#!/usr/bin/env python3
"""
AM Material Selector — Additive Manufacturing Expert Skill
Filters and ranks materials from the database based on engineering requirements.
Usage: python3 select_material.py --help
"""
import json, argparse, sys
from pathlib import Path

DB_PATH = Path(__file__).parent.parent / "references" / "materials-db.json"

def load_db():
    with open(DB_PATH) as f:
        return json.load(f)

def parse_range(val):
    """Converts 'min-max' or a single number into (min, max)."""
    if val is None:
        return None, None
    s = str(val)
    if '-' in s:
        parts = s.split('-')
        return float(parts[0]), float(parts[1])
    return float(s), float('inf')

def score_material(mat, req):
    """Computes a 0-100 score for a material against requirements. Returns (score, reasons, disqualified)."""
    score = 100
    reasons = []
    disqualified = []

    mech = mat.get('mechanical', {})
    thermal = mat.get('thermal', {})
    flags = mat.get('flags', {})
    ra = mat.get('surface_roughness', {})

    # --- ELIMINATION FILTERS ---

    # Service temperature
    if req.get('T_service'):
        T = req['T_service']
        T_max = thermal.get('T_max_service', 9999)
        if isinstance(T_max, str):
            T_max = float(T_max.replace('>','').replace('~',''))
        if T_max < T:
            disqualified.append(f"T_max_service={T_max}°C < required {T}°C")

    # Process
    if req.get('process'):
        proc = req['process'].upper()
        mat_procs = [p.upper() for p in mat.get('processes', [])]
        if not any(proc in p or p in proc for p in mat_procs):
            disqualified.append(f"process {req['process']} not available (processes: {mat.get('processes')})")

    # Biocompatibility
    if req.get('biocompatible'):
        if not flags.get('biocompatible', False):
            disqualified.append("biocompatibility required but not available")

    # UV resistant
    if req.get('uv_resistant'):
        if not flags.get('uv_resistant', False):
            disqualified.append("UV resistance required but not guaranteed")

    # Minimum UTS
    if req.get('UTS_min') and disqualified == []:
        uts_min_req = req['UTS_min']
        uts_max_mat = mech.get('UTS_max') or mech.get('UTS_asbuilt_max') or mech.get('UTS_LPBF_max') or 0
        if uts_max_mat < uts_min_req:
            disqualified.append(f"UTS_max={uts_max_mat} MPa < required {uts_min_req} MPa")

    # Target roughness (Ra) — check if achievable
    if req.get('Ra_target') and disqualified == []:
        Ra_req = req['Ra_target']
        Ra_asbuilt = ra.get('Ra_asbuilt_typical', 50)
        postproc = ra.get('postprocess_achievable', {})
        Ra_achievable_min = Ra_asbuilt
        best_method = "as-built"
        for method, vals in postproc.items():
            if isinstance(vals, dict) and 'Ra_min' in vals:
                if vals['Ra_min'] < Ra_achievable_min:
                    Ra_achievable_min = vals['Ra_min']
                    best_method = method
        if Ra_achievable_min > Ra_req:
            disqualified.append(f"achievable Ra_min={Ra_achievable_min}µm > target {Ra_req}µm even with post-processing")
        else:
            if Ra_asbuilt > Ra_req:
                reasons.append(f"target Ra {Ra_req}µm achievable with {best_method} (as-built: {Ra_asbuilt}µm)")

    if disqualified:
        return 0, reasons, disqualified

    # --- POSITIVE SCORING ---

    # Temperature: more margin = better
    if req.get('T_service'):
        T = req['T_service']
        T_max = thermal.get('T_max_service', 9999)
        if isinstance(T_max, (int, float)):
            margin = T_max - T
            if margin > 100:
                score += 10
                reasons.append(f"excellent thermal margin (+{margin:.0f}°C)")
            elif margin > 30:
                score += 5

    # UTS: margin against requirement
    if req.get('UTS_min'):
        uts_min_req = req['UTS_min']
        uts_max_mat = mech.get('UTS_max') or mech.get('UTS_asbuilt_max') or mech.get('UTS_LPBF_max') or 0
        if uts_max_mat > 0:
            ratio = uts_max_mat / uts_min_req
            if ratio > 2:
                score += 10
            elif ratio > 1.5:
                score += 5

    # As-built Ra: if it already meets the target without post-processing -> advantage
    if req.get('Ra_target'):
        Ra_asbuilt = ra.get('Ra_asbuilt_typical', 50)
        if Ra_asbuilt <= req['Ra_target']:
            score += 15
            reasons.append(f"as-built Ra ({Ra_asbuilt}µm) already meets the target — no additional post-processing")

    # Printability
    difficulty_map = {
        "easy": 10, "moderate": 5, "difficult": 0, "very difficult": -5, "extreme": -10
    }
    diff = mat.get('print_difficulty', '')
    score += difficulty_map.get(diff, 0)

    # Cost
    cost = mat.get('cost_relative', 5)
    if cost <= 2:
        score += 8
        reasons.append(f"low cost (index {cost})")
    elif cost <= 5:
        score += 4
    elif cost > 15:
        score -= 10

    # Isotropy
    aniso = mech.get('anisotropy_Z_factor', 1.0)
    if aniso >= 0.9:
        score += 5
        reasons.append(f"good isotropy (Z/XY = {aniso})")

    # Quantity
    if req.get('quantity') and req['quantity'] > 100:
        procs = mat.get('processes', [])
        if any(p in ['SLS', 'MJF'] for p in procs):
            score += 8
            reasons.append("process well-suited for large series")
        if any(p == 'LPBF' for p in procs) and req['quantity'] > 50:
            score -= 5  # LPBF is expensive for large volumes

    return min(score, 100), reasons, []

def recommend(req, top_n=5):
    db = load_db()
    all_mats = db['polymers'] + db['metals']
    results = []
    eliminated = []

    for mat in all_mats:
        score, reasons, disqualified = score_material(mat, req)
        if disqualified:
            eliminated.append({'id': mat['id'], 'name': mat['name'], 'why': disqualified})
        else:
            results.append({
                'id': mat['id'],
                'name': mat['name'],
                'processes': mat.get('processes', []),
                'score': score,
                'reasons': reasons,
                'cost_relative': mat.get('cost_relative', '?'),
                'Ra_asbuilt': mat.get('surface_roughness', {}).get('Ra_asbuilt_typical', '?'),
                'T_max': mat.get('thermal', {}).get('T_max_service', '?'),
                'UTS_max': (mat.get('mechanical', {}).get('UTS_max') or
                            mat.get('mechanical', {}).get('UTS_asbuilt_max') or
                            mat.get('mechanical', {}).get('UTS_LPBF_max') or '?'),
                'postprocess_for_Ra': _ra_strategy(mat, req.get('Ra_target'))
            })

    results.sort(key=lambda x: x['score'], reverse=True)
    return results[:top_n], eliminated

def _ra_strategy(mat, Ra_target):
    """Returns the post-processing strategy to reach target Ra."""
    if Ra_target is None:
        return None
    ra = mat.get('surface_roughness', {})
    Ra_asbuilt = ra.get('Ra_asbuilt_typical', 50)
    if Ra_asbuilt <= Ra_target:
        return f"as-built is sufficient (Ra_typical={Ra_asbuilt}µm)"
    postproc = ra.get('postprocess_achievable', {})
    strategies = []
    for method, vals in postproc.items():
        if isinstance(vals, dict) and 'Ra_min' in vals:
            if vals['Ra_min'] <= Ra_target:
                note = vals.get('note', '')
                strategies.append(f"{method} → Ra≥{vals['Ra_min']}µm" + (f" ({note})" if note else ""))
    if strategies:
        return "; or ".join(strategies)
    return f"target Ra={Ra_target}µm NOT achievable (min={min((v['Ra_min'] for v in postproc.values() if isinstance(v,dict) and 'Ra_min' in v), default=Ra_asbuilt)}µm)"

def print_report(results, eliminated, req):
    print("\n" + "="*70)
    print("  AM MATERIAL SELECTOR — Results")
    print("="*70)
    print(f"\n  Requirements analyzed:")
    for k, v in req.items():
        if v is not None:
            print(f"    {k}: {v}")
    print(f"\n  Materials evaluated: {len(results)+len(eliminated)}")
    print(f"  Eligible: {len(results)} | Eliminated: {len(eliminated)}")

    print("\n" + "-"*70)
    print("  TOP CANDIDATES (sorted by score)")
    print("-"*70)
    for i, r in enumerate(results):
        print(f"\n  [{i+1}] {r['name']} (score: {r['score']}/100)")
        print(f"      Processes: {', '.join(r['processes'])}")
        print(f"      UTS_max: {r['UTS_max']} MPa | T_max: {r['T_max']}°C | Ra_asbuilt: {r['Ra_asbuilt']}µm | Cost: {r['cost_relative']}/10")
        if r['postprocess_for_Ra']:
            print(f"      Ra strategy: {r['postprocess_for_Ra']}")
        if r['reasons']:
            for reason in r['reasons'][:3]:
                print(f"      ✓ {reason}")

    if eliminated:
        print("\n" + "-"*70)
        print(f"  ELIMINATED ({len(eliminated)}) — main reasons")
        print("-"*70)
        shown = 0
        for e in eliminated[:10]:
            print(f"  ✗ {e['name']}: {'; '.join(e['why'][:2])}")
            shown += 1
        if len(eliminated) > shown:
            print(f"  ... and {len(eliminated)-shown} more")
    print("\n" + "="*70 + "\n")

def main():
    parser = argparse.ArgumentParser(description="AM Material Selector — filters materials by engineering requirements")
    parser.add_argument('--T',          type=float, help="Max service temperature (°C)")
    parser.add_argument('--UTS',        type=float, help="Minimum required UTS (MPa)")
    parser.add_argument('--Ra',         type=float, help="Target surface roughness Ra (µm)")
    parser.add_argument('--process',    type=str,   help="Specific process (FDM, SLS, LPBF, etc.)")
    parser.add_argument('--bio',        action='store_true', help="Biocompatibility required")
    parser.add_argument('--uv',         action='store_true', help="UV resistance required")
    parser.add_argument('--qty',        type=int,   help="Quantity (pcs)")
    parser.add_argument('--top',        type=int,   default=5, help="Number of results (default: 5)")
    parser.add_argument('--json',       action='store_true', help="JSON output")

    args = parser.parse_args()

    req = {
        'T_service':    args.T,
        'UTS_min':      args.UTS,
        'Ra_target':    args.Ra,
        'process':      args.process,
        'biocompatible':args.bio or None,
        'uv_resistant': args.uv or None,
        'quantity':     args.qty
    }
    req = {k: v for k, v in req.items() if v}

    if not req:
        print("ERROR: specify at least one requirement. Use --help for parameters.")
        sys.exit(1)

    results, eliminated = recommend(req, top_n=args.top)

    if args.json:
        print(json.dumps({'results': results, 'eliminated': eliminated}, indent=2))
    else:
        print_report(results, eliminated, req)

if __name__ == '__main__':
    main()