R/sanitization-amat.R

In bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

# sanity check adjacency matrices.
check.amat = function(amat, nodes) {

  # a node is needed.
  if (missing(amat))
    stop("no adjacency matrix specified.")
  # the adjacency matrix must, well, be a matrix.
  if (!is(amat, "matrix") || (ncol(amat) != nrow(amat)) || (length(dim(amat)) != 2))
    stop("an adjacency matrix must be a 2-dimensional square matrix.")
  # check the dimensions against the number of nodes in the graph.
  if (any(dim(amat) != length(nodes)))
    stop("the dimensions of the adjacency matrix do not agree with the number of nodes in the graph.")
  # column names must be valid node labels.
  if (!is.null(colnames(amat)))
    if (any(colnames(amat) %!in% nodes))
      stop("node (column label) not present in the graph.")
  # column names must be valid node labels.
  if (!is.null(rownames(amat)))
    if (any(rownames(amat) %!in% nodes))
      stop("node (row label) not present in the graph.")
  # column names must match with row names.
  if (!is.null(colnames(amat)) && !is.null(rownames(amat))) {

    if (!identical(colnames(amat), rownames(amat)))
      stop("row/column names mismatch in the adjacency matrix.")

    if (!identical(colnames(amat), nodes) || !identical(rownames(amat), nodes)) {

      warning("rearranging the rows/columns of the adjacency matrix.")

      amat = amat[nodes, nodes, drop = FALSE]

    }#THEN

  }#THEN
  # make really sure the adjacency matrix is made up of integers.
  if (storage.mode(amat) != "integer")
    storage.mode(amat) = "integer"
  # check the elements of the matrix.
  if (!all((amat == 0L) | (amat == 1L)))
    stop("all the elements of an adjacency matrix must be equal to either 0 or 1.")
  # no arcs from a node to itself.
  if (any(diag(amat) != 0))
    stop("the elements on the diagonal must be zero.")

  return(amat)

}#CHECK.AMAT