How to use the sidekit.factor_analyser.FactorAnalyser function in SIDEKIT

G=None,
                 H=None,
                 Sigma=None):
        """
        Initialize a Factor Analyser object to None or by reading from an HDF5 file.
        When loading from a file, other parameters can be provided to overwrite each of the component.

        :param input_file_name: name of the HDF5 file to read from, default is nNone
        :param mean: the mean vector
        :param F: between class matrix
        :param G: within class matrix
        :param H: MAP covariance matrix
        :param Sigma: residual covariance matrix
        """
        if input_file_name is not None:
            fa = FactorAnalyser.read(input_file_name)
            self.mean = fa.mean
            self.F = fa.F
            self.G = fa.G
            self.H = fa.H
            self.Sigma = fa.Sigma
        else:
            self.mean = None
            self.F = None
            self.G = None
            self.H = None
            self.Sigma = None

        if mean is not None:
            self.mean = mean
        if F is not None:
            self.F = F

def read(input_filename):
        """
         Read a generic FactorAnalyser model from a HDF5 file

        :param input_filename: the name of the file to read from

        :return: a FactorAnalyser object
        """
        fa = FactorAnalyser()
        with h5py.File(input_filename, "r") as fh:
            kind = fh.get("fa/kind").value
            if kind[0] != 0:
                fa.mean = fh.get("fa/mean").value
            if kind[1] != 0:
                fa.F = fh.get("fa/f").value
            if kind[2] != 0:
                fa.G = fh.get("fa/g").value
            if kind[3] != 0:
                fa.H = fh.get("fa/h").value
            if kind[4] != 0:
                fa.Sigma = fh.get("fa/sigma").value
        return fa