Function _spectral_helper

lib/matplotlib/mlab.py:223–391

Private helper implementing the common parts between the psd, csd, spectrogram and complex, magnitude, angle, and phase spectrums.

(x, y=None, NFFT=None, Fs=None, detrend_func=None,
                     window=None, noverlap=None, pad_to=None,
                     sides=None, scale_by_freq=None, mode=None)

def _spectral_helper(x, y=None, NFFT=None, Fs=None, detrend_func=None,
                     window=None, noverlap=None, pad_to=None,
                     sides=None, scale_by_freq=None, mode=None):
    """
    Private helper implementing the common parts between the psd, csd,
    spectrogram and complex, magnitude, angle, and phase spectrums.
    """
    if y is None:
        # if y is None use x for y
        same_data = True
    else:
        # The checks for if y is x are so that we can use the same function to
        # implement the core of psd(), csd(), and spectrogram() without doing
        # extra calculations.  We return the unaveraged Pxy, freqs, and t.
        same_data = y is x

    if Fs is None:
        Fs = 2
    if noverlap is None:
        noverlap = 0
    if detrend_func is None:
        detrend_func = detrend_none
    if window is None:
        window = window_hanning

    # if NFFT is set to None use the whole signal
    if NFFT is None:
        NFFT = 256

    if not (0 <= noverlap < NFFT):
        raise ValueError('noverlap must be less than NFFT')

    if mode is None or mode == 'default':
        mode = 'psd'
    _api.check_in_list(
        ['default', 'psd', 'complex', 'magnitude', 'angle', 'phase'],
        mode=mode)

    if not same_data and mode != 'psd':
        raise ValueError("x and y must be equal if mode is not 'psd'")

    # Make sure we're dealing with a numpy array. If y and x were the same
    # object to start with, keep them that way
    x = np.asarray(x)
    if not same_data:
        y = np.asarray(y)

    if sides is None or sides == 'default':
        if np.iscomplexobj(x):
            sides = 'twosided'
        else:
            sides = 'onesided'
    _api.check_in_list(['default', 'onesided', 'twosided'], sides=sides)

    # zero pad x and y up to NFFT if they are shorter than NFFT
    if len(x) < NFFT:
        n = len(x)
        x = np.resize(x, NFFT)