@verbose
    def plot(self, picks=None, baseline=None, mode='mean', tmin=None,
             tmax=None, fmin=None, fmax=None, vmin=None, vmax=None,
             cmap='RdBu_r', dB=False, colorbar=True, show=True,
             title=None, axes=None, layout=None, verbose=None):
        from ..viz.topo import _imshow_tfr
        import matplotlib.pyplot as plt
        times, freqs = self.times.copy(), self.freqs.copy()
        info = self.info
        data = self.data

        n_picks = len(picks)
        info, data, picks = _prepare_picks(info, data, picks)
        data = data[picks]

        data, times, freqs, vmin, vmax = \
            _preproc_tfr(data, times, freqs, tmin, tmax, fmin, fmax, mode,
                         baseline, vmin, vmax, dB, info['sfreq'])

        tmin, tmax = times[0], times[-1]
        if isinstance(axes, plt.Axes):
            axes = [axes]
        if isinstance(axes, list) or isinstance(axes, np.ndarray):
            if len(axes) != n_picks:
                raise RuntimeError('There must be an axes for each picked '
                                   'channel.')

        for idx in range(len(data)):
            if axes is None:
                fig = plt.figure()
                ax = fig.add_subplot(111)
            else:
                ax = axes[idx]
                fig = ax.get_figure()
            onselect_callback = partial(self._onselect, baseline=baseline,
                                        mode=mode, layout=layout)
            _imshow_tfr(ax, 0, tmin, tmax, vmin, vmax, onselect_callback,
                        ylim=None, tfr=data[idx: idx + 1], freq=freqs,
                        x_label='Time (ms)', y_label='Frequency (Hz)',
                        colorbar=colorbar, picker=False, cmap=cmap)
            if title:
                fig.suptitle(title)
            colorbar = False  # only one colorbar for multiple axes
        plt_show(show)
        return fig
Read data from the wrapped pipe connection.
dataset/ETHPy150Open mne-tools/mne-python/mne/time_frequency/tfr.py/AverageTFR.plot--crossover with--dataset/ETHPy150Open GoogleCloudPlatform/DataflowPythonSDK/google/cloud/dataflow/io/gcsio.py/GcsBufferedWriter.PipeStream.read