def table(cluster):
    """
    Create a numpy.ndarray with all observed fields and
    computed teff and luminosity values.
    """
    teffs = teff(cluster)
    lums = luminosity(cluster)
    arr = cluster.to_array()
    i = 0
    for row in arr:
        row['lum'][0] = np.array([lums[i]], dtype='f')
        row['temp'][0] = np.array([teffs[i]], dtype='f')
        i += 1
    arr = round_arr_teff_luminosity(arr)
    return arr
def table(cluster):
    """
    Create a numpy.ndarray with all observed fields and
    computed teff and luminosity values.
    """
    teffs = teff(cluster)
    lums = luminosity(cluster)
    arr = cluster.to_array()
    i = 0
    for row in arr:
        row['lum'][0] = np.array([lums[i]], dtype='f')
        row['temp'][0] = np.array([teffs[i]], dtype='f')
        i += 1
    arr = round_arr_teff_luminosity(arr)
    return arr
def table ( cluster ) : teffs = teff ( cluster ) lums = luminosity ( cluster ) arr = cluster . to_array ( ) i = 0 for row in arr : row [ 'lum' ] [ 0 ] = np . array ( [ lums [ i ] ] , dtype = 'f' ) row [ 'temp' ] [ 0 ] = np . array ( [ teffs [ i ] ] , dtype = 'f' ) i += 1 arr = round_arr_teff_luminosity ( arr ) return arr
Create a numpy.ndarray with all observed fields and
    computed teff and luminosity values.
Create a numpy . ndarray with all observed fields and computed teff and luminosity values .