r.stats.quantile should work:
https://grass.osgeo.org/grass72/manuals/r.stats.quantile.html
On Jan 26, 2018 4:44 PM, "Stefan Blumentrath"
wrote:
> Hi Nikos,
>
> Did you consider using r.univar (with a zones map, like v.rast.stats does:
>
Hi,
today I have uploaded a new toolset for downloading and importing
Sentinel products, namely two modules:
r.sentinel.download [1] and r.sentinel.import [2].
The first module requires Sentinelsat and Pandas library, the second
GDAL with OpenJPEG.
Testing and feedback welcome! Enjoy, Ma
[1]
Hi Nikos,
Did you consider using r.univar (with a zones map, like v.rast.stats does:
https://trac.osgeo.org/grass/browser/grass/branches/releasebranch_7_2/scripts/v.rast.stats/v.rast.stats.py#L238,
just with colon as separator) and using the resulting table as input to
r.recode
On Fri, 26 Jan 2018, Nikos Alexandris wrote:
As for the last comment: do you mean it's going to be computationally
"difficult", as in running time?
Nikos,
No, not running time. It was long ago when GRASS was still limited to
interger numbers, and I used postgres for attribute data storage.
On Fri, 26 Jan 2018, Nikos Alexandris wrote:
how can we compute the median of a floating point cover raster map, over a
base map (using the conventional terminology as in r.stats.zonal)?
Nikos,
By definition the median value has as many observations/measurements less
than this value as
Dear statistics experts,
how can we compute the median of a floating point cover raster map, over
a base map (using the conventional terminology as in r.stats.zonal)?
It appears that there is no module to get the median out of floating
point raster maps, using a base map as in r.stats.zonal or