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Continuum

Continuum

Bases: object

Source code in pyneb/core/continuum.py 
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class Continuum(object):

    def __init__(self):
        """Part of the PyNeb library.

        Mainly based on pySSN library        
        Adapted by V. Gomez-Llanos and C. Morisset, 2018
        """
        self.BE = None
        self.__HI_case = None
        self._set_HI_case('B')
        self.log_ = log_


    def _set_HI_case(self, case='B'):
        """Define the case (A or B) to be used for HI normalization line.

        Not sure that the Free-bound coefficients from Ercolano & Storey 2006 take case A option into account.

        Parameters:
            case (string): 'A' or 'B'
        """            
        if case != self.__HI_case:
            if case == 'A':
                pn.atomicData.setDataFile('h_i_rec_SH95-caseA.hdf5')
                self.HI = None
            elif case == 'B':
                pn.atomicData.setDataFile('h_i_rec_SH95.hdf5')
                self.HI = None
            else:
                raise ValueError('Unkown case {}. Should be A or B'.format(case))
            self.__HI_case = case

    def make_cont_Ercolano(self, tem, case, wl):
        """Adapted from http://adsabs.harvard.edu/abs/2006MNRAS.372.1875E

        Parameters:
            tem : electron temperature [K]. Can not be an array. 
                  In case of tem array, use get_continuum
            case: one of "H", "He1", "He2"
            wl: wavelength [Angstrom]. May be a float or a numpy array

        Returns:
            The continuum [erg/s.cm3/A]
        """
        try:
            _ = (e for e in wl)
        except TypeError:
            wl = np.array([wl])

        n_wl = len(wl)
        hnu =  CST.CLIGHT * 1e8 / wl * CST.HPLANCK  #!phy.c_ang_sec/wl*!phy.h
        if case == 'H':
            tab_T = 10**np.array([2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2,
                                  3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2, 4.3, 4.4, 4.5,
                                  4.6, 4.7, 4.8, 4.9, 5. ])
            D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_H.txt')
        elif case == 'He1':
            tab_T = 10**np.array([2.  , 2.04, 2.08, 2.12, 2.16, 2.2 , 2.24, 2.28, 2.32, 2.36, 2.4 ,
                                  2.44, 2.48, 2.52, 2.56, 2.6 , 2.64, 2.68, 2.72, 2.76, 2.8 , 2.84,
                                  2.88, 2.92, 2.96, 3.  , 3.04, 3.08, 3.12, 3.16, 3.2 , 3.24, 3.28,
                                  3.32, 3.36, 3.4 , 3.44, 3.48, 3.52, 3.56, 3.6 , 3.64, 3.68, 3.72,
                                  3.76, 3.8 , 3.84, 3.88, 3.92, 3.96, 4.  , 4.04, 4.08, 4.12, 4.16,
                                  4.2 , 4.24, 4.28, 4.32, 4.36, 4.4 , 4.44, 4.48, 4.52, 4.56, 4.6 ,
                                  4.64, 4.68, 4.72, 4.76, 4.8 , 4.84, 4.88, 4.92, 4.96, 5.  ])
            D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_He1.txt')
        elif case == 'He2':
            tab_T = 10**np.array([2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2,
                                  3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2, 4.3, 4.4, 4.5,
                                  4.6, 4.7, 4.8, 4.9, 5. ])
            D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_He2.txt')
        else:
            self.log_.warn('Invalid case {0}'.format(case), calling='Continuum.make_cont_Ercolano')
            return np.nan
        if (tem < np.min(tab_T)).any() or (tem > np.max(tab_T)).any():
            self.log_.warn('Invalid temperature {0}'.format(tem), calling='Continuum.make_cont_Ercolano')            
            return np.nan

        BE_E_Ry = D[:,1]
        BE_E_erg = BE_E_Ry * CST.RYD_erg
        BE_E_Thr = BE_E_erg[D[:,0] == 1]
        Delta_E = np.zeros(n_wl)
        for i in np.arange(n_wl):
            DE = hnu[i] - BE_E_Thr
            Delta_E[i] = np.min(DE[DE > 0])

        n_T_sup = np.min(np.where(tab_T >= tem)[0])
        n_T_inf = n_T_sup - 1
        T_sup = tab_T[n_T_sup]
        T_inf = tab_T[n_T_inf]

        BE_coeff_sup = D[:, n_T_sup+2]
        BE_coeff_inf = D[:, n_T_inf+2]

        coeff_sup = interp1d(BE_E_erg, BE_coeff_sup)(hnu)
        coeff_inf = interp1d(BE_E_erg, BE_coeff_inf)(hnu)

        C_interp= (np.log10(tem) - np.log10(T_inf)) / (np.log10(T_sup) - np.log10(T_inf))

        coeff = coeff_sup * C_interp + coeff_inf*(1. - C_interp)

        cont = coeff * 1e-34 * tem**(-1.5) * np.exp(-Delta_E / tem / CST.BOLTZMANN) / wl**2. * CST.CLIGHT * 1e8 # erg/s.cm3/A
        return cont.squeeze()

    def two_photon(self, tem, den, wl):
        """
        Parameters:
            tem: temperature [K]. May be a float or a numpy array
            den: density [cm-3]
            wl: wavelength [Angstrom]. May be a float or a numpy array

        Returns:
            2 photons continuum [erg/s.cm3/A]
        """
        #ToDo : See Schirmer, M. 2016, PASP, 128, 114001 
        try:
            _ = (e for e in wl)
        except TypeError:
            wl = np.array([wl])
        y = 1215.7 / wl
        A = 202.0 * (y * (1. - y) * (1. -(4. * y * (1 - y))**0.8) + 0.88 * ( y * (1 - y))**1.53 * (4. * y * (1 - y))**0.8)
        mask = y > 1.0 # Thanks to Daniel Schaerer for pointing out this potential issue
        A[mask] = 0.
        alfa_eff = 0.838e-13 * (tem / 1e4)**(-0.728) # fit DP de Osterbrock
        q = 5.31e-4 * (tem / 1e4)**(-0.17) # fit DP de Osterbrock
        n_crit = 8.226 / q
        twophot_cont = CST.HPLANCK * CST.CLIGHT * 1e8 / wl**3. * 1215.7 * A / 8.226 * alfa_eff / \
                       (1. + den/n_crit)                
        #twophot_cont[~np.isfinite(twophot_cont)] = 0.
        return twophot_cont

    def gff(self, Z, tem, wl):
        """Adaptated from http://adsabs.harvard.edu/abs/1991CoPhC..66..129S

        Parameters:
            Z: atomic number
            tem: temperature [K]
            wk: wavelength [Angstrom]
        """
        D= np.array([8.986940175e+00, -4.009515855e+00,  8.808871266e-01,
            2.640245111e-02, -4.580645915e-02, -3.568055702e-03,   
            2.827798067e-03,  3.365860195e-04, -8.006936989e-01,
            9.466021705e-01,  9.043402532e-02, -9.608451450e-02,
            -1.885629865e-02,  1.050313890e-02,  2.800889961e-03, 
            -1.078209202e-03, -3.781305103e-01,  1.102726332e-01, 
            -1.543619180e-02,  8.310561114e-03,  2.179620525e-02, 
            4.259726289e-03, -4.181588794e-03, -1.770208330e-03,   
            1.877213132e-02, -1.004885705e-01, -5.483366378e-02,   
            -4.520154409e-03,  8.366530426e-03,  3.700273930e-03, 
            6.889320423e-04,  9.460313195e-05,  7.300158392e-02,   
            3.576785497e-03, -4.545307025e-03, -1.017965604e-02,   
            -9.530211924e-03, -3.450186162e-03,  1.040482914e-03, 
            1.407073544e-03, -1.744671550e-03,  2.864013856e-02,   
            1.903394837e-02,  7.091074494e-03, -9.668371391e-04,   
            -2.999107465e-03, -1.820642230e-03, -3.874082085e-04, 
            -1.707268366e-02, -4.694254776e-03,  1.311691517e-03, 
            5.316703136e-03,  5.178193095e-03,  2.451228935e-03,   
            -2.277321615e-05, -8.182359057e-04,  2.567331664e-04, 
            -9.155339970e-03, -6.997479192e-03, -3.571518641e-03, 
            -2.096101038e-04,  1.553822487e-03,  1.509584686e-03, 
            6.212627837e-04,  4.098322531e-03,  1.635218463e-03,   
            -5.918883504e-04, -2.333091048e-03, -2.484138313e-03, 
            -1.359996060e-03, -5.371426147e-05,  5.553549563e-04, 
            3.837562402e-05,  2.938325230e-03,  2.393747064e-03,   
            1.328839809e-03,  9.135013312e-05, -7.137252303e-04,   
            -7.656848158e-04, -3.504683798e-04, -8.491991820e-04, 
            -3.615327726e-04,  3.148015257e-04,  8.909207650e-04, 
            9.869737522e-04,  6.134671184e-04,  1.068883394e-04,   
            -2.046080100e-04 ])

        try:
            _ = (e for e in wl)
        except TypeError:
            wl = np.array([wl])


        XLF = np.log10(CST.CLIGHT * 1e8 / wl)
        N_wl = len(wl)
        G = np.zeros(N_wl)
        D = D.reshape(11, 8)
        B = np.zeros(11)
        C = np.zeros(8)

        XLRKT = 5.1983649 - np.log10(tem)
        TXG = 0.66666667 * (2.0 * np.log10(Z) + XLRKT)

        for j in np.arange(7):
            B[10] = D[10, j]
            B[9] = TXG * B[10] + D[9, j]
            for IR in np.arange(8)[::-1]:
                B[IR] = TXG * B[IR+1] - B[IR+2] + D[IR, j]
            C[j] = 0.25 * (B[0] - B[2])               


        CON=0.72727273 * XLRKT - 10.376127  

        for i in np.arange(N_wl):
            TXU = 0.72727273 * XLF[i] + CON 
            B[7] = C[7]
            B[6] = TXU * B[7] + C[6] 
            for IR in np.arange(5)[::-1]: 
                B[IR] = TXU * B[IR+1] - B[IR+2] + C[IR]
            G[i] = B[0] - B[2]

        return G.squeeze()

    def FreeFree(self, tem, wl, He1_H=0., He2_H=0., tem_HeI=None, tem_HeII=None):
        """
        Parameters:
            tem:
            wl:
            He1_H (float) default: 0.
            He2_H (float) default: 0.
            tem_HeI (float) default: None.
            tem_HeII (float) default: None.
        """
        if tem_HeI is None:
            tem_HeI = tem
        if tem_HeII is None:
            tem_HeII = tem

        gff_HI = self.gff(1., tem, wl)
        gff_HeI = self.gff(1., tem_HeI, wl)
        gff_HeII = self.gff(4., tem_HeII, wl)

        FF_cont = (6.8391014e-38 * CST.CLIGHT * 1e8 / wl**2. * (
                        1.0**2. / np.sqrt(tem) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem) * gff_HI + 
                        He1_H * 1.0**2./ np.sqrt(tem_HeI) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem_HeI) * gff_HeI  + 
                        He2_H* 2.0**2. / np.sqrt(tem_HeII) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem_HeII) * gff_HeII))
        return FF_cont

    def _get_continuum1(self, tem, den, He1_H=0., He2_H=0., wl=None, 
                      cont_HI=True, cont_HeI=True, cont_HeII=True, 
                      cont_2p=True, cont_ff=True):
        """
        Type of continuum to take into acount defined a boolean, defaults are True

        Parameters:
            tem: temperature [K]. May be a float or an iterable
            den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem
            He1_H and He2_H: He+/H+ and He++/H+ abundances. Default = 0.0
            wl: wavelengths: May be an array
            cont_HI (bool) default: True
            cont_HeI (bool) default: True
            cont_HeII (bool) default:True using B. Ercolano 2006 data
            cont_2p (bool) default: True 2 photons, using D. Pequignot fit to Osterbrock
            cont_ff (bool) default: 

        Returns:
            The resulting continuum [erg/s.cm3/A]
        """

        cont = 0.
        if cont_HI:
            cont += self.make_cont_Ercolano(tem = tem, case = 'H', wl = wl)
        if cont_HeI and He1_H > 0.:
            cont += He1_H * self.make_cont_Ercolano(tem = tem, case = 'He1', wl = wl)
        if cont_HeII and He2_H > 0:
            cont += He2_H * self.make_cont_Ercolano(tem = tem, case = 'He2', wl = wl)
        if cont_2p:
            cont += self.two_photon(tem = tem, den = den, wl = wl)
        if cont_ff:
            cont += self.FreeFree(tem = tem, wl = wl, He1_H=He1_H, He2_H=He2_H)

        return cont

    def get_continuum(self, tem, den, He1_H=0., He2_H=0., wl=np.array([3500, 3600, 3700, 3800, 3900]), 
                      cont_HI=True, cont_HeI=True, cont_HeII=True, 
                      cont_2p=True, cont_ff=True, HI_label='11_2'):
        """

        Type of continuum to take into acount defined a boolean, defaults are True

        Parameters:
            tem: temperature [K]. May be a float or an iterable.
            den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem.
            He1_H (float):  He+/H+ abundance. Default = 0.0
            He2_H (float): He++/H+ abundances.  Default = 0.0
            wl (np.array): Wavelengths Default = np.array([3500, 3600, 3700, 3800, 3900])
            cont_HI (bool): using B. Ercolano 2006 data. Default: True
            cont_HeI (bool): using B. Ercolano 2006 data. Default: True
            cont_HeII (bool): using B. Ercolano 2006 data. Default: True
            cont_2p (bool): 2 photons, using D. Pequignot fit to Osterbrock. Default: True
            cont_ff (bool): from Storey & Hummer 1991. Default: True

            HI_label (str): HI label to normalize the continuum. If None, no normalization is done. Default: '11_2'

        Returns:
            The resulting continuum. Unit [A-1] if normalized, [erg/s.cm3/A] otherwise

        Exemple of use:
            C = pn.Continuum()
            wl = np.arange(3500, 4000, 1)
            cont = C.get_continuum(tem=1e4, den=1e2, He1_H=0.08, He2_H=0.02, wl=wl)
            plt.plot(wl, cont)
        """
        try:
            _ = (e for e in tem)
            T_iterable = True
            try:
                _ = (e for e in den)
            except:
                den = np.ones_like(tem) * den
            try:
                _ = (e for e in He1_H)
            except:
                He1_H = np.ones_like(tem) * He1_H
            try:
                _ = (e for e in He2_H)
            except:
                He2_H = np.ones_like(tem) * He2_H

        except TypeError:
            T_iterable = False
        if HI_label is None:
            norm = 1.0
        else:
            if self.HI is None:
                self.HI = pn.RecAtom('H',1)
            norm = self.HI.getEmissivity(tem, den, label = HI_label, product=False)

        if T_iterable:
            cont = np.array(list(map(lambda t, d, He1_H_1,He2_H_1 : self._get_continuum1(t, d, 
                                                                                  He1_H=He1_H_1, 
                                                                                  He2_H=He2_H_1, 
                                                                                  wl=wl, 
                                                                                  cont_HI=cont_HI, 
                                                                                  cont_HeI=cont_HeI, 
                                                                                  cont_HeII=cont_HeII, 
                                                                                  cont_2p=cont_2p, 
                                                                                  cont_ff=cont_ff), 
                                     tem, den, He1_H, He2_H))).T
            return cont.squeeze()/norm
        else:
            cont = self._get_continuum1(tem, den, He1_H=He1_H, He2_H=He2_H, wl=wl, 
                                        cont_HI=cont_HI, cont_HeI=cont_HeI, cont_HeII=cont_HeII, 
                                        cont_2p=cont_2p, cont_ff=cont_ff)
            return cont/norm

    def BJ_HI(self, tem, den, He1_H, He2_H, wl_bbj = 3643, wl_abj = 3861, HI_label='11_2'):
        """
        Parameters:
            tem: temperature [K]. May be a float or an iterable
            den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem
            He1_H: He+/H+ abundances.
            He2_H: He++/H+ abundances.

            wl_bbj (int): wavelengths below the jump resp. Default: 3643
            wl_abj (int): wavelengths above the jump resp. Defaults: 3861
            HI_label (str): reference HI line to normalize the jump. Default is 11_2

        Returns:
            The Balmer Jump (may be any other jump if wl are changed) normalized to the HI line
        """

        fl_bbj, fl_abj = self.get_continuum(tem = tem, den = den, He1_H = He1_H, 
                                            He2_H = He2_H, wl = np.array([wl_bbj, wl_abj]),
                                            HI_label=HI_label)

        BJ_HI = fl_bbj - fl_abj
        return BJ_HI

    def T_BJ(self, BJ_HI, den, He1_H, He2_H, wl_bbj = 3643, wl_abj = 3861, HI_label='11_2',
             T_min=5e2, T_max=3e4):
        """
        Parameters:
            BJ_HI: Balmer Jump (may be any other jump if wl are changed) normalized to the HI line
            den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem
            He1_H: He+/H+ abundances.
            He2_H: He++/H+ abundances.
            wl_bbj (int): wavelengths below the jump resp. Default: 3643
            wl_abj (int): wavelengths above the jump resp. Defaults: 3861
            HI_label: reference HI line to normalize the jump. Default: 11_2

            T_min: minimum temperature [K] for the root finding exploration. Default: 5e2
            T_max: maximum temperature [K] for the root finding exploration. Default: 3e4

        Returns:
            Temperature [K] corresponding to the jump
        """
        try:
            _ = (e for e in BJ_HI)
            BJ_iterable = True
        except TypeError:
            BJ_iterable = False

        def f2minimize(tem, BJ_HI):
            f = self.BJ_HI(tem, den=den, He1_H=He1_H, He2_H=He2_H, wl_bbj = wl_bbj, wl_abj=wl_abj, HI_label=HI_label) - BJ_HI
            return f

        def f2minimize_i(tem, i):
            f = self.BJ_HI(tem, den=den.ravel()[i], He1_H=He1_H.ravel()[i], He2_H=He2_H.ravel()[i], 
                           wl_bbj = wl_bbj, wl_abj=wl_abj, HI_label=HI_label) - BJ_HI.ravel()[i]
            return f

        if BJ_iterable:
            T_BJ = np.array(list(map(lambda i: optimize.brentq(f2minimize_i, T_min, T_max, args=i), np.arange(len(BJ_HI.ravel()))))).T
            return T_BJ.squeeze()
        else:
            T_BJ = optimize.brentq(f2minimize, T_min, T_max, args=BJ_HI)
            return T_BJ


    def T_BJ_Liu(self, BJ_H11, He1_H, He2_H):
        """
        From Liu, X.-W., Luo, S.-G., Barlow, M. J., Danziger, I. J., & Storey, P. J.
        2001, MNRAS, 327, 141-168

        Parameters:
            BJ_H11: Balmer Jump normalized to the H11 line
            He1_H: He+/H+ abundances.
            He2_H: He++/H+ abundances.
        """
        T = 368 * (1 + 0.259 * He1_H + 3.409 * He2_H) * (BJ_H11)**(-3./2)
        return T

BJ_HI(tem, den, He1_H, He2_H, wl_bbj=3643, wl_abj=3861, HI_label='11_2')

Parameters:

Name Type Description Default
tem

temperature [K]. May be a float or an iterable

 required
den

density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem

 required
He1_H

He+/H+ abundances.

 required
He2_H

He++/H+ abundances.

 required
wl_bbj int

wavelengths below the jump resp. Default: 3643

 3643
wl_abj int

wavelengths above the jump resp. Defaults: 3861

 3861
HI_label str

reference HI line to normalize the jump. Default is 11_2

 '11_2'

Returns:

Type Description

The Balmer Jump (may be any other jump if wl are changed) normalized to the HI line
Source code in pyneb/core/continuum.py 
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def BJ_HI(self, tem, den, He1_H, He2_H, wl_bbj = 3643, wl_abj = 3861, HI_label='11_2'):
    """
    Parameters:
        tem: temperature [K]. May be a float or an iterable
        den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem
        He1_H: He+/H+ abundances.
        He2_H: He++/H+ abundances.

        wl_bbj (int): wavelengths below the jump resp. Default: 3643
        wl_abj (int): wavelengths above the jump resp. Defaults: 3861
        HI_label (str): reference HI line to normalize the jump. Default is 11_2

    Returns:
        The Balmer Jump (may be any other jump if wl are changed) normalized to the HI line
    """

    fl_bbj, fl_abj = self.get_continuum(tem = tem, den = den, He1_H = He1_H, 
                                        He2_H = He2_H, wl = np.array([wl_bbj, wl_abj]),
                                        HI_label=HI_label)

    BJ_HI = fl_bbj - fl_abj
    return BJ_HI

FreeFree(tem, wl, He1_H=0.0, He2_H=0.0, tem_HeI=None, tem_HeII=None)

Parameters:

Name Type Description Default
tem
required
wl
required
He1_H float) default

0.

 0.0
He2_H float) default

0.

 0.0
tem_HeI float) default

None.

 None
tem_HeII float) default

None.

 None
Source code in pyneb/core/continuum.py 
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def FreeFree(self, tem, wl, He1_H=0., He2_H=0., tem_HeI=None, tem_HeII=None):
    """
    Parameters:
        tem:
        wl:
        He1_H (float) default: 0.
        He2_H (float) default: 0.
        tem_HeI (float) default: None.
        tem_HeII (float) default: None.
    """
    if tem_HeI is None:
        tem_HeI = tem
    if tem_HeII is None:
        tem_HeII = tem

    gff_HI = self.gff(1., tem, wl)
    gff_HeI = self.gff(1., tem_HeI, wl)
    gff_HeII = self.gff(4., tem_HeII, wl)

    FF_cont = (6.8391014e-38 * CST.CLIGHT * 1e8 / wl**2. * (
                    1.0**2. / np.sqrt(tem) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem) * gff_HI + 
                    He1_H * 1.0**2./ np.sqrt(tem_HeI) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem_HeI) * gff_HeI  + 
                    He2_H* 2.0**2. / np.sqrt(tem_HeII) * np.exp(-CST.HPLANCK*CST.CLIGHT*1e8/wl/CST.BOLTZMANN/tem_HeII) * gff_HeII))
    return FF_cont

T_BJ(BJ_HI, den, He1_H, He2_H, wl_bbj=3643, wl_abj=3861, HI_label='11_2', T_min=500.0, T_max=30000.0)

Parameters:

Name Type Description Default
BJ_HI

Balmer Jump (may be any other jump if wl are changed) normalized to the HI line

 required
den

density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem

 required
He1_H

He+/H+ abundances.

 required
He2_H

He++/H+ abundances.

 required
wl_bbj int

wavelengths below the jump resp. Default: 3643

 3643
wl_abj int

wavelengths above the jump resp. Defaults: 3861

 3861
HI_label

reference HI line to normalize the jump. Default: 11_2

 '11_2'
T_min

minimum temperature [K] for the root finding exploration. Default: 5e2

 500.0
T_max

maximum temperature [K] for the root finding exploration. Default: 3e4

 30000.0

Returns:

Type Description

Temperature [K] corresponding to the jump
Source code in pyneb/core/continuum.py 
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def T_BJ(self, BJ_HI, den, He1_H, He2_H, wl_bbj = 3643, wl_abj = 3861, HI_label='11_2',
         T_min=5e2, T_max=3e4):
    """
    Parameters:
        BJ_HI: Balmer Jump (may be any other jump if wl are changed) normalized to the HI line
        den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem
        He1_H: He+/H+ abundances.
        He2_H: He++/H+ abundances.
        wl_bbj (int): wavelengths below the jump resp. Default: 3643
        wl_abj (int): wavelengths above the jump resp. Defaults: 3861
        HI_label: reference HI line to normalize the jump. Default: 11_2

        T_min: minimum temperature [K] for the root finding exploration. Default: 5e2
        T_max: maximum temperature [K] for the root finding exploration. Default: 3e4

    Returns:
        Temperature [K] corresponding to the jump
    """
    try:
        _ = (e for e in BJ_HI)
        BJ_iterable = True
    except TypeError:
        BJ_iterable = False

    def f2minimize(tem, BJ_HI):
        f = self.BJ_HI(tem, den=den, He1_H=He1_H, He2_H=He2_H, wl_bbj = wl_bbj, wl_abj=wl_abj, HI_label=HI_label) - BJ_HI
        return f

    def f2minimize_i(tem, i):
        f = self.BJ_HI(tem, den=den.ravel()[i], He1_H=He1_H.ravel()[i], He2_H=He2_H.ravel()[i], 
                       wl_bbj = wl_bbj, wl_abj=wl_abj, HI_label=HI_label) - BJ_HI.ravel()[i]
        return f

    if BJ_iterable:
        T_BJ = np.array(list(map(lambda i: optimize.brentq(f2minimize_i, T_min, T_max, args=i), np.arange(len(BJ_HI.ravel()))))).T
        return T_BJ.squeeze()
    else:
        T_BJ = optimize.brentq(f2minimize, T_min, T_max, args=BJ_HI)
        return T_BJ

T_BJ_Liu(BJ_H11, He1_H, He2_H)

From Liu, X.-W., Luo, S.-G., Barlow, M. J., Danziger, I. J., & Storey, P. J. 2001, MNRAS, 327, 141-168

Parameters:

Name Type Description Default
BJ_H11

Balmer Jump normalized to the H11 line

 required
He1_H

He+/H+ abundances.

 required
He2_H

He++/H+ abundances.

 required
Source code in pyneb/core/continuum.py 
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def T_BJ_Liu(self, BJ_H11, He1_H, He2_H):
    """
    From Liu, X.-W., Luo, S.-G., Barlow, M. J., Danziger, I. J., & Storey, P. J.
    2001, MNRAS, 327, 141-168

    Parameters:
        BJ_H11: Balmer Jump normalized to the H11 line
        He1_H: He+/H+ abundances.
        He2_H: He++/H+ abundances.
    """
    T = 368 * (1 + 0.259 * He1_H + 3.409 * He2_H) * (BJ_H11)**(-3./2)
    return T

__init__()

Part of the PyNeb library.

Mainly based on pySSN library
Adapted by V. Gomez-Llanos and C. Morisset, 2018

Source code in pyneb/core/continuum.py 
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def __init__(self):
    """Part of the PyNeb library.

    Mainly based on pySSN library        
    Adapted by V. Gomez-Llanos and C. Morisset, 2018
    """
    self.BE = None
    self.__HI_case = None
    self._set_HI_case('B')
    self.log_ = log_

get_continuum(tem, den, He1_H=0.0, He2_H=0.0, wl=np.array([3500, 3600, 3700, 3800, 3900]), cont_HI=True, cont_HeI=True, cont_HeII=True, cont_2p=True, cont_ff=True, HI_label='11_2')

Type of continuum to take into acount defined a boolean, defaults are True

Parameters:

Name Type Description Default
tem

temperature [K]. May be a float or an iterable.

 required
den

density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem.

 required
He1_H float

He+/H+ abundance. Default = 0.0

 0.0
He2_H float

He++/H+ abundances. Default = 0.0

 0.0
wl np.array

Wavelengths Default = np.array([3500, 3600, 3700, 3800, 3900])

 np.array([3500, 3600, 3700, 3800, 3900])
cont_HI bool

using B. Ercolano 2006 data. Default: True

 True
cont_HeI bool

using B. Ercolano 2006 data. Default: True

 True
cont_HeII bool

using B. Ercolano 2006 data. Default: True

 True
cont_2p bool

2 photons, using D. Pequignot fit to Osterbrock. Default: True

 True
cont_ff bool

from Storey & Hummer 1991. Default: True

 True
HI_label str

HI label to normalize the continuum. If None, no normalization is done. Default: '11_2'

 '11_2'

Returns:

Type Description

The resulting continuum. Unit [A-1] if normalized, [erg/s.cm3/A] otherwise
Exemple of use

C = pn.Continuum() wl = np.arange(3500, 4000, 1) cont = C.get_continuum(tem=1e4, den=1e2, He1_H=0.08, He2_H=0.02, wl=wl) plt.plot(wl, cont)

Source code in pyneb/core/continuum.py 
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def get_continuum(self, tem, den, He1_H=0., He2_H=0., wl=np.array([3500, 3600, 3700, 3800, 3900]), 
                  cont_HI=True, cont_HeI=True, cont_HeII=True, 
                  cont_2p=True, cont_ff=True, HI_label='11_2'):
    """

    Type of continuum to take into acount defined a boolean, defaults are True

    Parameters:
        tem: temperature [K]. May be a float or an iterable.
        den: density [cm-3]. May be a float or an iterable. If iterable, must have same size than tem.
        He1_H (float):  He+/H+ abundance. Default = 0.0
        He2_H (float): He++/H+ abundances.  Default = 0.0
        wl (np.array): Wavelengths Default = np.array([3500, 3600, 3700, 3800, 3900])
        cont_HI (bool): using B. Ercolano 2006 data. Default: True
        cont_HeI (bool): using B. Ercolano 2006 data. Default: True
        cont_HeII (bool): using B. Ercolano 2006 data. Default: True
        cont_2p (bool): 2 photons, using D. Pequignot fit to Osterbrock. Default: True
        cont_ff (bool): from Storey & Hummer 1991. Default: True

        HI_label (str): HI label to normalize the continuum. If None, no normalization is done. Default: '11_2'

    Returns:
        The resulting continuum. Unit [A-1] if normalized, [erg/s.cm3/A] otherwise

    Exemple of use:
        C = pn.Continuum()
        wl = np.arange(3500, 4000, 1)
        cont = C.get_continuum(tem=1e4, den=1e2, He1_H=0.08, He2_H=0.02, wl=wl)
        plt.plot(wl, cont)
    """
    try:
        _ = (e for e in tem)
        T_iterable = True
        try:
            _ = (e for e in den)
        except:
            den = np.ones_like(tem) * den
        try:
            _ = (e for e in He1_H)
        except:
            He1_H = np.ones_like(tem) * He1_H
        try:
            _ = (e for e in He2_H)
        except:
            He2_H = np.ones_like(tem) * He2_H

    except TypeError:
        T_iterable = False
    if HI_label is None:
        norm = 1.0
    else:
        if self.HI is None:
            self.HI = pn.RecAtom('H',1)
        norm = self.HI.getEmissivity(tem, den, label = HI_label, product=False)

    if T_iterable:
        cont = np.array(list(map(lambda t, d, He1_H_1,He2_H_1 : self._get_continuum1(t, d, 
                                                                              He1_H=He1_H_1, 
                                                                              He2_H=He2_H_1, 
                                                                              wl=wl, 
                                                                              cont_HI=cont_HI, 
                                                                              cont_HeI=cont_HeI, 
                                                                              cont_HeII=cont_HeII, 
                                                                              cont_2p=cont_2p, 
                                                                              cont_ff=cont_ff), 
                                 tem, den, He1_H, He2_H))).T
        return cont.squeeze()/norm
    else:
        cont = self._get_continuum1(tem, den, He1_H=He1_H, He2_H=He2_H, wl=wl, 
                                    cont_HI=cont_HI, cont_HeI=cont_HeI, cont_HeII=cont_HeII, 
                                    cont_2p=cont_2p, cont_ff=cont_ff)
        return cont/norm

gff(Z, tem, wl)

Adaptated from http://adsabs.harvard.edu/abs/1991CoPhC..66..129S

Parameters:

Name Type Description Default
Z

atomic number

 required
tem

temperature [K]

 required
wk

wavelength [Angstrom]

 required
Source code in pyneb/core/continuum.py 
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def gff(self, Z, tem, wl):
    """Adaptated from http://adsabs.harvard.edu/abs/1991CoPhC..66..129S

    Parameters:
        Z: atomic number
        tem: temperature [K]
        wk: wavelength [Angstrom]
    """
    D= np.array([8.986940175e+00, -4.009515855e+00,  8.808871266e-01,
        2.640245111e-02, -4.580645915e-02, -3.568055702e-03,   
        2.827798067e-03,  3.365860195e-04, -8.006936989e-01,
        9.466021705e-01,  9.043402532e-02, -9.608451450e-02,
        -1.885629865e-02,  1.050313890e-02,  2.800889961e-03, 
        -1.078209202e-03, -3.781305103e-01,  1.102726332e-01, 
        -1.543619180e-02,  8.310561114e-03,  2.179620525e-02, 
        4.259726289e-03, -4.181588794e-03, -1.770208330e-03,   
        1.877213132e-02, -1.004885705e-01, -5.483366378e-02,   
        -4.520154409e-03,  8.366530426e-03,  3.700273930e-03, 
        6.889320423e-04,  9.460313195e-05,  7.300158392e-02,   
        3.576785497e-03, -4.545307025e-03, -1.017965604e-02,   
        -9.530211924e-03, -3.450186162e-03,  1.040482914e-03, 
        1.407073544e-03, -1.744671550e-03,  2.864013856e-02,   
        1.903394837e-02,  7.091074494e-03, -9.668371391e-04,   
        -2.999107465e-03, -1.820642230e-03, -3.874082085e-04, 
        -1.707268366e-02, -4.694254776e-03,  1.311691517e-03, 
        5.316703136e-03,  5.178193095e-03,  2.451228935e-03,   
        -2.277321615e-05, -8.182359057e-04,  2.567331664e-04, 
        -9.155339970e-03, -6.997479192e-03, -3.571518641e-03, 
        -2.096101038e-04,  1.553822487e-03,  1.509584686e-03, 
        6.212627837e-04,  4.098322531e-03,  1.635218463e-03,   
        -5.918883504e-04, -2.333091048e-03, -2.484138313e-03, 
        -1.359996060e-03, -5.371426147e-05,  5.553549563e-04, 
        3.837562402e-05,  2.938325230e-03,  2.393747064e-03,   
        1.328839809e-03,  9.135013312e-05, -7.137252303e-04,   
        -7.656848158e-04, -3.504683798e-04, -8.491991820e-04, 
        -3.615327726e-04,  3.148015257e-04,  8.909207650e-04, 
        9.869737522e-04,  6.134671184e-04,  1.068883394e-04,   
        -2.046080100e-04 ])

    try:
        _ = (e for e in wl)
    except TypeError:
        wl = np.array([wl])


    XLF = np.log10(CST.CLIGHT * 1e8 / wl)
    N_wl = len(wl)
    G = np.zeros(N_wl)
    D = D.reshape(11, 8)
    B = np.zeros(11)
    C = np.zeros(8)

    XLRKT = 5.1983649 - np.log10(tem)
    TXG = 0.66666667 * (2.0 * np.log10(Z) + XLRKT)

    for j in np.arange(7):
        B[10] = D[10, j]
        B[9] = TXG * B[10] + D[9, j]
        for IR in np.arange(8)[::-1]:
            B[IR] = TXG * B[IR+1] - B[IR+2] + D[IR, j]
        C[j] = 0.25 * (B[0] - B[2])               


    CON=0.72727273 * XLRKT - 10.376127  

    for i in np.arange(N_wl):
        TXU = 0.72727273 * XLF[i] + CON 
        B[7] = C[7]
        B[6] = TXU * B[7] + C[6] 
        for IR in np.arange(5)[::-1]: 
            B[IR] = TXU * B[IR+1] - B[IR+2] + C[IR]
        G[i] = B[0] - B[2]

    return G.squeeze()

make_cont_Ercolano(tem, case, wl)

Adapted from http://adsabs.harvard.edu/abs/2006MNRAS.372.1875E

Parameters:

Name Type Description Default
tem

electron temperature [K]. Can not be an array. In case of tem array, use get_continuum

 required
case

one of "H", "He1", "He2"

 required
wl

wavelength [Angstrom]. May be a float or a numpy array

 required

Returns:

Type Description

The continuum [erg/s.cm3/A]
Source code in pyneb/core/continuum.py 
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def make_cont_Ercolano(self, tem, case, wl):
    """Adapted from http://adsabs.harvard.edu/abs/2006MNRAS.372.1875E

    Parameters:
        tem : electron temperature [K]. Can not be an array. 
              In case of tem array, use get_continuum
        case: one of "H", "He1", "He2"
        wl: wavelength [Angstrom]. May be a float or a numpy array

    Returns:
        The continuum [erg/s.cm3/A]
    """
    try:
        _ = (e for e in wl)
    except TypeError:
        wl = np.array([wl])

    n_wl = len(wl)
    hnu =  CST.CLIGHT * 1e8 / wl * CST.HPLANCK  #!phy.c_ang_sec/wl*!phy.h
    if case == 'H':
        tab_T = 10**np.array([2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2,
                              3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2, 4.3, 4.4, 4.5,
                              4.6, 4.7, 4.8, 4.9, 5. ])
        D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_H.txt')
    elif case == 'He1':
        tab_T = 10**np.array([2.  , 2.04, 2.08, 2.12, 2.16, 2.2 , 2.24, 2.28, 2.32, 2.36, 2.4 ,
                              2.44, 2.48, 2.52, 2.56, 2.6 , 2.64, 2.68, 2.72, 2.76, 2.8 , 2.84,
                              2.88, 2.92, 2.96, 3.  , 3.04, 3.08, 3.12, 3.16, 3.2 , 3.24, 3.28,
                              3.32, 3.36, 3.4 , 3.44, 3.48, 3.52, 3.56, 3.6 , 3.64, 3.68, 3.72,
                              3.76, 3.8 , 3.84, 3.88, 3.92, 3.96, 4.  , 4.04, 4.08, 4.12, 4.16,
                              4.2 , 4.24, 4.28, 4.32, 4.36, 4.4 , 4.44, 4.48, 4.52, 4.56, 4.6 ,
                              4.64, 4.68, 4.72, 4.76, 4.8 , 4.84, 4.88, 4.92, 4.96, 5.  ])
        D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_He1.txt')
    elif case == 'He2':
        tab_T = 10**np.array([2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3. , 3.1, 3.2,
                              3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4. , 4.1, 4.2, 4.3, 4.4, 4.5,
                              4.6, 4.7, 4.8, 4.9, 5. ])
        D = np.loadtxt(ROOT_DIR + '/' + 'atomic_data/coeff_ercolano_He2.txt')
    else:
        self.log_.warn('Invalid case {0}'.format(case), calling='Continuum.make_cont_Ercolano')
        return np.nan
    if (tem < np.min(tab_T)).any() or (tem > np.max(tab_T)).any():
        self.log_.warn('Invalid temperature {0}'.format(tem), calling='Continuum.make_cont_Ercolano')            
        return np.nan

    BE_E_Ry = D[:,1]
    BE_E_erg = BE_E_Ry * CST.RYD_erg
    BE_E_Thr = BE_E_erg[D[:,0] == 1]
    Delta_E = np.zeros(n_wl)
    for i in np.arange(n_wl):
        DE = hnu[i] - BE_E_Thr
        Delta_E[i] = np.min(DE[DE > 0])

    n_T_sup = np.min(np.where(tab_T >= tem)[0])
    n_T_inf = n_T_sup - 1
    T_sup = tab_T[n_T_sup]
    T_inf = tab_T[n_T_inf]

    BE_coeff_sup = D[:, n_T_sup+2]
    BE_coeff_inf = D[:, n_T_inf+2]

    coeff_sup = interp1d(BE_E_erg, BE_coeff_sup)(hnu)
    coeff_inf = interp1d(BE_E_erg, BE_coeff_inf)(hnu)

    C_interp= (np.log10(tem) - np.log10(T_inf)) / (np.log10(T_sup) - np.log10(T_inf))

    coeff = coeff_sup * C_interp + coeff_inf*(1. - C_interp)

    cont = coeff * 1e-34 * tem**(-1.5) * np.exp(-Delta_E / tem / CST.BOLTZMANN) / wl**2. * CST.CLIGHT * 1e8 # erg/s.cm3/A
    return cont.squeeze()

two_photon(tem, den, wl)

Parameters:

Name Type Description Default
tem

temperature [K]. May be a float or a numpy array

 required
den

density [cm-3]

 required
wl

wavelength [Angstrom]. May be a float or a numpy array

 required

Returns:

Type Description

2 photons continuum [erg/s.cm3/A]
Source code in pyneb/core/continuum.py 
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def two_photon(self, tem, den, wl):
    """
    Parameters:
        tem: temperature [K]. May be a float or a numpy array
        den: density [cm-3]
        wl: wavelength [Angstrom]. May be a float or a numpy array

    Returns:
        2 photons continuum [erg/s.cm3/A]
    """
    #ToDo : See Schirmer, M. 2016, PASP, 128, 114001 
    try:
        _ = (e for e in wl)
    except TypeError:
        wl = np.array([wl])
    y = 1215.7 / wl
    A = 202.0 * (y * (1. - y) * (1. -(4. * y * (1 - y))**0.8) + 0.88 * ( y * (1 - y))**1.53 * (4. * y * (1 - y))**0.8)
    mask = y > 1.0 # Thanks to Daniel Schaerer for pointing out this potential issue
    A[mask] = 0.
    alfa_eff = 0.838e-13 * (tem / 1e4)**(-0.728) # fit DP de Osterbrock
    q = 5.31e-4 * (tem / 1e4)**(-0.17) # fit DP de Osterbrock
    n_crit = 8.226 / q
    twophot_cont = CST.HPLANCK * CST.CLIGHT * 1e8 / wl**3. * 1215.7 * A / 8.226 * alfa_eff / \
                   (1. + den/n_crit)                
    #twophot_cont[~np.isfinite(twophot_cont)] = 0.
    return twophot_cont