def get_stats_result(self, request):
        """Return the StatsResult object for this statistic"""
        stats_datasets = StatsMakerDataverses(**request.GET.dict())

        pub_state = self.get_pub_state(request)

        if pub_state == self.PUB_STATE_ALL:
            stats_result = stats_datasets.get_dataverse_counts_by_month()
        elif pub_state == self.PUB_STATE_UNPUBLISHED:
            stats_result = stats_datasets.get_dataverse_counts_by_month_unpublished()
        else:
            stats_result = stats_datasets.get_dataverse_counts_by_month_published()

        return stats_result
def compute_rbf_kernel_matrix(X):
    """Compute the RBF kernel matrix with sigma2 as the median pairwise
    distance.
    """
    sigma2 = np.median(pairwise_distances(X, metric='euclidean'))**2
    K = pairwise_kernels(X, X, metric='rbf', gamma=1.0/sigma2, n_jobs=-1)
    return K