From f830e140dc3c6088f76b41ff3d138027963da060 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Fri, 21 Jun 2019 10:18:40 +0000 Subject: [PATCH 01/41] Run usethis::use_tidy_style --- R/base.R | 48 ++-- R/discus.R | 8 +- R/filters.R | 5 +- R/fstadv.R | 353 +++++++++++++++------------ R/get_storm_data.R | 30 +-- R/get_storm_list.R | 25 +- R/get_storms.R | 28 ++- R/gis.R | 280 ++++++++++++--------- R/posest.R | 6 +- R/prblty.R | 39 +-- R/public.R | 8 +- R/scrapers.R | 153 +++++++----- R/tracking_chart.R | 68 ++++-- R/update.R | 6 +- R/wndprb.R | 115 ++++----- data-raw/audit.R | 182 ++++++++------ data-raw/build_scraped_datasets.R | 145 +++++------ data-raw/build_test_dataframes.R | 36 +-- data-raw/build_vignette_datasets.R | 58 ++--- data-raw/fetch_products.R | 263 ++++++++++---------- data-raw/update_datasets.R | 75 +++--- data-raw/update_storms.R | 12 +- man/al_tracking_chart.Rd | 18 +- man/ep_tracking_chart.Rd | 18 +- man/gis_prob_storm_surge.Rd | 6 +- man/tracking_chart.Rd | 12 +- tests/testthat/helpers-data.R | 21 +- tests/testthat/helpers-functions.R | 5 +- tests/testthat/test_base.R | 66 ++--- tests/testthat/test_discus.R | 1 - tests/testthat/test_filters.R | 2 +- tests/testthat/test_fstadv.R | 29 ++- tests/testthat/test_get_functions.R | 72 ++++-- tests/testthat/test_gis.R | 73 ++++-- tests/testthat/test_posest.R | 1 - tests/testthat/test_prblty.R | 1 - tests/testthat/test_products.R | 8 +- tests/testthat/test_public.R | 1 - tests/testthat/test_scrapers.R | 1 - tests/testthat/test_tracking_chart.R | 6 +- tests/testthat/test_update.R | 1 - tests/testthat/test_wndprb.R | 28 ++- 42 files changed, 1302 insertions(+), 1011 deletions(-) diff --git a/R/base.R b/R/base.R index d69af7d7..9de81363 100755 --- a/R/base.R +++ b/R/base.R @@ -141,13 +141,15 @@ hasData <- function(has_data = .pkgenv$has_data) { } } -utils::globalVariables(c("Date", "Hour", "Minute", "Lat", "LatHemi", "Lon", - "LonHemi", "Wind", "Gust", "Month", "Year", "FcstDate", - "WindField34", "WindField50", "WindField64", "lat", - "long", "group", ".", "NW34", "name", "data", "Basin", - stringr::str_c(c("NE", "SE", "SW", "NW", "64")), - stringr::str_c(c("NE", "SE", "SW", "NW", "50")), - stringr::str_c(c("NE", "SE", "SW", "NW", "34")))) +utils::globalVariables(c( + "Date", "Hour", "Minute", "Lat", "LatHemi", "Lon", + "LonHemi", "Wind", "Gust", "Month", "Year", "FcstDate", + "WindField34", "WindField50", "WindField64", "lat", + "long", "group", ".", "NW34", "name", "data", "Basin", + stringr::str_c(c("NE", "SE", "SW", "NW", "64")), + stringr::str_c(c("NE", "SE", "SW", "NW", "50")), + stringr::str_c(c("NE", "SE", "SW", "NW", "34")) +)) #' @title extract_year_archive_link #' @description Extracts the year from the archive link. @@ -156,7 +158,7 @@ utils::globalVariables(c("Date", "Hour", "Minute", "Lat", "LatHemi", "Lon", #' @keywords internal extract_year_archive_link <- function(link) { # Year is listed in link towards the end surrounded by slashes. - as.numeric(stringr::str_match(link, '/([:digit:]{4})/')[,2]) + as.numeric(stringr::str_match(link, "/([:digit:]{4})/")[, 2]) } #' @title get_url_contents @@ -167,7 +169,6 @@ extract_year_archive_link <- function(link) { #' @param link URL to download #' @keywords internal get_url_contents <- function(links) { - download_text <- function(grouped_links) { # Create a new Async object with `grouped_links` @@ -177,21 +178,24 @@ get_url_contents <- function(links) { results <- grouped_links$get() # Do we have any bad `grouped_links`? - bad_results_ind <- which(purrr::map(results, ~.$success()) == FALSE) + bad_results_ind <- which(purrr::map(results, ~ .$success()) == FALSE) if (length(bad_results_ind) > 0) { - warning(sprintf("URL %s was unsuccesful.\n", - purrr::map(results[bad_results_ind], ~.$url)), - call. = FALSE) + warning(sprintf( + "URL %s was unsuccesful.\n", + purrr::map(results[bad_results_ind], ~ .$url) + ), + call. = FALSE + ) # Remove bad `grouped_links` results <- results[-bad_results_ind] } - purrr::map_chr(results, ~.$parse("UTF-8")) + purrr::map_chr(results, ~ .$parse("UTF-8")) } # Create groups of links divisible by 80. We are to allow no more than 80 # requests every 10 seconds. If length of `link` is less than 80, then will # only have one group and should have no delay. - groups <- ceiling(seq_along(1:length(links))/80) + groups <- ceiling(seq_along(1:length(links)) / 80) links <- split(links, groups) # Set progress bar @@ -200,14 +204,14 @@ get_url_contents <- function(links) { contents <- links %>% purrr::imap(.f = function(x, y) { - if (as.numeric(y) != length(links)) { # Send group of links to `download_txt` txt <- download_text(x) # We are not in the last group; apply a delay p$tick()$print() - if (getOption("rrricanes.working_msg")) + if (getOption("rrricanes.working_msg")) { message("Waiting 10 seconds to retrieve large numbers of links.") + } p$pause(10) txt } else { @@ -218,7 +222,6 @@ get_url_contents <- function(links) { }) purrr::flatten_chr(contents) - } #' @title get_nhc_link @@ -228,8 +231,9 @@ get_url_contents <- function(links) { #' @param protocol https or http #' @keywords internal get_nhc_link <- function(withTrailingSlash = TRUE, protocol = "https") { - if (withTrailingSlash) + if (withTrailingSlash) { return(sprintf("%s://www.nhc.noaa.gov/", protocol)) + } sprintf("%s://www.nhc.noaa.gov", protocol) } @@ -238,8 +242,9 @@ get_nhc_link <- function(withTrailingSlash = TRUE, protocol = "https") { #' @inheritParams get_nhc_link #' @keywords internal get_nhc_ftp_link <- function(withTrailingSlash = TRUE) { - if (withTrailingSlash) + if (withTrailingSlash) { return("ftp://ftp.nhc.noaa.gov/") + } "ftp://ftp.nhc.noaa.gov" } @@ -272,8 +277,9 @@ mb_to_in <- function(x) { #' @keywords internal month_str_to_num <- function(m) { abbr <- which(month.abb == stringr::str_to_title(m)) - if (purrr::is_empty(abbr)) + if (purrr::is_empty(abbr)) { stop(sprintf("%s is not a valid month abbreviation.", m)) + } abbr } diff --git a/R/discus.R b/R/discus.R index 30a72675..02500649 100644 --- a/R/discus.R +++ b/R/discus.R @@ -30,7 +30,6 @@ get_discus <- function(links) { #' @seealso \code{\link{get_discus}} #' @keywords internal discus <- function(contents) { - status <- scrape_header( contents = contents, # The "SPECIAL" pattern has to be left here; moving it under @@ -43,12 +42,11 @@ discus <- function(contents) { key <- scrape_key(contents) tibble::tibble( - Status = status[,1], - Name = status[,2], - Adv = as.numeric(status[,3]), + Status = status[, 1], + Name = status[, 2], + Adv = as.numeric(status[, 3]), Date = issue_date, Key = key, Contents = contents ) - } diff --git a/R/filters.R b/R/filters.R index 9b65d1f5..e3f13098 100644 --- a/R/filters.R +++ b/R/filters.R @@ -41,8 +41,9 @@ filter_posest <- function(links) { #' @keywords internal filter_public <- function(links) { grep("/pub/P(AL|EP)|/pub/PA(AL|EP)|/pub/PB(AL|EP)|public", - x = links, - value = TRUE) + x = links, + value = TRUE + ) } #' @title filter_prblty diff --git a/R/fstadv.R b/R/fstadv.R index 6c319a14..e6581693 100644 --- a/R/fstadv.R +++ b/R/fstadv.R @@ -89,7 +89,6 @@ get_fstadv <- function(links) { #' @param contents URL of a specific FORECAST/ADVISORY product #' @keywords internal fstadv <- function(contents) { - status <- scrape_header( contents = contents, # The "SPECIAL" pattern has to be left here; moving it under @@ -108,29 +107,28 @@ fstadv <- function(contents) { wind_radius <- fstadv_wind_radius(contents) prev_pos <- fstadv_prev_pos(contents, issue_date) seas <- fstadv_seas(contents) - forecasts <- fstadv_forecasts(contents, key, status[,3], issue_date) + forecasts <- fstadv_forecasts(contents, key, status[, 3], issue_date) tibble::tibble( - Status = status[,1], - Name = status[,2], - Adv = as.numeric(status[,3]), + Status = status[, 1], + Name = status[, 2], + Adv = as.numeric(status[, 3]), Date = issue_date, Key = key, - Lat = lat_lon[,1], - Lon = lat_lon[,2], - Wind = winds_gusts[,1], - Gust = winds_gusts[,2], + Lat = lat_lon[, 1], + Lon = lat_lon[, 2], + Wind = winds_gusts[, 1], + Gust = winds_gusts[, 2], Pressure = pressure, PosAcc = posacc, - FwdDir = fwd_mvmt[,1], - FwdSpeed = fwd_mvmt[,2], + FwdDir = fwd_mvmt[, 1], + FwdSpeed = fwd_mvmt[, 2], Eye = eye, Seas = seas, WindRadius = wind_radius, Forecast = forecasts ) %>% tidyr::unnest() - } #' @title fstadv_eye @@ -139,10 +137,12 @@ fstadv <- function(contents) { #' @return numeric #' @keywords internal fstadv_eye <- function(contents) { - ptn <- stringr::str_c('EYE DIAMETER[ ]+', - '([0-9]{2,3})', # Eye diameter, integer - '[ ]+NM') - as.numeric(stringr::str_match(contents, ptn)[,2]) + ptn <- stringr::str_c( + "EYE DIAMETER[ ]+", + "([0-9]{2,3})", # Eye diameter, integer + "[ ]+NM" + ) + as.numeric(stringr::str_match(contents, ptn)[, 2]) } #' @title fstadv_fcst @@ -162,7 +162,6 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { # prefix, eliminate some vars where necessary, and return a filtered # dataframe. rebuild_forecasts <- function(hr, df) { - df <- df %>% dplyr::filter(.data$FcstPeriod == hr) %>% @@ -199,34 +198,35 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { } else { df } - } - ptn <- stringr::str_c("([:digit:]{2})/([:digit:]{2})([:digit:]{2})Z", - "[:blank:]+([:digit:]{1,2}\\.[:digit:])([N|S])", - "[:blank:]+([:digit:]{1,3}\\.[:digit:]{1})([E|W])", - "[[:space:][:punct:][:alpha:]]+", - "MAX WIND[:blank:]+([:digit:]{1,3})[:blank:]*KT", - "[[:blank:][:punct:]]+GUSTS[:blank:]+", - "([:digit:]{1,3})[:blank:]*KT[[:space:][:punct:]]+", - "(?:64 KT[[:blank:][:punct:]]+", - "([:digit:]{1,3})NE", - "[:blank:]+([:digit:]{1,3})SE", - "[:blank:]+([:digit:]{1,3})SW", - "[:blank:]+([:digit:]{1,3})NW", - "[[:punct:][:space:]]+)?", - "(?:50 KT[[:blank:][:punct:]]+", - "([:digit:]{1,3})NE", - "[:blank:]+([:digit:]{1,3})SE", - "[:blank:]+([:digit:]{1,3})SW", - "[:blank:]+([:digit:]{1,3})NW", - "[[:punct:][:space:]]+)?", - "(?:34 KT[[:blank:][:punct:]]+", - "([:digit:]{1,3})NE", - "[:blank:]+([:digit:]{1,3})SE", - "[:blank:]+([:digit:]{1,3})SW", - "[:blank:]+([:digit:]{1,3})NW", - "[[:punct:][:space:]]+)?") + ptn <- stringr::str_c( + "([:digit:]{2})/([:digit:]{2})([:digit:]{2})Z", + "[:blank:]+([:digit:]{1,2}\\.[:digit:])([N|S])", + "[:blank:]+([:digit:]{1,3}\\.[:digit:]{1})([E|W])", + "[[:space:][:punct:][:alpha:]]+", + "MAX WIND[:blank:]+([:digit:]{1,3})[:blank:]*KT", + "[[:blank:][:punct:]]+GUSTS[:blank:]+", + "([:digit:]{1,3})[:blank:]*KT[[:space:][:punct:]]+", + "(?:64 KT[[:blank:][:punct:]]+", + "([:digit:]{1,3})NE", + "[:blank:]+([:digit:]{1,3})SE", + "[:blank:]+([:digit:]{1,3})SW", + "[:blank:]+([:digit:]{1,3})NW", + "[[:punct:][:space:]]+)?", + "(?:50 KT[[:blank:][:punct:]]+", + "([:digit:]{1,3})NE", + "[:blank:]+([:digit:]{1,3})SE", + "[:blank:]+([:digit:]{1,3})SW", + "[:blank:]+([:digit:]{1,3})NW", + "[[:punct:][:space:]]+)?", + "(?:34 KT[[:blank:][:punct:]]+", + "([:digit:]{1,3})NE", + "[:blank:]+([:digit:]{1,3})SE", + "[:blank:]+([:digit:]{1,3})SW", + "[:blank:]+([:digit:]{1,3})NW", + "[[:punct:][:space:]]+)?" + ) quads <- c("NE", "SE", "SW", "NW") @@ -241,17 +241,21 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { # purrr::map(`[`, , 2:22) %>% # If any storm has 0 forecasts (i.e., the list element is empty), populate # all columns with NA - purrr::modify_if(.p = purrr::is_empty, - .f = ~matrix(data = NA_character_, ncol = 22)) %>% + purrr::modify_if( + .p = purrr::is_empty, + .f = ~ matrix(data = NA_character_, ncol = 22) + ) %>% # Convert to tibble cause God I hate working with lists like this though I # know I need the practice... purrr::map(tibble::as_tibble) %>% - purrr::map(rlang::set_names, - nm = c("String", "Date", "Hour", "Minute", - "Lat", "LatHemi", "Lon", "LonHemi", - "Wind", "Gust", stringr::str_c(quads, "64"), - stringr::str_c(quads, "50"), - stringr::str_c(quads, "34"))) + purrr::map( + rlang::set_names, + nm = c( + "String", "Date", "Hour", "Minute", "Lat", "LatHemi", "Lon", "LonHemi", + "Wind", "Gust", stringr::str_c(quads, "64"), + stringr::str_c(quads, "50"), stringr::str_c(quads, "34") + ) + ) forecast_periods <- c(12, 24, 36, 48, 72, 96, 120) @@ -281,11 +285,11 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { FcstPeriod = forecast_periods[1:dplyr::n()], FcstMonth = dplyr::case_when( as.numeric(.data$Date) < lubridate::day(.data$AdvDate) ~ lubridate::month(.data$AdvDate) + 1, - TRUE ~ lubridate::month(.data$AdvDate) + TRUE ~ lubridate::month(.data$AdvDate) ), FcstYear = dplyr::case_when( FcstMonth < lubridate::month(.data$AdvDate) ~ lubridate::year(.data$AdvDate) + 1, - TRUE ~ lubridate::year(.data$AdvDate) + TRUE ~ lubridate::year(.data$AdvDate) ), FcstDate = lubridate::ymd_hms( strftime( @@ -300,12 +304,12 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { # If Lat is in southern hemisphere (unlikely, but possible), make negative Lat = dplyr::case_when( LatHemi == "S" ~ as.numeric(.data$Lat) * -1, - TRUE ~ as.numeric(.data$Lat) + TRUE ~ as.numeric(.data$Lat) ), # If Lon in western hemisphere (most likely), make negative. Lon = dplyr::case_when( LonHemi == "W" ~ as.numeric(.data$Lon) * -1, - TRUE ~ as.numeric(.data$Lon) + TRUE ~ as.numeric(.data$Lon) ) ) %>% # Make Wind, Gust, relative wind/gust vars and sea vars all numeric @@ -317,7 +321,8 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { df <- df %>% dplyr::left_join( - rebuild_forecasts(hr, df = df_forecasts), by = c("Key", "Adv") + rebuild_forecasts(hr, df = df_forecasts), + by = c("Key", "Adv") ) } @@ -325,7 +330,6 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { dplyr::ungroup() %>% dplyr::select(-c(.data$Key, .data$Adv)) %>% split(seq(nrow(.))) - } #' @title fstadv_fwd_mvmt @@ -340,14 +344,14 @@ fstadv_forecasts <- function(content, key, adv, adv_date) { #' @return numeric #' @keywords internal fstadv_fwd_mvmt <- function(contents, what = NULL) { - - ptn <- stringr::str_c("PRESENT MOVEMENT TOWARD[[:alpha:][:punct:][:space:]]+", - "([:digit:]{1,3})[:blank:]+DEGREES AT[:blank:]+", - "([:digit:]{1,3})[:blank:]KT") + ptn <- stringr::str_c( + "PRESENT MOVEMENT TOWARD[[:alpha:][:punct:][:space:]]+", + "([:digit:]{1,3})[:blank:]+DEGREES AT[:blank:]+", + "([:digit:]{1,3})[:blank:]KT" + ) matches <- stringr::str_match(contents, ptn) - matrix(data = c(as.numeric(matches[,2]), as.numeric(matches[,3])), ncol = 2L) - + matrix(data = c(as.numeric(matches[, 2]), as.numeric(matches[, 3])), ncol = 2L) } #' @title fstadv_pos_accuracy() @@ -357,7 +361,7 @@ fstadv_fwd_mvmt <- function(contents, what = NULL) { #' @keywords internal fstadv_pos_accuracy <- function(contents) { ptn <- stringr::str_c("POSITION ACCURATE WITHIN[:blank:]+([0-9]{2,3})[:blank:]+NM") - as.numeric(stringr::str_match(contents, ptn)[,2]) + as.numeric(stringr::str_match(contents, ptn)[, 2]) } #' @title fstadv_pressure @@ -367,30 +371,40 @@ fstadv_pos_accuracy <- function(contents) { #' @return numeric #' @keywords internal fstadv_pressure <- function(contents) { - ptn <- stringr::str_c("MINIMUM CENTRAL PRESSURE[:blank:]+", - "([:digit:]{3,4})[:blank:]*MB") - as.numeric(stringr::str_match(contents, ptn)[,2]) + ptn <- stringr::str_c( + "MINIMUM CENTRAL PRESSURE[:blank:]+", + "([:digit:]{3,4})[:blank:]*MB" + ) + as.numeric(stringr::str_match(contents, ptn)[, 2]) } #' @title fstadv_prev_pos #' @description Get storm's previous position #' @keywords internal fstadv_prev_pos <- function(contents, adv_date) { - ptn <- "AT \\d\\d/\\d{4}Z CENTER WAS LOCATED NEAR (\\d\\d\\.\\d)(\\w)\\s+(\\d{1,3}\\.\\d)(\\w)" - matches <- stringr::str_match(contents, ptn)[,2:5] + + matches <- stringr::str_match(contents, ptn)[, 2:5] prev_pos_date <- adv_date - lubridate::hours(3) - prev_pos_lat <- ifelse(matches[,2] == "S", - as.numeric(matches[,1]) * -1, - as.numeric(matches[,1])) - prev_pos_lon <- ifelse(matches[,4] == "W", - as.numeric(matches[,3]) * -1, - as.numeric(matches[,3])) + + prev_pos_lat <- ifelse( + matches[, 2] == "S", + as.numeric(matches[, 1]) * -1, + as.numeric(matches[, 1]) + ) + + prev_pos_lon <- ifelse( + matches[, 4] == "W", + as.numeric(matches[, 3]) * -1, + as.numeric(matches[, 3]) + ) + tibble::tibble( PrevPosDate = prev_pos_date, PrevPosLat = prev_pos_lat, - PrevPosLon = prev_pos_lon) %>% + PrevPosLon = prev_pos_lon + ) %>% split(seq(nrow(.))) } @@ -404,23 +418,28 @@ fstadv_prev_pos <- function(contents, adv_date) { #' @return numeric #' @keywords internal fstadv_lat_lon <- function(contents) { - - ptn <- stringr::str_c("[CENTER LOCATED | DISSIPATING] NEAR[:blank:]+", - "([0-9\\.]{3,4})", # Latitude can be 9.9N or 99.9N - "([N|S]{1})", # Northern meisphere - "[:blank:]+([0-9\\.]{4,5})", #Longitude can be 0 to 180 - "([E|W]){1}", # Hemisphere - "[:blank:]+") + ptn <- stringr::str_c( + "[CENTER LOCATED | DISSIPATING] NEAR[:blank:]+", + "([0-9\\.]{3,4})", # Latitude can be 9.9N or 99.9N + "([N|S]{1})", # Northern meisphere + "[:blank:]+([0-9\\.]{4,5})", # Longitude can be 0 to 180 + "([E|W]){1}", # Hemisphere + "[:blank:]+" + ) matches <- stringr::str_match(contents, ptn) - lat <- ifelse(matches[, 3] == "S", - as.numeric(matches[, 2]) * -1, - as.numeric(matches[, 2]) * 1) + lat <- ifelse( + matches[, 3] == "S", + as.numeric(matches[, 2]) * -1, + as.numeric(matches[, 2]) * 1 + ) - lon <- ifelse(matches[, 5] == "W", - as.numeric(matches[, 4]) * -1, - as.numeric(matches[, 4]) * 1) + lon <- ifelse( + matches[, 5] == "W", + as.numeric(matches[, 4]) * -1, + as.numeric(matches[, 4]) * 1 + ) matrix(data = c(lat, lon), ncol = 2) } @@ -434,13 +453,15 @@ fstadv_lat_lon <- function(contents) { fstadv_seas <- function(content) { # 12 FT SEAS..125NE 90SE 90SW 175NW. - ptn <- stringr::str_c("12 FT SEAS", - "[[:punct:][:blank:]]+([0-9]{1,3})NE", - "[:blank:]+([0-9]{1,3})SE", - "[:blank:]+([0-9]{1,3})SW", - "[:blank:]+([0-9]{1,3})NW") + ptn <- stringr::str_c( + "12 FT SEAS", + "[[:punct:][:blank:]]+([0-9]{1,3})NE", + "[:blank:]+([0-9]{1,3})SE", + "[:blank:]+([0-9]{1,3})SW", + "[:blank:]+([0-9]{1,3})NW" + ) - stringr::str_match(content, ptn)[,2:5] %>% + stringr::str_match(content, ptn)[, 2:5] %>% apply(MARGIN = 2L, FUN = as.numeric) %>% tibble::as_tibble() %>% rlang::set_names(nm = stringr::str_c("Seas", c("NE", "SE", "SW", "NW"))) %>% @@ -461,32 +482,35 @@ fstadv_seas <- function(content) { #' @return dataframe #' @keywords internal fstadv_wind_radius <- function(content) { + ptn <- stringr::str_c( + "MAX SUSTAINED WINDS[:blank:]+[:digit:]{1,3} KT ", + "WITH GUSTS TO[:blank:]+[:digit:]{1,3} ", + "KT[[:punct:][:space:][:upper:]]+", + "(?:(64) KT[[:blank:][:punct:]]+([:digit:]{1,3})", + "NE[:blank:]+([:digit:]{1,3})", + "SE[:blank:]+([:digit:]{1,3})", + "SW[:blank:]+([:digit:]{1,3})", + "NW[[:punct:][:space:]]+)?", + "(?:(50) KT[[:blank:][:punct:]]+([:digit:]{1,3})", + "NE[:blank:]+([:digit:]{1,3})", + "SE[:blank:]+([:digit:]{1,3})", + "SW[:blank:]+([:digit:]{1,3})", + "NW[[:punct:][:space:]]+)?", + "(?:(34) KT[[:blank:][:punct:]]+([:digit:]{1,3})", + "NE[:blank:]+([:digit:]{1,3})", + "SE[:blank:]+([:digit:]{1,3})", + "SW[:blank:]+([:digit:]{1,3})", + "NW[[:punct:][:space:]]+)?" + ) - ptn <- stringr::str_c("MAX SUSTAINED WINDS[:blank:]+[:digit:]{1,3} KT ", - "WITH GUSTS TO[:blank:]+[:digit:]{1,3} ", - "KT[[:punct:][:space:][:upper:]]+", - "(?:(64) KT[[:blank:][:punct:]]+([:digit:]{1,3})", - "NE[:blank:]+([:digit:]{1,3})", - "SE[:blank:]+([:digit:]{1,3})", - "SW[:blank:]+([:digit:]{1,3})", - "NW[[:punct:][:space:]]+)?", - "(?:(50) KT[[:blank:][:punct:]]+([:digit:]{1,3})", - "NE[:blank:]+([:digit:]{1,3})", - "SE[:blank:]+([:digit:]{1,3})", - "SW[:blank:]+([:digit:]{1,3})", - "NW[[:punct:][:space:]]+)?", - "(?:(34) KT[[:blank:][:punct:]]+([:digit:]{1,3})", - "NE[:blank:]+([:digit:]{1,3})", - "SE[:blank:]+([:digit:]{1,3})", - "SW[:blank:]+([:digit:]{1,3})", - "NW[[:punct:][:space:]]+)?") - - stringr::str_match(content, ptn)[,2:16] %>% + stringr::str_match(content, ptn)[, 2:16] %>% apply(MARGIN = 2L, FUN = as.numeric) %>% tibble::as_tibble() %>% - rlang::set_names(nm = c("WindField64", "NE64", "SE64", "SW64", "NW64", - "WindField50", "NE50", "SE50", "SW50", "NW50", - "WindField34", "NE34", "SE34", "SW34", "NW34")) %>% + rlang::set_names(nm = c( + "WindField64", "NE64", "SE64", "SW64", "NW64", + "WindField50", "NE50", "SE50", "SW50", "NW50", + "WindField34", "NE34", "SE34", "SW34", "NW34" + )) %>% dplyr::select(-tidyselect::starts_with("WindField")) %>% split(seq(nrow(.))) } @@ -497,17 +521,17 @@ fstadv_wind_radius <- function(content) { #' @return numeric #' @keywords internal fstadv_winds_gusts <- function(contents) { - - ptn <- stringr::str_c('MAX SUSTAINED WINDS[ ]+', - '([0-9]{2,3})', # Winds - '[ ]+KT WITH GUSTS TO[ ]+', - '([0-9]{2,3})', # Gusts - '[ ]+KT') + ptn <- stringr::str_c( + "MAX SUSTAINED WINDS[ ]+", + "([0-9]{2,3})", # Winds + "[ ]+KT WITH GUSTS TO[ ]+", + "([0-9]{2,3})", # Gusts + "[ ]+KT" + ) matches <- stringr::str_match(contents, ptn) - matrix(data = c(as.numeric(matches[,2]), as.numeric(matches[,3])), ncol = 2L) - + matrix(data = c(as.numeric(matches[, 2]), as.numeric(matches[, 3])), ncol = 2L) } #' @title tidy_adv @@ -542,15 +566,19 @@ fstadv_winds_gusts <- function(contents) { #' } #' @export tidy_adv <- function(df) { - if (!is.data.frame(df)) + if (!is.data.frame(df)) { stop("Expecting a dataframe.") + } + df <- df %>% dplyr::select( "Key", .data$Adv:.data$Date, .data$Status:.data$Name, .data$Lat:.data$Eye, - dplyr::starts_with("Seas")) + dplyr::starts_with("Seas") + ) + return(df) } @@ -560,7 +588,9 @@ tidy_adv <- function(df) { #' @export tidy_fstadv <- function(df) { .Deprecated("tidy_adv", - msg = "`tidy_fstadv is deprecated and will be removed in v0.2.2") + msg = "`tidy_fstadv is deprecated and will be removed in v0.2.2" + ) + tidy_adv(df) } @@ -586,8 +616,9 @@ tidy_fstadv <- function(df) { #' } #' @export tidy_wr <- function(df) { - if (!is.data.frame(df)) + if (!is.data.frame(df)) { stop("Expecting a dataframe.") + } # Collapse wind radius fields to narrow dataframe then expand on the four # quadrants, keeping WindField as a variable. @@ -605,9 +636,11 @@ tidy_wr <- function(df) { "NE" = paste0("NE", y), "SE" = paste0("SE", y), "SW" = paste0("SW", y), - "NW" = paste0("NW", y)) %>% + "NW" = paste0("NW", y) + ) %>% dplyr::mutate("WindField" = y) - }) %>% + } + ) %>% dplyr::select(c( "Key", "Adv", "Date", "WindField", .data$NE:.data$NW )) %>% @@ -615,7 +648,7 @@ tidy_wr <- function(df) { dplyr::arrange(.data$Key, .data$Date, .data$Adv, .data$WindField) # Remove NA rows for windfield quadrants - wr <- wr[stats::complete.cases(wr$NE, wr$SE, wr$SW, wr$NW),] + wr <- wr[stats::complete.cases(wr$NE, wr$SE, wr$SW, wr$NW), ] return(wr) } @@ -644,8 +677,9 @@ tidy_wr <- function(df) { #' } #' @export tidy_fcst <- function(df) { - if (!is.data.frame(df)) + if (!is.data.frame(df)) { stop("Expecting a dataframe.") + } # Build forecasts dataframe with base data for each forecast position. This # does not include wind radius data; that comes next. This will be similar @@ -659,7 +693,7 @@ tidy_fcst <- function(df) { # #107 Modified regex pattern to look for Hr120, as well. fcst_periods <- as.list(names(df)) %>% stringr::str_match(pattern = "Hr([:digit:]{2,3})FcstDate") %>% - .[,2] %>% + .[, 2] %>% .[!rlang::are_na(.)] %>% as.numeric() @@ -668,18 +702,26 @@ tidy_fcst <- function(df) { .f = function(y) { df %>% dplyr::select(c("Key", "Adv", "Date", paste0("Hr", y, v))) %>% - dplyr::rename("Key" = "Key", "Adv" = "Adv", "Date" = "Date", - "FcstDate" = paste0("Hr", y, "FcstDate"), - "Lat" = paste0("Hr", y, "Lat"), - "Lon" = paste0("Hr", y, "Lon"), - "Wind" = paste0("Hr", y, "Wind"), - "Gust" = paste0("Hr", y, "Gust"))}) %>% + dplyr::rename( + "Key" = "Key", + "Adv" = "Adv", + "Date" = "Date", + "FcstDate" = paste0("Hr", y, "FcstDate"), + "Lat" = paste0("Hr", y, "Lat"), + "Lon" = paste0("Hr", y, "Lon"), + "Wind" = paste0("Hr", y, "Wind"), + "Gust" = paste0("Hr", y, "Gust") + ) + } + ) %>% dplyr::arrange(.data$Key, .data$Date, .data$Adv, .data$FcstDate) # Remove NA rows forecasts <- forecasts[stats::complete.cases( forecasts$FcstDate, forecasts$Lat, forecasts$Lon, forecasts$Wind, - forecasts$Gust),] + forecasts$Gust + ), ] + return(forecasts) } @@ -708,9 +750,9 @@ tidy_fcst <- function(df) { #' } #' @export tidy_fcst_wr <- function(df) { - - if (!is.data.frame(df)) + if (!is.data.frame(df)) { stop("Expecting a dataframe.") + } # Build wind radius dataframe for each forecast position (12:72 hours; 96 # and 120 hours are never forecasted). This dataframe will be similar to @@ -721,7 +763,7 @@ tidy_fcst_wr <- function(df) { # What forecast periods are in the current dataset? fcst_periods <- as.list(names(df)) %>% stringr::str_match(pattern = "Hr([:digit:]{2})FcstDate") %>% - .[,2] %>% + .[, 2] %>% .[!rlang::are_na(.)] %>% as.numeric() @@ -730,9 +772,10 @@ tidy_fcst_wr <- function(df) { .f = function(x) { if (x %in% c(12, 24, 36)) fcst_wind_radii <- c(34, 50, 64) if (x %in% c(48, 72)) fcst_wind_radii <- c(34, 50) - if (x %in% c(96, 120)) return(NULL) + if (x %in% c(96, 120)) { + return(NULL) + } y <- purrr::map_df(.x = fcst_wind_radii, .f = function(z) { - df %>% dplyr::select(c( "Key", "Adv", "Date", paste0("Hr", x, "FcstDate"), @@ -746,23 +789,27 @@ tidy_fcst_wr <- function(df) { "NE" = paste0("Hr", x, "NE", z), "SE" = paste0("Hr", x, "SE", z), "SW" = paste0("Hr", x, "SW", z), - "NW" = paste0("Hr", x, "NW", z)) %>% + "NW" = paste0("Hr", x, "NW", z) + ) %>% dplyr::mutate("WindField" = z) %>% dplyr::select(c( .data$Key:.data$FcstDate, "WindField", - .data$NE:.data$NW)) - }) + .data$NE:.data$NW + )) + }) + return(y) - }) + } + ) fcst_wr <- dplyr::arrange( fcst_wr, .data$Key, .data$Date, .data$Adv, .data$FcstDate, .data$WindField ) fcst_wr <- fcst_wr[stats::complete.cases( - fcst_wr$NE, fcst_wr$SE, fcst_wr$SW, fcst_wr$NW),] + fcst_wr$NE, fcst_wr$SE, fcst_wr$SW, fcst_wr$NW + ), ] return(fcst_wr) - } diff --git a/R/get_storm_data.R b/R/get_storm_data.R index 864ee38f..4c509339 100644 --- a/R/get_storm_data.R +++ b/R/get_storm_data.R @@ -4,7 +4,6 @@ #' @param product specific product to parse #' @keywords internal extract_product_contents <- function(links, product) { - contents <- get_url_contents(links) # Some products may not exist within HTML but as strict text. @@ -13,7 +12,7 @@ extract_product_contents <- function(links, product) { contents <- links %>% - get_url_contents() %>% # Read in contents as html + get_url_contents() %>% # Read in contents as html # If text is not within html, then we simply need to return the text. # Otherwise, extract the node from within the HTML and return the text of # that node. @@ -31,7 +30,6 @@ extract_product_contents <- function(links, product) { }) purrr::invoke_map_df(product, .x = list(list(contents))) - } #' @title extract_storm_links @@ -39,9 +37,9 @@ extract_product_contents <- function(links, product) { #' @param links URLs to a storm's archive page #' @keywords internal extract_storm_links <- function(links) { - - if (!is.vector(links)) + if (!is.vector(links)) { stop("Links must be a character vector.", call. = FALSE) + } # Get links of text products from each `links` product_links <- @@ -49,12 +47,12 @@ extract_storm_links <- function(links) { get_url_contents() %>% purrr::imap(.f = xml2::read_html) %>% # Extract the html tables from each link to get the storm's text products - purrr::imap(.f = ~rvest::html_nodes(.x, xpath = "//td//a")) %>% + purrr::imap(.f = ~ rvest::html_nodes(.x, xpath = "//td//a")) %>% # Extract the text product URLs from `nodes` - purrr::imap(.f = ~rvest::html_attr(.x, name = "href")) %>% + purrr::imap(.f = ~ rvest::html_attr(.x, name = "href")) %>% purrr::flatten_chr() %>% # Ensure we're only capturing archive pages - stringr::str_match( "archive.+") %>% + stringr::str_match("archive.+") %>% .[stats::complete.cases(.)] # Extract years from `links` @@ -64,8 +62,10 @@ extract_storm_links <- function(links) { # other years, product_links are absolute. If product_links exist for 1998 # they must be modified. All product_links must then be prefixed with # NHC URL. - product_links[years == 1998] <- stringr::str_c("/archive/1998/", - product_links[years == 1998]) + product_links[years == 1998] <- stringr::str_c( + "/archive/1998/", + product_links[years == 1998] + ) product_links <- stringr::str_c(get_nhc_link(), product_links) } @@ -128,10 +128,11 @@ get_product <- function(links, product) { #' get_storm_data(products = c("discus", "public")) #' } #' @export -get_storm_data <- function(links, products = c("discus", "fstadv", "posest", - "public", "prblty", "update", - "wndprb")) { - +get_storm_data <- function(links, products = c( + "discus", "fstadv", "posest", + "public", "prblty", "update", + "wndprb" + )) { products <- match.arg(products, several.ok = TRUE) product_links <- extract_storm_links(links) @@ -145,5 +146,4 @@ get_storm_data <- function(links, products = c("discus", "fstadv", "posest", product_links <- rlang::set_names(product_links, nm = products) purrr::map2(product_links, products, extract_product_contents) - } diff --git a/R/get_storm_list.R b/R/get_storm_list.R index a5c7ebaa..c33e31ae 100644 --- a/R/get_storm_list.R +++ b/R/get_storm_list.R @@ -11,7 +11,8 @@ get_storm_list <- function() { # Read in file as string txt <- readChar( "ftp://ftp.nhc.noaa.gov/atcf/index/storm_list.txt", - nchars = 252928) + nchars = 252928 + ) # Remove any trailing white space clean_txt <- stringr::str_trim(txt) @@ -63,11 +64,12 @@ get_ftp_dirs <- function(x) { #' @export #' @seealso \code{\link{get_storm_data}} get_ftp_storm_data <- function(stormid, - products = c("discus", "fstadv", "posest", - "public", "prblty", "update", - "wndprb")) { - - if (!grepl("(AL|EP)\\d{6}", stormid)) + products = c( + "discus", "fstadv", "posest", + "public", "prblty", "update", + "wndprb" + )) { + if (!grepl("(AL|EP)\\d{6}", stormid)) { stop( stringr::str_c( "stormid should be an alphanumeric string with the basin abbreviation ", @@ -76,9 +78,10 @@ get_ftp_storm_data <- function(stormid, .call = FALSE ) ) + } # What year is the storm? - yyyy <- as.integer(stringr::str_match(stormid, "^.+(\\d{4})$")[,2]) + yyyy <- as.integer(stringr::str_match(stormid, "^.+(\\d{4})$")[, 2]) # List all directories in the ftp's archives archives <- get_ftp_dirs(x = "/atcf/archive/") @@ -192,7 +195,6 @@ get_ftp_storm_data <- function(stormid, files_length <- purrr::map(.x = files, .f = file.info) %>% purrr::map_dbl("size") res_txt <- purrr::map2_chr(.x = files, .y = files_length, readChar) - } else { links <- sprintf( fmt = "ftp://ftp.nhc.noaa.gov/atcf/archive/%s/messages/%s", @@ -201,9 +203,8 @@ get_ftp_storm_data <- function(stormid, ) res <- get_url_contents(links) - res_parsed <- purrr::map(res, ~xml2::read_html(.$content)) + res_parsed <- purrr::map(res, ~ xml2::read_html(.$content)) res_txt <- purrr::map_chr(res_parsed, rvest::html_text) - } } else { # If the `yyyy` value is not in the ftp archives, then it is in a product @@ -251,14 +252,12 @@ get_ftp_storm_data <- function(stormid, ) res <- get_url_contents(links) - res_parsed <- purrr::map(res, ~xml2::read_html(.$content)) + res_parsed <- purrr::map(res, ~ xml2::read_html(.$content)) res_txt <- purrr::map_chr(res_parsed, rvest::html_text) - } df <- purrr::invoke_map_df( .f = utils::getFromNamespace(x = products, ns = "rrricanes"), .x = res_txt ) - } diff --git a/R/get_storms.R b/R/get_storms.R index 4e01842c..4088435f 100644 --- a/R/get_storms.R +++ b/R/get_storms.R @@ -5,7 +5,6 @@ #' @return 4xN Dataframe #' @keywords internal extract_storms <- function(basin, contents) { - xpaths <- list( "AL" = "//td[(((count(preceding-sibling::*) + 1) = 1) and parent::*)]//a", "EP" = "//td[(((count(preceding-sibling::*) + 1) = 2) and parent::*)]//a" @@ -28,7 +27,7 @@ extract_storms <- function(basin, contents) { links <- storms %>% purrr::map(rvest::html_attr, name = "href") %>% - purrr::map2(years, ~stringr::str_c(year_archives_link(.y), .x)) %>% + purrr::map2(years, ~ stringr::str_c(year_archives_link(.y), .x)) %>% purrr::flatten_chr() names <- @@ -92,16 +91,20 @@ extract_storms <- function(basin, contents) { #' @export get_storms <- function(years = format(Sys.Date(), "%Y"), basins = c("AL", "EP")) { - years <- as.integer(years) - if (!all(years %in% 1998:lubridate::year(Sys.Date()))) - stop(sprintf("Param `years` must be between 1998 and %s.", - lubridate::year(Sys.Date())), - call. = FALSE) + if (!all(years %in% 1998:lubridate::year(Sys.Date()))) { + stop(sprintf( + "Param `years` must be between 1998 and %s.", + lubridate::year(Sys.Date()) + ), + call. = FALSE + ) + } - if (!all(basins %in% c("AL", "EP"))) + if (!all(basins %in% c("AL", "EP"))) { stop("Basin must 'AL' and/or 'EP'.", call. = FALSE) + } links <- years %>% @@ -109,13 +112,14 @@ get_storms <- function(years = format(Sys.Date(), "%Y"), purrr::flatten_chr() # 1998 is only year with slightly different URL. Modify accordingly - links[grep("1998", links)] <- stringr::str_c(links[grep("1998", links)], - "1998archive.shtml") + links[grep("1998", links)] <- stringr::str_c( + links[grep("1998", links)], + "1998archive.shtml" + ) contents <- get_url_contents(links) purrr::map_df(basins, extract_storms, contents) - } #' @title year_archives_link @@ -124,5 +128,5 @@ get_storms <- function(years = format(Sys.Date(), "%Y"), #' @keywords internal year_archives_link <- function(year) { nhc_link <- get_nhc_link() - sprintf(stringr::str_c(nhc_link, 'archive/%i/'), year) + sprintf(stringr::str_c(nhc_link, "archive/%i/"), year) } diff --git a/R/gis.R b/R/gis.R index c8aa4229..3df87cf4 100644 --- a/R/gis.R +++ b/R/gis.R @@ -7,46 +7,61 @@ #' @seealso \code{\link{gis_download}} #' @export gis_advisory <- function(key, advisory = as.character()) { - - if (is.null(key)) + if (is.null(key)) { stop("Please provide a `key`.", call. = FALSE) + } key <- stringr::str_to_lower(key) - if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) + if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) { stop("`key` should be a 8-character alphanumeric string.", call. = FALSE) + } - key <- stringr::str_match(key, - pattern = stringr::str_c("([:lower:]{2})([:digit:]{2})", - "([:digit:]{4})")) + key <- stringr::str_match( + key, + pattern = stringr::str_c( + "([:lower:]{2})([:digit:]{2})", + "([:digit:]{4})" + ) + ) # Get list of GIS forecast zips for storm and download - url <- sprintf("%sgis/archive_forecast_results.php?id=%s%s&year=%s", - get_nhc_link(), - key[,2], # Basin - key[,3], # Storm number - key[,4]) # Year + url <- sprintf( + "%sgis/archive_forecast_results.php?id=%s%s&year=%s", + get_nhc_link(), + key[, 2], # Basin + key[, 3], # Storm number + key[, 4] + ) # Year contents <- readr::read_lines(url) # Match zip files. If advisory is empty then need to pull all zip files for # the storm. Otherwise, pull only selected advisory. if (purrr::is_empty(advisory)) { - ptn <- sprintf(".+(forecast/archive/%s.*?\\.zip).+", - stringr::str_to_lower(key[,1])) + ptn <- sprintf( + ".+(forecast/archive/%s.*?\\.zip).+", + stringr::str_to_lower(key[, 1]) + ) } else { advisory <- stringr::str_match(advisory, "([:digit:]{1,3})([:alpha:]*)") names(advisory) <- c("original", "advisory", "int_adv") - ptn <- sprintf(".+(forecast/archive/%s.*?%s%s\\.zip).+", - stringr::str_to_lower(key[,1]), - stringr::str_pad(string = advisory[["advisory"]], - width = 3, side = "left", pad = "0"), - advisory[["int_adv"]]) + ptn <- sprintf( + ".+(forecast/archive/%s.*?%s%s\\.zip).+", + stringr::str_to_lower(key[, 1]), + stringr::str_pad( + string = advisory[["advisory"]], + width = 3, side = "left", pad = "0" + ), + advisory[["int_adv"]] + ) } - matches <- stringr::str_match(contents, pattern = ptn)[,2] + matches <- stringr::str_match(contents, pattern = ptn)[, 2] matches <- matches[stats::complete.cases(matches)] - if (purrr::is_empty(matches)) return(NULL) + if (purrr::is_empty(matches)) { + return(NULL) + } # Append website domain to links stringr::str_c(get_nhc_link(), "gis/", matches) @@ -71,7 +86,6 @@ gis_advisory <- function(key, advisory = as.character()) { #' unofficial and sites not on the list can be selected if conditions warrant. #' @export gis_breakpoints <- function() { - breakpoint_file <- stringr::str_c(get_nhc_link, "gis/") %>% xml2::read_html() %>% @@ -84,7 +98,6 @@ gis_breakpoints <- function() { .[stats::complete.cases(.)] stringr::str_c(get_nhc_link(withTrailingSlash = FALSE), breakpoint_file) - } #' @title gis_download @@ -93,7 +106,6 @@ gis_breakpoints <- function() { #' @param ... additional parameters for rgdal::readOGR #' @export gis_download <- function(url, ...) { - destdir <- tempdir() utils::download.file(file.path(url), zip_file <- tempfile()) @@ -117,7 +129,6 @@ gis_download <- function(url, ...) { ) rlang::set_names(ds, nm = stringr::str_replace(shp_files, "\\.shp", "")) - } #' @title gis_latest @@ -126,23 +137,27 @@ gis_download <- function(url, ...) { #' @param ... additional parameters for rgdal::readOGR #' @export gis_latest <- function(basins = c("AL", "EP"), ...) { - - if (!(all(basins %in% c("AL", "EP")))) + if (!(all(basins %in% c("AL", "EP")))) { stop("Basin must be one or both of AL or EP.", call. = FALSE) + } - urls <- list("AL" = stringr::str_c(get_nhc_link(), "gis-at.xml"), - "EP" = stringr::str_c(get_nhc_link(), "gis-ep.xml")) + urls <- list( + "AL" = stringr::str_c(get_nhc_link(), "gis-at.xml"), + "EP" = stringr::str_c(get_nhc_link(), "gis-ep.xml") + ) gis_zips <- basins %>% - purrr::map(~xml2::read_xml(urls[[.x]])) %>% + purrr::map(~ xml2::read_xml(urls[[.x]])) %>% purrr::map(~ xml2::xml_find_all(.x, xpath = ".//link") %>% - xml2::xml_text()) %>% + xml2::xml_text()) %>% purrr::map(stringr::str_match, ".+\\.zip$") %>% purrr::flatten_chr() %>% .[!is.na(.)] - if (purrr::is_empty(gis_zips)) return(NULL) + if (purrr::is_empty(gis_zips)) { + return(NULL) + } purrr::map(gis_zips, gis_download, ...) } @@ -193,50 +208,65 @@ gis_outlook <- function() { #' gis_prob_storm_surge("AL092016", products = list("psurge" = 0, "esurge" = 10)) #' #' # Return all psurge0 products for Sep 2, 2016, storm AL092016 -#' gis_prob_storm_surge("AL092016", products = list("psurge" = 0), -#' datetime = "20160902") +#' gis_prob_storm_surge("AL092016", +#' products = list("psurge" = 0), +#' datetime = "20160902" +#' ) #' } #' @export gis_prob_storm_surge <- function(key, products, datetime = NULL) { - - if (is.null(key)) + if (is.null(key)) { stop("Please provide a storm `key`.", call. = FALSE) + } # Validate products - if (!(all(names(products) %in% c("psurge", "esurge")))) + if (!(all(names(products) %in% c("psurge", "esurge")))) { stop("`products` must be 'psurge' and/or 'esurge'.", call. = FALSE) + } - if (!is.null(products[["psurge"]])) - if (!(all(dplyr::between(products[["psurge"]], 0, 20)))) + if (!is.null(products[["psurge"]])) { + if (!(all(dplyr::between(products[["psurge"]], 0, 20)))) { stop("'psurge' values must be between 0 and 20.", call. = FALSE) + } + } - if (!is.null(products[["esurge"]])) - if (!(all(products[["esurge"]] %in% seq(10, 50, by = 10)))) + if (!is.null(products[["esurge"]])) { + if (!(all(products[["esurge"]] %in% seq(10, 50, by = 10)))) { stop("'esurge' values must be 10, 20, 30, 40 or 50.", call. = FALSE) + } + } key <- stringr::str_to_lower(key) - if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) + if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) { stop("`key` should be a 8-character alphanumeric string.", call. = FALSE) + } key <- stringr::str_match(key, - pattern = stringr::str_c("([:lower:]{2})([:digit:]", - "{2})([:digit:]{4})")) + pattern = stringr::str_c( + "([:lower:]{2})([:digit:]", + "{2})([:digit:]{4})" + ) + ) # Get list of GIS forecast zips for storm and download - url <- sprintf("%sgis/archive_psurge_results.php?id=%s%s&year=%s", - get_nhc_link(), - key[,2], # Basin - key[,3], # Storm number - key[,4]) # Year + url <- sprintf( + "%sgis/archive_psurge_results.php?id=%s%s&year=%s", + get_nhc_link(), + key[, 2], # Basin + key[, 3], # Storm number + key[, 4] + ) # Year contents <- readr::read_lines(url) # Build product pattern ptn_product <- - purrr::map2(.x = names(products), - .y = products, - .f = stringr::str_c) %>% + purrr::map2( + .x = names(products), + .y = products, + .f = stringr::str_c + ) %>% purrr::flatten_chr() # Build datetime pattern @@ -254,15 +284,19 @@ gis_prob_storm_surge <- function(key, products, datetime = NULL) { } # Match zip files. - ptn <- sprintf(".+(storm_surge/%s_(%s)_(%s)\\.zip).+", - stringr::str_to_lower(key[,1]), - stringr::str_c(ptn_product, collapse = "|"), - ptn_datetime) - - matches <- stringr::str_match(contents, pattern = ptn)[,2] + ptn <- sprintf( + ".+(storm_surge/%s_(%s)_(%s)\\.zip).+", + stringr::str_to_lower(key[, 1]), + stringr::str_c(ptn_product, collapse = "|"), + ptn_datetime + ) + + matches <- stringr::str_match(contents, pattern = ptn)[, 2] matches <- matches[stats::complete.cases(matches)] - if (purrr::is_empty(matches)) return(NULL) + if (purrr::is_empty(matches)) { + return(NULL) + } stringr::str_c(get_nhc_link(), "gis/", matches) } @@ -277,54 +311,67 @@ gis_prob_storm_surge <- function(key, products, datetime = NULL) { gis_storm_surge_flood <- function(key, advisory = as.numeric(), products = c("inundation", "tidalmask")) { - if (is.null(key)) stop("Please provide a storm `key`.", call. = FALSE) key <- stringr::str_to_upper(key) - if (!grepl("^[[:alpha:]]{2}[[:digit:]]{6}$", key)) + if (!grepl("^[[:alpha:]]{2}[[:digit:]]{6}$", key)) { stop("`key` should be a 8-character alphanumeric string.", call. = FALSE) + } - if (!(any(products %in% c("inundation", "tidalmask")))) + if (!(any(products %in% c("inundation", "tidalmask")))) { stop("`products` must be 'inundation' or 'tidalmask'.", call. = FALSE) + } key <- stringr::str_match(key, - pattern = stringr::str_c("([:alpha:]{2})([:digit:]", - "{2})([:digit:]{4})")) + pattern = stringr::str_c( + "([:alpha:]{2})([:digit:]", + "{2})([:digit:]{4})" + ) + ) # Get list of GIS zips for storm and download - url <- sprintf("%sgis/archive_inundation_results.php?id=%s%s&year=%s", - get_nhc_link(), - key[,2], # Basin - key[,3], # Storm number - key[,4]) # Year + url <- sprintf( + "%sgis/archive_inundation_results.php?id=%s%s&year=%s", + get_nhc_link(), + key[, 2], # Basin + key[, 3], # Storm number + key[, 4] + ) # Year contents <- readr::read_lines(url) if (purrr::is_empty(advisory)) { - ptn <- sprintf(".+(%s/%s%s%s_[:digit:]{1,2}_(%s)\\.zip).+", - "inundation/forecasts", - key[,2], - key[,3], - stringr::str_sub(key[,4], start = 3L, end = 4L), - stringr::str_c(products, collapse = "|")) + ptn <- sprintf( + ".+(%s/%s%s%s_[:digit:]{1,2}_(%s)\\.zip).+", + "inundation/forecasts", + key[, 2], + key[, 3], + stringr::str_sub(key[, 4], start = 3L, end = 4L), + stringr::str_c(products, collapse = "|") + ) } else { - ptn <- sprintf(".+(inundation/forecasts/%s%s%s_%s_(%s)\\.zip).+", - key[,2], - key[,3], - stringr::str_sub(key[,4], start = 3L, end = 4L), - stringr::str_pad(advisory, width = 2, side = "left", - pad = "0"), - stringr::str_c(products, collapse = "|")) + ptn <- sprintf( + ".+(inundation/forecasts/%s%s%s_%s_(%s)\\.zip).+", + key[, 2], + key[, 3], + stringr::str_sub(key[, 4], start = 3L, end = 4L), + stringr::str_pad(advisory, + width = 2, side = "left", + pad = "0" + ), + stringr::str_c(products, collapse = "|") + ) } - matches <- stringr::str_match(contents, pattern = ptn)[,2] + matches <- stringr::str_match(contents, pattern = ptn)[, 2] matches <- matches[stats::complete.cases(matches)] - if (purrr::is_empty(matches)) return(NULL) + if (purrr::is_empty(matches)) { + return(NULL) + } stringr::str_c(get_nhc_link(), "gis/", matches) - } #' @title gis_windfield @@ -345,47 +392,61 @@ gis_storm_surge_flood <- function(key, #' @seealso \code{\link{gis_download}} #' @export gis_windfield <- function(key, advisory = as.character()) { - - if (is.null(key)) + if (is.null(key)) { stop("Please provide a storm `key`.", call. = FALSE) + } key <- stringr::str_to_lower(key) - if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) + if (!grepl("^[[:lower:]]{2}[[:digit:]]{6}$", key)) { stop("`key` should be a 8-character alphanumeric string.", call. = FALSE) + } key <- stringr::str_match(key, - pattern = stringr::str_c("([:lower:]{2})([:digit:]", - "{2})([:digit:]{4})")) + pattern = stringr::str_c( + "([:lower:]{2})([:digit:]", + "{2})([:digit:]{4})" + ) + ) # Get list of GIS forecast zips for storm and download - url <- sprintf("%sgis/archive_forecast_info_results.php?id=%s%s&year=%s", - get_nhc_link(), - key[,2], # Basin - key[,3], # Storm number - key[,4]) # Year + url <- sprintf( + "%sgis/archive_forecast_info_results.php?id=%s%s&year=%s", + get_nhc_link(), + key[, 2], # Basin + key[, 3], # Storm number + key[, 4] + ) # Year contents <- readr::read_lines(url) # Match zip files. If advisory is empty then need to pull all zip files for # the storm. Otherwise, pull only selected advisory. if (purrr::is_empty(advisory)) { - ptn <- sprintf(".+(forecast/archive/%s.*?\\.zip).+", - stringr::str_to_lower(key[,1])) + ptn <- sprintf( + ".+(forecast/archive/%s.*?\\.zip).+", + stringr::str_to_lower(key[, 1]) + ) } else { advisory <- stringr::str_match(advisory, "([:digit:]{1,3})([:alpha:]*)") names(advisory) <- c("original", "advisory", "int_adv") - ptn <- sprintf(".+(forecast/archive/%s.*?%s%s\\.zip).+", - stringr::str_to_lower(key[,1]), - stringr::str_pad(string = advisory[["advisory"]], - width = 3, side = "left", pad = "0"), - advisory[["int_adv"]]) + ptn <- sprintf( + ".+(forecast/archive/%s.*?%s%s\\.zip).+", + stringr::str_to_lower(key[, 1]), + stringr::str_pad( + string = advisory[["advisory"]], + width = 3, side = "left", pad = "0" + ), + advisory[["int_adv"]] + ) } - matches <- stringr::str_match(contents, pattern = ptn)[,2] + matches <- stringr::str_match(contents, pattern = ptn)[, 2] matches <- matches[stats::complete.cases(matches)] - if (purrr::is_empty(matches)) return(NULL) + if (purrr::is_empty(matches)) { + return(NULL) + } stringr::str_c(get_nhc_link(), "gis/", matches) } @@ -410,12 +471,13 @@ gis_windfield <- function(key, advisory = as.character()) { #' } #' @export gis_wsp <- function(datetime, res = c(5, 0.5, 0.1)) { - - if (!grepl("[[:digit:]]{4,10}", datetime)) + if (!grepl("[[:digit:]]{4,10}", datetime)) { stop("`datetime` should be between 4 and 10 digits.", call. = FALSE) + } - if (!(all(res %in% c(5.0, 0.5, 0.1)))) + if (!(all(res %in% c(5.0, 0.5, 0.1)))) { stop("`res` should be one or more of 5.0, 0.5, or 0.1.", call. = FALSE) + } res <- as.character(res) res <- stringr::str_replace(res, "^5$", "5km") @@ -457,14 +519,14 @@ gis_wsp <- function(datetime, res = c(5, 0.5, 0.1)) { #' object and converts into a dataframe that can be plotted in ggplot2. #' @export shp_to_df <- function(obj) { - if (class(obj) %in% c("SpatialLinesDataFrame", "SpatialPolygonsDataFrame")) { obj@data$id <- rownames(obj@data) obj <- dplyr::left_join(broom::tidy(obj, region = "id"), - obj@data, by = "id") %>% + obj@data, + by = "id" + ) %>% tibble::as_tibble() } obj - } diff --git a/R/posest.R b/R/posest.R index abd7ec7d..e4999081 100644 --- a/R/posest.R +++ b/R/posest.R @@ -25,7 +25,6 @@ get_posest <- function(links) { #' @seealso \code{\link{get_posest}} #' @keywords internal posest <- function(contents) { - status <- scrape_header( contents = contents, ptn_product_title = "(?:POSITION ESTIMATE)?", @@ -37,10 +36,9 @@ posest <- function(contents) { key <- scrape_key(contents) tibble::tibble( - Status = status[,1], - Name = status[,2], + Status = status[, 1], + Name = status[, 2], Date = issue_date, Contents = contents ) - } diff --git a/R/prblty.R b/R/prblty.R index 0c397618..7c17e564 100644 --- a/R/prblty.R +++ b/R/prblty.R @@ -29,7 +29,6 @@ get_prblty <- function(links) { #' @seealso \code{\link{get_prblty}} #' @keywords internal prblty <- function(contents) { - status <- scrape_header( contents = contents, # The "SPECIAL" pattern has to be left here; moving it under @@ -42,30 +41,33 @@ prblty <- function(contents) { # 15.0N 43.4W 43 1 X X 44 16.8N 48.2W X 4 16 2 22 # 15.8N 45.9W 1 26 1 X 28 - ptn <- stringr::str_c("(?<=[:blank:]{3}|\n)", - "([[:alpha:][:digit:][:punct:][:blank:]]{17})", # Location - "[:blank:]+", # Delimiter - "([:digit:]{1,2}|X)", # A - "[:blank:]+", # Delimiter - "([:digit:]{1,2}|X)", # B - "[:blank:]+", # Delimiter - "([:digit:]{1,2}|X)", # C - "[:blank:]+", # Delimiter - "([:digit:]{1,2}|X)", # D - "[:blank:]+", # Delimiter - "([:digit:]{1,2}|X)") # E + ptn <- stringr::str_c( + "(?<=[:blank:]{3}|\n)", + "([[:alpha:][:digit:][:punct:][:blank:]]{17})", # Location + "[:blank:]+", # Delimiter + "([:digit:]{1,2}|X)", # A + "[:blank:]+", # Delimiter + "([:digit:]{1,2}|X)", # B + "[:blank:]+", # Delimiter + "([:digit:]{1,2}|X)", # C + "[:blank:]+", # Delimiter + "([:digit:]{1,2}|X)", # D + "[:blank:]+", # Delimiter + "([:digit:]{1,2}|X)" + ) # E prblty <- contents %>% stringr::str_match_all(ptn) %>% purrr::map(tibble::as_tibble) %>% purrr::map( - rlang::set_names, nm = c("X1", "Location", "A", "B", "C", "D", "E") + rlang::set_names, + nm = c("X1", "Location", "A", "B", "C", "D", "E") ) %>% - purrr::map2(status[,1], ~tibble::add_column(.x, Status = .y, .before = 1)) %>% - purrr::map2(status[,2], ~tibble::add_column(.x, Name = .y, .after = 1)) %>% - purrr::map2(status[,3], ~tibble::add_column(.x, Adv = .y, .after = 2)) %>% - purrr::map2(issue_date, ~tibble::add_column(.x, Date = .y, .after = 3)) %>% + purrr::map2(status[, 1], ~ tibble::add_column(.x, Status = .y, .before = 1)) %>% + purrr::map2(status[, 2], ~ tibble::add_column(.x, Name = .y, .after = 1)) %>% + purrr::map2(status[, 3], ~ tibble::add_column(.x, Adv = .y, .after = 2)) %>% + purrr::map2(issue_date, ~ tibble::add_column(.x, Date = .y, .after = 3)) %>% purrr::map_df(tibble::as_tibble) %>% dplyr::select(-c("X1")) %>% # Trim whitespace @@ -86,5 +88,4 @@ prblty <- function(contents) { .vars = c(6:10), .funs = "as.numeric" ) - } diff --git a/R/public.R b/R/public.R index b72beb60..e6c6ab66 100644 --- a/R/public.R +++ b/R/public.R @@ -25,7 +25,6 @@ get_public <- function(links) { #' @seealso \code{\link{get_public}} #' @keywords internal public <- function(contents) { - status <- scrape_header( contents = contents, # The "SPECIAL" pattern has to be left here; moving it under @@ -38,12 +37,11 @@ public <- function(contents) { key <- scrape_key(contents) tibble::tibble( - Status = status[,1], - Name = status[,2], - Adv = status[,3], + Status = status[, 1], + Name = status[, 2], + Adv = status[, 3], Date = issue_date, Key = key, Contents = contents ) - } diff --git a/R/scrapers.R b/R/scrapers.R index 7f3aa6db..4f0693de 100644 --- a/R/scrapers.R +++ b/R/scrapers.R @@ -4,9 +4,7 @@ #' @seealso \code{\link{scrape_header}} #' @keywords internal scrape_date <- function(header) { - maketime <- function(h, m, p) { - h <- as.numeric(h) m <- as.numeric(m) @@ -22,7 +20,6 @@ scrape_date <- function(header) { m <- stringr::str_pad(m, 2, side = "left", pad = "0") stringr::str_c(h, m, sep = ":") - } # The time value in the headers can vary depending on the product. In @@ -44,76 +41,97 @@ scrape_date <- function(header) { any( stringr::str_count( header, - pattern = stringr::str_c("\nNOON [:upper:]{3} [:upper:]{3} ", - "[:upper:]{3} [:digit:]{2} ", - "[:digit:]{4}\n")))) - + pattern = stringr::str_c( + "\nNOON [:upper:]{3} [:upper:]{3} ", + "[:upper:]{3} [:digit:]{2} ", + "[:digit:]{4}\n" + ) + ) + )) { header <- stringr::str_replace( header, - pattern = stringr::str_c("\n(NOON)", - "( [:upper:]{3}", - " [:upper:]{3} ", - "[:upper:]{3} ", - "[:digit:]{2} ", - "[:digit:]{4})\n"), - "\n12 PM\\2\n") + pattern = stringr::str_c( + "\n(NOON)", + "( [:upper:]{3}", + " [:upper:]{3} ", + "[:upper:]{3} ", + "[:digit:]{2} ", + "[:digit:]{4})\n" + ), + "\n12 PM\\2\n" + ) + } # Same thing for "MIDNIGHT" if ( any( stringr::str_count( header, - pattern = stringr::str_c("\nMIDNIGHT", - " [:upper:]{3} [:upper:]{3} ", - "[:upper:]{3} [:digit:]{2} ", - "[:digit:]{4}\n")))) - + pattern = stringr::str_c( + "\nMIDNIGHT", + " [:upper:]{3} [:upper:]{3} ", + "[:upper:]{3} [:digit:]{2} ", + "[:digit:]{4}\n" + ) + ) + )) { header <- stringr::str_replace( header, - pattern = stringr::str_c("\n(MIDNIGHT)( ", - "[:upper:]{3}", - " [:upper:]{3} ", - "[:upper:]{3} ", - "[:digit:]{2} ", - "[:digit:]{4})\n"), - "\n12 AM\\2\n") + pattern = stringr::str_c( + "\n(MIDNIGHT)( ", + "[:upper:]{3}", + " [:upper:]{3} ", + "[:upper:]{3} ", + "[:digit:]{2} ", + "[:digit:]{4})\n" + ), + "\n12 AM\\2\n" + ) + } # And yes there is actually an entry of 12 NOON; see AL132002 public adv 49A if ( any( stringr::str_count( header, - pattern = stringr::str_c("\n12 NOON", - " [:upper:]{3} [:upper:]{3} ", - "[:upper:]{3} [:digit:]{2} ", - "[:digit:]{4}\n")))) - + pattern = stringr::str_c( + "\n12 NOON", + " [:upper:]{3} [:upper:]{3} ", + "[:upper:]{3} [:digit:]{2} ", + "[:digit:]{4}\n" + ) + ) + )) { header <- stringr::str_replace( header, - pattern = stringr::str_c("\n(12 NOON)( ", - "[:upper:]{3}", - " [:upper:]{3} ", - "[:upper:]{3} ", - "[:digit:]{2} ", - "[:digit:]{4})\n"), - "\n12 PM\\2\n") + pattern = stringr::str_c( + "\n(12 NOON)( ", + "[:upper:]{3}", + " [:upper:]{3} ", + "[:upper:]{3} ", + "[:digit:]{2} ", + "[:digit:]{4})\n" + ), + "\n12 PM\\2\n" + ) + } ptn <- stringr::str_c( "(?<=(?:\n|\r))", - "([:digit:]{1,2})", # Hour + "([:digit:]{1,2})", # Hour "(?<=[:digit:]{1})([:digit:]{2})?", # Minute - "(?:Z)?", # For forecast; Z is (UTC) + "(?:Z)?", # For forecast; Z is (UTC) "[:blank:]", "(?:AM|PM)?[:blank:]?", - "([:alpha:]{3})*?", # Time zone, optional + "([:alpha:]{3})*?", # Time zone, optional "[:blank:]?", - "(?:[:alpha:]{3})", # Day of week, no capture + "(?:[:alpha:]{3})", # Day of week, no capture "[:blank:]", - "([:alpha:]{3})", # Month, abbreviated uppercase + "([:alpha:]{3})", # Month, abbreviated uppercase "[:blank:]", - "([:digit:]{1,2})", # Date + "([:digit:]{1,2})", # Date "[:blank:]", - "([:digit:]{4})", # Year + "([:digit:]{4})", # Year "[[:blank:]\n\r]*" ) @@ -123,23 +141,27 @@ scrape_date <- function(header) { period <- stringr::str_match(datetime.extracted, "[:blank:](AM|PM)[:blank:]") # Convert time values to 24-hour format, UTC - t <- maketime(datetime.extracted[,2], # Hour - datetime.extracted[,3], # Minute - period[,2]) + t <- maketime( + datetime.extracted[, 2], # Hour + datetime.extracted[, 3], # Minute + period[, 2] + ) # Format date - d <- as.Date(stringr::str_c(datetime.extracted[,5], # Month, abbreviated - datetime.extracted[,6], # Date, w/wo leading 0 - datetime.extracted[,7], # Year, four-digit format - sep = "-"), - format = "%b-%d-%Y") + d <- as.Date(stringr::str_c(datetime.extracted[, 5], # Month, abbreviated + datetime.extracted[, 6], # Date, w/wo leading 0 + datetime.extracted[, 7], # Year, four-digit format + sep = "-" + ), + format = "%b-%d-%Y" + ) # If time zone is NA, make UTC. Is NA because in forecast products time is # immeidately followed by Z which is not captured. Z is military code for # Zulu time which is equivalent of Z. # That should be the reason... - tz <- datetime.extracted[,4] + tz <- datetime.extracted[, 4] if (any(is.na(tz))) { i <- which(is.na(tz)) tz[i] <- "UTC" @@ -179,7 +201,6 @@ scrape_date <- function(header) { # Now convert to UTC lubridate::with_tz(dt, tzone = "UTC") - } #' @title scrape_header @@ -208,19 +229,20 @@ scrape_header <- function(contents, ptn_product_title, # Pattern for storm names ptn_names <- stringr::str_c("([\\w-]*?)") - ptn_adv = "NUMBER\\s+(\\d{1,3}\\w?)" + ptn_adv <- "NUMBER\\s+(\\d{1,3}\\w?)" # Combine patterns ptn <- stringr::str_c( - ptn_status, ptn_names, ptn_product_title, sep = "\\s" + ptn_status, ptn_names, ptn_product_title, + sep = "\\s" ) if (advisory_number) { - ptn <- stringr::str_c(ptn, ptn_adv, sep = "\\s") - matches <- stringr::str_match(header, ptn)[,2:4] + ptn <- stringr::str_c(ptn, ptn_adv, sep = "\\s") + matches <- stringr::str_match(header, ptn)[, 2:4] } else { - matches <- stringr::str_match(header, ptn)[,2:3] - status <- apply(stringr::str_match(header, ptn)[,2:3], 2, stringr::str_to_title) + matches <- stringr::str_match(header, ptn)[, 2:3] + status <- apply(stringr::str_match(header, ptn)[, 2:3], 2, stringr::str_to_title) } # String-to-title Status and Name @@ -230,11 +252,10 @@ scrape_header <- function(contents, ptn_product_title, matches[1:2] <- stringr::str_to_title(matches[1:2]) } else { # Working with a matrix - matches[,c(1:2)] <- apply(matches[,c(1:2)], 2, stringr::str_to_title) + matches[, c(1:2)] <- apply(matches[, c(1:2)], 2, stringr::str_to_title) } return(matches) - } #' @title scrape_key @@ -255,9 +276,7 @@ scrape_key <- function(header) { "([:alnum:]{6,8})" ) - ptn <- stringr::str_c(ptn, collapse = '') - - stringr::str_match(header, ptn)[,2] + ptn <- stringr::str_c(ptn, collapse = "") + stringr::str_match(header, ptn)[, 2] } - diff --git a/R/tracking_chart.R b/R/tracking_chart.R index 5a620052..72aca1e5 100644 --- a/R/tracking_chart.R +++ b/R/tracking_chart.R @@ -9,17 +9,23 @@ #' al_tracking_chart(color = "black", size = 0.1, fill = "white") #' #' # 50nm resolution, no states -#' al_tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white") +#' al_tracking_chart( +#' res = 50, states = FALSE, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # 50nm resolution, coastlines only -#' al_tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white") +#' al_tracking_chart( +#' countries = FALSE, res = 50, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # Adding and modifying with ggplot functions #' al_tracking_chart(color = "black", size = 0.1, fill = "white") + -#' ggplot2::labs(x = "Lon", y = "Lat", -#' title = "Base Atlantic Tracking Chart") +#' ggplot2::labs( +#' x = "Lon", y = "Lat", +#' title = "Base Atlantic Tracking Chart" +#' ) #' } #' @export al_tracking_chart <- function(...) { @@ -38,17 +44,23 @@ al_tracking_chart <- function(...) { #' ep_tracking_chart(color = "black", size = 0.1, fill = "white") #' #' # 50nm resolution, no states -#' ep_tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white") +#' ep_tracking_chart( +#' res = 50, states = FALSE, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # 50nm resolution, coastlines only -#' ep_tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white") +#' ep_tracking_chart( +#' countries = FALSE, res = 50, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # Adding and modifying with ggplot functions #' ep_tracking_chart(color = "black", size = 0.1, fill = "white") + -#' ggplot2::labs(x = "Lon", y = "Lat", -#' title = "Base East Pacific Tracking Chart") +#' ggplot2::labs( +#' x = "Lon", y = "Lat", +#' title = "Base East Pacific Tracking Chart" +#' ) #' } #' @export ep_tracking_chart <- function(...) { @@ -74,12 +86,16 @@ ep_tracking_chart <- function(...) { #' tracking_chart(color = "black", size = 0.1, fill = "white") #' #' # 50nm resolution, no states -#' tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white") +#' tracking_chart( +#' res = 50, states = FALSE, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # 50nm resolution, coastlines only -#' tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white") +#' tracking_chart( +#' countries = FALSE, res = 50, color = "black", size = 0.1, +#' fill = "white" +#' ) #' #' # Adding and modifying with ggplot functions #' tracking_chart(color = "black", size = 0.1, fill = "white") + @@ -92,8 +108,9 @@ tracking_chart <- function(countries = TRUE, states = TRUE, res = 110, ...) { res <- as.integer(res) # Validate res - if (!(res %in% c(110, 50, 10))) + if (!(res %in% c(110, 50, 10))) { stop("Chart resolution must be 110, 50, 10") + } pkg <- "rnaturalearth" if (res %in% c(110, 50)) { @@ -123,15 +140,18 @@ tracking_chart <- function(countries = TRUE, states = TRUE, res = 110, ...) { } p <- ggplot2::ggplot() + - ggplot2::geom_polygon(data = base_map_data, - ggplot2::aes(long, lat, group = group), ...) + - ggplot2::coord_equal() + ggplot2::geom_polygon( + data = base_map_data, + ggplot2::aes(.data$long, .data$lat, group = .data$group), ... + ) - if (exists("state_map_data")) + if (exists("state_map_data")) { p <- p + - ggplot2::geom_polygon(data = state_map_data, - ggplot2::aes(long, lat, group = group), ...) + ggplot2::geom_polygon( + data = state_map_data, + ggplot2::aes(.data$long, .data$lat, group = .data$group), ... + ) + } return(p) - } diff --git a/R/update.R b/R/update.R index 0500de4a..b4d0a47d 100644 --- a/R/update.R +++ b/R/update.R @@ -24,7 +24,6 @@ get_update <- function(links) { #' @seealso \code{\link{get_update}} #' @keywords internal update <- function(contents) { - status <- scrape_header( contents = contents, ptn_product_title = "(?:UPDATE )?", @@ -36,11 +35,10 @@ update <- function(contents) { key <- scrape_key(contents) tibble::tibble( - Status = status[,1], - Name = status[,2], + Status = status[, 1], + Name = status[, 2], Date = issue_date, Key = key, Contents = contents ) - } diff --git a/R/wndprb.R b/R/wndprb.R index 7058370d..c1c1f7b1 100644 --- a/R/wndprb.R +++ b/R/wndprb.R @@ -123,9 +123,10 @@ parse_stations <- function(x) { df <- readLines(x) %>% tibble::as_tibble() %>% tidyr::separate(.data$value, - c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7"), - sep = ",", - extra = "warn") %>% + c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7"), + sep = ",", + extra = "warn" + ) %>% dplyr::arrange(.data$Location) return(df) } @@ -137,7 +138,6 @@ parse_stations <- function(x) { #' @param contents Link to a storm's specific wind probability product. #' @keywords internal wndprb <- function(contents) { - status <- scrape_header( contents = contents, # The "SPECIAL" pattern has to be left here; moving it under @@ -149,51 +149,53 @@ wndprb <- function(contents) { key <- scrape_key(contents) - ptn <- stringr::str_c("(?<=\n)", # Look-behind - # Location - first value must be capital letter. - "([:upper:]{1}[[:alnum:][:blank:][:punct:]]{14})", - # Wind - "([[:digit:]]{2})", - # Wind12 - "[:blank:]+([:digit:]{1,2}|X)", - # Delim - "[:blank:]+", - # Wind24 - "([:digit:]{1,2}|X)", - # Wind24 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # Delim - "[:blank:]+", - # Wind36 - "([:digit:]{1,2}|X)", - # Wind36 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # Delim - "[:blank:]+", - # Wind48 - "([:digit:]{1,2}|X)", - # Wind48 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # Delim - "[:blank:]+", - # Wind72 - "([:digit:]{1,2}|X)", - # Wind72 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # Delim - "[:blank:]+", - # Wind96 - "([:digit:]{1,2}|X)", - # Wind96 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # Delim - "[:blank:]+", - # Wind120 - "([:digit:]{1,2}|X)", - # Wind120 cumulative - "+\\([:blank:]*([:digit:]{1,2}|X)\\)", - # End - "[[:blank:]\n]+") + ptn <- stringr::str_c( + "(?<=\n)", # Look-behind + # Location - first value must be capital letter. + "([:upper:]{1}[[:alnum:][:blank:][:punct:]]{14})", + # Wind + "([[:digit:]]{2})", + # Wind12 + "[:blank:]+([:digit:]{1,2}|X)", + # Delim + "[:blank:]+", + # Wind24 + "([:digit:]{1,2}|X)", + # Wind24 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # Delim + "[:blank:]+", + # Wind36 + "([:digit:]{1,2}|X)", + # Wind36 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # Delim + "[:blank:]+", + # Wind48 + "([:digit:]{1,2}|X)", + # Wind48 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # Delim + "[:blank:]+", + # Wind72 + "([:digit:]{1,2}|X)", + # Wind72 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # Delim + "[:blank:]+", + # Wind96 + "([:digit:]{1,2}|X)", + # Wind96 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # Delim + "[:blank:]+", + # Wind120 + "([:digit:]{1,2}|X)", + # Wind120 cumulative + "+\\([:blank:]*([:digit:]{1,2}|X)\\)", + # End + "[[:blank:]\n]+" + ) wndprb <- contents %>% @@ -201,13 +203,15 @@ wndprb <- function(contents) { purrr::map(tibble::as_tibble, .name_repair = "minimal") %>% purrr::map( .f = rlang::set_names, - nm = c("X1", "Location", "Wind", "Wind12", "Wind24", "Wind24Cum", - "Wind36", "Wind36Cum", "Wind48", "Wind48Cum", "Wind72", - "Wind72Cum", "Wind96", "Wind96Cum", "Wind120", "Wind120Cum") + nm = c( + "X1", "Location", "Wind", "Wind12", "Wind24", "Wind24Cum", + "Wind36", "Wind36Cum", "Wind48", "Wind48Cum", "Wind72", + "Wind72Cum", "Wind96", "Wind96Cum", "Wind120", "Wind120Cum" + ) ) %>% - purrr::map2(key, ~tibble::add_column(.x, Key = .y, .before = 1)) %>% - purrr::map2(status[,3], ~tibble::add_column(.x, Adv = .y, .after = 2)) %>% - purrr::map2(issue_date, ~tibble::add_column(.x, Date = .y, .after = 3)) %>% + purrr::map2(key, ~ tibble::add_column(.x, Key = .y, .before = 1)) %>% + purrr::map2(status[, 3], ~ tibble::add_column(.x, Adv = .y, .after = 2)) %>% + purrr::map2(issue_date, ~ tibble::add_column(.x, Date = .y, .after = 3)) %>% purrr::map_df(tibble::as_tibble) %>% dplyr::select(-c("X1")) %>% # Trim whitespace @@ -228,5 +232,4 @@ wndprb <- function(contents) { .vars = c(2, 5:18), .funs = "as.numeric" ) - } diff --git a/data-raw/audit.R b/data-raw/audit.R index 07542ccc..fe1a8336 100644 --- a/data-raw/audit.R +++ b/data-raw/audit.R @@ -17,10 +17,12 @@ library(rrricanes) ## ---- Options ---------------------------------------------------------------- ## ---- Variables -------------------------------------------------------------- -valid_options <- c("Hurricane", "Post-Tropical Cyclone", - "Potential Tropical Cyclone", "Remnants of", - "Subtropical Depression", "Tropical Depression", - "Tropical Storm") +valid_options <- c( + "Hurricane", "Post-Tropical Cyclone", + "Potential Tropical Cyclone", "Remnants of", + "Subtropical Depression", "Tropical Depression", + "Tropical Storm" +) invalid_names <- c("Center", "Test") @@ -32,16 +34,19 @@ discus <- read_csv("./datasets/discus.csv", col_types = cols()) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(discus$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in discus:\n%s", - sort(unique(discus$Status[!(discus$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in discus:\n%s", + sort(unique(discus$Status[!(discus$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- #' * discus$Name for EP192000 Adv 1 is "Test". This is an err on the NHC's part. discus_names <- sort(unique(discus$Name)) if (any(discus_names %in% invalid_names)) { - warning("Invalid Names in discus. See object df_discus_invalid_names.") - df_discus_invalid_names <- discus %>% filter(Name %in% invalid_names) + warning("Invalid Names in discus. See object df_discus_invalid_names.") + df_discus_invalid_names <- discus %>% filter(Name %in% invalid_names) } ## ---- * Adv ------------------------------------------------------------------ @@ -52,86 +57,104 @@ describe(discus$Date) #' ########################################################################## '# ## ---- Forecast/Advisory ------------------------------------------------------ -fstadv <- read_csv("./datasets/fstadv.csv", col_types = cols(), - guess_max = 13000) +fstadv <- read_csv("./datasets/fstadv.csv", + col_types = cols(), + guess_max = 13000 +) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(fstadv$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in fstadv:\n%s", - sort(unique(fstadv$Status[!(fstadv$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in fstadv:\n%s", + sort(unique(fstadv$Status[!(fstadv$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- fstadv_names <- sort(unique(fstadv$Name)) if (any(fstadv_names %in% invalid_names)) { - warning("Invalid Names in fstadv. See object df_fstadv_invalid_names.") - df_fstadv_invalid_names <- fstadv %>% filter(Name %in% invalid_names) + warning("Invalid Names in fstadv. See object df_fstadv_invalid_names.") + df_fstadv_invalid_names <- fstadv %>% filter(Name %in% invalid_names) } ## ---- * Date ----------------------------------------------------------------- describe(fstadv$Date) ## ---- * Key ------------------------------------------------------------------ -if (any(grepl("^[AL|EP][[:digit:]]{6}$", fstadv$Key))) - warning("Invalid Keys") +if (any(grepl("^[AL|EP][[:digit:]]{6}$", fstadv$Key))) { + warning("Invalid Keys") +} ## ---- * Lat ------------------------------------------------------------------ #' There may be NA values in Lat if a system is no longer tropical or has a #' closed center. fstadv_lat <- select(fstadv, dplyr::contains("Lat")) -if (!every(fstadv_lat, is.double)) - warning("Non-numeric lat values") +if (!every(fstadv_lat, is.double)) { + warning("Non-numeric lat values") +} -if (min(fstadv_lat, na.rm = TRUE) < 0 | max(fstadv_lat, na.rm = TRUE) > 90) - warning("Possible invalid latitude values") +if (min(fstadv_lat, na.rm = TRUE) < 0 | max(fstadv_lat, na.rm = TRUE) > 90) { + warning("Possible invalid latitude values") +} ## ---- * Lon ------------------------------------------------------------------ #' There may be NA values in Lon if a system is no longer tropical or has a #' closed center. fstadv_lon <- select(fstadv, dplyr::contains("Lon")) -if (!every(fstadv_lon, is.double)) - warning("Non-numeric lon values") +if (!every(fstadv_lon, is.double)) { + warning("Non-numeric lon values") +} -if (min(fstadv_lon, na.rm = TRUE) < -180 | max(fstadv_lon, na.rm = TRUE) > 180) - warning("Possible invalid longitude values") +if (min(fstadv_lon, na.rm = TRUE) < -180 | max(fstadv_lon, na.rm = TRUE) > 180) { + warning("Possible invalid longitude values") +} ## ---- * Wind, Gust ----------------------------------------------------------- fstadv_winds <- select(fstadv, ends_with("Wind"), ends_with("Gust")) -if (!every(fstadv_winds, is.numeric)) - warning("Non-numeric wind/gust values") +if (!every(fstadv_winds, is.numeric)) { + warning("Non-numeric wind/gust values") +} ## ---- * Pressure ------------------------------------------------------------- -if (!is.numeric(fstadv$Pressure)) - warning("Non-numeric values in Pressure") +if (!is.numeric(fstadv$Pressure)) { + warning("Non-numeric values in Pressure") +} ## ---- * PosAcc --------------------------------------------------------------- -if (!is.numeric(fstadv$PosAcc)) - warning("Non-numeric values in PosAcc") +if (!is.numeric(fstadv$PosAcc)) { + warning("Non-numeric values in PosAcc") +} ## ---- * FwdDir --------------------------------------------------------------- -if (!is.numeric(fstadv$FwdDir)) - warning("Non-numeric values in FwdDir") +if (!is.numeric(fstadv$FwdDir)) { + warning("Non-numeric values in FwdDir") +} ## ---- * FwdDir --------------------------------------------------------------- -if (!is.numeric(fstadv$FwdDir)) - warning("Non-numeric values in FwdDir") +if (!is.numeric(fstadv$FwdDir)) { + warning("Non-numeric values in FwdDir") +} ## ---- * FwdSpeed ------------------------------------------------------------- -if (!is.numeric(fstadv$FwdSpeed)) - warning("Non-numeric values in FwdSpeed") +if (!is.numeric(fstadv$FwdSpeed)) { + warning("Non-numeric values in FwdSpeed") +} ## ---- * Eye ------------------------------------------------------------------ -if (!is.numeric(fstadv$Eye)) - warning("Non-numeric values in Eye") +if (!is.numeric(fstadv$Eye)) { + warning("Non-numeric values in Eye") +} ## ---- * Wind Radii ----------------------------------------------------------- #' Convert to numeric, if not, which sould generate error if non-numeric values #' exist. -fstadv_wr <- fstadv %>% select(matches(".[NE|SE|SW|NW][34|50|64].")) %>% - map_df(as.numeric) +fstadv_wr <- fstadv %>% + select(matches(".[NE|SE|SW|NW][34|50|64].")) %>% + map_df(as.numeric) #' Forecast hours 48 and 72 should not have 64kt wind radius fields is_empty(select(fstadv, Hr48NE64:Hr48NW64, Hr72NE64:Hr72NW64) %>% describe()) @@ -145,15 +168,18 @@ posest <- read_csv("./datasets/posest.csv", col_types = cols()) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(posest$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in posest:\n%s", - sort(unique(posest$Status[!(posest$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in posest:\n%s", + sort(unique(posest$Status[!(posest$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- posest_names <- sort(unique(posest$Name)) if (any(posest_names %in% invalid_names)) { - warning("Invalid Names in posest. See object df_posest_invalid_names.") - df_posest_invalid_names <- posest %>% filter(Name %in% invalid_names) + warning("Invalid Names in posest. See object df_posest_invalid_names.") + df_posest_invalid_names <- posest %>% filter(Name %in% invalid_names) } ## ---- * Date ----------------------------------------------------------------- @@ -165,21 +191,25 @@ prblty <- read_csv("./datasets/prblty.csv", col_types = cols()) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(prblty$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in prblty:\n%s", - sort(unique(prblty$Status[!(prblty$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in prblty:\n%s", + sort(unique(prblty$Status[!(prblty$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- #' * prblty$Name for AL161999 Adv 1 is "Test". This is an err on the NHC's part. prblty_names <- sort(unique(prblty$Name)) if (any(prblty_names %in% invalid_names)) { - warning("Invalid Names in prblty. See object df_prblty_invalid_names.") - df_prblty_invalid_names <- prblty %>% filter(Name %in% invalid_names) + warning("Invalid Names in prblty. See object df_prblty_invalid_names.") + df_prblty_invalid_names <- prblty %>% filter(Name %in% invalid_names) } ## ---- * Wind:Wind120Cum ------------------------------------------------------ -if (!every(prblty %>% select(A:E), is.numeric)) - warning("Some probability cols not numeric.") +if (!every(prblty %>% select(A:E), is.numeric)) { + warning("Some probability cols not numeric.") +} #' ########################################################################## '# ## ---- Public Advisories ------------------------------------------------------ @@ -187,22 +217,25 @@ public <- read_csv("./datasets/public.csv", col_types = cols()) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(public$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in public:\n%s", - sort(unique(public$Status[!(public$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in public:\n%s", + sort(unique(public$Status[!(public$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- public_names <- sort(unique(public$Name)) if (any(public_names %in% invalid_names)) { - warning("Invalid Names in public. See object df_public_invalid_names.") - df_public_invalid_names <- public %>% filter(Name %in% invalid_names) + warning("Invalid Names in public. See object df_public_invalid_names.") + df_public_invalid_names <- public %>% filter(Name %in% invalid_names) } ## ---- * Adv ------------------------------------------------------------------ describe(public$Adv) if (any(is.na(public$Adv))) { - warning("Adv contains NA values.") - df_public_invalid_adv <- public %>% filter(is.na(Adv)) + warning("Adv contains NA values.") + df_public_invalid_adv <- public %>% filter(is.na(Adv)) } ## ---- * Date ----------------------------------------------------------------- @@ -214,15 +247,18 @@ update <- read_csv("./datasets/update.csv", col_types = cols()) ## ---- * Status --------------------------------------------------------------- status <- sort(unique(update$Status)) -if (!(any(status %in% valid_options))) - warning(sprintf("Invalid Status in update:\n%s", - sort(unique(update$Status[!(update$Status %in% valid_options)])))) +if (!(any(status %in% valid_options))) { + warning(sprintf( + "Invalid Status in update:\n%s", + sort(unique(update$Status[!(update$Status %in% valid_options)])) + )) +} ## ---- * Names ---------------------------------------------------------------- update_names <- sort(unique(update$Name)) if (any(update_names %in% invalid_names)) { - warning("Invalid Names in update. See object df_update_invalid_names.") - df_update_invalid_names <- update %>% filter(Name %in% invalid_names) + warning("Invalid Names in update. See object df_update_invalid_names.") + df_update_invalid_names <- update %>% filter(Name %in% invalid_names) } #' ########################################################################## '# @@ -230,19 +266,21 @@ if (any(update_names %in% invalid_names)) { wndprb <- read_csv("./datasets/wndprb.csv", col_types = cols()) ## ---- * Key ------------------------------------------------------------------ -if (any(grepl("^[AL|EP][[:digit:]]{6}$", wndprb$Key))) - warning("Invalid Keys") +if (any(grepl("^[AL|EP][[:digit:]]{6}$", wndprb$Key))) { + warning("Invalid Keys") +} ## ---- * Adv ------------------------------------------------------------------ describe(wndprb$Adv) if (any(is.na(wndprb$Adv))) { - warning("Adv contains NA values.") - df_wndprb_invalid_adv <- wndprb %>% filter(is.na(Adv)) + warning("Adv contains NA values.") + df_wndprb_invalid_adv <- wndprb %>% filter(is.na(Adv)) } ## ---- * Date ----------------------------------------------------------------- describe(wndprb$Date) ## ---- * Wind:Wind120Cum ------------------------------------------------------ -if (!every(wndprb %>% select(Wind:Wind120Cum), is.numeric)) - warning("Some Wind cols not numeric.") +if (!every(wndprb %>% select(Wind:Wind120Cum), is.numeric)) { + warning("Some Wind cols not numeric.") +} diff --git a/data-raw/build_scraped_datasets.R b/data-raw/build_scraped_datasets.R index bc6cff8e..46b8261e 100644 --- a/data-raw/build_scraped_datasets.R +++ b/data-raw/build_scraped_datasets.R @@ -15,42 +15,46 @@ library(rrricanes) ## ---- Variables -------------------------------------------------------------- basins <- c("AL", "EP") years <- 1998:2017 -products <- c("discus", "fstadv", "posest", "prblty", "public", "update", - "wndprb") +products <- c( + "discus", "fstadv", "posest", "prblty", "public", "update", + "wndprb" +) ## ---- Get Storms ------------------------------------------------------------- storms <- map_df(years, .f = function(year) { - map_df(basins, .f = function(basin) { - get_storms(year = year, basin = basin) - }) + map_df(basins, .f = function(basin) { + get_storms(year = year, basin = basin) + }) }) ## ---- Storm Discussions ------------------------------------------------------ discus <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_discus <- purrr::safely(get_discus) - df <- safely_get_discus(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Storm Discussion error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_discus <- purrr::safely(get_discus) + df <- safely_get_discus(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Storm Discussion error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(discus, "./datasets/discus.csv") ## ---- Forecast/Advisory ------------------------------------------------------ fstadv <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_fstadv <- purrr::safely(get_fstadv) - df <- safely_get_fstadv(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Forecast/Advisory error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_fstadv <- purrr::safely(get_fstadv) + df <- safely_get_fstadv(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Forecast/Advisory error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(fstadv, "./datasets/fstadv.csv") @@ -69,75 +73,80 @@ write_csv(fcst_wr, "./datasets/fcst_wr.csv") ## ---- Position Estimates ----------------------------------------------------- posest <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_posest <- purrr::safely(get_posest) - df <- safely_get_posest(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Position Estimate error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_posest <- purrr::safely(get_posest) + df <- safely_get_posest(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Position Estimate error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(posest, "./datasets/posest.csv") ## ---- Strike Probabilities --------------------------------------------------- prblty <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_prblty <- purrr::safely(get_prblty) - df <- safely_get_prblty(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Strike Probabilities error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_prblty <- purrr::safely(get_prblty) + df <- safely_get_prblty(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Strike Probabilities error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(prblty, "./datasets/prblty.csv") ## ---- Public Advisories ------------------------------------------------------ public <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_public <- purrr::safely(get_public) - df <- safely_get_public(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Public Advisory error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_public <- purrr::safely(get_public) + df <- safely_get_public(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Public Advisory error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(public, "./datasets/public.csv") ## ---- Updates ---------------------------------------------------------------- update <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_update <- purrr::safely(get_update) - df <- safely_get_update(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Update error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_update <- purrr::safely(get_update) + df <- safely_get_update(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Update error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(update, "./datasets/update.csv") ## ---- Wind Speed Probabilities ----------------------------------------------- wndprb <- map_df(storms %>% .$Link, .f = function(storm_link) { - safely_get_wndprb <- purrr::safely(get_wndprb) - df <- safely_get_wndprb(link = storm_link) - if (is.null(df$error)) { - return(df$result) - } else { - write(sprintf("Wind Probabilities error: %s\n%s", df$error, storm_link), - file = "log.txt", - append = TRUE) - } + safely_get_wndprb <- purrr::safely(get_wndprb) + df <- safely_get_wndprb(link = storm_link) + if (is.null(df$error)) { + return(df$result) + } else { + write(sprintf("Wind Probabilities error: %s\n%s", df$error, storm_link), + file = "log.txt", + append = TRUE + ) + } }) write_csv(wndprb, "./datasets/wndprb.csv") diff --git a/data-raw/build_test_dataframes.R b/data-raw/build_test_dataframes.R index df21130f..f1dafb76 100644 --- a/data-raw/build_test_dataframes.R +++ b/data-raw/build_test_dataframes.R @@ -7,32 +7,32 @@ al_2008 <- get_storms(years = 2008, basins = "AL") al_2017 <- get_storms(years = 2017, basins = "AL") al_01_2017_products <- get_storm_data( - links = al_2017[[1,4]], - products = c("discus", "fstadv") + links = al_2017[[1, 4]], + products = c("discus", "fstadv") ) -al_09_2008_discus <- get_discus(al_2008[[9,4]]) +al_09_2008_discus <- get_discus(al_2008[[9, 4]]) -al_09_2008_fstadv <- get_fstadv(al_2008[[9,4]]) +al_09_2008_fstadv <- get_fstadv(al_2008[[9, 4]]) -al_09_2008_posest <- get_posest(al_2008[[9,4]]) +al_09_2008_posest <- get_posest(al_2008[[9, 4]]) -al_01_1998_prblty <- get_prblty(al_1998[[1,4]]) +al_01_1998_prblty <- get_prblty(al_1998[[1, 4]]) -al_09_2008_public <- get_public(al_2008[[9,4]]) +al_09_2008_public <- get_public(al_2008[[9, 4]]) -al_09_2008_update <- get_update(al_2008[[9,4]]) +al_09_2008_update <- get_update(al_2008[[9, 4]]) -al_09_2008_wndprb <- get_wndprb(al_2008[[9,4]]) +al_09_2008_wndprb <- get_wndprb(al_2008[[9, 4]]) save( - al_01_1998_prblty, - al_01_2017_products, - al_09_2008_discus, - al_09_2008_fstadv, - al_09_2008_posest, - al_09_2008_public, - al_09_2008_update, - al_09_2008_wndprb, - file = ("./inst/extdata/tests_datasets.RData") + al_01_1998_prblty, + al_01_2017_products, + al_09_2008_discus, + al_09_2008_fstadv, + al_09_2008_posest, + al_09_2008_public, + al_09_2008_update, + al_09_2008_wndprb, + file = ("./inst/extdata/tests_datasets.RData") ) diff --git a/data-raw/build_vignette_datasets.R b/data-raw/build_vignette_datasets.R index dbb80b9c..e75fc886 100644 --- a/data-raw/build_vignette_datasets.R +++ b/data-raw/build_vignette_datasets.R @@ -8,51 +8,53 @@ library(rrricanes) df.al_2012 <- get_storms(year = 2012, basin = "AL") df.al_18_2012_fstadv <- df.al_2012 %>% - filter(Name == "Hurricane Sandy") %>% - .$Link %>% - get_fstadv() + filter(Name == "Hurricane Sandy") %>% + .$Link %>% + get_fstadv() df.al_18_2012 <- df.al_2012 %>% - filter(Name == "Hurricane Sandy") %>% - .$Link %>% - get_storm_data(c("fstadv", "wndprb")) + filter(Name == "Hurricane Sandy") %>% + .$Link %>% + get_storm_data(c("fstadv", "wndprb")) df.al_12_2005_prblty <- get_storms(year = 2005, basin = "AL") %>% - filter(Name == "Hurricane Katrina") %>% - .$Link %>% - get_prblty() + filter(Name == "Hurricane Katrina") %>% + .$Link %>% + get_prblty() df.al_18_2012_wndprb <- df.al_2012 %>% - filter(Name == "Hurricane Sandy") %>% - .$Link %>% - get_wndprb() + filter(Name == "Hurricane Sandy") %>% + .$Link %>% + get_wndprb() usethis::use_data( - df.al_2012, - df.al_18_2012_fstadv, - df.al_18_2012, - df.al_12_2005_prblty, - df.al_18_2012_wndprb, - overwrite = TRUE + df.al_2012, + df.al_18_2012_fstadv, + df.al_18_2012, + df.al_12_2005_prblty, + df.al_18_2012_wndprb, + overwrite = TRUE ) ## ---- GIS Data --------------------------------------------------------------- df.gis_adv <- gis_advisory(key = "AL182012", advisory = "18") %>% gis_download() -df.gis_storm_surge <- gis_prob_storm_surge(key = "AL142016", - products = list(psurge = 0), - datetime = "20161006") %>% - last() %>% - gis_download() +df.gis_storm_surge <- gis_prob_storm_surge( + key = "AL142016", + products = list(psurge = 0), + datetime = "20161006" +) %>% + last() %>% + gis_download() df.gis_wind_radii <- gis_windfield("AL142016", advisory = "33") %>% gis_download() df.gis_wsp <- gis_wsp(datetime = "2016100606", res = 0.5) %>% gis_download() usethis::use_data( - df.gis_adv, - df.gis_storm_surge, - df.gis_wind_radii, - df.gis_wsp, - overwrite = TRUE + df.gis_adv, + df.gis_storm_surge, + df.gis_wind_radii, + df.gis_wsp, + overwrite = TRUE ) diff --git a/data-raw/fetch_products.R b/data-raw/fetch_products.R index e578a02e..ea60a14e 100644 --- a/data-raw/fetch_products.R +++ b/data-raw/fetch_products.R @@ -1,8 +1,8 @@ -#'----------------------------------------------------------------------------'# +#' ----------------------------------------------------------------------------'# #' '# #' Fetch Products '# #' '# -#'----------------------------------------------------------------------------'# +#' ----------------------------------------------------------------------------'# #' #' Scrape basin index xml files for active storms. If no storms are present, #' exit script. @@ -50,123 +50,130 @@ repo <- repository("./datasets") ## ---- Functions -------------------------------------------------------------- parse_products <- function(x, y) { - # Load last published dates - pub_dates <- read_csv("./datasets/pub_dates.csv", col_types = cols()) - - # Get title of product - title <- xml_find_all(y, "title") %>% xml_text() - - # Get pubdate of products - pd <- xml_find_all(y, "pubDate") %>% xml_text() %>% - strptime(format = "%a, %d %b %Y %T", tz = "UTC") - - # Set product and column types of existing dataset. Remember Adv is char. - if (str_detect(title, "Public Advisory")) { - product = "public" - col_types = "cccTc" - } else if (str_detect(title, "Forecast Advisory")) { - product = "fstadv" - col_types = paste0("cccTcddiiniiiiiiiiiiiiiiii", - # 12 hrs - "Tddiiiiiiiiiiiiii", - # 24 hrs - "Tddiiiiiiiiiiiiii", - # 36 hrs - "Tddiiiiiiiiiiiiii", - # 48 hrs - "Tddiiiiiiiiiiiiii", - # 72 hrs - "Tddiiiiiiiiiiiiii", - # Seas - "iiii", - # 96 hrs - "Tddiiiiiiiiiiiiii", - #120 hrs - "Tddiiiiiiiiiiiiii") - } else if (str_detect(title, "Forecast Discussion")) { - product = "discus" - col_types = "cccTc" - } else if (str_detect(title, "Wind Speed Probabilities")) { - product = "wndprb" - col_types = "ccTciiiiiiiiiiiiii" - } else if (str_detect(title, "Tropical Cyclone Update")) { - product = "update" - col_types = "cccTc" - } - - last_update <- pub_dates %>% - filter(Product == product) %>% - .[[x]] %>% - as.POSIXct() - - if (pd <= last_update) return(NULL) - - # At this point we have a new product. Get URL to product and scrape - link <- xml_find_all(y, "link") %>% xml_text() - - func <- getAnywhere(product)$objs[[1]] - - func_call <- safely(func) - - ret <- func_call(link) - - if (!is.null(ret$error)) { - warning(sprintf("%s\n%s", ret$error, link)) - return(NULL) - } - - if (is.null(ret$result)) { - # wndprb product may not contain any probabilities making the dataframe - # empty. Return NULL in this instance. - - # Update pub_dates dataframe and save - pub_dates[pub_dates$Product == product,][x] <- as.POSIXct(pd) - write_csv(pub_dates, path = "./datasets/pub_dates.csv") - - add(repo, "./datasets/pub_dates.csv") - commit(repo, sprintf("pub_dates updated as of %s", pd)) - return(NULL) - } - - # Import and update latest product datafile - df <- read_csv(sprintf("./datasets/%s.csv", product), col_types = col_types) - - updated_df <- bind_rows(df, ret$result) - write_csv(updated_df, path = sprintf("./datasets/%s.csv", product)) - - if (product == "fstadv") { - ## ---- Tidy fstadv ---------------------------------------------------- - adv <- tidy_fstadv(updated_df) - write_csv(adv, path = "./datasets/adv.csv") - - fcst <- tidy_fcst(updated_df) - write_csv(fcst, path = "./datasets/fcst.csv") - - fcst_wr <- tidy_fcst_wr(updated_df) - write_csv(fcst_wr, path = "./datasets/fcst_wr.csv") - - wr <- tidy_wr(updated_df) - write_csv(wr, path = "./datasets/wr.csv") - } + # Load last published dates + pub_dates <- read_csv("./datasets/pub_dates.csv", col_types = cols()) + + # Get title of product + title <- xml_find_all(y, "title") %>% xml_text() + + # Get pubdate of products + pd <- xml_find_all(y, "pubDate") %>% + xml_text() %>% + strptime(format = "%a, %d %b %Y %T", tz = "UTC") + + # Set product and column types of existing dataset. Remember Adv is char. + if (str_detect(title, "Public Advisory")) { + product <- "public" + col_types <- "cccTc" + } else if (str_detect(title, "Forecast Advisory")) { + product <- "fstadv" + col_types <- paste0( + "cccTcddiiniiiiiiiiiiiiiiii", + # 12 hrs + "Tddiiiiiiiiiiiiii", + # 24 hrs + "Tddiiiiiiiiiiiiii", + # 36 hrs + "Tddiiiiiiiiiiiiii", + # 48 hrs + "Tddiiiiiiiiiiiiii", + # 72 hrs + "Tddiiiiiiiiiiiiii", + # Seas + "iiii", + # 96 hrs + "Tddiiiiiiiiiiiiii", + # 120 hrs + "Tddiiiiiiiiiiiiii" + ) + } else if (str_detect(title, "Forecast Discussion")) { + product <- "discus" + col_types <- "cccTc" + } else if (str_detect(title, "Wind Speed Probabilities")) { + product <- "wndprb" + col_types <- "ccTciiiiiiiiiiiiii" + } else if (str_detect(title, "Tropical Cyclone Update")) { + product <- "update" + col_types <- "cccTc" + } + + last_update <- pub_dates %>% + filter(Product == product) %>% + .[[x]] %>% + as.POSIXct() + + if (pd <= last_update) { + return(NULL) + } + + # At this point we have a new product. Get URL to product and scrape + link <- xml_find_all(y, "link") %>% xml_text() + + func <- getAnywhere(product)$objs[[1]] + + func_call <- safely(func) + + ret <- func_call(link) + + if (!is.null(ret$error)) { + warning(sprintf("%s\n%s", ret$error, link)) + return(NULL) + } + + if (is.null(ret$result)) { + # wndprb product may not contain any probabilities making the dataframe + # empty. Return NULL in this instance. # Update pub_dates dataframe and save - pub_dates[pub_dates$Product == product,][x] <- as.POSIXct(pd) + pub_dates[pub_dates$Product == product, ][x] <- as.POSIXct(pd) write_csv(pub_dates, path = "./datasets/pub_dates.csv") - ## ---- Stage Changes ------------------------------------------------------ - status <- status(repo) - status$unstaged - if (!is_empty(status$unstaged)) { - add(repo, status$unstaged %>% flatten() %>% sprintf("./datasets/%s", .)) - commit(repo, sprintf("%s updated as of %s", product, pd)) - push(repo) - } + add(repo, "./datasets/pub_dates.csv") + commit(repo, sprintf("pub_dates updated as of %s", pd)) + return(NULL) + } + + # Import and update latest product datafile + df <- read_csv(sprintf("./datasets/%s.csv", product), col_types = col_types) + + updated_df <- bind_rows(df, ret$result) + write_csv(updated_df, path = sprintf("./datasets/%s.csv", product)) + + if (product == "fstadv") { + ## ---- Tidy fstadv ---------------------------------------------------- + adv <- tidy_fstadv(updated_df) + write_csv(adv, path = "./datasets/adv.csv") + + fcst <- tidy_fcst(updated_df) + write_csv(fcst, path = "./datasets/fcst.csv") + + fcst_wr <- tidy_fcst_wr(updated_df) + write_csv(fcst_wr, path = "./datasets/fcst_wr.csv") + + wr <- tidy_wr(updated_df) + write_csv(wr, path = "./datasets/wr.csv") + } + + # Update pub_dates dataframe and save + pub_dates[pub_dates$Product == product, ][x] <- as.POSIXct(pd) + write_csv(pub_dates, path = "./datasets/pub_dates.csv") + + ## ---- Stage Changes ------------------------------------------------------ + status <- status(repo) + status$unstaged + if (!is_empty(status$unstaged)) { + add(repo, status$unstaged %>% flatten() %>% sprintf("./datasets/%s", .)) + commit(repo, sprintf("%s updated as of %s", product, pd)) + push(repo) + } } ## ---- Scrape Index ----------------------------------------------------------- # Index URLs to scrape for active cyclones -index_urls <- c("http://www.nhc.noaa.gov/index-at.xml", - "http://www.nhc.noaa.gov/index-ep.xml") +index_urls <- c( + "http://www.nhc.noaa.gov/index-at.xml", + "http://www.nhc.noaa.gov/index-ep.xml" +) # Load XML as list indices <- index_urls %>% map(read_xml) @@ -185,12 +192,13 @@ indices <- index_urls %>% map(read_xml) # (Atlantic) and wallet number (1). This should tell us there is an active # cyclone. wallets <- indices %>% - map(xml_find_all, xpath = ".//nhc:wallet") %>% - map(xml_text) %>% - flatten_chr() + map(xml_find_all, xpath = ".//nhc:wallet") %>% + map(xml_text) %>% + flatten_chr() -if (is_empty(wallets)) - stop("No active cyclones.") +if (is_empty(wallets)) { + stop("No active cyclones.") +} ## ---- Scrape Products -------------------------------------------------------- # At this point we have a vector of wallets that need to be parsed. Inside each @@ -198,18 +206,21 @@ if (is_empty(wallets)) # checked against the value in pub_dates.csv to ensure that we do not write # existing data. urls <- map_chr(wallets, str_to_lower) %>% - sprintf("http://www.nhc.noaa.gov/nhc_%s.xml", .) + sprintf("http://www.nhc.noaa.gov/nhc_%s.xml", .) # Extract all items items <- map(urls, read_xml) %>% map(xml_find_all, xpath = ".//item") # Match the products we need item_matches <- map(items, str_detect, - pattern = paste0("(Public Advisory|Forecast Advisory|", - "Forecast Discussion|", - "Wind Speed Probabilities|", - "Tropical Cyclone Update) ", - "Number")) + pattern = paste0( + "(Public Advisory|Forecast Advisory|", + "Forecast Discussion|", + "Wind Speed Probabilities|", + "Tropical Cyclone Update) ", + "Number" + ) +) # Keep only those matches items <- map2(items, item_matches, keep) @@ -227,6 +238,8 @@ from <- "" to <- "" subject <- "rrricanes fetch products" body <- read_file("fetch_products.Rout") -mailControl = list(smtpServer = "ASPMX.L.GOOGLE.COM") -sendmail(from = from, to = to, subject = subject, msg = body, - control = mailControl) +mailControl <- list(smtpServer = "ASPMX.L.GOOGLE.COM") +sendmail( + from = from, to = to, subject = subject, msg = body, + control = mailControl +) diff --git a/data-raw/update_datasets.R b/data-raw/update_datasets.R index d3d3b8ee..60c5d12a 100644 --- a/data-raw/update_datasets.R +++ b/data-raw/update_datasets.R @@ -1,8 +1,8 @@ -#'----------------------------------------------------------------------------'# +#' ----------------------------------------------------------------------------'# #' '# #' Update datasets '# #' '# -#'----------------------------------------------------------------------------'# +#' ----------------------------------------------------------------------------'# #' #' Update datasets with missing advisories. Currently expects that given a key #' looks for products with datetimes after the highest datetime value in the @@ -35,54 +35,59 @@ options("rrricanes.working_msg" = TRUE) wd <- getwd() setwd("~/Projects/rrricanes") -products <- c("discus", "fstadv", "posest", "public", "prblty", "update", - "wndprb") +products <- c( + "discus", "fstadv", "posest", "public", "prblty", "update", + "wndprb" +) keys <- commandArgs(trailingOnly = TRUE) -if (purrr::is_empty(keys)) - stop("No storm keys provided.") +if (purrr::is_empty(keys)) { + stop("No storm keys provided.") +} walk(keys, .f = function(key) { - walk(products, .f = function(product) { + walk(products, .f = function(product) { - # Extract command line arguments - basin <- str_sub(key, 0L, 2L) - year_num <- str_sub(key, 3L, 4L) %>% as.numeric() - year <- str_sub(key, 5L, 8L) %>% as.numeric() + # Extract command line arguments + basin <- str_sub(key, 0L, 2L) + year_num <- str_sub(key, 3L, 4L) %>% as.numeric() + year <- str_sub(key, 5L, 8L) %>% as.numeric() - # Get storm - storm_link <- get_storms(year = year, basin = basin) %>% - slice(year_num) %>% - .$Link + # Get storm + storm_link <- get_storms(year = year, basin = basin) %>% + slice(year_num) %>% + .$Link - # Get product for current cyclone - func <- get_storm_data - func_call <- safely(func) - ret <- func_call(storm_link, products = product) + # Get product for current cyclone + func <- get_storm_data + func_call <- safely(func) + ret <- func_call(storm_link, products = product) - if (!is.null(ret$error)) { - warning(sprintf("%s\n%s", ret$error, link)) - return(NULL) - } + if (!is.null(ret$error)) { + warning(sprintf("%s\n%s", ret$error, link)) + return(NULL) + } - # If no results, exit - if (purrr::is_empty(ret$result[[product]])) - return(NULL) + # If no results, exit + if (purrr::is_empty(ret$result[[product]])) { + return(NULL) + } - # Read in full dataset - full_df <- read_csv(sprintf("./datasets/%s.csv", product)) + # Read in full dataset + full_df <- read_csv(sprintf("./datasets/%s.csv", product)) - max_date <- full_df %>% dplyr::filter(Key == key) %>% .$Date %>% max() + max_date <- full_df %>% + dplyr::filter(Key == key) %>% + .$Date %>% + max() - filtered_df <- ret$result[[product]] %>% dplyr::filter(Date > max_date) + filtered_df <- ret$result[[product]] %>% dplyr::filter(Date > max_date) - df <- bind_rows(full_df, filtered_df) - - write_csv(df, sprintf("./datasets/%s.csv", product)) - - }) + df <- bind_rows(full_df, filtered_df) + write_csv(df, sprintf("./datasets/%s.csv", product)) + }) }) ## ---- Reset Options ---------------------------------------------------------- diff --git a/data-raw/update_storms.R b/data-raw/update_storms.R index b37071c0..8d3d7a64 100644 --- a/data-raw/update_storms.R +++ b/data-raw/update_storms.R @@ -5,10 +5,12 @@ library(rrricanes) fstadv <- load_storm_data("fstadv") storms <- fstadv %>% - group_by(Key) %>% - summarise(Name = last(Name), - Wind = max(Wind), - StartDate = first(Date), - EndDate = last(Date)) + group_by(Key) %>% + summarise( + Name = last(Name), + Wind = max(Wind), + StartDate = first(Date), + EndDate = last(Date) + ) write_csv(storms, "./datasets/storms.csv") diff --git a/man/al_tracking_chart.Rd b/man/al_tracking_chart.Rd index 6917a3e6..07cbbecb 100644 --- a/man/al_tracking_chart.Rd +++ b/man/al_tracking_chart.Rd @@ -21,17 +21,23 @@ Build tracking chart centered on Atlantic Basin. al_tracking_chart(color = "black", size = 0.1, fill = "white") # 50nm resolution, no states -al_tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white") +al_tracking_chart( + res = 50, states = FALSE, color = "black", size = 0.1, + fill = "white" +) # 50nm resolution, coastlines only -al_tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white") +al_tracking_chart( + countries = FALSE, res = 50, color = "black", size = 0.1, + fill = "white" +) # Adding and modifying with ggplot functions al_tracking_chart(color = "black", size = 0.1, fill = "white") + - ggplot2::labs(x = "Lon", y = "Lat", - title = "Base Atlantic Tracking Chart") + ggplot2::labs( + x = "Lon", y = "Lat", + title = "Base Atlantic Tracking Chart" + ) } } \seealso{ diff --git a/man/ep_tracking_chart.Rd b/man/ep_tracking_chart.Rd index 65f10859..6278cf06 100644 --- a/man/ep_tracking_chart.Rd +++ b/man/ep_tracking_chart.Rd @@ -21,17 +21,23 @@ Build tracking chart centered on northeast Pacific Basin. ep_tracking_chart(color = "black", size = 0.1, fill = "white") # 50nm resolution, no states -ep_tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white") +ep_tracking_chart( + res = 50, states = FALSE, color = "black", size = 0.1, + fill = "white" +) # 50nm resolution, coastlines only -ep_tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white") +ep_tracking_chart( + countries = FALSE, res = 50, color = "black", size = 0.1, + fill = "white" +) # Adding and modifying with ggplot functions ep_tracking_chart(color = "black", size = 0.1, fill = "white") + - ggplot2::labs(x = "Lon", y = "Lat", - title = "Base East Pacific Tracking Chart") + ggplot2::labs( + x = "Lon", y = "Lat", + title = "Base East Pacific Tracking Chart" + ) } } \seealso{ diff --git a/man/gis_prob_storm_surge.Rd b/man/gis_prob_storm_surge.Rd index cadcd88c..8cb297c5 100644 --- a/man/gis_prob_storm_surge.Rd +++ b/man/gis_prob_storm_surge.Rd @@ -52,8 +52,10 @@ gis_prob_storm_surge("AL092016", products = list("psurge" = 0)) gis_prob_storm_surge("AL092016", products = list("psurge" = 0, "esurge" = 10)) # Return all psurge0 products for Sep 2, 2016, storm AL092016 -gis_prob_storm_surge("AL092016", products = list("psurge" = 0), - datetime = "20160902") +gis_prob_storm_surge("AL092016", + products = list("psurge" = 0), + datetime = "20160902" +) } } \seealso{ diff --git a/man/tracking_chart.Rd b/man/tracking_chart.Rd index a1d86a8e..f4c246d6 100644 --- a/man/tracking_chart.Rd +++ b/man/tracking_chart.Rd @@ -31,12 +31,16 @@ Build base tracking chart using ggplot tracking_chart(color = "black", size = 0.1, fill = "white") # 50nm resolution, no states -tracking_chart(res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white") +tracking_chart( + res = 50, states = FALSE, color = "black", size = 0.1, + fill = "white" +) # 50nm resolution, coastlines only -tracking_chart(countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white") +tracking_chart( + countries = FALSE, res = 50, color = "black", size = 0.1, + fill = "white" +) # Adding and modifying with ggplot functions tracking_chart(color = "black", size = 0.1, fill = "white") + diff --git a/tests/testthat/helpers-data.R b/tests/testthat/helpers-data.R index a8d5527c..adf78fbf 100644 --- a/tests/testthat/helpers-data.R +++ b/tests/testthat/helpers-data.R @@ -44,7 +44,7 @@ files <- list( "fstadv" = c("mcp0394.001") ), "EP132014" = list( - "fstadv" = c("ep132014.fstadv.001.08220251") + "fstadv" = c("ep132014.fstadv.001.08220251") ) ) @@ -61,12 +61,13 @@ al_1998 <- get_storms(years = 1998, basins = "AL") al_2008 <- get_storms(years = 2008, basins = "AL") al_2017 <- get_storms(years = 2017, basins = "AL") -df.al_01_2017_products <- rrricanes:::get_storm_data(al_2017[[1,4]], - products = c("discus", "fstadv")) -df.al_09_2008_discus <- rrricanes:::get_discus(al_2008[[9,4]]) -df.al_09_2008_fstadv <- rrricanes:::get_fstadv(al_2008[[9,4]]) -df.al_09_2008_posest <- rrricanes:::get_posest(al_2008[[9,4]]) -df.al_01_1998_prblty <- rrricanes:::get_prblty(al_1998[[1,4]]) -df.al_09_2008_public <- rrricanes:::get_public(al_2008[[9,4]]) -df.al_09_2008_update <- rrricanes:::get_update(al_2008[[9,4]]) -df.al_09_2008_wndprb <- rrricanes:::get_wndprb(al_2008[[9,4]]) +df.al_01_2017_products <- rrricanes:::get_storm_data(al_2017[[1, 4]], + products = c("discus", "fstadv") +) +df.al_09_2008_discus <- rrricanes:::get_discus(al_2008[[9, 4]]) +df.al_09_2008_fstadv <- rrricanes:::get_fstadv(al_2008[[9, 4]]) +df.al_09_2008_posest <- rrricanes:::get_posest(al_2008[[9, 4]]) +df.al_01_1998_prblty <- rrricanes:::get_prblty(al_1998[[1, 4]]) +df.al_09_2008_public <- rrricanes:::get_public(al_2008[[9, 4]]) +df.al_09_2008_update <- rrricanes:::get_update(al_2008[[9, 4]]) +df.al_09_2008_wndprb <- rrricanes:::get_wndprb(al_2008[[9, 4]]) diff --git a/tests/testthat/helpers-functions.R b/tests/testthat/helpers-functions.R index 8535bf81..38764611 100644 --- a/tests/testthat/helpers-functions.R +++ b/tests/testthat/helpers-functions.R @@ -3,14 +3,11 @@ #' contents and collapses into a string. #' @param x File name located in inst/extdata directory. read_files <- function(x) { - f <- system.file("extdata", x, package = "rrricanes", mustWork = TRUE) - readChar(f, file.info(f)$size - ) + readChar(f, file.info(f)$size) } v <- function(r, c, link) { - content <- xml2::read_html(link) path <- sprintf( diff --git a/tests/testthat/test_base.R b/tests/testthat/test_base.R index 478b408a..30a75469 100644 --- a/tests/testthat/test_base.R +++ b/tests/testthat/test_base.R @@ -22,37 +22,37 @@ test_that("NHC Link", { ## ---- month_str_to_num() ----------------------------------------------------- test_that("Month Abbreviated String to Number", { - expect_identical(rrricanes:::month_str_to_num("JAN"), as.integer(1)) - expect_identical(rrricanes:::month_str_to_num("FEB"), as.integer(2)) - expect_identical(rrricanes:::month_str_to_num("MAR"), as.integer(3)) - expect_identical(rrricanes:::month_str_to_num("APR"), as.integer(4)) - expect_identical(rrricanes:::month_str_to_num("MAY"), as.integer(5)) - expect_identical(rrricanes:::month_str_to_num("JUN"), as.integer(6)) - expect_identical(rrricanes:::month_str_to_num("JUL"), as.integer(7)) - expect_identical(rrricanes:::month_str_to_num("AUG"), as.integer(8)) - expect_identical(rrricanes:::month_str_to_num("SEP"), as.integer(9)) - expect_identical(rrricanes:::month_str_to_num("OCT"), as.integer(10)) - expect_identical(rrricanes:::month_str_to_num("NOV"), as.integer(11)) - expect_identical(rrricanes:::month_str_to_num("DEC"), as.integer(12)) + expect_identical(rrricanes:::month_str_to_num("JAN"), as.integer(1)) + expect_identical(rrricanes:::month_str_to_num("FEB"), as.integer(2)) + expect_identical(rrricanes:::month_str_to_num("MAR"), as.integer(3)) + expect_identical(rrricanes:::month_str_to_num("APR"), as.integer(4)) + expect_identical(rrricanes:::month_str_to_num("MAY"), as.integer(5)) + expect_identical(rrricanes:::month_str_to_num("JUN"), as.integer(6)) + expect_identical(rrricanes:::month_str_to_num("JUL"), as.integer(7)) + expect_identical(rrricanes:::month_str_to_num("AUG"), as.integer(8)) + expect_identical(rrricanes:::month_str_to_num("SEP"), as.integer(9)) + expect_identical(rrricanes:::month_str_to_num("OCT"), as.integer(10)) + expect_identical(rrricanes:::month_str_to_num("NOV"), as.integer(11)) + expect_identical(rrricanes:::month_str_to_num("DEC"), as.integer(12)) }) test_that("Month Abbreviated String to Number Error", { - expect_error( - rrricanes:::month_str_to_num("JANN"), - "JANN is not a valid month abbreviation" - ) + expect_error( + rrricanes:::month_str_to_num("JANN"), + "JANN is not a valid month abbreviation" + ) }) ## ---- knots_to_mph() --------------------------------------------------------- test_that("Knots to Miles per Hour", { - expect_equal(knots_to_mph(91), 104.72093) - expect_equal(knots_to_mph(274), 315.313569) + expect_equal(knots_to_mph(91), 104.72093) + expect_equal(knots_to_mph(274), 315.313569) }) ## ---- mb_to_in() ------------------------------------------------------------- test_that("Millibars to Inches", { - expect_equal(mb_to_in(1010), 29.82528290171) - expect_equal(mb_to_in(888), 26.222624967048) + expect_equal(mb_to_in(1010), 29.82528290171) + expect_equal(mb_to_in(888), 26.222624967048) }) ## ---- nm_to_sm() ------------------------------------------------------------- @@ -62,21 +62,21 @@ test_that("Nautical Miles to Survey Miles", { ## ---- saffir() --------------------------------------------------------------- test_that("test saffir()", { - expect_identical( - saffir(c(32, 45, 70, 90, 110, 125, 140)), - c("TD", "TS", "HU1", "HU2", "HU3", "HU4", "HU5") - ) + expect_identical( + saffir(c(32, 45, 70, 90, 110, 125, 140)), + c("TD", "TS", "HU1", "HU2", "HU3", "HU4", "HU5") + ) }) ## ---- status_abbr_to_str() --------------------------------------------------- test_that("test status_abbr_to_str()", { - expect_identical(status_abbr_to_str("TD"), "Tropical Depression") - expect_identical(status_abbr_to_str("TS"), "Tropical Storm") - expect_identical(status_abbr_to_str("HU"), "Hurricane") - expect_identical(status_abbr_to_str("EX"), "Extratropical Cyclone") - expect_identical(status_abbr_to_str("SD"), "Subtropical Depression") - expect_identical(status_abbr_to_str("SS"), "Subtropical Storm") - expect_identical(status_abbr_to_str("LO"), "Low") - expect_identical(status_abbr_to_str("WV"), "Tropical Wave") - expect_identical(status_abbr_to_str("DB"), "Disturbance") + expect_identical(status_abbr_to_str("TD"), "Tropical Depression") + expect_identical(status_abbr_to_str("TS"), "Tropical Storm") + expect_identical(status_abbr_to_str("HU"), "Hurricane") + expect_identical(status_abbr_to_str("EX"), "Extratropical Cyclone") + expect_identical(status_abbr_to_str("SD"), "Subtropical Depression") + expect_identical(status_abbr_to_str("SS"), "Subtropical Storm") + expect_identical(status_abbr_to_str("LO"), "Low") + expect_identical(status_abbr_to_str("WV"), "Tropical Wave") + expect_identical(status_abbr_to_str("DB"), "Disturbance") }) diff --git a/tests/testthat/test_discus.R b/tests/testthat/test_discus.R index 86e69be5..0f9cc333 100644 --- a/tests/testthat/test_discus.R +++ b/tests/testthat/test_discus.R @@ -5,4 +5,3 @@ test_that("Test get_discus()", { expect_identical(al_09_2008_discus, df.al_09_2008_discus) }) - diff --git a/tests/testthat/test_filters.R b/tests/testthat/test_filters.R index e918a1fd..2b5746ee 100644 --- a/tests/testthat/test_filters.R +++ b/tests/testthat/test_filters.R @@ -3,7 +3,7 @@ context("Filters") #' Filters are to help extract product URL's from a storm's archive pages. test_that("Get products from storm archive", { # Test number of products for Katrina, 2005 - expect_equal(length(AL122005),154) + expect_equal(length(AL122005), 154) expect_equal(length(rrricanes:::filter_discus(AL122005)), 32) expect_equal(length(rrricanes:::filter_fstadv(AL122005)), 31) expect_equal(length(rrricanes:::filter_orig(AL122005)), 1) diff --git a/tests/testthat/test_fstadv.R b/tests/testthat/test_fstadv.R index fc7598dd..1d9e9e6a 100644 --- a/tests/testthat/test_fstadv.R +++ b/tests/testthat/test_fstadv.R @@ -3,33 +3,40 @@ test_that("Test tidy_fstadv()", { expect_warning(x <- rrricanes::tidy_fstadv(al_09_2008_fstadv)) expect_identical(dim(x), c(53L, 18L)) - expect_identical(names(x), c("Key", "Adv", "Date", "Status", "Name", "Lat", - "Lon", "Wind", "Gust", "Pressure", "PosAcc", - "FwdDir", "FwdSpeed", "Eye", "SeasNE", "SeasSE", - "SeasSW", "SeasNW")) + expect_identical(names(x), c( + "Key", "Adv", "Date", "Status", "Name", "Lat", + "Lon", "Wind", "Gust", "Pressure", "PosAcc", + "FwdDir", "FwdSpeed", "Eye", "SeasNE", "SeasSE", + "SeasSW", "SeasNW" + )) }) ## ---- * tidy_wr -------------------------------------------------------------- test_that("Test tidy_wr()", { x <- rrricanes::tidy_wr(al_09_2008_fstadv) expect_identical(dim(x), c(138L, 8L)) - expect_identical(names(x), c("Key", "Adv", "Date", "WindField", "NE", "SE", - "SW", "NW")) + expect_identical(names(x), c( + "Key", "Adv", "Date", "WindField", "NE", "SE", + "SW", "NW" + )) }) ## ---- * tidy_fcst ------------------------------------------------------------ test_that("Test tidy_fcst()", { x <- rrricanes::tidy_fcst(al_09_2008_fstadv) expect_identical(dim(x), c(336L, 8L)) - expect_identical(names(x), c("Key", "Adv", "Date", "FcstDate", "Lat", "Lon", - "Wind", "Gust")) + expect_identical(names(x), c( + "Key", "Adv", "Date", "FcstDate", "Lat", "Lon", + "Wind", "Gust" + )) }) ## ---- * tidy_fcst_wr --------------------------------------------------------- test_that("Test tidy_fcst_wr()", { x <- rrricanes::tidy_fcst_wr(al_09_2008_fstadv) expect_identical(dim(x), c(587L, 9L)) - expect_identical(names(x), c("Key", "Adv", "Date", "FcstDate", "WindField", - "NE", "SE", "SW", "NW")) + expect_identical(names(x), c( + "Key", "Adv", "Date", "FcstDate", "WindField", + "NE", "SE", "SW", "NW" + )) }) - diff --git a/tests/testthat/test_get_functions.R b/tests/testthat/test_get_functions.R index df398663..dffca4c3 100644 --- a/tests/testthat/test_get_functions.R +++ b/tests/testthat/test_get_functions.R @@ -20,31 +20,42 @@ test_that("URL Status", { ## ---- * HTML format ---------------------------------------------------------- #' Test that annual archive page formats haven't changed. test_that("HTML format", { - skip_on_cran() ## ---- * * 1998 ------------------------------------------------------------- #' 1998 expect_identical( v(1, 1, sprintf("%sarchive/1998/1998archive.shtml", get_nhc_link())), - "TROPICAL STORM ALEX") + "TROPICAL STORM ALEX" + ) expect_identical( v(29, 2, sprintf("%sarchive/1998/1998archive.shtml", get_nhc_link())), - "HURRICANE MADELINE") + "HURRICANE MADELINE" + ) ## ---- * * 2005 ------------------------------------------------------------- #' 2005 - expect_identical(v(1, 1, sprintf("%sarchive/2005/", get_nhc_link())), - "Tropical Storm ARLENE") - expect_identical(v(31, 2, sprintf("%sarchive/2005/", get_nhc_link())), - "Tropical Depression SIXTEEN-E") - expect_identical(v(59, 1, sprintf("%sarchive/2005/", get_nhc_link())), - "Tropical Storm ZETA") + expect_identical( + v(1, 1, sprintf("%sarchive/2005/", get_nhc_link())), + "Tropical Storm ARLENE" + ) + expect_identical( + v(31, 2, sprintf("%sarchive/2005/", get_nhc_link())), + "Tropical Depression SIXTEEN-E" + ) + expect_identical( + v(59, 1, sprintf("%sarchive/2005/", get_nhc_link())), + "Tropical Storm ZETA" + ) ## ---- * * 2016 ------------------------------------------------------------- #' 2016 - expect_identical(v(29, 1, sprintf("%sarchive/2016/", get_nhc_link())), - "Hurricane NICOLE") - expect_identical(v(41, 2, sprintf("%sarchive/2016/", get_nhc_link())), - "Tropical Storm TINA") + expect_identical( + v(29, 1, sprintf("%sarchive/2016/", get_nhc_link())), + "Hurricane NICOLE" + ) + expect_identical( + v(41, 2, sprintf("%sarchive/2016/", get_nhc_link())), + "Tropical Storm TINA" + ) }) ## ---- * Is Dataframe --------------------------------------------------------- @@ -54,18 +65,26 @@ test_that("Is Dataframe", { }) ## ---- * Column Names --------------------------------------------------------- -test_that('Column Names', { - expect_named(get_storms(2016, basin = "AL"), - c("Year", "Name", "Basin", "Link")) - expect_named(get_storms(2016, basin = "EP"), - c("Year", "Name", "Basin", "Link")) +test_that("Column Names", { + expect_named( + get_storms(2016, basin = "AL"), + c("Year", "Name", "Basin", "Link") + ) + expect_named( + get_storms(2016, basin = "EP"), + c("Year", "Name", "Basin", "Link") + ) }) ## ---- * Errors --------------------------------------------------------------- test_that("Errors", { - expect_error(get_storms(1997), - sprintf("Param `years` must be between 1998 and %s.", - lubridate::year(Sys.Date()))) + expect_error( + get_storms(1997), + sprintf( + "Param `years` must be between 1998 and %s.", + lubridate::year(Sys.Date()) + ) + ) }) ## ---- Get Storm Data --------------------------------------------------------- @@ -73,9 +92,11 @@ test_that("rrricanes:::get_storm_data()", { # ## ---- * 2017, AL, 01 ------------------------------------------------------- expect_identical(al_01_2017_products, df.al_01_2017_products) ## ---- * Errors ------------------------------------------------------------- - expect_error(rrricanes:::get_storm_data(al_2017[[1,4]], products = "test")) - expect_error(rrricanes:::get_storm_data(), - "argument \"links\" is missing, with no default") + expect_error(rrricanes:::get_storm_data(al_2017[[1, 4]], products = "test")) + expect_error( + rrricanes:::get_storm_data(), + "argument \"links\" is missing, with no default" + ) }) ## get_storm_list ---- @@ -96,7 +117,8 @@ test_that("Get Storm List", { expect_output(str(storm_list$result), "21 variables") expect_identical( names(storm_list$result), - c("STORM_NAME", "RE", "X", "R2", "R3", "R4", "R5", "CY", "YYYY", "TY", "I", + c( + "STORM_NAME", "RE", "X", "R2", "R3", "R4", "R5", "CY", "YYYY", "TY", "I", "YYY1MMDDHH", "YYY2MMDDHH", "SIZE", "GENESIS_NUM", "PAR1", "PAR2", "PRIORITY", "STORM_STATE", "WT_NUMBER", "STORMID" ) diff --git a/tests/testthat/test_gis.R b/tests/testthat/test_gis.R index df15b11d..d2c324a2 100644 --- a/tests/testthat/test_gis.R +++ b/tests/testthat/test_gis.R @@ -2,15 +2,19 @@ context("Test GIS functions.") ## ---- gis_advisory ----------------------------------------------------------- test_that("gis_advisory", { - expect_identical(gis_advisory("AL092008", 32), - sprintf("%s%s%s", - rrricanes:::get_nhc_link(), - "gis/forecast/archive/", - "al092008_5day_032.zip")) + expect_identical( + gis_advisory("AL092008", 32), + sprintf( + "%s%s%s", + rrricanes:::get_nhc_link(), + "gis/forecast/archive/", + "al092008_5day_032.zip" + ) + ) }) ## ---- gis_breakpoints -------------------------------------------------------- -#TODO #109 +# TODO #109 # test_that("gis_breakpoints", { # expect_identical(gis_breakpoints(2017), # sprintf("%s%s%s", @@ -21,39 +25,54 @@ test_that("gis_advisory", { ## ---- gis_outlook ------------------------------------------------------------ test_that("gis_outlook", { - expect_identical(gis_outlook(), - sprintf("%s%s", - rrricanes:::get_nhc_link(), - "xgtwo/gtwo_shapefiles.zip")) + expect_identical( + gis_outlook(), + sprintf( + "%s%s", + rrricanes:::get_nhc_link(), + "xgtwo/gtwo_shapefiles.zip" + ) + ) }) ## ---- gis_prob_storm_surge --------------------------------------------------- test_that("gis_prob_storm_surge", { expect_identical( gis_prob_storm_surge("AL092016", - products = list("psurge" = 0), - datetime = "2016090306"), - sprintf("%s%s%s", - rrricanes:::get_nhc_link(), - "gis/storm_surge/", - "al092016_psurge0_2016090306.zip")) + products = list("psurge" = 0), + datetime = "2016090306" + ), + sprintf( + "%s%s%s", + rrricanes:::get_nhc_link(), + "gis/storm_surge/", + "al092016_psurge0_2016090306.zip" + ) + ) }) ## ---- gis_windfield ---------------------------------------------------------- test_that("gis_windfield", { - expect_identical(gis_windfield("AL142016", advisory = 30), - sprintf("%s%s%s", - rrricanes:::get_nhc_link(), - "gis/forecast/archive/", - "al142016_fcst_030.zip")) + expect_identical( + gis_windfield("AL142016", advisory = 30), + sprintf( + "%s%s%s", + rrricanes:::get_nhc_link(), + "gis/forecast/archive/", + "al142016_fcst_030.zip" + ) + ) }) ## ---- gis_wsp ---------------------------------------------------------------- test_that("NHC Link", { - expect_identical(gis_wsp(datetime = "2016100606", res = 0.5), - sprintf("%s%s%s", - rrricanes:::get_nhc_link(), - "gis/forecast/archive/", - "2016100606_wsp_120hrhalfDeg.zip")) + expect_identical( + gis_wsp(datetime = "2016100606", res = 0.5), + sprintf( + "%s%s%s", + rrricanes:::get_nhc_link(), + "gis/forecast/archive/", + "2016100606_wsp_120hrhalfDeg.zip" + ) + ) }) - diff --git a/tests/testthat/test_posest.R b/tests/testthat/test_posest.R index 86ddc2cd..536e2628 100644 --- a/tests/testthat/test_posest.R +++ b/tests/testthat/test_posest.R @@ -4,4 +4,3 @@ test_that("Test get_posest()", { expect_identical(al_09_2008_posest, df.al_09_2008_posest) }) - diff --git a/tests/testthat/test_prblty.R b/tests/testthat/test_prblty.R index e9e3e61c..80ea8836 100644 --- a/tests/testthat/test_prblty.R +++ b/tests/testthat/test_prblty.R @@ -4,4 +4,3 @@ test_that("get_prblty()", { expect_identical(al_01_1998_prblty, df.al_01_1998_prblty) }) - diff --git a/tests/testthat/test_products.R b/tests/testthat/test_products.R index 2694fe29..4b63fdc9 100644 --- a/tests/testthat/test_products.R +++ b/tests/testthat/test_products.R @@ -2,12 +2,12 @@ context("Test Product functions.") ## ---- twoal() ---------------------------------------------------------------- test_that("twoal()", { - x <- twoal() - expect_identical(is.list(x), TRUE) + x <- twoal() + expect_identical(is.list(x), TRUE) }) ## ---- twoep() ---------------------------------------------------------------- test_that("twoep()", { - x <- twoep() - expect_identical(is.list(x), TRUE) + x <- twoep() + expect_identical(is.list(x), TRUE) }) diff --git a/tests/testthat/test_public.R b/tests/testthat/test_public.R index 0c28dab5..890febb8 100644 --- a/tests/testthat/test_public.R +++ b/tests/testthat/test_public.R @@ -4,4 +4,3 @@ test_that("get_public", { expect_equal(al_09_2008_public, df.al_09_2008_public) }) - diff --git a/tests/testthat/test_scrapers.R b/tests/testthat/test_scrapers.R index ebcd54db..ebb5371a 100644 --- a/tests/testthat/test_scrapers.R +++ b/tests/testthat/test_scrapers.R @@ -108,5 +108,4 @@ test_that("Key", { rrricanes:::scrape_key(read_files(files$AL151999$fstadv[1])), "AL1599" ) - }) diff --git a/tests/testthat/test_tracking_chart.R b/tests/testthat/test_tracking_chart.R index c10bec64..b1310d34 100644 --- a/tests/testthat/test_tracking_chart.R +++ b/tests/testthat/test_tracking_chart.R @@ -2,6 +2,8 @@ context("Test tracking chart") ## ---- tracking_chart() ------------------------------------------------------- test_that("tracking_chart Errors", { - expect_error(tracking_chart(res = 20), - "Chart resolution must be 110, 50, 10") + expect_error( + tracking_chart(res = 20), + "Chart resolution must be 110, 50, 10" + ) }) diff --git a/tests/testthat/test_update.R b/tests/testthat/test_update.R index f5587ced..5d528127 100644 --- a/tests/testthat/test_update.R +++ b/tests/testthat/test_update.R @@ -4,4 +4,3 @@ test_that("get_update", { expect_identical(al_09_2008_update, df.al_09_2008_update) }) - diff --git a/tests/testthat/test_wndprb.R b/tests/testthat/test_wndprb.R index 5c4b5afe..d0902774 100644 --- a/tests/testthat/test_wndprb.R +++ b/tests/testthat/test_wndprb.R @@ -3,28 +3,36 @@ ## ---- * al_prblty_stations --------------------------------------------------- test_that("al_prblty_stations", { expect_warning(x <- rrricanes::al_prblty_stations(), - "Expected 7 pieces. Additional pieces discarded in 1 rows [90].", - fixed = TRUE) + "Expected 7 pieces. Additional pieces discarded in 1 rows [90].", + fixed = TRUE + ) expect_identical(dim(x), c(216L, 7L)) - expect_identical(names(x), - c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7")) + expect_identical( + names(x), + c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7") + ) }) ## ---- * cp_prblty_stations --------------------------------------------------- test_that("cp_prblty_stations", { expect_identical(dim(rrricanes::cp_prblty_stations()), c(168L, 7L)) - expect_identical(names(rrricanes::cp_prblty_stations()), - c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7")) + expect_identical( + names(rrricanes::cp_prblty_stations()), + c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7") + ) }) ## ---- * ep_prblty_stations --------------------------------------------------- test_that("ep_prblty_stations", { expect_warning(x <- rrricanes::ep_prblty_stations(), - "Expected 7 pieces. Missing pieces filled with `NA` in 1 rows [41].", - fixed = TRUE) + "Expected 7 pieces. Missing pieces filled with `NA` in 1 rows [41].", + fixed = TRUE + ) expect_identical(dim(x), c(168L, 7L)) - expect_identical(names(x), - c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7")) + expect_identical( + names(x), + c("X1", "Location", "Lat", "Lon", "X5", "X6", "X7") + ) }) ## ---- * get_wndprb ----------------------------------------------------------- From d3e10a85833d8ea0f1fa3dbb2ae864c0b20e9453 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 07:52:44 -0500 Subject: [PATCH 02/41] Remove tracking_chart functions --- NAMESPACE | 3 - NEWS.md | 2 + R/tracking_chart.R | 157 --------------------------- man/al_tracking_chart.Rd | 45 -------- man/ep_tracking_chart.Rd | 45 -------- man/tracking_chart.Rd | 52 --------- tests/testthat/test_tracking_chart.R | 9 -- 7 files changed, 2 insertions(+), 311 deletions(-) delete mode 100644 R/tracking_chart.R delete mode 100644 man/al_tracking_chart.Rd delete mode 100644 man/ep_tracking_chart.Rd delete mode 100644 man/tracking_chart.Rd delete mode 100644 tests/testthat/test_tracking_chart.R diff --git a/NAMESPACE b/NAMESPACE index 192ac9ed..b6bbe654 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,10 +1,8 @@ # Generated by roxygen2: do not edit by hand export(al_prblty_stations) -export(al_tracking_chart) export(cp_prblty_stations) export(ep_prblty_stations) -export(ep_tracking_chart) export(get_discus) export(get_fstadv) export(get_ftp_storm_data) @@ -36,7 +34,6 @@ export(tidy_fcst) export(tidy_fcst_wr) export(tidy_fstadv) export(tidy_wr) -export(tracking_chart) export(twoal) export(twoep) importFrom(magrittr,"%>%") diff --git a/NEWS.md b/NEWS.md index eb64e3ed..2b6c3322 100644 --- a/NEWS.md +++ b/NEWS.md @@ -22,6 +22,8 @@ rrricanes Unreleased (yyyy-mm-dd) * `ep_prblty_stations` now returns dataset of east Pacific stations. (#46) +* `tracking_chart` and associated functions have been removed in favor of rnaturalearth and related packages. See `vignette("gis_data", package = "rrricanes") for details. + ### BUG FIXES * `tidy_fcst` only returned forecasts for hours 12:96. Now returns 120. (#107) diff --git a/R/tracking_chart.R b/R/tracking_chart.R deleted file mode 100644 index 72aca1e5..00000000 --- a/R/tracking_chart.R +++ /dev/null @@ -1,157 +0,0 @@ -#' @title al_tracking_chart -#' @description Build tracking chart centered on Atlantic Basin. -#' @param ... Additional parameters for \link{tracking_chart} and ggplot2 -#' @seealso \code{\link{tracking_chart}} -#' @return ggplot2 object centered on Atlantic basin. -#' @examples -#' \dontrun{ -#' # Build map with white land areas, thin black borders -#' al_tracking_chart(color = "black", size = 0.1, fill = "white") -#' -#' # 50nm resolution, no states -#' al_tracking_chart( -#' res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # 50nm resolution, coastlines only -#' al_tracking_chart( -#' countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # Adding and modifying with ggplot functions -#' al_tracking_chart(color = "black", size = 0.1, fill = "white") + -#' ggplot2::labs( -#' x = "Lon", y = "Lat", -#' title = "Base Atlantic Tracking Chart" -#' ) -#' } -#' @export -al_tracking_chart <- function(...) { - p <- tracking_chart(...) - p + ggplot2::coord_equal(xlim = c(-100, 0), ylim = c(0, 60)) -} - -#' @title ep_tracking_chart -#' @description Build tracking chart centered on northeast Pacific Basin. -#' @param ... Additional parameters for ggplot2 -#' @seealso \code{\link{tracking_chart}} -#' @return ggplot2 object centered on northeast Pacific basin. -#' @examples -#' \dontrun{ -#' # Build map with white land areas, thin black borders -#' ep_tracking_chart(color = "black", size = 0.1, fill = "white") -#' -#' # 50nm resolution, no states -#' ep_tracking_chart( -#' res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # 50nm resolution, coastlines only -#' ep_tracking_chart( -#' countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # Adding and modifying with ggplot functions -#' ep_tracking_chart(color = "black", size = 0.1, fill = "white") + -#' ggplot2::labs( -#' x = "Lon", y = "Lat", -#' title = "Base East Pacific Tracking Chart" -#' ) -#' } -#' @export -ep_tracking_chart <- function(...) { - p <- tracking_chart(...) - p + ggplot2::coord_equal(xlim = c(-140, -80), ylim = c(0, 35)) -} - -#' @title tracking_chart -#' @description Build base tracking chart using ggplot -#' @param countries Show country borders. Default TRUE. -#' @param states Show state boundaries. Default TRUE. Ignored if `countries` is -#' FALSE. -#' @param res Resolution of charts; 110 (1:110m), 50 (1:50m), 10 (1:10m). -#' Default is low. The higher the resolution, the longer the plot takes to -#' appear. -#' @param ... Additional ggplot2::aes parameters -#' @return Returns ggplot2 object that can be printed directly or have new -#' layers added. -#' @seealso \code{\link[ggplot2]{aes}} -#' @examples -#' \dontrun{ -#' # Build map with white land areas, thin black borders -#' tracking_chart(color = "black", size = 0.1, fill = "white") -#' -#' # 50nm resolution, no states -#' tracking_chart( -#' res = 50, states = FALSE, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # 50nm resolution, coastlines only -#' tracking_chart( -#' countries = FALSE, res = 50, color = "black", size = 0.1, -#' fill = "white" -#' ) -#' -#' # Adding and modifying with ggplot functions -#' tracking_chart(color = "black", size = 0.1, fill = "white") + -#' ggplot2::labs(x = "Lon", y = "Lat", title = "Base Tracking Chart") -#' } -#' @export -tracking_chart <- function(countries = TRUE, states = TRUE, res = 110, ...) { - - # Convert to numeric just in case - res <- as.integer(res) - - # Validate res - if (!(res %in% c(110, 50, 10))) { - stop("Chart resolution must be 110, 50, 10") - } - - pkg <- "rnaturalearth" - if (res %in% c(110, 50)) { - pkg <- stringr::str_c(pkg, "data") - } else { - pkg <- stringr::str_c(pkg, "hires") - } - - # A base map can be drawn off either coastlines data or countries data. If - # countries is FALSE, return coastlines data. Otherwise, build countries w/ - # states if states is TRUE. - if (!countries) { - dataset <- stringr::str_c("coastline", res) - base_map_data <- getExportedValue(ns = pkg, name = dataset) - } else { - dataset <- stringr::str_c("countries", res) - base_map_data <- getExportedValue(ns = pkg, name = dataset) - if (states) { - if (res >= 50) { - dataset <- stringr::str_c("states", 50) - state_map_data <- getExportedValue(ns = pkg, name = dataset) - } else { - dataset <- stringr::str_c("states", res) - state_map_data <- getExportedValue(ns = pkg, name = dataset) - } - } - } - - p <- ggplot2::ggplot() + - ggplot2::geom_polygon( - data = base_map_data, - ggplot2::aes(.data$long, .data$lat, group = .data$group), ... - ) - - if (exists("state_map_data")) { - p <- p + - ggplot2::geom_polygon( - data = state_map_data, - ggplot2::aes(.data$long, .data$lat, group = .data$group), ... - ) - } - - return(p) -} diff --git a/man/al_tracking_chart.Rd b/man/al_tracking_chart.Rd deleted file mode 100644 index 07cbbecb..00000000 --- a/man/al_tracking_chart.Rd +++ /dev/null @@ -1,45 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/tracking_chart.R -\name{al_tracking_chart} -\alias{al_tracking_chart} -\title{al_tracking_chart} -\usage{ -al_tracking_chart(...) -} -\arguments{ -\item{...}{Additional parameters for \link{tracking_chart} and ggplot2} -} -\value{ -ggplot2 object centered on Atlantic basin. -} -\description{ -Build tracking chart centered on Atlantic Basin. -} -\examples{ -\dontrun{ -# Build map with white land areas, thin black borders -al_tracking_chart(color = "black", size = 0.1, fill = "white") - -# 50nm resolution, no states -al_tracking_chart( - res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white" -) - -# 50nm resolution, coastlines only -al_tracking_chart( - countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white" -) - -# Adding and modifying with ggplot functions -al_tracking_chart(color = "black", size = 0.1, fill = "white") + - ggplot2::labs( - x = "Lon", y = "Lat", - title = "Base Atlantic Tracking Chart" - ) -} -} -\seealso{ -\code{\link{tracking_chart}} -} diff --git a/man/ep_tracking_chart.Rd b/man/ep_tracking_chart.Rd deleted file mode 100644 index 6278cf06..00000000 --- a/man/ep_tracking_chart.Rd +++ /dev/null @@ -1,45 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/tracking_chart.R -\name{ep_tracking_chart} -\alias{ep_tracking_chart} -\title{ep_tracking_chart} -\usage{ -ep_tracking_chart(...) -} -\arguments{ -\item{...}{Additional parameters for ggplot2} -} -\value{ -ggplot2 object centered on northeast Pacific basin. -} -\description{ -Build tracking chart centered on northeast Pacific Basin. -} -\examples{ -\dontrun{ -# Build map with white land areas, thin black borders -ep_tracking_chart(color = "black", size = 0.1, fill = "white") - -# 50nm resolution, no states -ep_tracking_chart( - res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white" -) - -# 50nm resolution, coastlines only -ep_tracking_chart( - countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white" -) - -# Adding and modifying with ggplot functions -ep_tracking_chart(color = "black", size = 0.1, fill = "white") + - ggplot2::labs( - x = "Lon", y = "Lat", - title = "Base East Pacific Tracking Chart" - ) -} -} -\seealso{ -\code{\link{tracking_chart}} -} diff --git a/man/tracking_chart.Rd b/man/tracking_chart.Rd deleted file mode 100644 index f4c246d6..00000000 --- a/man/tracking_chart.Rd +++ /dev/null @@ -1,52 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/tracking_chart.R -\name{tracking_chart} -\alias{tracking_chart} -\title{tracking_chart} -\usage{ -tracking_chart(countries = TRUE, states = TRUE, res = 110, ...) -} -\arguments{ -\item{countries}{Show country borders. Default TRUE.} - -\item{states}{Show state boundaries. Default TRUE. Ignored if `countries` is -FALSE.} - -\item{res}{Resolution of charts; 110 (1:110m), 50 (1:50m), 10 (1:10m). -Default is low. The higher the resolution, the longer the plot takes to -appear.} - -\item{...}{Additional ggplot2::aes parameters} -} -\value{ -Returns ggplot2 object that can be printed directly or have new - layers added. -} -\description{ -Build base tracking chart using ggplot -} -\examples{ -\dontrun{ -# Build map with white land areas, thin black borders -tracking_chart(color = "black", size = 0.1, fill = "white") - -# 50nm resolution, no states -tracking_chart( - res = 50, states = FALSE, color = "black", size = 0.1, - fill = "white" -) - -# 50nm resolution, coastlines only -tracking_chart( - countries = FALSE, res = 50, color = "black", size = 0.1, - fill = "white" -) - -# Adding and modifying with ggplot functions -tracking_chart(color = "black", size = 0.1, fill = "white") + - ggplot2::labs(x = "Lon", y = "Lat", title = "Base Tracking Chart") -} -} -\seealso{ -\code{\link[ggplot2]{aes}} -} diff --git a/tests/testthat/test_tracking_chart.R b/tests/testthat/test_tracking_chart.R deleted file mode 100644 index b1310d34..00000000 --- a/tests/testthat/test_tracking_chart.R +++ /dev/null @@ -1,9 +0,0 @@ -context("Test tracking chart") - -## ---- tracking_chart() ------------------------------------------------------- -test_that("tracking_chart Errors", { - expect_error( - tracking_chart(res = 20), - "Chart resolution must be 110, 50, 10" - ) -}) From 1a30c607c4ae3ad0d62ef7a1e85b85461dbe54bf Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 07:53:54 -0500 Subject: [PATCH 03/41] gis_download now downloads zips to specified dir Previous version downloaded and read shapefiles into a list of datasets. This has been modified to take a destination directory (tempdir by default), unzip the contents and return a vector of all file names. --- DESCRIPTION | 1 - NEWS.md | 2 ++ R/gis.R | 23 +++++------------------ man/gis_download.Rd | 6 ++++-- 4 files changed, 11 insertions(+), 21 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5c8630b5..8c6b11d1 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -45,7 +45,6 @@ Suggests: knitr, rmarkdown, sf, - sp, testthat RoxygenNote: 6.1.1 VignetteBuilder: knitr diff --git a/NEWS.md b/NEWS.md index 2b6c3322..c612b591 100644 --- a/NEWS.md +++ b/NEWS.md @@ -24,6 +24,8 @@ rrricanes Unreleased (yyyy-mm-dd) * `tracking_chart` and associated functions have been removed in favor of rnaturalearth and related packages. See `vignette("gis_data", package = "rrricanes") for details. +* `gis_download` no longer reads in the shapefiles; only downloads and extracts the zip files. + ### BUG FIXES * `tidy_fcst` only returned forecasts for hours 12:96. Now returns 120. (#107) diff --git a/R/gis.R b/R/gis.R index 3df87cf4..6e6f3b52 100644 --- a/R/gis.R +++ b/R/gis.R @@ -103,32 +103,19 @@ gis_breakpoints <- function() { #' @title gis_download #' @description Get GIS data for storm. #' @param url link to GIS dataset to download. -#' @param ... additional parameters for rgdal::readOGR +#' @param destdir The destination directory to download and extract the zip file +#' @param ... additional parameters for file.path #' @export -gis_download <- function(url, ...) { - destdir <- tempdir() +gis_download <- function(url, destdir = tempdir(), ...) { - utils::download.file(file.path(url), zip_file <- tempfile()) + utils::download.file(file.path(url), zip_file <- tempfile(), ...) zip_contents <- utils::unzip(zip_file, list = TRUE)$Name utils::unzip(zip_file, exdir = destdir) - shp_files <- stringr::str_match(zip_contents, pattern = ".+shp$") - shp_files <- shp_files[stats::complete.cases(shp_files)] - - ds <- - purrr::map2( - .x = destdir, - .y = stringr::str_replace(shp_files, "\\.shp", ""), - .f = rgdal::readOGR, - encoding = "UTF-8", - stringsAsFactors = FALSE, - use_iconv = TRUE, - ... - ) + return(zip_contents) - rlang::set_names(ds, nm = stringr::str_replace(shp_files, "\\.shp", "")) } #' @title gis_latest diff --git a/man/gis_download.Rd b/man/gis_download.Rd index a2071bbd..0f8d10ee 100644 --- a/man/gis_download.Rd +++ b/man/gis_download.Rd @@ -4,12 +4,14 @@ \alias{gis_download} \title{gis_download} \usage{ -gis_download(url, ...) +gis_download(url, destdir = tempdir(), ...) } \arguments{ \item{url}{link to GIS dataset to download.} -\item{...}{additional parameters for rgdal::readOGR} +\item{destdir}{The destination directory to download and extract the zip file} + +\item{...}{additional parameters for file.path} } \description{ Get GIS data for storm. From 8661338211ef86c7d78092deb2cae5d49f1da9d6 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 07:56:21 -0500 Subject: [PATCH 04/41] Minor reformatting --- NEWS.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/NEWS.md b/NEWS.md index c612b591..28e80c13 100644 --- a/NEWS.md +++ b/NEWS.md @@ -14,8 +14,7 @@ rrricanes Unreleased (yyyy-mm-dd) * Allow parameters for rgdal::readOGR (#104) -* Add `tidy_adv` to replace `tidy_fstadv`; `tidy_fstadv` will be removed in - release 0.2.2 (#103) +* Add `tidy_adv` to replace `tidy_fstadv`; `tidy_fstadv` will be removed in release 0.2.2 (#103) * `al_prblty_stations` and `cp_prblty_stations` updated to accomodate new dataset. (#46) From e1f43ae172b414a9b9265bd9e2dc16a83caced1c Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 08:13:33 -0500 Subject: [PATCH 05/41] Removed shp_file (see commit 8661338) --- CHANGELOG.md | 12 ++- NAMESPACE | 1 - NEWS.md | 2 + R/base.R | 5 - R/gis.R | 19 ---- man/rrricanes.Rd | 5 - man/shp_to_df.Rd | 18 ---- vignettes/probabilistic_storm_surge.Rmd | 128 ---------------------- vignettes/wind_speed_probabilities.Rmd | 136 ------------------------ 9 files changed, 11 insertions(+), 315 deletions(-) delete mode 100644 man/shp_to_df.Rd delete mode 100644 vignettes/probabilistic_storm_surge.Rmd delete mode 100644 vignettes/wind_speed_probabilities.Rmd diff --git a/CHANGELOG.md b/CHANGELOG.md index e81148e0..051a3593 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -14,16 +14,22 @@ project adheres to [Semantic Versioning](http://semver.org/). - `get_storm_list` returns dataframe of all known cyclones. (#114) ### Changed - - `gis_download` and `gis_latest` can accept parameters for rgdal::readOGR - (#104). + - `gis_latest` can accept parameters for rgdal::readOGR (#104). + - `gis_download` modified to download zip files and extract contents + returning a vector of files within the zip. + - `ep_prblty_stations` now returns all stations. - `al_prblty_stations`, `cp_prblty_stations` and `ep_prblty_stations` datasets were modified with additional columns. Changes are documented. ### Removed - - NA + - `tracking_chart`, `al_tracking_chart`, and `ep_tracking_chart` all removed + in favor of using `rnaturalearth` and associated data packages, or other + mapping packages. + + - `shp_to_df` removed; users can use `sf::st_read` ### Deprecated - NA diff --git a/NAMESPACE b/NAMESPACE index b6bbe654..fd0ec5a2 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -27,7 +27,6 @@ export(knots_to_mph) export(mb_to_in) export(nm_to_sm) export(saffir) -export(shp_to_df) export(status_abbr_to_str) export(tidy_adv) export(tidy_fcst) diff --git a/NEWS.md b/NEWS.md index 28e80c13..05ca3939 100644 --- a/NEWS.md +++ b/NEWS.md @@ -25,6 +25,8 @@ rrricanes Unreleased (yyyy-mm-dd) * `gis_download` no longer reads in the shapefiles; only downloads and extracts the zip files. +* `shp_to_df` also removed in favor of built-in `sf` and `ggplot2` functions. + ### BUG FIXES * `tidy_fcst` only returned forecasts for hours 12:96. Now returns 120. (#107) diff --git a/R/base.R b/R/base.R index 9de81363..39abd8f2 100755 --- a/R/base.R +++ b/R/base.R @@ -83,11 +83,6 @@ #' \code{\link{gis_download}} will download the datasets from the above #' functions. #' -#' Some GIS datasets will need to be converted to dataframes to plot geoms. Use -#' \code{\link{shp_to_df}} to convert SpatialLinesDataFrames and -#' SpatialPolygonsDataFrames. SpatialPointsDataFrames can be converted using -#' \code{tibble::as_data_frame} targeting the @data object. -#' #' @section Package Options: #' #' \code{dplyr.show_progress} displays the dplyr progress bar when scraping raw diff --git a/R/gis.R b/R/gis.R index 6e6f3b52..ae1cc38c 100644 --- a/R/gis.R +++ b/R/gis.R @@ -498,22 +498,3 @@ gis_wsp <- function(datetime, res = c(5, 0.5, 0.1)) { stringr::str_c(get_nhc_link(), "gis/", links) } - -#' @title shp_to_df -#' @description Convert shapefile object to dataframe -#' @param obj Spatial object to convert. See details. -#' @details Takes a SpatialLinesDataFrame object or SpatialPolygonsDataFrame -#' object and converts into a dataframe that can be plotted in ggplot2. -#' @export -shp_to_df <- function(obj) { - if (class(obj) %in% c("SpatialLinesDataFrame", "SpatialPolygonsDataFrame")) { - obj@data$id <- rownames(obj@data) - obj <- dplyr::left_join(broom::tidy(obj, region = "id"), - obj@data, - by = "id" - ) %>% - tibble::as_tibble() - } - - obj -} diff --git a/man/rrricanes.Rd b/man/rrricanes.Rd index b30a41f4..890d60d5 100644 --- a/man/rrricanes.Rd +++ b/man/rrricanes.Rd @@ -94,11 +94,6 @@ core GIS functions return URLs to help you refine the data you wish to view. \code{\link{gis_download}} will download the datasets from the above functions. - -Some GIS datasets will need to be converted to dataframes to plot geoms. Use -\code{\link{shp_to_df}} to convert SpatialLinesDataFrames and -SpatialPolygonsDataFrames. SpatialPointsDataFrames can be converted using -\code{tibble::as_data_frame} targeting the @data object. } \section{Package Options}{ diff --git a/man/shp_to_df.Rd b/man/shp_to_df.Rd deleted file mode 100644 index 99bb24c8..00000000 --- a/man/shp_to_df.Rd +++ /dev/null @@ -1,18 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/gis.R -\name{shp_to_df} -\alias{shp_to_df} -\title{shp_to_df} -\usage{ -shp_to_df(obj) -} -\arguments{ -\item{obj}{Spatial object to convert. See details.} -} -\description{ -Convert shapefile object to dataframe -} -\details{ -Takes a SpatialLinesDataFrame object or SpatialPolygonsDataFrame -object and converts into a dataframe that can be plotted in ggplot2. -} diff --git a/vignettes/probabilistic_storm_surge.Rmd b/vignettes/probabilistic_storm_surge.Rmd deleted file mode 100644 index fac622e2..00000000 --- a/vignettes/probabilistic_storm_surge.Rmd +++ /dev/null @@ -1,128 +0,0 @@ ---- -title: "Probabilistic Storm Surge" -author: "Tim Trice" -date: "June 11, 2017" -output: html_document ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE, - fig.width = 10, - fig.asp = 1, - fig.align = "center") -``` - -```{r, message = FALSE} -library(dplyr) -library(ggplot2) -library(rrricanes) -library(rrricanesdata) -library(sp) -``` - -## Data - -```{r} -key <- "AL092008" -adv <- 42 -``` - -```{r} -fstadv <- fstadv %>% filter(Key == key, Adv <= adv) -``` - -## Probabilistic Storm Surge - -Calculate the last date/time of forecast/advisory product and subtract 3 hrs - -```{r} -dt <- (last(fstadv$Date) - (60 * 60 * 3)) %>% - strftime(format = "%Y%m%d%H", tz = "UTC") -``` - -Wrap `gis_download` in `safely`. Not all products will exist for every storm or even every advisory. - -I'm downloading the `psurge` products for 5 feet since there are no other storm surge products available for Ike. - -```{r} -dl <- purrr::safely(.f = gis_download) -gis_surge <- gis_prob_storm_surge(key, products = list("psurge" = c(5)), - datetime = dt) %>% dl() - -if (!is.null(gis_surge$error)) - message(gis_surge$error) -``` - -Generate a base plot of the Atlantic ocean. - -```{r} -bp <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50) -``` - -Since we're dealing with a polygon shapefile, we can get the bounding box of the dataset. - -```{r} -bbox <- bbox(gis_surge$result$al092008_2008091112_gt5) -``` - -Add a little cushion for the map inset. - -```{r} -lat_min <- bbox[2,1] - 2 -lat_max <- bbox[2,2] + 2 -lon_min <- bbox[1,1] - 4 -lon_max <- bbox[1,2] + 4 -``` - -Build a map inset. - -```{r} -bp_inset <- ggplotGrob(bp + - geom_rect(mapping = aes(xmin = lon_min, xmax = lon_max, - ymin = lat_min, ymax = lat_max), - color = "red", alpha = 0) + - theme_bw() + - theme(axis.title = element_blank(), - axis.ticks = element_blank(), - axis.text.x = element_blank(), - axis.text.y = element_blank(), - plot.margin = margin(0, 0, 0, 0, "pt"))) -``` - -Modify original `bp` zoomed in on our area of interest. - -```{r} -bp <- bp + - coord_equal(xlim = c(lon_min, lon_max), - ylim = c(lat_min, lat_max)) + - scale_x_continuous(expand = c(0, 0)) + - scale_y_continuous(expand = c(0, 0)) + - labs(x = "Lon", - y = "Lat", - caption = sprintf("rrricanes %s", packageVersion("rrricanes"))) -``` - -Combine `bp` and `bp_inset` to finalize initial base plot. `bp` will be a base plot without the inset. `bpi` will have the inset. - -```{r} -bpi <- bp + annotation_custom(grob = bp_inset, xmin = lon_max - 5, - xmax = lon_max - 1, ymin = -Inf, - ymax = lat_min + 5) -``` - -Convert the SpatialPolygonsDataframe to a dataframe. - -```{r} -shp_storm_surge <- shp_to_df(gis_surge$result$al092008_2008091112_gt5) -``` - -Probability of storm surge greater than five feet. - -```{r} -bpi + geom_point(data = shp_storm_surge, - aes(x = long, y = lat, color = ProbSurge05), size = 1) + - theme(legend.position = "bottom", - legend.box = "vertical") + - labs(title = "Probabilistic Storm Surge > 5ft", - caption = sprintf("rrricanes %s", packageVersion("rrricanes"))) -``` diff --git a/vignettes/wind_speed_probabilities.Rmd b/vignettes/wind_speed_probabilities.Rmd deleted file mode 100644 index f29bbb20..00000000 --- a/vignettes/wind_speed_probabilities.Rmd +++ /dev/null @@ -1,136 +0,0 @@ ---- -title: "Wind Speed Probabilities" -author: "Tim Trice" -date: "June 11, 2017" -output: html_document ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE, - fig.width = 10, - fig.asp = 1, - fig.align = "center") -``` - -```{r, message = FALSE} -library(dplyr) -library(ggplot2) -library(rrricanes) -library(rrricanesdata) -library(sp) -``` - -```{r} -key <- "AL092008" -adv <- 42 -``` - -```{r} -wndprb <- wndprb %>% filter(Key == key, Adv <= adv) -``` - -### GIS Advisory Forecast Track, Cone of Uncertainty, and Watches/Warnings - -```{r} -gis_adv <- gis_advisory(key = key, advisory = adv) %>% gis_download() -``` - -Get bounding box of the forecast polygon. - -```{r} -bbox <- bbox(gis_adv$al092008.042_5day_pgn) -bbox -``` - -## Build a Tracking Chart - -Generate a base plot of the Atlantic ocean. - -```{r} -bp <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50) -bp -``` - -I like to add a little cushion for the map inset and forecast cone data. - -```{r} -lat_min <- bbox[2,1] - 5 -lat_max <- bbox[2,2] + 5 -lon_min <- bbox[1,1] - 10 -lon_max <- bbox[1,2] + 10 -``` - -Build a thin tracking map for the inset. - -```{r} -bp_inset <- ggplotGrob(bp + - geom_rect(mapping = aes(xmin = lon_min, xmax = lon_max, - ymin = lat_min, ymax = lat_max), - color = "red", alpha = 0) + - theme_bw() + - theme(axis.title = element_blank(), - axis.ticks = element_blank(), - axis.text.x = element_blank(), - axis.text.y = element_blank(), - plot.margin = margin(0, 0, 0, 0, "pt"))) -``` - -Modify original `bp` zoomed in on our area of interest. - -```{r} -bp <- bp + - coord_equal(xlim = c(lon_min, lon_max), - ylim = c(lat_min, lat_max)) + - scale_x_continuous(expand = c(0, 0)) + - scale_y_continuous(expand = c(0, 0)) + - labs(x = "Lon", - y = "Lat", - caption = sprintf("rrricanes %s", packageVersion("rrricanes"))) -bp -``` - -Combine `bp` and `bp_inset` to finalize initial base plot. `bp` will be a base plot without the inset. `bpi` will have the inset. - -```{r} -bpi <- bp + annotation_custom(grob = bp_inset, xmin = lon_max - 5, - xmax = lon_max - 1, ymin = -Inf, - ymax = lat_min + 5) -bpi -``` - -The `wndprb` will not have coordinates for cities. An option is `al_prblty_stations`. However, please note this function may become [deprecated](https://github.com/ropensci/rrricanes/issues/46). - -```{r} -wndprb <- - wndprb %>% - left_join(al_prblty_stations(), by = "Location") %>% - mutate_at(.vars = c("Lat", "Lon"), .funs = as.numeric) -``` - -Check `wndprb` for NA values in `Lat`, `Lon`. - -```{r} -any(is.na(wndprb$Lat), is.na(wndprb$Lon)) -``` - -```{r} -wndprb_adv42 <- filter(wndprb, Adv == adv, Wind >= 64) - -bpi + - geom_point( - data = wndprb_adv42, - aes( - x = Lon, - y = Lat, - color = Wind120Cum, - size = Wind120Cum - ) - ) + - scale_color_gradientn(colors = terrain.colors(10)) + - guides(size = FALSE) + - theme( - legend.position = "bottom", - legend.box = "vertical" - ) + - labs(title = "Total Probability of Wind >= 64kts within 120 Hours") -``` From 520456681825810684dd525f92e878f9eec26365 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 08:20:56 -0500 Subject: [PATCH 06/41] Remove unused `reports` dir --- reports/child_al.Rmd | 17 ---- reports/child_ep.Rmd | 4 - reports/child_storm.Rmd | 50 ---------- reports/latest.Rmd | 44 --------- reports/latest.html | 207 ---------------------------------------- reports/practice.Rmd | 100 ------------------- 6 files changed, 422 deletions(-) delete mode 100644 reports/child_al.Rmd delete mode 100644 reports/child_ep.Rmd delete mode 100644 reports/child_storm.Rmd delete mode 100644 reports/latest.Rmd delete mode 100644 reports/latest.html delete mode 100644 reports/practice.Rmd diff --git a/reports/child_al.Rmd b/reports/child_al.Rmd deleted file mode 100644 index 8df3fe1a..00000000 --- a/reports/child_al.Rmd +++ /dev/null @@ -1,17 +0,0 @@ - -```{r keys_al} -keys_al <- keys[str_which(keys, "^AL.")] -``` - -```{r} -if (is_empty(keys_al)) { - src <- "There are no storms in the Atlantic basin." -} else { - src <- walk(keys_al, function(x) { - knit_expand(file = "child_storm.Rmd", - arguments = list(key = x)) - }) -} -``` - -`r knit(text = unlist(src))` diff --git a/reports/child_ep.Rmd b/reports/child_ep.Rmd deleted file mode 100644 index 6e2a4eeb..00000000 --- a/reports/child_ep.Rmd +++ /dev/null @@ -1,4 +0,0 @@ - -```{r keys_ep} -(keys_ep <- keys[str_which(keys, "^EP.")]) -``` diff --git a/reports/child_storm.Rmd b/reports/child_storm.Rmd deleted file mode 100644 index 89034a1e..00000000 --- a/reports/child_storm.Rmd +++ /dev/null @@ -1,50 +0,0 @@ - -### {{arguments$key}} - -```{r} -# Find names of relevant datasets -ds <- grep(sprintf("^%s.", arguments$key), names(gis), ignore.case = TRUE, - value = TRUE) -``` - - -```{r} -# Get previous track points -points <- as_data_frame(gis[[ds[grep(sprintf("%s_pts", arguments$key), - ds, ignore.case = TRUE)]]]) -# Convert points$STORMTYPE to factor -points$STORMTYPE <- factor(points$STORMTYPE, - levels = c("DB", "LO", "TD", "TS", "HU", "MH"), - labels = c("Disturbance", "Low", - "Tropical Depression", "Tropical Storm", - "Hurricane", "Major Hurricane")) - -plot_points <- geom_point(data = points, aes(x = LON, y = LAT, size = STORMTYPE)) -``` - -```{r} -# Get forecast track points -fcst_points <- as_data_frame(gis[[ds[grep(sprintf("%s.+_5day_pts", - arguments$key), ds, - ignore.case = TRUE)]]]) - - -# Convert points$STORMTYPE to factor -fcst_points$STORMTYPE <- factor(fcst_points$STORMTYPE, - levels = c("DB", "LO", "TD", "TS", "HU", "MH"), - labels = c("Disturbance", "Low", - "Tropical Depression", "Tropical Storm", - "Hurricane", "Major Hurricane")) - -plot_fcst_points <- geom_point(data = fcst_points, - aes(x = LON, y = LAT, size = STORMTYPE)) -``` - -```{r} -tracking_chart(color = "black", fill = "white", size = 0.1, res = 50) + - plot_points + - plot_fcst_points + - theme(legend.position = "bottom", - legend.box = "vertical") -``` - diff --git a/reports/latest.Rmd b/reports/latest.Rmd deleted file mode 100644 index ac51a30c..00000000 --- a/reports/latest.Rmd +++ /dev/null @@ -1,44 +0,0 @@ ---- -title: "Latest Tropical Cyclone Activity" -output: - html_document: - toc: TRUE - code_folding: hide ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE) -``` - -```{r libraries} -library(ggplot2) -library(HURDAT) -library(knitr) -library(purrr) -library(rrricanes) -library(rrricanesdata) -library(stringr) -library(tibble) -``` - -```{r gis_latest, message = FALSE} -gis <- flatten(gis_latest(verbose = FALSE)) -``` - -```{r keys} -# Keys of existing storms -keys <- str_extract(names(gis), "(^[[:alpha:]]{2}[[:digit:]]{6})") %>% - toupper() %>% - unique() %>% - .[complete.cases(.)] -``` - -## Atlantic Basin - -```{r al, child = "child_al.Rmd"} -``` - -## East Pacific Basin - -```{r ep, child = "child_ep.Rmd"} -``` diff --git a/reports/latest.html b/reports/latest.html deleted file mode 100644 index 7c49e587..00000000 --- a/reports/latest.html +++ /dev/null @@ -1,207 +0,0 @@ - - - - - - - - - - - - - -Latest Tropical Cyclone Activity - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - -
library(HURDAT)
-library(knitr)
-library(purrr)
-library(rrricanes)
-
## rrricanes is not intended for use in emergency situations.
-
library(rrricanesdata)
-library(stringr)
-
gis <- flatten(gis_latest(verbose = FALSE))
-
# Keys of existing storms
-keys <- str_extract(names(gis), "(^[[:alpha:]]{2}[[:digit:]]{6})") %>% 
-  toupper() %>% 
-  unique() %>% 
-  .[complete.cases(.)]
-
-

Atlantic Basin

-
keys_al <- keys[str_which(keys, "^AL.")]
-
if (is_empty(keys_al)) {
-  src <- "There are no storms in the Atlantic basin."
-} else {
-  src <- walk(keys_al, function(x) {
-    knit_expand(file = "child_storm.Rmd", 
-                arguments = list(key = x))
-  })
-}
-

AL112017

-
-
-

East Pacific Basin

-
(keys_ep <- keys[str_which(keys, "^EP.")])
-
## [1] "EP142017"
-
- - - - -
- - - - - - - - diff --git a/reports/practice.Rmd b/reports/practice.Rmd deleted file mode 100644 index e225b462..00000000 --- a/reports/practice.Rmd +++ /dev/null @@ -1,100 +0,0 @@ ---- -title: "Practice" -author: "Tim Trice" -date: "June 27, 2017" -output: html_document ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE, - fig.align = "center") -``` - -```{r setup, include=FALSE} -knitr::opts_chunk$set(echo = TRUE) -``` - -```{r libraries} -library(ggplot2) -library(HURDAT) -library(knitr) -library(purrr) -library(rrricanes) -library(rrricanesdata) -library(sp) -library(stringr) -library(tibble) -``` - -```{r gis_latest, message = FALSE} -gis <- flatten(gis_latest(verbose = FALSE)) -``` - -```{r} -pts <- as_data_frame(gis$AL112017_pts) -lin <- shp_to_df(gis$AL112017_lin) -windswath <- shp_to_df(gis$AL112017_windswath) -radii <- shp_to_df(gis$AL112017_radii) -initial_radii <- shp_to_df(gis$al112017_2017090409_initialradii) -fcst_radii <- shp_to_df(gis$al112017_2017090409_forecastradii) -fcst_pts <- as_data_frame(gis$al112017_020_5day_pts) -fcst_lin <- shp_to_df(gis$al112017_020_5day_lin) -fcst_cone <- shp_to_df(gis$al112017_020_5day_pgn) -``` - -```{r} -l <- list("bbox.pts" = bbox(gis$AL112017_pts), - "bbox.lin" = bbox(gis$AL112017_lin), - "bbox.windswath" = bbox(gis$AL112017_windswath), - "bbox.radii" = bbox(gis$AL112017_radii), - "bbox.initial_radii" = bbox(gis$al112017_2017090309_initialradii), - "bbox.fcst_radii" = bbox(gis$al112017_2017090309_forecastradii), - "bbox.fcst_pts" = bbox(gis$al112017_016_5day_pts), - "bbox.fcst_lin" = bbox(gis$al112017_016_5day_lin), - "bbox.fcst_cone" = bbox(gis$al112017_016_5day_pgn)) - -bb <- matrix(c(map(l, `[[`, 1) %>% flatten_dbl() %>% min(), - map(l, `[[`, 2) %>% flatten_dbl() %>% max()), - nrow = 2, - ncol = 2) -``` - -```{r} -# Current and past details -plot_lin <- geom_path(data = lin, aes(x = long, y = lat, color = STORMTYPE)) - -plot_pts <- geom_point(data = pts, - aes(x = LON, y = LAT, color = STORMTYPE, size = INTENSITY)) - -# Forecast details -plot_fcst_lin <- geom_path(data = fcst_lin, - aes(x = long, y = lat, color = STORMTYPE)) - -plot_fcst_pts <- geom_point(data = fcst_pts, - aes(x = LON, y = LAT, color = STORMTYPE, - size = MAXWIND)) -# Forecast cone -plot_fcst_cone <- geom_polygon(data = fcst_cone, - aes(x = long, y = lat, group = group, - fill = FCSTPRD), alpha = 0.25) - -# Wind radii details -plot_initial_radii <- geom_polygon(data = initial_radii, - aes(x = long, y = lat, group = group, - fill = factor(RADII)), - alpha = 0.25) -``` - -```{r} -tracking_chart(color = "black", fill = "white", size = 0.1, res = 50) + - plot_lin + - plot_pts + - plot_fcst_lin + - plot_fcst_pts + - plot_fcst_cone + - coord_equal(xlim = c(-80, -16), - ylim = c(11.5, 25)) + - theme(legend.position = "bottom", - legend.direction = "vertical") -``` - From a6acf0496c6cbe28bfe959767ff91a9eb92f5680 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 08:58:30 -0500 Subject: [PATCH 07/41] Update GIS vignettes --- DESCRIPTION | 2 + vignettes/forecast_advisory.Rmd | 154 ------- vignettes/gis_data.Rmd | 693 +++++++++++++++++++++++++------- 3 files changed, 542 insertions(+), 307 deletions(-) delete mode 100644 vignettes/forecast_advisory.Rmd diff --git a/DESCRIPTION b/DESCRIPTION index 8c6b11d1..b7fffc41 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -44,6 +44,8 @@ Suggests: devtools, knitr, rmarkdown, + rnaturalearthhires, + scales, sf, testthat RoxygenNote: 6.1.1 diff --git a/vignettes/forecast_advisory.Rmd b/vignettes/forecast_advisory.Rmd deleted file mode 100644 index 6ffff426..00000000 --- a/vignettes/forecast_advisory.Rmd +++ /dev/null @@ -1,154 +0,0 @@ ---- -title: "Forecast/Advisory GIS" -author: "Tim Trice" -date: "June 11, 2017" -output: html_document ---- - -```{r setup, include=FALSE} -knitr::opts_chunk$set( - echo = TRUE, - fig.width = 7, - fig.asp = 1, - fig.align = "center" -) -``` - -```{r, message = FALSE} -library(dplyr) -library(ggplot2) -library(rrricanes) -library(rrricanesdata) -library(sp) -``` - -```{r} -key <- "AL092008" -adv <- 42 -``` - -```{r} -fstadv <- fstadv %>% filter(Key == key, Adv <= adv) -``` - -### GIS Advisory Forecast Track, Cone of Uncertainty, and Watches/Warnings - -```{r} -gis_adv <- gis_advisory(key = key, advisory = adv) %>% gis_download() -``` - -Get bounding box of the forecast polygon. - -```{r} -bbox <- bbox(gis_adv$al092008.042_5day_pgn) -``` - -Generate a base plot of the Atlantic ocean. - -```{r} -(bp <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50)) -``` - -I like to add a little cushion for the map inset and forecast cone data. - -```{r} -lat_min <- bbox[2,1] - 5 -lat_max <- bbox[2,2] + 5 -lon_min <- bbox[1,1] - 10 -lon_max <- bbox[1,2] + 10 -``` - -Build a thin tracking map for the inset. - -```{r} -bp_inset <- ggplotGrob(bp + - geom_rect(mapping = aes(xmin = lon_min, xmax = lon_max, - ymin = lat_min, ymax = lat_max), - color = "red", alpha = 0) + - theme_bw() + - theme(axis.title = element_blank(), - axis.ticks = element_blank(), - axis.text.x = element_blank(), - axis.text.y = element_blank(), - plot.margin = margin(0, 0, 0, 0, "pt"))) -``` - -Modify original `bp` zoomed in on our area of interest. - -```{r} -(bp <- bp + - coord_equal(xlim = c(lon_min, lon_max), - ylim = c(lat_min, lat_max)) + - scale_x_continuous(expand = c(0, 0)) + - scale_y_continuous(expand = c(0, 0)) + - labs(x = "Lon", - y = "Lat", - caption = sprintf("rrricanes %s", packageVersion("rrricanes")))) -``` - -Combine `bp` and `bp_inset` to finalize initial base plot. `bp` will be a base plot without the inset. `bpi` will have the inset. - -```{r} -(bpi <- bp + annotation_custom(grob = bp_inset, xmin = lon_max - 5, - xmax = lon_max - 1, ymin = -Inf, - ymax = lat_min + 5)) -``` - -## Current Advisory Details - -Lines and Polygons spatial dataframes can be helpfully converted using `shp_to_df`. The original spatial dataframes can be plotted directly in `ggplot2` but, to my understanding, access to the other variables are not available. - -```{r} -# Convert object SpatialLinesDataframe to dataframe -shp_storm_lin <- shp_to_df(gis_adv$al092008.042_5day_lin) -shp_storm_ww <- shp_to_df(gis_adv$al092008.042_ww_wwlin) -# Convert object SpatialPolygonsDataframe to dataframe -shp_storm_pgn <- shp_to_df(gis_adv$al092008.042_5day_pgn) -``` - -Points dataframes can just be converted with `tibble::as_data_frame`. - -```{r} -# Convert object SpatialPointsDataframe to dataframe -shp_storm_pts <- as_data_frame(gis_adv$al092008.042_5day_pts) -``` - -Modify `shp_storm_pts$DVLBL` with full strings and ordered factor. - -```{r} -shp_storm_pts$DVLBL <- factor(shp_storm_pts$DVLBL, - levels = c("D", "S", "H"), - labels = c("Tropical Depression", - "Tropical Storm", - "Hurricane")) -``` - -Same with `shp_storm_pts$TCWW`: - -```{r} -shp_storm_ww$TCWW <- factor(shp_storm_ww$TCWW, - levels = c("TWA", "TWR", "HWA", "HWR"), - labels = c("Tropical Storm Watch", - "Tropical Storm Warning", - "Hurricane Watch", - "Hurricane Warning")) -``` - -```{r} -bpi + geom_polygon(data = shp_storm_pgn, - aes(x = long, y = lat, group = group), - alpha = 0.15, fill = "orange") + - geom_path(data = shp_storm_lin, aes(x = long, y = lat, group = group)) + - geom_point(data = shp_storm_pts, aes(x = LON, y = LAT, fill = DVLBL, - shape = DVLBL, size = MAXWIND)) + - geom_path(data = shp_storm_ww, aes(x = long, y = lat, color = TCWW, - group = group), size = 1) + - scale_shape_manual(values = c(21, 21, 21, 21)) + - guides(shape = guide_legend(override.aes = list(size = 3)), - size = guide_legend(nrow = 1)) + - theme(legend.position = "bottom", - legend.box = "vertical") -``` - -Very often, areas that are under a hurricane watch may also be under a tropical storm warning. The chart above does not show the hurricane watch area. - diff --git a/vignettes/gis_data.Rmd b/vignettes/gis_data.Rmd index 1c9321a5..db264123 100644 --- a/vignettes/gis_data.Rmd +++ b/vignettes/gis_data.Rmd @@ -1,15 +1,20 @@ --- -title: "GIS data" +title: "Retrieving and Plotting GIS Data" author: "Tim Trice" date: "`r Sys.Date()`" -output: rmarkdown::html_vignette +output: + rmarkdown::html_vignette: + toc: true + toc_depth: 3 vignette: > %\VignetteIndexEntry{GIS data} - %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} + %\VignetteEngine{knitr::rmarkdown} +editor_options: + chunk_output_type: console --- -```{r, message = FALSE} +```{r libraries, message = FALSE} library(dplyr) library(ggplot2) library(rrricanes) @@ -26,261 +31,643 @@ Some datasets require the use of the storm key and an optional advisory. Other p ## Build a Tracking Chart -There are three functions available to help you plot GIS data; `tracking_chart`, `al_tracking_chart` and `ep_tracking_chart`. `al_tracking_chart` and `ep_tracking_chart` are just helpers centered on the Atlantic and northeast Pacific ocean, respectively. +As of version 0.2.7, the built-in tracking chart functions have been removed. Users are encouraged to use the `rnaturalearthdata` and associated packages to build tracking charts. -```{r} -args(rrricanes::tracking_chart) +The `rnaturalearthdata` package has many shapefile datasets that can be used to make maps. For this article I will only need countries and states. I will use the resolution of 10 nautical miles (available in the `rnaturalearthhires` package). Each dataset is named `countries10` and `states10`. + +```{r base-plot, fig.width = 7, fig.asp = 0.75, fig.align = "center"} +p <- + ggplot() + + geom_sf( + data = sf::st_as_sf(rnaturalearthhires::countries10), + fill = "gray95", + color = "black", + size = 0.1 + ) + + geom_sf( + data = sf::st_as_sf(rnaturalearthhires::states10), + fill = "gray95", + size = 0.1 + ) +p ``` -The `countries` and `states` parameters are TRUE by default. This means a basic call to `tracking_chart` will return a map with country and state borders. The `res` parameter is resolution; one of 110, 50 or 10 nautical miles. Resolutions 110nm and 50nm can be used immediately. To use lower resolution you must install the `rnaturalearthdatahires` package from ropensci: +I'll also remove the padding around the plot and change the color of the seas (`panel.background`). -```{r, eval = FALSE} -install.packages("rnaturalearthhires", - repos = "http://packages.ropensci.org", - type = "source") +```{r base-plot-plus-scale, fig.width = 7, fig.asp = 0.75, fig.align = "center"} +p <- + p + + scale_x_continuous( + expand = c(0, 0) + ) + + scale_y_continuous( + expand = c(0, 0) + ) + + theme( + panel.background = element_rect(fill = "white"), + panel.grid.major = element_line(color = "black", size = 0.1) + ) + + labs( + x = "", + y = "", + caption = sprintf("rrricanes %s", packageVersion("rrricanes")) + ) +p ``` -`tracking_chart` will print a basic tracking chart (a map of the planet). +## GIS Datasets -```{r, fig.width = 7, fig.align = "center"} -tracking_chart() -``` +There are several datasets that are published for active cyclones. The following functions are designed to return the URL to those datasets: -You can pass typical `aes` parameters to refine the color and fill of the plot; remember the tracking chart is a ggplot object. +* `gis_advisory` +* `gis_prob_storm_surge` +* `gis_windfield` +* `gis_latest` (only for active storms) + +It's important to note that not every storm will have a dataset available. Nor are datasets consistent from one storm to the next. For example, as we'll see below, a forecast cone should have two polygons for a 72-hour and 120-hour forecast; in this example, they are both 120-hours. -```{r, fig.width = 7, fig.align = "center"} -tracking_chart(color = "black", fill = "white", size = 0.1) +Let's take a look at Hurricane Matthew (AL142016) and focus on advisory 37. + +```{r vars} +key <- "AL142016" +adv <- 37 ``` -You may choose to only show coastline data instead. In this case, just set the countries parameter to FALSE. +### Data Scraping + +The functions listed above do not retrieve the data. They only return the URLs. This is to give you the opportunity to modify your requests to get the specific data needed, if it exists. + +#### `gis_advisory` -```{r, fig.width = 7, fig.align = "center"} -tracking_chart(countries = FALSE, res = 50, color = "black", fill = "white", - size = 0.1) +The `gis_advisory` function returns the URL for the GIS dataset by `key` and `advisory` number. Remember, a storm's key should always be eight alphanumeric characters; + + + Basin identifier ("AL", "CP", or "EP") + + + Storm number for the year + + + The four digit year + +The `fstadv` product will always have the storm key. In earlier years, the "year" portion of the key was only the year without the century; you will need to add it. + +```{r gis-advisory-args} +args(gis_advisory) ``` -For the purposes of this vignette we'll focus on Atlantic storms. +We can test that an advisory package does exist for our specific advisory. -```{r, fig.width = 7, fig.align = "center"} -(p <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50)) +```{r gis-advisory} +gis_advisory(key = key, advisory = adv) ``` -The `res` parameter defines the resolution of the chart presented. Options are in 110nm, 50nm and 10nm. The lower the resolution the longer the chart takes to be built. +This should work. -States cannot be drawn on resolution greater than 50nm. +#### `gis_windfield` -## GIS Datasets +The `gis_windfield` product is relatively new so it may not exist for some storms. As with `gis_advisory`, we only need the storms' key and advisory. -There are several datasets that are published for active cyclones. The following functions are designed to return the URL to those datasets: +```{r gis-windfield-args} +args(gis_windfield) +``` -* `gis_advisory` -* `gis_prob_storm_surge` -* `gis_windfield` -* `gis_latest` +```{r gis-windfield} +gis_windfield(key = key, advisory = adv) +``` + +#### `gis_prob_storm_surge` -## Advisory Package +The function `gis_prob_storm_surge` also uses the `key` variable, but not the advisory; instead, it uses `datetime`. -```{r} -gis_advisory(key = "AL182012", advisory = "18") +There are two types of products that can be retrieved, "esurge" and "psurge". psurge shows the probability of a specific height (in feet) of storm surge affecting an area. Values between 0 and 20 can be used. + +```r +gis_prob_storm_surge( + key = key, + datetime = "2016100706", + products = list( + # esurge = 10 + psurge = 5 + ) +) ``` -```{r, eval = FALSE} -df.gis_adv <- gis_advisory(key = "AL182012", advisory = "18") %>% gis_download() +In the example above, we are requesting the probabilities of a 5-foot storm surge affecting the coastline and inland waterways. + +esurge shows the probability of a specific storm surge height exceeding the forecast height. Valid values are 10, 20, 30, 04, and 50. Note the commented section in the code above. + +The `products` parameter expects a list, though you do not need to include both products. Additionally, each product expects a numeric or numeric vector. If you make a broad general request, the National Hurricane Center requests no more than 80 requests per 10 seconds, so please be respectful. Unlike retrieving text products, there is no throttle in this package to download GIS datasets. + +Regarding `datetime`, this value should be that of the advisory time minus 3 hours not including minutes and seconds. Let's get that value for Matthew's #37 advisory. + +```{r datetime} +datetime <- + get_storms(years = "2016", basins = "AL") %>% + filter(Name == "Hurricane Matthew") %>% + pull(Link) %>% + get_fstadv() %>% + filter(Adv == adv) %>% + pull(Date) + +# Subtract 3 hours +datetime <- datetime - 3 * 60 * 60 + +# Turn into string without the seconds. Format is YYYYMMDDHH +datetime <- as.character.Date(datetime, "%Y%m%d%H") + +datetime ``` -```{r} -names(df.gis_adv) +Let's make sure we can get a psurge 5 product for this datetime value. + +```{r gis-prob-storm-surge} +gis_prob_storm_surge(key = key, products = list(psurge = 5), datetime = datetime) ``` -For this particular storm and advisory, included are the base line, point and polygon datasets along with a dataset for watches and warnings. The objects returned are spatial dataframes contained within the list of dataframes, `df.gis_adv`. +Looks good. -### Line track +##### `gis_wsp` -```{r} -str(df.gis_adv$al182012.018_5day_lin) -``` +Wind speed probabilities exist in the `gis_wsp` datasets. Like `gis_prob_storm_surge`, we will need `datetime`, but we will not need `key`. The last parameter is `res` (resolution). Valid values are 5, 0.5, and 0.1 degrees. The default is all three. Not all resolutions will be available for all storms. -As we're dealing with a SpatialLinesDataFrame which needs to be modified, you can use the helper function `shp_to_df` for plotting. +```{r gis-wsp-args} +args(gis_wsp) +``` -```{r} -fcst_line <- shp_to_df(df.gis_adv$al182012.018_5day_lin) +```{r gis-wsp} +# List of datasets for 5-degree resolution +gis_wsp(datetime = datetime, res = 0.5) ``` -```{r, fig.width = 7, fig.align = "center"} -p + geom_path(data = fcst_line, aes(long, lat, group = FCSTPRD)) +#### Downloading Data + +Now that we've explored the various functions, let's go about downloading the datasets to plot. For efficiency, I use a lot of `purrr` mapping functions here, loading each step into one variable. + +First, I want to load all of my URLs into one vector. + +```{r get-urls} +# Get URLs of GIS datasets to analyze +urls <- c( + # Advisory package + gis_advisory(key = key, advisory = adv), + + # Wind field (initial and forecast) package + gis_windfield(key = key, advisory = adv), + + # Storm surge probability package + gis_prob_storm_surge( + key = key, + products = list(psurge = 5), + datetime = datetime + ), + + # Wind speed probability package + gis_wsp(datetime = datetime, res = 0.5) +) ``` -There are two groups of data in the set: one for 72-hour forecast period and one for 120-hour. Grouping by `FCSTPRD` will show the forecast track correctly. +Previously, `gis_download` would download the datasets, extract the shapefiles and convert them, if possible, into dataframes. Thankfully, this is no longer necessary with various improvements in the `sp` and `ggplot2` packages. Now, the `gis_download` function will only download the zip files into a specified directory. For this vignette, we'll use a temporary directory, `tempdir`. -There is a pretty wide field of view on the map above. You can use `sp::bbox` to "zoom in" on the map. +```{r download-data} +# Set our download directory +destdir <- tempdir() -```{r} -(bb <- sp::bbox(df.gis_adv$al182012.018_5day_lin)) +# Download datasets +file_list <- + urls %>% + purrr::map(gis_download, destdir) %>% + purrr::flatten_chr() + +file_list ``` -```{r, fig.width = 7, fig.align = "center"} -(p2 <- p + geom_path(data = fcst_line, aes(long, lat, group = FCSTPRD)) + - coord_equal(xlim = c(bb[1,1] - 5, bb[1,2] + 5), - ylim = c(bb[2,1] - 5, bb[2,2] + 5))) +There are a lot of files here. Thankfully, we only care about the shapefiles (marked by the ".shp" extension). Let's filter those. + +```{r filter-shapefiles} +# Filter out shapefiles +shp_files <- grep(".shp$", file_list, value = TRUE) +shp_files ``` -### Point track +We can use `sf::st_read` to read in each shapefile as a shapefile dataframe. The output is quite verbose; you can pass the parameter `quiet` as TRUE. + +```{r read-shapefiles} +# Read in shapefiles +shp_df <- purrr::map(shp_files, ~ sf::st_read(file.path(destdir, .x))) +``` -Each forecast position is also included in the points dataframe. You can access this in the `df.gis_adv$al182012.018_5day_pts@data` object; no conversion necessary. +And, while not necessary, I will rename the list of dataframes, `shp_df`, to the names of their respective shapefiles minus the file extension. -```{r, fig.width = 7, fig.align = "center"} -(p3 <- p2 + geom_point(data = df.gis_adv$al182012.018_5day_pts@data, aes(LON, LAT))) +```{r name-shapefiles} +# Create names from shapefiles by removing file extension +shp_df <- rlang::set_names(shp_df, nm = tools::file_path_sans_ext(shp_files)) +names(shp_df) ``` -## Forecast Cone +This next stop is also not necessary. I actually found it a bit broad and rarely used it but will leave it here as an example. + +Each shapefile has a bounding box; this box is a zoomed-in coordinate map of each dataset. We can access the bounding box of each dataset with the `sf::st_bbox` function. + +For example, in our advisory package we have the forecast cones (a polygon shapefile). Let's see what the bounding box is for that dataset. -Forecast cone data is contained in the polygon dataset. To deal with this dataset you can use the `shp_to_df` function again or take the slightly longer way: +```{r st-bbox} +sf::st_bbox(shp_df$`al142016-037_5day_pgn`) +``` + +Our data is contained between approximately 71°W and 81°W (note the negatives -- the western hemisphere), and between 23°N and 34°N. Let's see where that is. -```{r} -fcst_cone <- df.gis_adv$al182012.018_5day_pgn -fcst_cone@data$id <- rownames(fcst_cone@data) -fcst_cone.points <- broom::tidy(fcst_cone, region = "id") -fcst_cone <- dplyr::left_join(fcst_cone.points, fcst_cone@data, by = "id") +```{r zoom-base-plot, fig.width = 7, fig.asp = 0.75, fig.align = "center"} +p + + coord_sf( + xlim = c( + sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmin, + sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmax + ), + ylim = c( + sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymin, + sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymax + ) + ) ``` -```{r, fig.width = 7, fig.align = "center"} -p3 + geom_polygon(data = fcst_cone %>% filter(FCSTPRD == 120), - aes(long, lat, group = group, fill = factor(FCSTPRD)), - alpha = 0.5) + - geom_polygon(data = fcst_cone %>% filter(FCSTPRD == 72), - aes(long, lat, group = group, fill = factor(FCSTPRD)), - alpha = 0.5) +Nice! + +I want to find the largest bounding box within the datasets for my map. For this, I calculate the area for each box of each dataset, identify which has the largest area then extract the bounding box for that dataset. + +Notice I only search the advisory package datasets for a bounding box. The probability datasets may contain data for other cyclones across the world making our bounding box (and subsequent maps) quite wide. I have no interest in that so kept the focus only on Matthew. + +```{r calculate-max-bbox} +# Find which shapefile has the largest bounding box. Proability datasets are +# excluded as they may contain data for other cyclones. This may depend on +# the storm. +x <- purrr::map(shp_df[c(1:4)], sf::st_bbox) %>% + # Calculate the coverage for each bbox + purrr::map_dbl(~(.x$xmax - .x$xmin) * (.x$ymax - .x$ymin)) %>% + # Extract which shapefile has the largest coverage area + which.max() + +# Get the bounding box +(bbox <- sf::st_bbox(shp_df[[x]])) ``` -Note that in some GIS packages the forecast cones may be identical (though they shouldn't be). I've noticed it with Hurricanes Ike and Matthew; it's in the raw dataset. +### Advisory Package -## Watches and Warnings +Each dataset returned by the `gis_advisory` function should contain four datasets. -You can also plot watches and warnings if any are in effect for the package release time. + + 5day_lin - A line plot of the forecast (previous track not included) + + + 5day_pgn - A polygon identifying the forecast cone or area the center of the storm could travel within a given period of time. + + + 5day_pts - A points dataframe identifying the current location and each forecast position. + + + ww_wwlin - Any existing watches and warnings. + +Let's go ahead and create a plot and then I'll explain in detail what I'm doing here. -```{r} -ww_line <- shp_to_df(df.gis_adv$al182012.018_ww_wwlin) +```{r plot-gis-advisory, fig.width = 7, fig.asp = 1, fig.align = "center", class.source = c("numberLines")} +p + + # Despite two forecast periods, the cones are identical for both. + geom_sf( + data = shp_df$`al142016-037_5day_lin`, + aes(geometry = geometry) + ) + + geom_point( + data = shp_df$`al142016-037_5day_pts`, + aes( + x = .data$LON, + y = .data$LAT, + fill = .data$DVLBL, + shape = .data$DVLBL, + size = .data$MAXWIND + ) + ) + + geom_sf( + data = shp_df$`al142016-037_ww_wwlin`, + aes( + geometry = .data$geometry, + color = factor(.data$TCWW) + ), + size = 2, + # key_glyph available as of ggplot 3.2.0 + key_glyph = draw_key_path + ) + + geom_sf( + data = shp_df$`al142016-037_5day_pgn`, + aes( + geometry = geometry, + ), + color = "antiquewhite3", + fill = "transparent" + ) + + scale_shape_manual(name = "Status", values = c(rep(21, 4))) + + scale_fill_discrete(name = "Status") + + scale_size_continuous(name = "Wind (kts)") + + scale_color_manual( + name = "Watches/Warnings", + limits = c("TWA", "TWR", "HWA", "HWR"), + values = c("orange", "blue", "pink", "red"), + labels = c( + "Tropical Storm Watch", + "Tropical Storm Warning", + "Hurricane Watch", + "Hurricane Warning" + ), + drop = FALSE + ) + + coord_sf( + # Give some more breathing room on the x axis + xlim = c(scales::expand_range(c(bbox$xmax, bbox$xmin), mul = 0.25)), + ylim = c( + bbox$ymin, + bbox$ymax + ), + expand = FALSE + ) + + guides( + color = guide_legend(nrow = 2, byrow = TRUE) + ) + + theme( + panel.ontop = TRUE, + panel.background = element_blank(), + panel.grid.major = element_line(color = "lightgray", size = 0.1), + legend.position = "bottom", + legend.box = "vertical" + ) + + labs(title = "Hurricane Matthew Advisory #37") ``` +#### Forecast Line -```{r, fig.width = 7, fig.align = "center"} -p3 + geom_path(data = ww_line, - aes(x = long, y = lat, group = group, color = TCWW), size = 1) +```{r shp-lin-str} +str(shp_df$`al142016-037_5day_lin`) ``` -In the example above you can see tropical storm warnings issued for the Bahamas, North Carolina and portions of the South Carolina and Florida coast while tropical storm watches are in effect for northern Florida and South Carolina. +Plotting the forecast line is nothing fancy though you could define different linestyles depending on the status of the storm (`STORMTYPE`) or the forecast period (`FCSTPRD`). Additional variables are pretty self-explanatory; `STORMNAME`, `ADVDATE`, `ADVISNUM`, `STORMNUM`, and `BASIN`. -## Probabilistic Storm Surge +```{r forecast-line, ref.label = "plot-gis-advisory", echo = c(3:6), eval = FALSE, attr.source = c(".numberLines", "startFrom='3'")} +``` -The Tropical Cyclone Storm Surge Probabilities data shows the probability, in percent, of a specified storm surge occurring during the forecast period indicated. The product is based upon an ensemble of Sea, Lake, and Overland Surge from Hurricanes (SLOSH) model runs using the National Hurricane Center (NHC) official advisory and accounts for track, size, and intensity errors based on historical errors. +#### Forecast Points -```{r} -gis_prob_storm_surge(key = "AL142016", products = list(psurge = 0), - datetime = "20161006") +```{r shp-pts-str} +str(shp_df$`al142016-037_5day_pts`) ``` -```{r, eval = FALSE} -df.gis_storm_surge <- gis_prob_storm_surge(key = "AL142016", - products = list(psurge = 0), - datetime = "20161006") %>% - last() %>% - gis_download() +The points shapefile contains the same variables as the line shapefile and more. I am unable to find official documentation so let me give my best here to explain some of the added variables. + + + `TAU` - This appears to be the time period in hours for each forecast point, gruoped by `FCSTPRD` + + + `MSLP` - Forecast minimum sea level pressure. "9999" values simply indicate no forecast MSLP was provided. + + + `TCDVLP` - The forecast status of the cyclone. + + + `DVLBL` - A shorter label for `TCDVLP` + + + `SSNUM` - Sorry, no idea... + + + `TCDIR` - Foreward direction of the storm + + + `TCSPD` - Foreward speed of the storm + +```{r forecast-points-geom, ref.label = "plot-gis-advisory", echo = c(7:16), eval = FALSE, attr.source = c(".numberLines", "startFrom='7'")} ``` -```{r} -prob_surge <- shp_to_df(df.gis_storm_surge$al142016_2016100618_gt0) -bb <- sp::bbox(df.gis_storm_surge$al142016_2016100618_gt0) +Since we have the added variables `LAT` and `LON`, and I wanted to customize the aesthetics a bit, I chose to use the layer `geom_point`. I set fill and shape to `DVLBL` and size to `MAXWIND`. I also wanted to customize the appearance of each point and, since I'll be using the color aesthetic for watches and warnings as well, I needed to customize these scales. + +```{r forecast-points-scale, ref.label = "plot-gis-advisory", echo = c(35:37), eval = FALSE, attr.source = c(".numberLines", "startFrom='35'")} ``` -```{r, fig.width = 7, fig.align = "center"} -p + geom_path(data = prob_surge, - aes(x = long, y = lat, group = group, color = PSurge00c), - size = 1, alpha = 0.5) + - coord_equal(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2])) +#### Watches and Warnings + +```{r wwlin-shp-str} +str(shp_df$`al142016-037_ww_wwlin`) ``` -## Current and Forecast Wind Field Radii +In the watches and warnings dataset we have the `TCWW` variable which identifies the watch/warning issued for each line. There are only four possible candidates here: + + + `TWA` - Tropical storm watch + + + `TWR` - Tropical storm warning + + + `HWA` - Hurricane watch + + + `HWR` - Hurricane warning -Wind radii data may also be available for some cyclone advisory packages. This is the radius to which a minimum sustained wind speed may be felt from the center of circulation. +I use the `geom_sf` layer and set the color aesthetic. I also increased the size of the lines to stand out a bit and, with the introduction of key glyphs in ggplot 3.2.0, changed the legend style. -```{r} -gis_windfield("AL142016", advisory = "33") +```{r wwlin-geom, ref.label = "plot-gis-advisory", echo = c(17:26), eval = FALSE, attr.source = c(".numberLines", "startFrom='17'")} ``` -```{r, eval = FALSE} -df.gis_wind_radii <- gis_windfield("AL142016", advisory = "33") %>% gis_download() +Since I'm already using color in the points layer, I needed to add an additional legend to identify the watches and warnings. I set the `drop` parameter to FALSE to ensure that all four keys show regardless of what is in the dataset. + +```{r wwlin-scale, ref.label = "plot-gis-advisory", echo = c(38:49), eval = FALSE, attr.source = c(".numberLines", "startFrom='38'")} ``` -```{r} -wf_init <- shp_to_df(df.gis_wind_radii$al142016_2016100606_initialradii) -bb <- sp::bbox(df.gis_wind_radii$al142016_2016100606_forecastradii) +Below, I break the legend into two rows. + +```{r wwlin-guide, ref.label = "plot-gis-advisory", echo = c(59:61), eval = FALSE, attr.source = c(".numberLines", "startFrom='59'")} ``` -```{r, fig.width = 7, fig.align = "center"} -(p4 <- p + geom_polygon(data = wf_init, - aes(x = long, y = lat, fill = factor(RADII)), alpha = 0.5) + - coord_equal(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2]))) +#### Forecast Cone + +The forecast cone is contained in the polygon dataset of the advisory package. Take a look at the structure. + +```{r pgn-shp-str} +str(shp_df$`al142016-037_5day_pgn`) ``` -Additionally, forecast wind radii data is also generally available in some packages +The geometry should be slightly different depending on the `FCSTPRD`. However, for this dataset, that is not the case. -```{r} -wf_fcst <- shp_to_df(df.gis_wind_radii$al142016_2016100606_forecastradii) +```{r pgn-identical} +identical( + shp_df$`al142016-037_5day_pgn`$geometry[1], + shp_df$`al142016-037_5day_pgn`$geometry[2] +) ``` -```{r, fig.width = 7, fig.align = "center"} -p4 + geom_polygon(data = wf_fcst, - aes(x = long, y = lat, group = group, fill = factor(RADII)), - alpha = 0.5) +I could have filled differently depending on different geometries; unfortunately it was just not possible. So I kept the `geom_sf` call simple. + +```{r pgn-plot, ref.label = "plot-gis-advisory", echo = c(27:34), eval = FALSE, attr.source = c(".numberLines", "startFrom='27'")} ``` -## Wind Speed Probabilities +### Forecast Wind Radii -Wind Speed probabilities show the chance of experiencing a minimum-sustained winds of 34, 50 and 64 knots with a given period of time (typically, 120 hours). These products are not storm-specific but are global so other active cyclones in other basins may also appear. +The forecast wind radii dataset should contain two datasets; one for the current wind radius and another for the forecast wind radii. -```{r} -gis_wsp(datetime = "2016100606", res = 0.5) +```{r wind-radii-str} +str(shp_df$al142016_2016100706_initialradii) +str(shp_df$al142016_2016100706_forecastradii) ``` -```{r, eval = FALSE} -df.gis_wsp <- - gis_download( - "https://www.nhc.noaa.gov/gis/forecast/archive/2016100606_wsp_120hrhalfDeg.zip" - ) -``` +The "initialradii" dataset will contain up to three observations for each radii: 34 knots, 50 knots, and 64 knots. This is the expected distance from the center of circulation that minimum n-force winds can be expected. -### Cumulative Probability for >34kt Winds +The "forecastradii" can have many observations. For forecast periods up to 36 hours, all wind radii may be provided if the storm is strong enough. At 48 and 72 hours, only 34 and 50 knot wind radii are provided. No forecast wind radii are provided beyond 72 hours. -```{r, fig.width = 7, fig.align = "center"} -bb <- sp::bbox(df.gis_wsp$`2016100606_wsp34knt120hr_halfDeg`) +```{r plot-forecast-wind-radii, fig.width = 7, fig.asp = 1, fig.align = "center", class.source = c("numberLines")} p + geom_sf( - data = st_as_sf(df.gis_wsp$`2016100606_wsp34knt120hr_halfDeg`), - aes(color = PWIND120) + data = shp_df$al142016_2016100706_forecastradii, + aes( + geometry = geometry, + fill = factor(RADII) + ), + alpha = 0.25 + ) + + geom_sf( + data = shp_df$`al142016-037_5day_lin`, + aes(geometry = geometry) + ) + + geom_point( + data = shp_df$`al142016-037_5day_pts`, + aes( + x = .data$LON, + y = .data$LAT + ) + ) + + coord_sf( + xlim = c(-85, -70), + ylim = c(24, 37), + expand = FALSE ) + - coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2])) + scale_fill_discrete( + name = "Forecast Wind Radii" + ) + + theme( + panel.ontop = TRUE, + panel.background = element_blank(), + panel.grid.major = element_line(color = "lightgray", size = 0.1), + legend.position = "bottom", + legend.box = "vertical" + ) + + labs(title = "Hurricane Matthew Forecast Wind Radii, Adv #37") +``` + +In the plot above I take the same approach as the advisory package but only keep the line track and points to keep the graph simple. To add the forecast wind radii, I again use the `geom_sf` layer providing the `fill` aesthetic based on `RADII`. Outside of the aesthetic, I set alpha to 0.25 to make underlying radii visible as well as land areas. + +```{r forecast-radii-geom, ref.label = "plot-forecast-wind-radii", echo = c(2:9), eval = FALSE, attr.source = c(".numberLines", "startFrom='2'")} ``` -Cumulative wind speed probability for >50kt winds: +The initialradii dataset was intentionally left out; as you can see it is included in the forecastradii package. + +### Wind Speed Probabilities + +As noted previously, wind speed probabilities can be provided in different resolutions. Recall that I went with the 0.5° resolution dataset. There are three packages in this dataset; proabilities of at least 34 knot winds, 50 knot winds, and 64 knot winds. -```{r, fig.width = 7, fig.align = "center"} -bb <- sp::bbox(df.gis_wsp$`2016100606_wsp50knt120hr_halfDeg`) +```{r wsp-prb-str} +str(shp_df$`2016100706_wsp34knt120hr_halfDeg`) +str(shp_df$`2016100706_wsp50knt120hr_halfDeg`) +str(shp_df$`2016100706_wsp64knt120hr_halfDeg`) +``` + +Each dataset contains the variable `PWIND120`; the probability of n-speed winds up to 120 hours. + +```{r plot-wind-speed-probabilities, fig.width = 7, fig.asp = 1, fig.align = "center"} p + geom_sf( - data = st_as_sf(df.gis_wsp$`2016100606_wsp50knt120hr_halfDeg`), - aes(color = PWIND120) + data = shp_df$`2016100706_wsp64knt120hr_halfDeg`, + aes( + geometry = geometry, + # A little math to add % to legend + color = PWIND120/100, + size = PWIND120, + alpha = PWIND120 + ), ) + - coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2])) + coord_sf( + xlim = c( + -85, + bbox$xmax + ), + ylim = c( + bbox$ymin, + 37.5 + ), + expand = FALSE + ) + + scale_color_continuous( + name = "", + breaks = c(0.25, 0.75), + labels = scales::percent, + low = "white", + high = "red" + ) + + scale_size_continuous(guide = "none") + + scale_alpha_continuous(guide = "none") + + theme( + panel.ontop = TRUE, + panel.background = element_blank(), + panel.grid.major = element_line(color = "lightgray", size = 0.1), + legend.position = "bottom", + legend.box = "vertical" + ) + + labs(title = "Wind Speed Probabilities (>34kts), Adv #37") +``` + +The plot above focuses only on the wind speed probabilities. The forecast track of the cyclone is quite clear. I made the size and alpha aesthetic based on `PWIND120` but removed those legends. I kept the color `aesthetic` which I divided by 100 to make a fraction (default is a real). With that, I applied `scales::percent` to the legend to show a percentage and changed the breaks. + +### Storm Surge Probabilities + +```{r prob-storm-surge-str} +str(shp_df$al142016_2016100706_gt5) ``` -Cumulative probability for >64kt winds: +Similar to the wind speed probabilities, storm surge probabilties only has three variables, the `POINTID`, `geometry`, and, because we requested the psurge product for 5-feet, `PSurge05c` (this name changes depending on the product and value). + +Note that unlike wind speed probabilities which is a point shapefile, this dataset is a polygon shapefile. -```{r, fig.width = 7, fig.align = "center"} -bb <- sp::bbox(df.gis_wsp$`2016100606_wsp64knt120hr_halfDeg`) +```{r psurge, fig.width = 7, fig.asp = 1, fig.align = "center"} p + geom_sf( - data = st_as_sf(df.gis_wsp$`2016100606_wsp64knt120hr_halfDeg`), - aes(color = PWIND120) + data = shp_df$al142016_2016100706_gt5, + aes( + geometry = geometry, + color = PSurge05c/100 + ), ) + - coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2])) + # Show Lake George, FL + geom_curve( + aes( + x = -82, + y = 28, + xend = -81.58, + yend = 29.2 + ), + curvature = -0.5, + arrow = arrow(length = unit(0.01, "npc")) + ) + + annotate( + "text", + x = -81.5, + y = 27.9, + label = "Lake George, FL", + size = 3 + ) + + coord_sf( + xlim = c( + -85, + -74 + ), + ylim = c( + 25, + 36 + ), + expand = FALSE + ) + + scale_color_continuous( + name = "", + breaks = c(0.25, 0.75), + labels = scales::percent, + low = "white", + high = "red" + ) + + theme( + panel.ontop = TRUE, + panel.background = element_blank(), + panel.grid.major = element_line(color = "lightgray", size = 0.1), + legend.position = "bottom", + legend.box = "vertical" + ) + + labs(title = "Hurricane Matthew Storm Surge Probabilities (>5ft), Adv #37") ``` + +I took similar steps to creating this plot as I did with wind speed probabilties. + +Note what appears to be storm surge well inland from the coast in Lake George, St. Johns River, and elsewhere. From 85a591058fe7209d124592edd6f2072aa401e017 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 09:03:54 -0500 Subject: [PATCH 08/41] Add drat repos --- .travis.yml | 1 + DESCRIPTION | 1 + appveyor.yml | 1 + 3 files changed, 3 insertions(+) diff --git a/.travis.yml b/.travis.yml index 8269c2ed..3e89cc19 100644 --- a/.travis.yml +++ b/.travis.yml @@ -15,6 +15,7 @@ addons: before_install: - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" + - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" matrix: include: diff --git a/DESCRIPTION b/DESCRIPTION index b7fffc41..bbc65cd2 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -45,6 +45,7 @@ Suggests: knitr, rmarkdown, rnaturalearthhires, + rrricanesdata, scales, sf, testthat diff --git a/appveyor.yml b/appveyor.yml index bdebdf45..2ccec3c5 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -34,6 +34,7 @@ matrix: build_script: - travis-tool.sh install_deps - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source');" + - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source');" test_script: - travis-tool.sh run_tests From 0eab18337a119518fa043655a0ede8502e14d1d4 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 09:34:32 -0500 Subject: [PATCH 09/41] Update pkgdown docs --- _pkgdown.yml | 13 +- docs/404.html | 156 ++ docs/CHANGELOG.html | 21 +- docs/CONTRIBUTING.html | 13 +- docs/ISSUE_TEMPLATE.html | 13 +- docs/LICENSE-text.html | 13 +- docs/PULL_REQUEST_TEMPLATE.html | 13 +- docs/articles/accumulated_cyclone_energy.html | 19 +- .../figure-html/unnamed-chunk-6-1.png | Bin 21775 -> 21841 bytes docs/articles/getting_started.html | 24 +- docs/articles/gis_data.html | 1969 +++++++++-------- .../figure-html/base-plot-1.png | Bin 0 -> 122441 bytes .../figure-html/base-plot-plus-scale-1.png | Bin 0 -> 129103 bytes .../plot-forecast-wind-radii-1.png | Bin 0 -> 259260 bytes .../figure-html/plot-gis-advisory-1.png | Bin 0 -> 150707 bytes .../plot-wind-speed-probabilities-1.png | Bin 0 -> 175893 bytes .../gis_data_files/figure-html/psurge-1.png | Bin 0 -> 164753 bytes .../figure-html/zoom-base-plot-1.png | Bin 0 -> 34049 bytes docs/articles/index.html | 18 +- docs/articles/installing_rrricanesdata.html | 32 +- docs/articles/wind_pressure.html | 74 +- .../figure-html/unnamed-chunk-4-1.png | Bin 68061 -> 68081 bytes .../figure-html/unnamed-chunk-5-1.png | Bin 70643 -> 70644 bytes .../figure-html/unnamed-chunk-6-1.png | Bin 65192 -> 65229 bytes .../figure-html/unnamed-chunk-7-1.gif | Bin 1099290 -> 1098607 bytes docs/authors.html | 13 +- docs/index.html | 13 +- docs/news/index.html | 13 +- docs/pkgdown.yml | 3 - 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115 files changed, 1471 insertions(+), 2126 deletions(-) create mode 100644 docs/404.html create mode 100644 docs/articles/gis_data_files/figure-html/base-plot-1.png create mode 100644 docs/articles/gis_data_files/figure-html/base-plot-plus-scale-1.png create mode 100644 docs/articles/gis_data_files/figure-html/plot-forecast-wind-radii-1.png create mode 100644 docs/articles/gis_data_files/figure-html/plot-gis-advisory-1.png create mode 100644 docs/articles/gis_data_files/figure-html/plot-wind-speed-probabilities-1.png create mode 100644 docs/articles/gis_data_files/figure-html/psurge-1.png create mode 100644 docs/articles/gis_data_files/figure-html/zoom-base-plot-1.png diff --git a/_pkgdown.yml b/_pkgdown.yml index 1da426d8..bed90dbd 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -1,5 +1,6 @@ url: https://ropensci.github.io/rrricanes/ - +toc: + depth: 3 reference: - title: About `rrricanes` contents: @@ -14,17 +15,10 @@ reference: contents: - twoal - twoep - - title: Tracking charts - desc: Helper functions to plot storm data through `ggplot2`. - contents: - - al_tracking_chart - - ep_tracking_chart - - tracking_chart - title: GIS Data desc: Gathering GIS data from the National Hurricane Center. contents: - starts_with("gis_") - - shp_to_df - title: Helpers desc: > Helper functions. Please note `al_prblty_stations` and @@ -58,9 +52,6 @@ articles: contents: - getting_started - installing_rrricanesdata - - forecast_advisory - wind_pressure - - wind_speed_probabilities - gis_data - - probabilistic_storm_surge - accumulated_cyclone_energy diff --git a/docs/404.html b/docs/404.html new file mode 100644 index 00000000..1b1c0106 --- /dev/null +++ b/docs/404.html @@ -0,0 +1,156 @@ + + + + + + + + +Page not found (404) • rrricanes + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Page not found (404)

+
+ +Content not found. Please use links in the navbar. + +
+ +
+ + +
+
+

Developed by Tim Trice.

+
+ +
+

Site built with pkgdown 1.3.0.9100.

+
+
+
+ + + + + + diff --git a/docs/CHANGELOG.html b/docs/CHANGELOG.html index 33ffba41..b1e96679 100644 --- a/docs/CHANGELOG.html +++ b/docs/CHANGELOG.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -161,7 +152,8 @@

    Changed

      -

    • gis_download and gis_latest can accept parameters for rgdal::readOGR (#104).

      • +

    • gis_latest can accept parameters for rgdal::readOGR (#104).

      • +

    • gis_download modified to download zip files and extract contents returning a vector of files within the zip.

    • ep_prblty_stations now returns all stations.

    • al_prblty_stations, cp_prblty_stations and ep_prblty_stations datasets were modified with additional columns. Changes are documented.

    @@ -170,7 +162,8 @@

    Removed

      -
    • NA
      • +

    • tracking_chart, al_tracking_chart, and ep_tracking_chart all removed in favor of using rnaturalearth and associated data packages, or other mapping packages.

      • +

    • shp_to_df removed; users can use sf::st_read

    @@ -600,7 +593,7 @@

  • dplyr.progress_bar for all products
  • rrricanes.working_msg option to show current working advisory.
  • -tracking_chart() for a base world plot. al_tracking_chart() for chart centered on Atlantic basin. ep_tracking_chart() for chart centered on northeast Pacific.
    • +tracking_chart() for a base world plot. al_tracking_chart() for chart centered on Atlantic basin. ep_tracking_chart() for chart centered on northeast Pacific.

  • load_storm_data() helps get datasets that have already been scraped and processed. Designed to make it more efficient to get data faster.
  • diff --git a/docs/CONTRIBUTING.html b/docs/CONTRIBUTING.html index 762754a2..9ad2aaeb 100644 --- a/docs/CONTRIBUTING.html +++ b/docs/CONTRIBUTING.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/ISSUE_TEMPLATE.html b/docs/ISSUE_TEMPLATE.html index cbaaa22d..81c1038d 100644 --- a/docs/ISSUE_TEMPLATE.html +++ b/docs/ISSUE_TEMPLATE.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 192d3535..9236f6a6 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/PULL_REQUEST_TEMPLATE.html b/docs/PULL_REQUEST_TEMPLATE.html index f4c78a36..ef227d05 100644 --- a/docs/PULL_REQUEST_TEMPLATE.html +++ b/docs/PULL_REQUEST_TEMPLATE.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/articles/accumulated_cyclone_energy.html b/docs/articles/accumulated_cyclone_energy.html index 85c64731..da93ead1 100644 --- a/docs/articles/accumulated_cyclone_energy.html +++ b/docs/articles/accumulated_cyclone_energy.html @@ -31,7 +31,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -56,27 +56,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -220,9 +211,9 @@

    June 27, 2017

    ## 9 1961 205. ## 10 1998 182.

    This also matches relatively well with that on Wikipedia and other sources.

    -
    ggplot(df, aes(x = Year, y = ACE)) + 
-    geom_bar(stat = "identity") + 
-    theme_bw()
    +
    ggplot(df, aes(x = Year, y = ACE)) + 
+    geom_bar(stat = "identity") + 
+    theme_bw()

    It would certainly seem that tropical cyclone activity ebbs and flows over time.

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  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -105,7 +96,7 @@

    Getting Started

    Tim Trice

    -

    2019-06-16

    +

    2019-06-22

    Source: vignettes/getting_started.Rmd @@ -396,7 +387,14 @@

  • General Introduction
  • Get Storms
  • Getting Storm Data
    • -
  • Forecast/Advisory Product (fstadv)
    • +
  • +Forecast/Advisory Product (fstadv) +
  • Strike Probabilities (prblty)
  • Wind Speed Probabilities (wndprb)
  • Other products
    • diff --git a/docs/articles/gis_data.html b/docs/articles/gis_data.html index 195da278..78ab10c2 100644 --- a/docs/articles/gis_data.html +++ b/docs/articles/gis_data.html @@ -5,11 +5,11 @@ -GIS data • rrricanes +Retrieving and Plotting GIS Data • rrricanes - + @@ -31,7 +31,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -56,27 +56,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -

  • @@ -102,10 +93,10 @@
    -

    GIS data

    +

    Retrieving and Plotting GIS Data

    Tim Trice

    -

    2019-06-16

    +

    2019-06-22

    Source: vignettes/gis_data.Rmd @@ -125,36 +116,43 @@

    2019-06-16

    Build a Tracking Chart

    -

    There are three functions available to help you plot GIS data; tracking_chart, al_tracking_chart and ep_tracking_chart. al_tracking_chart and ep_tracking_chart are just helpers centered on the Atlantic and northeast Pacific ocean, respectively.

    -
    args(rrricanes::tracking_chart)
    -
    ## function (countries = TRUE, states = TRUE, res = 110, ...) 
-## NULL
    -

    The countries and states parameters are TRUE by default. This means a basic call to tracking_chart will return a map with country and state borders. The res parameter is resolution; one of 110, 50 or 10 nautical miles. Resolutions 110nm and 50nm can be used immediately. To use lower resolution you must install the rnaturalearthdatahires package from ropensci:

    - -

    tracking_chart will print a basic tracking chart (a map of the planet).

    - -
    ## Regions defined for each Polygons
-## Regions defined for each Polygons
    -

    -

    You can pass typical aes parameters to refine the color and fill of the plot; remember the tracking chart is a ggplot object.

    -
    tracking_chart(color = "black", fill = "white", size = 0.1)
    -
    ## Regions defined for each Polygons
-## Regions defined for each Polygons
    -

    -

    You may choose to only show coastline data instead. In this case, just set the countries parameter to FALSE.

    -
    tracking_chart(countries = FALSE, res = 50, color = "black", fill = "white", 
-               size = 0.1)
    -

    -

    For the purposes of this vignette we’ll focus on Atlantic storms.

    -
    (p <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50))
    -
    ## Regions defined for each Polygons
-## Regions defined for each Polygons
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    The res parameter defines the resolution of the chart presented. Options are in 110nm, 50nm and 10nm. The lower the resolution the longer the chart takes to be built.

    -

    States cannot be drawn on resolution greater than 50nm.

    +

    As of version 0.2.7, the built-in tracking chart functions have been removed. Users are encouraged to use the rnaturalearthdata and associated packages to build tracking charts.

    +

    The rnaturalearthdata package has many shapefile datasets that can be used to make maps. For this article I will only need countries and states. I will use the resolution of 10 nautical miles (available in the rnaturalearthhires package). Each dataset is named countries10 and states10.

    + +

    +

    I’ll also remove the padding around the plot and change the color of the seas (panel.background).

    + +

    @@ -164,895 +162,1008 @@

  • gis_advisory
  • gis_prob_storm_surge
  • gis_windfield
    • -
  • gis_latest
    • +
  • +gis_latest (only for active storms)
    • -

    -
    -

    -Advisory Package

    -
    gis_advisory(key = "AL182012", advisory = "18")
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al182012_5day_018.zip"
    -
    df.gis_adv <- gis_advisory(key = "AL182012", advisory = "18") %>% gis_download()
    -
    names(df.gis_adv)
    -
    ## [1] "al182012.018_5day_lin" "al182012.018_5day_pgn" "al182012.018_5day_pts"
-## [4] "al182012.018_ww_wwlin"
    -

    For this particular storm and advisory, included are the base line, point and polygon datasets along with a dataset for watches and warnings. The objects returned are spatial dataframes contained within the list of dataframes, df.gis_adv.

    -
    +

    It’s important to note that not every storm will have a dataset available. Nor are datasets consistent from one storm to the next. For example, as we’ll see below, a forecast cone should have two polygons for a 72-hour and 120-hour forecast; in this example, they are both 120-hours.

    +

    Let’s take a look at Hurricane Matthew (AL142016) and focus on advisory 37.

    + +

    -Line track

    -
    str(df.gis_adv$al182012.018_5day_lin)
    -
    ## Formal class 'SpatialLinesDataFrame' [package "sp"] with 4 slots
-##   ..@ data       :'data.frame':  2 obs. of  7 variables:
-##   .. ..$ STORMNAME: chr [1:2] "SANDY" "SANDY"
-##   .. ..$ STORMTYPE: chr [1:2] "HU" "HU"
-##   .. ..$ ADVDATE  : chr [1:2] "121026/2100" "121026/2100"
-##   .. ..$ ADVISNUM : chr [1:2] "18" "18"
-##   .. ..$ STORMNUM : num [1:2] 18 18
-##   .. ..$ FCSTPRD  : num [1:2] 72 120
-##   .. ..$ BASIN    : chr [1:2] "al" "al"
-##   ..@ lines      :List of 2
-##   .. ..$ :Formal class 'Lines' [package "sp"] with 2 slots
-##   .. .. .. ..@ Lines:List of 1
-##   .. .. .. .. ..$ :Formal class 'Line' [package "sp"] with 1 slot
-##   .. .. .. .. .. .. ..@ coords: num [1:6, 1:2] -77.1 -77 -76.1 -74.3 -72.6 ...
-##   .. .. .. ..@ ID   : chr "0"
-##   .. ..$ :Formal class 'Lines' [package "sp"] with 2 slots
-##   .. .. .. ..@ Lines:List of 1
-##   .. .. .. .. ..$ :Formal class 'Line' [package "sp"] with 1 slot
-##   .. .. .. .. .. .. ..@ coords: num [1:8, 1:2] -77.1 -77 -76.1 -74.3 -72.6 ...
-##   .. .. .. ..@ ID   : chr "1"
-##   ..@ bbox       : num [1:2, 1:2] -77.1 27.3 -71.5 41
-##   .. ..- attr(*, "dimnames")=List of 2
-##   .. .. ..$ : chr [1:2] "x" "y"
-##   .. .. ..$ : chr [1:2] "min" "max"
-##   ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
-##   .. .. ..@ projargs: chr "+proj=longlat +a=6371200 +b=6371200 +no_defs"
    -

    As we’re dealing with a SpatialLinesDataFrame which needs to be modified, you can use the helper function shp_to_df for plotting.

    -
    fcst_line <- shp_to_df(df.gis_adv$al182012.018_5day_lin)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    p + geom_path(data = fcst_line, aes(long, lat, group = FCSTPRD))
    -

    -

    There are two groups of data in the set: one for 72-hour forecast period and one for 120-hour. Grouping by FCSTPRD will show the forecast track correctly.

    -

    There is a pretty wide field of view on the map above. You can use sp::bbox to “zoom in” on the map.

    -
    (bb <- sp::bbox(df.gis_adv$al182012.018_5day_lin))
    -
    ##     min   max
-## x -77.1 -71.5
-## y  27.3  41.0
    -
    (p2 <- p + geom_path(data = fcst_line, aes(long, lat, group = FCSTPRD)) + 
-    coord_equal(xlim = c(bb[1,1] - 5, bb[1,2] + 5), 
-                ylim = c(bb[2,1] - 5, bb[2,2] + 5)))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    +Data Scraping +

    The functions listed above do not retrieve the data. They only return the URLs. This is to give you the opportunity to modify your requests to get the specific data needed, if it exists.

    +
    +

    +gis_advisory +

    +

    The gis_advisory function returns the URL for the GIS dataset by key and advisory number. Remember, a storm’s key should always be eight alphanumeric characters;

    +
      +

    • Basin identifier (“AL”, “CP”, or “EP”)

      • +

    • Storm number for the year

      • +

    • The four digit year

      • +
    +

    The fstadv product will always have the storm key. In earlier years, the “year” portion of the key was only the year without the century; you will need to add it.

    +
    args(gis_advisory)
    +
    ## function (key, advisory = as.character()) 
+## NULL
    +

    We can test that an advisory package does exist for our specific advisory.

    +
    gis_advisory(key = key, advisory = adv)
    +
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al142016_5day_037.zip"
    +

    This should work.

    +
    +
    +

    +gis_windfield +

    +

    The gis_windfield product is relatively new so it may not exist for some storms. As with gis_advisory, we only need the storms’ key and advisory.

    +
    args(gis_windfield)
    +
    ## function (key, advisory = as.character()) 
+## NULL
    +
    gis_windfield(key = key, advisory = adv)
    +
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al142016_fcst_037.zip"
    +
    +
    +

    +gis_prob_storm_surge +

    +

    The function gis_prob_storm_surge also uses the key variable, but not the advisory; instead, it uses datetime.

    +

    There are two types of products that can be retrieved, “esurge” and “psurge”. psurge shows the probability of a specific height (in feet) of storm surge affecting an area. Values between 0 and 20 can be used.

    + +

    In the example above, we are requesting the probabilities of a 5-foot storm surge affecting the coastline and inland waterways.

    +

    esurge shows the probability of a specific storm surge height exceeding the forecast height. Valid values are 10, 20, 30, 04, and 50. Note the commented section in the code above.

    +

    The products parameter expects a list, though you do not need to include both products. Additionally, each product expects a numeric or numeric vector. If you make a broad general request, the National Hurricane Center requests no more than 80 requests per 10 seconds, so please be respectful. Unlike retrieving text products, there is no throttle in this package to download GIS datasets.

    +

    Regarding datetime, this value should be that of the advisory time minus 3 hours not including minutes and seconds. Let’s get that value for Matthew’s #37 advisory.

    +
    datetime <- 
+  get_storms(years = "2016", basins = "AL") %>% 
+  filter(Name == "Hurricane Matthew") %>% 
+  pull(Link) %>% 
+  get_fstadv() %>% 
+  filter(Adv == adv) %>% 
+  pull(Date)
    +
    ## Registered S3 method overwritten by 'httr':
+##   method                 from
+##   as.character.form_file crul
    + +
    ## [1] "2016100706"
    +

    Let’s make sure we can get a psurge 5 product for this datetime value.

    +
    gis_prob_storm_surge(key = key, products = list(psurge = 5), datetime = datetime)
    +
    ## [1] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge5_2016100706.zip"
    +

    Looks good.

    +
    +
    +gis_wsp +
    +

    Wind speed probabilities exist in the gis_wsp datasets. Like gis_prob_storm_surge, we will need datetime, but we will not need key. The last parameter is res (resolution). Valid values are 5, 0.5, and 0.1 degrees. The default is all three. Not all resolutions will be available for all storms.

    +
    args(gis_wsp)
    +
    ## function (datetime, res = c(5, 0.5, 0.1)) 
+## NULL
    +
    # List of datasets for 5-degree resolution
+gis_wsp(datetime = datetime, res = 0.5)
    +
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/2016100706_wsp_120hrhalfDeg.zip"
    +
    +
    +
    +

    +Downloading Data

    +

    Now that we’ve explored the various functions, let’s go about downloading the datasets to plot. For efficiency, I use a lot of purrr mapping functions here, loading each step into one variable.

    +

    First, I want to load all of my URLs into one vector.

    + +

    Previously, gis_download would download the datasets, extract the shapefiles and convert them, if possible, into dataframes. Thankfully, this is no longer necessary with various improvements in the sp and ggplot2 packages. Now, the gis_download function will only download the zip files into a specified directory. For this vignette, we’ll use a temporary directory, tempdir.

    + +
    ##  [1] "al142016-037_5day_lin.dbf"                
+##  [2] "al142016-037_5day_pgn.dbf"                
+##  [3] "al142016-037_5day_pts.dbf"                
+##  [4] "al142016-037_ww_wwlin.dbf"                
+##  [5] "al142016-037_5day_lin.prj"                
+##  [6] "al142016-037_5day_pgn.prj"                
+##  [7] "al142016-037_5day_pts.prj"                
+##  [8] "al142016-037_ww_wwlin.prj"                
+##  [9] "al142016-037_5day_lin.shp"                
+## [10] "al142016-037_5day_pgn.shp"                
+## [11] "al142016-037_5day_pts.shp"                
+## [12] "al142016-037_ww_wwlin.shp"                
+## [13] "al142016-037_5day_lin.shx"                
+## [14] "al142016-037_5day_pgn.shx"                
+## [15] "al142016-037_5day_pts.shx"                
+## [16] "al142016-037_ww_wwlin.shx"                
+## [17] "al142016-037_5day_lin.shp.xml"            
+## [18] "al142016-037_5day_pgn.shp.xml"            
+## [19] "al142016-037_5day_pts.shp.xml"            
+## [20] "al142016-037_ww_wwlin.shp.xml"            
+## [21] "al142016_2016100706_forecastradii.dbf"    
+## [22] "al142016_2016100706_forecastradii.prj"    
+## [23] "al142016_2016100706_forecastradii.shp"    
+## [24] "al142016_2016100706_forecastradii.shp.xml"
+## [25] "al142016_2016100706_forecastradii.shx"    
+## [26] "al142016_2016100706_initialradii.dbf"     
+## [27] "al142016_2016100706_initialradii.prj"     
+## [28] "al142016_2016100706_initialradii.shp"     
+## [29] "al142016_2016100706_initialradii.shp.xml" 
+## [30] "al142016_2016100706_initialradii.shx"     
+## [31] "al142016_2016100706_gt5.dbf"              
+## [32] "al142016_2016100706_gt5.prj"              
+## [33] "al142016_2016100706_gt5.shx"              
+## [34] "al142016_2016100706_gt5.txt"              
+## [35] "al142016_2016100706_gt5.ave"              
+## [36] "al142016_2016100706_gt5.shp.xml"          
+## [37] "al142016_2016100706_gt5.shp"              
+## [38] "2016100706_wsp34knt120hr_halfDeg.dbf"     
+## [39] "2016100706_wsp34knt120hr_halfDeg.prj"     
+## [40] "2016100706_wsp34knt120hr_halfDeg.shp"     
+## [41] "2016100706_wsp34knt120hr_halfDeg.shp.xml" 
+## [42] "2016100706_wsp34knt120hr_halfDeg.shx"     
+## [43] "2016100706_wsp34knt120hr_halfDeg.txt"     
+## [44] "2016100706_wsp50knt120hr_halfDeg.dbf"     
+## [45] "2016100706_wsp50knt120hr_halfDeg.prj"     
+## [46] "2016100706_wsp50knt120hr_halfDeg.shp"     
+## [47] "2016100706_wsp50knt120hr_halfDeg.shp.xml" 
+## [48] "2016100706_wsp50knt120hr_halfDeg.shx"     
+## [49] "2016100706_wsp50knt120hr_halfDeg.txt"     
+## [50] "2016100706_wsp64knt120hr_halfDeg.dbf"     
+## [51] "2016100706_wsp64knt120hr_halfDeg.prj"     
+## [52] "2016100706_wsp64knt120hr_halfDeg.shp"     
+## [53] "2016100706_wsp64knt120hr_halfDeg.shp.xml" 
+## [54] "2016100706_wsp64knt120hr_halfDeg.shx"     
+## [55] "2016100706_wsp64knt120hr_halfDeg.txt"
    +

    There are a lot of files here. Thankfully, we only care about the shapefiles (marked by the “.shp” extension). Let’s filter those.

    +
    # Filter out shapefiles
+shp_files <- grep(".shp$", file_list, value = TRUE)
+shp_files
    +
    ##  [1] "al142016-037_5day_lin.shp"            
+##  [2] "al142016-037_5day_pgn.shp"            
+##  [3] "al142016-037_5day_pts.shp"            
+##  [4] "al142016-037_ww_wwlin.shp"            
+##  [5] "al142016_2016100706_forecastradii.shp"
+##  [6] "al142016_2016100706_initialradii.shp" 
+##  [7] "al142016_2016100706_gt5.shp"          
+##  [8] "2016100706_wsp34knt120hr_halfDeg.shp" 
+##  [9] "2016100706_wsp50knt120hr_halfDeg.shp" 
+## [10] "2016100706_wsp64knt120hr_halfDeg.shp"
    +

    We can use sf::st_read to read in each shapefile as a shapefile dataframe. The output is quite verbose; you can pass the parameter quiet as TRUE.

    + +
    ## Reading layer `al142016-037_5day_lin' from data source `/tmp/RtmplcF52d/al142016-037_5day_lin.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 2 features and 7 fields
+## geometry type:  LINESTRING
+## dimension:      XY
+## bbox:           xmin: -80.6 ymin: 27 xmax: -74.5 ymax: 33.1
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016-037_5day_pgn' from data source `/tmp/RtmplcF52d/al142016-037_5day_pgn.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 2 features and 7 fields
+## geometry type:  POLYGON
+## dimension:      XY
+## bbox:           xmin: -81.4783 ymin: 23.15623 xmax: -71.83253 ymax: 34.47927
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016-037_5day_pts' from data source `/tmp/RtmplcF52d/al142016-037_5day_pts.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 14 features and 23 fields
+## geometry type:  POINT
+## dimension:      XY
+## bbox:           xmin: -80.6 ymin: 27 xmax: -74.5 ymax: 33.1
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016-037_ww_wwlin' from data source `/tmp/RtmplcF52d/al142016-037_ww_wwlin.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 10 features and 8 fields
+## geometry type:  LINESTRING
+## dimension:      XY
+## bbox:           xmin: -83.17 ymin: 23.75 xmax: -76.13 ymax: 34.44
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016_2016100706_forecastradii' from data source `/tmp/RtmplcF52d/al142016_2016100706_forecastradii.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 16 features and 11 fields
+## geometry type:  POLYGON
+## dimension:      XY
+## bbox:           xmin: -82.89683 ymin: 25.85747 xmax: -71.57337 ymax: 35.94275
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016_2016100706_initialradii' from data source `/tmp/RtmplcF52d/al142016_2016100706_initialradii.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 3 features and 11 fields
+## geometry type:  POLYGON
+## dimension:      XY
+## bbox:           xmin: -82.01794 ymin: 26.16483 xmax: -77.13445 ymax: 30.62306
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `al142016_2016100706_gt5' from data source `/tmp/RtmplcF52d/al142016_2016100706_gt5.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 99 features and 2 fields
+## geometry type:  MULTIPOLYGON
+## dimension:      XY
+## bbox:           xmin: -82.75004 ymin: 27.54227 xmax: -76.7436 ymax: 35.57721
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
+## Reading layer `2016100706_wsp34knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp34knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 4367 features and 2 fields
+## geometry type:  POINT
+## dimension:      XY
+## bbox:           xmin: -87 ymin: 6 xmax: 128.5 ymax: 43.5
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
+## Reading layer `2016100706_wsp50knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp50knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 2302 features and 2 fields
+## geometry type:  POINT
+## dimension:      XY
+## bbox:           xmin: -86 ymin: 8 xmax: 127 ymax: 42
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
+## Reading layer `2016100706_wsp64knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp64knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
+## Simple feature collection with 1367 features and 2 fields
+## geometry type:  POINT
+## dimension:      XY
+## bbox:           xmin: -83 ymin: 12 xmax: 126.5 ymax: 39
+## epsg (SRID):    NA
+## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
    +

    And, while not necessary, I will rename the list of dataframes, shp_df, to the names of their respective shapefiles minus the file extension.

    + +
    ##  [1] "al142016-037_5day_lin"            
+##  [2] "al142016-037_5day_pgn"            
+##  [3] "al142016-037_5day_pts"            
+##  [4] "al142016-037_ww_wwlin"            
+##  [5] "al142016_2016100706_forecastradii"
+##  [6] "al142016_2016100706_initialradii" 
+##  [7] "al142016_2016100706_gt5"          
+##  [8] "2016100706_wsp34knt120hr_halfDeg" 
+##  [9] "2016100706_wsp50knt120hr_halfDeg" 
+## [10] "2016100706_wsp64knt120hr_halfDeg"
    +

    This next stop is also not necessary. I actually found it a bit broad and rarely used it but will leave it here as an example.

    +

    Each shapefile has a bounding box; this box is a zoomed-in coordinate map of each dataset. We can access the bounding box of each dataset with the sf::st_bbox function.

    +

    For example, in our advisory package we have the forecast cones (a polygon shapefile). Let’s see what the bounding box is for that dataset.

    +
    sf::st_bbox(shp_df$`al142016-037_5day_pgn`)
    +
    ##      xmin      ymin      xmax      ymax 
+## -81.47830  23.15623 -71.83253  34.47927
    +

    Our data is contained between approximately 71°W and 81°W (note the negatives – the western hemisphere), and between 23°N and 34°N. Let’s see where that is.

    +
    p + 
+  coord_sf(
+    xlim = c(
+      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmin, 
+      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmax
+    ), 
+    ylim = c(
+      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymin, 
+      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymax
+    )
+  )
    +

    +

    Nice!

    +

    I want to find the largest bounding box within the datasets for my map. For this, I calculate the area for each box of each dataset, identify which has the largest area then extract the bounding box for that dataset.

    +

    Notice I only search the advisory package datasets for a bounding box. The probability datasets may contain data for other cyclones across the world making our bounding box (and subsequent maps) quite wide. I have no interest in that so kept the focus only on Matthew.

    + +
    ##      xmin      ymin      xmax      ymax 
+## -81.47830  23.15623 -71.83253  34.47927
    -
    +
    +

    -Point track

    -

    Each forecast position is also included in the points dataframe. You can access this in the df.gis_adv$al182012.018_5day_pts@data object; no conversion necessary.

    -
    (p3 <- p2 + geom_point(data = df.gis_adv$al182012.018_5day_pts@data, aes(LON, LAT)))
    -

    +Advisory Package +

    Each dataset returned by the gis_advisory function should contain four datasets.

    +
      +

    • 5day_lin - A line plot of the forecast (previous track not included)

      • +

    • 5day_pgn - A polygon identifying the forecast cone or area the center of the storm could travel within a given period of time.

      • +

    • 5day_pts - A points dataframe identifying the current location and each forecast position.

      • +

    • ww_wwlin - Any existing watches and warnings.

      • +
    +

    Let’s go ahead and create a plot and then I’ll explain in detail what I’m doing here.

    +
    p + 
+  # Despite two forecast periods, the cones are identical for both.
+  geom_sf(
+    data = shp_df$`al142016-037_5day_lin`,
+    aes(geometry = geometry)
+  ) +
+  geom_point(
+    data = shp_df$`al142016-037_5day_pts`,
+    aes(
+      x = .data$LON,
+      y = .data$LAT,
+      fill = .data$DVLBL,
+      shape = .data$DVLBL,
+      size = .data$MAXWIND
+    )
+  ) +
+  geom_sf(
+    data = shp_df$`al142016-037_ww_wwlin`,
+    aes(
+      geometry = .data$geometry,
+      color = factor(.data$TCWW)
+    ),
+    size = 2,
+    # key_glyph available as of ggplot 3.2.0
+    key_glyph = draw_key_path
+  ) +
+  geom_sf(
+    data = shp_df$`al142016-037_5day_pgn`, 
+    aes(
+      geometry = geometry,
+    ), 
+    color = "antiquewhite3", 
+    fill = "transparent"
+  ) +
+  scale_shape_manual(name = "Status", values = c(rep(21, 4))) +
+  scale_fill_discrete(name = "Status") +
+  scale_size_continuous(name = "Wind (kts)") +
+  scale_color_manual(
+    name = "Watches/Warnings",
+    limits = c("TWA", "TWR", "HWA", "HWR"),
+    values = c("orange", "blue", "pink", "red"),
+    labels = c(
+      "Tropical Storm Watch",
+      "Tropical Storm Warning",
+      "Hurricane Watch",
+      "Hurricane Warning"
+    ),
+    drop = FALSE
+  ) +
+  coord_sf(
+    # Give some more breathing room on the x axis
+    xlim = c(scales::expand_range(c(bbox$xmax, bbox$xmin), mul = 0.25)), 
+    ylim = c(
+      bbox$ymin, 
+      bbox$ymax
+    ), 
+    expand = FALSE
+  ) + 
+  guides(
+    color = guide_legend(nrow = 2, byrow = TRUE)
+  ) + 
+  theme(
+    panel.ontop = TRUE,
+    panel.background = element_blank(), 
+    panel.grid.major = element_line(color = "lightgray", size = 0.1),
+    legend.position = "bottom", 
+    legend.box = "vertical"
+  ) +
+  labs(title = "Hurricane Matthew Advisory #37")
    +
    ## Warning: Ignoring unknown parameters: key_glyph
    +

    +
    +

    +Forecast Line

    +
    str(shp_df$`al142016-037_5day_lin`)
    +
    ## Classes 'sf' and 'data.frame':   2 obs. of  8 variables:
+##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1
+##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1
+##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1
+##  $ ADVISNUM : Factor w/ 1 level "37": 1 1
+##  $ STORMNUM : num  14 14
+##  $ FCSTPRD  : num  72 120
+##  $ BASIN    : Factor w/ 1 level "al": 1 1
+##  $ geometry :sfc_LINESTRING of length 2; first list element:  'XY' num [1:6, 1:2] -80 -80.6 -80.5 -79.2 -77.7 ...
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA
+##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    +

    Plotting the forecast line is nothing fancy though you could define different linestyles depending on the status of the storm (STORMTYPE) or the forecast period (FCSTPRD). Additional variables are pretty self-explanatory; STORMNAME, ADVDATE, ADVISNUM, STORMNUM, and BASIN.

    +
    +
    +

    +Forecast Points

    +
    str(shp_df$`al142016-037_5day_pts`)
    +
    ## Classes 'sf' and 'data.frame':   14 obs. of  24 variables:
+##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ ADVISNUM : Factor w/ 1 level "37": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14 ...
+##  $ FCSTPRD  : num  72 72 72 72 72 72 120 120 120 120 ...
+##  $ BASIN    : Factor w/ 1 level "al": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ LAT      : num  28.2 29.6 31.5 32.6 33.1 31.5 28.2 29.6 31.5 32.6 ...
+##  $ LON      : num  -80 -80.6 -80.5 -79.2 -77.7 -74.5 -80 -80.6 -80.5 -79.2 ...
+##  $ VALIDTIME: Factor w/ 8 levels "07/0900","07/1800",..: 1 2 3 4 5 6 1 2 3 4 ...
+##  $ TAU      : num  3 12 24 36 48 72 3 12 24 36 ...
+##  $ MAXWIND  : num  105 100 90 80 65 50 105 100 90 80 ...
+##  $ GUST     : num  130 120 110 100 80 60 130 120 110 100 ...
+##  $ MSLP     : num  938 9999 9999 9999 9999 ...
+##  $ TCDVLP   : Factor w/ 3 levels "Hurricane","Major Hurricane",..: 2 2 1 1 1 3 2 2 1 1 ...
+##  $ DVLBL    : Factor w/ 3 levels "H","M","S": 2 2 1 1 1 3 2 2 1 1 ...
+##  $ SSNUM    : num  3 3 2 1 1 0 3 3 2 1 ...
+##  $ TCDIR    : num  330 9999 9999 9999 9999 ...
+##  $ TCSPD    : num  11 9999 9999 9999 9999 ...
+##  $ DATELBL  : Factor w/ 8 levels "2:00 AM Mon",..: 8 6 2 7 3 1 8 6 2 7 ...
+##  $ FLDATELBL: Factor w/ 8 levels "2016-10-07 2:00 PM Fri EDT",..: 2 1 3 4 5 6 2 1 3 4 ...
+##  $ TIMEZONE : Factor w/ 1 level "EDT": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ STORMSRC : Factor w/ 1 level "Tropical Cyclone": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ geometry :sfc_POINT of length 14; first list element:  'XY' num  -80 28.2
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
+##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    +

    The points shapefile contains the same variables as the line shapefile and more. I am unable to find official documentation so let me give my best here to explain some of the added variables.

    +
      +

    • TAU - This appears to be the time period in hours for each forecast point, gruoped by FCSTPRD

      • +

    • MSLP - Forecast minimum sea level pressure. “9999” values simply indicate no forecast MSLP was provided.

      • +

    • TCDVLP - The forecast status of the cyclone.

      • +

    • DVLBL - A shorter label for TCDVLP

      • +

    • SSNUM - Sorry, no idea…

      • +

    • TCDIR - Foreward direction of the storm

      • +

    • TCSPD - Foreward speed of the storm

      • +
    + +

    Since we have the added variables LAT and LON, and I wanted to customize the aesthetics a bit, I chose to use the layer geom_point. I set fill and shape to DVLBL and size to MAXWIND. I also wanted to customize the appearance of each point and, since I’ll be using the color aesthetic for watches and warnings as well, I needed to customize these scales.

    +
      scale_shape_manual(name = "Status", values = c(rep(21, 4))) +
+  scale_fill_discrete(name = "Status") +
+  scale_size_continuous(name = "Wind (kts)") +
    -
    -

    -Forecast Cone

    -

    Forecast cone data is contained in the polygon dataset. To deal with this dataset you can use the shp_to_df function again or take the slightly longer way:

    - -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    fcst_cone <- dplyr::left_join(fcst_cone.points, fcst_cone@data, by = "id")
    -
    p3 + geom_polygon(data = fcst_cone %>% filter(FCSTPRD == 120), 
-                 aes(long, lat, group = group, fill = factor(FCSTPRD)), 
-                 alpha = 0.5) + 
-    geom_polygon(data = fcst_cone %>% filter(FCSTPRD == 72), 
-                 aes(long, lat, group = group, fill = factor(FCSTPRD)), 
-                 alpha = 0.5)
    -

    -

    Note that in some GIS packages the forecast cones may be identical (though they shouldn’t be). I’ve noticed it with Hurricanes Ike and Matthew; it’s in the raw dataset.

    +
    +

    +Watches and Warnings

    +
    str(shp_df$`al142016-037_ww_wwlin`)
    +
    ## Classes 'sf' and 'data.frame':   10 obs. of  9 variables:
+##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1 1 1 1 1 1 1 1 1
+##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1 1 1 1 1 1 1 1 1
+##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1 1 1 1 1 1 1 1 1
+##  $ ADVISNUM : Factor w/ 1 level "37": 1 1 1 1 1 1 1 1 1 1
+##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14
+##  $ FCSTPRD  : num  120 120 120 120 120 120 120 120 120 120
+##  $ BASIN    : Factor w/ 1 level "al": 1 1 1 1 1 1 1 1 1 1
+##  $ TCWW     : Factor w/ 3 levels "HWR","TWA","TWR": 1 1 1 1 1 1 3 3 3 2
+##  $ geometry :sfc_LINESTRING of length 10; first list element:  'XY' num [1:5, 1:2] -77.6 -77.7 -78.2 -78.4 -77.6 ...
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA
+##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    +

    In the watches and warnings dataset we have the TCWW variable which identifies the watch/warning issued for each line. There are only four possible candidates here:

    +
      +

    • TWA - Tropical storm watch

      • +

    • TWR - Tropical storm warning

      • +

    • HWA - Hurricane watch

      • +

    • HWR - Hurricane warning

      • +
    +

    I use the geom_sf layer and set the color aesthetic. I also increased the size of the lines to stand out a bit and, with the introduction of key glyphs in ggplot 3.2.0, changed the legend style.

    + +

    Since I’m already using color in the points layer, I needed to add an additional legend to identify the watches and warnings. I set the drop parameter to FALSE to ensure that all four keys show regardless of what is in the dataset.

    + +

    Below, I break the legend into two rows.

    +
      guides(
+    color = guide_legend(nrow = 2, byrow = TRUE)
+  ) +
    -
    -

    -Watches and Warnings

    -

    You can also plot watches and warnings if any are in effect for the package release time.

    -
    ww_line <- shp_to_df(df.gis_adv$al182012.018_ww_wwlin)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    p3 + geom_path(data = ww_line, 
-               aes(x = long, y = lat, group = group, color = TCWW), size = 1)
    -

    -

    In the example above you can see tropical storm warnings issued for the Bahamas, North Carolina and portions of the South Carolina and Florida coast while tropical storm watches are in effect for northern Florida and South Carolina.

    +
    +

    +Forecast Cone

    +

    The forecast cone is contained in the polygon dataset of the advisory package. Take a look at the structure.

    +
    str(shp_df$`al142016-037_5day_pgn`)
    +
    ## Classes 'sf' and 'data.frame':   2 obs. of  8 variables:
+##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1
+##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1
+##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1
+##  $ ADVISNUM : Factor w/ 1 level "37": 1 1
+##  $ STORMNUM : num  14 14
+##  $ FCSTPRD  : num  72 120
+##  $ BASIN    : Factor w/ 1 level "al": 1 1
+##  $ geometry :sfc_POLYGON of length 2; first list element: List of 1
+##   ..$ : num [1:274, 1:2] -79.9 -80.2 -80.4 -80.6 -80.7 ...
+##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA
+##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    +

    The geometry should be slightly different depending on the FCSTPRD. However, for this dataset, that is not the case.

    + +
    ## [1] TRUE
    +

    I could have filled differently depending on different geometries; unfortunately it was just not possible. So I kept the geom_sf call simple.

    +
    -
    -

    -Probabilistic Storm Surge

    -

    The Tropical Cyclone Storm Surge Probabilities data shows the probability, in percent, of a specified storm surge occurring during the forecast period indicated. The product is based upon an ensemble of Sea, Lake, and Overland Surge from Hurricanes (SLOSH) model runs using the National Hurricane Center (NHC) official advisory and accounts for track, size, and intensity errors based on historical errors.

    -
    gis_prob_storm_surge(key = "AL142016", products = list(psurge = 0), 
-                     datetime = "20161006")
    -
    ## [1] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge0_2016100600.zip"
-## [2] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge0_2016100606.zip"
-## [3] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge0_2016100612.zip"
-## [4] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge0_2016100618.zip"
    - -
    prob_surge <- shp_to_df(df.gis_storm_surge$al142016_2016100618_gt0)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    bb <- sp::bbox(df.gis_storm_surge$al142016_2016100618_gt0)
    -
    p + geom_path(data = prob_surge, 
-               aes(x = long, y = lat, group = group, color = PSurge00c), 
-              size = 1, alpha = 0.5) + 
-    coord_equal(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2]))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -
    -

    -Current and Forecast Wind Field Radii

    -

    Wind radii data may also be available for some cyclone advisory packages. This is the radius to which a minimum sustained wind speed may be felt from the center of circulation.

    -
    gis_windfield("AL142016", advisory = "33")
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al142016_fcst_033.zip"
    -
    df.gis_wind_radii <- gis_windfield("AL142016", advisory = "33") %>% gis_download()
    -
    wf_init <- shp_to_df(df.gis_wind_radii$al142016_2016100606_initialradii)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    bb <- sp::bbox(df.gis_wind_radii$al142016_2016100606_forecastradii)
    -
    (p4 <- p + geom_polygon(data = wf_init, 
-                  aes(x = long, y = lat, fill = factor(RADII)), alpha = 0.5) + 
-    coord_equal(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2])))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    Additionally, forecast wind radii data is also generally available in some packages

    -
    wf_fcst <- shp_to_df(df.gis_wind_radii$al142016_2016100606_forecastradii)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    p4 + geom_polygon(data = wf_fcst, 
-                  aes(x = long, y = lat, group = group, fill = factor(RADII)), 
-                  alpha = 0.5)
    -

    +
    +

    +Forecast Wind Radii

    +

    The forecast wind radii dataset should contain two datasets; one for the current wind radius and another for the forecast wind radii.

    +
    str(shp_df$al142016_2016100706_initialradii)
    +
    ## Classes 'sf' and 'data.frame':   3 obs. of  12 variables:
+##  $ RADII    : num  34 50 64
+##  $ STORMID  : Factor w/ 1 level "al142016": 1 1 1
+##  $ BASIN    : Factor w/ 1 level "AL": 1 1 1
+##  $ STORMNUM : num  14 14 14
+##  $ VALIDTIME: Factor w/ 1 level "2016100709": 1 1 1
+##  $ SYNOPTIME: Factor w/ 1 level "2016100706": 1 1 1
+##  $ TAU      : num  3 3 3
+##  $ NE       : num  160 70 50
+##  $ SE       : num  140 70 40
+##  $ SW       : num  80 50 30
+##  $ NW       : num  120 70 50
+##  $ geometry :sfc_POLYGON of length 3; first list element: List of 1
+##   ..$ : num [1:364, 1:2] -77.8 -77.8 -77.8 -77.7 -77.7 ...
+##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
+##   ..- attr(*, "names")= chr  "RADII" "STORMID" "BASIN" "STORMNUM" ...
    +
    str(shp_df$al142016_2016100706_forecastradii)
    +
    ## Classes 'sf' and 'data.frame':   16 obs. of  12 variables:
+##  $ RADII    : num  34 34 34 34 34 34 50 50 50 50 ...
+##  $ STORMID  : Factor w/ 1 level "al142016": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ BASIN    : Factor w/ 1 level "AL": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14 ...
+##  $ VALIDTIME: Factor w/ 6 levels "2016100709","2016100718",..: 1 2 3 4 5 6 1 2 3 4 ...
+##  $ SYNOPTIME: Factor w/ 1 level "2016100706": 1 1 1 1 1 1 1 1 1 1 ...
+##  $ TAU      : num  3 12 24 36 48 72 3 12 24 36 ...
+##  $ NE       : num  160 170 180 200 150 120 70 70 80 80 ...
+##  $ SE       : num  140 140 160 160 150 150 70 70 70 70 ...
+##  $ SW       : num  80 80 80 90 120 150 50 50 50 40 ...
+##  $ NW       : num  120 120 110 90 90 120 70 70 70 40 ...
+##  $ geometry :sfc_POLYGON of length 16; first list element: List of 1
+##   ..$ : num [1:364, 1:2] -80 -79.9 -79.9 -79.8 -79.8 ...
+##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
+##   ..- attr(*, "names")= chr  "RADII" "STORMID" "BASIN" "STORMNUM" ...
    +

    The “initialradii” dataset will contain up to three observations for each radii: 34 knots, 50 knots, and 64 knots. This is the expected distance from the center of circulation that minimum n-force winds can be expected.

    +

    The “forecastradii” can have many observations. For forecast periods up to 36 hours, all wind radii may be provided if the storm is strong enough. At 48 and 72 hours, only 34 and 50 knot wind radii are provided. No forecast wind radii are provided beyond 72 hours.

    + +

    +

    In the plot above I take the same approach as the advisory package but only keep the line track and points to keep the graph simple. To add the forecast wind radii, I again use the geom_sf layer providing the fill aesthetic based on RADII. Outside of the aesthetic, I set alpha to 0.25 to make underlying radii visible as well as land areas.

    + +

    The initialradii dataset was intentionally left out; as you can see it is included in the forecastradii package.

    -
    -

    -Wind Speed Probabilities

    -

    Wind Speed probabilities show the chance of experiencing a minimum-sustained winds of 34, 50 and 64 knots with a given period of time (typically, 120 hours). These products are not storm-specific but are global so other active cyclones in other basins may also appear.

    -
    gis_wsp(datetime = "2016100606", res = 0.5)
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/2016100606_wsp_120hrhalfDeg.zip"
    - -
    +

    -Cumulative Probability for >34kt Winds

    -
    bb <- sp::bbox(df.gis_wsp$`2016100606_wsp34knt120hr_halfDeg`)
-p + 
-  geom_sf(
-    data = st_as_sf(df.gis_wsp$`2016100606_wsp34knt120hr_halfDeg`), 
-    aes(color = PWIND120)
-  ) +
-  coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2]))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    Cumulative wind speed probability for >50kt winds:

    -
    bb <- sp::bbox(df.gis_wsp$`2016100606_wsp50knt120hr_halfDeg`)
-p + 
-  geom_sf(
-    data = st_as_sf(df.gis_wsp$`2016100606_wsp50knt120hr_halfDeg`), 
-    aes(color = PWIND120)
-  ) +
-  coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2]))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    Cumulative probability for >64kt winds:

    -
    bb <- sp::bbox(df.gis_wsp$`2016100606_wsp64knt120hr_halfDeg`)
-p + 
-  geom_sf(
-    data = st_as_sf(df.gis_wsp$`2016100606_wsp64knt120hr_halfDeg`), 
-    aes(color = PWIND120)
-  ) +
-  coord_sf(xlim = c(bb[1,1], bb[1,2]), ylim = c(bb[2,1], bb[2,2]))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    +Wind Speed Probabilities +

    As noted previously, wind speed probabilities can be provided in different resolutions. Recall that I went with the 0.5° resolution dataset. There are three packages in this dataset; proabilities of at least 34 knot winds, 50 knot winds, and 64 knot winds.

    +
    str(shp_df$`2016100706_wsp34knt120hr_halfDeg`)
    +
    ## Classes 'sf' and 'data.frame':   4367 obs. of  3 variables:
+##  $ POINTID : int  90011 100011 100012 100013 10014 110014 120014 130014 140014 150014 ...
+##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 ...
+##  $ geometry:sfc_POINT of length 4367; first list element:  'XY' num  104 6
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
+##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    +
    str(shp_df$`2016100706_wsp50knt120hr_halfDeg`)
    +
    ## Classes 'sf' and 'data.frame':   2302 obs. of  3 variables:
+##  $ POINTID : int  10015 10016 30017 40017 130017 40018 120018 130018 140018 90019 ...
+##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ...
+##  $ geometry:sfc_POINT of length 2302; first list element:  'XY' num  100 8
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
+##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    +
    str(shp_df$`2016100706_wsp64knt120hr_halfDeg`)
    +
    ## Classes 'sf' and 'data.frame':   1367 obs. of  3 variables:
+##  $ POINTID : int  140023 150023 140024 150024 160024 170024 160025 170025 180025 80026 ...
+##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 ...
+##  $ geometry:sfc_POINT of length 1367; first list element:  'XY' num  106 12
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
+##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    +

    Each dataset contains the variable PWIND120; the probability of n-speed winds up to 120 hours.

    + +

    +

    The plot above focuses only on the wind speed probabilities. The forecast track of the cyclone is quite clear. I made the size and alpha aesthetic based on PWIND120 but removed those legends. I kept the color aesthetic which I divided by 100 to make a fraction (default is a real). With that, I applied scales::percent to the legend to show a percentage and changed the breaks.

    +
    +
    +

    +Storm Surge Probabilities

    +
    str(shp_df$al142016_2016100706_gt5)
    +
    ## Classes 'sf' and 'data.frame':   99 obs. of  3 variables:
+##  $ POINTID  : int  1 2 3 4 5 6 7 8 9 10 ...
+##  $ PSurge05c: num  1 2 3 4 5 6 7 8 9 10 ...
+##  $ geometry :sfc_MULTIPOLYGON of length 99; first list element: List of 554
+##   ..$ :List of 1
+##   .. ..$ : num [1:43, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:23, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:13, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:13, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:19, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:5, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:5, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:17, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:45, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:15, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:7, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:13, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:19, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:67, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:33, 1:2] -82.6 -82.6 -82.6 -82.6 -82.6 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:15, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:15, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:17, 1:2] -80.7 -80.6 -80.6 -80.7 -80.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:13, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:11, 1:2] -80.6 -80.6 -80.6 -80.6 -80.6 ...
+##   ..$ :List of 1
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+##   .. ..$ : num [1:5, 1:2] -81.5 -81.5 -81.5 -81.5 -81.5 ...
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+##   .. ..$ : num [1:5, 1:2] -81.4 -81.4 -81.4 -81.4 -81.4 ...
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+##   .. ..$ : num [1:5, 1:2] -81.5 -81.5 -81.5 -81.5 -81.5 ...
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+##   .. ..$ : num [1:5, 1:2] -81.7 -81.7 -81.7 -81.7 -81.7 ...
+##   ..$ :List of 1
+##   .. ..$ : num [1:5, 1:2] -81.7 -81.7 -81.7 -81.7 -81.7 ...
+##   .. [list output truncated]
+##   ..- attr(*, "class")= chr  "XY" "MULTIPOLYGON" "sfg"
+##  - attr(*, "sf_column")= chr "geometry"
+##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
+##   ..- attr(*, "names")= chr  "POINTID" "PSurge05c"
    +

    Similar to the wind speed probabilities, storm surge probabilties only has three variables, the POINTID, geometry, and, because we requested the psurge product for 5-feet, PSurge05c (this name changes depending on the product and value).

    +

    Note that unlike wind speed probabilities which is a point shapefile, this dataset is a polygon shapefile.

    + +

    +

    I took similar steps to creating this plot as I did with wind speed probabilties.

    +

    Note what appears to be storm surge well inland from the coast in Lake George, St. Johns River, and elsewhere.

    @@ -1063,13 +1174,15 @@

    Contents

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    @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -145,11 +136,8 @@

    Articles

    diff --git a/docs/articles/installing_rrricanesdata.html b/docs/articles/installing_rrricanesdata.html index 742e824d..2d3193e2 100644 --- a/docs/articles/installing_rrricanesdata.html +++ b/docs/articles/installing_rrricanesdata.html @@ -31,7 +31,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -56,27 +56,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -105,7 +96,7 @@

    Installing rrricanesdata

    Tim Trice

    -

    2019-06-16

    +

    2019-06-22

    Source: vignettes/installing_rrricanesdata.Rmd @@ -359,7 +350,22 @@

    Contents

    diff --git a/docs/articles/wind_pressure.html b/docs/articles/wind_pressure.html index ae42fc1b..b62eabf7 100644 --- a/docs/articles/wind_pressure.html +++ b/docs/articles/wind_pressure.html @@ -31,7 +31,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -56,27 +56,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -131,14 +122,14 @@

    Wind Profile

    # Plot wind values
-fstadv %>% ggplot(aes(x = Date, y = Wind)) + 
-  geom_line() + 
-  geom_point(aes(color = Status), size = 3) + 
-  scale_y_continuous(name = "Wind (kts)") + 
-  theme_bw() + 
-  theme(legend.position = "bottom", 
+fstadv %>% ggplot(aes(x = Date, y = Wind)) + 
+  geom_line() + 
+  geom_point(aes(color = Status), size = 3) + 
+  scale_y_continuous(name = "Wind (kts)") + 
+  theme_bw() + 
+  theme(legend.position = "bottom", 
         legend.box = "vertical") +
-  labs(title = "Wind Profile", 
+  labs(title = "Wind Profile", 
        caption = sprintf("rrricanes %s", packageVersion("rrricanes")))

    @@ -146,14 +137,14 @@

    Pressure Profile

    # Plot pressure values
-fstadv %>% ggplot(aes(x = Date, y = Pressure)) + 
-  geom_line() + 
-  geom_point(aes(color = Status), size = 3) + 
-  scale_y_continuous(name = "Pressure (mb)") + 
-  theme_bw() + 
-  theme(legend.position = "bottom", 
+fstadv %>% ggplot(aes(x = Date, y = Pressure)) + 
+  geom_line() + 
+  geom_point(aes(color = Status), size = 3) + 
+  scale_y_continuous(name = "Pressure (mb)") + 
+  theme_bw() + 
+  theme(legend.position = "bottom", 
         legend.box = "vertical") +
-  labs(title = "Pressure Profile", 
+  labs(title = "Pressure Profile", 
        caption = sprintf("rrricanes %s", packageVersion("rrricanes")))

    @@ -164,13 +155,13 @@

    mutate(WindDist = (Wind - min(Wind))/(max(Wind) - min(Wind)), PressDist = (Pressure - max(Pressure))/(max(Pressure) - min(Pressure))) %>% gather(Var, Val, WindDist, PressDist) %>% - ggplot(aes(x = Date, y = Val, group = Var, color = Var)) + - geom_line(size = 1) + - scale_color_discrete(labels = c("Pressure Change", "Wind Change")) + - theme_bw() + - theme(legend.position = "bottom", - legend.title = element_blank()) + - labs(title = "Wind/Pressure Relational Change", + ggplot(aes(x = Date, y = Val, group = Var, color = Var)) + + geom_line(size = 1) + + scale_color_discrete(labels = c("Pressure Change", "Wind Change")) + + theme_bw() + + theme(legend.position = "bottom", + legend.title = element_blank()) + + labs(title = "Wind/Pressure Relational Change", subtitle = "", caption = sprintf("rrricanes %s", packageVersion("rrricanes")), y = "") @@ -183,20 +174,20 @@

    fstadv %>% tidy_wr() %>% gather(Quadrant, Radius, NE:NW) %>% - ggplot( - aes( + ggplot( + aes( x = Quadrant, y = Radius, fill = factor(WindField), frame = Adv ) ) + - geom_bar(stat = "identity", position = "identity", width = 1) + - guides(fill = guide_legend(title = "Wind Field")) + - coord_polar() + - theme_minimal() + - theme(legend.position = "bottom") + - labs( + geom_bar(stat = "identity", position = "identity", width = 1) + + guides(fill = guide_legend(title = "Wind Field")) + + coord_polar() + + theme_minimal() + + theme(legend.position = "bottom") + + labs( title = "Wind Radius for Advisory {frame}", subtitle = "Minimum sustained one-minute wind speed in knots", caption = sprintf("rrricanes %s", packageVersion("rrricanes")), @@ -229,7 +220,8 @@

    Contents

  • diff --git a/docs/news/index.html b/docs/news/index.html index 53d58d14..bb2600e5 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 2ed70fab..542fcb4b 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -3,13 +3,10 @@ pkgdown: 1.3.0 pkgdown_sha: ~ articles: accumulated_cyclone_energy: accumulated_cyclone_energy.html - forecast_advisory: forecast_advisory.html getting_started: getting_started.html gis_data: gis_data.html installing_rrricanesdata: installing_rrricanesdata.html - probabilistic_storm_surge: probabilistic_storm_surge.html wind_pressure: wind_pressure.html - wind_speed_probabilities: wind_speed_probabilities.html urls: reference: https://ropensci.github.io/rrricanes//reference article: https://ropensci.github.io/rrricanes//articles diff --git a/docs/reference/al_prblty_stations.html b/docs/reference/al_prblty_stations.html index 72a4aa28..f7c39acc 100644 --- a/docs/reference/al_prblty_stations.html +++ b/docs/reference/al_prblty_stations.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/cp_prblty_stations.html b/docs/reference/cp_prblty_stations.html index 777e84df..27042bc3 100644 --- a/docs/reference/cp_prblty_stations.html +++ b/docs/reference/cp_prblty_stations.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.al_12_2005_prblty.html b/docs/reference/df.al_12_2005_prblty.html index 663e3c70..77f86a25 100644 --- a/docs/reference/df.al_12_2005_prblty.html +++ b/docs/reference/df.al_12_2005_prblty.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.al_18_2012.html b/docs/reference/df.al_18_2012.html index 0bc9f26f..d9f0fd3f 100644 --- a/docs/reference/df.al_18_2012.html +++ b/docs/reference/df.al_18_2012.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.al_18_2012_fstadv.html b/docs/reference/df.al_18_2012_fstadv.html index 3089a911..b621abfd 100644 --- a/docs/reference/df.al_18_2012_fstadv.html +++ b/docs/reference/df.al_18_2012_fstadv.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.al_18_2012_wndprb.html b/docs/reference/df.al_18_2012_wndprb.html index 3b99c9d5..026b7140 100644 --- a/docs/reference/df.al_18_2012_wndprb.html +++ b/docs/reference/df.al_18_2012_wndprb.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.al_2012.html b/docs/reference/df.al_2012.html index 602f88e0..d4edd47f 100644 --- a/docs/reference/df.al_2012.html +++ b/docs/reference/df.al_2012.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.gis_adv.html b/docs/reference/df.gis_adv.html index ad39941a..f9e39865 100644 --- a/docs/reference/df.gis_adv.html +++ b/docs/reference/df.gis_adv.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.gis_storm_surge.html b/docs/reference/df.gis_storm_surge.html index 066f2699..58b14f68 100644 --- a/docs/reference/df.gis_storm_surge.html +++ b/docs/reference/df.gis_storm_surge.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.gis_wind_radii.html b/docs/reference/df.gis_wind_radii.html index ddeaf4a2..1d359974 100644 --- a/docs/reference/df.gis_wind_radii.html +++ b/docs/reference/df.gis_wind_radii.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/df.gis_wsp.html b/docs/reference/df.gis_wsp.html index 17fb8f01..f6caf38e 100644 --- a/docs/reference/df.gis_wsp.html +++ b/docs/reference/df.gis_wsp.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/discus.html b/docs/reference/discus.html index 062373a4..abeff66f 100644 --- a/docs/reference/discus.html +++ b/docs/reference/discus.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/ep_prblty_stations.html b/docs/reference/ep_prblty_stations.html index 77ba4657..28c7d802 100644 --- a/docs/reference/ep_prblty_stations.html +++ b/docs/reference/ep_prblty_stations.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/extract_product_contents.html b/docs/reference/extract_product_contents.html index 9b4d6634..56bbb58d 100644 --- a/docs/reference/extract_product_contents.html +++ b/docs/reference/extract_product_contents.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/extract_storm_links.html b/docs/reference/extract_storm_links.html index af1488c3..7dec0226 100644 --- a/docs/reference/extract_storm_links.html +++ b/docs/reference/extract_storm_links.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/extract_storms.html b/docs/reference/extract_storms.html index e28741e9..d7e2a58e 100644 --- a/docs/reference/extract_storms.html +++ b/docs/reference/extract_storms.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/extract_year_archive_link.html b/docs/reference/extract_year_archive_link.html index 0ba28df6..bd4d012f 100644 --- a/docs/reference/extract_year_archive_link.html +++ b/docs/reference/extract_year_archive_link.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_discus.html b/docs/reference/filter_discus.html index d5e6a9c5..bdd77d9e 100644 --- a/docs/reference/filter_discus.html +++ b/docs/reference/filter_discus.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_fstadv.html b/docs/reference/filter_fstadv.html index dd0dce21..04f640a5 100644 --- a/docs/reference/filter_fstadv.html +++ b/docs/reference/filter_fstadv.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_orig.html b/docs/reference/filter_orig.html index e0049628..f9751942 100644 --- a/docs/reference/filter_orig.html +++ b/docs/reference/filter_orig.html @@ -70,7 +70,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -95,27 +95,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_posest.html b/docs/reference/filter_posest.html index 9d5fc1ec..a6b349b5 100644 --- a/docs/reference/filter_posest.html +++ b/docs/reference/filter_posest.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_prblty.html b/docs/reference/filter_prblty.html index ac9476d1..fbdd6648 100644 --- a/docs/reference/filter_prblty.html +++ b/docs/reference/filter_prblty.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_public.html b/docs/reference/filter_public.html index 67826b65..b142455b 100644 --- a/docs/reference/filter_public.html +++ b/docs/reference/filter_public.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_update.html b/docs/reference/filter_update.html index f4292d3f..1cebb295 100644 --- a/docs/reference/filter_update.html +++ b/docs/reference/filter_update.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/filter_wndprb.html b/docs/reference/filter_wndprb.html index 0b7b7cfb..82b289cd 100644 --- a/docs/reference/filter_wndprb.html +++ b/docs/reference/filter_wndprb.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv.html b/docs/reference/fstadv.html index a8d20b8a..7d5c08e9 100644 --- a/docs/reference/fstadv.html +++ b/docs/reference/fstadv.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_eye.html b/docs/reference/fstadv_eye.html index 2337851b..9368414c 100644 --- a/docs/reference/fstadv_eye.html +++ b/docs/reference/fstadv_eye.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_forecasts.html b/docs/reference/fstadv_forecasts.html index 851d4ee2..a4f8df57 100644 --- a/docs/reference/fstadv_forecasts.html +++ b/docs/reference/fstadv_forecasts.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_fwd_mvmt.html b/docs/reference/fstadv_fwd_mvmt.html index f08088ef..9ab5c666 100644 --- a/docs/reference/fstadv_fwd_mvmt.html +++ b/docs/reference/fstadv_fwd_mvmt.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_lat_lon.html b/docs/reference/fstadv_lat_lon.html index b1246197..b80f1f40 100644 --- a/docs/reference/fstadv_lat_lon.html +++ b/docs/reference/fstadv_lat_lon.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_pos_accuracy.html b/docs/reference/fstadv_pos_accuracy.html index c5786366..851dcfaa 100644 --- a/docs/reference/fstadv_pos_accuracy.html +++ b/docs/reference/fstadv_pos_accuracy.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_pressure.html b/docs/reference/fstadv_pressure.html index 4cf813d4..fae75cf2 100644 --- a/docs/reference/fstadv_pressure.html +++ b/docs/reference/fstadv_pressure.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_prev_pos.html b/docs/reference/fstadv_prev_pos.html index b5ad7d18..ba19e4bf 100644 --- a/docs/reference/fstadv_prev_pos.html +++ b/docs/reference/fstadv_prev_pos.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_seas.html b/docs/reference/fstadv_seas.html index d7afc1f2..af66154b 100644 --- a/docs/reference/fstadv_seas.html +++ b/docs/reference/fstadv_seas.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_wind_radius.html b/docs/reference/fstadv_wind_radius.html index 87e14200..8c62092f 100644 --- a/docs/reference/fstadv_wind_radius.html +++ b/docs/reference/fstadv_wind_radius.html @@ -71,7 +71,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -96,27 +96,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/fstadv_winds_gusts.html b/docs/reference/fstadv_winds_gusts.html index 2d3fe90c..6f124b04 100644 --- a/docs/reference/fstadv_winds_gusts.html +++ b/docs/reference/fstadv_winds_gusts.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_discus.html b/docs/reference/get_discus.html index b55f995e..e2d73b32 100644 --- a/docs/reference/get_discus.html +++ b/docs/reference/get_discus.html @@ -73,7 +73,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -98,27 +98,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_fstadv.html b/docs/reference/get_fstadv.html index 150db991..7683d320 100644 --- a/docs/reference/get_fstadv.html +++ b/docs/reference/get_fstadv.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_ftp_dirs.html b/docs/reference/get_ftp_dirs.html index dd03bd33..04107c72 100644 --- a/docs/reference/get_ftp_dirs.html +++ b/docs/reference/get_ftp_dirs.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_ftp_storm_data.html b/docs/reference/get_ftp_storm_data.html index 3646aeaa..b78ac2b2 100644 --- a/docs/reference/get_ftp_storm_data.html +++ b/docs/reference/get_ftp_storm_data.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_nhc_ftp_link.html b/docs/reference/get_nhc_ftp_link.html index 94fa722c..ae1e9c69 100644 --- a/docs/reference/get_nhc_ftp_link.html +++ b/docs/reference/get_nhc_ftp_link.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_nhc_link.html b/docs/reference/get_nhc_link.html index fb158da3..2d2a8df0 100644 --- a/docs/reference/get_nhc_link.html +++ b/docs/reference/get_nhc_link.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_posest.html b/docs/reference/get_posest.html index 1f5dfe6d..e511b996 100644 --- a/docs/reference/get_posest.html +++ b/docs/reference/get_posest.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_prblty.html b/docs/reference/get_prblty.html index d2b850dc..e4cd949c 100644 --- a/docs/reference/get_prblty.html +++ b/docs/reference/get_prblty.html @@ -78,7 +78,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -103,27 +103,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_product.html b/docs/reference/get_product.html index 8d826c05..a858575f 100644 --- a/docs/reference/get_product.html +++ b/docs/reference/get_product.html @@ -67,7 +67,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -92,27 +92,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_public.html b/docs/reference/get_public.html index e0164482..5aedd69f 100644 --- a/docs/reference/get_public.html +++ b/docs/reference/get_public.html @@ -73,7 +73,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -98,27 +98,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_storm_data.html b/docs/reference/get_storm_data.html index 5e2e5fac..b953f7dd 100644 --- a/docs/reference/get_storm_data.html +++ b/docs/reference/get_storm_data.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_storm_list.html b/docs/reference/get_storm_list.html index e78a89a9..c05c21e1 100644 --- a/docs/reference/get_storm_list.html +++ b/docs/reference/get_storm_list.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_storms.html b/docs/reference/get_storms.html index a50575f6..d29cd2f2 100644 --- a/docs/reference/get_storms.html +++ b/docs/reference/get_storms.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_update.html b/docs/reference/get_update.html index f6ac22d4..918cc4bd 100644 --- a/docs/reference/get_update.html +++ b/docs/reference/get_update.html @@ -72,7 +72,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -97,27 +97,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_url_contents.html b/docs/reference/get_url_contents.html index df0d3ec9..b8546a1d 100644 --- a/docs/reference/get_url_contents.html +++ b/docs/reference/get_url_contents.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/get_wndprb.html b/docs/reference/get_wndprb.html index e570e9e1..84a59b59 100644 --- a/docs/reference/get_wndprb.html +++ b/docs/reference/get_wndprb.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_advisory.html b/docs/reference/gis_advisory.html index e6a9b4b9..208bb158 100644 --- a/docs/reference/gis_advisory.html +++ b/docs/reference/gis_advisory.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_breakpoints.html b/docs/reference/gis_breakpoints.html index 26a27e2b..0acfeea3 100644 --- a/docs/reference/gis_breakpoints.html +++ b/docs/reference/gis_breakpoints.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_download.html b/docs/reference/gis_download.html index 61e85313..5531dc0d 100644 --- a/docs/reference/gis_download.html +++ b/docs/reference/gis_download.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -148,7 +139,7 @@

    gis_download

    - 
    gis_download(url, ...)
    + 
    gis_download(url, destdir = tempdir(), ...)

    Arguments

    @@ -157,9 +148,13 @@

    Arg

    + + + + - +
    url

    link to GIS dataset to download.
    destdir

    The destination directory to download and extract the zip file

    ...

    additional parameters for rgdal::readOGR

    additional parameters for file.path
    diff --git a/docs/reference/gis_latest.html b/docs/reference/gis_latest.html index 70a7c0bd..f97b5c09 100644 --- a/docs/reference/gis_latest.html +++ b/docs/reference/gis_latest.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_outlook.html b/docs/reference/gis_outlook.html index 0d671982..63491457 100644 --- a/docs/reference/gis_outlook.html +++ b/docs/reference/gis_outlook.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_prob_storm_surge.html b/docs/reference/gis_prob_storm_surge.html index 9288b77c..d5229aab 100644 --- a/docs/reference/gis_prob_storm_surge.html +++ b/docs/reference/gis_prob_storm_surge.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -210,8 +201,10 @@

    Examp gis_prob_storm_surge("AL092016", products = list("psurge" = 0, "esurge" = 10)) # Return all psurge0 products for Sep 2, 2016, storm AL092016 -gis_prob_storm_surge("AL092016", products = list("psurge" = 0), - datetime = "20160902") +gis_prob_storm_surge("AL092016", + products = list("psurge" = 0), + datetime = "20160902" +) # } @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -

  • diff --git a/docs/reference/gis_windfield.html b/docs/reference/gis_windfield.html index 11971f63..9be29d9a 100644 --- a/docs/reference/gis_windfield.html +++ b/docs/reference/gis_windfield.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/gis_wsp.html b/docs/reference/gis_wsp.html index e1bfe0e2..eacc2a7b 100644 --- a/docs/reference/gis_wsp.html +++ b/docs/reference/gis_wsp.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/index.html b/docs/reference/index.html index 6672daa4..f96dce7b 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -63,7 +63,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -88,27 +88,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -254,32 +245,6 @@

    -

    Tracking charts

    -

    Helper functions to plot storm data through ggplot2.

    - - - - - -

    al_tracking_chart()

    - -

    al_tracking_chart

    - - - -

    ep_tracking_chart()

    - -

    ep_tracking_chart

    - - - -

    tracking_chart()

    - -

    tracking_chart

    - @@ -341,12 +306,6 @@

    gis_wsp()

    gis_wsp

    - - - -

    shp_to_df()

    - -

    shp_to_df

    @@ -500,7 +459,6 @@

    Contents

  • About `rrricanes`
  • Getting Storm Data
  • Daily Discussions
    • -
  • Tracking charts
  • GIS Data
  • Helpers
  • Datasets
    • diff --git a/docs/reference/knots_to_mph.html b/docs/reference/knots_to_mph.html index 679220e2..6e694041 100644 --- a/docs/reference/knots_to_mph.html +++ b/docs/reference/knots_to_mph.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/mb_to_in.html b/docs/reference/mb_to_in.html index 7ba3b7c3..f36bc0ef 100644 --- a/docs/reference/mb_to_in.html +++ b/docs/reference/mb_to_in.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/month_str_to_num.html b/docs/reference/month_str_to_num.html index 415e826b..e1196dd9 100644 --- a/docs/reference/month_str_to_num.html +++ b/docs/reference/month_str_to_num.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/nm_to_sm.html b/docs/reference/nm_to_sm.html index 351a3594..0b8e9449 100644 --- a/docs/reference/nm_to_sm.html +++ b/docs/reference/nm_to_sm.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/parse_stations.html b/docs/reference/parse_stations.html index e0f8be7e..bba1459a 100644 --- a/docs/reference/parse_stations.html +++ b/docs/reference/parse_stations.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/posest.html b/docs/reference/posest.html index 36ab7781..cd4dedae 100644 --- a/docs/reference/posest.html +++ b/docs/reference/posest.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/prblty.html b/docs/reference/prblty.html index 5a1d5db5..006a1f01 100644 --- a/docs/reference/prblty.html +++ b/docs/reference/prblty.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/public.html b/docs/reference/public.html index 4b46d7f0..4cf47445 100644 --- a/docs/reference/public.html +++ b/docs/reference/public.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/rrricanes.html b/docs/reference/rrricanes.html index 3bdfb0ea..68b55a8a 100644 --- a/docs/reference/rrricanes.html +++ b/docs/reference/rrricanes.html @@ -73,7 +73,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -98,27 +98,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • @@ -231,10 +222,6 @@

    GIS D

    gis_download will download the datasets from the above functions.

    -

    Some GIS datasets will need to be converted to dataframes to plot geoms. Use -shp_to_df to convert SpatialLinesDataFrames and -SpatialPolygonsDataFrames. SpatialPointsDataFrames can be converted using -tibble::as_data_frame targeting the @data object.

    Package Options

    diff --git a/docs/reference/saffir.html b/docs/reference/saffir.html index 4a47cbf1..b8b473a1 100644 --- a/docs/reference/saffir.html +++ b/docs/reference/saffir.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/scrape_date.html b/docs/reference/scrape_date.html index d7eda7e2..3b0fb70f 100644 --- a/docs/reference/scrape_date.html +++ b/docs/reference/scrape_date.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/scrape_header.html b/docs/reference/scrape_header.html index fe4cd45f..907cb7c3 100644 --- a/docs/reference/scrape_header.html +++ b/docs/reference/scrape_header.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/scrape_key.html b/docs/reference/scrape_key.html index 8495f09c..54d7545f 100644 --- a/docs/reference/scrape_key.html +++ b/docs/reference/scrape_key.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/status_abbr_to_str.html b/docs/reference/status_abbr_to_str.html index ef9391c8..1e9bd808 100644 --- a/docs/reference/status_abbr_to_str.html +++ b/docs/reference/status_abbr_to_str.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/tidy_adv.html b/docs/reference/tidy_adv.html index 153ea61f..234b85cc 100644 --- a/docs/reference/tidy_adv.html +++ b/docs/reference/tidy_adv.html @@ -66,7 +66,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -91,27 +91,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/tidy_fcst.html b/docs/reference/tidy_fcst.html index 883f69cd..43bc0464 100644 --- a/docs/reference/tidy_fcst.html +++ b/docs/reference/tidy_fcst.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/tidy_fcst_wr.html b/docs/reference/tidy_fcst_wr.html index e7d1b677..38cb28ca 100644 --- a/docs/reference/tidy_fcst_wr.html +++ b/docs/reference/tidy_fcst_wr.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/tidy_wr.html b/docs/reference/tidy_wr.html index 67f68735..292fde9b 100644 --- a/docs/reference/tidy_wr.html +++ b/docs/reference/tidy_wr.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/twoal.html b/docs/reference/twoal.html index ca645ef0..b27e620b 100644 --- a/docs/reference/twoal.html +++ b/docs/reference/twoal.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/twoep.html b/docs/reference/twoep.html index 13a9d143..a26e6b2c 100644 --- a/docs/reference/twoep.html +++ b/docs/reference/twoep.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/update.html b/docs/reference/update.html index 06e63bc7..27c841e5 100644 --- a/docs/reference/update.html +++ b/docs/reference/update.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/wndprb.html b/docs/reference/wndprb.html index e1f3120d..cefa34a2 100644 --- a/docs/reference/wndprb.html +++ b/docs/reference/wndprb.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/reference/year_archives_link.html b/docs/reference/year_archives_link.html index 3fd23b71..ae19e1c9 100644 --- a/docs/reference/year_archives_link.html +++ b/docs/reference/year_archives_link.html @@ -65,7 +65,7 @@ rrricanes - 0.2.0.6.9001 + 0.2.0.6.9002 @@ -90,27 +90,18 @@
  • Accumulated Cyclone Energy (ACE)
    • -
  • - Forecast/Advisory GIS -
  • Getting Started
  • - GIS data + Retrieving and Plotting GIS Data
  • Installing rrricanesdata
    • -
  • - Probabilistic Storm Surge -
  • Wind and Pressure
    • -
  • - Wind Speed Probabilities -
  • diff --git a/docs/sitemap.xml b/docs/sitemap.xml index a4f838d2..67f3dd9e 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -6,9 +6,6 @@ https://ropensci.github.io/rrricanes//reference/al_prblty_stations.html - - https://ropensci.github.io/rrricanes//reference/al_tracking_chart.html - https://ropensci.github.io/rrricanes//reference/cp_prblty_stations.html @@ -45,9 +42,6 @@ https://ropensci.github.io/rrricanes//reference/ep_prblty_stations.html - - https://ropensci.github.io/rrricanes//reference/ep_tracking_chart.html - https://ropensci.github.io/rrricanes//reference/extract_product_contents.html @@ -231,9 +225,6 @@ https://ropensci.github.io/rrricanes//reference/scrape_key.html - - https://ropensci.github.io/rrricanes//reference/shp_to_df.html - https://ropensci.github.io/rrricanes//reference/status_abbr_to_str.html @@ -249,9 +240,6 @@ https://ropensci.github.io/rrricanes//reference/tidy_wr.html - - https://ropensci.github.io/rrricanes//reference/tracking_chart.html - https://ropensci.github.io/rrricanes//reference/twoal.html @@ -270,9 +258,6 @@ https://ropensci.github.io/rrricanes//articles/accumulated_cyclone_energy.html - - https://ropensci.github.io/rrricanes//articles/forecast_advisory.html - https://ropensci.github.io/rrricanes//articles/getting_started.html @@ -282,13 +267,7 @@ https://ropensci.github.io/rrricanes//articles/installing_rrricanesdata.html - - https://ropensci.github.io/rrricanes//articles/probabilistic_storm_surge.html - https://ropensci.github.io/rrricanes//articles/wind_pressure.html - - https://ropensci.github.io/rrricanes//articles/wind_speed_probabilities.html - From 38c3bfcd5014d627d921e837091efefe6a1f1d98 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 09:51:59 -0500 Subject: [PATCH 10/41] Add travis deploy for pkgdown --- .travis.yml | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/.travis.yml b/.travis.yml index 3e89cc19..d7b3a9cf 100644 --- a/.travis.yml +++ b/.travis.yml @@ -21,6 +21,12 @@ matrix: include: - r: oldrel - r: release + after_success: Rscript -e "covr::codecov()" + before_deploy: Rscript -e "remotes::install_cran('pkgdown')" + deploy: + provider: script + script: Rscript -e "pkgdown::deploy_site_github()"" + skip_cleanup: true - r: devel env: @@ -31,9 +37,6 @@ r_packages: - covr - sf -after_success: - - Rscript -e 'library(covr); codecov()' - env: global: secure: 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 From ac435cb90159c07176ea4abb2c60d5f8377a30a3 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 09:52:12 -0500 Subject: [PATCH 11/41] Attempt to install in lib --- appveyor.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index 2ccec3c5..0dd20724 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -33,8 +33,8 @@ matrix: build_script: - travis-tool.sh install_deps - - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source');" - - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source');" + - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" + - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" test_script: - travis-tool.sh run_tests From 77365eea119c47a737dd7937062adad1be1c2b9a Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:12:40 -0500 Subject: [PATCH 12/41] Add covr::codecov yaml --- codecov.yml | 12 ++++++++++++ 1 file changed, 12 insertions(+) create mode 100644 codecov.yml diff --git a/codecov.yml b/codecov.yml new file mode 100644 index 00000000..7568e9eb --- /dev/null +++ b/codecov.yml @@ -0,0 +1,12 @@ +comment: false + +coverage: + status: + patch: + default: + target: 0 + threshold: 100 + project: + default: + target: 70 + threshold: 100 From c72c347062b0b12b7592d506b9870634056ea844 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:13:30 -0500 Subject: [PATCH 13/41] Rearrange build script order --- appveyor.yml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index 0dd20724..c70a410c 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -32,9 +32,11 @@ matrix: fast_finish: true build_script: +# - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" +# - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" + - travis-tool.sh install_github ropensci/rrricanesdata + - travis-tool.sh install_github ropensci/rnaturalearthhires - travis-tool.sh install_deps - - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" - - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" test_script: - travis-tool.sh run_tests From 5ed1516666690600facf0ee3dd6103920aec6ea2 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:27:52 -0500 Subject: [PATCH 14/41] Use remotes::install_github --- .travis.yml | 4 ++-- appveyor.yml | 2 -- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/.travis.yml b/.travis.yml index d7b3a9cf..767452b1 100644 --- a/.travis.yml +++ b/.travis.yml @@ -14,8 +14,8 @@ addons: - libgdal-dev before_install: - - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" - - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" + - Rscript -e "remotes::install_github('ropensci/rrricanesdata')" + - Rscript -e "remotes::install_github('ropensci/rnaturalearthhires')" matrix: include: diff --git a/appveyor.yml b/appveyor.yml index c70a410c..158f1f3e 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -32,8 +32,6 @@ matrix: fast_finish: true build_script: -# - Rscript -e "install.packages('rrricanesdata', repos = 'https://timtrice.github.io/drat/', type = 'source', lib = .libPaths()[3]);" -# - Rscript -e "install.packages('rnaturalearthhires', repos = 'http://packages.ropensci.org', type = 'source', lib = .libPaths()[3]);" - travis-tool.sh install_github ropensci/rrricanesdata - travis-tool.sh install_github ropensci/rnaturalearthhires - travis-tool.sh install_deps From 08c09e926cd392f4e5caf48bf837f4e2fc7cd0b0 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:36:18 -0500 Subject: [PATCH 15/41] Ignore codecov yaml --- .Rbuildignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.Rbuildignore b/.Rbuildignore index 4515246d..f71ad8ac 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -8,6 +8,7 @@ ^docker$ ^appveyor\.yml$ ^CHANGELOG\.md$ +^codecov.yml$ ^data-raw$ ^datasets/ ^deploy\.sh$ From e373fd6bcc44d4430f97783d6a0d964770fa5f8c Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:44:59 -0500 Subject: [PATCH 16/41] Update instructions for rrricanesdata --- R/base.R | 4 +--- README.Rmd | 8 ++------ README.md | 8 ++------ docker/devel/Dockerfile | 4 +++- docker/oldrelease/Dockerfile | 4 +++- docker/release/Dockerfile | 4 +++- man/rrricanes.Rd | 4 +--- vignettes/installing_rrricanesdata.Rmd | 4 +--- 8 files changed, 16 insertions(+), 24 deletions(-) diff --git a/R/base.R b/R/base.R index 39abd8f2..4035f7fa 100755 --- a/R/base.R +++ b/R/base.R @@ -54,9 +54,7 @@ #' To install \code{rrricanesdata}, run #' #' \code{ -#' install.packages("rrricanesdata", -#' repos = "https://timtrice.github.io/drat/", -#' type = "source") +#' remotes::install_github("ropensci/rrricanesdata") #' } #' #' See \code{vignette("installing_rrricanesdata", package = "rrricanes")} for diff --git a/README.Rmd b/README.Rmd index 360bc0bd..5af33a74 100644 --- a/README.Rmd +++ b/README.Rmd @@ -73,17 +73,13 @@ Linux users must also have the `libgdal-dev`, `libproj-dev` and `libxml2-dev` pa To add `rrricanesdata`, a [package of post-scraped datasets](https://github.com/ropensci/rrricanesdata), ```r -install.packages("rrricanesdata", - repos = "https://timtrice.github.io/drat/", - type = "source") +remotes::install_github("ropensci/rrricanesdata") ``` To use high resolution tracking maps you will need to install the `rnaturalearthhires` package. ```r -install.packages("rnaturalearthhires", - repos = "http://packages.ropensci.org", - type = "source") +remotes::install_github("ropensci/rnaturalearthhires") ``` ### Installing diff --git a/README.md b/README.md index d6a0a870..062d0faa 100644 --- a/README.md +++ b/README.md @@ -108,18 +108,14 @@ To add `rrricanesdata`, a [package of post-scraped datasets](https://github.com/ropensci/rrricanesdata), ``` r -install.packages("rrricanesdata", - repos = "https://timtrice.github.io/drat/", - type = "source") +remotes::install_github("ropensci/rrricanesdata") ``` To use high resolution tracking maps you will need to install the `rnaturalearthhires` package. ``` r -install.packages("rnaturalearthhires", - repos = "http://packages.ropensci.org", - type = "source") +remotes::install_github("ropensci/rnaturalearthhires") ``` ### Installing diff --git a/docker/devel/Dockerfile b/docker/devel/Dockerfile index e3c90c16..718d91eb 100644 --- a/docker/devel/Dockerfile +++ b/docker/devel/Dockerfile @@ -42,7 +42,9 @@ RUN install2.r -e \ remotes \ xml2 -RUN Rscript -e 'install.packages("rrricanesdata", repos = "https://timtrice.github.io/drat/", type = "source");' +RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' + +RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ diff --git a/docker/oldrelease/Dockerfile b/docker/oldrelease/Dockerfile index 845ce1dc..0e1384f5 100644 --- a/docker/oldrelease/Dockerfile +++ b/docker/oldrelease/Dockerfile @@ -42,7 +42,9 @@ RUN install2.r -e \ remotes \ xml2 -RUN Rscript -e 'install.packages("rrricanesdata", repos = "https://timtrice.github.io/drat/", type = "source");' +RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' + +RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ diff --git a/docker/release/Dockerfile b/docker/release/Dockerfile index 0695814c..be48d6cd 100644 --- a/docker/release/Dockerfile +++ b/docker/release/Dockerfile @@ -42,7 +42,9 @@ RUN install2.r -e \ remotes \ xml2 -RUN Rscript -e 'install.packages("rrricanesdata", repos = "https://timtrice.github.io/drat/", type = "source");' +RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' + +RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ diff --git a/man/rrricanes.Rd b/man/rrricanes.Rd index 890d60d5..94c4ec74 100644 --- a/man/rrricanes.Rd +++ b/man/rrricanes.Rd @@ -64,9 +64,7 @@ of the current month, use the \code{rrricanesdata} package. To install \code{rrricanesdata}, run \code{ -install.packages("rrricanesdata", - repos = "https://timtrice.github.io/drat/", - type = "source") +remotes::install_github("ropensci/rrricanesdata") } See \code{vignette("installing_rrricanesdata", package = "rrricanes")} for diff --git a/vignettes/installing_rrricanesdata.Rmd b/vignettes/installing_rrricanesdata.Rmd index 72bf2d6b..2a924bac 100644 --- a/vignettes/installing_rrricanesdata.Rmd +++ b/vignettes/installing_rrricanesdata.Rmd @@ -19,9 +19,7 @@ With `rrricanes` you can access current and archived advisories as-issued from t Installing `rrricanesdata` is simple: ```{r, eval = FALSE} -install.packages("rrricanesdata", - repos = "https://timtrice.github.io/drat/", - type = "source") +remotes::install_github("ropensci/rrricanesdata") ``` Data in `rrricanesdata` will be updated on the first of every month with a cutoff date of midnight on the last day of the month. So, advisories issued at any time during the current month will not be available; you will need to use any of `rrricanes` `get_*` functions. From e330fff2d2a33dc24880a9e8634fcbeda736c18d Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:47:00 -0500 Subject: [PATCH 17/41] Specify deploy build on master, develop branch I am attempting to deploy pkgdown::build_site docs to gh-pages after push. Though travis tests pass, deploy fails: > Skipping a deployment with the script provider because this branch is not permitted: feature/113 I'm pushing from branch feature/113 I'm thinking if I push from develop or master, then deploy should succeed, which is fine. That's done with the on: branch: commands in the file. Additional === Set deploy_site_github verbose param to TRUE Removed R packages to install (covr, sf); already in DESCRIPTION --- .travis.yml | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/.travis.yml b/.travis.yml index 767452b1..e4c688d4 100644 --- a/.travis.yml +++ b/.travis.yml @@ -22,21 +22,20 @@ matrix: - r: oldrel - r: release after_success: Rscript -e "covr::codecov()" - before_deploy: Rscript -e "remotes::install_cran('pkgdown')" + before_cache: Rscript -e "remotes::install_cran('pkgdown')" deploy: provider: script - script: Rscript -e "pkgdown::deploy_site_github()"" + script: Rscript -e "pkgdown::deploy_site_github(verbose = TRUE)"" skip_cleanup: true + on: + all_branches: true + condition: $TRAVIS_BRANCH =~ ^master|develop$ - r: devel env: global: - _R_CHECK_FORCE_SUGGESTS_=false -r_packages: - - covr - - sf - env: global: secure: 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 From ffb7bbd1a4f44d8478116d5583c6eae3c25993cf Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 10:59:10 -0500 Subject: [PATCH 18/41] Install ropenscilabs/travis in Docker --- docker/devel/Dockerfile | 2 ++ docker/oldrelease/Dockerfile | 2 ++ docker/release/Dockerfile | 2 ++ 3 files changed, 6 insertions(+) diff --git a/docker/devel/Dockerfile b/docker/devel/Dockerfile index 718d91eb..252658b7 100644 --- a/docker/devel/Dockerfile +++ b/docker/devel/Dockerfile @@ -46,6 +46,8 @@ RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' +RUN Rscript -e 'remotes::install_github("ropenscilabs/travis");' + RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ && wget https://gist.githubusercontent.com/timtrice/94a679b51388faf99ef7918c7bdaff8d/raw/9a52ffebd1e2e8587918a31ff8e962110b816936/user-settings \ diff --git a/docker/oldrelease/Dockerfile b/docker/oldrelease/Dockerfile index 0e1384f5..8d2da160 100644 --- a/docker/oldrelease/Dockerfile +++ b/docker/oldrelease/Dockerfile @@ -46,6 +46,8 @@ RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' +RUN Rscript -e 'remotes::install_github("ropenscilabs/travis");' + RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ && wget https://gist.githubusercontent.com/timtrice/94a679b51388faf99ef7918c7bdaff8d/raw/9a52ffebd1e2e8587918a31ff8e962110b816936/user-settings \ diff --git a/docker/release/Dockerfile b/docker/release/Dockerfile index be48d6cd..26189634 100644 --- a/docker/release/Dockerfile +++ b/docker/release/Dockerfile @@ -46,6 +46,8 @@ RUN Rscript -e 'remotes::install_github("ropensci/rrricanesdata");' RUN Rscript -e 'remotes::install_github("ropensci/rnaturalearthhires");' +RUN Rscript -e 'remotes::install_github("ropenscilabs/travis");' + RUN cd /home/rstudio/.rstudio/monitored/user-settings/ \ && mv user-settings user-settings.copy \ && wget https://gist.githubusercontent.com/timtrice/94a679b51388faf99ef7918c7bdaff8d/raw/9a52ffebd1e2e8587918a31ff8e962110b816936/user-settings \ From b88345ad38e82cf704980fff53bfb3f1edd53e17 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 11:03:20 -0500 Subject: [PATCH 19/41] When IDE autocomplete lets you down --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index e4c688d4..49300179 100644 --- a/.travis.yml +++ b/.travis.yml @@ -25,7 +25,7 @@ matrix: before_cache: Rscript -e "remotes::install_cran('pkgdown')" deploy: provider: script - script: Rscript -e "pkgdown::deploy_site_github(verbose = TRUE)"" + script: Rscript -e "pkgdown::deploy_site_github(verbose = TRUE)" skip_cleanup: true on: all_branches: true From 5c50daff2c3696d280c350d577ec7af215967914 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 11:16:23 -0500 Subject: [PATCH 20/41] Add HURDAT for vignette --- DESCRIPTION | 1 + 1 file changed, 1 insertion(+) diff --git a/DESCRIPTION b/DESCRIPTION index bbc65cd2..09c70f74 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -42,6 +42,7 @@ Imports: Suggests: covr, devtools, + HURDAT, knitr, rmarkdown, rnaturalearthhires, From adb1d7908a64431bd9ffb2b6be367534b2fdd24f Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 11:27:39 -0500 Subject: [PATCH 21/41] Add gganimate to Suggests --- DESCRIPTION | 1 + 1 file changed, 1 insertion(+) diff --git a/DESCRIPTION b/DESCRIPTION index 09c70f74..0e2cdf8a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -42,6 +42,7 @@ Imports: Suggests: covr, devtools, + gganimate, HURDAT, knitr, rmarkdown, From 29441506e722c8b51ab077a54b580ae7af99f36d Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 11:27:39 -0500 Subject: [PATCH 22/41] Add gganimate to Suggests --- .travis.yml | 1 + DESCRIPTION | 1 + 2 files changed, 2 insertions(+) diff --git a/.travis.yml b/.travis.yml index 49300179..8293edc0 100644 --- a/.travis.yml +++ b/.travis.yml @@ -8,6 +8,7 @@ addons: sources: - sourceline: 'ppa:ubuntugis/ppa' packages: + - libmagick++-dev - libudunits2-dev - libproj-dev - libgeos-dev diff --git a/DESCRIPTION b/DESCRIPTION index 09c70f74..0e2cdf8a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -42,6 +42,7 @@ Imports: Suggests: covr, devtools, + gganimate, HURDAT, knitr, rmarkdown, From e9e297aa13d41e8c557d8cb3e3992967c01f4a67 Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 11:56:09 -0500 Subject: [PATCH 23/41] Add R magick pkg --- DESCRIPTION | 1 + 1 file changed, 1 insertion(+) diff --git a/DESCRIPTION b/DESCRIPTION index 0e2cdf8a..29077bed 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -45,6 +45,7 @@ Suggests: gganimate, HURDAT, knitr, + magick, rmarkdown, rnaturalearthhires, rrricanesdata, From e8ad8073f01aaa396a9433b197fefd08a42f1c0c Mon Sep 17 00:00:00 2001 From: Tim Trice Date: Sat, 22 Jun 2019 12:11:39 -0500 Subject: [PATCH 24/41] Remove pkgdown docs dir --- .Rbuildignore | 5 +- .gitignore | 2 +- docs/404.html | 156 --- docs/CHANGELOG.html | 752 ---------- docs/CONTRIBUTING.html | 219 --- docs/ISSUE_TEMPLATE.html | 171 --- docs/LICENSE-text.html | 178 --- docs/PULL_REQUEST_TEMPLATE.html | 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rrricanes.code-workspace rrricanes.Rcheck -rrricanes.wiki/ doc +docs Meta diff --git a/docs/404.html b/docs/404.html deleted file mode 100644 index 1b1c0106..00000000 --- a/docs/404.html +++ /dev/null @@ -1,156 +0,0 @@ - - - - - - - - -Page not found (404) • rrricanes - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    Page not found (404)

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    Developed by Tim Trice.

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    Site built with pkgdown 1.3.0.9100.

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    Change Log

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    All notable changes to this project will be documented in this file.

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    The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

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    -[Unreleased] yyyy-mm-dd

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    • -nm_to_sm Convert nautical miles to survey miles. (#99)
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    • -tidy_adv to replace tidy_fstadv which will be removed in release 0.2.2 (#103)
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    • -get_storm_list returns dataframe of all known cyclones. (#114)
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    • gis_latest can accept parameters for rgdal::readOGR (#104).

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    • gis_download modified to download zip files and extract contents returning a vector of files within the zip.

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    • ep_prblty_stations now returns all stations.

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    • al_prblty_stations, cp_prblty_stations and ep_prblty_stations datasets were modified with additional columns. Changes are documented.

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    • tracking_chart, al_tracking_chart, and ep_tracking_chart all removed in favor of using rnaturalearth and associated data packages, or other mapping packages.

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    • shp_to_df removed; users can use sf::st_read

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    • NHC GIS page went from using POST to GET parameters at some point recently for wind speed probability datasets. Func gis_wsp modified accordingly. (#108)
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    -[0.2.0-6] 2017-07-16

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    -[0.2.0-5.1] 2017-07-10

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    -[0.2.0-5] 2017-07-08

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    -[0.2.0-4] 2017-06-25

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    -[0.2.0-3] 2017-06-22

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    -[0.2.0-2] 2017-06-22

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    -[0.2.0-1] 2017-06-16

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    -[0.1.3] 2017-06-11

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    -[0.1.2] - 2017-06-08

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    -[0.1.0] - 2017-05-12

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    • -get_prblty get strike probabilities from a storm’s archive page.
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    - - - - - - diff --git a/docs/articles/accumulated_cyclone_energy.html b/docs/articles/accumulated_cyclone_energy.html deleted file mode 100644 index da93ead1..00000000 --- a/docs/articles/accumulated_cyclone_energy.html +++ /dev/null @@ -1,240 +0,0 @@ - - - - - - - -Accumulated Cyclone Energy (ACE) • rrricanes - - - - - - - - - - -
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    Accumulated Cyclone Energy (ACE)

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    Tim Trice

    - -

    June 27, 2017

    - - Source: vignettes/accumulated_cyclone_energy.Rmd - - -
    - - - -
    library(dplyr)
-library(ggplot2)
-library(HURDAT)
-library(lubridate)
-library(readr)
-library(rrricanes)
-library(rrricanesdata)
    -

    ACE or Accumulated Cyclone Energy is a method of measuring energy of a cyclone or for an entire season. It is calculated by the formula

    -

    \[ \text{ACE} = 10^{-4}\sum{v^2_\text{max}} \]

    -

    where \(v_\text{max}\) is the wind speed in knots. Values may only be used when a storm is a tropical system with winds of at least 35 knots. Additionally, only six-hour intervals are used.

    -

    To calculate ACE you would want to use the fstadv dataset and apply the following rules:

    -
      -
    • since forecast/advisory products are typically issued at 03:00, 09:00, 15:00 and 21:00 UTC filter out odd hours
      • -
    • -Status is Tropical Storm or Hurricane.
      • -
    • -Wind is not NA
      • -
    • group by Key -
      • -
    • select Wind -
      • -
    -
    fstadv <- fstadv %>% 
-    filter(hour(Date) %in% c(3, 9, 15, 21), 
-           Status %in% c("Tropical Storm", "Hurricane"), 
-           !is.na(Wind)) %>% 
-    group_by(Key) %>% 
-    select(Name, Wind)
    -
    ## Adding missing grouping variables: `Key`
    -

    Now let’s summarise our dataset with new variable ACE.

    -
    fstadv %>% 
-    summarise(Name = last(Name), 
-              ACE = sum(Wind^2) * 1e-04) %>% 
-    arrange(desc(ACE)) %>% 
-    top_n(10)
    -
    ## Selecting by ACE
    -
    ## # A tibble: 10 x 3
-##    Key      Name      ACE
-##    <chr>    <chr>   <dbl>
-##  1 AL092004 Ivan     69.9
-##  2 AL112017 Irma     66.6
-##  3 AL132003 Isabel   62.5
-##  4 AL142016 Matthew  48.0
-##  5 AL062004 Frances  46.9
-##  6 AL152017 Maria    44.6
-##  7 AL091999 Gert     44.0
-##  8 AL112010 Igor     42.9
-##  9 AL102003 Fabian   42.6
-## 10 EP071999 Dora     42.2
    -

    This matches somewhat well with Wikipedia and other sources. But, you may notice we’re missing some storms. rrricanes currently only holds data back to 1998; this data is considered “real-time”.

    -

    A companion package, HURDAT is available in CRAN that has data for all cyclones dating back as far as 1851. This package has less data than rrricanes. But, as it is based on a post-storm reanalysis project, the data is more accurate.

    -

    Let’s revisit the top 10 using HURDAT:

    -
    AL %>% 
-    filter(hour(DateTime) %in% c(0, 6, 12, 18), 
-           Status %in% c("TS", "HU"), 
-           !is.na(Wind)) %>% 
-    group_by(Key) %>% 
-    summarise(Name = last(Name), 
-              ACE = sum(Wind^2) * 1e-04) %>% 
-    arrange(desc(ACE)) %>% 
-    top_n(10)
    -
    ## Selecting by ACE
    -
    ## # A tibble: 10 x 3
-##    Key      Name      ACE
-##    <chr>    <chr>   <dbl>
-##  1 AL031899 UNNAMED  73.6
-##  2 AL092004 IVAN     71.5
-##  3 AL112017 IRMA     64.9
-##  4 AL091893 UNNAMED  63.5
-##  5 AL132003 ISABEL   63.3
-##  6 AL041926 UNNAMED  60.9
-##  7 AL141932 UNNAMED  59.8
-##  8 AL041906 UNNAMED  56.0
-##  9 AL041957 CARRIE   55.8
-## 10 AL091966 INEZ     54.6
    -

    A couple of things to notice here:

    -
      -
    1. in HURDAT, the common times used are 00:00, 06:00, 12:00 and 18:00 UTC
      2. -
    2. Our list is more comprehensive than the Wikipedia list as that list only measures storms after 1950.
      3. -
    -

    ACE is slightly higher and that could be for a number of reasons. For example, on re-analysis the Hurricane Research Division may have determined a cyclone was actually tropical (shown in HURDAT) when initially it was believed to be extratropical (as shown in rrricanes). Or, and more likely, they determined through additional data that a storm was actually stronger than originally though.

    -

    You can also calculate ACE for a season. Instead of grouping by Key we group by Year. I’ll stick with HURDAT in this example.

    -
    (df <- AL %>% 
-    mutate(Year = year(DateTime)) %>% 
-    filter(hour(DateTime) %in% c(0, 6, 12, 18), 
-           Status %in% c("TS", "HU"), 
-           !is.na(Wind)) %>% 
-    group_by(Year) %>% 
-    summarise(ACE = sum(Wind^2) * 1e-04) %>% 
-    arrange(desc(ACE))) %>% 
-    top_n(10)
    -
    ## Selecting by ACE
    -
    ## # A tibble: 10 x 2
-##     Year   ACE
-##    <dbl> <dbl>
-##  1  1933  259.
-##  2  2005  246.
-##  3  1893  231.
-##  4  1926  230.
-##  5  1995  228.
-##  6  2004  226.
-##  7  2017  225.
-##  8  1950  211.
-##  9  1961  205.
-## 10  1998  182.
    -

    This also matches relatively well with that on Wikipedia and other sources.

    -
    ggplot(df, aes(x = Year, y = ACE)) + 
-    geom_bar(stat = "identity") + 
-    theme_bw()
    -

    -

    It would certainly seem that tropical cyclone activity ebbs and flows over time.

    -
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    Developed by Tim Trice.

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    Site built with pkgdown 1.3.0.

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    Forecast/Advisory GIS

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    Tim Trice

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    June 11, 2017

    - - Source: vignettes/forecast_advisory.Rmd - - -
    - - - -
    library(dplyr)
-library(ggplot2)
-library(rrricanes)
-library(rrricanesdata)
-library(sp)
    - -
    fstadv <- fstadv %>% filter(Key == key, Adv <= adv)
    -
    -

    -GIS Advisory Forecast Track, Cone of Uncertainty, and Watches/Warnings

    -
    gis_adv <- gis_advisory(key = key, advisory = adv) %>% gis_download()
    -
    ## OGR data source with driver: ESRI Shapefile 
-## Source: "/tmp/Rtmpo0A76k", layer: "al092008.042_5day_lin"
-## with 2 features
-## It has 9 fields
-## OGR data source with driver: ESRI Shapefile 
-## Source: "/tmp/Rtmpo0A76k", layer: "al092008.042_5day_pgn"
-## with 2 features
-## It has 9 fields
-## OGR data source with driver: ESRI Shapefile 
-## Source: "/tmp/Rtmpo0A76k", layer: "al092008.042_5day_pts"
-## with 13 features
-## It has 20 fields
-## OGR data source with driver: ESRI Shapefile 
-## Source: "/tmp/Rtmpo0A76k", layer: "al092008.042_ww_wwlin"
-## with 5 features
-## It has 10 fields
    -

    Get bounding box of the forecast polygon.

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    bbox <- bbox(gis_adv$al092008.042_5day_pgn)
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    Generate a base plot of the Atlantic ocean.

    -
    (bp <- al_tracking_chart(color = "black", fill = "white", size = 0.1, res = 50))
    -
    ## Regions defined for each Polygons
-## Regions defined for each Polygons
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    I like to add a little cushion for the map inset and forecast cone data.

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    Build a thin tracking map for the inset.

    - -

    Modify original bp zoomed in on our area of interest.

    -
    (bp <- bp +
-     coord_equal(xlim = c(lon_min, lon_max),
-                 ylim = c(lat_min, lat_max)) +
-     scale_x_continuous(expand = c(0, 0)) +
-     scale_y_continuous(expand = c(0, 0)) +
-     labs(x = "Lon",
-          y = "Lat",
-          caption = sprintf("rrricanes %s", packageVersion("rrricanes"))))
    -
    ## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
    -

    -

    Combine bp and bp_inset to finalize initial base plot. bp will be a base plot without the inset. bpi will have the inset.

    - -

    -
    -
    -

    -Current Advisory Details

    -

    Lines and Polygons spatial dataframes can be helpfully converted using shp_to_df. The original spatial dataframes can be plotted directly in ggplot2 but, to my understanding, access to the other variables are not available.

    - -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
    -
    ## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -
    shp_storm_ww <- shp_to_df(gis_adv$al092008.042_ww_wwlin)
    -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    - -
    ## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
-
-## Warning in bind_rows_(x, .id): binding character and factor vector,
-## coercing into character vector
    -

    Points dataframes can just be converted with tibble::as_data_frame.

    - -
    ## Warning: `as_data_frame()` is deprecated, use `as_tibble()` (but mind the new semantics).
-## This warning is displayed once per session.
    -

    Modify shp_storm_pts$DVLBL with full strings and ordered factor.

    -
    shp_storm_pts$DVLBL <- factor(shp_storm_pts$DVLBL, 
-                              levels = c("D", "S", "H"), 
-                              labels = c("Tropical Depression", 
-                                         "Tropical Storm", 
-                                         "Hurricane"))
    -

    Same with shp_storm_pts$TCWW:

    -
    shp_storm_ww$TCWW <- factor(shp_storm_ww$TCWW, 
-                            levels = c("TWA", "TWR", "HWA", "HWR"), 
-                            labels = c("Tropical Storm Watch", 
-                                       "Tropical Storm Warning", 
-                                       "Hurricane Watch", 
-                                       "Hurricane Warning"))
    -
    bpi + geom_polygon(data = shp_storm_pgn, 
-                   aes(x = long, y = lat, group = group),
-                   alpha = 0.15, fill = "orange") + 
-    geom_path(data = shp_storm_lin, aes(x = long, y = lat, group = group)) + 
-    geom_point(data = shp_storm_pts, aes(x = LON, y = LAT, fill = DVLBL,
-                                         shape = DVLBL, size = MAXWIND)) + 
-    geom_path(data = shp_storm_ww, aes(x = long, y = lat, color = TCWW, 
-                                       group = group), size = 1) + 
-    scale_shape_manual(values = c(21, 21, 21, 21)) + 
-    guides(shape = guide_legend(override.aes = list(size = 3)), 
-           size = guide_legend(nrow = 1)) + 
-    theme(legend.position = "bottom", 
-          legend.box = "vertical")
    -

    -

    Very often, areas that are under a hurricane watch may also be under a tropical storm warning. The chart above does not show the hurricane watch area.

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    Developed by Tim Trice.

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    Site built with pkgdown 1.3.0.

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z4NXgjt?2U|#`mMLqMqL428QuAtoL^Q(2B{B;aLcvC{jGFD+ZU3pNMu`U{2a)kJ#9Z zR1V4BNqUW4Ov`3DvbokjKPJj<5SkD`NWZxmzu45U0%qll{aR5LCS_LysF1cNY1d5s zZcC`nVVA%I{&Ka=&PE0PWrD4iSqmaT6Li2;?|-qsJo|NH)}l8WP(4{UHp)kE1LDA( zLhhB4jn9g&yk~Jju)Q(-;Zm*W*aAN`m2RylPVj4Kma0T_&84-Vsy#XkiQ;KoOzZ~_ z1}d%FtIH_+18yVu{RgtHi}vL?)o^QIe=Qq}7MnpA2-=|AzAjf)NA`+G=6WG`BtMfNnRRrpUXJjqm4~Sf~I@*0(ss>mlsU z#>F&dEf}@oe!q}=+uT*Ui<-0>fhUH-owvxalcwub*C20RhUlV=y4Gbrsik|9#eiDF zFULJ>z(Cl4mnJX_al14-BOD{b;PNQ{!p-sHDgu3Ft3{{|vV4anc2zc)J-OaHlz)N# zWIxLKS*EM}qUQE}5}rK?G;sJ#bU8D_W@&6kq3U_o08a)Cfz9w%5fZ2&IUi4FC4WO&oFit+VTFXYB0fHm!!s z`jBA)%6Q%QDdMySo`c`{o5M$!<2ec{waZxbqK*}h|J z!Zp8TT@isNdnJe}vY|uJ^t)7dbh~swv!qKW30MG2oZFFvt&Pga`d-f3sK-Jb?+%>; zuh%!O7T?@ESuDOCkQM8&)7(T2Rd?=~E`Us)E$#J78{fmT!{gQ8?w%b`1`)F#9NR>{ z=d$90Z4OZxQlI3|ANpn=y06S682el{<7JKLE? - - - - - - -Getting Started • rrricanes - - - - - - - - - - -

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    Getting Started

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    Tim Trice

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    2019-06-22

    - - Source: vignettes/getting_started.Rmd - - -
    - - - -
    library(dplyr)
-library(rrricanes)
    -
    -

    -General Introduction

    -

    rrricanes is intended to give easy access to hurricane archives. It is a web-scraping tool that parses the National Hurricane Center’s (NHC) archives to get storm data. Data is available for storms dating back to 1998.

    -

    There are two basins which data is available: north Atlantic (“AL”) and northeastern Pacific (“EP”). The northeastern Pacific basin typically covers from the west coast of North America to -140° longitude (140°W).

    -
    -
    -

    -Get Storms

    -

    By default, get_storms will return all storms that have developed for the current year in both basins. If no storms have developed, an error will be generated. For this example, we’ll use 2012.

    -
    df.al_2012 <- get_storms(years = 2012, basins = "AL")
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    -
    -

    -Getting Storm Data

    -

    get_storm_data can be used to retrieve one or multiple products for one or more cyclones. A list of dataframes is returned.

    -
    df.al_18_2012_fstadv <- df.al_2012 %>% 
-    filter(Name == "Hurricane Sandy") %>% 
-    .$Link %>% 
-    get_storm_data(products = "fstadv")
    -

    We can get the forecast/advisory data and wind speed probabilities at once:

    -
    df.al_18_2012 <- df.al_2012 %>% 
-    filter(Name == "Hurricane Sandy") %>% 
-    .$Link %>% 
-    get_storm_data(c("fstadv", "wndprb"))
    -

    df.al_18_2012 now contains two dataframes for Hurricane Sandy; fstadv and wndprb.

    -
    -
    -

    -Forecast/Advisory Product (fstadv)

    -

    The core of a storm’s dataset is located in the Forecast/Advisory product, fstadv. This product contains current location, forecast position, movement and structural details of the cyclone.

    -

    To access only this product, we can use get_fstadv:

    - -

    As you may have noticed above, the dataframe is very wide at 149 variables. There are four groups of variables in this dataset: current details, current wind radii, forecast positions, and forecast wind radii.

    -
    -

    -Current Details

    -

    Let’s look at an example of the current details.

    -
    str(df.al_18_2012_fstadv %>% select(Status:Eye, SeasNE:SeasNW))
    -
    ## Classes 'tbl_df', 'tbl' and 'data.frame':    31 obs. of  18 variables:
-##  $ Status  : chr  "Tropical Depression" "Tropical Storm" "Tropical Storm" "Tropical Storm" ...
-##  $ Name    : chr  "Eighteen" "Sandy" "Sandy" "Sandy" ...
-##  $ Adv     : num  1 2 3 4 5 6 7 8 9 10 ...
-##  $ Date    : POSIXct, format: "2012-10-22 15:00:00" "2012-10-22 21:00:00" ...
-##  $ Key     : chr  "AL182012" "AL182012" "AL182012" "AL182012" ...
-##  $ Lat     : num  13.5 12.5 12.7 13.3 13.8 14.3 15.2 16.3 17.1 18.3 ...
-##  $ Lon     : num  -78 -78.5 -78.6 -78.6 -77.8 -77.6 -77.2 -77 -76.7 -76.6 ...
-##  $ Wind    : num  25 35 40 40 45 45 50 60 70 70 ...
-##  $ Gust    : num  35 45 50 50 55 55 60 75 85 85 ...
-##  $ Pressure: num  1003 999 998 998 993 ...
-##  $ PosAcc  : num  45 50 25 40 30 30 20 20 20 20 ...
-##  $ FwdDir  : num  230 NA NA 360 20 20 15 10 15 10 ...
-##  $ FwdSpeed: num  4 NA NA 3 4 5 9 12 11 12 ...
-##  $ Eye     : num  NA NA NA NA NA NA 25 NA NA NA ...
-##  $ SeasNE  : num  NA 60 60 70 75 90 180 180 180 180 ...
-##  $ SeasSE  : num  NA 60 45 80 60 90 180 180 240 240 ...
-##  $ SeasSW  : num  NA 0 0 0 0 0 0 45 0 0 ...
-##  $ SeasNW  : num  NA 0 45 50 50 50 0 100 90 90 ...
    -

    The most important variable in this dataset is Key. Key is a unique identifier for each storm that develops in either basin. It is formatted such as “AABBCCCC” where “AA” is the basin abbreviation (AL or EP), “BB” is the year number of the storm left-padded, and “CC” is the year of the storm.

    -

    Adv is the second-most important variable here. You’ll notice it is in character format. For regularly-scheduled advisories, advisory numbers are always numeric. However, when watches and warnings are in effect, intermediate advisories are issued which are given alpha suffixes; i.e., 1, 2, 3, 3A, 4, 4A, 4B, 5, etc.

    -

    Only the Public Advisory (public) will be issued more frequently. All other regular products (discus, fstadv, prblty, wndprb) are generally issued every six hours.

    -

    Status lists the current designation of the cyclone, i.e., Tropical Depression, Tropical Storm, etc. A Name is given once a storm crosses the threshold of Tropical Storm; that is, winds greater than 33kts.

    -

    Lat and Lon are the current position of the storm within PosAcc nautical miles. All distance measurements are in nautical miles.

    -

    Wind and Gust are current one-minute sustained wind speeds in knots (kts). You can use the function knots_to_mph to convert this. All wind speed values are in knots.

    -

    Pressure is the lowest atmospheric pressure of the cyclone either measured or estimated. It’s value is in millibars but you can use mb_to_in() to convert to inches.

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    FwdDir and FwdSpeed show the compass direction of the forward movement of the cyclone. NA values indicate the storm is stationary or drifting. FwdSpeed is measured in knots.

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    In some cases, where hurricanes have an identifiable Eye, it’s diameter in nautical miles will also be listed.

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    Lastly, the Seas variables will exist for a storm of at least tropical storm-strength. This is the distance from the center of circulation that 12ft seas can be found in each quadrant. The measurement is in nautical miles.

    -

    Helper function tidy_fstadv will subset this data to a narrow dataframe.

    -
    tidy_fstadv(df.al_18_2012_fstadv)
    -
    ## Warning: `tidy_fstadv is deprecated and will be removed in v0.2.2
    -
    ## # A tibble: 31 x 18
-##    Key     Adv Date                Status Name    Lat   Lon  Wind  Gust
-##    <chr> <dbl> <dttm>              <chr>  <chr> <dbl> <dbl> <dbl> <dbl>
-##  1 AL18…     1 2012-10-22 15:00:00 Tropi… Eigh…  13.5 -78      25    35
-##  2 AL18…     2 2012-10-22 21:00:00 Tropi… Sandy  12.5 -78.5    35    45
-##  3 AL18…     3 2012-10-23 03:00:00 Tropi… Sandy  12.7 -78.6    40    50
-##  4 AL18…     4 2012-10-23 09:00:00 Tropi… Sandy  13.3 -78.6    40    50
-##  5 AL18…     5 2012-10-23 15:00:00 Tropi… Sandy  13.8 -77.8    45    55
-##  6 AL18…     6 2012-10-23 21:00:00 Tropi… Sandy  14.3 -77.6    45    55
-##  7 AL18…     7 2012-10-24 03:00:00 Tropi… Sandy  15.2 -77.2    50    60
-##  8 AL18…     8 2012-10-24 09:00:00 Tropi… Sandy  16.3 -77      60    75
-##  9 AL18…     9 2012-10-24 15:00:00 Hurri… Sandy  17.1 -76.7    70    85
-## 10 AL18…    10 2012-10-24 21:00:00 Hurri… Sandy  18.3 -76.6    70    85
-## # … with 21 more rows, and 9 more variables: Pressure <dbl>, PosAcc <dbl>,
-## #   FwdDir <dbl>, FwdSpeed <dbl>, Eye <dbl>, SeasNE <dbl>, SeasSE <dbl>,
-## #   SeasSW <dbl>, SeasNW <dbl>
    -
    -
    -

    -Wind Radius

    -

    Any cyclone of at least tropical storm-strength will have associated wind radius values. This is the distance from the center of circulation that a specified wind speed (34kts, 50kts, 64kts) can be found in each quadrant. Measurement is in nautical miles.

    -
    str(df.al_18_2012_fstadv %>% select(NE64:NW34))
    -
    ## Classes 'tbl_df', 'tbl' and 'data.frame':    31 obs. of  12 variables:
-##  $ NE64: num  NA NA NA NA NA NA NA NA 20 25 ...
-##  $ SE64: num  NA NA NA NA NA NA NA NA 20 20 ...
-##  $ SW64: num  NA NA NA NA NA NA NA NA 0 0 ...
-##  $ NW64: num  NA NA NA NA NA NA NA NA 0 0 ...
-##  $ NE50: num  NA NA NA NA NA NA 0 50 50 50 ...
-##  $ SE50: num  NA NA NA NA NA NA 80 70 60 60 ...
-##  $ SW50: num  NA NA NA NA NA NA 0 0 30 40 ...
-##  $ NW50: num  NA NA NA NA NA NA 0 0 30 40 ...
-##  $ NE34: num  NA 50 50 70 70 80 90 100 110 110 ...
-##  $ SE34: num  NA 60 60 80 80 90 120 120 120 120 ...
-##  $ SW34: num  NA 0 0 0 0 0 0 45 60 70 ...
-##  $ NW34: num  NA 0 0 0 0 0 30 45 60 60 ...
    -

    A helper function, tidy_wr will reorganize this data into a narrow format and tidied up. Complete wind radius values that are NA are removed for efficiency.

    -
    tidy_wr(df.al_18_2012_fstadv)
    -
    ## # A tibble: 77 x 8
-##    Key        Adv Date                WindField    NE    SE    SW    NW
-##    <chr>    <dbl> <dttm>                  <dbl> <dbl> <dbl> <dbl> <dbl>
-##  1 AL182012     2 2012-10-22 21:00:00        34    50    60     0     0
-##  2 AL182012     3 2012-10-23 03:00:00        34    50    60     0     0
-##  3 AL182012     4 2012-10-23 09:00:00        34    70    80     0     0
-##  4 AL182012     5 2012-10-23 15:00:00        34    70    80     0     0
-##  5 AL182012     6 2012-10-23 21:00:00        34    80    90     0     0
-##  6 AL182012     7 2012-10-24 03:00:00        34    90   120     0    30
-##  7 AL182012     7 2012-10-24 03:00:00        50     0    80     0     0
-##  8 AL182012     8 2012-10-24 09:00:00        34   100   120    45    45
-##  9 AL182012     8 2012-10-24 09:00:00        50    50    70     0     0
-## 10 AL182012     9 2012-10-24 15:00:00        34   110   120    60    60
-## # … with 67 more rows
    -
    -
    -

    -Forecast

    -

    Most Forecast/Advisory products will have forecast data associated with it unless the storm has dissipated or is no longer tropical. There may be up to seven forecast positions. These positions are issued by 12-hour intervals through 48 hours where they are then at 24-hour intervals; 12, 24, 36, 48, 72, 96 and 120 hours.

    -
    str(df.al_18_2012_fstadv %>% select(Hr12FcstDate:Hr12Gust))
    -

    Notice each variable begins with the prefix “Hrn” where n is the forecast period as noted above. Only Date, Lat, Lon, Wind, Gust and wind radius (will discuss shortly) are given for forecast periods.

    -

    Use tidy_fcst to tidy forecast data.

    -
    tidy_fcst(df.al_18_2012_fstadv)
    -
    ## # A tibble: 216 x 8
-##    Key     Adv Date                FcstDate              Lat   Lon  Wind
-##    <chr> <dbl> <dttm>              <dttm>              <dbl> <dbl> <dbl>
-##  1 AL18…     1 2012-10-22 15:00:00 2012-10-23 00:00:00  13.7 -78.3    35
-##  2 AL18…     1 2012-10-22 15:00:00 2012-10-23 12:00:00  14.3 -78.1    45
-##  3 AL18…     1 2012-10-22 15:00:00 2012-10-24 00:00:00  15.7 -77.6    55
-##  4 AL18…     1 2012-10-22 15:00:00 2012-10-24 12:00:00  17.4 -77      60
-##  5 AL18…     1 2012-10-22 15:00:00 2012-10-25 12:00:00  20.5 -76      55
-##  6 AL18…     1 2012-10-22 15:00:00 2012-10-26 12:00:00  24.5 -74.5    55
-##  7 AL18…     1 2012-10-22 15:00:00 2012-10-27 12:00:00  27   -73      50
-##  8 AL18…     2 2012-10-22 21:00:00 2012-10-23 06:00:00  13.6 -78.5    35
-##  9 AL18…     2 2012-10-22 21:00:00 2012-10-23 18:00:00  14.9 -78.3    45
-## 10 AL18…     2 2012-10-22 21:00:00 2012-10-24 06:00:00  16.4 -77.8    55
-## # … with 206 more rows, and 1 more variable: Gust <dbl>
    -
    -

    -Forecast Dates/Times

    -

    A note about forecast times.

    -
    df.al_18_2012_fstadv %>% select(Date, Hr12FcstDate) %>% slice(1)
    -
    ## # A tibble: 1 x 2
-##   Date                Hr12FcstDate       
-##   <dttm>              <dttm>             
-## 1 2012-10-22 15:00:00 2012-10-23 00:00:00
    -

    Notice the Date of this advisory is Oct 22 at 15:00 UTC. The Hr12FcstDate is Oct 23, 00:00 UTC. This difference, obviously, is not 12 hours. What gives? Forecast/Advisory products are issued with two “current” positions: one that is current (and provided in the dataset) and a position from three hours prior. So, in this specific advisory the text would contain the position of the storm for Oct 22, 12:00 UTC. It is from this position the forecast points are based. I do not know why.

    -

    Therefore, while officially the forecast periods are 12, 24, 36, … hours, in reality they are 9, 21, 33, … hours from the issuance time of the product.

    -
    -
    -
    -

    -Forecast Wind Radius

    -

    Some forecast positions may also contain wind radius information (only up to 72 hours).

    -
    str(df.al_18_2012_fstadv %>% select(Hr12NE64:Hr12NW34))
    -

    Again, these variables are prepended with the prefix prefix “Hrn” where n notes the forecast period.

    -

    tidy_fcst_wr will tidy this subset of data.

    -
    tidy_fcst_wr(df.al_18_2012_fstadv)
    -
    ## # A tibble: 337 x 9
-##    Key     Adv Date                FcstDate            WindField    NE
-##    <chr> <dbl> <dttm>              <dttm>                  <dbl> <dbl>
-##  1 AL18…     1 2012-10-22 15:00:00 2012-10-23 00:00:00        34    40
-##  2 AL18…     1 2012-10-22 15:00:00 2012-10-23 12:00:00        34    50
-##  3 AL18…     1 2012-10-22 15:00:00 2012-10-24 00:00:00        34    80
-##  4 AL18…     1 2012-10-22 15:00:00 2012-10-24 00:00:00        50    30
-##  5 AL18…     1 2012-10-22 15:00:00 2012-10-24 12:00:00        34    90
-##  6 AL18…     1 2012-10-22 15:00:00 2012-10-24 12:00:00        50    40
-##  7 AL18…     1 2012-10-22 15:00:00 2012-10-25 12:00:00        34   200
-##  8 AL18…     1 2012-10-22 15:00:00 2012-10-25 12:00:00        50    50
-##  9 AL18…     2 2012-10-22 21:00:00 2012-10-23 06:00:00        34    50
-## 10 AL18…     2 2012-10-22 21:00:00 2012-10-23 18:00:00        34    50
-## # … with 327 more rows, and 3 more variables: SE <dbl>, SW <dbl>, NW <dbl>
    -

    Please see the National Hurricane Center’s website for more information on understanding the Forecast/Advisory product.

    -
    -
    -
    -

    -Strike Probabilities (prblty)

    -

    Strike probabilities were discontinued after the 2005 hurricane season (replaced by Wind Speed Probabilities; wndprb). For this example, we’ll look at Hurricane Katrina. For this we use the function get_prblty.

    -
    df.al_12_2005_prblty <- get_storms(year = 2005, basin = "AL") %>% 
-    filter(Name == "Hurricane Katrina") %>% 
-    .$Link %>% 
-    get_prblty()
    -
    str(df.al_12_2005_prblty)
    -
    ## Classes 'tbl_df', 'tbl' and 'data.frame':    937 obs. of  10 variables:
-##  $ Status  : chr  "Tropical Depression" "Tropical Depression" "Tropical Depression" "Tropical Depression" ...
-##  $ Name    : chr  "Twelve" "Twelve" "Twelve" "Twelve" ...
-##  $ Adv     : chr  "1" "1" "1" "1" ...
-##  $ Date    : POSIXct, format: "2005-08-23 21:00:00" "2005-08-23 21:00:00" ...
-##  $ Location: chr  "25.0N  77.7W" "JACKSONVILLE FL" "25.7N  78.5W" "SAVANNAH GA" ...
-##  $ A       : num  50 0 36 0 19 0 0 0 0 0 ...
-##  $ B       : num  0 0 0 0 6 0 1 0 0 5 ...
-##  $ C       : num  0 2 0 0 1 0 0 0 0 3 ...
-##  $ D       : num  0 9 1 6 1 3 3 2 2 5 ...
-##  $ E       : num  50 11 37 6 27 3 4 2 2 13 ...
    -

    This dataframe contains the possibility of a cyclone passing within 65 nautical miles of Location. The variables A, B, C, D, and E are as they appear in the products and were left as-is to avoid confusion. They’re definition is as follows:

    -
      -
    • -A - current through 12 hours.
      • -
    • -B - within the next 12-24 hours
      • -
    • -C - within the next 24-36 hours
      • -
    • -D - within the next 36-48 hours
      • -
    • -E - Total probability from current through 48 hours.
      • -
    -

    Many values in the text product may be “X” for less than 1% chance of a strike. These values are converted to 0 as the fields are numeric.

    -

    The strike probability products did not contain Key which is the unique identifier for every cyclone. So the best way to do any joins will be by Name, Adv and Date.

    -

    Strike Probabilities may not exist for most Pacific cyclones.

    -
    -
    -

    -Wind Speed Probabilities (wndprb)

    - -
    str(df.al_18_2012_wndprb)
    -
    ## Classes 'tbl_df', 'tbl' and 'data.frame':    2227 obs. of  18 variables:
-##  $ Key       : chr  "AL182012" "AL182012" "AL182012" "AL182012" ...
-##  $ Adv       : num  1 1 1 1 1 1 1 1 1 1 ...
-##  $ Date      : POSIXct, format: "2012-10-22 15:00:00" "2012-10-22 15:00:00" ...
-##  $ Location  : chr  "FT PIERCE FL" "W PALM BEACH" "MIAMI FL" "MARATHON FL" ...
-##  $ Wind      : num  34 34 34 34 34 34 34 50 64 34 ...
-##  $ Wind12    : num  0 0 0 0 0 0 0 0 0 0 ...
-##  $ Wind24    : num  0 0 0 0 1 0 0 0 0 0 ...
-##  $ Wind24Cum : num  0 0 0 0 1 0 0 0 0 0 ...
-##  $ Wind36    : num  0 0 0 0 1 0 0 0 0 0 ...
-##  $ Wind36Cum : num  0 0 0 0 2 0 0 0 0 0 ...
-##  $ Wind48    : num  0 0 0 0 1 0 0 0 0 0 ...
-##  $ Wind48Cum : num  0 0 0 0 3 0 0 0 0 0 ...
-##  $ Wind72    : num  0 0 0 0 0 0 3 0 0 5 ...
-##  $ Wind72Cum : num  0 0 0 0 3 0 3 0 0 5 ...
-##  $ Wind96    : num  1 2 3 2 0 5 10 3 1 12 ...
-##  $ Wind96Cum : num  1 2 3 2 3 5 13 3 1 17 ...
-##  $ Wind120   : num  2 2 1 1 0 3 5 2 0 3 ...
-##  $ Wind120Cum: num  3 4 4 3 3 8 18 5 1 20 ...
    -

    Wind Speed Probabilities are a bit more advanced than their predecessor. The Wind variable is for 34kt, 50kt and 64kt winds expected within a specific time period.

    -

    Each consecutive variable is within a specific time-frame (12, 24, 36, 48, 72, 96 and 120 hours) for both that time frame and cumulative.

    -

    For example, Wind24 is the chance of Wind between 12-24 hours. Wind24Cum is the cumulative probability from Date through 24 hours.

    -

    As with strike probabilities, an “X” in the original text product meant less than 0.5% chance for the specified wind in the specified time period. “X” has been replaced by 0 in this package.

    -

    Wind Speed Probabilities may not exist for most Pacific cyclones.

    -

    See Tropical Cyclone Wind Speed Probabilities Products for more information.

    -
    -
    -

    -Other products

    -

    Other products are available:

    -
      -

    • get_public for Public Advisory statements. Think general information for the public audience. May not exist for some Pacific cyclones. Additionally, when watches and warnings are issued, these are issued every 3 hours (and, in some cases, every two).

      • -

    • get_discus for Storm Discussions. These are more technical statements on the structure of a storm, forecast model tendencies and satellite presentation.

      • -

    • get_update These are brief update statements when something considerable has changed in the cyclone or if the cyclone is making landfall.

      • -

    • get_posest. Position estimates are generally issued when a storm is making landfall and may be issued hourly.

      • -
    -

    Hurricane Ike, 2008, has both updates and position estimates.

    -

    At this time none of these products are parsed. Only the content of the product is returned.

    -
    -
    - - - -
    - - -
    -

    Developed by Tim Trice.

    -
    - -
    -

    Site built with pkgdown 1.3.0.

    -
    -
    -
    - - - - - diff --git a/docs/articles/gis_data.html b/docs/articles/gis_data.html deleted file mode 100644 index 78ab10c2..00000000 --- a/docs/articles/gis_data.html +++ /dev/null @@ -1,1206 +0,0 @@ - - - - - - - -Retrieving and Plotting GIS Data • rrricanes - - - - - - - - - - -
    -
    - - - -
    -
    -
    -

    Retrieving and Plotting GIS Data

    -

    Tim Trice

    - -

    2019-06-22

    - - Source: vignettes/gis_data.Rmd - - -
    - - - -
    library(dplyr)
-library(ggplot2)
-library(rrricanes)
-library(sf)
    -

    Most storms will contain a variation of GIS datasets that can be plotted with ggplot2. The helper functions for this have the prefix ‘gis’.

    -

    All products are experimental and there maybe fluctuations particularly in current datasets.

    -

    In general, datasets are available for storms dated back to 1998. However, products such as Wind Speed Probabilities only go back to 1999.

    -

    Some datasets require the use of the storm key and an optional advisory. Other products require a datetime value and cannot be isolated by storm key or advisory. The datetime values are not based on the issue time of the advisory, but rather three hours prior. For example, if you are seeking a dataset where the forecast/advisory was issued at 9:00AM UTC, you will want the dataset for 6:00AM UTC. This will be explained a little further below.

    -
    -

    -Build a Tracking Chart

    -

    As of version 0.2.7, the built-in tracking chart functions have been removed. Users are encouraged to use the rnaturalearthdata and associated packages to build tracking charts.

    -

    The rnaturalearthdata package has many shapefile datasets that can be used to make maps. For this article I will only need countries and states. I will use the resolution of 10 nautical miles (available in the rnaturalearthhires package). Each dataset is named countries10 and states10.

    - -

    -

    I’ll also remove the padding around the plot and change the color of the seas (panel.background).

    - -

    -
    -
    -

    -GIS Datasets

    -

    There are several datasets that are published for active cyclones. The following functions are designed to return the URL to those datasets:

    -
      -
    • gis_advisory
      • -
    • gis_prob_storm_surge
      • -
    • gis_windfield
      • -
    • -gis_latest (only for active storms)
      • -
    -

    It’s important to note that not every storm will have a dataset available. Nor are datasets consistent from one storm to the next. For example, as we’ll see below, a forecast cone should have two polygons for a 72-hour and 120-hour forecast; in this example, they are both 120-hours.

    -

    Let’s take a look at Hurricane Matthew (AL142016) and focus on advisory 37.

    - -
    -

    -Data Scraping

    -

    The functions listed above do not retrieve the data. They only return the URLs. This is to give you the opportunity to modify your requests to get the specific data needed, if it exists.

    -
    -

    -gis_advisory -

    -

    The gis_advisory function returns the URL for the GIS dataset by key and advisory number. Remember, a storm’s key should always be eight alphanumeric characters;

    -
      -

    • Basin identifier (“AL”, “CP”, or “EP”)

      • -

    • Storm number for the year

      • -

    • The four digit year

      • -
    -

    The fstadv product will always have the storm key. In earlier years, the “year” portion of the key was only the year without the century; you will need to add it.

    -
    args(gis_advisory)
    -
    ## function (key, advisory = as.character()) 
-## NULL
    -

    We can test that an advisory package does exist for our specific advisory.

    -
    gis_advisory(key = key, advisory = adv)
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al142016_5day_037.zip"
    -

    This should work.

    -
    -
    -

    -gis_windfield -

    -

    The gis_windfield product is relatively new so it may not exist for some storms. As with gis_advisory, we only need the storms’ key and advisory.

    -
    args(gis_windfield)
    -
    ## function (key, advisory = as.character()) 
-## NULL
    -
    gis_windfield(key = key, advisory = adv)
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/al142016_fcst_037.zip"
    -
    -
    -

    -gis_prob_storm_surge -

    -

    The function gis_prob_storm_surge also uses the key variable, but not the advisory; instead, it uses datetime.

    -

    There are two types of products that can be retrieved, “esurge” and “psurge”. psurge shows the probability of a specific height (in feet) of storm surge affecting an area. Values between 0 and 20 can be used.

    - -

    In the example above, we are requesting the probabilities of a 5-foot storm surge affecting the coastline and inland waterways.

    -

    esurge shows the probability of a specific storm surge height exceeding the forecast height. Valid values are 10, 20, 30, 04, and 50. Note the commented section in the code above.

    -

    The products parameter expects a list, though you do not need to include both products. Additionally, each product expects a numeric or numeric vector. If you make a broad general request, the National Hurricane Center requests no more than 80 requests per 10 seconds, so please be respectful. Unlike retrieving text products, there is no throttle in this package to download GIS datasets.

    -

    Regarding datetime, this value should be that of the advisory time minus 3 hours not including minutes and seconds. Let’s get that value for Matthew’s #37 advisory.

    -
    datetime <- 
-  get_storms(years = "2016", basins = "AL") %>% 
-  filter(Name == "Hurricane Matthew") %>% 
-  pull(Link) %>% 
-  get_fstadv() %>% 
-  filter(Adv == adv) %>% 
-  pull(Date)
    -
    ## Registered S3 method overwritten by 'httr':
-##   method                 from
-##   as.character.form_file crul
    - -
    ## [1] "2016100706"
    -

    Let’s make sure we can get a psurge 5 product for this datetime value.

    -
    gis_prob_storm_surge(key = key, products = list(psurge = 5), datetime = datetime)
    -
    ## [1] "https://www.nhc.noaa.gov/gis/storm_surge/al142016_psurge5_2016100706.zip"
    -

    Looks good.

    -
    -
    -gis_wsp -
    -

    Wind speed probabilities exist in the gis_wsp datasets. Like gis_prob_storm_surge, we will need datetime, but we will not need key. The last parameter is res (resolution). Valid values are 5, 0.5, and 0.1 degrees. The default is all three. Not all resolutions will be available for all storms.

    -
    args(gis_wsp)
    -
    ## function (datetime, res = c(5, 0.5, 0.1)) 
-## NULL
    -
    # List of datasets for 5-degree resolution
-gis_wsp(datetime = datetime, res = 0.5)
    -
    ## [1] "https://www.nhc.noaa.gov/gis/forecast/archive/2016100706_wsp_120hrhalfDeg.zip"
    -
    -
    -
    -

    -Downloading Data

    -

    Now that we’ve explored the various functions, let’s go about downloading the datasets to plot. For efficiency, I use a lot of purrr mapping functions here, loading each step into one variable.

    -

    First, I want to load all of my URLs into one vector.

    - -

    Previously, gis_download would download the datasets, extract the shapefiles and convert them, if possible, into dataframes. Thankfully, this is no longer necessary with various improvements in the sp and ggplot2 packages. Now, the gis_download function will only download the zip files into a specified directory. For this vignette, we’ll use a temporary directory, tempdir.

    - -
    ##  [1] "al142016-037_5day_lin.dbf"                
-##  [2] "al142016-037_5day_pgn.dbf"                
-##  [3] "al142016-037_5day_pts.dbf"                
-##  [4] "al142016-037_ww_wwlin.dbf"                
-##  [5] "al142016-037_5day_lin.prj"                
-##  [6] "al142016-037_5day_pgn.prj"                
-##  [7] "al142016-037_5day_pts.prj"                
-##  [8] "al142016-037_ww_wwlin.prj"                
-##  [9] "al142016-037_5day_lin.shp"                
-## [10] "al142016-037_5day_pgn.shp"                
-## [11] "al142016-037_5day_pts.shp"                
-## [12] "al142016-037_ww_wwlin.shp"                
-## [13] "al142016-037_5day_lin.shx"                
-## [14] "al142016-037_5day_pgn.shx"                
-## [15] "al142016-037_5day_pts.shx"                
-## [16] "al142016-037_ww_wwlin.shx"                
-## [17] "al142016-037_5day_lin.shp.xml"            
-## [18] "al142016-037_5day_pgn.shp.xml"            
-## [19] "al142016-037_5day_pts.shp.xml"            
-## [20] "al142016-037_ww_wwlin.shp.xml"            
-## [21] "al142016_2016100706_forecastradii.dbf"    
-## [22] "al142016_2016100706_forecastradii.prj"    
-## [23] "al142016_2016100706_forecastradii.shp"    
-## [24] "al142016_2016100706_forecastradii.shp.xml"
-## [25] "al142016_2016100706_forecastradii.shx"    
-## [26] "al142016_2016100706_initialradii.dbf"     
-## [27] "al142016_2016100706_initialradii.prj"     
-## [28] "al142016_2016100706_initialradii.shp"     
-## [29] "al142016_2016100706_initialradii.shp.xml" 
-## [30] "al142016_2016100706_initialradii.shx"     
-## [31] "al142016_2016100706_gt5.dbf"              
-## [32] "al142016_2016100706_gt5.prj"              
-## [33] "al142016_2016100706_gt5.shx"              
-## [34] "al142016_2016100706_gt5.txt"              
-## [35] "al142016_2016100706_gt5.ave"              
-## [36] "al142016_2016100706_gt5.shp.xml"          
-## [37] "al142016_2016100706_gt5.shp"              
-## [38] "2016100706_wsp34knt120hr_halfDeg.dbf"     
-## [39] "2016100706_wsp34knt120hr_halfDeg.prj"     
-## [40] "2016100706_wsp34knt120hr_halfDeg.shp"     
-## [41] "2016100706_wsp34knt120hr_halfDeg.shp.xml" 
-## [42] "2016100706_wsp34knt120hr_halfDeg.shx"     
-## [43] "2016100706_wsp34knt120hr_halfDeg.txt"     
-## [44] "2016100706_wsp50knt120hr_halfDeg.dbf"     
-## [45] "2016100706_wsp50knt120hr_halfDeg.prj"     
-## [46] "2016100706_wsp50knt120hr_halfDeg.shp"     
-## [47] "2016100706_wsp50knt120hr_halfDeg.shp.xml" 
-## [48] "2016100706_wsp50knt120hr_halfDeg.shx"     
-## [49] "2016100706_wsp50knt120hr_halfDeg.txt"     
-## [50] "2016100706_wsp64knt120hr_halfDeg.dbf"     
-## [51] "2016100706_wsp64knt120hr_halfDeg.prj"     
-## [52] "2016100706_wsp64knt120hr_halfDeg.shp"     
-## [53] "2016100706_wsp64knt120hr_halfDeg.shp.xml" 
-## [54] "2016100706_wsp64knt120hr_halfDeg.shx"     
-## [55] "2016100706_wsp64knt120hr_halfDeg.txt"
    -

    There are a lot of files here. Thankfully, we only care about the shapefiles (marked by the “.shp” extension). Let’s filter those.

    -
    # Filter out shapefiles
-shp_files <- grep(".shp$", file_list, value = TRUE)
-shp_files
    -
    ##  [1] "al142016-037_5day_lin.shp"            
-##  [2] "al142016-037_5day_pgn.shp"            
-##  [3] "al142016-037_5day_pts.shp"            
-##  [4] "al142016-037_ww_wwlin.shp"            
-##  [5] "al142016_2016100706_forecastradii.shp"
-##  [6] "al142016_2016100706_initialradii.shp" 
-##  [7] "al142016_2016100706_gt5.shp"          
-##  [8] "2016100706_wsp34knt120hr_halfDeg.shp" 
-##  [9] "2016100706_wsp50knt120hr_halfDeg.shp" 
-## [10] "2016100706_wsp64knt120hr_halfDeg.shp"
    -

    We can use sf::st_read to read in each shapefile as a shapefile dataframe. The output is quite verbose; you can pass the parameter quiet as TRUE.

    - -
    ## Reading layer `al142016-037_5day_lin' from data source `/tmp/RtmplcF52d/al142016-037_5day_lin.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 2 features and 7 fields
-## geometry type:  LINESTRING
-## dimension:      XY
-## bbox:           xmin: -80.6 ymin: 27 xmax: -74.5 ymax: 33.1
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016-037_5day_pgn' from data source `/tmp/RtmplcF52d/al142016-037_5day_pgn.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 2 features and 7 fields
-## geometry type:  POLYGON
-## dimension:      XY
-## bbox:           xmin: -81.4783 ymin: 23.15623 xmax: -71.83253 ymax: 34.47927
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016-037_5day_pts' from data source `/tmp/RtmplcF52d/al142016-037_5day_pts.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 14 features and 23 fields
-## geometry type:  POINT
-## dimension:      XY
-## bbox:           xmin: -80.6 ymin: 27 xmax: -74.5 ymax: 33.1
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016-037_ww_wwlin' from data source `/tmp/RtmplcF52d/al142016-037_ww_wwlin.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 10 features and 8 fields
-## geometry type:  LINESTRING
-## dimension:      XY
-## bbox:           xmin: -83.17 ymin: 23.75 xmax: -76.13 ymax: 34.44
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016_2016100706_forecastradii' from data source `/tmp/RtmplcF52d/al142016_2016100706_forecastradii.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 16 features and 11 fields
-## geometry type:  POLYGON
-## dimension:      XY
-## bbox:           xmin: -82.89683 ymin: 25.85747 xmax: -71.57337 ymax: 35.94275
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016_2016100706_initialradii' from data source `/tmp/RtmplcF52d/al142016_2016100706_initialradii.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 3 features and 11 fields
-## geometry type:  POLYGON
-## dimension:      XY
-## bbox:           xmin: -82.01794 ymin: 26.16483 xmax: -77.13445 ymax: 30.62306
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `al142016_2016100706_gt5' from data source `/tmp/RtmplcF52d/al142016_2016100706_gt5.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 99 features and 2 fields
-## geometry type:  MULTIPOLYGON
-## dimension:      XY
-## bbox:           xmin: -82.75004 ymin: 27.54227 xmax: -76.7436 ymax: 35.57721
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371200 +b=6371200 +no_defs
-## Reading layer `2016100706_wsp34knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp34knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 4367 features and 2 fields
-## geometry type:  POINT
-## dimension:      XY
-## bbox:           xmin: -87 ymin: 6 xmax: 128.5 ymax: 43.5
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
-## Reading layer `2016100706_wsp50knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp50knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 2302 features and 2 fields
-## geometry type:  POINT
-## dimension:      XY
-## bbox:           xmin: -86 ymin: 8 xmax: 127 ymax: 42
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
-## Reading layer `2016100706_wsp64knt120hr_halfDeg' from data source `/tmp/RtmplcF52d/2016100706_wsp64knt120hr_halfDeg.shp' using driver `ESRI Shapefile'
-## Simple feature collection with 1367 features and 2 fields
-## geometry type:  POINT
-## dimension:      XY
-## bbox:           xmin: -83 ymin: 12 xmax: 126.5 ymax: 39
-## epsg (SRID):    NA
-## proj4string:    +proj=longlat +a=6371.229 +b=6371.229 +no_defs
    -

    And, while not necessary, I will rename the list of dataframes, shp_df, to the names of their respective shapefiles minus the file extension.

    - -
    ##  [1] "al142016-037_5day_lin"            
-##  [2] "al142016-037_5day_pgn"            
-##  [3] "al142016-037_5day_pts"            
-##  [4] "al142016-037_ww_wwlin"            
-##  [5] "al142016_2016100706_forecastradii"
-##  [6] "al142016_2016100706_initialradii" 
-##  [7] "al142016_2016100706_gt5"          
-##  [8] "2016100706_wsp34knt120hr_halfDeg" 
-##  [9] "2016100706_wsp50knt120hr_halfDeg" 
-## [10] "2016100706_wsp64knt120hr_halfDeg"
    -

    This next stop is also not necessary. I actually found it a bit broad and rarely used it but will leave it here as an example.

    -

    Each shapefile has a bounding box; this box is a zoomed-in coordinate map of each dataset. We can access the bounding box of each dataset with the sf::st_bbox function.

    -

    For example, in our advisory package we have the forecast cones (a polygon shapefile). Let’s see what the bounding box is for that dataset.

    -
    sf::st_bbox(shp_df$`al142016-037_5day_pgn`)
    -
    ##      xmin      ymin      xmax      ymax 
-## -81.47830  23.15623 -71.83253  34.47927
    -

    Our data is contained between approximately 71°W and 81°W (note the negatives – the western hemisphere), and between 23°N and 34°N. Let’s see where that is.

    -
    p + 
-  coord_sf(
-    xlim = c(
-      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmin, 
-      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$xmax
-    ), 
-    ylim = c(
-      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymin, 
-      sf::st_bbox(shp_df$`al142016-037_5day_pgn`)$ymax
-    )
-  )
    -

    -

    Nice!

    -

    I want to find the largest bounding box within the datasets for my map. For this, I calculate the area for each box of each dataset, identify which has the largest area then extract the bounding box for that dataset.

    -

    Notice I only search the advisory package datasets for a bounding box. The probability datasets may contain data for other cyclones across the world making our bounding box (and subsequent maps) quite wide. I have no interest in that so kept the focus only on Matthew.

    - -
    ##      xmin      ymin      xmax      ymax 
-## -81.47830  23.15623 -71.83253  34.47927
    -
    -
    -
    -

    -Advisory Package

    -

    Each dataset returned by the gis_advisory function should contain four datasets.

    -
      -

    • 5day_lin - A line plot of the forecast (previous track not included)

      • -

    • 5day_pgn - A polygon identifying the forecast cone or area the center of the storm could travel within a given period of time.

      • -

    • 5day_pts - A points dataframe identifying the current location and each forecast position.

      • -

    • ww_wwlin - Any existing watches and warnings.

      • -
    -

    Let’s go ahead and create a plot and then I’ll explain in detail what I’m doing here.

    -
    p + 
-  # Despite two forecast periods, the cones are identical for both.
-  geom_sf(
-    data = shp_df$`al142016-037_5day_lin`,
-    aes(geometry = geometry)
-  ) +
-  geom_point(
-    data = shp_df$`al142016-037_5day_pts`,
-    aes(
-      x = .data$LON,
-      y = .data$LAT,
-      fill = .data$DVLBL,
-      shape = .data$DVLBL,
-      size = .data$MAXWIND
-    )
-  ) +
-  geom_sf(
-    data = shp_df$`al142016-037_ww_wwlin`,
-    aes(
-      geometry = .data$geometry,
-      color = factor(.data$TCWW)
-    ),
-    size = 2,
-    # key_glyph available as of ggplot 3.2.0
-    key_glyph = draw_key_path
-  ) +
-  geom_sf(
-    data = shp_df$`al142016-037_5day_pgn`, 
-    aes(
-      geometry = geometry,
-    ), 
-    color = "antiquewhite3", 
-    fill = "transparent"
-  ) +
-  scale_shape_manual(name = "Status", values = c(rep(21, 4))) +
-  scale_fill_discrete(name = "Status") +
-  scale_size_continuous(name = "Wind (kts)") +
-  scale_color_manual(
-    name = "Watches/Warnings",
-    limits = c("TWA", "TWR", "HWA", "HWR"),
-    values = c("orange", "blue", "pink", "red"),
-    labels = c(
-      "Tropical Storm Watch",
-      "Tropical Storm Warning",
-      "Hurricane Watch",
-      "Hurricane Warning"
-    ),
-    drop = FALSE
-  ) +
-  coord_sf(
-    # Give some more breathing room on the x axis
-    xlim = c(scales::expand_range(c(bbox$xmax, bbox$xmin), mul = 0.25)), 
-    ylim = c(
-      bbox$ymin, 
-      bbox$ymax
-    ), 
-    expand = FALSE
-  ) + 
-  guides(
-    color = guide_legend(nrow = 2, byrow = TRUE)
-  ) + 
-  theme(
-    panel.ontop = TRUE,
-    panel.background = element_blank(), 
-    panel.grid.major = element_line(color = "lightgray", size = 0.1),
-    legend.position = "bottom", 
-    legend.box = "vertical"
-  ) +
-  labs(title = "Hurricane Matthew Advisory #37")
    -
    ## Warning: Ignoring unknown parameters: key_glyph
    -

    -
    -

    -Forecast Line

    -
    str(shp_df$`al142016-037_5day_lin`)
    -
    ## Classes 'sf' and 'data.frame':   2 obs. of  8 variables:
-##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1
-##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1
-##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1
-##  $ ADVISNUM : Factor w/ 1 level "37": 1 1
-##  $ STORMNUM : num  14 14
-##  $ FCSTPRD  : num  72 120
-##  $ BASIN    : Factor w/ 1 level "al": 1 1
-##  $ geometry :sfc_LINESTRING of length 2; first list element:  'XY' num [1:6, 1:2] -80 -80.6 -80.5 -79.2 -77.7 ...
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA
-##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    -

    Plotting the forecast line is nothing fancy though you could define different linestyles depending on the status of the storm (STORMTYPE) or the forecast period (FCSTPRD). Additional variables are pretty self-explanatory; STORMNAME, ADVDATE, ADVISNUM, STORMNUM, and BASIN.

    - -
    -
    -

    -Forecast Points

    -
    str(shp_df$`al142016-037_5day_pts`)
    -
    ## Classes 'sf' and 'data.frame':   14 obs. of  24 variables:
-##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ ADVISNUM : Factor w/ 1 level "37": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14 ...
-##  $ FCSTPRD  : num  72 72 72 72 72 72 120 120 120 120 ...
-##  $ BASIN    : Factor w/ 1 level "al": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ LAT      : num  28.2 29.6 31.5 32.6 33.1 31.5 28.2 29.6 31.5 32.6 ...
-##  $ LON      : num  -80 -80.6 -80.5 -79.2 -77.7 -74.5 -80 -80.6 -80.5 -79.2 ...
-##  $ VALIDTIME: Factor w/ 8 levels "07/0900","07/1800",..: 1 2 3 4 5 6 1 2 3 4 ...
-##  $ TAU      : num  3 12 24 36 48 72 3 12 24 36 ...
-##  $ MAXWIND  : num  105 100 90 80 65 50 105 100 90 80 ...
-##  $ GUST     : num  130 120 110 100 80 60 130 120 110 100 ...
-##  $ MSLP     : num  938 9999 9999 9999 9999 ...
-##  $ TCDVLP   : Factor w/ 3 levels "Hurricane","Major Hurricane",..: 2 2 1 1 1 3 2 2 1 1 ...
-##  $ DVLBL    : Factor w/ 3 levels "H","M","S": 2 2 1 1 1 3 2 2 1 1 ...
-##  $ SSNUM    : num  3 3 2 1 1 0 3 3 2 1 ...
-##  $ TCDIR    : num  330 9999 9999 9999 9999 ...
-##  $ TCSPD    : num  11 9999 9999 9999 9999 ...
-##  $ DATELBL  : Factor w/ 8 levels "2:00 AM Mon",..: 8 6 2 7 3 1 8 6 2 7 ...
-##  $ FLDATELBL: Factor w/ 8 levels "2016-10-07 2:00 PM Fri EDT",..: 2 1 3 4 5 6 2 1 3 4 ...
-##  $ TIMEZONE : Factor w/ 1 level "EDT": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ STORMSRC : Factor w/ 1 level "Tropical Cyclone": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ geometry :sfc_POINT of length 14; first list element:  'XY' num  -80 28.2
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
-##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    -

    The points shapefile contains the same variables as the line shapefile and more. I am unable to find official documentation so let me give my best here to explain some of the added variables.

    -
      -

    • TAU - This appears to be the time period in hours for each forecast point, gruoped by FCSTPRD

      • -

    • MSLP - Forecast minimum sea level pressure. “9999” values simply indicate no forecast MSLP was provided.

      • -

    • TCDVLP - The forecast status of the cyclone.

      • -

    • DVLBL - A shorter label for TCDVLP

      • -

    • SSNUM - Sorry, no idea…

      • -

    • TCDIR - Foreward direction of the storm

      • -

    • TCSPD - Foreward speed of the storm

      • -
    - -

    Since we have the added variables LAT and LON, and I wanted to customize the aesthetics a bit, I chose to use the layer geom_point. I set fill and shape to DVLBL and size to MAXWIND. I also wanted to customize the appearance of each point and, since I’ll be using the color aesthetic for watches and warnings as well, I needed to customize these scales.

    -
      scale_shape_manual(name = "Status", values = c(rep(21, 4))) +
-  scale_fill_discrete(name = "Status") +
-  scale_size_continuous(name = "Wind (kts)") +
    -
    -
    -

    -Watches and Warnings

    -
    str(shp_df$`al142016-037_ww_wwlin`)
    -
    ## Classes 'sf' and 'data.frame':   10 obs. of  9 variables:
-##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1 1 1 1 1 1 1 1 1
-##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1 1 1 1 1 1 1 1 1
-##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1 1 1 1 1 1 1 1 1
-##  $ ADVISNUM : Factor w/ 1 level "37": 1 1 1 1 1 1 1 1 1 1
-##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14
-##  $ FCSTPRD  : num  120 120 120 120 120 120 120 120 120 120
-##  $ BASIN    : Factor w/ 1 level "al": 1 1 1 1 1 1 1 1 1 1
-##  $ TCWW     : Factor w/ 3 levels "HWR","TWA","TWR": 1 1 1 1 1 1 3 3 3 2
-##  $ geometry :sfc_LINESTRING of length 10; first list element:  'XY' num [1:5, 1:2] -77.6 -77.7 -78.2 -78.4 -77.6 ...
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA
-##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    -

    In the watches and warnings dataset we have the TCWW variable which identifies the watch/warning issued for each line. There are only four possible candidates here:

    -
      -

    • TWA - Tropical storm watch

      • -

    • TWR - Tropical storm warning

      • -

    • HWA - Hurricane watch

      • -

    • HWR - Hurricane warning

      • -
    -

    I use the geom_sf layer and set the color aesthetic. I also increased the size of the lines to stand out a bit and, with the introduction of key glyphs in ggplot 3.2.0, changed the legend style.

    - -

    Since I’m already using color in the points layer, I needed to add an additional legend to identify the watches and warnings. I set the drop parameter to FALSE to ensure that all four keys show regardless of what is in the dataset.

    - -

    Below, I break the legend into two rows.

    -
      guides(
-    color = guide_legend(nrow = 2, byrow = TRUE)
-  ) +
    -
    -
    -

    -Forecast Cone

    -

    The forecast cone is contained in the polygon dataset of the advisory package. Take a look at the structure.

    -
    str(shp_df$`al142016-037_5day_pgn`)
    -
    ## Classes 'sf' and 'data.frame':   2 obs. of  8 variables:
-##  $ STORMNAME: Factor w/ 1 level "MATTHEW": 1 1
-##  $ STORMTYPE: Factor w/ 1 level "HU": 1 1
-##  $ ADVDATE  : Factor w/ 1 level "161007/0900": 1 1
-##  $ ADVISNUM : Factor w/ 1 level "37": 1 1
-##  $ STORMNUM : num  14 14
-##  $ FCSTPRD  : num  72 120
-##  $ BASIN    : Factor w/ 1 level "al": 1 1
-##  $ geometry :sfc_POLYGON of length 2; first list element: List of 1
-##   ..$ : num [1:274, 1:2] -79.9 -80.2 -80.4 -80.6 -80.7 ...
-##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA
-##   ..- attr(*, "names")= chr  "STORMNAME" "STORMTYPE" "ADVDATE" "ADVISNUM" ...
    -

    The geometry should be slightly different depending on the FCSTPRD. However, for this dataset, that is not the case.

    - -
    ## [1] TRUE
    -

    I could have filled differently depending on different geometries; unfortunately it was just not possible. So I kept the geom_sf call simple.

    - -
    -
    -
    -

    -Forecast Wind Radii

    -

    The forecast wind radii dataset should contain two datasets; one for the current wind radius and another for the forecast wind radii.

    -
    str(shp_df$al142016_2016100706_initialradii)
    -
    ## Classes 'sf' and 'data.frame':   3 obs. of  12 variables:
-##  $ RADII    : num  34 50 64
-##  $ STORMID  : Factor w/ 1 level "al142016": 1 1 1
-##  $ BASIN    : Factor w/ 1 level "AL": 1 1 1
-##  $ STORMNUM : num  14 14 14
-##  $ VALIDTIME: Factor w/ 1 level "2016100709": 1 1 1
-##  $ SYNOPTIME: Factor w/ 1 level "2016100706": 1 1 1
-##  $ TAU      : num  3 3 3
-##  $ NE       : num  160 70 50
-##  $ SE       : num  140 70 40
-##  $ SW       : num  80 50 30
-##  $ NW       : num  120 70 50
-##  $ geometry :sfc_POLYGON of length 3; first list element: List of 1
-##   ..$ : num [1:364, 1:2] -77.8 -77.8 -77.8 -77.7 -77.7 ...
-##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
-##   ..- attr(*, "names")= chr  "RADII" "STORMID" "BASIN" "STORMNUM" ...
    -
    str(shp_df$al142016_2016100706_forecastradii)
    -
    ## Classes 'sf' and 'data.frame':   16 obs. of  12 variables:
-##  $ RADII    : num  34 34 34 34 34 34 50 50 50 50 ...
-##  $ STORMID  : Factor w/ 1 level "al142016": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ BASIN    : Factor w/ 1 level "AL": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ STORMNUM : num  14 14 14 14 14 14 14 14 14 14 ...
-##  $ VALIDTIME: Factor w/ 6 levels "2016100709","2016100718",..: 1 2 3 4 5 6 1 2 3 4 ...
-##  $ SYNOPTIME: Factor w/ 1 level "2016100706": 1 1 1 1 1 1 1 1 1 1 ...
-##  $ TAU      : num  3 12 24 36 48 72 3 12 24 36 ...
-##  $ NE       : num  160 170 180 200 150 120 70 70 80 80 ...
-##  $ SE       : num  140 140 160 160 150 150 70 70 70 70 ...
-##  $ SW       : num  80 80 80 90 120 150 50 50 50 40 ...
-##  $ NW       : num  120 120 110 90 90 120 70 70 70 40 ...
-##  $ geometry :sfc_POLYGON of length 16; first list element: List of 1
-##   ..$ : num [1:364, 1:2] -80 -79.9 -79.9 -79.8 -79.8 ...
-##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
-##   ..- attr(*, "names")= chr  "RADII" "STORMID" "BASIN" "STORMNUM" ...
    -

    The “initialradii” dataset will contain up to three observations for each radii: 34 knots, 50 knots, and 64 knots. This is the expected distance from the center of circulation that minimum n-force winds can be expected.

    -

    The “forecastradii” can have many observations. For forecast periods up to 36 hours, all wind radii may be provided if the storm is strong enough. At 48 and 72 hours, only 34 and 50 knot wind radii are provided. No forecast wind radii are provided beyond 72 hours.

    - -

    -

    In the plot above I take the same approach as the advisory package but only keep the line track and points to keep the graph simple. To add the forecast wind radii, I again use the geom_sf layer providing the fill aesthetic based on RADII. Outside of the aesthetic, I set alpha to 0.25 to make underlying radii visible as well as land areas.

    - -

    The initialradii dataset was intentionally left out; as you can see it is included in the forecastradii package.

    -
    -
    -

    -Wind Speed Probabilities

    -

    As noted previously, wind speed probabilities can be provided in different resolutions. Recall that I went with the 0.5° resolution dataset. There are three packages in this dataset; proabilities of at least 34 knot winds, 50 knot winds, and 64 knot winds.

    -
    str(shp_df$`2016100706_wsp34knt120hr_halfDeg`)
    -
    ## Classes 'sf' and 'data.frame':   4367 obs. of  3 variables:
-##  $ POINTID : int  90011 100011 100012 100013 10014 110014 120014 130014 140014 150014 ...
-##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 ...
-##  $ geometry:sfc_POINT of length 4367; first list element:  'XY' num  104 6
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
-##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    -
    str(shp_df$`2016100706_wsp50knt120hr_halfDeg`)
    -
    ## Classes 'sf' and 'data.frame':   2302 obs. of  3 variables:
-##  $ POINTID : int  10015 10016 30017 40017 130017 40018 120018 130018 140018 90019 ...
-##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ...
-##  $ geometry:sfc_POINT of length 2302; first list element:  'XY' num  100 8
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
-##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    -
    str(shp_df$`2016100706_wsp64knt120hr_halfDeg`)
    -
    ## Classes 'sf' and 'data.frame':   1367 obs. of  3 variables:
-##  $ POINTID : int  140023 150023 140024 150024 160024 170024 160025 170025 180025 80026 ...
-##  $ PWIND120: num  0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 ...
-##  $ geometry:sfc_POINT of length 1367; first list element:  'XY' num  106 12
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
-##   ..- attr(*, "names")= chr  "POINTID" "PWIND120"
    -

    Each dataset contains the variable PWIND120; the probability of n-speed winds up to 120 hours.

    - -

    -

    The plot above focuses only on the wind speed probabilities. The forecast track of the cyclone is quite clear. I made the size and alpha aesthetic based on PWIND120 but removed those legends. I kept the color aesthetic which I divided by 100 to make a fraction (default is a real). With that, I applied scales::percent to the legend to show a percentage and changed the breaks.

    -
    -
    -

    -Storm Surge Probabilities

    -
    str(shp_df$al142016_2016100706_gt5)
    -
    ## Classes 'sf' and 'data.frame':   99 obs. of  3 variables:
-##  $ POINTID  : int  1 2 3 4 5 6 7 8 9 10 ...
-##  $ PSurge05c: num  1 2 3 4 5 6 7 8 9 10 ...
-##  $ geometry :sfc_MULTIPOLYGON of length 99; first list element: List of 554
-##   ..$ :List of 1
-##   .. ..$ : num [1:43, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:23, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:13, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:13, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:19, 1:2] -80.3 -80.3 -80.3 -80.3 -80.3 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:5, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:5, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:17, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:45, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:15, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:7, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:13, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:19, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:67, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:33, 1:2] -82.6 -82.6 -82.6 -82.6 -82.6 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:15, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:9, 1:2] -80.7 -80.7 -80.7 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:15, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:17, 1:2] -80.7 -80.6 -80.6 -80.7 -80.7 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:13, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:11, 1:2] -80.6 -80.6 -80.6 -80.6 -80.6 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:15, 1:2] -80.4 -80.4 -80.4 -80.4 -80.4 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:9, 1:2] -80.6 -80.6 -80.7 -80.6 -80.6 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:7, 1:2] -80.8 -80.8 -80.8 -80.8 -80.8 ...
-##   ..$ :List of 1
-##   .. ..$ : num [1:87, 1:2] -82.7 -82.7 -82.7 -82.7 -82.7 ...
-##   ..$ :List of 1
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-##   .. [list output truncated]
-##   ..- attr(*, "class")= chr  "XY" "MULTIPOLYGON" "sfg"
-##  - attr(*, "sf_column")= chr "geometry"
-##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA
-##   ..- attr(*, "names")= chr  "POINTID" "PSurge05c"
    -

    Similar to the wind speed probabilities, storm surge probabilties only has three variables, the POINTID, geometry, and, because we requested the psurge product for 5-feet, PSurge05c (this name changes depending on the product and value).

    -

    Note that unlike wind speed probabilities which is a point shapefile, this dataset is a polygon shapefile.

    - -

    -

    I took similar steps to creating this plot as I did with wind speed probabilties.

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    Note what appears to be storm surge well inland from the coast in Lake George, St. Johns River, and elsewhere.

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    Developed by Tim Trice.

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    Site built with pkgdown 1.3.0.

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