R Under development (unstable) (2024-04-23 r86473 ucrt) -- "Unsuffered Consequences"
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> library(epigrowthfit)
> options(warn = 2L, error = if (interactive()) recover)
> 
> o.1  <- egf_cache(        "egf-1.rds")
> o.1s <- egf_cache("summary-egf-1.rds")
List of 5
 $ fitted     : num [1:6, 1:2] -3.28 -3.18 -3.13 -3.09 -3.01 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:6] "Min." "1st Qu." "Median" "Mean" ...
  .. ..$ : chr [1:2] "log(r)" "log(c0)"
 $ convergence: int 0
 $ value      : num 1032
 $ gradient   : num [1:5] -1.63e-03 -4.25e-04 5.68e-05 2.73e-04 1.79e-04
 $ hessian    : logi TRUE
 - attr(*, "class")= chr "summary.egf"
> o.1f <- egf_cache( "fitted-egf-1.rds")
> 
> 
> ## object ##############################################################
> 
> stopifnot(exprs = {
+ 	is.list(o.1s)
+ 	identical(oldClass(o.1s), "summary.egf")
+ 	length(o.1s) == 5L
+ 	identical(names(o.1s), c("fitted", "convergence", "value", "gradient", "hessian"))
+ 	identical(o.1s[["convergence"]], o.1[["optimizer_out"]][["convergence"]])
+ 	identical(o.1s[["value"]], o.1[["value"]])
+ 	identical(o.1s[["gradient"]], o.1[["gradient"]])
+ 	identical(o.1s[["hessian"]], o.1[["hessian"]])
+ 	all.equal(o.1s[["fitted"]], simplify2array(c(tapply(o.1f[["value"]], o.1f[["top"]], summary))))
+ })
> 
> 
> ## print ###############################################################
> 
> vv <- withVisible(print(o.1s))
Fitted values ..........................................................

             log(r)  log(c0)
  Min.    -3.280004 5.569983
  1st Qu. -3.180285 6.026158
  Median  -3.127046 6.347277
  Mean    -3.094246 6.418744
  3rd Qu. -3.006118 6.773228
  Max.    -2.818894 7.424955

Negative log marginal likelihood .......................................

  convergence          0                        
  value                1.032019e+03             
  range(abs(gradient)) 5.675084e-05 1.625871e-03
  pos. def. Hessian    TRUE                     
> stopifnot(exprs = {
+ 	identical(vv[["value"]], o.1s)
+ 	identical(vv[["visible"]], FALSE)
+ })
> 
> proc.time()
   user  system elapsed 
   1.54    0.12    1.65