generate_distribution#
- generate_distribution(domain, population=None, include_boundaries=None, exclude_boundaries=None, boundary_exclude_distance=0, kernel_radius=150, kernel_sigma=50, mesh_step=10, kernel_function=None, add_contribution_as_labels=False, contribution_label_name='Distribution values', visualise_output=False, visualise_heatmap_kwargs={})#
Generate a spatial distribution heatmap for a given domain.
- Parameters:
- domainDomain
A muspan domain object.
- populationquery-like
A population of objects or a query to select them.
- include_boundariesarray-like, query-like, or None, optional
Boundaries to include in the analysis. Defaults to None.
- exclude_boundariesarray-like, query-like, or None, optional
Boundaries to exclude from the analysis. Defaults to None.
- boundary_exclude_distancefloat, optional
Distance from the boundary to exclude objects, by default 0.
- kernel_radiusfloat, optional
Radius of the kernel, by default 150.
- kernel_sigmafloat, optional
Standard deviation of the default Gaussian kernel, by default 50. This will be used if kernel_function is None.
- mesh_stepfloat, optional
Step size for the mesh grid, by default 10.
- kernel_functioncallable, optional
Custom kernel function. If None, a Gaussian kernel is used.
- add_contribution_as_labelsbool, optional
Whether to add contributions as labels to the domain objects, by default False.
- contribution_label_namestr, optional
Name of the contribution label, by default ‘Distribution values’.
- visualise_outputbool, optional
Whether to visualize the output heatmap, by default False.
- visualise_heatmap_kwargsdict, optional
Additional keyword arguments for the visualization function.
- Returns:
- heatmapndarray
The generated heatmap as a 2D numpy array.
- Raises:
- ValueError
If kernel_radius is less than mesh_step. If kernel_function is not None or a callable.