diff options
Diffstat (limited to 'pyspike/DiscreteFunc.py')
| -rw-r--r-- | pyspike/DiscreteFunc.py | 43 |
1 files changed, 23 insertions, 20 deletions
diff --git a/pyspike/DiscreteFunc.py b/pyspike/DiscreteFunc.py index a8c054e..4fd496d 100644 --- a/pyspike/DiscreteFunc.py +++ b/pyspike/DiscreteFunc.py @@ -137,9 +137,8 @@ class DiscreteFunc(object): :rtype: pair of float """ - if len(self.y) <= 2: - # no actual values in the profile, return spike sync of 1 - return 1.0, 1.0 + value = 0.0 + multiplicity = 0.0 def get_indices(ival): """ Retuns the indeces surrounding the given interval""" @@ -152,25 +151,29 @@ class DiscreteFunc(object): if interval is None: # no interval given, integrate over the whole spike train # don't count the first value, which is zero by definition - return (1.0 * np.sum(self.y[1:-1]), np.sum(self.mp[1:-1])) - - # check if interval is as sequence - assert isinstance(interval, collections.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): - # find the indices corresponding to the interval - start_ind, end_ind = get_indices(interval) - return (np.sum(self.y[start_ind:end_ind]), - np.sum(self.mp[start_ind:end_ind])) + value = 1.0 * np.sum(self.y[1:-1]) + multiplicity = np.sum(self.mp[1:-1]) else: - value = 0.0 - multiplicity = 0.0 - for ival in interval: + # check if interval is as sequence + assert isinstance(interval, collections.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): # find the indices corresponding to the interval - start_ind, end_ind = get_indices(ival) - value += np.sum(self.y[start_ind:end_ind]) - multiplicity += np.sum(self.mp[start_ind:end_ind]) + start_ind, end_ind = get_indices(interval) + value = np.sum(self.y[start_ind:end_ind]) + multiplicity = np.sum(self.mp[start_ind:end_ind]) + else: + for ival in interval: + # find the indices corresponding to the interval + start_ind, end_ind = get_indices(ival) + value += np.sum(self.y[start_ind:end_ind]) + multiplicity += np.sum(self.mp[start_ind:end_ind]) + if multiplicity == 0.0: + # empty profile, return spike sync of 1 + value = 1.0 + multiplicity = 1.0 return (value, multiplicity) def avrg(self, interval=None): |