wip: convert to R-package

tensorPredictors/DESCRIPTION

@@ -0,0 +1,13 @@
+Package: tensorPredictors
+Type: Package
+Title: Tensor/Matrix valued predictors for regression and dimension reduction
+Version: 0.1
+Date: 2021-10-28
+Author: Daniel Kapla [aut]
+Maintainer: Daniel Kapla <daniel@kapla.at>
+Description: Multiple methods using tensor/matrix valued predictors for
+    regression or sufficient dimension reduction.
+License: GPL-3
+Depends: 
+Encoding: UTF-8
+RoxygenNote: 7.1.1

tensorPredictors/NAMESPACE

@@ -0,0 +1,7 @@
+# Generated by roxygen2: do not edit by hand
+
+export(LSIR)
+export(PCA2d)
+export(POI)
+export(approx.kronecker)
+useDynLib(tensorPredictors, .registration = TRUE)

tensorPredictors/R/approx_kronecker.R

@@ -22,6 +22,7 @@
 #'
 #' @imports RSpectra
 #'
+#' @export
 approx.kronecker <- function(C, dimA, dimB) {
 
     dim(C) <- c(dimB[1L], dimA[1L], dimB[2L], dimA[2L])

tensorPredictors/R/lsir.R

@@ -1,5 +1,3 @@
-source('../tensor_predictors/matpow.R')
-
 #' Longitudinal Sliced Inverse Regression
 #'
 #' @param X matrix of dim \eqn{n \times p t} with each row representing a
@@ -13,6 +11,7 @@ source('../tensor_predictors/matpow.R')
 #'
 #' TODO: finish
 #'
+#' @export
 LSIR <- function(X, y, p, t, k = 1L, r = 1L) {
     # the code assumes:
     # alpha: T x r, beta: p x k, X_i: p x T, for ith observation

tensorPredictors/R/matpow.R

@@ -55,6 +55,7 @@
 #' all.equal(B %*% A, t(B %*% A))
 #' all.equal(A %*% B, t(A %*% B))
 #'
+#' @keywords internal
 matpow <- function(A, pow, tol = 1e-7) {
     if (nrow(A) != ncol(A)) {
         stop("Expected a square matix, but 'A' is ", nrow(A), " by ", ncol(A))

tensorPredictors/R/multi_assign.R

@@ -22,6 +22,7 @@
 #' c(d1, d2, d3) %<-% 1:10
 #' extracting the first three valus from the vector of length 10.
 #'
+#' @keywords internal
 "%<-%" <- function(lhs, rhs) {
     var.names <- make.names(as.list(substitute(lhs))[-1])
     values <- as.list(rhs)

tensorPredictors/R/pca2d.R

@@ -1,4 +1,5 @@
-
+#'2-Dimensional Principal Component Analysis
+#'
 #' @param X Matrix of dim (n, p * t) with each row the vectorized (p, t) observation.
 #' @param p nr. predictors
 #' @param t nr. timepoints
@@ -7,7 +8,8 @@
 #'
 #' @details The `i`th observation is stored in a row such that its matrix equiv
 #'  is given by `matrix(X[i, ], p, t)`.
-#' 
+#'
+#' @export
 PCA2d <- function(X, p, t, ppc, tpc, scale = FALSE) {
     stopifnot(ncol(X) == p * t, ppc <= p, tpc <= t)
 

tensorPredictors/R/poi.R

@@ -4,6 +4,8 @@
 #'
 #' @note use.C required 'poi.so' beeing dynamicaly loaded.
 #'  dyn.load('../tensor_predictors/poi.so')
+#'
+#' @export
 POI <- function(A, B, d,
                 lambda = 0.75 * sqrt(max(rowSums(Delta^2))),
                 update.tol = 1e-3,
@@ -33,7 +35,7 @@ POI <- function(A, B, d,
     # The "inner" optimization loop, aka repeated coordinate optimization.
     if (use.C) {
         Z <- .Call('FastPOI_C_sub', A, B, Delta, lambda, as.integer(maxit.inner),
-                   PACKAGE = 'poi')
+                   PACKAGE = 'tensorPredictors')
     } else {
         p <- nrow(Z)
         for (iter.inner in 1:maxit.inner) {

tensorPredictors/R/tensor_predictors.R

@@ -1,6 +1,13 @@
-source('../tensor_predictors/matpow.R')
-source('../tensor_predictors/multi_assign.R')
-source('../tensor_predictors/approx_kronecker.R')
+#' Tensor/Matrix valued Predictors for Regression and Dimension Reduction
+#'
+#' Multiple methods using tensor/matrix valued predictors for regression or
+#' sufficient dimension reduction.
+#'
+#' @author Daniel Kapla
+#'
+#' @docType package
+#' @useDynLib tensorPredictors, .registration = TRUE
+"_PACKAGE"
 
 log.likelihood <- function(par, X, Fy, Delta.inv, da, db) {
     alpha <- matrix(par[1:prod(da)], da[1L])

tensorPredictors/src/poi.c

@@ -3,7 +3,8 @@
 #include <R.h>
 #include <Rinternals.h>
 
-SEXP FastPOI_C_sub(SEXP in_A, SEXP in_B, SEXP in_Delta, SEXP in_lambda, SEXP in_maxit) {
+/* invoced by .Call */
+extern SEXP FastPOI_C_sub(SEXP in_A, SEXP in_B, SEXP in_Delta, SEXP in_lambda, SEXP in_maxit) {
     int i, j, k, g;
 
     int p = nrows(in_Delta);
@@ -72,3 +73,14 @@ SEXP FastPOI_C_sub(SEXP in_A, SEXP in_B, SEXP in_Delta, SEXP in_lambda, SEXP in_
     UNPROTECT(1);
     return out_Z;
 }
+
+static const R_CallMethodDef CallEntries[] = {
+    {"FastPOI_C_sub", (DL_FUNC) &FastPOI_C_sub, 5},
+    {NULL, NULL, 0}
+};
+
+/* Restrict C entry points to registered routines. */
+void R_init_CVE(DllInfo *dll) {
+    R_registerRoutines(dll, NULL, CallEntries, NULL, NULL);
+    R_useDynamicSymbols(dll, FALSE);
+}