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read_tide_level.R
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read_tide_level.R
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#' Read and parse tide level text data
#'
#' @description
#' `r lifecycle::badge("stable")`
#'
#' @param path URL or local file path to sea tide level file
#' @param .year A.D. 1997 to present year.
#' @param .month Month number. 1997 only, valid after March.
#' @param .stn Station identification name in uppercase two-digit letters.
#' @param raw If *TRUE*, return raw format data
#' @seealso <https://www.data.jma.go.jp/gmd/kaiyou/db/tide/suisan/readme.html>
#' @examples
#' # Read a local storage file (dummy data)
#' read_tide_level(system.file("dummy/tide.txt", package = "jmastats"))
#' \donttest{
#' # Request from URL
#' read_tide_level("https://www.data.jma.go.jp/gmd/kaiyou/data/db/tide/suisan/txt/2020/TK.txt")
#' # Request from parameters
#' read_tide_level(.year = 2020, .month = 2, .stn = "TK")
#' }
#' @export
#' @return a `tbl` object
read_tide_level <- function(path = NULL, .year, .month, .stn, raw = FALSE) {
if (is.null(path)) {
path <-
request_tide_level_url(.year, .month, .stn)
}
d <-
readr::read_lines(path)
if (raw == FALSE) {
d <-
d |>
purrr::map(
~ .x |>
stringr::str_split(pattern = stringr::boundary("character"),
simplify = TRUE) |>
as.data.frame(stringsAsFactors = FALSE)
) |>
purrr::list_rbind() |>
tibble::as_tibble() |>
parse_tide_file() |>
dplyr::mutate(
dplyr::across(c(tidyselect::num_range("hry_",
range = seq.int(0, 23),
width = 2),
tidyselect::contains("tide_level")),
function(x) units::set_units(x, "cm")))
}
d
}
request_tide_level_url <- function(.year, .month, .stn) {
jma_site <- # nolint
"https://www.data.jma.go.jp"
year <-
check_input_tidal_year(.year)
month <-
sprintf("%02d", .month)
month <-
rlang::arg_match(month,
sprintf("%02d", seq.int(12)))
if (year == 1997 && month %in% c("01", "02", "03")) {
rlang::abort("Old format")
}
stn_candidate <-
tide_station |>
dplyr::filter(year == !!rlang::enquo(year)) |>
dplyr::pull(stn)
stn <-
stn_candidate[stn_candidate %in% .stn]
if (length(stn) == 0) {
rlang::abort("In that year, there was no data from the target observatory.")
}
stringr::str_glue("{jma_site}/gmd/kaiyou/data/db/tide/genbo/{year}/{year}{month}/hry{year}{month}{stn}.txt") # nolint
}
parse_tide_file <- function(data) {
year_last2 <- month_last2 <- day_last2 <- stn <- NULL
seq.int(nrow(data)) |>
purrr::map(
function(.x) {
cbind(parse_hry(data[.x, ]),
parse_ymd(data[.x, ], "year"),
parse_ymd(data[.x, ], "month"),
parse_ymd(data[.x, ], "day"),
parse_tide_station(data[.x, ]),
parse_hm(data[.x, ], "low_tide"),
parse_tide(data[.x, ], "low_tide"),
parse_hm(data[.x, ], "high_tide"),
parse_tide(data[.x, ], "high_tide")
) |>
dplyr::mutate(date = lubridate::make_date(year = paste0("20", year_last2),
month_last2,
day_last2)) |>
dplyr::select(!c(year_last2, month_last2, day_last2)) |>
tibble::as_tibble()
}) |>
purrr::list_rbind() |>
dplyr::select(
tidyselect::starts_with("hry"),
date,
stn,
tidyselect::ends_with("obs1"),
tidyselect::ends_with("obs2"),
tidyselect::ends_with("obs3"),
tidyselect::ends_with("obs4")) |>
dplyr::mutate(
dplyr::across(c(tidyselect::contains("tide_hm_obs")),
function(x) dplyr::na_if(x, "99:99"))) |>
dplyr::mutate(
dplyr::across(c(tidyselect::contains("tide_tidal_level_cm_obs")),
function(x) dplyr::na_if(x, "99:99"))) |>
readr::type_convert(col_types = readr::cols(
stn = readr::col_character(),
low_tide_hm_obs1 = readr::col_time(format = ""),
low_tide_level_obs1 = readr::col_double(),
high_tide_hm_obs1 = readr::col_time(format = ""),
high_tide_level_obs1 = readr::col_double(),
low_tide_hm_obs2 = readr::col_time(format = ""),
low_tide_level_obs2 = readr::col_double(),
high_tide_hm_obs2 = readr::col_time(format = ""),
high_tide_level_obs2 = readr::col_double(),
low_tide_hm_obs3 = readr::col_time(format = ""),
low_tide_level_obs3 = readr::col_double(),
high_tide_hm_obs3 = readr::col_time(format = ""),
high_tide_level_obs3 = readr::col_double(),
low_tide_hm_obs4 = readr::col_time(format = ""),
low_tide_level_obs4 = readr::col_double(),
high_tide_hm_obs4 = readr::col_time(format = ""),
high_tide_level_obs4 = readr::col_double()
))
}
parse_hry <- function(d) {
purrr::map2_chr(
.x = seq.int(1, 72, by = 3),
.y = seq.int(1, 72, by = 3) + 2,
.f = ~ d[.x:.y] |>
paste(collapse = "")
) |>
purrr::set_names(paste0("hry_", sprintf("%02d", seq.int(0, 23)))) |>
as.data.frame() |>
t() |>
as.data.frame(stringsAsFactors = FALSE) |>
dplyr::mutate(
dplyr::across(tidyselect::everything(),
readr::parse_number)) |>
tibble::as_tibble()
}
parse_ymd <- function(d, type) {
type <-
rlang::arg_match(type,
c("year", "month", "day"))
index_list <-
list(x = 73, y = 74)
index_list <-
switch (type,
"year" = index_list,
"month" = index_list |>
purrr::list_modify(x = index_list$x + 2,
y = index_list$y + 2),
"day" = index_list |>
purrr::list_modify(x = index_list$x + 4,
y = index_list$y + 4)
)
d[seq.int(index_list$x, index_list$y)] |>
paste(collapse = "") |>
purrr::set_names(paste0(type, "_last2")) |>
as.data.frame() |>
t() |>
as.data.frame(stringsAsFactors = FALSE) |>
dplyr::mutate(
dplyr::across(tidyselect::everything(),
readr::parse_number)) |>
tibble::as_tibble()
}
parse_tide_station <- function(d) {
d[seq.int(79, 80)] |>
paste(collapse = "") |>
purrr::set_names("stn") |>
as.data.frame() |>
t() |>
as.data.frame(stringsAsFactors = FALSE) |>
tibble::as_tibble()
}
parse_hm <- function(d, time) {
time <-
rlang::arg_match(time,
c("low_tide", "high_tide"))
index_list <-
switch (time,
low_tide = list(
x =
seq(81, 108, by = 7),
y =
seq(84, 108, by = 7)),
high_tide = list(
x =
seq(109, 136, by = 7),
y =
seq(112, 136, by = 7)
))
d <-
purrr::map2(
index_list$x,
index_list$y,
~ d[seq.int(.x, .y)] |>
purrr::set_names(c("h1", "h2", "m1", "m2")) |>
dplyr::mutate(
across(tidyselect::everything(),
function(x) stringr::str_replace(x,
pattern = "[[:blank:]]",
replacement = "0"))) |>
dplyr::mutate(hm = paste(paste0(h1, h2, collapse = ""),
paste0(m1, m2, collapse = ""),
sep = ":"),
.keep = "none")) |>
purrr::list_cbind()
d |>
purrr::set_names(paste0(time,
"_hm",
"_obs",
seq.int(length(d))))
}
parse_tide <- function(d, time) {
time <-
rlang::arg_match(time,
c("low_tide", "high_tide"))
index_list <-
switch (time,
low_tide = list(
x =
seq(85, 108, by = 7),
y =
seq(87, 108, by = 7)),
high_tide = list(
x =
seq(113, 136, by = 7),
y =
seq(115, 136, by = 7)
))
d <-
purrr::map2(
index_list$x,
index_list$y,
~ d[seq.int(.x, .y)] |>
purrr::set_names(c("obs1", "obs2", "obs3")) |>
dplyr::mutate(
dplyr::across(
tidyselect::everything(),
function(x) stringr::str_replace(x,
pattern = "[[:blank:]]",
replacement = "0"))) |>
dplyr::mutate(tidal_level_cm = paste0(obs1, obs2, obs3, collapse = ""),
.keep = "none")) |>
purrr::list_cbind()
d |>
purrr::set_names(paste0(time,
"_level",
"_obs",
seq.int(length(d))))
}