test

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# def zodiacal(ra, dec, time):

#     """

#         For given RA, DEC and TIME, return the interpolated zodical spectrum in Leinert-1998.

#     :param ra: RA in unit of degree, ICRS frame

#     :param dec: DEC in unit of degree, ICRS frame

#     :param time: the specified string that in ISO format i.e., yyyy-mm-dd.

#     :return:

#         wave_A: wavelength of the zodical spectrum

#         spec_mjy: flux of the zodical spectrum, in unit of MJy/sr

#         spec_erg: flux of the zodical spectrum, in unit of erg/s/cm^2/A/sr

#     """

#     # get solar position

#     dt = datetime.fromisoformat(time)

#     #jd = julian.to_jd(dt, fmt='jd')

#     jd = time2jd(dt)

#     t = Time(jd, format='jd', scale='utc')

#     astro_sun = get_sun(t)

#     ra_sun, dec_sun = astro_sun.gcrs.ra.deg, astro_sun.gcrs.dec.deg

#     radec_sun = SkyCoord(ra=ra_sun*u.degree, dec=dec_sun*u.degree, frame='gcrs')

#     lb_sun = radec_sun.transform_to('geocentrictrueecliptic')

#     # get offsets between the target and sun.

#     radec_obj = SkyCoord(ra=ra*u.degree, dec=dec*u.degree, frame='icrs')

#     lb_obj = radec_obj.transform_to('geocentrictrueecliptic')

#     beta = abs(lb_obj.lat.degree)

#     lamda = abs(lb_obj.lon.degree - lb_sun.lon.degree)

#     # interpolated zodical surface brightness at 0.5 um

#     zodi = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/zodi_map.dat', sep='\s+', header=None, comment='#')

#     beta_angle = np.array([0, 5, 10, 15, 20, 25, 30, 45, 60, 75])

#     lamda_angle = np.array([0, 5, 10, 15, 20, 25, 30, 35, 40, 45,

#                           60, 75, 90, 105, 120, 135, 150, 165, 180])

#     xx, yy = np.meshgrid(beta_angle, lamda_angle)

#     #xx, yy = np.meshgrid(beta_angle, lamda_angle,indexing='ij', sparse=True)

#     f = interpolate.interp2d(xx, yy, zodi, kind='linear')

#     #f = interpolate.RegularGridInterpolator((xx, yy), zodi, method='linear')

#     zodi_obj = f(beta, lamda)       # 

#     # read the zodical spectrum in the ecliptic

#     cat_spec = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/solar_spec.dat', sep='\s+', header=None, comment='#')

#     wave = cat_spec[0].values       # A

#     spec0 = cat_spec[1].values      # 

#     zodi_norm = 252                 # 

#     spec = spec0 * (zodi_obj / zodi_norm) * 1e-8  # 

#     # convert to the commonly used unit of MJy/sr, erg/s/cm^2/A/sr

#     wave_A = wave                                               # A

#     #spec_mjy = spec * 0.1 * wave_A**2 / 3e18 * 1e23 * 1e-6      # MJy/sr

#     spec_erg = spec * 0.1                                       # erg/s/cm^2/A/sr

#     spec_erg2 = spec_erg / 4.25452e10                           # erg/s/cm^2/A/arcsec^2

#     # self.zodiacal_wave=wave_A    # in A

#     # self.zodiacal_flux=spec_erg2

#     return  wave_A, spec_erg2

    ###################################################################################

#from astropy import units as u

#from astropy.coordinates import SkyCoord

def earth_angle(time_jd, x_sat, y_sat, z_sat, ra_obj, dec_obj):

    ra_sat = np.arctan2(y_sat, x_sat) / np.pi * 180

        self.zodiacal_flux=spec_erg2

        return 

        return wave_A, spec_erg2

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