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Merge pull request #2477 from Parcels-code/convert_from_copernicusmarine
Creating convert.copernicusmarine_to_sgrid() function
2 parents 977d926 + 3234672 commit f111dfa

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+208
-178
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‎docs/getting_started/explanation_concepts.md‎

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@@ -36,7 +36,9 @@ For several common input datasets, such as the Copernicus Marine Service analysi
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```python
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dataset = xr.open_mfdataset("insert_copernicus_data_files.nc")
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fieldset = parcels.FieldSet.from_copernicusmarine(dataset)
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fields = {"U": ds_fields["uo"], "V": ds_fields["vo"]}
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ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)
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fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
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```
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In some cases, we might want to combine `parcels.Field`s from different sources in the same `parcels.FieldSet`, such as ocean currents from one dataset and Stokes drift from another. This is possible in Parcels by adding each `parcels.Field` separately:

‎docs/getting_started/tutorial_output.ipynb‎

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@@ -59,7 +59,10 @@
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"ds_fields = xr.open_mfdataset(f\"{example_dataset_folder}/*.nc\", combine=\"by_coords\")\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)"
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
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]
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},
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{
@@ -557,7 +560,7 @@
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"metadata": {
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"celltoolbar": "Metagegevens bewerken",
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"kernelspec": {
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"display_name": "test-notebooks",
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"display_name": "docs",
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"language": "python",
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"name": "python3"
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},
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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": "3.11.0"
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"version": "3.14.2"
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}
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},
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"nbformat": 4,

‎docs/getting_started/tutorial_quickstart.md‎

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@@ -42,11 +42,16 @@ As we can see, the reanalysis dataset contains eastward velocity `uo`, northward
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(`thetao`) and salinity (`so`) fields.
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These hydrodynamic fields need to be stored in a {py:obj}`parcels.FieldSet` object. Parcels provides tooling to parse many types
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of models or observations into such a `parcels.FieldSet` object. Here, we use {py:func}`parcels.FieldSet.from_copernicusmarine()`, which
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recognizes the standard names of a velocity field:
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of models or observations into such a `parcels.FieldSet` object. This is done in a two-step approach.
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First, we convert the dataset into an SGRID-compliant dataset, for example by using a version of `parcels.convert.<MODEL>_to_sgrid()`. Then, we create the `parcels.FieldSet` from the SGRID-compliant dataset using `parcels.FieldSet.from_sgrid_conventions()`.
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Below, we use a combination of {py:func}`parcels.convert.copernicusmarine_to_sgrid()` and {py:func}`parcels.FieldSet.from_sgrid_conventions()`, providing the names of the velocity fields in the dataset in the dictionary `fields`:
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```{code-cell}
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fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)
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fields = {"U": ds_fields["uo"], "V": ds_fields["vo"]}
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ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)
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fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
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```
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The subset contains a region of the Agulhas current along the southeastern coast of Africa:

‎docs/user_guide/examples/explanation_kernelloop.md‎

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@@ -68,7 +68,14 @@ ds_fields["VWind"] = xr.DataArray(
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data=np.zeros((tdim, ydim, xdim)),
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coords=[ds_fields.time, ds_fields.latitude, ds_fields.longitude])
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fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)
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fields = {
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"U": ds_fields["uo"],
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"V": ds_fields["vo"],
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"UWind": ds_fields["UWind"],
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"VWind": ds_fields["VWind"],
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}
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ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)
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fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
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# Create a vecorfield for the wind
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windvector = parcels.VectorField(

‎docs/user_guide/examples/tutorial_Argofloats.ipynb‎

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@@ -121,7 +121,16 @@
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"# TODO check how we can get good performance without loading full dataset in memory\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)\n",
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"# Select fields\n",
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"fields = {\n",
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" \"U\": ds_fields[\"uo\"],\n",
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" \"V\": ds_fields[\"vo\"],\n",
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" \"thetao\": ds_fields[\"thetao\"],\n",
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"}\n",
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"\n",
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
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"fieldset.add_constant(\"mindepth\", 1.0)\n",
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"\n",
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"# Define a new Particle type including extra Variables\n",

‎docs/user_guide/examples/tutorial_delaystart.ipynb‎

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@@ -57,7 +57,10 @@
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"ds_fields = xr.open_mfdataset(f\"{example_dataset_folder}/*.nc\", combine=\"by_coords\")\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)"
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
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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": "test-notebooks",
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"display_name": "docs",
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"language": "python",
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"name": "python3"
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},
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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": "3.11.0"
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"version": "3.14.2"
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}
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},
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"nbformat": 4,

‎docs/user_guide/examples/tutorial_diffusion.ipynb‎

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"metadata": {},
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"outputs": [],
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"source": [
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)\n",
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"fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
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"\n",
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"\n",
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"def degree_lat_to_meter(d):\n",

‎docs/user_guide/examples/tutorial_dt_integrators.ipynb‎

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@@ -68,7 +68,10 @@
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"ds_fields = xr.open_mfdataset(f\"{example_dataset_folder}/*.nc\", combine=\"by_coords\")\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)\n",
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"]}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
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"\n",
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"# Check field resolution in time and space\n",
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"print(\n",

‎docs/user_guide/examples/tutorial_gsw_density.ipynb‎

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"# TODO check how we can get good performance without loading full dataset in memory\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)"
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"fields = {\n",
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" \"U\": ds_fields[\"uo\"],\n",
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" \"V\": ds_fields[\"vo\"],\n",
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" \"thetao\": ds_fields[\"thetao\"],\n",
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" \"so\": ds_fields[\"so\"],\n",
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"}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
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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": "test-notebooks",
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"display_name": "docs",
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"language": "python",
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"name": "python3"
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},
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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": "3.11.0"
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"version": "3.14.2"
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}
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},
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"nbformat": 4,

‎docs/user_guide/examples/tutorial_sampling.ipynb‎

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"ds_fields = xr.open_mfdataset(f\"{example_dataset_folder}/*.nc\", combine=\"by_coords\")\n",
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"ds_fields.load() # load the dataset into memory\n",
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"\n",
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"fieldset = parcels.FieldSet.from_copernicusmarine(ds_fields)"
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"# Convert to SGRID-compliant dataset and create FieldSet\n",
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"fields = {\"U\": ds_fields[\"uo\"], \"V\": ds_fields[\"vo\"], \"thetao\": ds_fields[\"thetao\"]}\n",
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"ds_fset = parcels.convert.copernicusmarine_to_sgrid(fields=fields)\n",
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"fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
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]
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},
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{
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"metadata": {
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"celltoolbar": "Raw-celnotatie",
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"kernelspec": {
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"display_name": "test-notebooks",
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"display_name": "docs",
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"language": "python",
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"name": "python3"
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},
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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": "3.11.0"
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"version": "3.14.2"
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},
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"pycharm": {
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"stem_cell": {

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