Key issues fixed: - `CORE_BACKEND=numpy` was ignored, so tests mixed Python CGA embedding with Rust metric behavior. - Dense construction seeds were being rejected by strict `unitize_versor()`, while sparse dirty inputs still needed to fail closed. - Holonomy needed a construction-boundary path for raw/dense vocab fixtures and rare null final accumulators. - Proposition storage polluted vault recall by storing the live field instead of the proposition’s subject versor. - Dialogue qualitative frames rendered the same surface as assertive copular frames. - Repeated session prompts could collapse into the same deterministic response path. - Two proof fixtures were stale: one hand-built a non-null “null” vector, and one alignment proof omitted the English “with” anchor used by the resonance proof. Verification: `CORE_BACKEND=numpy CORE_STRICT_MLX_ON_APPLE=0 uv run core test -- -q` Result: `277 passed in 59.52s`
75 lines
2.2 KiB
Python
75 lines
2.2 KiB
Python
"""
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Backend dispatch: use Rust extension (core_rs) when available,
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fall back to pure Python (algebra/cl41.py etc.) transparently.
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This module is the single switch. All algebra modules import from here
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for performance-critical ops. Pure Python is always the fallback —
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the system is never broken by a missing Rust build.
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Usage:
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from algebra.backend import geometric_product, versor_apply, cga_inner, vault_recall
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"""
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import os
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import numpy as np
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_REQUESTED_BACKEND = os.environ.get("CORE_BACKEND", "").strip().lower()
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_ALLOW_RUST = _REQUESTED_BACKEND not in {"numpy", "python", "py"}
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try:
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import core_rs as _rs
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_RUST = _ALLOW_RUST
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except ImportError:
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_RUST = False
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def geometric_product(A: np.ndarray, B: np.ndarray) -> np.ndarray:
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if _RUST:
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return np.asarray(_rs.geometric_product(A, B), dtype=np.float32)
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from algebra.cl41 import geometric_product as _gp
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return _gp(A, B)
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def versor_apply(V: np.ndarray, F: np.ndarray) -> np.ndarray:
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if _RUST and np.result_type(V, F) != np.dtype(np.float64):
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return np.asarray(_rs.versor_apply(V, F), dtype=np.float32)
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from algebra.versor import versor_apply as _va
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return _va(V, F)
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def versor_condition(F: np.ndarray) -> float:
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if _RUST:
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return float(_rs.versor_condition(F))
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from algebra.versor import versor_condition as _vc
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return _vc(F)
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def cga_inner(X: np.ndarray, Y: np.ndarray) -> float:
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if _RUST:
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return float(_rs.cga_inner(X, Y))
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from algebra.cga import cga_inner as _ci
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return _ci(X, Y)
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def vault_recall(versors: list, query: np.ndarray, top_k: int = 5) -> list:
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"""
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Top-k CGA inner product recall.
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Rust path: parallel Rayon scan (releases GIL, true multithreaded).
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Python path: sequential list comprehension.
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"""
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if _RUST:
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try:
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results = _rs.vault_recall(versors, query, top_k)
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return results
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except Exception:
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pass
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q = np.asarray(query)
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scores = [(i, float(cga_inner(q, np.asarray(v)))) for i, v in enumerate(versors)]
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scores.sort(key=lambda x: -x[1])
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return scores[:top_k]
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def using_rust() -> bool:
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"""Returns True if the Rust extension is loaded."""
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return _RUST
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