Esempio n. 1
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def test_geodataframe_multi_attr():
    cluster_object = AZPReactiveTabu(max_iterations=max_it, k1=k1, k2=k2,
                                     random_state=0)
    cluster_object.fit_from_geodataframe(gdf, double_attr_str,
                                         n_regions=n_reg)
    obtained = region_list_from_array(cluster_object.labels_)
    compare_region_lists(obtained, optimal_clustering)
Esempio n. 2
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def test_geodataframe():
    cluster_object = AZPReactiveTabu(max_iterations=max_it,
                                     k1=k1,
                                     k2=k2,
                                     random_state=0)
    cluster_object.fit_from_geodataframe(gdf, attr_str, n_regions=n_reg)
    result = region_list_from_array(cluster_object.labels_)
    compare_region_lists(result, optimal_clustering)
Esempio n. 3
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def test_geodataframe():
    cluster_object = AZPReactiveTabu(max_iterations=max_it, k1=k1, k2=k2,
                                     random_state=0)
    cluster_object.fit_from_geodataframe(gdf, attr_str, n_regions=n_reg)
    result = region_list_from_array(cluster_object.labels_)
    compare_region_lists(result, optimal_clustering)