Fix: Spike prior was applied too often in SIC, filter output norm was not updated
Simulation specific: Always use full epoch and don't care about filter norm
Hybrid implementation works
Treat corner cases: If the largest overlap template is detected, discard and use regular SIC. This removes errors occuring on sligthly larger taus than the maximum overlap template tau.
Fixed overlaps(), verbose plots
Fixed for general use
Corrected minimum SNR
Sic guard parameter (determines if norm of residuals is checked)
Spike prior bias needs to be applied in both directions
Handle deactivated filters correctly when using overlap templates
Fixed: Spikes with only a single sample discriminant sample above noise were not being found
neo compatibility fixes:
* sortrows needs array in continuous memory to work
* extract epochs has some weird behaviour when astyping float spiketrains to int64 (seems to apply floor ops for numbers represented like n.99999999 => n)
* removed deprecated decorator
Sort spike times before returning
Faster epoch_merge when using min_dist
min_len parameter for chunk_data function addded
Merge branch 'hybrid' into merge_hybrid

Conflicts:
	botmpy/test/test_common.py