7ea8c3e6d162ef47fbcfcb6621ff7633d91ae61d,tslearn/early_classification.py,NonMyopicEarlyClassification,_expected_cost,#NonMyopicEarlyClassification#Any#Any#,180

Before Change

        cost = 0
        proba_clusters = self.get_cluster_probas(X=X)
        truncated_t = X.shape[-1]
        for k in range(0, self.n_clusters):
            sum_pyhatyck = np.sum(self.pyhatyck_["pyhatycks{0}".format(k)][
                                truncated_t + tau - self.minimum_time_stamp
                            ], axis=0)
            sum_global = np.dot(sum_pyhatyck, self.pyck_[:, k])
            cost = cost + proba_clusters[:, k] * sum_global

        return cost

    def minimize_integer(self, end_of_time, xt):
        

After Change

        proba_clusters = self.get_cluster_probas(X=X)
        truncated_t = X.shape[-1]
        sum_pyhatyck = np.sum(self.pyhatyck_[truncated_t + tau - self.minimum_time_stamp], axis=1)
        sum_pyhatyck = np.transpose(sum_pyhatyck)
        sum_global = np.sum((sum_pyhatyck * self.pyck_), axis=0)
        cost = np.dot(proba_clusters, sum_global)
        return cost + self._cost_time(truncated_t + tau)

    def cost_function_minimizer(self, end_of_time, xt):
        

Instances