Пример #1
0
        'Kr': Kr,
        'Lr': Lr,
        'd': d,
        'q': q,
        'alphastar': alphastar,
        'astar': astar,
        'lattice': lattice,
        'Hh': Hh,
        'Kh': Kh,
        'Lh': Lh
    }

    lowerm = [0, 0]
    upperm = [100, pi / 2]
    p0,jmin=anneal(chisq_an,p0,args=(Hr,Kr,Lr,d,q,alphastar,astar,lattice,Hh,Kh,Lh,y,yerr),\
                      schedule='simple',lower=lowerm,upper=upperm,\
                      maxeval=None, maxaccept=None,dwell=500,maxiter=6000,T0=None)
    dof = len(y) - len(p0)
    fake_dof = len(y)
    chimin = (cost_func(p0, Hr, Kr, Lr, d, q, alphastar, astar, lattice, Hh,
                        Kh, Lh, y, yerr)**2).sum()
    chimin = chimin / dof if dof > 0 else chimin / fake_dof
    print 'p0_anneal', p0[0], N.degrees(p0[1])
    print 'chi_anneal', chimin

    m = mpfit(myfunctlin, p0, parinfo=parinfo, functkw=fa)
    print 'status = ', m.status
    print 'params = ', m.params
    p1 = m.params
    covariance = m.covar
Пример #2
0
       'Hr':Hr
       ,'Kr':Kr
       ,'Lr':Lr
       ,'d':d
       ,'q':q
       ,'alphastar':alphastar,
       'astar':astar,
       'lattice':lattice,
       'Hh':Hh,
       'Kh':Kh,
       'Lh':Lh}
 
 lowerm=[0,0,0,0,0]
 upperm=[100,pi,pi/2,2*pi,pi]
 p0,jmin=anneal(chisq_an,p0,args=(Hr,Kr,Lr,d,q,alphastar,astar,lattice,Hh,Kh,Lh,y,yerr),\
                   schedule='simple',lower=lowerm,upper=upperm,\
                   maxeval=None, maxaccept=None,dwell=50,maxiter=60,T0=None)
 dof=len(y)-len(p0)
 fake_dof=len(y)
 chimin=(cost_func(p0,Hr,Kr,Lr,d,q,alphastar,astar,lattice,Hh,Kh,Lh,y,yerr)**2).sum()
 chimin=chimin/dof if dof>0 else chimin/fake_dof 
 print 'p0_anneal',p0[0],N.degrees(p0[1:])
 print 'chi_anneal', chimin
 
 
 
 
 m = mpfit(myfunctlin, p0, parinfo=parinfo,functkw=fa) 
 print 'status = ', m.status
 print 'params = ', m.params
 p1=m.params
Пример #3
0
        #scale by nuclear factor
        y = y / A
        yerr = yerr / A

        if 1:
            print 'annealing'
            #myschedule='fast'
            myschedule = 'simple'
            lowerm = 1e-4 * N.ones(len(pfit))
            #lowerm[0:3]=[-1,-1,-1]
            #upperm=N.ones(len(pfit))
            myargs = (Qlist, y, yerr, corrections)
            upperm = np.array(
                [1.0, 2.0, pi, pi, pi, pi, 2 * pi, 2 * pi, 2 * pi, 2 * pi])
            pout,jmin=anneal(chisq_an,pfit,args=myargs,\
                          schedule=myschedule,lower=lowerm,upper=upperm,\
                          maxeval=1000, maxaccept=None,dwell=2000,maxiter=120,feps=1e-2,full_output = 0)

            print 'annealed', pout
            pfit = pout

        parbase = {
            'value': 0.,
            'fixed': 0,
            'limited': [0, 0],
            'limits': [0., 0.]
        }
        parinfo = []
        for i in range(len(pfit)):
            parinfo.append(copy.deepcopy(parbase))
        for i in range(len(pfit)):
Пример #4
0
        print 'fm',fm
        #scale by nuclear factor
        y=y/A
        yerr=yerr/A

        if 0:
            print 'annealing'
            #myschedule='fast'
            myschedule='simple'
            lowerm=1e-4*N.ones(len(pfit))
                 #lowerm[0:3]=[-1,-1,-1]
            #upperm=N.ones(len(pfit))
            myargs=(Qlist,y,yerr,corrections)
            upperm=np.array([1000.0])
            pout,jmin=anneal(chisq_an,pfit,args=myargs,\
                          schedule=myschedule,lower=lowerm,upper=upperm,\
                          maxeval=1000, maxaccept=None,dwell=2000,maxiter=120,feps=1e-2,full_output = 0)

            print 'annealed',pout
            pfit=pout



        parbase={'value':0., 'fixed':0, 'limited':[0,0], 'limits':[0.,0.]}
        parinfo=[]
        for i in range(len(pfit)):
            parinfo.append(copy.deepcopy(parbase))
        for i in range(len(pfit)):
            parinfo[i]['value']=pfit[i]
        fa = {'x':Qlist, 'y':y, 'err':yerr, 'correction':corrections}
        m = mpfit(myfunctlin, pfit, parinfo=parinfo,functkw=fa)
Пример #5
0

        if 0:
            scipy.optimize.optimize.fmin_l_bfgs_b(max_wrap, p0, fprime = None, args=h_args, approx_grad = 0, \
                          bounds = None, m = 10, factr = 10000000.0, \
                          pgtol = 1.0000000000000001e-05, epsilon = 1e-08, iprint = -Const(1), maxfun = 15)
        if 0:
            print 'fmin'

            pout=scipy.optimize.optimize.fmin(max_wrap,p0,maxiter = 5, maxfun = 100,disp=1,args=h_args)
        if 0:
            print 'annealing'
            myschedule='fast'
            #myschedule='simple'
            pout,jmin=anneal(max_wrap,p0,args=h_args,\
                          schedule=myschedule,lower=lowerm,upper=upperm,\
                          maxeval=100, maxaccept=None,dwell=20,maxiter=20,feps=1e-1,full_output = 0)

        if 0:
            multipliers=pout[0:3]
            print 'multipliers',multipliers
            pout=pout[3::]

    if 0:
        myfilestr=r'c:\structfactors_density.dat'
        x2,y2,z2=N.loadtxt(myfilestr).T
        P2=z2.reshape((Mx,Mz))

        #P2=P2/P2.max()
        fq_density=calc_model(P2,h,k,l,fq,fqerr,x,z,cosmat_list,coslist,flist)
        X3,Z3,P3=plotdensity(h,k,l,fq)
Пример #6
0
def getmatrix(sx,sy,sz,mytol=1e-45,maxiter=2):
    print "(sx, sy, sz) = ", (sx, sy, sz)
    
    p0=N.array([0,1,0,1],'d')
    p0=N.array([0,0,0,1],'d')
    #p0=N.array([0,1,0,1],'d')
    lowerm=[-2,-2,-2,-2]
    upperm=[2,2,2,2]
    lowerm=[-1,-1,-1,-1]
    upperm=[1,1,1,1]
    flag=True
    smat=N.empty((3,1),'float64')
    smat=N.matrix(smat)
    smat[0]=0
    smat[1]=0
    smat[2]=1
    iter=0
    pbest=p0
    currbest=chisq_an(p0,sx,sy,sz)
    while flag:
        print 'iter',iter
        p0,jmin=anneal(chisq_an,p0,args=(sx,sy,sz),\
                      schedule='simple',lower=lowerm,upper=upperm,\
                      maxeval=None, maxaccept=None,dwell=10,maxiter=600,T0=10000)
        
    
        
        print 'p0',p0
        p = NLSP(chisq, p0,xtol=1e-37)
        #p = NLP(chisq_an, p0,xtol=1e-17)
        p.args.f=(sx,sy,sz)
        p.iprint = 10
        p.ftol=1e-30
        p.maxFunEvals = 1e10
        #p.checkdf()
        r = p.solve('nssolve')
        #r = p.solve('scipy_fsolve')
        #r = p.solve('nlp:ralg')
        #r = p.solve('ralg')
        #r = p.solve('scipy_cobyla')
        print 'solution:', r.xf
        a,b,c,s=r.xf 
        if 1:
            p0=[a,b,c,s]
            p=scipy.optimize.minpack.fsolve(chisq_f,p0,args=(sx,sy,sz),xtol=1e-37)
            a,b,c,s=p
            print '2nd soln',p
 
        amat=genmat(a,b,c,s)
        if 1:
            array_err=1e-2
            for i in range(3):
                for j in range(3):
                    if N.absolute(amat[i,j])<array_err:
                        amat[i,j]=0 
        sout=amat*smat
        curr_score=chisq_an(p0,sx,sy,sz)
        if curr_score<currbest:
            currbest=curr_score
            pbest=p
        if (N.abs(sout[0]-sx)<mytol and N.abs(sout[1]-sy)<mytol and N.abs(sout[2]-sz)<mytol) or iter>maxiter:
            flag=False
        iter=iter+1


    a,b,c,s=pbest    
    amat=genmat(a,b,c,s)
    
    if 1:
            array_err=1e-5
            for i in range(3):
                for j in range(3):
                    if N.absolute(amat[i,j])<array_err:
                        amat[i,j]=0 
    #print 'amat',amat
    print "AMAT\n\n\nAMAT: \n", amat, "\nSMAT\n" , smat, "\nAMAT * SMAT\n\n", amat*smat, "\nsx, sy, sz\n", (sx,sy,sz)
    return amat
Пример #7
0
                          pgtol = 1.0000000000000001e-05, epsilon = 1e-08, iprint = -Const(1), maxfun = 15)
        if 0:
            print 'fmin'

            pout = scipy.optimize.optimize.fmin(max_wrap,
                                                p0,
                                                maxiter=5,
                                                maxfun=100,
                                                disp=1,
                                                args=h_args)
        if 0:
            print 'annealing'
            myschedule = 'fast'
            #myschedule='simple'
            pout,jmin=anneal(max_wrap,p0,args=h_args,\
                          schedule=myschedule,lower=lowerm,upper=upperm,\
                          maxeval=100, maxaccept=None,dwell=20,maxiter=20,feps=1e-1,full_output = 0)

        if 0:
            multipliers = pout[0:3]
            print 'multipliers', multipliers
            pout = pout[3::]

    if 0:
        myfilestr = r'c:\structfactors_density.dat'
        x2, y2, z2 = N.loadtxt(myfilestr).T
        P2 = z2.reshape((Mx, Mz))

        #P2=P2/P2.max()
        fq_density = calc_model(P2, h, k, l, fq, fqerr, x, z, cosmat_list,
                                coslist, flist)
Пример #8
0
def getmatrix(sx, sy, sz, mytol=1e-45, maxiter=2):
    print "(sx, sy, sz) = ", (sx, sy, sz)

    p0 = N.array([0, 1, 0, 1], 'd')
    p0 = N.array([0, 0, 0, 1], 'd')
    #p0=N.array([0,1,0,1],'d')
    lowerm = [-2, -2, -2, -2]
    upperm = [2, 2, 2, 2]
    lowerm = [-1, -1, -1, -1]
    upperm = [1, 1, 1, 1]
    flag = True
    smat = N.empty((3, 1), 'float64')
    smat = N.matrix(smat)
    smat[0] = 0
    smat[1] = 0
    smat[2] = 1
    iter = 0
    pbest = p0
    currbest = chisq_an(p0, sx, sy, sz)
    while flag:
        print 'iter', iter
        p0,jmin=anneal(chisq_an,p0,args=(sx,sy,sz),\
                      schedule='simple',lower=lowerm,upper=upperm,\
                      maxeval=None, maxaccept=None,dwell=10,maxiter=600,T0=10000)

        print 'p0', p0
        p = NLSP(chisq, p0, xtol=1e-37)
        #p = NLP(chisq_an, p0,xtol=1e-17)
        p.args.f = (sx, sy, sz)
        p.iprint = 10
        p.ftol = 1e-30
        p.maxFunEvals = 1e10
        #p.checkdf()
        r = p.solve('nssolve')
        #r = p.solve('scipy_fsolve')
        #r = p.solve('nlp:ralg')
        #r = p.solve('ralg')
        #r = p.solve('scipy_cobyla')
        print 'solution:', r.xf
        a, b, c, s = r.xf
        if 1:
            p0 = [a, b, c, s]
            p = scipy.optimize.minpack.fsolve(chisq_f,
                                              p0,
                                              args=(sx, sy, sz),
                                              xtol=1e-37)
            a, b, c, s = p
            print '2nd soln', p

        amat = genmat(a, b, c, s)
        if 1:
            array_err = 1e-2
            for i in range(3):
                for j in range(3):
                    if N.absolute(amat[i, j]) < array_err:
                        amat[i, j] = 0
        sout = amat * smat
        curr_score = chisq_an(p0, sx, sy, sz)
        if curr_score < currbest:
            currbest = curr_score
            pbest = p
        if (N.abs(sout[0] - sx) < mytol and N.abs(sout[1] - sy) < mytol
                and N.abs(sout[2] - sz) < mytol) or iter > maxiter:
            flag = False
        iter = iter + 1

    a, b, c, s = pbest
    amat = genmat(a, b, c, s)

    if 1:
        array_err = 1e-5
        for i in range(3):
            for j in range(3):
                if N.absolute(amat[i, j]) < array_err:
                    amat[i, j] = 0
    #print 'amat',amat
    print "AMAT\n\n\nAMAT: \n", amat, "\nSMAT\n", smat, "\nAMAT * SMAT\n\n", amat * smat, "\nsx, sy, sz\n", (
        sx, sy, sz)
    return amat