On 6/19/08, Nikos Alexandris <[EMAIL PROTECTED]> wrote: > On Wed, 2008-06-18 at 22:41 +0100, Glynn Clements wrote: >> Glynn Clements wrote: >> >> > > Thanks! Multiplying by 1000 with r.mapcalc gives better results. Any >> > > chance adding floating points (FCELL) to i.cluster? >> > >> > I had a brief look at the code[1], and cannot see any obvious reason >> > why the values would need to be integers, so I'm assuming that it's >> > just a legacy of the days before FP support was added. >> > >> > [1] Most of the code is actually in the lib/imagery/c_*.c files. That >> > should either be made part of i.cluster (nothing else uses it), or at >> > least split into a separate library. >> >> I have committed these changes (splitting the cluster code off to a >> separate library, and changing it to use DCELL instead of CELL) to the >> SVN trunk. >> >> I would appreciate it if someone who understands i.cluster could test >> the current version. >> > > I've compiled and run it yesterday. How can I tell that the changes are > effective? Should i.cluster NOT work before the changes with FP maps? >From my previous run of i.cluster Very low values like this: r.info -r tcor.lsat7_2000.toar.1 min=0.039443 max=0.442334
Gives out low separability: means and standard deviations for 3 bands means 0.00 0.00 0.00 stddev 0.06 0.00 0.00 initial means for each band class 1 -0.05 0.00 0.00 class 2 -0.05 0.00 0.00 class 3 -0.05 0.00 0.00 class 4 -0.05 0.00 0.00 class 5 -0.04 0.00 0.00 class 6 -0.04 0.00 0.00 class 7 -0.04 0.00 0.00 class 8 -0.04 0.00 0.00 class 9 -0.03 0.00 0.00 class 10 -0.03 0.00 0.00 ... 1 classes (convergence=100.0%) class separability matrix 1 1 0 class means/stddev for each band class 1 (2161) means 0.00 0.00 0.00 stddev 0.00 0.00 0.00 Whereas recalculating using the same layers multiplied by 1000 with r.mapcalc gives better results: means and standard deviations for 3 bands means 316.19 82.61 -78.36 stddev 63.13 54.24 41.51 initial means for each band class 1 253.06 28.38 -119.87 class 2 255.64 30.59 -118.18 class 3 258.21 32.80 -116.49 class 4 260.79 35.02 -114.79 class 5 263.37 37.23 -113.10 class 6 265.94 39.44 -111.40 .... lass distribution 172 15 20 21 41 22 20 27 27 28 29 36 27 37 45 35 35 44 53 53 52 50 57 54 45 56 48 58 61 47 58 59 65 50 47 52 35 34 35 41 41 34 27 25 27 24 29 10 15 145 ######## iteration 1 ########### 50 classes, 19.37% points stable class distribution 60 45 19 98 10 18 71 13 8 112 176 8 10 15 7 6 9 23 124 22 8 53 13 125 134 10 14 10 52 8 101 12 19 39 45 12 4 178 119 11 8 11 29 77 18 Can you report back your results? I hope I dont have to do r.mapcalc and run i.cluster from the original layer values. cheers, maning _______________________________________________ > grass-user mailing list > [EMAIL PROTECTED] > http://lists.osgeo.org/mailman/listinfo/grass-user > -- |---------|----------------------------------------------------------| | __.-._ |"Ohhh. Great warrior. Wars not make one great." -Yoda | | '-._"7' |"Freedom is still the most radical idea of all" -N.Branden| | /'.-c |Linux registered user #402901, http://counter.li.org/ | | | /T |http://esambale.wikispaces.com| | _)_/LI |---------|----------------------------------------------------------| _______________________________________________ grass-dev mailing list grass-dev@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-dev