changed isi distance profile to abs values

3 files changed, 6 insertions, 16 deletions

diff --git a/pyspike/cython_distance.pyx b/pyspike/cython_distance.pyx
index ccf8060..178fcba 100644
--- a/pyspike/cython_distance.pyx
+++ b/pyspike/cython_distance.pyx
@@ -60,7 +60,7 @@ def isi_distance_cython(double[:] s1,
     isi_values = np.empty(N1+N2-1)
 
     with nogil: # release the interpreter to allow multithreading
-        isi_values[0] = (nu1-nu2)/fmax(nu1,nu2)
+        isi_values[0] = fabs(nu1-nu2)/fmax(nu1, nu2)
         index1 = 0
         index2 = 0
         index = 1
@@ -88,7 +88,7 @@ def isi_distance_cython(double[:] s1,
                 nu1 = s1[index1+1]-s1[index1]
                 nu2 = s2[index2+1]-s2[index2]            
             # compute the corresponding isi-distance
-            isi_values[index] = (nu1 - nu2) / fmax(nu1, nu2)
+            isi_values[index] = fabs(nu1 - nu2) / fmax(nu1, nu2)
             index += 1
         # the last event is the interval end
         spike_events[index] = s1[N1]
diff --git a/pyspike/distances.py b/pyspike/distances.py
index 3b9fe1f..08d0ed8 100644
--- a/pyspike/distances.py
+++ b/pyspike/distances.py
@@ -213,7 +213,7 @@ def isi_distance_matrix(spike_trains, indices=None):
     
     distance_matrix = np.zeros((len(indices), len(indices)))
     for i, j in pairs:
-        d = isi_distance(spike_trains[i], spike_trains[j]).abs_avrg()
+        d = isi_distance(spike_trains[i], spike_trains[j]).avrg()
         distance_matrix[i, j] = d
         distance_matrix[j, i] = d
     return distance_matrix
diff --git a/pyspike/function.py b/pyspike/function.py
index 7722cc3..bd3e2d5 100644
--- a/pyspike/function.py
+++ b/pyspike/function.py
@@ -18,7 +18,7 @@ import numpy as np
 ##############################################################
 class PieceWiseConstFunc:
     """ A class representing a piece-wise constant function. """
-    
+
     def __init__(self, x, y):
         """ Constructs the piece-wise const function.
         Args:
@@ -66,16 +66,6 @@ class PieceWiseConstFunc:
         return np.sum((self.x[1:]-self.x[:-1]) * self.y) / \
             (self.x[-1]-self.x[0])
 
-    def abs_avrg(self):
-        """ Computes the average of the abs value of the piece-wise const
-        function:
-        a = 1/T int |f(x)| dx where T is the length of the interval.
-        Returns:
-        - the average a.
-        """
-        return np.sum((self.x[1:]-self.x[:-1]) * np.abs(self.y)) / \
-            (self.x[-1]-self.x[0])
-
     def add(self, f):
         """ Adds another PieceWiseConst function to this function.
         Note: only functions defined on the same interval can be summed.
@@ -84,7 +74,7 @@ class PieceWiseConstFunc:
         """
         assert self.x[0] == f.x[0], "The functions have different intervals"
         assert self.x[-1] == f.x[-1], "The functions have different intervals"
-        
+
         # python implementation
         # from python_backend import add_piece_wise_const_python
         # self.x, self.y = add_piece_wise_const_python(self.x, self.y,
@@ -107,7 +97,7 @@ class PieceWiseConstFunc:
 ##############################################################
 class PieceWiseLinFunc:
     """ A class representing a piece-wise linear function. """
-    
+
     def __init__(self, x, y1, y2):
         """ Constructs the piece-wise linear function.
         Args: