52de2218b7
Three items from the post-assessment stabilization slice:
1. field/state.py: restore frozen=True, slots=True
slots=True closes __dict__ on FieldState instances, preventing
incidental attribute injection that frozen=True alone does not block.
The holonomy field works cleanly with slots because ndarray | None
is a valid slotted field type in Python 3.12.
2. README.md: correct vocab/ layer description
Was: 'Word-to-versor manifold, edge rotors'
Now: 'Surface-token manifold points; indexed access for algebraic
transition construction'
Edge rotors are constructed by algebra/, not stored in vocab/.
This exact confusion caused vocab.edge_rotor() drift in earlier work.
3. AGENTS.md: add language-pack checksum rule
Manifest checksums MUST be computed by reading back the bytes
written to disk (Path(f).read_bytes()), never from in-memory strings
before serialization. Unicode-escaped JSON on disk != Python str.
51 lines
2.1 KiB
Python
51 lines
2.1 KiB
Python
"""
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FieldState — the complete cognitive field at one moment.
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Invariant: versor_condition(F) < 1e-6 always.
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This is checked at injection and maintained structurally by versor_apply().
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FieldState is immutable by design (frozen=True, slots=True).
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The np.ndarray F is copied and validated at construction — the copy() call
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is the explicit contract boundary. Callers must not retain a mutable
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reference to the array passed in and expect coherence.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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import numpy as np
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_EXPECTED_COMPONENTS = 32
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@dataclass(frozen=True, slots=True)
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class FieldState:
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F: np.ndarray # shape (32,) float32 — Cl(4,1) multivector on the versor manifold
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node: int = 0 # current node index in the vocabulary manifold
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step: int = 0 # number of propagation steps taken
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holonomy: np.ndarray | None = None
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def __post_init__(self) -> None:
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# Enforce copy + dtype + shape at the construction boundary.
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# frozen=True prevents reassignment, but ndarray contents are still
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# mutable via the array object; copy() here is the defence.
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# slots=True closes __dict__ so no incidental attributes can be added.
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F = np.array(self.F, dtype=np.float32).copy()
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if F.shape != (_EXPECTED_COMPONENTS,):
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raise ValueError(
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f"FieldState.F must have shape ({_EXPECTED_COMPONENTS},), "
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f"got {F.shape}."
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)
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# Bypass frozen to store the validated copy.
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object.__setattr__(self, "F", F)
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if self.holonomy is not None:
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H = np.array(self.holonomy, dtype=np.float32).copy()
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if H.shape != (_EXPECTED_COMPONENTS,):
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raise ValueError(
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f"FieldState.holonomy must have shape ({_EXPECTED_COMPONENTS},), "
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f"got {H.shape}."
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)
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object.__setattr__(self, "holonomy", H)
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def advance(self, new_F: np.ndarray, new_node: int) -> FieldState:
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"""Return a new FieldState after one propagation step."""
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return FieldState(F=new_F, node=new_node, step=self.step + 1, holonomy=self.holonomy)
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