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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 transform(self, X, lenscale=None):
 """ Apply the Fast Food RBF basis to X. Parameters X: ndarray (N, d) array of observations where N is the number of samples, and d is the dimensionality of X. lenscale: scalar or ndarray, optional scalar or array of shape (d,) length scales (one for each dimension of X).If not input, this uses the value of the initial length scale. Returns ------- ndarray: of shape (N, 2*nbases) where nbases is number of random bases to use, given in the constructor (to nearest larger two power). """

        lenscale = self._check_dim(X.shape[1], lenscale)

        VX = self._makeVX(X / lenscale)
        Phi = np.hstack((np.cos(VX), np.sin(VX))) / np.sqrt(self.n)
        return Phi