Ocetrac: A Python package to track the spatiotemporal evolution of marine heatwaves

[hscannell]

Submitting Author: Hillary Scannell (@hscannell)
Package Name: Ocetrac One-Line Description of Package: Ocetrac is a python package to detect and track the spatiotemporal evolution of marine heatwaves. Repository Link: https://github.com/ocetrac/ocetrac Version submitted: 0.1.4 Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
Version accepted: TBD

---

Description

Ocetrac is an analysis routine and data processing tool used to extract the spatial trajectories of marine heatwaves (MHW) over time. It utilizes both morphological image processing and multiple object tracking to provide a new set metrics including event size, location, intensity, and duration. We anticipate that these metrics will be incorporated into machine learning forecasts to predict when and where MHWs are likely to occur, with the intent for operational use in warning vulnerable coastal communities of physical risk. While the motivation behind developing Ocetrac was to study MHWs, the algorithm could be applied to track any geographically coherent spatiotemporal anomaly.

Scope

• Please indicate which category or categories this package falls under:
  • [ ] Data retrieval
  • [ ] Data extraction
  • [ ] Data munging
  • [ ] Data deposition
  • [ ] Reproducibility
  • [x] Geospatial
  • [ ] Education
  • [ ] Data visualization*

* Please fill out a pre-submission inquiry before submitting a data visualization package. For more info, see notes on categories of our guidebook.

• Explain how the and why the package falls under these categories (briefly, 1-2 sentences): Ocetrac analyzes the spatiotemporal connectivity amongst geospatial anomalies. In doing so, it makes use of common morphological operations borrowed from multidimensional image processing.

• Who is the target audience and what are scientific applications of this package?
  The target audiences are data analysts and physical scientists charged with understanding the spatiotemporal evolution of anomalous events.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ? To our knowledge, there is no other Python package that achieves the goals of Ocetrac.

• 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:

Technical checks

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

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

Publication options

• [ ] Do you wish to automatically submit to the Journal of Open Source Software? If so:

JOSS Checks

- [ ] The package has an **obvious research application** according to JOSS's definition in their [submission requirements][JossSubmissionRequirements]. 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][JossSubmissionRequirements]: "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][JossPaperRequirements] 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: Do not submit your package separately to JOSS*

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

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.

• [x] 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.

Code of conduct

• [x] I agree to abide by pyOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

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

Editor and Review Templates

Editor and review templates can be found here

[lwasser]

Thank you for this submission @hscannell Given we are approaching the holidays and this week is the AGU meeting we will do our best to get back to you but if we determine this is in scope, The review likely won't begin until january given it's difficult to find reviewers at this time of the year! I just wanted to check in to let you know that this is on our radar! Welcome to pyopensc!

[lwasser]

@hscannell can you please update the template at hte top to ensure it contains the package repo link and also the description and in the correct spot? thank you.

[lwasser]

hi there @hscannell i am going to close this due to a lack of response. However if you decide you wish to have this package considered, please feel free to reopen and ping us here! All the best!!

[hscannell]

Hi @lwasser, sorry I missed your earlier comment! I will reopen another issue and address those changes.

[lwasser]

hey there @hscannell i am going through and cleaning up old issues and just noticed your reply here. i somehow must have missed it. If you are still interested in our review process in the future please feel free to start a new submission!! I know a lot of time has passed but I just wanted to say hi given i missed responding here and that I hope all is well!