tests/testthat/test-nimo-ui.R

In nlmixr: Nonlinear Mixed Effects Models in Population PK/PD

nlmixrTest(
  {
    context("Make sure Nimo has a correct parsing for nlmixr")
    test_that("Nimo", {
      nimo <- function() {
        ini({
          ## Note that the UI can take expressions
          ## Also note that these initial estimates should be provided on the log-scale
          tcl <- log(0.001)
          tv1 <- log(1.45)
          tQ <- log(0.004)
          tv2 <- log(44)
          tkss <- log(12)
          tkint <- log(0.3)
          tksyn <- log(1)
          tkdeg <- log(7)
          ## Initial estimates should be high for SAEM ETAs
          eta.cl ~ 2
          eta.v1 ~ 2
          eta.kss ~ 2
          ##  Also true for additive error (also ignored in SAEM)
          add.err <- 10
        })
        model({
          cl <- exp(tcl + eta.cl)
          v1 <- exp(tv1 + eta.v1)
          Q <- exp(tQ)
          v2 <- exp(tv2)
          kss <- exp(tkss + eta.kss)
          kint <- exp(tkint)
          ksyn <- exp(tksyn)
          kdeg <- exp(tkdeg)

          k <- cl / v1
          k12 <- Q / v1
          k21 <- Q / v2

          eff(0) <- ksyn / kdeg ## initializing compartment

          ## Concentration is calculated
          conc <- 0.5 * (central / v1 - eff - kss) + 0.5 * sqrt((central / v1 - eff - kss)**2 + 4 * kss * central / v1)

          d / dt(central) <- -(k + k12) * conc * v1 + k21 * peripheral - kint * eff * conc * v1 / (kss + conc)
          d / dt(peripheral) <- k12 * conc * v1 - k21 * peripheral ## Free Drug second compartment amount
          d / dt(eff) <- ksyn - kdeg * eff - (kint - kdeg) * conc * eff / (kss + conc)

          IPRED <- log(conc)

          IPRED ~ add(add.err)
        })
      }

      f <- nlmixr(nimo)

      expect_false(is.null(f$saem.pars))
    })
  },
  test = "saem"
)