Comments (4)
Hi @samuelstjean ! Thanks for this!
- A quick workaround is to call separately each factor that you are interested in, e.g.:
pg.pairwise_ttests(..., between="fac1")
followed by
pg.pairwise_ttests(..., between="fac2")
instead of pg.pairwise_ttests(..., between=["fac1", "fac2"])
I'll try to add an option to test only the interaction or main effect in future release.
- I agree with you on this point; the current implementation is designed for flexibility, but not really for speed / memory efficiency (in my field of research we rarely apply T-tests on more than 1000 rows so memory has never been an issue). I'll try to look into that in future releases but please feel free to have a look at the code and suggest any ideas to improve this.
Thanks!
Raphael
from pingouin.
Ah yes, kind of did that, I cheated by taking parts of my panda frame (reusing the same memory array every time), calling the whole thing on it, and finally re-computing correct pvals for the final result, therefore avoiding the interaction effects.
I guess it's a bit too specific, but well for general purpose tests (and other fields) it may be helpful indeed. I'm afraid I'm a bit busy to have a shot at it myself before at least november though, thesis writing and everything.
from pingouin.
- Added
interaction
argument to pairwise_ttests in cef2a0f - Currently working on improving speed and memory
from pingouin.
Minor improvements in speed and memory:
These changes are available on the develop branch and will be released in Pingouin 0.2.9 (sometimes in September).
Closing the issue for now but please feel free to reopen.
Thanks
Raphael
from pingouin.
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