Installation

This guide covers the installation of the SNN2 framework on various platforms.

Prerequisites

System Requirements

Python: 3.7 or higher
Operating System: Linux, macOS (Not tested), or Windows (Not tensted)
Memory: Depends on the datasets used, suggested at least 16GB RAM
GPU: NVIDIA GPU with CUDA support (optional but recommended)

Required Dependencies

The framework relies on several key libraries:

TensorFlow: 2.x (for neural network operations)
NumPy: For numerical computations
Pandas: For data manipulation
Matplotlib/Seaborn: For visualization
scikit-learn: For machine learning utilities
UMAP: For dimensionality reduction
FastDTW: For dynamic time warping

Installation Methods

From Source (Recommended)

Clone the Repository
```
git clone <repository-url>
cd SNN2
```

Create Virtual Environment (Recommended)

# Install the required applications (linux system)
make install

# Create the virtual environment automatically manages the installation of the latest requirements
make virtualenv

Install the Package

# Development installation (editable)
pip install -e .

# Or regular installation
pip install .

GPU Support

CUDA Setup

For GPU acceleration, ensure you have:

NVIDIA Drivers: Latest drivers for your GPU
CUDA Toolkit: Compatible version with TensorFlow
cuDNN: NVIDIA Deep Neural Network library

# Verify GPU detection
python -c "import tensorflow as tf; print('GPU Available:', tf.config.list_physical_devices('GPU'))"

TensorFlow GPU

Install TensorFlow with GPU support:

pip install tensorflow-gpu

Or use the unified TensorFlow package (TF 2.1+):

pip install tensorflow

Verification

Test Installation

Basic Import Test

python -c "import SNN2; print('SNN2 imported successfully')"

Run Help Command
```
python SNN2/main.py --help
```

Development Setup

Up to now the development setup is identically to the main setup. The following sections will be updated once there will be a differentiation between the two setups.

Next Steps

After successful installation:

Review Command Line Arguments: Command Line Arguments
Explore Configuration Options: Configuration Settings