x
, y
(, z
) coordinates and thus everything has to be specified in this reference system. For simple domains this is no problem, but for complicated, unstructured domains using higher order shape functions for the individual elements this poses a significant challenge.simple_config
interface.# This line helps with tab-completion of the simple_config objects.
# The IPython/Jupyter project default to a differnet inference based
# tab completion engine which unfortunately does not yet fully work
# with SalvusFlow. This is completely optional and a convenience
# option.
%config Completer.use_jedi = False
import os
from salvus.flow import simple_config
SALVUS_FLOW_SITE_NAME = os.environ.get("SITE_NAME", "local")
simple_config.receiver.cartesian.Point2D
simple_config.receiver.cartesian.Point3D
simple_config
, it is not possible to initialize invalid objects.rec = simple_config.receiver.cartesian.Point2D(
# Cartesian coordinates.
x=2000.0,
y=2000.0,
# The network is optional but helps to group receivers.
network_code="XX",
# The name of the receiver.
station_code="A1",
# An additional level to group receivers.
location_code="",
# At least one output field is required. More are possible.
# Have a look at the API documentation for a list of all
# available fields.
fields=["displacement", "acceleration"],
)
# They are internally represented as dictionaries exactly
# corresponding to what SalvusCompute demands.
print(rec)
{'fields': ['displacement', 'acceleration'], 'location': [2000.0, 2000.0], 'location_code': '', 'network_code': 'XX', 'station_code': 'A1'}
simple_config.source.cartesian.ScalarPoint2D
simple_config.source.cartesian.ScalarPoint3D
simple_config.source.cartesian.ScalarGradientPoint2D
simple_config.source.cartesian.ScalarGradientPoint3D
simple_config.source.cartesian.VectorPoint2D
simple_config.source.cartesian.VectorPoint3D
simple_config.source.cartesian.MomentTensorPoint2D
simple_config.source.cartesian.MomentTensorPoint3D
src = simple_config.source.cartesian.VectorPoint2D(
# Coordinates of the source.
x=500.0,
y=1000.0,
# Force vector in x and y direction in Nm.
fx=1e5,
fy=-1e4,
# It also requires a source time function.
source_time_function=simple_config.stf.Ricker(center_frequency=1.0),
)
# They are again internally represented as a dictionary.
print(src)
{'location': [500.0, 1000.0], 'source_time_function': {'center_frequency': 1.0, 'wavelet': 'ricker'}, 'spatial_type': 'vector', 'spatial_weights': [100000.0, -10000.0]}
SalvusCompute
as of now supports 4 parameterized source time functions as well as a custom source time function. A source object cannot be initialized without one.simple_config.stf.Delta
simple_config.stf.GaussianRate
simple_config.stf.Heaviside
simple_config.stf.Ricker
simple_config.stf.Custom
from salvus.mesh import simple_mesh
m = simple_mesh.CartesianHomogeneousIsotropicElastic2D(
vp=2000.0,
vs=1500.0,
rho=2000.0,
x_max=3000.0,
y_max=2000.0,
max_frequency=2.0,
)
w = simple_config.simulation.Waveform(mesh=m.create_mesh())
w.add_receivers(rec)
w.add_sources(src)
w
<salvus.flow.simple_config.simulation.waveform.Waveform object at 0x7e789623e990>
import salvus.flow.api
salvus.flow.api.run(
site_name=SALVUS_FLOW_SITE_NAME, input_file=w, output_folder="output"
)
SalvusJob `job_2411062226545697_b0bdf1ce6f` running on `local` with 4 rank(s). Site information: * Salvus version: 2024.1.2 * Floating point size: 32 -> Current Task: Time loop complete* Downloaded 17.9 KB of results to `output`. * Total run time: 0.74 seconds. * Pure simulation time: 0.41 seconds.
<salvus.flow.executors.salvus_job.SalvusJob at 0x7e787df38f90>