unreal.LearningAgentsObservations
¶
- class unreal.LearningAgentsObservations(outer: Object | None = None, name: Name | str = 'None')¶
Bases:
BlueprintFunctionLibrary
Learning Agents Observations
C++ Source:
Plugin: LearningAgents
Module: LearningAgents
File: LearningAgentsObservations.h
- classmethod find_enum_by_name(name) Enum ¶
Find an Enum type by Name. This can be used to find Enum types defined in C++. This call can be expensive so the result should be cached.
- classmethod get_angle_observation(object, element, relative_angle=0.000000, tag='AngleObservation') float or None ¶
Get Angle Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_angle (float) –
tag (Name) –
- Returns:
out_angle (float):
- Return type:
float or None
- classmethod get_angle_observation_radians(object, element, relative_angle=0.000000, tag='AngleObservation') float or None ¶
Get Angle Observation Radians
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_angle (float) –
tag (Name) –
- Returns:
out_angle (float):
- Return type:
float or None
- classmethod get_array_observation(object, element, max_num, tag='ArrayObservation') Array[LearningAgentsObservationObjectElement] or None ¶
Get Array Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
max_num (int32) –
tag (Name) –
- Returns:
out_elements (Array[LearningAgentsObservationObjectElement]):
- Return type:
- classmethod get_array_observation_num(object, element, tag='ArrayObservation') int32 or None ¶
Get Array Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_bitmask_observation(object, element, enum, tag='BitmaskObservation') int32 or None ¶
Get Bitmask Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
enum (Enum) –
tag (Name) –
- Returns:
out_bitmask_value (int32):
- Return type:
int32 or None
- classmethod get_bool_observation(object, element, tag='BoolObservation') bool or None ¶
Get Bool Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_value (bool):
- Return type:
bool or None
- classmethod get_continuous_observation(object, element, tag='ContinuousObservation') Array[float] or None ¶
Get Continuous Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_values (Array[float]):
- Return type:
- classmethod get_continuous_observation_num(object, element, tag='ContinuousObservation') int32 or None ¶
Get Continuous Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_count_observation(object, element, max_num, tag='CountObservation') int32 or None ¶
Get Count Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
max_num (int32) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_direction_along_spline_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], tag='DirectionAlongSplineObservation') Vector or None ¶
Get Direction Along Spline Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
tag (Name) –
- Returns:
out_direction (Vector):
- Return type:
Vector or None
- classmethod get_direction_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], tag='DirectionObservation') Vector or None ¶
Get Direction Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
tag (Name) –
- Returns:
out_direction (Vector):
- Return type:
Vector or None
- classmethod get_either_observation(object, element, tag='EitherObservation') (out_either=LearningAgentsEitherObservation, out_element=LearningAgentsObservationObjectElement) or None ¶
Get Either Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_either (LearningAgentsEitherObservation):
out_element (LearningAgentsObservationObjectElement):
- Return type:
tuple or None
- classmethod get_encoding_observation(object, element, tag='EncodingObservation') LearningAgentsObservationObjectElement or None ¶
Get Encoding Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_element (LearningAgentsObservationObjectElement):
- Return type:
- classmethod get_enum_observation(object, element, enum, tag='EnumObservation') uint8 or None ¶
Get Enum Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
enum (Enum) –
tag (Name) –
- Returns:
out_enum_value (uint8):
- Return type:
uint8 or None
- classmethod get_exclusive_discrete_observation(object, element, tag='ExclusiveDiscreteObservation') int32 or None ¶
Get Exclusive Discrete Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_index (int32):
- Return type:
int32 or None
- classmethod get_exclusive_union_observation(object, element, tag='ExclusiveUnionObservation') (out_element_name=Name, out_element=LearningAgentsObservationObjectElement) or None ¶
Get Exclusive Union Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_element_name (Name):
out_element (LearningAgentsObservationObjectElement):
- Return type:
tuple or None
- classmethod get_float_observation(object, element, float_scale=1.000000, tag='FloatObservation') float or None ¶
Get Float Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
float_scale (float) –
tag (Name) –
- Returns:
out_value (float):
- Return type:
float or None
- classmethod get_inclusive_discrete_observation(object, element, tag='InclusiveDiscreteObservation') Array[int32] or None ¶
Get Inclusive Discrete Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_indices (Array[int32]):
- Return type:
Array[int32] or None
- classmethod get_inclusive_discrete_observation_num(object, element, tag='InclusiveDiscreteObservation') int32 or None ¶
Get Inclusive Discrete Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_inclusive_union_observation(object, element, tag='InclusiveUnionObservation') Map[Name, LearningAgentsObservationObjectElement] or None ¶
Get Inclusive Union Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Map[Name, LearningAgentsObservationObjectElement]):
- Return type:
Map[Name, LearningAgentsObservationObjectElement] or None
- classmethod get_inclusive_union_observation_num(object, element, tag='InclusiveUnionObservation') int32 or None ¶
Get Inclusive Union Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_inclusive_union_observation_to_arrays(object, element, tag='InclusiveUnionObservation') (out_element_names=Array[Name], out_elements=Array[LearningAgentsObservationObjectElement]) or None ¶
Get Inclusive Union Observation to Arrays
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_element_names (Array[Name]):
out_elements (Array[LearningAgentsObservationObjectElement]):
- Return type:
tuple or None
- classmethod get_location_along_spline_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='LocationAlongSplineObservation') Vector or None ¶
Get Spline Observations
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
location_scale (float) –
tag (Name) –
- Returns:
out_location (Vector):
- Return type:
Vector or None
- classmethod get_location_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='LocationObservation') Vector or None ¶
Get Location Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
location_scale (float) –
tag (Name) –
- Returns:
out_location (Vector):
- Return type:
Vector or None
- classmethod get_map_observation(object, element, tag='MapObservation') Map[LearningAgentsObservationObjectElement, LearningAgentsObservationObjectElement] or None ¶
Get Map Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Map[LearningAgentsObservationObjectElement, LearningAgentsObservationObjectElement]):
- Return type:
Map[LearningAgentsObservationObjectElement, LearningAgentsObservationObjectElement] or None
- classmethod get_map_observation_num(object, element, tag='MapObservation') int32 or None ¶
Get Map Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_map_observation_to_arrays(object, element, tag='MapObservation') (out_keys=Array[LearningAgentsObservationObjectElement], out_values=Array[LearningAgentsObservationObjectElement]) or None ¶
Get Map Observation to Arrays
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_keys (Array[LearningAgentsObservationObjectElement]):
out_values (Array[LearningAgentsObservationObjectElement]):
- Return type:
tuple or None
- classmethod get_null_observation(object, element, tag='NullObservation') bool ¶
Get Basic Observations
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Return type:
- classmethod get_optional_observation(object, element, tag='OptionalObservation') (out_option=LearningAgentsOptionalObservation, out_element=LearningAgentsObservationObjectElement) or None ¶
Get Optional Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_option (LearningAgentsOptionalObservation):
out_element (LearningAgentsObservationObjectElement):
- Return type:
tuple or None
- classmethod get_pair_observation(object, element, tag='PairObservation') (out_key=LearningAgentsObservationObjectElement, out_value=LearningAgentsObservationObjectElement) or None ¶
Get Pair Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_key (LearningAgentsObservationObjectElement):
out_value (LearningAgentsObservationObjectElement):
- Return type:
tuple or None
- classmethod get_proportion_along_ray_observation(object, element, tag='ProportionAlongRayObservation') float or None ¶
Get Ray Cast Observations
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_proportion (float):
- Return type:
float or None
- classmethod get_proportion_along_spline_observation(object, element, tag='ProportionAlongSplineObservation') (out_is_closed_loop=bool, out_angle=float, out_propotion=float) or None ¶
Get Proportion Along Spline Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_is_closed_loop (bool):
out_angle (float):
out_propotion (float):
- Return type:
tuple or None
- classmethod get_rotation_observation(object, element, relative_rotation=[0.000000, 0.000000, 0.000000], tag='RotationObservation') Rotator or None ¶
Get Rotation Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_rotation (Rotator) –
tag (Name) –
- Returns:
out_rotation (Rotator):
- Return type:
Rotator or None
- classmethod get_rotation_observation_as_quat(object, element, relative_rotation, tag='RotationObservation') Quat or None ¶
Get Rotation Observation as Quat
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_rotation (Quat) –
tag (Name) –
- Returns:
out_rotation (Quat):
- Return type:
Quat or None
- classmethod get_scale_observation(object, element, relative_scale=[1.000000, 1.000000, 1.000000], tag='ScaleObservation') Vector or None ¶
Get Scale Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_scale (Vector) –
tag (Name) –
- Returns:
out_scale (Vector):
- Return type:
Vector or None
- classmethod get_set_observation(object, element, tag='SetObservation') Set[LearningAgentsObservationObjectElement] or None ¶
Get Set Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Set[LearningAgentsObservationObjectElement]):
- Return type:
- classmethod get_set_observation_num(object, element, tag='SetObservation') int32 or None ¶
Get Set Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_set_observation_to_array(object, element, tag='SetObservation') Array[LearningAgentsObservationObjectElement] or None ¶
Get Set Observation to Array
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Array[LearningAgentsObservationObjectElement]):
- Return type:
- classmethod get_static_array_observation(object, element, tag='StaticArrayObservation') Array[LearningAgentsObservationObjectElement] or None ¶
Get Static Array Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Array[LearningAgentsObservationObjectElement]):
- Return type:
- classmethod get_static_array_observation_num(object, element, tag='StaticArrayObservation') int32 or None ¶
Get Static Array Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_struct_observation(object, element, tag='StructObservation') Map[Name, LearningAgentsObservationObjectElement] or None ¶
Get Struct Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_elements (Map[Name, LearningAgentsObservationObjectElement]):
- Return type:
Map[Name, LearningAgentsObservationObjectElement] or None
- classmethod get_struct_observation_num(object, element, tag='StructObservation') int32 or None ¶
Get Struct Observation Num
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_num (int32):
- Return type:
int32 or None
- classmethod get_struct_observation_to_arrays(object, element, tag='StructObservation') (out_element_names=Array[Name], out_elements=Array[LearningAgentsObservationObjectElement]) or None ¶
Get Struct Observation to Arrays
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
tag (Name) –
- Returns:
out_element_names (Array[Name]):
out_elements (Array[LearningAgentsObservationObjectElement]):
- Return type:
tuple or None
- classmethod get_transform_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='TransformObservation') Transform or None ¶
Get Transform Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
location_scale (float) –
tag (Name) –
- Returns:
out_transform (Transform):
- Return type:
Transform or None
- classmethod get_velocity_observation(object, element, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], velocity_scale=200.000000, tag='VelocityObservation') Vector or None ¶
Get Velocity Observation
- Parameters:
object (LearningAgentsObservationObject) –
element (LearningAgentsObservationObjectElement) –
relative_transform (Transform) –
velocity_scale (float) –
tag (Name) –
- Returns:
out_velocity (Vector):
- Return type:
Vector or None
- classmethod log_observation(object, element) None ¶
Logs an Observation Object Element. Useful for debugging.
- Parameters:
object (LearningAgentsObservationObject) – Observation Object
element (LearningAgentsObservationObjectElement) –
- classmethod make_angle_observation(object, angle, relative_angle=0.000000, tag='AngleObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new angle observation. Angles should be given in degrees.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
angle (float) – The angle of interest to the agent.
relative_angle (float) – The angle the provided angle should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_angle_observation_radians(object, angle, relative_angle=0.000000, tag='AngleObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new angle observation. Angles should be given in radians.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
angle (float) – The angle of interest to the agent.
relative_angle (float) – The angle the provided angle should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_array_observation(object, elements, max_num, tag='ArrayObservation') LearningAgentsObservationObjectElement ¶
Make a new array observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Array[LearningAgentsObservationObjectElement]) – The sub-observations. The number of elements here must be less than or equal to the maximum that was given during Specify.
max_num (int32) – The maximum number of elements possible for this observation. Must match what was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_bitmask_observation(object, enum, bitmask_value, tag='BitmaskObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new bitmask observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
enum (Enum) – The enum type for this observation. Must match what was given during Specify.
bitmask_value (int32) – The bitmask value.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_bool_observation(object, value, tag='BoolObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new bool observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
value (bool) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_continuous_observation(object, values, tag='ContinuousObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new continuous observation. The size of Values must match the Size given during Specify.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_count_observation(object, num, max_num, tag='CountObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new count observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
num (int32) – The number of items. Must be less than or equal to MaxNum.
max_num (int32) – The maximum number of items possible.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_direction_along_spline_observation(object, spline_component, distance_along_spline, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], tag='DirectionAlongSplineObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_arrow_length=100.000000, visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new direction along spline observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
spline_component (SplineComponent) – The spline to observe.
distance_along_spline (float) – The distance along that spline.
relative_transform (Transform) – The transform the provided direction should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_arrow_length (float) – The length of the arrow to display to represent the direction.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_direction_observation(object, direction, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], tag='DirectionObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_direction_location=[0.000000, 0.000000, 0.000000], visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_arrow_length=100.000000, visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new direction observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
direction (Vector) – The direction of interest to the agent.
relative_transform (Transform) – The transform the provided direction should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_direction_location (Vector) – A location for the visual logger to display the direction in the world.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_arrow_length (float) – The length of the arrow to display to represent the direction.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_either_a_observation(object, a, tag='EitherObservation') LearningAgentsObservationObjectElement ¶
Make a new either A observation. Use this to provide option A.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_either_b_observation(object, b, tag='EitherObservation') LearningAgentsObservationObjectElement ¶
Make a new either B observation. Use this to provide option B.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_either_observation(object, element, either, tag='EitherObservation') LearningAgentsObservationObjectElement ¶
Make a new either observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element (LearningAgentsObservationObjectElement) – The sub-observation given.
either (LearningAgentsEitherObservation) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_encoding_observation(object, element, tag='EncodingObservation') LearningAgentsObservationObjectElement ¶
Make a new encoding observation. This must be used in conjunction with SpecifyEncodingObservation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element (LearningAgentsObservationObjectElement) – The Observation Element to be encoded.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_enum_observation(object, enum, enum_value, tag='EnumObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new enum observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
enum (Enum) – The enum type for this observation. Must match what was given during Specify.
enum_value (uint8) – The enum value.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_exclusive_discrete_observation(object, discrete_index, size, tag='ExclusiveDiscreteObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new exclusive discrete observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
discrete_index (int32) – The index of the discrete observation. Values must be smaller than the given Size.
size (int32) – The size of the discrete observation. Must be equal to the size given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_exclusive_union_observation(object, element_name, element, tag='ExclusiveUnionObservation') LearningAgentsObservationObjectElement ¶
Make a new exclusive union observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element_name (Name) – The name of the chosen sub-observation.
element (LearningAgentsObservationObjectElement) – The corresponding chosen sub-observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_float_observation(object, value, float_scale=1.000000, tag='FloatObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new float observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
value (float) – The new value of this observation.
float_scale (float) – Used to normalize the data for this observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_inclusive_discrete_observation(object, discrete_indices, size, tag='InclusiveDiscreteObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new inclusive discrete observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
discrete_indices (Array[int32]) – The indices of the discrete observations. All values must be smaller than the given Size.
size (int32) – The size of the discrete observation. Must be equal to the size given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_inclusive_union_observation(object, elements, tag='InclusiveUnionObservation') LearningAgentsObservationObjectElement ¶
Make a new inclusive union observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Map[Name, LearningAgentsObservationObjectElement]) – The chosen sub-observations.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_inclusive_union_observation_from_arrays(object, element_names, elements, tag='InclusiveUnionObservation') LearningAgentsObservationObjectElement ¶
Make a new inclusive union observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element_names (Array[Name]) – The names of the chosen sub-observations.
elements (Array[LearningAgentsObservationObjectElement]) – The corresponding chosen sub-observations.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_location_along_spline_observation(object, spline_component, distance_along_spline, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='LocationAlongSplineObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new location along spline observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
spline_component (SplineComponent) – The spline to observe.
distance_along_spline (float) – The distance along that spline.
relative_transform (Transform) – The transform the provided location should be encoded relative to.
location_scale (float) – Used to normalize the transform’s location for this observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_location_observation(object, location, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='LocationObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new location observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
location (Vector) – The location of interest to the agent.
relative_transform (Transform) – The transform the provided location should be encoded relative to.
location_scale (float) – Used to normalize the data for this observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_map_observation(object, map, tag='MapObservation') LearningAgentsObservationObjectElement ¶
Make a new map observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
map (Map[LearningAgentsObservationObjectElement, LearningAgentsObservationObjectElement]) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_map_observation_from_arrays(object, keys, values, tag='MapObservation') LearningAgentsObservationObjectElement ¶
Make a new map observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
keys (Array[LearningAgentsObservationObjectElement]) –
values (Array[LearningAgentsObservationObjectElement]) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_null_observation(object, tag='NullObservation') LearningAgentsObservationObjectElement ¶
Make a new null observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_optional_null_observation(object, tag='OptionalObservation') LearningAgentsObservationObjectElement ¶
Make a new null optional observation. Use this to provide a null optional observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_optional_observation(object, element, option, tag='OptionalObservation') LearningAgentsObservationObjectElement ¶
Make a new optional observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element (LearningAgentsObservationObjectElement) – The sub-observation given.
option (LearningAgentsOptionalObservation) – The indicator as to if this is observation should be used.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_optional_valid_observation(object, element, tag='OptionalObservation') LearningAgentsObservationObjectElement ¶
Make a new valid optional observation. Use this to provide a valid optional observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element (LearningAgentsObservationObjectElement) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_pair_observation(object, key, value, tag='PairObservation') LearningAgentsObservationObjectElement ¶
Make a new pair observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
key (LearningAgentsObservationObjectElement) – The key sub-observation.
value (LearningAgentsObservationObjectElement) –
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_proportion_along_ray_observation(object, ray_start, ray_end, ray_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], collision_channel=CollisionChannel.ECC_WORLD_STATIC, tag='ProportionAlongRayObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new proportion along ray observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
ray_start (Vector) – The local ray start location.
ray_end (Vector) – The local ray end location.
ray_transform (Transform) – The transform to use to transform the local ray starts and ends into the world space.
collision_channel (CollisionChannel) – The collision channel to collide against.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_proportion_along_spline_observation(object, spline_component, distance_along_spline, tag='ProportionAlongSplineObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new proportion along spline observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
spline_component (SplineComponent) – The spline to observe.
distance_along_spline (float) – The distance along that spline.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_rotation_observation(object, rotation, relative_rotation=[0.000000, 0.000000, 0.000000], tag='RotationObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_rotation_location=[0.000000, 0.000000, 0.000000], visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new rotation observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
rotation (Rotator) – The rotation of interest to the agent.
relative_rotation (Rotator) – The rotation the provided rotation should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_rotation_location (Vector) – A location for the visual logger to display the rotation in the world.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_rotation_observation_from_quat(object, rotation, relative_rotation, tag='RotationObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_rotation_location=[0.000000, 0.000000, 0.000000], visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new rotation observation from a quaternion.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
rotation (Quat) – The rotation of interest to the agent.
relative_rotation (Quat) – The rotation the provided rotation should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_rotation_location (Vector) – A location for the visual logger to display the rotation in the world.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_scale_observation(object, scale, relative_scale=[1.000000, 1.000000, 1.000000], tag='ScaleObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_scale_location=[0.000000, 0.000000, 0.000000], visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new scale observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
scale (Vector) – The scale of interest to the agent.
relative_scale (Vector) – The scale the provided scale should be encoded relative to.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_scale_location (Vector) – A location for the visual logger to display the scale in the world.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_set_observation(object, elements, tag='SetObservation') LearningAgentsObservationObjectElement ¶
Make a new set observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Set[LearningAgentsObservationObjectElement]) – The sub-observations. The number of elements here must be less than or equal to the maximum that was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_set_observation_from_array(object, elements, tag='SetObservation') LearningAgentsObservationObjectElement ¶
Make a new set observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Array[LearningAgentsObservationObjectElement]) – The sub-observations. The number of elements here must be less than or equal to the maximum that was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_static_array_observation(object, elements, tag='StaticArrayObservation') LearningAgentsObservationObjectElement ¶
Make a new static array observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Array[LearningAgentsObservationObjectElement]) – The sub-observations. The number of elements here must match what was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_struct_observation(object, elements, tag='StructObservation') LearningAgentsObservationObjectElement ¶
Make a new struct observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
elements (Map[Name, LearningAgentsObservationObjectElement]) – The named sub-observations. Must match what was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_struct_observation_from_arrays(object, element_names, elements, tag='StructObservation') LearningAgentsObservationObjectElement ¶
Make a new struct observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
element_names (Array[Name]) – The names of the sub-observations. Must match what was given during Specify.
elements (Array[LearningAgentsObservationObjectElement]) – The corresponding sub-observations. Must match what was given during Specify.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_transform_observation(object, transform, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], location_scale=100.000000, tag='TransformObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new transform observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
transform (Transform) – The transform of interest to the agent.
relative_transform (Transform) – The transform the provided transform should be encoded relative to.
location_scale (float) – Used to normalize the transform’s location for this observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod make_velocity_observation(object, velocity, relative_transform=[[0.000000, 0.000000, 0.000000], [-0.000000, 0.000000, 0.000000], [1.000000, 1.000000, 1.000000]], velocity_scale=200.000000, tag='VelocityObservation', visual_logger_enabled=False, visual_logger_listener=None, visual_logger_agent_id=-1, visual_logger_velocity_location=[0.000000, 0.000000, 0.000000], visual_logger_location=[0.000000, 0.000000, 0.000000], visual_logger_color=[1.000000, 0.000000, 0.000000, 1.000000]) LearningAgentsObservationObjectElement ¶
Make a new velocity observation.
- Parameters:
object (LearningAgentsObservationObject) – The Observation Object
velocity (Vector) – The velocity of interest to the agent.
relative_transform (Transform) – The transform the provided velocity should be encoded relative to.
velocity_scale (float) – Used to normalize the data for this observation.
tag (Name) – The tag of the corresponding observation. Must match the tag given during Specify.
visual_logger_enabled (bool) – When true, debug data will be sent to the visual logger.
visual_logger_listener (LearningAgentsManagerListener) – The listener object which is making this observation. This must be set to use logging.
visual_logger_agent_id (int32) – The agent id associated with this observation.
visual_logger_velocity_location (Vector) – A location for the visual logger to display the velocity in the world.
visual_logger_location (Vector) – A location for the visual logger information in the world.
visual_logger_color (LinearColor) – The color for the visual logger display.
- Returns:
The newly created observation object element.
- Return type:
- classmethod project_transform_onto_ground_plane(transform, local_forward_vector=[1.000000, 0.000000, 0.000000], ground_plane_height=0.000000) Transform ¶
Project a transform onto the ground plane, leaving just rotation around the vertical axis
- classmethod specify_angle_observation(schema, tag='AngleObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new angle observation. This will be encoded as a 2-dimension Cartesian vector so that 0 and 350 are close to each other in the encoded space.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_array_observation(schema, element, max_num, attention_encoding_size=32, attention_head_num=4, value_encoding_size=32, tag='ArrayObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new array observation. This represents an observation made up of an Array of some other observation. This Array can be variable in size (up to some fixed maximum size) and the order of elements is taken into consideration. Internally this observation uses Attention so can be slower to evaluate and more difficult to train than other observation types. For this reason it should be used sparingly.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element (LearningAgentsObservationSchemaElement) – The sub-observation that represents elements of this array.
max_num (int32) – The maximum number of elements that can be included in the array.
attention_encoding_size (int32) – The encoding size used by the attention mechanism.
attention_head_num (int32) – The number of heads used by the attention mechanism.
value_encoding_size (int32) – The output encoding size used by the attention mechanism.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_bitmask_observation(schema, enum, tag='BitmaskObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new bitmask observation. This represents an inclusive choice from elements of the given Enum. To use this with an Enum defined in C++ use the FindEnumByName convenience function.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
enum (Enum) – The enum type to use.
tag (Name) –
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_bool_observation(schema, tag='BoolObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new bool observation. A true or false observation.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_continuous_observation(schema, size, tag='ContinuousObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new continuous observation. This represents an observation made up of several float values.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
size (int32) – The number of float values in the observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_count_observation(schema, tag='CountObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new count observation. This represents a count of something such as the size of, or index into, an array.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_direction_along_spline_observation(schema, tag='DirectionAlongSplineObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new direction along spline observation. This observes the direction of the spline at the given distance along that spline.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_direction_observation(schema, tag='DirectionObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new direction observation. Allows an agent to observe the direction of some entity.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_either_observation(schema, a, b, encoding_size=128, tag='EitherObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new either observation. This represents an observation which will be either sub-observation A or sub-observation B.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
a (LearningAgentsObservationSchemaElement) – The first sub-observation.
encoding_size (int32) – The encoding size used to encode each sub-observation.
tag (Name) –
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_encoding_observation(schema, element, encoding_size=128, hidden_layer_num=1, activation_function=LearningAgentsActivationFunction.ELU, tag='EncodingObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new encoding observation. This represents an observation which will be an encoding of another sub-observation using a small neural network.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element (LearningAgentsObservationSchemaElement) – The sub-observation to be encoded.
encoding_size (int32) – The encoding size used to encode this sub-observation.
hidden_layer_num (int32) – The number of hidden layers used to encode this sub-observation.
activation_function (LearningAgentsActivationFunction) – The activation function used to encode this sub-observation.
tag (Name) –
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_enum_observation(schema, enum, tag='EnumObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new enum observation. This represents an exclusive choice from elements of the given Enum. To use this with an Enum defined in C++ use the FindEnumByName convenience function.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
enum (Enum) – The enum type to use.
tag (Name) –
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_exclusive_discrete_observation(schema, size, tag='ExclusiveDiscreteObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new exclusive discrete observation. This represents a discrete observation which is an exclusive selection from multiple choices.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
size (int32) – The number of discrete options in the observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_exclusive_union_observation(schema, elements, encoding_size=128, tag='ExclusiveUnionObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new exclusive union observation. This represents an observation which is exclusively chosen from a set of named sub-observations. In other words, when this observation is created, you only need to provide one observation from the given sub-observations.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
elements (Map[Name, LearningAgentsObservationSchemaElement]) – The sub-observations that make up this union.
encoding_size (int32) – The encoding size used to encode each sub-observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_exclusive_union_observation_from_arrays(schema, element_names, elements, encoding_size=128, tag='ExclusiveUnionObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new exclusive union observation. This represents an observation which is exclusively chosen from a set of named sub-observations. In other words, when this observation is created, you only need to provide one observation from the given sub-observations.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element_names (Array[Name]) – The names of the sub-observations that make up this union.
elements (Array[LearningAgentsObservationSchemaElement]) – The corresponding sub-observations that make up this union. Must be the same size as ElementNames.
encoding_size (int32) – The encoding size used to encode each sub-observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_float_observation(schema, tag='FloatObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new float observation. A simple observation which can be used as a catch-all for situations where a type-specific observation does not exist.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_inclusive_discrete_observation(schema, size, tag='InclusiveDiscreteObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new inclusive discrete observation. This represents a discrete observation which is an inclusive selection from multiple choices.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
size (int32) – The number of discrete options in the observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_inclusive_union_observation(schema, elements, attention_encoding_size=32, attention_head_num=4, value_encoding_size=32, tag='InclusiveUnionObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new inclusive union observation. This represents an observation which is inclusively chosen from a set of named sub-observations. In other words, when this observation is created, you can provide any combination of observations from the given sub-observations. Internally this observation uses Attention so can be slower to evaluate and more difficult to train than other observation types. For this reason it should be used sparingly.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
elements (Map[Name, LearningAgentsObservationSchemaElement]) – The sub-observations that make up this union.
attention_encoding_size (int32) – The encoding size used by the attention mechanism.
attention_head_num (int32) – The number of heads used by the attention mechanism.
value_encoding_size (int32) – The output encoding size used by the attention mechanism.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_inclusive_union_observation_from_arrays(schema, element_names, elements, attention_encoding_size=32, attention_head_num=4, value_encoding_size=32, tag='InclusiveUnionObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new inclusive union observation. This represents an observation which is inclusively chosen from a set of named sub-observations. In other words, when this observation is created, you can provide any combination of observations from the given sub-observations. Internally this observation uses Attention so can be slower to evaluate and more difficult to train than other observation types. For this reason it should be used sparingly.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element_names (Array[Name]) – The names of the sub-observations that make up this union.
elements (Array[LearningAgentsObservationSchemaElement]) – The corresponding sub-observations that make up this union. Must be the same size as ElementNames.
attention_encoding_size (int32) – The encoding size used by the attention mechanism.
attention_head_num (int32) – The number of heads used by the attention mechanism.
value_encoding_size (int32) – The output encoding size used by the attention mechanism.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_location_along_spline_observation(schema, tag='LocationAlongSplineObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new location along spline observation. This observes the location of the spline at the given distance along that spline.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_location_observation(schema, tag='LocationObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new location observation. Allows an agent to observe the location of some entity.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_map_observation(schema, key_element, value_element, max_num, attention_encoding_size=32, attention_head_num=4, value_encoding_size=32, tag='MapObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new map observation. This represents an observation made up of a Map of some other key and pair observations. This Map can be variable in size (up to some fixed maximum size) and elements are considered unordered. Internally this observation uses Attention so can be slower to evaluate and more difficult to train than other observation types. For this reason it should be used sparingly.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
key_element (LearningAgentsObservationSchemaElement) – The sub-observation that represents keys in this map.
value_element (LearningAgentsObservationSchemaElement) – The sub-observation that represents values in this map.
max_num (int32) – The maximum number of elements that can be included in the map.
attention_encoding_size (int32) – The encoding size used by the attention mechanism.
attention_head_num (int32) – The number of heads used by the attention mechanism.
value_encoding_size (int32) – The output encoding size used by the attention mechanism.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_null_observation(schema, tag='NullObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new null observation. This represents an empty observation and can be useful when an observation is needed which has no value.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_optional_observation(schema, element, encoding_size=128, tag='OptionalObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new optional observation. This represents an observation which may or may not be provided.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element (LearningAgentsObservationSchemaElement) –
encoding_size (int32) – The encoding size used to encode this sub-observation.
tag (Name) –
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_pair_observation(schema, key, value, tag='PairObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new pair observation. This represents an observation made up of two sub-observations.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
key (LearningAgentsObservationSchemaElement) – The first sub-observation.
value (LearningAgentsObservationSchemaElement) – The second sub-observation.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_proportion_along_ray_observation(schema, tag='ProportionAlongRayObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new proportion along ray observation. This observes how far a you can travel along a ray before collision. Rays that can travel the full distance are encoded as zero, while rays that collide instantly are encoded as one.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_proportion_along_spline_observation(schema, tag='ProportionAlongSplineObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new proportion along spline observation. This observes the proportion along a spline at the given distance. For looped splines this will be treated effectively like an angle between 0 and 360 degrees and encoded appropriately so that 0 and 350 are close to each other in the encoded space, while for non-looped splines this will be treated as a value between 0 and 1.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_rotation_observation(schema, tag='RotationObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new rotation observation. Allows an agent to observe the rotation of some entity. Rotations are encoded as two columns of the rotation matrix to ensure there is no discontinuity in the encoding.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_scale_observation(schema, tag='ScaleObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new scale observation. Allows an agent to observe the scale of some entity. Negative scales are not supported by this observation type.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_set_observation(schema, element, max_num, attention_encoding_size=32, attention_head_num=4, value_encoding_size=32, tag='SetObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new set observation. This represents an observation made up of a Set of some other observation. This Set can be variable in size (up to some fixed maximum size) and elements are considered unordered. Internally this observation uses Attention so can be slower to evaluate and more difficult to train than other observation types. For this reason it should be used sparingly.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element (LearningAgentsObservationSchemaElement) – The sub-observation that represents elements of this array.
max_num (int32) – The maximum number of elements that can be included in the set.
attention_encoding_size (int32) – The encoding size used by the attention mechanism.
attention_head_num (int32) – The number of heads used by the attention mechanism.
value_encoding_size (int32) – The output encoding size used by the attention mechanism.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_static_array_observation(schema, element, num, tag='StaticArrayObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new static array observation. This represents an observation made up of a fixed-size array of some other observation.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element (LearningAgentsObservationSchemaElement) – The sub-observation that represents elements of this array.
num (int32) – The number of elements in the fixed size array.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_struct_observation(schema, elements, tag='StructObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new struct observation. This represents a group of named sub-observations.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
elements (Map[Name, LearningAgentsObservationSchemaElement]) – The sub-observations that make up this struct.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_struct_observation_from_arrays(schema, element_names, elements, tag='StructObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new struct observation. This represents a group of named sub-observations.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
element_names (Array[Name]) – The names of the sub-observations that make up this struct.
elements (Array[LearningAgentsObservationSchemaElement]) – The corresponding sub-observations that make up this struct. Must be the same size as ElementNames.
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_transform_observation(schema, tag='TransformObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new transform observation. Allows an agent to observe the transform of some entity.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod specify_velocity_observation(schema, tag='VelocityObservation') LearningAgentsObservationSchemaElement ¶
Specifies a new velocity observation. Allows an agent to observe the velocity of some entity.
- Parameters:
schema (LearningAgentsObservationSchema) – The Observation Schema
tag (Name) – The tag of this new observation. Used during observation object validation and debugging.
- Returns:
The newly created observation schema element.
- Return type:
- classmethod validate_observation_object_matches_schema(schema, schema_element, object, object_element) bool ¶
Validates that the given observation object matches the schema. Will log errors on objects that don’t match.
- Parameters:
schema (LearningAgentsObservationSchema) – Observation Schema
schema_element (LearningAgentsObservationSchemaElement) – Observation Schema Element
object (LearningAgentsObservationObject) – Observation Object
object_element (LearningAgentsObservationObjectElement) – Observation Object Element
- Returns:
true if the object matches the schema
- Return type: