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Jul 1, 2018 - Running the example data I received this error: SparCC.py example/fakedata.txt -i 5 -corfile=example/basiscorr/corsparcc.out reading.
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![Range Range](/uploads/1/2/5/8/125857435/937107866.png)
commented Feb 21, 2018 • edited
edited
Hi there nice package. Just a quick one, in line 409 at core.py there is:I am not sure that is necessary? For example using sparse matrices this return an array with the sparse matrix 'inside' (i.e. no shape) rather than an array THAT IS the sparse matrix. This will throw an error at line 502:as I am at the moment running it just commenting out those lines with no problem. Just that, maybe considering commenting out the lines or add an if statement for sparse matrices?Thanks |
added a commit that referenced this issue Feb 21, 2018
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commented Feb 21, 2018
Thanks a lot! Nice catch! At this point in code we must check arrays, because unexpected array types may give very strange errors later. So I followed scikit-learn recommendation and used functions check_X_y and check_array as follows: I’ve just fixed the issue. Please look at this commit. You can reinstall package from github directly (without git and without updating dependencies): pip install --upgrade --no-deps https://github.com/vecxoz/vecstack/archive/master.zip Thanks again! Please report if you find anything strange. |
commented Feb 23, 2018
Related note. In 0.2.2 release I finally used accept_sparse=['csr'] instead of accept_sparse=True .accept_sparse=['csr'] means that we allow CSR and transform all other sparse types to CSR.This approach is more consistent because some sparse types e.g. COO are not subscriptable (so we can't make CV split directly) but allow transformation to CSR. |
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