Documentation issues

NEWS.md

@@ -1,4 +1,9 @@
 # PhylogeneticEM 1.6.0.9000
+* Bug fixes:
+  * Fix documentation notes on CRAN checks.
+* New functions and features:
+  * Function `node_optimal_values` for optimal values computation at each nodes.
+  * Trait names are now inherited by the `params_process` objects.
 
 # PhylogeneticEM 1.6.0
 * Deprecation fix:

R/M_step.R

@@ -543,7 +543,7 @@ compute_var_diff.OU <- function(phylo, conditional_law_X, selection.strength) {
 #' @title Compute weighted sum of var_diff
 #'
 #' @description
-#' \code{compute_sum_var_diff} computes sum_{e edge} ell_j * Var[X_j - X_pa(j) | Y]
+#' \code{compute_sum_var_diff} computes \sum_\{e edge\} ell_j * Var[X_j - X_pa(j) | Y]
 #'
 #' @param phylo a phylogenetic tree
 #' @param var_diff result of function \code{compute_var_diff.BM}

R/generic_functions.R

@@ -666,7 +666,8 @@ check_dimensions.shifts <- function(p, shifts){
 #' @title Find a reasonable grid for alpha
 #' 
 #' @description Grid so that 
-#' 2*ln(2)*quantile(d_ij)/factor_up_alpha < t_{1/2} < factor_down_alpha * ln(2) * h_tree
+#' 2*ln(2)*quantile(d_ij)/factor_up_alpha < t_1/2 < factor_down_alpha * ln(2) * h_tree,
+#' with t_1/2 the phylogenetic half life: t_1/2 = log(2)/alpha.
 #' Ensures that for alpha_min, it is almost a BM, and for alpha_max,
 #' almost all the tips are decorrelated.
 #' 

R/parsimonyNumber.R

@@ -150,7 +150,7 @@ extract.parsimonyCost <- function(x,
 #' 
 #' @details
 #' At a tip i in state k, the line-vector is initialized as follow : 
-#' (1 - Ind(k=p)_{1<=p<=nclus})*Inf (where Inf * 0 = 0)
+#' (1 - Ind(k=p)_\{1<=p<=nclus\})*Inf (where Inf * 0 = 0)
 #'
 #' @param phy a phylogenetic tree, class \code{\link[ape]{phylo}}.
 #' @param clusters the vector of the clusters of the tips.
@@ -356,7 +356,7 @@ extract.parsimonyNumber <- function(x,
 #' NAs everywhere, except for the tips.
 #' 
 #' @details
-#' At a tip i in state k, the line-vector is initialized as follow : Ind(k=p)_{1<=p<=nclus}
+#' At a tip i in state k, the line-vector is initialized as follow : Ind(k=p)_\{1<=p<=nclus\}
 #'
 #' @param phy phylogenetic tree.
 #' @param clusters the vector of the clusters of the tips.

R/shifts_manipulations.R

@@ -334,7 +334,7 @@ shifts.matrix_to_list <- function(delta){
 #'
 #' @description
 #' \code{incidence_matrix_actualization_factors} computes a ntaxa x Nedge matrix of the 
-#' (1 - exp(-alpha * (t_i - t_pa(j) - nu_j * l_j)))_{i tip, j node}.
+#' (1 - exp(-alpha * (t_i - t_pa(j) - nu_j * l_j)))_\{i tip, j node\}.
 #' This matrix is to be multiplied to the incidence matrix with an outer product.
 #'
 #' @param tree a phylogenetic tree.
@@ -375,7 +375,7 @@ incidence_matrix_actualization_factors <- function(tree,
 #'
 #' @description
 #' \code{compute_actualization_matrix_ultrametric} computes a squares  p*Nedge bloc diagonal
-#' matrix of the (I_p - exp(-A * (h - t_pa(j))))_{j node}.
+#' matrix of the (I_p - exp(-A * (h - t_pa(j))))_\{j node\}.
 #'
 #' @details
 #' Careful: the root is not taken into account in this function.
@@ -419,7 +419,7 @@ compute_actualization_matrix_ultrametric <- function(tree,
 #' tips, with the value at the root.
 #'
 #' @details
-#' This function is used in function \code{compute_betas_from_shifts_from_shifts} and is designed to 
+#' This function is used in function \code{compute_betas_from_shifts} and is designed to 
 #' furnish function \code{update.compute_betas_from_shifts} with the right structure of data.
 #'
 #' @param phy Input tree.

R/shutoff.R

@@ -120,86 +120,6 @@ shutoff.EM.OU.stationary.root_AND_shifts_at_nodes.half_life <- function(params_o
   }
 }
 
-#' ######################################################
-#' ## Finite parameters ?
-#' ######################################################
-# ##
-# # @title Check whether parameters are finite.
-# #
-# # @description
-# # \code{is.finite.params} checks whether calculated parameters in the EM are
-# # finite or not.
-# #
-# # @details
-# # This function is used to test the convergence of the algorithm.
-# #
-# # @param params list of parameters with the correct structure
-# #
-# # @return boolean
-# # 
-# # @keywords internal
-# #
-# #10/06/14 - Initial release
-# ##
-#' 
-#' is.finite.params.BM <- function(params) {
-#'   if (params$root.state$random) {
-#'     return(is.finite.params.BM.randroot(params))
-#'   } else {
-#'     return(is.finite.params.BM.fixedroot(params))
-#'   }
-#' }
-#' 
-#' is.finite.params.BM.randroot <- function(params) {
-#'   if (is.finite(params$variance) &&
-#'         is.finite(params$root.state$exp.root) &&
-#'         is.finite(params$root.state$var.root) ) {
-#'     return(TRUE)
-#'   } else {
-#'     return(FALSE)
-#'   }
-#' }
-#' 
-#' is.finite.params.BM.fixedroot <- function(params) {
-#'   if ( is.finite(params$variance) &&
-#'          is.finite(params$root.state$value.root) ) {
-#'     return(TRUE)
-#'   } else {
-#'     return(FALSE)
-#'   }
-#' }
-#' 
-#' is.finite.params.OU <- function(stationary.root, shifts_at_nodes, alpha_known){
-#'   if (stationary.root && shifts_at_nodes && alpha_known) {
-#'     return(is.finite.params.OU.specialCase)
-#'   } else if (stationary.root && shifts_at_nodes) {
-#'     return(is.finite.params.OU.stationary.root_AND_shifts_at_nodes)
-#'   } else {
-#'     stop("The EM algorithm for the OU is only defined (for the moment) for a stationary root and shifts at nodes !")
-#'   }
-#' }
-#' 
-#' is.finite.params.OU.specialCase <- function(params) {
-#'   if (is.finite(params$variance) &&
-#'         is.finite(params$root.state$exp.root) &&
-#'         is.finite(params$root.state$var.root) ) {
-#'     return(TRUE)
-#'   } else {
-#'     return(FALSE)
-#'   }
-#' }
-#' 
-#' is.finite.params.OU.stationary.root_AND_shifts_at_nodes <- function(params) {
-#'   if (is.finite(params$variance) &&
-#'         is.finite(params$root.state$exp.root) &&
-#'         is.finite(params$root.state$var.root) &&
-#'         is.finite(params$selection.strength)) {
-#'     return(TRUE)
-#'   } else {
-#'     return(FALSE)
-#'   }
-#' }
-
 #################################################################
 ## Are parameters in ranges ?
 #################################################################