Moving 3D Random Point Clouds

Ver. 1.0.5 (2023-05-21)

This module provides the native stream class StreamMLProStaticClouds3D. This stream provides self.C_NUM_INSTANCES instances per cluster with 3-dimensional random feature data placed around centers (can be defined by user) which move over time.

class mlpro.bf.streams.streams.clouds3d_dynamic.StreamMLProDynamicClouds3D(p_pattern: str = 'random', p_no_clouds: int = 8, p_variance: float = 5.0, p_velocity: float = 0.1, p_logging=True, **p_kwargs)

Bases: StreamMLProBase

This demo stream provides self.C_NUM_INSTANCES 3-dimensional instances per cluster randomly positioned around centers which move over time.

p_patternstr

Pattern for cloud movements. Possible values are ‘random’, ‘random chain’, ‘static’, ‘merge’. Default = ‘random’.

p_no_cloudsint

Number of clouds. Default = 4.

p_variancefloat

Variance of points around the cloud centeres. Default = 5.0.

p_velocityfloat

Velocity factor for the centers. Default = 0.1.

p_logging

Log level (see constants of class Log). Default: Log.C_LOG_ALL.

C_ID = 'DynamicClouds3D'

C_NAME = 'Dynamic Clouds 3D'

C_TYPE = 'Demo'

C_VERSION = '1.0.0'

C_NUM_INST_PER_CLOUD = 250

C_SCIREF_ABSTRACT = 'Demo stream provides self.C_NUM_INSTANCES 3-dimensional instances per cluster randomly positioned around centers which move over time.'

C_BOUNDARIES = [-60, 60]

C_PATTERN = ['random', 'random chain', 'static', 'merge']

C_NUM_INSTANCES = 0

_setup_feature_space() → MSpace

Custom method to set up the feature space of the stream. It is called by method get_feature_space().

Returns:

feature_space – Feature space of the stream.

Return type:

MSpace

_init_dataset()

Custom method to generate stream data as a numpy array named self._dataset.