Re: st: Mata - extracting various vectors of different sizes in one loop

[George Vega Yon <g.vegayon@gmail.com>]

Dear Nicolas,

I guess a more efficient way to do this would be filling a matrix and
after that replacing the data in Stata. That way you won't need to
make a fancy replacement during the loop; will be a clearer code.

Best wishes!

George
George Vega Yon
7 647 2552
http://cl.linkedin.com/in/georgevegayon


2013/4/4 Matthew Baker <matthew.baker@hunter.cuny.edu>:
> Nicholas --
>
> I have run into this problem as well, but have a slightly different
> solution (I'm not sure it's more elegant, though!) One thing that
> wasn't quite clear from your message was whether or not the values you
> were computing had to be placed in a particular place or if they could
> just be listed "from the beginning of a row," so I assumed not.
>
> My solution is to create a matrix with a maximal number of columns and
> then fill it in on the fly, and then get everything into stata using
> st_view - which has the property that variables can be overwritten
> from within mata. Anyways:
>
> clear all
> set seed 8675309
> set obs 100
> mata:
>
> // Random lengths for vectors:
> ni=J(100,1,1)
> for (i=1;i<=100;i++) ni[i]=round(runiform(1,1)*20)+1
>
> // Random vectors of random lengths placed in the array,
> // Which will also store a scalar which is length:
>
> Z=J(100,30,.)
> for (i=1;i<=100;i++) {
> Stuff=runiform(1,ni[i])
> length=cols(Stuff)
> Z[i,1::length]=Stuff
> }
> end
>
> local zvals
> forvalues i=1/30 {
> gen z`i'=.
> local zvals "`zvals' z`i'"
> }
> mata
> st_view(Ztemp=.,.,"`zvals'")
> Ztemp[.,.]=Z
> end
>
> On Thu, Apr 4, 2013 at 6:26 AM, nick bungy <nickbungystata@hotmail.co.uk> wrote:
>> I have a mata code that cycles through grid references (eastings, northings) of x entities and calculates for each entity all the other entities which are within a 10km radius of it.
>> So each individual entity has a row vector, with dimensions anywhere between 1 row (1 firm within 10km radius) and ~80 rows (80 firms within 10km radius). This is throwing up conformity errors when I try to store these vectors into a selection of ~80 variables in Stata.
>> My thought was to artifically inflate all row vectors to say 100 and fill all of the extra cells in each row vector with 0, then I can extract to 100 variables without conformity errors. I can then clean this up quite easily using Stata functions. I'm not quite sure how to go about this though.
>> My mata code is the following:
>>
>> mata:
>>          geoeasta = st_data(., "Geoeast")
>>          geonortha = st_data(., "Geonorth")
>>          n = rows(geoeasta)
>>
>>    density = .
>>    densitytwo = .
>>    densitythree = .
>>    dups   = .
>>
>>
>>          for(i=1; i<=n; ++i) {
>>
>>                  d = sqrt((geoeasta:-geoeasta[i]):^2 + (geonortha:-geonortha[i]):^2)
>>                  d[i] = .
>>                  density = select(d, d[.,1]:<10000)
>>                  minindex(density, 80, densitytwo, dups)
>>                  st_store(i, ("MSOA1", "MSOA2", "MSOA3" etc etc.), densitytwo)
>>      //This stores the nearest neighbours into our variables, which we defined at the top.
>>
>>   }
>>
>>
>>   end
>> I suspect I need a line or two below minidex, which inflates densitytwo to a 100 row vector and fills all the extra rows generated with 0. Or perhaps there is a more elegent way?
>> Many thanks,
>> Nicholas
>> *
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>
>
>
> --
> Dr. Matthew J. Baker
> Department of Economics
> Hunter College and the Graduate Center, CUNY
>
> *
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*
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