pattern for aggregate functions from
r.mapcalc…
Cheers
Stefan
From: grass-user On Behalf Of Veronica
Andreo
Sent: torsdag 28. januar 2021 16:43
To: Nikos Alexandris
Cc: grass-user @lists.osgeo.org
Subject: Re: [GRASS-user] Median filtering time series in time only
El jue, 28 ene 2021 a las 0
El jue, 28 ene 2021 a las 0:05, escribió:
> On 2021-01-27 16:59, Veronica Andreo wrote:
>
> Both r.series and t.rast.series will estimate the median per pixel in time
> (either for the whole series or the time period you want). Would it be
> possible then with so e sort of special for cycle?
>
>
On 2021-01-27 16:59, Veronica Andreo wrote:
Both r.series and t.rast.series will estimate the median per pixel in time
(either for the whole series or the time period you want). Would it be possible
then with so e sort of special for cycle?
Sorry, I didn't pay attention. Reading more
An example:
In [1]: from scipy.signal import medfilt
In [4]: ts = [1, 2, 2, 6, 3, 3, 4, 4, 3, 2, 2, 1]
In [5]: medfilt(ts, kernel_size=3)
Out[5]: array([1., 2., 2., 3., 3., 3., 4., 4., 3., 2., 2., 1.])___
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Yes, I have tried `r.series.fiter` with winsize=3 and winsize=9 for a
year of MODIS products.
It seems it works. But I want to ensure I am not filtering in space
too.-
Vero, it feels nice to read you understand what I am trying to describe.
As usual there is an excuse/justification: workload
El mié., 27 ene. 2021 11:33, escribió:
> Thank you Vero.
>
> Consider the following time series [1, 2, 2, 6, 3, 3, 4, 4, 3, 2, 2, 1] <-
> evolution of a pixel in time.
>
> Say this is always the same pixel indexed at [0, 0] in each of 12 raster
> maps registered in a GRASS GIS STRDS.
>
> Median
Thank you Vero.
Consider the following time series [1, 2, 2, 6, 3, 3, 4, 4, 3, 2, 2, 1]
<- evolution of a pixel in time.
Say this is always the same pixel indexed at [0, 0] in each of 12 raster
maps registered in a GRASS GIS STRDS.
Median filtering pixel-wise in time, only, with a
What exactly do you mean by median-filtering in time only, Nikos? Get the
median and then filtering out all pixels above/below that value? If that's
the case, then maybe some of the examples here
https://grasswiki.osgeo.org/wiki/Temporal_data_processing#Spatio-temporal_algebra_with_STRDS
might be
I am trying to median-filter time series in time and not in space.
Not sure `r.series.filter` is the right tool.
I skimmed through the manual, the paper and the source code. Yet I am
asking for a confirmation.
Its (odd integer) parameter `winsize=` implies a moving window (of size
winsize^2).
