Module containing the helpers for streamlines.

Streamlines

ansys.dpf.post.helpers.streamlines.plot_streamlines(dataframe: DataFrame, sources: List[dict], set_id: int = 1, streamline_thickness: float | List[float] = 0.01, plot_mesh: bool = True, mesh_opacity: float = 0.3, plot_contour: bool = True, contour_opacity: float = 0.3, **kwargs)

Plot streamlines based on a vector field DataFrame.

Parameters:

• dataframe (DataFrame) – A post.DataFrame object containing a vector field. If present, merges the DataFrame across its zone label before plotting.

• sources (List[dict]) – A list of dictionaries defining spherical point sources for the streamlines. Expected keywords are “center”, “radius”, “max_time” and “n_points”. Keyword “max_time” is for the maximum integration pseudo-time for the streamline computation algorithm, which defines the final length of the lines. More information is available at pyvista.DataSetFilters.streamlines().

• set_id (int, default: 1) – ID of the set (time-step) for which to compute streamlines if the DataFrame object contains temporal data.

• streamline_thickness (Union[float, List[float]], default: 0.01) – Thickness of the streamlines plotted. Use a list to specify a value for each source.

• plot_contour (bool, default: True) – Whether to plot the field’s norm contour along with the streamlines.

• contour_opacity (float, default: 0.3) – Opacity to use for the field contour in case “plot_contour=True”.

• plot_mesh (bool, default: True) – Whether to plot the mesh along the streamlines in case “plot_contour=False”.

• mesh_opacity (float, default: 0.3) – Opacity to use for the mesh in case “plot_contour=False” and “plot_mesh=True”.

• **kwargs –