teste modificando o parâmetro de camadas:
mesh_delta_coeff = 1.0d0 (padrão do teste = 1.5d0)
e adicionando os parâmetros:
mesh_delta_coeff_for_highT = 0.33d0
logT_max_for_standard_mesh_delta_coeff = 8.0d0
logT_min_for_highT_mesh_delta_coeff = 8.6d0
pretendo ~triplicar a quantidade de camadas na faixa de temperatura entre 8 e 8.6 logTc (Tc= temperatura central)
In [1]:
import mesa as ms
folder = '/media/glauffer/Data/mesa/alpha2_3x1_camadas/LOGS'
s = ms.history_data(folder)
# extraindo os modelos, temperatura central e quantidade de zonas
model = s.get('model_number')
zones = s.get('num_zones')
ct = s.get('log_center_T')
In [18]:
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams["figure.figsize"] = (15., 10.)
# plot do HRD
t = s.get('log_Teff')
L = s.get('log_L')
plt.plot(t, L)
plt.plot(t[154], L[154], 'ro')
plt.plot(t[2149], L[2149], 'go')
plt.gca().invert_xaxis()
plt.title(r'HRD $\alpha_{MLT}=2$', fontsize=18)
plt.xlabel(r'$\log T_{Eff}$', fontsize=16)
plt.ylabel(r'$\log L$', fontsize=16)
plt.savefig('alpha2_hrd_3x1.png')
In [3]:
# zoom do HRD
plt.plot(t, L)
plt.plot(t[154], L[154], 'r.')
plt.plot(t[2149], L[2149], 'go')
plt.gca().invert_xaxis()
plt.title(r'HRD $\alpha_{MLT}=2$', fontsize=18)
plt.xlabel(r'$\log T_{Eff}$', fontsize=16)
plt.ylabel(r'$\log L$', fontsize=16)
plt.xlim(4, 3.5)
#plt.ylim(3.5,4.5)
plt.ylim(4,4.4)
Out[3]:
In [10]:
# grafico de zonas vs model
plt.plot(model, zones, 'b-')
plt.plot(model[154], zones[154], 'ro')
plt.plot(model[2149], zones[2149], 'ro')
plt.savefig('alpha2_3x_camadas.png')
In [16]:
# Luminosidade He vs Model
he = s.get('log_LHe')
plt.plot(model, he)
plt.plot(model[154], he[154], 'ko')
plt.plot(model[439], he[439], 'k.')
plt.plot(model[2149], he[2149], 'ko')
plt.title(r'$\log L_{He}$ vs model $n$', fontsize=18)
plt.xlabel('model', fontsize=16)
plt.ylabel(r'$\log L_{He}$', fontsize=16)
#plt.savefig('alpha2_3x_log_L_he.png')
Out[16]:
In [29]:
# o pequeno pico ocorre em torno do modelo 440, vou ver onde se localiza no HRD
plt.plot(t, L)
#plt.plot(t[154], L[154], 'ro')
plt.plot(t[439], L[439], 'ko')
#plt.plot(t[2149], L[2149], 'go')
plt.gca().invert_xaxis()
plt.title(r'HRD $\alpha_{MLT}=2$', fontsize=18)
plt.xlabel(r'$\log T_{Eff}$', fontsize=16)
plt.ylabel(r'$\log L$', fontsize=16)
plt.xlim(3.7, 3.5)
#plt.ylim(3.5,4.5)
plt.ylim(3.7,4.4)
plt.savefig('alpha2_3x_hrd_zoom.png')
In [30]:
# grafico luminosidade por modelo
plt.plot(model, L)
Out[30]:
In [32]:
# perda de massa X model
mass = s.get('star_mass')
plt.plot(model, mass)
plt.plot(model[154], mass[154], 'ko')
plt.plot(model[2149], mass[2149], 'ko')
print 'massa modelo 155: ', mass[154]
print 'massa modelo 2149: ',mass[2149]
print 'variacao: ',abs(mass[154] - mass[2149])
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