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Installation Guide

From PyPI (Once Published)

The easiest way to install NDT:

pip install ndtracker

From Source (Development)

Prerequisites

  • Python 3.8 or higher
  • pip (latest version recommended)

Clone and Install

# Clone the repository
git clone https://github.com/Javihaus/ndt.git
cd ndt

# Create virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode with dev dependencies
pip install -e ".[dev]"

Verify Installation

python -c "from ndt import HighFrequencyTracker; print('NDT installed successfully!')"

Optional Dependencies

For JAX Support

pip install ndtracker[jax]

For Documentation Building

pip install ndtracker[docs]

All Optional Dependencies

pip install ndtracker[dev,docs,jax]

System Requirements

  • CPU: Any modern CPU (x86_64, ARM64)
  • Memory: Depends on model size; typically < 1GB overhead
  • GPU: Optional, automatically used if available via PyTorch
  • Disk: ~50MB for package, variable for results storage

Supported Platforms

  • Linux: Ubuntu 18.04+, CentOS 7+, other major distributions
  • macOS: 10.15+ (Catalina and later)
  • Windows: 10 and 11

Dependencies

Core dependencies (automatically installed):

  • torch >= 1.12.0
  • numpy >= 1.21.0
  • pandas >= 1.3.0
  • matplotlib >= 3.5.0
  • seaborn >= 0.11.0
  • plotly >= 5.0.0
  • scipy >= 1.7.0
  • tqdm >= 4.62.0
  • pyyaml >= 6.0
  • h5py >= 3.6.0

Troubleshooting

Import Errors

If you get import errors, ensure your Python path is correct:

export PYTHONPATH=/path/to/ndt/src:$PYTHONPATH

PyTorch Installation

If PyTorch is not installed or you need GPU support:

# CPU only
pip install torch --index-url https://download.pytorch.org/whl/cpu

# CUDA 11.8
pip install torch --index-url https://download.pytorch.org/whl/cu118

# See https://pytorch.org for more options

Testing Installation

Run the test suite:

pytest tests/ -v

Uninstallation

pip uninstall ndtracker

Docker (Coming Soon)

Pre-configured Docker images will be available for easy deployment.

Support

For installation issues:

  1. Check GitHub Issues
  2. Search existing issues
  3. Create a new issue with your environment details