[Project Proposal]: Python Package to 3D Plot Stick Plots from ADCP Data in ERDDAP

[fgayanilo]

Project Description

Some RAs had been compiling data from ADCPs. Some of these profile data in GCOOS ERDDAP, report currents to 3,000m. Accessing the data from ERDDAP and plotting the ocean currents in 3D is a challenge. Overlaying the 2D plot from various selected stations on a Google Map is also desired. The later, is useful to validate hydrodynamic models of the study area.

Expected Outcomes

python package that can be imported to a project that can access ADCP data from an ERDDAP data endpoint and plot the results in 3D or 2D when appropriate that can be overlaid on a map, improving the plotting of the seawater surface current that is currently available in ERDDAP,

Skills required

python, Google map

Expertise

Intermediate

Topic Lead(s)

fgayanilo, mathewbiddle,

Relevant links

https://erddap2.gcoos.org/erddap

[SandeepJilla]

I am interested in this topic.

[Harish-2003]

Are there any good first issues so that i can able to familiarise myself with this project

[fgayanilo]

@Harish-2003 the GCOOS data portal has routines to plot the ADCP data on the fly but given the 'slowness' and unconfigurable (e.g., cannot add colors to indicate strength), we decided to hide the option from users. The following are useful links: • https://www.ndbc.noaa.gov/faq/adcp.shtml • https://notebook.community/rsignell-usgs/notebook/stickplot

Example of ADCP data in the Gulf of Mexico region on an ERDDAP: https://erddap.gcoos.org/erddap/search/index.html?page=1&itemsPerPage=1000&searchFor=NTL%20wmo-42

[MathewBiddle]

Thank you for taking the time to propose this topic! From the Code Sprint topic survey, this has garnered a lot of interest.

Following the contributing guidelines on selecting a code sprint topic I have assigned this topic to @fgayanilo. Unless indicated otherwise, the assignee will be responsible for identifying a plan for the code sprint topic, establishing a team, and taking the lead on executing said plan. The first action for the lead is to:

• [ ] Create a Sprint Topic website - https://github.com/ioos/ioos-code-sprint/blob/main/CONTRIBUTING.md#creating-sprint-topic-webpages

[fgayanilo]

Thanks @MathewBiddle

[MathewBiddle]

Hi @fgayanilo to make things a little bit easier, please edit this file https://github.com/ioos/ioos-code-sprint/blob/gh-pages/_topics/2024-05-01-01-test_something.md?plain=1 to reflect the plan discussed in this issue. Please rename the file to something more appropriate like 2024-05-01-01-adcp_visualization.md.

If you need any help with this, please don't hesitate to reach out.

[fgayanilo]

@MathewBiddle just completed the inputs, please check, and I can add/modify them as the need arises

[MathewBiddle]

@fgayanilo I see your changes in https://github.com/fgayanilo/ioos-code-sprint/blob/patch-1/_topics/2024-05-01-01-ADCP_visualization.md. That looks great!

Do you mind submitting a Pull Request to the gh-pages branch here?

[MathewBiddle]

See this documentation for help https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request#changing-the-branch-range-and-destination-repository

[MathewBiddle]

And we have a webpage! https://ioos.github.io/ioos-code-sprint/2024/topics/01-ADCP_visualization.html

Thanks @fgayanilo!

[FloraSauerbronn]

Hello, I am a GSoC contributor for the gliderpy project. Currently, I am familiarizing myself with accessing the ERDDAP service. I am registered for the code sprint, and this issue interests me. If there are any instructions on how to prepare and anything I can start working on related to this topic, I would appreciate it.

Thank you!

[fgayanilo]

Note that I have updated the list of contributors to Topic 1 and will make few more minor changes today. The full solution to the posted issue is now available at https://github.com/SandeepJilla/erddap_stick. You are welcome to submit changes as needed, and to continue to enhance the tool. Sample outputs (3D is interactive and using plotly):