mihaiconstantin · mihaiconstantin · Apr 12, 2023 · Apr 12, 2023 · Apr 12, 2023 · Apr 12, 2023
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -26,7 +26,6 @@ Imports:
     parallel,
     splines2,
     quadprog,
-    osqp,
     bootnet,
     qgraph,
     ggplot2,
@@ -53,7 +52,6 @@ Collate:
     'StepOne.R'
     'Range.R'
     'Method.R'
-    'OsqpSolver.R'
     'QuadprogSolver.R'
     'Solver.R'
     'SolverFactory.R'

diff --git a/NAMESPACE b/NAMESPACE
@@ -41,8 +41,6 @@ importFrom(ggplot2,stat_ecdf)
 importFrom(ggplot2,theme)
 importFrom(ggplot2,theme_bw)
 importFrom(mvtnorm,rmvnorm)
-importFrom(osqp,osqp)
-importFrom(osqp,osqpSettings)
 importFrom(parallel,clusterCall)
 importFrom(parallel,clusterEvalQ)
 importFrom(parallel,clusterExport)

diff --git a/R/OsqpSolver.R b/R/OsqpSolver.R
diff --git a/R/SolverFactory.R b/R/SolverFactory.R
@@ -1,11 +1,10 @@
-#' @include OsqpSolver.R QuadprogSolver.R
+#' @include QuadprogSolver.R
 
 SolverFactory <- R6::R6Class("SolverFactory",
     public = list(
         get_solver = function(type) {
             return(
                 switch(type,
-                    osqp = OsqpSolver$new(),
                     quadprog = QuadprogSolver$new(),
                     stop(.__ERRORS__$not_developed)
                 )

diff --git a/R/powerly-package.R b/R/powerly-package.R
@@ -28,7 +28,6 @@
 #' @importFrom patchwork plot_layout
 #' @importFrom R6 R6Class
 #' @importFrom bootnet genGGM ggmGenerator
-#' @importFrom osqp osqpSettings osqp
 #' @importFrom progress progress_bar
 #' @importFrom qgraph EBICglasso
 #' @importFrom quadprog solve.QP

diff --git a/docs/reference/function/powerly.md b/docs/reference/function/powerly.md
@@ -60,7 +60,7 @@ powerly(
 |    `monotone`     | A logical value indicating whether a monotonicity assumption should be placed on the values of the performance measure. The default is `TRUE` meaning that the performance measure changes as a function of sample size (i.e., either by increasing or decreasing as the sample size goes up). The alternative `FALSE` indicates that the performance measure it is not assumed to change as a function a sample size.     |
 |   `increasing`    | A logical value indicating whether the performance measure is assumed to follow a non-increasing or non-decreasing trend. `TRUE` (the default) indicates a non-decreasing trend (i.e., the performance measure increases as the sample size goes up). `FALSE` indicates a non-increasing trend (i.e., the performance measure decreases as the sample size goes up).                                                       |
 |    `spline_df`    | A vector of positive integers representing the degrees of freedom considered for constructing the spline basis, or `NULL`. The best degree of freedom is selected based on Leave One Out Cross-Validation. If `NULL` (the default) is provided, a vector of degrees of freedom is automatically created with all integers between `3` and `20`.                                                                            |
-|   `solver_type`   | A character string representing the type of the quadratic solver used for estimating the spline coefficients. Possible values are `"quadprog"` (the default) and `"osqp"`. Currently, the "`osqp`" solver does not play nicely with `R`'s [`parallel`](https://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf) package and cannot be used when the `powerly` function is ran in parallel.                 |
+|   `solver_type`   | A character string representing the type of the quadratic solver used for estimating the spline coefficients. Currently only `"quadprog"` (the default) is supported.                                                                                                                                                                                                                                                      |
 |      `boots`      | A positive integer representing the number of bootstrap runs to perform on the matrix of performance measures in order to obtained bootstrapped values for the statistic of interest. The default is `10000`.                                                                                                                                                                                                              |
 |    `lower_ci`     | A single numerical value indicating the lower bound for the confidence interval to be computed on the bootstrapped statistics. The default is `0.025` (i.e., $2.5\%$).                                                                                                                                                                                                                                                     |
 |    `upper_ci`     | A single numerical value indicating the upper bound for the confidence to be computed on the bootstrapped statistics. The default is `0.975` (i.e., $97.5\%$).                                                                                                                                                                                                                                                             |

diff --git a/man-roxygen/powerly.R b/man-roxygen/powerly.R
@@ -69,10 +69,8 @@
 #' automatically created with all integers between `3` and `20`.
 #'
 #' @param solver_type A character string representing the type of the quadratic
-#' solver used for estimating the spline coefficients. Possible values are
-#' `"quadprog"` (the default) and `"osqp"`. Currently, the "`osqp`" solver does
-#' not play nicely with `R`'s [`parallel::parallel`] package and cannot be used
-#' when powerly is ran in parallel.
+#' solver used for estimating the spline coefficients. Currently only
+#' `"quadprog"` (the default) is supported.
 #'
 #' @param boots A positive integer representing the number of bootstrap runs to
 #' perform on the matrix of performance measures in order to obtained

diff --git a/man/powerly.Rd b/man/powerly.Rd
diff --git a/tests/testthat/helpers.R b/tests/testthat/helpers.R
@@ -13,38 +13,6 @@ solve_qp <- function(basis_matrix, y, a_mat, b_vec, meq = 0) {
     return(quadprog::solve.QP(Dmat = d_mat, dvec = d_vec, Amat = t(a_mat), bvec = b_vec, meq = meq)$solution)
 }
 
-# Helper based on `osqp` for testing the `Solver` class.
-solve_osqp <- function(basis_matrix, y, lower, upper) {
-    # Set settings.
-    settings <- osqp::osqpSettings(
-        verbose = FALSE,
-        eps_abs = 1e-10,
-        eps_rel = 1e-10,
-        linsys_solver = 0L,
-        warm_start = FALSE
-    )
-
-    # Create matrices for `osqp`.
-    p_mat <- crossprod(basis_matrix, basis_matrix)
-    q_vec <- -crossprod(basis_matrix, y)
-
-    # Create constraint matrix.
-    a_mat <- diag(1, ncol(basis_matrix))
-
-    # Create model.
-    model <- osqp::osqp(
-        P = p_mat,
-        q = q_vec,
-        A = a_mat,
-        l = lower,
-        u = upper,
-        pars = settings
-    )
-
-    # Optimize.
-    return(model$Solve()$x)
-}
-
 # Compute performance measures.
 compute_measure <- function(true_parameters, estimated_parameters, measure) {
     # Extract the true and estimated parameters from the weights matrices.