@staticmethod
    def transform(samples, win_shape=numpy.hamming, pre_var=None):
        if not pre_var:
            pre_var = Spectrum.pre_calculate(len(samples), win_shape, False)
        return numpy.fft.rfft(pre_var.W * samples) / pre_var.WL
dataset/ETHPy150Open dongying/dear/dear/spectrum/dft.py/Spectrum.transform/original