Jyotisha/tests/test_report_chart_blank_columns.py

"""Blank report and chart columns (TASK-report-chart-blank-columns-20261003).

BUG-1199 Kranti column with no producer; BUG-1200 Ashtakavarga house table
labelled the with-Lagna total as SAV (split in the reader: ashtakavarga.py is
in the frozen rectification identity and stays byte-identical); BUG-1201 ascendant without nakshatra;
BUG-1203 the divisional-chart caveat moved to the chart section. Every chart
here is fictional.
"""

from __future__ import annotations

import copy
import json
import re
from pathlib import Path

import pytest

from scripts.ashtakavarga import BAV_TOTALS, EXPECTED_SAV_TOTAL, SIGNS
from scripts.jyotish_engine import NAKSHATRA_LIST, _nakshatra_fields, compute_chart_data
from scripts.pl9_reader_export import _pl9_export_markdown_for_edition
from tests.test_report_english_edition import CASES, _packet

ROOT = Path(__file__).resolve().parents[1]
CAVEAT_ZH = "分盘对出生时间敏感，原始计算供核对，不单独增加结论的确定性。"


def _independent_nakshatra(lon: float) -> tuple[str, int, str]:
    minutes = (lon % 360) * 60
    index = int(minutes // 800)  # 13°20′ = 800′
    pada = int((minutes % 800) // 200) + 1  # 3°20′ = 200′
    name, lord, _ = NAKSHATRA_LIST[index]
    return name, pada, lord


@pytest.mark.parametrize("lon,expected", [
    (0.0, ("Ashwini", 1, "Ketu")),
    (13.33, ("Ashwini", 4, "Ketu")),
    (13.34, ("Bharani", 1, "Venus")),
    (134.53, ("Purva Phalguni", 1, "Venus")),
    (149.3994, ("Uttara Phalguni", 1, "Sun")),
    (359.99, ("Revati", 4, "Mercury")),
    (360.0, ("Ashwini", 1, "Ketu")),
])
def test_nakshatra_fields_at_boundaries(lon, expected) -> None:
    fields = _nakshatra_fields(lon)
    assert (fields["nakshatra"], fields["nakshatra_pada"], fields["nakshatra_lord"]) == expected


def test_chart_ascendant_carries_its_nakshatra_and_planets_are_unchanged() -> None:
    golden = json.loads((ROOT / "frontend/tests/fixtures/chart-view-golden.json").read_text(encoding="utf-8"))
    chart, *_ = compute_chart_data(1990, 6, 15, 12, 0, 39.9042, 116.4074, 8.0, ayanamsa_name="raman")
    asc = chart["ascendant"]
    assert (asc["nakshatra"], asc["nakshatra_pada"], asc["nakshatra_lord"]) == _independent_nakshatra(asc["lon"])
    assert {k: asc[k] for k in ("nakshatra", "nakshatra_pada", "nakshatra_lord")} == {
        k: golden["chart"]["ascendant"][k] for k in ("nakshatra", "nakshatra_pada", "nakshatra_lord")
    }
    for name, planet in chart["planets"].items():
        stored = golden["chart"]["planets"][name]
        assert (planet["nakshatra"], planet["nakshatra_pada"], planet["nakshatra_lord"]) == (
            stored["nakshatra"], stored["nakshatra_pada"], stored["nakshatra_lord"]), name


@pytest.fixture(scope="module")
def editions() -> tuple[str, str, dict]:
    packet = _packet(CASES["day"])
    zh = _pl9_export_markdown_for_edition(copy.deepcopy(packet), "reader_main")
    english = copy.deepcopy(packet)
    english["report_language"] = "en"
    return zh, _pl9_export_markdown_for_edition(english, "reader_main"), packet


def _table_after(markdown: str, heading: str) -> list[list[str]]:
    lines = markdown.splitlines()
    start = next(i for i, line in enumerate(lines) if line.startswith("### ") and heading in line)
    rows = []
    for line in lines[start + 1:]:
        if line.startswith("### ") or (rows and not line.startswith("|")):
            break
        if line.startswith("|") and not set(line) <= set("|- "):
            rows.append([cell.strip() for cell in line.strip("|").split("|")])
    return rows


def test_declination_table_has_no_kranti_column(editions) -> None:
    for markdown, heading in ((editions[0], "Declination / Speed"), (editions[1], "Declination / Speed")):
        assert "Kranti" not in markdown
        rows = _table_after(markdown, heading)
        assert rows[0] == ["Planet", "Degree", "Declination", "Speed"]
        assert len(rows) == 8 and all(len(row) == 4 and "-" not in row for row in rows)


def test_ashtakavarga_house_table_shows_three_real_columns(editions) -> None:
    zh, en, packet = editions
    expected_sav = packet["worksheets"]["strengths_and_scores"]["ashtakavarga"]["sav"]["scores"]
    for markdown, heading, header, total in (
        (zh, "Ashtakavarga 完整宫位分数", ["House", "Sign", "SAV", "上升 BAV", "SAV + 上升"], "合计"),
        (en, "Ashtakavarga Full House Scores", ["House", "Sign", "SAV", "Lagna BAV", "SAV + Lagna"], "Total"),
    ):
        rows = _table_after(markdown, heading)
        assert rows[0] == header
        body, totals = rows[1:13], rows[13]
        for row in body:
            sav, lagna, full = (int(cell) for cell in row[2:])
            assert sav + lagna == full
        assert totals == [total, "-", str(EXPECTED_SAV_TOTAL), str(BAV_TOTALS["Lagna"]), str(EXPECTED_SAV_TOTAL + BAV_TOTALS["Lagna"])]
    # SAV equals the per-sign SAV table, Lagna BAV the Lagna bindus, and the last
    # column the engine's `house_scores_full` total that rectification reads.
    ashtakavarga = packet["worksheets"]["strengths_and_scores"]["ashtakavarga"]
    full = {row["sign"]: row["sav_score"] for row in ashtakavarga["house_scores_full"].values()}
    for row in _table_after(en, "Ashtakavarga Full House Scores")[1:13]:
        assert int(row[2]) == expected_sav[row[1]]
        assert int(row[3]) == ashtakavarga["bav"]["Lagna"]["bindus"][SIGNS.index(row[1])]
        assert int(row[4]) == full[row[1]]


def test_ashtakavarga_house_table_never_labels_the_total_as_sav(editions) -> None:
    packet = copy.deepcopy(editions[2])
    del packet["worksheets"]["strengths_and_scores"]["ashtakavarga"]["bav"]["Lagna"]
    rows = _table_after(_pl9_export_markdown_for_edition(packet, "reader_main"), "Ashtakavarga 完整宫位分数")
    assert len(rows) == 13, "no total row without the split"
    for row in rows[1:]:
        assert row[2:4] == ["-", "-"]
        assert row[4].isdigit()


def test_chart_section_carries_the_divisional_caveat(editions) -> None:
    zh, en, _ = editions
    assert re.search(r"### 本命与分盘北印度图盘\n\n" + re.escape(CAVEAT_ZH) + r"\n", zh)
    assert re.search(r"### Natal and Divisional Charts \(North Indian\)\n\nDivisional charts are sensitive to birth time\.", en)