:4])), 4), 0.8693)
result3 <- coldist(colspace(vismodel(flowers, visual = "canis", achromatic = "all")),
n = c(1, 2), achromatic = TRUE, subset = "Hibbertia_acicularis")
expect_equal(dim(result3), c(35, 4))
expect_equal(round(mean(unlist(result3[, 3:4])), 4), 0.5388)
result4 <- coldist(colspace(vismodel(flowers, visual = "apis", achromatic = "all",
relative = FALSE, vonkries = TRUE), space = "hexagon"),
n = c(1, 2), achromatic = TRUE, subset = c("Hibbertia_acicularis", "Grevillea_buxifolia"))
expect_equal(dim(result4), c(1, 4))
expect_equal(round(mean(unlist(result4[, 3:4])), 4), 0.464)
result5 <- coldist(colspace(vismodel(flowers, visual = "segment")), achromatic = TRUE)
expect_equal(dim(result5), c(630, 4))
expect_equal(round(mean(unlist(result5[, 3:4])), 4), 0.2685)
result6 <- coldist(colspace(vismodel(flowers,
visual = "cie10",
illum = "D65",
vonkries = TRUE,
relative = FALSE), "cielab"))
expect_equal(dim(result6), c(630, 4))
expect_equal(round(mean(unlist(result6[, 3])), 4), 28.7164)
result7 <- coldist(as.matrix(vismodel(flowers, achro = "bt.dc")), qcatch = "Qi", achromatic = TRUE)
expect_equal(dim(result7), c(630, 4))
expect_equal(round(mean(unlist(result7[, 3])), 4), 11.7606)
})
test_that("bootcoldist", {
# Empirical means
data(sicalis)
vm.sic <- vismodel(sicalis, visual = "apis", achromatic = "l")
gr.sic <- gsub("ind..", "", rownames(vm.sic))
bcd.sic <- suppressWarnings(bootcoldist(
vm.sic,
by = gr.sic,
n = c(1, 2, 3),
weber = 0.1,
weber.achro = 0.1
))
expect_equal(
unname(round(c(bcd.sic[, 1], bcd.sic[, 4]), 4)),
c(4.5760, 1.1340, 5.6378, 8.2510, 0.0124, 8.2387))
})
test_that("special_colspace", {
# Dispace
result8 <- colspace(vismodel(flowers, visual = "canis", achromatic = "all"))
expect_equal(dim(result8), c(36, 5))
expect_equal(round(mean(unlist(result8)), 4), 0.4061)
# Trispace
result9 <- colspace(vismodel(flowers, visual = "apis", achromatic = "l"))
expect_equal(dim(result9), c(36, 8))
expect_equal(round(mean(unlist(result9)), 4), 0.0876)
# tcs
result10 <- colspace(vismodel(flowers, visual = "bluetit", achromatic = "ch.dc"))
expect_equal(dim(result10), c(36, 17))
expect_equal(round(mean(unlist(result10)), 4), 0.0923)
# categorical
result11 <- colspace(vismodel(flowers, visual = "musca", achro = "md.r1"), space = "categorical")
expect_equal(dim(result11), c(36, 10))
expect_equal(round(mean(unlist(result11[, -7])), 4), -0.0949)
# segment
result12 <- colspace(vismodel(flowers, visual = "segment", achromatic = "bt.dc"), space = "segment")
expect_equal(dim(result12), c(36, 9))
expect_equal(round(mean(unlist(result12)), 4), 20.4668)
# coc
result13 <- colspace(vismodel(flowers, visual = "apis", relative = FALSE, qcatch = "Ei",
vonkries = TRUE, achromatic = "l"), space = "coc")
expect_equal(dim(result13), c(36, 7))
expect_equal(round(mean(unlist(result13)), 4), 0.5304)
# hexagon
result14 <- colspace(vismodel(flowers, visual = "apis", qcatch = "Ei",
vonkries = TRUE, relative = FALSE, achromatic = "l"), space = "hexagon")
expect_equal(dim(result14), c(36, 10))
expect_equal(round(mean(unlist(result14[-9])), 4), 20.3489)
# ciezyx
result15 <- colspace(vismodel(flowers, visual = "cie10"), space = "ciexyz")
expect_equal(dim(result15), c(36, 6))
expect_equal(round(mean(unlist(result15)), 4), 0.3596)
# cielab
result16 <- colspace(vismodel(flowers, visual = "cie10"), space = "cielab")
expect_equal(dim(result16), c(36, 6))
expect_equal(round(mean(unlist(result16)), 4), 9.5446)
# cielch
result17 <- colspace(vismodel(flowers, visual = "cie10"), space = "cielch")
expect_equal(dim(result17), c(36, 8))
expect_equal(round(mean(unlist(result17)), 4), 26.2162)
})
test_that("voloverlap()", {
tcs.sicalis.C <- subset(colspace(vismodel(sicalis)), "C")
tcs.sicalis.T <- subset(colspace(vismodel(sicalis)), "T")
tcs.sicalis.B <- subset(colspace(vismodel(sicalis)), "B")
expect_equal(round(mean(unlist(voloverlap(tcs.sicalis.T, tcs.sicalis.B, type = "convex"))), 4), 0.0395)
expect_equal(round(mean(unlist(voloverlap(tcs.sicalis.T, tcs.sicalis.C, type = "convex"))[1:2]^-1), 4), 201959.93)
})
test_that("processing & general", {
# Sensdata
result18 <- sensdata(illum = "all", bkg = "all", trans = "all")
expect_equal(dim(result18), c(401, 7))
expect_equal(round(mean(unlist(result18)), 4), 72.8731)
# Peakshape
result19 <- peakshape(flowers, absolute.min = TRUE)
expect_equal(dim(result19), c(36, 7))
expect_equal(round(mean(unlist(result19[, 2:6]), na.rm = TRUE), 4), 287.7377)
# Simulate
# Ideal
result20 <- summary(simulate_spec(ylim = c(0, 50)))
expect_equal(dim(result20), c(1, 23))
expect_equal(round(mean(unlist(result20)), 4), 928.3311)
# Sigmoidd low-high
result21 <- summary(simulate_spec(wl_inflect = 550))
expect_equal(dim(result21), c(1, 23))
expect_equal(round(mean(unlist(subset(result21, select = -c(S2))), na.rm = TRUE), 4), 1479.6564)
# Sigmoid high-low
result22 <- summary(simulate_spec(wl_inflect = 550, ylim = c(100, 0)))
expect_equal(dim(result22), c(1, 23))
expect_equal(round(mean(unlist(subset(result22, select = -c(S2, S9))), na.rm = TRUE), 4), 1885.9745)
# Gaussian
result23 <- summary(simulate_spec(wl_peak = 400))
expect_equal(dim(result23), c(1, 23))
expect_equal(round(mean(unlist(subset(result23, select = -c(S2, S9))), na.rm = TRUE), 4), 694.4126)
# Merge
teal1 <- teal[, c(1, 3:5)]
teal2 <- teal[, c(1, 2, 6:12)]
expect_equal(round(mean(unlist(merge(teal1, teal2, by = "wl"))), 4), 51.1874)
# Subset
vis.sicalis <- vismodel(sicalis)
tcs.sicalis <- colspace(vis.sicalis, space = "tcs")
expect_equal(round(mean(unlist(subset(vis.sicalis, "C")), na.rm = TRUE), 4), 0.25)
expect_equal(round(mean(unlist(subset(sicalis, "T", invert = TRUE)), na.rm = TRUE), 4), 40.1018)
# Summary
expect_equal(round(mean(unlist(summary(teal))), 4), 287.9638)
expect_equal(round(mean(unlist(subset(summary(sicalis), select = -c(S2)))), 4), 313.7217)
})
test_that("images", {
papilio <-
getimg(system.file("testdata", "images", "butterflies", "papilio.png", package = "pavo"))
snakes <-
getimg(system.file("testdata", "images", "snakes", package = "pavo"))
expect_equal(unlist(unname(summary(papilio))), 'papilio')
expect_equal(unlist(unname(summary(snakes))), c('snake_01', 'snake_02'))
})
test_that("vismodel", {
result24 <- vismodel(flowers, visual = "canis", achromatic = "all", illum = "bluesky")
expect_equal(dim(result24), c(36, 3))
expect_equal(round(mean(unlist(result24)), 4), 0.4572)
result25 <- vismodel(flowers, visual = "apis", qcatch = "fi", achromatic = "ml", scale = 10000)
expect_equal(dim(result25), c(36, 4))
expect_equal(round(mean(unlist(result25)), 4), 2.3597)
result26 <- vismodel(flowers, visual = "bluetit", achromatic = "ch.dc", trans = "bluetit")
expect_equal(dim(result26), c(36, 5))
expect_equal(round(mean(unlist(result26)), 4), 0.2832)
result27 <- vismodel(flowers, visual = "musca", achromatic = "md.r1", relative = FALSE)
expect_equal(dim(result27), c(36, 5))
expect_equal(round(mean(unlist(result27)), 4), 0.1904)
result28 <- vismodel(flowers, visual = "apis", relative = FALSE, qcatch = "Ei", bkg = "green",
vonkries = TRUE, achromatic = "l")
expect_equal(dim(result28), c(36, 4))
expect_equal(round(mean(unlist(result28)), 4), 0.5457)
result29 <- vismodel(flowers, visual = "cie10")
expect_equal(dim(result29), c(36, 4))
expect_equal(round(mean(unlist(result29), na.rm = TRUE), 4), 0.3859)
})
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