#' Given a fitted lavaan model (e.g., CFA), prepares a table that contains 
#' parameters that can be fixed/freed as part of a model specification search.
#'
#'@param fitted.model - an object of class "lavaan" that contains the initially fitted model for the search
#'@param loadings - a logical value that indicates whether cross-loadings will be part of the search
#'@param fcov - a logical value indicating whether factor covariances will be part of the search
#'@param errors - a logical value indicating whether error covariances will be part of the search
#'
#'@return A \code{data.frame} with lavaan-formatted parameter values.
#'@family Tabu Search
#'@import lavaan
#'@export
#'
#'@examples
#'\dontrun{
#'# load simulation data and select columns used in this example
#'data(simulated_test_data) 
#'tabuData <- simulated_test_data[,c(1:10)]
#'
#'# specify an improper model (improper because data is unidimensional)
#'tabuModel <- "
#'Ability =~ Item1 + Item2 + Item3 + Item4
#'FakeAbility =~ Item5 + Item6 + Item7 + Item8
#'Ability ~ Outcome
#'FakeAbility ~ 0*Outcome"
#'
#'# run the initial misspecified model for Tabu
#'
#'init.model <- lavaan::lavaan(model = tabuModel, data = tabuData, 
#'auto.var=TRUE, auto.fix.first=FALSE, std.lv=TRUE,auto.cov.lv.x=TRUE)
#'
#'# Use search.prep to prepare for the Tabu search
#'ptab <- search.prep(fitted.model = init.model,loadings=TRUE,fcov=TRUE,errors=FALSE)
#'
#'# add an additional (mispecified) parameter
#'additional.param <- 'Item1 ~~ 0.5*Item3'
#'ptab <- add.param(fitted.model = init.model, ptab = ptab, syntax = additional.param)
#'
#'# Perform Tabu Search
#'trial <- tabu.sem(init.model = init.model, ptab = ptab, obj = AIC, niter = 2, tabu.size = 5)
#'}
#'@author Carl F. Falk
#'@references \url{https://doi.org/10.1080/10705511.2017.1409074}

search.prep<-function(fitted.model,loadings=TRUE,fcov=TRUE,errors=FALSE){
  
  # Parameter table from fitted model
  ptab<-lavaan::parTable(fitted.model)
  
  # Full parameter table
  fulltab<-lav_partable_full(ptab)
  
  # Merge together so we have what's free
  mergetab<-lavaan::lav_partable_merge(ptab,fulltab, remove.duplicated=TRUE, warn=FALSE)
  
  idx<-vector("numeric")
  null.val<-vector("numeric")
  
  lv.names<-vnames(ptab,type="lv") # extract names of latent vars
  ov.names<-vnames(ptab,type="ov.nox") # indicators
  
  # Loadings
  if(loadings){
    # Index for which rows of table are loadings
    indx<-mergetab$op=="=~"
    
    # Omit any loadings that are fixed to a non-zero value
    # These may be fixed for identification
    indx[mergetab$free[indx]==0&mergetab$ustart[indx]!=0]<-FALSE
    
    idx<-c(idx,which(indx))
    null.val<-c(null.val,rep(0,sum(indx)))
  }
  
  # Factor cov
  if(fcov){
    # Index for which rows are cov among latent vars
    indx<-mergetab$op=="~~"&mergetab$lhs%in%lv.names&mergetab$lhs!=mergetab$rhs
    idx<-c(idx,which(indx))
    null.val<-c(null.val,rep(0,sum(indx)))
  }
  
  # Error covariances among indicators
  if(errors){
    # Index for which rows are cov among indicators
    indx<-mergetab$op=="~~"&mergetab$lhs%in%ov.names&mergetab$lhs!=mergetab$rhs
    idx<-c(idx,which(indx))
    null.val<-c(null.val,rep(0,sum(indx)))
  }
  
  # Check whether any parameters in the table are involved in any constraints
  flag<-check.const(fitted.model,mergetab[idx,])
  
  if(flag){
    warning("Some parameters in this table may be involved in (in)equality constraints")
  }
  
  # Clean up
  mergetab<-mergetab[idx,c("lhs","op","rhs","block","free","label")]
  mergetab$nullval<-null.val
  mergetab$free<-ifelse(mergetab$free==0,0,1)
  
  # Sort table
  lvnames<-lavaan::lavNames(mergetab,"lv")
  ovnames<-lavaan::lavNames(mergetab,"ov")
  mergetab<-mergetab[order(mergetab$block, # by group (or block)
                           is.na(match(mergetab$lhs,c(lvnames))), # put latent vars first
                           mergetab$op, # by op w/in lv and ov sections
                           match(mergetab$lhs,c(lvnames,ovnames)), # then by lv and ov names on lhs
                           match(mergetab$rhs,c(lvnames,ovnames))),] # then by same on rhs
  rownames(mergetab)<-1:nrow(mergetab)
  
  ret<-mergetab
  
  return(ret)
}