From 44044d0ef91da0115706c925f471e788be804495 Mon Sep 17 00:00:00 2001
From: Matthew Fidler <matthew.fidler@gmail.com>
Date: Fri, 18 Oct 2024 19:04:35 -0500
Subject: [PATCH] Update poped tests and news

---
 NEWS.md                     |  2 +-
 tests/testthat/test-poped.R | 14 +++++++-------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index 0b045619..c554b364 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -13,7 +13,7 @@
   `PopED` code between two different `PopED` databases, like in issue
   #131.
 
-* Added a new function `popedBpopIdx(poped.db, "par")` which will get
+* Added a new function `babelBpopIdx(poped.db, "par")` which will get
   the poped index for a model generated from `babelmixr2`, which is
   useful when calculating the power (as in example 11).
 
diff --git a/tests/testthat/test-poped.R b/tests/testthat/test-poped.R
index 07d88e01..7582b8f7 100644
--- a/tests/testthat/test-poped.R
+++ b/tests/testthat/test-poped.R
@@ -379,27 +379,22 @@ if (requireNamespace("PopED", quietly=TRUE)) {
         tCl <- 3.75
         tF <- fix(0.9)
         pedCL <- 0.8
-
         eta.v ~ 0.09
         eta.ka ~ 0.09
         eta.cl ~0.25^2
-
         prop.sd <- fix(sqrt(0.04))
         add.sd <- fix(sqrt(5e-6))
-
       })
       model({
         V<-tV*exp(eta.v)
-        KA<-tKa*exp(eta.ka) * (pedCL**isPediatric) # add covariate for pediatrics
-        CL<-tCl*exp(eta.cl)
+        KA<-tKa*exp(eta.ka)
+        CL<-tCl*exp(eta.cl)  * (pedCL^isPediatric) # add covariate for pediatrics
         Favail <- tF
-
         N <-  floor(t/TAU)+1
         y <- (DOSE*Favail/V)*(KA/(KA - CL/V)) *
           (exp(-CL/V * (t - (N - 1) * TAU)) *
              (1 - exp(-N * CL/V * TAU))/(1 - exp(-CL/V * TAU)) -
              exp(-KA * (t - (N - 1) * TAU)) * (1 - exp(-N * KA * TAU))/(1 - exp(-KA * TAU)))
-
         y ~ prop(prop.sd) + add(add.sd)
       })
     }
@@ -436,6 +431,11 @@ if (requireNamespace("PopED", quietly=TRUE)) {
     vdiffr::expect_doppelganger("poped-ped-next",
                                 plot_model_prediction(babel.db.ped,
                                                       model_num_points = 300))
+
+    expect_equal(babelBpopIdx(babel.db.ped, "pedCL"), 4L)
+
+    expect_error(babelBpopIdx(babel.db, "matt"))
+
   })
 
   ##  The tests run interactively runs OK