Memory consumption using pygrass.utils.get_raster_for_points

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Memory consumption using pygrass.utils.get_raster_for_points

stevenpawley
Hello devs,

When running pygrass.utils.get_raster_for_points repeatedly, it appears
that the python memory allocation continuously increases until all ram
is consumed, even if the extracted values are not being collected (or
are overwriting the same variable).

I noticed this when extracting raster data at point locations, when
using a large point dataset, even though I had pre-allocated a numpy
array to receive the results.

Below is an example on the nc_spm_08_grass7 example data (in the landsat
mapset), repeating the operation say 50 times on the same point vector
dataset. I wouldn't have expected the memory consumption to continuously
increase for this operation, because I'm overwriting the 'arr' variable
each time. However, if you repeat this enough times, you will run out of
system memory and the allocated memory does not appear to be released,
i.e. even if you manually force garbage collection.

Any suggestions?


from grass.pygrass.vector import VectorTopo
from grass.pygrass.raster import RasterRow
from grass.pygrass.modules.shortcuts import raster as r
from grass.pygrass.gis.region import Region
from grass.pygrass.utils import get_raster_for_points

reg = Region()
reg.from_rast("landclass96")
reg.write()
reg.set_raster_region()

r.random(input="landclass96", npoints=200000, vector="landclass96_roi",
          overwrite=True)

points = VectorTopo("landclass96_roi")
points.open("r")

# repeat spatial query of raster
for i in range(50):
     with RasterRow("lsat5_1987_10") as src:
         arr = get_raster_for_points(points, src)

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Re: Memory consumption using pygrass.utils.get_raster_for_points

Markus Neteler
hi Steven

(yes, the mail came through)

On Sat, Feb 9, 2019 at 5:39 PM Steven Pawley <[hidden email]> wrote:

>
> Hello devs,
>
> When running pygrass.utils.get_raster_for_points repeatedly, it appears
> that the python memory allocation continuously increases until all ram
> is consumed, even if the extracted values are not being collected (or
> are overwriting the same variable).
>
> I noticed this when extracting raster data at point locations, when
> using a large point dataset, even though I had pre-allocated a numpy
> array to receive the results.

Do you see a chance to run valgrind on this? (maybe there are more
appropriate tools in the Python world):

https://grasswiki.osgeo.org/wiki/GRASS_Debugging#Using_Valgrind

> Below is an example on the nc_spm_08_grass7 example data (in the landsat
> mapset), repeating the operation say 50 times on the same point vector
> dataset. I wouldn't have expected the memory consumption to continuously
> increase for this operation, because I'm overwriting the 'arr' variable
> each time. However, if you repeat this enough times, you will run out of
> system memory and the allocated memory does not appear to be released,
> i.e. even if you manually force garbage collection.
>
> Any suggestions?
>
>
> from grass.pygrass.vector import VectorTopo
> from grass.pygrass.raster import RasterRow
> from grass.pygrass.modules.shortcuts import raster as r
> from grass.pygrass.gis.region import Region
> from grass.pygrass.utils import get_raster_for_points
>
> reg = Region()
> reg.from_rast("landclass96")
> reg.write()
> reg.set_raster_region()
>
> r.random(input="landclass96", npoints=200000, vector="landclass96_roi",
>           overwrite=True)
>
> points = VectorTopo("landclass96_roi")
> points.open("r")
>
> # repeat spatial query of raster
> for i in range(50):
>      with RasterRow("lsat5_1987_10") as src:
>          arr = get_raster_for_points(points, src)

Hope someone here can support you!

Markus
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