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Datashift - Rigid and Segmented Registration #29
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- eMouse simulation example - Jenkins report builder - Simple comparison analysis
* 'master' of github.com:rossant/pykilosort: Typed Configuration (MouseLand#28) Comparison between MATLAB & Python Versions (MouseLand#25) Add dockerfile for running tests with GPU (MouseLand#22)
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counter = np.zeros(2, dtype=np.int32, order='F') | ||
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# filter the data with the temporal templates | ||
Conv1D = cp.RawKernel(code, 'Conv1D') |
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@kushbanga was this Conv1D function the one you said had a bug?
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These files are for regression tests.
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(the output is from the MATLAB version)
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TEST_DATA_FOLDER = "tests/fixtures/data" | ||
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@pytest.mark.requires_gpu |
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Not sure this one does require gpu...
Suggestion from @kushbanga. Let's add a test against the MATLAB version that the depth shift is exactly the same for each time segment. |
* 'master' of github.com:rossant/pykilosort: fixes bug fix minor fix
…ashift * 'datashift' of github.com:alexmorley/pykilosort: minor bug
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# upsample the shift for each channel using interpolation | ||
if len(ysamp) > 1: | ||
# zero pad input so "extrapolation" tends to zero |
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Try:
- regression towards mean
- mirror
) # this kernel is fixed as a variance of 1 | ||
dcs = cp.array(dcs) | ||
# dcs = my_conv2_cpu(dcs, .5, [0,1,2]) | ||
for i in range(dcs.shape[0]): |
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@kushbanga I just pushed a bunch of fixes that I had sitting on my laptop just FYI! |
more tests here alexmorley/kilosort-testing#2 |
V1 working version of datashift.
Probably could use a) a couple more unit tests and b) better integration with the sorting flow.
Check for: