CRAN version 1.2.111

MazamaScience · Jul 8, 2020 · d2e1cc0 · d2e1cc0
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Type: Package
 Package: PWFSLSmoke
-Version: 1.2.109
+Version: 1.2.111
 Title: Utilities for Working with Air Quality Monitoring Data
 Authors@R: c(
     person("Jonathan", "Callahan", email="[email protected]", role=c("aut","cre")), 

diff --git a/NAMESPACE b/NAMESPACE
@@ -194,5 +194,4 @@ importFrom(methods,as)
 importFrom(rlang,":=")
 importFrom(rlang,.data)
 importFrom(utils,download.file)
-importFrom(utils,installed.packages)
 importFrom(utils,read.table)
diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,19 @@
+# PWFSLSmoke 1.2.111
+
+CRAN manual review suggestions:
+
+* Use `find.package()` instead of the much slower `installed.packages()` to
+determine if a package is installed.
+* When using `par()` to set graphical parameters, always use save the previously
+set parameters and then `on.exit(par(opar))` as the very next line.
+* Ensure that `tempdir()` or `tempfile()` are used in all examples, tests and
+vignettes so that no files are written to user directories.
+* Changed many examples from `\dontrun{}` to `\donttest{}`.
+
+# PWFSLSmoke 1.2.110
+
+* Tweaks for CRAN submission.
+
 # PWFSLSmoke 1.2.109
 
 * Removed logging setup from `initializeMazamaSpatialutils()`.

diff --git a/R/addEsriAddress.R b/R/addEsriAddress.R
@@ -1,7 +1,6 @@
 #' @keywords internal
 #' @export
 #' @import MazamaCoreUtils
-#' @importFrom utils installed.packages
 #'
 #' @title Add address information to a dataframe
 #'

diff --git a/R/addGoogleAddress.R b/R/addGoogleAddress.R
@@ -1,7 +1,6 @@
 #' @keywords internal
 #' @export
 #' @import MazamaCoreUtils
-#' @importFrom utils installed.packages
 #'
 #' @title Add address information to a dataframe
 #'
@@ -53,7 +52,7 @@ addGoogleAddress <- function(
 
   # Use ggmap::revgeocode to return a dataframe with (address, street number, route, locality , ...)
   # (2500 queries allowed per day in August, 2015)
-  if ('ggmap' %in% installed.packages()[,1]) {
+  if ( length(find.package("ggmap", quiet = TRUE)) > 0 ) {
 
     for ( i in seq_len(nrow(df)) ) {
 

diff --git a/R/addGoogleElevation.R b/R/addGoogleElevation.R
@@ -1,7 +1,7 @@
 #' @keywords internal
 #' @export
 #' @import MazamaCoreUtils
-#' @importFrom utils installed.packages
+#'
 #' @title Add Elevation Data to a Dataframe
 #' @param df dataframe with geolocation information (\emph{e.g.} those created by \code{wrcc_qualityControl()} or \code{airsis_qualityControl})
 #' @param lonVar name of longitude variable in the incoming dataframe
@@ -69,7 +69,7 @@ addGoogleElevation <- function(
     dfList <- list()
     for (i in 1:loopCount) {
 
-      startIndex <- (i-1) * 300 + 1
+      startIndex <- (i - 1) * 300 + 1
       if (i != loopCount) {
         endIndex <- i * 300
       } else {

diff --git a/R/addUSGSElevation.R b/R/addUSGSElevation.R
@@ -2,8 +2,6 @@
 #' @export
 #' @import MazamaCoreUtils
 #'
-#' @importFrom utils installed.packages
-#'
 #' @title Add Elevation Data to a Dataframe
 #' @param df dataframe with geolocation information (\emph{e.g.} created by \code{wrcc_qualityControl()} or \code{airsis_qualityControl})
 #' @param lonVar name of longitude variable in the incoming dataframe
@@ -24,7 +22,7 @@ addUSGSElevation <- function(
   logger.debug(" ----- addUSGSElevation() ----- ")
 
   # Sanity check -- make sure df does not have class "tbl_df" or "tibble"
-  df <- as.data.frame(df, stringsAsFactors=FALSE)
+  df <- as.data.frame(df, stringsAsFactors = FALSE)
 
   # Sanity check -- names
   if ( !lonVar %in% names(df) || !latVar %in% names(df) ) {
@@ -46,7 +44,7 @@ addUSGSElevation <- function(
     # NOTE:  If existingMeta is passed in, assume we are in an operational environment where we want to minimize web service calls.
 
     # Sanity check -- make sure df does not have class "tbl_df" or "tibble"
-    df <- as.data.frame(df, stringsAsFactors=FALSE)
+    df <- as.data.frame(df, stringsAsFactors = FALSE)
 
     for ( i in seq_len(nrow(df)) ) {
       monitorID <- df[i,'monitorID']
@@ -73,10 +71,10 @@ addUSGSElevation <- function(
       lon <- lons[i]
       lat <- lats[i]
 
-      url$query <- list(x=lon,
-                        y=lat,
-                        units='Meters',
-                        output='json')
+      url$query <- list(x = lon,
+                        y = lat,
+                        units = 'Meters',
+                        output = 'json')
 
       # Get and parse the return
       r <- httr::GET(httr::build_url(url))

diff --git a/R/airsis_createRawDataframe.R b/R/airsis_createRawDataframe.R
@@ -39,6 +39,8 @@
 #'
 #' @examples
 #' \dontrun{
+#' library(PWFSLSmoke)
+#'
 #' raw <- airsis_createRawDataframe(startdate = 20160901,
 #'                                  provider = 'USFS',
 #'                                  unitID = '1033')

diff --git a/R/monitor_aqi.R b/R/monitor_aqi.R
@@ -10,17 +10,21 @@
 #' @references \url{https://docs.airnowapi.org/aq101}
 #' @examples
 #' \dontrun{
+#' library(PWFSLSmoke)
+#'
 #' ws_monitor <- monitor_subset(Northwest_Megafires, tlim=c(20150815,20150831))
 #' aqi <- monitor_aqi(ws_monitor)
 #' monitor_timeseriesPlot(aqi, monitorID=aqi$meta$monitorID[1], ylab="PM25 AQI")
 #' }
 
 # NOTE: set up with argument to handle pm25 only; but write code to handle other pollutants if we ever get there
 
-monitor_aqi <- function(ws_monitor,
-                        aqiParameter='pm25',
-                        nowcastVersion='pm',
-                        includeShortTerm=FALSE) {
+monitor_aqi <- function(
+  ws_monitor,
+  aqiParameter = 'pm25',
+  nowcastVersion = 'pm',
+  includeShortTerm = FALSE
+) {
 
   # Sanity check
   if ( monitor_isEmpty(ws_monitor) ) stop("ws_monitor object contains zero monitors")
@@ -40,7 +44,7 @@ monitor_aqi <- function(ws_monitor,
   data[data<0] <- 0
 
   # TODO: include/expand checks to ensure values are appropriately truncated
-  if ( aqiParameter=="pm25" || nowcastVersion=="pm" ) {
+  if ( aqiParameter == "pm25" || nowcastVersion == "pm" ) {
     digits <- 1
   } else {
     digits <- 0
@@ -80,10 +84,12 @@ monitor_aqi <- function(ws_monitor,
 
   if ( parameter == "pm25") {
     # From Table 2 at https://www.ecfr.gov/cgi-bin/retrieveECFR?n=40y6.0.1.1.6#ap40.6.58_161.g
-    breakpointsTable <- data.frame(rangeLow=c(0.0, 12.1, 35.5, 55.5, 150.5, 250.5, 350.5),
-                                   rangeHigh=c(12.0, 35.4, 55.4, 150.4, 250.4, 350.4, 500.4),
-                                   aqiLow=c(0, 51, 101, 151, 201, 301, 401),
-                                   aqiHigh=c(50, 100, 150, 200, 300, 400, 500))
+    breakpointsTable <- data.frame(
+      rangeLow = c(0.0, 12.1, 35.5, 55.5, 150.5, 250.5, 350.5),
+      rangeHigh = c(12.0, 35.4, 55.4, 150.4, 250.4, 350.4, 500.4),
+      aqiLow = c(0, 51, 101, 151, 201, 301, 401),
+      aqiHigh = c(50, 100, 150, 200, 300, 400, 500)
+    )
   } else {
     stop("only pm25 currently supported")
   }

diff --git a/R/monitor_asDataframe.R b/R/monitor_asDataframe.R
@@ -36,12 +36,17 @@
 #' @seealso \code{\link{monitor_nowcast}}
 #' @seealso \code{\link{monitor_dailyStatistic}}
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
 #' wa <- monitor_subset(Northwest_Megafires, stateCodes='WA')
+#'
 #' Omak_df <- monitor_asDataframe(wa, monitorID='530470013_01',
 #'                                extraColumns=c('nowcast','dailyAvg'),
 #'                                metaColumns=c('aqsID','siteName','timezone'),
 #'                                tlim=c(20150801,20150901))
+#'
+#' dplyr::glimpse(Omak_df)
 #' }
 
 

diff --git a/R/monitor_collapse.R b/R/monitor_collapse.R
@@ -35,11 +35,15 @@
 #' @export
 #'
 #' @examples
+#' library(PWFSLSmoke)
+#'
 #' N_M <- Northwest_Megafires
 #' # monitor_leaflet(N_M) # to identify Spokane monitorIDs
+#'
 #' Spokane <- monitor_subsetBy(N_M, stringr::str_detect(N_M$meta$monitorID,'^53063'))
 #' Spokane_min <- monitor_collapse(Spokane, monitorID='Spokane_min', FUN=min)
 #' Spokane_max <- monitor_collapse(Spokane, monitorID='Spokane_max', FUN=max)
+#'
 #' monitor_timeseriesPlot(Spokane, tlim=c(20150619,20150626),
 #'                        style='gnats', shadedNight=TRUE)
 #' monitor_timeseriesPlot(Spokane_max, col='red', type='s', add=TRUE)

diff --git a/R/monitor_combine.R b/R/monitor_combine.R
@@ -11,14 +11,20 @@
 #' objects. This can be used to 'grow' a \emph{ws_monitor} object by appending subsequent months
 #' or years. (Note, however, that this can be CPU intensive process.)
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#' initializeMazamaSpatialUtils()
+#'
 #' monitorList <- list()
 #' monitorList[[1]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1031')
 #' monitorList[[2]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1032')
 #' monitorList[[3]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1033')
 #' monitorList[[4]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1034')
 #' ws_monitor <- monitor_combine(monitorList)
-#' monitor_leaflet(ws_monitor)
+#'
+#' if ( interactive() ) {
+#'   monitor_leaflet(ws_monitor)
+#' }
 #' }
 
 monitor_combine <- function(monitorList) {

diff --git a/R/monitor_dailyBarplot.R b/R/monitor_dailyBarplot.R
@@ -37,13 +37,14 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
+#' library(PWFSLSmoke)
+#'
 #' N_M <- monitor_subset(Northwest_Megafires, tlim = c(20150715, 20150930))
 #' main <- "Daily Average PM2.5 for Omak, WA"
 #' monitor_dailyBarplot(N_M, monitorID = "530470013_01", main = main,
 #'                          labels_x_nudge = 1)
 #' addAQILegend(fill = rev(AQI$colors), pch = NULL)
-#' }
+
 monitor_dailyBarplot <- function(ws_monitor,
                                  monitorID = NULL,
                                  tlim = NULL,

diff --git a/R/monitor_dailyStatistic.R b/R/monitor_dailyStatistic.R
@@ -22,7 +22,7 @@
 #' The returned \emph{ws_monitor} object has a daily time axis where each
 #' \code{datetime} is set to the beginning of each day, 00:00:00, local time.
 #' @examples
-#' \dontrun{
+#' \donttest{
 #' N_M <- monitor_subset(Northwest_Megafires, tlim=c(20150801,20150831))
 #' WinthropID <- '530470010_01'
 #' TwispID <- '530470009_01'

diff --git a/R/monitor_dailyStatisticList.R b/R/monitor_dailyStatisticList.R
@@ -20,12 +20,17 @@
 #'
 #' @references \link{monitor_dailyStatistic}
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
 #' airnow <- airnow_loadLatest()
 #' nw <- monitor_subset(airnow, stateCodes = c('WA','OR','ID','MT'))
 #' dailyList <- monitor_dailyStatisticList(nw)
+#'
 #' monitor_leaflet(dailyList[["America/Los_Angeles"]])
+#'
 #' monitor_leaflet(dailyList[["America/Boise"]])
+#'
 #' monitor_leaflet(dailyList[["America/Denver"]])
 #' }
 

diff --git a/R/monitor_dailyThreshold.R b/R/monitor_dailyThreshold.R
@@ -18,13 +18,13 @@
 #'
 #' The returned \emph{ws_monitor} object has a daily time axis where each time is set to 00:00, local time.
 #' @examples
-#' \dontrun{
+#' library(PWFSLSmoke)
+#'
 #' N_M <- monitor_subset(Northwest_Megafires, tlim=c(20150801,20150831))
 #' Twisp <- monitor_subset(N_M, monitorIDs='530470009_01')
 #' Twisp_daily <- monitor_dailyThreshold(Twisp, "unhealthy", dayStart='midnight', minHours=1)
 #' monitor_timeseriesPlot(Twisp_daily, type='h', lwd=6, ylab="Hours")
 #' title("Twisp, Washington Hours per day Above 'Unhealthy', 2015")
-#' }
 
 monitor_dailyThreshold <- function(ws_monitor,
                                    threshold="unhealthy",

diff --git a/R/monitor_distance.R b/R/monitor_distance.R
@@ -10,6 +10,8 @@
 #' @return Vector of of distances (km).
 #' @seealso \code{\link{distance}}
 #' @examples
+#' library(PWFSLSmoke)
+#'
 #' N_M <- Northwest_Megafires
 #' # Walla Walla
 #' WW_lon <- -118.330278

diff --git a/R/monitor_downloadAnnual.R b/R/monitor_downloadAnnual.R
@@ -50,17 +50,21 @@
 #' \href{https://haze.airfire.org/monitoring/latest/RData/}{https://haze.airfire.org/monitoring/latest/RData/}
 #' @seealso \code{\link{monitor_loadDaily}}
 #' @examples
-#' \dontrun{
-#' monitor_loadLatest() %>%
-#'   monitor_subset(stateCodes=CONUS) %>%
-#'   monitor_map()
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
+#' monitor_loadAnnual(2018) %>%
+#'   monitor_subset(stateCodes = "WA", tlim = c(20180701, 20181001)) %>%
+#'   monitor_timeseriesPlot(style = 'gnats')
 #' }
 
-monitor_downloadAnnual <- function(year = NULL,
-                                   parameter='PM2.5',
-                                   baseUrl='https://haze.airfire.org/monitoring',
-                                   dataDir = "~/Data/monitoring/RData",
-                                   ...) {
+monitor_downloadAnnual <- function(
+  year = NULL,
+  parameter='PM2.5',
+  baseUrl='https://haze.airfire.org/monitoring',
+  dataDir = "~/Data/monitoring/RData",
+  ...
+) {
 
   # Validate parameters --------------------------------------------------------
 

diff --git a/R/monitor_downloadDaily.R b/R/monitor_downloadDaily.R
@@ -49,7 +49,9 @@
 #' \href{https://haze.airfire.org/monitoring/latest/RData/}{https://haze.airfire.org/monitoring/latest/RData/}
 #' @seealso \code{\link{monitor_loadDaily}}
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
 #' monitor_loadLatest() %>%
 #'   monitor_subset(stateCodes=CONUS) %>%
 #'   monitor_map()

diff --git a/R/monitor_downloadLatest.R b/R/monitor_downloadLatest.R
@@ -49,7 +49,9 @@
 #' \href{https://haze.airfire.org/monitoring/latest/RData/}{https://haze.airfire.org/monitoring/latest/RData/}
 #' @seealso \code{\link{monitor_loadDaily}}
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
 #' monitor_loadLatest() %>%
 #'   monitor_subset(stateCodes=CONUS) %>%
 #'   monitor_map()

diff --git a/R/monitor_dygraph.R b/R/monitor_dygraph.R
@@ -12,16 +12,25 @@
 #'   in RStudio's 'Viewer' tab.
 #' @return Initiates the interactive dygraph plot in RStudio's 'Viewer' tab.
 #' @examples
-#' \dontrun{
+#' \donttest{
+#' library(PWFSLSmoke)
+#'
 #' # Napa Fires -- October, 2017
 #' ca <- airnow_load(2017) %>%
 #'   monitor_subset(tlim=c(20171001,20171101), stateCodes='CA')
+#'
 #' Vallejo <- monitor_subset(ca, monitorIDs='060950004_01')
-#' Napa_Fires <- monitor_subsetByDistance(ca,
-#'                                        longitude = Vallejo$meta$longitude,
-#'                                        latitude = Vallejo$meta$latitude,
-#'                                        radius = 50)
-#' monitor_dygraph(Napa_Fires, title='Napa Fires in California, Oct. 2017')
+#'
+#' Napa_Fires <- monitor_subsetByDistance(
+#'   ca,
+#'   longitude = Vallejo$meta$longitude,
+#'   latitude = Vallejo$meta$latitude,
+#'   radius = 50
+#' )
+#'
+#' if ( interactive() ) {
+#'   monitor_dygraph(Napa_Fires, title='Napa Fires in California, Oct. 2017')
+#' }
 #' }
 
 monitor_dygraph <- function(ws_monitor,