Installation

System Requirements

Requirement	Minimum	Recommended
Python	3.9	3.11+
PyTorch	2.0	2.2+
CUDA	-- (CPU works)	11.8+ with a GPU
RAM	8 GB	16 GB+
OS	Linux, macOS	Linux with NVIDIA GPU

Install from Source

git clone https://github.com/type1compute/SPIKESEG--Spiking-Neural-Network-for-Event-Based-Space-Domain-Awareness.git
cd SPIKESEG--Spiking-Neural-Network-for-Event-Based-Space-Domain-Awareness
pip install -e .

This installs SpikeSEG in editable mode together with all core dependencies.

Core Dependencies

Installed automatically by pip install -e .:

Package	Version	Purpose
torch	≥2.0	Tensor operations, spiking layers
numpy	≥1.24	Array manipulation
scipy	≥1.10	Signal processing, sparse ops
h5py	≥3.8	HDF5 dataset I/O
opencv-python	≥4.7	Image processing utilities
matplotlib	≥3.7	Visualization and plotting
pyyaml	≥6.0	YAML configuration parsing
tqdm	≥4.65	Progress bars
scikit-learn	≥1.2	Clustering, metrics

Optional Extras

# Development tools (pytest, black, ruff, mypy)
pip install -e ".[dev]"

# Visualization extras (TensorBoard, Plotly, Seaborn)
pip install -e ".[vis]"

# Everything
pip install -e ".[all]"

Verify the Installation

python -c "import spikeseg; print(spikeseg.__version__)"
# Expected output: 0.1.0

To confirm PyTorch sees your GPU:

python -c "import torch; print(torch.cuda.is_available(), torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'CPU')"

Running the Tests

pytest tests/ -v

Skip GPU-only tests on a CPU machine:

pytest tests/ -v -m "not cuda"