[REVIEW]: nnde: A Python package for solving differential equations using neural networks

whedon commented 3 years ago

Submitting author: @elwinter (Eric Winter) Repository: https://github.com/elwinter/nnde Version: v1.0 Editor: @diehlpk Reviewer: @taless474, @hayesall Archive: 10.5281/zenodo.5879387

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Review checklist for @taless474

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@elwinter) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

Review checklist for @hayesall

Conflict of interest

[x] I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

[x] Repository: Is the source code for this software available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Contribution and authorship: Has the submitting author (@elwinter) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
[x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
[x] Functionality: Have the functional claims of the software been confirmed?
[x] Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
[x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support

Software paper

[x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
[x] A statement of need: Does the paper have a section titled 'Statement of Need' that clearly states what problems the software is designed to solve and who the target audience is?
[x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
[x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
[x] References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

whedon commented 3 years ago

Hello human, I'm @whedon, a robot that can help you with some common editorial tasks. @taless474, @hayesall it looks like you're currently assigned to review this paper :tada:.

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whedon commented 3 years ago

Software report (experimental):

github.com/AlDanial/cloc v 1.88  T=0.09 s (969.6 files/s, 99205.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          86           2298           2106           4781
Markdown                         2             27              0             47
TeX                              1              3              0             32
make                             1              3              0              8
JSON                             1              0              0              6
-------------------------------------------------------------------------------
SUM:                            91           2331           2106           4874
-------------------------------------------------------------------------------

Statistical information for the repository 'be66f95afd6266cb60f8d390' was
gathered on 2021/07/09.
The following historical commit information, by author, was found:

Author                     Commits    Insertions      Deletions    % of changes
Eric Winter                    192         18132           8947          100.00

Below are the number of rows from each author that have survived and are still
intact in the current revision:

Author                     Rows      Stability          Age       % in comments
Eric Winter                9185           50.7          8.3               13.41

whedon commented 3 years ago

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1109/72.712178 is OK
- 10.1007/978-94-017-9816-7 is OK

MISSING DOIs

- None

INVALID DOIs

- None

whedon commented 3 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

hayesall commented 3 years ago

I made the first review pass @elwinter. I need some additional time to check functionality, but all of the points below should be possible to do parallel to that.

Overall Feedback

All of the components are here (software, docstrings, tests), the final step is to make these components accessible to a user. Many of these could be addressed by incorporating a documentation system (e.g. sphinx) to pull docstrings and present them alongside a high-level overview.

If possible: After writing the high-level documentation; schedule a meeting with a colleague (someone who is fairly comfortable in Python and knows a little about this problem setting), give them links to the software and documentation, and watch them get started with it. This almost always helps reveal theories of the software that are inaccessible.

Functionality / Installation

Documentation, Testing, and Community Guidelines

Paper Feedback

elwinter commented 3 years ago

Excellent. Thanks for your time. I'll start addressing these over the next week or so and resubmit.

Take care Eric

Get Outlook for Androidhttps://aka.ms/ghei36

From: Alexander L. Hayes @.> Sent: Tuesday, July 13, 2021 7:21:22 PM To: openjournals/joss-reviews @.> Cc: Eric Winter @.>; Mention @.> Subject: Re: [openjournals/joss-reviews] [REVIEW]: nnde: A Python package for solving differential equations using neural networks (#3465)

I made the first review pass @elwinterhttps://github.com/elwinter. I need some additional time to check functionality, but all of the points below should be possible to do parallel to that.

Overall Feedback

All of the components are here (software, docstrings, tests), the final step is to make these components accessible to a user. Many of these could be addressed by incorporating a documentation system (e.g. sphinxhttps://www.sphinx-doc.org/en/master/) to pull docstrings and collect high-level overviews.

If possible: After writing the high-level documentation; schedule a meeting with a colleague (someone who is fairly comfortable in Python and knows a little about this problem setting), give them links to the software and documentation, and watch them get started with it.

Functionality / Installation

elwinter/nnde#4https://github.com/elwinter/nnde/issues/4
elwinter/nnde#6https://github.com/elwinter/nnde/issues/6
elwinter/nnde#8https://github.com/elwinter/nnde/issues/8

Documentation, Testing, and Community Guidelines

elwinter/nnde#7https://github.com/elwinter/nnde/issues/7
elwinter/nnde#9https://github.com/elwinter/nnde/issues/9
elwinter/nnde#10https://github.com/elwinter/nnde/issues/10
elwinter/nnde#11https://github.com/elwinter/nnde/issues/11
elwinter/nnde#12https://github.com/elwinter/nnde/issues/12
elwinter/nnde#13https://github.com/elwinter/nnde/issues/13
elwinter/nnde#14https://github.com/elwinter/nnde/issues/14
elwinter/nnde#15https://github.com/elwinter/nnde/issues/15

Paper Feedback

elwinter/nnde#5https://github.com/elwinter/nnde/issues/5
elwinter/nnde#16https://github.com/elwinter/nnde/issues/16

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://github.com/openjournals/joss-reviews/issues/3465#issuecomment-879468265, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ABSFWC2YWYSFXXK554RSF3DTXTC7FANCNFSM5AC2IOEQ.

diehlpk commented 3 years ago

Hey @taless474 how is your review going?

whedon commented 3 years ago

:wave: @hayesall, please update us on how your review is going (this is an automated reminder).

whedon commented 3 years ago

:wave: @taless474, please update us on how your review is going (this is an automated reminder).

diehlpk commented 3 years ago

@whedon remind @taless474 in 2 weeks

whedon commented 3 years ago

Reminder set for @taless474 in 2 weeks

taless474 commented 3 years ago

I made the first review pass at @elwinter's nnde. As @hayesall did a great job on creating on-point issues, I went through the functionality check first. Executing this:

pip install nnde
git clone https://github.com/elwinter/nnde_demos
cd nnde_demos; python lagaris01_demo.py

(--update does not work the first time), the demo was successful. However, the demos are located in another repository.

I also ran the tests and they all pass. I will test it further after elwinter/nnde#9 is resolved.

diehlpk commented 3 years ago

Hey @elwinter how is your revision going?

elwinter commented 3 years ago

Hi Patrick. Revisions are proceeding. I have closed all but 3 issues opened by the reviewers now, and I hope to have the rest closed by the end of this week.

Take care

Eric

From: Patrick Diehl @.> Sent: Monday, August 9, 2021 10:14 AM To: openjournals/joss-reviews @.> Cc: Eric Winter @.>; Mention @.> Subject: Re: [openjournals/joss-reviews] [REVIEW]: nnde: A Python package for solving differential equations using neural networks (#3465)

Hey @elwinter https://github.com/elwinter how is your revision going?

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/3465#issuecomment-895259410 , or unsubscribe https://github.com/notifications/unsubscribe-auth/ABSFWCZRWTQIP2HGYUHBGEDT37PBFANCNFSM5AC2IOEQ . Triage notifications on the go with GitHub Mobile for iOS https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Android https://play.google.com/store/apps/details?id=com.github.android&utm_campaign=notification-email . https://github.com/notifications/beacon/ABSFWC4PPKH7BIVA7AL563DT37PBFA5CNFSM5AC2IOE2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOGVOJGEQ.gif

diehlpk commented 3 years ago

@hayesall The author has addressed most of your concerns. Would you mind to check if you are satisfied.

hayesall commented 3 years ago

I'll check this evening. I saw the last main change got cleared over the weekend.

diehlpk commented 3 years ago

I made the first review pass at @elwinter's nnde. As @hayesall did a great job on creating on-point issues, I went through the functionality check first. Executing this:
pip install nnde
git clone https://github.com/elwinter/nnde_demos
cd nnde_demos; python lagaris01_demo.py
(--update does not work the first time), the demo was successful. However, the demos are located in another repository.

I also ran the tests and they all pass. I will test it further after elwinter/nnde#9 is resolved.

@taless474 I think #9 is resolved and you can start to review again.

diehlpk commented 3 years ago

@hayesall and @taless474 The author has addressed most of your concerns. Would you mind to check if you are satisfied.

hayesall commented 3 years ago

Hey @diehlpk I checked off all but "Functionality" from my tasklist a couple days ago (but I didn't want to cause notification noise). I still need a little more time on functionality.

Follow-up: This would be a stronger submission with sphinx/mkdocs and https://github.com/elwinter/nnde/issues/13, but nnde currently meets the baseline requirements.

hayesall commented 3 years ago

@whedon generate pdf

whedon commented 3 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

diehlpk commented 3 years ago

@elwinter Can you have a look at elwinter/nnde#13 and sphinx/mkdocs?

hayesall commented 3 years ago

@diehlpk Sorry, my previous statement was vague. Those things would be good to have (and should probably be done in the future), but I think this is satisfactory without them.

Update on functionality review: I've used nnde to reproduce some numerical results, some notes are included here https://github.com/elwinter/nnde_demos/pull/4

taless474 commented 3 years ago

@elwinter, thank you for addressing the issues. I started checking the installation and created #22. Would you please take a look at it?

@diehlpk, do we need the demo to be in the same repository? I am not sure if this is an issue and thank you in advance for your response.

diehlpk commented 3 years ago

@diehlpk, do we need the demo to be in the same repository? I am not sure if this is an issue and thank you in advance for your response.

I think that is not an issue, if it is well documented.

diehlpk commented 3 years ago

@elwinter How is your revision going?

diehlpk commented 3 years ago

@taless474 How is your review going?

diehlpk commented 3 years ago

@elwinter How is your revision going?

diehlpk commented 3 years ago

@taless474 How is your review going?

taless474 commented 3 years ago

@diehlpk, thank you for your comment. We are waiting for @elwinter to address #22, so I can go forward with the next round of review.

diehlpk commented 3 years ago

@elwinter Could you please fix the issues so Bita can proceed with the review?

diehlpk commented 3 years ago

@elwinter Could you please fix the issues so Bita can proceed with the review?

elwinter commented 3 years ago

Hmm. I thought I had fixed and closed all but one issue a couple of weeks ago, and was waiting for a response on my test coverage question. Did i miss something? Please let me know and i will take care of it.

Thanks Eric

Get Outlook for Androidhttps://aka.ms/ghei36

From: Patrick Diehl @.> Sent: Thursday, October 14, 2021 10:47:07 PM To: openjournals/joss-reviews @.> Cc: Eric Winter @.>; Mention @.> Subject: Re: [openjournals/joss-reviews] [REVIEW]: nnde: A Python package for solving differential equations using neural networks (#3465)

@elwinterhttps://github.com/elwinter Could you please fix the issues so Bita can proceed with the review?

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://github.com/openjournals/joss-reviews/issues/3465#issuecomment-943941666, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ABSFWC6VT325ZS533WSRFYLUG6I2XANCNFSM5AC2IOEQ. Triage notifications on the go with GitHub Mobile for iOShttps://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Androidhttps://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.

diehlpk commented 3 years ago

@elwinter @taless474 opened that issue https://github.com/elwinter/nnde/issues/22 in your repo. Could you please have a look into that?

diehlpk commented 3 years ago

@taless474 It seems that @elwinter has fixed the issue and you can proceed with your review.

taless474 commented 3 years ago

@diehlpk, I think this is ready. Please proceed with your review/comments, thanks!

diehlpk commented 3 years ago

@diehlpk, I think this is ready. Please proceed with your review/comments, thanks!

@taless474

Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?

Could you please validate if this box should be checked or is still missing?

taless474 commented 3 years ago

@diehlpk, I think it can be improved. I didn't check it to ask for your opinion. But overly, it is ready.

diehlpk commented 3 years ago

@whedon generate pdf

whedon commented 3 years ago

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

diehlpk commented 3 years ago

@elwinter I briefly read the paper and have the following remarks, so far

[x] Please add the city, state, and country to the affiliation
[x] Provide some reference to PyTorch and TensorFlow 2. In addition, I think the related work section is really sparse and some mention of other packages and how they differ would be beneficial for the reader.
[x] You mention that FEM and FDM can be difficult to parallelize. Can you provide some reference for that claim?

hayesall commented 3 years ago

I read through and checked off the last box. I think this is in a pretty good state.

diehlpk commented 3 years ago

@hayesall and @taless474 thanks for finishing the review.

diehlpk commented 3 years ago

@elwinter Please address the editorial comments and we are good to accept the paper.

diehlpk commented 3 years ago

@elwinter Please address the editorial comments and we are good to accept the paper.

elwinter commented 2 years ago

Hi Patrick. I apologize for the delayed response. As shown below, test coverage (the only remaining issue) is now at 76%. Is this sufficient to continue?

Thanks Eric

Coverage report: 76%[image: Show keyboard shortcuts] Modulestatementsmissingexcludedcoverage Total 6341 1508 0 76% nnde/init.py 0 0 0 100% nnde/differentialequation/init.py

0 0 0 100% nnde/differentialequation/differentialequation.py 6 0 0 100% nnde/differentialequation/examples/__init__.py 0 0 0 100% nnde/differentialequation/examples/diff1d_half.py 69 0 0 100% nnde/differentialequation/examples/diff1d_halfsine.py 87 0 0 100% nnde/differentialequation/examples/diff1d_halfsine_increase.py 106 0 0 100% nnde/differentialequation/examples/diff1d_one.py 70 0 0 100% nnde/differentialequation/examples/diff1d_zero.py 70 0 0 100% nnde/differentialequation/examples/diff2d_halfsine.py 142 7 0 95% nnde/differentialequation/examples/diff2d_halfsine_increase.py 122 1 0 99% nnde/differentialequation/examples/diff3d_halfsine.py 213 118 0 45% nnde/differentialequation/examples/diff3d_halfsine_increase.py 188 11 0 94% nnde/differentialequation/examples/example_pde1ivp_01.py 53 28 0 47% nnde/differentialequation/examples/lagaris_01.py 13 5 0 62% nnde/differentialequation/examples/lagaris_02.py 13 5 0 62% nnde/differentialequation/examples/tests/__init__.py 0 0 0 100% nnde/differentialequation/examples/tests/test_diff1d_half.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_halfsine.py 262 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_halfsine_increase.py 272 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_one.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_zero.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff2d_halfsine.py 493 11 0 98% nnde/differentialequation/examples/tests/test_diff2d_halfsine_increase.py 428 1 0 99% nnde/differentialequation/examples/tests/test_diff3d_halfsine.py 92 89 0 3% nnde/differentialequation/examples/tests/test_diff3d_halfsine_increase.py 710 1 0 99% nnde/differentialequation/examples/tests/test_example_pde1ivp_01.py 35 32 0 9% nnde/differentialequation/examples/tests/test_lagaris_01.py 8 5 0 38% nnde/differentialequation/examples/tests/test_lagaris_02.py 8 5 0 38% nnde/differentialequation/ode/__init__.py 0 0 0 100% nnde/differentialequation/ode/ode.py 3 0 0 100% nnde/differentialequation/ode/ode1.py 5 0 0 100% nnde/differentialequation/ode/ode1ivp.py 27 14 0 48% nnde/differentialequation/ode/tests/__init__.py 0 0 0 100% nnde/differentialequation/ode/tests/test_ODE.py 9 1 0 89% nnde/differentialequation/ode/tests/test_ODE1.py 12 1 0 92% nnde/differentialequation/ode/tests/test_ODE1IVP.py 7 1 0 86% nnde/differentialequation/pde/__init__.py 0 0 0 100% nnde/differentialequation/pde/pde.py 3 0 0 100% nnde/differentialequation/pde/pde1.py 5 0 0 100% nnde/differentialequation/pde/pde1ivp.py 29 16 0 45% nnde/differentialequation/pde/pde2.py 5 0 0 100% nnde/differentialequation/pde/pde2diff.py 47 28 0 40% nnde/differentialequation/pde/tests/__init__.py 0 0 0 100% nnde/differentialequation/pde/tests/test_PDE.py 9 1 0 89% nnde/differentialequation/pde/tests/test_PDE1.py 12 1 0 92% nnde/differentialequation/pde/tests/test_PDE1IVP.py 8 1 0 88% nnde/differentialequation/pde/tests/test_PDE2.py 12 1 0 92% nnde/differentialequation/pde/tests/test_PDE2DIFF.py 7 1 0 86% nnde/differentialequation/tests/__init__.py 0 0 0 100% nnde/differentialequation/tests/test_DifferentialEquation.py 12 1 0 92% nnde/exceptions/__init__.py 0 0 0 100% nnde/exceptions/nndeexception.py 2 0 0 100% nnde/exceptions/tests/__init__.py 0 0 0 100% nnde/exceptions/tests/test_NNDEException.py 7 1 0 86% nnde/math/__init__.py 0 0 0 100% nnde/math/kdelta.py 2 0 0 100% nnde/math/sigma.py 22 0 0 100% nnde/math/tests/__init__.py 0 0 0 100% nnde/math/tests/test_kdelta.py 11 1 0 91% nnde/math/tests/test_sigma.py 37 1 0 97% nnde/math/tests/test_trainingdata.py 27 1 0 96% nnde/math/trainingdata.py 41 16 0 61% nnde/neuralnetwork/__init__.py 0 0 0 100% nnde/neuralnetwork/neuralnetwork.py 8 0 0 100% nnde/neuralnetwork/nnode1ivp.py 250 214 0 14% nnde/neuralnetwork/nnpde1ivp.py 474 425 0 10% nnde/neuralnetwork/nnpde2diff.py 490 448 0 9% nnde/neuralnetwork/slffnn.py 3 0 0 100% nnde/neuralnetwork/tests/__init__.py 0 0 0 100% nnde/neuralnetwork/tests/test_NNODE1IVP.py 29 1 0 97% nnde/neuralnetwork/tests/test_NNPDE1IVP.py 7 1 0 86% nnde/neuralnetwork/tests/test_NeuralNetwork.py 15 1 0 93% nnde/neuralnetwork/tests/test_PDE2DIFF.py 27 1 0 96% nnde/neuralnetwork/tests/test_SLFFNN.py 9 1 0 89% nnde/trialfunction/__init__.py 0 0 0 100% nnde/trialfunction/diff1dtrialfunction.py 73 0 0 100% nnde/trialfunction/diff2dtrialfunction.py 79 0 0 100% nnde/trialfunction/diff3dtrialfunction.py 85 0 0 100% nnde/trialfunction/tests/__init__.py 0 0 0 100% nnde/trialfunction/tests/test_Diff1DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_Diff2DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_Diff3DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_TrialFunction.py 8 1 0 88% nnde/trialfunction/trialfunction.py 3 1 0 67% coverage.py v5.5 , created at 2021-11-06 10:13 -0400 On Mon, Nov 1, 2021 at 11:17 AM Patrick Diehl ***@***.***> wrote: > @elwinter Please address the editorial > comments and we are good to accept the paper. > > — > You are receiving this because you were mentioned. > Reply to this email directly, view it on GitHub > , > or unsubscribe > > . > Triage notifications on the go with GitHub Mobile for iOS > > or Android > . > >

hayesall commented 2 years ago

I just tested the master branch and got 72% coverage.

Terminal Recap

```bash git clone git@github.com:elwinter/nnde.git cd nnde pip install pytest pytest-cov pip install -e . pytest --cov=nnde . # --- # TOTAL 6550 1857 72% ```

This seems fine (I tend to think coverage numbers are more a rule-of-thumb than an absolute threshold).

If you want to report coverage stats on push/pull requests, you can add something like this to the .github/workflows/github-run-nnde-tests.yml:

    - name: Test with pytest
      run:  pytest --cov=nnde .
    - name: Upload coverage to Codecov
      uses: codecov/codecov-action@v1

diehlpk commented 2 years ago

Hi Patrick. I apologize for the delayed response. As shown below, test coverage (the only remaining issue) is now at 76%. Is this sufficient to continue? Thanks Eric Coverage report: 76%[image: Show keyboard shortcuts] Modulestatementsmissingexcludedcoverage Total 6341 1508 0 76% nnde/init.py 0 0 0 100% nnde/differentialequation/init.py 0 0 0 100% nnde/differentialequation/differentialequation.py 6 0 0 100% nnde/differentialequation/examples/init.py 0 0 0 100% nnde/differentialequation/examples/diff1d_half.py 69 0 0 100% nnde/differentialequation/examples/diff1d_halfsine.py 87 0 0 100% nnde/differentialequation/examples/diff1d_halfsine_increase.py 106 0 0 100% nnde/differentialequation/examples/diff1d_one.py 70 0 0 100% nnde/differentialequation/examples/diff1d_zero.py 70 0 0 100% nnde/differentialequation/examples/diff2d_halfsine.py 142 7 0 95% nnde/differentialequation/examples/diff2d_halfsine_increase.py 122 1 0 99% nnde/differentialequation/examples/diff3d_halfsine.py 213 118 0 45% nnde/differentialequation/examples/diff3d_halfsine_increase.py 188 11 0 94% nnde/differentialequation/examples/example_pde1ivp_01.py 53 28 0 47% nnde/differentialequation/examples/lagaris_01.py 13 5 0 62% nnde/differentialequation/examples/lagaris_02.py 13 5 0 62% nnde/differentialequation/examples/tests/init.py 0 0 0 100% nnde/differentialequation/examples/tests/test_diff1d_half.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_halfsine.py 262 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_halfsine_increase.py 272 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_one.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff1d_zero.py 263 1 0 99% nnde/differentialequation/examples/tests/test_diff2d_halfsine.py 493 11 0 98% nnde/differentialequation/examples/tests/test_diff2d_halfsine_increase.py 428 1 0 99% nnde/differentialequation/examples/tests/test_diff3d_halfsine.py 92 89 0 3% nnde/differentialequation/examples/tests/test_diff3d_halfsine_increase.py 710 1 0 99% nnde/differentialequation/examples/tests/test_example_pde1ivp_01.py 35 32 0 9% nnde/differentialequation/examples/tests/test_lagaris_01.py 8 5 0 38% nnde/differentialequation/examples/tests/test_lagaris_02.py 8 5 0 38% nnde/differentialequation/ode/init.py 0 0 0 100% nnde/differentialequation/ode/ode.py 3 0 0 100% nnde/differentialequation/ode/ode1.py 5 0 0 100% nnde/differentialequation/ode/ode1ivp.py 27 14 0 48% nnde/differentialequation/ode/tests/init.py 0 0 0 100% nnde/differentialequation/ode/tests/test_ODE.py 9 1 0 89% nnde/differentialequation/ode/tests/test_ODE1.py 12 1 0 92% nnde/differentialequation/ode/tests/test_ODE1IVP.py 7 1 0 86% nnde/differentialequation/pde/init.py 0 0 0 100% nnde/differentialequation/pde/pde.py 3 0 0 100% nnde/differentialequation/pde/pde1.py 5 0 0 100% nnde/differentialequation/pde/pde1ivp.py 29 16 0 45% nnde/differentialequation/pde/pde2.py 5 0 0 100% nnde/differentialequation/pde/pde2diff.py 47 28 0 40% nnde/differentialequation/pde/tests/init.py 0 0 0 100% nnde/differentialequation/pde/tests/test_PDE.py 9 1 0 89% nnde/differentialequation/pde/tests/test_PDE1.py 12 1 0 92% nnde/differentialequation/pde/tests/test_PDE1IVP.py 8 1 0 88% nnde/differentialequation/pde/tests/test_PDE2.py 12 1 0 92% nnde/differentialequation/pde/tests/test_PDE2DIFF.py 7 1 0 86% nnde/differentialequation/tests/init.py 0 0 0 100% nnde/differentialequation/tests/test_DifferentialEquation.py 12 1 0 92% nnde/exceptions/init.py 0 0 0 100% nnde/exceptions/nndeexception.py 2 0 0 100% nnde/exceptions/tests/init.py 0 0 0 100% nnde/exceptions/tests/test_NNDEException.py 7 1 0 86% nnde/math/init.py 0 0 0 100% nnde/math/kdelta.py 2 0 0 100% nnde/math/sigma.py 22 0 0 100% nnde/math/tests/init.py 0 0 0 100% nnde/math/tests/test_kdelta.py 11 1 0 91% nnde/math/tests/test_sigma.py 37 1 0 97% nnde/math/tests/test_trainingdata.py 27 1 0 96% nnde/math/trainingdata.py 41 16 0 61% nnde/neuralnetwork/init.py 0 0 0 100% nnde/neuralnetwork/neuralnetwork.py 8 0 0 100% nnde/neuralnetwork/nnode1ivp.py 250 214 0 14% nnde/neuralnetwork/nnpde1ivp.py 474 425 0 10% nnde/neuralnetwork/nnpde2diff.py 490 448 0 9% nnde/neuralnetwork/slffnn.py 3 0 0 100% nnde/neuralnetwork/tests/init.py 0 0 0 100% nnde/neuralnetwork/tests/test_NNODE1IVP.py 29 1 0 97% nnde/neuralnetwork/tests/test_NNPDE1IVP.py 7 1 0 86% nnde/neuralnetwork/tests/test_NeuralNetwork.py 15 1 0 93% nnde/neuralnetwork/tests/test_PDE2DIFF.py 27 1 0 96% nnde/neuralnetwork/tests/test_SLFFNN.py 9 1 0 89% nnde/trialfunction/init.py 0 0 0 100% nnde/trialfunction/diff1dtrialfunction.py 73 0 0 100% nnde/trialfunction/diff2dtrialfunction.py 79 0 0 100% nnde/trialfunction/diff3dtrialfunction.py 85 0 0 100% nnde/trialfunction/tests/init.py 0 0 0 100% nnde/trialfunction/tests/test_Diff1DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_Diff2DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_Diff3DTrialFunction.py 57 1 0 98% nnde/trialfunction/tests/test_TrialFunction.py 8 1 0 88% nnde/trialfunction/trialfunction.py 3 1 0 67% coverage.py v5.5 https://coverage.readthedocs.io, created at 2021-11-06 10:13 -0400 … On Mon, Nov 1, 2021 at 11:17 AM Patrick Diehl @.***> wrote: @elwinter https://github.com/elwinter Please address the editorial comments and we are good to accept the paper. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#3465 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABSFWC3G43L6PAECHZKKROLUJ2VO5ANCNFSM5AC2IOEQ . Triage notifications on the go with GitHub Mobile for iOS https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Android https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.

@elwinter Yes, that seems to be fine and this issue is resolved.

diehlpk commented 2 years ago

@elwinter I briefly read the paper and have the following remarks, so far

* [ ]  Please add the city, state, and country to the affiliation

* [ ]  Provide some reference to PyTorch and TensorFlow 2. In addition, I think the related work section is really sparse and some mention of other packages and how they differ would be beneficial for the reader.

* [ ]  You mention that FEM and FDM can be difficult to parallelize. Can you provide some reference for that claim?

@winter I think these are the last open items for the paper.

elwinter commented 2 years ago

Ok are there issues open for them, or are they to be handled outside the issue flow? Thanks Eric

Get Outlook for Androidhttps://aka.ms/ghei36

From: Patrick Diehl @.> Sent: Sunday, November 7, 2021 3:19:31 PM To: openjournals/joss-reviews @.> Cc: Eric Winter @.>; Mention @.> Subject: Re: [openjournals/joss-reviews] [REVIEW]: nnde: A Python package for solving differential equations using neural networks (#3465)

@elwinterhttps://github.com/elwinter I briefly read the paper and have the following remarks, so far

[ ] Please add the city, state, and country to the affiliation
[ ] Provide some reference to PyTorch and TensorFlow 2. In addition, I think the related work section is really sparse and some mention of other packages and how they differ would be beneficial for the reader.
[ ] You mention that FEM and FDM can be difficult to parallelize. Can you provide some reference for that claim?

@Winterhttps://github.com/Winter I think these are the last open items for the paper.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://github.com/openjournals/joss-reviews/issues/3465#issuecomment-962674280, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ABSFWC4Y6MD7IZFBM2K3NZTUK3NNHANCNFSM5AC2IOEQ. Triage notifications on the go with GitHub Mobile for iOShttps://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Androidhttps://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.

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