Moving 2D Random Point Clouds
Ver. 1.0.5 (2023-05-21)
This module provides the native stream class StreamMLProStaticClouds2D. This stream provides 250 instances per cluster with 2-dimensional random feature data placed around centers which move over time.
- class mlpro.bf.streams.streams.clouds2d_dynamic.StreamMLProDynamicClouds2D(p_pattern: str = 'random', p_no_clouds: int = 4, p_variance: float = 5.0, p_velocity: float = 0.1, p_logging=True, **p_kwargs)
Bases:
StreamMLProBase
This demo stream provides 250 2-dimensional instances per cluster randomly positioned around centers which move over time.
- Parameters:
p_pattern (str) – Pattern for cloud movements. Possible values are ‘random’, ‘random chain’, ‘static’, ‘merge’. Default = ‘random’.
p_no_clouds (int) – Number of clouds. Default = 4.
p_variance (float) – Variance of points around the cloud centeres. Default = 5.0.
p_velocity (float) – Velocity factor for the centers. Default = 0.1.
p_logging – Log level (see constants of class Log). Default: Log.C_LOG_ALL.
- C_ID = 'DynamicClouds2D'
- C_NAME = 'Dynamic Clouds 2D'
- C_TYPE = 'Demo'
- C_VERSION = '1.0.0'
- C_NUM_INST_PER_CLOUD = 250
- C_SCIREF_ABSTRACT = 'Demo stream provides 250 2-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:
- _init_dataset()
Custom method to generate stream data as a numpy array named self._dataset.