def _match_filter_plot(stream, cccsum, template_names, rawthresh, plotdir,<EOL>plot_format, i):  
import matplotlib.pyplot as plt<EOL>plt.ioff()<EOL>stream_plot = copy.deepcopy(stream[<NUM_LIT:0>])<EOL>stream_plot = _plotting_decimation(stream_plot, <NUM_LIT>, <NUM_LIT:4>)<EOL>cccsum_plot = Trace(cccsum)<EOL>cccsum_plot.stats.sampling_rate = stream[<NUM_LIT:0>].stats.sampling_rate<EOL>cccsum_hist = cccsum_plot.copy()<EOL>cccsum_hist = cccsum_hist.decimate(int(stream[<NUM_LIT:0>].stats.<EOL>sampling_rate / <NUM_LIT:10>)).data<EOL>cccsum_plot = chunk_data(cccsum_plot, <NUM_LIT:10>, '<STR_LIT>').data<EOL>stream_plot.data = stream_plot.data[<NUM_LIT:0>:len(cccsum_plot)]<EOL>cccsum_plot = cccsum_plot[<NUM_LIT:0>:len(stream_plot.data)]<EOL>cccsum_hist = cccsum_hist[<NUM_LIT:0>:len(stream_plot.data)]<EOL>plot_name = (plotdir + os.sep + '<STR_LIT>' + template_names[i] + '<STR_LIT:_>' +<EOL>stream[<NUM_LIT:0>].stats.starttime.datetime.strftime('<STR_LIT>') +<EOL>'<STR_LIT:.>' + plot_format)<EOL>triple_plot(cccsum=cccsum_plot, cccsum_hist=cccsum_hist,<EOL>trace=stream_plot, threshold=rawthresh, save=True,<EOL>savefile=plot_name)<EOL>
Plotting function for match_filter.

:param stream: Stream to plot
:param cccsum: Cross-correlation sum to plot
:param template_names: Template names used
:param rawthresh: Threshold level
:param plotdir: Location to save plots
:param plot_format: Output plot type (e.g. png, svg, eps, pdf...)
:param i: Template index name to plot.