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app.R.bak
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library(shiny)
library(shinydashboard)
library(tidyverse)
library(lubridate)
library(openair)
library(RMySQL)
library(magick)
rain_corr = 1.255411
Sys.setenv(tz = 'America/Los_Angeles')
# print(getwd())
credentials = read.csv('../credentials.csv')
db_user = credentials[credentials$field == 'db_user',2]
db_password = credentials[credentials$field == 'db_password',2]
db_name = credentials[credentials$field == 'db_name',2]
db_table = credentials[credentials$field == 'db_table',2]
db_host = credentials[credentials$field == 'db_host',2]
get_recent_data = function() {
mydb = dbConnect(
MySQL(),
user = db_user, password = db_password, dbname = db_name, host = db_host
)
s = paste0("select * from ",db_table)
rs = dbSendQuery(mydb, s)
df = fetch(rs, n = -2)
on.exit(dbDisconnect(mydb))
data = df %>%
filter(
ID>6,
SerialNumber %in% c(116,236)
) %>%
mutate(
ts_GMT = force_tz(as_datetime(TimeStamp), tzone = 'GMT'),
ts_PST = with_tz(ts_GMT, tzone = 'America/Los_Angeles'),
TotalRain = case_when(
ID <= 676 ~ 0,
ID >= 37254 & ID <=37269 & TotalRain != 355.8 ~ TotalRain + 355.8,
ID > 37269 ~ TotalRain + 355.8,
T ~ TotalRain
),
InstantRain = c(0,diff(TotalRain)),
SunlightVisible = case_when(
ts_PST < '2022-02-25' ~ as.numeric(NA),
SunlightVisible > 200000 ~ as.numeric(NA),
T ~ SunlightVisible
),
SunlightUVIndex = case_when(
ts_PST < '2022-02-25' ~ as.numeric(NA),
T ~ SunlightUVIndex
)
) %>%
select(ID,TimeStamp,ts_PST, OutdoorTemperature,OutdoorHumidity,IndoorTemperature,IndoorHumidity,TotalRain,InstantRain,SunlightVisible,SunlightUVIndex,WindGust,
WindDirection,WindSpeed,BarometricPressure,BarometricPressureSeaLevel,BarometricTemperature,PM_1_0,PM_2_5,PM_10,AQI,AQI24Average,SNR) %>%
filter(ts_PST > '2022-02-23 17:00:00')
dbClearResult(dbListResults(mydb)[[1]])
return(data)
}
df_local = get_recent_data()
# UI ####
ui = dashboardPage(
dashboardHeader(title = 'Cartagena Farm Weather Station'),
dashboardSidebar(
sidebarMenu(
menuItem('Current Conditions', tabName = 'conds', icon = icon('wind')),
menuItem('Detailed Plots', tabName = 'plots', icon = icon('chart-line')),
menuItem('Time Lapse', tabName = 'images')
),
dateRangeInput(
'range','Date Range',start = NULL, end = NULL
),
selectInput(
inputId = 'hourstart',
label = 'Hour Start',
choices = seq(0,24,1),
selected = 0
),
selectInput(
inputId = 'hourend',
label = 'Hour End',
choices = seq(0,24,1),
selected = 24
),
selectInput(
inputId = 'resolution',label = "Select Temporal Resolution",
choices = c('5 minutes','Hourly','Daily','Weekly','Monthly'),
selected = '5 minutes'
),
checkboxInput('smooth','Show Trend Line?',FALSE),
sliderInput('smoothness','Level of smoothing',min = 0.02,max = 0.5, value = 0.05),
checkboxInput('rain_correct', "Correct Rainfall?", FALSE),
checkboxInput('high_low', 'Show High/Low?', FALSE)
),
dashboardBody(
tabItems(
tabItem(
tabName = 'conds',
fluidRow(
column(
4,
div(textOutput('CurrentHeader'),style = 'font-size:200%'),
div(tableOutput('CurrentConditions1'), style = 'font-size:150%'),
div(tableOutput('CurrentConditions2'), style = 'font-size:150%'),
div(tableOutput('CurrentConditions3'), style = 'font-size:150%'),
div(tableOutput('CurrentConditions4'), style = 'font-size:150%'),
div(tableOutput('CurrentConditions5'), style = 'font-size:150%')
),
column(
8,
imageOutput(outputId = 'farmpic')
)
)
),
tabItem(
tabName = 'plots',
fluidRow(
column(
3,
plotOutput('TempPlot'),
plotOutput('AQIPlot')
),
column(
3,
plotOutput('RainPlot'),
plotOutput('PressurePlot')
),
column(
3,
plotOutput('HumPlot'),
plotOutput('WindPlot')
),
column(
3,
plotOutput('LightPlot'),
plotOutput('WindRose')
)
)
),
tabItem(
tabName = 'images',
fluidRow(
column(
6,
actionButton('gif','Make New Timelapse'),
imageOutput(outputId = 'timelapse'),
div(),div(),div()
)
)
)
)
)
)
server <- function(input, output,session) {
recent_data <- reactivePoll(
intervalMillis = 75 * 1e3,
session = session,
checkFunc = get_recent_data,
valueFunc = function() {
raw_df <- get_recent_data()
}
)
# Temperature Plot ####
output$TempPlot <- renderPlot({
plot_df = recent_data()[,c('ts_PST','OutdoorTemperature','IndoorTemperature')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
data.frame()
ylim_set = range(plot_df[,c('OutdoorTemperature','IndoorTemperature')]) * c(1,1.1)
par(mar = c(6, 4.1, 4, 4))
# * 5 minutes ####
if(input$resolution == '5 minutes') {
plot(
plot_df$OutdoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = expression('Temp ('*degree*'C)')
)
par(new = T)
plot(
plot_df$IndoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Temperature",'Indoor Temperature'))
mtext(side = 3, line = 2, text = 'Temperature', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2)
axis(
side = 4,
las = 2,
at = (axisTicks(ylim_set*1.8+32, log = F)-32)/1.8,
labels = axisTicks(ylim_set*1.8+32, log = F)
)
mtext(side = 4, line = 2, text = expression('Temperature ('*degree*'F)'))
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$OutdoorTemperature),1), round(last(plot_df$IndoorTemperature),1), sep = ','))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round(last(plot_df$OutdoorTemperature)*1.8+32,1),round(last(plot_df$IndoorTemperature)*1.8+32,1), sep = ','))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Hourly ####
} else if (input$resolution == 'Hourly') {
plot_df = recent_data()[,c('ts_PST','OutdoorTemperature','IndoorTemperature')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
hour = hour(ts_PST), date = date(ts_PST)
) %>%
group_by(date, hour) %>%
summarise(
min_ot = min(OutdoorTemperature), max_ot = max(OutdoorTemperature),
min_it = min(IndoorTemperature), max_it = max(IndoorTemperature),
ts_PST = first(ts_PST),
OutdoorTemperature = mean(OutdoorTemperature), IndoorTemperature = mean(IndoorTemperature)
) %>%
data.frame()
plot(
plot_df$OutdoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = expression('Temp ('*degree*'C)')
)
par(new = T)
plot(
plot_df$IndoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_ot, rev(plot_df$max_ot)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_it, rev(plot_df$max_it)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Temperature",'Indoor Temperature'))
mtext(side = 3, line = 2, text = 'Mean Hourly Temperature', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2, format = '%a %H')
axis(
side = 4,
las = 2,
at = (axisTicks(ylim_set*1.8+32, log = F, nint = 6)-32)/1.8,
labels = axisTicks(ylim_set*1.8+32, log = F, nint = 6)
)
mtext(side = 4, line = 2, text = expression('Temperature ('*degree*'F)'))
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature),1),', IT: ', round(last(plot_df$IndoorTemperature),1), sep = ''))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature)*1.8+32,1),', IT: ', round(last(plot_df$IndoorTemperature)*1.8+32,1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Daily ####
} else if (input$resolution == 'Daily') {
plot_df = recent_data()[,c('ts_PST','OutdoorTemperature','IndoorTemperature')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
date = date(ts_PST)
) %>%
group_by(date) %>%
summarise(
min_ot = min(OutdoorTemperature), max_ot = max(OutdoorTemperature),
min_it = min(IndoorTemperature), max_it = max(IndoorTemperature),
ts_PST = first(ts_PST),
OutdoorTemperature = mean(OutdoorTemperature), IndoorTemperature = mean(IndoorTemperature)
) %>%
data.frame()
plot(
plot_df$OutdoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = expression('Temp ('*degree*'C)')
)
par(new = T)
plot(
plot_df$IndoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_ot, rev(plot_df$max_ot)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_it, rev(plot_df$max_it)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Temperature",'Indoor Temperature'))
mtext(side = 3, line = 2, text = 'Mean Daily Temperature', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2)
axis(
side = 4,
las = 2,
at = (axisTicks(ylim_set*1.8+32, log = F, nint = 6)-32)/1.8,
labels = axisTicks(ylim_set*1.8+32, log = F, nint = 6)
)
mtext(side = 4, line = 2, text = expression('Temperature ('*degree*'F)'))
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature),1),', IT: ', round(last(plot_df$IndoorTemperature),1), sep = ''))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature)*1.8+32,1),', IT: ', round(last(plot_df$IndoorTemperature)*1.8+32,1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'date'],
y = plot_df[,'OutdoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'date'],
y = plot_df[,'IndoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Weekly ####
} else if (input$resolution == 'Weekly') {
plot_df = recent_data()[,c('ts_PST','OutdoorTemperature','IndoorTemperature')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
week = week(ts_PST), year = year(ts_PST)
) %>%
group_by(year, week) %>%
summarise(
min_ot = min(OutdoorTemperature), max_ot = max(OutdoorTemperature),
min_it = min(IndoorTemperature), max_it = max(IndoorTemperature),
ts_PST = first(ts_PST),
OutdoorTemperature = mean(OutdoorTemperature), IndoorTemperature = mean(IndoorTemperature)
) %>%
data.frame()
plot(
plot_df$OutdoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = expression('Temp ('*degree*'C)'), type = 'b'
)
par(new = T)
plot(
plot_df$IndoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue', type = 'b'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_ot, rev(plot_df$max_ot)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_it, rev(plot_df$max_it)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Temperature",'Indoor Temperature'))
mtext(side = 3, line = 2, text = 'Mean Weekly Temperature', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2)
axis(
side = 4,
las = 2,
at = (axisTicks(ylim_set*1.8+32, log = F, nint = 6)-32)/1.8,
labels = axisTicks(ylim_set*1.8+32, log = F, nint = 6)
)
mtext(side = 4, line = 2, text = expression('Temperature ('*degree*'F)'))
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature),1),', IT: ', round(last(plot_df$IndoorTemperature),1), sep = ''))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature)*1.8+32,1),', IT: ', round(last(plot_df$IndoorTemperature)*1.8+32,1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Monthly ####
} else if (input$resolution == 'Monthly') {
plot_df = recent_data()[,c('ts_PST','OutdoorTemperature','IndoorTemperature')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
month = month(ts_PST), year = year(ts_PST)
) %>%
group_by(year, month) %>%
summarise(
min_ot = min(OutdoorTemperature), max_ot = max(OutdoorTemperature),
min_it = min(IndoorTemperature), max_it = max(IndoorTemperature),
ts_PST = first(ts_PST),
OutdoorTemperature = mean(OutdoorTemperature), IndoorTemperature = mean(IndoorTemperature)
) %>%
data.frame()
plot(
plot_df$OutdoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = expression('Temp ('*degree*'C)')
)
par(new = T)
plot(
plot_df$IndoorTemperature~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_ot, rev(plot_df$max_ot)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_it, rev(plot_df$max_it)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Temperature",'Indoor Temperature'))
mtext(side = 3, line = 2, text = 'Mean Monthly Temperature', cex = 1.5)
axis.POSIXct(x = plot_df$datetime,side = 1, las = 2)
axis(
side = 4,
las = 2,
at = (axisTicks(ylim_set*1.8+32, log = F, nint = 6)-32)/1.8,
labels = axisTicks(ylim_set*1.8+32, log = F, nint = 6)
)
mtext(side = 4, line = 2, text = expression('Temperature ('*degree*'F)'))
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature),1),', IT: ', round(last(plot_df$IndoorTemperature),1), sep = ''))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste('OT: ',round(last(plot_df$OutdoorTemperature)*1.8+32,1),', IT: ', round(last(plot_df$IndoorTemperature)*1.8+32,1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorTemperature'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
}
})
#
# RainPlot ####
output$RainPlot = renderPlot({
par(mar = c(6, 4.1, 4, 4))
# * 5 minutes ####
if(input$resolution == '5 minutes') {
plot_df = recent_data()[,c('ts_PST','TotalRain','InstantRain')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
data.frame()
zero_value = max(c(0, last(filter(recent_data()[,c('ts_PST','TotalRain','InstantRain')], ts_PST < first(plot_df$ts_PST))$TotalRain)), na.rm = T)
if(input$rain_correct == T) {
plot_df$TotalRain = plot_df$TotalRain * rain_corr
plot_df$InstantRain = plot_df$InstantRain * rain_corr
zero_value = zero_value * rain_corr
}
plot(
I(plot_df$TotalRain-zero_value)~plot_df$ts_PST,
las = 2, pch = 20, cex = 1, xlab = '',
ylab = 'mm', xaxt = 'n'
)
mtext(side = 3, line = 2, text = 'Cumulative Rainfall', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,format = '%a %H',side = 1, las = 2)
axis(
side = 4,
las = 2,
at = axisTicks(range((plot_df$TotalRain-zero_value))/25.4, log = F, nint = 6)*25.4,
labels = axisTicks(range((plot_df$TotalRain-zero_value)/25.4), log = F, nint = 6)
)
mtext(side = 4, line = 2, text = 'Inches')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$TotalRain)-zero_value,1)))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round((last(plot_df$TotalRain)-zero_value)/25.4,2)))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST']-zero_value,
y = plot_df[,'TotalRain'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Hourly ####
} else if (input$resolution == 'Hourly') {
plot_df = recent_data()[,c('ts_PST','InstantRain')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
hour = hour(ts_PST), date = date(ts_PST)
) %>%
group_by(date, hour) %>%
summarise(across(where(is.numeric), ~sum(.x)), ts_PST =first(ts_PST)) %>%
mutate(
datetime = format(ts_PST, format = '%b-%d %H')
) %>%
data.frame()
if(input$rain_correct == T) {
# plot_df$TotalRain = plot_df$TotalRain * rain_corr
plot_df$InstantRain = plot_df$InstantRain * rain_corr
# zero_value = zero_value * rain_corr
}
b_rain = barplot(plot_df$InstantRain~plot_df$ts_PST, las = 2, ylab = 'mm', xlab = '', xaxt = 'n')
mtext(side = 3, line = 2, text = 'Total Hourly Rainfall', cex = 1.5)
axis(at = b_rain, labels = format(plot_df$ts_PST, format = '%a %H'),side = 1, las = 2)
axis(
side = 4,
las = 2,
at = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)*25.4,
labels = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)
)
mtext(side = 4, line = 2, text = 'Inches')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain),1)))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain)/25.4,2)))
# * Daily ####
} else if (input$resolution == 'Daily') {
plot_df = recent_data()[,c('ts_PST','InstantRain')] %>%
filter(
ts_PST > as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
date = date(ts_PST)
) %>%
group_by(date) %>%
summarise(across(where(is.numeric), ~sum(.x)), ts_PST = round(first(ts_PST), units = 'days')) %>%
mutate(
datetime = format(ts_PST, format = '%b-%d')
) %>%
data.frame()
if(input$rain_correct == T) {
# plot_df$TotalRain = plot_df$TotalRain * rain_corr
plot_df$InstantRain = plot_df$InstantRain * rain_corr
# zero_value = zero_value * rain_corr
}
b_rain = barplot(plot_df$InstantRain, las = 2, ylab = 'mm', xlab = '')
mtext(side = 3, line = 2, text = 'Total Daily Rainfall', cex = 1.5)
axis(at = b_rain, labels = format(plot_df$ts_PST, format = '%b %a'),side = 1, las = 2)
axis(
side = 4,
las = 2,
at = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)*25.4,
labels = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)
)
mtext(side = 4, line = 2, text = 'Inches')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain),1)))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain)/25.4,2)))
# * Weekly ####
} else if (input$resolution == 'Weekly') {
plot_df = recent_data()[,c('ts_PST','InstantRain')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
year = year(ts_PST), week = week(ts_PST)
) %>%
group_by(year,week) %>%
summarise(across(where(is.numeric), ~sum(.x)), ts_PST = first(ts_PST)) %>%
data.frame()
if(input$rain_correct == T) {
# plot_df$TotalRain = plot_df$TotalRain * rain_corr
plot_df$InstantRain = plot_df$InstantRain * rain_corr
# zero_value = zero_value * rain_corr
}
b_rain = barplot(plot_df$InstantRain, las = 2, xlab = '', ylab = '', xaxt = 'n')
mtext(side = 3, line = 2, text = 'Total Weekly Rainfall', cex = 1.5)
axis(at = b_rain, labels = format(plot_df$ts_PST, format = '%b %a'),side = 1, las = 2)
axis(
side = 4,
las = 2,
at = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)*25.4,
labels = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)
)
mtext(side = 4, line = 2, text = 'Inches')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain),1)))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain)/25.4,2)))
# * Monthly ####
} else if (input$resolution == 'Monthly') {
plot_df = recent_data()[,c('ts_PST','InstantRain')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
month = month(ts_PST), year = year(ts_PST)
) %>%
group_by(year, month) %>%
summarise(across(where(is.numeric), ~sum(.x)), ts_PST = first(ts_PST)) %>%
mutate(
date = format(ts_PST, format = '%Y %b')
) %>%
data.frame()
if(input$rain_correct == T) {
# plot_df$TotalRain = plot_df$TotalRain * rain_corr
plot_df$InstantRain = plot_df$InstantRain * rain_corr
# zero_value = zero_value * rain_corr
}
b_rain = barplot(plot_df$InstantRain, las = 2, xlab = '', ylab = '', xaxt = 'n')
mtext(side = 3, line = 2, text = 'Total Monthly Rainfall', cex = 1.5)
axis(at = b_rain, labels = format(plot_df$ts_PST, format = '%Y %b'),side = 1, las = 2)
axis(
side = 4,
las = 2,
at = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)*25.4,
labels = axisTicks(range(c(0,(plot_df$InstantRain))/25.4), log = F, nint = 6)
)
mtext(side = 4, line = 2, text = 'Inches')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain),1)))
mtext(side = 3, adj = 1, cex = 1.5,line = 0, text = paste(round(last(plot_df$InstantRain)/25.4)))
}
})
# Humidity Plot ####
output$HumPlot <- renderPlot({
plot_df = recent_data()[,c('ts_PST','OutdoorHumidity','IndoorHumidity')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
data.frame()
ylim_set = range(plot_df[,c('OutdoorHumidity','IndoorHumidity')]) * c(1,1.1)
par(mar = c(6, 4.1, 4, 4))
# * 5 minutes ####
if(input$resolution == '5 minutes') {
plot(
plot_df$OutdoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = 'Relative %'
)
par(new = T)
plot(
plot_df$IndoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Humidity",'Indoor Humidity'))
mtext(side = 3, line = 2, text = 'Humidity', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2)
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OH: ',round(last(plot_df$OutdoorHumidity),1),', IH: ', round(last(plot_df$IndoorHumidity),1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Hourly ####
} else if (input$resolution == 'Hourly') {
plot_df = recent_data()[,c('ts_PST','OutdoorHumidity','IndoorHumidity')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
hour = hour(ts_PST), date = date(ts_PST)
) %>%
group_by(date, hour) %>%
summarise(
min_ih = min(IndoorHumidity), max_ih = max(IndoorHumidity),
min_oh = min(OutdoorHumidity), max_oh = max(OutdoorHumidity),
IndoorHumidity = mean(IndoorHumidity), OutdoorHumidity = mean(OutdoorHumidity),
ts_PST = first(ts_PST)
) %>%
mutate(
datetime = format(ts_PST, format = '%b-%d %H')
) %>%
data.frame()
plot(
plot_df$OutdoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = 'Relative %', xaxt = 'n'
)
par(new = T)
plot(
plot_df$IndoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_oh, rev(plot_df$max_oh)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_ih, rev(plot_df$max_ih)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Humidity",'Indoor Humidity'))
mtext(side = 3, line = 2, text = 'Hourly Mean Humidity', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2, format = '%a %H')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OH: ',round(last(plot_df$OutdoorHumidity),1),', IH: ', round(last(plot_df$IndoorHumidity),1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'OutdoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'ts_PST'],
y = plot_df[,'IndoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Daily ####
} else if (input$resolution == 'Daily') {
plot_df = recent_data()[,c('ts_PST','OutdoorHumidity','IndoorHumidity')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
date = date(ts_PST)
) %>%
group_by(date) %>%
summarise(
min_ih = min(IndoorHumidity), max_ih = max(IndoorHumidity),
min_oh = min(OutdoorHumidity), max_oh = max(OutdoorHumidity),
IndoorHumidity = mean(IndoorHumidity), OutdoorHumidity = mean(OutdoorHumidity),
ts_PST = first(ts_PST)
) %>%
mutate(
datetime = format(ts_PST, format = '%b-%d %H')
) %>%
data.frame()
plot(
plot_df$OutdoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = 'Relative %', xaxt = 'n'
)
par(new = T)
plot(
plot_df$IndoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_oh, rev(plot_df$max_oh)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)
)
polygon(
y = c(plot_df$min_ih, rev(plot_df$max_ih)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('blue', alpha.f = 0.3)
)
}
legend('topleft',bty = 'n', pch = 20, col = c('black','blue'), legend = c("Outdoor Humidity",'Indoor Humidity'))
mtext(side = 3, line = 2, text = 'Weekly Mean Humidity', cex = 1.5)
axis.POSIXct(x = plot_df$ts_PST,side = 1, las = 2, format = '%b %a')
mtext(side = 3, adj = 0, cex = 1.5,line = 0, text = paste('OH: ',round(last(plot_df$OutdoorHumidity),1),', IH: ', round(last(plot_df$IndoorHumidity),1), sep = ''))
if(input$smooth == T) {
lines(
smooth.spline(
x = plot_df[,'date'],
y = plot_df[,'OutdoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
lines(
smooth.spline(
x = plot_df[,'date'],
y = plot_df[,'IndoorHumidity'],
df = max(round(nrow(plot_df)*input$smoothness,0),2)
),
col = 'red', lwd = 2
)
}
# * Weekly ####
} else if (input$resolution == 'Weekly') {
plot_df = recent_data()[,c('ts_PST','OutdoorHumidity','IndoorHumidity')] %>%
filter(
ts_PST >as.POSIXct(as.character(input$range[1]), tz = '') + 3600*(as.numeric(input$hourstart)),
ts_PST < as.POSIXct(as.character(input$range[2]), tz = '') + 3600*as.numeric(input$hourend)
) %>%
mutate(
week = week(ts_PST), year = year(ts_PST)
) %>%
group_by(year, week) %>%
summarise(
min_ih = min(IndoorHumidity), max_ih = max(IndoorHumidity),
min_oh = min(OutdoorHumidity), max_oh = max(OutdoorHumidity),
IndoorHumidity = mean(IndoorHumidity), OutdoorHumidity = mean(OutdoorHumidity),
ts_PST = first(ts_PST)
) %>%
mutate(
datetime = format(ts_PST, format = '%b-%d %H')
) %>%
data.frame()
plot(
plot_df$OutdoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
ylab = 'Relative %', xaxt = 'n', type = 'b'
)
par(new = T)
plot(
plot_df$IndoorHumidity~plot_df$ts_PST,
las = 2, xaxt = 'n', pch = 20, cex = 1, xlab = '', ylim = ylim_set,
xaxt = 'n', yaxt = 'n', ylab = '', col = 'blue', type = 'b'
)
if (input$high_low == TRUE) {
polygon(
y = c(plot_df$min_oh, rev(plot_df$max_oh)),
x = c(plot_df$ts_PST, rev(plot_df$ts_PST)),
border = NA, col = adjustcolor('grey', alpha.f = 0.3)