various cleanup for v_0.9.3

DESCRIPTION

@@ -26,7 +26,7 @@ Depends:
     MazamaSpatialUtils (>= 0.4.4)
 Imports:
     cluster,
-    dygraphs,
+    dygraphs (>= 1.1.1.4),
     futile.logger,
     ggmap,
     httr,

NAMESPACE

@@ -16,7 +16,6 @@ export(addLegend)
 export(addMazamaMetadata)
 export(addShadedBackground)
 export(addShadedNights)
-export(adjustRange)
 export(airnow_createDataDataframes)
 export(airnow_createMetaDataframes)
 export(airnow_downloadData)
@@ -35,7 +34,6 @@ export(airsis_createMonitorObject)
 export(airsis_createRawDataframe)
 export(airsis_downloadData)
 export(airsis_identifyMonitorType)
-export(airsis_load)
 export(airsis_loadLatest)
 export(airsis_parseData)
 export(airsis_qualityControl)
@@ -48,8 +46,9 @@ export(logger.setLevel)
 export(logger.setup)
 export(logger.trace)
 export(logger.warn)
+export(monitorDygraph)
 export(monitorGoogleMap)
-export(monitorInteractiveMap)
+export(monitorLeaflet)
 export(monitorMap)
 export(monitorMap_performance)
 export(monitorPlot_dailyBarplot)
@@ -59,11 +58,11 @@ export(monitorPlot_rollingMean)
 export(monitorPlot_timeOfDaySpaghetti)
 export(monitorPlot_timeseries)
 export(monitor_aqi)
+export(monitor_collapse)
 export(monitor_combine)
 export(monitor_dailyStatistic)
 export(monitor_dailyThreshold)
 export(monitor_distance)
-export(monitor_dygraph)
 export(monitor_isolate)
 export(monitor_nowcast)
 export(monitor_performance)
@@ -81,7 +80,6 @@ export(openaq_assignStateCode)
 export(openaq_createDataDataframes)
 export(openaq_createMetaDataframes)
 export(openaq_downloadData)
-export(openaq_load)
 export(parseDatetime)
 export(rawPlot_pollutionRose)
 export(rawPlot_timeOfDaySpaghetti)
@@ -104,7 +102,7 @@ export(wrcc_createMonitorObject)
 export(wrcc_createRawDataframe)
 export(wrcc_downloadData)
 export(wrcc_identifyMonitorType)
-export(wrcc_load)
+export(wrcc_loadLatest)
 export(wrcc_parseData)
 export(wrcc_qualityControl)
 import(MazamaSpatialUtils)

R/airnow_downloadHourlyData.R

@@ -1,11 +1,9 @@
-#' @keywords internal AirNow
+#' @keywords AirNow
 #' @export
 #' @importFrom utils read.table
 #' @title Download Hourly Data from AirNow
 #' @param datestamp integer or character representing YYYYMMDDHH
-#' @param tries number of download attempts in the face of timeouts
 #' @param baseUrl base URL for archived hourly data
-#' @param curl previously initialized CURL context/handle (see RCurl::getURL())
 #' @return Dataframe of AirNow hourly data.
 #' @description The \url{http://airnowtech.org} site provides both air pollution
 #' monitoring data as well as monitoring site location metadata. The \code{airnow_downloadHourlyData()}

R/airnow_load.R

@@ -15,7 +15,7 @@
 #' \dontrun{
 #' airnow <- airnow_load(20150901, 20150930)
 #' airnow_conus <- monitor_subset(airnow, stateCodes=CONUS)
-#' monitorInteractiveMap(airnow_conus)
+#' monitorLeaflet(airnow_conus)
 #' }
 
 airnow_load <- function(startdate, enddate, stateCodes=NULL, monitorIDs=NULL,

R/airsisDump_createMonitorObject.R

@@ -1,4 +1,4 @@
-#' @keywords AIRSIS
+#' @keywords internal
 #' @export
 #' @title Ingest AIRSIS Dump File and Create ws_monitor Object
 #' @param filepath absolute path of the AIRSIS dump file

R/airsisDump_identifyMonitorType.R

@@ -1,4 +1,4 @@
-#' @keywords AIRSIS
+#' @keywords internal
 #' @export
 #' @title Identify AIRSIS Dump File Monitor Type
 #' @param df dataframe or raw character string containing AIRSIS data

R/airsisDump_parseData.R

@@ -1,4 +1,4 @@
-#' @keywords AIRSIS
+#' @keywords internal
 #' @export
 #' @title Parse AIRSIS Dump File Data String
 #' @param fileString character string containing AIRSIS data as a csv

R/airsis_createMonitorObject.R

@@ -31,6 +31,11 @@
 #' @seealso \code{\link{addClustering}}
 #' @seealso \code{\link{airsis_createMetaDataframe}}
 #' @seealso \code{\link{airsis_createDataDataframe}}
+#' @examples
+#' \dontrun{
+#' usfs_1013 <- airsis_createMonitorObject(20150301, 20150831, 'USFS', unitID='1013')
+#' monitorLeaflet(usfs_1013)
+#' }
 
 airsis_createMonitorObject <- function(startdate=20020101,
                                        enddate=strftime(lubridate::now(),"%Y%m%d",tz="GMT"),
@@ -49,6 +54,19 @@ airsis_createMonitorObject <- function(startdate=20020101,
     logger.error("Required parameter 'unitID' is missing")
     stop(paste0("Required parameter 'unitID' is missing"))
   }
+
+  startdateCount <- stringr::str_count(as.character(startdate))
+  if ( !startdateCount %in% c(8,10,12) ) {
+    logger.error("Cannot parse 'startdate' with %d characters", startdateCount)
+    stop(paste0("Cannot parse 'startdate' with ",startdateCount," characters"))
+  }
+
+  enddateCount <- stringr::str_count(as.character(enddate))
+  if ( !enddateCount %in% c(8,10,12) ) {
+    logger.error("Cannot parse 'enddate' with %d characters", enddateCount)
+    stop(paste0("Cannot parse 'enddate' with ",enddateCount," characters"))
+  }
+
 
   # Read in AIRSIS .csv data
   logger.info("Downloading AIRSIS data ...")

R/airsis_loadLatest.R

@@ -2,38 +2,17 @@
 #' @export
 #' @title Load Recent AIRSIS Monitoring Data
 #' @param baseUrl The location of the meta and data files
-#' @description The most recent 10 days of AIRSIS data are updated in quasi-real time
+#' @description The most recent 45 days of AIRSIS data are updated in real time
 #' at PWFSL and can be loaded with this function.
 #' @return A ws_monitor object with AIRSIS data.
 #' @examples
 #' \dontrun{
 #' airsis <- airsis_loadLatest()
 #' }
 
-airsis_loadLatest <- function(baseUrl='http://tools.airfire.org/monitoring/v3/data') {
+airsis_loadLatest <- function(baseUrl='https://haze.airfire.org/monitoring/RData/airsis_pm25_latest.RData') {
 
-  # Get the most recent data and metadata
-  data <- get(load(url(paste0(baseUrl,'/EBAM_PM2.5_Latest.RData'))))
-  meta <- get(load(url(paste0(baseUrl,'/EBAM_SitesMetadata.RData'))))
-
-  # Only include metadata for sites found in data
-  meta <- monitor_subsetMeta(meta, monitorIDs=colnames(data)[-1])
-
-  # Add missing metadata to 'old-style' Latest data
-  # The columns are already present but may contain missing data
-  if ( any(is.na(meta$timezone)) || any(is.na(meta$countryCode)) || any(is.na(meta$stateCode)) ) {
-    meta <- addMazamaMetadata(meta)
-  }
-  if ( any(is.na(meta$elevation)) || any(is.na(meta$siteName)) ) { # OK if countyName is NA
-    meta <- addGoogleMetadata(meta)
-  }
-
-  # Create the 'ws_monitor' object
-  ws_monitor <- list(meta=meta, data=data)
-  ws_monitor <- structure(ws_monitor, class = c("ws_monitor", "list"))
-
-  # Run through subsetting to remove sites with all missing data
-  ws_monitor <- monitor_subset(ws_monitor, dropMonitors=TRUE)
+  ws_monitor <- get(load(url(baseUrl)))
 
   return(ws_monitor)
 }

R/distance.R

@@ -9,6 +9,15 @@
 #' than the spherical law of cosines for very short distances.
 #' @references \url{http://www.r-bloggers.com/great-circle-distance-calculations-in-r/} 
 #' @return Vector of distances in km.
+#' @examples
+#' \dontrun{
+#' # Seattle to Portland airports
+#' SEA_lon <- -122.3088
+#' SEA_lat <- 47.4502
+#' PDX_lon <- -122.5951
+#' PDX_lat <- 45.5898
+#' distance(SEA_lon, SEA_lat, PDX_lon, PDX_lat)
+#' }
 
 distance <- function(targetLon, targetLat, lons, lats) {
 

R/monitor_dygraph.R → R/monitorDygraph.R

@@ -13,11 +13,11 @@
 #' \dontrun{
 #' airnow <- airnow_load(20140913, 20141010)
 #' King_Fire <- monitor_subsetByDistance(airnow, lon=-120.604, lat=38.782, radius=50)
-#' monitor_dygraph(King_Fire, title='KingFire/California/2014', rollPeriod=3)
+#' monitorDygraph(King_Fire, title='KingFire/California/2014', rollPeriod=3)
 #' } 
 
-monitor_dygraph <- function(ws_monitor, title='title', ylab='PM2.5 Concentration', 
-                            dateWindow=NULL, rollPeriod=1, showLegend=TRUE) {
+monitorDygraph <- function(ws_monitor, title='title', ylab='PM2.5 Concentration', 
+                           dateWindow=NULL, rollPeriod=1, showLegend=TRUE) {
 
   # Sanity check
   tzCount <- length(unique(ws_monitor$meta$timezone))

R/monitorInteractiveMap.R → R/monitorLeaflet.R

@@ -36,16 +36,16 @@
 #' airnow <- airnow_load(20140913, 20141010)
 #' v_low <- AQI$breaks_24[4] 
 #' CA_unhealthy_monitors <- monitor_subset(airnow, stateCodes='CA', vlim=c(v_low, Inf))
-#' monitorInteractiveMap(CA_unhealthy_monitors, maptype="toner")
+#' monitorLeaflet(CA_unhealthy_monitors, maptype="toner")
 #' }
 
-monitorInteractiveMap <- function(ws_monitor, slice=get('max'),
-                                  breaks=AQI$breaks_24,
-                                  colors=AQI$colors,
-                                  labels=AQI$names,
-                                  legendTitle='Max AQI Level',
-                                  radius=10, opacity=0.7, maptype="terrain",
-                                  popupInfo=c('siteName','monitorID','elevation')) {
+monitorLeaflet <- function(ws_monitor, slice=get('max'),
+                           breaks=AQI$breaks_24,
+                           colors=AQI$colors,
+                           labels=AQI$names,
+                           legendTitle='Max AQI Level',
+                           radius=10, opacity=0.7, maptype="terrain",
+                           popupInfo=c('siteName','monitorID','elevation')) {
 
   # BEGIN verbatim from monitor_map.R -----------------------------------------
 
@@ -82,7 +82,7 @@ monitorInteractiveMap <- function(ws_monitor, slice=get('max'),
     }
 
     if ( missing(labels) ){
-    labels <- paste(sprintf("%.1f",breaks[-length(breaks)]),'--',sprintf("%.1f",breaks[-1]))
+      labels <- paste(sprintf("%.1f",breaks[-length(breaks)]),'--',sprintf("%.1f",breaks[-1]))
     } else if ( length(labels) != length(colors) ) {
       stop("The number of labels should be equal to the number of colors")
     }

R/monitorMap_performance.R

@@ -30,11 +30,10 @@
 #' @examples 
 #' \dontrun{
 #' # Spokane summer of 2015
-#' airnow <- airnow_load(20150701,20150930)
-#' airnow <- monitor_rollingMean(airnow, width=3)
-#' WA <- monitor_subset(airnow, stateCode='WA', countryCode="US")
-#' MonroeSt <- monitor_subset(WA, monitorIDs=530630047)
-#' monitorMap_performance(WA, MonroeSt, cex=2)
+#' wa <- airnow_load(20150701, 20150930, stateCodes='WA')
+#' wa <- monitor_rollingMean(wa, width=3)
+#' MonroeSt <- monitor_subset(wa, monitorIDs=530630047)
+#' monitorMap_performance(wa, MonroeSt, cex=2)
 #' title('Heidike Skill of monitors predicting another monitor.')
 #' }
 

R/monitorPlot_noData.R

@@ -1,4 +1,4 @@
-#' @keywords ws_monitor
+#' @keywords internal
 #' @export
 #' @import graphics
 #' @title Create Blank Plot with "No Data" Message

R/monitor_collapse.R

@@ -1,5 +1,5 @@
-#' @keywords ws_monitor
-# @export
+#' @keywords internal
+#' @export
 #' @title Collapse a ws_monitor Object into a ws_monitor Object with a Single Monitor
 #' @param ws_monitor ws_monitor object
 #' @param lon longitude of the collapsed monitoring station. (Default = mean of the longitudes)

R/monitor_combine.R

@@ -13,7 +13,7 @@
 #' monitorList[[3]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1033')
 #' monitorList[[4]] <- airsis_createMonitorObject(20160701, 20161231, 'USFS', '1034')
 #' ws_monitor <- monitor_combine(monitorList)
-#' monitorInteractiveMap(ws_monitor)
+#' monitorLeaflet(ws_monitor)
 #' } 
 
 monitor_combine <- function(monitorList) {

R/monitor_dailyThreshold.R

@@ -21,7 +21,7 @@
 #' 
 #' WA_IDS <- AirNow$meta$monitorID[AirNow$meta$stateCode == 'WA']
 #' WA <- monitor_subset(AirNow, monitorIDs=WA_IDS)
-#' monitorInteractiveMap(WA)
+#' monitorLeaflet(WA)
 #' 
 #' # Pull out specific locations
 #' Twisp <- monitor_subset(WA, monitorIDs='530470009')

R/monitor_subsetBy.R

@@ -13,8 +13,8 @@
 #' airnow <- airnow_load(20150101, 20151231)
 #' mySubset <- monitor_subsetBy(airnow, timezone == 'America/Los_Angeles')
 #' hazardousSubset <- monitor_subsetBy(mySubset, data > AQI$breaks_24[6])
-#' monitorInteractiveMap(hazardousSubset,
-#'                 popupInfo=c('siteName', 'agencyName', 'elevation','monitorID'))
+#' monitorLeaflet(hazardousSubset,
+#'                popupInfo=c('siteName', 'agencyName', 'elevation','monitorID'))
 #' }
 
 monitor_subsetBy <- function(ws_monitor, filter) {

R/monitor_subsetByDistance.R

@@ -20,7 +20,7 @@
 #' \dontrun{
 #' airnow <- airnow_load(20140913, 20141010)
 #' KingFire <- monitor_subsetByDistance(airnow, lon=-120.604, lat=38.782, radius=50)
-#' monitorInteractiveMap(KingFire)
+#' monitorLeaflet(KingFire)
 #' } 
 
 monitor_subsetByDistance <- function(ws_monitor, lon=NULL, lat=NULL, radius=50, count=NULL) {

R/monitor_trim.R

@@ -5,7 +5,14 @@
 #' @return A ws_monitor object with missing data trimmed.
 #' @description Trims the time axis of a ws_monitor object to exclude timestamps prior to the first and
 #' after the last valid datapoint for any monitor.
-
+#' @examples
+#' \dontrun{
+#' sm13 <- wrcc_createMonitorObject(20150101, 20151231, stationID='sm13')
+#' sm13$meta[,c('stateCode','countyName','siteName','monitorID')]
+#' Deschutes <- monitor_subset(sm13, monitorIDs='Smoke..13__001')
+#' Deschutes <- monitor_trim(Deschutes)
+#' monitorPlot_dailyBarplot(Deschutes)
+#' }
 monitor_trim <- function(ws_monitor) {
 
   # Vectors of first and last valid indices excluding 'datetime'

R/wrccDump_createMonitorObject.R

@@ -1,4 +1,4 @@
-#' @keywords WRCC
+#' @keywords internal
 #' @export
 #' @title Ingest WRCC Dump File and Create ws_monitor Object
 #' @param filepath absolute path of the WRCC dump file

R/wrccDump_identifyMonitorType.R

@@ -1,4 +1,4 @@
-#' @keywords WRCC
+#' @keywords internal
 #' @export
 #' @title Identify WRCC Dump File Monitor Type
 #' @param fileString character string containing WRCC dump file

R/wrccDump_parseData.R

@@ -1,4 +1,4 @@
-#' @keywords WRCC
+#' @keywords internal
 #' @export
 #' @title Parse WRCC Dump File String
 #' @param fileString character string containing WRCC dump file