"""Browser adapter for fixed synthetic projected-area scenes; NumPy only."""
import json,math,time
from pathlib import Path
import numpy as np
from leaf_kernel import scene,segment,measure
CONTROLS = {'scene': {'type': 'enum', 'values': ['clean', 'green_tag', 'dim', 'clipped'], 'default': 'clean'}, 'min_v': {'type': 'number', 'min': 0, 'max': 255, 'default': 100, 'step': 1, 'integer': True, 'unit': '0–255'}, 'roi': {'type': 'enum', 'values': ['full', 'tag_safe', 'small'], 'default': 'full'}, 'mm_per_pixel': {'type': 'number', 'min': 0.1, 'max': 1, 'default': 0.5, 'step': 0.1, 'unit': 'mm/pixel'}}
ROIS={'full':None,'tag_safe':(50,20,230,190),'small':(140,60,20,30)}
UNITS={'pixels':'pixel','reference_pixels':'pixel','projected_mm2':'mm²','mask_area_error_percent':'%','iou':'1','precision':'1','recall':'1','touches_frame':'0/1'}

def spans(name,mask):
    # Lossless horizontal runs; each x is a row-major pixel index, y a length.
    xs=[];ys=[]
    for row in range(mask.shape[0]):
        edges=np.diff(np.pad(mask[row].astype(np.int8),(1,1)))
        starts=np.flatnonzero(edges==1);ends=np.flatnonzero(edges==-1)
        xs.extend((row*320+starts).tolist());ys.extend((ends-starts).tolist())
    return dict(id=name,x=xs,y=ys,x_unit='row-major start pixel',y_unit='run length (pixels)')

def run(name,p):
    if name!='leaf' or set(p)!=set(CONTROLS):raise ValueError('Unknown experiment or parameters')
    for k,c in CONTROLS.items():
        v=p[k]
        if c['type']=='enum':
            if type(v) is not str or v not in c['values']:raise ValueError('Unknown choice: '+k)
        else:
            if type(v) not in (int,float) or not math.isfinite(v) or not c['min']<=v<=c['max']:raise ValueError('Parameter out of range: '+k)
            ticks=(v-c['min'])/c['step']
            if abs(ticks-round(ticks))>1e-8:raise ValueError('Parameter off step: '+k)
    start=time.perf_counter()
    rgb,reference=scene(dim=p['scene']=='dim',tag=p['scene']=='green_tag',clipped=p['scene']=='clipped')
    roi=ROIS[p['roi']];mask=segment(rgb,int(p['min_v']),roi);values=measure(mask,reference,p['mm_per_pixel'])
    metrics=[]
    for k,v in values.items():
        item=dict(id=k,value=int(v) if type(v) is bool else v,unit=UNITS[k])
        if v is None:item['reason']='Undefined ratio: denominator is zero'
        metrics.append(item)
    roi_mask=np.zeros(reference.shape,dtype=bool)
    if roi is not None:
        x,y,w,h=roi;roi_mask[y,x:x+w]=True;roi_mask[y+h-1,x:x+w]=True;roi_mask[y:y+h,x]=True;roi_mask[y:y+h,x+w-1]=True
    series=[spans('input_green',np.all(rgb==(50,160,65),axis=2)),spans('input_dim',np.all(rgb==(20,60,25),axis=2)),spans('reference_mask',reference),spans('selected_mask',mask),spans('false_positive',mask & ~reference),spans('false_negative',~mask & reference),spans('roi_outline',roi_mask)]
    return dict(metrics=metrics,series=series,stdout='',provenance=dict(data_type='synthetic',compute_ms=(time.perf_counter()-start)*1000))

if __name__=='__main__':
    import argparse
    parser=argparse.ArgumentParser(description=__doc__);parser.add_argument('--parameters',default=json.dumps({k:c['default'] for k,c in CONTROLS.items()}))
    print(json.dumps(run('leaf',json.loads(parser.parse_args().parameters)),allow_nan=False))