modifs typs

diff --git a/IWCMC14/argmin.tex b/IWCMC14/argmin.tex
index be684d45b5657674491e9625fe56d969c0c9ec6e..6aae1e500c96c6cec1c00cb9febf1f707c1153eb 100644 (file)
--- 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 0f7bf7e7e6f076cf4a54ccf8c6c0db1d854c787f..b1f29001a479b0489a92eba31434a13b18cfe808 100644 (file)
--- 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 218ecb7bc27746b049b3d9b3db3edca1caf48a53..7ca4bd5d22977de781f11709bac26c1c130e6253 100644 (file)
--- 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__()