def build_models(Mcore,
rho_core,
L_M_whittle,
L_M_start,
L_M_end,
NL,
Teq,
Xstart,
Xend,
Nenv,
planet_dir,
Xbondi,
istart=0,
jstart=1):
# this function builds many models with envolope mass fractions and luminosities
#create initial population
import os
import numpy as np
import math
import mesa as ms
import shutil
import planet_prop as pp
curr_dir = os.getcwd()
cs = (1.38e-16 * Teq / (2.35 * 1.67e-24))**0.5
if istart == 0 and jstart == 1:
build_starting_models(Mcore, rho_core, L_M_whittle, L_M_start, Teq,
Xstart, Xend, Nenv, planet_dir)
else:
print "Resuming from previous models..."
L_M_grid = np.logspace(math.log10(L_M_start), math.log10(L_M_end), NL)
for i in range(istart, Nenv):
if i == istart:
j0 = jstart
else:
j0 = 1
for j in range(j0, NL):
print "***123", i, j
#read in history file and check planet radius
his_file = "his_%d_L%d.data" % (i, j - 1)
shutil.copyfile("%s/%s" % (planet_dir, his_file), "history.data")
try:
his = ms.history_data('.', clean_starlog=True)
except: # avoid errors from bad files
break
rad = 10**(his.get('log_R')) * pp.rsun
mass = his.get('star_mass') * pp.msun
Rbondi = 6.67e-8 * mass[-1] / (2.0 * cs**2.0)
XB = rad[-1] / Rbondi
if XB > Xbondi:
break
# else heat-up to next value
L_M_curr = (np.float64(L_M_grid[j]).item())
heat_up_model(planet_dir, L_M_curr, Teq, i, j)
os.chdir(curr_dir)
def load(widget):
clear_output()
data = None
mass = float(frame.get_attribute("mass", "value"))
Z = float(frame.get_attribute("Z", "value"))
dir = frame.get_attribute("address_bar", "value")
if frame.get_attribute("model_select", "value") != "":
model = int(frame.get_attribute("model_select", "value"))
else:
model = 1
module = frame.get_attribute("select_module", "value")
if module == "H5 out":
if manual_data_select:
data = mp.se(dir)
else:
data = mp.se(mass=mass, Z=Z)
frame.set_state("nugrid_w_data")
properties = ["mass", "radius", "rho", "temperature"]
frame.set_attributes("xaxis",
options=properties + data.se.isotopes)
frame.set_attributes("yaxis",
options=properties + data.se.isotopes)
elif module == "History":
if manual_data_select:
data = ms.history_data(dir)
else:
data = ms.history_data(mass=mass, Z=Z)
frame.set_state("mesa_w_data")
frame.set_attributes("xaxis", options=sorted(data.cols.keys()))
frame.set_attributes("yaxis", options=sorted(data.cols.keys()))
elif module == "Profile":
if manual_data_select:
data = ms.mesa_profile(dir, num=model)
else:
data = ms.mesa_profile(mass=mass, Z=Z, num=model)
frame.set_state("mesa_w_data")
frame.set_attributes("xaxis", options=sorted(data.cols.keys()))
frame.set_attributes("yaxis", options=sorted(data.cols.keys()))
else:
nugrid_or_mesa = frame.get_attribute("select_nugrid_mesa", 'value')
if nugrid_or_mesa == "NuGrid":
frame.set_state("nugrid")
elif nugrid_or_mesa == "Mesa":
frame.set_state("mesa")
frame.set_state_data("class_instance", data)
frame.set_attributes("select_plot", selected_label="")
def load(widget):
clear_output()
data = None
mass = float(frame.get_attribute("mass", "value"))
Z = float(frame.get_attribute("Z", "value"))
dir = frame.get_attribute("address_bar", "value")
if frame.get_attribute("model_select", "value") != "":
model = int(frame.get_attribute("model_select", "value"))
else:
model = 1
module = frame.get_attribute("select_module", "value")
if module == "H5 out":
if manual_data_select:
data = mp.se(dir)
else:
data = mp.se(mass=mass, Z=Z)
frame.set_state("nugrid_w_data")
properties = ["mass", "radius", "rho", "temperature"]
frame.set_attributes("xaxis", options=properties+data.se.isotopes)
frame.set_attributes("yaxis", options=properties+data.se.isotopes)
elif module == "History":
if manual_data_select:
data = ms.history_data(dir)
else:
data = ms.history_data(mass=mass, Z=Z)
frame.set_state("mesa_w_data")
frame.set_attributes("xaxis", options=sorted(data.cols.keys()))
frame.set_attributes("yaxis", options=sorted(data.cols.keys()))
elif module == "Profile":
if manual_data_select:
data = ms.mesa_profile(dir, num=model)
else:
data = ms.mesa_profile(mass=mass, Z=Z, num=model)
frame.set_state("mesa_w_data")
frame.set_attributes("xaxis", options=sorted(data.cols.keys()))
frame.set_attributes("yaxis", options=sorted(data.cols.keys()))
else:
nugrid_or_mesa = frame.get_attribute("select_nugrid_mesa", 'value')
if nugrid_or_mesa == "NuGrid":
frame.set_state("nugrid")
elif nugrid_or_mesa == "Mesa":
frame.set_state("mesa")
frame.set_state_data("class_instance", data)
frame.set_attributes("select_plot", selected_label="")
def run_models(Teq, sep, NL, Nenv, planet_dir, min_mass, Xbondi, Tevolve,
Evolve_star):
import os
import numpy as np
import math
import mesa as ms
import shutil
import planet_prop as pp
import mesa_namelist as mn
curr_dir = os.getcwd()
file_in = "model_in.mod"
file_out = "model_out.mod"
run_dir = "make_planets"
sb = 5.6704e-5
Flux = 4.0 * sb * Teq**4.0
Sigma = 250 # heating depth in F-Sigma routine
cs = (1.38e-16 * Teq / (2.35 * 1.67e-24))**0.5
for i in range(0, Nenv):
for j in range(0, NL):
print "***123", i, j
#read in history file and check planet radius
his_file = "his_%d_L%d.data" % (i, j)
shutil.copyfile("%s/%s" % (planet_dir, his_file), "history.data")
try:
his = ms.history_data('.', clean_starlog=True)
except ZeroDivisionError: # arises when trying to read in bad model
break
rad = 10**(his.get('log_R')) * pp.rsun
mass = his.get('star_mass') * pp.msun
Rbondi = 6.67e-8 * mass[-1] / (2.0 * cs**2.0)
XB = rad[-1] / Rbondi
if XB > Xbondi:
break
# can run model
os.chdir(run_dir)
mod_file = "model_%d_L%d.mod" % (i, j)
shutil.copyfile("%s/%s" % (planet_dir, mod_file), file_in)
nml = mn.build_namelist_ev_Fsigma_we(Tevolve, Flux, Sigma, Teq,
sep, min_mass, Evolve_star)
nml.write('inlist', force=True)
os.system("./create_planet")
his_out = "e_his_%d_L%d.data" % (i, j)
shutil.copyfile("LOGS/history.data",
"%s/%s" % (planet_dir, his_out))
os.chdir(curr_dir)
dir1 = []
dir2 = []
m1 = []
m2 = []
for j in range(len(direct)):
dir1.append(j)
dir2.append(j)
dir1[j] = direct[j] + '/LOGS1'
dir2[j] = direct[j] + '/LOGS2'
m1.append(j)
m2.append(j)
for path, dirs, files in os.walk(
dir1[j]): #os.walk avoids [Errno21] Is a directory
m1[j] = ms.history_data(dir1[j], clean_starlog=False)
for path, dirs, files in os.walk(dir2[j]):
m2[j] = ms.history_data(dir2[j], clean_starlog=False)
log_center_Rho_1.append(j)
log_center_T_1.append(j)
log_center_P_1.append(j)
star_age_1.append(j)
star_mass_1.append(j)
model_number_1.append(j)
#log_L_1.append(j)
#log_R_1.append(j)
#log_Teff_1.append(j)
#log_g_1.append(j)
#center_h1_1.append(j)
#center_he4_1.append(j)
"/Users/tassos/Dropbox/Projects/CE/SINGLEgrid/4.0/LOGS/",
"/Users/tassos/Dropbox/Projects/CE/SINGLEgrid/5.0/LOGS/",
"/Users/tassos/Dropbox/Projects/CE/SINGLEgrid/7.0/LOGS/",]
profileN = [100, 1000, 1500, 2000, 2500]
fig = plt.figure(figsize=(8.267, 11.692))
# gridspec inside gridspec
gs = gridspec.GridSpec(5, 4, wspace=0.1, hspace=0.1)
for i in range(4):
h=ms.history_data(model_paths[i])
for j in range(5):
ax = plt.subplot(gs[j,i])
print i,j
p=ms.mesa_profile(model_paths[i],profileN[j],num_type='nearest_model')
mass = p.get('mass') * u.Msun # solar mass
dm = copy.deepcopy(mass)
dm[:-1] = mass[:-1]-mass[1:]
r = p.get('radius') * u.Rsun# solar radius
dr = copy.deepcopy(r)
dr[:-1] = r[:-1]-r[1:]
csound = p.get('csound') * u.cm/u.s #cm/s
t_sc = dr/(csound)
mdot_sc = dm/t_sc
t_ff = math.pi/2. * r**(3./2.) / np.sqrt(2.*const.G*(mass))
# Get the final masses from the folders
#masses = []
for file in os.listdir(i):
# Check if it's a directory, if it's a file, we'll ignore it
if os.path.isdir(i+'/'+file) == True:
if os.path.isdir(i+'/'+file) == i+'/data':
print(file+' is the data folder, ignoring...')
else:
os.chdir(i+'/'+file)
currd = os.getcwd()
print('Now in directory... '+os.getcwd())
os.system('rm ./LOGS/history.datasa')
s = ms.history_data()
lum = s.get('log_L')
mass = s.get('star_mass')
fl = lum[ len(lum)-1 ]
fm = mass[ len(mass)-1 ]
rv = ReadInls('inlist_1.0','Reimers_scaling')
bv = ReadInls('inlist_1.0','Blocker_scaling')
if fl < 0. :
masses.append(fm)
reims.append(rv)
block.append(bv)
print('Final mass is: '+str(fm))
print('Reimers: '+str(rv))
inl = open(inlist, 'r')
for line in inl:
if str(value) in line:
a = line
val = float(a.split()[-1])
return val
# We compute the c_k values using the results of the MESA run,
# and the results of the midpoints of the intervals, ytilde
# Meaning if our x_1 = [0.3,0.9] and x_2 = [0.01,0.1] then
# ytile = final mass from MESA run with x_1 = 0.6 and x_2 = 0.05
midrun = '/data/mhoffman/NUQ/new_midpoints/tile4' # This should be a path the the ytilde folder
os.chdir(midrun)
s = ms.history_data()
mass = s.get('star_mass')
ytilde = mass[(len(mass) - 1)] # obtain the last mass
# now read in all the star masses
# Name of top directory and current directory
#path = raw_input('Please provide path of top folder using: ')
#os.chdir(path)
paths = ['/data/mhoffman/NUQ/cdtiles/tile4']
kvals = []
masses = []
reims = []
block = []
# Creates a title which includes some parts of the current work directory. I am removing all the "/" and other characters
title = '_' #+os.path.dirname(path)[-22:-18]+'_'+os.path.dirname(path)[-12:-8]+'_'+os.path.dirname(path)[-7:]
# Start an instance of the history.data
dir1 = path + '/LOGS1'
dir2 = path + '/LOGS2'
#dir1='/../'
#dir2='/../'
#dir1 = raw_input ('Please, insert the name of the directory where the first history.data and profiles are:\n')
#dir2 = raw_input ('Please, insert the name of the directory where the second history.data and profiles are:\n')
for path, dirs, files in os.walk(
dir1): #os.walk avoids [Errno21] Is a directory
m1 = ms.history_data(dir1, clean_starlog=False)
for path, dirs, files in os.walk(dir2):
m2 = ms.history_data(dir2, clean_starlog=False)
log_center_Rho_1 = m1.get('log_center_Rho')
log_center_T_1 = m1.get('log_center_T')
log_center_P_1 = m1.get('log_center_P')
star_age_1 = m1.get('star_age')
star_mass_1 = m1.get('star_mass')
model_number_1 = m1.get('model_number')
#log_L_1=m1.get('log_L')
#log_R_1=m1.get('log_R')
#log_Teff_1=m1.get('log_Teff')
#log_g_1=m1.get('log_g')
#center_h1_1=m1.get('center_h1')
RED_PURPLE = (0.80,0.60,0.70)
#hexcols[0] dark bluish
#hexcols[1] light blue
#hexcols[2] greenish
#hexcols[3] dark green
#hexcols[4] brownish
#hexcols[5] light brown
#hexcols[6] pinkish
#hexcols[7] dark something redish
#hexcols[8] magentish
hexcols = ['#332288', '#88CCEE', '#44AA99', '#117733', '#999933', '#DDCC77',\
'#CC6677', '#882255', '#AA4499', '#661100', '#6699CC', '#AA4466','#4477AA']
hist1 = ms.history_data("double_bh_Z50/1.9_0.8_1.10/LOGS1", slname = "history.data")
hist2 = ms.history_data("double_bh_Z50/1.9_0.8_1.10/LOGS2", slname = "history.data")
plt.plot(hist1.get("log_Teff")[279:],hist1.get("log_L")[279:], '-', color = hexcols[0])
plt.plot(hist2.get("log_Teff")[279:],hist2.get("log_L")[279:], '-', color = hexcols[5], lw=1.5)
plt.gca().text(0.12, 0.9, "$M_1=79M_\odot,M_2=64M_\odot,\;P_\mathrm{i}=1.1\;\mathrm{d}$", fontsize = 13, transform=plt.gca().transAxes)
plt.legend(loc=2)
plt.xlim([5.25,4.68])
plt.ylim([5.65,6.55])
plt.xlabel("$\log\;T_{\mathrm{eff}}$")
plt.ylabel("$\log\;L/L_\odot$")
ax = plt.gca()
import mesa as ms
import os
# Start an instance of the history.data
#pathwork=os.getcwd() # Current work directory
#direc=pathwork+'/LOGS'
#direc='/../'
direc = raw_input(
'Please, insert the name of the directory where the history.data and profiles are:\n'
)
for path, dirs, files in os.walk(
direc): #os.walk avoids [Errno21] Is a directory
m1 = ms.history_data(direc, clean_starlog=False)
star_age = m1.get('star_age')
model_number = m1.get('model_number')
## Profiles
# Start from the first profile and find the corresponding model_number
prof_index = Table.read(direc + '/profiles.index', format='ascii.fixed_width')
idx = []
idxa = []
idxb = []
idxc = []
index = []
for i in range(len(prof_index)):
#Zmass = 0.007167
#Porb = 235.29852 # orbital period in days, needed for delta-ln-e
#t0 = 2e9 # age in years to begin integrating star (set near end of MS phase)
f = 1.0 # fudge factors are fun (read the paper, it's ~1), needed for delta-ln-e
idxstart = 10 # timestamp at which to begin plotting points (default = 20)
q = Mcomp/Mstar # mass ratio = M_comp/M
# ***** DEFINE AT MOST ONE OF THESE TWO THINGS ***** #
Rnow = Rstar # option to stop integration at some radius
#idxstop = 2890 # option to stop integration at some index
# ***** DEFINE AT MOST ONE OF THESE TWO THINGS ***** #
# Read in MESA stellar model data from a history file
# Save only values corresponding to age > t0 years
model = ms.history_data(modeldir)
times = model.get('star_age')
t0idx = np.argmax(times > t0)
times = times[t0idx:]
logTeffs = model.get('log_Teff')[t0idx:]
logRs = model.get('log_R')[t0idx:]
cz_masses = model.get('cz_xm')[t0idx:]
loggs = model.get('log_g')[t0idx:]
Teffs = np.power(10, logTeffs)
Rads = np.power(10, logRs)
#len1 = len(times) #original length of timestamps
#times = np.array([time for time in times if time >= 1e7])
#len2 = len(times) #truncated length of timestamps >= 1e7
