WaveformGeneratorDrift#
- class capymoa.stream.generator.WaveformGeneratorDrift[source]#
Bases:
MOAStream
An Waveform Generator Drift
>>> from capymoa.stream.generator import WaveformGeneratorDrift ... >>> stream = WaveformGeneratorDrift() >>> stream.next_instance() LabeledInstance( Schema(generators.WaveformGeneratorDrift -d 10), x=[3.787 3.658 5.136 ... 5.723 2.665 2.681], y_index=1, y_label='class2' ) >>> stream.next_instance().x array([ 0.54985074, 2.17089406, 0.6142235 , 3.18809944, -1.81293483, -0.11717947, -1.77198821, -0.14927903, -0.49779111, -1.33272998, -0.38139892, -1.49682927, 1.49204371, 2.65344343, 4.25116434, 3.39751393, 2.90259886, 4.21403878, 1.98411715, 3.33956917, 4.08153654])
- __init__(
- instance_random_seed: int = 1,
- noise: bool = False,
- number_of_attributes_with_drift: int = 10,
Construct a WaveformGeneratorDrift Generator .
- Parameters:
instance_random_seed – Seed for random generation of instances, defaults to 1
noise – Adds noise for a total of 40 attributes
number_of_attributes_with_drift – Number of attributes with drift
- __iter__() Iterator[_AnyInstance] [source]#
Get an iterator over the stream.
This will NOT restart the stream if it has already been iterated over. Please use the
restart()
method to restart the stream.- Yield:
An iterator over the stream.
- __next__() _AnyInstance [source]#
Get the next instance in the stream.
- Returns:
The next instance in the stream.