From 304f956a0a8cf33234ebb31dbfec2720acab8fe4 Mon Sep 17 00:00:00 2001
From: Nima Hejazi <nh@nimahejazi.org>
Date: Thu, 8 Feb 2018 15:06:52 -0800
Subject: [PATCH] unbreak the breakage

---
 R/adaptest.R | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/R/adaptest.R b/R/adaptest.R
index ff10ee9..243d02a 100644
--- a/R/adaptest.R
+++ b/R/adaptest.R
@@ -36,11 +36,11 @@ data_adapt <- function(Y,
                        negative,
                        parameter_wrapper,
                        SL_lib) {
-  if (!data.table::is.data.table(Y)) {
+  if (!is.data.frame(Y)) {
     if (!is.matrix(Y)) {
       stop("Argument Y must be a data.frame or a matrix.")
     }
-    Y <-  (Y)
+    Y <- as.matrix(Y)
   }
   if (!is.vector(A)) stop("Argument A must be numeric.")
   if (!is.null(W)) if (!is.matrix(W)) stop("Argument W must be matrix.")
@@ -362,7 +362,6 @@ adaptest <- function(Y,
 #' @param SL_lib character of \code{SuperLearner} library
 #'
 #' @importFrom origami training validation
-#' @importFrom data.table as.data.table
 #' @importFrom tmle tmle
 #
 cv_param_est <- function(fold,
@@ -375,6 +374,7 @@ cv_param_est <- function(fold,
                          Y_name,
                          A_name,
                          W_name) {
+
   # define training and validation sets based on input object of class "folds"
   param_data <- origami::training(data)
   estim_data <- origami::validation(data)
@@ -382,11 +382,11 @@ cv_param_est <- function(fold,
   # get param generating data (NOTE: these are data.table's)
   A_param <- param_data[, grep(A_name, colnames(data))]
   Y_param <- param_data[, grep(Y_name, colnames(data))]
-  W_param <- param_data[, grep(W_name, colnames(data))]
+  W_param <- param_data[, grep(W_name, colnames(data)), FALSE]
   # get estimation data (NOTE: these are data.table's)
   A_estim <- estim_data[, grep(A_name, colnames(data))]
   Y_estim <- estim_data[, grep(Y_name, colnames(data))]
-  W_estim <- estim_data[, grep(W_name, colnames(data))]
+  W_estim <- estim_data[, grep(W_name, colnames(data)), FALSE]
 
   # generate data-adaptive target parameter
   data_adaptive_index <- parameter_wrapper(