| """Assay Engine: Form-Factor Baseline Matching, BIS Calculation & Dynamic Price Adjustments.""" |
| from __future__ import annotations |
|
|
| import json |
| from dataclasses import dataclass, field |
| from pathlib import Path |
| from typing import Any |
|
|
| from .model_client import Detection |
|
|
|
|
| @dataclass |
| class AssayedBoard: |
| form_factor: str |
| board_integrity_score: float |
| base_price: float |
| adjusted_price: float |
| price_floor: float |
| detected_counts: dict[str, int] |
| expected_counts: dict[str, int] |
| fraud_desoldered_pads: int |
| factory_unpopulated_pads: int |
| occluded_regions: int |
| status_band: str |
| discrepancy_status: str = "pass" |
|
|
|
|
| PROFILES_FILE = Path(__file__).parent / "board_profiles.json" |
|
|
|
|
| def load_board_profiles() -> dict: |
| if PROFILES_FILE.exists(): |
| with open(PROFILES_FILE, "r", encoding="utf-8") as f: |
| return json.load(f) |
| return {} |
|
|
|
|
| def calculate_board_integrity_score( |
| detections: list[Detection], |
| form_factor: str = "desktop_atx", |
| profiles: dict | None = None, |
| ) -> tuple[float, dict[str, int], dict[str, int], int, int, int]: |
| """Calculate Board Integrity Score (BIS 0-100) using form factor baselines.""" |
| if profiles is None: |
| profiles = load_board_profiles() |
|
|
| profile = profiles.get(form_factor) or profiles.get("default") or { |
| "price_floor": 0.35, |
| "expected_components": {"cpu_socket": 1, "gold_finger": 1, "ic_chip": 3, "tantalum_capacitor": 4}, |
| "weights": {"cpu_socket": 0.40, "gold_finger": 0.25, "ic_chip": 0.20, "tantalum_capacitor": 0.15}, |
| } |
|
|
| expected = profile.get("expected_components", {}) |
| weights = profile.get("weights", {}) |
|
|
| detected_counts: dict[str, int] = {} |
| fraud_pads = 0 |
| factory_pads = 0 |
| occluded = 0 |
|
|
| for d in detections: |
| c = d.class_name |
| if c == "forcibly_desoldered_pad": |
| fraud_pads += 1 |
| elif c == "factory_unpopulated_pad": |
| factory_pads += 1 |
| elif c == "occluded_region": |
| occluded += 1 |
| else: |
| detected_counts[c] = detected_counts.get(c, 0) + 1 |
|
|
| |
| weighted_score = 0.0 |
| total_weight = sum(weights.values()) or 1.0 |
|
|
| for cls_name, exp_num in expected.items(): |
| if exp_num > 0: |
| det_num = detected_counts.get(cls_name, 0) |
| ratio = min(1.0, det_num / float(exp_num)) |
| else: |
| ratio = 1.0 |
|
|
| w = weights.get(cls_name, 0.0) |
| weighted_score += w * ratio |
|
|
| |
| bis_raw = (weighted_score / total_weight) * 100.0 |
|
|
| |
| fraud_penalty = fraud_pads * 25.0 |
|
|
| final_bis = max(0.0, min(100.0, bis_raw - fraud_penalty)) |
| return final_bis, detected_counts, expected, fraud_pads, factory_pads, occluded |
|
|
|
|
| def calculate_adjusted_scrap_price( |
| bis: float, |
| base_price: float, |
| form_factor: str = "desktop_atx", |
| profiles: dict | None = None, |
| ) -> tuple[float, float]: |
| """Calculate dynamic scrap purchase price based on category scrap grade floor: |
| |
| Adjusted Price = Base Price * (Floor + (1 - Floor) * (BIS / 100)) |
| """ |
| if profiles is None: |
| profiles = load_board_profiles() |
|
|
| profile = profiles.get(form_factor) or profiles.get("default") or {"price_floor": 0.35} |
| price_floor = float(profile.get("price_floor", 0.35)) |
|
|
| adjusted_price = base_price * (price_floor + (1.0 - price_floor) * (bis / 100.0)) |
| return round(adjusted_price, 2), price_floor |
|
|
|
|
| def assess_bis_discrepancy(collector_bis: float, recycler_bis: float) -> str: |
| """Assess mid-chain cannibalization fraud discrepancy bands. |
| |
| < 12% BIS Drop -> pass (normal capture variance) |
| 12-25% BIS Drop -> advisory_flag |
| > 25% BIS Drop -> critical_fraud_alert |
| """ |
| bis_drop = collector_bis - recycler_bis |
| if bis_drop < 12.0: |
| return "pass" |
| elif bis_drop <= 25.0: |
| return "advisory_flag" |
| else: |
| return "critical_fraud_alert" |
|
|
|
|
| def assay_pcb( |
| detections: list[Detection], |
| base_price: float = 100.0, |
| form_factor: str = "desktop_atx", |
| profiles: dict | None = None, |
| ) -> AssayedBoard: |
| """Complete Board Integrity Assay workflow.""" |
| bis, det_counts, exp_counts, fraud_pads, factory_pads, occluded = calculate_board_integrity_score( |
| detections, form_factor, profiles |
| ) |
| adj_price, floor = calculate_adjusted_scrap_price(bis, base_price, form_factor, profiles) |
|
|
| if bis >= 85.0: |
| status_band = "pristine" |
| elif bis >= 50.0: |
| status_band = "partial" |
| else: |
| status_band = "severe" |
|
|
| return AssayedBoard( |
| form_factor=form_factor, |
| board_integrity_score=round(bis, 1), |
| base_price=base_price, |
| adjusted_price=adj_price, |
| price_floor=floor, |
| detected_counts=det_counts, |
| expected_counts=exp_counts, |
| fraud_desoldered_pads=fraud_pads, |
| factory_unpopulated_pads=factory_pads, |
| occluded_regions=occluded, |
| status_band=status_band, |
| discrepancy_status="pass", |
| ) |
|
|
