pyEQUIB

pyEQUIB - Python Package for Plasma Diagnostics and Abundance Analysis

Description

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.

Installation

Dependent Python Packages

This package requires the following packages:

NumPy

SciPy

AtomNeb

To get this package with the AtomNeb FITS files, you can simply use git command 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

How to Use

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

Documentation

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.

References

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.

Citation

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}
}

Learn More

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