From 1aae72c3b2aa64bf5b70978ef1474bff72f61f93 Mon Sep 17 00:00:00 2001
From: Sebastian Henz <sebastian.henz@ufz.de>
Date: Tue, 7 Apr 2020 15:08:26 +0200
Subject: [PATCH] Version 2.6.0: Improve ec() and axis concentration handling
Replace the "use_for_plotting" column in mod$curves with the plot axis
concentrations, which is far more useful. Add "refence" argument to ec() and
some minor improvements.
---
DESCRIPTION | 4 +-
NEWS.md | 8 +++
R/ec.R | 109 +++++++++++++++++++++++++++--------
R/ecxsys.R | 40 +++++++++++--
R/helpers.R | 26 ---------
R/plot_effect.R | 30 +++++-----
R/plot_stress.R | 32 +++++-----
man/ec.Rd | 26 +++++++--
man/ecxsys.Rd | 2 +-
tests/testthat/test-ec.R | 62 ++++++++++++--------
tests/testthat/test-ecxsys.R | 4 +-
11 files changed, 226 insertions(+), 117 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index f327c51..74f812b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
Package: stressaddition
Type: Package
Title: Modeling Tri-Phasic Concentration-Response Relationships
-Version: 2.5.0
-Date: 2020-03-16
+Version: 2.6.0
+Date: 2020-04-07
Authors@R: c(person("Sebastian",
"Henz",
role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index 1270c2a..3c1cfec 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,11 @@
+# stressaddition 2.6.0
+
+* The `curves` data frame in the output of `ecxsys()` now contains a column with the concentrations which are used for the plot functions in this package. This is useful for generating a nicer concentration axis.
+* Changes to `ec()`:
+ * Renamed `response_value` to `effect` in the output list.
+ * `response_level` of 0 or 100 is now allowed. 0 returns the concentration 0 and 100 returns the concentration `Inf`. Previously this resulted in an error.
+ * It is now possible to set the reference to a custom value, for example 100.
+
# stressaddition 2.5.0
* Fixed unintended behaviour in `plot_effect()` and `plot_stress()` where supplying an empty vector caused the four standard curves to show. Now setting `which` to an empty vector or `NULL` shows just the axes. The default value is NA.
diff --git a/R/ec.R b/R/ec.R
index 69c9da6..9f89821 100644
--- a/R/ec.R
+++ b/R/ec.R
@@ -34,6 +34,7 @@
#' @param model This can be one of three types of objects: Either the output of
#' \code{\link{ecxsys}} or the output of \code{\link{predict_ecxsys}} or a
#' data frame with a "concentration" column and a \code{response_name} column.
+#' In the case of the data frame the first row is assumed to be the control.
#' See the examples.
#' @param response_name The name of the effect or stress for which you want to
#' calculate the EC. Must be one of \code{colnames(model$curves)}.
@@ -41,12 +42,21 @@
#' and 100. For example with the value 10 the function will return the EC10,
#' i.e. the concentration where the response falls below 90 \% of the control
#' response.
+#' @param reference The reference value of the response, usually the control at
+#' concentration 0. This argument is optional. If it is missing, the first
+#' value of the response is used as control. This value determines what number
+#' \code{response_level} actually corresponds to. For example if
+#' response_level is 10 and reference is 45, then the function returns the
+#' concentration where the curve is reduced by 10\% relative to 45 = 40.5.
+#' @param warn Logical. Should the function emit a warning if the calculation of
+#' the effect concentration is not possible?
#'
-#' @return A list containing the response concentration and the corresponding
-#' response value.
+#' @return A list containing the effect concentration and the corresponding
+#' effect. The effect will be \code{NA} if its calculation is impossible from
+#' the supplied data.
#'
-#' @examples # Calculate the EC_10, the concentration where the effect falls
-#' # below 90 % of the effect in the control.
+#' @examples # Calculate the EC10, the concentration where the effect falls
+#' # below 90% of the effect in the control.
#'
#' model <- ecxsys(
#' concentration = c(0, 0.05, 0.5, 5, 30),
@@ -70,8 +80,16 @@
#' )
#' ec(df_custom, "foo", 10)
#'
+#' # Calculate the EC50 relative to an effect of 100
+#' # instead of relative to the control:
+#' ec(model, "effect_tox_sys", 50, reference = 100)
+#'
#' @export
-ec <- function(model, response_name, response_level) {
+ec <- function(model,
+ response_name,
+ response_level,
+ reference,
+ warn = TRUE) {
if (inherits(model, "drc")) {
stop("Please use drc::ED for drc objects.")
}
@@ -80,8 +98,8 @@ ec <- function(model, response_name, response_level) {
is.character(response_name),
length(response_name) == 1,
response_name != "concentration",
- response_level > 0,
- response_level < 100
+ response_level >= 0,
+ response_level <= 100
)
if (!inherits(model, c("ecxsys", "ecxsys_predicted"))) {
@@ -99,28 +117,73 @@ ec <- function(model, response_name, response_level) {
response <- model[, response_name]
}
- reference <- response[1]
- if (reference == 0) {
- stop("Reference value is zero, calculation of EC is impossible.")
+ if (missing(reference)) {
+ reference_value <- response[1]
+ } else {
+ stopifnot(reference > 0)
+ if (inherits(model, "ecxsys")) {
+ stopifnot(reference <= model$args$effect_max)
+ }
+ reference_value <- reference
}
- response_value <- (1 - response_level / 100) * reference
- output <- list(response_value = response_value)
- # Get the index of where the response changes from above to below
- # response_value:
- below <- which(response < response_value)[1]
- if (is.na(below)) {
- stop("The curve '", response_name, "' does not fall below ",
- 100 - response_level, "% of the control, which makes ",
- "determining the EC", response_level, " impossible.\n You could ",
- "try using predict_ecxsys() to predict more values in a wider ",
- "concentration range.")
+ if (reference_value == 0) {
+ # May happen with horizontal Sys curves.
+ if (warn) {
+ warning("Reference value is zero, calculation of EC is impossible.")
+ }
+ return(list(effect = 0, concentration = NA))
+ }
+
+ if (response_level == 0) {
+ return(list(effect = reference_value, concentration = 0))
+ } else if (response_level == 100) {
+ return(list(effect = 0, concentration = Inf))
+ }
+
+ response_value <- (1 - response_level / 100) * reference_value
+
+ response_smaller <- response < response_value
+ if (response_smaller[1]) {
+ if (warn) {
+ warning(
+ "The first values of '",
+ response_name,
+ "' are smaller than ",
+ 100 - response_level,
+ "% of the reference value, which makes determining the EC",
+ response_level,
+ " impossible."
+ )
+ }
+ return(list(effect = response_value, concentration = NA))
+ }
+ if (!any(response_smaller)) {
+ if (warn) {
+ warning(
+ "The curve '",
+ response_name,
+ "' does not fall below ",
+ 100 - response_level,
+ "% of the reference, which makes determining the EC",
+ response_level,
+ " impossible. You could try using predict_ecxsys() to predict ",
+ "more values in a wider concentration range."
+ )
+ }
+ return(list(effect = response_value, concentration = NA))
}
+ if (response[1] == response_value) {
+ return(list(effect = response_value, concentration = 0))
+ }
+
+ below <- which(response < response_value)[1]
above <- below - 1
# linear interpolation
dist <- (response_value - response[below]) / (response[above] - response[below])
- output$concentration <- dist *
+ effect_concentration <- dist *
(concentration[above] - concentration[below]) + concentration[below]
- output
+
+ list(effect = response_value, concentration = effect_concentration)
}
diff --git a/R/ecxsys.R b/R/ecxsys.R
index 80e05b4..a257531 100644
--- a/R/ecxsys.R
+++ b/R/ecxsys.R
@@ -77,7 +77,7 @@
#' returned by \code{\link{predict_ecxsys}}. The concentrations are
#' regularly spaced on a logarithmic scale in the given concentration range.
#' The control is approximated by the lowest non-control concentration times
-#' 1e-7. The additional column \code{use_for_plotting} is used by the
+#' 1e-7. The additional column \code{concentration_for_plots} is used by the
#' plotting functions of this package to approximate the control and
#' generate a break in the concentration axis.}
#' }
@@ -311,9 +311,15 @@ ecxsys <- function(concentration,
length.out = len_curves
)
output$curves <- predict_ecxsys(output, curves_concentration)
- output$curves$use_for_plotting <-
- curves_concentration < min_conc * conc_adjust_factor * 1.5 |
- curves_concentration > min_conc * 1.5
+
+ conc_axis <- adjust_plot_concentrations(
+ curves_concentration,
+ min_conc,
+ conc_adjust_factor
+ )
+ output$curves$concentration_for_plots <- conc_axis$concentration
+ output$axis_break_conc <- conc_axis$axis_break_conc
+
output
}
@@ -432,3 +438,29 @@ interpolate <- function(x, to_index, n_new, conc = FALSE) {
}
append(x, x_new[-c(1, len)], from_index)
}
+
+
+adjust_plot_concentrations <- function(concentration,
+ min_conc,
+ conc_adjust_factor) {
+ # Deals with the concentrations which are unnecessary for plotting. This
+ # means it removes the concentrations in the gap and increases the
+ # concentrations below the gap.
+ use_for_plotting <- (
+ concentration < min_conc * conc_adjust_factor * 1.5 |
+ concentration > min_conc * 1.5
+ )
+ gap_idx <- min(which(!use_for_plotting))
+
+ # Add NAs to force breaks in the lines:
+ axis_break_conc <- concentration[use_for_plotting][gap_idx]
+ concentration[!use_for_plotting] <- NA
+
+ # Shift the small concentrations upwards so the plot has a nice x-axis:
+ concentration[1:gap_idx] <- concentration[1:gap_idx] / conc_adjust_factor
+
+ list(
+ concentration = concentration,
+ axis_break_conc = axis_break_conc
+ )
+}
diff --git a/R/helpers.R b/R/helpers.R
index acdfaff..fcc3052 100644
--- a/R/helpers.R
+++ b/R/helpers.R
@@ -50,29 +50,3 @@ get_log_ticks <- function(x) {
major_labels = major_tick_labels
)
}
-
-
-adjust_plot_concentrations <- function(model) {
- # Helper for the plot functions, not exported.
- # Deals with the concentrations which are unnecessary for plotting. This
- # means it removes the concentrations in the gap and increases the
- # concentrations left of the gap.
- curves <- model$curves
- gap_idx <- min(which(!curves$use_for_plotting))
-
- # Keep only the values to the left and right of the axis break:
- curves <- curves[curves$use_for_plotting, ]
-
- # Add NAs to force breaks in the lines:
- axis_break_conc <- curves$concentration[gap_idx]
- curves[gap_idx, ] <- NA
-
- # Shift the small concentrations upwards so the plot has a nice x-axis:
- curves$concentration[1:gap_idx] <-
- curves$concentration[1:gap_idx] / model$conc_adjust_factor
-
- list(
- curves = curves,
- axis_break_conc = axis_break_conc
- )
-}
diff --git a/R/plot_effect.R b/R/plot_effect.R
index 942b3cc..0fb0293 100644
--- a/R/plot_effect.R
+++ b/R/plot_effect.R
@@ -52,15 +52,17 @@ plot_effect <- function(model,
which <- which[which %in% valid_names]
}
- temp <- adjust_plot_concentrations(model)
- curves <- temp$curves
- log_ticks <- get_log_ticks(curves$concentration)
- concentration <- c(curves$concentration[1], model$args$concentration[-1])
+ curves <- model$curves
+ log_ticks <- get_log_ticks(curves$concentration_for_plots)
+ point_concentration <- c(
+ curves$concentration_for_plots[1],
+ model$args$concentration[-1]
+ )
plot(
NA,
NA,
- xlim = range(curves$concentration, na.rm = TRUE),
+ xlim = range(curves$concentration_for_plots, na.rm = TRUE),
ylim = c(0, model$args$effect_max),
log = "x",
xlab = xlab,
@@ -75,7 +77,7 @@ plot_effect <- function(model,
# are on top of solid lines for better visibility.
if ("effect_tox_observed" %in% which) {
points(
- concentration,
+ point_concentration,
model$args$effect_tox_observed,
pch = 16,
col = "blue"
@@ -83,14 +85,14 @@ plot_effect <- function(model,
}
if ("effect_tox_sys" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox_sys,
col = "blue"
)
}
if ("effect_tox" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox,
col = "deepskyblue",
lty = 2
@@ -98,7 +100,7 @@ plot_effect <- function(model,
}
if ("effect_tox_LL5" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox_LL5,
col = "darkblue",
lty = 3
@@ -107,7 +109,7 @@ plot_effect <- function(model,
if (model$with_env) {
if ("effect_tox_env_observed" %in% which) {
points(
- concentration,
+ point_concentration,
model$args$effect_tox_env_observed,
pch = 16,
col = "red"
@@ -115,14 +117,14 @@ plot_effect <- function(model,
}
if ("effect_tox_env_sys" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox_env_sys,
col = "red"
)
}
if ("effect_tox_env" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox_env,
col = "orange",
lty = 2
@@ -130,7 +132,7 @@ plot_effect <- function(model,
}
if ("effect_tox_env_LL5" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$effect_tox_env_LL5,
col = "darkred",
lty = 3
@@ -145,7 +147,7 @@ plot_effect <- function(model,
col = NA, col.ticks = par("fg"))
axis(1, at = log_ticks$minor, labels = FALSE, tcl = -0.25,
col = NA, col.ticks = par("fg"))
- plotrix::axis.break(1, breakpos = temp$axis_break_conc)
+ plotrix::axis.break(1, breakpos = model$axis_break_conc)
axis(2, col = NA, col.ticks = par("fg"), las = 1)
if (show_legend) {
diff --git a/R/plot_stress.R b/R/plot_stress.R
index 152b0a3..7c2f5da 100644
--- a/R/plot_stress.R
+++ b/R/plot_stress.R
@@ -51,10 +51,12 @@ plot_stress <- function(model,
which <- which[which %in% valid_names]
}
- temp <- adjust_plot_concentrations(model)
- curves <- temp$curves
- log_ticks <- get_log_ticks(curves$concentration)
- concentration <- c(curves$concentration[1], model$args$concentration[-1])
+ curves <- model$curves
+ log_ticks <- get_log_ticks(curves$concentration_for_plots)
+ point_concentration <- c(
+ curves$concentration_for_plots[1],
+ model$args$concentration[-1]
+ )
curves_w <- curves[, which[!endsWith(which, "observed")]]
ymax <- if (NCOL(curves_w) == 0) 1 else max(curves_w, 1, na.rm = TRUE)
@@ -62,7 +64,7 @@ plot_stress <- function(model,
plot(
NA,
NA,
- xlim = range(curves$concentration, na.rm = TRUE),
+ xlim = range(curves$concentration_for_plots, na.rm = TRUE),
ylim = c(0, ymax),
log = "x",
xlab = xlab,
@@ -77,7 +79,7 @@ plot_stress <- function(model,
# are on top of solid lines for better visibility.
if ("sys_tox_observed" %in% which) {
points(
- concentration,
+ point_concentration,
model$sys_tox_observed,
pch = 16,
col = "steelblue3"
@@ -85,14 +87,14 @@ plot_stress <- function(model,
}
if ("stress_tox_sys" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$stress_tox_sys,
col = "blue"
)
}
if ("stress_tox" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$stress_tox,
col = "deepskyblue",
lty = 2
@@ -100,7 +102,7 @@ plot_stress <- function(model,
}
if ("sys_tox" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$sys_tox,
col = "steelblue3"
)
@@ -108,7 +110,7 @@ plot_stress <- function(model,
if (model$with_env) {
if ("sys_tox_env_observed" %in% which) {
points(
- concentration,
+ point_concentration,
model$sys_tox_env_observed,
pch = 16,
col = "violetred"
@@ -116,14 +118,14 @@ plot_stress <- function(model,
}
if ("stress_tox_env_sys" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$stress_tox_env_sys,
col = "red"
)
}
if ("stress_env" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$stress_env,
col = "forestgreen",
lty = 3
@@ -131,7 +133,7 @@ plot_stress <- function(model,
}
if ("stress_tox_env" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$stress_tox_env,
col = "orange",
lty = 2
@@ -139,7 +141,7 @@ plot_stress <- function(model,
}
if ("sys_tox_env" %in% which) {
lines(
- curves$concentration,
+ curves$concentration_for_plots,
curves$sys_tox_env,
col = "violetred"
)
@@ -153,7 +155,7 @@ plot_stress <- function(model,
col = NA, col.ticks = par("fg"))
axis(1, at = log_ticks$minor, labels = FALSE, tcl = -0.25,
col = NA, col.ticks = par("fg"))
- plotrix::axis.break(1, breakpos = temp$axis_break_conc)
+ plotrix::axis.break(1, breakpos = model$axis_break_conc)
axis(2, col = NA, col.ticks = par("fg"), las = 1)
if (show_legend) {
diff --git a/man/ec.Rd b/man/ec.Rd
index 0cacd6a..9ddf03f 100644
--- a/man/ec.Rd
+++ b/man/ec.Rd
@@ -4,12 +4,13 @@
\alias{ec}
\title{Effect Concentrations}
\usage{
-ec(model, response_name, response_level)
+ec(model, response_name, response_level, reference, warn = TRUE)
}
\arguments{
\item{model}{This can be one of three types of objects: Either the output of
\code{\link{ecxsys}} or the output of \code{\link{predict_ecxsys}} or a
data frame with a "concentration" column and a \code{response_name} column.
+In the case of the data frame the first row is assumed to be the control.
See the examples.}
\item{response_name}{The name of the effect or stress for which you want to
@@ -19,10 +20,21 @@ calculate the EC. Must be one of \code{colnames(model$curves)}.}
and 100. For example with the value 10 the function will return the EC10,
i.e. the concentration where the response falls below 90 \% of the control
response.}
+
+\item{reference}{The reference value of the response, usually the control at
+concentration 0. This argument is optional. If it is missing, the first
+value of the response is used as control. This value determines what number
+\code{response_level} actually corresponds to. For example if
+response_level is 10 and reference is 45, then the function returns the
+concentration where the curve is reduced by 10\% relative to 45 = 40.5.}
+
+\item{warn}{Logical. Should the function emit a warning if the calculation of
+the effect concentration is not possible?}
}
\value{
-A list containing the response concentration and the corresponding
- response value.
+A list containing the effect concentration and the corresponding
+ effect. The effect will be \code{NA} if its calculation is impossible from
+ the supplied data.
}
\description{
Estimate the concentration to reach a certain effect or stress level relative
@@ -39,8 +51,8 @@ increasing concentration, i.e. all \code{effect_*} curves and also
unexpected results, if any.
}
\examples{
-# Calculate the EC_10, the concentration where the effect falls
-# below 90 \% of the effect in the control.
+# Calculate the EC10, the concentration where the effect falls
+# below 90\% of the effect in the control.
model <- ecxsys(
concentration = c(0, 0.05, 0.5, 5, 30),
@@ -64,4 +76,8 @@ df_custom <- data.frame(
)
ec(df_custom, "foo", 10)
+# Calculate the EC50 relative to an effect of 100
+# instead of relative to the control:
+ec(model, "effect_tox_sys", 50, reference = 100)
+
}
diff --git a/man/ecxsys.Rd b/man/ecxsys.Rd
index 4d5bed1..f8a83b8 100644
--- a/man/ecxsys.Rd
+++ b/man/ecxsys.Rd
@@ -60,7 +60,7 @@ A list (of class ecxsys) containing many different objects of which
returned by \code{\link{predict_ecxsys}}. The concentrations are
regularly spaced on a logarithmic scale in the given concentration range.
The control is approximated by the lowest non-control concentration times
- 1e-7. The additional column \code{use_for_plotting} is used by the
+ 1e-7. The additional column \code{concentration_for_plots} is used by the
plotting functions of this package to approximate the control and
generate a break in the concentration axis.}
}
diff --git a/tests/testthat/test-ec.R b/tests/testthat/test-ec.R
index 0371c7d..fe5bbfc 100644
--- a/tests/testthat/test-ec.R
+++ b/tests/testthat/test-ec.R
@@ -17,12 +17,16 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
+# shared model for some of the tests
+model <- ecxsys(
+ concentration = c(0, 0.05, 0.5, 5, 30),
+ hormesis_concentration = 0.5,
+ effect_tox_observed = c(90, 81, 92, 28, 0),
+ effect_tox_env_observed = c(29, 27, 33, 5, 0)
+)
+
+
test_that("all input formats produce identical models", {
- model <- ecxsys(
- concentration = c(0, 0.05, 0.5, 5, 30),
- hormesis_concentration = 0.5,
- effect_tox_observed = c(90, 81, 92, 28, 0)
- )
# using the ecxsys() output or the curves therein directly:
ec10_a <- ec(model, "effect_tox_sys", 10)
ec10_b <- ec(model$curves, "effect_tox_sys", 10)
@@ -46,64 +50,72 @@ test_that("all input formats produce identical models", {
test_that("ec values have not changed", {
- model <- ecxsys(
- concentration = c(0, 0.05, 0.5, 5, 30),
- hormesis_concentration = 0.5,
- effect_tox_observed = c(90, 81, 92, 28, 0),
- effect_tox_env_observed = c(29, 27, 33, 5, 0)
- )
expect_equal(
ec(model, "effect_tox_sys", 50),
- list(response_value = 44.95368, concentration = 3.375735),
+ list(effect = 44.95368, concentration = 3.375735),
tolerance = 1e-4
)
expect_equal(
ec(model, "effect_tox_sys", 10),
- list(response_value = 80.91662, concentration = 1.098648),
+ list(effect = 80.91662, concentration = 1.098648),
tolerance = 1e-4
)
expect_equal(
- ec(model, "effect_tox_sys", 5),
- list(response_value = 85.41198, concentration = 0.005502182),
+ ec(model, "effect_tox", 100/3),
+ list(effect = 66.66667, concentration = 1.902125),
tolerance = 1e-4
)
expect_equal(
- ec(model, "effect_tox_sys", 1),
- list(response_value = 89.00828, concentration = 8.53288e-05),
+ ec(model, "effect_tox_LL5", 42),
+ list(effect = 52.2, concentration = 2.054426),
tolerance = 1e-4
)
expect_equal(
ec(model, "effect_tox_env_sys", 50),
- list(response_value = 14.67725, concentration = 1.299516),
+ list(effect = 14.67725, concentration = 1.299516),
tolerance = 1e-4
)
expect_equal(
ec(model, "effect_tox_env_sys", 10),
- list(response_value = 26.41904, concentration = 0.0008571244),
+ list(effect = 26.41904, concentration = 0.0008571244),
tolerance = 1e-4
)
expect_equal(
- ec(model, "effect_tox_env_sys", 5),
- list(response_value = 27.88677, concentration = 0.0001044245),
+ ec(model, "effect_tox_env", 67.89),
+ list(effect = 24.51453, concentration = 0.7890892),
tolerance = 1e-4
)
expect_equal(
- ec(model, "effect_tox_env_sys", 1),
- list(response_value = 29.06095, concentration = 1.388112e-06),
+ ec(model, "effect_tox_env_LL5", 3.14159),
+ list(effect = 28.73466, concentration = 0.7267524),
tolerance = 1e-4
)
})
-test_that("ec fails when response_level is outside the range of the curve", {
+test_that("ec warns when response_level is outside the range of the curve", {
model <- ecxsys(
concentration = c(0, 0.05, 0.5, 5),
hormesis_concentration = 0.5,
effect_tox_observed = c(90, 81, 92, 28)
)
- expect_error(
+ expect_warning(
ec(model, "effect_tox_sys", 90),
"You could try using predict_ecxsys() to predict more values",
fixed = TRUE
)
})
+
+
+test_that("reference argument works", {
+ expect_equal(
+ ec(model, "effect_tox_LL5", 50, reference = 100),
+ list(effect = 50, concentration = 2.208119),
+ tolerance = 1e-4
+ )
+ expect_equal(
+ ec(model, "effect_tox_LL5", 50, reference = 75),
+ list(effect = 37.5, concentration = 3.342715),
+ tolerance = 1e-4
+ )
+})
diff --git a/tests/testthat/test-ecxsys.R b/tests/testthat/test-ecxsys.R
index d04e16f..ffc2608 100644
--- a/tests/testthat/test-ecxsys.R
+++ b/tests/testthat/test-ecxsys.R
@@ -161,7 +161,7 @@ test_that("the curves have not changed", {
sys_tox_env = c(0.25443, 0.20496, 0.04445, 0.00000, 0.00000),
stress_tox_env_sys = c(0.61020, 0.63691, 0.59102, 0.85800, 1.33916),
effect_tox_env_sys = c(29.35449, 24.84147, 32.75385, 1.93182, 0),
- use_for_plotting = c(TRUE, TRUE, TRUE, TRUE, TRUE)
+ concentration_for_plots = c(0.0001, 0.03004, 0.30512, 3.02551, 30)
)
class(new_curves) <- class(reference_curves)
expect_equal(new_curves, reference_curves, tolerance = 1e-3)
@@ -171,7 +171,7 @@ test_that("the curves have not changed", {
test_that("the returned fn works the same way as internally", {
# I don't know why it would fail but it doesn't hurt to test it.
curves <- mod$curves
- curves$use_for_plotting <- NULL # remove column "use_for_plotting"
+ curves$concentration_for_plots <- NULL
expect_identical(curves, predict_ecxsys(mod, curves$concentration))
})
--
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