de645055ea
Adds the correct grade-raising "wire" the field substrate was missing — so cga_inner
can operate on RELATIONS among entities (lines/planes/incidence), not just pairwise
point distance. Built only from existing Cl(4,1) primitives (geometric_product,
grade_project) + the pseudoscalar; no normalization, no approximation, versor_condition
path untouched (flats are null-cone wedges, not unit versors).
- outer_product: DOCSTRING-ONLY honesty fix (behavior byte-identical, every caller
unchanged). It is the commutator 0.5*(XY-YX) = the wedge ONLY for grade-1 vectors;
for higher grades it is the Lie bracket, NOT the wedge, and does NOT build a k-blade
by repetition. Existing callers consume it as an opaque cga_inner-reduced feature
(none read it by grade), so the relabel is safe. Points to graded_wedge for the real
exterior product.
- graded_wedge(X,Y) = <XY>_{grade(X)+grade(Y)} — the true wedge; agrees with
outer_product on grade-1, differs above (pinned by test). Builds lines/planes.
- is_incident(point, flat): EXACT zero-test (point^flat == 0, no float tolerance to
admit — near-incident is refused, per wrong=0). Exact at scale in f64.
- dual(X) = X*I5^{-1} (I5^2=-1 confirmed); involutive up to sign.
- meet(A,B) = dual(dual(A)^dual(B)): correct for spanning operands (two planes -> their
line, incidence verified). HONEST ENVELOPE: degenerates for non-spanning operands
(coplanar lines) — returns the ZERO multivector (detectable, documented, tested),
never a silent wrong value. The general coplanar intersection needs the join-relative
meet, deliberately NOT faked here.
Green: smoke 87, algebra 82, incidence 8, outer_product consumers + invariants 109;
zero regressions (outer_product behavior unchanged).
19 lines
505 B
Python
19 lines
505 B
Python
from .cl41 import geometric_product, reverse, grade_project, scalar_part, norm_squared, basis_vector
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from .versor import versor_apply, normalize_to_versor, versor_condition
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from .cga import (
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EMBED_EXACT_MAX,
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cga_inner,
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outer_product,
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is_null,
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null_project,
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embed_point,
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read_scalar_e1,
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blade_grade,
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blade_norm,
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graded_wedge,
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is_incident,
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dual,
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meet,
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)
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from .holonomy import holonomy_encode, holonomy_similarity
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from .rotor import word_transition_rotor
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