from __future__ import annotations import sys from pathlib import Path import pytest SCRIPTS = Path(__file__).resolve().parents[1] / "scripts" if str(SCRIPTS) not in sys.path: sys.path.insert(0, str(SCRIPTS)) from jyotish_api_server import BadRequest, JyotishAPIHandler # noqa: E402 def _handler() -> JyotishAPIHandler: return JyotishAPIHandler.__new__(JyotishAPIHandler) def test_active_rectification_questions_api_builds_choice_workflow() -> None: result = _handler()._compute_active_rectification_questions( { "birth_time": "1993-04-17 14:49", "uncertainty_minutes": 30, "step_minutes": 1, } ) assert result["success"] is True assert result["endpoint"] == "active_rectification_questions" assert result["scope"] == "active_birth_time_rectification_questionnaire" assert result["candidate_scan"]["start"] == "1993-04-17 14:19" assert result["candidate_scan"]["end"] == "1993-04-17 15:19" assert result["candidate_scan"]["candidate_count"] == 61 assert result["questions"] assert {option["key"] for option in result["questions"][0]["options"]} == {"A", "B", "C", "D"} assert "dynamic_candidate_cluster_scoring" in result["workflow"] def test_active_rectification_questions_api_accepts_location_for_true_recast() -> None: result = _handler()._compute_active_rectification_questions( { "birth_time": "1993-04-17 14:49", "uncertainty_minutes": 30, "lat": 36.683333, "lon": 114.35, "tz": 8, } ) summary = result["candidate_scan"]["sensitivity_summary"] assert "true_varga_recast" in summary["computed_layers"] assert "true_arudha_recast" in summary["computed_layers"] assert "true_kp_cusp_recast" in summary["computed_layers"] assert "true_varga_recast" not in summary["blocked_layers"] assert "true_kp_cusp_recast" not in summary["blocked_layers"] def test_active_rectification_score_api_returns_rankings_and_next_questions() -> None: questionnaire = _handler()._compute_active_rectification_questions( {"birth_time": "1993-04-17 14:49", "uncertainty_minutes": 30} ) scored = _handler()._compute_active_rectification_score( { "questionnaire": questionnaire, "answers": { "education_environment_shift": "A", "residence_relocation_shift": "B", "relationship_or_partner_entry": "D", "career_responsibility_pressure": "A", "research_tool_expression_shift": "C", }, } ) assert scored["success"] is True assert scored["endpoint"] == "active_rectification_score" assert scored["scope"] == "active_birth_time_rectification_scoring" assert scored["answered_count"] == 5 assert scored["candidate_cluster_rankings"] assert scored["next_round_questions"] assert scored["candidate_cluster_rankings"][0]["score"] >= scored["candidate_cluster_rankings"][-1]["score"] def test_active_rectification_questions_api_validates_request() -> None: with pytest.raises(BadRequest, match="birth_time must be a string"): _handler()._compute_active_rectification_questions({}) with pytest.raises(BadRequest, match="uncertainty_minutes must be between 1 and 180"): _handler()._compute_active_rectification_questions( {"birth_time": "1993-04-17 14:49", "uncertainty_minutes": 0} ) with pytest.raises(BadRequest, match="step_minutes must be between 1 and 30"): _handler()._compute_active_rectification_questions( {"birth_time": "1993-04-17 14:49", "step_minutes": 31} ) def test_active_rectification_score_api_validates_payload() -> None: with pytest.raises(BadRequest, match="questionnaire must be an object"): _handler()._compute_active_rectification_score({"answers": {}}) with pytest.raises(BadRequest, match="answers must be an object"): _handler()._compute_active_rectification_score({"questionnaire": {}}) def _answered_rectification_score() -> dict: questionnaire = _handler()._compute_active_rectification_questions( { "birth_time": "1993-04-17 14:49", "uncertainty_minutes": 30, "step_minutes": 1, "lat": 36.683333, "lon": 114.35, "tz": 8, } ) return _handler()._compute_active_rectification_score( { "questionnaire": questionnaire, "answers": { "education_environment_shift": "A", "residence_relocation_shift": "B", "relationship_or_partner_entry": "D", "career_responsibility_pressure": "A", "research_tool_expression_shift": "C", }, } ) def test_rectification_score_exposes_narayana_cross_score_red() -> None: scored = _answered_rectification_score() assert scored["candidate_cluster_rankings"] assert all( "narayana_cross_score" in candidate for candidate in scored["candidate_cluster_rankings"] ) def test_rectification_technique_audit_mentions_narayana_red() -> None: scored = _answered_rectification_score() audit_rows = scored["technique_audit_table"] assert any( row.get("technique") == "Narayana Dasha Rectification" and row.get("status") in {"used", "partial"} for row in audit_rows ) def test_narayana_conflict_downgrades_without_replacing_vimshottari_red() -> None: scored = _handler()._compute_active_rectification_score( { "questionnaire": { "questions": [ { "id": "career_responsibility_pressure", "round": 1, "scoring_map": { "A": { "cluster": "middle_candidate_cluster", "points": 9, } }, } ] }, "answers": {"career_responsibility_pressure": "A"}, "narayana_cross_scores": { "early_candidate_cluster": 10, "middle_candidate_cluster": -10, }, } ) top = scored["candidate_cluster_rankings"][0] assert top["cluster"] == "middle_candidate_cluster" assert top["claim_status"] == "candidate" assert top["confidence_cap"] == "low" assert top["conflict_policy"] == "downgrade_without_replacement" def test_rectification_claim_remains_candidate_not_birth_time_truth_red() -> None: scored = _answered_rectification_score() assert scored["claim_status"] == "candidate" assert scored["truth_status"] != "birth_time_truth" def test_rectification_score_exposes_jaimini_karaka_cross_score_red() -> None: scored = _answered_rectification_score() assert scored["candidate_cluster_rankings"] assert all( "jaimini_karaka_cross_score" in candidate for candidate in scored["candidate_cluster_rankings"] ) def test_rectification_technique_audit_mentions_jaimini_karaka_red() -> None: scored = _answered_rectification_score() audit_rows = scored["technique_audit_table"] assert any( row.get("technique") == "Jaimini Karaka Rectification" and row.get("status") == "partial" for row in audit_rows ) def test_jaimini_karaka_conflict_downgrades_without_replacing_primary_rank_red() -> None: scored = _handler()._compute_active_rectification_score( { "questionnaire": { "questions": [ { "id": "career_responsibility_pressure", "round": 1, "scoring_map": { "A": { "cluster": "middle_candidate_cluster", "points": 9, } }, } ] }, "answers": {"career_responsibility_pressure": "A"}, "jaimini_karaka_cross_scores": { "early_candidate_cluster": 10, "middle_candidate_cluster": -10, }, } ) top = scored["candidate_cluster_rankings"][0] assert top["cluster"] == "middle_candidate_cluster" assert top["claim_status"] == "candidate" assert top["confidence_cap"] == "low" assert "jaimini_karaka" in top["downgrade_reasons"] def test_rectification_score_exposes_vimsopaka_avastha_cross_score_red() -> None: scored = _answered_rectification_score() assert scored["candidate_cluster_rankings"] assert all( "vimsopaka_avastha_cross_score" in candidate for candidate in scored["candidate_cluster_rankings"] ) def test_rectification_technique_audit_mentions_vimsopaka_avastha_red() -> None: scored = _answered_rectification_score() audit_rows = scored["technique_audit_table"] assert any( row.get("technique") == "Vimsopaka Avastha Rectification" and row.get("status") == "partial" for row in audit_rows ) def test_vimsopaka_avastha_conflict_downgrades_without_replacing_primary_rank_red() -> None: scored = _handler()._compute_active_rectification_score( { "questionnaire": { "questions": [ { "id": "career_responsibility_pressure", "round": 1, "scoring_map": { "A": { "cluster": "middle_candidate_cluster", "points": 9, } }, } ] }, "answers": {"career_responsibility_pressure": "A"}, "vimsopaka_avastha_cross_scores": { "early_candidate_cluster": 10, "middle_candidate_cluster": -10, }, } ) top = scored["candidate_cluster_rankings"][0] assert top["cluster"] == "middle_candidate_cluster" assert top["claim_status"] == "candidate" assert top["confidence_cap"] == "low" assert "vimsopaka_avastha" in top["downgrade_reasons"] def test_rectification_score_exposes_shadbala_av_observation_score_red() -> None: scored = _answered_rectification_score() assert scored["candidate_cluster_rankings"] assert all( "shadbala_av_observation_score" in candidate for candidate in scored["candidate_cluster_rankings"] ) assert scored["formula_unit_parity_status"] == "partial" def test_rectification_technique_audit_mentions_shadbala_av_low_weight_red() -> None: scored = _answered_rectification_score() audit_rows = scored["technique_audit_table"] assert any( row.get("technique") == "Shadbala Ashtakavarga Rectification" and row.get("status") == "partial_observation" and row.get("weight_policy") == "low_weight_only" for row in audit_rows ) def test_shadbala_av_conflict_downgrades_without_replacing_primary_rank_red() -> None: scored = _handler()._compute_active_rectification_score( { "questionnaire": { "questions": [ { "id": "career_responsibility_pressure", "round": 1, "scoring_map": { "A": { "cluster": "middle_candidate_cluster", "points": 9, } }, } ] }, "answers": {"career_responsibility_pressure": "A"}, "shadbala_av_observation_scores": { "early_candidate_cluster": 10, "middle_candidate_cluster": -10, }, } ) top = scored["candidate_cluster_rankings"][0] assert top["cluster"] == "middle_candidate_cluster" assert top["claim_status"] == "candidate" assert top["confidence_cap"] == "low" assert "shadbala_av" in top["downgrade_reasons"] def test_rectification_score_exposes_gochara_observation_score_red() -> None: scored = _answered_rectification_score() assert scored["candidate_cluster_rankings"] assert all( "gochara_transit_observation_score" in candidate for candidate in scored["candidate_cluster_rankings"] ) assert scored["timing_claim_status"] == "exploratory_unvalidated" def test_rectification_technique_audit_mentions_gochara_holdout_gate_red() -> None: scored = _answered_rectification_score() audit_rows = scored["technique_audit_table"] assert any( row.get("technique") == "Gochara Transit Rectification" and row.get("status") == "blocked_from_verified_timing" and row.get("holdout_gate") == "negative_holdout_required" for row in audit_rows ) def test_gochara_conflict_downgrades_without_verified_timing_claim_red() -> None: scored = _handler()._compute_active_rectification_score( { "questionnaire": { "questions": [ { "id": "career_responsibility_pressure", "round": 1, "scoring_map": { "A": { "cluster": "middle_candidate_cluster", "points": 9, } }, } ] }, "answers": {"career_responsibility_pressure": "A"}, "gochara_transit_observation_scores": { "early_candidate_cluster": 10, "middle_candidate_cluster": -10, }, } ) top = scored["candidate_cluster_rankings"][0] assert top["cluster"] == "middle_candidate_cluster" assert top["claim_status"] == "candidate" assert top["confidence_cap"] == "low" assert "gochara_transit" in top["downgrade_reasons"] assert scored["timing_claim_status"] == "exploratory_unvalidated"