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cortex-lab / KiloSort

GPU code for spike sorting
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Question regarding the templates #64

Open hendrikrth opened 7 years ago

hendrikrth commented 7 years ago

Hi, I have a question regarding the file ‘templates.npy’. I run Kilosort on my data which has 16 Channels with the following parameters: ops.NchanTOT = 16 ops.Nchan = 16 ops.Nfilt = 64

The matrix in ‘templates.npy’ is of shape 64x82x16, the similarity matrix ‘similar_templates.npy’ has the shape 64x64. My question is now how are these two matrices related? How do I find out which template in ‘similar_templates.npy’ corresponds to the templates in ‘templates.npy’? And do I understand it correctly that the templates are local for each channel and in my case there are 64 on each of them?

nsteinme commented 7 years ago

Because you set ops.Nfilt = 64, Kilosort finds 64 templates. Each template is 82 time samples long, and covers all 16 channels. The first template is found in this way:

temps = readNPY('templates.npy'); template1 = squeeze(temps(1,:,:)); and so on.

The similar_templates file has the similarity between each pair of templates, i.e. the similarity measure between template 1 and template 10 is given by:

sim = readNPY('similar_templates.npy'); sim1vs10 = sim(1,10);

Hth - I wasn't sure what you meant by "local for each channel" so maybe I didn't answer everything...

On Fri, Apr 21, 2017 at 10:06 AM, hendrikrth notifications@github.com wrote:

Hi, I have a question regarding the file ‘templates.npy’. I run Kilosort on my data which has 16 Channels with the following parameters: ops.NchanTOT = 16 ops.Nchan = 16 ops.Nfilt = 64

The matrix in ‘templates.npy’ is of shape 64x82x16, the similarity matrix ‘similar_templates.npy’ has the shape 64x64. My question is now how are these two matrices related? How do I find out which template in ‘similar_templates.npy’ corresponds to the templates in ‘templates.npy’? And do I understand it correctly that the templates are local for each channel and in my case there are 64 on each of them?

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