Re: v.surf.bspline

Hi Paulo,

On Sun, Oct 4, 2020 at 3:46 PM Paulo van Breugel <[email protected]> wrote:
>
> Hi devs,
>
> I am running a v.surf.bspline (grass 7.8.3 on Windows) using the bilinear and de bicubic algorithm, like e.g. (NC dataset)
>
> g.region raster=elev_lid792_1m
> r.random input=elev_lid792_1m npoints=200 vector=samplepoints seed=20
> v.surf.bspline input=samplepoints column=value raster_output=bspline_bilinear ew_step=50 ns_step=50

 --> raster_output=bspline_bilinear   - ok

> v.surf.bspline input=samplepoints column=value raster_output=bspline_bilinear ew_step=50 ns_step=50 method=bicubic

 --> raster_output=bspline_bilinear   - a copy-paste error in this email?

> Results are exactly the same. Any idea if I am missing something here?

I tried myself:

g.region raster=elev_lid792_1m
r.random input=elev_lid792_1m npoints=200 vector=samplepoints seed=20

# verify the sample point values
v.univar samplepoints column=value
 100%
number of features with non NULL attribute: 200
number of missing attributes: 0
number of NULL attributes: 0
minimum: 104.283
maximum: 131.352
range: 27.0692
sum: 24232.3
mean: 121.162
mean of absolute values: 121.162
population standard deviation: 6.16656
population variance: 38.0265
population coefficient of variation: 0.0508953
sample standard deviation: 6.18204
sample variance: 38.2176
kurtosis: -0.548097
skewness: -0.362208

# now interpolate and check what's being used
g.gisenv set="DEBUG=1"
v.surf.bspline input=samplepoints column=value
raster_output=bspline_bilinear1 ew_step=50 ns_step=50 method=bilinear
...
D1/1: Interpolation: (1,1): Bilinear interpolation...
...

v.surf.bspline input=samplepoints column=value
raster_output=bspline_bicubic1 ew_step=50 ns_step=50 method=bicubic
...
D1/1: Interpolation: (1,1): Bicubic interpolation...
...

g.gisenv set="DEBUG=0"
# calculate differences
r.mapcalc "diff = bspline_bilinear - bspline_bicubic"

# verify differences
r.univar diff -eg
n=525000
null_cells=0
cells=525000
min=-1.35428900518949
max=1.47700431246362
range=2.83129331765311
mean=0.0372330733156362
mean_of_abs=0.189272111683445
stddev=0.24882465890669
variance=0.0619137108800304
coeff_var=668.289337270996
sum=19547.363490709
first_quartile=-0.108568
median=0.0209677
third_quartile=0.181387
percentile_90=0.352807

Looks fine to me.

Markus
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