Issue with Error message stating inputs are of wrong sizes

[swzCuroverse]

I am getting the following error, my inputs are of the correct input size. I am not sure where to contact the authors for assistance so writing this up as an issue. Xtrain is all ones and zeros (it comes from a 1hot encoder) and y is all ones and zeros. Example code given in documentation works fine so not an install issue.

I used the following code (I am running on a 16 core machine):
fs = ReliefF(n_features_to_select=2000, n_neighbors=100,n_jobs=-1)
fs.fit(Xtrain, y)

Shapes for additional info:

y.shape
(3672,)
Xtrain.shape
(3672, 1688789)

Error message:
Traceback (most recent call last):
File "reliefChr19.py", line 180, in
fs.fit(Xtrain, y)
File "/usr/local/lib/python2.7/dist-packages/skrebate/relieff.py", line 154, in fit
self.attr = self._get_attribute_info() #Examines each feature and applies discrete_threshold to determine variable type.
File "/usr/local/lib/python2.7/dist-packages/skrebate/relieff.py", line 280, in _get_attribute_info
zlen = len(np.unique(z))
File "/usr/local/lib/python2.7/dist-packages/numpy/lib/arraysetops.py", line 210, in unique
return _unique1d(ar, return_index, return_inverse, return_counts)
File "/usr/local/lib/python2.7/dist-packages/numpy/lib/arraysetops.py", line 279, in _unique1d
flag = np.concatenate(([True], aux[1:] != aux[:-1]))
ValueError: all the input arrays must have same number of dimensions

[ryanurbs]

were you able to figure out this issue?

[swzCuroverse]

No, I have not. However, I know have a set of data that we can use that is public so I can give it to you for debugging purposes. I will write up a script in the next few days if that is useful?

[weixuanfu]

A script for reproducing this issue is helpful. Thank you!

One questions, what is type(Xtrain) in your codes?

[ryanurbs]

Yeah i'm just trying to figure out if there is a bug that needs to be fixed or if there might be a user error issue. Last night we just released a new version with a number of updates/fixes. So perhaps that alone might resolve your issue.

[swzCuroverse]

Ok, I will update the version and try again.

[swzCuroverse]

Xtrain was a sparse that I made using the 1-hot encoding in sci-kit learn that I convert to dense using Xtrain = Xtrain.todense(),

[swzCuroverse]

I updated and it seems to be chugging away with no error, so a good sign!