def plotZoneFMD(cls,
feature_data,
normalize=FMD_COMPUTE_ANNUAL_RATE,
title=''):
window = plots.createPlotWindow(cls)
fits = []
fmd = feature_data['fmd']
parameters = feature_data['parameters']
if fmd is None:
return None
if fmd.GR['fit'] is not None:
activity_ml_arr = numpy.vstack((fmd.GR['mag_fit'], fmd.GR['fit']))
fits.append({'data': activity_ml_arr, 'label': "Activity (ML)"})
central_A = utils.centralValueOfList(parameters['activity_a'])
central_b = utils.centralValueOfList(parameters['activity_b'])
a_value = atticivy.activity2aValue(central_A, central_b,
parameters['activity_mmin'])
activity_rm_arr = computeFMDArray(a_value,
central_b,
fmd.fmd[0, :],
timespan=cls.catalog_time_span[0])
fits.append({'data': activity_rm_arr, 'label': "Activity (RM)"})
# new FMD plot
figure = fmd.plot(imgfile=None,
fits=fits,
fmdtype='cumulative',
normalize=normalize)
if title == '':
title = parameters['plot_title_fmd']
canvas = plots.PlotCanvas(figure, title=title)
canvas.draw()
# FMD plot window, re-populate layout
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure
def plotRecurrence(cls, feature, feature_data=None, title=''):
window = plots.createPlotWindow(cls)
pr = cls.fault_source_layer.dataProvider()
activity_min_name = features.FAULT_SOURCE_ATTR_ACTIVITYRATE_MIN ['name']
activity_max_name = features.FAULT_SOURCE_ATTR_ACTIVITYRATE_MAX ['name']
activity_min_idx = pr.fieldNameIndex(activity_min_name)
activity_max_idx = pr.fieldNameIndex(activity_max_name)
distrostring_min = str(feature[activity_min_idx].toString())
distrostring_max = str(feature[activity_max_idx].toString())
distrodata_min = utils.distrostring2plotdata(distrostring_min)
distrodata_max = utils.distrostring2plotdata(distrostring_max)
distrodata = numpy.vstack((distrodata_min, distrodata_max[1, :]))
fits = []
if feature_data['fmd'].GR['fit'] is not None:
activity_ml_arr = numpy.vstack((
feature_data['fmd'].GR['mag_fit'],
feature_data['fmd'].GR['fit'] / cls.catalog_time_span[0]))
fits.append({'data': activity_ml_arr, 'label': "FBZ (ML)"})
# scale EQ rates per year
fmd = numpy.vstack((
feature_data['fmd'].fmd[0, :],
feature_data['fmd'].fmd[1, :] / cls.catalog_time_span[0],
feature_data['fmd'].fmd[2, :] / cls.catalog_time_span[0]))
# new recurrence FMD plot (returns figure)
plot = qpplot.FMDPlotRecurrence()
figure = plot.plot(imgfile=None, occurrence=distrodata, fmd=fmd,
fits=fits)
if title == '':
title = feature_data['parameters']['plot_title_recurrence']
canvas = plots.PlotCanvas(figure, title=title)
canvas.draw()
# FMD plot window, re-populate layout
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure
def plotRecurrence(cls, feature, feature_data=None, title=''):
window = plots.createPlotWindow(cls)
pr = cls.fault_source_layer.dataProvider()
activity_min_name = features.FAULT_SOURCE_ATTR_ACTIVITYRATE_MIN['name']
activity_max_name = features.FAULT_SOURCE_ATTR_ACTIVITYRATE_MAX['name']
activity_min_idx = pr.fieldNameIndex(activity_min_name)
activity_max_idx = pr.fieldNameIndex(activity_max_name)
distrostring_min = str(feature[activity_min_idx].toString())
distrostring_max = str(feature[activity_max_idx].toString())
distrodata_min = utils.distrostring2plotdata(distrostring_min)
distrodata_max = utils.distrostring2plotdata(distrostring_max)
distrodata = numpy.vstack((distrodata_min, distrodata_max[1, :]))
fits = []
if feature_data['fmd'].GR['fit'] is not None:
activity_ml_arr = numpy.vstack(
(feature_data['fmd'].GR['mag_fit'],
feature_data['fmd'].GR['fit'] / cls.catalog_time_span[0]))
fits.append({'data': activity_ml_arr, 'label': "FBZ (ML)"})
# scale EQ rates per year
fmd = numpy.vstack(
(feature_data['fmd'].fmd[0, :],
feature_data['fmd'].fmd[1, :] / cls.catalog_time_span[0],
feature_data['fmd'].fmd[2, :] / cls.catalog_time_span[0]))
# new recurrence FMD plot (returns figure)
plot = qpplot.FMDPlotRecurrence()
figure = plot.plot(imgfile=None, occurrence=distrodata, fmd=fmd, fits=fits)
if title == '':
title = feature_data['parameters']['plot_title_recurrence']
canvas = plots.PlotCanvas(figure, title=title)
canvas.draw()
# FMD plot window, re-populate layout
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure
def updatePlotMomentRateArea(cls, parameters):
window = plots.createPlotWindow(cls)
# new moment rate plot
plot = plots.MomentRateComparisonPlotArea()
figure = plot.plot(imgfile=None, data=parameters)
canvas = plots.PlotCanvas(figure, title=parameters['plot_title_fmd'])
canvas.draw()
# plot widget
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure
def updatePlotMomentRateArea(cls, parameters):
window = plots.createPlotWindow(cls)
# new moment rate plot
plot = plots.MomentRateComparisonPlotArea()
figure = plot.plot(imgfile=None, data=parameters)
canvas = plots.PlotCanvas(figure, title=parameters['plot_title_fmd'])
canvas.draw()
# plot widget
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure
def plotZoneFMD(cls, feature_data, normalize=FMD_COMPUTE_ANNUAL_RATE,
title=''):
window = plots.createPlotWindow(cls)
fits = []
fmd = feature_data['fmd']
parameters = feature_data['parameters']
if fmd is None:
return None
if fmd.GR['fit'] is not None:
activity_ml_arr = numpy.vstack((fmd.GR['mag_fit'], fmd.GR['fit']))
fits.append({'data': activity_ml_arr, 'label': "Activity (ML)"})
central_A = utils.centralValueOfList(parameters['activity_a'])
central_b = utils.centralValueOfList(parameters['activity_b'])
a_value = atticivy.activity2aValue(central_A, central_b,
parameters['activity_mmin'])
activity_rm_arr = computeFMDArray(a_value, central_b, fmd.fmd[0, :],
timespan=cls.catalog_time_span[0])
fits.append({'data': activity_rm_arr, 'label': "Activity (RM)"})
# new FMD plot
figure = fmd.plot(imgfile=None, fits=fits, fmdtype='cumulative',
normalize=normalize)
if title == '':
title = parameters['plot_title_fmd']
canvas = plots.PlotCanvas(figure, title=title)
canvas.draw()
# FMD plot window, re-populate layout
window.layoutPlot.addWidget(canvas)
toolbar = plots.createToolbar(canvas, window)
window.layoutPlot.addWidget(toolbar)
return figure