def _get_df(self):
        """Returns stellar model grid with desired bandpasses and with standard column names

        bands must be iterable, and are parsed according to :func:``get_band``
        """
        grids = {}
        df = pd.DataFrame()
        for bnd in self.bands:
            s,b = self.get_band(bnd, **self.kwargs)
            logging.debug('loading {} band from {}'.format(b,s))
            if s not in grids:
                grids[s] = self.get_hdf(s)
            if self.common_columns[0] not in df:
                df[list(self.common_columns)] = grids[s][list(self.common_columns)]
            col = grids[s][b]
            n_nan = np.isnan(col).sum()
            if n_nan > 0:
                logging.debug('{} NANs in {} column'.format(n_nan, b))
            df.loc[:, bnd] = col.values #dunno why it has to be this way; something
                                        # funny with indexing.

        return df
def _get_df ( self ) : grids = { } df = pd . DataFrame ( ) for bnd in self . bands : s , b = self . get_band ( bnd , ** self . kwargs ) logging . debug ( 'loading {} band from {}' . format ( b , s ) ) if s not in grids : grids [ s ] = self . get_hdf ( s ) if self . common_columns [ 0 ] not in df : df [ list ( self . common_columns ) ] = grids [ s ] [ list ( self . common_columns ) ] col = grids [ s ] [ b ] n_nan = np . isnan ( col ) . sum ( ) if n_nan > 0 : logging . debug ( '{} NANs in {} column' . format ( n_nan , b ) ) df . loc [ : , bnd ] = col . values return df
Returns stellar model grid with desired bandpasses and with standard column names

        bands must be iterable, and are parsed according to :func:``get_band``