test_optimalK.py 文件源码

def test_optimalk(parallel_backend, n_jobs, n_clusters):
    """
    Test core functionality of OptimalK using all backends.
    """
    import numpy as np
    from sklearn.datasets.samples_generator import make_blobs
    from gap_statistic import OptimalK

    # Create optimalK instance
    optimalK = OptimalK(parallel_backend=parallel_backend, n_jobs=n_jobs)

    # Create data
    X, y = make_blobs(n_samples=int(1e3), n_features=2, centers=3)

    suggested_clusters = optimalK(X, n_refs=3, cluster_array=np.arange(1, 10))

    assert np.allclose(suggested_clusters, n_clusters, 2), ('Correct clusters is {}, OptimalK suggested {}'
                                                            .format(n_clusters, suggested_clusters))