In MazamaScience/PWFSLSmoke: Utilities for Working with Air Quality Monitoring Data

suppressPackageStartupMessages({
  library(PWFSLSmoke)
  library(ggplot2)
})
setSpatialDataDir(params$spatialDataDir)
ws_monitor <- params$ws_monitor

Monitor Leaflet map

monitor_leaflet(ws_monitor)

Monthly Maps

# Get a bounding box that will include all monitor locations
bbox <- RgoogleMaps::qbbox(ws_monitor$meta$latitude, ws_monitor$meta$longitude, margin = list(m = c(10,10,10,10), TYPE = "perc"))

# Get the map image from esri
basemap <- esriMap_getMap(bboxString = paste0(bbox$lonR[1], ",", bbox$latR[1], ",", bbox$lonR[2], ",", bbox$latR[2]))


yearCount <- length(unique(lubridate::year(ws_monitor$data$datetime)))
monthCount <-length(unique(lubridate::month(ws_monitor$data$datetime)))
layout(matrix(1:((monthCount+1)*(yearCount+1)), monthCount+1, yearCount+1, byrow = FALSE), 
       widths=c(.8,rep(4, yearCount)), heights = c(1,rep(4, monthCount+1)))
par(mar = c(0,0,0,0))
plot.new()

# Write the month names
for( month in sort(unique(lubridate::month(ws_monitor$data$datetime))) ){
  text <- month.name[month]
  plot(0,0,col="transparent", axes = F)
  text(0,0,text, srt = 90, cex = 1.5)
}

# Map monitors from every month in each year
for ( year in sort(unique(lubridate::year(ws_monitor$data$datetime))) ){
  plot(0,0,col="transparent", axes = F)
  text(0,0, as.character(year), cex = 2)

  for ( month in sort(unique(lubridate::month(ws_monitor$data$datetime))) ) {
    if ( month < 12 ) {
      tlim <- paste0(as.character(year), stringr::str_pad(as.character(c(month, month+1)), 2, side = 'left', "0"), '01')
    } else {
      tlim <- paste0(as.character(year), c("120100", "123123"))
    }
    monitor <- monitor_subset(ws_monitor, tlim = tlim)

    result <- try (
      monitor_esriMap(monitor, mapRaster = basemap)
    )
    if ("try-error" %in% class(result)) {
      esriMap_plotOnStaticMap(basemap)
    }
    box("figure", col = 'gray50')
  }
}

Deployments

counts2015 <-  data.frame(time = ws_monitor$data$datetime, 
                          count = apply(ws_monitor$data[-1], 1, function(x) sum(!is.na(x))))
ggplot(counts2015, aes(time, count))+
  geom_bar(stat="identity")+
  labs(title='Number of valid data points by hour', subtitle='2015')

Timeseries of all readings

monitor_timeseriesPlot(ws_monitor, style='gnats', xlab = "", localTime = FALSE, ylim = c(0,1000))

MazamaScience/PWFSLSmoke documentation built on July 3, 2023, 11:03 a.m.