version 0.8.7

DESCRIPTION

@@ -2,8 +2,8 @@ Package: worldmet
 Type: Package
 Title: Import Surface Meteorological Data from NOAA Integrated Surface
         Database (ISD)
-Version: 0.8.4
-Date: 2018-02-27
+Version: 0.8.7
+Date: 2019-04-17
 Authors@R: c(person("David", "Carslaw", role = c("aut", "cre"), email =
     "david.carslaw@york.ac.uk"))
 ByteCompile: true
@@ -19,9 +19,10 @@ URL: http://github.com/davidcarslaw/worldmet
 BugReports: http://github.com/davidcarslaw/worldmet/issues
 LazyLoad: true
 LazyData: true
-RoxygenNote: 6.0.1
+Encoding: UTF-8
+RoxygenNote: 6.1.1
 NeedsCompilation: no
-Packaged: 2018-02-27 13:54:35 UTC; David
+Packaged: 2019-04-17 08:05:15 UTC; davidcarslaw
 Author: David Carslaw [aut, cre]
 Repository: CRAN
-Date/Publication: 2018-02-27 14:16:34 UTC
+Date/Publication: 2019-04-17 08:20:03 UTC

MD5

@@ -1,19 +1,17 @@
-cf54c0aeb41be2ca443c73c08b0c4793 *DESCRIPTION
-0fb1b2ac28a1bb97e4726f2a546c353b *NAMESPACE
-fde382d0eda08d1f08aaffa5bb40c92f *R/exportADMS.R
-bd28cb4f44a1a1b19fde283990525289 *R/getMeta.R
-5171f60d1c13156a56ebb0847d72c0b6 *R/metNOAA.R
-b15a961f15873be7d691ca7eb1dffebf *R/meta.R
-7cfccd5e8a36ebd23b3d3b7406507524 *R/sysdata.rda
-072fafd8f8db6bf7a3138ea8a2735b16 *R/weatherCodes.R
-b0ee29b89da7fa78035a2c171aca205c *R/worldmet-package.R
-cc167598e5b17a10afb4d83e73e8a827 *README.md
-7cfccd5e8a36ebd23b3d3b7406507524 *data/meta.rda
-8699a0e8e38705634dd0ae8f861ea0c4 *data/weatherCodes.rda
+3548133603512b7a6c65d999a4c6507f *DESCRIPTION
+c3e84490aa32f5408c4b61c35b98197c *NAMESPACE
+dfe77d899ba5964a17143dd2f0f20716 *R/exportADMS.R
+e88c9bec4b14e8b651120d3c97d163ef *R/getMeta.R
+e95f4154f85fbe814501ae038ef4a2dc *R/metNOAA.R
+2d8a8e546196ab6f547cc99b76dc6842 *R/sysdata.rda
+dfd79efabee5ea65b0ee279b9f8330de *R/weatherCodes.R
+97f08f4288246821805256f22b5abe76 *R/worldmet-package.R
+8df567a5cf8efae68c0385d8b205a71b *README.md
+8a37aa4cb828770bb2e1c7d6d4f7e34d *data/weatherCodes.rda
 84f21841c2bbb1c09c3ffbcf11ec2145 *inst/images/map.PNG
-6fbcf4883b82a1b0bfa61465ce32f1ac *man/exportADMS.Rd
-9fa5c61807f1f86079eb52f699576354 *man/getMeta.Rd
-fa32bfe9485a9ca294867042d138d111 *man/importNOAA.Rd
-f2cefd98affecb5b3afaf90b79db7036 *man/meta.Rd
-ec57f553d8801d0013614cbc37a6f6c7 *man/weatherCodes.Rd
-6ab42224111ef0481fb97bb9eb324d79 *man/worldmet.Rd
+ca62b4153959d89af26f07cc4e2e1d32 *man/exportADMS.Rd
+9f7b3ef698c60a10a7d824267dff8c9e *man/getMeta.Rd
+40c9a88ccb100f7fc94a4e3899406085 *man/getMetaLive.Rd
+b0292cea67ead0fc5d2c6012b1624d28 *man/importNOAA.Rd
+033635944e83ba6b778f20d6c189adb2 *man/weatherCodes.Rd
+9d97d7d263569f65699961d8765657c5 *man/worldmet.Rd

NAMESPACE

@@ -1,19 +1,21 @@
-# Generated by roxygen2: do not edit by hand
-
-export(exportADMS)
-export(getMeta)
-export(importNOAA)
-import(doParallel)
-import(dplyr)
-import(foreach)
-import(openair)
-import(parallel)
-import(readr)
-importFrom(leaflet,addCircles)
-importFrom(leaflet,addMarkers)
-importFrom(leaflet,addTiles)
-importFrom(leaflet,leaflet)
-importFrom(utils,download.file)
-importFrom(utils,head)
-importFrom(utils,write.table)
-importFrom(zoo,na.approx)
+# Generated by roxygen2: do not edit by hand
+
+export(exportADMS)
+export(getMeta)
+export(getMetaLive)
+export(importNOAA)
+import(doParallel)
+import(dplyr)
+import(foreach)
+import(openair)
+import(parallel)
+import(readr)
+importFrom(leaflet,addCircles)
+importFrom(leaflet,addMarkers)
+importFrom(leaflet,addTiles)
+importFrom(leaflet,leaflet)
+importFrom(leaflet,markerClusterOptions)
+importFrom(utils,download.file)
+importFrom(utils,head)
+importFrom(utils,write.table)
+importFrom(zoo,na.approx)

R/exportADMS.R

@@ -1,117 +1,117 @@
-#' Export a meteorological data frame in ADMS format
-#'
-#' @param dat A data frame imported by \code{\link{importNOAA}}.
-#' @param out A file name for the ADMS file. The file is written to the working
-#'   directory by default.
-#' @param interp Should interpolation of missing values be undertaken? If
-#'   \code{TRUE} linear interpolation is carried out for gaps of up to and
-#'   including \code{maxgap}.
-#' @param maxgap The maximum gap in hours that should be interpolated where
-#'   there are missing data when \code{interp = TRUE.} Data with gaps more than
-#'   \code{maxgap} are left as missing.
-#'
-#' @return Writes a text file to a location of the user's choosing.
-#' @export
-#' @importFrom zoo na.approx
-#' @examples
-#'
-#' \dontrun{
-#' ## import some data then export it
-#' dat <- importNOAA(year = 2012)
-#' exportADMS(dat, file = "~/temp/adms_met.MET")
-#' }
-exportADMS <- function(dat, out = "./ADMS_met.MET", interp = FALSE, maxgap = 2) {
-
-  # keep R check quiet
-  wd <- u <- v <- NULL
-
-  ## make sure the data do not have gaps
-  all.dates <- data.frame(
-    date = seq(ISOdatetime(
-      year = as.numeric(format(dat$date[1], "%Y")),
-      month = 1, day = 1, hour = 0, min = 0,
-      sec = 0, tz = "GMT"
-    ),
-    ISOdatetime(
-      year = as.numeric(format(dat$date[1], "%Y")),
-      month = 12, day = 31, hour = 23, min = 0,
-      sec = 0, tz = "GMT"
-    ),
-    by = "hour"
-    )
-  )
-
-  dat <- merge(dat, all.dates, all = TRUE)
-
-  ## make sure precipitation is available
-  if (!"precip" %in% names(dat)) {
-    dat$precip <- NA
-  }
-
-  if (interp) {
-
-    ## variables to interpolate
-    ## note need to deal with wd properly
-    dat <- transform(dat, u = sin(pi * wd / 180), v = cos(pi * wd / 180))
-
-    varInterp <- c("ws", "u", "v", "air_temp", "RH", "cl", "precip")
-
-    # don't want to try and interpret fields that are all missing
-    ids <- sapply(varInterp, function(x) !all(is.na(dat[[x]])))
-    varInterp <- varInterp[ids]
-
-    dat[varInterp] <- zoo::na.approx(dat[varInterp], maxgap = maxgap, na.rm = FALSE)
-
-    ## now put wd back
-    dat <- transform(dat, wd = as.vector(atan2(u, v) * 360 / 2 / pi))
-
-    ## correct for negative wind directions
-    ids <- which(dat$wd < 0) ## ids where wd < 0
-    dat$wd[ids] <- dat$wd[ids] + 360
-  }
-
-  ## exports met data to ADMS format file
-  year <- as.numeric(format(dat$date, "%Y"))
-  day <- as.numeric(format(dat$date, "%j"))
-  hour <- as.numeric(format(dat$date, "%H"))
-  station <- "0000"
-
-  ## data frame of met data needed
-  adms <- data.frame(station, year, day, hour,
-    round(dat$air_temp, 1), round(dat$ws, 1),
-    round(dat$wd, 1), round(dat$RH, 1),
-    round(dat$cl), round(dat$precip, 1),
-    stringsAsFactors = FALSE
-  )
-
-  ## print key data capture rates to the screen
-  dc <- round(100 - 100 * (length(which(is.na(dat$ws))) / length(dat$ws)), 1)
-  print(paste("Data capture for wind speed:", dc, "%"))
-
-  dc <- round(100 - 100 * (length(which(is.na(dat$wd))) / length(dat$wd)), 1)
-  print(paste("Data capture for wind direction:", dc, "%"))
-
-  dc <- round(100 - 100 * (length(which(is.na(dat$air_temp))) / length(dat$air_temp)), 1)
-  print(paste("Data capture for temperature:", dc, "%"))
-
-  dc <- round(100 - 100 * (length(which(is.na(dat$cl))) / length(dat$cl)), 1)
-  print(paste("Data capture for cloud cover:", dc, "%"))
-
-  ## replace NA with -999
-  adms[] <- lapply(adms, function(x) replace(x, is.na(x), -999))
-
-  ## write the data file
-  write.table(adms,
-    file = out, col.names = FALSE, row.names = FALSE,
-    sep = ",", quote = FALSE
-  )
-
-  ## add the header lines
-  fConn <- file(out, "r+")
-  Lines <- readLines(fConn)
-  writeLines(c(
-    "VARIABLES:\n10\nSTATION DCNN\nYEAR\nTDAY\nTHOUR\nT0C\nU\nPHI\nRHUM\nCL\nP\nDATA:",
-    Lines
-  ), con = fConn)
-  close(fConn)
-}
+#' Export a meteorological data frame in ADMS format
+#'
+#' @param dat A data frame imported by \code{\link{importNOAA}}.
+#' @param out A file name for the ADMS file. The file is written to the working
+#'   directory by default.
+#' @param interp Should interpolation of missing values be undertaken? If
+#'   \code{TRUE} linear interpolation is carried out for gaps of up to and
+#'   including \code{maxgap}.
+#' @param maxgap The maximum gap in hours that should be interpolated where
+#'   there are missing data when \code{interp = TRUE.} Data with gaps more than
+#'   \code{maxgap} are left as missing.
+#'
+#' @return Writes a text file to a location of the user's choosing.
+#' @export
+#' @importFrom zoo na.approx
+#' @examples
+#'
+#' \dontrun{
+#' ## import some data then export it
+#' dat <- importNOAA(year = 2012)
+#' exportADMS(dat, file = "~/temp/adms_met.MET")
+#' }
+exportADMS <- function(dat, out = "./ADMS_met.MET", interp = FALSE, maxgap = 2) {
+
+  # keep R check quiet
+  wd <- u <- v <- NULL
+
+  ## make sure the data do not have gaps
+  all.dates <- data.frame(
+    date = seq(ISOdatetime(
+      year = as.numeric(format(dat$date[1], "%Y")),
+      month = 1, day = 1, hour = 0, min = 0,
+      sec = 0, tz = "GMT"
+    ),
+    ISOdatetime(
+      year = as.numeric(format(dat$date[1], "%Y")),
+      month = 12, day = 31, hour = 23, min = 0,
+      sec = 0, tz = "GMT"
+    ),
+    by = "hour"
+    )
+  )
+
+  dat <- merge(dat, all.dates, all = TRUE)
+
+  ## make sure precipitation is available
+  if (!"precip" %in% names(dat)) {
+    dat$precip <- NA
+  }
+
+  if (interp) {
+
+    ## variables to interpolate
+    ## note need to deal with wd properly
+    dat <- transform(dat, u = sin(pi * wd / 180), v = cos(pi * wd / 180))
+
+    varInterp <- c("ws", "u", "v", "air_temp", "RH", "cl", "precip")
+
+    # don't want to try and interpret fields that are all missing
+    ids <- sapply(varInterp, function(x) !all(is.na(dat[[x]])))
+    varInterp <- varInterp[ids]
+
+    dat[varInterp] <- zoo::na.approx(dat[varInterp], maxgap = maxgap, na.rm = FALSE)
+
+    ## now put wd back
+    dat <- transform(dat, wd = as.vector(atan2(u, v) * 360 / 2 / pi))
+
+    ## correct for negative wind directions
+    ids <- which(dat$wd < 0) ## ids where wd < 0
+    dat$wd[ids] <- dat$wd[ids] + 360
+  }
+
+  ## exports met data to ADMS format file
+  year <- as.numeric(format(dat$date, "%Y"))
+  day <- as.numeric(format(dat$date, "%j"))
+  hour <- as.numeric(format(dat$date, "%H"))
+  station <- "0000"
+
+  ## data frame of met data needed
+  adms <- data.frame(station, year, day, hour,
+    round(dat$air_temp, 1), round(dat$ws, 1),
+    round(dat$wd, 1), round(dat$RH, 1),
+    round(dat$cl), round(dat$precip, 1),
+    stringsAsFactors = FALSE
+  )
+
+  ## print key data capture rates to the screen
+  dc <- round(100 - 100 * (length(which(is.na(dat$ws))) / length(dat$ws)), 1)
+  print(paste("Data capture for wind speed:", dc, "%"))
+
+  dc <- round(100 - 100 * (length(which(is.na(dat$wd))) / length(dat$wd)), 1)
+  print(paste("Data capture for wind direction:", dc, "%"))
+
+  dc <- round(100 - 100 * (length(which(is.na(dat$air_temp))) / length(dat$air_temp)), 1)
+  print(paste("Data capture for temperature:", dc, "%"))
+
+  dc <- round(100 - 100 * (length(which(is.na(dat$cl))) / length(dat$cl)), 1)
+  print(paste("Data capture for cloud cover:", dc, "%"))
+
+  ## replace NA with -999
+  adms[] <- lapply(adms, function(x) replace(x, is.na(x), -999))
+
+  ## write the data file
+  write.table(adms,
+    file = out, col.names = FALSE, row.names = FALSE,
+    sep = ",", quote = FALSE
+  )
+
+  ## add the header lines
+  fConn <- file(out, "r+")
+  Lines <- readLines(fConn)
+  writeLines(c(
+    "VARIABLES:\n10\nSTATION DCNN\nYEAR\nTDAY\nTHOUR\nT0C\nU\nPHI\nRHUM\nCL\nP\nDATA:",
+    Lines
+  ), con = fConn)
+  close(fConn)
+}