Dear Petr,
Thank you for your answer. This will probably save me three lines of
script, which is appreciable.
Unfortunately, this does not solve my main issue, that is:
If my condition is not fulfilled (some points are outside the
landscape), I have to go back in the script to the first step, again and
again until the condition "none individual is outside the landscape" is
fulfilled.
Is it a trick in R that makes that possible ? Or am I obliged to
copy-paste : step 1 - step 2 - step 1 - step 2 .... lot of times and
hope that the number of steps was sufficient enough to avoid ALL the
outliers ?
Regards,
Gwennaël
Le 20/03/2014 14:15, PIKAL Petr a écrit :
Hi
I have a strong suspiction that you want to reinvent wheel.
does functions
?chull (grDevices) and ?pip (splancs) do what you want?
Regards
Petr
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Gwennaël Bataille
Sent: Thursday, March 20, 2014 9:55 AM
To: r-help@r-project.org
Subject: [R] How to make a code last until a condition is completed ?
# Dear all,
# I simulate individual paths in a landscape (let's say coordinates in
x
and y range
# from -100 to 100 both) and would like to replace each individual
going
outside the
# landscape by a new simulation... until none of them goes outside the
landscape.
# For example, I simulate 100 coordinates :
# Step 1 : Simulate the individuals coordinates
paths_x<- rnorm(100)*100 # This is a simplification for the example
paths_y<- rnorm(100)*100
# Step 2 : Detect individuals outside the landscape to simulate them
again
# The OUTSIDE variable tells if we need further simulations or not
# The OUTSIDE_IND variable informs about which individuals are outside
the landscape
IS_OUTSIDE<- c(-min(paths_x), max(paths_x), -min(paths_y),
max(paths_y)) # this gives the absolute value of min and max
if( any(IS_OUTSIDE> 100) ) { OUTSIDE<- TRUE } else { OUTSIDE<- FALSE
}
if(OUTSIDE == TRUE) { OUTSIDE_IND<- c(which(paths_x< -100),
which(paths_x> 100), which(paths_y< - 100), which(paths_y> 100)) } #
Identifies the outliers
# What I would like to do is :
if( OUTSIDE == TRUE ) { # Go to step 1 again
paths_x[ OUTSIDE_IND ]<- rnorm(100)[ length( OUTSIDE_IND ) ]*100
paths_y[ OUTSIDE_IND ]<- rnorm(100)[ length( OUTSIDE_IND ) ]*100
} # And then, go to step 2 again :
# are there some individuals outside the landscape again ? -> if yes,
go
to step 1 untill none is left
else { # Go to step 3 }
# I could easily copy-paste steps 1 and 2 a lot of time, but I want to
make sure all the individuals are OK,
# that none remains outside the landscape "by chance"
# Thank you very much in advance for your help,
# Gwennaël Bataille
--
Gwennaël BATAILLE, PhD student - Teaching assistant
Earth and Life Institute
Université Catholique de Louvain
SST/ELI/ELIB
Bâtiment Carnoy, c.145
Croix du sud 4-5, bte L7.07.04
1348 Louvain-la-Neuve
BELGIUM
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--
Gwennaël BATAILLE, PhD student - Teaching assistant
Earth and Life Institute
Université Catholique de Louvain
SST/ELI/ELIB
Bâtiment Carnoy, c.145
Croix du sud 4-5, bte L7.07.04
1348 Louvain-la-Neuve
BELGIUM
______________________________________________
R-help@r-project.org mailing list
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.
