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mtl-brainhack-school-2019 / PLS_PV_Behaviour

Run multivariate anaylysis to relate behavioral and electropyhysiological data
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Starting my to-do list #1

Open mcfneuro opened 4 years ago

mcfneuro commented 4 years ago

Just opening an "issue" to document our discussion from yesterday PM

illdopejake commented 4 years ago

OK cool - tag me when you have a draft and I'll look it over!

mcfneuro commented 4 years ago

OK, I have a first draft and started working of organizing my data (uploaded/updated a short code using a bunch of your suggestions)

illdopejake commented 4 years ago

Looks great! I like the general format of everything. It might be helpful to mention what kind of subjects you are working with (mice? rats? humans?) and your N. Otherwise, I like it!

illdopejake commented 4 years ago

One other thing to mention is that, unless it is very small, it's usually not a great idea to store data on your git repo. If you must, it's create to try to compress it as much as possible. But generally you don't want to store large files on github for a number of reasons. Remember also that this is a public repo and anyone can download what you put up.

mcfneuro commented 4 years ago

Looks great! I like the general format of everything. It might be helpful to mention what kind of subjects you are working with (mice? rats? humans?) and your N. Otherwise, I like it!

Done. Thanks

One other thing to mention is that, unless it is very small, it's usually not a great idea to store data on your git repo. If you must, it's create to try to compress it as much as possible. But generally you don't want to store large files on github for a number of reasons. Remember also that this is a public repo and anyone can download what you put up.

Where/how would you store it ? Files are small (2 files of 20 MB each). But, regardless, I'd like to know what would be best practice ?

illdopejake commented 4 years ago

Where/how would you store it ? Files are small (2 files of 20 MB each). But, regardless, I'd like to know what would be best practice ?

20 MB is actually pretty big for git.. keep in mind that usually you're storing text files and such that rarely get larger than a few MB. Although, once you convert these to numpy arrays, you can use np.savez_compressed() to create very compressed arrays that should be way smaller than those matfiles.

Generally, you store the data locally -- it's the code that you're sharing and versioning on git. If you want to host data online, there are other better ways to do it. If you want to store metadata or map your directories, you can also check out datalad