fixed params in nexrad fxn, replace maelles old github user name thro…

…ughout, fix #211

DESCRIPTION

@@ -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: 0.6.7.9211
+Version: 0.6.7.9214
 License: MIT + file LICENSE
 Encoding: UTF-8
 Authors@R: c(

NEWS.md

@@ -3,9 +3,9 @@ rnoaa 0.6.6
 
 ### NEW FEATURES
 
-* `isd()` now using a new package `isdparser` to parse 
-NOAA ISD files. We still fetch the file within `rnoaa`, but the 
-file parsing is done by `isdparser` (#176) (#177) (#180) thanks @mrubayet 
+* `isd()` now using a new package `isdparser` to parse
+NOAA ISD files. We still fetch the file within `rnoaa`, but the
+file parsing is done by `isdparser` (#176) (#177) (#180) thanks @mrubayet
 for the push
 
 ### MINOR IMPROVEMENTS
@@ -15,13 +15,13 @@ thanks @mrubayet
 
 ### BUG FIXES
 
-* Fixed bug in `ghcnd()` where internal unexported function 
+* Fixed bug in `ghcnd()` where internal unexported function
 was not found (#179)
-* Fix to `isd_stations()` and `isd_stations_search()` to work 
+* Fix to `isd_stations()` and `isd_stations_search()` to work
 correctly on Windows (#181) thanks @GuodongZhu
-* Changed base URL for all NOAA NCDC functions (those starting with 
+* Changed base URL for all NOAA NCDC functions (those starting with
 `ncdc`) to `https` from `http` (#182) thanks @maspotts
-* Changed base URL for all NOAA HOMR functions (those starting with 
+* Changed base URL for all NOAA HOMR functions (those starting with
 `homr`) to `https` from `http` (#183)
 
 
@@ -97,7 +97,7 @@ and determine the "coverage" for a station data frame (`meteo_coverage()`).
 In addition, `vis_miss()` added to visualize missingness in a data.frame. See
 the [PR diff against master](https://github.com/ropensci/rnoaa/pull/159/files)
 for all the changes. (#159) Thanks a ton to @geanders _et al_. (@hrbrmstr,
-@masalmon, @jdunic, @njtierney, @leighseverson, @RyanGan, @mandilin, @jferreri,
+@maelle, @jdunic, @njtierney, @leighseverson, @RyanGan, @mandilin, @jferreri,
 @cpatrizio88, @ryan-hicks, @Ewen2015, @mgutilla, @hakessler, @rodlammers)
 
 ### MINOR IMPROVEMENTS

R/ghcnd.R

@@ -185,13 +185,20 @@ ghcnd <- function(stationid, ...){
   if (!is_ghcnd(x = csvpath)) {
     res <- ghcnd_GET(path, stationid, ...)
   } else {
-    res <- read.csv(csvpath, stringsAsFactors = FALSE)
+    # res <- read.csv(csvpath, stringsAsFactors = FALSE)
+    res <- read.csv(csvpath, stringsAsFactors = FALSE,
+                    colClasses = ghcnd_col_classes)
   }
   res <- tibble::as_data_frame(res)
   attr(res, 'source') <- csvpath
   res
 }
 
+ghcnd_col_classes <- c(
+  "character", "integer", "integer", "character",
+  rep(c("integer", "character", "character", "character"), times = 31)
+)
+
 fm <- function(n) {
   gsub("\\s", "0", n)
 }
@@ -453,6 +460,9 @@ ghcnd_GET <- function(bp, stationid, ...){
       lapply(1:31, function(x) paste0(c("VALUE","MFLAG","QFLAG","SFLAG"), x))))
   df <- read.fwf(textConnection(tt), c(11,4,2,4,rep(c(5,1,1,1), 31)),
                  na.strings = "-9999")
+  df[] <- Map(function(a, b) {
+    eval(parse(text = paste0("as.", b)))(a)
+  }, df, ghcnd_col_classes)
   dat <- stats::setNames(df, vars)
   write.csv(dat, fp, row.names = FALSE)
   return(dat)

R/nexrad.R

@@ -1,17 +1,23 @@
 #' NEXRAD II data
 #'
 #' @export
-#' @param x xx
+#' @param year xx
+#' @param month xx
+#' @param day xx
+#' @param station xx
+#' @param filename xx
+#' @param path xx
+#' @param ... curl options
 #' @details
 #' xx
 #' @return data.frame
 #' @examples \dontrun{
 #' f <- tempfile(fileext = ".zip")
 #' nexrad2(2017, 4, 1, 'KAMX', 'KAMX20170401_002500_V06', f)
 #' }
-nexrad2 <- function(year, month, day, station, filename, out, ...) {
+nexrad2 <- function(year, month, day, station, filename, path, ...) {
   url <- file.path(nexs3base(), year, add0(month), add0(day), station, filename)
-  res <- GET(url, write_disk(path, TRUE), verbose())
+  res <- httr::GET(url, write_disk(path, TRUE), httr::verbose())
 }
 
 nexs3base <- function() 'https://noaa-nexrad-level2.s3.amazonaws.com'

README.Rmd

@@ -282,7 +282,7 @@ coops_search(station_name = 9063053, begin_date = 20150927, end_date = 20150928,
 
 * [Scott Chamberlain](https://github.com/sckott)
 * [Brooke Anderson](https://github.com/geanders)
-* [Maëlle Salmon](https://github.com/masalmon)
+* [Maëlle Salmon](https://github.com/maelle)
 * [Adam Erickson](https://github.com/adam-erickson)
 * [Nicholas Potter](https://github.com/potterzot)
 * [Joseph Stachelek](https://github.com/jsta)

README.md

@@ -145,14 +145,14 @@ ncdc_locs(locationcategoryid='CITY', sortfield='name', sortorder='desc')
 #> $meta
 #> $meta$totalCount
 #> [1] 1980
-#> 
+#>
 #> $meta$pageCount
 #> [1] 25
-#> 
+#>
 #> $meta$offset
 #> [1] 1
-#> 
-#> 
+#>
+#>
 #> $data
 #>       mindate    maxdate                  name datacoverage            id
 #> 1  1892-08-01 2016-12-31            Zwolle, NL       1.0000 CITY:NL000012
@@ -180,7 +180,7 @@ ncdc_locs(locationcategoryid='CITY', sortfield='name', sortorder='desc')
 #> 23 1893-01-01 2017-02-14     Youngstown, OH US       1.0000 CITY:US390028
 #> 24 1894-01-01 2017-02-14           York, PA US       1.0000 CITY:US420024
 #> 25 1876-01-01 2017-02-14        Yonkers, NY US       1.0000 CITY:US360031
-#> 
+#>
 #> attr(,"class")
 #> [1] "ncdc_locs"
 ```
@@ -192,13 +192,13 @@ ncdc_locs(locationcategoryid='CITY', sortfield='name', sortorder='desc')
 ncdc_stations(datasetid='GHCND', locationid='FIPS:12017', stationid='GHCND:USC00084289')
 #> $meta
 #> NULL
-#> 
+#>
 #> $data
 #>   elevation    mindate    maxdate latitude                  name
 #> 1      12.2 1899-02-01 2017-02-13  28.8029 INVERNESS 3 SE, FL US
 #>   datacoverage                id elevationUnit longitude
 #> 1            1 GHCND:USC00084289        METERS  -82.3126
-#> 
+#>
 #> attr(,"class")
 #> [1] "ncdc_stations"
 ```
@@ -256,14 +256,14 @@ ncdc_datasets()
 #> $meta
 #> $meta$offset
 #> [1] 1
-#> 
+#>
 #> $meta$count
 #> [1] 11
-#> 
+#>
 #> $meta$limit
 #> [1] 25
-#> 
-#> 
+#>
+#>
 #> $data
 #>                     uid    mindate    maxdate                        name
 #> 1  gov.noaa.ncdc:C00861 1763-01-01 2017-02-14             Daily Summaries
@@ -289,7 +289,7 @@ ncdc_datasets()
 #> 9          1.00 NORMAL_MLY
 #> 10         0.25  PRECIP_15
 #> 11         1.00 PRECIP_HLY
-#> 
+#>
 #> attr(,"class")
 #> [1] "ncdc_datasets"
 ```
@@ -302,14 +302,14 @@ ncdc_datacats(locationid = 'CITY:US390029')
 #> $meta
 #> $meta$totalCount
 #> [1] 38
-#> 
+#>
 #> $meta$pageCount
 #> [1] 25
-#> 
+#>
 #> $meta$offset
 #> [1] 1
-#> 
-#> 
+#>
+#>
 #> $data
 #>                     name            id
 #> 1    Annual Agricultural        ANNAGR
@@ -337,7 +337,7 @@ ncdc_datacats(locationid = 'CITY:US390029')
 #> 23  Spring Precipitation        SPPRCP
 #> 24    Spring Temperature        SPTEMP
 #> 25   Summer Agricultural         SUAGR
-#> 
+#>
 #> attr(,"class")
 #> [1] "ncdc_datacats"
 ```
@@ -349,15 +349,15 @@ The function `tornadoes()` simply gets __all the data__. So the call takes a whi
 
 ```r
 shp <- tornadoes()
-#> OGR data source with driver: ESRI Shapefile 
+#> OGR data source with driver: ESRI Shapefile
 #> Source: "/Users/sacmac/.rnoaa/tornadoes/tornadoes", layer: "tornado"
 #> with 57988 features
 #> It has 21 fields
 library('sp')
 plot(shp)
 ```
 
-![plot of chunk unnamed-chunk-17](inst/img/unnamed-chunk-17-1.png) 
+![plot of chunk unnamed-chunk-17](inst/img/unnamed-chunk-17-1.png)
 
 ## HOMR metadata
 
@@ -369,19 +369,19 @@ homr(qid = 'COOP:046742')
 #> $`20002078`
 #> $`20002078`$id
 #> [1] "20002078"
-#> 
+#>
 #> $`20002078`$head
 #>                  preferredName latitude_dec longitude_dec precision
 #> 1 PASO ROBLES MUNICIPAL AP, CA      35.6697     -120.6283    DDMMSS
 #>             por.beginDate por.endDate
 #> 1 1949-10-05T00:00:00.000     Present
-#> 
+#>
 #> $`20002078`$namez
 #>                         name  nameType
 #> 1   PASO ROBLES MUNICIPAL AP      COOP
 #> 2   PASO ROBLES MUNICIPAL AP PRINCIPAL
 #> 3 PASO ROBLES MUNICIPAL ARPT       PUB
-#> 
+#>
 #> $`20002078`$identifiers
 #>      idType          id
 #> 1     GHCND USW00093209
@@ -469,17 +469,17 @@ coops_search(station_name = 9063053, begin_date = 20150927, end_date = 20150928,
 #> $metadata
 #> $metadata$id
 #> [1] "9063053"
-#> 
+#>
 #> $metadata$name
 #> [1] "Fairport"
-#> 
+#>
 #> $metadata$lat
 #> [1] "41.7598"
-#> 
+#>
 #> $metadata$lon
 #> [1] "-81.2811"
-#> 
-#> 
+#>
+#>
 #> $data
 #>            t       v   f
 #> 1 2015-09-27 174.430 0,0
@@ -490,7 +490,7 @@ coops_search(station_name = 9063053, begin_date = 20150927, end_date = 20150928,
 
 * [Scott Chamberlain](https://github.com/sckott)
 * [Brooke Anderson](https://github.com/geanders)
-* [Maëlle Salmon](https://github.com/masalmon)
+* [Maëlle Salmon](https://github.com/maelle)
 * [Adam Erickson](https://github.com/adam-erickson)
 * [Nicholas Potter](https://github.com/potterzot)
 * [Joseph Stachelek](https://github.com/jsta)

inst/vign/rnoaa_ropenaq.Rmd

@@ -10,15 +10,15 @@ __Author__ Maëlle Salmon
 
 # Introduction: getting air quality data
 
-This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/masalmon/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
+This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/ropensci/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
 
 First, we need to know how many measures are available for Delhi for March 2016.
 
 ```{r, message = FALSE, warning = FALSE, eval = FALSE, echo = TRUE}
 library("ropenaq")
 
 measurementsDelhi <- aq_measurements(city = "Delhi", parameter = "pm25",
-                                     date_from = "2016-03-01", 
+                                     date_from = "2016-03-01",
                                      date_to = "2016-03-31")
 
 save(measurementsDelhi, file = "data/measurementsDelhi.RData")

inst/vign/rnoaa_ropenaq.md

@@ -10,7 +10,7 @@ __Author__ Maëlle Salmon
 
 # Introduction: getting air quality data
 
-This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/masalmon/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
+This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/ropensci/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
 
 First, we need to know how many measures are available for Delhi for March 2016.
 
@@ -19,7 +19,7 @@ First, we need to know how many measures are available for Delhi for March 2016.
 library("ropenaq")
 
 measurementsDelhi <- aq_measurements(city = "Delhi", parameter = "pm25",
-                                     date_from = "2016-03-01", 
+                                     date_from = "2016-03-01",
                                      date_to = "2016-03-31")
 
 save(measurementsDelhi, file = "data/measurementsDelhi.RData")

tests/testthat/test-ghcnd.R

@@ -69,7 +69,15 @@ test_that("get data", {
   expect_is(aa, "data.frame")
   expect_is(bb, "data.frame")
   expect_is(cc, "data.frame")
+
+  expect_is(aa$id, "character")
+  expect_is(aa$year, "integer")
+  expect_is(aa$month, "integer")
   expect_is(aa$element, "character")
+  expect_is(aa$VALUE1, "integer")
+  expect_is(aa$MFLAG1, "character")
+  expect_is(aa$QFLAG1, "character")
+  expect_is(aa$SFLAG1, "character")
 
   expect_lt(NROW(cc), NROW(aa))
   expect_lt(NROW(aa), NROW(bb))

vignettes/rnoaa_ropenaq.Rmd

@@ -10,7 +10,7 @@ __Author__ Maëlle Salmon
 
 # Introduction: getting air quality data
 
-This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/masalmon/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
+This vignette aims at explaining how you can complement a data.frame with weather data using rnoaa. In this vignette we shall use air quality data from the OpenAQ platform queried with the ropenaq package, for India. Using [ropenaq](https://github.com/ropensci/ropenaq) one can get e.g. PM2.5 values over time in Delhi in March 2016. For getting all data for march we'll loop over several pages.
 
 First, we need to know how many measures are available for Delhi for March 2016.
 
@@ -19,7 +19,7 @@ First, we need to know how many measures are available for Delhi for March 2016.
 library("ropenaq")
 
 measurementsDelhi <- aq_measurements(city = "Delhi", parameter = "pm25",
-                                     date_from = "2016-03-01", 
+                                     date_from = "2016-03-01",
                                      date_to = "2016-03-31")
 
 save(measurementsDelhi, file = "data/measurementsDelhi.RData")