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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 evaluate(self, x):
 r"""Evaluate the kernels at given frequencies. Parameters x : array_like Graph frequencies at which to evaluate the filter. Returns ------- y : ndarray Frequency response of the filters. Shape ``(g.Nf, len(x))``. Examples -------- Frequency response of a low-pass filter: """

        x = np.asanyarray(x)
        # Avoid to copy data as with np.array([g(x) for g in self._kernels]).
        y = np.empty([self.Nf] + list(x.shape))
        for i, kernel in enumerate(self._kernels):
            y[i] = kernel(x)
        return y