Streamlines computation specific helpers.
- class ansys.dpf.core.helpers.streamlines.Streamlines(data)#
Class to define the Streamlines object scripting with ansys-dpf-core.
- class ansys.dpf.core.helpers.streamlines.StreamlinesSource(data)#
Class to define the StreamlinesSource object scripting with ansys-dpf-core.
- ansys.dpf.core.helpers.streamlines.compute_streamlines(meshed_region, field, **kwargs)#
Compute the streamlines for a given mesh and velocity field.
- Parameters:
meshed_region (MeshedRegion) – MeshedRegion the streamline will be computed on.
field (Field) – Field containing raw vector data the streamline is computed from. The data location must be nodal, velocity values must be defined at nodes.
**kwargs (optional) – Additional keyword arguments for the streamline computation. More information is available at
pyvista.DataSetFilters.streamlines()
.
- Returns:
streamlines
- Return type:
Examples
>>> from ansys.dpf import core as dpf >>> from ansys.dpf.core import examples >>> from ansys.dpf.core.helpers.streamlines import compute_streamlines >>> # Get model and meshed region >>> files = examples.download_fluent_mixing_elbow_steady_state() >>> ds = dpf.DataSources() >>> ds.set_result_file_path(files["cas"][0], "cas") >>> ds.add_file_path(files["dat"][1], "dat") >>> model = dpf.Model(ds) >>> mesh = model.metadata.meshed_region >>> # Get velocity data >>> velocity_op = model.results.velocity() >>> fc = velocity_op.outputs.fields_container() >>> op = dpf.operators.averaging.to_nodal_fc(fields_container=fc) >>> field = op.outputs.fields_container()[0] >>> # compute streamline >>> streamline_obj = compute_streamlines( ... meshed_region=mesh, ... field=field, ... source_center=(0.55, 0.55, 0.), ... n_points=10, ... source_radius=0.08, ... max_time=10.0 ... )