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omar

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omar (Open Multivariate Adaptive Regression) is a Python package for discovering localised, linear structure in complex, high-dimensional datasets. It implements a modernized version of the Multivariate Adaptive Regression Splines (MARS) algorithm with improved numerical efficiency, based on modern rank-one update strategies and optional Fortran acceleration.

Installation

From PyPI

pip install omar

From Source

See the Getting Started wiki page.


Quick Example

import numpy as np
from omar import OMAR

np.random.seed(0)

x = np.random.normal(2, 1, size=(1000, 3))
noise = np.random.normal(size=1000)
y = ((x[:, 0] + np.maximum(0, (x[:, 0] - 1)) +
      np.maximum(0, (x[:, 0] - 1)) * x[:, 1] +
      np.maximum(0, (x[:, 0] - 1)) * np.maximum(0, (x[:, 1] - 0.8))) +
     0.12 * noise)
model = OMAR(max_nbases=11)
model.find_bases(X, y)
print(model)

Documentation

Visit omar wiki


Contributing

We welcome contributions! See Contributing for code guidelines, tests, and CI workflow.


License

This project is licensed under the MIT License. See LICENSE.txt.

Metadata

Release files for omar 1.0

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Source distribution for omar 1.0
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omar-1.0-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
omar-1.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.17+ x86-64 Details
omar-1.0-cp313-cp313-macosx_14_0_arm64.whl CPython 3.13 CPython 3.13 macOS 14.0+ ARM64 Details
omar-1.0-cp313-cp313-macosx_13_0_x86_64.whl CPython 3.13 CPython 3.13 macOS 13.0+ x86-64 Details
omar-1.0-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
omar-1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.17+ x86-64 Details
omar-1.0-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details
omar-1.0-cp312-cp312-macosx_13_0_x86_64.whl CPython 3.12 CPython 3.12 macOS 13.0+ x86-64 Details

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