Merge pull request #110 from tlverse/fix-matrix

Fix matrix

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: hal9001
 Title: The Scalable Highly Adaptive Lasso
-Version: 0.4.3
+Version: 0.4.6
 Authors@R: c(
   person("Jeremy", "Coyle", email = "[email protected]",
          role = c("aut", "cre"),
@@ -68,5 +68,5 @@ LinkingTo:
   Rcpp,
   RcppEigen
 VignetteBuilder: knitr
-RoxygenNote: 7.2.0
+RoxygenNote: 7.2.3
 Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -26,18 +26,15 @@ importFrom(data.table,setorder)
 importFrom(glmnet,cv.glmnet)
 importFrom(glmnet,glmnet)
 importFrom(methods,is)
-importFrom(origami,cross_validate)
 importFrom(origami,folds2foldvec)
 importFrom(origami,make_folds)
 importFrom(stats,aggregate)
 importFrom(stats,as.formula)
 importFrom(stats,coef)
-importFrom(stats,gaussian)
 importFrom(stats,median)
 importFrom(stats,plogis)
 importFrom(stats,predict)
 importFrom(stats,quantile)
-importFrom(stats,sd)
 importFrom(stringr,str_detect)
 importFrom(stringr,str_extract)
 importFrom(stringr,str_match)

NEWS.md

@@ -1,3 +1,24 @@
+# hal9001 0.4.6
+* Fixed predict method to address changes required by Matrix 1.6.2
+
+# hal9001 0.4.5
+* Added multivariate outcome prediction
+
+# hal9001 0.4.4
+* Fixed bug with `prediction_bounds` (a `fit_hal` argument in `fit_control` 
+  list), which would error when it was specified as a numeric vector. Also, 
+  added a check to assert this argument is correctly specified, and tests
+  to ensure a numeric vector of bounds is provided.
+* Simplified `fit_control` list arguments in `fit_hal`. Users can still specify
+  additional arguments to `cv.glmnet` and `glmnet` in this list.
+* Defined `weights` as a formal argument in `fit_hal`, opposed to an optional
+  argument in `fit_control`, to facilitate specification and avoid confusion. 
+  This increases flexibility with SuperLearner wrapper `SL.hal9001` as well; 
+  `fit_control` can now be customized with `SL.hal9001`.
+
+# hal9001 0.4.3
+* Version bump for CRAN resubmission following archiving.
+
 # hal9001 0.4.2
 * Version bump for CRAN resubmission following archiving.
 

R/formula_hal9001.R

@@ -143,7 +143,7 @@ h <- function(..., k = NULL, s = NULL, pf = 1,
     var_names <- unlist(list(...))
   }
   formula_term <- paste0("h(", paste0(var_names, collapse = ", "), ")")
-  
+
   if (is.null(k)) {
     k <- get("num_knots", envir = parent.frame())
     k <- suppressWarnings(k + rep(0, length(var_names))) # recycle
@@ -152,8 +152,8 @@ h <- function(..., k = NULL, s = NULL, pf = 1,
   if (is.null(s)) {
     s <- get("smoothness_orders", envir = parent.frame())[1]
   }
-  
-  
+
+
   if ("." %in% var_names) {
     var_names_filled <- fill_dots(var_names, . = .)
 
@@ -186,7 +186,7 @@ h <- function(..., k = NULL, s = NULL, pf = 1,
     return(all_items)
   }
 
-   
+
 
 
   # Get corresponding column indices
@@ -240,6 +240,7 @@ h <- function(..., k = NULL, s = NULL, pf = 1,
   return(out)
 }
 
+
 #' Print formula_hal9001 object
 #'
 #' @param x A formula_hal9001 object.
@@ -250,16 +251,18 @@ print.formula_hal9001 <- function(x, ...) {
   cat(paste0("A hal9001 formula object of the form: ~ ", x$formula_term))
 }
 
-#' Formula Helpers
 #'
-#' @param var_names A \code{character} vector of variable names.
+#' @param var_names A \code{character} vector of variable names representing a single type of interaction
+# " (e.g. var_names = c("W1", "W2", "W3") encodes three way interactions between W1, W2 and W3.
+#' var_names may include the wildcard variable "." in which case the argument `.` must be specified
+#' so that all interactions matching the form of var_names are generated.
 #' @param . Specification of variables for use in the formula.
-#'
-#' @name formula_helpers
-NULL
-
+#'   This function takes a character vector `var_names` of the form c(name1, name2, ".", name3, ".")
+#' with any number of name{int} variables and any number of wild card variables ".".
+#' It returns a list of character vectors of the form c(name1, name2, wildcard1, name3, wildcard2)
+#' where wildcard1 and wildcard2 are iterated over all possible character names given in the argument `.`.
 #' @rdname formula_helpers
-fill_dots_helper <- function(var_names, .) {
+fill_dots <- function(var_names, .) {
   index <- which(var_names == ".")
   if (length(index) == 0) {
     return(sort(var_names))
@@ -269,26 +272,23 @@ fill_dots_helper <- function(var_names, .) {
   all_items <- lapply(., function(var) {
     new_var_names <- var_names
     new_var_names[index] <- var
-    out <- fill_dots_helper(new_var_names, .)
-
-    if (is.list(out[[1]])) {
-      out <- unlist(out, recursive = FALSE)
-    }
+    out <- fill_dots(new_var_names, .)
     return(out)
   })
-
-
-  return(unique(all_items))
-}
-
-#' @rdname formula_helpers
-fill_dots <- function(var_names, .) {
-  x <- unique(unlist(fill_dots_helper(var_names, . = .), recursive = FALSE))
-  keep <- sapply(x, function(item) {
+  is_nested <- is.list(all_items[[1]])
+  while (is_nested) {
+    all_items <- unlist(all_items, recursive = FALSE)
+    is_nested <- is.list(all_items[[1]])
+  }
+  # Remove combinations of variable names that have duplicates.
+  # This removes generated interactions that include two of the same variable.
+  keep <- sapply(all_items, function(item) {
     if (any(duplicated(item))) {
       return(FALSE)
     }
     return(TRUE)
   })
-  return(x[keep])
+  all_items <- all_items[keep]
+
+  return(unique(all_items))
 }