Custom pedestal api #1752
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Custom pedestal api #1752
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This commit implements a Custom Pedestal Model API that allows users to define custom pedestal scaling laws without modifying TORAX source code. Fixes google-deepmind#1711 ## Changes - Add CustomPedestalModel class supporting user-defined callable functions - Add CustomPedestal Pydantic configuration - Update PedestalConfig union to include CustomPedestal - Add comprehensive unit tests (7 test cases) - Add example configuration with EPED-like scaling - Add complete API documentation ## Features Users can now provide Python functions to compute: - Ion temperature at pedestal (T_i_ped) - Electron temperature at pedestal (T_e_ped) - Electron density at pedestal (n_e_ped) - Optional dynamic pedestal location (rho_norm_ped_top) Functions receive full access to runtime parameters, geometry, and core profiles, enabling machine-specific scaling laws (e.g., STEP pedestal models with Europed data fits). ## API Design Follows the transport model pattern with: - JAX Model Layer: CustomPedestalModel (frozen dataclass) - Pydantic Config Layer: CustomPedestal (validation) - Runtime Parameters: time-varying support Fully backwards compatible - no changes to existing models.
- Add public pedestal API (torax/pedestal.py) following transport model pattern - Remove PR documentation files (PR_SUMMARY.md, PR_TEXT.md, CUSTOM_PEDESTAL_API.md) - Add RST documentation (docs/custom_pedestal_models.rst) - concise and properly formatted - Simplify example to single model using public API and StaticDataclass - Fix test imports (removed 'as pm' alias) - Revert PedestalConfig formatting to single line Addresses all review comments from @tamaranorman
- Use public API throughout (Geometry, CoreProfiles, JAX_STATIC from torax) - Remove StaticDataclass from inheritance (parent already has it) - Simplify example config (minimal pedestal-only config) - Add test for custom_pedestal_example in examples_test.py - Clarify in RST docs that config example is minimal Addresses all review comments from @tamaranorman
| register_model.register_pedestal_model(TestPedestal) | ||
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| # Verify it can be instantiated | ||
| config = TestPedestal(test_value=99.0) |
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What we need to test is that it can be instantiated through the ModelConfig API not directly which works even without the test
| register_model.register_pedestal_model(Config1) | ||
| register_model.register_pedestal_model(Config2) | ||
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| # Verify both can be instantiated |
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Add a reference to this to init.py
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Can you also fix the broken tests |
…le to __init__.py - Update register_model_test.py to test model instantiation through ToraxConfig.from_dict() instead of direct class instantiation - Add pedestal module import to torax/__init__.py for better API accessibility - Tests now properly verify that registered models work through the pydantic discriminator system Addresses maintainer feedback on PR.
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| # Verify it can be instantiated through the ModelConfig API | ||
| # Create a minimal ToraxConfig using from_dict to test the registration | ||
| minimal_config_dict = { |
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Just use the config from test_utils.default_configs here and below
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Please also fix the tests |
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@Aaryan-549 are you still working on this PR and planning to make the changes in response to the review comments? |
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Yes, I am really sorry for the delay. I'll push a PR with all the changes required ASAP. |
…nfig, update IMAS exception type, and add eq=False to pedestal model tests
Contributor
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Fixed the test failures and resolved conflicts! |
Member
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The tests still seem to be failing - can you make sure to run them manually and fix properly before sending again |
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