lsimodel.py 文件源码

def clip_spectrum(s, k, discard=0.001):
    """
    Given eigenvalues `s`, return how many factors should be kept to avoid
    storing spurious (tiny, numerically instable) values.

    This will ignore the tail of the spectrum with relative combined mass < min(`discard`, 1/k).

    The returned value is clipped against `k` (= never return more than `k`).
    """
    # compute relative contribution of eigenvalues towards the energy spectrum
    rel_spectrum = numpy.abs(1.0 - numpy.cumsum(s / numpy.sum(s)))
    # ignore the last `discard` mass (or 1/k, whichever is smaller) of the spectrum
    small = 1 + len(numpy.where(rel_spectrum > min(discard, 1.0 / k))[0])
    k = min(k, small) # clip against k
    logger.info("keeping %i factors (discarding %.3f%% of energy spectrum)" %
                (k, 100 * rel_spectrum[k - 1]))
    return k