localExamples/Boise_SmokeMtg_2018.R
In MazamaScience/PWFSLSmoke: Utilities for Working with Air Quality Monitoring Data
#
library(PWFSLSmoke)
airnow <- airnow_load(2017)
airsis <- airsis_load(2017)
wrcc <- wrcc_load(2017)
oridwa <- monitor_combine(list(airsis, airnow, wrcc)) %>%
monitor_subset(stateCodes=c('OR','ID','WA'))
# # Timeseries 'gnats' plot (takes forever to plot!)
# monitor_timeseriesPlot(oridwa, style='gnats')
# monitor_timeseriesPlot(oridwa, style='gnats', ylim=c(0,500), xpd=NA)
jas <- monitor_subset(oridwa, tlim=c(20170701,20171001))
# Save default graphical parameters
oldPar <- par()
# -----------------------------------------------------------------------------
# All hourly data plot
dataCount <- nrow(jas$data) * (ncol(jas$data) - 1)
dataCountString <- prettyNum(dataCount, big.mark=",")
png('oridwa_hourly.png', width=800, height=600)
par(mar=c(5.1,4.1,9.1,8.1))
monitor_timeseriesPlot(jas, style='gnats', xlab='2017', ylim=c(0,400), xpd=NA)
addAQIStackedBar(pos='left', width=0.01)
addAQILines(lwd=2)
text(par('usr')[2], AQI$breaks_24[2:6], AQI$names[2:6], pos=4, xpd=NA)
mtext('Hourly PM2.5', side=3, line=6, adj=0, cex=2.0, font=2)
mtext('Washginton-Oregon-Idaho', side=3, line=4, adj=0, cex=1.8, font=1)
mtext(paste0(dataCountString,' measurements'), side=3, line=2, adj=0, cex=1.8, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# All daily data plot
dailyMean <- monitor_dailyStatistic(jas)
dataCount <- nrow(dailyMean$data) * (ncol(dailyMean$data) - 1)
dataCountString <- prettyNum(dataCount, big.mark=",")
png('oridwa_daily.png', width=800, height=600)
par(mar=c(5.1,4.1,9.1,8.1))
monitor_timeseriesPlot(dailyMean, style='gnats', xlab='2017', ylim=c(0,200), xpd=NA)
addAQIStackedBar(pos='left', width=0.01)
addAQILines(lwd=2)
text(par('usr')[2], AQI$breaks_24[2:5], AQI$names[2:5], pos=4, xpd=NA)
mtext('Daily Mean PM2.5', side=3, line=6, adj=0, cex=2.0, font=2)
mtext('Washginton-Oregon-Idaho', side=3, line=4, adj=0, cex=1.8, font=1)
mtext(paste0(dataCountString,' daily means'), side=3, line=2, adj=0, cex=1.8, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Daily max map
png('daily_max_map.png', width=800, height=600)
monitor_map(dailyMean, max, mar=c(1,1,9.1,1), cex=1.8)
addAQILegend("topright", cex=1.2, pt.cex=1.5)
mtext('Highest Daily Mean PM2.5 during Jul-Aug-Sep', side=3, line=2, adj=0, cex=2.0, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Nez Perce monitors
as <- monitor_subset(jas, tlim=c(20170801,20170915), timezone="America/Los_Angeles")
Lewiston <- monitor_subset(as, monitorIDs='160690012_01')
Clarkston <- monitor_subset(as, monitorIDs='530030004_01')
Juliaetta <- monitor_subset(as, monitorIDs='160571012_01')
Orofino <- monitor_subset(as, monitorIDs='lon_.116.235_lat_46.465_apcd.1000')
Lapwai <- monitor_subset(as, monitorIDs='160690013_01')
Reubens <- monitor_subset(as, monitorIDs='160690014_01')
Nezperce <- monitor_subset(as, monitorIDs='lon_.116.248_lat_46.234_apcd.1006')
Kamiah <- monitor_subset(as, monitorIDs='160490003_01')
Cottonwood <- monitor_subset(as, monitorIDs='160491012_01')
Grangeville <- monitor_subset(as, monitorIDs='160490002_01')
Nezperce_area <- monitor_combine(list(Clarkston,
Lewiston,
Juliaetta,
Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah,
Cottonwood,
Grangeville))
onRez <- monitor_combine(list(Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah))
offRez <- monitor_combine(list(Clarkston,
Lewiston,
Juliaetta,
Cottonwood,
Grangeville))
onRezList <- list(Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah)
onRezLabels <- c('Orofino','Lapwai','Reubens','Nezperce','Kamiah')
offRezList <- list(Clarkston,
Lewiston,
Juliaetta,
Cottonwood,
Grangeville)
offRezLabels <- c('Clarkston','Lewiston','Juliaetta','Cottonwood','Grangeville')
# -----------------------------------------------------------------------------
# Nez Perce zoom out map
Nezperce_area_daily <- monitor_dailyStatistic(Nezperce_area)
png('nezperce_map_zoom_out.png', width=800, height=600)
monitor_esriMap(Nezperce_area_daily, zoom=7, width=640, height=640, cex=3)
addAQILegend(cex=1.5, pt.cex=2, title='Max Daily Mean')
dev.off()
par(oldPar)
png('nezperce_map_zoom_in.png', width=800, height=600)
monitor_esriMap(Nezperce_area_daily, zoom=9, width=640, height=640, cex=5)
addAQILegend(cex=1.5, pt.cex=2, title='Max Daily Mean')
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Nez Perce area unhealthy hours
Nezperce_single <- monitor_collapse(Nezperce_area, monitorID='Nezperce_single')
unhealthyHours <- monitor_dailyThreshold(Nezperce_single, threshold="unhealthy")
png('nezperce_area_unhealthy.png', width=800, height=600)
par(cex=1.5)
unhealthyHours$data[unhealthyHours$data == 0] <- 0.1 # so we don't get blank bars
monitor_timeseriesPlot(unhealthyHours, type='h', lend='butt', lwd=12,
col='black',
xlab='2017', ylab="Hours Above Unhealthy")
usr <- par('usr')
rect(usr[1],18,usr[2],24, col=adjustcolor('red',.2), border=NA)
monitor_timeseriesPlot(unhealthyHours, type='h', lend='butt', lwd=12, add=TRUE)
title("Nez Perce Area 10 Monitor Average")
text(usr[1], 21, "18-24 Hours per day >= 'Unhealthy'", pos=4, font=2, col='red')
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
# PLOT -- dailyBarplot for onRez
png('daily_barplot_onrez.png', width=800, height=600)
layout(matrix(seq(5)))
par(cex=1.0)
par(mar=c(3,4,1,2)+.1)
monitor_dailyBarplot(Orofino, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Orofino', line=-1)
monitor_dailyBarplot(Lapwai, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Lapwai', line=-1)
monitor_dailyBarplot(Reubens, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Reubens', line=-1)
monitor_dailyBarplot(Nezperce, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Nezperce', line=-1)
monitor_dailyBarplot(Kamiah, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Kamiah', line=-1)
par(mar=c(5,4,4,2)+.1)
par(cex=1)
layout(1)
dev.off()
# -----------------------------------------------------------------------------
# PLOT -- dailyBarplot for offRez
png('daily_barplot_offrez.png', width=800, height=600)
layout(matrix(seq(5)))
par(cex=1.0)
par(mar=c(3,4,1,2)+.1)
monitor_dailyBarplot(Clarkston, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Clarkston', line=-1)
monitor_dailyBarplot(Lewiston, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Lewiston', line=-1)
monitor_dailyBarplot(Juliaetta, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Juliaetta', line=-1)
monitor_dailyBarplot(Cottonwood, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Cottonwood', line=-1)
monitor_dailyBarplot(Grangeville, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Grangeville', line=-1)
layout(1)
par(mar=c(5,4,4,2)+.1)
par(mar=c(5,4,4,2)+.1)
par(cex=1)
layout(1)
dev.off()
# -----------------------------------------------------------------------------
# stacked barplot
png('stacked_bars_onrez.png', width=800, height=600)
#png('stacked_bars_offrez.png', width=800, height=600)
par(mar=c(3.1,4.1,3.1,2.1))
layout(matrix(seq(5)))
for ( i in 1:5 ) {
mon <- onRezList[[i]]
#mon <- offRezList[[i]]
hours_1 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[1])
hours_2 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[2])
hours_3 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[3])
hours_4 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[4])
hours_5 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[5])
hours_6 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[6])
datetime <- hours_1$data[,1]
h6 <- hours_6$data[,2]
h5 <- hours_5$data[,2] - h6
h4 <- hours_4$data[,2] - h6 - h5
h3 <- hours_3$data[,2] - h6 - h5 - h4
h2 <- hours_2$data[,2] - h6 - h5 - h4 - h3
h1 <- hours_1$data[,2] - h6 - h5 - h4 - h3 - h2
mat <- cbind(h1,h2,h3,h4,h5,h6)
barplot(t(mat), col=AQI$colors[1:6], border='white', axes=FALSE)
title(onRezLabels[i], cex.main=3)
#title(offRezLabels[i], cex.main=3)
###axis(2, at=seq(0,24,6), las=1)
###axis.POSIXct(1, mon$data$datetime)
aug09Index <- which(hours_1$data$datetime == lubridate::ymd_h("2017-08-09 00", tz="America/Los_Angeles"))
sep05Index <- which(hours_1$data$datetime == lubridate::ymd_h("2017-09-05 00", tz="America/Los_Angeles"))
# NOTE: Need to account for 0.2 spacing between bars so 1.2 axis units per label
at <- 1.2 * c(aug09Index,sep05Index) - 0.6
axis(1, at=at, labels=c('Aug 9', 'Sep 5'), lwd=0, lwd.ticks=2, cex.axis=2)
}
layout(1)
par(oldPar)
dev.off()
# -----------------------------------------------------------------------------
nowcast_Cottonwood <- monitor_nowcast(Cottonwood)
bad_Cottonwood <- monitor_subset(Cottonwood, tlim=c(20170901, 20170914))
bad_nowcast_Cottonwood <- monitor_subset(nowcast_Cottonwood, tlim=c(20170901, 20170914))
# PLOT -- hourly/nowcast comparison
png('cottonwood_nowcast_comparison.png', width=1000, height=750)
par(cex=1.5)
monitor_timeseriesPlot(bad_Cottonwood, type='p', pch=16, col='red', shadedNight=TRUE)
monitor_timeseriesPlot(bad_nowcast_Cottonwood, type='l', col='black', lwd=2, add=TRUE)
legend("topright", legend=c('Hourly','Nowcast'), col=c('red','black'), lwd=c(NA,2), pch=c(16,NA))
title('Cottonwood Hourly and Nowcast')
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
bad_Cottonwood <- monitor_subset(Cottonwood, tlim=c(20170903, 20170911))
bad_nowcast_Cottonwood <- monitor_subset(nowcast_Cottonwood, tlim=c(20170904, 20170911))
# PLOT -- hourlyBarplot for Cottonwood
png('cottonwood_hourly.png', width=800, height=600)
par(cex=1.5)
monitor_hourlyBarplot(bad_Cottonwood, dayCol='transparent', hourLwd=0,
ylab='', main='Cottonwood Hourly',
labels_x_nudge=5, labels_y_nudge=20,
border=adjustcolor('white',0.2))
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
MazamaScience/PWFSLSmoke documentation built on July 3, 2023, 11:03 a.m.
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#
library(PWFSLSmoke)
airnow <- airnow_load(2017)
airsis <- airsis_load(2017)
wrcc <- wrcc_load(2017)
oridwa <- monitor_combine(list(airsis, airnow, wrcc)) %>%
monitor_subset(stateCodes=c('OR','ID','WA'))
# # Timeseries 'gnats' plot (takes forever to plot!)
# monitor_timeseriesPlot(oridwa, style='gnats')
# monitor_timeseriesPlot(oridwa, style='gnats', ylim=c(0,500), xpd=NA)
jas <- monitor_subset(oridwa, tlim=c(20170701,20171001))
# Save default graphical parameters
oldPar <- par()
# -----------------------------------------------------------------------------
# All hourly data plot
dataCount <- nrow(jas$data) * (ncol(jas$data) - 1)
dataCountString <- prettyNum(dataCount, big.mark=",")
png('oridwa_hourly.png', width=800, height=600)
par(mar=c(5.1,4.1,9.1,8.1))
monitor_timeseriesPlot(jas, style='gnats', xlab='2017', ylim=c(0,400), xpd=NA)
addAQIStackedBar(pos='left', width=0.01)
addAQILines(lwd=2)
text(par('usr')[2], AQI$breaks_24[2:6], AQI$names[2:6], pos=4, xpd=NA)
mtext('Hourly PM2.5', side=3, line=6, adj=0, cex=2.0, font=2)
mtext('Washginton-Oregon-Idaho', side=3, line=4, adj=0, cex=1.8, font=1)
mtext(paste0(dataCountString,' measurements'), side=3, line=2, adj=0, cex=1.8, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# All daily data plot
dailyMean <- monitor_dailyStatistic(jas)
dataCount <- nrow(dailyMean$data) * (ncol(dailyMean$data) - 1)
dataCountString <- prettyNum(dataCount, big.mark=",")
png('oridwa_daily.png', width=800, height=600)
par(mar=c(5.1,4.1,9.1,8.1))
monitor_timeseriesPlot(dailyMean, style='gnats', xlab='2017', ylim=c(0,200), xpd=NA)
addAQIStackedBar(pos='left', width=0.01)
addAQILines(lwd=2)
text(par('usr')[2], AQI$breaks_24[2:5], AQI$names[2:5], pos=4, xpd=NA)
mtext('Daily Mean PM2.5', side=3, line=6, adj=0, cex=2.0, font=2)
mtext('Washginton-Oregon-Idaho', side=3, line=4, adj=0, cex=1.8, font=1)
mtext(paste0(dataCountString,' daily means'), side=3, line=2, adj=0, cex=1.8, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Daily max map
png('daily_max_map.png', width=800, height=600)
monitor_map(dailyMean, max, mar=c(1,1,9.1,1), cex=1.8)
addAQILegend("topright", cex=1.2, pt.cex=1.5)
mtext('Highest Daily Mean PM2.5 during Jul-Aug-Sep', side=3, line=2, adj=0, cex=2.0, font=1)
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Nez Perce monitors
as <- monitor_subset(jas, tlim=c(20170801,20170915), timezone="America/Los_Angeles")
Lewiston <- monitor_subset(as, monitorIDs='160690012_01')
Clarkston <- monitor_subset(as, monitorIDs='530030004_01')
Juliaetta <- monitor_subset(as, monitorIDs='160571012_01')
Orofino <- monitor_subset(as, monitorIDs='lon_.116.235_lat_46.465_apcd.1000')
Lapwai <- monitor_subset(as, monitorIDs='160690013_01')
Reubens <- monitor_subset(as, monitorIDs='160690014_01')
Nezperce <- monitor_subset(as, monitorIDs='lon_.116.248_lat_46.234_apcd.1006')
Kamiah <- monitor_subset(as, monitorIDs='160490003_01')
Cottonwood <- monitor_subset(as, monitorIDs='160491012_01')
Grangeville <- monitor_subset(as, monitorIDs='160490002_01')
Nezperce_area <- monitor_combine(list(Clarkston,
Lewiston,
Juliaetta,
Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah,
Cottonwood,
Grangeville))
onRez <- monitor_combine(list(Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah))
offRez <- monitor_combine(list(Clarkston,
Lewiston,
Juliaetta,
Cottonwood,
Grangeville))
onRezList <- list(Orofino,
Lapwai,
Reubens,
Nezperce,
Kamiah)
onRezLabels <- c('Orofino','Lapwai','Reubens','Nezperce','Kamiah')
offRezList <- list(Clarkston,
Lewiston,
Juliaetta,
Cottonwood,
Grangeville)
offRezLabels <- c('Clarkston','Lewiston','Juliaetta','Cottonwood','Grangeville')
# -----------------------------------------------------------------------------
# Nez Perce zoom out map
Nezperce_area_daily <- monitor_dailyStatistic(Nezperce_area)
png('nezperce_map_zoom_out.png', width=800, height=600)
monitor_esriMap(Nezperce_area_daily, zoom=7, width=640, height=640, cex=3)
addAQILegend(cex=1.5, pt.cex=2, title='Max Daily Mean')
dev.off()
par(oldPar)
png('nezperce_map_zoom_in.png', width=800, height=600)
monitor_esriMap(Nezperce_area_daily, zoom=9, width=640, height=640, cex=5)
addAQILegend(cex=1.5, pt.cex=2, title='Max Daily Mean')
dev.off()
par(oldPar)
# -----------------------------------------------------------------------------
# Nez Perce area unhealthy hours
Nezperce_single <- monitor_collapse(Nezperce_area, monitorID='Nezperce_single')
unhealthyHours <- monitor_dailyThreshold(Nezperce_single, threshold="unhealthy")
png('nezperce_area_unhealthy.png', width=800, height=600)
par(cex=1.5)
unhealthyHours$data[unhealthyHours$data == 0] <- 0.1 # so we don't get blank bars
monitor_timeseriesPlot(unhealthyHours, type='h', lend='butt', lwd=12,
col='black',
xlab='2017', ylab="Hours Above Unhealthy")
usr <- par('usr')
rect(usr[1],18,usr[2],24, col=adjustcolor('red',.2), border=NA)
monitor_timeseriesPlot(unhealthyHours, type='h', lend='butt', lwd=12, add=TRUE)
title("Nez Perce Area 10 Monitor Average")
text(usr[1], 21, "18-24 Hours per day >= 'Unhealthy'", pos=4, font=2, col='red')
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
# PLOT -- dailyBarplot for onRez
png('daily_barplot_onrez.png', width=800, height=600)
layout(matrix(seq(5)))
par(cex=1.0)
par(mar=c(3,4,1,2)+.1)
monitor_dailyBarplot(Orofino, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Orofino', line=-1)
monitor_dailyBarplot(Lapwai, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Lapwai', line=-1)
monitor_dailyBarplot(Reubens, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Reubens', line=-1)
monitor_dailyBarplot(Nezperce, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Nezperce', line=-1)
monitor_dailyBarplot(Kamiah, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Kamiah', line=-1)
par(mar=c(5,4,4,2)+.1)
par(cex=1)
layout(1)
dev.off()
# -----------------------------------------------------------------------------
# PLOT -- dailyBarplot for offRez
png('daily_barplot_offrez.png', width=800, height=600)
layout(matrix(seq(5)))
par(cex=1.0)
par(mar=c(3,4,1,2)+.1)
monitor_dailyBarplot(Clarkston, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Clarkston', line=-1)
monitor_dailyBarplot(Lewiston, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Lewiston', line=-1)
monitor_dailyBarplot(Juliaetta, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Juliaetta', line=-1)
monitor_dailyBarplot(Cottonwood, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Cottonwood', line=-1)
monitor_dailyBarplot(Grangeville, ylim=c(0,300), ylab='', main='', labels_x_nudge=1.0, labels_y_nudge=70)
title('Grangeville', line=-1)
layout(1)
par(mar=c(5,4,4,2)+.1)
par(mar=c(5,4,4,2)+.1)
par(cex=1)
layout(1)
dev.off()
# -----------------------------------------------------------------------------
# stacked barplot
png('stacked_bars_onrez.png', width=800, height=600)
#png('stacked_bars_offrez.png', width=800, height=600)
par(mar=c(3.1,4.1,3.1,2.1))
layout(matrix(seq(5)))
for ( i in 1:5 ) {
mon <- onRezList[[i]]
#mon <- offRezList[[i]]
hours_1 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[1])
hours_2 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[2])
hours_3 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[3])
hours_4 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[4])
hours_5 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[5])
hours_6 <- monitor_dailyThreshold(mon, threshold=AQI$breaks_24[6])
datetime <- hours_1$data[,1]
h6 <- hours_6$data[,2]
h5 <- hours_5$data[,2] - h6
h4 <- hours_4$data[,2] - h6 - h5
h3 <- hours_3$data[,2] - h6 - h5 - h4
h2 <- hours_2$data[,2] - h6 - h5 - h4 - h3
h1 <- hours_1$data[,2] - h6 - h5 - h4 - h3 - h2
mat <- cbind(h1,h2,h3,h4,h5,h6)
barplot(t(mat), col=AQI$colors[1:6], border='white', axes=FALSE)
title(onRezLabels[i], cex.main=3)
#title(offRezLabels[i], cex.main=3)
###axis(2, at=seq(0,24,6), las=1)
###axis.POSIXct(1, mon$data$datetime)
aug09Index <- which(hours_1$data$datetime == lubridate::ymd_h("2017-08-09 00", tz="America/Los_Angeles"))
sep05Index <- which(hours_1$data$datetime == lubridate::ymd_h("2017-09-05 00", tz="America/Los_Angeles"))
# NOTE: Need to account for 0.2 spacing between bars so 1.2 axis units per label
at <- 1.2 * c(aug09Index,sep05Index) - 0.6
axis(1, at=at, labels=c('Aug 9', 'Sep 5'), lwd=0, lwd.ticks=2, cex.axis=2)
}
layout(1)
par(oldPar)
dev.off()
# -----------------------------------------------------------------------------
nowcast_Cottonwood <- monitor_nowcast(Cottonwood)
bad_Cottonwood <- monitor_subset(Cottonwood, tlim=c(20170901, 20170914))
bad_nowcast_Cottonwood <- monitor_subset(nowcast_Cottonwood, tlim=c(20170901, 20170914))
# PLOT -- hourly/nowcast comparison
png('cottonwood_nowcast_comparison.png', width=1000, height=750)
par(cex=1.5)
monitor_timeseriesPlot(bad_Cottonwood, type='p', pch=16, col='red', shadedNight=TRUE)
monitor_timeseriesPlot(bad_nowcast_Cottonwood, type='l', col='black', lwd=2, add=TRUE)
legend("topright", legend=c('Hourly','Nowcast'), col=c('red','black'), lwd=c(NA,2), pch=c(16,NA))
title('Cottonwood Hourly and Nowcast')
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
bad_Cottonwood <- monitor_subset(Cottonwood, tlim=c(20170903, 20170911))
bad_nowcast_Cottonwood <- monitor_subset(nowcast_Cottonwood, tlim=c(20170904, 20170911))
# PLOT -- hourlyBarplot for Cottonwood
png('cottonwood_hourly.png', width=800, height=600)
par(cex=1.5)
monitor_hourlyBarplot(bad_Cottonwood, dayCol='transparent', hourLwd=0,
ylab='', main='Cottonwood Hourly',
labels_x_nudge=5, labels_y_nudge=20,
border=adjustcolor('white',0.2))
par(cex=1)
dev.off()
# -----------------------------------------------------------------------------
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