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[REVIEW]: mpnum: A matrix product representation library for Python #465
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@SylvainCorlay, please carry out your review in this issue by updating the checklist below. If you cannot edit the checklist please:
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referenced this issue
Nov 17, 2017
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I found that there is a DOI for the reference Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition.
Very minor: on this point, a "contributing" section in the readme could be added (simply linking to the relevant section of the documentation).
For some reason, I had to install
@SylvainCorlay Thanks for the feedback.
Added DOI and updated arXiv references for another paper in
Right, I recalled that we had to manually install test dependencies on travis for that reason. I have added a note to the README as well as to the documentation. (The latter should appear once readthedocs renders the new version)
I could install, run the tests, and the example notebook. The whole process was straightforward. The need for the package is properly justified and prior work appropriately cited. Documentation includes both high-level narrative documentation introducing the package and an API reference generated from the doc strings (although a few items are left as todo).
Thanks a lot @SylvainCorlay for the helpful comments. We already implemented remark 1 on the master branch in the repo. We will address the other remarks shortly after fixing some slight mistakes in some images.
@labarba I would move the
I have uploaded the final version v1.0.2 with the DOI 10.5281/zenodo.1115574. We have updated the refereed version according to the suggestions of the referee:
We also migrated all the figures from Inkscape to LaTeX/TikZ and fixed some notation errors.
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