"""Rescore fixed detections across IoU and semantic acceptance thresholds."""

from metrics.classification import compute_classification_metrics
from metrics.localisation import compute_localisation_metrics
from metrics.semantic import SemanticPolicy, compute_semantic_classification_metrics, compute_semantic_localisation_metrics

IOU_GRID = (0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90)
SEMANTIC_GRID = (0.50, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.0)


def policy_at_threshold(payload: dict, threshold: float) -> SemanticPolicy:
    if not 0 <= threshold <= 1:
        raise ValueError("Semantic threshold must be between zero and one")
    return SemanticPolicy.from_dict({**payload, "accepted_matrix": [
        [int(i == j or (threshold < 1 and value > threshold)) for j, value in enumerate(row)]
        for i, row in enumerate(payload["cosine_matrix"])
    ]})


def build_sensitivity(predictions, gold, policy_payload) -> dict:
    clean = [r for r in predictions if r.parsed_cleanly]
    exact_class = compute_classification_metrics(clean, gold)["summary"]["micro"]
    exact_iou = [{"iou": t, **compute_localisation_metrics(clean, gold, t)["summary"]["micro"]} for t in IOU_GRID]
    classifications, localisations = [], []
    for threshold in SEMANTIC_GRID:
        policy = policy_at_threshold(policy_payload, threshold)
        classification = compute_semantic_classification_metrics(clean, gold, policy)
        classifications.append({"threshold": threshold, **classification["summary"]["micro"], "newly_credited": len(classification["credited_matches"])})
        for iou in IOU_GRID:
            loc = compute_semantic_localisation_metrics(clean, gold, policy, iou)
            localisations.append({"threshold": threshold, "iou": iou, **loc["summary"]["micro"], "newly_credited": len(loc["credited_matches"])})
    return {
        "n_images": len(clean), "iou_grid": IOU_GRID, "semantic_grid": SEMANTIC_GRID,
        "scoring_definition": "All retained detections are evaluated without confidence filtering, weighting, or ranking. Only the IoU and semantic acceptance rules change; exact class IDs at IoU >= 0.50 remain primary.",
        "retention_caveat": "Results are conditional on saved predictions. Inference-time detector confidence filtering and score-ranked output caps can affect which detections were retained.",
        "exact_classification": exact_class, "exact_iou": exact_iou,
        "classification": classifications, "localisation": localisations,
    }