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ransac

Fits a model to observed data via the RANSAC-method.

Introduction

ransac is a Python module that provides the RANSAC-method for fitting a model to observed data. The method is robust as it ignores outlier data. An iterative, non-deterministic algorithm is used which means that you might need to tune it in order for it to work for a specific problem.

You can read more about RANSAC here.

Installation

Install ransac with python setup.py install

Usage

>>> import numpy as np
>>> X = np.asarray(range(10))
>>> Y = 2 * X
>>> data = np.asarray([X, Y]).T
>>> import ransac
>>> model = ransac.LineModel()
>>> (params, inliers, residual) = ransac.ransac(data, model, 2, 8)
>>> params
[2.0, 0.0]
>>> residual
0.0

License

Distributed under the MIT license. See the LICENSE file.