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torax/transport_model/tests/tglf_based_transport_model.py
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| # Copyright 2024 DeepMind Technologies Limited | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
|
|
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| """Unit tests for torax.transport_model.tglf_based_transport_model.""" | ||
| from absl.testing import absltest | ||
| from absl.testing import parameterized | ||
| import chex | ||
| import jax.numpy as jnp | ||
| from torax import core_profile_setters | ||
| from torax import state | ||
| from torax.config import runtime_params as general_runtime_params | ||
| from torax.config import runtime_params_slice | ||
| from torax.geometry import geometry | ||
| from torax.pedestal_model import pedestal_model as pedestal_model_lib | ||
| from torax.pedestal_model import set_tped_nped | ||
| from torax.sources import source_models as source_models_lib | ||
| from torax.transport_model import tglf_based_transport_model | ||
| from torax.transport_model import quasilinear_transport_model | ||
| from torax.transport_model import runtime_params as runtime_params_lib | ||
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|
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| def _get_model_inputs(transport: tglf_based_transport_model.RuntimeParams): | ||
| """Returns the model inputs for testing.""" | ||
| runtime_params = general_runtime_params.GeneralRuntimeParams() | ||
| geo = geometry.build_circular_geometry() | ||
| source_models_builder = source_models_lib.SourceModelsBuilder() | ||
| source_models = source_models_builder() | ||
| pedestal_model_builder = ( | ||
| set_tped_nped.SetTemperatureDensityPedestalModelBuilder() | ||
| ) | ||
| dynamic_runtime_params_slice = ( | ||
| runtime_params_slice.DynamicRuntimeParamsSliceProvider( | ||
| runtime_params=runtime_params, | ||
| transport=transport, | ||
| sources=source_models_builder.runtime_params, | ||
| pedestal=pedestal_model_builder.runtime_params, | ||
| torax_mesh=geo.torax_mesh, | ||
| )( | ||
| t=runtime_params.numerics.t_initial, | ||
| ) | ||
| ) | ||
| static_slice = runtime_params_slice.build_static_runtime_params_slice( | ||
| runtime_params=runtime_params, | ||
| source_runtime_params=source_models_builder.runtime_params, | ||
| torax_mesh=geo.torax_mesh, | ||
| ) | ||
| core_profiles = core_profile_setters.initial_core_profiles( | ||
| dynamic_runtime_params_slice=dynamic_runtime_params_slice, | ||
| static_runtime_params_slice=static_slice, | ||
| geo=geo, | ||
| source_models=source_models, | ||
| ) | ||
| return dynamic_runtime_params_slice, geo, core_profiles | ||
|
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|
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| class TGLFBasedTransportModelTest(parameterized.TestCase): | ||
| """Unit tests for the `torax.transport_model.tglf_based_transport_model` module.""" | ||
|
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| def test_tglf_based_transport_model_output_shapes(self): | ||
| """Tests that the core transport output has the right shapes.""" | ||
| transport = tglf_based_transport_model.RuntimeParams( | ||
| **runtime_params_lib.RuntimeParams() | ||
| ) | ||
| transport_model = FakeTGLFBasedTransportModel() | ||
| dynamic_runtime_params_slice, geo, core_profiles = _get_model_inputs( | ||
| transport | ||
| ) | ||
| pedestal_model = set_tped_nped.SetTemperatureDensityPedestalModel() | ||
| pedestal_model_outputs = pedestal_model( | ||
| dynamic_runtime_params_slice, geo, core_profiles | ||
| ) | ||
|
|
||
| core_transport = transport_model( | ||
| dynamic_runtime_params_slice, geo, core_profiles, pedestal_model_outputs | ||
| ) | ||
| expected_shape = geo.rho_face_norm.shape | ||
| self.assertEqual(core_transport.chi_face_ion.shape, expected_shape) | ||
| self.assertEqual(core_transport.chi_face_el.shape, expected_shape) | ||
| self.assertEqual(core_transport.d_face_el.shape, expected_shape) | ||
| self.assertEqual(core_transport.v_face_el.shape, expected_shape) | ||
|
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| def test_tglf_based_transport_model_prepare_tglf_inputs_shapes(self): | ||
| """Tests that the tglf inputs have the expected shapes.""" | ||
| transport = tglf_based_transport_model.RuntimeParams( | ||
| **runtime_params_lib.RuntimeParams() | ||
| ) | ||
| dynamic_runtime_params_slice, geo, core_profiles = _get_model_inputs( | ||
| transport | ||
| ) | ||
| transport_model = FakeTGLFBasedTransportModel() | ||
| tglf_inputs = transport_model._prepare_tglf_inputs( | ||
| Zeff_face=dynamic_runtime_params_slice.plasma_composition.Zeff_face, | ||
| q_correction_factor=dynamic_runtime_params_slice.numerics.q_correction_factor, | ||
| geo=geo, | ||
| core_profiles=core_profiles, | ||
| ) | ||
|
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||
| # Inputs that are 1D | ||
| vector_keys = [ | ||
| 'chiGB', | ||
| 'lref_over_lti', | ||
| 'lref_over_lte', | ||
| 'lref_over_lne', | ||
| 'lref_over_lni0', | ||
| 'lref_over_lni1', | ||
| 'Ti_over_Te', | ||
| 'drmaj', | ||
| 'q', | ||
| 's_hat', | ||
| 'nu_ee', | ||
| 'kappa', | ||
| 'kappa_shear', | ||
| 'delta', | ||
| 'delta_shear', | ||
| 'beta_e', | ||
| 'Zeff', | ||
| ] | ||
| # Inputs that are 0D | ||
| scalar_keys = ['Rmaj', 'Rmin'] | ||
|
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||
| expected_vector_length = geo.rho_face_norm.shape[0] | ||
| for key in vector_keys: | ||
| try: | ||
| self.assertEqual( | ||
| getattr(tglf_inputs, key).shape, (expected_vector_length,) | ||
| ) | ||
| except Exception as e: | ||
| print(key, getattr(tglf_inputs, key)) | ||
| raise e | ||
| for key in scalar_keys: | ||
| self.assertEqual(getattr(tglf_inputs, key).shape, ()) | ||
|
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|
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| class FakeTGLFBasedTransportModel( | ||
| tglf_based_transport_model.TGLFBasedTransportModel | ||
| ): | ||
| """Fake TGLFBasedTransportModel for testing purposes.""" | ||
|
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||
| def __init__(self): | ||
| super().__init__() | ||
| self._frozen = True | ||
|
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| # pylint: disable=invalid-name | ||
| def prepare_tglf_inputs( | ||
| self, | ||
| Zeff_face: chex.Array, | ||
| q_correction_factor: chex.Numeric, | ||
| geo: geometry.Geometry, | ||
| core_profiles: state.CoreProfiles, | ||
| ) -> tglf_based_transport_model.TGLFInputs: | ||
| """Exposing prepare_tglf_inputs for testing.""" | ||
| return self._prepare_tglf_inputs( | ||
| Zeff_face=Zeff_face, | ||
| q_correction_factor=q_correction_factor, | ||
| geo=geo, | ||
| core_profiles=core_profiles, | ||
| ) | ||
|
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| # pylint: enable=invalid-name | ||
|
|
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| def _call_implementation( | ||
| self, | ||
| dynamic_runtime_params_slice: runtime_params_slice.DynamicRuntimeParamsSlice, | ||
| geo: geometry.Geometry, | ||
| core_profiles: state.CoreProfiles, | ||
| pedestal_model_output: pedestal_model_lib.PedestalModelOutput, | ||
| ) -> state.CoreTransport: | ||
| tglf_inputs = self._prepare_tglf_inputs( | ||
| Zeff_face=dynamic_runtime_params_slice.plasma_composition.Zeff_face, | ||
| q_correction_factor=dynamic_runtime_params_slice.numerics.q_correction_factor, | ||
| geo=geo, | ||
| core_profiles=core_profiles, | ||
| ) | ||
|
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| transport = dynamic_runtime_params_slice.transport | ||
| # Assert required for pytype. | ||
| assert isinstance( | ||
| transport, | ||
| tglf_based_transport_model.DynamicRuntimeParams, | ||
| ) | ||
|
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| return self._make_core_transport( | ||
| qi=jnp.ones(geo.rho_face_norm.shape) * 0.4, | ||
| qe=jnp.ones(geo.rho_face_norm.shape) * 0.5, | ||
| pfe=jnp.ones(geo.rho_face_norm.shape) * 1.6, | ||
| quasilinear_inputs=tglf_inputs, | ||
| transport=transport, | ||
| geo=geo, | ||
| core_profiles=core_profiles, | ||
| gradient_reference_length=geo.Rmaj, # TODO | ||
| gyrobohm_flux_reference_length=geo.Rmin, # TODO | ||
| ) | ||
|
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|
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| if __name__ == '__main__': | ||
| absltest.main() |
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