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That's great news. current wradlib statusI'm not sure if PyArt devs have followed the developments within wradlib in the last 3 years. Currently wradlib is able to read It's currently designed as xarray-Backends ("odim", "gamic", "cfradial1", "cfradial2", "iris", "rainbow") so that you can get the volume with wradlib-function: f = 'cfrad.20080604_002217_000_SPOL_v36_SUR.nc'
vol = wrl.io.open_cfradial1_dataset(f) or just one sweep using plain swp = xr.open_dataset(f, engine="cfradial1", group="sweep_9") Even reading multiple timesteps into one dataset is as easy as using the available other resourcesWith the recently emerging https://github.com/TomNicholas/datatree and https://github.com/alexamici/xarray-datagroup the wradlib developments will surely follow those tracks with nested (group) structures. FM301The overall implementation should closely adhere or be based on the approaching FM301 WMO standard (https://community.wmo.int/wmo-jet-owr-seminar-series-weather-radar-data-exchange). So the RecommendationsFor a PyArt Another idea would be to just use the already implemented wradlib xarray backends/reading functionality as loader/base for the Anyway, great to see this coming to PyArt. I'm open to answer any questions regarding implementation details on the wradlib side, problems we had over time and how they have been solved. |
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This is wonderful to hear, and I'm excited to follow along as this moves forward! I wouldn't be able to make the next dev call due to travel, but I'd love to be able to join in later on. A few limited thoughts from a downstream "PyART consumer" project (OpenMosaic):
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Just here to encourage you all to engage with the design conversations happening around the datatree/datagroup concept. Based on your slide that references a dict-like object that points to multiresolution dataarrays/datasets, I suspect there is a good deal of synergy in the development happening there right now. |
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After some conversations with @TomNicholas at SciPy last week, I put together a prototype of this functionality I think we should decide where we want to allow multiple volumes in a single object, or just a single volume. Open to discussion! The linked notebook combines multiple volumes with their associated sweeps, with the hierarchy being:
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Coming back to this - we are moving development to the xradar, a dedicated IO package that will used both here as well as wradlib! From @kmuehlbauer 's discussion over in the wradlib repository: "wradlib's xarray reading capability will be moved to xradar. If that process is finished, xradar becomes a dependency of wradlib. For the user only minor adaptions on the code are needed" A similar path will be taken with Py-ART. Xradar will become a dependency of Py-ART, and will enable this xarray integration. |
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Starting a discussion here to open the conversation about updating the Radar object to utilize the xarray data model!
We have started a design presentation, and open to feedback/discussion!
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