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Merge branch 'v4-dev' into feature/from_fesom2
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‎.github/ci/recipe.yaml‎

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- python >=3.11
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- cftime >=1.6.3
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- dask >=2024.5.1
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- matplotlib-base >=2.0.2
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- netcdf4 >=1.7.2
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- numpy >=2.1.0
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- platformdirs
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- pytest
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- trajan
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- tqdm >=4.50.0
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- xarray >=2024.5.0
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- cf_xarray >=0.8.6

‎docs/examples/tutorial_gsw_density.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "0",
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"metadata": {},
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"source": [
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"# Using the `gsw` toolbox to compute density"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1",
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"metadata": {},
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"source": [
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"This tutorial shows how to use the [`gsw` toolbox](https://teos-10.github.io/GSW-Python/) (the Gibbs SeaWater Oceanographic Toolbox of TEOS-10) within Parcels to compute density from temperature and salinity fields. The `gsw` toolbox can be installed via `conda install gsw`."
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]
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},
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{
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"cell_type": "markdown",
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"id": "2",
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"metadata": {},
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"source": [
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"First, load the necessary libraries and the data:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gsw # The package to calculate density from temperature, salinity and depth\n",
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"import numpy as np\n",
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"import xarray as xr\n",
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"\n",
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"import parcels\n",
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"\n",
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"# Load the CopernicusMarine data in the Agulhas region from the example_datasets\n",
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"example_dataset_folder = parcels.download_example_dataset(\n",
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" \"CopernicusMarine_data_for_Argo_tutorial\"\n",
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")\n",
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"\n",
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"ds = xr.open_mfdataset(f\"{example_dataset_folder}/*.nc\", combine=\"by_coords\")\n",
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"\n",
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"# TODO check how we can get good performance without loading full dataset in memory\n",
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"ds.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4",
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"metadata": {},
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"source": [
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"Now, define a custom Particle class that includes temperature, salinity, and density as variables, and create a ParticleSet with one particle at a known location:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5",
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"metadata": {},
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"outputs": [],
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"source": [
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"GSWParticle = parcels.Particle.add_variable(\n",
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" [\n",
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" parcels.Variable(\"temp\", dtype=np.float32, initial=np.nan),\n",
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" parcels.Variable(\"salt\", dtype=np.float32, initial=np.nan),\n",
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" parcels.Variable(\"density\", dtype=np.float32, initial=np.nan),\n",
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" ]\n",
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")\n",
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"\n",
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"# Initiate one Argo float in the Agulhas Current\n",
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"pset = parcels.ParticleSet(\n",
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" fieldset=fieldset,\n",
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" pclass=GSWParticle,\n",
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" lon=[32],\n",
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" lat=[-31],\n",
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" z=[200],\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6",
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"metadata": {},
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"source": [
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"Now (as the core part of this tutorial) define a custom kernel that uses the `gsw` toolbox to compute density from temperature and salinity:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7",
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"metadata": {},
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"outputs": [],
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"source": [
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"def ParcelsGSW(particles, fieldset):\n",
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" particles.temp = fieldset.thetao[particles]\n",
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" particles.salt = fieldset.so[particles]\n",
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" pressure = gsw.p_from_z(-particles.z, particles.lat)\n",
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" particles.density = gsw.density.rho(particles.salt, particles.temp, pressure)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8",
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"metadata": {},
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"source": [
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"Finally, run the `ParcelsGSW` Kernel for one timestep and check (for Continuous Integration purposes) that the computed density is as expected:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9",
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"metadata": {},
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"outputs": [],
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"source": [
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"pset.execute(ParcelsGSW, runtime=np.timedelta64(1, \"s\"), dt=np.timedelta64(1, \"s\"))\n",
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"\n",
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"np.testing.assert_allclose(pset.density, [1026.8281], rtol=1e-5)\n",
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"\n",
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"print(\n",
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" f\"Temperature: {pset.temp[0]:.2f}, Salinity: {pset.salt[0]:.2f}, Density: {pset.density[0]:.2f}\"\n",
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")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "parcels",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎pixi.toml‎

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[workspace]
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name = "Parcels"
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preview = ["pixi-build"]
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channels = ["conda-forge"]
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platforms = ["win-64", "linux-64", "osx-64", "osx-arm64"]
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[package]
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name = "parcels"
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version = "dynamic" # dynamic versioning needs better support in pixi https://github.com/prefix-dev/pixi/issues/2923#issuecomment-2598460666 . Putting `version = "dynamic"` here for now until pixi recommends something else.
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license = "MIT" # can remove this once https://github.com/prefix-dev/pixi-build-backends/issues/397 is resolved
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[package.build]
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backend = { name = "pixi-build-python", version = "==0.4.0" }
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[package.host-dependencies]
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setuptools = "*"
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setuptools_scm = "*"
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# TODO: Re-enable pixi-build once https://github.com/prefix-dev/pixi-build-backends/issues/411 is fixed, and remove pypi install of Parcels
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# preview = ["pixi-build"]
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# [package]
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# name = "parcels"
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# version = "dynamic" # dynamic versioning needs better support in pixi https://github.com/prefix-dev/pixi/issues/2923#issuecomment-2598460666 . Putting `version = "dynamic"` here for now until pixi recommends something else.
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# license = "MIT" # can remove this once https://github.com/prefix-dev/pixi-build-backends/issues/397 is resolved
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#
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# [package.build]
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# backend = { name = "pixi-build-python", version = "==0.4.0" }
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#
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# [package.host-dependencies]
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# setuptools = "*"
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# setuptools_scm = "*"
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[environments]
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test-latest = { features = ["test"], solve-group = "test" }
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[dependencies] # keep section in sync with pyproject.toml dependencies
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python = ">=3.11,<3.13"
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parcels = { path = "." }
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# parcels = { path = "." }
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netcdf4 = ">=1.7.2"
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numpy = ">=2.1.0"
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tqdm = ">=4.50.0"
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cftime = ">=1.6.3"
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pooch = ">=1.8.0"
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[pypi-dependencies]
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parcels = { path = ".", editable = true }
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[feature.minimum.dependencies]
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python = "==3.11"
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netcdf4 = "==1.7.2"
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jupyter = "*"
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trajan = "*"
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matplotlib-base = ">=2.0.2"
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gsw = "*"
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[feature.docs.dependencies]
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numpydoc = "!=1.9.0"

‎src/parcels/_core/kernel.py‎

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from __future__ import annotations
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import math # noqa: F401
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import random # noqa: F401
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import types
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import warnings
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from typing import TYPE_CHECKING
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def add_positionupdate_kernels(self):
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# Adding kernels that set and update the coordinate changes
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def Setcoords(particles, fieldset): # pragma: no cover
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import numpy as np # noqa
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particles.lon += particles.dlon
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particles.lat += particles.dlat
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particles.z += particles.dz

‎src/parcels/_tutorial.py‎

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],
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"CopernicusMarine_data_for_Argo_tutorial": [
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"cmems_mod_glo_phy-cur_anfc_0.083deg_P1D-m_uo-vo_31.00E-33.00E_33.00S-30.00S_0.49-2225.08m_2024-01-01-2024-02-01.nc",
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"cmems_mod_glo_phy-so_anfc_0.083deg_P1D-m_so_31.00E-33.00E_33.00S-30.00S_0.49-2225.08m_2024-01-01-2024-02-01.nc",
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"cmems_mod_glo_phy-thetao_anfc_0.083deg_P1D-m_thetao_31.00E-33.00E_33.00S-30.00S_0.49-2225.08m_2024-01-01-2024-02-01.nc",
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],
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"DecayingMovingEddy_data": [

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