debugged some code fragments while trying to solve the load event data problem
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@@ -218,7 +218,7 @@ class AICcf(CharacteristicFunction):
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def calcCF(self, data):
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print 'Calculating AIC ...'
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#print 'Calculating AIC ...' ## MP MP output suppressed
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x = self.getDataArray()
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xnp = x[0].data
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nn = np.isnan(xnp)
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@@ -260,7 +260,7 @@ class HOScf(CharacteristicFunction):
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y = np.power(xnp, 3)
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y1 = np.power(xnp, 2)
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elif self.getOrder() == 4: # this is kurtosis
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print 'Calculating kurtosis ...'
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#print 'Calculating kurtosis ...' ## MP MP output suppressed
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y = np.power(xnp, 4)
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y1 = np.power(xnp, 2)
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@@ -18,6 +18,7 @@ calculated after Diehl & Kissling (2009).
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:author: MAGS2 EP3 working group / Ludger Kueperkoch
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from pylot.core.pick.utils import getnoisewin, getsignalwin
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@@ -245,8 +246,7 @@ class AICPicker(AutoPicking):
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if datafit[0] >= datafit[len(datafit) - 1]:
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print 'AICPicker: Negative slope, bad onset skipped!'
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return
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self.slope = 1 / tslope * datafit[len(dataslope) - 1] - datafit[0]
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self.slope = 1 / tslope * (datafit[len(dataslope) - 1] - datafit[0])
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else:
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self.SNR = None
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@@ -43,7 +43,13 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
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LPick = None
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EPick = None
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PickError = None
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<<<<<<< Updated upstream
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print ("earllatepicker: Get earliest and latest possible pick relative to most likely pick ...")
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=======
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# MP MP ++ output suppressed
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#print 'earllatepicker: Get earliest and latest possible pick relative to most likely pick ...'
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# MP MP --
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>>>>>>> Stashed changes
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x = X[0].data
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t = np.arange(0, X[0].stats.npts / X[0].stats.sampling_rate,
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@@ -386,6 +386,9 @@ class Data(object):
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"""
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return self.evtdata
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def setEvtData(self, event):
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self.evtdata = event
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def applyEVTData(self, data, type='pick', authority_id='rub'):
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"""
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@@ -447,7 +450,10 @@ class Data(object):
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:param event:
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"""
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pass
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if not self.isNew():
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self.setEvtData(event)
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else:
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raise OverwriteError('Acutal event would be overwritten!')
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applydata = {'pick': applyPicks,
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'arrival': applyArrivals,
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@@ -105,10 +105,10 @@ class MPLWidget(FigureCanvas):
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for level in noiselevel:
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self.getAxes().plot([time_ax[0], time_ax[-1]],
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[level, level], '--k')
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xlabel = 'seconds since {0}'.format(wfstart)
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ylabel = ''
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self.updateWidget(xlabel, ylabel, title)
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self.setPlotDict(n, (station, channel))
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xlabel = 'seconds since {0}'.format(wfstart)
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ylabel = ''
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self.updateWidget(xlabel, ylabel, title)
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self.setXLims([0, wfend - wfstart])
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self.setYLims([-0.5, n + 0.5])
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if zoomx is not None:
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