Predict survival function.

        Parameters
        ----------
        linear_predictor : array-like, shape = (n_samples,)
            Linear predictor of risk: `X @ coef`.

        Returns
        -------
        survival : ndarray, shape = (n_samples,)
            Predicted survival functions.

def get_survival_function(self, linear_predictor):
        """Predict survival function.

        Parameters
        ----------
        linear_predictor : array-like, shape = (n_samples,)
            Linear predictor of risk: `X @ coef`.

        Returns
        -------
        survival : ndarray, shape = (n_samples,)
            Predicted survival functions.
        """
        risk_score = numpy.exp(linear_predictor)
        n_samples = risk_score.shape[0]
        funcs = numpy.empty(n_samples, dtype=numpy.object_)
        for i in range(n_samples):
            funcs[i] = StepFunction(x=self.baseline_survival_.x,
                                    y=numpy.power(self.baseline_survival_.y, risk_score[i]))
        return funcs