Remove concentration vector length restriction

DESCRIPTION

 Package: stressaddition
 Type: Package
 Title: Modeling Tri-Phasic Concentration-Response Relationships
-Version: 2.4.1
+Version: 2.5.0
 Date: 2020-03-16
 Authors@R: c(person("Sebastian", 
                     "Henz", 

NEWS.md

-# stressaddition 2.4.1
+# 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.
 * Renamed the `mixture_effect` column in the `predict_mixture` output data frame to `effect`.
+* Remove the restriction that the concentration vectors in `predict_mixture()` must be the same length. The longer length must be a multiple of the shorter length because the shorter vector gets recycled to the longer length.
 
 # stressaddition 2.4.0
 

R/predict_mixture.R

@@ -31,7 +31,9 @@
 #'
 #' @param model_a,model_b The ecxsys models of the toxicants.
 #' @param concentration_a,concentration_b The concentrations of the toxicants in
-#'   the mixture. Both vectors must be the same length.
+#'   the mixture. Both vectors must either be the same length or the longer
+#'   length must be a multiple of the shorter length. That's because the shorter
+#'   concentration vector gets recycled to the length of the longer one.
 #' @param proportion_ca The proportion of concentration addition in the
 #'   calculation of the toxicant stress of the mixture. Must be between 0 and 1.
 #' @param effect_max Controls the scaling of the result. This represents the
@@ -61,7 +63,7 @@
 #'
 #' # Example of symmetric prediction:
 #' conc_a <- c(0, 0.03, 0.3, 3)
-#' conc_b <- rep(5.5, 4)
+#' conc_b <- 5.5
 #' prop_ca <- 0.75
 #' mix_a <- predict_mixture(toxicant_a , toxicant_b , conc_a, conc_b, prop_ca)
 #' mix_b <- predict_mixture(toxicant_b , toxicant_a , conc_b, conc_a, prop_ca)
@@ -81,7 +83,6 @@ predict_mixture <- function(model_a,
         is.numeric(concentration_b),
         length(concentration_a) > 0,
         length(concentration_b) > 0,
-        length(concentration_a) == length(concentration_b),
         all(!is.na(concentration_a)),
         all(!is.na(concentration_b)),
         proportion_ca >= 0,

man/predict_mixture.Rd

@@ -17,7 +17,9 @@ predict_mixture(
 \item{model_a, model_b}{The ecxsys models of the toxicants.}
 
 \item{concentration_a, concentration_b}{The concentrations of the toxicants in
-the mixture. Both vectors must be the same length.}
+the mixture. Both vectors must either be the same length or the longer
+length must be a multiple of the shorter length. That's because the shorter
+concentration vector gets recycled to the length of the longer one.}
 
 \item{proportion_ca}{The proportion of concentration addition in the
 calculation of the toxicant stress of the mixture. Must be between 0 and 1.}
@@ -63,7 +65,7 @@ predict_mixture(
 
 # Example of symmetric prediction:
 conc_a <- c(0, 0.03, 0.3, 3)
-conc_b <- rep(5.5, 4)
+conc_b <- 5.5
 prop_ca <- 0.75
 mix_a <- predict_mixture(toxicant_a , toxicant_b , conc_a, conc_b, prop_ca)
 mix_b <- predict_mixture(toxicant_b , toxicant_a , conc_b, conc_a, prop_ca)

tests/testthat/test-predict_mixture.R

@@ -38,7 +38,7 @@ test_that("results have not changed", {
         model_a,
         model_b,
         c(0, 0.01, 0.1, 1, 7, 15),
-        rep(5, 6),
+        5,
         0.3
     )$effect
     reference <- c(88.574578, 84.361552, 80.633762, 56.730550, 2.882718, 0)
@@ -71,7 +71,7 @@ test_that("results have not changed", {
 
 test_that("predictions are symmetric", {
     conc_a <- c(0, 10^seq(log10(0.001), log10(40), length.out = 50))
-    conc_b <- rep(3.5, length(conc_a))
+    conc_b <- 3.5
     prop_ca <- 0.8
     effect_12 <- predict_mixture(model_a, model_b, conc_a, conc_b, prop_ca)$effect
     effect_21 <- predict_mixture(model_b, model_a, conc_b, conc_a, prop_ca)$effect