Rename the mixture_effect column to effect

R/predict_mixture.R

@@ -63,9 +63,9 @@
 #' conc_a <- c(0, 0.03, 0.3, 3)
 #' conc_b <- rep(5.5, 4)
 #' prop_ca <- 0.75
-#' effect_a <- predict_mixture(toxicant_a , toxicant_b , conc_a, conc_b, prop_ca)
-#' effect_b <- predict_mixture(toxicant_b , toxicant_a , conc_b, conc_a, prop_ca)
-#' identical(effect_a$mixture_effect, effect_b$mixture_effect)
+#' 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)
+#' identical(mix_a$effect, mix_b$effect)
 #'
 #' @export
 predict_mixture <- function(model_a,
@@ -129,11 +129,11 @@ predict_mixture <- function(model_a,
     proportion_sam <- 1 - proportion_ca
     stress_tox_total <- stress_tox_ca * proportion_ca + stress_tox_sam * proportion_sam
     stress_total <- stress_tox_total + sys_total
-    mixture_effect <- stress_to_effect(stress_total) * effect_max
+    effect <- stress_to_effect(stress_total) * effect_max
 
-    # unname() to remove the name when concentration_a is a single number.
-    mixture_effect <- unname(mixture_effect)
-    data.frame(concentration_a, concentration_b, mixture_effect)
+    # Setting row.names to NULL to prevent row names when one of the
+    # concentrations is a single number.
+    data.frame(concentration_a, concentration_b, effect, row.names = NULL)
 }
 
 

man/predict_mixture.Rd

@@ -65,8 +65,8 @@ predict_mixture(
 conc_a <- c(0, 0.03, 0.3, 3)
 conc_b <- rep(5.5, 4)
 prop_ca <- 0.75
-effect_a <- predict_mixture(toxicant_a , toxicant_b , conc_a, conc_b, prop_ca)
-effect_b <- predict_mixture(toxicant_b , toxicant_a , conc_b, conc_a, prop_ca)
-identical(effect_a$mixture_effect, effect_b$mixture_effect)
+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)
+identical(mix_a$effect, mix_b$effect)
 
 }

tests/testthat/test-predict_mixture.R

@@ -40,7 +40,7 @@ test_that("results have not changed", {
         c(0, 0.01, 0.1, 1, 7, 15),
         rep(5, 6),
         0.3
-    )$mixture_effect
+    )$effect
     reference <- c(88.574578, 84.361552, 80.633762, 56.730550, 2.882718, 0)
     expect_equal(new, reference, tolerance = 1e-5)
 
@@ -51,7 +51,7 @@ test_that("results have not changed", {
         c(0, 0.01, 0.1, 1, 7, 15),
         c(0, 0.02, 0.2, 2, 14, 30),
         0.3
-    )$mixture_effect
+    )$effect
     reference <- c(88.2698383, 79.9617127, 78.1574808, 65.7999834, 0.3861678, 0)
     expect_equal(new, reference, tolerance = 1e-5)
 
@@ -63,7 +63,7 @@ test_that("results have not changed", {
         c(0, 0.02, 0.2, 2, 14, 30),
         0.3,
         42
-    )$mixture_effect
+    )$effect
     reference <- c(88.2698383, 79.9617127, 78.1574808, 65.7999834, 0.3861678, 0) * 0.42
     expect_equal(new, reference, tolerance = 1e-5)
 })
@@ -73,8 +73,8 @@ 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))
     prop_ca <- 0.8
-    effect_12 <- predict_mixture(model_a, model_b, conc_a, conc_b, prop_ca)$mixture_effect
-    effect_21 <- predict_mixture(model_b, model_a, conc_b, conc_a, prop_ca)$mixture_effect
+    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
     expect_equal(effect_12, effect_21)
 })