@staticmethod
    def load_mat(filename):
        from scipy.io import loadmat

        d = loadmat(filename)

        M = d['M'][0][0]
        Cs = tuple(map(np.squeeze, np.split(d['Cs'], 2, axis=0)))
        Rs = tuple(map(np.squeeze, np.split(d['Rs'], 2, axis=0)))
        mus = tuple(map(np.squeeze, np.split(d['mus'], 2, axis=0)))

        subs = tuple([map(np.squeeze, np.split(half, M / 2, axis=0)) for half in map(np.squeeze, np.split(d['subs'], 2, axis=0))])

        return LOPQModel(parameters=(Cs, Rs, mus, subs))
Reconstitute an LOPQModel in the format exported by the `export_mat` method above.
dataset/ETHPy150Open yahoo/lopq/python/lopq/model.py/LOPQModel.load_mat