The pyEQUIB library is a collection of Python programs developed to perform plasma diagnostics and abundance analysis using emission line fluxes measured in ionzed nebulae. It uses the AtomNeb Python Package to read collision strengths and transition probabilities for collisionally excited lines (CEL), and recombination coefficients for recombination lines (RL). This Python package can be used to determine interstellar extinctions, electron temperatures, electron densities, and ionic abundances from the measured fluxes of emission lines. It mainly contains the follwing API functions written purely in Python:
- API functions for collisionally excited lines (CEL) have been developed based on the algorithm of the FORTRAN program EQUIB originally written in FORTRAN by Howarth & Adams (1981), extended and customized by other people (R. Clegg, D. Ruffle, X.-W. Liu, C. Pritchet, B. Ercolano, & R. Wesson). The program EQUIB calculates atomic level populations and line emissivities in statistical equilibrium in multi-level atoms for different physical conditions of the stratification layers where the chemical elements are ionized. Using the Python implementation of the program EQUIB, electron temperatures, electron densities, and ionic abundances are determined from the measured fluxes of collisionally excited lines.
- API functions for recombination lines (RL) have been developed based on the algorithm of the recombination scripts by X. W. Liu and Y. Zhang from output_mod.f90 included in the FORTRAN program MOCASSIN. These API functiosn are used to determine ionic abundances from recombination lines for some heavy element ions.
- API functions for reddening and extinctions have been developed according to the methods of the reddening law functions from STSDAS IRAF Package, which are used to obtain interstellar extinctions and deredden measured fluxes based on different reddening laws.
This package requires the following packages:
- To get this package with the AtomNeb FITS files, you can simply use
gitcommand as follows:
git clone --recursive https://github.com/equib/pyEQUIB
To install the last version, all you should need to do is
$ python setup.py install
To install the stable version, you can use the preferred installer program (pip):
$ pip install pyequib
or you can install it from the cross-platform package manager conda:
$ conda install -c conda-forge pyequib
The Documentation of the Python functions provides in detail in the API Documentation (equib.github.io/pyEQUIB/doc).
See Jupyter Notebooks: Notebooks.ipynb
Run Jupyter Notebooks on Binder:
There are three main object units:
Collision Unit has the API functions for plasma diagnostics and abundance analysis of collisionally excited lines. Here are some examples of using Collision Unit:
Temperature:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom = 's' ion = 'ii' s_ii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) s_ii_omij = atomneb.read_omij(atom_omij_file, atom, ion) s_ii_aij = atomneb.read_aij(atom_aij_file, atom, ion) upper_levels='1,2,1,3/' lower_levels='1,5/' density = np.float64(2550) line_flux_ratio=np.float64(10.753) temperature = pyequib.calc_temperature(line_flux_ratio=line_flux_ratio, density=density, upper_levels=upper_levels, lower_levels=lower_levels, elj_data=s_ii_elj, omij_data=s_ii_omij, aij_data=s_ii_aij) print("Electron Temperature:", temperature)
which gives:
Electron Temperature: 7920.2865
Density:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom = 's' ion = 'ii' s_ii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) s_ii_omij = atomneb.read_omij(atom_omij_file, atom, ion) s_ii_aij = atomneb.read_aij(atom_aij_file, atom, ion) upper_levels='1,2/' lower_levels='1,3/' temperature=np.float64(7000.0)# line_flux_ratio=np.float64(1.506)# density = pyequib.calc_density(line_flux_ratio=line_flux_ratio, temperature=temperature, upper_levels=upper_levels, lower_levels=lower_levels, elj_data=s_ii_elj, omij_data=s_ii_omij, aij_data=s_ii_aij) print("Electron Density:", density)
which gives:
Electron Density: 2312.6395
Ionic Abundance:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') data_rc_dir = os.path.join('atomic-data-rc') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'h' ion = 'ii' # H I Rec hi_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) atom = 'o' ion = 'iii' # [O III] o_iii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) # read Energy Levels (Ej) o_iii_omij = atomneb.read_omij(atom_omij_file, atom, ion) # read Collision Strengths (Omegaij) o_iii_aij = atomneb.read_aij(atom_aij_file, atom, ion) # read Transition Probabilities (Aij) levels5007='3,4/' temperature=np.float64(10000.0) density=np.float64(5000.0) iobs5007=np.float64(1200.0) abb5007 = pyequib.calc_abundance(temperature=temperature, density=density, line_flux=iobs5007, atomic_levels=levels5007, elj_data=o_iii_elj, omij_data=o_iii_omij, aij_data=o_iii_aij, h_i_aeff_data=hi_rc_data['aeff'][0]) print('N(O^2+)/N(H+):', abb5007)
which gives:
N(O^2+)/N(H+): 0.00041256231
Emissivity:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') data_rc_dir = os.path.join('atomic-data-rc') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'h' ion = 'ii' # H I Rec hi_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) atom = 'o' ion = 'iii' # [O III] o_iii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) # read Energy Levels (Ej) o_iii_omij = atomneb.read_omij(atom_omij_file, atom, ion) # read Collision Strengths (Omegaij) o_iii_aij = atomneb.read_aij(atom_aij_file, atom, ion) # read Transition Probabilities (Aij) levels5007='3,4/' temperature=np.float64(10000.0) density=np.float64(5000.0) iobs5007=np.float64(1200.0) emis = pyequib.calc_emissivity(temperature=temperature, density=density, atomic_levels=levels5007, elj_data=o_iii_elj, omij_data=o_iii_omij, aij_data=o_iii_aij) print('Emissivity(O III 5007):', emis)
which gives:
Emissivity(O III 5007): 3.6041012e-21
Atomic Level Population:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom = 's' ion = 'ii' s_ii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) s_ii_omij = atomneb.read_omij(atom_omij_file, atom, ion) s_ii_aij = atomneb.read_aij(atom_aij_file, atom, ion) density = np.float64(1000) temperature=np.float64(10000.0)# nlj = pyequib.calc_populations(temperature=temperature, density=density, elj_data=s_ii_elj, omij_data=s_ii_omij, aij_data=s_ii_aij) print('Populations:', nlj)
which prints:
Populations: 0.96992832 0.0070036315 0.023062261 2.6593671e-06 3.1277019e-06
Critical Density:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom = 's' ion = 'ii' s_ii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) s_ii_omij = atomneb.read_omij(atom_omij_file, atom, ion) s_ii_aij = atomneb.read_aij(atom_aij_file, atom, ion) temperature=np.float64(10000.0) n_crit = pyequib.calc_crit_density(temperature=temperature, elj_data=s_ii_elj, omij_data=s_ii_omij, aij_data=s_ii_aij) print('Critical Densities:', n_crit)
which gives:
Critical Densities: 0.0000000 5007.8396 1732.8414 1072685.0 2220758.1
All Ionic Level Information:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_dir = os.path.join('atomic-data', 'chianti70') data_rc_dir = os.path.join('atomic-data-rc') atom_elj_file = os.path.join(base_dir,data_dir, 'AtomElj.fits') atom_omij_file = os.path.join(base_dir,data_dir, 'AtomOmij.fits') atom_aij_file = os.path.join(base_dir,data_dir, 'AtomAij.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'h' ion = 'ii' # H I Rec hi_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) atom = 'o' ion = 'iii' # [O III] o_iii_elj = atomneb.read_elj(atom_elj_file, atom, ion, level_num=5) # read Energy Levels (Ej) o_iii_omij = atomneb.read_omij(atom_omij_file, atom, ion) # read Collision Strengths (Omegaij) o_iii_aij = atomneb.read_aij(atom_aij_file, atom, ion) # read Transition Probabilities (Aij) temperature=np.float64(10000.0) density=np.float64(5000.0) pyequib.print_ionic(temperature=temperature, density=density, elj_data=o_iii_elj, omij_data=o_iii_omij, aij_data=o_iii_aij, h_i_aeff_data=hi_rc_data['aeff'][0])
which gives:
Temperature = 10000.0 K Density = 1000.0 cm-3 Level Populations Critical Densities Level 1: 3.063E-01 0.000E+00 Level 2: 4.896E-01 4.908E+02 Level 3: 2.041E-01 3.419E+03 Level 4: 4.427E-05 6.853E+05 Level 5: 2.985E-09 2.547E+07 2.597E-05 88.34um (2-->1) 2.859E-22 0.000E+00 9.632E-05 32.66um 51.81um (3-->1) (3-->2) 0.000E+00 7.536E-22 2.322E-06 6.791E-03 2.046E-02 4932.60A 4960.29A 5008.24A (4-->1) (4-->2) (4-->3) 4.140E-25 1.204E-21 3.593E-21 0.000E+00 2.255E-01 6.998E-04 1.685E+00 2315.58A 2321.67A 2332.12A 4364.45A (5-->1) (5-->2) (5-->3) (5-->4) 0.000E+00 5.759E-24 1.779E-26 2.289E-23 H-beta emissivity: 1.237E-25 N(H+) Ne [erg/s]
Recombination Unit has the API functions for plasma diagnostics and abundance analysis of recombination lines. Here are some examples of using Recombination Unit:
He+ Ionic Abundance:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_he_i_file = os.path.join(base_dir,data_rc_dir, 'rc_he_ii_PFSD12.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) atom = 'he' ion = 'ii' # He I he_i_rc_data = atomneb.read_aeff_he_i_pfsd12(atom_rc_he_i_file, atom, ion) h_i_aeff_data = h_i_rc_data['aeff'][0] he_i_aeff_data = he_i_rc_data['aeff'][0] temperature=np.float64(10000.0) density=np.float64(5000.0) he_i_4471_flux= 2.104 linenum=10# 4471.50 abund_he_i = pyequib.calc_abund_he_i_rl(temperature=temperature, density=density, linenum=linenum, line_flux=he_i_4471_flux, he_i_aeff_data=he_i_aeff_data, h_i_aeff_data=h_i_aeff_data) print('N(He^+)/N(H^+):', abund_he_i)
which gives:
N(He^+)/N(H^+): 0.040848393
He++ Ionic Abundance:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) atom = 'he' ion = 'iii' # He II he_ii_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) h_i_aeff_data = h_i_rc_data['aeff'][0] he_ii_aeff_data = he_ii_rc_data['aeff'][0] temperature=np.float64(10000.0) density=np.float64(5000.0) he_ii_4686_flux = 135.833 abund_he_ii = pyequib.calc_abund_he_ii_rl(temperature=temperature, density=density, line_flux=he_ii_4686_flux, he_ii_aeff_data=he_ii_aeff_data, h_i_aeff_data=h_i_aeff_data) print('N(He^2+)/N(H^+):', abund_he_ii)
which gives:
N(He^2+)/N(H^+): 0.11228817
C++ Ionic Abundance:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'c' ion = 'iii' # C II c_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) temperature=np.float64(10000.0) density=np.float64(5000.0) wavelength=6151.43 c_ii_6151_flux = 0.028 abund_c_ii = pyequib.calc_abund_c_ii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=c_ii_6151_flux, c_ii_rc_data=c_ii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(C^2+)/N(H+):', abund_c_ii)
which gives:
N(C^2+)/N(H+): 0.00063404650
C3+ Ionic Abundance:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_ppb91_file = os.path.join(base_dir,data_rc_dir, 'rc_PPB91.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'c' ion = 'iv' # C III c_iii_rc_data = atomneb.read_aeff_ppb91(atom_rc_ppb91_file, atom, ion) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) temperature=np.float64(10000.0) density=np.float64(5000.0) wavelength=4647.42 c_iii_4647_flux = 0.107 abund_c_iii = pyequib.calc_abund_c_iii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=c_iii_4647_flux, c_iii_rc_data=c_iii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(C^3+)/N(H+):', abund_c_iii)
which gives:
N(C^3+)/N(H+): 0.00017502840
N++ Ionic Abundance:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'n' ion = 'iii' # N II n_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) n_ii_rc_data_br = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion, br=True) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) wavelength=4442.02 n_ii_4442_flux = 0.017 abund_n_ii = pyequib.calc_abund_n_ii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=n_ii_4442_flux, n_ii_rc_br=n_ii_rc_data_br, n_ii_rc_data=n_ii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(N^2+)/N(H+):', abund_n_ii)
which gives:
N(N^2+)/N(H+): 0.00069297541
N3+ Ionic Abundance:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_ppb91_file = os.path.join(base_dir,data_rc_dir, 'rc_PPB91.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'n' ion = 'iv' # N III n_iii_rc_data = atomneb.read_aeff_ppb91(atom_rc_ppb91_file, atom, ion) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) wavelength=4640.64 n_iii_4641_flux = 0.245 abund_n_iii = pyequib.calc_abund_n_iii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=n_iii_4641_flux, n_iii_rc_data=n_iii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(N^3+)/N(H+):', abund_n_iii)
which gives:
N(N^3+)/N(H+): 6.3366175e-05
O++ Ionic Abundance:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'o' ion = 'iii' # O II o_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) o_ii_rc_data_br = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion, br=True) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) wavelength=4613.68 o_ii_4614_flux = 0.009 abund_o_ii = pyequib.calc_abund_o_ii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=o_ii_4614_flux, o_ii_rc_br=o_ii_rc_data_br, o_ii_rc_data=o_ii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(O^2+)/N(H+):', abund_o_ii)
which gives:
N(O^2+)/N(H+): 0.0018886330
Ne++ Ionic Abundance:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'ne' ion = 'iii' # Ne II ne_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) atom = 'h' ion = 'ii' # H I h_i_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) wavelength=3777.14 ne_ii_3777_flux = 0.056 abund_ne_ii = pyequib.calc_abund_ne_ii_rl(temperature=temperature, density=density, wavelength=wavelength, line_flux=ne_ii_3777_flux, ne_ii_rc_data=ne_ii_rc_data, h_i_aeff_data=h_i_aeff_data) print('N(Ne^2+)/N(H+):', abund_ne_ii)
which gives:
N(Ne^2+)/N(H+): 0.00043376850
He I Emissivity:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_he_i_file = os.path.join(base_dir,data_rc_dir, 'rc_he_ii_PFSD12.fits') atom = 'he' ion = 'ii' # He I he_i_rc_data = atomneb.read_aeff_he_i_pfsd12(atom_rc_he_i_file, atom, ion) he_i_aeff_data = he_i_rc_data['aeff'][0] temperature=np.float64(10000.0) density=np.float64(5000.0) linenum=10# 4471.50 emiss_he_i = pyequib.calc_emiss_he_i_rl(temperature=temperature, density=density, linenum=linenum, he_i_aeff_data=he_i_aeff_data) print('He I Emissivity:', emiss_he_i)
which gives:
He I Emissivity: 6.3822830e-26
He II Emissivity:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_sh95_file = os.path.join(base_dir,data_rc_dir, 'rc_SH95.fits') atom = 'he' ion = 'iii' # He II he_ii_rc_data = atomneb.read_aeff_sh95(atom_rc_sh95_file, atom, ion) he_ii_aeff_data = he_ii_rc_data['aeff'][0] temperature=np.float64(10000.0) density=np.float64(5000.0) emiss_he_ii = pyequib.calc_emiss_he_ii_rl(temperature=temperature, density=density, he_ii_aeff_data=he_ii_aeff_data) print('He II Emissivity:', emiss_he_ii)
which gives:
He II Emissivity: 1.4989134e-24
C II Emissivity:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom = 'c' ion = 'iii' # C II c_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) temperature=np.float64(10000.0) density=np.float64(5000.0) wavelength=6151.43 emiss_c_ii = pyequib.calc_emiss_c_ii_rl(temperature=temperature, density=density, wavelength=wavelength, c_ii_rc_data=c_ii_rc_data) print('C II Emissivity:', emiss_c_ii)
which gives:
C II Emissivity: 5.4719511e-26
C III Emissivity:
import pyequib import atomneb import numpy as np import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_ppb91_file = os.path.join(base_dir,data_rc_dir, 'rc_PPB91.fits') atom = 'c' ion = 'iv' # C III c_iii_rc_data = atomneb.read_aeff_ppb91(atom_rc_ppb91_file, atom, ion) temperature=np.float64(10000.0) density=np.float64(5000.0) wavelength=4647.42 emiss_c_iii = pyequib.calc_emiss_c_iii_rl(temperature=temperature, density=density, wavelength=wavelength, c_iii_rc_data=c_iii_rc_data) print('C III Emissivity:', emiss_c_iii)
which gives:
C III Emissivity: 7.5749632e-25
N II Emissivity:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom = 'n' ion = 'iii' # N II n_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) n_ii_rc_data_br = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion, br=True) wavelength=4442.02 emiss_n_ii = pyequib.calc_emiss_n_ii_rl(temperature=temperature, density=density, wavelength=wavelength, n_ii_rc_br=n_ii_rc_data_br, n_ii_rc_data=n_ii_rc_data) print('N II Emissivity:', emiss_n_ii)
which gives:
N II Emissivity: 3.0397397e-26
N III Emissivity:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_ppb91_file = os.path.join(base_dir,data_rc_dir, 'rc_PPB91.fits') atom = 'n' ion = 'iv' # N III n_iii_rc_data = atomneb.read_aeff_ppb91(atom_rc_ppb91_file, atom, ion) wavelength=4640.64 emiss_n_iii = pyequib.calc_emiss_n_iii_rl(temperature=temperature, density=density, wavelength=wavelength, n_iii_rc_data=n_iii_rc_data) print('N III Emissivity:', emiss_n_iii)
which gives:
N III Emissivity: 4.7908644e-24
O II Emissivity:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom = 'o' ion = 'iii' # O II o_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) o_ii_rc_data_br = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion, br=True) wavelength=4613.68 emiss_o_ii = pyequib.calc_emiss_o_ii_rl(temperature=temperature, density=density, wavelength=wavelength, o_ii_rc_br=o_ii_rc_data_br, o_ii_rc_data=o_ii_rc_data) print('O II Emissivity:', emiss_o_ii)
which gives:
O II Emissivity: 5.9047319e-27
Ne II Emissivity:
import pyequib import atomneb import os base_dir = 'externals/atomneb' data_rc_dir = os.path.join('atomic-data-rc') atom_rc_all_file = os.path.join(base_dir,data_rc_dir, 'rc_collection.fits') atom = 'ne' ion = 'iii' # Ne II ne_ii_rc_data = atomneb.read_aeff_collection(atom_rc_all_file, atom, ion) wavelength=3777.14 emiss_ne_ii = pyequib.calc_emiss_ne_ii_rl(temperature=temperature, density=density, wavelength=wavelength, ne_ii_rc_data=ne_ii_rc_data) print('Ne II Emissivity:', emiss_ne_ii)
which gives:
Ne II Emissivity: 1.5996881e-25
Reddening Unit has the API functions for estimating logarithmic extinctions at H-beta and dereddening observed fluxes based on reddening laws and extinctions. Here are some examples of using Reddening Unit:
Reddening Law Function:
import pyequib wavelength=6563.0 r_v=3.1 fl=pyequib.redlaw(wavelength, rv=r_v, ext_law='GAL') print('fl(6563):', fl)
which gives:
fl(6563): -0.32013816
Galactic Reddening Law Function based on Seaton (1979), Howarth (1983), & CCM (1983):
import pyequib wavelength=6563.0 r_v=3.1 fl=pyequib.redlaw_gal(wavelength, rv=r_v) print('fl(6563):', fl)
which gives:
fl(6563): -0.32013816
Galactic Reddening Law Function based on Savage & Mathis (1979):
import pyequib wavelength=6563.0 fl=pyequib.redlaw_gal2(wavelength) print('fl(6563):', fl)
which gives:
fl(6563): -0.30925984
Reddening Law Function based on Cardelli, Clayton & Mathis (1989):
import pyequib wavelength=6563.0 r_v=3.1 fl=pyequib.redlaw_ccm(wavelength, rv=r_v) print('fl(6563):', fl)
which gives:
fl(6563): -0.29756615
Galactic Reddening Law Function based on Whitford (1958), Seaton (1977), & Kaler(1976):
import pyequib wavelength=6563.0 fl=pyequib.redlaw_jbk(wavelength) print('fl(6563):', fl)
which gives:
fl(6563): -0.33113684
Reddening Law Function based on Fitzpatrick & Massa (1990), Fitzpatrick (1999), Misselt (1999):
import pyequib wavelength=6563.0 r_v=3.1 fmlaw='AVGLMC' fl=pyequib.redlaw_fm(wavelength, fmlaw=fmlaw, rv=r_v) print('fl(6563):', fl)
which gives:
fl(6563): -0.35053032
Reddening Law Function for the Small Magellanic Cloud:
import pyequib wavelength=6563.0 fl=pyequib.redlaw_smc(wavelength) print('fl(6563):', fl)
which gives:
fl(6563): -0.22659261
Reddening Law Function for the Large Magellanic Cloud:
import pyequib wavelength=6563.0 fl=pyequib.redlaw_lmc(wavelength) print('fl(6563):', fl)
which gives:
fl(6563): -0.30871187
Dereddening Relative Flux:
import pyequib wavelength=6563.0 m_ext=1.0 flux=1.0 ext_law='GAL' r_v=3.1 flux_deredden=pyequib.deredden_relflux(wavelength, flux, m_ext, ext_law=ext_law, rv=r_v) print('dereddened flux(6563)', flux_deredden)
which gives:
dereddened flux(6563) 0.47847785
Dereddening Absolute Flux:
import pyequib wavelength=6563.0 m_ext=1.0 flux=1.0 ext_law='GAL' r_v=3.1 flux_deredden=pyequib.deredden_flux(wavelength, flux, m_ext, ext_law=ext_law, rv=r_v) print('dereddened flux(6563)', flux_deredden)
which gives:
dereddened flux(6563) 4.7847785
For more information on how to use the API functions from the pyEQUIB libray, please read the API Documentation published on equib.github.io/pyEQUIB.
- Danehkar, A. (2020). pyEQUIB Python Package, an addendum to proEQUIB: IDL Library for Plasma Diagnostics and Abundance Analysis. J. Open Source Softw., 5, 2798. doi: 10.21105/joss.02798 ads: 2020JOSS....5.2798D.
- Danehkar, A. (2018). proEQUIB: IDL Library for Plasma Diagnostics and Abundance Analysis. J. Open Source Softw., 3, 899. doi: 10.21105/joss.00899 ads: 2018JOSS....3..899D.
- Danehkar, A. (2018). Bi-Abundance Ionisation Structure of the Wolf-Rayet Planetary Nebula PB 8, PASA, 35, e005. doi: 10.1017/pasa.2018.1 ads: 2018PASA...35....5D.
- Danehkar, A. (2021). Physical and Chemical Properties of Wolf-Rayet Planetary Nebulae, ApJS, 257, 58. doi: 10.3847/1538-4365/ac2310 ads: 2021ApJS..257...58D.
Using the pyEQUIB Python package in a scholarly publication? Please cite thess papers:
@article{Danehkar2020,
author = {{Danehkar}, Ashkbiz},
title = {pyEQUIB Python Package, an addendum to proEQUIB: IDL Library
for Plasma Diagnostics and Abundance Analysis},
journal = {Journal of Open Source Software},
volume = {5},
number = {55},
pages = {2798},
year = {2020},
doi = {10.21105/joss.02798}
}and if you use the proEQUIB IDL library:
@article{Danehkar2018,
author = {{Danehkar}, Ashkbiz},
title = {proEQUIB: IDL Library for Plasma Diagnostics and Abundance Analysis},
journal = {Journal of Open Source Software},
volume = {3},
number = {32},
pages = {899},
year = {2018},
doi = {10.21105/joss.00899}
}| Documentation | https://pyequib.readthedocs.io/ |
| Repository | https://github.com/equib/pyEQUIB |
| Issues & Ideas | https://github.com/equib/pyEQUIB/issues |
| Conda-Forge | https://anaconda.org/conda-forge/pyequib |
| PyPI | https://pypi.org/project/pyequib/ |
| DOI | 10.21105/joss.02798 |
| Archive | 10.5281/zenodo.4287575 |