FinDer Mask#
Principle#
FinDer interpolates the recorded acceleration amplitudes in the area of interest before applying the template matching algorithm for estimating the source parameters.
The area of interest for FinDer is restricted via a custom mask: the mask enabled region is constructed as the union of the disks of radius
MASK_STATION_DISTANCE
centered on every enabled stations. In other words, any interpolated point that is located more than MASK_STATION_DISTANCE
away
from every enabled station is not considered for FinDer source estimation.
The setup of the FinDer Mask requires:
defining a white list and/or black list of the stations to use or discard with finder
running scfinder once with the mask creation switch activated
setting the path to the generated mask in the finder configuration file
Warning
The following steps will only work if you use a recent version of the finder docker image (downloaded after July 28 2025). Make sure to update you finder image as needed.
Setup#
Log into the docker container to access the configuration files:
docker exec -u sysop -w /home/sysop/.seiscomp -it finder bash
- Select the stations to enable or disable in
scfinder.cfg
(all the inventory is enabled by default): Use vim to set or edit the streams.whitelist and streams.blacklist parameters.
- Select the stations to enable or disable in
- (Optional) Change the default
MASK_STATION_DISTANCE
parameter: This parameter is defined in the
finder.config
file (default to 75.0 km) and will be used to generate the mask. You can adapt it according to your network density.
- (Optional) Change the default
Generate the Mask by runing scfinder with the
--calculate-mask
option and the path to the output file:scfinder --calculate-mask ./finder_mask.nc --debug --offline
- Add the path to the new mask file in the
finder.config
configuration file: Set the
REGIONAL_MASK
parameter to:REGIONAL_MASK /home/sysop/.seiscomp/finder_mask.nc
- Add the path to the new mask file in the
Visualization#
Extract the grid boundaries from the mask file into variables (requires GMT):
# You may need to adjust the commands depending on the GMT version read minlon maxlon < <(gmt grdinfo finder_mask.nc | awk '/x_min:/ {print $3, $5}') read minlat maxlat < <(gmt grdinfo finder_mask.nc | awk '/y_min:/ {print $3, $5}')
Create a postscript image:
gmt psbasemap -Bpxa5f5 -Bpya5f5 -JM5.5i -R${minlon}/${maxlon}/${minlat}/${maxlat} -X2 -Y6 -P -K -V > mask.ps gmt grdimage finder_mask.nc -JM5.5i -R${minlon}/${maxlon}/${minlat}/${maxlat} -n+c -V -K -P -O -Q >> mask.ps gmt pscoast -JM5.5i -R${minlon}/${maxlon}/${minlat}/${maxlat} -W0.75p -Df -A10 -Na/0.75p -P -O -V >> mask.ps
Copy the postscript file to the host for visualization:
# From a terminal on host docker cp finder:/home/sysop/.seiscomp/mask.ps ./
Convert to pdf if needed (requires ghostscript):
gs -sDEVICE=pdfwrite -dNOPAUSE -dBATCH -sOutputFile=mask.pdf mask.ps