implied stealth mode
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@ -24,7 +24,7 @@ class CharacteristicFunction(object):
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'''
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SuperClass for different types of characteristic functions.
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'''
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def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None):
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def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None, stealthMode=False):
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'''
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Initialize data type object with information from the original
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Seismogram.
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@ -61,6 +61,7 @@ class CharacteristicFunction(object):
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self.calcCF(self.getDataArray())
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self.arpara = np.array([])
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self.xpred = np.array([])
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self.stealthMode = stealthMode
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def __str__(self):
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return '''\n\t{name} object:\n
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@ -218,7 +219,8 @@ class AICcf(CharacteristicFunction):
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def calcCF(self, data):
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#print 'Calculating AIC ...' ## MP MP output suppressed
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if self.stealthMode is False:
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print 'Calculating AIC ...'
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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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@ -256,11 +258,13 @@ class HOScf(CharacteristicFunction):
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if len(nn) > 1:
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xnp[nn] = 0
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if self.getOrder() == 3: # this is skewness
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print 'Calculating skewness ...'
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if self.stealthMode is False:
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print 'Calculating skewness ...'
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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 ...' ## MP MP output suppressed
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if self.stealthMode is False:
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print 'Calculating kurtosis ...'
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y = np.power(xnp, 4)
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y1 = np.power(xnp, 2)
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