R help - Mar 2008 - R code for selecting places spatially and by time

Hi all

The code of trying to write relates to selecting properties (given by x
and y co-ordinates) spatially (distance "X" from "infected"
properties
identified by date) over a certain time period.

i.e. what properties are within 3 km from properties infected on
"2008-01-01" over the last 14 days.

Is any one able to give me some clues on how to write code to solve this
problem.

Some sample data is as follows:

x<-rep(c(2660156,2660203,2658165,2659303,2661531,2660914),c(2,2,2,2,1,1)
)
y<-rep(c(6476767,6475013,6475487,6479659,6477004,6476388),c(2,2,2,2,1,1)
)
date<-as.character(rep(as.Date(c("2008-01-02","2008-01-17","2008-01-01")
,format = "%Y-%m-%d"),c(4,4,2)))
cbind(x,y,date)

Regards

Andrew

Andrew McFadden MVS BVSc
Incursion Investigator
Investigation & Diagnostic Centres - Wallaceville Biosecurity New 
Zealand Ministry of Agriculture and Forestry

Phone 04 894 5600 Fax 04 894 4973 Mobile 029 894 5611 Postal address: 
Investigation and Diagnostic Centre- Wallaceville Box 40742 Ward St 
Upper Hutt


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Andrew,

You haven't defined the problem clearly, but I will try to guess what
you mean...
>  i.e. what properties are within 3 km from properties infected on
>  "2008-01-01" over the last 14 days.
I'm guessing that each row of your sample data represents one
infection event, and you want to find all rows where the date is
within 14 days following "2008-01-01" and the location is within 3 km
of any of the sites listed as "2008-01-01".

Presumably the x and y coordinates are already in units of metres;
otherwise use "project" in package rgdal.

Then:

x <- rep(c(2660156,2660203,2658165,2659303,2661531,2660914),c(2,2,2,2,1,1)
)
y <- rep(c(6476767,6475013,6475487,6479659,6477004,6476388),c(2,2,2,2,1,1)
)
date <-
rep(as.Date(c("2008-01-02","2008-01-17","2008-01-01"),
    format = "%Y-%m-%d"),c(4,4,2))
## the set of properties or infections or something
props <- data.frame(x, y, date)
## find indices of source events
src.date <- as.Date("2008-01-01")
src.i <- which(date == src.date)
## distances between properties
dists <- as.matrix(dist(cbind(x,y)))
## select sites within space and time bounds
hits <- FALSE
for (i in src.i) {
    i.hits <- (src.date < date) & (date <= src.date + 14) &
        (dists[i,] < 3000)
    hits <- hits | i.hits
}
## look at matching sites
props[hits,]
## look at distances of matching sites from source sites
dists[src.i,hits]


It would also be possible to do it more efficiently if that is an issue.


On Fri, Mar 7, 2008 at 9:40 AM, Andrew McFadden
<Andrew.McFadden at maf.govt.nz> wrote:
>
>  Hi all
>
>  The code of trying to write relates to selecting properties (given by x
>  and y co-ordinates) spatially (distance "X" from
"infected" properties
>  identified by date) over a certain time period.
>
>  i.e. what properties are within 3 km from properties infected on
>  "2008-01-01" over the last 14 days.
>
>  Is any one able to give me some clues on how to write code to solve this
>  problem.
>
>  Some sample data is as follows:
>
> 
x<-rep(c(2660156,2660203,2658165,2659303,2661531,2660914),c(2,2,2,2,1,1)
>  )
> 
y<-rep(c(6476767,6475013,6475487,6479659,6477004,6476388),c(2,2,2,2,1,1)
>  )
> 
date<-as.character(rep(as.Date(c("2008-01-02","2008-01-17","2008-01-01")
>  ,format = "%Y-%m-%d"),c(4,4,2)))
>  cbind(x,y,date)
>
>  Regards
>
>  Andrew
>
>  Andrew McFadden MVS BVSc
>  Incursion Investigator
>  Investigation & Diagnostic Centres - Wallaceville Biosecurity New
>  Zealand Ministry of Agriculture and Forestry
>
>  Phone 04 894 5600 Fax 04 894 4973 Mobile 029 894 5611 Postal address:
>  Investigation and Diagnostic Centre- Wallaceville Box 40742 Ward St
>  Upper Hutt
>
>
>  ########################################################################
>  This email message and any attachment(s) is intended solely for the
>  addressee(s) named above. The information it contains is confidential
>  and may be legally privileged.  Unauthorised use of the message, or the
>  information it contains, may be unlawful. If you have received this
>  message by mistake please call the sender immediately on 64 4 8940100
>  or notify us by return email and erase the original message and
>  attachments. Thank you.
>
>  The Ministry of Agriculture and Forestry accepts no responsibility for
>  changes made to this email or to any attachments after transmission from
>  the office.
>  ########################################################################
>
>         [[alternative HTML version deleted]]
>
>  ______________________________________________
>  R-help at 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.
>


-- 
Felix Andrews / $B0BJ!N)(B
PhD candidate
Integrated Catchment Assessment and Management Centre
The Fenner School of Environment and Society
The Australian National University (Building 48A), ACT 0200
Beijing Bag, Locked Bag 40, Kingston ACT 2604
http://www.neurofractal.org/felix/
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Andrew McFadden <Andrew.McFadden <at> maf.govt.nz> writes:
> 
> 
> Hi all
> 
> The code of trying to write relates to selecting properties (given by x
> and y co-ordinates) spatially (distance "X" from
"infected" properties
> identified by date) over a certain time period.
> 
> i.e. what properties are within 3 km from properties infected on
> "2008-01-01" over the last 14 days.
> 
> Is any one able to give me some clues on how to write code to solve this
> problem.
> 
> Some sample data is as follows:
> 
> x<-rep(c(2660156,2660203,2658165,2659303,2661531,2660914),c(2,2,2,2,1,1)
> )
> y<-rep(c(6476767,6475013,6475487,6479659,6477004,6476388),c(2,2,2,2,1,1)
> )
>
date<-as.character(rep(as.Date(c("2008-01-02","2008-01-17","2008-01-01")
> ,format = "%Y-%m-%d"),c(4,4,2)))
> cbind(x,y,date)
  This should certainly be possible.  Your description of the
problem isn't entirely clear to me, but here's a first approximation:

dat <- data.frame(x,y,date)
## data.frame is better than cbind, it can hold dates and locations

infdate <- as.Date("2008-01-01")
infprem <- subset(dat,date==infdate)
otherprem <- subset(dat,date>=infdate)
## or:
elapsed <- dat$date-infdate
otherprem <- subset(dat,elapsed>0 & elapsed<14)
## I'm not sure this is what you wanted in terms
##  of date restrictions, but you could adjust appropriately
dist <- sqrt(outer(infprem$x,otherprem$x,"-")^2+
             outer(infprem$y,otherprem$y,"-")^2)
             
mindist <- apply(dist,2,min)

minval <- 1000 ## (I don't know what the units are??)
prem <- subset(otherprem,mindist<minval)
## or prem <- otherprem[mindist<minval,]