Add mapping for output core_transport to IMAS#2224
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| # pylint: disable=invalid-name,unused-argument,too-many-positional-arguments | ||
| def core_transport_to_IMAS( | ||
| torax_config: model_config.ToraxConfig, |
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I think again, the config is not used?
| return ids | ||
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| def _fill_metadata(ids: ids_toplevel.IDSToplevel): |
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Is it possible to abstract the common parts of this to a function that can be used for multiple IDS?
| _fill_metadata(ids) | ||
| ids.time = times | ||
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| model_names = ["combined", "transport_solver", "neoclassical", "anomalous"] |
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can you retrieve these from the .keys() defined above?
| for idx, model_name in enumerate(model_names): | ||
| model_node = ids.model[idx] | ||
| model_node.identifier.name = model_name | ||
| model_node.identifier.index = _IMAS_MODEL_ID_TO_IDENTIFIER_INDEX.get( |
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similar comment if we actually need the index
| model_name, 0 | ||
| ) | ||
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| if model_name == "anomalous": |
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discussed to only fill in the turbulent transport models in the anomalous field here
| """Fills metadata in-place for the core_transport IDS.""" | ||
| ids.ids_properties.comment = ( | ||
| "IDS built from TORAX simulation transport coefficients. Grid based on " | ||
| "TORAX cell grid + boundaries." |
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similar comment to core_sources, probably best to output quantities on face grid here (as that's where TORAX transport coefficients are computed)
| ] | ||
| if non_constant_names: | ||
| model_node.code.name = "+".join(non_constant_names) | ||
| elif not model_name == "constant": |
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should this be transport_cfg.model_name?
| from torax._src.output_tools import post_processing | ||
| from torax._src.torax_pydantic import model_config | ||
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| _IMAS_MODEL_ID_TO_IDENTIFIER_INDEX = { |
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the values of this mapping are not used, does it need to be a mapping?
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| model_node.profiles_1d.resize(len(times)) | ||
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| for i in range(len(times)): |
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you can use enumerate here to get i and the t
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