diff options
Diffstat (limited to 'pyspike/PieceWiseConstFunc.py')
| -rw-r--r-- | pyspike/PieceWiseConstFunc.py | 40 |
1 files changed, 26 insertions, 14 deletions
diff --git a/pyspike/PieceWiseConstFunc.py b/pyspike/PieceWiseConstFunc.py index 5ce5f27..e33c61d 100644 --- a/pyspike/PieceWiseConstFunc.py +++ b/pyspike/PieceWiseConstFunc.py @@ -5,7 +5,7 @@ from __future__ import absolute_import, print_function import numpy as np -import collections +import collections.abc import pyspike @@ -39,7 +39,7 @@ class PieceWiseConstFunc(object): ind = np.searchsorted(self.x, t, side='right') - if isinstance(t, collections.Sequence): + if isinstance(t, collections.abc.Sequence): # t is a sequence of values # correct the cases t == x[0], t == x[-1] ind[ind == 0] = 1 @@ -129,19 +129,31 @@ class PieceWiseConstFunc(object): # no interval given, integrate over the whole spike train a = np.sum((self.x[1:]-self.x[:-1]) * self.y) else: + if interval[0]>interval[1]: + raise ValueError("Invalid averaging interval: interval[0]>=interval[1]") + if interval[0]<self.x[0]: + raise ValueError("Invalid averaging interval: interval[0]<self.x[0]") + if interval[1]>self.x[-1]: + raise ValueError("Invalid averaging interval: interval[0]<self.x[-1]") # find the indices corresponding to the interval start_ind = np.searchsorted(self.x, interval[0], side='right') end_ind = np.searchsorted(self.x, interval[1], side='left')-1 - assert start_ind > 0 and end_ind < len(self.x), \ - "Invalid averaging interval" - # first the contribution from between the indices - a = np.sum((self.x[start_ind+1:end_ind+1] - - self.x[start_ind:end_ind]) * - self.y[start_ind:end_ind]) - # correction from start to first index - a += (self.x[start_ind]-interval[0]) * self.y[start_ind-1] - # correction from last index to end - a += (interval[1]-self.x[end_ind]) * self.y[end_ind] + if start_ind > end_ind: + # contribution from between two closest edges + a = (self.x[start_ind]-self.x[end_ind]) * self.y[end_ind] + # minus the part that is not within the interval + a -= ((interval[0]-self.x[end_ind])+(self.x[start_ind]-interval[1])) * self.y[end_ind] + else: + assert start_ind > 0 and end_ind < len(self.x), \ + "Invalid averaging interval" + # first the contribution from between the indices + a = np.sum((self.x[start_ind+1:end_ind+1] - + self.x[start_ind:end_ind]) * + self.y[start_ind:end_ind]) + # correction from start to first index + a += (self.x[start_ind]-interval[0]) * self.y[start_ind-1] + # correction from last index to end + a += (interval[1]-self.x[end_ind]) * self.y[end_ind] return a def avrg(self, interval=None): @@ -161,10 +173,10 @@ class PieceWiseConstFunc(object): return self.integral() / (self.x[-1]-self.x[0]) # check if interval is as sequence - assert isinstance(interval, collections.Sequence), \ + assert isinstance(interval, collections.abc.Sequence), \ "Invalid value for `interval`. None, Sequence or Tuple expected." # check if interval is a sequence of intervals - if not isinstance(interval[0], collections.Sequence): + if not isinstance(interval[0], collections.abc.Sequence): # just one interval a = self.integral(interval) / (interval[1]-interval[0]) else: |