def read_rho_rh(modelpath):
mstar_conv = dyn.conv('mstar', modelpath + 'initial.conv.sh')
l_conv = dyn.conv('l', modelpath + 'initial.conv.sh')
#datarho = np.genfromtxt(modelpath+'initial.rho_lagrad.dat')
#rho_rh0 = datarho[:,20][0]*mstar_conv/l_conv**3
filerho = modelpath + 'initial.rho_lagrad.dat'
with open(filerho, 'r') as frho:
for i, line in enumerate(frho):
if i == 2: # 3th line
data = line.split()
rho_rh0 = float(data[20]) * mstar_conv / l_conv**3
break
return rho_rh0
def estimate_Nmsp_Lgamma_atpresent():
sample_init = np.genfromtxt(
'/projects/b1095/syr904/projects/GCE/catalog/cluster_sample_initial.dat',
dtype=str)
N_star = sample_init[:, 0]
rv = sample_init[:, 1]
rg = sample_init[:, 2]
z = sample_init[:, 3]
rg_init = sample_init[:, 5].astype(float)
num_msp = []
L_gamma = []
Mass = []
for ii in range(len(N_star)):
if rg_init[ii] <= 3.:
modelpath = '/projects/b1091/CMC_Grid_March2019/rundir/rv' + rv[
ii] + '/rg' + rg[ii] + '/z' + z[ii] + '/' + N_star[ii] + '/'
m_conv = dyn.conv('m', modelpath + 'initial.conv.sh')
nsfile = modelpath + 'initial.ns.dat'
with open(nsfile, 'r') as fns:
for line in fns:
pass
ns_last_line = line
datans = ns_last_line.split()
num_msp.append(int(datans[6]))
dynfile = modelpath + 'initial.dyn.dat'
with open(dynfile, 'r') as fdyn:
for line in fdyn:
pass
dyn_last_line = line
datadyn = dyn_last_line.split()
Mass.append(float(datadyn[4]) * m_conv)
lgammafile = '/projects/b1095/syr904/projects/GCE/catalog/Lgamma_alltime_maingrid.dat'
pathfile = '/projects/b1095/syr904/projects/GCE/catalog/path_allfinished_newruns_maingrid.dat'
datalg = np.genfromtxt(lgammafile)
modellg = datalg[:, 0]
tlg = datalg[:, 1]
lmsp = datalg[:, 2]
sourcedir = np.genfromtxt(pathfile, dtype=str)
paths = list(sourcedir[:, 0])
model_no = paths.index(modelpath)
print(model_no, modelpath)
lg_last = lmsp[modellg == model_no]
if not len(lg_last): continue
lg_last = lg_last[-1]
print(lg_last, model_no)
L_gamma.append(lg_last)
print(sum(num_msp), sum(L_gamma), sum(Mass))
def find_rh_density(modelpath, thesnap):
filestr = modelpath + 'initial'
snap = modelpath + thesnap
dynfile = np.genfromtxt(filestr + '.dyn.dat')
tdyn = dynfile[:, 0]
r_h = dynfile[:, 20]
m = []
radius = []
t_conv = dyn.conv('t', filestr + '.conv.sh')
l_conv = dyn.conv('l', filestr + '.conv.sh')
print(l_conv)
tsnap = dyn.get_time(snap)
for xx in range(len(tdyn)):
if round(tdyn[xx], 6) == tsnap:
rh_snap = r_h[xx]
print(rh_snap)
with gzip.open(snap, 'r') as fsnap:
next(fsnap)
next(fsnap)
for line in fsnap:
data = line.split()
m.append(float(data[1]))
radius.append(float(data[2]) * l_conv)
if float(data[2]) > rh_snap:
break
#vol = (2*twopi/3)*(rh_snap*l_conv)**3
vol = (2 * twopi / 3) * (radius[-1])**3
averho_rh = sum(m) / vol
return averho_rh, m, radius
modelfiles = np.genfromtxt(
'/projects/b1091/CMC_Grid_March2019/rundir/path.dat',
dtype=str,
delimiter='')
sourcedir = modelfiles[:, 0]
status = []
for i in range(len(sourcedir)):
filestr1 = sourcedir[i] + 'initial'
dynfile1 = filestr1 + '.dyn.dat'
filestr2 = sourcedir[i] + 'initial2'
dynfile2 = filestr2 + '.dyn.dat'
if os.path.isfile(dynfile2) and os.path.getsize(dynfile2) > 0:
t_conv = dyn.conv('t', filestr1 + '.conv.sh')
with open(dynfile2, 'r') as fdyn:
next(fdyn)
next(fdyn)
for line in fdyn:
datadyn = line.split()
totaln = float(datadyn[3])
break
with open(dynfile2, 'r') as fdyn:
for line in fdyn:
pass
lastdyn = line.split()
time = float(lastdyn[0]) * t_conv
def find_BH_XX_atsnap(filepath, lowlim, highlim, snapno, savename):
property_init, property_finl, property_des = ntc.find_tc_properties_final(
filepath)
ID0 = property_init['id0']
ID1 = property_init['id1']
T = property_init['time']
Types = property_init['type']
filestr = filepath + 'initial'
#snaps=dyn.get_snapshots(filestr)
#lastsnap=snaps[-1]
snap = filepath + 'initial.snap0' + str(snapno) + '.dat.gz'
t_conv = dyn.conv('t', filestr + '.conv.sh')
l_conv = dyn.conv('l', filestr + '.conv.sh')
time = dyn.get_time(snap) * t_conv
#os.system('rm '+savepath)
fmsb = open(filepath + savename + str(snapno) + '.dat', 'w+')
fmsb.write(
'#1.ID0 2.ID1 3.M0 4.M1 5.K0 6.K1 7.a(AU) 8.ecc 9.radrol0 10.radrol1 11.B(G) 12.P(sec) 13.tcflag 14.SN 15.TC_time(Myr) 16.r(pc)\n'
)
with gzip.open(snap, 'r') as flast:
next(flast)
next(flast)
for line in flast:
datalast = line.split()
if int(datalast[7]) == 1:
if int(datalast[17]) == 14 and lowlim <= int(
datalast[18]) <= highlim:
ID0ms = int(datalast[10])
ID1ms = int(datalast[11])
tcflag = 4
tctime = -100
for ii in range(len(ID0)):
if (ID0ms == ID0[ii] and ID1ms == ID1[ii]) or (
ID1ms == ID0[ii] and ID0ms == ID1[ii]):
if Types[ii] == 'SS_COLL_Giant':
tcflag = 81
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 91
tctime = T[ii] * t_conv
break
elif ID0ms == ID0[ii] or ID0ms == ID1[ii]:
if Types[ii] == 'SS_COLL_Giant':
tcflag = 82
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 92
tctime = T[ii] * t_conv
break
fmsb.write(
'%d %d %f %f %d %d %f %f %f %f %e %f %d %d %f %f\n' %
(int(datalast[10]), int(datalast[11]),
float(datalast[8]), float(
datalast[9]), int(datalast[17]), int(
datalast[18]), float(datalast[12]),
float(datalast[13]), float(datalast[43]),
float(datalast[44]), float(datalast[47]),
float(twopi * yearsc / float(datalast[45])), tcflag,
int(datalast[49]), tctime,
float(datalast[2]) * l_conv))
if lowlim <= int(datalast[17]) <= highlim and int(
datalast[18]) == 14:
ID0ms = int(datalast[11])
ID1ms = int(datalast[10])
tcflag = 4
tctime = -100
for ii in range(len(ID0)):
if (ID0ms == ID0[ii] and ID1ms == ID1[ii]) or (
ID1ms == ID0[ii] and ID0ms == ID1[ii]):
if Types[ii] == 'SS_COLL_Giant':
tcflag = 81
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 91
tctime = T[ii] * t_conv
break
elif ID0ms == ID0[ii] or ID0ms == ID1[ii]:
if Types[ii] == 'SS_COLL_Giant':
tcflag = 82
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 92
tctime = T[ii] * t_conv
break
fmsb.write(
'%d %d %f %f %d %d %f %f %f %f %e %f %d %d %f %f\n' %
(int(datalast[11]), int(datalast[10]),
float(datalast[9]), float(
datalast[8]), int(datalast[18]), int(
datalast[17]), float(datalast[12]),
float(datalast[13]), float(datalast[44]),
float(datalast[43]), float(datalast[48]),
float(twopi * yearsc / float(datalast[46])), tcflag,
int(datalast[50]), tctime,
float(datalast[2]) * l_conv))
fmsb.close()
def find_WD_XX_atsnap_hdf5(filepath, lowlim, highlim, snapno, savename):
property_init, property_finl, property_des = nhf.find_tc_properties(
filepath)
ID0 = property_init['id0']
ID1 = property_init['id1']
T = property_init['time']
Types = property_init['type']
all_keys = np.genfromtxt(filepath + 'snap_keys.txt', dtype='str')
all_snapno = all_keys[:, 0]
all_snaptime = all_keys[:, 1]
thekey = '/' + str(snapno) + '(t=' + all_snaptime[snapno] + ')'
filestr = filepath + 'initial'
snap = cmct.Snapshot(
fname=filepath + 'initial.snapshots.h5',
snapshot_name=thekey,
conv=filepath + 'initial.conv.sh',
dist=4.52, # distance to cluster in kpc
z=0.0038)
t_conv = dyn.conv('t', filestr + '.conv.sh')
l_conv = dyn.conv('l', filestr + '.conv.sh')
#os.system('rm '+savepath)
fmsb = open(filepath + savename + str(snapno) + '.dat', 'w+')
fmsb.write(
'#1.ID0 2.ID1 3.M0 4.M1 5.K0 6.K1 7.a(AU) 8.ecc 9.radrol0 10.radrol1 11.B(G) 12.P(sec) 13.tcflag 14.SN 15.TC_time(Myr) 16.R(pc)\n'
)
binflag = snap.data['binflag']
k0 = snap.data['bin_startype0']
k1 = snap.data['bin_startype1']
id0 = snap.data['id0']
id1 = snap.data['id1']
m0 = snap.data['m0_MSUN']
m1 = snap.data['m1_MSUN']
sma = snap.data['a_AU']
ecc = snap.data['e']
rad0 = snap.data['radrol0']
rad1 = snap.data['radrol1']
B0 = snap.data['B0']
B1 = snap.data['B1']
ospin0 = snap.data['ospin0']
ospin1 = snap.data['ospin1']
SN0 = snap.data['formation0']
SN1 = snap.data['formation1']
Rpc = snap.data['r'] * l_conv
for xx in range(len(binflag)):
if binflag[xx] == 1:
if 10 <= k0[xx] <= 12 and lowlim <= k1[xx] <= highlim:
ID0ms = id0[xx]
ID1ms = id1[xx]
tcflag = 4
tctime = -100
for ii in range(len(ID0)):
if (ID0ms == ID0[ii]
and ID1ms == ID1[ii]) or (ID1ms == ID0[ii]
and ID0ms == ID1[ii]):
if Types[ii] == 'SS_COLL_Giant':
tcflag = 81
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 91
tctime = T[ii] * t_conv
break
elif ID0ms == ID0[ii] or ID0ms == ID1[ii]:
if Types[ii] == 'SS_COLL_Giant':
tcflag = 82
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 92
tctime = T[ii] * t_conv
break
fmsb.write(
'%d %d %f %f %d %d %f %f %f %f %e %f %d %d %f %f\n' %
(id0[xx], id1[xx], m0[xx], m1[xx], k0[xx], k1[xx], sma[xx],
ecc[xx], rad0[xx], rad1[xx], B0[xx], twopi * yearsc /
ospin0[xx], tcflag, SN0[xx], tctime, Rpc[xx]))
if lowlim <= k0[xx] <= highlim and 10 <= k1[xx] <= 12:
ID0ms = id1[xx]
ID1ms = id0[xx]
tcflag = 4
tctime = -100
for ii in range(len(ID0)):
if (ID0ms == ID0[ii]
and ID1ms == ID1[ii]) or (ID1ms == ID0[ii]
and ID0ms == ID1[ii]):
if Types[ii] == 'SS_COLL_Giant':
tcflag = 81
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 91
tctime = T[ii] * t_conv
break
elif ID0ms == ID0[ii] or ID0ms == ID1[ii]:
if Types[ii] == 'SS_COLL_Giant':
tcflag = 82
tctime = T[ii] * t_conv
break
if Types[ii] == 'SS_COLL_TC_P':
tcflag = 92
tctime = T[ii] * t_conv
break
fmsb.write(
'%d %d %f %f %d %d %f %f %f %f %e %f %d %d %f %f\n' %
(id1[xx], id0[xx], m1[xx], m0[xx], k1[xx], k0[xx], sma[xx],
ecc[xx], rad1[xx], rad0[xx], B1[xx], twopi * yearsc /
ospin1[xx], tcflag, SN1[xx], tctime, Rpc[xx]))
fmsb.close()
def cluster_inspiral(r_initial, cluster_path, rho_initial, cluster_status):
#datadyn = np.genfromtxt(cluster_path+'initial.dyn.dat')
#datarho = np.genfromtxt(cluster_path+'initial.rho_lagrad.dat')
#m_gc = np.array(datadyn[:,4])*m_conv
#rho_halfm = np.array(datarho[:,20])*(mstar_conv/l_conv**3)
#t_rho = np.array(datarho[:,0])*t_conv
#for kk in range(len(t_rho)-1):
# delta_t = (t_rho[kk+1]-t_rho[kk])/1000.
# rg_new = df(delta_t, rg_old, m_gc[kk])
# rho_ga_new = galaxy_rho_r(rg_new, circ_vel)
# if rho_halfm[kk+1] <= rho_ga_new:
# print('cluster disrupted', t_rho[kk+1], rg_new, rho_halfm[kk+1])
# rg_disrupt = rg_new; t_disrupt = t_rho[kk+1]; rho_disrupt = rho_halfm[kk+1]
# break
# rg_old = rg_new
t_conv = dyn.conv('t', cluster_path + 'initial.conv.sh')
l_conv = dyn.conv('l', cluster_path + 'initial.conv.sh')
m_conv = dyn.conv('m', cluster_path + 'initial.conv.sh')
mstar_conv = dyn.conv('mstar', cluster_path + 'initial.conv.sh')
rg_disrupt = -100
t_disrupt = -100
rho_disrupt = -100
filerho = cluster_path + 'initial.rho_lagrad.dat'
filedyn = cluster_path + 'initial.dyn.dat'
with open(filerho, 'r') as fr:
next(fr)
next(fr)
for i_rho, l_rho in enumerate(fr):
pass
nline_rho = i_rho + 1
#print(nline_rho)
line_cut = int(0.7 * nline_rho)
with open(filedyn, 'r') as fd:
next(fd)
next(fd)
for l_dyn in fd:
data = l_dyn.split()
m_old = float(data[4])
break
print(m_old)
##Initialize the spiral in
rg_old = r_initial
t_old = 0.
m_old = m_old * m_conv
rho_halfm_old = rho_initial
##Starting spiral in
check = 0
with open(filerho, 'r') as frho, open(filedyn, 'r') as fdyn:
next(frho)
next(frho)
next(fdyn)
next(fdyn)
for i, lines in enumerate(zip(frho, fdyn)):
if i == 0: continue
if i <= line_cut and i % 10 != 0:
continue
datarho = lines[0].split()
datadyn = lines[1].split()
t_curr = float(datarho[0])
rho_halfm_curr = float(datarho[20]) * (mstar_conv / l_conv**3)
m_curr = float(datadyn[4]) * m_conv
delta_t = (t_curr - t_old) * t_conv / 1000.
rg_new = df(delta_t, rg_old, m_old)
if rg_new <= 0:
check = 1
print('cluster reached center', t_curr * t_conv, rg_new,
rho_halfm_curr)
rg_disrupt = rg_old
t_disrupt = t_old * t_conv
rho_disrupt = rho_halfm_old
type_disrupt = 1
break
rho_ga_new = galaxy_rho_r(rg_new, circ_vel)
if (rho_halfm_curr <= rho_ga_new):
check = 1
print('cluster disrupted', t_curr * t_conv, rg_new,
rho_halfm_curr)
rg_disrupt = rg_new
t_disrupt = t_curr * t_conv
rho_disrupt = rho_halfm_curr
type_disrupt = 2
break
t_old = t_curr
m_old = m_curr
rg_old = rg_new
rho_halfm_old = rho_halfm_curr
#print(i)
#print(rho_halfm_curr, rho_ga_new, m_curr, rg_new)
if check == 0:
rg_disrupt = rg_new
t_disrupt = t_curr * t_conv
rho_disrupt = rho_halfm_curr
type_disrupt = 3
print(rg_disrupt, t_disrupt, rho_disrupt)
return rg_disrupt, t_disrupt, rho_disrupt, type_disrupt
def read_property_attime(modelpath, time): ##time in Myr
Num_msp = -100
Mass = -100
Lum_gamma = -100
Num_msp_old = -100
Mass_old = -100
Lum_gamma_old = -100
t_conv = dyn.conv('t', modelpath + 'initial.conv.sh')
m_conv = dyn.conv('m', modelpath + 'initial.conv.sh')
##Extract number of MSP
with open(modelpath + 'initial.ns.dat', 'r') as fns:
next(fns)
for i, line in enumerate(fns):
datans = line.split()
t_ns = float(datans[0]) * t_conv
if i == 0: n_msp_old = int(datans[6])
if round(t_ns, 6) >= round(time, 6):
print(t_ns, time)
Num_msp = int(datans[6])
Num_msp_old = n_msp_old
break
n_msp_old = int(datans[6])
if Num_msp == -100:
Num_msp = int(datans[6])
Num_msp_old = int(datans[6])
##Extract mass of cluster
datadyn = np.genfromtxt(modelpath + 'initial.dyn.dat')
with open(modelpath + 'initial.dyn.dat', 'r') as fdyn:
next(fdyn)
next(fdyn)
for i, line in enumerate(fdyn):
datadyn = line.split()
t_dyn = float(datadyn[0]) * t_conv
if i == 0: m_dyn_old = float(datadyn[4]) * m_conv
if round(t_dyn, 6) >= round(time, 6):
print(t_dyn, time)
Mass = float(datadyn[4]) * m_conv
Mass_old = m_dyn_old
break
m_dyn_old = float(datadyn[4]) * m_conv
if Mass == -100:
Mass = float(datadyn[4]) * m_conv
Mass_old = float(datadyn[4]) * m_conv
##Extract Lgamma
if Num_msp != 0 or Num_msp_old != 0:
sourcedir = np.genfromtxt(
'/projects/b1095/syr904/projects/GCE/catalog/path_allfinished_newruns_maingrid.dat',
dtype=str)
paths = sourcedir[:, 0]
model_no = list(paths).index(modelpath)
datagama = np.genfromtxt(
'/projects/b1095/syr904/projects/GCE/catalog/Lgamma_alltime_maingrid.dat'
)
model_gama = datagama[:, 0]
t_gama = datagama[:, 1]
lgama = datagama[:, 2]
t_model = t_gama[model_gama == model_no]
lum_model = lgama[model_gama == model_no]
for xx in range(len(t_model)):
if round(t_model[xx], 6) >= round(time, 6):
Lum_gamma = lum_model[xx]
Lum_gamma_old = lum_model[xx - 1]
#print(Num_msp, Mass, Lum_gamma, Num_msp_old, Mass_old, Lum_gamma_old)
return Num_msp, Mass, Lum_gamma, Num_msp_old, Mass_old, Lum_gamma_old
def find_Lgammaray_alltime(pathlist, start, end, eta_gamma=0.1):
Cscale = 9.6 * 10**33 ##in erg/s
sourcedir = np.genfromtxt(pathlist, dtype=str)
paths = sourcedir[:, 0]
status = sourcedir[:, 1]
#fgamma=open('/projects/b1095/syr904/N1e7_rg8_f5_z0.002/Lgamma_alltime_N1e7.dat', 'a+')
#fgamma.write('#1.Model 2.T(Myr) 3.Lmsp\n')
for ii in range(start, end):
print(paths[ii])
filestr = paths[ii] + 'initial'
t_conv = dyn.conv('t', filestr + '.conv.sh')
s = paths[ii].split('/')
n_star = s[-2]
z = s[-3][1:]
rg = s[-4][2:]
rv = s[-5][2:]
Lmsp = []
time = []
with open(filestr + '.morepulsars.dat', 'r') as fpsr:
next(fpsr)
for line in fpsr:
data = line.split()
if int(data[2]) != 1:
Pspin = float(data[9]) ##in sec
B = float(data[7])
if Pspin <= 0.03:
Lmsp.append(Cscale * (eta_gamma / 0.2) *
(B / 10**8.5)**2 * (3. /
(Pspin * 1000.))**4)
time.append(float(data[1]) * t_conv)
else:
if int(data[11]) == 13:
Pspin = float(data[9]) ##in sec
B = float(data[7])
if Pspin <= 0.03:
Lmsp.append(Cscale * (eta_gamma / 0.2) *
(B / 10**8.5)**2 *
(3. / (Pspin * 1000.))**4)
time.append(float(data[1]) * t_conv)
if int(data[12]) == 13:
Pspin = float(data[10]) ##in sec
B = float(data[8])
if Pspin <= 0.03:
Lmsp.append(Cscale * (eta_gamma / 0.2) *
(B / 10**8.5)**2 *
(3. / (Pspin * 1000.))**4)
time.append(float(data[1]) * t_conv)
#print(time)
#sums = {}
#for key, value in zip(time,Lmsp):
# try:
# sums[key] += value
# except KeyError:
# sums[key] = value
#print(sums, sums.keys())
#allkey = sums.keys()
#for key in sums:
# thetime = float(key)
# #print(thetime)
# theL = sums[key]
# fgamma.write('%d %f %e\n'%(ii, thetime, theL))
fgamma = open(
'/projects/b1095/syr904/projects/GCE/catalog/data_lgamma/model_rv'
+ rv + '_rg' + rg + '_z' + z + '_' + n_star + '.txt', 'a+')
fgamma.write('#1.Model 2.T(Myr) 3.Lmsp\n')
allkey = list(Counter(time).keys())
#print(allkey)
for x in range(len(allkey)):
theL = 0
for y in range(len(time)):
if time[y] == allkey[x]:
theL += Lmsp[y]
fgamma.write('%d %f %e\n' % (ii, allkey[x], theL))
print(ii)
fgamma.close()