Texture unimodal odf#941
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Core Functions: - validate_orientations(): Input validation for orientation matrices - eval_odf(): Unified evaluation interface for any ODF object - eval_odf_batch(): Memory-efficient processing of large orientation datasets - eval_at_identity(): Convenience function for identity orientation evaluation - eval_random_orientations(): Random orientation generation with proper rotation matrices Signed-off-by: Brianna Major <brianna.major@kitware.com>
Implement basic unimodal orientation distribution function representing textured materials with preferred orientations using kernel functions. Signed-off-by: Brianna Major <brianna.major@kitware.com>
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Overview
UnimodalODFclass and a shared ODF evaluation layer tohexrd.phase_transition.textureUniformODFbranchesWhat's new
unimodal_odf.py: kernel-based ODF with one or more modal orientations and optional weights,f(g) = Σᵢ wᵢ K(g, g₀ᵢ)withΣ wᵢ = 1. Because the de la Vallée Poussin kernel integrates to mean 1 over SO(3), the weighted sum is already a valid ODF in MRD unitsUnimodalODFtakes no symmetry arguments; it delegatescrystal_symmetry/sample_symmetryto its kernelTODO(perf)at the symmetry-reduced misorientation loop: it callsrotations.misorientationonce per orientation and is ~1400× slower than the no-symmetry path; vectorization is deferred to thetexture-normalizationbranch.test_unimodal_odf.py: construction (single/multi-modal, weights), symmetry delegation to the kernel, MRD normalization via a Monte-Carlomean ≈ 1.0check,estimated_max_value, getters-return-copies, repr/strtest_evaluation.py: real ODFs through the public package pathtest_delavalleepoussin_kernel.py: symmetry-label property tests andtest_trivial_symmetry_takes_fast_pathregression testAffected Workflows
Documentation Changes
None.
Depends on #939