transformations.py 文件源码

def __call__(self, x, inverse=False):
        """Rotates the input array `x` with a fixed rotation matrix
           (``self.dicMatrices[len(x)]``)
        """
        x = np.array(x, copy=False)
        N = x.shape[0]  # can be an array or matrix, TODO: accept also a list of arrays?
        if N not in self.dicMatrices:  # create new N-basis once and for all
            rstate = np.random.get_state()
            np.random.seed(self.seed) if self.seed else np.random.seed()
            self.state = np.random.get_state()  # only keep last state
            B = np.random.randn(N, N)
            np.random.set_state(rstate)  # keep untouched/good sequence from outside view
            for i in range(N):
                for j in range(0, i):
                    B[i] -= np.dot(B[i], B[j]) * B[j]
                B[i] /= sum(B[i]**2)**0.5
            self.dicMatrices[N] = B
        if inverse:
            return np.dot(self.dicMatrices[N].T, x)  # compute rotation
        else:
            return np.dot(self.dicMatrices[N], x)  # compute rotation