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helper.R
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helper.R
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library(shiny)
library(maps)
library(dplyr)
library(tidyr)
library(lubridate)
library(ggplot2)
library(magrittr)
library(rmarkdown)
library(rlang)
################################################################################
# Helper functions
# -homogenize_tibble(file_name)
# -give_title(parenthesis)
# -give_ylabel(ylabel)
# -give_table()
# -draw_plots()
`%and%` <- function(x, y){
as.logical(x*y)
}
# this function homogenize tibble
# reads csv assigning value types to columns
# and returns a tibble.
homogenize_tibble<-function(file_name){
#forces same column type
temp<-read_csv(file_name,col_types=cols(ob_time=col_character(),
hour=col_integer(),
day=col_integer(),
month=col_integer(),
wind_speed=col_integer(),
air_temperature=col_double(),
rltv_hum=col_double(),
visibility=col_integer(),
Site=col_integer()))
#change date time (cause of site_4)
temp<-temp %>%
mutate(ob_time=parse_date_time(ob_time,orders=c("YmdHMS","dmYHM")))
as_tibble(temp)
}
give_hutton_tibble<-function(name){
sites<-read_csv("./Data/Sites.csv")
first_tibble<-homogenize_tibble(name)
first_tibble<-first_tibble%>%
inner_join(sites,by=c("Site"="Site_ID"))
first_tibble%<>%select(c(ob_time,air_temperature,rltv_hum))
}
give_title<-function(parenthesis,weather){
if (weather=="wind_speed"){
x=paste("Wind speed"," (",parenthesis,")",sep="")
} else {
if (weather=="air_temperature"){
x=paste("Air temperature"," (",parenthesis,")",sep="")
} else {
if (weather=="rltv_hum"){
x=paste("Relative Humidity"," (",parenthesis,")",sep="")
} else {
if (weather=="visibility"){
x=paste("Visibility"," (",parenthesis,")",sep="")
}
}
}
}
}
give_ylabel<-function(ylabel,weather){
if (weather=="wind_speed"){
x=paste(ylabel,"wind speed",sep=" ")
} else {
if (weather=="air_temperature"){
x=paste(ylabel,"air temperature",sep=" ")
} else {
if (weather=="rltv_hum"){
x=paste(ylabel,"relative humidity",sep=" ")
} else {
if (weather=="visibility"){
x=paste(ylabel,"visibility",sep=" ")
}
}
}
}
}
give_table<-function(temp){
#steps for summary table
# 1. filter last 7 days (remove rows)
# 2. remove columns that are not needed
# 3. change ob_time to contain only dates
# 4. groupby ob_time and summarise (with mean)
# 5. convert to wide format for beter visibility.
if(!is_empty(temp)){
temp<-temp%>%filter(ob_time>=as.Date("2020-11-24"))
temp<-temp%>%select(ob_time,wind_speed,air_temperature,rltv_hum,visibility,Site_Name)
temp<-temp%>%mutate(ob_time=as.Date(ob_time))
temp<-temp%>%group_by(ob_time,Site_Name)%>%summarise_all(list(mean),na.rm=TRUE)
temp
round(temp[,3:6],2)
te<-bind_cols(temp[,1:2],round(temp[,3:6],2))
te
}
}
#hutton_table<-function(){
#}
draw_plots<-function(temp,time,weather){
temp%<>%select(ob_time,hour,day,month,!!sym(weather),Site_Name) #keep just the necessary columns
req(time)
if (time==1){ #Selected "Raw hourly data" & "Week hours"
temp%<>%mutate(Weekdays=wday(ob_time)) #make a column with Weekdays (1-7)
temp%<>%mutate(Week_hours=(Weekdays-1)*24+hour) #make a column with the hours (1-168)
ggplot(temp,aes(Week_hours,!!sym(weather),colour=Site_Name,na.rm=TRUE))+geom_point(alpha=0.5)+
ggtitle(give_title("Raw hourly data",weather))+
xlab("Weekly hours")+
ylab(give_ylabel("Hourly",weather))
}
else {
if (time==2){ #Selected "Raw hourly data" & "24 hours"
ggplot(temp,aes(hour,!!sym(weather),colour=Site_Name,na.rm=TRUE))+geom_point(alpha=0.3)+
ggtitle(give_title("Raw hourly data",weather))+
xlab("24 hours")+
ylab(give_ylabel("Hourly",weather))
} else {
if (time==3){ #Selected "Daily averages" & "Calendar time"
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #from ob_time which holds the date time keep the date
temp<-temp%>%group_by(ob_time,Site_Name)%>%summarise(avg=mean(!!sym(weather),na.rm = TRUE)) #get daily average based on date and site
ggplot(temp,aes(ob_time,avg,colour=Site_Name,na.rm=TRUE))+geom_line()+
ggtitle(give_title("Daily averages",weather))+
xlab("Calendar time (Days)")+
ylab(give_ylabel("Daily",weather))
} else {
if(time==4){ #Selected "Daily averages" & "Week days"
temp<-temp%>%mutate(Weekdays=wday(ob_time)) #make a column Weekdats (1-7)
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #keep from ob_time with date time just the date
temp<-temp%>%group_by(ob_time,Weekdays,Site_Name)%>%summarise(avg=mean(!!sym(weather),na.rm=TRUE)) #get average based on SiteName, date and weekday
ggplot(temp,aes(Weekdays,avg,colour=Site_Name,na.rm=TRUE))+geom_point(alpha=0.5)+
ggtitle(give_title("Daily averages",weather))+
xlab("Week days")+
ylab(give_ylabel("Daily",weather))
} else {
if(time==5){ #Selected "Monthly averages" & "Calendar time"
temp<-temp%>%mutate(ob_time=month(ob_time)) #make a column with Months (1-12)
temp<-temp%>%group_by(ob_time,Site_Name)%>%summarise(avg=mean(!!sym(weather),na.rm=TRUE)) #get average per month and site
ggplot(temp,aes(ob_time,avg,colour=Site_Name,na.rm=TRUE))+geom_line()+
ggtitle(give_title("Monthly averages",weather))+
xlab("Calendar time (Months)")+
ylab(give_ylabel("Monthly",weather))
} else {
if(time==6){ #Selected "Daily maxima" & "Calendar time"
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #make-transform ob_time column with dates only
temp<-temp%>%group_by(ob_time,Site_Name)%>%summarise(max=max(!!sym(weather),na.rm=TRUE)) #get max for each date and site name
ggplot(temp,aes(ob_time,max,colour=Site_Name,na.rm=TRUE))+geom_line()+
ggtitle(give_title("Daily maxima",weather))+
xlab("Calendar time (Days)")+
ylab(give_ylabel("Daily",weather))
} else {
if(time==7){ #Selected "Daily maxima" & "Week days"
temp<-temp%>%mutate(Weekdays=wday(ob_time)) #make a new column with Weekdays (1-7)
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #transform ob_time with only date
temp<-temp%>%group_by(ob_time,Weekdays,Site_Name)%>%summarise(max=max(!!sym(weather),na.rm=TRUE)) #for each date,weekday and site name
ggplot(temp,aes(Weekdays,max,colour=Site_Name,na.rm=TRUE))+geom_point(alpha=0.5)+
ggtitle(give_title("Daily maxima",weather))+
xlab("Week days")+
ylab(give_ylabel("Daily",weather))
} else {
if(time==8){ #Selected "Daily minima" & "Calendar time"
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #transform ob_time with only date
temp<-temp%>%group_by(ob_time,Site_Name)%>%summarise(min=min(!!sym(weather),na.rm=TRUE)) #get minima based on date and site name
ggplot(temp,aes(ob_time,min,colour=Site_Name,na.rm=TRUE))+geom_line()+
ggtitle(give_title("Daily minima",weather))+
xlab("Calendar time (Days)")+
ylab(give_ylabel("Daily",weather))
} else {
if(time==9){ #Selected "Daily minima" & "Week days"
temp<-temp%>%mutate(Weekdays=wday(ob_time)) #make a column Weekdays (1-7)
temp<-temp%>%mutate(ob_time=as.Date(ob_time)) #transform ob_time to keep just date
temp<-temp%>%group_by(ob_time,Weekdays,Site_Name)%>%summarise(min=min(!!sym(weather),na.rm=TRUE)) #get min based on ob_time,weekdays,site name
ggplot(temp,aes(Weekdays,min,colour=Site_Name,na.rm=TRUE))+geom_point(alpha=0.5)+
ggtitle(give_title("Daily minima",weather))+
xlab("Week days")+
ylab(give_ylabel("Daily",weather))
}
}
}
}
}
}
}
}
}
}