"""RegalFire original procedural fixture generators. Independent validation lives in check.py."""
import argparse
from collections import deque
import heapq
import json
from pathlib import Path
import random
import sys
from common import *

def astar(grid,costs,start,goal):
    h,w=len(grid),len(grid[0]); start=tuple(start); goal=tuple(goal)
    distance={start:0}; parent={}; queue=[(0,0,start)]
    while queue:
        _,cost,cell=heapq.heappop(queue)
        if distance[cell]!=cost: continue
        if cell==goal:
            path=[list(cell)]
            while cell!=start: cell=parent[cell]; path.append(list(cell))
            return {'cost':cost,'path':path[::-1]}
        y,x=cell
        for dy,dx in [(1,0),(-1,0),(0,1),(0,-1)]:
            b=(y+dy,x+dx)
            if 0<=b[0]<h and 0<=b[1]<w and grid[b[0]][b[1]]=='.':
                d=cost+costs[b[0]][b[1]]
                if d<distance.get(b,10**9):
                    distance[b]=d; parent[b]=cell
                    heapq.heappush(queue,(d+abs(b[0]-goal[0])+abs(b[1]-goal[1]),d,b))
    return {'cost':None,'path':None}
def nav(r,family):
    h,w=r.randint(6,10),r.randint(6,10); wall=r.randint(2,w-3)
    gap=0 if family=='boundary_gap' else r.randint(1,h-2)
    if family=='two_gap_detour': gap=1
    g=[['#' if r.random()<.22 else '.' for _ in range(w)] for _ in range(h)]
    for y in range(h): g[y][wall]='#'
    rows=[gap,h-2] if family=='two_gap_detour' else [gap]
    for y in rows:
        for x in range(w): g[y][x]='.'
    start=[r.randrange(h),r.randrange(wall)]; goal=[r.randrange(h),r.randint(wall+1,w-1)]
    if family=='two_gap_detour': start[0]=goal[0]=1
    for p in [start,goal]:
        for row in rows:
            for y in range(min(p[0],row),max(p[0],row)+1): g[y][p[1]]='.'
    if family=='gap_open': g[gap][wall]='#'
    grid=[''.join(row) for row in g]
    costs=[[r.randint(1,5) if family=='weighted_gap_close' else 1 for x in range(w)] for y in range(h)]
    before=astar(grid,costs,start,goal)
    changed=[list(row) for row in grid]; changed[gap][wall]='.' if changed[gap][wall]=='#' else '#'
    after=astar([''.join(row) for row in changed],costs,start,goal)
    if before['cost']==after['cost']: raise ValueError('edit not critical')
    return {'grid':grid,'costs':costs,'start':start,'goal':goal,'edit':[gap,wall]}, {'before':before,'after':after,'reachability_changed':(before['cost'] is None)!=(after['cost'] is None)}

def neighbors(grid,p,goal=None):
    y,x=p; options=[]
    for dy,dx in [(0,0),(1,0),(-1,0),(0,1),(0,-1)]:
        yy,xx=y+dy,x+dx
        if 0<=yy<len(grid) and 0<=xx<len(grid[0]) and grid[yy][xx]=='.': options.append((yy,xx))
    return [p] if goal is not None and p==goal else options
def single(grid,start,goal):
    q=deque([(tuple(start),0)]); seen={tuple(start)}
    while q:
        p,d=q.popleft()
        if p==tuple(goal): return d
        for b in neighbors(grid,p):
            if b not in seen: seen.add(b);q.append((b,d+1))
    return None
def joint_bfs(grid,starts,goals):
    start=tuple(map(tuple,starts)); target=tuple(map(tuple,goals)); q=deque([start]); parent={start:None}
    moves={tuple([y,x]):neighbors(grid,(y,x)) for y in range(len(grid)) for x in range(len(grid[0])) if grid[y][x]=='.'}
    while q:
        p=q.popleft()
        if p==target:
            plan=[]
            while p is not None: plan.append([list(p[0]),list(p[1])]);p=parent[p]
            return plan[::-1]
        for a in ([p[0]] if p[0]==target[0] else moves[p[0]]):
            for b in ([p[1]] if p[1]==target[1] else moves[p[1]]):
                state=(a,b)
                if a==b or (a==p[1] and b==p[0]) or state in parent: continue
                parent[state]=p;q.append(state)
    return None
def coord(r,family):
    h,w=r.choice([4,5,6]),r.choice([4,5,6])
    grid=[['#' if r.random()<.28 else '.' for _ in range(w)] for _ in range(h)]
    if family in ['bottleneck','separated']:
        wall=w//2
        for y in range(h): grid[y][wall]='#'
        if family=='bottleneck': grid[r.randrange(h)][wall]='.'
    free=[[y,x] for y in range(h) for x in range(w) if grid[y][x]=='.']
    if len(free)<8: raise ValueError('too few cells')
    starts=r.sample(free,2)
    if family=='adjacent_swap':
        adjacent=[p for p in free if abs(p[0]-starts[0][0])+abs(p[1]-starts[0][1])==1]
        if not adjacent: raise ValueError('no neighbor')
        starts[1]=r.choice(adjacent);goals=starts[::-1]
    elif family in ['bottleneck','separated']:
        left=[p for p in free if p[1]<w//2];right=[p for p in free if p[1]>w//2]
        if not left or not right: raise ValueError('empty region')
        starts=[r.choice(left),r.choice(right)];goals=starts[::-1]
    elif family=='crossing':
        rows=[[p for p in free if p[0]==y] for y in range(h)]
        candidates=[row for row in rows if len(row)>=2 and row[-1][1]-row[0][1]>=2]
        if not candidates:raise ValueError('no crossing row')
        row=r.choice(candidates);starts=[row[0],row[-1]];goals=starts[::-1]
    else: goals=r.sample([p for p in free if p not in starts],2)
    grid=[''.join(row) for row in grid]
    lower=[single(grid,s,g) for s,g in zip(starts,goals)]
    plan=joint_bfs(grid,starts,goals) if all(x is not None for x in lower) else None
    lb=max(lower) if all(x is not None for x in lower) else None
    cost=len(plan)-1 if plan else None
    return {'grid':grid,'starts':starts,'goals':goals}, {'plan':plan,'optimal_makespan':cost,'independent_lower_bound':lb,'coordination_overhead':cost-lb if cost is not None else None}

def read_label(fastq,policy):
    header,seq,sep,qual=fastq.split('\n'); errors=[]
    if not header.startswith('@'): errors.append('header')
    if sep!='+': errors.append('separator')
    if any(x not in 'ACGTN' for x in seq): errors.append('alphabet')
    if len(seq)!=len(qual): errors.append('quality_length')
    if any(not 33<=ord(q)<=74 for q in qual): errors.append('quality_ascii')
    if errors: return {'valid_fastq':False,'errors':sorted(errors),'passed_filter':False,'trimmed_sequence':None,'trimmed_quality':None,'quality_sum':None,'length':None,'n_count':None,'gc_count':None}
    end=len(seq)
    while end>0 and ord(qual[end-1])-33<policy['trim_q_min']: end-=1
    seq=seq[:end];qual=qual[:end];total=sum(ord(x)-33 for x in qual)
    return {'valid_fastq':True,'errors':[],'passed_filter':len(seq)>=policy['min_length'] and seq.count('N')<=policy['max_n'] and total>=policy['mean_q_min']*len(seq),
        'trimmed_sequence':seq,'trimmed_quality':qual,'quality_sum':total,'length':len(seq),'n_count':seq.count('N'),'gc_count':seq.count('G')+seq.count('C')}
def reads(r,family):
    policy={'min_length':r.randint(20,50),'max_n':r.randint(0,3),'mean_q_min':r.randint(18,28),'trim_q_min':r.randint(4,15)}
    length=r.randint(24,90)
    if family=='length_boundary': length=policy['min_length']+r.choice([-1,0,1])
    seq=''.join(r.choices('ACGT',k=length));q=[r.randint(30,41) for _ in seq]
    if family=='quality_boundary':
        level=policy['mean_q_min']+r.choice([-1,0,1]);q=[level for _ in seq]
    if family=='ambiguous_bases':
        count=policy['max_n']+r.choice([0,1]);idx=r.sample(range(length),count);s=list(seq)
        for i in idx:s[i]='N'
        seq=''.join(s)
    if family=='clean':
        tail=r.randint(1,8);q[-tail:]=[2]*tail
    qual=''.join(chr(x+33) for x in q);header='@synthetic_read';sep='+'
    if family=='malformed_record':
        error=r.choice(['header','separator','alphabet','quality_length','quality_ascii'])
        if error=='header':header='synthetic_read'
        elif error=='separator':sep='-'
        elif error=='alphabet':seq=seq[:-1]+'X'
        elif error=='quality_length':qual=qual[:-1]
        else:qual=qual[:-1]+chr(32)
    fastq='\n'.join([header,seq,sep,qual])
    return {'fastq':fastq,'policy':policy},read_label(fastq,policy)

def alignment(a,b):
    n,m=len(a),len(b);d=[[0]*(m+1) for _ in range(n+1)]
    for i in range(n+1):d[i][0]=i
    for j in range(m+1):d[0][j]=j
    for i in range(1,n+1):
        for j in range(1,m+1):d[i][j]=min(d[i-1][j]+1,d[i][j-1]+1,d[i-1][j-1]+(a[i-1]!=b[j-1]))
    aa=[];bb=[];i=n;j=m
    while i or j:
        if i and j and d[i][j]==d[i-1][j-1]+(a[i-1]!=b[j-1]):aa.append(a[i-1]);bb.append(b[j-1]);i-=1;j-=1
        elif i and d[i][j]==d[i-1][j]+1:aa.append(a[i-1]);bb.append('-');i-=1
        else:aa.append('-');bb.append(b[j-1]);j-=1
    return d[n][m],''.join(aa[::-1]),''.join(bb[::-1])
def align(r,family):
    rand=lambda n:''.join(r.choices('ACGT',k=n))
    if family=='homopolymer':a=rand(10)+r.choice('ACGT')*r.randint(8,16)+rand(10)
    elif family=='tandem_repeat':a=rand(9)+rand(3)*r.randint(3,7)+rand(9)
    else:a=rand(r.randint(24,50))
    if family=='literal_N':a=a[:10]+'NN'+a[12:]
    source=a
    if family=='reverse_complement':b=rc(a)
    else:
        b=list(a)
        for _ in range(r.randint(1,5)):
            pos=r.randrange(len(b));operation=r.choice(['sub','ins','del'])
            if operation=='sub':b[pos]=r.choice('ACGTN' if family=='literal_N' else 'ACGT')
            elif operation=='ins':b.insert(pos,r.choice('ACGT'))
            else:b.pop(pos)
        b=''.join(b)
    distance,aa,bb=alignment(a,b);threshold=max(0,distance+r.choice([-1,0,1]))
    return {'a':a,'b':b,'source_sequence':source,'threshold':threshold},{'edit_distance':distance,'within_threshold':distance<=threshold,'aligned_a':aa,'aligned_b':bb}

def interval_label(inp):
    def bed(v):return v['start']-(v['basis']=='one_closed'),v['end']
    q=inp['query'];a,b=bed(q);matches=[];segments=[]
    for i,f in enumerate(inp['features']):
        if f['contig']!=q['contig'] or (inp['same_strand'] and f['strand']!=q['strand']):continue
        c,d=bed(f);lo,hi=max(a,c),min(b,d)
        if lo<hi:matches.append({'feature_index':i,'overlap_bases':hi-lo});segments.append((lo,hi))
    covered=0;end=-1
    for lo,hi in sorted(segments):covered+=max(0,hi-max(lo,end));end=max(end,hi)
    return {'query_bed':[a,b],'matches':matches,'union_overlap_bases':covered,'query_length':b-a}
def intervals(r,family):
    contigs={'synthetic_A':r.randint(600,1800),'synthetic_B':r.randint(600,1800)}
    c=r.choice(list(contigs));a=r.randint(20,contigs[c]-200);b=a+r.randint(5,80)
    q={'contig':c,'start':a,'end':b,'strand':r.choice(['+','-']),'basis':'zero_half_open'}
    features=[]
    for _ in range(r.randint(5,12)):
        cc=r.choice(list(contigs));x=r.randint(0,contigs[cc]-120);features.append({'contig':cc,'start':x,'end':x+r.randint(1,120),'strand':r.choice(['+','-']),'basis':'zero_half_open'})
    def feature(start,end,strand=None):return {'contig':c,'start':start,'end':end,'strand':strand or q['strand'],'basis':'zero_half_open'}
    if family=='touching_boundary':features[:2]=[feature(max(0,a-r.randint(1,20)),a),feature(b,b+r.randint(1,40))]
    elif family=='nested':features[:2]=[feature(a-5,b+5),feature(a+1,b-1)]
    elif family=='overlapping_blocks':features[:3]=[feature(a-3,a+3),feature(a+1,b),feature(b-2,b+3)]
    elif family=='stranded':features[:2]=[feature(a,b,'+'),feature(a,b,'-')]
    else:features[0]=feature(a,b)
    for f in features+[q]:
        if r.random()<.5 or family=='coordinate_conversion':f['start']+=1;f['basis']='one_closed'
    inp={'contigs':contigs,'features':features,'query':q,'same_strand':family=='stranded' or r.choice([True,False])}
    return inp,interval_label(inp)

MAKERS={'nav':nav,'coord':coord,'reads':reads,'align':align,'intervals':intervals}
def generate(kind,out,count,seed,resume=False):
    out=Path(out)
    if out.exists() and not resume:raise ValueError('output exists; use --resume')
    out.mkdir(parents=True,exist_ok=True);chunks=out/'chunks';chunks.mkdir(exist_ok=True)
    binding={'kind':kind,'count':count,'seed':seed,'source_sha256':sha(Path(__file__).read_text(encoding='utf-8')),'common_sha256':sha(Path(__file__).with_name('common.py').read_text(encoding='utf-8'))}
    if (out/'config.json').exists() and strict((out/'config.json').read_text())!=binding:raise ValueError('resume parameters/source mismatch')
    write_json(out/'config.json',binding)
    seen=set();total=0
    for file in sorted(chunks.glob('*.jsonl')):
        for line in file.read_text(encoding='utf-8').splitlines():
            row=strict(line)
            if row['index']!=total or row['fingerprint'] in seen:raise ValueError('invalid checkpoint shard')
            seen.add(row['fingerprint']);total+=1
    if total>count:raise ValueError('count below checkpoint size')
    attempts=0
    while total<count:
        batch=[];start=total
        while len(batch)<min(500,count-start):
            i=total;family=FAMILIES[kind][i%5]
            for retry in range(1000):
                try:
                    inp,expected=MAKERS[kind](random.Random(seed+i*1009+retry*100000003),family)
                    fp,group=semantic(kind,inp)
                    if fp in seen:continue
                    seen.add(fp);break
                except ValueError:continue
            else:raise ValueError('cannot produce unique record')
            attempts+=retry
            batch.append({'id':kind.upper()+f'-{i:07d}','index':i,'seed':seed,'family':family,'input':inp,'expected':expected,'fingerprint':fp,'group_id':group,'split':split(group),'provenance':provenance(kind)})
            total+=1
        temp=chunks/f'{start:07d}.jsonl.tmp';temp.write_text(''.join(enc(x)+'\n' for x in batch),encoding='utf-8');temp.replace(chunks/f'{start:07d}.jsonl')
        write_json(out/'checkpoint.json',{'committed_records':total,'target':count,'attempt_retries_this_run':attempts})
        print(f'{kind}: generated {total}/{count}',flush=True)
    with (out/'dataset.jsonl.tmp').open('w',encoding='utf-8',newline='\n') as dest:
        for file in sorted(chunks.glob('*.jsonl')):dest.write(file.read_text(encoding='utf-8'))
    (out/'dataset.jsonl.tmp').replace(out/'dataset.jsonl')
    return total
def main():
    p=argparse.ArgumentParser();p.add_argument('--kind',choices=NAMES,required=True);p.add_argument('--out',type=Path,required=True);p.add_argument('--count',type=int,required=True);p.add_argument('--seed',type=int,default=20261001);p.add_argument('--resume',action='store_true');a=p.parse_args()
    if not 100<=a.count<=100000:raise ValueError('count must be 100-100000')
    generate(a.kind,a.out,a.count,a.seed,a.resume)
if __name__=='__main__':main()