comp_kernels_pred: Computes CMF kernel matrices for prediction and saves them to...
In conmolfields: Continuous molecular fields

Computes CMF kernel matrices for prediction and saves them to file

comp_kernels_pred(train_fname = "ligands-train.mol2", pred_fname = "ligands-pred.mol2", kernels_pred_fname = "ligands-kernels-pred.RData", mfields = c("q", "vdw", "logp", "abra", "abrb"), print_comp_kernels = TRUE, ...)

`train_fname`
`pred_fname`
`kernels_pred_fname`
`mfields`
`print_comp_kernels`
`...`

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (train_fname = "ligands-train.mol2", pred_fname = "ligands-pred.mol2", 
    kernels_pred_fname = "ligands-kernels-pred.RData", mfields = c("q", 
        "vdw", "logp", "abra", "abrb"), print_comp_kernels = TRUE, 
    ...) 
{
    mdb0_train <- read_mol2(train_fname)
    mdb0_pred <- read_mol2(pred_fname)
    mdb_train <- cmf_params_tripos(mdb0_train)
    mdb_pred <- cmf_params_tripos(mdb0_pred)
    nfields <- length(mfields)
    syb_types <- get_syb_types_list(mdb_train)
    kernels_pred <- list()
    kernels_pred$alphas <- alphas
    for (f in 1:nfields) {
        kernels_pred[[mfields[f]]] <- list()
    }
    for (ialpha in 1:length(alphas)) {
        alpha <- alphas[ialpha]
        for (f in 1:nfields) {
            field <- mfields[f]
            if (print_comp_kernels) {
                cat(sprintf("computing kernel_%s for alpha=%g\n", 
                  field, alpha))
                flush.console()
            }
            if (field == "ind") {
                Km <- 0
                for (type in syb_types) {
                  if (print_comp_kernels) 
                    cat(type)
                  Km <- Km + cmf_indicator_kernel_matrix_pred(mdb_pred, 
                    mdb_train, alpha, type, verbose = print_comp_kernels)
                }
            }
            else {
                Km <- cmf_kernel_matrix_tp(field, mdb_pred, mdb_train, 
                  alpha, verbose = print_comp_kernels)
            }
            kernels_pred[[field]][[ialpha]] <- Km
        }
    }
    save(kernels_pred, file = kernels_pred_fname)
  }