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https://github.com/allaunthefox/BioSight.git
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allaun
41fcbc3daa
BioSight encodes mathematical equations as 30-base hachimoji DNA sequences for Adleman/Lipton-style DNA computing. 4-layer Φ mapping: Layer 1: F(E) — byte-class histogram on Δ₇ Layer 3: τ(E) + δ(E) — parse tree structure Layer 4: 6 consistency rules → allele-specific PCR pass/fail Independent phi/ modules: charclass, ast_parse, consistency, embed, output Build: python3 -m py_compile — all modules clean
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
"""
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phi.charclass — Layer 1: Character classification → Δ₇ byte histogram
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Each ASCII character maps to 1 of 8 archetypal classes. The histogram
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over these 8 classes is the F(E) feature vector — the first component
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of the Φ embedding.
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Dependencies: none (stdlib only)
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"""
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from __future__ import annotations
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from typing import List
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# ── 8 character classes ──────────────────────────────────────────────────
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# Each class corresponds to a dimension of Δ₇ (the 7-simplex).
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# The classes partition the visible ASCII range into 8 bins.
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CHAR_CLASSES = {
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"digit": 0, # 0-9
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"lower_alpha": 1, # a-z
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"upper_alpha": 2, # A-Z
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"operator": 3, # + - * / ^ % = < > ! & | ~
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"bracket": 4, # ( ) [ ] { }
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"punctuation": 5, # . , ; : ' " @ # $ _ \
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"whitespace": 6, # space, tab, newline
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"other": 7, # everything else (Greek, Unicode math, etc.)
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}
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OPERATOR_CHARS = set("+-*/^%=<>!&|~")
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BRACKET_CHARS = set("()[]{}")
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PUNCT_CHARS = set(".,;:'\"@#$ _\\")
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def classify_char(c: str) -> int:
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"""Classify a single character into 1 of 8 classes (0-7)."""
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if c.isdigit():
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return 0
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if c.isalpha():
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return 1 if c.islower() else 2
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if c in OPERATOR_CHARS:
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return 3
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if c in BRACKET_CHARS:
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return 4
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if c in PUNCT_CHARS:
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return 5
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if c in (" ", "\t", "\n", "\r"):
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return 6
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return 7
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def compute_F(equation: str) -> List[float]:
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"""Compute F(E) — normalized byte-class histogram on Δ₇.
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Returns 8 floats summing to 1.0. This is Layer 1 of the Φ embedding.
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Pure function: no state, no side effects.
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"""
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counts = [0] * 8
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for c in equation:
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counts[classify_char(c)] += 1
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total = sum(counts)
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if total == 0:
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return [1.0 / 8] * 8
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return [c / total for c in counts]
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