updates

Author: Carly Lovas

R/mrip.R

@@ -42,7 +42,7 @@ pull_mrip_catch <- function(proj_path){
   )
 
   region_levels <- c(
-    "North Atlantic",
+    "New England",
     "Mid Atlantic",
     "South Atlantic",
     "Gulf of Mexico"
@@ -56,6 +56,7 @@ pull_mrip_catch <- function(proj_path){
     dplyr::mutate(common_name = tolower(common_name),
            state  = stringr::str_to_title(state),
            state  = factor(state, levels = states_ns),
+           region = str_replace(region, "North Atlantic", "New England"),
            region = factor(region, levels = region_levels))
 
   data <- data |>

R/nefsc.R

@@ -103,10 +103,10 @@ pull_nefsc <- function(proj_path){
 #' @export
 #' @examples # map_nefsc_cob(species = "black sea bass", data = nefsc)
 
-map_nefsc_cob <- function(species = "all", data = "nefsc"){
+map_nefsc_cob <- function(species = "all", data = NULL){
 
   # Get species list
-  species_list <- species.shift::species_list(source = "nefsc")
+  species_list <- species.shifts::species_list(source = "nefsc")
 
   # Base filter
   data <- data |>
@@ -195,6 +195,8 @@ map_nefsc_cob <- function(species = "all", data = "nefsc"){
   }
 }
 
+# ggsave(filename = here::here("summer flounder cob map.png"), map_nefsc_cob(species = "summer flounder", data = nefsc), width = 13)
+
 ## Seasonal percentile plots
 #' @title Plot edges of distribution
 #'
@@ -206,10 +208,10 @@ map_nefsc_cob <- function(species = "all", data = "nefsc"){
 #' @export
 #' @examples # plot_nefsc_edges(species = "summer flounder", data = nefsc)
 
-plot_nefsc_edges <- function(species = "all", data = "nefsc"){
+plot_nefsc_edges <- function(species = "all", data = NULL){
 
   # Get species list
-  species_list <- species.shift::species_list(source = "nefsc")
+  species_list <- species.shifts::species_list(source = "nefsc")
 
   # Base filter
   data <- data |>
@@ -280,6 +282,7 @@ plot_nefsc_edges <- function(species = "all", data = "nefsc"){
   }
 }
 
+
 ## Distance between centroids
 #' @title Plot NEFSC Bottom Trawl Center of Biomass
 #'
@@ -291,10 +294,10 @@ plot_nefsc_edges <- function(species = "all", data = "nefsc"){
 #' @export
 #' @examples # plot_nefsc_centers(species = "black sea bass", data = nefsc)
 
-plot_nefsc_centers <- function(species = "all", data = "nefsc"){
+plot_nefsc_centers <- function(species = "all", data = NULL){
 
   # Get species list
-  species_list <- species.shift::species_list(source = "nefsc")
+  species_list <- species.shifts::species_list(source = "nefsc")
 
   # Base filter
   data <- data |>
@@ -368,12 +371,12 @@ plot_nefsc_centers <- function(species = "all", data = "nefsc"){
 #' @param data Default is "nefsc" `nefsc` must be run and named "observer" in order to run this function.
 #' @return Map of distribution of biomass along the Northeast US. Selecting `all` species will return a list.
 #' @export
-#' @examples # map_nefsc(species = "summer flounder", data = "nefsc")
+#' @examples # map_nefsc(species = "summer flounder", data = nefsc)
 #'
-map_nefsc <- function(species = "all", data = "nefsc"){
+map_nefsc <- function(species = "all", data = NULL){
 
   # Get species list
-  species_list <- species.shift::species_list(source = "nefsc")
+  species_list <- species.shifts::species_list(source = "nefsc")
 
   # Base filter
   data <- data |>
@@ -474,3 +477,4 @@ map_nefsc <- function(species = "all", data = "nefsc"){
     return(plots$out[[1]])
   }
 }
+

R/permits.R

@@ -6,9 +6,9 @@
 
 #' @title Pull federal permits data
 #'
-#' @description Function to pull, clean and geocode GARFO commercial fishing permits from pre-existing confidential repository. Note that due to spelling error, geocoding principal ports removes 1% of permit entries, and takes approximately 25 minutes to run.
+#' @description Function to pull, clean and geocode GARFO commercial fishing permits from pre-existing confidential repository. Note that due to spelling error, geocoding principal ports removes `1%` of permit entries, and takes approximately 25 minutes to run.
 #'
-#' @param proj_path Local path to data file
+#' @param proj_path Local path to data folder. Note that this code is designed to read in multiple Excel files from a single folder, as each year is its own Excel file. If other Excel files are included in the same location, this function will not be able to discern it from the permits data and will not run.
 #' @return Data frame of permits; includes year, prinicpal port and state, permit type, target species, and category (commerical, for-hire).
 #' @export
 #' @examples # permits <- pull_permits(proj_path = proj_path)
@@ -229,7 +229,7 @@ pull_permits <- function(proj_path){
 #'
 #' @examples # plot_state_permits(species = "summer flounder", data = permits)
 
-plot_state_permits <- function(species = "all", data = "permits") {
+plot_state_permits <- function(species = "all", data = NULL) {
 
 
   # Get species list

R/vtr.R

@@ -6,7 +6,7 @@
 #'
 #' @description Function to pull and clean Vessel Trip Reports from pre-existing confidential repository.
 #'
-#' @param proj_path Local path to data file
+#' @param proj_path Local path to data folder. Note that VTR data was provided in multiple CSV files. This function is designed to read all CSV files within a central location. If other CSVs are stored in the same location as the VTR, this function will not be able to discern the different data and will not run.
 #' @return Data frame of vessel trip reports; includes year, sub_trip_id, latitude, longitude, port name and state, species caught, weight of kept and discarded catch.
 #' @export
 #' @examples # not run
@@ -58,15 +58,15 @@ pull_vtr <- function(proj_path){
 #' @param data Default is "vtr." `pull_vtr` must be run and named "vtr" in order to run this function.
 #' @return Map of distribution of observed kept catch along the Northeast US. Selecting `all` species will return a list.
 #' @export
-#' @examples # map_vtr(species = "summer flounder", data = "vtr")
+#' @examples # map_vtr(species = "summer flounder", data = vtr)
 #'
-map_vtr <- function(species = "all", data = "vtr"){
+map_vtr <- function(species = "all", data = NULL){
 
   # Get species list
   species_list <- species.shifts::species_list(source = "vtr")
 
   # Base filter
-  data <- vtr |>
+  data <- data |>
     dplyr::mutate(comname = tolower(species_name),
                   decade  = 10*year%/%10) |>
     dplyr::right_join(species_list)