[GRASS-dev] i.colors.enhance: G_calloc() error in r.quantile with large maps

Markus Metz markus.metz.giswork at gmail.com
Mon May 1 06:27:14 PDT 2017

On Mon, May 1, 2017 at 11:17 AM, Markus Neteler <neteler at osgeo.org> wrote:
> On Sun, Apr 30, 2017 at 10:39 PM, Markus Metz
> <markus.metz.giswork at gmail.com> wrote:
> ...
> > 16+GB of RAM still seems too much to me, unless the histograms of the
> > values are highly skewed. What is the output of r.stats -c for B04_255,
> > B11_255, B8A_255?
> Since this comes from our automated processing chain I could only
> reimport the resulting S2 bands which should not change much.

If NULL values are correctly set, I would assume about 4 GB of RAM needed
by r.quantile.
If there are no NULL cells, I would assume about 14 GB of RAM which is
close to what you observed.

Can you check your processing chain to make sure the nodata value is
correctly set?

Also note that there are about 7 billion NULL cells in B04, but only 1.7
billion NULL cells in B8A and B11.

> I think they are (strongly) skewed: will send the data off-list to you.

The cell count for value 1 is quite high in all three bands. Is this
expected? However, the cell count for value 1 does not explain the high RAM
consumption of 16+ GB.

Markus M
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