Spike Encoders
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Spike encoders for Spiking Neural Network.
This package consists of three types of spike encoders for spatio-temporal data:
- Threshold Based Representation (TBR) encoder
- Bens Spiker Algorithm (BSA) encoder
- Step Forward (SF) encoder
Data
The data given to the encoders are spatio-temporal. Each sample is one csv file. In each file, every column is a feature and the rows are time points.
For example, each file in tests/test-data is one second of EEG from the PhysioNet EEG Motor Movement/Imagery Dataset: 160 rows (time points at 160 Hz) and 14 columns (EEG channels). See its README for details and citation.
Instillation
pip install pyspikes
BSA and Step Forward run faster with Numba installed. The spikes are the same either way:
pip install pyspikes[numba]
Example
from spikes import encoder
from spikes.utility import ReadCSV
data = ReadCSV("tests/test-data").get_samples()["samples"]
bsa = encoder.BSA(data)
print(bsa.get_spikes())
tbr = encoder.TBR(data)
print(tbr.get_spikes())
sf = encoder.StepForward(data)
print(sf.get_spikes())
Contribution
All contributions are welcome.
Issues
Issues can be opened through Github's Issues tab.
1 maintainer
Metadata
1 maintainer
Release files for pyspikes 0.3.1
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| File | Size | Uploaded | Provenance | Actions |
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| pyspikes-0.3.1-py3-none-any.whl | Python 3 | none | any | Details for pyspikes-0.3.1-py3-none-any.whl |
Total release size: 27.4 kB
Release files / pyspikes-0.3.1.tar.gz
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