====== Astrophysical Bolometric Corrections Computational Tool ======

This Python script defines classes for calculating astrophysical bolometric corrections. Bolometric corrections are essential for converting observed magnitudes into absolute luminosities. The script reads from data files containing effective temperature (Teff), surface gravity (logg), and bolometric corrections for various filters, allowing for the interpolation of magnitudes for given stellar parameters. It supports handling different atmospheric parameters (Av and Rv) related to interstellar extinction. This tool is valuable for astronomers and astrophysicists involved in analyzing and interpreting stellar photometric data.

<code python>
from __future__ import print_function
from numpy import array,asscalar,concatenate,empty,float64
from numpy import genfromtxt,shape,squeeze,unique,where
from scipy.interpolate import griddata, pchip

class BCTable(object):
    """Holds a table of Teff, logg, and bolometric corrections."""

    def __init__(self,filename,skip=None):
        f=filename.strip()
        try:
            if skip:
                self.data=genfromtxt(f,names=True,dtype=None,
                                     skip_header=skip[0],skip_footer=skip[1])
                off=0
            else:
                self.data=genfromtxt(f,names=True,dtype=None,skip_header=1)
                off=0
        except IOError:
            print("Failed to open input file: ")
            print(f)

        grid=[]; mags=[]
        Teff=[]; logg=[]
        for d in self.data:
            Teff.append(d['Teff'])
            logg.append(d['logg'])
            grid.append([d['Teff'],d['logg']])
            dl=list(d)
            mags.append([dl[off:]])
        self.Teff=array(sorted(set(Teff)))
        self.logg=array(sorted(set(logg)))
        self.grid=array(grid)
        self.mags=array(mags)
        self.FeH=self.data[0]['FeH']
        self.names=self.data.dtype.names[off:]
        if skip:
            self.Av=self.data['Av'][0]
            self.Rv=self.data['Rv'][0]
        else:
            self.Av=0.0
            self.Rv=0.0
        self.SolBol = 4.75

    def get_mags(self,Teff,logg,logL,interp_method='cubic'):
        if shape(Teff)==shape(logg)==shape(logL):
            Teff=array(Teff,ndmin=1)
            logg=array(logg,ndmin=1)
            logL=array(logL,ndmin=1)
            formats=[float64 for name in self.names]
            BCs=squeeze(griddata(self.grid,self.mags,(Teff,logg),method=interp_method))

        mags=empty((Teff.shape[0], 29),{'names':self.names,'formats':formats})
        for idx, mag in enumerate(mags):
        # for i in range(len(mags)):
            mags[idx]=BCs[idx]
            for name in self.names:
                if name not in ['Teff','logg','FeH','Av','Rv']:
                    mags[idx][name]=self.SolBol-2.5*logL[idx] - mags[idx][name]
        return mags

    def table_check(self):
        count=0
        for i in range(1,len(self.grid)):
            Teff1=self.grid[i-1][0]
            Teff2=self.grid[i][0]
            if Teff1 == Teff2:
                logg1=self.grid[i-1][1]
                logg2=self.grid[i][1]
                dg=logg2-logg1
                if logg2 > logg1 and dg == 0.5:
                    pass
                else:
                    print(Teff1, Teff2)
                    print(logg1, logg2)
                    index=where((self.logg>logg1)&(self.logg<logg2))
                    gnew=self.logg[index]
                    tnew=Teff1
                    result=self.table_interp(tnew,gnew)[0][0]
                    print(result)
                    count+=1
        return count


class BC_Av_Table(object):
    """ Holds an expanded version of BCTable that specifies Av and Rv"""
    def __init__(self,filename):
        def count(filename):
            #first part gets the first line
            with open(filename) as f:
                f.readline()
                f.readline()
                res=f.readline().split()
            #res[0] = '#'
            #res[1] = number of filters
            #res[2] = number of spectra
            #res[3] = number of Av
            #res[4] = number of Rv
            # => number of tables = res[3]*res[4]
            #second part gets the total number of lines
            lines=0
            for line in open(filename):
                lines += 1
            return int(res[2]), int(res[3])*int(res[4]), lines

        def start_of_table(tup,n):
            header=4
            tbl_head=2
            tbl_foot=0
            tbl_rows=tup[0]
            sot = header + (n-1)*(tbl_head+tbl_rows+tbl_foot) + 1
            return sot

        def end_of_table(tup,n):
            sot=start_of_table(tup,n)
            eot=sot+1+tup[0]
            return eot

        def skip_header_footer(tup,n):
            header=start_of_table(tup,n)
            finish=end_of_table(tup,n)
            footer=tup[2]-finish+2*(n-tup[1])
            return header, footer

        x=count(filename)

        self.lines_per_table=x[0]
        self.tables_per_file=x[1]
        self.lines_per_file =x[2]

        self.data=[]
        self.Av=[]
        self.Rv=[]

        for i in range(1,self.tables_per_file+1):
            header,footer=skip_header_footer(x,i)
            d=BCTable(filename,[header,footer])
            self.data.append(d)
            self.Av.append(d.Av)
            self.Rv.append(d.Rv)

        self.Av=array(self.Av)
        self.Rv=asscalar(unique(self.Rv))


    def get_mags(self,Teff,logg,logL):
        x=self.Av
        y=[]
        for d in self.data:
            y.append(d.get_mags(Teff,logg,logL))
        return concatenate(y)

</code>