from itertools import *
from scipy import optimize as opt
from copy import deepcopy
+ import sys as sy
+
+
error = 0.1
epsilon = 1E-10
vrate = 0.8
POS_NUL = 2
POSINF1 = 3
init = []
+ fichier_init="config_initiale_default.txt"
beta = 1.3E-8
gamma = 55.54
delta = 0.2
+ zeta = 0.1
amplifieur = 1
sigma2 = 3500
Bi = 5
vp = {}
for h in V:
if not ASYNC or random() < taux_succes:
- s = Rh[h]- mt.log(float(sigma2)/D)/(gamma*mt.pow(Ps[h],float(1)/3))
+ s = Rh[h]- mt.log(float(sigma2)/D)/(gamma*mt.pow(Ps[h],float(2)/3))
if abs(s) > mxg :
print "ds calcul v",abs(s),idxexp
mxg = abs(s)
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(1)/3))) +la[h]*psh
- return v[h]* mt.log(float(sigma2)/D)/(gamma*mt.pow(float(2)/3)) +la[h]*psh
- for h in V:
- if not ASYNC or random() < taux_succes:
- lah = 0.05 if la[h] == 0 else la[h]
- rep = (float(2*v[h]*mt.log(float(sigma2)/D))/mt.pow(3*gamma*lah,float(3)/5))
- Psp[h] = epsilon if rep <= 0 else rep
- else :
+ #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
+ 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 :
Psp[h] = Ps[h]
- def __evalue_maj_theta__():
+ def initialisation_():
+ global u, v, la, w, theta , q, Ps, Rh, eta, x,init
+ fd = open(fichier_init,"r")
+ l= fd.readline()
+ init_p = eval(l)
+ print init_p
+ theta = omega
+ (q,Ps,Rh,eta,x,u,v,la,w) = tuple([deepcopy(x) for x in init_p])
+ init = [deepcopy(q),deepcopy(Ps),deepcopy(Rh),deepcopy(eta),
+ deepcopy(x),deepcopy(u),deepcopy(v),deepcopy(la),deepcopy(w)]
+
+
+
+ def __evalue_maj_theta__(nbexp,out=False):
global u, v, la, w, theta , q, Ps, Rh, eta, x, valeurFonctionDuale
+ nbexp = 10
res = {}
m = []
itermax = 100000
def __maj_theta(k):
+ mem = []
om = omega/(mt.pow(k,0.75))
return om
for idxexp in range(nbexp):
mxg = 0
- initialisation()
+ if not(out):
+ initialisation()
+ else :
+ initialisation_()
+
k = 1
arret = False
sm = 0
arret = errorq < error
k+=1
variation = "+" if smax > sm else "-"
- sm = smax
print variation,
if k%100 ==0 :
print "k:",k,"erreur sur q", errorq, "et q:",q
print "maxg=", mxg
+ mem = [deepcopy(q),deepcopy(Ps),deepcopy(Rh),deepcopy(eta),
+ deepcopy(x),deepcopy(u),deepcopy(v),deepcopy(la),deepcopy(w)]
+ if k%4500 == 0 :
+ print "#########\n",mem,"\#########\n"
+ if k%4600 == 0 :
+ print "#########\n",mem,"\#########\n"
+
+
+
if smax - sm > 500:
print "variation trop grande"
print "init"
print init
- sy.exit(0)
+ exit
+ sm = smax
+
if k == itermax:
print "nbre d'iteration trop grand"
print "init"
print init
- exit
+ sy.exit(1)
print "###############"
print k
+def __une_seule_exp__(fichier_donees):
+ global u, v, la, w, theta , q, Ps, Rh, eta, x, valeurFonctionDuale
+ initialisation()
+
+ fichier = open(fichier_donees, "r")
+ instructions ={}
+ for line in fichier:
+ l = line.split("=")
+ instructions[l[0]] = eval(l[1])
+ u, v, la, w, q, Ps, Rh, eta, x, = instructions['u'], instructions['v'], instructions['la'], instructions['w'], instructions['q'], instructions['Ps'], instructions['Rh'], instructions['eta'], instructions['x']
+ nbexp = 1
+ res = {}
+ m = []
+ itermax = 100000
+
+ def __maj_theta(k):
+ om = omega/(mt.pow(k,0.75))
+ return om
+ for idxexp in range(nbexp):
+ mxg = 0
+ k = 1
+ arret = False
+ sm = 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)
+ errorq = (max(q.values()) - min(q.values()))/min(q.values())
+ arret = errorq < error
+ k+=1
+ variation = "+" if smax > sm else "-"
+ print variation,
+ if k%100 ==0 :
+ print "k:",k,"erreur sur q", errorq, "et q:",q
+ print "maxg=", mxg
+ if smax - sm > 500:
+ print "variation trop grande"
+ print "init"
+ print init
+ exit
+ sm = smax
-ASYNC = False
-__evalue_maj_theta__(1,True)
-
+ if k == itermax:
+ print "nbre d'iteration trop grand"
+ print "init"
+ print init
+ exit
+ print "###############"
+ print k
+ print "###############"
+ m += [k]
-#ASYNC = True
-#taux_succes = 0.9
-#__evalue_maj_theta__()
+ print (min(m),max(m),float(sum(m))/nbexp,m),m
-"""
-initialisation()
-k = 1
-arret = False
-while k < 10000 and not arret :
- (u,v,la,w,theta,eta,q,Ps,Rh,x,valeurFonctionDuale,ar)=maj(k,maj_theta)
- arret = ar
- k+=1
- errorq = abs(min(q.values())-max(q.values()))
- print "errorq",errorq
- arret = errorq < error
-"""
-"""
- print "u",u
- print "w",w
- print "theta",theta
- print "eta", eta
- print "q",q
- print "v",v
- print "lambda",la
- print "Ps",Ps
- print "Rh",Rh
- print "x",x
-"""
+ASYNC = False
+__une_seule_exp__("config_initiale.py")
+#__evalue_maj_theta__()
+#ASYNC = True
+#taux_succes = 0.9
+#__evalue_maj_theta__()
-"""
- k +=1
-"""
