Extract individual spikes from the high pass filtered data problem

[skjenks]

Hi,
I am trying to extract individual spikes from the high pass filtered data from kilosort2 by using getWaveForms (https://github.com/cortex-lab/spikes/blob/master/analysis/getWaveForms.m). My params are :

gwfparams.fileName = 'temp_wh.dat'; % .dat file containing the raw
gwfparams.dataType = 'int16'; % Data type of .dat file (this should be BP filtered)
gwfparams.nCh = 16; % Number of channels that were streamed to disk in .dat file
gwfparams.wfWin = [-40 41]; % Number of samples before and after spiketime to include in waveform
gwfparams.nWf = 2000; % Number of waveforms per unit to pull out
gwfparams.spikeTimes = readNPY('spike_times.npy'); % Vector of cluster spike times (in samples) same length as .spikeClusters
gwfparams.spikeClusters = readNPY('spike_clusters.npy'); % Vector of cluster IDs (Phy nomenclature) same length as .spikeTimes

I have been able to isolate a spike by using the raw data .dat file. However I would like to use the filtered data. What I did was switch the raw data file with temp_wh.dat run the code and I didn't get a spike but something that looked like it was from a different timestamp.

My questions are:

1. is temp_wh.dat the high pass filtered data?
2. if so, then how should I extract the times from the temp_wh.dat so they correspond to the raw data's channels?

@nsteinme

[marius10p]

temp_wh.dat is data in batches, which also contains overlap between batches, which will throw off your spike times.

You are better off filtering the data yourself, by following lines 93-126 in this script

[marius10p]

Issue has become inactive. Closing.