Python pylab 模块，loglog() 实例源码

def plot_eigenspectrum(G, s, nvis, nhid):
    with misc.gnumpy_conversion_check('allow'):
        dim = G.shape[0]
        d, Q = scipy.linalg.eigh(G)
        d = d[::-1]
        Q = Q[:, ::-1]

        pts = np.unique(np.floor(np.logspace(0., np.log10(dim-1), 500)).astype(int)) - 1

        cf = [fisher.correlation_fraction(Q[:, i], s, nvis, nhid) for i in pts]

        pylab.figure()
        pylab.subplot(2, 1, 1)
        pylab.loglog(range(1, dim+1), d, 'b-', lw=2.)
        pylab.xticks([])
        pylab.yticks(fontsize='large')

        pylab.subplot(2, 1, 2)
        pylab.semilogx(pts+1, cf, 'r-', lw=2.)
        pylab.xticks(fontsize='x-large')
        pylab.yticks(fontsize='large')

def ComputePer(self,beta):
        """
        compute a periodigram for the data and compared it to a theorical line

        """

        datafft=np.fft.fft(self.data)
        per=np.abs(datafft)**2
        py.plot(per)
        x=np.array([100.*i+1 for i in range(self.length*self.res)])
        y=per[0]*(1./x)**(beta/2)
        py.loglog(x,y,c='red')
        py.show()

def plot_responses(options, config, event_names):
    import pylab as lab

    conf = config['iris_pull_config']
    if not event_names:
        sys.exit('need event name')

    for event_name in event_names:
        conf.event_name = event_name
        stations = _get_stations(conf)
        event = _get_event_infos(conf)
        fband = conf.inv_response_frequencyband


        combi_get_responses(stations, event.time, conf.path('resp_path'))

        for station in stations:

            for cha in station.get_channels():
                resp = cha.inv_response

                fmin, fmax = fband[0], fband[3]
                freqs = num.exp(num.linspace(num.log(fmin), num.log(fmax), 400))
                amps = num.abs(resp.evaluate(freqs))

                lab.loglog(freqs, amps)


    lab.show()