Expose t_inc param in HS
@@ -42,6 +42,7 @@ class HerdingspikesSorter(BaseSorter):
'probe_peak_jitter': 0.2,
# extra detection params
+ 't_inc': 100000,
'num_com_centers': 1,
'maa': 12,
'ahpthr': 11,
@@ -88,6 +89,7 @@ class HerdingspikesSorter(BaseSorter):
'probe_peak_jitter': "Maxmimum peak misalignment for synchronous spike (ms)",
# extra detection params
+ 't_inc': "Number of samples per chunk during detection.",
'num_com_centers': "Number of centroids to average when localizing.",
'maa': "Minimum summed spike amplitude for spike acceptance.",
'ahpthr': "Requires magnitude of spike rebound for acceptance",
@@ -191,7 +193,7 @@ class HerdingspikesSorter(BaseSorter):
spk_evaluation_time=p['spk_evaluation_time']
)
- H.DetectFromRaw(load=True, tInc=100000)
+ H.DetectFromRaw(load=True, tInc=int(p['t_inc']))
sorted_file = str(output_folder / 'HS2_sorted.hdf5')
if(not H.spikes.empty):
