[cleanup] pycharm code inspection

pylot/core/pick/charfuns.py

@@ -26,7 +26,7 @@ class CharacteristicFunction(object):
     SuperClass for different types of characteristic functions.
     '''
 
-    def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None, stealthMode=False):
+    def __init__(self, data, cut, t2=None, order=None, t1=None, fnoise=None):
         '''
         Initialize data type object with information from the original
         Seismogram.
@@ -63,7 +63,6 @@ class CharacteristicFunction(object):
         self.calcCF(self.getDataArray())
         self.arpara = np.array([])
         self.xpred = np.array([])
-        self._stealthMode = stealthMode
 
     def __str__(self):
         return '''\n\t{name} object:\n
@@ -137,9 +136,6 @@ class CharacteristicFunction(object):
     def getXCF(self):
         return self.xcf
 
-    def _getStealthMode(self):
-        return self._stealthMode()
-
     def getDataArray(self, cut=None):
         '''
         If cut times are given, time series is cut from cut[0] (start time)
@@ -224,8 +220,6 @@ class AICcf(CharacteristicFunction):
 
     def calcCF(self, data):
 
-        # if self._getStealthMode() is False:
-        #    print 'Calculating AIC ...'
         x = self.getDataArray()
         xnp = x[0].data
         nn = np.isnan(xnp)
@@ -264,13 +258,9 @@ class HOScf(CharacteristicFunction):
         if len(nn) > 1:
             xnp[nn] = 0
         if self.getOrder() == 3:  # this is skewness
-            # if self._getStealthMode() is False:
-            #    print 'Calculating skewness ...'
             y = np.power(xnp, 3)
             y1 = np.power(xnp, 2)
         elif self.getOrder() == 4:  # this is kurtosis
-            # if self._getStealthMode() is False:
-            #    print 'Calculating kurtosis ...'
             y = np.power(xnp, 4)
             y1 = np.power(xnp, 2)