Installation

Requirements: Python 3.10 and 3.11 have been tested with this beta release.

Python Installation via pip:
```
pip install bioneuralnet==0.1.0b1
```
Dependencies Installation with `fast-install.py`:

BioNeuralNet uses a variety of Python and R packages for data processing and graph generation. We have provided a quick way to install these dependencies using a script.

Download options:
- Download zip content
- Clone or download from the BioNeuralNet GitHub repository
Continue from .zip download:
- Extract the contents of the .zip file to a folder. - In the example below, the folder is named ‘tutorial’.
- Open a terminal window and navigate to the folder.
- Run the following command from the root directory:
```
cd tutorial/BioNeuralNet-main
python3 scripts/fast-install.py
```
fast-install.py Options:

The script offers a few options depending on your system and requirements:
- GPU-acceleration:
  - BioNeuralNet supports GPU-accelerated training with CUDA.
  - We support all stable CUDA versions (11.8, 12.1, 12.4) as detailed in the PyTorch documentation.
  - First, check your installed CUDA version with:
    
    nvcc --version
  - Pass the version number when using the script:
    
    python3 scripts/fast-install.py --cuda --cuda-version 12.1
- Development dependencies: - For testing, documentation, and contributing, you can install development dependencies:
  python3 scripts/fast-install.py --dev
- Combined Installation: - Install both CUDA and development dependencies with:
  python3 scripts/fast-install.py --cuda --cuda-version 11.8 --dev
Command Examples:
- Default Installation (CPU-only, no dev dependencies):
```
python fast-install.py
```
- Install Development Dependencies:
```
python fast-install.py --dev
```
- Install CUDA-enabled PyTorch (Default CUDA Version Detection):
```
python fast-install.py --cuda
```
- Install Specific CUDA Version with Development Dependencies:
```
python fast-install.py --cuda --cuda-version 12.1 --dev
```
- Install Both CUDA and Development Dependencies with a Supported CUDA Version:
```
python fast-install.py --cuda --cuda-version 11.8 --dev
```
If you cloned the repository:
```
git clone https://github.com/UCD-BDLab/BioNeuralNet.git
cd BioNeuralNet
python3 scripts/fast-install.py
```
Follow the same steps as above.
Success Message:

If you see the following message, the installation was successful:

You can now activate your virtual environment and start using BioNeuralNet:
```
source ./bioneuralnet-env/bin/activate
```
See the tutorials or tools sections for examples.
Running tests:

If you install development dependencies, you can run tests with the following command from the root directory:
```
pytest tests/
```
- You should see the following output if installation was successful:
This script: - Creates and activates a virtual environment. - Installs base, development, and R dependencies for graph generation.

After installation, proceed to the tutorials or tools sections for code examples.