[GRASSLIST:354] Re: a huge matrix ?
glynn.clements at virgin.net
Wed Jun 11 11:45:05 EDT 2003
> >>I have a huge matrix containing 7 column and 10500 rows.
> >>Each columns stand for different maps. Each rows represent "unique"
> >>combinations of catagories of maps and probability values
> >>of each row.
> >>Something like:
> >> map1 map2 map3 ... prob
> >>1 cat1 x x x x
> >>2 cat2 x x x x
> >>. .
> >>. .
> >>10500 .
> >>So I have 10500 if-clause to create a probability map.
> >>I tried r.mapcalc (as from a text file) but grass gave "stack overflow"
> >I'm not surprised.
> >>Is there anyone making suggestions ?
> >You need to describe your problem in more detail; it isn't clear what
> >you are trying to calculate.
> Thank you for your interest
> You wanted to know the problem in more detail:
> what I did:
> 1- using r.stat command I produced a text file for statistical calculations
> 2- using R statistical package I produced probability results of each
> map's for each categories.
> it means 7 columns of maps 10500 rows plus probability of each
> combination. Actually it is a contingency table. Any data in table
> (matrix) is resulting from unique combination of maps and their
> 3- I want to port these results to grass to create a map (of landslide
> susceptibility map) . Firstly I thought I used r.mapcalc with piping
> from text file. But because text file contains a huge matrix that is
> made up of 10500 if statement (for same number of rows) process failed.
> I attached a part of text file after modifying for r.mapcalc. you see
> all ifs are unique.
OK, so: each line is a rule; for each pixel you scan the list of rules
to find the first match, then output the associated result. Right?
The most straightforward approach (although not particularly
efficient), would be to use an iterative approach, i.e.
while read a1 a2 a3 a4 a5 a6 a7 a8 ; do
r.mapcalc "$result = if (f28geo5==$a1 && f28slpcat==$a2 && f28concavity==$a3 && n_facing==$a4 && road_bas==$a5 &&str_buf==$a6 && f28f4==$a7, $a8, $last)"
done < rules.txt
where rules.txt looks like:
21 6 1 1 1 1 0 701.22
7 4 2 1 1 2 1 702.06
Alternatively, you could combine this with your initial approach, only
matching a limited number of rules on each pass, and using several
However, I note that there seem to be very few possible values for
most of the maps. In that case, a far more efficient approach would be
1. Reclass each input map so that all of the significant categories
are consecutively numbered from zero (0,1,2,3,...); any insignificant
categories would be merged into the last category.
2. Compute a composite map, using e.g.
composite = f28geo5 + 22 * (f28slpcat + 9 * (f28concavity + 3 * ...
where the numbers are the total number of categories in the preceding
3. Assign the values as labels for the composite categories.
4. Use "@map" in r.mapcalc to use the label instead of the category.
Glynn Clements <glynn.clements at virgin.net>
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