unreal.PCGBlueprintElement

class unreal.PCGBlueprintElement(outer: Object | None = None, name: Name | str = 'None')

Bases: Object

PCGBlueprint Element

C++ Source:

  • Plugin: PCG

  • Module: PCG

  • File: PCGExecuteBlueprint.h

Editor Properties: (see get_editor_property/set_editor_property)

  • can_be_multithreaded (bool): [Read-Write] Controls whether this node execution can be run from a non-game thread. This is not related to the Loop functions provided/implemented in this class, which should always run on any thread.

  • category (Text): [Read-Write]

  • compute_full_data_crc (bool): [Read-Write] In cases where your node is non-cacheable but is likely to yield the same results on subsequent executions, this controls whether we will do a deep & computationally intensive CRC computation (true), which will allow cache usage in downstream nodes in your graph, or, by default (false), a shallow but quick crc computation which will not be cache-friendly.

  • custom_input_pins (Array[PCGPinProperties]): [Read-Write]

  • custom_output_pins (Array[PCGPinProperties]): [Read-Write]

  • dependency_parsing_depth (int32): [Read-Write]

  • description (Text): [Read-Write]

  • enable_preconfigured_settings (bool): [Read-Write]

  • expose_to_library (bool): [Read-Write]

  • has_default_in_pin (bool): [Read-Write]

  • has_default_out_pin (bool): [Read-Write]

  • input_pin_labels (Set[Name]): [Read-Write] deprecated: Property ‘InputPinLabels’ is deprecated.

  • is_cacheable (bool): [Read-Write] Controls whether results can be cached so we can bypass execution if the inputs & settings are the same in a subsequent execution. If you have implemented the IsCacheableOverride function, then this value is ignored. Note that if your node relies on data that is not directly tracked by PCG or creates any kind of artifact (adds components, creates actors, etc.) then it should not be cacheable.

  • only_expose_preconfigured_settings (bool): [Read-Write]

  • output_pin_labels (Set[Name]): [Read-Write]

  • preconfigured_info (Array[PCGPreConfiguredSettingsInfo]): [Read-Write]

apply_preconfigured_settings(preconfigure_info) → None

Apply Preconfigured Settings

Parameters:

preconfigure_info (PCGPreConfiguredSettingsInfo) –

property can_be_multithreaded: bool

[Read-Write] Controls whether this node execution can be run from a non-game thread. This is not related to the Loop functions provided/implemented in this class, which should always run on any thread.

Type:

(bool)

property category: Text

[Read-Write]

Type:

(Text)

property compute_full_data_crc: bool

[Read-Write] In cases where your node is non-cacheable but is likely to yield the same results on subsequent executions, this controls whether we will do a deep & computationally intensive CRC computation (true), which will allow cache usage in downstream nodes in your graph, or, by default (false), a shallow but quick crc computation which will not be cache-friendly.

Type:

(bool)

custom_input_labels() → Set[Name]

Returns the labels of custom input pins only

Return type:

Set[Name]

property custom_input_pins: None

[Read-Write]

Type:

(Array[PCGPinProperties])

custom_output_labels() → Set[Name]

Returns the labels of custom output pins only

Return type:

Set[Name]

property custom_output_pins: None

[Read-Write]

Type:

(Array[PCGPinProperties])

property dependency_parsing_depth: int

[Read-Write]

Type:

(int32)

property description: Text

[Read-Write]

Type:

(Text)

property enable_preconfigured_settings: bool

[Read-Write]

Type:

(bool)

execute(input) → PCGDataCollection

Execute

Parameters:

input (PCGDataCollection) –

Returns:

output (PCGDataCollection):

Return type:

PCGDataCollection

execute_with_context(context, input) -> (context=PCGContext, output=PCGDataCollection)

~End UObject interface

Parameters:
Returns:

context (PCGContext):

output (PCGDataCollection):

Return type:

tuple

property expose_to_library: bool

[Read-Write]

Type:

(bool)

get_context() → PCGContext

Retrieves the execution context - note that this will not be valid outside of the Execute functions

Return type:

PCGContext

get_input_pin_by_label(pin_label) → PCGPinProperties or None

Returns true if there is an input pin with the matching label. If found, will copy the pin properties in OutFoundPin

Parameters:

pin_label (Name) –

Returns:

out_found_pin (PCGPinProperties):

Return type:

PCGPinProperties or None

get_input_pins() → Array[PCGPinProperties]

Get Input Pins

Return type:

Array[PCGPinProperties]

get_output_pin_by_label(pin_label) → PCGPinProperties or None

Returns true if there is an output pin with the matching label. If found, will copy the pin properties in OutFoundPin

Parameters:

pin_label (Name) –

Returns:

out_found_pin (PCGPinProperties):

Return type:

PCGPinProperties or None

get_output_pins() → Array[PCGPinProperties]

Get Output Pins

Return type:

Array[PCGPinProperties]

get_random_stream(context) -> (RandomStream, context=PCGContext)

Creates a random stream from the settings & source component

Parameters:

context (PCGContext) –

Returns:

context (PCGContext):

Return type:

PCGContext

get_seed(context) -> (int32, context=PCGContext)

Gets the seed from the associated settings & source component

Parameters:

context (PCGContext) –

Returns:

context (PCGContext):

Return type:

PCGContext

property has_default_in_pin: bool

[Read-Write]

Type:

(bool)

property has_default_out_pin: bool

[Read-Write]

Type:

(bool)

input_labels() → None

deprecated: ‘input_labels’ was renamed to ‘custom_input_labels’.

property input_pin_labels: None

[Read-Only] deprecated: Property ‘InputPinLabels’ is deprecated.

Type:

(Set[Name])

property is_cacheable: bool

[Read-Write] Controls whether results can be cached so we can bypass execution if the inputs & settings are the same in a subsequent execution. If you have implemented the IsCacheableOverride function, then this value is ignored. Note that if your node relies on data that is not directly tracked by PCG or creates any kind of artifact (adds components, creates actors, etc.) then it should not be cacheable.

Type:

(bool)

is_cacheable_override() → bool

Override for the IsCacheable node property when it depends on the settings in your node

Return type:

bool

iteration_loop(context, num_iterations, optional_a=None, optional_b=None, optional_out_data=None) -> (context=PCGContext, out_data=PCGPointData)

Calls the IterationLoopBody a fixed number of times, optional parameters are used to potentially initialized the Out Data, but otherwise are used to remove the need to have variables

Parameters:
Returns:

context (PCGContext):

out_data (PCGPointData):

Return type:

tuple

iteration_loop_body(context, iteration, a, b, out_metadata) → PCGPoint or None

Iteration Loop Body

Parameters:
Returns:

out_point (PCGPoint):

Return type:

PCGPoint or None

loop_n_times(context: PCGContext, num_iterations: int, optional_a: PCGSpatialData = Ellipsis, optional_b: PCGSpatialData = Ellipsis, optional_out_data: PCGPointData = Ellipsis) → Tuple[PCGContext, PCGPointData]

deprecated: ‘loop_n_times’ was renamed to ‘iteration_loop’.

loop_on_point_pairs(context: PCGContext, outer_data: PCGPointData, inner_data: PCGPointData, optional_out_data: PCGPointData = Ellipsis) → Tuple[PCGContext, PCGPointData]

deprecated: ‘loop_on_point_pairs’ was renamed to ‘nested_loop’.

loop_on_points(context: PCGContext, data: PCGPointData, optional_out_data: PCGPointData = Ellipsis) → Tuple[PCGContext, PCGPointData]

deprecated: ‘loop_on_points’ was renamed to ‘point_loop’.

multi_loop_on_points(context: PCGContext, data: PCGPointData, optional_out_data: PCGPointData = Ellipsis) → Tuple[PCGContext, PCGPointData]

deprecated: ‘multi_loop_on_points’ was renamed to ‘variable_loop’.

multi_point_loop_body(context: PCGContext, data: PCGPointData, point: PCGPoint, out_metadata: PCGMetadata) → None

deprecated: ‘multi_point_loop_body’ was renamed to ‘variable_loop_body’.

nested_loop(context, outer_data, inner_data, optional_out_data=None) -> (context=PCGContext, out_data=PCGPointData)

Calls the NestedLoopBody function on all nested loop pairs (e.g. (o, i) for all o in Outer, i in Inner)

Parameters:
Returns:

context (PCGContext):

out_data (PCGPointData):

Return type:

tuple

nested_loop_body(context, outer_data, inner_data, outer_point, inner_point, out_metadata) → PCGPoint or None

Nested Loop Body

Parameters:
Returns:

out_point (PCGPoint):

Return type:

PCGPoint or None

node_color_override() → LinearColor

Node Color Override

Return type:

LinearColor

node_title_override() → Name

Override for the default node name

Return type:

Name

node_type_override() → PCGSettingsType

Node Type Override

Return type:

PCGSettingsType

property only_expose_preconfigured_settings: bool

[Read-Write]

Type:

(bool)

output_labels() → None

deprecated: ‘output_labels’ was renamed to ‘custom_output_labels’.

property output_pin_labels: None

[Read-Only]

Type:

(Set[Name])

point_loop(context, data, optional_out_data=None) -> (context=PCGContext, out_data=PCGPointData)

Calls the PointLoopBody function on all points

Parameters:
Returns:

context (PCGContext):

out_data (PCGPointData):

Return type:

tuple

point_loop_body(context, data, point, out_metadata) → PCGPoint or None

Point Loop Body

Parameters:
Returns:

out_point (PCGPoint):

Return type:

PCGPoint or None

point_pair_loop_body(context: PCGContext, outer_data: PCGPointData, inner_data: PCGPointData, outer_point: PCGPoint, inner_point: PCGPoint, out_metadata: PCGMetadata) → PCGPoint | None

deprecated: ‘point_pair_loop_body’ was renamed to ‘nested_loop_body’.

property preconfigured_info: None

[Read-Write]

Type:

(Array[PCGPreConfiguredSettingsInfo])

variable_loop(context, data, optional_out_data=None) -> (context=PCGContext, out_data=PCGPointData)

Calls the VariableLoopBody function on all points, each call can return a variable number of points

Parameters:
Returns:

context (PCGContext):

out_data (PCGPointData):

Return type:

tuple

variable_loop_body(context, data, point, out_metadata) → Array[PCGPoint]

Variable Loop Body

Parameters:
Return type:

Array[PCGPoint]