fixed up spurious document build

R/RcppExports.R

@@ -48,7 +48,7 @@ distance_matrix_cpp <- function(facility, user) {
 #' you are interested in. If a number is less than distance_cutoff, it will be
 #' 1, if it is greater than it, it will be 0.
 #'
-#' @return a logical matrix 1 if distance between element[i,j] is less than or
+#' @return a logical matrix 1 if distance between element i, j is less than or
 #' equal to the distance_cutoff, and 0 otherwise
 #'
 #' @export

R/extract_mc_result.R

@@ -15,14 +15,14 @@
 
 extract_mc_results <- function(x){
 
-# find the facilities selected ------------------------------------------------
+# find the facilities selected ================================================
 
     mc_facilities_selected <- extract_facility_selected(
         solution_vector = x$lp_solution$solution,
         A_mat = x$A,
         proposed_facilities = x$proposed_facility)
 
-# user_affected ---------------------------------------------------------------
+# user_affected ==============================================================
 
     mc_users_affected <- extract_users_affected(
         A_mat = x$A,
@@ -90,7 +90,7 @@ extract_mc_results <- function(x){
 }
 
 #
-#     # extract results ---------------------------------------------------------
+#     # extract results =======================================================
 #
 #     # get the dimenions from the matrix
 #     J <- nrow(x$A)

R/extract_mc_result_relocation.R

@@ -316,7 +316,7 @@ extract_mc_results_relocation <- function(x){
 #     # n_existing_removed
 #     # which_existing_removed
 #
-#     # back to old summary method ---------------------------------------------------
+#     # back to old summary method =============================================
 #
 #     # ... surprisingly (!) this works with very few changes  good job, past nick!
 #

R/facility_user_dist.R

@@ -35,7 +35,7 @@ facility_user_dist <- function(facility,
                                coverage_distance = 100,
                                nearest = "facility"){
 
-    # check that lat and long are specified -----------------------------------
+    # check that lat and long are specified
     # if(
     #     (c("lat") %in% names(facility) == TRUE) |
     #     (c("long") %in% names(facility) == TRUE) |
@@ -45,7 +45,7 @@ facility_user_dist <- function(facility,
     #     warning("make sure lat and long are in the names")
     # }
 
-    # dodgy method to get the cross product ---------------------------------------
+    # dodgy method to get the cross product
 
     # do a dodgy cross product by adding a column of 1
     # and then joining on this column

R/max_cov_relocation.R

@@ -118,7 +118,7 @@ c <- c(rep(0, Ny), rep(1,Nx))
 # this is a line to optimise with cpp
 Ain <- cbind(-A, diag(Nx))
 
-# create the m vector ----------------------------------------------------------
+# create the m vector =========================================================
 
 # this is the vector of costs, which will have the length
 # of the number of rows of y plus the number of x's as 0s

R/maxcovr-refactor-vectors.R

@@ -61,7 +61,7 @@ max_coverage_vec <- function(existing_facility = NULL,
     # constraint_dir
     # rhs
 
-# create objective -------------------------------------------------------------
+# create objective =============================================================
     # this should be made into a function that would perform different
     # functions based on whether relocation == TRUE
 
@@ -121,12 +121,12 @@ c <- c(rep(0, Ny), rep(1,Nx))
     # Ny
     # c (objective_in)
 
-# perform extra functions for data munging -------------------------------------
+# perform extra functions for data munging ===================================
 facility_id_list <- 1:nrow(proposed_facility)
 colnames(A) <- facility_id_list
 user_id_list <- 1:nrow(user_not_covered)
 
-# create constraint matrix -----------------------------------------------------
+# create constraint matrix ====================================================
     # this should be made into a function that would perform different
     # functions based on whether relocation == TRUE
     # create_constraint_matrix(..., relocation){
@@ -143,7 +143,7 @@ constraint_matrix <- rbind(
     c(rep(1, Ny), rep(0,Nx))
     )
 
-# create constraint directions -------------------------------------------------
+# create constraint directions ================================================
 
 # lpSolve: const.dir
 # glpk: dir
@@ -164,7 +164,7 @@ constraint_directions <- c(rep("<=", Nx), "==")
 
 } # end else
 
-# create right hand side matrix ------------------------------------------------
+# create right hand side matrix ===============================================
 
 # bin <- matrix(rep(0,Nx), ncol = 1)
 # rhs_matrix <- rbind(bin, beq)
@@ -180,7 +180,7 @@ rhs_matrix <- purrr::map(
     )
 )
 
-# solve the model --------------------------------------------------------------
+# solve the model =============================================================
 
 # at this point, all of the model outputs, independent of being relocation or
 # not, are ready for the analysis.
@@ -301,7 +301,7 @@ x <- list(
     # model_call = model_call
 )
 
-# extract the model results ----------------------------------------------------
+# extract the model results ===================================================
 
 # this is a place where I'll need to generalise it into separate function for
 # relocation and fixed methods.
@@ -440,7 +440,7 @@ return(res)
 
 
 
-# return the model -------------------------------------------------------------
+# return the model ===========================================================
 
 # model_result <- extract_mc_results_2(x)
 

src/distanceHelpers.cpp

@@ -91,7 +91,7 @@ return dist_mat;
 //' you are interested in. If a number is less than distance_cutoff, it will be
 //' 1, if it is greater than it, it will be 0.
 //'
-//' @return a logical matrix 1 if distance between element[i,j] is less than or
+//' @return a logical matrix 1 if distance between element i, j is less than or
 //' equal to the distance_cutoff, and 0 otherwise
 //'
 //' @export

tests/testthat/test_distance_matrix.R

@@ -29,7 +29,7 @@ my_dist_cpp <- distance_matrix_cpp(facility_test_cpp, user_test_cpp)
 
 # my_dist_cpp[1:5,1:5]
 
-# compare this to the dplyr method ---------------------------------------------
+# compare this to the dplyr method ============================================
 
 # maxcovr::facility_user_dist(facility = york,
 #                                          user = york_crime,
@@ -65,10 +65,6 @@ my_dist_dplyr <- user %>%
     select(-user_id) %>%
     as.matrix()
 
-# my_dist_dplyr[1:5,1:5]
-
-# my_dist_dplyr <-
-# -----------------
 
 testthat::test_that("cpp distance matrix produces same numeric result as using dplyr method",{
     # I still need to make a method that gives the big matrix names

tests/testthat/test_nearest_distance.R

@@ -16,7 +16,7 @@ near_cpp <- nearest_facility_dist(facility = facility_test_cpp,
 #                                  coverage_distance = 100)
 
 
-# begin old dplyr way ---------------------------------------------------------
+# begin old dplyr way =========================================================
 
 facility <- dplyr::mutate(york, key = 1) %>%
     dplyr::rename(lat_facility = lat,