R/print.R

Defines functions printmany print.multigroup print.multigroupfit print.lvmfit.randomslope `print.lvmfit` `print.lvm`

###{{{ print.lvm

##' @export
`print.lvm` <-
function(x, ..., print.transform=TRUE,print.exogenous=TRUE) {
  res <- NULL
  myhooks <- gethook("print.hooks")
  for (f in myhooks) {
      res <- do.call(f, list(x=x, ...))
  }
  if (is.null(res)) {
    k <- length(vars(x))
    L <- rep(FALSE, k); names(L) <- vars(x); L[latent(x)] <- TRUE
    cat("Latent Variable Model\n") ##;" \n\twith: ", k, " variables.\n", sep="");
    if (k==0) {
        cat("\nEmpty\n")
        return()
    }
    ff <- formula(x, char=TRUE, all=TRUE)
    R <- Rx <- Rt <- c()
    exo <- exogenous(x)
    for (f in ff) {
      oneline <- as.character(f);
      y <- strsplit(f, "~")[[1]][1]
      y <- trim(y)
      {
        col1 <- as.character(oneline)
        D <- attributes(distribution(x)[[y]])$family
        Tr <- x$attributes$transform[[y]]
        col2 <- tryCatch(x$attributes$type[[y]], error=function(...) NULL)
        if (is.null(col2) || is.na(col2)) {
            if (!is.na(x$covfix[y, y]) && x$covfix[y, y]==0L) {
                col2 <- "deterministic"
            } else {
                col2 <- "gaussian"
            }
        }
        if (!is.null(Tr)){
            col1 <- paste0(y, " ~ ", paste0(Tr$x, collapse="+"), sep="")
            Rt <- rbind(Rt, c(col1, ""))
        }
        if (!is.null(D$family)) {
            col2 <- paste0(D$family)
        }
        if (!is.null(D$link)) col2 <- paste0(col2, "(", D$link, ")")
        if (!is.null(D$par)) col2 <- paste0(col2, "(", paste(D$par, collapse=","), ")")
        if (is.list(distribution(x)[[y]]) && is.vector(distribution(x)[[y]][[1]])) col2 <- "fixed"
        if (L[y]) col2 <- paste0(col2, ", latent")
        if (y%in%exo) {
            Rx <- rbind(Rx,c(col1, col2))
        } else {
            if (is.null(Tr)) {
                R <- rbind(R,c(col1, col2))
            }
        }
      }
    }
    if (length(R)>0) {
        rownames(R) <- paste(" ", R[, 1], " "); colnames(R) <- rep("", ncol(R))
        print(R[, 2, drop=FALSE], quote=FALSE, ...)
    }
    if (print.exogenous && length(Rx)>0) {
        cat("\nExogenous variables:")
        rownames(Rx) <- paste(" ", gsub("~ 1", "", Rx[, 1]), "     "); colnames(Rx) <- rep("", ncol(Rx))
        print(Rx[, 2, drop=FALSE], quote=FALSE, ...)
    }
    if (print.transform && length(Rt)>0) {
        cat("\nTransformations:")
        rownames(Rt) <- paste(" ", gsub("~ 1", "", Rt[,1]), "     "); colnames(Rt) <- rep("", ncol(Rt))
        print(Rt[,2,drop=FALSE],quote=FALSE, ...)
    }
  }
  cat("\n")
  invisible(x)
}

###}}} print.lvm

###{{{ print.lvmfit

##' @export
`print.lvmfit` <-
function(x,type=2,labels=FALSE,...) {
    print(CoefMat(x,labels=labels,type=type,...),quote=FALSE,right=TRUE)
    minSV <- attr(vcov(x),"minSV")
    if (!is.null(minSV) && minSV<1e-12) {
        warning("Small singular value: ", format(minSV))
    }
    pseudo <- attr(vcov(x),"pseudo")
    if (!is.null(pseudo) && pseudo) warning("Singular covariance matrix. Pseudo-inverse used.")
    invisible(x)
}

###}}} print.lvmfit

###{{{ print.lvmfit.randomslope

##' @export
print.lvmfit.randomslope <- function(x,labels=FALSE,type=2,...) {
  print(CoefMat(x,labels=labels,type=type,...),quote=FALSE,right=TRUE)
  invisible(x)
}

###}}}

###{{{ print.multigroupfit

##' @export
print.multigroupfit <- function(x,groups=NULL,...)  {
  if (is.null(groups)) {
    if (x$model$missing) {
      modelclass <- attributes(x$model0)$modelclass
      nmis <- attributes(x$model0)$nmis
      orggroup <- unique(modelclass)
      groupn <- unlist(lapply(orggroup,function(i) sum(modelclass==i)))
      cumsumgroup <- cumsum(c(0,groupn))
      groups <- unlist(lapply(orggroup,function(i)
                              which.min(nmis[which(modelclass==i)])+cumsumgroup[i])) ##  groups with max. number of variables
      for (i in seq_len(length(groups))) {
        if (nmis[groups[i]]>0) warning("No complete cases in group ",i,". Showing results of group with max number of variables. All coefficients can be extracted with 'coef'. All missing pattern groups belonging to this sub-model can be extracted by calling: coef(..., groups=c(",paste(which(modelclass==i),collapse=","),"))")
      }
      if (!is.null(x$model$mnameses))
        x$model$names <- x$model$mnames
    } else {
      groups <- seq_len(length(x$model$lvm))
    }
  }
  res <- coef(x,type=2,groups=groups,...)
  counter <- 0
  dots <- list(...)
  dots$groups <- groups
  type <- if (is.null(dots$type)) {
    dots$type <- 2
##    dots$type <- ifelse("lvmfit.randomslope"%in%class(x),2,9)
  }
  myargs <- c(list(x=x), dots)
  myargs$groups <- groups
  CC <- do.call("CoefMat.multigroupfit",myargs)
  for (cc in res) {
    counter <- counter+1
    cat(rep("_",52),"\n",sep="")
    cat("Group ", counter, sep="")
    myname <- x$model$names[counter]
    if (!is.null(myname) && !is.na(myname))
      cat(": ",myname,sep="")
    if (!x$model$missing) cat(" (n=",nrow(Model(x)$data[[groups[counter]]]), ")", sep="")
    cat("\n")
    print(CC[[counter]],quote=FALSE,right=TRUE)
  }
  cat("\n")
  invisible(x)
}

###}}} print.multigroupfit

###{{{ print.multigroup

##' @export
print.multigroup <- function(x,...) {
  cat("\n")
  cat("Number of groups:", x$ngroup, "\n")
  cat("Number of free parameters (not counting mean-parameters):", x$npar,"\n")
##  cat("Parameter-vector:", unlist(x$parlist), "\n\n")
  cat("Number of free mean parameters:", length(grep("m",x$mean)),"\n")
##  cat("Mean-vector:", x$mean, "\n\n")
  invisible(x)
}

###}}} print.multigroup

###{{{ printmany

printmany <- function(A,B,nspace=1,name1=NULL,name2=NULL,digits=3,rownames=NULL,emptystr=" ",bothrows=!is.table(A),right=TRUE,print=TRUE,...) {
  A <- format(A, digits=digits, right=right, ...)
  B <- format(B, digits=digits, right=right, ...)
  nA <- nrow(A); nB <- nrow(B)
  if (nrow(A)<nrow(B)) {
    A <- rbind(A, matrix("", nrow=nB-nA, ncol=ncol(A)))
  }
  if (nrow(B)<nrow(A)) {
    B <- rbind(B, rep("", nrow=nA-nB, ncol=ncol(B)))
  }
  if (!is.null(rownames) & length(rownames)==nrow(A))
    rownames(A) <- rownames(B) <- rownames
  res <- cbind(A, matrix("", nrow=nrow(A), ncol=nspace));
  dnn <- dimnames(A)
  dnn[[2]] <- c(dnn[[2]],rep(emptystr,nspace))
  dimnames(res) <- dnn
  ##dimnames(res)[[2]] <- c(dimnames(res)[[2]],rep(emptystr,nspace))
  if (!is.null(name1)) {
      oldname <- colnames(res)
      res <- cbind(rep("",nrow(res)), rownames(res), res);
      cres <- name1
      if (!is.null(rownames(res))) cres <- c(cres,"")
      colnames(res) <- c(cres,oldname)
      rownames(res) <- rep("",nrow(res))
  }
  if (!is.null(name2)) {
    oldname <- colnames(res)
    res <- cbind(res,rep("",nrow(res))); colnames(res) <- c(oldname,name2)
  }
  if (!identical(rownames(A),rownames(B)) & bothrows)
      res <- cbind(res, rownames(B))
  res <- cbind(res, B)
  if (is.null(name2)) {
      dnn[[2]] <- c(dnn[[2]],dimnames(B)[[2]])
      dimnames(res) <- dnn
  }
  if (print) print(res, quote=FALSE, right=right, ...)
  invisible(res)
}

###}}} printmany
kkholst/lava documentation built on Sept. 6, 2021, 11:36 p.m.