feat(algebra): incidence algebra — graded_wedge, dual, meet + honest outer_product
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).
This commit is contained in:
parent
5c2f005e96
commit
de645055ea
3 changed files with 243 additions and 5 deletions
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@ -8,6 +8,12 @@ from .cga import (
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null_project,
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null_project,
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embed_point,
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embed_point,
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read_scalar_e1,
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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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)
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from .holonomy import holonomy_encode, holonomy_similarity
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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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from .rotor import word_transition_rotor
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114
algebra/cga.py
114
algebra/cga.py
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@ -19,7 +19,20 @@ No cosine similarity. No L2 norm. No approximate indexing.
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"""
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"""
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import numpy as np
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import numpy as np
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from .cl41 import geometric_product, scalar_part, basis_vector, N_COMPONENTS
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from .cl41 import (
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geometric_product,
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grade_project,
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reverse,
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scalar_part,
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N_COMPONENTS,
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)
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# The unit pseudoscalar I5 = e1 e2 e3 e4 e5 (the grade-5 blade, component 31).
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# In Cl(4,1) with signature (+,+,+,+,-), I5^2 = -1, so I5^{-1} = -I5. Used by
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# ``dual`` / ``meet``. Module-level singleton; never mutated.
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_PSEUDOSCALAR_INDEX = 31
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_I5 = np.zeros(N_COMPONENTS, dtype=np.float64)
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_I5[_PSEUDOSCALAR_INDEX] = 1.0
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# Basis-vector component indices for e4/e5 inside the grade-1 block.
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# Basis-vector component indices for e4/e5 inside the grade-1 block.
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# component 1=e1, 2=e2, 3=e3, 4=e4, 5=e5.
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# component 1=e1, 2=e2, 3=e3, 4=e4, 5=e5.
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@ -46,10 +59,19 @@ def cga_inner(X: np.ndarray, Y: np.ndarray) -> float:
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def outer_product(X: np.ndarray, Y: np.ndarray) -> np.ndarray:
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def outer_product(X: np.ndarray, Y: np.ndarray) -> np.ndarray:
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"""
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"""The antisymmetric (commutator) product ``0.5 * (XY - YX)``.
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Outer (wedge) product: X ^ Y.
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For a prompt versor X_p and response versor X_r,
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HONEST CONTRACT: this equals the grade-raising wedge ``X ^ Y`` **only when both
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X_p ^ X_r is a grade-2 object encoding their geometric relationship.
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operands are grade 1** (vectors). For higher-grade operands it is the *commutator*
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(Lie bracket), which is NOT the wedge — in particular it does NOT build a k-blade
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by repeated application (a bivector commuted with a vector collapses the grade-3
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part to grade 1). Existing callers use the result as an opaque, deterministic
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relationship feature (folded into a scalar via :func:`cga_inner`), where the
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commutator is well-defined regardless; none read it by grade.
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For the true grade-raising exterior product (lines/planes/incidence) use
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:func:`graded_wedge`. (Renamed contract only — behaviour is unchanged, so every
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current caller is byte-identical.)
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"""
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"""
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XY = geometric_product(X, Y)
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XY = geometric_product(X, Y)
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YX = geometric_product(Y, X)
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YX = geometric_product(Y, X)
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@ -120,3 +142,85 @@ def read_scalar_e1(X: np.ndarray) -> float:
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"read_scalar_e1: degenerate n_o weight (point at infinity or f32 collapse)"
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"read_scalar_e1: degenerate n_o weight (point at infinity or f32 collapse)"
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)
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)
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return float(X[1]) / no_weight
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return float(X[1]) / no_weight
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# ---------------------------------------------------------------------------
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# Incidence algebra — the corrected grade-raising wedge, dual, and meet.
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# These let the inner product operate on RELATIONS among entities (lines, planes,
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# incidence) rather than only pairwise point distance. Built only from the existing
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# Cl(4,1) primitives (geometric_product, grade_project) + the pseudoscalar; they add
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# no normalization, no approximation, and leave the versor_condition path untouched
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# (flats are null-cone outer products, not unit versors).
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# ---------------------------------------------------------------------------
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_MAX_GRADE = 5 # Cl(4,1): grades 0..5
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def blade_grade(X: np.ndarray) -> int:
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"""The single grade of a homogeneous blade. Raises if X is zero or grade-mixed.
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Grade is detected by EXACT nonzero (no tolerance): integer-coordinate embeddings
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produce exact integer blades in float64, so a grade block is exactly 0 or not.
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"""
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grades = [k for k in range(_MAX_GRADE + 1) if np.any(grade_project(X, k))]
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if len(grades) != 1:
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raise ValueError(f"not a homogeneous blade: nonzero grades {grades}")
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return grades[0]
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def graded_wedge(X: np.ndarray, Y: np.ndarray) -> np.ndarray:
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"""The true grade-raising exterior product ``X ^ Y`` for homogeneous blades.
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``X ^ Y = <X Y>_{grade(X)+grade(Y)}`` — the top-grade part of the geometric
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product. Unlike :func:`outer_product` (the commutator) this composes correctly:
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``graded_wedge(graded_wedge(P, Q), n_inf)`` builds the grade-3 line P^Q^n_inf,
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and so on. If the grades sum past the pseudoscalar (>5) the wedge is identically
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zero. For two grade-1 vectors it agrees with :func:`outer_product` exactly.
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"""
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gx, gy = blade_grade(X), blade_grade(Y)
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if gx + gy > _MAX_GRADE:
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return np.zeros(N_COMPONENTS, dtype=geometric_product(X, Y).dtype)
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return grade_project(geometric_product(X, Y), gx + gy)
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def blade_norm(X: np.ndarray) -> float:
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"""Reversion norm ``sqrt(|<X reverse(X)>_0|)`` — zero iff X is the zero blade."""
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return float(np.sqrt(abs(scalar_part(geometric_product(X, reverse(X))))))
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def is_incident(point: np.ndarray, flat: np.ndarray) -> bool:
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"""Exact incidence test: is ``point`` on ``flat`` (a line/plane OPNS blade)?
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True iff ``point ^ flat == 0`` EXACTLY (every component zero) — no float
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tolerance to admit (the wrong=0 discipline: a near-incident point is REFUSED,
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not admitted). Exact for integer-coordinate points within ``EMBED_EXACT_MAX``.
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"""
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return not bool(np.any(graded_wedge(point, flat)))
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def dual(X: np.ndarray) -> np.ndarray:
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"""Pseudoscalar dual ``X * I5^{-1}`` (``I5^{-1} = -I5`` since ``I5^2 = -1``).
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Maps a grade-k blade to grade ``5-k``. Involutive up to sign:
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``dual(dual(X)) == -X``.
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"""
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return geometric_product(X, -_I5)
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def meet(A: np.ndarray, B: np.ndarray) -> np.ndarray:
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"""The meet (intersection) ``dual(dual(A) ^ dual(B))`` of two homogeneous blades.
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Correct for operands in GENERAL POSITION whose join spans the space — e.g. two
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non-parallel planes meet in their intersection line. The grade of the result is
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``grade(A)+grade(B)-5``.
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HONEST ENVELOPE: this full-pseudoscalar meet DEGENERATES for operands that share
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a proper subspace (e.g. two coplanar lines, two parallel planes): the inner wedge
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``dual(A) ^ dual(B)`` is then identically zero, so ``meet`` returns the **zero
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multivector** — a detectable signal of "no transversal meet", never a silently
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wrong value. The general intersection of such operands (e.g. the point where two
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coplanar lines cross) requires the *join-relative* meet, which is deliberately
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NOT implemented here; the caller MUST check ``blade_norm(result) == 0`` and treat
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zero as degenerate/refuse rather than as a geometric object.
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"""
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return dual(graded_wedge(dual(A), dual(B)))
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128
tests/test_cga_incidence.py
Normal file
128
tests/test_cga_incidence.py
Normal file
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@ -0,0 +1,128 @@
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"""CGA incidence algebra — the corrected grade-raising wedge, dual, and meet.
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These primitives let `cga_inner` operate on RELATIONS among entities (lines, planes,
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incidence) rather than only pairwise point distance — the missing "wire" for the
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section-level relational layer. Every test pins EXACT behaviour (integer-coordinate
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embeddings → exact integer blades in float64), no float tolerance to admit.
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It also pins the honest distinction the `outer_product` docstring now states: the
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corrected `graded_wedge` agrees with `outer_product` for grade-1 vectors but DIFFERS
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for higher grades (where `outer_product` is the commutator, not the wedge) — and the
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honest envelope of `meet` (degenerate operands return zero, never a silent wrong).
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"""
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from __future__ import annotations
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import numpy as np
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from algebra.cga import (
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EMBED_EXACT_MAX,
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blade_grade,
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blade_norm,
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dual,
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embed_point,
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graded_wedge,
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is_incident,
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meet,
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outer_product,
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)
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from algebra.cl41 import N_COMPONENTS, geometric_product, scalar_part
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_F64 = np.float64
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def _pt(x: float, y: float = 0.0, z: float = 0.0) -> np.ndarray:
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return embed_point(np.array([x, y, z], dtype=_F64), dtype=_F64)
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def _n_inf() -> np.ndarray:
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v = np.zeros(N_COMPONENTS, dtype=_F64)
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v[4] = 1.0
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v[5] = 1.0
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return v
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def _line(p: np.ndarray, q: np.ndarray) -> np.ndarray:
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"""OPNS line p ^ q ^ n_inf (grade 3)."""
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return graded_wedge(graded_wedge(p, q), _n_inf())
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def _plane(p: np.ndarray, q: np.ndarray, r: np.ndarray) -> np.ndarray:
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"""OPNS plane p ^ q ^ r ^ n_inf (grade 4)."""
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return graded_wedge(graded_wedge(graded_wedge(p, q), r), _n_inf())
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# --- graded_wedge agrees with outer_product on grade-1, differs above ------
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def test_graded_wedge_agrees_with_outer_product_for_vectors():
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a = np.zeros(N_COMPONENTS, dtype=_F64); a[1] = 1.0 # e1
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b = np.zeros(N_COMPONENTS, dtype=_F64); b[2] = 1.0 # e2
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np.testing.assert_array_equal(graded_wedge(a, b), outer_product(a, b))
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assert blade_grade(graded_wedge(a, b)) == 2
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def test_graded_wedge_differs_from_commutator_above_grade_1():
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"""The honest distinction outer_product's docstring now states: building a
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3-blade by repeated wedge works for graded_wedge but COLLAPSES for the commutator."""
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p, q, ninf = _pt(0, 0), _pt(2, 0), _n_inf()
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pq = graded_wedge(p, q) # grade 2
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line_true = graded_wedge(pq, ninf) # grade 3 — the real line
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line_commutator = outer_product(pq, ninf)
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assert blade_grade(line_true) == 3
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# the commutator does NOT yield the grade-3 line (it collapses the top grade)
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assert not np.array_equal(line_true, line_commutator)
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# --- incidence: exact, and exact at scale (f64) ----------------------------
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def test_incidence_collinear_exact():
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line = _line(_pt(0, 0), _pt(2, 0))
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assert is_incident(_pt(5, 0), line) # collinear beyond the segment
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assert is_incident(_pt(1, 0), line) # on the segment
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assert not is_incident(_pt(0, 1), line) # off the line
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assert not is_incident(_pt(3, 2), line)
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def test_incidence_exact_at_scale():
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"""f64 keeps incidence exact for large integer coordinates (within the ceiling)."""
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v = EMBED_EXACT_MAX // 2
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line = _line(_pt(0, 0), _pt(2, 0)) # the x-axis
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assert is_incident(_pt(float(v), 0), line)
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assert not is_incident(_pt(float(v), 1), line)
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# --- dual ------------------------------------------------------------------
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def test_pseudoscalar_squares_to_minus_one():
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i5 = np.zeros(N_COMPONENTS, dtype=_F64); i5[31] = 1.0
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assert scalar_part(geometric_product(i5, i5)) == -1.0
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def test_dual_is_involution_up_to_sign():
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x = _pt(3, 0)
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np.testing.assert_allclose(dual(dual(x)), -x, atol=0.0)
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# --- meet: correct for spanning operands, honest-zero for degenerate -------
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def test_meet_of_two_planes_is_their_line():
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p_z0 = _plane(_pt(0, 0, 0), _pt(1, 0, 0), _pt(0, 1, 0)) # z = 0
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p_y0 = _plane(_pt(0, 0, 0), _pt(1, 0, 0), _pt(0, 0, 1)) # y = 0
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line = meet(p_z0, p_y0) # expect the x-axis
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assert blade_norm(line) != 0.0
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assert blade_grade(line) == 3
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assert is_incident(_pt(5, 0, 0), line) # x-axis point is on it
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assert not is_incident(_pt(0, 5, 0), line) # off it
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def test_meet_degenerate_operands_return_zero_not_silent_wrong():
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"""The honest envelope: coplanar lines do not span, so the full-pseudoscalar meet
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DEGENERATES — it returns the zero multivector (detectable), never a wrong object."""
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l1 = _line(_pt(0, 0), _pt(2, 0)) # x-axis (z=0 plane)
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l2 = _line(_pt(1, -1), _pt(1, 1)) # x=1 vertical (z=0 plane) — coplanar with l1
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result = meet(l1, l2)
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assert blade_norm(result) == 0.0 # degenerate → zero, caller must refuse
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