ClaudeandClaude Opus 5.5
17d932a517
Product approved 2026-11-08 (astrologer round-5 rulings 1, 3; same basis as the report and the chat card): - functional roles: drop the bphs_exception_profile pin at the three scoring call sites (+ research mirror); default pvr_table_30 with Moon paksha. - Narayana: narayana_rath.calc_narayana_rath (two cycles) / antardasha, ages via narayana_age from the candidate birth moment; probes date from the birth moment. A blocked source step makes the layer unavailable, never the old algorithm. Blocked count on all three datasets: 0. - Reseal: sealed 20, offset 900, live v5 231 under the new tag; identical to measurement variant (c) trial by trial. float_split / 166d kept. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DbBXoyn7Hj3LCW3BUs5bZ8
57 lines
2.2 KiB
Python
57 lines
2.2 KiB
Python
"""One functional benefic/malefic snapshot for the engine, API, and MCP.
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This module is not ``functional_benefics.py``. Every product surface,
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rectification scoring included (BUG-1759, product 2026-11-08), takes the
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default ``pvr_table_30``; ``bphs_exception_profile`` is a comparison only.
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"""
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from __future__ import annotations
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from typing import Any
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def functional_layer_for_ascendant(
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ascendant: Any,
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planets: Any = None,
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*,
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functional_profile: str | None = None,
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) -> dict[str, Any]:
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"""Return the functional layer for an ascendant payload.
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A dict uses its ``sign``. Anything else is a missing sign and follows
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the normal ``derive_functional_benefic_malefic`` blocked result.
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Import or calculation failures return the engine's blocked shape.
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The exception text stays inside ``effect_on_confidence`` because that
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field already did; callers must not write this dict to a log.
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占星师 2026-11-08 第五轮裁定 3: the default profile is PVR Table 30
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(``functional_benefics.DEFAULT_FUNCTIONAL_PROFILE``). ``planets`` (Sun and
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Moon longitudes) gives the Moon's paksha, which Table 30's note needs for
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Aries / Libra / Capricorn lagnas.
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"""
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try:
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try:
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import functional_benefics as fb
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except ModuleNotFoundError:
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from scripts import functional_benefics as fb
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sign = ascendant.get("sign") if isinstance(ascendant, dict) else None
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return fb.derive_functional_benefic_malefic(
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sign,
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functional_profile=functional_profile or fb.DEFAULT_FUNCTIONAL_PROFILE,
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moon_paksha=fb.moon_paksha_from_planets(planets),
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)
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except Exception as exc:
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sign = ascendant.get("sign") if isinstance(ascendant, dict) else None
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return {
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"status": "blocked",
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"ascendant": sign,
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"functional_benefics": [],
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"functional_malefics": [],
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"functional_neutrals": [],
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"yogakarakas": [],
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"owned_houses": {},
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"effect_on_confidence": f"未完成功能性吉凶星判定，需降低高严谨结论置信度: {exc}",
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"source": "strict_functional_benefic_malefic_v2",
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}
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