Mondaic
This tutorial is presented as Python code running inside a Jupyter Notebook, the recommended way to use Salvus. To run it yourself you can copy/type each individual cell or directly download the full notebook, including all required files.
Salvus contains a powerful set of tools that enable users to output simulated
dynamic quantities, such as velocity, displacement, or strain, within volumes
and along surfaces. These outputs are, in general, saved on unstructured
meshes, making them somewhat awkward to work with using standard tools such as
numpy or xarray. To remedy this, Salvus contains a lightweight
WavefieldOutput class that enables the simple extraction of stored
quantities to regular grids. Let's dive in and take a look.import os
import numpy as np
import salvus.namespace as sn
from salvus.mesh import layered_meshing as lm
from salvus.toolbox.helpers import wavefield_output
SALVUS_FLOW_SITE_NAME = os.environ.get("SITE_NAME", "local")We'll demonstrate the basic concepts with a 2-D isotropic elastic mesh created
using Salvus'
layered_meshing API. The use of this API, however, is not
required to use the functionality presented herein, and any volumetric
simulation output from a Salvus simulation will suffice.material = lm.material.elastic.Velocity.from_params(
rho=1.0, vp=1.0, vs=np.sqrt(1 / 3)
)
mesh_2d = lm.mesh_from_domain(
sn.domain.dim2.BoxDomain(x0=0, x1=1, y0=0, y1=1),
material,
sn.MeshResolution(reference_frequency=10.0, elements_per_wavelength=2.0),
)
mesh_2d
<salvus.mesh.unstructured_mesh.UnstructuredMesh at 0x7fd60af85e10>
We'll then create a source at the top of the domain ...
stf = sn.simple_config.stf.Ricker(center_frequency=2.5)
src_2d = sn.simple_config.source.cartesian.VectorPoint2D(
x=0.5, y=1.0, fx=0.0, fy=-1.0, source_time_function=stf
)... and set up a simple simulation.
w_2d = sn.simple_config.simulation.Waveform(
mesh=mesh_2d, sources=src_2d, end_time_in_seconds=2.0
)
w_2d