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Stefano Sofia

2018-Aug-10 16:48 UTC

[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals

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 at regione.marche.it
---Oo---------oO----------------

________________________________

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Jim Lemon

2018-Aug-12 23:55 UTC

head link

[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 at 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 at regione.marche.it
> ---Oo---------oO----------------
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere
informazioni confidenziali, pertanto ? destinato solo a persone autorizzate alla
ricezione. I messaggi di posta elettronica per i client di Regione Marche
possono contenere informazioni confidenziali e con privilegi legali. Se non si ?
il destinatario specificato, non leggere, copiare, inoltrare o archiviare questo
messaggio. Se si ? ricevuto questo messaggio per errore, inoltrarlo al mittente
ed eliminarlo completamente dal sistema del proprio computer. Ai sensi dell?art.
6 della DGR n. 1394/2008 si segnala che, in caso di necessit? ed urgenza, la
risposta al presente messaggio di posta elettronica pu? essere visionata da
persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only by
persons entitled to receive the confidential information it may contain. E-mail
messages to clients of Regione Marche may contain information that is
confidential and legally privileged. Please do not read, copy, forward, or store
this message unless you are an intended recipient of it. If you have received
this message in error, please forward it to the sender and delete it completely
from your computer system.
>
> --
> Questo messaggio  stato analizzato da Libra ESVA ed  risultato non infetto.
> This message was scanned by Libra ESVA and is believed to be clean.
>
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

Stefano Sofia

2018-Aug-16 10:33 UTC

head link

[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals

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 at regione.marche.it
---Oo---------oO----------------
________________________________________
Da: Jim Lemon [drjimlemon at gmail.com]
Inviato: luned? 13 agosto 2018 1.55
A: Stefano Sofia
Cc: r-help at 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 at 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 at regione.marche.it
> ---Oo---------oO----------------
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere
informazioni confidenziali, pertanto ? destinato solo a persone autorizzate alla
ricezione. I messaggi di posta elettronica per i client di Regione Marche
possono contenere informazioni confidenziali e con privilegi legali. Se non si ?
il destinatario specificato, non leggere, copiare, inoltrare o archiviare questo
messaggio. Se si ? ricevuto questo messaggio per errore, inoltrarlo al mittente
ed eliminarlo completamente dal sistema del proprio computer. Ai sensi dell?art.
6 della DGR n. 1394/2008 si segnala che, in caso di necessit? ed urgenza, la
risposta al presente messaggio di posta elettronica pu? essere visionata da
persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only by
persons entitled to receive the confidential information it may contain. E-mail
messages to clients of Regione Marche may contain information that is
confidential and legally privileged. Please do not read, copy, forward, or store
this message unless you are an intended recipient of it. If you have received
this message in error, please forward it to the sender and delete it completely
from your computer system.
>
> --
> Questo messaggio  stato analizzato da Libra ESVA ed  risultato non infetto.
> This message was scanned by Libra ESVA and is believed to be clean.
>
>
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R help - Aug 2018 - cumulate of snow cumulates from daily values of different automatic stations for some time intervals

[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals

[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals

[R] cumulate of snow cumulates from daily values of different automatic stations for some time intervals