Metadata-Version: 2.1
Name: robustranking
Version: 0.2
Summary: Package for ranking algorithms
Author-email: Jeroen Rook <j.g.rook@utwente.nl>
Maintainer-email: Jeroen Rook <j.g.rook@utwente.nl>
Project-URL: Homepage, https://github.com/jeroenrook/robustranking
Project-URL: Repository, https://github.com/jeroenrook/robustranking
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: matplotlib>=3.5.2
Requires-Dist: numpy>=1.23
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: statsmodels
Requires-Dist: typing_extensions
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: flake8-docstrings; extra == "dev"
Requires-Dist: flake8-import-order; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pylint; extra == "dev"
Requires-Dist: YAPF; extra == "dev"
Requires-Dist: isort; extra == "dev"

# Robust Ranking

!Warning! This package is currently still under heavy development. 

A Python package for robust ranking. 

## Installation

```
pip install git+https://github.com/jeroenrook/robustranking
```

## Example usage

```
from robustranking.benchmark import Benchmark
from robustranking.comparison import BootstrapComparison

# Load benchmark data
benchmark = Benchmark()
benchmark.from_pandas(df, "algorithm", "instance", "pqr10")
print(benchmark.show_stats())

comparison = BootstrapComparison(benchmark,
                                 alpha=0.05,
                                 minimise=True,
                                 bootstrap_runs=10000,
                                 aggregation_method=np.mean)

robust_ranks = comparison.get_ranking()

print(robust_ranks)

```

