cat(crayon::yellow("\ntest-mv:"))

if (FALSE) {
  source(paste0(spaMM::projpath(),"/package/tests/testthat/extralong/test-mv-extra.R"))
  source(paste0(spaMM::projpath(),"/package/tests/testthat/extralong/test-composite-extra.R"))
  source(paste0(spaMM::projpath(),"/package/tests/testthat/extralong/test-mv-corrFamily.R"))
} else {
  data("wafers")
  me <- fitme(y ~ 1+(1|batch), family=Gamma(log), data=wafers)
  set.seed(123)
  y2 <- simulate(me, type="residual")
  wafmv <- wafers
  wafmv$batch2 <- wafmv$batch
  wafmv$y2 <- y2
  wafmv$ly <- log(wafmv$y)
  wafmv$y3 <- log(y2)
  (zut1 <- fitmv(submodels=list(mod1=list(formula=ly ~ 1+(1|batch), family=gaussian()),
                                mod2=list(formula=y3 ~ 1+(1|batch2), family=gaussian())), 
                 data=wafmv))
  testthat::expect_true(diff(range( predict(zut1, newdata=zut1$data)-predict(zut1)))<1e-14)
  testthat::expect_true(diff(range( get_predVar(zut1, newdata=zut1$data)-get_predVar(zut1)))<1e-14) ## there a resid.model so nothing is done with phi
  simulate(zut1, newdata=wafmv)
  simulate(zut1, newdata=wafmv, re.form=~(1|batch2))
  length(unique(predict(zut1, re.form=~(1|batch2))[seq(1,198,18)])) # must 1 as 'batch' effect removed
  update_resp(zut1,newresp = simulate(zut1))
  #
  if (spaMM.getOption("example_maxtime")>0.7) { # confint with resid.model
    (zut1 <- fitmv(submodels=list(mod1=list(formula=y ~ 1+(1|batch), family=Gamma(log),resid.model= ~  1+(1|batch)),
                                  mod2=list(formula=y2 ~ 1+(1|batch), family=Gamma(log))), 
                   data=wafmv))
    confint(zut1,"(Intercept)_1") 
    get_fittedPars(zut1) # handling of heterogeneous resid.models
    # numInfo(zut1) # mixed resid.model issue, not specific to mv...
  }
  
  data("recond") # private data set for test
  (spast <- fitmv(submodels=list(
    has_survived=list(resp ~ varld + nsloc + ewloc, family=binomial()),
    has_flowers=list(resp ~ varfl + nsloc + ewloc, family=binomial()),
    head_count=list(resp ~ varhdct + nsloc + ewloc+pop, family=Tpoisson())),
    data=recond))
  
}