elephant.statistics.lvr¶

elephant.statistics.
lvr
(time_intervals, R=array(5.) * ms, with_nan=False)[source]¶ Calculate the measure of revised local variation LvR for a sequence of time intervals between events [st5].
Given a vector containing a sequence of intervals, the LvR is defined as:
The LvR is a revised version of the Lv, with enhanced invariance to firing rate fluctuations by introducing a refractoriness constant R. The LvR with R=5ms was shown to outperform other ISI variability measures in spike trains with firing rate fluctuations and sensory stimuli [st5].
Parameters:  time_intervalspq.Quantity or np.ndarray or list
Vector of consecutive time intervals. Must have time units, if not unit is passed ms are assumed.
 Rpq.Quantity or int or float
Refractoriness constant (R >= 0). If no quantity is passed ms are assumed. Default: 5 ms
 with_nanbool, optional
If True, LvR of a spike train with less than two spikes results in a np.NaN value and a warning is raised. If False, a ValueError exception is raised with a spike train with less than two spikes. Default: True
Returns:  float
The LvR of the interspike interval of the input sequence.
Raises:  ValueError
If an empty list is specified, or if the sequence has less than two entries and with_nan is False.
If a matrix is passed to the function. Only vector inputs are supported.
Warns:  UserWarning
If with_nan is True and the lvr is calculated for a spike train with less than two spikes, generating a np.NaN. If R is passed without any units attached milliseconds are assumed.
Examples
>>> from elephant import statistics >>> statistics.lvr([0.3, 4.5, 6.7, 9.3], R=0.005) 0.833907445980624