Fix checks: "R code for possible problems", "Rd files"/"metadata"/"cross-references"/"code/documentation mismatches"; kml_to_csv bug/tests

R/extdata.r

@@ -8,8 +8,8 @@
 #'
 #' @section Filename: walleye_detections.zip
 #'
-#' @usage
-#' system.file("extdata", "walleye_detections.zip", package="glatos")
+#' @examples
+#' system.file("extdata", "walleye_detections.zip", package = "glatos")
 #'
 #' @author Todd Hayden
 #'
@@ -37,8 +37,8 @@ NULL
 #'
 #' @section Filename: SMRSL_GLATOS_20140828.xlsm
 #'
-#' @usage
-#' system.file("extdata", "SMRSL_GLATOS_20140828.xlsm", package="glatos")
+#' @examples
+#' system.file("extdata", "SMRSL_GLATOS_20140828.xlsm", package = "glatos")
 #'
 #' @author Chris Holbrook
 #'
@@ -53,12 +53,12 @@ NULL
 #'
 #' @format Folder contains 30 sequentially labeled .png image files
 #'
-#' @name video images
+#' @name video-images
 #'
 #' @section Filename: frames
 #'
-#' @usage
-#' system.file("extdata", "frames", package="glatos")
+#' @examples
+#' system.file("extdata", "frames", package = "glatos")
 #'
 #' @author Todd Hayden
 #'
@@ -77,8 +77,8 @@ NULL
 #'
 #' @section Filename: shoreline.zip
 #'
-#' @usage
-#' system.file("extdata", "shoreline.zip", package="glatos")
+#' @examples
+#' system.file("extdata", "shoreline.zip", package = "glatos")
 #'
 #' @author Todd Hayden
 #'
@@ -95,7 +95,7 @@ NULL
 #'
 #' @section Filename: otn_aat_animals.csv
 #'
-#' @usage
+#' @examples
 #' system.file("extdata", "otn_aat_animals.csv", package = "glatos")
 #'
 #' @source Ryan Gosse, Ocean Tracking Network
@@ -111,7 +111,7 @@ NULL
 #'
 #' @section Filename: otn_aat_receivers.csv
 #'
-#' @usage
+#' @examples
 #' system.file("extdata", "otn_aat_receivers.csv", package = "glatos")
 #'
 #' @source Ryan Gosse, Ocean Tracking Network
@@ -127,7 +127,7 @@ NULL
 #'
 #' @section Filename: otn_aat_tag_releases.csv
 #'
-#' @usage
+#' @examples
 #' system.file("extdata", "otn_aat_tag_releases.csv", package = "glatos")
 #'
 #' @source Ryan Gosse, Ocean Tracking Network

R/load-prepare_deploy_sheet.R

@@ -36,6 +36,13 @@
 #' @export
 
 prepare_deploy_sheet <- function(path, header_line = 5, sheet_name = 1, combine_arr_stn = TRUE) {
+  ##  Declare global variables for NSE & R CMD check
+  DEPLOY_LAT <- DEPLOY_LONG <- INS_MODEL_NO <-
+    `DEPLOY_DATE_TIME   (yyyy-mm-ddThh:mm:ss)` <-
+    `RECOVER_DATE_TIME (yyyy-mm-ddThh:mm:ss)` <- STATION_NO <-
+    OTN_ARRAY <- station <- ins_model_no <- deploy_lat <- deploy_long <-
+    deploy_date_time <- recover_date_time <- NULL
+
   deploy_sheet <- readxl::read_excel(path,
     sheet = sheet_name,
     skip = header_line - 1,

R/load-prepare_tag_sheet.R

@@ -31,6 +31,10 @@
 #' @export
 
 prepare_tag_sheet <- function(path, header_line = 5, sheet_name = 2) {
+  ##  Declare global variables for NSE & R CMD check
+  TAG_CODE_SPACE <- TAG_ID_CODE <- EST_TAG_LIFE <- UTC_RELEASE_DATE_TIME <-
+    SEX <- RELEASE_LATITUDE <- RELEASE_LONGITUDE <- SCIENTIFIC_NAME <- NULL
+
   tag_sheet <- readxl::read_excel(path, sheet = sheet_name, skip = header_line - 1)
   tag_sheet <- tag_sheet %>% dplyr::mutate(
     transmitter_id = paste(TAG_CODE_SPACE, TAG_ID_CODE, sep = "-"),

R/load-read_vdat_csv.r

@@ -1,7 +1,5 @@
 #' Read data from an Innovasea Fathom VDAT CSV file
 #'
-#' Read data from an Innovasea Fathom VDAT CSV file
-#'
 #' @param src A character string with path and name of an Innovasea VDAT CSV
 #'   detection file. If only file name is given, then the file must be located
 #'   in the working directory.
@@ -136,6 +134,9 @@ read_vdat_csv <- function(src,
     return()
   }
 
+  ##  Declare global variables for NSE & R CMD check
+  record_type <- NULL
+
   # Identify vdat csv format version and vdat.exe version that created input csv
   vdat_header <- data.table::fread(file = src, nrows = 1L, header = FALSE)
 
@@ -218,13 +219,13 @@ read_vdat_csv <- function(src,
     keep.by = FALSE
   )
 
-  data(vdat_csv_schema)
+  utils::data("vdat_csv_schema", envir = environment())
 
   vdat_csv_schema <- vdat_csv_schema[[paste0("v", src_version$fathom_csv)]]
 
 
   # Preallocate list; element = record type
-  vdat <- setNames(
+  vdat <- stats::setNames(
     object = vector("list", length(vdat_list)),
     nm = names(vdat_list)
   )

R/load-write_vdat_csv.r

@@ -74,6 +74,11 @@ write_vdat_csv <- function(vdat,
                            out_file = NULL,
                            output_format = "csv.fathom",
                            include_empty = FALSE) {
+  ##  Declare global variables for NSE & R CMD check
+  record_type <- dt2 <- `Device Time (UTC)` <- `Time Correction (s)` <-
+    `Ambient (deg C)` <- `Ambient Min (deg C)` <- `Ambient Max (deg C)` <-
+    `Ambient Mean (deg C)` <- `Internal (deg C)` <- ..txt_cols <- txt <- NULL
+
   # Check input class
   if (!inherits(vdat, "vdat_list")) {
     stop(
@@ -107,7 +112,7 @@ write_vdat_csv <- function(vdat,
   if (out_file_type == "dir") {
     out_file_name <- gsub("\\.vrl$|\\.vdat$",
       out_file_ext,
-      tail(vdat$DATA_SOURCE_FILE$`File Name`, 1),
+      utils::tail(vdat$DATA_SOURCE_FILE$`File Name`, 1),
       ignore.case = TRUE
     )
 
@@ -142,12 +147,12 @@ write_vdat_csv <- function(vdat,
 
   # Compress each list element into a character vector
 
-  vdat_lines_body <- setNames(
+  vdat_lines_body <- stats::setNames(
     object = vector("list", length(record_types)),
     record_types
   )
 
-  vdat_lines_header <- setNames(
+  vdat_lines_header <- stats::setNames(
     object = vector("list", length(record_types)),
     record_types
   )

R/package-glatos.r

@@ -35,12 +35,12 @@
 #'
 #'   \item{[real_sensor_values]}{ Converts 'raw' transmitter sensor (e.g.,
 #'   depth, temperature) to 'real'-scale values (e.g., depth in meters) using
-#'   transmitter specification data (e.g., from read\_vemco\_tag\_specs).} }
+#'   transmitter specification data (e.g., from [read_vemco_tag_specs]).} }
 #'
 #' @section Filtering and summarizing: \describe{
 #'   \item{[min_lag]}{
 #'   Facilitates identification and removal of false positive detections by
-#'   calculating the minimum time interval (min\_lag) between successive
+#'   calculating the minimum time interval (min_lag) between successive
 #'   detections.}
 #'
 #'  \item{[false_detections]}{ Removes potential false positive detections
@@ -123,7 +123,10 @@
 #'   txtProgressBar unzip write.csv write.table zip
 #' @importFrom grDevices bmp colorRampPalette dev.new dev.off jpeg png rainbow
 #'   tiff
-globalVariables(".") # to avoid R CMD check note
+"_PACKAGE"
+
+# avoid R CMD check note
+globalVariables(".")
 
 # package startup message
 .onAttach <- function(libname, pkgname) {

R/proc-min_lag.r

@@ -64,6 +64,10 @@
 #' @export
 
 min_lag <- function(det) {
+  ##  Declare global variables for NSE & R CMD check
+  ord <- transmitter_codespace <- transmitter_id <- receiver_sn <-
+    detection_timestamp_utc <- NULL
+
   # coerce to data.table
   dtc <- data.table::as.data.table(det)
 

R/proc-real_sensor_values.r

@@ -110,6 +110,10 @@
 #' @export
 
 real_sensor_values <- function(det, tag_specs) {
+  ##  Declare global variables for NSE & R CMD check
+  ord <- transmitter_codespace <- transmitter_id <- code_space <- id_code <-
+    sensor_value_real <- sensor_intercept <- sensor_value <- sensor_slope <- NULL
+
   # coerce to data.table
   dtc <- data.table::as.data.table(det)
 

R/sim-crw_in_polygon.r

@@ -9,14 +9,14 @@
 #'   are also accepted); \cr *OR* \cr A polygon defined as data frame or
 #'   matrix with numeric columns x and y.
 #'
-#' @param theta A 2-element numeric vector with turn angle parameters (theta[1]
-#'   = mean; theta[2] = sd), in degrees, from normal distribution.
+#' @param theta A 2-element numeric vector with turn angle parameters (`theta[1]`
+#'   = mean; `theta[2]` = sd), in degrees, from normal distribution.
 #'
 #' @param stepLen A numeric scalar with total distance moved in each step, in
 #'   meters.
 #'
 #' @param initPos A 2-element numeric vector with initial position
-#'   (initPos[1]=x, initPos[2]=y) in same coordinate reference system as
+#'   (`initPos[1]`=x, `initPos[2]`=y) in same coordinate reference system as
 #'   `polyg`.
 #'
 #' @param initHeading A numeric scalar with initial heading in degrees. E.g., 0
@@ -242,7 +242,7 @@ crw_in_polygon <- function(polyg, theta = c(0, 10), stepLen = 100,
     }
 
     # Close polyg if needed (first and last point must be same)
-    if (!identical(polyg[1, ], tail(polyg, 1))) polyg <- rbind(polyg, polyg[1, ])
+    if (!identical(polyg[1, ], utils::tail(polyg, 1))) polyg <- rbind(polyg, polyg[1, ])
 
     # Make sf object
     polyg_sf <- sf::st_polygon(list(as.matrix(polyg[c("x", "y")])))
@@ -429,8 +429,8 @@ check_cross_boundary <- function(path, boundary, EPSG) {
   # Make line segment objects of sequential point-pairs in path
 
   segs_mat <- cbind(
-    head(path, -1),
-    tail(path, -1)
+    utils::head(path, -1),
+    utils::tail(path, -1)
   )
 
   in_poly <-

R/sim-detect_transmissions.r

@@ -219,6 +219,9 @@ detect_transmissions <- function(trnsLoc = NA,
                                  inputCRS = NA,
                                  sp_out = TRUE,
                                  show_progress = TRUE) {
+  ##  Declare global variables for NSE & R CMD check
+  trns_x <- trns_y <- NULL
+
   # Check input class - trnsLoc
   if (!inherits(trnsLoc, c("data.frame", "sf", "sfc", "SpatialPointsDataFrame"))) {
     stop(

R/sim-transmit_along_path.r

@@ -179,6 +179,9 @@ transmit_along_path <- function(path = NA,
                                 ),
                                 pathCRS = NA,
                                 sp_out = TRUE) {
+  ##  Declare global variables for NSE & R CMD check
+  cumdistm <- NULL
+
   # Check input class
   if (!inherits(path, c("data.frame", "sf", "sfc", "SpatialPointsDataFrame"))) {
     stop(

R/simutil-crw.r

@@ -4,12 +4,12 @@
 #'   drawn from a normal distribution.
 #'
 #' @param theta A 2-element numeric vector with turn angle parameters
-#'   (theta[1] = mean; theta[2] = sd) from normal distribution.
+#'   (`theta[1]` = mean; `theta[2]` = sd) from normal distribution.
 #'
 #' @param stepLen A numeric scalar with total distance moved in each step.
 #'
-#' @param initPos A 2-element numeric vector with nital position (initPos[1]=x,
-#'   initPos[2]=y).
+#' @param initPos A 2-element numeric vector with nital position (`initPos[1]`=x,
+#'   `initPos[2]`=y).
 #'
 #' @param initHeading A numeric scalar with initial heading in degrees.
 #'

R/summ-receiver_efficiency.r

@@ -55,6 +55,10 @@
 #' @export
 
 REI <- function(detections, deployments) {
+  ##  Declare global variables for NSE & R CMD check
+  recover_date_time <- last_download <- station <- days_deployed <- deploy_lat <-
+    deploy_long <- animal_id <- common_name_e <- detection_timestamp_utc <- NULL
+
   # Check for proper columns
   required_deployment_columns <- c("station", "deploy_date_time", "recover_date_time")
   required_detection_columns <- c("station", "common_name_e", "animal_id", "detection_timestamp_utc")

R/summ-residence_index.r

@@ -174,6 +174,11 @@ residence_index <- function(
     detections, calculation_method = "kessel",
     locations = NULL, group_col = "animal_id", time_interval_size = "1 day",
     groupwise_total = TRUE) {
+  # Declare global variables for R CMD check
+  location <- mean_latitude <- mean_longitude <- days_detected <-
+    total_days <- NULL
+
+
   # set to NULL if NA
   if (!is.null(group_col)) if (is.na(group_col)) group_col <- NULL
   if (!is.null(locations)) if (all(is.na(locations))) locations <- NULL
@@ -237,7 +242,7 @@ residence_index <- function(
   # numerator
   group_cols <- c("location", group_col)
 
-  detections <- dplyr::group_by(detections, across(group_cols))
+  detections <- dplyr::group_by(detections, dplyr::across(group_cols))
 
   ri <- dplyr::do(
     detections,
@@ -263,7 +268,7 @@ residence_index <- function(
       time_interval_size
     )
   } else {
-    detections <- dplyr::group_by(detections, across(group_col))
+    detections <- dplyr::group_by(detections, dplyr::across(group_col))
     ri <- dplyr::left_join(ri,
       dplyr::do(
         detections,
@@ -365,6 +370,9 @@ total_diff_days <- function(detections) {
 #'
 #' @importFrom dplyr mutate
 aggregate_total_with_overlap <- function(detections) {
+  # Declare global variables for R CMD check
+  last_detection <- first_detection <- NULL
+
   detections <- mutate(detections, timedelta = as.double(difftime(last_detection, first_detection, units = "secs")))
   detections <- mutate(detections, timedelta = dplyr::recode(detections$timedelta, `0` = 1))
   total <- as.double(sum(detections$timedelta)) / 86400.0
@@ -382,6 +390,9 @@ aggregate_total_with_overlap <- function(detections) {
 #'
 #' @importFrom data.table foverlaps
 aggregate_total_no_overlap <- function(detections) {
+  # Declare global variables for R CMD check
+  t1 <- t2 <- first_detection <- last_detection <- xid <- yid <- tdiff <- NULL
+
   # extract intervals, rename
   ints <- data.table::as.data.table(detections)[, .(
     t1 = first_detection,

R/summ-summarize_detections.r

@@ -194,6 +194,11 @@
 summarize_detections <- function(det, location_col = "glatos_array",
                                  receiver_locs = NULL, animals = NULL,
                                  summ_type = "animal") {
+  ##  Declare global variables for NSE & R CMD check
+  deploy_lat <- deploy_long <- detection_timestamp_utc <- num_fish <- animal_id <-
+    num_locs <- num_dets <- NULL
+
+
   # coerce to data.table
   dtc <- data.table::as.data.table(det)
 

R/testdata.r

@@ -10,7 +10,7 @@
 #'
 #' @section Filename: higgins_lake_transition.rds
 #'
-#' @usage
+#' @examples
 #' system.file("testdata", "higgins_lake_transition.rds", package = "glatos")
 #'
 #' @author Chris Holbrook
@@ -29,7 +29,7 @@ NULL
 #'
 #' @section Filename: flynn_island_transition.rds
 #'
-#' @usage
+#' @examples
 #' system.file("testdata", "flynn_island_transition.rds", package = "glatos")
 #'
 #' @author Chris Holbrook

R/util-convert_glatos_to_att.r

@@ -42,6 +42,11 @@
 
 convert_glatos_to_att <- function(detectionObj, receiverObj,
                                   crs = sp::CRS("+init=epsg:4326")) {
+  ##  Declare global variables for R CMD check
+  Sex <- glatos_array <- station_no <- deploy_lat <- deploy_long <-
+    station <- dummy <- ins_model_no <- ins_serial_no <-
+    deploy_date_time <- recover_date_time <- detection_timestamp_utc <- NULL
+
   transmitters <-
     if (all(grepl("-", detectionObj$transmitter_id, fixed = TRUE))) {
       detectionObj$transmitter_id