cogpy.decomposition.match

Cross-recording factor matching via Hungarian algorithm.

Matches factors across multiple SpatSpecDecomposition instances by maximising spatial-spectral similarity, using scipy.optimize.linear_sum_assignment.

Functions

compress_fac_match_df(match_df, nrec, nfac)
concat_ss_series(ss_series)	Concatenate a series of SpatSpecDecompositions along a rec dim.
cutoff_lowsimil(match_df[, threshold])
get_fac_match_df(ss_series, freq_threshold, ...)
get_match_fac_ref(simil_arr, ...[, ...])	Get factor match DataFrame for a given reference recording.
get_remapping(simil_arr, nrec)	Compute optimal factor remapping via linear sum assignment.
get_similx_flat(simil_arr, nrec)	Flatten similarity array into a stacked xr.DataArray.
match_factors(spatspec_series, nrec, nfac[, ...])	Match factors across recordings and return matched + centroid results.
match_metric(x, eps)
optimal_refrec(match_fac_ref[, eps])	Return the recording index with highest mean match metric.
remap_fac_xr(arrx, remap)
remap_ss(ss, fac_remap)	Remap factors of a SpatSpecDecomposition.
set_offdiag_elements(a, val)