#!/usr/bin/env python3
"""unify.py — global unified-law fit: cut = alpha*ln1p(am*s/res^p / beta)+c
across multi6 (6 peaks) + tt-series (8 points, both peaks)."""
import numpy as np, glob, wave
from scipy.optimize import least_squares

def deepest(dirname,b):
    best=None
    for fn in sorted(glob.glob(dirname+'/ph*.npz')):
        d=np.load(fn)
        if '0x540628' not in d.files: continue
        s=d['0x540628'].astype(np.float64)
        if best is None or s[b]<best[0]: best=(s[b],s)
    return best[1] if best else None

def loadwav(p):
    w=wave.open(p,'rb'); n=w.getnframes(); ch=w.getnchannels(); sw=w.getsampwidth()
    d=w.readframes(n); w.close()
    if sw==2: return np.frombuffer(d,dtype=np.int16).astype(np.float64).reshape(-1,ch).mean(1)/32768
    raw=np.frombuffer(d,dtype=np.uint8).reshape(-1,ch,3)
    s=raw[:,:,0].astype(np.int64)|(raw[:,:,1].astype(np.int64)<<8)|(raw[:,:,2].astype(np.int64)<<16)
    return np.where(s>=0x800000,s-0x1000000,s).astype(np.float64).reshape(-1,ch).mean(1)/8388608

def ta(x,f,sr=44100,L=None):
    x=x[-L:]; t=np.arange(len(x))/sr; c=np.cos(2*np.pi*f*t); sn=np.sin(2*np.pi*f*t)
    return np.hypot(2*(x*c).sum(),2*(x*sn).sum())/len(x)

pts=[]
# multi6 six peaks
S=deepest('/tmp/opencode/sc_multi6',85)
cut=np.maximum(-S*8.685889638,0)
am=np.zeros(len(S)); rs=np.zeros(len(S))
for ln in open('/tmp/opencode/tract_multi6.txt'):
    if ln.startswith('#'): continue
    p=ln.split(); kk=int(p[0])
    if kk<len(S): am[kk]=float(p[1]); rs[kk]=float(p[2])
for kk in range(1,len(S)):
    if cut[kk]>1.0 and am[kk]>0.01:
        pts.append(('m6',am[kk],rs[kk],cut[kk]))
# tt-series 4 drives x 2 peaks (ref-domain cuts via Goertzel)
inp0=loadwav('/tmp/opencode/tt0_in.wav')
rc={0:(10.34,11.84),6:(8.12,9.57),12:(6.12,7.45),18:(4.40,5.55)}
for att,(c1v,c2v) in rc.items():
    tf='/tmp/opencode/tract_tt%d.txt'%att
    d43=d171=None; r43=r171=None
    for ln in open(tf):
        if ln.startswith('#'): continue
        p=ln.split(); kk=int(p[0])
        if kk==43: r43=float(p[2]); d43=am0=None; d43=float(p[1])
        if kk==171: r171=float(p[2]); d171=float(p[1])
    pts.append(('tt%d-pk1'%att,d43,r43,c1v))
    pts.append(('tt%d-pk2'%att,d171,r171,c2v))
print('points:',len(pts))

def resid(p):
    al,be,cc,pp,ss=p
    out=[]
    for nm,a,r,c in pts:
        X=a*ss/max(r**pp,1e-12)
        out.append(al*np.log1p(X/be)+cc-c)
    return np.array(out)

p0=[3.28,0.56,0.77,1.25,1.0]
lb=[0.5,0.01,-5,0.05,0.05]
ub=[8,5,5,4,50]
r=least_squares(resid,p0,bounds=(lb,ub),max_nfev=8000)
mm=-resid(r.x)+np.array([c for _,_,_,c in pts])
tgt=np.array([c for _,_,_,c in pts])
rms=np.sqrt(((mm-tgt)**2).mean())
print('UNIFIED: alpha=%.3f beta=%.4f c=%+.3f p=%.3f s=%.3f ; rms=%.4f max=%.3f' % (
    *r.x,rms,np.abs(mm-tgt).max()))
for (nm,a,rr,c),pv in zip(pts,mm):
    print('  %-10s am=%.4f res=%.4f cut=%6.2f pred=%6.2f err=%+.2f' % (nm,a,rr,c,pv,c-pv))