Open clkruse opened 1 year ago
Thanks for reporting this. Indeed, the numpy aliases to Python dtypes have been removed in 1.24, ref. For the time being skhubness thus requires numpy<1.24.
Is this package still being developed?
Not very actively, though I might find some time to do maintenance tasks like this (which likely only requires changing np.float
to np.float32
in the code; PR welcome).
This package would be extremely useful for my research as I've been trying to implement some of these methods myself but I don't really have the background for it.
I can take a crack at updating the code to use the newest numpy and scikit learn because I'm unable to install this with pip.
Is there anything in particular I should be aware of in terms of porting to the newest versions?
@jolespin Thank you, but now I believe this is in fact not necessary:
I have just tested skhubness==0.30 with Python=3.10 and recent numpy, sklearn etc. This runs the example code from the readme just fine. Also, at a quick glance, I could not find any usage of np.float
in the code base that would have caused the initial error reported here. So I suppose this error came from an earlier version of skhubness (v.20.x indeed used np.float).
Awesome. A few hours ago I forked it and got it to install just fine from source. I just changed a single line in the test directory under the neighbor module.
Is the 0.30 version ready for public by any chance? Maybe under beta release?
Thx for the feedback. Which line did you change?
It is ready enough that I pushed the changes to main. Since the docs are not yet fully updated to reflect changes in v.30, I've never created an "official" release for PyPI. I cannot guarantee for anything, but please feel free to try and test.
I just remove the np.float32 and np.float64 parts but I didn't even need to since I was already working with v0.30a.
It throws the following error when trying to import the skhubness package.
AttributeError: module 'numpy' has no attribute 'float'
The float attribute seems to have been removed in numpy 1.24, so I resolved this by downgrading to
numpy==1.23
.