Metadata-Version: 2.1
Name: mcbs
Version: 0.1.1
Summary: A benchmarking sandbox for mode choice models
Home-page: https://github.com/carlosguirado/mode-choice-benchmarking-sandbox
Author: Carlos Guirado
Author-email: guirado@berkeley.edu
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=2.0.0
Requires-Dist: pandas>=2.0.0
Requires-Dist: biogeme>=3.2.14
Requires-Dist: matplotlib>=3.0.0

# Mode Choice Benchmarking Sandbox (MCBS)

A Python package for benchmarking discrete choice models for transportation mode choice analysis.

## Installation

You can install MCBS using pip:

```bash
pip install mcbs
```

## Quick Start

```python
from mcbs.benchmarking import Benchmark
from mcbs.datasets import DatasetLoader

# Load a dataset
benchmark = Benchmark("swissmetro_dataset")

# Define your models
models = {
    "MNL - Base Model": your_model_function
}

# Run benchmark
results = benchmark.run(models)

# Compare results
benchmark.compare_results(results)
```

## Features

- Easy access to transportation mode choice datasets
- Standardized benchmarking metrics
- Support for Biogeme model estimation
- Visualization of benchmark results

## Datasets

Currently available datasets:
- Swissmetro
- London Transport
- Mode Canada

## Requirements

- Python >=3.8
- NumPy >=2.0.0
- Pandas >=2.0.0
- Biogeme >=3.2.14
- Matplotlib >=3.0.0

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our contributing guidelines for details.
