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Add example for em_coupling conversion
Fixes iterorganization#22.
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‎docs/source/examples.rst‎

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.. _`IMAS-Python Examples`:
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IMAS-Python Examples
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====================
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Most IMAS-Python usage examples can be found throughout the documentation pages. On this
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page we collect some examples that are too big or too generic to include in specific
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pages. Currently this is a short list, but we expect that it will grow over time.
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.. toctree::
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:caption: IMAS-Python examples
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:maxdepth: 1
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examples/custom_conversion_em_coupling

‎docs/source/examples/custom_conversion_em_coupling.py‎

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"""IMAS-Python example for custom conversion logic.
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This example script loads a Data Entry (in Data Dictionary 3.38.1) created by
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DINA and converts the em_coupling IDS to DD 4.0.0.
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"""
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import imas
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from imas.ids_defs import IDS_TIME_MODE_INDEPENDENT
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input_uri = "imas:hdf5?path=/work/imas/shared/imasdb/ITER_SCENARIOS/3/105013/1"
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# An error is reported when there's already data at the output_uri!
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output_uri = "imas:hdf5?path=105013-1-converted"
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target_dd_version = "4.0.0"
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# Mapping of DD 3.38.1 em_coupling data to DD 4.0.0
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# Map the name of the matrix in DD 3.38.1 to the identifier and coordinate URIs
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COUPLING_MAPS = {
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"field_probes_active": dict(
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coupling_quantity=2,
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rows_uri="#magnetics/b_field_pol_probe",
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columns_uri="#pf_active/coil",
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),
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"field_probes_grid": dict(
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coupling_quantity=2,
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rows_uri="#magnetics/b_field_pol_probe",
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columns_uri="#pf_plasma/element",
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),
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"field_probes_passive": dict(
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coupling_quantity=2,
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rows_uri="#magnetics/b_field_pol_probe",
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columns_uri="#pf_passive/loop",
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),
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"mutual_active_active": dict(
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coupling_quantity=1,
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rows_uri="#pf_active/coil",
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columns_uri="#pf_active/coil",
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),
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"mutual_grid_active": dict(
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coupling_quantity=1,
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rows_uri="#pf_plasma/element",
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columns_uri="#pf_active/coil",
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),
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"mutual_grid_grid": dict(
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coupling_quantity=1,
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rows_uri="#pf_plasma/element",
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columns_uri="#pf_plasma/element",
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),
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"mutual_grid_passive": dict(
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coupling_quantity=1,
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rows_uri="#pf_plasma/element",
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columns_uri="#pf_passive/loop",
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),
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"mutual_loops_active": dict(
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coupling_quantity=1,
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rows_uri="#magnetics/flux_loop",
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columns_uri="#pf_active/coil",
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),
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"mutual_loops_passive": dict(
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coupling_quantity=1,
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rows_uri="#magnetics/flux_loop",
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columns_uri="#pf_passive/loop",
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),
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"mutual_loops_grid": dict(
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coupling_quantity=1,
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rows_uri="#magnetics/flux_loop",
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columns_uri="#pf_plasma/element",
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),
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"mutual_passive_active": dict(
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coupling_quantity=1,
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rows_uri="#pf_passive/loop",
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columns_uri="#pf_active/coil",
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),
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"mutual_passive_passive": dict(
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coupling_quantity=1,
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rows_uri="#pf_passive/loop",
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columns_uri="#pf_passive/loop",
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),
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}
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with (
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imas.DBEntry(input_uri, "r") as entry,
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imas.DBEntry(output_uri, "x", dd_version=target_dd_version) as out,
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):
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print("Loaded IMAS Data Entry:", input_uri)
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print("This data entry contains the following IDSs:")
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filled_idss = []
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for idsname in entry.factory.ids_names():
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occurrences = entry.list_all_occurrences(idsname)
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if occurrences:
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filled_idss.append(idsname)
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print(f"- {idsname}, occurrences: {occurrences}")
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print("")
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# Load and convert all IDSs (except em_coupling) with imas.convert_ids()
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# N.B. we know that the input URI doesn't have multiple occurrences, so
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# we do not need to worry about them:
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for idsname in filled_idss:
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if idsname == "em_coupling":
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continue
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print(f"Loading IDS: {idsname}...")
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ids = entry.get(idsname, autoconvert=False)
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print(f"Converting IDS {idsname} to DD {target_dd_version}...")
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ids4 = imas.convert_ids(
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ids,
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target_dd_version,
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provenance_origin_uri=input_uri,
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)
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print(f"Storing IDS {idsname} to output data entry...")
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out.put(ids4)
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print("Conversion for em_coupling:")
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emc = entry.get("em_coupling", autoconvert=False)
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print("Using standard convert, this may log warnings about discarding data")
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emc4 = imas.convert_ids(
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emc,
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target_dd_version,
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provenance_origin_uri=input_uri,
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)
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print("Starting custom conversion of the coupling matrices")
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for matrix_name, mapping in COUPLING_MAPS.items():
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# Skip empty matrices
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if not emc[matrix_name].has_value:
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continue
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# Allocate a new coupling_matrix AoS element
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emc4.coupling_matrix.resize(len(emc4.coupling_matrix) + 1, keep=True)
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# And fill it
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emc4.coupling_matrix[-1].name = matrix_name
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# Assigning an integer to the identifier will automatically fill the
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# index/name/description. See documentation:
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# https://imas-python.readthedocs.io/en/latest/identifiers.html
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emc4.coupling_matrix[-1].quantity = mapping["coupling_quantity"]
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emc4.coupling_matrix[-1].rows_uri = [mapping["rows_uri"]]
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emc4.coupling_matrix[-1].columns_uri = [mapping["columns_uri"]]
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emc4.coupling_matrix[-1].data = emc[matrix_name].value
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# N.B. the original data has no error_upper/error_lower so we skip these
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# Store em_coupling IDS
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out.put(emc4)
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print("Generating pf_plasma IDS...")
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# N.B. This logic is specific to DINA
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# Create a new pf_plasma IDS and set basic properties
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pf_plasma = out.factory.pf_plasma()
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pf_plasma.ids_properties.homogeneous_time = IDS_TIME_MODE_INDEPENDENT
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pf_plasma.ids_properties.comment = "PF Plasma generated from equilibrium"
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equilibrium = entry.get("equilibrium", lazy=True, autoconvert=False)
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r = equilibrium.time_slice[0].profiles_2d[0].grid.dim1
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z = equilibrium.time_slice[0].profiles_2d[0].grid.dim2
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nr, nz = len(r), len(z)
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# Generate a pf_plasma element for each grid point:
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pf_plasma.element.resize(nr * nz)
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for ir, rval in enumerate(r):
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for iz, zval in enumerate(z):
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element = pf_plasma.element[ir * nr + iz]
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element.geometry.geometry_type = 2 # rectangle
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element.geometry.rectangle.r = rval
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element.geometry.rectangle.z = zval
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# Store pf_plasma IDS
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out.put(pf_plasma)
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print("Conversion finished")

‎docs/source/examples/custom_conversion_em_coupling.rst‎

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Custom conversion of the ``em_coupling`` IDS
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============================================
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The ``em_coupling`` IDS has had a big change between Data Dictionary 3.x and Data
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Dictionary 4.x. These changes are not covered by the automatic conversions of
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:py:meth:`imas.convert_ids <imas.ids_convert.convert_ids>` because these are too
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code-specific.
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Instead we show on this page an example to convert a DINA dataset from DD 3.38.1 to DD
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4.0.0, which can be used as a starting point for converting output data from other codes
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as well.
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.. literalinclude:: custom_conversion_em_coupling.py

‎docs/source/index.rst‎

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cli
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netcdf
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changelog
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examples
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.. toctree::
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:caption: IMAS-Python training courses

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