elephant.spade.pattern_set_reduction¶

elephant.spade.
pattern_set_reduction
(concepts, ns_signatures, winlen, spectrum, h_subset_filtering=0, k_superset_filtering=0, l_covered_spikes=0, min_spikes=2, min_occ=2)[source]¶ Takes a list concepts and performs pattern set reduction (PSR).
PSR determines which patterns in concepts_psf are statistically significant given any other pattern, on the basis of the pattern size and occurrence count (“support”). Only significant patterns are retained. The significance of a pattern A is evaluated through its signature , where is the size and  the support of A, by either of:
 subset filtering: any pattern B is discarded if concepts contains a superset A of B such that
 superset filtering: any pattern A is discarded if concepts contains a subset B of A such that
 coveredspikes criterion: for any two patterns A, B with , B is discarded if , A is discarded otherwise;
 combined filtering: combines the three procedures above: takes a list concepts (see output psf function) and performs combined filtering based on the signature (z, c) of each pattern, where z is the pattern size and c the pattern support.
For any two patterns A and B in concepts_psf such that , check:
 , and
 .
Then:
 if 1) and not 2): discard B
 if 2) and not 1): discard A
 if 1) and 2): discard B if
 , otherwise discard A
 if neither 1) nor 2): keep both patterns
Assumptions/Approximations:
 a pair of concepts cannot cause one another to be rejected
 if two concepts overlap more than min_occ times, one of them can account for all occurrences of the other one if it passes the filtering
Parameters:  conceptslist
List of concepts, each consisting in its intent and extent
 ns_signatureslist
A list of nonsignificant pattern signatures (z, c)
 winlenint
The size (number of bins) of the sliding window used for the analysis. The maximal length of a pattern (delay between first and last spike) is then given by winlen*bin_size.
 spectrum{‘#’, ‘3d#’}
Define the signature of the patterns.
 ‘#’: pattern spectrum using the as signature the pair:
(number of spikes, number of occurrences)
 ‘3d#’: pattern spectrum using the as signature the triplets:
(number of spikes, number of occurrence, difference between last and first spike of the pattern)
 h_subset_filteringint, optional
Correction parameter for subset filtering Default: 0
 k_superset_filteringint, optional
Correction parameter for superset filtering Default: 0
 l_covered_spikesint, optional
Correction parameter for coveredspikes criterion Default: 0
 min_spikesint, optional
Minimum pattern size Default: 2
 min_occint, optional
Minimum number of pattern occurrences Default: 2
Returns:  tuple
A tuple containing the elements of the input argument that are significant according to combined filtering.