unreal.PCGClusterSettings¶
- class unreal.PCGClusterSettings(outer: Object | None = None, name: Name | str = 'None')¶
Bases:
PCGSettingsGiven a desired number of clusters (categories), find the best fit cluster for each point by distance, using one of various clustering algorithms.
C++ Source:
Plugin: PCG
Module: PCG
File: PCGClusterElement.h
Editor Properties: (see get_editor_property/set_editor_property)
algorithm(PCGClusterAlgorithm): [Read-Write] Mathematical algorithm for selecting clusters.break_debugger(bool): [Read-Write] If a debugger is attached, triggers a breakpoint inside IPCGElement::Execute(). Editor only. Transient.category(Text): [Read-Write]cluster_attribute(Name): [Read-Write] Cluster IDs will be written to this attribute on the output.debug(bool): [Read-Write]debug_buffer_size(int32): [Read-Write] Size (in number of floats) of the shader debug print buffer.debug_settings(PCGDebugVisualizationSettings): [Read-Write]description(Text): [Read-Write]determinism_settings(PCGDeterminismSettings): [Read-Write]dump_cooked_hlsl(bool): [Read-Write] Dump the cooked HLSL into the log after it is generated.dump_data_descriptions(bool): [Read-Write] Dump the data descriptions of input/output pins to the log.enabled(bool): [Read-Write]execute_on_gpu(bool): [Read-Write] Whether this node should be executed on the GPU.expose_to_library(bool): [Read-Write]max_iterations(int32): [Read-Write] A limit on the number of iterations to run on each algorithm, if it doesn’t otherwise converge. A higher number can offer more accuracy at the cost of processing time.num_clusters(int32): [Read-Write] Number of clusters (segments) to group the points into. Each point will be assigned a cluster at the end.output_final_centroids(bool): [Read-Write] Output the final location of the centroids or gaussians.print_shader_debug_values(bool): [Read-Write] Enable use of ‘WriteDebugValue(uint Index, float Value)’ function in your kernel. Allows you to write float values to a buffer for logging on the CPU.seed(int32): [Read-Write]tolerance(double): [Read-Write] For EM, the maximum allowed difference between the last two iterations’ “Log Likelihood”–which converges from positive infinity to 0 in relation to point-to-cluster probabilities. It is exponential, so raising this number can offer faster iteration if exact precision isn’t needed.use_seed(bool): [Read-Write] deprecated: Implement the PCGSettings virtual UseSeed() override.
- property algorithm: PCGClusterAlgorithm¶
[Read-Write] Mathematical algorithm for selecting clusters.
- Type:
- property cluster_attribute: Name¶
[Read-Write] Cluster IDs will be written to this attribute on the output.
- Type:
(Name)
- property max_iterations: int¶
[Read-Write] A limit on the number of iterations to run on each algorithm, if it doesn’t otherwise converge. A higher number can offer more accuracy at the cost of processing time.
- Type:
(int32)
- property num_clusters: int¶
[Read-Write] Number of clusters (segments) to group the points into. Each point will be assigned a cluster at the end.
- Type:
(int32)
- property output_final_centroids: bool¶
[Read-Write] Output the final location of the centroids or gaussians.
- Type:
(bool)
- property tolerance: float¶
[Read-Write] For EM, the maximum allowed difference between the last two iterations’ “Log Likelihood”–which converges from positive infinity to 0 in relation to point-to-cluster probabilities. It is exponential, so raising this number can offer faster iteration if exact precision isn’t needed.
- Type:
(double)