mcbs

Name	mcbs JSON
Version	0.1.1 JSON
	download
home_page	https://github.com/carlosguirado/mode-choice-benchmarking-sandbox
Summary	A benchmarking sandbox for mode choice models
upload_time	2024-10-22 05:27:20
maintainer	None
docs_url	None
author	Carlos Guirado
requires_python	>=3.8
license	None
keywords
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # 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.

            

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