Lv3_analyze_xspec_pars.py
def model_par(model):
    """
    Given the model, return a list of associated Parameters

    model - name of the model used
    """
    if model == 'powerlaw':
        return ['PhoIndex','norm']
    if model == 'bbodyrad':
        return ['kT','norm']
    if model == 'ezdiskbb':
        return ['T_max','norm']
    if model == 'diskbb':
        return ['Tin','norm']
    if model == 'cutoffpl':
        return ['PhoIndex','HighECut','norm']
    if model == 'fdcut':
        return ['cutoffE','foldE']
    if model == 'relxill':
        return ['gamma','logxi','refl_frac','norm']
    if model == 'gauss':
        return ['LineE','Sigma','norm']
    if model == 'laor':
        return ['lineE','norm']
    else:
        raise ValueError("This is not a model pre-entered into model_par!")

    Given the model, return a list of associated Parameters

    model - name of the model used
    
Given the model, return a list of associated Parameters
model - name of the model used
Given the model return a list of associated Parameters model - name of the model used
def model_par(model):
    if model == 'powerlaw':
        return ['PhoIndex','norm']
    if model == 'bbodyrad':
        return ['kT','norm']
    if model == 'ezdiskbb':
        return ['T_max','norm']
    if model == 'diskbb':
        return ['Tin','norm']
    if model == 'cutoffpl':
        return ['PhoIndex','HighECut','norm']
    if model == 'fdcut':
        return ['cutoffE','foldE']
    if model == 'relxill':
        return ['gamma','logxi','refl_frac','norm']
    if model == 'gauss':
        return ['LineE','Sigma','norm']
    if model == 'laor':
        return ['lineE','norm']
    else:
        raise ValueError("This is not a model pre-entered into model_par!")
def model_par ( model ) : if model == 'powerlaw' : return [ 'PhoIndex' , 'norm' ] if model == 'bbodyrad' : return [ 'kT' , 'norm' ] if model == 'ezdiskbb' : return [ 'T_max' , 'norm' ] if model == 'diskbb' : return [ 'Tin' , 'norm' ] if model == 'cutoffpl' : return [ 'PhoIndex' , 'HighECut' , 'norm' ] if model == 'fdcut' : return [ 'cutoffE' , 'foldE' ] if model == 'relxill' : return [ 'gamma' , 'logxi' , 'refl_frac' , 'norm' ] if model == 'gauss' : return [ 'LineE' , 'Sigma' , 'norm' ] if model == 'laor' : return [ 'lineE' , 'norm' ] else : raise ValueError ( "This is not a model pre-entered into model_par!" )
Given the model, return a list of associated Parameters
model - name of the model used
Given the model return a list of associated Parameters model - name of the model used
"""
    Given the model, return a list of associated Parameters

    model - name of the model used
    """
model