Sorry for the big delay of my report, but prolonged severe weather conditions 
often absorb a large amount of time and energies to my studies.

Thanks to all of you for your suggestions.

I have not been able to implement Bert Gunter's hint, his code gave me an error 
I have not been able to fix.

Bill Dunlap's hint is smart and has been resolutive.


Thank you again to all of you

Stefano



         (oo)
--oOO--( )--OOo--------------------------------------
Stefano Sofia PhD
Civil Protection - Marche Region - Italy
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona (AN)
Uff: +39 071 806 7743
E-mail: stefano.so...@regione.marche.it
---Oo---------oO----------------------------------------


________________________________
Da: Bill Dunlap <williamwdun...@gmail.com>
Inviato: sabato 13 maggio 2023 22:38
A: Stefano Sofia
Cc: r-help@R-project.org
Oggetto: Re: [R] aggregate wind direction data with wind speed required

I think that using complex numbers to represent the wind velocity makes this 
simpler.  You would need to write some simple conversion functions since wind 
directions are typically measured clockwise from north and the argument of a 
complex number is measured counterclockwise from east.  E.g.,

windToComplex <-
function(speed, degreesCW) {
  complex(mod=speed, arg=(90-degreesCW)/180*pi)
}
complexToWind <-
function(z) {
  # Convert complex velocity z to speed and direction (degrees clockwise
  # from north, in range [0,360)).
  stopifnot(is.complex(z))
  data.frame(speed = Mod(z), degreesCW = (pi - Arg(z*1i))/(2*pi)*360)
}

Then use FUN=mean instead of my_fun.

-Bill

On Sat, May 13, 2023 at 7:51 AM Stefano Sofia 
<stefano.so...@regione.marche.it<mailto:stefano.so...@regione.marche.it>> wrote:
Dear list users,

I have to aggregate wind direction data (wd) using a function that requires 
also a second input variable, wind speed (ws).

This is the function that I need to use:


my_fun <- function(wd1, ws1){

  u_component <- -ws1*sin(2*pi*wd1/360)
  v_component <- -ws1*cos(2*pi*wd1/360)
  mean_u <- mean(u_component, na.rm=T)
  mean_v <- mean(v_component, na.rm=T)
  mean_wd <- (atan2(mean_u, mean_v) * 360/2/pi) + 180
  result <- mean_wd
  result
}

Does the aggregate function work only with functions with a single input 
variable (the one that I want to aggregate), or its use can be extended to 
functions with two input variables?

Here a simple example (which is meaningless, the important think is the concept 
behind it):
df <- data.frame(day=c(1, 1, 1, 2, 2, 2, 3, 3), month=c(1, 1, 2, 2, 2, 2, 2, 
2), wd=c(45, 90, 90, 135, 180, 270, 270, 315), ws=c(7, 7, 8, 3, 2, 7, 14, 13))

aggregate(wd ~ day + month, data=df, FUN = my_fun)

cannot work, because ws is not taken into consideration.

I got lost. Any hint, any help?
I hope to have been able to explain my problem.
Thank you for your attention,
Stefano


         (oo)
--oOO--( )--OOo--------------------------------------
Stefano Sofia PhD
Civil Protection - Marche Region - Italy
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona (AN)
Uff: +39 071 806 7743
E-mail: stefano.so...@regione.marche.it<mailto:stefano.so...@regione.marche.it>
---Oo---------oO----------------------------------------

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