Waveform¶
Waveform stream generator.
Generates samples with 21 numeric features and 3 classes, based on a random differentiation of some base waveforms. Supports noise addition, in this case the samples will have 40 features.
Parameters¶
-
seed (int) – defaults to
None
If int,
seed
is used to seed the random number generator; If RandomState instance,seed
is the random number generator; If None, the random number generator is theRandomState
instance used bynp.random
. -
has_noise (bool) – defaults to
False
Adds 19 unrelated features to the stream.
Attributes¶
-
desc
Return the description from the docstring.
Examples¶
>>> from river import synth
>>> dataset = synth.Waveform(seed=42, has_noise=True)
>>> for x, y in dataset.take(5):
... print(list(x.values()), y)
[0.5437, -0.6154, -1.1978, 2.1417, -0.0946, -0.7254, -0.4783, 0.1982, 0.3312, 1.9780, 3.0469, 3.5249, 5.4624, 6.1318, 2.7471, 4.7896, 2.9351, 2.2258, 0.1168, 2.2835, -0.0245, 0.3556, 0.4170, 0.8325, -0.2934, -0.0298, 0.0951, 0.6647, -0.1402, -0.0332, -0.7491, -0.7784, 0.9488, 1.5809, -0.3682, 0.3756, -1.1932, -0.4091, -0.4467, 1.5242] 2
[0.2186, 1.4285, 0.0843, 0.0568, 2.9605, 2.6487, 2.8402, 3.2128, 2.8694, 4.0410, 4.3953, 3.7009, 2.7075, 2.1149, 0.6994, -0.1702, -1.5082, 1.0996, -0.1777, -0.4104, 1.1797, -0.8982, 0.8348, 0.2966, -1.0378, -0.0758, 0.9730, 0.7956, 1.4954, 0.3382, 3.3723, -0.9204, -0.3986, -0.0609, -1.4188, 1.0425, 0.9035, 0.0190, -0.5344, -1.4951] 1
[0.1358, 0.6081, 0.7050, 0.3609, -1.4670, 1.6896, 1.4886, 1.4355, 2.7730, 2.7890, 4.8437, 5.3447, 3.6724, 2.5445, 2.5541, 2.2732, -0.5371, -0.4099, 0.5331, -1.0464, 1.9451, -0.1533, -0.9070, -0.8174, -0.4831, -0.5698, -2.0916, 1.2637, -0.0155, -0.0274, 0.8179, -1.0546, -0.7583, 0.4574, -0.0644, 0.3449, -0.0801, -0.2414, 1.4335, 1.0658] 2
[1.1428, 1.2414, 1.7699, 0.5590, 3.3606, 1.0454, 3.5236, 4.6377, 0.9673, 1.4126, 2.0997, 1.5176, 0.4915, 2.6213, 2.0010, 3.0263, 1.1228, 3.0816, 0.2378, 0.1885, 0.8135, -1.2309, 0.2275, 1.3071, -1.6075, 0.1846, 0.2599, 0.7818, -1.2370, -1.3205, 0.5219, 0.2970, 0.2505, 0.3464, -0.6800, 0.2323, 0.2931, -0.7144, 1.8658, 0.4738] 0
[-0.9747, 1.0114, 1.6071, -0.1479, 1.8605, 1.5341, 2.1677, 3.0181, 0.6517, 0.6948, 1.1105, 1.7357, 3.0258, 4.2198, 4.9311, 4.7058, 3.1159, 3.7807, 1.2868, 3.4959, 0.6257, -0.8572, -1.0709, 0.4825, -0.2235, 0.7140, 0.4732, -0.0728, -0.8468, -1.5148, -0.4465, 0.8564, 0.2141, -1.2457, 0.1732, 0.3853, -0.8839, 0.1537, 0.0582, -1.1430] 0
Methods¶
take
Iterate over the k samples.
Parameters
- k (int)
Notes¶
An instance is generated based on the parameters passed. The generator will randomly choose one of the hard coded waveforms, as well as random multipliers. For each feature, the actual value generated will be a a combination of the hard coded functions, with the multipliers and a random value.
If noise is added then the features 21 to 40 will be replaced with a random normal value.