def isochrone(self,age,feh=<NUM_LIT:0.0>,minm=None,maxm=None,dm=<NUM_LIT>,<EOL>return_df=True,distance=None,AV=<NUM_LIT:0.0>):
if minm is None:<EOL><INDENT>minm = self.minmass<EOL><DEDENT>if maxm is None:<EOL><INDENT>maxm = self.maxmass<EOL><DEDENT>ms = np.arange(minm,maxm,dm)<EOL>ages = np.ones(ms.shape)*age<EOL>Ms = self.mass(ms,ages,feh)<EOL>Rs = self.radius(ms,ages,feh)<EOL>logLs = self.logL(ms,ages,feh)<EOL>loggs = self.logg(ms,ages,feh)<EOL>Teffs = self.Teff(ms,ages,feh)<EOL>mags = {band:self.mag[band](ms,ages,feh) for band in self.bands}<EOL>if distance is not None:<EOL><INDENT>dm = <NUM_LIT:5>*np.log10(distance) - <NUM_LIT:5><EOL>for band in mags:<EOL><INDENT>A = AV*EXTINCTION[band]<EOL>mags[band] = mags[band] + dm + A<EOL><DEDENT><DEDENT>props = {'<STR_LIT:M>':Ms,'<STR_LIT:R>':Rs,'<STR_LIT>':logLs,'<STR_LIT>':loggs,<EOL>'<STR_LIT>':Teffs,'<STR_LIT>':mags}<EOL>if not return_df:<EOL><INDENT>return props<EOL><DEDENT>else:<EOL><INDENT>d = {}<EOL>for key in props.keys():<EOL><INDENT>if key=='<STR_LIT>':<EOL><INDENT>for m in props['<STR_LIT>'].keys():<EOL><INDENT>d['<STR_LIT>'.format(m)] = props['<STR_LIT>'][m]<EOL><DEDENT><DEDENT>else:<EOL><INDENT>d[key] = props[key]<EOL><DEDENT><DEDENT>try:<EOL><INDENT>df = pd.DataFrame(d)<EOL><DEDENT>except ValueError:<EOL><INDENT>df = pd.DataFrame(d, index=[<NUM_LIT:0>])<EOL><DEDENT>return df<EOL><DEDENT>
Returns stellar models at constant age and feh, for a range of masses

:param age:
    log10(age) of desired isochrone.

:param feh: (optional)
    Metallicity of desired isochrone (default = 0.0)

:param minm, maxm: (optional)
    Mass range of desired isochrone (will default to max and min available)

:param dm: (optional)
    Spacing in mass of desired isochrone.  Default = 0.02 Msun.

:param return_df: (optional)
    Whether to return a :class:``pandas.DataFrame`` or dictionary.  Default is ``True``.

:param distance:
    Distance in pc.  If passed, then mags will be converted to
    apparent mags based on distance (and ``AV``).

:param AV:
    V-band extinction (magnitudes).

:return:
    :class:`pandas.DataFrame` or dictionary containing results.