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Commit a816099d authored by Yan Zhaojun's avatar Yan Zhaojun
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csst_mci_sim/csst_mci_sim.py
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......@@ -2234,124 +2234,124 @@ class MCIsimulator():
################################################################################
#################################################################################
########################################################################
def earthshine(self, theta):
"""
For given theta angle, return the earth-shine spectrum.
# def earthshine(self, theta):
# """
# For given theta angle, return the earth-shine spectrum.
:param theta: angle (in degree) from the target to earth limb.
:return: the scaled solar spectrum
template_wave: unit in A
template_flux: unit in erg/s/cm^2/A/arcsec^2
# :param theta: angle (in degree) from the target to earth limb.
# :return: the scaled solar spectrum
# template_wave: unit in A
# template_flux: unit in erg/s/cm^2/A/arcsec^2
"""
# """
# read solar template
solar_template = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/solar_spec.dat', sep='\s+',
header=None, comment='#')
template_wave = solar_template[0].values
template_flux = solar_template[1].values
# read earth shine surface brightness
earthshine_curve = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/earthshine.dat',
header=None, comment='#')
angle = earthshine_curve[0].values
surface_brightness = earthshine_curve[1].values
# read V-band throughtput
cat_filter_V = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/filter_Bessell_V.dat', sep='\s+',
header=None, comment='#')
filter_wave = cat_filter_V[0].values
filter_response = cat_filter_V[1].values
# interplate to the target wavelength in V-band
ind_filter = (template_wave >= np.min(filter_wave)) & (template_wave <= np.max(filter_wave))
filter_wave_interp = template_wave[ind_filter]
filter_response_interp = np.interp(filter_wave_interp, filter_wave, filter_response)
filter_constant = simps(filter_response_interp * filter_wave_interp, filter_wave_interp)
template_constant = simps(filter_response_interp * template_wave[ind_filter] * template_flux[ind_filter],
template_wave[ind_filter])
dwave = filter_wave_interp[1:] - filter_wave_interp[:-1]
wave_eff = np.nansum(dwave * filter_wave_interp[1:] * filter_response_interp[1:]) / \
np.nansum(dwave * filter_response_interp[1:])
# get the normalized value at theta.
u0 = np.interp(theta, angle, surface_brightness) # mag/arcsec^2
u0 = 10**((u0 + 48.6)/(-2.5)) # target flux in erg/s/cm^2/Hz unit
u0 = u0 * 3e18 / wave_eff**2 # erg/s/cm^2/A/arcsec^2
factor = u0 * filter_constant / template_constant
norm_flux = template_flux * factor # erg/s/cm^2/A/arcsec^2
self.earthshine_wave=template_wave # A
self.earthshine_flux=norm_flux
# # read solar template
# solar_template = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/solar_spec.dat', sep='\s+',
# header=None, comment='#')
# template_wave = solar_template[0].values
# template_flux = solar_template[1].values
# # read earth shine surface brightness
# earthshine_curve = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/earthshine.dat',
# header=None, comment='#')
# angle = earthshine_curve[0].values
# surface_brightness = earthshine_curve[1].values
# # read V-band throughtput
# cat_filter_V = pd.read_csv(self.information['dir_path']+'MCI_inputData/refs/filter_Bessell_V.dat', sep='\s+',
# header=None, comment='#')
# filter_wave = cat_filter_V[0].values
# filter_response = cat_filter_V[1].values
# # interplate to the target wavelength in V-band
# ind_filter = (template_wave >= np.min(filter_wave)) & (template_wave <= np.max(filter_wave))
# filter_wave_interp = template_wave[ind_filter]
# filter_response_interp = np.interp(filter_wave_interp, filter_wave, filter_response)
# filter_constant = simps(filter_response_interp * filter_wave_interp, filter_wave_interp)
# template_constant = simps(filter_response_interp * template_wave[ind_filter] * template_flux[ind_filter],
# template_wave[ind_filter])
# dwave = filter_wave_interp[1:] - filter_wave_interp[:-1]
# wave_eff = np.nansum(dwave * filter_wave_interp[1:] * filter_response_interp[1:]) / \
# np.nansum(dwave * filter_response_interp[1:])
# # get the normalized value at theta.
# u0 = np.interp(theta, angle, surface_brightness) # mag/arcsec^2
# u0 = 10**((u0 + 48.6)/(-2.5)) # target flux in erg/s/cm^2/Hz unit
# u0 = u0 * 3e18 / wave_eff**2 # erg/s/cm^2/A/arcsec^2
# factor = u0 * filter_constant / template_constant
# norm_flux = template_flux * factor # erg/s/cm^2/A/arcsec^2
# self.earthshine_wave=template_wave # A
# self.earthshine_flux=norm_flux
return
# return
########################################################################################################################################################################################################################################################
# ########################################################################################################################################################################################################################################################
def zodiacal(self, ra, dec, time):
"""
For given RA, DEC and TIME, return the interpolated zodical spectrum in Leinert-1998.
# def zodiacal(self, 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
# :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')
# # get solar position
# dt = datetime.fromisoformat(time)
# ###jd = julian.to_jd(dt, fmt='jd')
jd = time2jd(dt)
t = Time(jd, format='jd', scale='utc')
# 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
# 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')
# 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')
# # 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)
# 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)
f = interpolate.interp2d(xx, yy, zodi, kind='linear')
zodi_obj = f(beta, lamda) # 10^�? W m�? sr�? um�?
# # 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)
# f = interpolate.interp2d(xx, yy, zodi, kind='linear')
# zodi_obj = f(beta, lamda) # 10^�? W m�? sr�? um�?
# 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 # 10^-8 W m^�? sr^�? μm^�?
zodi_norm = 252 # 10^-8 W m^�? sr^�? μm^�?
# # 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 # 10^-8 W m^�? sr^�? μm^�?
# zodi_norm = 252 # 10^-8 W m^�? sr^�? μm^�?
spec = spec0 * (zodi_obj / zodi_norm) * 1e-8 # W m^�? sr^�? μm^�?
# spec = spec0 * (zodi_obj / zodi_norm) * 1e-8 # W m^�? sr^�? μm^�?
# 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
# # 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_wave=wave_A # in A
self.zodiacal_flux=spec_erg2
# self.zodiacal_flux=spec_erg2
return wave_A, spec_erg2
# return wave_A, spec_erg2
###################################################################################
##########################################################################
......
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