# R script for batch parsing and loading GHCN daily station files

# (*.dly) into a SQLite database. Script will process all such files in

# the current working directory.

#

# As written, the script is intended to create and populate the database

# from scratch, reporting an error if it already exists. In principle

# though, the code that processes and loads a given *.dly file could be

# run on its own to load additional data into an already existing

# database file.

#

# At the moment, only TMIN and TMAX are loaded, but that can easily be

# changed.

#

# Jim Regetz

# NCEAS

# Created on 09-May-2012

require(RSQLite)

#-------------#

# "constants" #

#-------------#

# name of target db

db.path <- "ghcn_all.db"

# variables to keep

VARS <- c("TMIN", "TMAX")

# column characteristics of the *.dly data files

DLY.COLS <- c("character", "integer", "integer", "character",

    rep(c("numeric", "character", "character", "character"), times=31))

NUM.WIDE.COLS <- 4 + 4*31

DAYS <- lapply(seq(from=5, to=NUM.WIDE.COLS, by=4), function(i) i:(i+3))

#------------------#

# helper functions #

#------------------#

# bulk insert helper function (adapted from RSQLite documentation)

ghcn_bulk_insert <- function(db, sql, dat) {

    dbBeginTransaction(db)

    dbGetPreparedQuery(db, sql, bind.data = dat)

    dbCommit(db)

}

# shell out to OS to leverage grep/awk/tr for faster initial parsing and

# filtering of data; if no data records are read in, this function

# returns NULL

loadAsCSV <- function(dly, patt=NULL) {

    awk <- paste(

        "awk -v FIELDWIDTHS='",

        paste(c(11, 4, 2, 4, rep(c(5,1,1,1), times=31)), collapse=" "),

        "' -v OFS=',' '{ $1=$1 \"\"; print }'", sep="")

    tr <- "tr -d ' '"

    if (is.null(patt)) {

        cmd <- paste(awk, dly, "|", tr)

    } else {

        patt <- shQuote(paste(patt, collapse="\\|"))

        cmd <- paste("grep -e", patt, dly, "|", awk, "|", tr)

    }

    csv <- system(cmd, intern=TRUE)

    if (length(csv)>0) {

        read.csv(textConnection(csv), header=FALSE, colClasses=DLY.COLS)

    } else {

        NULL

    }

}

# split data columnwise by day, then recombine into long format; note

# that the indexing here is hard-coded to work for the *.dly files, and

# simply assumes that they are all consistent

wideToLong <- function(dat, days) {

    daily.data <- lapply(seq_along(days), function(i) {

        dat <- data.frame(dat[1:4], day=i, dat[days[[i]]])

        dat$srcrowid <- seq(nrow(dat))

        names(dat) <- 1:ncol(dat)

        dat

        })

    do.call("rbind", daily.data)

}

#-----------------#

# procedural code #

#-----------------#

# establish database connection

con <- dbDriver("SQLite")

if (file.exists(db.path)) {

    stop("database already exists at ", db.path)

}

db <- dbConnect(con, dbname=db.path)

# create main ghcn table

sql <- "

    CREATE TABLE ghcn (

        id text,

        year int,

        month int,

        element text,

        day int,

        value int,

        mflag text,

        qflag text,

        sflag text,

        srcrowid int)

"

dbGetQuery(db, sql)

# prepare sql insert statement

params.clist <- paste(rep("?", length(dbListFields(db, "ghcn"))),

    collapse=", ")

sql <- paste("insert into ghcn values (", params.clist, ")", sep="")

# process and insert daily data

dailies <- list.files(pattern="*.dly")

for (file in dailies) {

    dly <- loadAsCSV(file, VARS)

    if (!is.null(dly)) {

        long <- wideToLong(dly, DAYS)

        ghcn_bulk_insert(db, sql, long)

    } else {

        message("no rows imported for ", file)

    }

}