[edit] changed calculation of difference pdf to include large differences also
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@ -142,7 +142,9 @@ class ProbabilityDensityFunction(object):
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x0, incr, npts, pdf_self, pdf_other = self.rearrange(other)
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x0, incr, npts, pdf_self, pdf_other = self.rearrange(other)
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pdf = np.correlate(pdf_self, pdf_other, 'same') * incr
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pdf = np.correlate(pdf_self, pdf_other, 'full') * incr
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npts = len(pdf)
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# shift axis values for correct plotting
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# shift axis values for correct plotting
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midpoint = npts / 2
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midpoint = npts / 2
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@ -181,6 +181,9 @@ class ComparisonDialog(QDialog):
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if name in self.widgets.keys():
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if name in self.widgets.keys():
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self._widgets[name] = widget
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self._widgets[name] = widget
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def clf(self):
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self.canvas.figure.clf()
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def hasvalue(self, sender):
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def hasvalue(self, sender):
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text = sender.currentText()
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text = sender.currentText()
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index = sender.findText(text.upper())
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index = sender.findText(text.upper())
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@ -204,9 +207,9 @@ class ComparisonDialog(QDialog):
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def plotcomparison(self):
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def plotcomparison(self):
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from matplotlib import gridspec
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from matplotlib import gridspec
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_axes = self.canvas.figure.add_subplot(111)
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_gs = gridspec.GridSpec(3, 2)
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_gs = gridspec.GridSpec(3, 2)
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self.clf()
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_axes = self.canvas.figure.add_subplot(_gs[0:2, :])
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_axes = self.canvas.figure.add_subplot(_gs[0:2, :])
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_ax1 = self.canvas.figure.add_subplot(_gs[2, 0])
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_ax1 = self.canvas.figure.add_subplot(_gs[2, 0])
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_ax2 = self.canvas.figure.add_subplot(_gs[2, 1])
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_ax2 = self.canvas.figure.add_subplot(_gs[2, 1])
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@ -232,6 +235,7 @@ class ComparisonDialog(QDialog):
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pdf_a = self.data.get('auto')[station][phase]
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pdf_a = self.data.get('auto')[station][phase]
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pdf_m = self.data.get('manu')[station][phase]
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pdf_m = self.data.get('manu')[station][phase]
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xauto, yauto, stdauto, expauto = pdf_a.axis, pdf_a.data, \
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xauto, yauto, stdauto, expauto = pdf_a.axis, pdf_a.data, \
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pdf_a.standard_deviation(), \
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pdf_a.standard_deviation(), \
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pdf_a.expectation()
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pdf_a.expectation()
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@ -240,8 +244,23 @@ class ComparisonDialog(QDialog):
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pdf_m.expectation()
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pdf_m.expectation()
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_ax1.plot(xauto, yauto)
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_ax1.plot(xauto, yauto)
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mannotation = "probability density for manual pick\n" \
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"expectation: {exp}\n" \
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"std: {std}".format(std=stdmanu, exp=expmanu)
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_anno = _ax1.annotate(mannotation, xy=(.05, .5), xycoords='axes '
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'fraction')
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bbox_props = dict(boxstyle='round', facecolor='lightgrey', alpha=.7)
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_anno.set_bbox(bbox_props)
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_ax2.plot(xmanu, ymanu)
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_ax2.plot(xmanu, ymanu)
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aannotation = "probability density for automatic pick\n" \
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"expectation: {exp}\n" \
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"std: {std}".format(std=stdauto, exp=expauto)
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_anno = _ax2.annotate(aannotation, xy=(.05, .5), xycoords='axes '
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'fraction')
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bbox_props = dict(boxstyle='round', facecolor='lightgrey', alpha=.7)
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_anno.set_bbox(bbox_props)
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_gs.update(wspace=0.5, hspace=0.5)
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_gs.update(wspace=0.5, hspace=0.5)
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