Nothing
context('test of power distribution predictions')
S0 <- 31
N0 <- 877
E0 <- 917872
this.esf <- meteESF(S0=S0, N0=N0, E=E0/1.134)
## data from figure 2 in Newman et al. 2014 Ecology
test_that('predicted rank ipd is correct', {
yRaw <- c(0.072, 0.498, 0.929, 1.356, 1.787, 2.208, 2.639)
yAct <- 6:0
newmanPsi <- predict(lm(yAct~yRaw),
newdata=data.frame(yRaw=c(0.555, 0.637, 0.801, 1.171, 1.186,
1.202, 1.217, 1.73, 1.766, 1.802,
1.843, 2.567, 2.603, 2.642)))
newmanRank <- c(1, 2, 7, 65, 65, 65, 65, 605, 605, 605, 605, 877, 877, 877)
this.ipd <- ipd(this.esf)
this.ipdRank <- meteDist2Rank(this.ipd)
expect_true(all(abs(log(this.ipdRank[newmanRank[1:3]], 10) - newmanPsi[1:3]) < 0.06))
minmax <- do.call(rbind, tapply(newmanPsi, newmanRank, range))
expect_true(all(log(this.ipdRank[unique(newmanRank[-(1:3)])], 10) <= minmax[-(1:3), 2] &
log(this.ipdRank[unique(newmanRank[-(1:3)])], 10) >= minmax[-(1:3), 1]))
})
## data from figure 6 in Newman et al. 2014 Ecology
test_that('predicted rank sipd is correct', {
xRaw <- c(1886, 1690, 1494, 1294, 1096, 900, 702, 502, 306, 108)
xAct <- seq(5.5, 1, by=-0.5)
x <- predict(lm(xAct~xRaw), newdata=data.frame(xRaw=c(326, 524, 810, 1078, 1316, 1614, 1784)))
yRaw <- c(44, 214, 386, 556, 724, 894, 1066, 1236)
yAct <- 1:-6
y <- predict(lm(yAct~yRaw), newdata=data.frame(yRaw=c(958, 854, 722, 606, 508, 396, 338)))
this.sipd <- sipd(this.esf, n=103)
expect_true(all(abs(log(this.sipd$p(exp(x))) - y) < 0.15*abs(y)))
})
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