Update README.md
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README.md
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@@ -484,6 +484,28 @@ With the release of this dataset, we aim to lower the barrier for optimization a
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- **Paper:** [not published yet]
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- **Code:** https://github.com/proximafusion/constellaration
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## Uses
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### Basic Usage
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visualization.plot_flux_surfaces(vmecpp_wout, boundary)
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```
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Save ideal MHD equilibrium to VMEC2000 WOut file:
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```python
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import pathlib
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from constellaration.utils import file_exporter
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file_exporter.to_vmec2000_wout_file(vmecpp_wout, pathlib.Path("vmec2000_wout.nc"))
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```
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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The dataset consists of 2 tabular parts. Both parts have a column `plasma_config_id` in common which can be used to associate respective entries.
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### 1. `full_json`/`full_flat`
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Contains information about:
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- plasma boundaries
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- ideal MHD metrics
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- omnigenous field and targets, used as input for sampling of plasma boundaries
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- sampling settings for various methods ([DESC](https://desc-docs.readthedocs.io/en/stable/), [VMEC](https://github.com/proximafusion/vmecpp), QP initialization, Near-axis expansion)
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- Miscellaneous information about errors that might have occurred during sampling or metrics computation.
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The `full_json` variant of the dataset contains for each of the components listed about an identifier column (ending with `.id`), as well as a JSON column.
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The `full_flat` variant contains the same information as `full_json` but with all JSON columns flattened into one column per leaf in the nested JSON structure (with `.` separating the keys on the JSON path to the respective leaf).
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### 2. `vmecpp_ideal_mhd_equilibria`
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Contain for each plasma boundary a JSON representations of the "WOut" file as obtained when running VMEC++ initialized on the boundary.
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The JSON representation can be converted to a VMEC2000 output file.
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## Dataset Creation
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### Curation Rationale
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**BibTeX:**
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## Glossary
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- **Paper:** [not published yet]
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- **Code:** https://github.com/proximafusion/constellaration
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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The dataset consists of 2 tabular parts. Both parts have a column `plasma_config_id` in common which can be used to associate respective entries.
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### 1. `full_json`/`full_flat`
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Contains information about:
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- plasma boundaries
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- ideal MHD metrics
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- omnigenous field and targets, used as input for sampling of plasma boundaries
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- sampling settings for various methods ([DESC](https://desc-docs.readthedocs.io/en/stable/), [VMEC](https://github.com/proximafusion/vmecpp), QP initialization, Near-axis expansion)
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- Miscellaneous information about errors that might have occurred during sampling or metrics computation.
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+
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The `full_json` variant of the dataset contains for each of the components listed about an identifier column (ending with `.id`), as well as a JSON column.
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+
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The `full_flat` variant contains the same information as `full_json` but with all JSON columns flattened into one column per leaf in the nested JSON structure (with `.` separating the keys on the JSON path to the respective leaf).
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### 2. `vmecpp_ideal_mhd_equilibria`
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Contain for each plasma boundary a JSON representations of the "WOut" file as obtained when running VMEC++ initialized on the boundary.
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The JSON representation can be converted to a VMEC2000 output file.
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## Uses
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### Basic Usage
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visualization.plot_flux_surfaces(vmecpp_wout, boundary)
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```
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Save ideal MHD equilibrium to *VMEC2000 WOut* file:
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```python
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import pathlib
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from constellaration.utils import file_exporter
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file_exporter.to_vmec2000_wout_file(vmecpp_wout, pathlib.Path("vmec2000_wout.nc"))
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```
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## Dataset Creation
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### Curation Rationale
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**BibTeX:**
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@article{article_id,
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author = {Santiago A Cadena, Andrea Merlo, Emanuel Laude, Alexander Bauer, Atul Agrawal, Maria Pascu, Marija Savtchouk, Lukas Bonauer, Enrico Guiraud, Stuart R. Hudson, Markus Kaiser},
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title = {ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks},
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journal = {NeurIPS 2025 Datasets and Benchmarks Track},
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year = {2025}
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}
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## Glossary
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