This documentation is not for the latest stable Salvus version.
SimulationConfigurationobject, and investigate how high-order accurate topography / material interpolation can be used to improve simulation performance. To accomplish this, we'll focus on a real-life use case using the area around Mt. St. Helens in Washington state as an example. Of course please feel free to adapt the geographical area.
%matplotlib inline import os import pathlib import salvus.namespace as sn
--> Server: 'https://data.mondaic.com/license_server/licensing_server', User: '_MONDAIC_INTERNAL_', Group: '_MONDAIC_INTERNAL_'. --> Negotiating 1 license instance(s) for 'SalvusMesh' [license version 1.0.0] for 1 seconds ... --> Success! [Total duration: 1.07 seconds]
# This notebook will use this variable to determine which # remote site to run on. SALVUS_FLOW_SITE_NAME = os.environ.get("SITE_NAME", "local") PROJECT_DIR = "project"
UtmDomain.from_spherical_chunkconstructor that takes WGS84 coordinates and converts them to an appropriate UTM domain. The UTM zone and coordinates could of course also be specified directly.
d = sn.domain.dim3.UtmDomain.from_spherical_chunk( min_latitude=46.15, max_latitude=46.30, min_longitude=-122.28, max_longitude=-122.12, ) # Have a look at the domain to make sure it is correct. d.plot()