Open shihchengyen opened 5 years ago
Here is some data (vmhighpass.mat & hmmsort.mat):
https://cortex.nus.edu.sg:8399/sharing/l4Bao1FH3 https://cortex.nus.edu.sg:8399/sharing/qfzO4jv1j
You can view the highpass with spikes by doing:
load vmhighpass.mat InspectGUI(vh2,'LoadSort')
You will have to clone the Hippocampus repository to get the code for vmhighpass.
Hi Roger,
That was fast!
I have shared some data with you in the GitHub comments.
Let me know if you have any problems working with the data.
Thanks!
Shih Cheng
On Dec 20, 2018, at 5:48 PM, Roger Herikstad notifications@github.com<mailto:notifications@github.com> wrote:
I have opened some pull-requests for the 3 issues we discussed today. As soon as I have a sample of a data where these problems are apparent, I can check whether these fixes are sufficient.
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Hm, do you usually save the data in pre v7.3 format? I try to always use -v7.3 when saving so that everything is saved in an HDF5 compatible format. It makes it easier to read in python. I'm actually a bit surprised that sorting this file worked in the first place, since I have trouble loading it now..
Roger,
I think I encountered some issue that was fixed with the older format, but I can check to see if we still need it.
I also changed the data to single precision floats, so I wonder if that is causing problems in Python?
Shih Cheng
On Dec 21, 2018, at 9:32 AM, Roger Herikstad notifications@github.com<mailto:notifications@github.com> wrote:
Hm, do you usually save the data in pre v7.3 format? I try to always use -v7.3 when saving so that everything is saved in an HDF5 compatible format. It makes it easier to read in python. I'm actually a bit surprised that sorting this file worked in the first place, since I have trouble loading it now..
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHubhttps://github.com/grero/hmmsort.py/issues/25#issuecomment-449204991, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AdfZh11sf1t5j5hnRspinZwd0MWmtdwbks5u7DoIgaJpZM4Zbks1.
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OK, so it turns out that using single instead of double confuses matlab. hmm_decode returns a log likelihood of NaN when the data has single precision.
I have opened some pull-requests for the 3 issues we discussed today. As soon as I have a sample of a data where these problems are apparent, I can check whether these fixes are sufficient.