Incorporate methods documentations remove extra functions

apeterson91 · Jul 25, 2020 · 9591982 · 9591982
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: rstapDP
 Type: Package
 Title: Functional Dirichlet Process Spatial Temporal Aggregated Predicators in R
 Version: 0.1.0
-Date: 2020-07-16
+Date: 2020-07-25
 Authors@R: person("Adam", "Peterson", , "atpvyc@umich.edu", c("aut", "cre"))
 Encoding: UTF-8
 Description: rsstap is a package that implements spatial-temporal aggregated predictor functions using splines in R. This allows for the modeling of features impact on measured subjects that can be related either through space or time.

diff --git a/NAMESPACE b/NAMESPACE
@@ -1,7 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method(diagnostics,stapDP)
-S3method(green_loss,stapDP)
 S3method(plot,stapDP)
 S3method(plot_pairs,stapDP)
 S3method(plotpars,stapDP)
@@ -12,7 +11,6 @@ export("%>%")
 export(diagnostics)
 export(fdp_staplm)
 export(fdp_staplm.fit)
-export(green_loss)
 export(plot_pairs)
 export(plotpars)
 export(ppc)

diff --git a/R/RcppExports.R b/R/RcppExports.R
@@ -26,31 +26,3 @@ stappDP_fit <- function(y, Z, X, S, w, alpha_a, alpha_b, sigma_a, sigma_b, tau_a
     .Call(`_rstapDP_stappDP_fit`, y, Z, X, S, w, alpha_a, alpha_b, sigma_a, sigma_b, tau_a, tau_b, K, num_penalties, iter_max, burn_in, thin, seed, num_posterior_samples, fix_alpha)
 }
 
-#' Computes Green and Lau loss function with unknown classification
-#'
-#' @param cluster_assignment iter_total x J cluster assignment matrix
-#' @param pmat J x J pairwise probability of co-clustering matrix
-#' @param tau penalty parameter 
-green_loss_unknown <- function(cluster_assignment, pmat, tau) {
-    .Call(`_rstapDP_green_loss_unknown`, cluster_assignment, pmat, tau)
-}
-
-#' Computes Green and Lau Loss function with known classification
-#'
-#' @param cluster_assignment iter_total x J cluster assignment matrix
-#' @param pmat J x J pairwise probability of co-clustering matrix
-#' @param true_cluster_assignment J x J true Adjacency Matrix
-#' @param a mis-classification penalty parameter
-#' @param b classification penalty parameter
-green_loss_known <- function(cluster_assignment, pmat, true_cluster_assignment, a, b) {
-    .Call(`_rstapDP_green_loss_known`, cluster_assignment, pmat, true_cluster_assignment, a, b)
-}
-
-#' Computes Square loss with unknown classification
-#'
-#' @param cluster_assignment iter_total x J cluster assignment matrix
-#' @param pmat J x J pairwise probability of co-clustering matrix
-square_error <- function(cluster_assignment, pmat) {
-    .Call(`_rstapDP_square_error`, cluster_assignment, pmat)
-}
-
diff --git a/R/green_loss.R b/R/green_loss.R
diff --git a/docs/articles/Introduction_files/figure-html/pairs-1.png b/docs/articles/Introduction_files/figure-html/pairs-1.png
diff --git a/docs/articles/Introduction_files/figure-html/ppcs-1.png b/docs/articles/Introduction_files/figure-html/ppcs-1.png
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
@@ -3,5 +3,5 @@ pkgdown: 1.5.1
 pkgdown_sha: ~
 articles:
   Introduction: Introduction.html
-last_built: 2020-07-25T22:34Z
+last_built: 2020-07-25T23:14Z
 
diff --git a/docs/reference/diagnostics.html b/docs/reference/diagnostics.html
diff --git a/docs/reference/index.html b/docs/reference/index.html
diff --git a/man/diagnostics.Rd b/man/diagnostics.Rd
diff --git a/man/green_loss.Rd b/man/green_loss.Rd
diff --git a/man/green_loss_known.Rd b/man/green_loss_known.Rd
diff --git a/man/green_loss_unknown.Rd b/man/green_loss_unknown.Rd
diff --git a/man/plot.stapDP.Rd b/man/plot.stapDP.Rd
diff --git a/man/plot_pairs.Rd b/man/plot_pairs.Rd
diff --git a/man/plotpars.Rd b/man/plotpars.Rd
diff --git a/man/ppc.Rd b/man/ppc.Rd
diff --git a/man/square_error.Rd b/man/square_error.Rd
diff --git a/man/traceplots.Rd b/man/traceplots.Rd
diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp
@@ -35,52 +35,9 @@ BEGIN_RCPP
     return rcpp_result_gen;
 END_RCPP
 }
-// green_loss_unknown
-Eigen::ArrayXd green_loss_unknown(const Eigen::ArrayXXi& cluster_assignment, const Eigen::ArrayXXd& pmat, const double& tau);
-RcppExport SEXP _rstapDP_green_loss_unknown(SEXP cluster_assignmentSEXP, SEXP pmatSEXP, SEXP tauSEXP) {
-BEGIN_RCPP
-    Rcpp::RObject rcpp_result_gen;
-    Rcpp::RNGScope rcpp_rngScope_gen;
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXi& >::type cluster_assignment(cluster_assignmentSEXP);
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXd& >::type pmat(pmatSEXP);
-    Rcpp::traits::input_parameter< const double& >::type tau(tauSEXP);
-    rcpp_result_gen = Rcpp::wrap(green_loss_unknown(cluster_assignment, pmat, tau));
-    return rcpp_result_gen;
-END_RCPP
-}
-// green_loss_known
-Eigen::ArrayXd green_loss_known(const Eigen::ArrayXXi& cluster_assignment, const Eigen::ArrayXXd& pmat, const Eigen::ArrayXXi& true_cluster_assignment, const double& a, const double& b);
-RcppExport SEXP _rstapDP_green_loss_known(SEXP cluster_assignmentSEXP, SEXP pmatSEXP, SEXP true_cluster_assignmentSEXP, SEXP aSEXP, SEXP bSEXP) {
-BEGIN_RCPP
-    Rcpp::RObject rcpp_result_gen;
-    Rcpp::RNGScope rcpp_rngScope_gen;
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXi& >::type cluster_assignment(cluster_assignmentSEXP);
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXd& >::type pmat(pmatSEXP);
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXi& >::type true_cluster_assignment(true_cluster_assignmentSEXP);
-    Rcpp::traits::input_parameter< const double& >::type a(aSEXP);
-    Rcpp::traits::input_parameter< const double& >::type b(bSEXP);
-    rcpp_result_gen = Rcpp::wrap(green_loss_known(cluster_assignment, pmat, true_cluster_assignment, a, b));
-    return rcpp_result_gen;
-END_RCPP
-}
-// square_error
-Eigen::ArrayXd square_error(const Eigen::ArrayXXi& cluster_assignment, const Eigen::ArrayXXd& pmat);
-RcppExport SEXP _rstapDP_square_error(SEXP cluster_assignmentSEXP, SEXP pmatSEXP) {
-BEGIN_RCPP
-    Rcpp::RObject rcpp_result_gen;
-    Rcpp::RNGScope rcpp_rngScope_gen;
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXi& >::type cluster_assignment(cluster_assignmentSEXP);
-    Rcpp::traits::input_parameter< const Eigen::ArrayXXd& >::type pmat(pmatSEXP);
-    rcpp_result_gen = Rcpp::wrap(square_error(cluster_assignment, pmat));
-    return rcpp_result_gen;
-END_RCPP
-}
 
 static const R_CallMethodDef CallEntries[] = {
     {"_rstapDP_stappDP_fit", (DL_FUNC) &_rstapDP_stappDP_fit, 19},
-    {"_rstapDP_green_loss_unknown", (DL_FUNC) &_rstapDP_green_loss_unknown, 3},
-    {"_rstapDP_green_loss_known", (DL_FUNC) &_rstapDP_green_loss_known, 5},
-    {"_rstapDP_square_error", (DL_FUNC) &_rstapDP_square_error, 2},
     {NULL, NULL, 0}
 };