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Pessoal, há tempo venho me enrolando quando preciso ler um arquivo como esse que está abaixo (spec.dat). Qual seria a melhor maneira de ler os dados desse arquivo separadamente e,então, contruir tabelas e histogramas ? Por exemplo: Ler os elementos da coluna x_j(%) e age_j(yr). Ler o valor de [N_base] ## Some input info Base.M05SFull [arq_base] 57 [N_base] 0 [N_YAV_components = # of components with extra extinction!] 0 [i_FitPowerLaw (1/0 = Yes/No)] ## (Re)Sampling Parameters 11610.00 [l_ini (A)] 24500.00 [l_fin (A)] ## Normalization info 12230.00 [l_norm (A) - for base] 12200.00 [llow_norm (A) - window for f_obs] 12260.00 [lupp_norm (A) - window for f_obs] 3.120000E-17 [fobs_norm (in input units)] # j x_j(%) Mini_j(%) Mcor_j(%) age_j(yr) Z_j (L/M)_j YAV? Mstars component_j a/Fe... SSP_chi2r SSP_adev(%) SSP_AV SSP_x(%) 1 1.4781 3.6233E-01 5.2752E-01 1.000000E+07 0.00040 1.779E-04 0 0.9094 m05.z0.0004A_0. 0.0000 1.7210E+03 38.7910 5.0000 130.7247 2 0.0031 7.5960E-04 1.0559E-03 3.000000E+07 0.00040 1.791E-04 0 0.8683 m05.z0.0004A_0. 0.0000 6.2722E+02 22.6184 5.0000 123.1968 3 0.0012 3.4120E-04 4.6125E-04 5.000000E+07 0.00040 1.503E-04 0 0.8444 m05.z0.0004A_0. 0.0000 5.7873E+02 21.5826 5.0000 122.4820 4 0.0000 0.0000E+00 0.0000E+00 1.000000E+08 0.00040 1.235E-04 0 0.8073 m05.z0.0004A_0. 0.0000 5.1668E+02 20.1777 5.0000 121.4757 5 0.0304 1.3696E-02 1.6948E-02 2.000000E+08 0.00040 9.689E-05 0 0.7729 m05.z0.0004A_0. 0.0000 5.1557E+02 20.1942 5.0000 121.4867 6 13.4567 4.1353E+00 4.8065E+00 5.000000E+08 0.00040 1.419E-04 0 0.7260 m05.z0.0004A_0. 0.0000 1.4574E+02 9.4474 3.0902 103.2744 7 4.4286 1.7307E+00 1.9639E+00 7.000000E+08 0.00040 1.116E-04 0 0.7088 m05.z0.0004A_0. 0.0000 1.6090E+02 11.1368 5.0000 88.9404 8 3.9027 2.1085E+00 2.3292E+00 1.000000E+09 0.00040 8.071E-05 0 0.6900 m05.z0.0004A_1. 0.0000 9.5583E+01 8.9517 5.0000 94.3401 9 0.7589 7.5818E-01 8.0028E-01 2.000000E+09 0.00040 4.365E-05 0 0.6593 m05.z0.0004A_2. 0.0000 6.6007E+01 6.4125 5.0000 103.0134 10 5.4062 2.7183E+01 2.5872E+01 1.300000E+10 0.04000 8.672E-06 0 0.5945 m05.z0.04A_13.0 0.0000 6.3328E+01 7.2153 5.0000 101.1410 11 0.0000 0.0000E+00 0.0000E+00 1.000000E+00 0.00000 9.952E+00 0 1.0000 BB_700 0.0000 4.3247E+03 44.0822 0.0000 0.5478 12 9.8411 4.2904E-04 6.8688E-04 1.000000E+00 0.00000 1.000E+00 0 1.0000 Power_150 0.0000 1.1203E+02 7.9543 0.0000 87.0399 ## Synthesis Results - Average & Chains ## # j x_j: min, <> & last-chain-values for 1 ... 12 chains 1 1.4781 2.3577 2.4191 2.1424 2.3087 2.2562 2.3316 2.1499 2.1073 2.3995 2.3102 2.3386 2.2189 2.3029 2 0.0031 0.2126 0.3424 0.0425 0.3953 0.1954 0.0000 0.1363 0.0000 0.0577 0.1445 0.4121 0.1843 0.8749 3 0.0012 0.1785 0.0000 0.0000 0.0690 0.1942 0.0105 0.1394 0.0129 0.2873 0.4481 0.0000 0.2058 0.0000 # AV, chi2 & Mass for <> & i_chain = 1 ... 12 solutions AV 0.9529 0.9180 0.9256 0.9333 0.9127 0.9175 0.9327 0.9154 0.9142 0.9273 0.9372 0.9260 0.9219 0.9309 chi2 8.0773E+00 8.0951E+00 8.0903E+00 8.0895E+00 8.0988E+00 8.0904E+00 8.0906E+00 8.0913E+00 8.0908E+00 8.0916E+00 8.0880E+00 8.0917E+00 8.0912E+00 8.0919E+00 Mass 5.7755E-13 5.1633E-13 5.3867E-13 5.2781E-13 5.1839E-13 5.4180E-13 5.2434E-13 5.1936E-13 5.3047E-13 5.1270E-13 5.2630E-13 4.9951E-13 5.2338E-13 5.2286E-13 0.00 [v0_min (km/s) before EX0s...] 150.00 [vd_min (km/s) before EX0s...] ## Synthetic spectrum (Best Model) ##l_obs f_obs f_syn wei 2579 [Nl_obs] 11610.00 0.94817 1.02827 116.669 11615.00 0.96295 1.02735 116.669 11620.00 1.03489 1.02735 116.669 11625.00 1.09356 1.02753 116.669 11630.00 1.13951 1.02773 116.669 11635.00 1.11024 1.02797 116.669 Obrigado