This is a C++ implemenation of the sklearn MeanShift algorithm (https://github.com/scikit-learn/scikit-learn/blob/98cf537f5/sklearn/cluster/_mean_shift.py), with Eigen3 and OpenMP acceleration, and Python API provided via Pybind11. Comparing to sklearn, this implementation is much more efficient on high-dimensional data (>100D). But a larger memory space is required as the implementation generates large intermediate matrices.
To compile the library, please make sure you have GCC & G++ installed, and the support for C++ 11 is required.
First install the Pybind11 library:
pip install pybind11
Then compile the c++ backend and the python API:
make fast_mean_shift
Finally copy the generated library file (located in the directory lib/) to your python package installation directory. You can use this command to check the package directory:
python -m site
Two major APIs:
(1) mean_shift_clustering: accepting the same parameter list as sklearn.cluster.MeanShift in sklean, returning the centroids (shape (n_centroids, n_features)) and the cluster IDs for all data points (shape (n_points,)).
(2) mean_shift_density_peaks_detecting: accepting the same parameter list as mean_shift_clustering, returning the centroids (also the density peaks) found by mean shift algorithm, whose shape is (n_centroids, n_features).
Two minor APIs:
(1) estimate_bandwidth: accepting the same parameter list as sklearn.cluster.estimate_bandwidth in sklean, estimating and returning the proper bandwidth.
(2) setDistanceMetric: setting the distance metric used in FastMeanShift, supported metrics are Metric.DIST_L2 for L2 distance and Metric.DIST_COS for cosine distance.
Please see test_fast_mean_shift.ipynb for a demo that compares sklearn.cluster.MeanShift and fast_mean_shift.FastMeanShift.
Most of the functions in fast_mean_shift.cpp are translated from those in sklearn, please refer to file https://github.com/scikit-learn/scikit-learn/blob/98cf537f5/sklearn/cluster/_mean_shift.py for detailed comments.
(1) The APIs only accept numpy arrays with float32 data type. To make it accept float64, please change the definition of VectorElemType in util.h from float to double.