[edit] probability density function superclass implemented due to the different character of these functions

pylot/core/util/pdf.py

@@ -109,6 +109,50 @@ class ProbabilityDensityFunction(object):
 
     version = __version__
 
+    def __init__(self, x, pdf):
+        self.axis = x
+        self.data = pdf
+
+    def __add__(self, other):
+        assert isinstance(other, ProbabilityDensityFunction), \
+            'both operands must be of type ProbabilityDensityFunction'
+        if self.sampling_rate() == other.sampling_rate():
+            max = np.maximum(self.axis, other.axis)
+            x = np.arange(-max, max + self.sampling_rate(), self.sampling_rate())
+        else:
+            raise ValueError('Sampling rates do not match!')
+
+        pdf1 = self.data
+
+        return ProbabilityDensityFunction(x, pdf)
+
+    def __sub__(self, other):
+        pass
+
+    def __nonzero__(self):
+        return True
+
+    @property
+    def data(self):
+        return self.data
+
+    @data.setter
+    def data(self, pdf):
+        self.data = np.array(pdf)
+
+    @property
+    def axis(self):
+        return self.axis
+
+    @axis.setter
+    def axis(self, x):
+        self.axis = np.array(x)
+
+    def sampling_rate(self):
+        return self.axis[1] - self.axis[0]
+
+class PickPDF(ProbabilityDensityFunction):
+
     def __init__(self, x, lbound, midpoint, rbound, decfact=0.01, type='gauss'):
         '''
         Initialize a new ProbabilityDensityFunction object. Takes arguments x,
@@ -126,15 +170,9 @@ class ProbabilityDensityFunction(object):
          branches
         '''
 
-        self.axis = np.array(x)
-        self.nodes = dict(lbound=lbound, midpoint=midpoint, rbound=rbound, eta=decfact)
+        self.nodes = dict(te=lbound, tm=midpoint, tl=rbound, eta=decfact)
         self.type = type
-
-    def __add__(self, other):
-        pass
-
-    def __sub__(self, other):
-        pass
+        super(PickPDF, self).__init__(x, self.pdf())
 
     @property
     def type(self):
@@ -147,5 +185,8 @@ class ProbabilityDensityFunction(object):
     def params(self):
         return parameter[self.type](**self.nodes)
 
-    def data(self):
-        return branches[self.type](self.axis, self.nodes['midpoint'], *self.params())
+    def get(self, key):
+        return self.nodes[key]
+
+    def pdf(self):
+        return branches[self.type](self.axis, self.get('tm'), *self.params())