Set num_histogram_bins in amplitude_cutoff (back) to 100

[ecobost]

#4353 changed the default num_histogram_bins in AmplitudeCutoff from 100 to 200 to get a more granular histogram/estimate.

spikeinterface/src/spikeinterface/metrics/quality/misc_metrics.py

Line 1034 in 797f0e8

"num_histogram_bins": 200,

But given the default amplitudes_bins_min_ratio=5, any cell with less than 1000 spikes will return amplitude_cutoff = NaN. That is (I think?) too big a hurdle (a unit with 0.1Hz firing rate will require 2.8 hours to spike 1000 times).

Assuming 500 spikes are enough to model the amplitude distribution, I change it back to 100 here. I also change the default value on the low-level amplitude_cutoff()to match this default.

EDIT: Even if we don't think 500 spikes are enough to model the distribution, the right parameter to change would be amplitudes_bins_min_ratio and not num_histogram_bins as we would rather have more samples per bin (lower variance)