[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals
Stefano Sofia
@te|@no@@o||@ @end|ng |rom reg|one@m@rche@|t
Thu Aug 16 12:33:28 CEST 2018
Hi Jim.
Thank you for your help. I found very useful cum_snow and cum_list, but I decided to manage the list and dates in a different way.
First of all I decided to deal with a unique data frame (called df_CFS) where I attached all the 10 data frames, and instead to build a list with the 10 different data frames I created a list with the 10 station codes (217, 2018, ...):
list_station_code <- list(217, 218, 219, ...)
For managing dates, I created a vector of length 6. This is an example
my_date <- c("1999-12-17-00-00", "2000-01-07-00-00", "2000-01-10-00-00", "2000-01-15-00-00", NA, NA)
and then I created three functions based on the non NA elements of my_date:
sum_prec1 <- function(x, init_day1_POSIX, fin_day1_POSIX) {
sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day1_POSIX & df_CFS$data_POSIX <= fin_day1_POSIX], na.rm=T)
}
sum_prec2 <- function(x, init_day1_POSIX, fin_day1_POSIX, init_day2_POSIX, fin_day2_POSIX) {
print("sum_prec2")
sum1 <- sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day1_POSIX & df_CFS$data_POSIX <= fin_day1_POSIX], na.rm=T)
sum2 <- sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day2_POSIX & df_CFS$data_POSIX <= fin_day2_POSIX], na.rm=T)
sum <- sum1 + sum2
}
sum_prec3 <- function(x, init_day1_POSIX, fin_day1_POSIX, init_day2_POSIX, fin_day2_POSIX, init_day3_POSIX, fin_day3_POSIX) {
print("sum_prec3")
sum1 <- sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day1_POSIX & df_CFS$data_POSIX <= fin_day1_POSIX], na.rm=T)
sum2 <- sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day2_POSIX & df_CFS$data_POSIX <= fin_day2_POSIX], na.rm=T)
sum3 <- sum(df_CFS$Hn[df_CFS$Codice_sensore==x & df_CFS$data_POSIX >= init_day3_POSIX & df_CFS$data_POSIX <= fin_day3_POSIX], na.rm=T)
sum <- sum1 + sum2 + sum3
}
Finally
my_date_POSIX <- as.POSIXct(my_date), format="%Y-%m-%d-%H-%M")
my_date_POSIX <- my_dates[!is.na(my_date_POSIX)]
if (length(my_date_POSIX)==2) my_output <- lapply(list_station_code, sum_prec1, my_date_POSIX[[1]], my_date_POSIX[[2]])
else if (length(my_date_POSIX)==4) my_output <- lapply(list_station_code, sum_prec2, my_date_POSIX[[1]], my_date_POSIX[[2]], my_date_POSIX[[3]], my_date_POSIX[[4]])
else if (length(my_dates)==6) my_output <- lapply(list_station_code, sum_prec3, my_date_POSIX[[1]], my_date_POSIX[[2]], my_date_POSIX[[3]], my_date_POSIX[[4]], my_date_POSIX[[5]], my_date_POSIX[[6]])
df_snow_totals <- data.frame("station_code" = c(217, 218, 219))
df_snow_totals$Cumulata <- as.vector(my_output)
df_snow_totals$Cumulata <- as.numeric(as.character(unlist(df_snow_totals$Cumulata)))
It works.
Thank you for your help
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Area Meteorologica e Area nivologica - Centro Funzionale
Servizio Protezione Civile - Regione Marche
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia using regione.marche.it
---Oo---------oO----------------
________________________________________
Da: Jim Lemon [drjimlemon using gmail.com]
Inviato: lunedì 13 agosto 2018 1.55
A: Stefano Sofia
Cc: r-help using r-project.org
Oggetto: Re: [R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals
Hi Stefano,
This was such a stinker of a problem that I just had to crack it:
# create some data the lazy man's way
year_dates<-c(paste(2000,rep("01",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("02",29),formatC(1:29,width=2,flag=0),sep="-"),
paste(2000,rep("03",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("04",30),formatC(1:30,width=2,flag=0),sep="-"),
paste(2000,rep("05",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("06",30),formatC(1:30,width=2,flag=0),sep="-"),
paste(2000,rep("07",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("08",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("09",30),formatC(1:30,width=2,flag=0),sep="-"),
paste(2000,rep("10",31),formatC(1:31,width=2,flag=0),sep="-"),
paste(2000,rep("11",30),formatC(1:30,width=2,flag=0),sep="-"),
paste(2000,rep("12",31),formatC(1:31,width=2,flag=0),sep="-"))
df1<-data.frame(station_code=rep(217,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df2<-data.frame(station_code=rep(218,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df3<-data.frame(station_code=rep(219,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df4<-data.frame(station_code=rep(220,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df5<-data.frame(station_code=rep(221,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df6<-data.frame(station_code=rep(222,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df7<-data.frame(station_code=rep(223,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df8<-data.frame(station_code=rep(224,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df9<-data.frame(station_code=rep(225,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
df10<-data.frame(station_code=rep(226,366),
date_factor=year_dates,date_POSIX=year_dates,
snow=c(sample(0:70,31),sample(0:50,29),sample(0:10,31,TRUE),rep(0,214),
sample(0:20,30,TRUE),sample(0:60,31)))
snow_list<-list(df1,df2,df3,df4,df5,df6,df7,df8,df9,df10)
for(station in 1:10)
snow_list[[station]]$doy<-1:length(snow_list[[station]]$date_POSIX)
select_days<-c(1:12,83:88)
cum_snow<-function(x,which_days) {
return(list(x$station_code[1],sum(x$snow[which_days])))
}
cum_list<-lapply(lapply(snow_list,cum_snow,select_days),unlist)
snow_totals<-data.frame(station_code=NULL,snow_cumulate=NULL)
for(station in 1:10) snow_totals<-rbind(snow_totals,cum_list[[station]])
names(snow_totals)<-c("station_code","snow_cumulate")
Jim
On Sat, Aug 11, 2018 at 2:48 AM, Stefano Sofia
<stefano.sofia using regione.marche.it> wrote:
> Dear R-list users,
> I have 10 data frames (called df1, df2, ... df10), where each of them contains snow data from an automatic meteorological station (obviously each station has a different station code).
> Here is an example of df1:
>
> station_code date_factor date_POSIX snow
> 217 1999-12-15 1999-12-15 0
> 217 1999-12-16 1999-12-16 0
> 217 1999-12-17 1999-12-17 38
> 217 1999-12-18 1999-12-18 31
> 217 1999-12-19 1999-12-19 21
> 217 1999-12-20 1999-12-20 12
> 217 1999-12-21 1999-12-21 42
> 217 1999-12-22 1999-12-22 61
> 217 1999-12-23 1999-12-23 57
> 217 1999-12-24 1999-12-24 48
> ...
>
> where
>> sapply(df1, class)
> $station_code
> [1] "numeric"
>
> $date_factor
> [1] "factor"
>
> $date_POSIX
> [1] "POSIXct" "POSIXt"
>
> $snow
> [1] "integer"
>
> Given a series of max three intervals (example with two intervals: from 1st to 12th of January 2000 and from 23rd to 28th of March 2000), I need to evaluate for each station the total snow cumulate for all the intervals selected, and finally create a data frame where for each line there is the station code and the snow cumulate. It should be like
>
> station_code total_snow_cumulate
> 217 125
> 218 80
> ...
>
> Could somebody show me a direction for an efficient solution?
>
> Thank you for your attention and your help
> Stefano
>
>
> (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Area Meteorologica e Area nivologica - Centro Funzionale
> Servizio Protezione Civile - Regione Marche
> Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: stefano.sofia using regione.marche.it
> ---Oo---------oO----------------
>
> ________________________________
>
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