def musearch(newmdot, newps):
tstart = time.time()
d.XQset(1.0, 0.99)
f = open('musearch.txt', 'w')
newmu1 = 1.
newmu2 = 100.
# right boundary, probably no solution here
# b.parset(newmu=newmu2, newmdot=newmdot,newps=newps,neweta=0.,newalpha=0.1)
# print "after bparset mu="+str(mu)
# d.parset(newmu=newmu2, newmdot=newmdot,newps=newps,neweta=0.,newalpha=0.1)
# print "after parset mu="+str(mu)
x0, x1, converged = d.ordiv_smart(newmu2, newmdot, newps)
if (converged):
print "musearch converged, unexpectedly; increase your magnetic field"
print "mu = " + str(newmu2)
print "xi = " + str(x0) + ", qeq = " + str(x1)
ii = raw_input("?")
xi = []
muu = []
while ((newmu2 / newmu1 - 1.) > 0.1):
newmu = sqrt(newmu1 * newmu2)
b.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
d.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
x0, x1, converged = d.ordiv_smart(newmu, newmdot, newps)
if (converged):
d.XQset(x0, x1)
xiest = d.xiest
qeqest = d.qeqest
newmu1 = newmu
f.write(str(newmu) + ' ' + str(xiest) + ' ' + str(qeqest) + '\n')
print str(newmu) + ' ' + str(xiest) + ' ' + str(qeqest) + '\n'
xi.append(xiest)
muu.append(newmu)
else:
newmu2 = newmu
print str(newmu) + ' ' + " not converged"
f.close()
tend = time.time()
clf()
plot(muu, xi, '.k')
xlabel(r'$\mu$, $10^{30}$G')
ylabel(r'$\xi$')
savefig('musearch.eps')
print "musearch took " + str(tend - tstart)
return muu[-1]
def rmmclone(inspirefile, newps, neweta):
tstart = time.time()
# muar=[] ; mdar=[] ; xi0ar=[] ; qeq0ar=[]; xiar=[] ; qeqar=[]
muar, mdar, xi0ar, qeq0ar = rk.rmmread(inspirefile)
nn = np.size(muar)
# xiar=np.zeros(nn, dtype=double) ; qeqar=np.zeros(nn, dtype=double)
fout = open(
inspirefile + '_ps' + str(newps) + '_eta' + str(neweta) + '.txt', 'w')
for kk in np.arange(nn):
d.XQset(xi0ar[kk], qeq0ar[kk])
print "xi estimate = " + str(xi0ar[kk])
rscale = mdar[kk] # outer radius is the maximum of mdot and 100
if (rscale < 100.):
rscale = 100.
xiar, qeqar, conv = d.ordiv_smart(muar[kk],
mdar[kk],
-newps,
neweta=neweta,
routscale=rscale)
fout.write(
str(muar[kk]) + ' ' + str(mdar[kk]) + ' ' + str(xiar) + ' ' +
str(qeqar) + '\n ')
print str(muar[kk]) + ' ' + str(
mdar[kk]) + ' ' + str(xiar) + ' ' + str(qeqar) + '\n '
print "Delta xi = " + str(xiar - xi0ar[kk])
fout.flush()
fout.close()
tend = time.time()
print "RMMclone: the grid took " + str(tend - tstart) + "s = " + str(
(tend - tstart) / 3600.) + "h"
def varpsi():
newmu = 1.
newmdot = 10.
newps = -10.
b.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.0,
newalpha=0.1)
d.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.0,
newalpha=0.1)
d.XQset(0.55, 5.)
psi1 = 1.45
psidiff = 0.04
psi2 = 50.
d.psiset(psi1)
fout = open('psivar.dat', 'w+')
xiar = []
psiar = []
qeqar = []
converged = True
while (converged & (psi1 < psi2)):
thp = d.ordiv_smart(newmu, newmdot, newps)
xi = thp[0]
qeq = thp[1]
converged = thp[2]
if (converged):
d.XQset(xi, qeq)
xiar.append(xi)
psiar.append(psi1)
qeqar.append(qeq)
print "xi = " + str(xi)
fout.write(str(psi1) + ' ' + str(xi) + ' ' + str(qeq) + '\n')
fout.flush()
psi1 += psidiff
d.psiset(psi1)
fout.close()
xiar = asarray(xiar, dtype=double)
qeqar = asarray(qeqar, dtype=double)
psiar = asarray(psiar, dtype=double)
clf()
subplot(2, 1, 1)
plot(psiar, xiar, '.k')
xscale('log')
# xlabel(r'$\psi$')
ylabel(r'$\xi$')
subplot(2, 1, 2)
plot(psiar, qeqar, '.k')
xscale('log')
xlabel(r'$\psi$')
ylabel(r'$q$')
savefig('psivar.eps')
def xiqeqplane():
newmu = 1.
newmdot = 10.
newps = -10.
b.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.0,
newalpha=0.1)
d.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.0,
newalpha=0.1)
xi1 = 0.2
xi2 = 1.2
nxi = 11
xi = (xi2 - xi1) * np.arange(nxi) / double(nxi - 1) + xi1
qeq1 = 0.2
qeq2 = 1.2
nq = 10
qeq = (qeq2 - qeq1) * np.arange(nq) / double(nq - 1) + qeq1
aar = np.zeros([nxi, nq], dtype=double)
bar = np.zeros([nxi, nq], dtype=double)
x2 = np.zeros([nxi, nq], dtype=double)
q2 = np.zeros([nxi, nq], dtype=double)
fout = open('xqout.txt', 'w')
for kx in np.arange(nxi):
for kq in np.arange(nq):
at, bt = d.vrapper([xi[kx], qeq[kq]])
aar[kx, kq] = at
bar[kx, kq] = bt
x2[kx, kq] = xi[kx]
q2[kx, kq] = qeq[kq]
fout.write(
str(xi[kx]) + ' ' + str(qeq[kq]) + ' ' + str(at) + ' ' +
str(bt) + '\n')
fout.flush()
fout.close()
xi0, qeq0, conv = d.ordiv_smart(newmu, newmdot, newps)
clf()
contourf(x2, q2, np.log(aar**2 + bar**2), nlevels=20)
colorbar()
contour(x2, q2, aar, levels=[0.], colors='w')
contour(x2, q2, bar, levels=[0.], colors='k')
if (conv):
plot(xi0, qeq0, 'or')
savefig('xiqeqmap.eps')
def varps(newmu, newmdot):
tstart = time.time()
d.XQset(1.0, 0.9)
ps1 = b.peq() * 10.
psfac = 0.95
newps = ps1
converged = True
psar = []
xar = []
qeqar = []
f = open('varps.txt', 'w')
while (converged):
rscale = newmdot
if (newmdot < 100.):
rscale = 100.
b.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
d.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
x0, x1, converged = d.ordiv_smart(newmu,
newmdot,
newps,
routscale=rscale)
d.XQset(x0, x1)
print "varps: P = " + str(newps) + ": " + str(x0) + ", " + str(x1)
print "(Peq = " + str(b.peq()) + ")"
# print str(xiest)+", "+str(qeqest)
if (converged):
psar.append(newps)
xar.append(x0)
qeqar.append(x1)
f.write(str(newps) + ' ' + str(x0) + ' ' + str(x1) + '\n')
f.flush()
newps *= psfac
f.close()
tend = time.time()
def varrout():
newmu = 1.
newmdot = 1e5
d.XQset(1.34, 2.69)
xi0 = 1.34
qeq0 = 2.69
rmin = 1e3
rmax = 1.e4
nrads = 10
rr = (rmax / rmin)**(np.arange(nrads) / double(nrads - 1)) * rmin
xiar = np.zeros(nrads, dtype=double)
qeqar = np.zeros(nrads, dtype=double)
qeqarest = (sqrt(rr) - sqrt(rr[0])) / 2. + qeq0
print qeqarest
r = raw_input("ew")
fout = open('varrout.txt', 'w')
for k in np.arange(nrads):
d.XQset(xi0, qeqarest[k])
thp = d.ordiv_smart(newmu, newmdot, -10., routscale=rr[k])
xiar[k] = thp[0]
qeqar[k] = thp[1]
if (thp[2]):
# d.XQset(xiar[k], qeqar[k])
print "xi = " + str(xiar[k])
fout.write(
str(rr[k]) + ' ' + str(xiar[k]) + ' ' + str(qeqar[k]) + '\n')
fout.flush()
fout.close()
clf()
subplot(121)
plot(rr, xiar, '.k')
xscale('log')
# xlabel(r'$R_{\rm in}/R_{\rm out}$')
ylabel(r'$\xi$')
subplot(121)
plot(rr, qeqar, '.k')
xscale('log')
xlabel(r'$R_{\rm in}/R_{\rm out}$')
ylabel(r'$qeq$')
savefig('xrouttest.eps')
def varmdot(newmu, newps):
tstart = time.time()
d.XQset(1.05, 0.965)
newmdot1 = 1000.
newmdot2 = 10000.
nmdot = 25
mdar = (newmdot2 / newmdot1)**(arange(nmdot) /
double(nmdot - 1)) * newmdot1
xx = xiest
qq = qeqest
f = open('varmdot.txt', 'w')
for i in arange(nmdot):
newmdot = mdar[i]
b.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
d.parset(newmu=newmu,
newmdot=newmdot,
newps=newps,
neweta=0.,
newalpha=0.1)
x0, x1, converged = d.ordiv_smart(newmu, newmdot, newps)
d.XQset(x0, x1)
f.write(
str(newmu) + ' ' + str(newmdot) + ' ' + str(x0) + ' ' + str(x1) +
'\n')
print str(newmu) + ' ' + str(newmdot) + ' ' + str(x0) + ' ' + str(
x1) + '\n'
f.flush()
f.close()
tend = time.time()
def rmm(newps, neweta):
d.XQset(1., 1.1)
tstart = time.time()
mumin = 1.
mumax = 100.
mdmin = 1.e4
mdmax = 1.e5
nmu = 17
nd = 5
muar = (mumax / mumin)**(arange(nmu) / double(nmu - 1)) * mumin
mdar = (mdmax / mdmin)**(arange(nd) / double(nd - 1)) * mdmin
mu2 = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
md2 = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
xi = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
qeq = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
har = np.zeros([nmu, nd], dtype=double) + sqrt(
-1.) # inner disc thickness (absolute)
betar = np.zeros([nmu, nd], dtype=double) + sqrt(
-1.) # maximal relative thickness
oar = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
tauar = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
raam = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
mddotint = np.zeros([nmu, nd], dtype=double) + sqrt(-1.)
conv = np.zeros([nmu, nd], dtype=bool)
fname = 'rmm_op' + str(newps) + '_eta' + str(neweta)
fout = open(fname + '.dat', 'w')
for ku in arange(nmu):
if (ku > 0):
d.XQset(
xi[ku - 1, 0], qeq[ku - 1, 0]
) # the closest value, calculated for the previous row, same column
for kd in arange(nd):
mu2[ku, kd] = muar[ku]
md2[ku, kd] = mdar[kd]
rscale = mdar[kd] # outer radius is the maximum of mdot and 100
if (rscale < 100.):
rscale = 100.
xi[ku, kd], qeq[ku, kd], conv[ku,
kd] = d.ordiv_smart(muar[ku],
mdar[kd],
-newps,
neweta=neweta,
routscale=rscale)
if (conv[ku, kd]):
d.XQset(xi[ku, kd], qeq[ku, kd]) #
if (not (conv[ku, kd])):
xi[ku, kd] = sqrt(-1)
qeq[ku, kd] = sqrt(-1)
print "xi (mu=" + str(muar[ku]) + ", mdot=" + str(
mdar[kd]) + ") = " + str(xi[ku, kd])
# oin,hin,tin,bmax,mdotint,ll=d.rastr(xi[ku,kd], qeq[ku,kd])
# oar[ku,kd]=oin
# har[ku,kd]=hin
# tauar[ku,kd]=tin
# betar[ku,kd]=bmax
# mddotint[ku,kd]=mdotint
# raam[ku,kd]=raffugen(muar[ku], mdar[kd])
fout.write(
str(muar[ku]) + ' ' + str(mdar[kd]) + ' ' + str(xi[ku, kd]) +
' ' + str(qeq[ku, kd]) + '\n ')
#str(oin)+' '+str(hin/raam[ku,kd]/xi[ku,kd])+' '+str(tin)+' '+str(bmax)+' '+str(mddotint[ku,kd])+'\n')
print str(muar[ku]) + ' ' + str(mdar[kd]) + ' ' + str(
xi[ku, kd]) + ' ' + str(qeq[ku, kd]) + '\n '
fout.flush()
fout.close()
tend = time.time()
print "RMM: the grid took " + str(tend - tstart) + "s = " + str(
(tend - tstart) / 3600.) + "h"