rm(list = ls())
library(discountingtools)
og_k <- 0.2038359
og_b <- -0.01289119
og_ln_ed50 <- 3.480851e-05
og_mb_auc <- 0.0009689925
og_mb_auc_log <- 0.07645845
data_frame = data.frame(
ids = 1,
ks = og_k,
bs = og_b,
delay = c(1, 30, 180, 540, 1080, 2160, 4320, 8640)
)
data_frame[, 'value'] <- dd_discount_func_rodriguezlogue(
data_frame$delay,
data_frame$ks,
data_frame$bs) +
c(0.0109249702,
0.0305477299,
-0.0118369887,
0.0052715790,
-0.0454706108,
0.0068767728,
0.0008717358,
-0.0044386829)
describe("dd_fit: Rodriguez and Logue Model", {
cached_results = fit_dd_curves(
data = data_frame,
settings = list(Delays = delay,
Values = value,
Individual = ids),
maxValue = 1,
plan = c('rodriguezlogue')) |>
dd_analyze(modelSelection = FALSE) |>
summary()
it("Should not fail with simple data", {
expect_no_error(
fit_dd_curves(
data = data_frame,
settings = list(Delays = delay,
Values = value,
Individual = ids),
maxValue = 1,
plan = c('rodriguezlogue')) |>
dd_analyze(modelSelection = FALSE)
)
})
# TODO: clean up simulation for these
# it("Should be close to simulated parameter (15%)", {
# testthat::expect_equal(
# cached_results[1, 'RodriguezLogue.Lnk'],
# og_k,
# tolerance = 0.15
# )
# })
#
# it("Should be close to simulated parameter (15%)", {
# testthat::expect_equal(
# cached_results[1, 'RodriguezLogue.Beta'],
# og_b,
# tolerance = 0.15
# )
# })
it("Should be close to expected LnED50", {
testthat::expect_equal(
cached_results[1, 'RodriguezLogue.LnED50'],
og_ln_ed50,
tolerance = 0.1
)
})
it("Should be close to expected MBAUC", {
testthat::expect_equal(
cached_results[1, 'RodriguezLogue.MBAUC'],
og_mb_auc,
tolerance = 0.1
)
})
it("Should be close to expected Log10 MBAUC", {
testthat::expect_equal(
cached_results[1, 'RodriguezLogue.Log10MBAUC'],
og_mb_auc_log,
tolerance = 0.1
)
})
})
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