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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def _generate_feature_labels(self, X):
        '''
        Generates string feature labels
        '''
        Xt, Xc = get_ts_data_parts(X)

        ftr_sizes = self._check_features(self.features, Xt[0:3])
        f_labels = []

        # calculated features
        for key in ftr_sizes:
            for i in range(ftr_sizes[key]):
                f_labels += [key + '_' + str(i)]

        # contextual features
        if Xc is not None:
            Ns = len(np.atleast_1d(Xc[0]))
            s_labels = ["context_" + str(i) for i in range(Ns)]
            f_labels += s_labels

        return f_labels