Getting started

Installation

Install from source:

pip install .

Or for development:

pip install -e .

Dependencies: scikit-learn>=1.6.1, scipy>=1.6.0, numpy>=1.20.0.

Quick Example

import numpy as np
from popsregression import POPSRegression
from sklearn.preprocessing import PolynomialFeatures

# Generate low-noise data
rng = np.random.RandomState(42)
x = np.sort(rng.uniform(-1, 1, 50)) * 10
y = np.sin(x) * x + 0.001 * rng.randn(50)

# Create polynomial features
poly = PolynomialFeatures(degree=4, include_bias=True)
X = poly.fit_transform(x.reshape(-1, 1))

# Fit POPS Regression
model = POPSRegression(resampling_method='sobol')
model.fit(X, y)

# Predict with uncertainty
y_pred, y_std = model.predict(X, return_std=True)

Running Tests

pytest -vsl popsregression

Building Documentation

cd doc && make html

Using pixi

If you have pixi installed, you can use the pre-configured tasks:

pixi run test    # run tests
pixi run lint    # check code style
pixi run build-doc  # build documentation