refactor: rewrite plotWFData to reduce complexity
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090bfb47d1
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@ -140,18 +140,6 @@ class LogWidget(QtWidgets.QWidget):
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self.stderr.append(60 * '#' + '\n\n')
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def getDataType(parent):
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type = QInputDialog().getItem(parent, "Select phases type", "Type:",
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["manual", "automatic"])
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if type[0].startswith('auto'):
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type = 'auto'
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else:
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type = type[0]
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return type
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def plot_pdf(_axes, x, y, annotation, bbox_props, xlabel=None, ylabel=None,
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title=None):
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# try method or data
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@ -1009,15 +997,6 @@ class WaveformWidgetPG(QtWidgets.QWidget):
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time_ax = np.linspace(time_ax[0], time_ax[-1], num=len(data))
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return data, time_ax
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# def getAxes(self):
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# return self.axes
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# def getXLims(self):
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# return self.getAxes().get_xlim()
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# def getYLims(self):
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# return self.getAxes().get_ylim()
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def setXLims(self, lims):
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vb = self.plotWidget.getPlotItem().getViewBox()
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vb.setXRange(float(lims[0]), float(lims[1]), padding=0)
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@ -1171,8 +1150,6 @@ class PylotCanvas(FigureCanvas):
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break
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if not ax_check: return
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# self.updateCurrentLimits() #maybe put this down to else:
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# calculate delta (relative values in axis)
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old_x, old_y = self.press_rel
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xdiff = gui_event.x - old_x
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@ -1380,125 +1357,140 @@ class PylotCanvas(FigureCanvas):
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component='*', nth_sample=1, iniPick=None, verbosity=0,
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plot_additional=False, additional_channel=None, scaleToChannel=None,
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snr=None):
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def get_wf_dict(data: Stream = Stream(), linecolor = 'k', offset: float = 0., **plot_kwargs):
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return dict(data=data, linecolor=linecolor, offset=offset, plot_kwargs=plot_kwargs)
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ax = self.prepare_plot()
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self.clearPlotDict()
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wfstart, wfend = self.get_wf_range(wfdata)
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compclass = self.get_comp_class()
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plot_streams = self.get_plot_streams(wfdata, wfdata_compare, component, compclass)
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st_main = plot_streams['wfdata']['data']
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if mapping:
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plot_positions = self.calcPlotPositions(st_main, compclass)
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nslc = self.get_sorted_nslc(st_main)
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nmax = self.plot_traces(ax, plot_streams, nslc, wfstart, mapping, plot_positions,
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scaleToChannel, noiselevel, scaleddata, nth_sample, verbosity)
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if plot_additional and additional_channel:
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self.plot_additional_trace(ax, wfdata, additional_channel, scaleToChannel,
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scaleddata, nth_sample, wfstart)
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self.finalize_plot(ax, wfstart, wfend, nmax, zoomx, zoomy, iniPick, title, snr)
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def prepare_plot(self):
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ax = self.axes[0]
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ax.cla()
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return ax
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self.clearPlotDict()
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wfstart, wfend = full_range(wfdata)
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nmax = 0
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def get_wf_range(self, wfdata):
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return full_range(wfdata)
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def get_comp_class(self):
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settings = QSettings()
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compclass = SetChannelComponents.from_qsettings(settings)
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return SetChannelComponents.from_qsettings(settings)
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def get_plot_streams(self, wfdata, wfdata_compare, component, compclass):
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def get_wf_dict(data=Stream(), linecolor='k', offset=0., **plot_kwargs):
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return dict(data=data, linecolor=linecolor, offset=offset, plot_kwargs=plot_kwargs)
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linecolor = (0., 0., 0., 1.) if not self.style else self.style['linecolor']['rgba_mpl']
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plot_streams = {
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'wfdata': get_wf_dict(linecolor=linecolor, linewidth=0.7),
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'wfdata_comp': get_wf_dict(offset=0.1, linecolor='b', alpha=0.7, linewidth=0.5)
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}
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plot_streams = dict(wfdata=get_wf_dict(linecolor=linecolor, linewidth=0.7),
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wfdata_comp=get_wf_dict(offset=0.1, linecolor='b', alpha=0.7, linewidth=0.5))
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if not component == '*':
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if component != '*':
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alter_comp = compclass.getCompPosition(component)
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# alter_comp = str(alter_comp[0])
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plot_streams['wfdata']['data'] = wfdata.select(component=component)
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plot_streams['wfdata']['data'] += wfdata.select(component=alter_comp)
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plot_streams['wfdata']['data'] = wfdata.select(component=component) + wfdata.select(component=alter_comp)
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if wfdata_compare:
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plot_streams['wfdata_comp']['data'] = wfdata_compare.select(component=component)
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plot_streams['wfdata_comp']['data'] += wfdata_compare.select(component=alter_comp)
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plot_streams['wfdata_comp']['data'] = wfdata_compare.select(
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component=component) + wfdata_compare.select(component=alter_comp)
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else:
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plot_streams['wfdata']['data'] = wfdata
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if wfdata_compare:
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plot_streams['wfdata_comp']['data'] = wfdata_compare
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st_main = plot_streams['wfdata']['data']
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return plot_streams
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if mapping:
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plot_positions = self.calcPlotPositions(st_main, compclass)
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# list containing tuples of network, station, channel and plot position (for sorting)
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nslc = []
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for plot_pos, trace in enumerate(st_main):
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if not trace.stats.channel[-1] in ['Z', 'N', 'E', '1', '2', '3']:
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print('Warning: Unrecognized channel {}'.format(trace.stats.channel))
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continue
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nslc.append(trace.get_id())
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nslc.sort()
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nslc.reverse()
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def get_sorted_nslc(self, st_main):
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nslc = [trace.get_id() for trace in st_main if trace.stats.channel[-1] in ['Z', 'N', 'E', '1', '2', '3']]
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nslc.sort(reverse=True)
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return nslc
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def plot_traces(self, ax, plot_streams, nslc, wfstart, mapping, plot_positions, scaleToChannel, noiselevel,
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scaleddata, nth_sample, verbosity):
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nmax = 0
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for n, seed_id in enumerate(nslc):
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network, station, location, channel = seed_id.split('.')
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for wf_name, wf_dict in plot_streams.items():
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st_select = wf_dict.get('data')
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if not st_select:
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continue
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st = st_select.select(id=seed_id)
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trace = st[0].copy()
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trace = st_select.select(id=seed_id)[0].copy()
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if mapping:
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n = plot_positions[trace.stats.channel]
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if n > nmax:
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nmax = n
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if verbosity:
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msg = 'plotting %s channel of station %s' % (channel, station)
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print(msg)
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stime = trace.stats.starttime - wfstart
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time_ax = prep_time_axis(stime, trace)
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if time_ax is not None:
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if scaleToChannel:
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st_scale = wfdata.select(channel=scaleToChannel)
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if st_scale:
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tr = st_scale[0]
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(tr.data)) * 2)
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scaleddata = True
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if not scaleddata:
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(trace.data)) * 2)
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print(f'plotting {channel} channel of station {station}')
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time_ax = prep_time_axis(trace.stats.starttime - wfstart, trace)
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self.plot_trace(ax, trace, time_ax, wf_dict, n, scaleToChannel, noiselevel, scaleddata, nth_sample)
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self.setPlotDict(n, seed_id)
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return nmax
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offset = wf_dict.get('offset')
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def plot_trace(self, ax, trace, time_ax, wf_dict, n, scaleToChannel, noiselevel, scaleddata, nth_sample):
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if time_ax is not None:
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if scaleToChannel:
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self.scale_trace(trace, scaleToChannel)
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scaleddata = True
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if not scaleddata:
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(trace.data)) * 2)
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offset = wf_dict.get('offset')
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times = [time for index, time in enumerate(time_ax) if not index % nth_sample]
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data = [datum + n + offset for index, datum in enumerate(trace.data) if not index % nth_sample]
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ax.axhline(n, color="0.5", lw=0.5)
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ax.plot(times, data, color=wf_dict.get('linecolor'), **wf_dict.get('plot_kwargs'))
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if noiselevel is not None:
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for level in [-noiselevel[channel], noiselevel[channel]]:
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ax.plot([time_ax[0], time_ax[-1]],
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[n + level, n + level],
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color=wf_dict.get('linecolor'),
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linestyle='dashed')
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self.setPlotDict(n, seed_id)
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if plot_additional and additional_channel:
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compare_stream = wfdata.select(channel=additional_channel)
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if compare_stream:
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trace = compare_stream[0]
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if scaleToChannel:
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st_scale = wfdata.select(channel=scaleToChannel)
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if st_scale:
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tr = st_scale[0]
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(tr.data)) * 2)
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scaleddata = True
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if not scaleddata:
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(trace.data)) * 2)
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time_ax = prep_time_axis(stime, trace)
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times = [time for index, time in enumerate(time_ax) if not index % nth_sample]
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p_data = compare_stream[0].data
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# #normalize
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# p_max = max(abs(p_data))
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# p_data /= p_max
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for index in range(3):
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ax.plot(times, p_data, color='red', alpha=0.5, linewidth=0.7)
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p_data += 1
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times = [time for index, time in enumerate(time_ax) if not index % nth_sample]
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data = [datum + n + offset for index, datum in enumerate(trace.data) if not index % nth_sample]
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ax.axhline(n, color="0.5", lw=0.5)
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ax.plot(times, data, color=wf_dict.get('linecolor'), **wf_dict.get('plot_kwargs'))
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if noiselevel is not None:
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self.plot_noise_level(ax, time_ax, noiselevel, channel, n, wf_dict.get('linecolor'))
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def scale_trace(self, trace, scaleToChannel):
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st_scale = wfdata.select(channel=scaleToChannel)
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if st_scale:
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tr = st_scale[0]
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(tr.data)) * 2)
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def plot_noise_level(self, ax, time_ax, noiselevel, channel, n, linecolor):
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for level in [-noiselevel[channel], noiselevel[channel]]:
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ax.plot([time_ax[0], time_ax[-1]], [n + level, n + level], color=linecolor, linestyle='dashed')
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def plot_additional_trace(self, ax, wfdata, additional_channel, scaleToChannel, scaleddata, nth_sample, wfstart):
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compare_stream = wfdata.select(channel=additional_channel)
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if compare_stream:
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trace = compare_stream[0]
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if scaleToChannel:
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self.scale_trace(trace, scaleToChannel)
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scaleddata = True
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if not scaleddata:
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trace.detrend('constant')
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trace.normalize(np.max(np.abs(trace.data)) * 2)
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time_ax = prep_time_axis(trace.stats.starttime - wfstart, trace)
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self.plot_additional_data(ax, trace, time_ax, nth_sample)
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def plot_additional_data(self, ax, trace, time_ax, nth_sample):
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times = [time for index, time in enumerate(time_ax) if not index % nth_sample]
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p_data = trace.data
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for index in range(3):
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ax.plot(times, p_data, color='red', alpha=0.5, linewidth=0.7)
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p_data += 1
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def finalize_plot(self, ax, wfstart, wfend, nmax, zoomx, zoomy, iniPick, title, snr):
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if iniPick:
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ax.vlines(iniPick, ax.get_ylim()[0], ax.get_ylim()[1],
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colors='m', linestyles='dashed',
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linewidth=2)
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xlabel = 'seconds since {0}'.format(wfstart)
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ax.vlines(iniPick, ax.get_ylim()[0], ax.get_ylim()[1], colors='m', linestyles='dashed', linewidth=2)
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xlabel = f'seconds since {wfstart}'
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ylabel = ''
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self.updateWidget(xlabel, ylabel, title)
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self.setXLims(ax, [0, wfend - wfstart])
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@ -1508,15 +1500,14 @@ class PylotCanvas(FigureCanvas):
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if zoomy is not None:
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self.setYLims(ax, zoomy)
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if snr is not None:
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if snr < 2:
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warning = 'LOW SNR'
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if snr < 1.5:
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warning = 'VERY LOW SNR'
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ax.text(0.1, 0.9, 'WARNING - {}'.format(warning), ha='center', va='center', transform=ax.transAxes,
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color='red')
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self.plot_snr_warning(ax, snr)
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self.draw()
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def plot_snr_warning(self, ax, snr):
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if snr < 2:
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warning = 'LOW SNR' if snr >= 1.5 else 'VERY LOW SNR'
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ax.text(0.1, 0.9, f'WARNING - {warning}', ha='center', va='center', transform=ax.transAxes, color='red')
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@staticmethod
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def getXLims(ax):
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return ax.get_xlim()
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