analise da taxa de energia por camadas no teste make o ne wd com alpha=2


In [1]:
import mesa as ms
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams["figure.figsize"] = (15., 10.)

In [2]:
folder = '/media/glauffer/Data/mesa/alpha2_r8845/LOGS'
# lendo os dados do history
s = ms.history_data(folder)
s.cols


Using old history.datasa file ...
 reading ...100% 

Out[2]:
{'burn_qtop_1': 156,
 'burn_qtop_10': 174,
 'burn_qtop_11': 176,
 'burn_qtop_12': 178,
 'burn_qtop_13': 180,
 'burn_qtop_14': 182,
 'burn_qtop_15': 184,
 'burn_qtop_16': 186,
 'burn_qtop_17': 188,
 'burn_qtop_18': 190,
 'burn_qtop_19': 192,
 'burn_qtop_2': 158,
 'burn_qtop_20': 194,
 'burn_qtop_21': 196,
 'burn_qtop_22': 198,
 'burn_qtop_23': 200,
 'burn_qtop_24': 202,
 'burn_qtop_25': 204,
 'burn_qtop_26': 206,
 'burn_qtop_27': 208,
 'burn_qtop_28': 210,
 'burn_qtop_29': 212,
 'burn_qtop_3': 160,
 'burn_qtop_30': 214,
 'burn_qtop_31': 216,
 'burn_qtop_32': 218,
 'burn_qtop_33': 220,
 'burn_qtop_34': 222,
 'burn_qtop_35': 224,
 'burn_qtop_36': 226,
 'burn_qtop_37': 228,
 'burn_qtop_38': 230,
 'burn_qtop_39': 232,
 'burn_qtop_4': 162,
 'burn_qtop_40': 234,
 'burn_qtop_41': 236,
 'burn_qtop_42': 238,
 'burn_qtop_43': 240,
 'burn_qtop_44': 242,
 'burn_qtop_45': 244,
 'burn_qtop_46': 246,
 'burn_qtop_47': 248,
 'burn_qtop_48': 250,
 'burn_qtop_49': 252,
 'burn_qtop_5': 164,
 'burn_qtop_50': 254,
 'burn_qtop_51': 256,
 'burn_qtop_52': 258,
 'burn_qtop_53': 260,
 'burn_qtop_54': 262,
 'burn_qtop_55': 264,
 'burn_qtop_56': 266,
 'burn_qtop_57': 268,
 'burn_qtop_58': 270,
 'burn_qtop_59': 272,
 'burn_qtop_6': 166,
 'burn_qtop_60': 274,
 'burn_qtop_61': 276,
 'burn_qtop_62': 278,
 'burn_qtop_63': 280,
 'burn_qtop_64': 282,
 'burn_qtop_65': 284,
 'burn_qtop_66': 286,
 'burn_qtop_67': 288,
 'burn_qtop_68': 290,
 'burn_qtop_69': 292,
 'burn_qtop_7': 168,
 'burn_qtop_70': 294,
 'burn_qtop_71': 296,
 'burn_qtop_72': 298,
 'burn_qtop_73': 300,
 'burn_qtop_74': 302,
 'burn_qtop_75': 304,
 'burn_qtop_76': 306,
 'burn_qtop_77': 308,
 'burn_qtop_78': 310,
 'burn_qtop_79': 312,
 'burn_qtop_8': 170,
 'burn_qtop_80': 314,
 'burn_qtop_9': 172,
 'burn_type_1': 155,
 'burn_type_10': 173,
 'burn_type_11': 175,
 'burn_type_12': 177,
 'burn_type_13': 179,
 'burn_type_14': 181,
 'burn_type_15': 183,
 'burn_type_16': 185,
 'burn_type_17': 187,
 'burn_type_18': 189,
 'burn_type_19': 191,
 'burn_type_2': 157,
 'burn_type_20': 193,
 'burn_type_21': 195,
 'burn_type_22': 197,
 'burn_type_23': 199,
 'burn_type_24': 201,
 'burn_type_25': 203,
 'burn_type_26': 205,
 'burn_type_27': 207,
 'burn_type_28': 209,
 'burn_type_29': 211,
 'burn_type_3': 159,
 'burn_type_30': 213,
 'burn_type_31': 215,
 'burn_type_32': 217,
 'burn_type_33': 219,
 'burn_type_34': 221,
 'burn_type_35': 223,
 'burn_type_36': 225,
 'burn_type_37': 227,
 'burn_type_38': 229,
 'burn_type_39': 231,
 'burn_type_4': 161,
 'burn_type_40': 233,
 'burn_type_41': 235,
 'burn_type_42': 237,
 'burn_type_43': 239,
 'burn_type_44': 241,
 'burn_type_45': 243,
 'burn_type_46': 245,
 'burn_type_47': 247,
 'burn_type_48': 249,
 'burn_type_49': 251,
 'burn_type_5': 163,
 'burn_type_50': 253,
 'burn_type_51': 255,
 'burn_type_52': 257,
 'burn_type_53': 259,
 'burn_type_54': 261,
 'burn_type_55': 263,
 'burn_type_56': 265,
 'burn_type_57': 267,
 'burn_type_58': 269,
 'burn_type_59': 271,
 'burn_type_6': 165,
 'burn_type_60': 273,
 'burn_type_61': 275,
 'burn_type_62': 277,
 'burn_type_63': 279,
 'burn_type_64': 281,
 'burn_type_65': 283,
 'burn_type_66': 285,
 'burn_type_67': 287,
 'burn_type_68': 289,
 'burn_type_69': 291,
 'burn_type_7': 167,
 'burn_type_70': 293,
 'burn_type_71': 295,
 'burn_type_72': 297,
 'burn_type_73': 299,
 'burn_type_74': 301,
 'burn_type_75': 303,
 'burn_type_76': 305,
 'burn_type_77': 307,
 'burn_type_78': 309,
 'burn_type_79': 311,
 'burn_type_8': 169,
 'burn_type_80': 313,
 'burn_type_9': 171,
 'c_core_mass': 26,
 'center_ar36': 64,
 'center_c12': 58,
 'center_ca40': 65,
 'center_cr56': 69,
 'center_entropy': 51,
 'center_fe54': 66,
 'center_fe56': 67,
 'center_h1': 56,
 'center_he4': 57,
 'center_n14': 59,
 'center_ne20': 61,
 'center_ni56': 68,
 'center_o16': 60,
 'center_omega': 48,
 'center_omega_div_omega_crit': 49,
 'center_s32': 63,
 'center_si28': 62,
 'center_ye': 50,
 'conv_mx1_bot': 10,
 'conv_mx1_top': 9,
 'conv_mx2_bot': 12,
 'conv_mx2_top': 11,
 'epsnuc_M_1': 17,
 'epsnuc_M_2': 18,
 'epsnuc_M_3': 19,
 'epsnuc_M_4': 20,
 'epsnuc_M_5': 21,
 'epsnuc_M_6': 22,
 'epsnuc_M_7': 23,
 'epsnuc_M_8': 24,
 'fe_core_mass': 29,
 'he_core_mass': 25,
 'kh_timescale': 30,
 'log_L': 33,
 'log_LH': 31,
 'log_LHe': 32,
 'log_R': 35,
 'log_Teff': 34,
 'log_abs_mdot': 4,
 'log_average_h1': 70,
 'log_average_h2': 71,
 'log_average_he3': 72,
 'log_average_he4': 73,
 'log_average_li7': 74,
 'log_center_P': 47,
 'log_center_Rho': 46,
 'log_center_T': 45,
 'log_dt': 6,
 'log_g': 36,
 'log_rotational_mdot_boost': 5,
 'log_total_angular_momentum': 8,
 'mix_qtop_1': 76,
 'mix_qtop_10': 94,
 'mix_qtop_11': 96,
 'mix_qtop_12': 98,
 'mix_qtop_13': 100,
 'mix_qtop_14': 102,
 'mix_qtop_15': 104,
 'mix_qtop_16': 106,
 'mix_qtop_17': 108,
 'mix_qtop_18': 110,
 'mix_qtop_19': 112,
 'mix_qtop_2': 78,
 'mix_qtop_20': 114,
 'mix_qtop_21': 116,
 'mix_qtop_22': 118,
 'mix_qtop_23': 120,
 'mix_qtop_24': 122,
 'mix_qtop_25': 124,
 'mix_qtop_26': 126,
 'mix_qtop_27': 128,
 'mix_qtop_28': 130,
 'mix_qtop_29': 132,
 'mix_qtop_3': 80,
 'mix_qtop_30': 134,
 'mix_qtop_31': 136,
 'mix_qtop_32': 138,
 'mix_qtop_33': 140,
 'mix_qtop_34': 142,
 'mix_qtop_35': 144,
 'mix_qtop_36': 146,
 'mix_qtop_37': 148,
 'mix_qtop_38': 150,
 'mix_qtop_39': 152,
 'mix_qtop_4': 82,
 'mix_qtop_40': 154,
 'mix_qtop_5': 84,
 'mix_qtop_6': 86,
 'mix_qtop_7': 88,
 'mix_qtop_8': 90,
 'mix_qtop_9': 92,
 'mix_type_1': 75,
 'mix_type_10': 93,
 'mix_type_11': 95,
 'mix_type_12': 97,
 'mix_type_13': 99,
 'mix_type_14': 101,
 'mix_type_15': 103,
 'mix_type_16': 105,
 'mix_type_17': 107,
 'mix_type_18': 109,
 'mix_type_19': 111,
 'mix_type_2': 77,
 'mix_type_20': 113,
 'mix_type_21': 115,
 'mix_type_22': 117,
 'mix_type_23': 119,
 'mix_type_24': 121,
 'mix_type_25': 123,
 'mix_type_26': 125,
 'mix_type_27': 127,
 'mix_type_28': 129,
 'mix_type_29': 131,
 'mix_type_3': 79,
 'mix_type_30': 133,
 'mix_type_31': 135,
 'mix_type_32': 137,
 'mix_type_33': 139,
 'mix_type_34': 141,
 'mix_type_35': 143,
 'mix_type_36': 145,
 'mix_type_37': 147,
 'mix_type_38': 149,
 'mix_type_39': 151,
 'mix_type_4': 81,
 'mix_type_40': 153,
 'mix_type_5': 83,
 'mix_type_6': 85,
 'mix_type_7': 87,
 'mix_type_8': 89,
 'mix_type_9': 91,
 'model_number': 1,
 'mx1_bot': 14,
 'mx1_top': 13,
 'mx2_bot': 16,
 'mx2_top': 15,
 'num_backups': 317,
 'num_retries': 316,
 'num_zones': 7,
 'o_core_mass': 27,
 'si_core_mass': 28,
 'star_age': 2,
 'star_mass': 3,
 'surf_avg_Lrad_div_Ledd': 44,
 'surf_avg_j_rot': 37,
 'surf_avg_omega': 38,
 'surf_avg_omega_crit': 39,
 'surf_avg_omega_div_omega_crit': 40,
 'surf_avg_v_crit': 42,
 'surf_avg_v_div_v_crit': 43,
 'surf_avg_v_rot': 41,
 'surface_c12': 53,
 'surface_he4': 52,
 'surface_n14': 54,
 'surface_o16': 55,
 'v_div_csound_surf': 315}

In [3]:
# dados por modelo
a = ms.mesa_profile(folder, 500, num_type='nearest_model')
a.cols


58 in profiles.index file ...
Found and load nearest profile for cycle 500
reading /media/glauffer/Data/mesa/alpha2_r8845/LOGS/profile16.data ...
 reading ...100% 

Out[3]:
{'abar': 29,
 'am_log_D_DSI': 117,
 'am_log_D_ES': 120,
 'am_log_D_GSF': 121,
 'am_log_D_SH': 118,
 'am_log_D_SSI': 119,
 'am_log_D_ST': 122,
 'am_log_nu_ST': 123,
 'am_log_sig': 116,
 'burn_ar': 86,
 'burn_c': 78,
 'burn_ca': 87,
 'burn_cr': 89,
 'burn_fe': 90,
 'burn_mg': 83,
 'burn_n': 79,
 'burn_na': 82,
 'burn_ne': 81,
 'burn_o': 80,
 'burn_s': 85,
 'burn_si': 84,
 'burn_ti': 88,
 'c12': 62,
 'c12_c12': 91,
 'c12_o16': 92,
 'c13': 63,
 'cno': 76,
 'conv_vel_div_csound': 44,
 'csound': 11,
 'dlnT_dt': 55,
 'dlnd_dt': 54,
 'dq_ratio': 18,
 'dynamo_log_B_phi': 125,
 'dynamo_log_B_r': 124,
 'entropy': 9,
 'eps_grav': 34,
 'eps_nuc': 32,
 'eta': 15,
 'f19': 70,
 'fp_rot': 106,
 'free_e': 28,
 'ft_rot': 107,
 'gradL': 51,
 'gradT': 47,
 'gradT_sub_grada': 37,
 'grad_density': 50,
 'grad_temperature': 49,
 'grada': 27,
 'gradr': 48,
 'gradr_sub_grada': 126,
 'h1': 59,
 'he3': 60,
 'he4': 61,
 'i_rot': 104,
 'j_rot': 105,
 'ledoux_stable': 53,
 'logL': 7,
 'logP': 4,
 'logPgas': 26,
 'logR': 5,
 'logRho': 3,
 'logT': 2,
 'log_D_conv': 38,
 'log_D_mix': 42,
 'log_D_ovr': 40,
 'log_D_semi': 39,
 'log_D_thrm': 41,
 'log_J_div_M53': 100,
 'log_J_inside': 101,
 'log_abs_shear': 102,
 'log_am_nu': 108,
 'log_conv_vel': 43,
 'log_j_rot': 99,
 'log_mlt_D_mix': 45,
 'log_omega': 98,
 'log_opacity': 31,
 'log_r_equatorial': 112,
 'log_r_polar': 110,
 'logdq': 17,
 'logtau': 23,
 'logxq': 58,
 'luminosity': 6,
 'mass': 56,
 'mg24': 73,
 'mixing_type': 10,
 'mlt_mixing_length': 35,
 'mlt_mixing_type': 36,
 'mmid': 57,
 'mu': 16,
 'n13': 64,
 'n14': 65,
 'n15': 66,
 'ne20': 71,
 'ne22': 72,
 'non_nuc_neu': 33,
 'o16': 67,
 'o16_o16': 93,
 'o17': 68,
 'o18': 69,
 'omega': 97,
 'omega_crit': 114,
 'omega_div_omega_crit': 115,
 'other': 96,
 'pgas_div_ptotal': 25,
 'photo': 95,
 'pnhe4': 94,
 'pp': 75,
 'pressure': 24,
 'pressure_scale_height': 46,
 'q': 19,
 'r_e_div_r_p': 113,
 'r_equatorial': 111,
 'r_polar': 109,
 'radius': 20,
 'sch_stable': 52,
 'si28': 74,
 'tau': 22,
 'temperature': 21,
 'total_energy': 13,
 'tri_alfa': 77,
 'v_div_csound': 12,
 'v_div_r': 14,
 'v_rot': 103,
 'velocity': 8,
 'ye': 30,
 'zone': 1}

In [37]:
# Pelo arquivo profile_columns.list dentro da pasta defaults, o header eps_nuc seria a taxa de energia 
# das reacoes nucleares menos a energia dos neutrinos ( ergs/g/s )
import numpy as np
e_nuc = a.get('eps_nuc')
zone = a.get('zone')
mass = a.get('mass')
q = -np.log(1 - a.get('q'))


-c:7: RuntimeWarning: divide by zero encountered in log

In [51]:
plt.plot(mass/9, e_nuc)
plt.title('modelo 500 - antes dos TP')
plt.xlim(0,1)


Out[51]:
(0, 1)

In [11]:
plt.plot(mass, e_nuc)


Out[11]:
[<matplotlib.lines.Line2D at 0x7fa6c8764990>]

In [8]:
print mass


[  7.88791080e+00   7.88791080e+00   7.88791080e+00   7.88791080e+00
   7.88791080e+00   7.88791080e+00   7.88791080e+00   7.88791080e+00
   7.88791080e+00   7.88791080e+00   7.88791080e+00   7.88791079e+00
   7.88791078e+00   7.88791077e+00   7.88791073e+00   7.88791068e+00
   7.88791061e+00   7.88791054e+00   7.88791041e+00   7.88791023e+00
   7.88790999e+00   7.88790971e+00   7.88790910e+00   7.88790798e+00
   7.88790584e+00   7.88790221e+00   7.88789738e+00   7.88788977e+00
   7.88787672e+00   7.88784809e+00   7.88783566e+00   7.88781784e+00
   7.88779048e+00   7.88775952e+00   7.88772264e+00   7.88769817e+00
   7.88768033e+00   7.88763862e+00   7.88760550e+00   7.88758459e+00
   7.88753474e+00   7.88750434e+00   7.88747821e+00   7.88742358e+00
   7.88737470e+00   7.88730949e+00   7.88726239e+00   7.88721807e+00
   7.88717191e+00   7.88712333e+00   7.88708747e+00   7.88704058e+00
   7.88699943e+00   7.88695763e+00   7.88691925e+00   7.88690006e+00
   7.88688087e+00   7.88686099e+00   7.88684111e+00   7.88682124e+00
   7.88680136e+00   7.88678077e+00   7.88676017e+00   7.88673958e+00
   7.88671899e+00   7.88667633e+00   7.88663367e+00   7.88654529e+00
   7.88645375e+00   7.88635893e+00   7.88626072e+00   7.88615900e+00
   7.88605364e+00   7.88594453e+00   7.88583153e+00   7.88571451e+00
   7.88559331e+00   7.88546781e+00   7.88533785e+00   7.88520327e+00
   7.88506392e+00   7.88491963e+00   7.88477023e+00   7.88461554e+00
   7.88437319e+00   7.88420447e+00   7.88393938e+00   7.88366176e+00
   7.88346797e+00   7.88305970e+00   7.88273351e+00   7.88250712e+00
   7.88227280e+00   7.88190694e+00   7.88138739e+00   7.88111393e+00
   7.88082601e+00   7.88022978e+00   7.87954728e+00   7.87917420e+00
   7.87873828e+00   7.87833913e+00   7.87788638e+00   7.87751789e+00
   7.87723682e+00   7.87672007e+00   7.87643000e+00   7.87599491e+00
   7.87525484e+00   7.87476403e+00   7.87449740e+00   7.87410330e+00
   7.87370920e+00   7.87292101e+00   7.87233276e+00   7.87203864e+00
   7.87174452e+00   7.87103657e+00   7.87032862e+00   7.86928264e+00
   7.86823665e+00   7.86771366e+00   7.86693281e+00   7.86615196e+00
   7.86537111e+00   7.86380941e+00   7.86302856e+00   7.86186720e+00
   7.85945664e+00   7.85765661e+00   7.85585659e+00   7.85405657e+00
   7.85225655e+00   7.84836087e+00   7.84641304e+00   7.84446520e+00
   7.84047233e+00   7.83647947e+00   7.83248660e+00   7.83049017e+00
   7.82849374e+00   7.82450087e+00   7.82050800e+00   7.81651514e+00
   7.81252227e+00   7.80942801e+00   7.80633374e+00   7.80014521e+00
   7.79395668e+00   7.78776815e+00   7.78157961e+00   7.77539108e+00
   7.76920255e+00   7.76301402e+00   7.75662134e+00   7.75022867e+00
   7.74383600e+00   7.73744332e+00   7.73105065e+00   7.72465798e+00
   7.71187263e+00   7.69856202e+00   7.68525142e+00   7.67194082e+00
   7.65863021e+00   7.64950467e+00   7.64037912e+00   7.63125357e+00
   7.62212803e+00   7.60805389e+00   7.59397976e+00   7.57990562e+00
   7.56583148e+00   7.54646523e+00   7.52709898e+00   7.50727191e+00
   7.48744483e+00   7.45676189e+00   7.42607894e+00   7.40506252e+00
   7.38404610e+00   7.35166309e+00   7.31928008e+00   7.29702425e+00
   7.27476842e+00   7.22923506e+00   7.19404233e+00   7.15884961e+00
   7.11068640e+00   7.08606456e+00   7.06144272e+00   7.02354885e+00
   6.98565498e+00   6.93363901e+00   6.88048416e+00   6.82617388e+00
   6.77069177e+00   6.71402154e+00   6.65614709e+00   6.59705250e+00
   6.53672209e+00   6.50593125e+00   6.47514041e+00   6.41229232e+00
   6.34816299e+00   6.31545046e+00   6.28273793e+00   6.21600309e+00
   6.14794485e+00   6.11324747e+00   6.07855008e+00   6.00780618e+00
   5.97192452e+00   5.93570110e+00   5.89913451e+00   5.82496638e+00
   5.76838595e+00   5.71110752e+00   5.68211787e+00   5.65295230e+00
   5.58416454e+00   5.53434792e+00   5.49410395e+00   5.44330940e+00
   5.41254716e+00   5.37123288e+00   5.32956045e+00   5.27697667e+00
   5.24513900e+00   5.20238905e+00   5.12672160e+00   5.07197851e+00
   5.02778750e+00   4.94959714e+00   4.89305207e+00   4.84742014e+00
   4.77834325e+00   4.73181361e+00   4.66130367e+00   4.62578109e+00
   4.58999163e+00   4.54212438e+00   4.51796940e+00   4.46948314e+00
   4.43289844e+00   4.39605080e+00   4.34677500e+00   4.30949184e+00
   4.24700751e+00   4.19660727e+00   4.14586571e+00   4.09478528e+00
   4.06907697e+00   4.01749366e+00   3.95255840e+00   3.91333460e+00
   3.84758254e+00   3.80787419e+00   3.76800681e+00   3.73457427e+00
   3.70114173e+00   3.66080536e+00   3.59317018e+00   3.55912714e+00
   3.52508411e+00   3.48399652e+00   3.44958798e+00   3.41517945e+00
   3.35283360e+00   3.30414201e+00   3.26221253e+00   3.24118125e+00
   3.20608532e+00   3.17085974e+00   3.12847484e+00   3.10725087e+00
   3.07171387e+00   3.05394538e+00   3.01477143e+00   2.99336599e+00
   2.95753727e+00   2.93962290e+00   2.90640891e+00   2.89110928e+00
   2.87580965e+00   2.84697298e+00   2.82055124e+00   2.79478183e+00
   2.78189713e+00   2.76966476e+00   2.74699108e+00   2.72610845e+00
   2.70200942e+00   2.67469398e+00   2.66103625e+00   2.64461684e+00
   2.62819744e+00   2.61176232e+00   2.60078464e+00   2.58431813e+00
   2.57334045e+00   2.56234304e+00   2.54676022e+00   2.53758938e+00
   2.52841854e+00   2.51466229e+00   2.50731803e+00   2.49445684e+00
   2.48618146e+00   2.47790608e+00   2.46963071e+00   2.46135117e+00
   2.45583009e+00   2.45030902e+00   2.43926271e+00   2.43373747e+00
   2.42821224e+00   2.41992241e+00   2.41162862e+00   2.40333484e+00
   2.39503710e+00   2.38950396e+00   2.38673738e+00   2.38120424e+00
   2.37567110e+00   2.37290452e+00   2.36737138e+00   2.36459951e+00
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   2.31470126e+00   2.31192784e+00   2.30915443e+00   2.30638102e+00
   2.30360761e+00   2.30222090e+00   2.29944595e+00   2.29805770e+00
   2.29528120e+00   2.29250471e+00   2.29111646e+00   2.28833996e+00
   2.28695171e+00   2.28556346e+00   2.28417521e+00   2.28139872e+00
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   2.09663635e+00   2.09628812e+00   2.09593989e+00   2.09524342e+00
   2.09489519e+00   2.09454696e+00   2.09385049e+00   2.09315403e+00
   2.09286377e+00   2.09257352e+00   2.09199300e+00   2.09141249e+00
   2.09112223e+00   2.09083197e+00   2.09025146e+00   2.08967094e+00
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   2.08560734e+00   2.08502683e+00   2.08444631e+00   2.08386580e+00
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   1.61124045e+00   1.60362525e+00   1.58822392e+00   1.56970771e+00
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   1.43364716e+00   1.41783955e+00   1.40688069e+00   1.38907254e+00
   1.37332508e+00   1.35795839e+00   1.34259171e+00   1.32351268e+00
   1.30715922e+00   1.29192426e+00   1.27902277e+00   1.26612127e+00
   1.25819525e+00   1.25180267e+00   1.24805210e+00   1.24430153e+00
   1.24055096e+00   1.23643558e+00   1.23232021e+00   1.22820484e+00
   1.22408947e+00   1.21997410e+00   1.21585873e+00   1.21315908e+00
   1.21045943e+00   1.20506013e+00   1.20236048e+00   1.19966083e+00
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   1.15128936e+00   1.14771205e+00   1.14413474e+00   1.14055742e+00
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   1.12206944e+00   1.12018055e+00   1.11829165e+00   1.11451386e+00
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   1.08186046e+00   1.07992227e+00   1.07604590e+00   1.07216953e+00
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   1.01666553e+00   1.01228119e+00   1.01008901e+00   1.00789684e+00
   1.00351249e+00   9.99128144e-01   9.95192329e-01   9.93224421e-01
   9.91256514e-01   9.87320698e-01   9.83384883e-01   9.79464770e-01
   9.77504713e-01   9.75544657e-01   9.73584600e-01   9.71624544e-01
   9.69664487e-01   9.67704430e-01   9.65744374e-01   9.63784317e-01
   9.61824261e-01   9.59864204e-01   9.57904148e-01   9.55944091e-01
   9.53984034e-01   9.52023978e-01   9.48124401e-01   9.44224824e-01
   9.40325247e-01   9.38375459e-01   9.36425670e-01   9.32526093e-01
   9.28626517e-01   9.24726940e-01   9.22777151e-01   9.18022958e-01
   9.12414148e-01   9.09609743e-01   9.04000932e-01   9.01196527e-01
   8.98392122e-01   8.92400340e-01   8.89404448e-01   8.86408557e-01
   8.80416774e-01   8.77420883e-01   8.74424991e-01   8.72082648e-01
   8.69740304e-01   8.67397960e-01   8.65055617e-01   8.62713273e-01
   8.60370930e-01   8.55686243e-01   8.53343899e-01   8.52172727e-01
   8.51001555e-01   8.48659212e-01   8.46316868e-01   8.43974525e-01
   8.41632181e-01   8.39289837e-01   8.35248880e-01   8.31851653e-01
   8.26755812e-01   8.23358584e-01   8.19961357e-01   8.13166902e-01
   8.09769675e-01   8.03136843e-01   7.98714954e-01   7.96504010e-01
   7.92082122e-01   7.86186271e-01   7.80356556e-01   7.74526842e-01
   7.71611985e-01   7.66510984e-01   7.62138699e-01   7.55580270e-01
   7.51207984e-01   7.48293127e-01   7.42463412e-01   7.35193757e-01
   7.30838958e-01   7.26484159e-01   7.22129360e-01   7.16322962e-01
   7.13849495e-01   7.11376027e-01   7.07665826e-01   7.03955625e-01
   6.99008690e-01   6.93884173e-01   6.91233124e-01   6.88582075e-01
   6.85931025e-01   6.83279976e-01   6.77977877e-01   6.75289330e-01
   6.72600782e-01   6.69874736e-01   6.67148690e-01   6.65104156e-01
   6.63059622e-01   6.61015087e-01   6.58970553e-01   6.56244507e-01
   6.53518461e-01   6.49429392e-01   6.45340323e-01   6.42614277e-01
   6.39888231e-01   6.37162185e-01   6.34436139e-01   6.32183941e-01
   6.29931742e-01   6.25427344e-01   6.22285970e-01   6.19144595e-01
   6.17050345e-01   6.14956096e-01   6.12861846e-01   6.10767596e-01
   6.07983333e-01   6.05199070e-01   6.01749004e-01   5.98298939e-01
   5.96110869e-01   5.93922799e-01   5.91734730e-01   5.89546660e-01
   5.87049899e-01   5.84553138e-01   5.82056378e-01   5.79559617e-01
   5.74233194e-01   5.70238377e-01   5.68240968e-01   5.66243559e-01
   5.62666305e-01   5.59089050e-01   5.56803942e-01   5.54518834e-01
   5.49948619e-01   5.46958249e-01   5.43967879e-01   5.41643313e-01
   5.39318746e-01   5.36994179e-01   5.34669612e-01   5.31182762e-01
   5.27695912e-01   5.24209062e-01   5.22465636e-01   5.20722211e-01
   5.17858720e-01   5.14995230e-01   5.09268248e-01   5.05844724e-01
   5.04132962e-01   5.02421200e-01   4.98997676e-01   4.95574152e-01
   4.93291803e-01   4.91009454e-01   4.86444755e-01   4.82194790e-01
   4.77944824e-01   4.74009590e-01   4.70074357e-01   4.66139124e-01
   4.60236274e-01   4.54333424e-01   4.47056922e-01   4.35255344e-01
   4.24910126e-01   4.11828081e-01   4.03691137e-01   3.90628630e-01
   3.83476386e-01   3.77408680e-01   3.64133246e-01   3.47973740e-01
   3.34682909e-01   3.28475472e-01   3.15159394e-01   3.00942112e-01
   2.90430943e-01   2.83474094e-01   2.69560397e-01   2.60288406e-01
   2.46671977e-01   2.39654800e-01   2.23561641e-01   2.12426853e-01
   2.06859459e-01   1.93285660e-01   1.70962706e-01   1.61842901e-01
   1.55639481e-01   1.43232640e-01   1.31180178e-01   1.13812221e-01
   1.03181234e-01   9.23577755e-02   8.27126175e-02   6.75346136e-02
   5.92353448e-02   4.95404237e-02   3.57768850e-02   2.95310124e-02
   1.72404334e-02   1.15980598e-02   7.69545108e-03   4.23747535e-03
   2.16374041e-03   1.12687294e-03   6.08439201e-04   3.49222334e-04
   2.19613900e-04   1.54809683e-04   9.00054662e-05   4.50027330e-05
   2.25013664e-05   1.12506831e-05   5.62534141e-06   2.81267059e-06
   1.40633517e-06   7.03167466e-07]

In [12]:
# analizando para um modelo apos os "TP"
a2 = ms.mesa_profile(folder, 2090, num_type='nearest_model')
e_nuc2 = a2.get('eps_nuc')
zone2 = a2.get('zone')
mass2 = a2.get('mass')


58 in profiles.index file ...
Found and load nearest profile for cycle 2100
reading /media/glauffer/Data/mesa/alpha2_r8845/LOGS/profile48.data ...
 reading ...100% 


In [52]:
plt.plot(mass2/9, e_nuc2)
plt.title('modelo 2090 - depois dos TP')
plt.xlim(0,1)


Out[52]:
(0, 1)

In [28]:
# extraindo os dados de reacao pp, cno e 3_alpha do modelo apos os TP
cno2 = a2.get('cno')
tri_alfa2 = a2.get('tri_alfa')
pp2 = a2.get('pp')

In [35]:
import numpy as np
#plt.plot(zone2, tri_alfa2)
#plt.plot(zone2,pp2)
plt.plot(zone2, cno2)
#plt.plot(-np.log(1-a2.get('q')), cno2)


Out[35]:
[<matplotlib.lines.Line2D at 0x7fa6c78b36d0>]

In [27]:
# extraindo energia total
e2 = a2.get('total_energy')
plt.plot(mass2, e2)


Out[27]:
[<matplotlib.lines.Line2D at 0x7fa6c8202290>]

In [ ]: