Changelog

with sn.functions.add_new_executor(
    site_name="my_other_site",
    executor_type="local",
    salvus_binary=salvus_binary,
    run_directory=run_directory_2,
    tmp_directory=tmp_directory_2,
    use_cuda_capable_gpus=False,
    default_ranks=1,
    max_ranks=2,
):
    # Site is available here.
    sn.functions.get_site("my_other_site")

from salvus.flow.simple_config.source.srf_file_reader import _read_srf_file
srf_data = _read_srf_file(
    "example.srf",
    plot=True,
)

%load_ext salvus
%salvus_snippets

from salvus.data import external_data_to_hdf5
for event in project.events.list():
  external_data_to_hdf5(
    data=data_per_event,
    receivers=event.receivers,
    receiver_field="displacement",
    output_filename=external_data_path,
  )
  project.waveforms.add_external(
        data_name="observed_data",
        event=event.event_name,
        data_filename=external_data_path,
  )

%load_ext salvus
%salvus_snippets

• New EventData.get_wavefield_output() method parsing outputs to WavefieldOutput objects.
• New EventData.get_associated_salvus_job() method returning a potentially still existing Salvus job for the EventData object.
• New EventData.get_remote_extra_output_filenames() method to get paths of remote output files.
• New EventData.download_extra_outputs() method to download remote wavefield output data.
• New EventData.delete_associated_job_and_data() method to delete potentially still existing remote wavefield data.

w = sn.simple_config.simulation.Waveform(mesh=m)

# If all settings for the same type of boundary condition are the same,
# the side sets will be merged.
w.add_boundary_conditions([
  sn.simple_config.boundary.HomogeneousDirichlet(side_sets=["x0"]),
  sn.simple_config.boundary.HomogeneousDirichlet(side_sets=["x1"])
])

# However, using different settings for a boundary type will raise an error.
w.add_boundary_conditions([
  sn.simple_config.boundary.Absorbing(
    side_sets=["x0"], taper_amplitude=0.0, width_in_meters=0.0
  )
  sn.simple_config.boundary.Absorbing(
    side_sets=["x1"], taper_amplitude=1.0, width_in_meters=1.0
  )
])

[sites.my_site.ssh_settings]
    hostname = "some_host"
    username = "some_user"
    [sites.my_site.ssh_settings.extra_paramiko_connect_arguments.disabled_algorithms]
        pubkeys = ["rsa-sha2-512", "rsa2-sha2-256"]

salvus-cli init-site my_site --verbose

[sites.my_site.site_specific]
    mpirun_template = "/custom/mpirun -machinefile ~/mf -n {RANKS}"

# Construct a forward simulation object.
w_forward = sn.simple_config.simulation.Waveform(
    ..., store_adjoint_checkpoints=True
)

# Construct an adjoint simulation object.
w_adjoint = sn.simple_config.simulation.Waveform(...)
...
# There is a new `PROMISE_FILE:` prefix to tell SalvusFlow that a file does
# not exist yet but it will exist when the simulation is run.
w_adjoint.adjoint.point_source_block = {
    "filename": "PROMISE_FILE:task_2_of_2/input/adjoint_source.h5",
    "groups": ["adjoint_sources"],
}

# Define a Python function that is run between forward and adjoint simulations
# to generate the adjoint sources.
def compute_adjoint_source(
    task_index: int, task_index_folder_map: typing.Dict[int, pathlib.Path]
):
    folder_forward = task_index_folder_map[task_index - 1]
    folder_adjoint = task_index_folder_map[task_index + 1]

    output_folder = folder_forward / "output"

    event = sn.EventData.from_output_folder(output_folder=output_folder)

    event_misfit = sn.EventMisfit(
        synthetic_event=event,
        misfit_function="L2_energy_no_observed_data",
        receiver_field="displacement",
    )

    input_folder_adjoint = folder_adjoint / "input"
    event_misfit.write(input_folder_adjoint / "adjoint_source.h5")


# Launch the task chain. It will serialize the Python function and launches
# everything either locally or in Slurm/other supported systems.
tc = sn.api.run_task_chain_async(
    site_name="local",
    tasks=[w_forward, compute_adjoint_source, w_adjoint],
    ranks=4,
)
# Wait until it finishes.
tc.wait()

[[sites.site_name.site_specific.additional_qsub_arguments]]
      name = "pe"
      value = "mpi {NODES * TASKS_PER_NODE}"

  [[sites.site_name.site_specific.additional_qsub_arguments]]
      name = "l"
      value = "ngpus={int(ceil(RANKS / 12))}"