[ENH] Add magnetic forward modeling for Total Magnetic Intensity (TMI) calculation #39
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Introduce new test cases to validate the forthcoming magnetics implementation: - Add analytical benchmark test comparing induced-only TMI against analytical solutions for a spherical anomaly. - Add symmetry benchmark test to verify induced-only TMI spatial accuracy along a line profile. Also include a placeholder magnetics gradient computation module (`magnetic_gradient.py`) with core physics for initial testing.
Introduce functionality for induced-only TMI anomaly computation using precomputed voxel-based TMI kernels and geologic unit susceptibilities. Updates include: - `compute_tmi`: Core TMI calculation logic based on magnetics kernel and voxel susceptibilities in `fw_magnetic.py`. - Extended `GeophysicsInput` to include magnetics-specific fields such as `mag_kernel`, `susceptibilities`, and `igrf_params`. - Modified `model_api.py` to integrate magnetics into geophysics workflows alongside gravity computations. - Updated `solutions.py` to include magnetics in forward modeling outputs. Ensures magnetics functionality remains optional without impacting gravity workflows.
- Updated `model_api.py` to make gravity computations conditional, enabling workflows without gravity inputs. - Modified `GeophysicsInput` to allow `tz` and `densities` as optional fields for magnetics-only workflows. - Added `tmi` alias property in `solutions.py` for Total Magnetic Intensity outputs. - Improved formatting in geophysics README for better readability.
…hts, unit handling, and output sign - Adjust `observation_heights` for improved test consistency. - Fix `units_nT` parameter to ensure correct unit handling in TMI computation. - Correct output sign for numerical TMI results to align with analytical expectations.
- Introduced parametrized cases for directional cosines, path equivalence, and kernel decay. - Added edge case tests for zero and negative susceptibilities. - Validated kernel symmetry and kernel reusability with different IGRF configurations. - Enhanced `CenteredGrid` with methods for voxel calculations.
…s and symmetry checks - Adjust grid dimensions to account for resolution changes and ensure shape consistency. - Add assertions for expected voxel counts to validate kernel reshaping. - Update symmetry check orientation from slices to a more accurate coordinate axis.
…lidation - Refined `test_kernel_decay_with_distance` to enhance clarity and correctness of magnetic anomaly decay behavior. - Updated grid scaling and observation point handling for better volume coverage. - Adjust
…edge cases and symmetry validation - Introduced new test file `test_magnetic_benchmark_II.py` covering multiple scenarios: - Symmetry checks for TMI profiles. - Edge cases for zero and negative susceptibilities. - Observation distance decay validation. - Kernel property tests for symmetry and resolution. - Enhanced and streamlined existing tests in `test_magnetic_benchmark.py`: - Adjusted formatting for clearer readability. - Updated comments and formulas for analytical benchmarks to improve documentation consistency.
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Add magnetics (TMI) forward modeling to geophysics workflows
Introduce functionality for induced-only TMI anomaly computation using precomputed voxel-based TMI kernels and geologic unit susceptibilities. Updates include:
compute_tmi: Core TMI calculation logic based on magnetics kernel and voxel susceptibilities infw_magnetic.py.GeophysicsInputto include magnetics-specific fields such asmag_kernel,susceptibilities, andigrf_params.model_api.pyto integrate magnetics into geophysics workflows alongside gravity computations.solutions.pyto include magnetics in forward modeling outputs.Ensures magnetics functionality remains optional without impacting gravity workflows.
Additional changes
model_api.pyto make gravity computations conditional, enabling workflows without gravity inputs.GeophysicsInputto allowtzanddensitiesas optional fields for magnetics-only workflows.tmialias property insolutions.pyfor Total Magnetic Intensity outputs.