eve-floquet-defect-rigidity / code /verify_maxwell_resource.py
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"""Full two-resource rectangle checks. Random testing does not prove theorems."""
from __future__ import annotations
import json,math,time,platform
from pathlib import Path
import numpy as np
from scipy.optimize import brentq
from scipy.integrate import quad
from maxwell_rectangle import Rectangle,generator_transfer,phase_speed
from maxwell_resource import *
from floquet import log_spectral_radius
from resource_floquet import lifted_phase_map
ROOT=Path(__file__).resolve().parents[1]
rng=np.random.default_rng(260926);start=time.time()
report={'seed':260926,'python':platform.python_version()}
boxes=[Rectangle(1,2,1,3),Rectangle(1,2,1,2),Rectangle(.7,2.5,.4,4)]
canonical=0;gainerr=0.;timeerr=0.;dualerr=0.;switcherr=0.;balanceerr=0.;signerr=0;tests=[]
for box in boxes:
for j in range(600):
eta,xi,zeta=rng.normal(size=3)*float(rng.choice([.15,.6,2.]))
if j%7==0:eta=0.
cell=calibrated_resource_cell(box,eta,xi,zeta)
am,ap,bm,bp=box.amin,box.amax,box.bmin,box.bmax
if min(cell.mean_a-am,ap-cell.mean_a,cell.mean_b-bm,bp-cell.mean_b)<1e-7 or cell.log_gain<1e-7:continue
explicit=explicit_resource_cell(box,cell.period,cell.mean_a,cell.mean_b)
assert cell_winding(explicit)==1
gainerr=max(gainerr,abs(cell.log_gain-explicit.log_gain))
dual,res,sw=resource_dual_parameters(box,explicit)
dualerr=max(dualerr,max(abs(a-b) for a,b in zip(dual,(eta,xi,zeta))))
switcherr=max(switcherr,res)
P=(cell.mean_a-am)/(ap-am);Q=(cell.mean_b-bm)/(bp-bm);w=P+Q-1
if abs(w)>1e-10:assert eta*w>0
# Cyclically merge an origin-split diagonal piece before comparing visits.
st=list(cell.states)
if st[0][:2]==st[-1][:2] and len(st)>1:
a,b,t=st.pop();aa,bb,tt=st[0];st[0]=(aa,bb,t+tt)
diagonal=(ap,bp) if eta>0 else (am,bm)
visits=[t for a,b,t in st if (a,b)==diagonal]
if eta:
assert len(visits)==2
balanceerr=max(balanceerr,abs(visits[0]-visits[1]))
else:assert len(st)==2
for i in range(20):
th=float(rng.uniform(0,math.pi));c,s=math.cos(th),math.sin(th)
K=s*c+xi*c*c-zeta*s*s
if eta>0:ab=(am,bp) if K>eta*s*s/bp else ((ap,bm) if K<-eta*c*c/ap else (ap,bp))
elif eta<0:ab=(am,bp) if K>-eta*c*c/am else ((ap,bm) if K<eta*s*s/bm else (am,bm))
else:ab=(am,bp) if K>0 else (ap,bm)
H=lambda a,b:((b-a)*s*c-eta-xi*a-zeta*b)/(b*c*c+a*s*s)
assert H(*ab)>=max(H(a,b) for a in [am,ap] for b in [bm,bp])-1e-10
canonical+=1
assert gainerr<1e-8 and dualerr<1e-7 and switcherr<1e-10 and balanceerr<1e-9
report['canonical']={'calibrated_cells':canonical,'pointwise_corner_checks':canonical*20,'max_gain_error':gainerr,'max_dual_error':dualerr,'max_switch_equation_residual':switcherr,'max_diagonal_visit_mismatch':balanceerr}
count=0;hyper=0;worst=-math.inf;meanerr=0.;defect_cases=[]
for box in boxes:
am,ap,bm,bp=box.amin,box.amax,box.bmin,box.bmax
for p,q in [(.2,.25),(.3,.7),(.7,.7),(.8,.1),(.2,.9)]:
abar=am+(ap-am)*p;bbar=bm+(bp-bm)*q
for S in np.linspace(.6,8,14):
F,cs=rectangle_resource_optimum(box,float(S),abar,bbar)
for j in range(16):
if j%2:
z=float(rng.uniform(max(0,p+q-1),min(p,q)))
fracs=[z,q-z,p-z,1-p-q+z];corners=[(ap,bp),(am,bp),(ap,bm),(am,bm)]
states=[]
for (a,b),f in zip(corners,fracs):
for t in rng.dirichlet(np.ones(3))*f*S:states.append((a,b,float(t)))
rng.shuffle(states)
else:
N=int(rng.integers(2,15));ts=rng.dirichlet(np.ones(N))*S
raw1=rng.uniform(-1,1,N);raw2=rng.uniform(-1,1,N)
sh1=brentq(lambda x:np.dot(np.clip(raw1+x,0,1),ts)/S-p,-3,3,xtol=1e-14)
sh2=brentq(lambda x:np.dot(np.clip(raw2+x,0,1),ts)/S-q,-3,3,xtol=1e-14)
aa=am+(ap-am)*np.clip(raw1+sh1,0,1);bb=bm+(bp-bm)*np.clip(raw2+sh2,0,1)
states=list(zip(aa,bb,ts))
M=np.eye(2)
for a,b,t in states:M=generator_transfer(a,b,t)@M
L=log_spectral_radius(M);worst=max(worst,L-F);count+=1
meanerr=max(meanerr,abs(sum(a*t for a,b,t in states)/S-abar),abs(sum(b*t for a,b,t in states)/S-bbar))
assert L<=F+2e-8,(box,S,p,q,L,F)
if L>1e-6:
hyper+=1
if len(defect_cases)<50 and j%3==0:defect_cases.append((box,S,abar,bbar,states,M,L,cs))
report['fixed_resource_random']={'profiles':count,'hyperbolic':hyper,'max_bound_excess':worst,'max_mean_error':meanerr}
errors=[];mindef=math.inf
for box,S,abar,bbar,states,M,L,cs in defect_cases:
vals,vecs=np.linalg.eig(M);x=np.real(vecs[:,np.argmax(np.abs(vals))]);theta0=math.atan2(-x[1],x[0]);theta=theta0
for a,b,t in states:
w=math.sqrt(b/a);theta=lifted_phase_map(lifted_phase_map(theta,w)+math.sqrt(a*b)*t,w,True)
n=round((theta-theta0)/math.pi)
cells=[c for j,c in cs if j==n];assert cells
opt=cells[0];dual,_,switches=resource_dual_parameters(box,opt);eta,xi,zeta=dual
corners=[(a,b) for a in [box.amin,box.amax] for b in [box.bmin,box.bmax]]
def defect(th,a,b):
c,s=math.cos(th),math.sin(th)
H=lambda aa,bb:((bb-aa)*s*c-eta-xi*aa-zeta*bb)/(bb*c*c+aa*s*s)
return max(H(*ab) for ab in corners)-H(a,b)
integral=0.;theta=theta0
for a,b,t in states:
w=math.sqrt(b/a);end=lifted_phase_map(lifted_phase_map(theta,w)+math.sqrt(a*b)*t,w,True)
points=[]
for z in switches:
z%=math.pi
for j in range(math.floor(theta/math.pi)-1,math.ceil(end/math.pi)+2):
zz=z+j*math.pi
if theta+1e-12<zz<end-1e-12:points.append(zz)
integral+=quad(lambda th:defect(th,a,b),theta,end,points=sorted(set(points)),epsabs=2e-10,limit=200)[0]
theta=end
errors.append(abs(integral-(n*opt.log_gain-L)));mindef=min(mindef,integral)
assert max(errors)<1e-7
report['defects']={'cases':len(errors),'max_absolute_error':max(errors),'minimum_defect':mindef}
# Resource-ray strict concavity, dual tangency, and two adjacent winners.
concavity_excess=0.;neighbor_checks=0;tangency_error=0.
for box in boxes:
for p,q in [(.2,.25),(.3,.7),(.7,.7),(.2,.9)]:
abar=box.amin+(box.amax-box.amin)*p;bbar=box.bmin+(box.bmax-box.bmin)*q
lo,hi=rectangle_resource_gap_interval(box,abar,bbar)
values=[explicit_resource_cell(box,float(t),abar,bbar).log_gain for t in np.linspace(lo+.02*(hi-lo),hi-.02*(hi-lo),21)]
concavity_excess=max(concavity_excess,float(np.max(np.diff(values,2))))
free=rectangle_resource_free(box,abar,bbar)
eta,xi,zeta=resource_dual_parameters(box,free)[0]
tangency_error=max(tangency_error,abs(eta+xi*abar+zeta*bbar-free.log_gain/free.period))
for S in np.linspace(.5,15,30):
F,cs=rectangle_resource_optimum(box,float(S),abar,bbar)
if cs:
n,c=max(cs,key=lambda z:z[0]*z[1].log_gain)
assert n in {math.floor(S/free.period),math.ceil(S/free.period)}
neighbor_checks+=1
assert concavity_excess<1e-8 and tangency_error<1e-6
report['resource_ray']={'concavity_curves':12,'max_discrete_concavity_excess':concavity_excess,'neighbor_winding_checks':neighbor_checks,'max_free_rate_dual_tangency_error':tangency_error}
# Endpoint means reduce exactly to the retained scalar resource theorem.
from resource_floquet import resource_optimum
endpoint_checks=0;endpoint_error=0.
for box in boxes:
for S in np.linspace(.5,7,8):
for aa,bb in [(box.amin,(box.bmin+box.bmax)/2),(box.amax,(box.bmin+box.bmax)/2),((box.amin+box.amax)/2,box.bmin),((box.amin+box.amax)/2,box.bmax)]:
F,cs=rectangle_resource_optimum(box,float(S),aa,bb)
for n,cell in cs:
endpoint_error=max(endpoint_error,abs(log_spectral_radius(resource_cell_monodromy(cell))-cell.log_gain))
assert cell_winding(cell)==1
endpoint_checks+=1
assert endpoint_error<1e-8
report['endpoint_reductions']={'cases':endpoint_checks,'max_equality_error':endpoint_error}
box=boxes[0];examples=[]
for abar,bbar,S in [(1.7,2.4,1.6),(1.7,2.4,2.),(1.3,1.4,2.),(1.3,2.4,2.)]:
F,cs=rectangle_resource_optimum(box,S,abar,bbar)
examples.append({'bounds':[1,2,1,3],'period':S,'mean_a':abar,'mean_b':bbar,'maximum_log_gain':F,'candidates':[{'winding':n,'gain':n*c.log_gain,'states':c.states,'duals':resource_dual_parameters(box,c)[0]} for n,c in cs]})
report['examples']=examples
report['elapsed_seconds']=time.time()-start;report['all_assertions_passed']=True
(ROOT/'results'/'verification_maxwell_resource.json').write_text(json.dumps(report,indent=2)+'\n')
print(json.dumps(report,indent=2))