[ferret_users] Randomly distributed time series plots

["'Fabio' via _OAR PMEL Ferret Users" <ferret_users@xxxxxxxx>]

Dear all,
 
Sometimes I need to do a 'quick check' across a large area and visualize 
the time series of a particular variable at random locations to get an 
idea of the general trend through time.
 
At the moment I am using a not-so-flexible approach, such as
 
let indice_a = {1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4}
let indice_b = {1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3}
let indice_x = {73,75,77,79}
let indice_y = {11,13,15}
go multi_view 4,3
 
repeat/RANGE=1:10/NAME=m (let a = indice_a[i=`m`] ;\
let b = indice_b[i=`m`] ;\
let x = indice_x[i=`m`] ;\
let y = indice_y[i=`m`] ;\
set view V`a``b`;\
plot my_variable[x=`x`,y=`y`,k=2]
 
This nested loop is not working, but it's a concept I tried to develop 
based on a single loop. As you can see it's rather tedious to write 
these indices and not easily adaptable to any region when lat and long 
can vary. Also I need two or three nested loops, which for now I can't 
make them work.
 
Additionally, I want to use the maximum allowed by multi_view, which I 
think is 15 windows, and do it multiple times in a loop if I need to 
sample a large region.
 
Is there anyway to make this more automatic? Such as sampling randomly 
lat and long from the available range? For example In R I would use the 
sampling function to create indices for x and y, and then use them in a 
loop.
 
I am sure other people have a need to check spatial change in a variable 
across time. Any suggestion or idea is well appreciated.
 
Thanks