import numpy as np

class RuleBasedQualityEvaluator:

    def evaluate(self, f: dict, shape: str):
        shape = shape.lower()

        if shape == "circle":
            circ = f["circularity"]
            ecc = f["eccentricity"]

            score = np.clip((circ - 0.8) / 0.2, 0, 1)

            if circ >= 0.95 and ecc < 0.3:
                return "perfect", float(score)
            elif circ >= 0.85:
                return "medium", float(score * 0.8)
            else:
                return "irregular", float(score * 0.6)

        if shape in ["square", "rectangle"]:
            ang = f["angle_error"]
            side_var = f["side_length_variance"]

            score = 1 - np.clip((ang/30 + side_var) / 2, 0, 1)

            if ang <= 5 and side_var <= 0.05:
                return "perfect", float(score)
            elif ang <= 15 and side_var <= 0.15:
                return "medium", float(score * 0.8)
            else:
                return "irregular", float(score * 0.6)

        if shape == "triangle":
            ang = f["angle_error"]
            side_var = f["side_length_variance"]

            score = 1 - np.clip((ang/25 + side_var) / 2, 0, 1)

            if ang <= 5 and side_var <= 0.05:
                return "perfect", float(score)
            elif ang <= 15 and side_var <= 0.15:
                return "medium", float(score * 0.8)
            else:
                return "irregular", float(score * 0.6)

        return "unknown", 0.0