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Submission for AMS #174

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14 of 32 tasks
jinningwang opened this issue Apr 22, 2024 · 8 comments
Open
14 of 32 tasks

Submission for AMS #174

jinningwang opened this issue Apr 22, 2024 · 8 comments
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@jinningwang
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jinningwang commented Apr 22, 2024

Submitting Author: Jinning Wang (@jinningwang)
All current maintainers: @jinningwang
Package Name: AMS
One-Line Description of Package: Power system dispatch modeling and dispatch-dynamic co-simulation.
Repository Link: https://github.com/CURENT/ams
Version submitted: v0.9.6
EIC: @Batalex
Editor: @NimaSarajpoor
Reviewer 1: Alireza Gholamzadeh Khoee @Alizak-Mech
Reviewer 2: Alireza Alamgir Tehrani @AlirezaAlamgir
Reviewer 3: Kavian Mashayekhi @Kawians
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD


Code of Conduct & Commitment to Maintain Package

Description

As part of CURENT Large-scale Testbed platform, AMS serves as power system production cost modeling. Our framework offers a modularized approach that seamlessly incorporates dynamics, enhancing traditional dispatch modeling methods. We create a versatile solution that bridges the gap between device-level and system-level models. The tool is developed to be extensible, scalable, compatible, and interoperable.

Scope

  • Please indicate which category or categories.
    Check out our package scope page to learn more about our
    scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

    • Data retrieval
    • Data extraction
    • Data processing/munging
    • Data deposition
    • Data validation and testing
    • Data visualization1
    • Workflow automation
    • Citation management and bibliometrics
    • Scientific software wrappers
    • Database interoperability

Domain Specific

  • Geospatial
  • Education

Community Partnerships

If your package is associated with an
existing community please check below:

  • For all submissions, explain how the and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

    • Who is the target audience and what are scientific applications of this package?
      Power system researchers and engineers.
      Power system steady state modeling and analysis.

    • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
      There are some Python packages cover part of our functions: PYPOWER, pandapower, and PyPSA.
      Compared to existing tools that focus on fixed power system optimization problems, our package AMS enables customizing formulations thus enable rapid prototyping for renewables integration.
      Additionally, with the built-in interface with dynamic simulator ANDES, AMS allows native interoperation between dynamics and dispatch, which significantly relieves the researchers manual efforts when conducting power system simulations.

    • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:
      Presubmission Inquiry for AMS #169
      @Batalex

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

  • does not violate the Terms of Service of any service it interacts with.
  • uses an OSI approved license.
  • contains a README with instructions for installing the development version.
  • includes documentation with examples for all functions.
  • contains a tutorial with examples of its essential functions and uses.
  • has a test suite.
  • has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

JOSS Checks
  • The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
  • The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

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This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

  • Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

  • I have read the author guide.
  • I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

Please fill out our survey

P.S. Have feedback/comments about our review process? Leave a comment here

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The editor template can be found here.

The review template can be found here.

Footnotes

  1. Please fill out a pre-submission inquiry before submitting a data visualization package.

@Batalex
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Batalex commented Apr 24, 2024

Editor in Chief checks

Hi there! Thank you for submitting your package for pyOpenSci review. Below are the basic checks that your package needs to pass to begin our review. If some of these are missing, we will ask you to work on them before the review process begins.

Please check our Python packaging guide for more information on the elements below.

  • Installation The package can be installed from a community repository such as PyPI (preferred), and/or a community channel on conda (e.g. conda-forge, bioconda).
    • The package imports properly into a standard Python environment import package.
      Just so you know, I was unable to import the package on OS X with the following error: symbol not found in flat namespace '_klu_l_analyze'. I'll report it properly later.
  • Fit The package meets criteria for fit and overlap.
  • Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
    • User-facing documentation that overviews how to install and start using the package.
    • Short tutorials that help a user understand how to use the package and what it can do for them.
    • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
  • Core GitHub repository Files
    • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
    • Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
    • Code of Conduct The package has a CODE_OF_CONDUCT.md file.
    • License The package has an OSI approved license.
      NOTE: We prefer that you have development instructions in your documentation too.
  • Issue Submission Documentation All of the information is filled out in the YAML header of the issue (located at the top of the issue template).
  • Automated tests Package has a testing suite and is tested via a Continuous Integration service.
  • Repository The repository link resolves correctly.
  • Package overlap The package doesn't entirely overlap with the functionality of other packages that have already been submitted to pyOpenSci.
  • Archive (JOSS only, may be post-review): The repository DOI resolves correctly.
  • Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

  • Initial onboarding survey was filled out
    We appreciate each maintainer of the package filling out this survey individually. 🙌
    Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. 🙌

@jinningwang
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Hi @Batalex,

Thanks for your response.

Just so you know, I was unable to import the package on OS X with the following error: symbol not found in flat namespace '_klu_l_analyze'. I'll report it properly later.

We run into it before and have addressed it, CURENT/andes#508

Another possible solution is to add the used environment to path:

export PATH="/path/to/conda/envs/ams/bin:$PATH"

@Batalex
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Batalex commented Jun 11, 2024

Hey there @jinningwang!
We have an editor 🙌

@NimaSarajpoor will take over this submission, and will most likely handle ANDES after that.
Happy reviewing y'all

@Batalex Batalex removed their assignment Jun 11, 2024
@NimaSarajpoor
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NimaSarajpoor commented Jun 12, 2024

Editor response to review:


Editor comments

👋 Hi (reviewer1 @Alizak-Mech and reviewer2 @AlirezaAlamgir) and reviewer3 @Kawians. Thank you for volunteering to review for pyOpenSci!

[Note] Reviewer 1 and 2 (@Alizak-Mech and @AlirezaAlamgir) will collaborate together and submit one review from their side.

Please fill out our pre-review survey

Before beginning your review, please fill out our pre-review survey. This helps us improve all aspects of our review and better understand our community. No personal data will be shared from this survey - it will only be used in an aggregated format by our Executive Director to improve our processes and programs.

  • reviewer 1 survey completed.
  • reviewer 2 survey completed.
  • reviewer 3 survey completed.

The following resources will help you complete your review:

  1. Here is the reviewers guide. This guide contains all of the steps and information needed to complete your review.
  2. Here is the review template that you will need to fill out and submit
    here as a comment, once your review is complete.

Please get in touch with any questions or concerns! Your review is due:

Reviewers: @Alizak-Mech @AlirezaAlamgir @Kawians
Due date: Regular deadline 2024-08-15 (see note below)

[Note] deadline extension
Yellow deadline: 2024-08-30
Red deadline: 2024-09-07

@NimaSarajpoor
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@jinningwang
Still looking for reviewers. Not easy to find people with domain knowledge interested in reviewing software. I found two reviewers who seem to have domain knowledge and experience in python programming. They, however, are looking for 4-6 weeks (rather than 3 weeks). It might make sense as it is summer.

I was wondering if you are okay with that?

@jinningwang
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@jinningwang Still looking for reviewers. Not easy to find people with domain knowledge interested in reviewing software. I found two reviewers who seem to have domain knowledge and experience in python programming. They, however, are looking for 4-6 weeks (rather than 3 weeks). It might make sense as it is summer.

I was wondering if you are okay with that?

Yes, it works for me. Thanks for your efforts, especially considering it is a small crowded domain-software.

@NimaSarajpoor
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Top comment and Editor's Response are updated.

@NimaSarajpoor
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@Alizak-Mech @AlirezaAlamgir @Kawians
Please gives a thumbs up (👍) on this comment so that I know if anyone is missing.

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