signal.py 文件源码

def spectrum(x,
             n0=0,
             T_s=1,
             oversample=1,
             only_positive=True):
    """
    Return the spectrum for the signal *x* calculated via FFT and the
    associated frequencies as a tuple. The *n0* parameter gives the
    index in *x* for time index 0 (*n0* = 0 means that `x[0]` is at
    time 0). The number of spectral samples returned is the next power
    of 2 greater than the length of *x* multiplied by *oversample*. If
    *only_positive*, return the spectrum only for positive frequencies
    (and raise an exception if *x* is not real).
    """
    assert oversample >= 1 and isinstance(oversample, int)
    N = nextpow2(len(x)) * 2**(oversample - 1)
    X = NP.fft.fft(x, n=N) * T_s
    f = NP.fft.fftfreq(N, d=T_s)
    if n0 != 0:
        X *= NP.exp(-1j * 2 * math.pi * NP.arange(N) * n0 / N)
    X = NP.fft.fftshift(X)
    f = NP.fft.fftshift(f)
    if only_positive:
        if any(NP.iscomplex(x)):
            raise ValueError('x is complex and only returning information for positive frequencies --- this is likely not what you want to do')
        X = X[f >= 0]
        f = f[f >= 0]
    return X, f