dominosee.es.create_null_model_from_indices

dominosee.es.create_null_model_from_indices(da_timeIndex, tm, max_events, significances=[0.05], samples=2000, min_es=None, parallel=True)[source]

Creates a null model for event synchronization based on actual time indices

Return type:

DataArray

Parameters:

da_timeIndexxr.DataArray

Array of time indices where events occur in datasets of two locations

tmint

Maximum time interval parameter for ES

max_eventsint, tuple of two ints, or numpy.ndarray

Maximum number of events to consider. If a single int or 1D array with one element, calculates over [max_events, max_events]. If a tuple or 1D array with two elements, calculates over [max_events[0], max_events[1]].

significancesfloat, or list, optional

Significance levels to calculate thresholds for

samplesint, optional

Number of samples to generate, by default 2000

min_esint, optional

Minimum number of event synchronizations, by default None

parallelbool, optional

Whether to use parallelization, by default True

Returns:

: da_critical_values : xr.DataArray

List of arrays containing critical values for event synchronizations