Erik van Sebille

This has been fixed now with the implementation of native zarr output in #1199 and v2.4.0

Thanks for the update, @graceebc9. Could you try to install the parcels development again, but adapt line 8 in the `environment_py3_osx.yml` file from ``` - clang_osx-64 ``` to ``` -...

Or, perhaps what you could try first (before reinstalling with `clang_osx-arm64`) is to issue ``` export CC=gcc ``` Can you let me know if that worked?

Thanks for trying @graceebc9. Just to be clear, the steps should be 1. activate your condo environment 2. type `export CC=gcc` 3. start Jupyter If it still doesn't work with...

Has this been solved, @graceebc9? Perhaps try the new version v2.4.0 on https://anaconda.org/conda-forge/parcels, which also includes support for osx-arm64

Thanks for posting out that osx-arm is not listed at https://anaconda.org/conda-forge/parcels; perhaps @willirath can help us to support that too? I'll look into it as well In the meantime, v2.0...

Hi @JamiePringle! Thanks for raising this Issue/Question! Parallelisation is something we're still improving on, and indeed is a bit rudimentary now. Indeed, the clustering is based on lon/lat instead of...

Hi @JamiePringle. Yes, there is code to identify which grid cell indices particles are occupying, see https://github.com/OceanParcels/parcels/blob/master/parcels/particleset/particlesetsoa.py#L237-L265 (contributed by @angus-g). So you could call `pset.populate_indices()` to set values for `particle.xi`...

Thanks for the feedback, @JamiePringle . I leave it to @angus-g to comment why he chose to use `pykdtree` rather than `sklearn` for the KDtree implementation As for the `ParticleCollectionSOA`,...

Thanks @JamiePringle, for this extensive summary and feedback! Really useful also to have at hand when we further develop MPI capacity in Parcels One thing though that struck me as...