Thanks. I am using EPSG:3081 <http://spatialreference.org/ref/epsg/3081/>, and its unit is meters. So is it the case that a SD of *x* on EPSG:3081 means a search radius of 4*x *meters? If so, why 4*x*?
Aren On Thu, Dec 6, 2012 at 2:29 AM, Markus Metz <[email protected]>wrote: > On Thu, Dec 6, 2012 at 3:58 AM, Aren Cambre <[email protected]> wrote: > > It's gotten slow again. This run will probably take more than 10 hours. > > However, I am using a standard deviation of 1000. Is that what could be > > causing this? > > Yes. With a standard deviation of 1000, the search radius is now 4000, > that is, for each cell a 8000x8000 box is searched. With many densely > packed points, this can take quite some time. > > Markus M > > > > > v.kernel input=tickets@PERMANENT output=tickets_new_heatmap_1000 > > stddeviation=1000 > > STDDEV: 1000.000000 > > RES: 18.290457 ROWS: 2370 COLS: 2650 > > > > Writing output raster map using smooth parameter=1000.000000. > > > > Normalising factor=6482635.018778. > > > > On Sat, Nov 24, 2012 at 9:03 PM, Aren Cambre <[email protected]> > wrote: > >> > >> I installed r53983. The v.kernel execution that took almost a day now > >> executes in 25.5 minutes. Thank you! > >> > >> Aren > >> > >> > >> On Fri, Nov 23, 2012 at 12:51 PM, Markus Metz > >> <[email protected]> wrote: > >>> > >>> On Fri, Nov 23, 2012 at 5:35 PM, Aren Cambre <[email protected]> > wrote: > >>> > Thanks! > >>> > > >>> > I am not familiar with GRASS's release customs. Will this become part > >>> > of a > >>> > binary release soon, or should I just pull down the latest release in > >>> > the > >>> > 6.4.2 trunk? I'm assuming this has been merged into the trunk... > >>> > >>> It should be available as a binary for Windows by tomorrow in the > >>> nightly builds [0]. > >>> > >>> Markus M > >>> > >>> [0] http://wingrass.fsv.cvut.cz/grass64/ > >>> > >>> > > >>> > Aren > >>> > > >>> > > >>> > On Fri, Nov 23, 2012 at 7:32 AM, Markus Metz > >>> > <[email protected]> > >>> > wrote: > >>> >> > >>> >> On Fri, Nov 23, 2012 at 2:07 PM, Aren Cambre <[email protected]> > >>> >> wrote: > >>> >> > Isn't taking about 10,000% too much time considered a bug? :-) > >>> >> > >>> >> Hmm, yes. v.kernel is fixed in devbr6 and relbr6 with r53982 and > >>> >> r53983, respectively. > >>> >> > >>> >> Markus M > >>> >> > >>> >> > > >>> >> > On Nov 23, 2012 5:11 AM, "Markus Metz" > >>> >> > <[email protected]> > >>> >> > wrote: > >>> >> >> > >>> >> >> On Fri, Nov 23, 2012 at 4:14 AM, Aren Cambre < > [email protected]> > >>> >> >> wrote: > >>> >> >> > I'm able to reproduce reliably here. I'll email you details > >>> >> >> > privately. > >>> >> >> > >>> >> >> Thanks. I can confirm that v.kernel takes a long time in GRASS 6 > >>> >> >> with > >>> >> >> the settings provided by you. It does not crash, however. > >>> >> >> > >>> >> >> I can speed up v.kernel in GRASS 6 to complete in 10 minutes > >>> >> >> instead > >>> >> >> of 16+ hours, but I am not sure if this fix can/will go into > GRASS > >>> >> >> 6.4 > >>> >> >> because by now only bugs should be fixed. > >>> >> >> > >>> >> >> Markus M > >>> >> >> > >>> >> >> > > >>> >> >> > Aren > >>> >> >> > > >>> >> >> > > >>> >> >> > On Thu, Nov 22, 2012 at 9:02 AM, Markus Metz > >>> >> >> > <[email protected]> > >>> >> >> > wrote: > >>> >> >> >> > >>> >> >> >> On Sat, Nov 17, 2012 at 4:06 PM, Aren Cambre > >>> >> >> >> <[email protected]> > >>> >> >> >> wrote: > >>> >> >> >> > I have a dataset of just over 700,000 incidents that > happened > >>> >> >> >> > in > >>> >> >> >> > square-ish > >>> >> >> >> > Texas county that's about 30 miles on each side. > >>> >> >> >> > > >>> >> >> >> > Here's the parameters reported by v.kernel as it's > executing: > >>> >> >> >> > > >>> >> >> >> > STDDEV: 1000.000000 > >>> >> >> >> > RES: 111.419043 ROWS: 458 COLS: 447 > >>> >> >> >> > > >>> >> >> >> > Writing output raster map using smooth > parameter=1000.000000. > >>> >> >> >> > > >>> >> >> >> > Normalising factor=6482635.018778. > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > I am running this on a Windows 7 x64 machine with 8 GB RAM > and > >>> >> >> >> > an > >>> >> >> >> > Intel > >>> >> >> >> > Core > >>> >> >> >> > i7 Q720 1.6 GHz with 4 physical cores. I notice that it's > not > >>> >> >> >> > multithreaded, > >>> >> >> >> > only using 1 core. > >>> >> >> >> > > >>> >> >> >> > It takes about 16 hours to complete. Is this correct? I'd > like > >>> >> >> >> > to > >>> >> >> >> > use > >>> >> >> >> > this > >>> >> >> >> > on a dataset with closer to 5 million records, and I'm > really > >>> >> >> >> > concerned > >>> >> >> >> > how > >>> >> >> >> > long it may take. > >>> >> >> >> > >>> >> >> >> The time required by v.kernel is a function of the number of > >>> >> >> >> cells > >>> >> >> >> and > >>> >> >> >> the input parameter stddeviation. The larger any of these > values > >>> >> >> >> is, > >>> >> >> >> the more time v.kernel will need. Nevertheless, I think that > the > >>> >> >> >> 16+ > >>> >> >> >> hours are not correct. I tested with a vector with 3 million > >>> >> >> >> points > >>> >> >> >> for a grid with 2700 rows and 1087 columns, magnitudes larger > >>> >> >> >> than > >>> >> >> >> the > >>> >> >> >> grid used by you. v.kernel completes in just over one minute. > >>> >> >> >> > >>> >> >> >> > > >>> >> >> >> > I posted my question about the 16+ hours at > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > > http://gis.stackexchange.com/questions/41058/how-do-i-compute-v-kernel-maps-in-less-than-16-hours/ > . > >>> >> >> >> > Bill Huber, who si apparently knowledgeable about kernel > >>> >> >> >> > density > >>> >> >> >> > calculations in general, posted a response, and he felt > like a > >>> >> >> >> > kernel > >>> >> >> >> > density map shouldn't take much time at all. But digging > more > >>> >> >> >> > deeply, > >>> >> >> >> > turns > >>> >> >> >> > out he had come up with a kernel density calculation method > >>> >> >> >> > over a > >>> >> >> >> > decade > >>> >> >> >> > ago using Fourier transforms. See > >>> >> >> >> > http://www.directionsmag.com/features/convolution/129753and > >>> >> >> >> > the > >>> >> >> >> > next > >>> >> >> >> > two > >>> >> >> >> > articles linked to it (they are short articles). Apparently > >>> >> >> >> > this > >>> >> >> >> > transforms > >>> >> >> >> > it from an O(n^2) problem to an O(n ln n) complexity > problem. > >>> >> >> >> > >>> >> >> >> The approach of Bill Huber is raster-based, not vector based, > >>> >> >> >> making > >>> >> >> >> some things easier, at the cost of precision. The coordinate > >>> >> >> >> precision, however, is only needed for kernel functions other > >>> >> >> >> than > >>> >> >> >> uniform. In GRASS, you could get something like a raster-based > >>> >> >> >> density > >>> >> >> >> map by > >>> >> >> >> > >>> >> >> >> - exporting the points with v.out.ascii > >>> >> >> >> - re-importing the points with r.in.xyz method=n to get the > >>> >> >> >> number > >>> >> >> >> of > >>> >> >> >> points per cell > >>> >> >> >> - running a neighborhood analysis using a circular window with > >>> >> >> >> r.neighbors method=sum -c > >>> >> >> >> > >>> >> >> >> Optionally you could use the gauss option of r.neighbors to > get > >>> >> >> >> an > >>> >> >> >> equivalent to v.kernel kernel=gaussian > >>> >> >> >> > >>> >> >> >> HTH, > >>> >> >> >> > >>> >> >> >> Markus M > >>> >> >> >> > >>> >> >> >> > > >>> >> >> >> > I inspected v.kernel's main.c > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > > >>> >> >> >> > ( > http://trac.osgeo.org/grass/browser/grass/trunk/vector/v.kernel/main.c), > >>> >> >> >> > and looks like v.kernel uses an output-centric method (using > >>> >> >> >> > Bill's > >>> >> >> >> > wording) > >>> >> >> >> > of calculating the output, which seems like O(n^2) > complexity. > >>> >> >> >> > > >>> >> >> >> > So I guess what I'm getting at is it appears to me that the > >>> >> >> >> > algorithm > >>> >> >> >> > behind > >>> >> >> >> > GRASS GIS's v.kernel is straightforward but is a greedy > >>> >> >> >> > algorithm > >>> >> >> >> > (http://en.wikipedia.org/wiki/Greedy_algorithm), which is > >>> >> >> >> > fine, > >>> >> >> >> > but > >>> >> >> >> > it > >>> >> >> >> > make > >>> >> >> >> > take a while to execute. Is this true? > >>> >> >> >> > > >>> >> >> >> > Is there not spatial indexing I could add to the dataset? > I've > >>> >> >> >> > done > >>> >> >> >> > various > >>> >> >> >> > Google searches on that and can't come up with anything > clear. > >>> >> >> >> > > >>> >> >> >> > Aren > >>> >> >> >> > > >>> >> >> >> > _______________________________________________ > >>> >> >> >> > grass-user mailing list > >>> >> >> >> > [email protected] > >>> >> >> >> > http://lists.osgeo.org/mailman/listinfo/grass-user > >>> >> >> >> > > >>> >> >> > > >>> >> >> > > >>> > > >>> > > >> > >> > > >
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