geco_slow_channel_plot.py 文件源码

def plot_timeseries(self, ax, **kwargs):
        """Scale up by 10^9 since plots are in ns, not seconds.
        Remove any indices considered bad in ``plot_properties``"""
        # define the variables for our plots
        t = np.delete(self.t_axis, self.bad_indices.means)
        y = np.delete(self.plot_vars.means - self.trend,
                      self.bad_indices.means) / SEC_PER['ns']
        yerr = np.delete(self.plot_vars.stds,
                         self.bad_indices.means) / SEC_PER['ns']
        mint = np.delete(self.t_axis, self.bad_indices.absmins)
        miny = np.delete(self.plot_vars.absmins - self.trend,
                         self.bad_indices.absmins) / SEC_PER['ns']
        maxt = np.delete(self.t_axis, self.bad_indices.absmaxs)
        maxy = np.delete(self.plot_vars.absmaxs - self.trend,
                         self.bad_indices.absmaxs) / SEC_PER['ns']
        # plot everything, but only if the plotted data has nonzero length
        # in order to avoid an annoying matplotlib bug when adding legends.
        if len(t) != 0:
            ax.errorbar(t, y, marker="o", color="green", linestyle='none',
                        yerr=yerr, label="Means +/- Std. Dev.")
        if len(mint) != 0:
            ax.scatter(mint,miny,marker="^", color="blue", label="Abs. Minima")
        if len(maxt) != 0:
            ax.scatter(maxt,maxy,marker="v", color="red", label="Abs. Maxima")