HypercubeRC
⚠️ DEPRECATED — renamed to hypercube-esn.
hypercube-rcis no longer maintained;0.2.5is the final release. Install the drop-in successor instead:pip install hypercube-esnThen update imports from
hypercube_rctohypercube_esn.
Python bindings for a reservoir computer whose neurons live on a Boolean hypercube — a
DIM-dimensional graph where each vertex is addressed by a DIM-bit binary
index, with all connectivity defined by XOR operations on those indices.
Neuron states are continuous real values (driven through tanh
nonlinearity); only the addressing scheme is binary. No adjacency list
is stored. N = 2^DIM neurons (DIM 5-16, i.e. 32 to 65,536 neurons).
Scale-invariant hyperparameters: the same SR and input_scaling work at every DIM.
Installation
pip install hypercube-rc
Pre-built wheels for Python 3.10-3.13 on Windows (x64), Linux (x86_64, aarch64), and macOS (x86_64, arm64). No compiler required.
Quick Start
import numpy as np
import hypercube_rc as hrc
# One-step-ahead sine prediction
signal = np.sin(np.linspace(0, 20 * np.pi, 2000)).astype(np.float32)
esn = hrc.ESN(dim=7, seed=42)
esn.fit(signal, warmup=200)
print(f"R2 = {esn.r2():.6f}") # R2 = 0.999999
print(f"NRMSE = {esn.nrmse():.6f}") # NRMSE = 0.000129
Features
- Simple API --
fit()handles warmup, run, and train in one call - DIM 5-16 -- 32 to 65,536 neurons, scale-invariant defaults
- HCNN readout -- learned convolutional readout on raw reservoir state
- Multi-input -- multiple input channels via stride-interleaved driving
- Streaming mode -- online training for real-time applications
- Model persistence -- pickle, save/load to disk
Documentation
Full API reference: docs/Python_SDK.md
Project repository: github.com/dliptak001/HypercubeRC
1 maintainer
Metadata
1 maintainer
Release files for hypercube-rc 0.2.5
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