From: couchot Date: Fri, 6 Dec 2013 08:24:40 +0000 (+0100) Subject: modifs typs X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/desynchronisation-controle.git/commitdiff_plain/ee130e6966e1e2f76dbf655947b04762008e12b9?hp=e6cd9df3d469f7916d513610d3bc22ab055f790a modifs typs --- diff --git a/IWCMC14/argmin.tex b/IWCMC14/argmin.tex index be684d4..6aae1e5 100644 --- a/IWCMC14/argmin.tex +++ b/IWCMC14/argmin.tex @@ -47,8 +47,8 @@ v_h^{(k)}.\dfrac{\ln(\sigma^2/D_h)}{\gamma p^{2/3}} + \lambda_h^{(k)}p \max \left\{\epsilon, \left( \dfrac{ --\lambda_h^{(k)} + \sqrt{(\lambda_h^{(k)})^2 + \dfrac{64}{9}\alpha} -}{\frac{16}{3}\delta_p} +-3\lambda_h^{(k)} + \sqrt{(3\lambda_h^{(k)})^2 + 64\delta_p/\gamma.\ln(\sigma^2/D_h)} +}{16\delta_p} \right)^{\frac{3}{5}} \right\} \\ \hline diff --git a/IWCMC14/convexity.tex b/IWCMC14/convexity.tex index 0f7bf7e..b1f2900 100644 --- a/IWCMC14/convexity.tex +++ b/IWCMC14/convexity.tex @@ -38,7 +38,7 @@ $$ \begin{array}{rcl} f'(p) &=& -2/3.v_h.\dfrac{\ln(\sigma^2/D_h)}{\gamma p^{5/3}} + \lambda_h + 8/3.\delta_p p^{5/3} \\ -& = & \dfrac {8/3\gamma.\delta_p p^{10/3} + \lambda_h p^{5/3} -2/3.v_h\ln(\sigma^2/D_h) }{p^{5/3}} +& = & \dfrac {8/3.\delta_p p^{10/3} + \lambda_h p^{5/3} -2/3\gamma.v_h\ln(\sigma^2/D_h) }{p^{5/3}} \end{array} $$ which is positive if and only if the numerator is. diff --git a/exp_controle_asynchrone/simulMWSN.py b/exp_controle_asynchrone/simulMWSN.py index 218ecb7..7ca4bd5 100644 --- a/exp_controle_asynchrone/simulMWSN.py +++ b/exp_controle_asynchrone/simulMWSN.py @@ -9,14 +9,15 @@ from copy import deepcopy import sys as sy import cv as cv import cv2 as cv2 +import datetime as dt errorq = 0.1 -errorD = 1E-5 +errorD = 1E-1 epsilon = 1E-10 vrate = 0.8 p = 0.7 coteCarre = 50 -distanceEmmissionMax = 20 +distanceEmmissionMax = 30 nbiter = 1000 POS = 1 POS_NUL = 2 @@ -108,13 +109,15 @@ G.add_weighted_edges_from(lg) #nx.draw(G) #pb.show() -(G,l) = genereGraph() +#(G,l) = genereGraph() N = G.nodes() #V = list(set(sample(N,int(len(N)*vrate)))-set([sink])) V = list(set(N)-set([sink])) source = V print "source",source -afficheGraph(G,l,500,500,sink) + + +#afficheGraph(G,l,500,500,sink) #nx.draw(G) #pb.show() @@ -122,7 +125,7 @@ afficheGraph(G,l,500,500,sink) -exit() + #print G.edges(data=True) #TODO afficher le graphe et etre sur qu'il est connexe @@ -163,7 +166,6 @@ alpha = 0.5 beta = 1.3E-8 gamma = 55.54 delta = 0.2 -zeta = 0.1 amplifieur = 1 sigma2 = 3500 Bi = 5 @@ -241,19 +243,11 @@ def armin(f,xini,xr,args): #xpos = lambda x : x if x > 0 else -1 r = 0 if xr == POS : - #print "strictement pos" - #print "parametres passes a cobyla",xini,xpos,args,"consargs=(),rhoend=1E-5,iprint=0,maxfun=1000" - r= opt.fmin_cobyla(f,xini,cons=[xpos],args=args,consargs=(),rhoend=1E-3,iprint=0,maxfun=nbiter) - #print "le min str pos est",r - #print "le min pos est", r,"avec xini",xini + r= opt.fmin_cobyla(f,xini,cons=[xpos],args=args,consargs=(),rhoend=errorD/100,iprint=0,maxfun=nbiter) elif xr == POS_NUL : - #print "pos ou nul" - r = opt.fmin_cobyla(f,xini,[xposounul],args,consargs=(),rhoend=1E-3,iprint=0,maxfun=nbiter) - # print "le min pos est", r - #print "le min pos null est", r,"avec xini",xini + r = opt.fmin_cobyla(f,xini,[xposounul],args,consargs=(),rhoend=errorD/100,iprint=0,maxfun=nbiter) elif xr == POSINF1: - r = opt.fmin_cobyla(f,xini,[entre0et1],args,consargs=(),rhoend=1E-3,iprint=0,maxfun=nbiter) - #print "le min pos inf 1 est", r,"avec xini",xini + r = opt.fmin_cobyla(f,xini,[entre0et1],args,consargs=(),rhoend=errorD/100,iprint=0,maxfun=nbiter) return r @@ -344,39 +338,48 @@ def maj(k,maj_theta,mxg,idxexp): qp={} - def f_q(qi,i): + def f_q(qi,*args): fa = sum([a[i][l]*w[l] for l in L]) - la[i]*Bi return qi*qi + qi*fa + tq,tqa = 0,0 for i in N: if not ASYNC or random() < taux_succes: + n1 = dt.datetime.now() c = -float(sum([a[i][l]*w[l] for l in L]) - la[i]*Bi)/(2*amplifieur) + n2 = dt.datetime.now() + cp = armin(f_q,q[i],POS,tuple([i])) + n3 = dt.datetime.now() + tq += (n2-n1).microseconds + tqa += (n3-n2).microseconds rep = epsilon if c <= 0 else c qp[i] = rep else : qp[i] = q[i] - - + tp,tpa = 0,0 Psp={} - #print "maj des des Psh" def f_Ps(psh,h): - #print "ds f_ps",psh, v[h]* mt.log(float(sigma2)/D)/(gamma*((psh**2)**(float(2)/3))) +la[h]*psh - return v[h]* mt.log(float(sigma2)/D)/(gamma*mt.pow(float(2)/3)) +la[h]*psh + try: + #print psh,(gamma*mt.pow(psh,float(2)/3)) + res= v[h]* mt.log(float(sigma2)/D)/(gamma*mt.pow(psh,float(2)/3)) +la[h]*psh + delta*mt.pow(psh,float(8)/3) + return res + except : + return 0 for h in V: - if not ASYNC or random() < taux_succes: - """ - lah = 0.05 if la[h] == 0 else la[h] - rep = mt.pow(float(2*v[h]*mt.log(float(sigma2)/D))/(3*gamma*lah),float(3)/5) - Psp[h] = epsilon if rep <= 0 else rep - """ - t= float(-3*la[h]+mt.sqrt(9*(la[h]**2)+64*zeta*v[h]*mt.log(float(sigma2)/D)/gamma))/(16*zeta) - #print t - rep = mt.pow(t,float(3)/5) - Psp[h]=rep - else : + if not ASYNC or random() < taux_succes: + n1 = dt.datetime.now() + t= float(-3*la[h]+mt.sqrt(9*(la[h]**2)+64*delta*v[h]*mt.log(float(sigma2)/D)/gamma))/(16*delta) + rep = mt.pow(t,float(3)/5) + n2 = dt.datetime.now() + cp = armin(f_Ps,Ps[h],POS,tuple([h])) + n3 = dt.datetime.now() + tp += (n2-n1).microseconds + tpa += (n3-n2).microseconds + Psp[h]=rep + else : Psp[h] = Ps[h] @@ -390,26 +393,43 @@ def maj(k,maj_theta,mxg,idxexp): Rhp={} + tr,tra=0,0 def f_Rh(rh,h): return delta*rh*rh-v[h]*rh-sum([u[(h,i)]*eta[(h,i)] for i in N]) - for h in V: if not ASYNC or random() < taux_succes: rep = float(v[h])/(2*delta) + n1 = dt.datetime.now() + rep = float(v[h])/(2*delta) + n2 = dt.datetime.now() + cp = armin(f_Rh,Rh[h],POS_NUL,tuple([h])) + n3 = dt.datetime.now() + tr += (n2-n1).microseconds + tra += (n3-n2).microseconds Rhp[h] = 0 if rep < 0 else rep else : Rhp[h] = Rh[h] + + + xp={} + tx,txa=0,0 def f_x(xhl,h,l): r = delta*xhl*xhl + xhl*(cs[l]*sum([la[i]*aplus[i][l] for i in N]) +cr*sum([la[i]*amoins[i][l] for i in N])+sum([u[(h,i)]*a[i][l] for i in N])) return r - for h in V: for l in L: if not ASYNC or random() < taux_succes: + n1 = dt.datetime.now() rep = -float(cs[l]*sum([la[i]*aplus[i][l] for i in N]) +cr*sum([la[i]*amoins[i][l] for i in N])+sum([u[(h,i)]*a[i][l] for i in N]))/(2*delta) + n2 = dt.datetime.now() + cp = armin(f_x,x[(h,l)],POS_NUL,tuple([h,l])) + n3 = dt.datetime.now() + tx += (n2-n1).microseconds + txa += (n3-n2).microseconds + xp[(h,l)] = 0 if rep < 0 else rep else : xp[(h,l)] = x[(h,l)] @@ -432,7 +452,7 @@ def maj(k,maj_theta,mxg,idxexp): arret = abs(valeurFonctionDuale-valeurFonctionDualep) - return (up,vp,lap,wp,thetap,etap,qp,Psp,Rhp,xp,valeurFonctionDualep,arret,mxg,smax) + return (up,vp,lap,wp,thetap,etap,qp,Psp,Rhp,xp,valeurFonctionDualep,arret,mxg,smax,tq+tp+tr+tx,tqa+tpa+tra+txa) @@ -525,7 +545,7 @@ def __evalue_maj_theta__(nbexp,out=False): res = {} m = [] itermax = 100000 - + def __maj_theta(k): mem = [] om = omega/(mt.pow(k,0.75)) @@ -542,15 +562,18 @@ def __evalue_maj_theta__(nbexp,out=False): arret = False sm = 0 err, ar = 0,0 + dur,dura=0,0 while k < itermax and not arret : - (u,v,la,w,theta,eta,q,Ps,Rh,x,valeurFonctionDuale,ar,mxg,smax)=maj(k,__maj_theta,mxg,idxexp) + print "ici" + (u,v,la,w,theta,eta,q,Ps,Rh,x,valeurFonctionDuale,ar,mxg,smax,ct,cta)=maj(k,__maj_theta,mxg,idxexp) err = (max(q.values()) - min(q.values()))/min(q.values()) - + dur += ct + dura += cta arret = err < errorq or ar < errorD k+=1 variation = "+" if smax > sm else "-" if out : print variation, - if k%500 ==0 : + if k%10 ==0 : print "k:", k, "erreur sur q", errorq, "erreur sur F", ar, "et q:", q @@ -563,7 +586,7 @@ def __evalue_maj_theta__(nbexp,out=False): #print "#########\n",mem,"\#########\n" if k%4600 == 0 : - #print "#########\n",mem,"\#########\n" + #print "#########m\n",mem,"\#########\n" """ @@ -589,7 +612,7 @@ def __evalue_maj_theta__(nbexp,out=False): #print liste_arret #print (min(m),max(m),float(sum(m))/nbexp,m),m - return liste_arret + return (liste_arret,dur,dura) def __une_seule_exp__(fichier_donees): @@ -651,12 +674,33 @@ def __une_seule_exp__(fichier_donees): ASYNC = False #__une_seule_exp__("config_initiale.py") +#pour evaluerle test d'arret +""" listederes=[] for k in list(np.logspace(-6, -3, num=15)): errorD = k listederes += __evalue_maj_theta__(5) print listederes +""" + + + +# pour evaluer argmin +listederes=[] +k=0 +for k in list(np.logspace(-5, -3, num=10)): + print "k",k + errorD = k + listederes += [(k,__evalue_maj_theta__(3))] + k+=1 +print listederes + + + +print"#######################" + + #ASYNC = True #taux_succes = 0.9 #__evalue_maj_theta__()