Running a model changes the source object

[billdenney]

I'm iteratively working within a similar set of models making some minor modifications and trying to improve the model fits. With that, I am sometimes running a model multiple times.

The issue that I have is that the object that I'm passing to nlmixr2 to try to estimate the model changes when I try to rerun it. More specifically, I would have assumed that the pheno_prep$iniDf would be unchanged before vs. after the fit while the fit object would have the new $iniDf:

library(nlmixr2)
#> Loading required package: nlmixr2data
library(tidyverse)
pheno <- function() {
  ini({
    tcl <- log(0.008) # typical value of clearance
    tv <-  log(0.6)   # typical value of volume
    ## var(eta.cl)
    eta.cl + eta.v ~ c(1, 
                       0.01, 1) ## cov(eta.cl, eta.v), var(eta.v)
    # interindividual variability on clearance and volume
    add.err <- 0.1    # residual variability
  })
  model({
    cl <- exp(tcl + eta.cl) # individual value of clearance
    v <- exp(tv + eta.v)    # individual value of volume
    ke <- cl / v            # elimination rate constant
    d/dt(A1) = - ke * A1    # model differential equation
    cp = A1 / v             # concentration in plasma
    cp ~ add(add.err)       # define error model
  })
}

pheno_prep <-
  # make an nlmixr2est object
  nlmixr(pheno)
#> ℹ parameter labels from comments will be replaced by 'label()'
pheno_prep$iniDf
#>   ntheta neta1 neta2           name lower        est upper   fix
#> 1      1    NA    NA            tcl  -Inf -4.8283137   Inf FALSE
#> 2      2    NA    NA             tv  -Inf -0.5108256   Inf FALSE
#> 3      3    NA    NA        add.err     0  0.1000000   Inf FALSE
#> 4     NA     1     1         eta.cl  -Inf  1.0000000   Inf FALSE
#> 5     NA     2     1 (eta.cl,eta.v)  -Inf  0.0100000   Inf FALSE
#> 6     NA     2     2          eta.v  -Inf  1.0000000   Inf FALSE
#>                        label backTransform condition  err
#> 1 typical value of clearance          <NA>      <NA> <NA>
#> 2    typical value of volume          <NA>      <NA> <NA>
#> 3       residual variability          <NA>        cp  add
#> 4                       <NA>          <NA>        id <NA>
#> 5                       <NA>          <NA>        id <NA>
#> 6                       <NA>          <NA>        id <NA>
fit <- nlmixr(pheno_prep, pheno_sd, "focei", control=list(print=0))
#> rxode2 2.0.7 using 8 threads (see ?getRxThreads)
#>   no cache: create with `rxCreateCache()`
#> calculating covariance matrix
#> done
#> → Calculating residuals/tables
#> ✔ done
#> → compress origData in nlmixr2 object, save 33192
#> → compress parHist in nlmixr2 object, save 2960
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Warning: last objective function was not at minimum, possible problems in
#> optimization
#> Warning: ETAs were reset to zero during optimization; (Can control by
#> foceiControl(resetEtaP=.))
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=.,
#> etaNudge2=))
pheno_prep$iniDf
#>   ntheta neta1 neta2           name lower        est upper   fix
#> 1      1    NA    NA            tcl  -Inf -5.0001418   Inf FALSE
#> 2      2    NA    NA             tv  -Inf  0.3341971   Inf FALSE
#> 3      3    NA    NA        add.err     0  2.8356874   Inf FALSE
#> 4     NA     1     1         eta.cl  -Inf  0.2529083   Inf FALSE
#> 5     NA     2     1 (eta.cl,eta.v)  -Inf  0.1942066   Inf FALSE
#> 6     NA     2     2          eta.v  -Inf  0.1552687   Inf FALSE
#>                        label backTransform condition  err
#> 1 typical value of clearance          <NA>      <NA> <NA>
#> 2    typical value of volume          <NA>      <NA> <NA>
#> 3       residual variability          <NA>        cp  add
#> 4                       <NA>          <NA>        id <NA>
#> 5                       <NA>          <NA>        id <NA>
#> 6                       <NA>          <NA>        id <NA>

^{Created on 2022-08-31 by the reprex package (v2.0.1)}

[mattfidler]

This probably needs the ui object to be cloned.