Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Isd changes done #180

Merged
merged 4 commits into from
Nov 5, 2016
Merged

Isd changes done #180

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
1bb13d2
#176, #177 incorporated new isdparser pkg as an import
sckott Nov 1, 2016
a962953
remove commented out code
sckott Nov 1, 2016
f8d3520
remove commentd out code
sckott Nov 5, 2016
384230e
remove isdparser pkg from Remotes
sckott Nov 5, 2016
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 3 additions & 2 deletions DESCRIPTION
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ Description: Client for many 'NOAA' data sources including the 'NCDC' climate
for 'NOAA' sea ice data, the 'NOAA' severe weather inventory, 'NOAA' Historical
Observing 'Metadata' Repository ('HOMR') data, 'NOAA' storm data via 'IBTrACS',
tornado data via the 'NOAA' storm prediction center, and more.
Version: 0.6.5.9000
Version: 0.6.5.9400
License: MIT + file LICENSE
Encoding: UTF-8
Authors@R: c(
Expand Down Expand Up @@ -38,7 +38,8 @@ Imports:
jsonlite,
rappdirs,
gridExtra,
tibble
tibble,
isdparser
Suggests:
roxygen2 (>= 5.0.1),
testthat,
Expand Down
292 changes: 33 additions & 259 deletions R/isd.R
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
#' Get NOAA ISD/ISH data from NOAA FTP server.
#' Get and parse NOAA ISD/ISH data
#'
#' @export
#'
Expand All @@ -11,6 +11,12 @@
#' at end of function execution. Processing data takes up a lot of time, so we
#' cache a cleaned version of the data. Cleaning up will save you on disk
#' space. Default: \code{TRUE}
#' @param parallel (logical) do processing in parallel. Default: \code{FALSE}
#' @param cores (integer) number of cores to use: Default: 2. We look in
#' your option "cl.cores", but use default value if not found.
#' @param progress (logical) print progress - ignored if \code{parallel=TRUE}.
#' The default is \code{FALSE} because printing progress adds a small bit of
#' time, so if processing time is important, then keep as \code{FALSE}
#' @param ... Curl options passed on to \code{\link[httr]{GET}}
#'
#' @references ftp://ftp.ncdc.noaa.gov/pub/data/noaa/
Expand All @@ -20,6 +26,9 @@
#' site locally in the directory specified by the \code{path} argument. You
#' can access the path for the cached file via \code{attr(x, "source")}
#'
#' We use \pkg{isdparser} internally to parse ISD files. They are
#' relatively complex to parse, so a separate package takes care of that.
#'
#' @return A tibble (data.frame).
#'
#' @details This function first looks for whether the data for your specific
Expand Down Expand Up @@ -97,8 +106,17 @@
#' ggplot(res_all, aes(date_time, temperature)) +
#' geom_line() +
#' facet_wrap(~usaf_station, scales = "free_x")
#'
#' # print progress
#' (res <- isd(usaf="011690", wban="99999", year=1993, progress=TRUE))
#'
#' # parallelize processing
#' (res <- isd(usaf="172007", wban="99999", year=2015, parallel=TRUE))
#' }
isd <- function(usaf, wban, year, overwrite = TRUE, cleanup = TRUE, ...) {
isd <- function(usaf, wban, year, overwrite = TRUE, cleanup = TRUE,
parallel = FALSE, cores = getOption("cl.cores", 2),
progress = FALSE, ...) {

calls <- names(sapply(match.call(), deparse))[-1]
calls_vec <- "path" %in% calls
if (any(calls_vec)) {
Expand All @@ -111,20 +129,24 @@ isd <- function(usaf, wban, year, overwrite = TRUE, cleanup = TRUE, ...) {
if (!is_isd(x = rdspath)) {
isd_GET(bp = path, usaf, wban, year, overwrite, ...)
}
message(sprintf("<path>%s", rdspath), "\n")
df <- read_isd(x = rdspath, sections, cleanup)
df <- read_isd(x = rdspath, sections, cleanup, parallel, cores, progress)
attr(df, "source") <- rdspath
df
}

isd_GET <- function(bp, usaf, wban, year, overwrite, ...) {
dir.create(bp, showWarnings = FALSE, recursive = TRUE)
fp <- isd_local(usaf, wban, year, bp, ".gz")
tryget <- tryCatch(suppressWarnings(GET(isd_remote(usaf, wban, year), write_disk(fp, overwrite), ...)),
error = function(e) e)
tryget <- tryCatch(
suppressWarnings(
GET(isd_remote(usaf, wban, year), write_disk(fp, overwrite), ...)
),
error = function(e) e
)
if (inherits(tryget, "error")) {
unlink(fp)
stop("download failed for\n ", isd_remote(usaf, wban, year), call. = FALSE)
stop("download failed for\n ", isd_remote(usaf, wban, year),
call. = FALSE)
} else {
tryget
}
Expand All @@ -144,16 +166,14 @@ is_isd <- function(x) {

isdbase <- function() 'ftp://ftp.ncdc.noaa.gov/pub/data/noaa'

read_isd <- function(x, sections, cleanup) {
#path_rds <- sub("gz", "rds", x)
read_isd <- function(x, sections, cleanup, parallel, cores, progress) {
path_rds <- x
if (file.exists(path_rds)) {
message("found in cache")
df <- readRDS(path_rds)
} else {
lns <- readLines(sub("rds", "gz", x), encoding = "latin1")
linesproc <- lapply(lns, each_line, sections = sections)
df <- bind_rows(linesproc)
df <- trans_vars(df)
df <- isdparser::isd_parse(sub("rds", "gz", x), parallel = parallel,
cores = cores, progress = progress)
cache_rds(path_rds, df)
if (cleanup) {
unlink(sub("rds", "gz", x))
Expand All @@ -167,249 +187,3 @@ cache_rds <- function(x, y) {
saveRDS(y, file = x)
}
}

# cache_csv <- function(x, y) {
# if (!file.exists(x)) {
# write.csv(y, file = x, row.names = FALSE)
# }
# }

trans_vars <- function(w) {
# fix scaled variables
w$latitude <- trans_var(trycol(suppressWarnings(w$latitude)), 1000)
w$longitude <- trans_var(trycol(suppressWarnings(w$longitude)), 1000)
w$elevation <- trans_var(trycol(suppressWarnings(w$elevation)), 10)
w$wind_speed <- trans_var(trycol(suppressWarnings(w$wind_speed)), 10)
w$temperature <- trans_var(trycol(suppressWarnings(w$temperature)), 10)
w$temperature_dewpoint <- trans_var(trycol(suppressWarnings(w$temperature_dewpoint)), 10)
w$air_pressure <- trans_var(trycol(suppressWarnings(w$air_pressure)), 10)
w$precipitation <- trans_var(trycol(suppressWarnings(w$precipitation)), 10)

# as date
w$date <- as.Date(w$date, "%Y%m%d")

# change class
w$wind_direction <- as.numeric(w$wind_direction)
w$total_chars <- as.numeric(w$total_chars)

return(w)
}

trycol <- function(x) {
tt <- tryCatch(x, error = function(e) e)
if (inherits(tt, "error")) NULL else tt
}

trans_var <- function(x, n) {
if (is.null(x)) {
x
} else {
as.numeric(x)/n
}
}

each_line <- function(y, sections){
normal <- Map(function(a,b) subs(y, a, b), pluck(sections, "start"), pluck(sections, "stop"))
other <- gsub("\\s+$", "", substring(y, 106, nchar(y)))
oth <- proc_other(other)
if (is.null(oth)) {
dplyr::as_data_frame(normal)
#data.frame(normal, stringsAsFactors = FALSE)
} else {
dplyr::as_data_frame(c(normal, oth))
#data.frame(normal, oth, stringsAsFactors = FALSE)
}
}

pluck <- function(input, x) vapply(input, "[[", numeric(1), x)

subs <- function(z, start, stop) substring(z, start, stop)

sections <- list(
total_chars = list(start = 1,stop = 4),
usaf_station = list(start = 5,stop = 10),
wban_station = list(start = 11,stop = 15),
date = list(start = 16,stop = 23),
time = list(start = 24,stop = 27),
date_flag = list(start = 28,stop = 28),
latitude = list(start = 29,stop = 34),
longitude = list(start = 35,stop = 41),
type_code = list(start = 42,stop = 46),
elevation = list(start = 47,stop = 51),
call_letter = list(start = 52,stop = 56),
quality = list(start = 57,stop = 60),
wind_direction = list(start = 61,stop = 63),
wind_direction_quality = list(start = 64,stop = 64),
wind_code = list(start = 65,stop = 65),
wind_speed = list(start = 66,stop = 69),
wind_speed_quality = list(start = 70,stop = 70),
ceiling_height = list(start = 71,stop = 75),
ceiling_height_quality = list(start = 76,stop = 76),
ceiling_height_determination = list(start = 77,stop = 77),
ceiling_height_cavok = list(start = 78,stop = 78),
visibility_distance = list(start = 79,stop = 84),
visibility_distance_quality = list(start = 85,stop = 85),
visibility_code = list(start = 86,stop = 86),
visibility_code_quality = list(start = 87,stop = 87),
temperature = list(start = 88,stop = 92),
temperature_quality = list(start = 93,stop = 93),
temperature_dewpoint = list(start = 94,stop = 98),
temperature_dewpoint_quality = list(start = 99,stop = 99),
air_pressure = list(start = 100,stop = 104),
air_pressure_quality = list(start = 105,stop = 105)
)

proc_other <- function(x){
# x <- substring(x, 4, nchar(x))
tt <- list(check_get(x, "SA1", sa1),
check_get(x, "REM", rem),
check_get(x, "AY1", ay1),
check_get(x, "AY2", ay2),
check_get(x, "AG1", ag1),
check_get(x, "GF1", gf1),
check_get(x, "KA1", ka1),
check_get(x, "EQD", eqd),
check_get(x, "MD1", md1),
check_get(x, "MW1", mw1)
)
other <- tt[!vapply(tt, function(x) is.null(x[[1]]), TRUE)]
unlist(lapply(other, function(z) {
nms <- names(z)
tmp <- if (!is_named(z[[1]])) z[[1]][[1]] else z[[1]]
stats::setNames(tmp, paste(nms, names(tmp), sep = "_"))
}), FALSE)
}

is_named <- function(x) !is.null(names(x))

check_get <- function(string, pattern, fxn) {
yy <- regexpr(pattern, string)
tt <- if (yy > 0) fxn(string) else NULL
stats::setNames(list(tt), pattern)
}

# str_match_len(x, "SA1", 8)
str_match_len <- function(x, index, length){
sa1 <- regexpr(index, x)
if (sa1 > 0) {
substring(x, sa1[1], sa1[1] + (length - 1))
} else {
NULL
}
}

str_from_to <- function(x, a, b){
substring(x, a, a + b)
}

str_pieces <- function(z, pieces, nms=NULL){
tmp <- lapply(pieces, function(x) substring(z, x[1], if (x[2] == 999) nchar(z) else x[2]))
if (is.null(nms)) tmp else stats::setNames(tmp, nms)
}

# sea surface temperature data
# sa1(x)
sa1 <- function(x) {
str_pieces(
str_match_len(x, "SA1", 8),
list(c(1,3),c(4,7),c(8,8)),
c('sea_surface','temp','quality')
)
}

# remarks section
# rem(x)
rem <- function(x){
str_pieces(
str_match_len(x, "REM", nchar(x)),
list(c(1,3),c(4,6),c(7,9),c(10,999)),
c('remarks','identifier','length_quantity','comment')
)
}

# past weather manual observation
# ay1(x)
ay1 <- function(x){
str_pieces(
str_match_len(x, "AY1", 8),
list(c(1,3),c(4,4),c(5,5),c(6,7),c(8,8)),
c('manual_occurrence','condition_code','condition_quality','period','period_quality')
)
}

# past weather manual observation
# ay2(x)
ay2 <- function(x){
str_pieces(
str_match_len(x, "AY2", 8),
list(c(1,3),c(4,4),c(5,5),c(6,7),c(8,8)),
c('manual_occurrence','condition_code','condition_quality','period','period_quality')
)
}

# PRECIPITATION-ESTIMATED-OBSERVATION identifier
# ag1(x)
ag1 <- function(x){
str_pieces(
str_match_len(x, "AG1", 7),
list(c(1,3),c(4,4),c(5,7)),
c('precipitation','discrepancy','est_water_depth')
)
}

# sky condition
# gf1(x)
gf1 <- function(x){
str_pieces(
str_match_len(x, "GF1", 26),
list(c(1,3),c(4,5),c(6,7),c(8,8),c(9,10),c(11,11),c(12,13),c(14,14),c(15,19),c(20,20),c(21,22),c(23,23),c(24,25),c(26,26)),
c('sky_condition','coverage','opaque_coverage','coverage_quality','lowest_cover','lowest_cover_quality',
'low_cloud_genus','low_cloud_genus_quality','lowest_cloud_base_height','lowest_cloud_base_height_quality',
'mid_cloud_genus','mid_cloud_genus_quality','high_cloud_genus','high_cloud_genus_quality')
)
}

# extreme air temperature
# ka1(x)
ka1 <- function(x){
str_pieces(
str_match_len(x, "KA1", 13),
list(c(1,3),c(4,6),c(7,7),c(8,12),c(13,13)),
c('extreme_temp','period_quantity','max_min','temp','temp_quality')
)
}

# element data quality section
# eqd(x)
eqd <- function(x){
eqdtmp <- str_match_len(x, "EQD", nchar(x))
eqdmtchs <- gregexpr("Q[0-9]{2}", eqdtmp)
segments <- str_from_to(eqdtmp, eqdmtchs[[1]], 13)
lapply(segments, function(m){
str_pieces(m,
list(c(1,3),c(4,9),c(10,10),c(11,16)),
c('observation_identifier','observation_text','reason_code','parameter')
)
})
}

# atmospheric pressure change
# md1(x)
md1 <- function(x){
str_pieces(
str_match_len(x, "MD1", 14),
list(c(1,3),c(4,4),c(5,5),c(6,8),c(9,9),c(10,13),c(14,14)),
c('atmospheric_change','tendency','tendency_quality','three_hr','three_hr_quality',
'twentyfour_hr','twentyfour_hr_quality')
)
}

# PRESENT-WEATHER-OBSERVATION manual occurrence identifier, MW1=first weather reported
# mw1(x)
mw1 <- function(x){
str_pieces(
str_match_len(x, "MW1", 6),
list(c(1,3),c(4,5),c(6,6)),
c('first_weather_reported','condition','condition_quality')
)
}
Loading