upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation module

Post-Twin Validation – Part L of the Twinned FCC walkthrough.

Builds the post-twin voxel quaternion field, validates the CLEANED, twinned structure’s misorientation distribution against the full EBSD MDF (twins present – unlike Pre-Twin Validation, which deliberately used the twins-merged-out reference), per axis, then compares the full 3D MDF curve directly.

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.validate_crystallographic_representativeness(cleaner, mdf, n_slices=(10, 10, 10), test_axes=('x', 'y', 'z'), p_percentage=60.0, wasserstein_threshold=5.0)

Builds the post-twin voxel quaternion field (no parameters of its own – always freshly derived from the cleaned structure) then validates it against the EBSD full MDF.

Returns:

• (validator, quat_3d_clean) (validator.axis_acceptance/)

• validator.overall_accepted/validator.report() are the results;

• quat_3d_clean feeds compare_full_3d_mdf() below.

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.compare_full_3d_mdf(cleaner, quat_3d_clean, n_bins=65, angle_max=65.0)

Computes the post-twin structure’s full 3D misorientation distribution (every grain-grain neighbour pair, not just the slice sample validate_crystallographic_representativeness used), directly comparable to the EBSD full MDF curve computed back in EBSD Analysis-2.

Returns:

• dict (mc_mdf_post, same shape as steps_ebsd_analysis_2’s MDF result)

• (hist_bin_centers, hist_density, mean_angle, …).

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.representative_slice_mdfs(validator, cleaner, quat_3d_clean, axes=None)

Per-axis MDF for every slice validator already found passing (during validate_crystallographic_representativeness above), plus their mean – the representative-slice MDF a passing 2D section should reproduce, directly comparable to the full EBSD MDF curve.

Returns:

• dict {axis_name ({‘n_passing’, ‘slice_mdfs’, ‘mean_bin_centers’,)

• ’mean_density’}} – one entry per axis with at least one slice

• result recorded.

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.twin_thickness_three_way_comparison(tg, cleaner, twin_thickness, validator)

Three-way twin-thickness population comparison: the EBSD target, the actual 3D thickness as introduced (from tg.twin_halfwidths_vox), and the apparent 2D thickness measured on the validator’s own representative slices, per axis – shows how much a 2D-slice measurement understates or overstates the true 3D lamella thickness.

Returns:

• dict {‘ebsd_um’, ‘ebsd_mean_um’, ‘actual_3d_um’, ‘actual_3d_mean_um’,

• ’per_axis_um’, ‘per_axis_means_um’}.

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.twin_thickness_representativeness_score(comparison)

A single [0, 1] “how well does the actual 3D twin thickness introduced during generation match the EBSD target” score, from twin_thickness_three_way_comparison()’s output. Compares ‘ebsd_um’ against ‘actual_3d_um’ – the per-axis apparent 2D populations are left out, since they illustrate how much a 2D slice understates the true 3D thickness rather than representing a separate target to be matched – via TwinnedSimple3DBase.compare_property_distributions, the same generic distribution comparator mdf_representativeness_score() applies to the misorientation distribution.

Returns:

• dict or None (see compare_property_distributions – None if either)

• side has no values left after outlier trimming.

upxo.pxtal.twinned_simple_3d.steps.steps_post_twin_validation.mdf_representativeness_score(mdf, mc_mdf_post)

A single [0, 1] “how well does the achieved neighbour-grain misorientation distribution match EBSD” score – distinct from validate_crystallographic_representativeness’s per-axis pass/fail, which only says whether individual 2D slices cleared a threshold, not how close the OVERALL match is. Compares the full pooled angle populations (mdf[‘miso_deg’] vs mc_mdf_post[‘miso_deg’], both raw per-neighbour-pair arrays, not the binned histograms) via TwinnedSimple3DBase.compare_property_distributions – the same generic distribution comparator the temporal-slice ranking (Part G) uses internally.

Returns:

• dict or None ({‘wasserstein’, ‘energy’, ‘ks_similarity’, ‘ratio’,)

• ’wasserstein_score’, ‘energy_score’, ‘representativeness_score’} –

• None if either side has no values left after outlier trimming.