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Description
as discussed in #154 I make a full submission
Submitting Author: Romain Caneill (@rcaneill)
All current maintainers: (@rcaneill)
Package Name: xnemogcm
One-Line Description of Package: Interface to open NEMO global circulation model output dataset with xarray and create a xgcm grid.
Repository Link: https://github.com/rcaneill/xnemogcm/
Version submitted: 0.4.2
Editor: @ocefpaf
Reviewer 1: @paigem
Reviewer 2: @callumrollo
Archive:
Version accepted: 0.4.3
JOSS DOI: N/A
Date accepted (month/day/year): 04/02/2024
Code of Conduct & Commitment to Maintain Package
- I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package after should it be accepted.
- I have read and will commit to package maintenance after the review as per the pyOpenSci Policies Guidelines.
Description
xnemogcm is an interface to open NEMO ocean global circulation model output dataset and create a xgcm grid. NEMO 3.6, 4.0, and 4.2.0 are tested and supported. It can handle large simulations, is aware of meshgrid files, and makes it easy to handle the netCDF outputs od NEMO.
Scope
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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 visualization[^1]
- Workflow automation
- Citation management and bibliometrics
- Scientific software wrappers
- Database interoperability
Domain Specific & Community Partnerships
- [ ] Geospatial
- [ ] Education
- [x] Pangeo
Community Partnerships
If your package is associated with an
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- My package adheres to the Pangeo standards listed in the pyOpenSci peer review guidebook
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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):
xnemogcm extracts the NEMO output and adds metadata (+ do some other things as change coordinate names, etc), and produces new xarray datasets. It is thus data processing.
- Who is the target audience and what are scientific applications of this package?
The target audience is anyone working with NEMO outputs and python. The scientific applications are any analyse that one want to do with NEMO outputs.
- Are there other Python packages that accomplish the same thing? If so, how does yours differ?
Yes, xorca. My package differs as 1) it is more recent, updated to work with newer versions of NEMO, and 2) it uses a very different method to sort variables on the proper grid point (center, face, etc) (cf https://xgcm.readthedocs.io/en/latest/grids.html). xorca uses hardcoded variables, while xnemogcm uses attributes (either output directly by NEMO, or they can also be given while calling the processing functions).
- If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or
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the editor you contacted:
I made a pre-submission enquiry, issue #154
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- 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.
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paper.md
matching JOSS's requirements with a high-level description in the package root or ininst/
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