diff --git a/csst_mci_sim/CTI/__pycache__/CTI.cpython-311.pyc b/csst_mci_sim/CTI/__pycache__/CTI.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..36a5b0b7f16698e60430bbe20606f3c526d7948a Binary files /dev/null and b/csst_mci_sim/CTI/__pycache__/CTI.cpython-311.pyc differ diff --git a/csst_mci_sim/CTI/__pycache__/__init__.cpython-311.pyc b/csst_mci_sim/CTI/__pycache__/__init__.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..4b612526d0d45577a8e58279c99f8810797247b2 Binary files /dev/null and b/csst_mci_sim/CTI/__pycache__/__init__.cpython-311.pyc differ diff --git a/csst_mci_sim/__pycache__/csst_mci_sim.cpython-311.pyc b/csst_mci_sim/__pycache__/csst_mci_sim.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..1bed457ca91784f314c2f8d849248657b78b4cff Binary files /dev/null and b/csst_mci_sim/__pycache__/csst_mci_sim.cpython-311.pyc differ diff --git a/csst_mci_sim/csst_mci_sim.py b/csst_mci_sim/csst_mci_sim.py index 78f69aead92b3596119ca099f7b2ec5491ba8a2b..c8076ce4f2ace6568c13643734a84e639530ed63 100644 --- a/csst_mci_sim/csst_mci_sim.py +++ b/csst_mci_sim/csst_mci_sim.py @@ -1,6 +1,8 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ +Created on Mon Oct 18 09:38:35 2021 + @author: yan, zhaojun""" @@ -18,8 +20,11 @@ The approximate sequence of events in the simulator is as follows: plate scale and pixel scale, exposure time etc.). #. Read in another file containing charge trap definitions (for CTI modelling). #. Read in a file defining the cosmic rays (trail lengths and cumulative distributions). - - #. Loop over the number of exposures to co-add and for each object in the galaxy fits file: + + + #. Loop over the number of exposures to co-add and for each object in the object catalog: + + #. Apply a multiplicative flat-field map to emulate pixel-to-pixel non-uniformity [optional]. @@ -29,7 +34,7 @@ The approximate sequence of events in the simulator is as follows: #. Add photon (Poisson) noise [optional] #. Add cosmetic defects from an input file [optional]. - #. Add prescan and overscan regions in the serial direction [optional]. + #. Add overscan regions in the serial direction [optional]. #. Apply the CDM03 radiation damage model [optional]. #. Apply non-linearity model to the pixel data [optional]. #. Add readout noise selected [optional]. @@ -51,15 +56,20 @@ Contact Information: zhaojunyan@shao.ac.cn import galsim import pandas as pd from scipy.integrate import simps -import julian + from datetime import datetime, timedelta from astropy.time import Time from astropy.coordinates import get_sun +import scipy.io as sio +import cmath + import numpy as np from tqdm import tqdm +from astropy.table import Table + from astropy.wcs import WCS as WCS from astropy.io import fits @@ -72,8 +82,25 @@ import configparser as ConfigParser from optparse import OptionParser +from matplotlib import pyplot as plt + from scipy import ndimage +#sys.path.append('./csst_mci_sim') +##sys.path.append('..') +from CTI import CTI +from support import logger as lg +from support import cosmicrays + +from support import shao + +from support import sed +#from shao import onOrbitObsPosition + +from support import MCIinstrumentModel + +from joblib import Parallel, delayed +#import multiprocessing from astropy.coordinates import SkyCoord @@ -81,21 +108,368 @@ from scipy import interpolate from scipy.signal import fftconvolve +import pandas +# sys.path.append('../MCI_inputData/TianCe') +# sys.path.append('../MCI_inputData/SED_Code') + + + + + + +# import jax +#import jax.numpy as jnp + +# from jax import config +# config.update("jax_enable_x64", True) + +# os.environ['CUDA_VISIBLE_DEVICES'] = '0' +# devices = jax.local_devices() -sys.path.append('..') -from CTI import CTI -from support import logger as lg -from support import cosmicrays -from support import MCIinstrumentModel -from support import shao -from support import sed # set the folder FOLDER ='../' ##################################################################################### +############################################################################### +import ctypes + +import astropy.coordinates as coord + +from scipy.interpolate import interp1d + +#from sky_bkg import sky_bkg + + +filterPivotWave = {'nuv':2875.5,'u':3629.6,'g':4808.4,'r':6178.2, 'i':7609.0, 'z':9012.9,'y':9627.9} +filterIndex = {'nuv':0,'u':1,'g':2,'r':3, 'i':4, 'z':5,'y':6} +# filterCCD = {'nuv':'UV0','u':'UV0','g':'Astro_MB','r':'Astro_MB', 'i':'Basic_NIR', 'z':'Basic_NIR','y':'Basic_NIR'} +# bandRange = {'nuv':[2504.0,3230.0],'u':[3190.0,4039.0],'g':[3989.0,5498.0],'r':[5438.0,6956.0], 'i':[6886.0,8469.0], +# 'z':[8379.0,10855.0],'y':[9217.0, 10900.0], 'GU':[2550, 4000],'GV':[4000, 6200],'GI':[6200,10000]} +# Instrument_dir = '/Users/linlin/Data/csst/straylightsim-master/Instrument/' +# SpecOrder = ['-2','-1','0','1','2'] +# +# filterMirrorEff = {'nuv':0.54,'u':0.68,'g':0.8,'r':0.8, 'i':0.8, 'z':0.8,'y':0.8} + + +def transRaDec2D(ra, dec): + # radec转为竞天程序里的ob, 赤道坐标系下的笛卡尔三维坐标xyz. + x1 = np.cos(dec / 57.2957795) * np.cos(ra / 57.2957795) + y1 = np.cos(dec / 57.2957795) * np.sin(ra / 57.2957795) + z1 = np.sin(dec / 57.2957795) + return np.array([x1, y1, z1]) +############################################################################### + +def flux2ill(wave, flux): + + # erg/s/cm^2/A/arcsec^2 to W/m^2 + + # 1 W/m^2/sr/μm = 0.10 erg/cm^2/s/sr/A + # 1 sr = 1 rad^2 = 4.25452e10 arcsec^2 + # 1 J/s = 1 W + # 1 J = 10^7 erg + + # convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr + flux1 = flux / (1/4.25452e10) + # convert erg/s/cm^2/A/sr to W/m^2/sr/um + flux2 = flux1 * 10 + + # 对接收面积积分，输出单位 W/m^2/nm + D = 2 # meter + f = 28 # meter + flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3 + + # # # u_lambda: W/m^2/nm + # # obj0: + # V = 73 * 1e-8 # W/m^2/nm + # Es = V * np.pi * D**2 / 4 / f**2 / 10**3 + # c1 = 3.7418e-16 + # c2 = 1.44e-2 + # t = 5700 + # # wave需要代入meter. + # wave0 = np.arange(380, 780) # nm + # delta_lamba0 = 1 # nm + # u_lambda = c1 / (wave0*1e-9)**5 / (np.exp(c2 / (wave0*1e-9) / t) - 1) + # f_lambda = (u_lambda / u_lambda[wave0 == 500]) * Es + # E0 = np.sum(f_lambda * 1) + # # plt.plot(wave, u_lambda) + # # plt.show() + + # 对波长积分 + f = interp1d(wave, flux3) + wave_interp = np.arange(3800, 7800) + flux3_interp = f(wave_interp) + # 输出单位 W/m^2 + delta_lamba = 0.1 # nm + E = np.sum(flux3_interp * delta_lamba) + + # pdb.set_trace() + + return E + +################################################################ +def ill2flux(E): + + # use template from sky_bkg (background_spec_hst.dat) + filename = '../MCI_inputData/refs/background_spec_hst.dat' + cat_spec = pd.read_csv(filename, sep='\s+', header=None, comment='#') + wave0 = cat_spec[0].values # A + spec0 = cat_spec[2].values # erg/s/cm^2/A/arcsec^2 + + # convert erg/s/cm^2/A/arcsec^2 to erg/s/cm^2/A/sr + flux1 = spec0 / (1/4.25452e10) + # convert erg/s/cm^2/A/sr to W/m^2/sr/um + flux2 = flux1 * 10 + + # 对接收面积积分，输出单位 W/m^2/nm + D = 2 # meter + f = 28 # meter, 焦距，转换关系来源于王维notes. + flux3 = flux2 * np.pi * D**2 / 4 / f**2 / 10**3 + + f = interp1d(wave0, flux3) + wave_range = np.arange(3800, 7800) + flux3_mean = f(wave_range) + delta_lamba = 0.1 # nm + E0 = np.sum(flux3_mean * delta_lamba) + + factor = E / E0 + spec_scaled = factor * spec0 + + return wave0, spec_scaled + +############################################################## + +########################################################## +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('../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('../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 + dec_sat = np.arctan2(z_sat, np.sqrt(x_sat**2+y_sat**2)) / np.pi * 180 + radec_sat = SkyCoord(ra=ra_sat*u.degree, dec=dec_sat*u.degree, frame='gcrs') + lb_sat = radec_sat.transform_to('geocentrictrueecliptic') + + # get the obj location + radec_obj = SkyCoord(ra=ra_obj*u.degree, dec=dec_obj*u.degree, frame='gcrs') + lb_obj = radec_obj.transform_to('geocentrictrueecliptic') + + # calculate the angle between sub-satellite point and the earth side + earth_radius = 6371 # km + sat_height = np.sqrt(x_sat**2 + y_sat**2 + z_sat**2) + angle_a = np.arcsin(earth_radius/sat_height) / np.pi * 180 + + # calculate the angle between satellite position and the target position + angle_b = lb_sat.separation(lb_obj) + + # calculat the earth angle + angle = 180 - angle_a - angle_b.degree + + return angle + + + + #################################################3 + +def MCIinformation(): + """ + Returns a dictionary describing MCI CCD. The following information is provided (id: value - reference):: + + + dob: 0 - CDM03 (Short et al. 2010) + fwc: 90000 - CCD spec EUCL-EST-RS-6-002 (for CDM03) + rdose: 30000000000.0 - derived (above the PLM requirement) + sfwc: 730000.0 - CDM03 (Short et al. 2010), see also the CCD spec EUCL-EST-RS-6-002 + st: 5e-06 - CDM03 (Short et al. 2010) + svg: 1e-10 - CDM03 (Short et al. 2010) + t: 0.01024 - CDM03 (Short et al. 2010) + trapfile: cdm_euclid.dat - CDM03 (derived, refitted to CCD204 data) + vg: 6e-11 - CDM03 (Short et al. 2010) + vth: 11680000.0 - CDM03 (Short et al. 2010) + + + + :return: instrument model parameters + :rtype: dict + """ + + ######################################################################################################### + out=dict() + out.update({'dob' : 0, 'rdose' : 8.0e9, + 'parallelTrapfile' : 'cdm_euclid_parallel.dat', 'serialTrapfile' : 'cdm_euclid_serial.dat', + 'beta_s' : 0.6, 'beta_p': 0.6, 'fwc' : 90000, 'vth' : 1.168e7, 't' : 20.48e-3, 'vg' : 6.e-11, + 'st' : 5.0e-6, 'sfwc' : 730000., 'svg' : 1.0e-10}) + + return out +####################################### + +def CCDnonLinearityModel(data, beta=6e-7): + """ + + The non-linearity is modelled based on the results presented. + :param data: data to which the non-linearity model is being applied to + :type data: ndarray + + :return: input data after conversion with the non-linearity model + :rtype: float or ndarray + """ + out = data-beta*data**2 + + return out +#############################################################33333 + +class StrayLight(object): + + def __init__(self, jtime = 2460843., sat = np.array([0,0,0]), radec = np.array([0,0])): + self.jtime = jtime + self.sat = sat + self.equator = coord.SkyCoord(radec[0]*u.degree, radec[1]*u.degree,frame='icrs') + self.ecliptic = self.equator.transform_to('barycentrictrueecliptic') + self.pointing = transRaDec2D(radec[0], radec[1]) + self.slcdll = ctypes.CDLL('../MCI_inputData/refs/libstraylight.so') #dylib + + self.slcdll.Calculate.argtypes = [ctypes.c_double, ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double), ctypes.c_char_p] + + self.slcdll.PointSource.argtypes = [ctypes.c_double ,ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double),ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double), ctypes.c_char_p] + + self.slcdll.EarthShine.argtypes = [ctypes.c_double ,ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double)] + + self.slcdll.Zodiacal.argtypes = [ctypes.c_double ,ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double)] + self.slcdll.ComposeY.argtypes = [ctypes.POINTER(ctypes.c_double), ctypes.POINTER(ctypes.c_double), + ctypes.POINTER(ctypes.c_double)] + self.slcdll.Init.argtypes=[ctypes.c_char_p,ctypes.c_char_p,ctypes.c_char_p,ctypes.c_char_p] + self.deFn = "../MCI_inputData/refs/DE405" + self.PSTFn = "../MCI_inputData/refs/PST" + self.RFn = "../MCI_inputData/refs/R" + self.ZolFn = "../MCI_inputData/refs/Zodiacal" + self.brightStarTabFn = "../MCI_inputData/refs/BrightGaia_with_csst_mag" + + self.slcdll.Init(str.encode(self.deFn),str.encode(self.PSTFn),str.encode(self.RFn),str.encode(self.ZolFn)) + + + def caculateStarLightFilter(self, filter='i'): + + sat = (ctypes.c_double*3)() + sat[:] = self.sat + ob = (ctypes.c_double*3)() + ob[:] = self.pointing + + py1 = (ctypes.c_double*3)() + py2 = (ctypes.c_double*3)() + self.slcdll.ComposeY(ob, py1, py2) + + star_e1 = (ctypes.c_double*7)() + self.slcdll.PointSource(self.jtime, sat, ob, py1, star_e1, str.encode(self.brightStarTabFn)) + star_e2 = (ctypes.c_double*7)() + self.slcdll.PointSource(self.jtime, sat, ob, py2, star_e2, str.encode(self.brightStarTabFn)) + + band_star_e1 = star_e1[:][filterIndex[filter]] + band_star_e2 = star_e2[:][filterIndex[filter]] + + return max(band_star_e1, band_star_e2) + + def caculateEarthShineFilter(self, filter='i'): + sat = (ctypes.c_double*3)() + sat[:] = self.sat + ob = (ctypes.c_double*3)() + ob[:] = self.pointing + + py1 = (ctypes.c_double*3)() + py2 = (ctypes.c_double*3)() + self.slcdll.ComposeY(ob, py1, py2) + + earth_e1 = (ctypes.c_double*7)() + self.slcdll.EarthShine(self.jtime, sat, ob, py1, earth_e1) # e[7]代表7个波段的照度 + + earth_e2 = (ctypes.c_double*7)() + self.slcdll.EarthShine(self.jtime, sat, ob, py2, earth_e2) + + band_earth_e1 = earth_e1[:][filterIndex[filter]] + band_earth_e2 = earth_e2[:][filterIndex[filter]] + + return max(band_earth_e1, band_earth_e2) + +############################################################################### +#################################################################################### def processArgs(printHelp=False): @@ -212,71 +586,41 @@ def dt2hmd(dt): ############################################################################### -def deg2HMS(ra, dec, rou=False): - '''convert deg to ra's HMS or dec's DHS''' - RA, DEC, rs, ds = '000000', '000000', '', '' - if dec: - if str(dec)[0] == '-': - ds, dec = '-', abs(dec) - deg = int(dec) - decM = abs(int((dec-deg)*60)) - - if rou: - decS = round((abs((dec-deg)*60)-decM)*60,1) - else: - decS = int((abs((dec-deg)*60)-decM)*60) - - if deg ==0: - deg ="00" - elif deg <10: - deg = "0%s"%deg - - if decM ==0: - decM ="00" - elif decM <10: - decM = "0%s"%decM - - if decS ==0: - decS ="00" - elif decS <10: - decS = "0%s"%decS - - DEC = '{0}{1}{2}{3}'.format(ds, deg, decM, decS) - - if ra: - if str(ra)[0] == '-': - rs, ra = '-', abs(ra) - raH = int(ra/15) - raM = int(((ra/15)-raH)*60) - - if rou: - raS = round(((((ra/15)-raH)*60)-raM)*60,1) - else: - raS = int(((((ra/15)-raH)*60)-raM)*60) - - if raH ==0: - raH = "00" - - elif raH <10: - raH = "0%s"%raH - - if raM ==0: - raM = "00" - elif raM <10: - raM = "0%s"%raM - - if raS ==0: - raS = "00" + +def deg2HMS(ra0, dec0): + '''convert deg to ra's HMS and dec's DMS''' + c = SkyCoord(ra=ra0*u.degree, dec=dec0*u.degree) + ss=c.to_string('hmsdms') + print(ss) + for k in range(5,len(ss)-1): + + if ss[k]=='s': + s_idx=k - elif raS <10: - raS = "0%s"%raS + if ss[k]=='d': + d_idx=k - RA = '{0}{1}{2}{3}'.format(rs, raH, raM, raS) - - if ds=='-': - return RA+DEC - else: - return RA+'+'+DEC + if ss[k]=='m': + m_idx=k + + if c.ra.hms.s<10 and c.ra.hms.s>0.1: + temp=str(c.ra.hms.s) + ra_ss='0'+temp[:3] + if c.ra.hms.s>10: + temp=str(c.ra.hms.s) + ra_ss=temp[:4] + + if c.ra.hms.s<0.1: + temp=str(c.ra.hms.s) + ra_ss='00.0' + + dms_d=ss[s_idx+2:d_idx] + dms_m=ss[d_idx+1:m_idx] + dms_s=ss[m_idx+1:m_idx+3] + + hhmmss=ss[0:2]+ss[3:5]+ra_ss + return hhmmss+dms_d+dms_m+dms_s + ################################################################################ def cut_radius(rcutstar, mstar, mag): return rcutstar * 10**(0.4*2*(mstar-mag)/3.125) @@ -294,7 +638,7 @@ def v_disp(sigstar, mstar, mag): def distortField(ra, dec, ch): ###% ra ,dec are the idea position in arcsec , and the center position is ra=0, dec=0 - '''MCI geometry distortion effect in channel G R and I''' + '''MCI geometry distortion effect in channel G R and I''' distortA=dict() distortB=dict() @@ -419,6 +763,18 @@ def krebin(a, sample): return a.reshape(sh).sum(-1).sum(1) ##################################################################### + + +def float2char(a, z): + ### a is input float value + ### transfer float a to chars and save z bis + b=str(a) + n=len(b) + + if z>=n: + return b + else: + return b[:z] ######################################################### def centroid(data): @@ -442,9 +798,323 @@ def centroid(data): ############################################################################### +def fftrange(n, dtype=float): + """FFT-aligned coordinate grid for n samples.""" + return np.arange(-n//2, -n//2+n, dtype=dtype) + +############################################################################### + + +def dft2(ary, Q, samples, shift=None): + """Compute the two dimensional Discrete Fourier Transform of a matrix. + + Parameters + ---------- + ary : `numpy.ndarray` + an array, 2D, real or complex. Not fftshifted. + Q : `float` + oversampling / padding factor to mimic an FFT. If Q=2, Nyquist sampled + samples : `int` or `Iterable` + number of samples in the output plane. + If an int, used for both dimensions. If an iterable, used for each dim + shift : `float`, optional + shift of the output domain, as a frequency. Same broadcast + rules apply as with samples. + + Returns + ------- + `numpy.ndarray` + 2D array containing the shifted transform. + Equivalent to ifftshift(fft2(fftshift(ary))) modulo output + sampling/grid differences + + """ + + # this is for dtype stabilization + Q = float(Q) ## Q=lambda*f/D/pixelsize + + n, m = ary.shape ###ary maybe is the pupil function + N, M = samples,samples + + X, Y, U, V = (fftrange(n) for n in (m, n, M, N)) + + a = 1 / Q + + ################################################################### + Eout_fwd = np.exp(-1j * 2 * np.pi * a / n * np.outer(Y, V).T) + Ein_fwd = np.exp(-1j * 2 * np.pi * a / m * np.outer(X, U)) + + ############################################################################# + + out = Eout_fwd @ ary @ Ein_fwd #### ary is the input pupil function + + return out +############################################################################## + +def idft2(ary, Q, samples, shift=None): + """Compute the two dimensional inverse Discrete Fourier Transform of a matrix. + + Parameters + ---------- + ary : `numpy.ndarray` + an array, 2D, real or complex. Not fftshifted. + Q : `float` + oversampling / padding factor to mimic an FFT. If Q=2, Nyquist sampled + samples : `int` or `Iterable` + number of samples in the output plane. + If an int, used for both dimensions. If an iterable, used for each dim + shift : `float`, optional + shift of the output domain, as a frequency. Same broadcast + rules apply as with samples. + + Returns + ------- + `numpy.ndarray` + 2D array containing the shifted transform. + Equivalent to ifftshift(ifft2(fftshift(ary))) modulo output + sampling/grid differences + + """ + # this is for dtype stabilization + Q = float(Q) ## Q=lambda*f/D/pixelsize + + n, m = ary.shape ###ary maybe is the pupil function + N, M = samples + + X, Y, U, V = (fftrange(n) for n in (m, n, M, N)) + + ############################################################################### + nm = n*m + NM = N*M + r = NM/nm + a = 1 / Q + + ################################################################### + # Eout_fwd = np.exp(-1j * 2 * np.pi * a / n * np.outer(Y, V).T) + # Ein_fwd = np.exp(-1j * 2 * np.pi * a / m * np.outer(X, U)) + Eout_rev = np.exp(1j * 2 * np.pi * a / n * np.outer(Y, V).T) * (1/r) + Ein_rev = np.exp(1j * 2 * np.pi * a / m * np.outer(X, U)) * (1/nm) + + ########################################################################### + + out = Eout_rev @ ary @ Ein_rev + + return out +############################################################################### ############################################################################### +def opd2psf(opd,cwave,oversampling): + ''' + calculate psf from opd data with defined wavelength + + Parameters + ---------- + opd : TYPE + the input opd data. + cwave : TYPE + the defined wavelength. + + ''' + + D=2; + focLength=41.253 # % MCI focal length in meters + pixel=10/oversampling # % pixel size in microns + + opd=opd*1e9; ## convert opd unit of meter to nm + + zoomopd=ndimage.zoom(opd, 2, order=1) + + m,n=np.shape(zoomopd); + clambda=cwave; + + wfe=zoomopd/clambda; #%% the main telescope aberration ,in wavelength; + + Q=clambda*1e-3*focLength/D/pixel + + pupil=np.zeros((m,m)); + + pupil[abs(zoomopd)>0]=1; + #idx=pupil>0; + + Nt=512 + + phase=2*np.pi*wfe; #% wavefront phase in radians + + #%generalized pupil function of channel1; + pk=pupil*np.exp(cmath.sqrt(-1)*(phase)) + + pf=dft2(pk, Q, Nt) + + pf2 = abs(pf)**2 + psfout=pf2/pf2.sum() + + cx,cy=centroid(psfout) + + psf=ndimage.shift(psfout,[Nt/2-1-cy, Nt/2-1-cx],order=1, mode='nearest' ) + + return psf +######################################################################## + +def cal_PSF_new(channel,wfetimes,oversampling): + # filed postion: Ra=ys1, Dec=ys2 + + ############ use opd cal PSF on the defined field; + #% psf interpolation test 20210207 + # xfmin=-0.07 # % the filed minmum value in the x direction in degrees + # xfmax= 0.07 #% the filed maxmum value in the x direction in degrees + # yfmin=-0.35 #% the filed minmum value in the y direction in degrees + # yfmax=-0.49 # % the filed maxmum value in the y direction in degrees + + cfx= 0.2*3600; # % field center in x derection in arcsec; + cfy= -0.45*3600; # % field center in y derection in arcsec; + + #wavelength=[255,337,419,501,583,665,747,829,911,1000] + + cwave=dict() + + if channel == 'g': + cwave[channel]=475 + waven=4 + if channel == 'r': + cwave[channel]=625 + waven=6 + if channel == 'i': + cwave[channel]=776 + waven=7 + + n=np.arange(1,101,1) + + ffx= 0.1+ 0.02222222*((n-1)%10) + ffy=-0.35-0.02222222*np.floor((n-0.1)/10) + + psf=dict() + fx=dict() + fy=dict() + fx[channel]=ffx*3600-cfx + + fy[channel]=ffy*3600-cfy + + Nt=512 + + psf[channel]=np.zeros((len(n),Nt,Nt)) + + for i in range(len(n)): + #waven + # waven=4 + # fieldn=10 + file='../MCI_inputData/MCI_wavefront/wave_'+str(waven+1)+'/wavefront/opd_'+str(i+1)+'.mat' + data=sio.loadmat(file) + opd=data['opd'] ## opd data; + psf[channel][i,:,:]=opd2psf(wfetimes*opd, cwave[channel],oversampling) + + + hdu1=fits.PrimaryHDU(psf[channel]) + + hdu1.header.append(('channel', channel, 'MCI PSF channel')) + + + hdu1.header['pixsize']=(0.05/oversampling, 'PSF pixel size in arcsec') + + hdu1.header['wfetimes']=(wfetimes, 'wavefront error magnification to CSST primary wavefront ') + + dtime=datetime.datetime.utcnow().strftime('%Y -%m -%d %H: %M: %S') + hdu1.header.add_history('PSF is generated on :'+dtime) + + hdu2=fits.ImageHDU(fx[channel]) + + hdu2.header.append(('field_X', 'arcsec')) + + hdu3=fits.ImageHDU(fy[channel]) + + hdu3.header.append(('field_Y', 'arcsec')) + + newd=fits.HDUList([hdu1,hdu2,hdu3]) + + PSFfilename='../MCI_inputData/PSF/PSF_'+channel+'.fits' + + newd.writeto(PSFfilename,overwrite=True) + + return +############################################################################# + + +def cal_Filter_PSF(wfetimes): + # filed postion: Ra=ys1, Dec=ys2 + + ############ use opd cal PSF on the defined field; + #% psf interpolation test 20210207 + # xfmin=-0.07 # % the filed minmum value in the x direction in degrees + # xfmax= 0.07 #% the filed maxmum value in the x direction in degrees + # yfmin=-0.35 #% the filed minmum value in the y direction in degrees + # yfmax=-0.49 # % the filed maxmum value in the y direction in degrees + oversampling=2 + + cfx= 0.2*3600; # % field center in x derection in arcsec; + cfy= -0.45*3600; # % field center in y derection in arcsec; + + wavelist =np.array([255, 337,419,501,583,665,747,829,911,1000]) + + filterP=np.load('../MCI_inputData/MCI_filters/mci_filterPWTC.npy',allow_pickle=True).item() + + fn=np.arange(1,101,1) ### PSF field point + ffx= 0.1+ 0.02222222*((fn-1)%10) + ffy=-0.35-0.02222222*np.floor((fn-0.1)/10) + + psf=dict() + fx=dict() + fy=dict() + fx=ffx*3600-cfx + fy=ffy*3600-cfy + Nt=512 + + + for filterk in filterP.keys(): + filtername=filterk + print(filtername) + + filterwaveC=filterP[filterk]['Clambda'] + filterFwhm=filterP[filterk]['FWHM'] + + fdis=abs(filterwaveC-wavelist) + + findex=np.argsort(fdis) + + waven=findex[0] + + psf[filtername]=dict() + + psf[filtername]['psf_field_X'] =fx + psf[filtername]['psf_field_Y'] =fy + psf[filtername]['psf_scale'] =0.05/oversampling + psf[filtername]['wfetimes'] =wfetimes + psf[filtername]['psf_mat'] =np.zeros( (Nt,Nt,7,len(fn)) ) + psf[filtername]['filter_name'] =filtername + psf[filtername]['filter_channel']=filterP[filterk]['channel'] + psf[filtername]['psf_iwave'] =np.zeros(7) + + for ii in range(len(fn)): + #waven + # waven=4 + # fieldn=10 + file='../MCI_input/MCI_wavefront/wave_'+str(waven+1)+'/wavefront/opd_'+str(ii+1)+'.mat' + data=sio.loadmat(file) + opd=data['opd'] ## opd data; + for kk in range(7): + ### + wavek=filterwaveC+filterFwhm*(kk-3)*0.25 + + psfd=opd2psf(wfetimes*opd, wavek, oversampling) + + psf[filtername]['psf_mat'][:,:,kk,ii]=psfd[:,:] + + if ii==0: + psf[filtername]['psf_iwave'][kk]=wavek + + np.save('../MCI_inputData/PSF/'+filtername+'_PSF.npy', psf[filtername]) + + return + ######################################################################### @@ -479,7 +1149,7 @@ def findNeighbors(tx, ty, px, py, dn=5): ############################################################################### ###PSF-IDW### -def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=5, OnlyNeighbors=True): +def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, dn=5, IDWindex=3, OnlyNeighbors=True): """ psf interpolation by IDW @@ -499,24 +1169,21 @@ def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=5, OnlyNeighbors=Tru ref_row = py ### target position in y ngy, ngx = PSFMat[:, :, 0, 0].shape ### PSF data size - npsf = PSFMat[:, :, :,:].shape[3] ### total psf number in one wavelength - psfWeight = np.zeros([npsf]) + + #################################### + ####### my code ###### + psfWeight = np.zeros([dn]) if OnlyNeighbors == True: - neigh = findNeighbors(px, py, cen_col, cen_row, dn=5) - # if hoc is not None: - # neigh = findNeighbors_hoclist(cen_col, cen_row, tx=px,ty=py, dn=4, hoc=hoc, hoclist=hoclist) - - neighFlag = np.zeros(npsf) - neighFlag[neigh] = 1 - - for ipsf in range(npsf): - if OnlyNeighbors == True: - if neighFlag[ipsf] != 1: - continue + neigh = findNeighbors(px, py, cen_col, cen_row, dn) + + ####################################################################### + for ipsf in range(len(neigh)): - dist = np.sqrt((ref_col - cen_col[ipsf])**2 + (ref_row - cen_row[ipsf])**2) + idx=neigh[ipsf] + dist = np.sqrt((ref_col - cen_col[idx])**2 + (ref_row - cen_row[idx])**2) + if IDWindex == 1: psfWeight[ipsf] = dist if IDWindex == 2: @@ -525,30 +1192,35 @@ def psfMaker_IDW(px, py, PSFMat, cen_col, cen_row, IDWindex=5, OnlyNeighbors=Tru psfWeight[ipsf] = dist**3 if IDWindex == 4: psfWeight[ipsf] = dist**4 + if IDWindex == 5: + psfWeight[ipsf] = dist**5 psfWeight[ipsf] = max(psfWeight[ipsf], minimum_psf_weight) psfWeight[ipsf] = 1./psfWeight[ipsf] + ##################################3 + psfWeight /= np.sum(psfWeight) psfMaker = np.zeros([ngy, ngx, 7 ], dtype=np.float32) - + ######################################################### for waven in range(7): - for ipsf in range(npsf): - if OnlyNeighbors == True: - if neighFlag[ipsf] != 1: - continue + for ipsf in range(len(neigh)): - iPSFMat = PSFMat[:, :, waven,ipsf].copy() + idx=neigh[ipsf] + + iPSFMat = PSFMat[:, :, waven,idx].copy() + ipsfWeight = psfWeight[ipsf] psfMaker[:, :, waven] += iPSFMat * ipsfWeight psfMaker[:, :, waven] /= np.nansum(psfMaker[:, :, waven]) - - return psfMaker + + + return psfMaker ############################################################################### ############################################################################### @@ -570,26 +1242,48 @@ class MCIsimulator(): :type opts: OptionParser instance """ - def __init__(self, opts): + def __init__(self, configfile): """ Class Constructor. :param opts: OptionParser instance :type opts: OptionParser instance """ - self.configfile = opts.configfile - - if opts.section is None: - ####self.section = 'DEFAULT' - self.section = 'TEST' #####simulation section; - else: - self.section = opts.section - - + self.configfile = configfile + self.section = 'TEST' #####simulation section; + #load instrument model, these values are also stored in the FITS header + self.information = MCIinstrumentModel.MCIinformation() + self.information['G_filters']=["F275W", "F280N","NUV", "WU", "CBU", "F343N", "u", "F373N", "F395N", "F336W"] + self.information['R_filters']=["F487N", "F502N", "CBV", "r", "F656N", "F658N", "F467M", "F555W", "F606W", "F673N"] + self.information['I_filters']=["z", "y", "F815N", "CBI", "F925N", "F960M", "F968N", "F845M" ,"F850LP" ,"F814W"] + + #### load telescope efficiency data + self.tel_eff=np.load('../MCI_inputData/tel_eff/tel_eff.npy',allow_pickle=True).item() + + #### load MCI filter data + self.filterP=np.load('../MCI_inputData/MCI_filters/mci_filterPWTC.npy',allow_pickle=True).item() + ########################################################################### + now=datetime.utcnow() + #data_time=now.strftime("%Y-%m-%d-%H-%M-%S") + result_day=now.strftime("%Y-%m-%d") + #self.result_path='../MCI_simData_'+result_day + + if os.getcwd() =='/home/zjyan/work/MCI/simulator': + self.result_path='/data/mci_simData/'+result_day ### CSST1 + else: + self.result_path='/home/yan/MCI/simData/'+result_day ### my PC + + if os.path.isdir(self.result_path)==False: + os.mkdir(self.result_path) + os.mkdir(self.result_path+'/cali_Data') + os.mkdir(self.result_path+'/log_Data') + os.mkdir(self.result_path+'/ori_Cali') + os.mkdir(self.result_path+'/ori_Sky') + os.mkdir(self.result_path+'/sky_Data') + os.mkdir(self.result_path+'/PSF_Data') - self.information = MCIinstrumentModel.MCIinformation() #update settings with defaults self.information.update(dict(quadrant=int(0), ccdx=int(0), @@ -599,41 +1293,49 @@ class MCIsimulator(): xsize=2000, ysize=2000, fullwellcapacity=90000, + pixel_size=0.05, dark=0.001, exptime=300.0, readouttime=4., rdose=8.0e9, ghostCutoff=22.0, ghostRatio=5.e-5, - coveringfraction=1.0, - pixel_size=0.05)) - - - self.configure(1) #print the configfile name and path; - - self.information.update(dict( - - cosmicraylengths =self.information['indata_path']+'/data/cdf_cr_length.dat', - cosmicraydistance=self.information['indata_path']+'/data/cdf_cr_total.dat', - parallelTrapfile =self.information['indata_path']+'/data/cdm_euclid_parallel.dat', - serialTrapfile =self.information['indata_path']+'/data/cdm_euclid_serial.dat', - cosmeticsfile_g =self.information['indata_path']+'/data/Cosmetics_g.txt', - cosmeticsfile_r =self.information['indata_path']+'/data/Cosmetics_r.txt' , - cosmeticsfile_i =self.information['indata_path']+'/data/Cosmetics_i.txt' )) + coveringfraction=0.1, #CR: + cosmicraylengths =FOLDER+'MCI_inputData/data/cdf_cr_length.dat', + cosmicraydistance=FOLDER+'MCI_inputData/data/cdf_cr_total.dat', + parallelTrapfile =FOLDER+'MCI_inputData/data/cdm_euclid_parallel.dat', + serialTrapfile =FOLDER+'MCI_inputData/data/cdm_euclid_serial.dat', + mode='same')) ############################################################################### - def readConfigs(self,simnumber): + def readConfigs(self,simnumber,source): """ Reads the config file information using configParser and sets up a logger. """ self.config = ConfigParser.RawConfigParser() - + if simnumber==1: + print('beging config file name : ') + print(self.configfile) #self.config.readfp(open(self.configfile)) self.config.read_file(open(self.configfile)) + now=datetime.utcnow() + + data_time=now.strftime("%Y-%m-%d-%H-%M-%S") + + print('simnumber', simnumber) + self.log = lg.setUpLogger(self.result_path+'/log_Data/MCIsim_'+source+'_'+data_time+'_Num_'+str(simnumber)+'.log') + + #print('logger.handlers=', self.log.handlers) + + self.log.info('-------STARTING A NEW SIMULATION------------') + + self.log.info('The exposure order is %i ' % simnumber ) + + #self.log.info(self.information) ################################################################################################3 @@ -659,29 +1361,30 @@ class MCIsimulator(): self.information.update(settings) - - #ghost ratio can be in engineering format, so getfloat does not capture it... try: self.information['ghostRatio'] = float(self.config.get(self.section, 'ghostRatio')) except: pass - ######### + + ################################################################################################### + ################################################################################################## + #booleans to control the flow - self.cosmicRays = self.config.getboolean(self.section, 'cosmicRays') - self.darknoise = self.config.getboolean(self.section, 'darknoise') + self.cosmicRays = self.config.getboolean(self.section, 'cosmicRays') + self.darknoise = self.config.getboolean(self.section, 'darknoise') self.cosmetics = self.config.getboolean(self.section, 'cosmetics') self.radiationDamage = self.config.getboolean(self.section, 'radiationDamage') - self.bleeding = self.config.getboolean(self.section, 'bleeding') - self.overscans = self.config.getboolean(self.section, 'overscans') - self.nonlinearity = self.config.getboolean(self.section, 'nonlinearity') - self.readoutNoise = self.config.getboolean(self.section, 'readoutNoise') + self.bleeding = self.config.getboolean(self.section, 'bleeding') + self.overscans = self.config.getboolean(self.section, 'overscans') + self.nonlinearity = self.config.getboolean(self.section, 'nonlinearity') + self.readoutNoise = self.config.getboolean(self.section, 'readoutNoise') self.skyback = self.config.getboolean(self.section, 'skyback') self.TianceEffect = self.config.getboolean(self.section, 'TianceEffect') self.intscale = self.config.getboolean(self.section, 'intscale') - self.ghosts = self.config.getboolean(self.section, 'ghosts') + self.ghosts = self.config.getboolean(self.section, 'ghosts') self.shutterEffect =self.config.getboolean(self.section, 'shutterEffect') self.flatfieldM =self.config.getboolean(self.section, 'flatfieldm') self.PRNUeffect =self.config.getboolean(self.section, 'PRNUeffect') @@ -691,6 +1394,8 @@ class MCIsimulator(): self.sim_star =self.config.getboolean(self.section, 'sim_star') self.sim_galaxy =self.config.getboolean(self.section, 'sim_galaxy') + self.save_starpsf =self.config.getboolean(self.section, 'save_starpsf') + self.save_cosmicrays =self.config.getboolean(self.section, 'save_cosmicrays') ###############################################3################################# self.booleans = dict(cosmicRays =self.cosmicRays, @@ -704,7 +1409,7 @@ class MCIsimulator(): skyback =self.skyback, TianceEffect =self.TianceEffect, intscale =self.intscale, - ghosts =self.ghosts , + ghosts =self.ghosts , shutterEffect =self.shutterEffect, flatfieldM =self.flatfieldM, PRNUeffect =self.PRNUeffect, @@ -712,58 +1417,17 @@ class MCIsimulator(): sky_shift_rot =self.sky_shift_rot, distortion =self.distortion, sim_star =self.sim_star, - sim_galaxy =self.sim_galaxy) - ##################################################################### - - - now=datetime.now() - #data_time=now.strftime("%Y-%m-%d-%H-%M-%S") - result_day=now.strftime("%Y-%m-%d") - - self.result_path=self.information['result_path']+'/'+result_day ### CSST1 - - - if os.path.isdir(self.result_path)==False: - os.mkdir(self.result_path) - os.mkdir(self.result_path+'/cali_Data') - os.mkdir(self.result_path+'/log_Data') - os.mkdir(self.result_path+'/sky_Data') - ############################################################# - - - data_time=now.strftime("%Y-%m-%d-%H-%M-%S") - - - self.log = lg.setUpLogger(self.result_path+'/log_Data/MCIsim_'+'_'+data_time+'.log') - - - self.log.info('-------STARTING A NEW SIMULATION------------') - - - self.log.info(self.information) - - ############################################## - #load instrument model, these values are also stored in the FITS header - - self.information['G_filters']=["F275W", "F280N","NUV", "WU", "CBU", "F343N", "u", "F373N", "F395N", "F336W"] - self.information['R_filters']=["F487N", "F502N", "CBV", "r", "F656N", "F658N", "F467M", "F555W", "F606W", "F673N"] - self.information['I_filters']=["z", "y", "F815N", "CBI", "F925N", "F960M", "F968N", "F845M" ,"F850LP" ,"F814W"] - - #### load telescope efficiency data - self.tel_eff=np.load(self.information['indata_path']+'/tel_eff/tel_eff.npy',allow_pickle=True).item() - - #### load MCI filter data - self.filterP=np.load(self.information['indata_path']+'/MCI_filters/mci_filterPWTC.npy',allow_pickle=True).item() - - - ##################################################################### - - self.log.info('Using the following input values:') - for key, value in self.information.items(): - self.log.info('%s = %s' % (key, value)) - self.log.info('Using the following booleans:') - for key, value in self.booleans.items(): - self.log.info('%s = %s' % (key, value)) + sim_galaxy =self.sim_galaxy, + save_starpsf =self.save_starpsf, + save_cosmicrays =self.save_cosmicrays ) + ##################################################################### + + # self.log.info('Using the following input values:') + # for key, value in self.information.items(): + # self.log.info('%s = %s' % (key, value)) + # self.log.info('Using the following booleans:') + # for key, value in self.booleans.items(): + # self.log.info('%s = %s' % (key, value)) return @@ -788,15 +1452,36 @@ class MCIsimulator(): Creates lensing parameters; """ - self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) + self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) return ######################################################################################################################### ######################################################################################################### + def smoothingWithChargeDiffusion(self, image, sigma=(0.32, 0.32)): + """ + Smooths a given image with a gaussian kernel with widths given as sigmas. + This smoothing can be used to mimic charge diffusion within the CCD. + + The default values are from Table 8-2 of CCD_273_Euclid_secification_1.0.130812.pdf converted + to sigmas (FWHM / (2sqrt(2ln2)) and rounded up to the second decimal. + + .. Note:: This method should not be called for the full image if the charge spreading + has already been taken into account in the system PSF to avoid float counting. + + :param image: image array which is smoothed with the kernel + :type image: ndarray + :param sigma: widths of the gaussian kernel that approximates the charge diffusion [0.32, 0.32]. + :param sigma: tuple + + :return: smoothed image array + :rtype: ndarray + """ + return ndimage.filters.gaussian_filter(image, sigma) + def _loadGhostModel(self): """ @@ -835,12 +1520,12 @@ class MCIsimulator(): ############################################################################### ############################################################################### - def configure(self,simnumber): + def configure(self,simnumber,source): """ Configures the simulator with input information and creates and empty array to which the final image will be build on. """ - self.readConfigs(simnumber) + self.readConfigs(simnumber,source) self.processConfigs() @@ -862,13 +1547,13 @@ class MCIsimulator(): self.filter_psf=dict() filtername=self.filter_g - self.filter_psf['g']=np.load(self.information['indata_path']+'/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() + self.filter_psf['g']=np.load('../MCI_inputData/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() filtername=self.filter_r - self.filter_psf['r']=np.load(self.information['indata_path']+'/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() + self.filter_psf['r']=np.load('../MCI_inputData/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() filtername=self.filter_i - self.filter_psf['i']=np.load(self.information['indata_path']+'/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() + self.filter_psf['i']=np.load('../MCI_inputData/PSF/'+filtername+'_PSF.npy', allow_pickle=True).item() return @@ -983,17 +1668,17 @@ class MCIsimulator(): wave = np.linspace(2500,11000, 8501) # set the wavelenth for MCI from 250nm to 1100nm - wavearr =self.earthshine_wave # A - fluxarr =self.earthshine_flux # erg/s/cm^2/A/arcsec^2 - earthshinefluxarr=np.interp(wave, wavearr, fluxarr) # erg/s/cm^2/A/arcsec^2 + # wavearr =self.earthshine_wave # A + # fluxarr =self.earthshine_flux # erg/s/cm^2/A/arcsec^2 + # earthshinefluxarr=np.interp(wave, wavearr, fluxarr) # erg/s/cm^2/A/arcsec^2 - wavearr =self.zodiacal_wave # A - fluxarr =self.zodiacal_flux # erg/s/cm^2/A/arcsec^2 - zodiacalfluxarr=np.interp(wave, wavearr, fluxarr) # erg/s/cm^2/A/arcsec^2 + # wavearr =self.zodiacal_wave # A + # fluxarr =self.zodiacal_flux # erg/s/cm^2/A/arcsec^2 + # zodiacalfluxarr=np.interp(wave, wavearr, fluxarr) # erg/s/cm^2/A/arcsec^2 - skynoise_flux=earthshinefluxarr+zodiacalfluxarr # erg/s/cm^2/A/arcsec^2 + skynoise_flux=self.earthshine_flux+self.zodiacal_flux # erg/s/cm^2/A/arcsec^2 - wave = np.linspace(2500,10000,8501) # set the wavelenth for MCI from 250nm to 1100nm + wave=wave/10 # data: input data, two-dimentional, unit : 1e-17 erg/s/A/cm^2 @@ -1053,33 +1738,50 @@ class MCIsimulator(): pixelscale=self.information['pixel_size'] ## arcsec, pixel scale size ghostOffsetX =self.information['ghostoffsetx'] - ghostOffsetY =self.information['ghostoffsety'] - ghostMx =self.information['ghostratio'] + ghostOffsetY=self.information['ghostoffsety'] + ghostMx=self.information['ghostratio'] rotTelPos=self.information['rotTelPos'] rotSkyPos=self.information['rotSkyPos'] theta = rotTelPos - rotSkyPos - ############ load star data catlog ##################### - - df0=pd.read_csv(self.information['indata_path']+'/star_input/GaiaSource_675688-675713.csv') + ############ load star data catlog ##################### + starcat='selection_MACSJ0744.9 3927_20230517_concat.csv' + #starcat='selection_yuyong20230609_sim.csv' + + self.log.info('Stat catlog file name is %s' % (starcat)) + + df0=pandas.read_csv(self.information['dir_path']+'MCI_inputData/star_input/'+starcat) #### - df=df0.fillna(1000) - df2=df[ (df['phot_rp_mean_mag']>16)&(df['phot_bp_mean_mag']>16) & (df['phot_bp_mean_mag']<31) & (df['pmra']<100) & (df['phot_rp_mean_mag']<31)] + #df=df0.fillna(1000) + #df2=df[ (df['phot_rp_mean_mag']>16)&(df['phot_bp_mean_mag']>16) & (df['phot_bp_mean_mag']<31) & (df['pmra']<100) & (df['phot_rp_mean_mag']<31)] + #df2=df[ (df['umag']>16)&(df['zmag']>16) ] - df2.index = range(len(df2)) + #df2.index = range(len(df2)) ## limit the filed of view to 600*600 arcsec^2 square zone; - df3=df2[ (abs(df2['ra']-df2['ra'].mean())<300/3600.0) & (abs(df2['dec']-df2['dec'].mean())<300/3600.0) ] + df2=df0 + df3=df2[ (abs(df2['ra_gaia']-df2['ra_gaia'].mean())<400/3600.0) & (abs(df2['dec_gaia']-df2['dec_gaia'].mean())<400/3600.0) ] df3.index = range(len(df3)) + + np.save('umag.npy', df3['umag'] ) + + + + + self.star=df3 - del df0,df,df2,df3 + del df0,df2,df3 + + self.information['ra_obj'] = self.star['ra_gaia'].mean() + self.information['dec_obj'] = self.star['dec_gaia'].mean() - self.information['ra_obj'] = self.star['ra'].mean() - self.information['dec_obj'] = self.star['dec'].mean() + + self.information['star_ra'] = self.information['ra_obj'] + self.information['star_dec']= self.information['dec_obj'] center_ra =self.information['T_disRa'] +self.information['ra_obj'] center_dec=self.information['T_disDec'] +self.information['dec_obj'] @@ -1089,9 +1791,127 @@ class MCIsimulator(): channel=['g','r','i'] ####################################################################### - - nsrcs=len(self.star) + #################### cal_PSF_array ################################# + + + if self.save_starpsf: + + self.log.info('calculate and save star PSF data......') + + primary_g=fits.PrimaryHDU() + PSF_g=fits.HDUList([primary_g]) + + primary_r=fits.PrimaryHDU() + PSF_r=fits.HDUList([primary_r]) + + primary_i=fits.PrimaryHDU() + PSF_i=fits.HDUList([primary_i]) + + fov=0.05*min(self.information['xsize'],self.information['ysize']) + + dec_arr,ra_arr=make_c_coor(fov,25) + + k=0; + + ####################################################################### + for ii in range(len(ra_arr)): + for jj in range(len(ra_arr)): + + ################################################################## + + galRa = ra_arr[ii,jj] +center_ra*3600 # ra of PFS, arcsecond + galDec = dec_arr[ii,jj]+center_dec*3600 # dec of PSF, arcsecond + + fsx,fsy=cal_pos(center_ra,center_dec, rotTelPos, rotSkyPos, galRa, galDec) + + ############# do field distottion ########## + + if self.distortion: + + for i in range(3): + ch=channel[i] + fpx,fpy=distortField(fsx, fsy, ch) + + else: + + fpx=fsx + fpy=fsy + + ################################################################### + + psf=dict() + + for i in range(3): + + ch=channel[i] + + psfmat=self.get_PSF(fpx, fpy, ch) + + temp=0 + + for iwave in range(7): + temp=temp+1/7.0*psfmat[:,:,iwave] + + temp=temp/temp.sum() + + ####rotate the PSF data + if abs(theta.deg)>0: + psf[ch]=ndimage.rotate(temp, theta.deg, order=1, reshape=False) # here we choose reshape=False, the rotated image will + else: + psf[ch]=temp + ################################### + + hdu_g=fits.ImageHDU(psf['g']) + hdu_g.header['ra'] = ra_arr[ii,jj] + hdu_g.header['dec'] = dec_arr[ii,jj] + hdu_g.header['rot_deg']=-theta.deg + PSF_g.append(hdu_g) + ################################### + hdu_r=fits.ImageHDU(psf['r']) + hdu_r.header['ra'] = ra_arr[ii,jj] + hdu_r.header['dec'] = dec_arr[ii,jj] + hdu_r.header['rot_deg']=-theta.deg + PSF_r.append(hdu_r) + ################################### + hdu_i=fits.ImageHDU(psf['i']) + hdu_i.header['ra'] = ra_arr[ii,jj] + hdu_i.header['dec']= dec_arr[ii,jj] + hdu_i.header['rot_deg']=-theta.deg + PSF_i.append(hdu_i) + ################################### + del hdu_g + del hdu_r + del hdu_i + k=k+1 + + ############################################ + file_g=self.result_path+'/PSF_Data/'+'PSF_sim_No.'+str(self.information['simnumber'])+'_C1.fits' + PSF_g.writeto(file_g,overwrite=True) + + file_r=self.result_path+'/PSF_Data/'+'PSF_sim_No.'+str(self.information['simnumber'])+'_C2.fits' + PSF_r.writeto(file_r,overwrite=True) + + file_i=self.result_path+'/PSF_Data/'+'PSF_sim_No.'+str(self.information['simnumber'])+'_C3.fits' + PSF_i.writeto(file_i,overwrite=True) + + del PSF_g + del PSF_r + del PSF_i + ########## finish save PSF fits ########################################## + ############################################################################ + ###### add binary stars to the star catlog ####### + binary_star=np.array([[-0.05, 20, 20.5, 20, 19.5, 19, 18.8], + [-0.12, 20, 20.5, 20, 19.5, 19, 18.8], + [-5.45, 20, 20.5, 20, 19.5, 19, 18.8], + [-5.55, 20, 20.5, 20, 19.5, 19, 18.8], + [-10.05, 20, 20.5, 20, 19.5, 19, 18.8], + [-10.17, 20, 20.5, 20, 19.5, 19, 18.8], + [-15.45, 20, 20.5, 20, 19.5, 19, 18.8], + [-15.60, 20, 20.5, 20, 19.5, 19, 18.8]]) + + + nsrcs=len(self.star['ra_gaia']) + 8 ################################################################## obj=dict() obj['g']=np.zeros(3) @@ -1121,11 +1941,64 @@ class MCIsimulator(): final_image['i'].setOrigin(0,0) ####################################################################### nlayccd = 0 - - #### calculate sky noise ##### - self.earthshine(self.earthshine_theta) - self.zodiacal(self.information['ra_obj'], self.information['dec_obj'], self.dt.strftime("%Y-%m-%d")) + ############################################ + #### calculate sky noise , old code ##### + # self.earthshine(self.earthshine_theta) + + # self.zodiacal(self.information['ra_obj'], self.information['dec_obj'], self.dt.strftime("%Y-%m-%d")) + + ############### calculate the earthshine and zodiacal noise ,new code 2023.11.1 ############ + ############### + # self.earthshine(self.earthshine_theta) + # self.zodiacal(self.information['ra_obj'], self.information['dec_obj'], self.zodiacal_time) + + ra = self.information['ra_pnt0'] + dec = self.information['dec_pnt0'] + + time_jd=time2jd(self.dt) + + x_sat=float(self.orbit_pars[self.orbit_exp_num,1]) + y_sat=float(self.orbit_pars[self.orbit_exp_num,2]) + z_sat=float(self.orbit_pars[self.orbit_exp_num,3]) + + wave0, zodi0 = zodiacal(ra, dec, self.TianCe_day) # erg/s/cm^2/A/arcsec^2 + + # EarthShine from straylight + sl = StrayLight(jtime=time_jd, sat=np.array([x_sat, y_sat, z_sat]), + radec=np.array([(ra*u.degree).value, (dec*u.degree).value])) + + earth_e = sl.caculateEarthShineFilter(filter='r') + star_e = sl.caculateStarLightFilter(filter='r') + angle_earth = earth_angle(time_jd, x_sat, y_sat, z_sat, ra, dec) + + if angle_earth < 0: + earth_e = 0 + + earthshine_wave0, earthshine_flux0 = ill2flux(earth_e+star_e) + + # sample as ifs wavelength + wave_mci = np.linspace(2500, 11000, 8501) #np.arange(2500, 11000, 1) + f1 = interp1d(wave0, zodi0) + zodi_mci = f1(wave_mci) + + f2 = interp1d(earthshine_wave0, earthshine_flux0) + earthshine_mci = f2(wave_mci) + + # df = pd.DataFrame({'wave': wave_ifs, + # 'zodi': zodi_ifs, + # 'earthshine': earthshine_ifs}) + + self.zodiacal_wave = wave_mci # in A + self.zodiacal_flux = zodi_mci + + self.earthshine_wave = wave_mci # A + self.earthshine_flux = earthshine_mci + + ######################################################################################## + + + ######################################################################################### self.cal_sky_noise() @@ -1148,41 +2021,102 @@ class MCIsimulator(): ####################################################################### if self.TianceEffect: - ra_list = self.star['ra'].tolist() - dec_list = self.star['dec'].tolist() - pmra_list = self.star['pmra'].tolist() - pmdec_list = self.star['pmdec'].tolist() - parallax_list = self.star['parallax'].tolist() + ra_list = self.star['ra_gaia'].tolist() + dec_list = self.star['dec_gaia'].tolist() + pmra_list = self.star['pmra_gaia'].tolist() + pmdec_list = self.star['pmdec_gaia'].tolist() + parallax_list = self.star['parallax_gaia'].tolist() rv_list = [0.0 for i in range(len(ra_list))] - ################################################ - + ################################################ newRa, newDec = shao.onOrbitObsPosition(ra_list, dec_list, pmra_list, \ pmdec_list, rv_list, parallax_list, len(ra_list), \ self.information['pos_x'], self.information['pos_y'], self.information['pos_z'], self.information['velocity_x'],self.information['velocity_y'],self.information['velocity_z'], "J2000", self.TianCe_day, self.TianCe_exp_start) else: - newRa =self.star['ra'] - newDec =self.star['dec'] + newRa =self.star['ra_gaia'] + newDec =self.star['dec_gaia'] ###################################################### + + st_ra=[] + st_dec =[] + st_phot_C1=[] + st_phot_C2=[] + st_phot_C3=[] + + st_posX_C1=[] + st_posX_C2=[] + st_posX_C3=[] + + st_posY_C1=[] + st_posY_C2=[] + st_posY_C3=[] + + st_magu=[] + st_magg=[] + st_magr=[] + st_magi=[] + st_magz=[] + + #################### generate star image ########## - for j in tqdm(range(nsrcs)): ### nsrcs length + + if self.debug: + nstar=100 + else: + nstar=nsrcs + + sim_binary_star=False + + if sim_binary_star: + Nstar=nstar + else: + Nstar=nstar-8 + + for j in tqdm(range(Nstar)): ### nsrcs length - starRa = 3600.0*( newRa[j] ) # ra of star, arcsecond - starDec = 3600.0*( newDec[j] ) # dec of star, arcsecond - + if j=self.information['ysize']+100 or row<=-100 or col>=self.information['xsize']+100 or col <=-100: continue nlayccd=nlayccd+1 + + if self.debug: + if nlayccd>10: + continue + + st_ra.append( np.float64(starRa/3600.0)) + st_dec.append(np.float64(starDec/3600.0)) + ################################################################ for i in range(3): ### @@ -1225,39 +2159,81 @@ class MCIsimulator(): # SED of j-th star if j0.1/1500: + if ghostphotons.flux.max()>0.01: ghostphotons.addTo(final_image[ch]) - - ######################################################### - photons.x=photons.x/0.05+gy[ch] - photons.y=photons.y/0.05+gx[ch] - - photons.addTo(final_image[ch]) - - - ############################################################### + ############################################################### - #print('total star nummber on CCD is: ',nlayccd ) + print('total star nummber on CCD is: ',nlayccd ) + + tab=Table() + tab['st_ra'] =np.asarray(st_ra) + tab['st_dec'] =np.asarray(st_dec) + + tab['phot_C1']=np.asarray(st_phot_C1) + tab['phot_C2']=np.asarray(st_phot_C2) + tab['phot_C3']=np.asarray(st_phot_C3) + + tab['posX_C1']=np.asarray(st_posX_C1) + tab['posX_C2']=np.asarray(st_posX_C2) + tab['posX_C3']=np.asarray(st_posX_C3) + + tab['posY_C1']=np.asarray(st_posY_C1) + tab['posY_C2']=np.asarray(st_posY_C2) + tab['posY_C3']=np.asarray(st_posY_C3) + + + tab['st_magu']=np.asarray(st_magu) + tab['st_magg']=np.asarray(st_magg) + tab['st_magr']=np.asarray(st_magr) + tab['st_magi']=np.asarray(st_magi) + tab['st_magz']=np.asarray(st_magz) + + + + ###################################33 + + + file=self.result_path+'/log_Data/star_info'+'_SN_'+str(self.information['simnumber'])+'.fits' + tab.write(file,overwrite=True) ################################################################# - - ####################################################################### + ################################################################# fullimg['g']=final_image['g'].array fullimg['r']=final_image['r'].array @@ -1375,19 +2388,19 @@ class MCIsimulator(): """ # read solar template - solar_template = pd.read_csv(self.information['indata_path']+'/refs/solar_spec.dat', sep='\s+', + solar_template = pd.read_csv('../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['indata_path']+'/refs/earthshine.dat', + earthshine_curve = pd.read_csv('../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['indata_path']+'/refs/filter_Bessell_V.dat', sep='\s+', + cat_filter_V = pd.read_csv('../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 @@ -1435,7 +2448,9 @@ class MCIsimulator(): # get solar position dt = datetime.fromisoformat(time) - jd = julian.to_jd(dt, fmt='jd') + ###jd = julian.to_jd(dt, fmt='jd') + + jd = time2jd(dt) t = Time(jd, format='jd', scale='utc') astro_sun = get_sun(t) @@ -1452,25 +2467,21 @@ class MCIsimulator(): lamda = abs(lb_obj.lon.degree - lb_sun.lon.degree) # interpolated zodical surface brightness at 0.5 um - zodi = pd.read_csv(self.information['indata_path']+'/refs/zodi_map.dat', sep='\s+', header=None, comment='#') + zodi = pd.read_csv('../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) # + zodi_obj = f(beta, lamda) # 10^�? W m�? sr�? um�? # read the zodical spectrum in the ecliptic - cat_spec = pd.read_csv(self.information['indata_path']+'/refs/solar_spec.dat', sep='\s+', header=None, comment='#') + cat_spec = pd.read_csv('../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 # + 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 # + 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 @@ -1498,11 +2509,12 @@ class MCIsimulator(): ### galaxy catlog information ra = 74.0563449685417 dec = -34.155241212932374 - # halo_id = 229600100382 - - self.information['star_ra'] = 249.70093286177536 - self.information['star_dec'] =-44.60485406119162 + # halo_id = 229600100382 + if self.sim_star ==False : + self.information['star_ra'] = ra + self.information['star_dec'] = dec + self.information['gal_ra'] = ra self.information['gal_dec']= dec @@ -1510,10 +2522,55 @@ class MCIsimulator(): self.information['dec_obj'] =self.information['star_dec'] ##################################################################### - self.earthshine(self.earthshine_theta) + # self.earthshine(self.earthshine_theta) - self.zodiacal(self.information['star_ra'], self.information['star_dec'], self.dt.strftime("%Y-%m-%d")) + # self.zodiacal(self.information['star_ra'], self.information['star_dec'], self.dt.strftime("%Y-%m-%d")) + ################################################################################## + ra = self.information['ra_pnt0'] + dec = self.information['dec_pnt0'] + time_jd=time2jd(self.dt) + + x_sat=float(self.orbit_pars[self.orbit_exp_num,1]) + y_sat=float(self.orbit_pars[self.orbit_exp_num,2]) + z_sat=float(self.orbit_pars[self.orbit_exp_num,3]) + + wave0, zodi0 = zodiacal(ra, dec, self.TianCe_day) # erg/s/cm^2/A/arcsec^2 + + # EarthShine from straylight + sl = StrayLight(jtime=time_jd, sat=np.array([x_sat, y_sat, z_sat]), + radec=np.array([(ra*u.degree).value, (dec*u.degree).value])) + + earth_e = sl.caculateEarthShineFilter(filter='r') + star_e = sl.caculateStarLightFilter(filter='r') + angle_earth = earth_angle(time_jd, x_sat, y_sat, z_sat, ra, dec) + + if angle_earth < 0: + earth_e = 0 + + earthshine_wave0, earthshine_flux0 = ill2flux(earth_e+star_e) + + # sample as ifs wavelength + wave_mci = np.linspace(2500, 11000, 8501) #np.arange(2500, 11000, 1) + f1 = interp1d(wave0, zodi0) + zodi_mci = f1(wave_mci) + + f2 = interp1d(earthshine_wave0, earthshine_flux0) + earthshine_mci = f2(wave_mci) + + # df = pd.DataFrame({'wave': wave_ifs, + # 'zodi': zodi_ifs, + # 'earthshine': earthshine_ifs}) + + self.zodiacal_wave = wave_mci # in A + self.zodiacal_flux = zodi_mci + + self.earthshine_wave = wave_mci # A + self.earthshine_flux = earthshine_mci + + ######################################################################################## + + ################################################################################## self.cal_sky_noise() ############ load galaxy data with SED ############################ @@ -1575,57 +2632,145 @@ class MCIsimulator(): final_image['i'].setOrigin(0,0) - #################################################################### + #################################################################### + + gal_ra=[]##.append(np.float64(galRa/3600.0)) + gal_dec=[]###.append(np.float64(galDec/3600.0)) + + phot_C1=[]##.append(intscales['g']) + phot_C2=[]###.append(intscales['r']) + phot_C3=[]###.append(intscales['i']) + + posX_C1=[]##.append(gx['g']) + posX_C2=[]#.append(gx['r']) + posX_C3=[]#.append(gx['i']) + + posY_C1=[]#.append(gy['g']) + posY_C2=[]#.append(gy['r']) + posY_C3=[]#.append(gy['i']) + + + gal_magu=[] + gal_magg=[] + gal_magr=[] + gal_magi=[] + gal_magz=[] + + ######################################## nlayccd = 0 ####################generate loc image - for k2 in (range(13)): ### + + if self.debug: + nk2=1 + else: + nk2=1 + + for k2 in (range(nk2)): ### print('k2=',k2) # - filename=self.information['indata_path']+'/galaxy_Input/Lens_SED_IMG_V3_0.025/Lens_img_cut_IMG_'+str(k2+1)+'.fits' + filename='../MCI_inputData/galaxy_Input/noLens_SED_IMG_0.025_230626/Lens_img_cut_IMG_'+str(k2+1)+'.fits' + self.log.info('galaxy_Input image path is: %s' %(filename)) + if not os.path.exists(filename): - #print('finish load all the input galaxy image fits files already') + print('finish load all the input galaxy image fits files') break srcs_cat=fits.open(filename) #### load galaxy SED fitsfile ### - filename=self.information['indata_path']+'/galaxy_Input/Lens_SED_IMG_V3_0.025/Lens_img_cut_SED_'+str(k2+1)+'.fits' - srcs_sed=fits.open(filename) + filename='../MCI_inputData/galaxy_Input/noLens_SED_IMG_0.025_230626/Lens_img_cut_SED_'+str(k2+1)+'.fits' + srcs_sed=fits.open(filename) - ################################################################### - for k1 in tqdm(range(1,len(srcs_cat))): - + self.log.info('galaxy_Input SED path is: %s' %(filename)) + + ###### do Tiance Effect ### + ra_list =[] + dec_list=[] + + + for kkk in range(1,len(srcs_cat)): + t1=srcs_cat[kkk].header['new_ra'] -self.information['gal_ra'] +self.information['star_ra'] + ra_list.append(t1) - galRa = 3600*(srcs_cat[k1].header['new_ra'] -self.information['gal_ra'] +self.information['star_ra']) # ra of galaxies, arcsecond - galDec = 3600*(srcs_cat[k1].header['new_dec']-self.information['gal_dec']+self.information['star_dec']) # dec of galaxies, arcsecond - + t2=srcs_cat[kkk].header['new_dec'] -self.information['gal_dec'] +self.information['star_dec'] + dec_list.append(t2) + + + if self.TianceEffect: + + pmra_list = [0.0 for i in range(len(ra_list))] + pmdec_list = [0.0 for i in range(len(ra_list))] + parallax_list = [0.0 for i in range(len(ra_list))] + rv_list = [0.0 for i in range(len(ra_list))] + + ################################################ + newRa, newDec = shao.onOrbitObsPosition(ra_list, dec_list, pmra_list, \ + pmdec_list, rv_list, parallax_list, len(ra_list), \ + self.information['pos_x'], self.information['pos_y'], self.information['pos_z'], self.information['velocity_x'],self.information['velocity_y'],self.information['velocity_z'], "J2000", self.TianCe_day, self.TianCe_exp_start) + else: + newRa =ra_list + newDec =dec_list + + + ############################################################################ + ################################################################### + for k1 in tqdm(range(len(newRa))): + + #print('k1=', k1) + + galRa = newRa[k1]*3600##*(srcs_cat[k1].header['new_ra'] -self.information['gal_ra'] +self.information['star_ra']) # ra of galaxies, arcsecond + galDec = newDec[k1]*3600####(srcs_cat[k1].header['new_dec']-self.information['gal_dec']+self.information['star_dec']) # dec of galaxies, arcsecond + #spa = srcs_cat[k1].header['spa'] + + + ########################################################################### + ############################################################################ + ### test code #### + # galRa=self.information['star_ra']*3600 + # galDec=self.information['star_dec']*3600 + ########### + # tx, ty = world_to_pixel(galRa/3600, + # galDec/3600, + # theta.deg, + # center_ra, + # center_dec, + # self.information['xsize']/2-0.5, + # self.information['ysize']/2-0.5, + # pixelsize=0.05) + ################################################################# fsx,fsy=cal_pos(center_ra,center_dec, rotTelPos, rotSkyPos, galRa, galDec) - row= fsy/losscale+self.information['ysize']/2-0.5 ### row number on CCD image, dec direction ,y direction - col= fsx/losscale+self.information['xsize']/2-0.5 ### col number on CCD image, ra direction, x direction + # row= fsy/losscale+self.information['ysize']/2-0.5 ### row number on CCD image, dec direction ,y direction + # col= fsx/losscale+self.information['xsize']/2-0.5 ### col number on CCD image, ra direction, x direction + - if row>=self.information['ysize']+100 or row<=-100 or col>=self.information['xsize']+100 or col <=-100: + if abs(fsx)>235 or abs(fsy)>235: continue + + # if row>=self.information['ysize']+200 or row<=-200 or col>=self.information['xsize']+200 or col <=-200: + # continue - # # SED of j-th galaxy ,# unit of 10-17 erg/s/A/cm2 - gal_flux=srcs_sed[k1].data + # # SED of j-th galaxy ,# unit of 10-17 erg/s/A/cm2 + gal_flux=srcs_sed[k1+1].data ## here is k1+1, not k1, k1 begins with 0 + + # print('nlaccd = ', nlayccd) ################################ ### rotate the lensed_images_g ### if abs(theta.deg)>0: - lensed_images_g=ndimage.rotate(srcs_cat[k1].data, -theta.deg, order=1, reshape=True) # here we choose reshape=False, the rotated image will + lensed_images_g=ndimage.rotate(srcs_cat[k1+1].data, -theta.deg, order=1, reshape=True) # here we choose reshape=False, the rotated image will else: - lensed_images_g=srcs_cat[k1].data + lensed_images_g=srcs_cat[k1+1].data + if lensed_images_g.sum()<=0: continue - nlayccd=nlayccd+1 ################################################################ for i in range(3): @@ -1633,7 +2778,7 @@ class MCIsimulator(): ch=channel[i] galaxy_input[ch][int(nlayccd)-1, 0] =fsx #ra galaxy_input[ch][int(nlayccd)-1, 1] =fsy #dec - # + #galaxy_input[ch][int(nlayccd)-1, 2] =mag[ch] # mag g ############# do field distottion ########## @@ -1646,40 +2791,80 @@ class MCIsimulator(): fpx,fpy=distortField(fsx, fsy, ch) obj[ch][0]=fpx obj[ch][1]=fpy - + #obj[ch][2]=mag[ch] + galaxy_output[ch][int(nlayccd)-1, 0] =fpx #ra galaxy_output[ch][int(nlayccd)-1, 1] =fpy #dec - + #galaxy_output[ch][int(nlayccd)-1, 2] =mag[ch] # mag g + + else: fpx=fsx fpy=fsy + for i in range(3): ch=channel[i] obj[ch][0]=fpx - obj[ch][1]=fpy - + obj[ch][1]=fpy + #obj[ch][2]=mag[ch] + galaxy_output[ch][int(nlayccd)-1, 0] =fpx #ra galaxy_output[ch][int(nlayccd)-1, 1] =fpy #dec - + #galaxy_output[ch][int(nlayccd)-1, 2] =mag[ch] # mag g ####################################################################### - - self.log.info('Galaxy number=%i, Ra(in arcsec)=%f, Dec(in arcsec)=%f' % (nlayccd, fpx, fpy)) - + #self.log.info('Galaxy number=%i, Ra(in arcsec)=%f, Dec(in arcsec)=%f' % (nlayccd, fpx, fpy)) + #self.log.info('Galaxy number=%i, Mag_g=%f, Mag_r=%f,Mag_i=%f' % (nlayccd, mag['g'],mag['r'],mag['i'])) + + #print('Flux sum =', gal_flux.sum()) + ##cal_SED_photons(self, flux_arr): intscales,PSF_eff_weight=self.cal_SED_photons(gal_flux) + + + ls_imgsum=lensed_images_g.sum() + + if intscales['g'].max()/ls_imgsum<0.1 and intscales['r'].max()/ls_imgsum<0.1 and intscales['i'].max()/ls_imgsum<0.1: + ######### + continue + ######## test code ########## + + if self.debug: + if nlayccd>10: + ######### + continue + + ############################33 img=dict() - lensed_images_g=lensed_images_g/lensed_images_g.sum() + lensed_images_g=lensed_images_g/ls_imgsum img['g']=lensed_images_g*intscales['g'] img['r']=lensed_images_g*intscales['r'] img['i']=lensed_images_g*intscales['i'] + if img['g'].max()<0.01 and img['r'].max()<0.01 and img['i'].max()<0.01: + ######### + continue + + + + nlayccd=nlayccd+1 + + + ####### test code only ######## + # img['g']=lensed_images_g + # img['r']=lensed_images_g + # img['i']=lensed_images_g + # print('------------------------------------') + # print('galaxy mag=',srcs_cat[k1].header['magu'] ,srcs_cat[k1].header['magg'] ,srcs_cat[k1].header['magr'],srcs_cat[k1].header['magi'],srcs_cat[k1].header['magz']) + # print('total photons=', intscales['g'],intscales['r'],intscales['i']) + # print('k1 =',k1) + ################################################ gx=dict() @@ -1692,7 +2877,43 @@ class MCIsimulator(): gy[ch]= obj[ch][1]/losscale+self.information['ysize']/2-0.5 ### row number on CCD image gx[ch]= obj[ch][0]/losscale+self.information['xsize']/2-0.5 ### col number on CCD image - ###################################################################### + ###################################################################### + + + + gal_ra.append(np.float64(galRa/3600.0)) + gal_dec.append(np.float64(galDec/3600.0)) + + phot_C1.append(intscales['g']) + phot_C2.append(intscales['r']) + phot_C3.append(intscales['i']) + + posX_C1.append(gx['g']) + posX_C2.append(gx['r']) + posX_C3.append(gx['i']) + + posY_C1.append(gy['g']) + posY_C2.append(gy['r']) + posY_C3.append(gy['i']) + + + gal_magu.append(srcs_cat[k1+1].header['magu']) + gal_magg.append(srcs_cat[k1+1].header['magg']) + gal_magr.append(srcs_cat[k1+1].header['magr']) + gal_magi.append(srcs_cat[k1+1].header['magi']) + gal_magz.append(srcs_cat[k1+1].header['magz']) + + #self.log.info('Galaxy number=%i, Mag_g=%f, Mag_r=%f,Mag_i=%f' % (nlayccd, mag['g'],mag['r'],mag['i'])) + + if nlayccd %1000 ==0: + self.log.info('Galaxy number on CCD is = %i' % (nlayccd)) + # gal_magu.append(np.float64(self.star['umag'][j])) + # gal_magg.append(np.float64(self.star['gmag'][j])) + # gal_magr.append(np.float64(self.star['rmag'][j])) + # gal_magi.append(np.float64(self.star['imag'][j])) + # gal_magz.append(np.float64(self.star['zmag'][j])) + + psf=dict() @@ -1700,7 +2921,7 @@ class MCIsimulator(): for i in range(3): ch=channel[i] - + psfmat=self.get_PSF(fsx, fsy, ch) temp=0 @@ -1716,8 +2937,11 @@ class MCIsimulator(): else: psf[ch]=temp + conv = fftconvolve(img[ch], psf[ch], mode='full') - #suppress negative numbers + #continue + #suppress negative numbers + conv[conv < 0.0] = 0.0 ################################################# @@ -1767,12 +2991,52 @@ class MCIsimulator(): photons.addTo(final_image[ch]) #################################################### + ### debug code + # fi= galsim.ImageF(int(self.information['xsize']), int(self.information['ysize'])) + # fi.setOrigin(0,0) + # photons.addTo(fi) + # cx,cy=centroid(fi.array) + # print('cx, cy=', cx, cy) + # print('gx, gy=' ,gx[ch],gy[ch]) + ############################################ + ############################################ ######################################################################## - ##print('total los nummber on CCD is: ',nlayccd ) + print('total los nummber on CCD is: ',nlayccd ) ################################################################# - ################################################################# + tab=Table() + tab['gal_ra']=np.asarray(gal_ra) + tab['gal_dec']=np.asarray(gal_dec) + + tab['phot_C1']=np.asarray(phot_C1) + tab['phot_C2']=np.asarray(phot_C2) + tab['phot_C3']=np.asarray(phot_C3) + + tab['posX_C1']=np.asarray(posX_C1) + tab['posX_C2']=np.asarray(posX_C2) + tab['posX_C3']=np.asarray(posX_C3) + + tab['posY_C1']=np.asarray(posY_C1) + tab['posY_C2']=np.asarray(posY_C2) + tab['posY_C3']=np.asarray(posY_C3) + + + tab['gal_magu']=np.asarray(gal_magu) + tab['gal_magg']=np.asarray(gal_magg) + tab['gal_magr']=np.asarray(gal_magr) + tab['gal_magi']=np.asarray(gal_magi) + tab['gal_magz']=np.asarray(gal_magz) + + + data_time=self.dt.strftime("%Y-%m-%d") + + #################################################################### + + file=self.result_path+'/log_Data/gal_info'+'_SN_'+str(self.information['simnumber'])+'.fits' + tab.write(file,overwrite=True) + + ####################################################################### fullimg['g']=final_image['g'].array fullimg['r']=final_image['r'].array @@ -1783,6 +3047,8 @@ class MCIsimulator(): ############################################################################### +############################################################################### + ############################################################################### def generatePRNU(self, ave=1.0, sigma=0.01): @@ -1854,9 +3120,9 @@ class MCIsimulator(): the sky. """ ### generate flatfiledfile, with - prnu_sigma=self.information['prnu_sigma'] + flatsigma=self.information['flatsigma'] - self.generatePRNU(ave=1.0, sigma=prnu_sigma) + self.generatePRNU(ave=1.0, sigma=flatsigma) self.image_g *= self.PRNU['g'] self.image_r *= self.PRNU['r'] self.image_i *= self.PRNU['i'] @@ -1876,7 +3142,7 @@ class MCIsimulator(): self.cr['exptime'] = self.information['exptime'] #to scale the number of cosmics with exposure time #cosmic ray image - crImage = np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) + crImage = np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) #cosmic ray instance cosmics_g = cosmicrays.cosmicrays(self.log, crImage, crInfo=self.cr) @@ -1884,42 +3150,47 @@ class MCIsimulator(): cosmics_i = cosmicrays.cosmicrays(self.log, crImage, crInfo=self.cr) #add cosmic rays up to the covering fraction - - CCD_cr_g = cosmics_g.addUpToFraction(self.information['coveringfraction'], limit=None) - CCD_cr_r = cosmics_r.addUpToFraction(self.information['coveringfraction'], limit=None) - CCD_cr_i = cosmics_i.addUpToFraction(self.information['coveringfraction'], limit=None) + #CCD_cr = cosmics.addUpToFraction(self.information['coveringFraction'], limit=None) + + CCD_cr_g = cosmics_g.addUpToFraction(self.information['coveringfraction']*self.information['exptime']/300.0, limit=None) + CCD_cr_r = cosmics_r.addUpToFraction(self.information['coveringfraction']*self.information['exptime']/300.0, limit=None) + CCD_cr_i = cosmics_i.addUpToFraction(self.information['coveringfraction']*self.information['exptime']/300.0, limit=None) #paste the information - + #self.image += CCD_cr self.image_g += CCD_cr_g self.image_r += CCD_cr_r self.image_i += CCD_cr_i #save cosmic ray image map - - self.cosmicMap_g = CCD_cr_g - self.cosmicMap_r = CCD_cr_r - self.cosmicMap_i = CCD_cr_i - + #self.cosmicMap = CCD_cr + + if self.save_cosmicrays and self.cosmicRays: + + self.log.info('Saved the cosmicRays fits...') + fits.writeto(self.result_path+'/ori_Sky/cosmicMap_C1_N_'+str(self.information['simnumber'])+'.fits',np.int32(CCD_cr_g), overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/cosmicMap_C2_N_'+str(self.information['simnumber'])+'.fits',np.int32(CCD_cr_r), overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/cosmicMap_C3_N_'+str(self.information['simnumber'])+'.fits',np.int32(CCD_cr_i), overwrite=True) + + #count the covering factor - - area_cr_g = np.count_nonzero(self.cosmicMap_g) - area_cr_r = np.count_nonzero(self.cosmicMap_r) - area_cr_i = np.count_nonzero(self.cosmicMap_i) + #area_cr = np.count_nonzero(self.cosmicMap) + area_cr_g = np.count_nonzero(CCD_cr_g) + area_cr_r = np.count_nonzero(CCD_cr_r) + area_cr_i = np.count_nonzero(CCD_cr_i) #self.log.info('The cosmic ray covering factor is %i pixels ' % area_cr) - self.log.info('The cosmic ray in G channel covering factor is %i pixels ' % area_cr_g) - self.log.info('The cosmic ray in R channel covering factor is %i pixels ' % area_cr_r) - self.log.info('The cosmic ray in I channel covering factor is %i pixels ' % area_cr_i) - - + self.log.info('The cosmic ray in C1 channel covering factor is %i pixels ' % area_cr_g) + self.log.info('The cosmic ray in C2 channel covering factor is %i pixels ' % area_cr_r) + self.log.info('The cosmic ray in C3 channel covering factor is %i pixels ' % area_cr_i) + ######################################################################################## - def ShutterEffectMat(self, img, t_exp, t_shutter=1.3, dist_bearing=4000, dt=0.001): + def ShutterEffectMat(self, img, t_exp=300, t_shutter=1.3, dist_bearing=4000, dt=0.001): # Generate Shutter-Effect normalized image # t_shutter: time of shutter movement # dist_bearing: distance between two bearings of shutter leaves - # dt: delta_t of sampling + # dt: delta_t of sampling SampleNumb = int(t_shutter/dt+1) @@ -1977,24 +3248,30 @@ class MCIsimulator(): exparrnormal = np.tile(expeffect, (sizey,1)) # Image *= exparrnormal + + shutter=(1-exparrnormal)*t_exp + shutter=shutter/shutter.max()*(t_shutter*2) - return exparrnormal + return shutter ######################################################################################## def addshuttereffect(self): ''' apply shutter effect to image''' # - self.shutterMat=self.ShutterEffectMat(self.image_g, self.information['exptime']) - self.image_g *= self.shutterMat - self.image_r *= self.shutterMat - self.image_i *= self.shutterMat + if self.information['exptime']>0: + self.shutter=self.ShutterEffectMat(self.image_g) + + self.shutterMat=1-self.shutter/self.information['exptime'] + + self.image_g *= self.shutterMat + self.image_r *= self.shutterMat + self.image_i *= self.shutterMat + if self.information['simnumber']==1: + fits.writeto(self.result_path+'/cali_Data/'+'shutter.fits', self.shutter, overwrite=True) + return - -############################################################################### -############################################################################### - - +######################################################################################## def applyDarkCurrent(self): """ Apply dark current. Scales the dark with the exposure time. @@ -2008,39 +3285,33 @@ class MCIsimulator(): self.image_g += dark self.image_r += dark self.image_i += dark - self.log.info('Added dark current = %f' % dark) - return ########################################################################### - - ########################################################################### def applyPoissonSkyNoise(self): """ Add Poisson sky noise to the image. """ - skynoise_g=self.Sky_Noise['g']*np.ones_like(self.image_g) - np.random.seed() + + np.random.seed(11*self.information['simnumber']) self.image_g =self.image_g+ np.random.poisson(lam=skynoise_g) self.log.info('Added Poisson sky noise on channel g') skynoise_r=self.Sky_Noise['r']*np.ones_like(self.image_r) - np.random.seed() + np.random.seed(111*self.information['simnumber']) self.image_r =self.image_r+ np.random.poisson(lam=skynoise_r) self.log.info('Added Poisson sky noise on channel r') skynoise_i=self.Sky_Noise['i']*np.ones_like(self.image_i) - np.random.seed() + np.random.seed(1111*self.information['simnumber']) self.image_i =self.image_i+ np.random.poisson(lam=skynoise_i) self.log.info('Added Poisson sky noise on channel i') return - ############################################################################### - ############################################################################### def applyCosmetics(self): """ @@ -2051,15 +3322,15 @@ class MCIsimulator(): .. Warning:: This method does not work if the input file has exactly one line. """ ####################################################################### - cosmetics = np.loadtxt(self.information['indata_path']+'/data/Cosmetics_g.txt') + cosmetics = np.loadtxt('../MCI_inputData/data/Cosmetics_g.txt') x = np.round(cosmetics[:, 0]).astype(int) ## row number y = np.round(cosmetics[:, 1]).astype(int) ## col number - value = np.round(cosmetics[:, 1]).astype(int) + value = np.round(cosmetics[:, 2]).astype(int) #cosmetics_g=np.zeros((4636,235526)) - self.log.info('Adding cosmetic defects to G channel:' ) + self.log.info('Adding cosmetic defects to C1 channel:' ) for xc, yc, val in zip(x, y, value): if 0 < xc < 4616 and 27 < (yc % 1499) <1179: @@ -2068,15 +3339,15 @@ class MCIsimulator(): self.log.info('x=%i, y=%i, value=%f' % (xc, yc, val)) ###################################################################### ####################################################################### - cosmetics = np.loadtxt(self.information['indata_path']+'/data/Cosmetics_r.txt') + cosmetics = np.loadtxt('../MCI_inputData/data/Cosmetics_r.txt') x = np.round(cosmetics[:, 0]).astype(int) ## row number y = np.round(cosmetics[:, 1]).astype(int) ## col number - value = np.round(cosmetics[:, 1]).astype(int) + value = np.round(cosmetics[:, 2]).astype(int) #cosmetics_r=np.zeros((4636,235526)) - self.log.info('Adding cosmetic defects to R channel:' ) + self.log.info('Adding cosmetic defects to C2 channel:' ) for xc, yc, val in zip(x, y, value): if 0 < xc < 4616 and 27 < (yc % 1499) <1179: @@ -2085,23 +3356,36 @@ class MCIsimulator(): self.log.info('x=%i, y=%i, value=%f' % (xc, yc, val)) ############################################################################## ####################################################################### - cosmetics = np.loadtxt(self.information['indata_path']+'/data/Cosmetics_i.txt') + cosmetics = np.loadtxt('../MCI_inputData/data/Cosmetics_i.txt') x = np.round(cosmetics[:, 0]).astype(int) ## row number y = np.round(cosmetics[:, 1]).astype(int) ## col number - value = np.round(cosmetics[:, 1]).astype(int) + value = np.round(cosmetics[:, 2]).astype(int) #cosmetics_i=np.zeros((4636,235526)) - self.log.info('Adding cosmetic defects to I channel:' ) + self.log.info('Adding cosmetic defects to C3 channel:' ) for xc, yc, val in zip(x, y, value): if 0 < xc < 4616 and 27 < (yc % 1499) <1179: self.image_i[xc, yc] = val #cosmetics_i[yc,xc]=val self.log.info('x=%i, y=%i, value=%f' % (xc, yc, val)) - return - + + ####### save cosmetics image code #### + # if self.simnumber<2: + # #save cosmic ray image map + + # obsid=self.simnumber + # bluefile=self.result_path+'/calibration_Data/IFS_cosmetics'+'_'+str(obsid)+'_B.fits' + # redfile =self.result_path+'/calibration_Data/IFS_cosmetics'+'_'+str(obsid)+'_R.fits' + + # fits.writeto(bluefile, cosmetics_b, overwrite=True) + # fits.writeto(redfile, cosmetics_r, overwrite=True) + + # #output information to a FITS file + + # self.log.info('Save cosmetics images fits file to calibration_Data file ') ############################################################################################################################# def applyRadiationDamage(self): """ @@ -2109,8 +3393,6 @@ class MCIsimulator(): .. seealso:: Class :`CDM03` """ - - #save image without CTI self.noCTI_g = self.image_g.copy() @@ -2148,7 +3430,6 @@ class MCIsimulator(): #here we need the right input data self.image_i = cti.applyRadiationDamage(self.image_i.copy().transpose(), iquadrant=self.information['quadrant']).transpose() self.log.info('Radiation damage added.') - return ########################################################################### @@ -2160,20 +3441,19 @@ class MCIsimulator(): """ self.log.debug('Starting to apply non-linearity model...') - self.image_g = MCIinstrumentModel.CCDnonLinearityModel(self.image_g.copy()) + self.image_g = CCDnonLinearityModel(self.image_g.copy()) self.log.info('Non-linearity effects included.') ######################################################################## self.log.debug('Starting to apply non-linearity model...') - self.image_r = MCIinstrumentModel.CCDnonLinearityModel(self.image_r.copy()) + self.image_r = CCDnonLinearityModel(self.image_r.copy()) self.log.info('Non-linearity effects included.') ######################################################################## self.log.debug('Starting to apply non-linearity model...') - self.image_i = MCIinstrumentModel.CCDnonLinearityModel(self.image_i.copy()) + self.image_i = CCDnonLinearityModel(self.image_i.copy()) self.log.info('Non-linearity effects included.') - return ############################################################################### @@ -2184,7 +3464,7 @@ class MCIsimulator(): The noise is drawn from a Normal (Gaussian) distribution with average=0.0 and std=readout noise. """ - if self.information['xsize']==9216 and self.information['ysize']==9232 : + if self.overscans and self.information['xsize']==9216 and self.information['ysize']==9232 : xmin=dict() xmax=dict() ymin=dict() @@ -2198,17 +3478,17 @@ class MCIsimulator(): ymin[k]=(1152+self.prescan+self.overscan)*(k-1) ymax[k]=(1152+self.prescan+self.overscan)*(k) ############### - np.random.seed() + np.random.seed(2*self.information['simnumber']) noise_g = np.random.normal(loc=0.0, scale=self.information['g_rdnois'+str(k)], size=(4616+self.overscan,1152+self.overscan+self.prescan)) self.image_g[xmin[k]:xmax[k], ymin[k]:ymax[k]]+=noise_g self.log.info('Bias of %i counts were added to the g band image' % self.information['g_rdnois'+str(k)]) - np.random.seed() + np.random.seed(22*self.information['simnumber']) noise_r = np.random.normal(loc=0.0, scale=self.information['r_rdnois'+str(k)], size=(4616+self.overscan,1152+self.overscan+self.prescan)) self.image_r[xmin[k]:xmax[k], ymin[k]:ymax[k]]+=noise_r self.log.info('Bias of %i counts were added to the r band image' % self.information['r_rdnois'+str(k)]) - np.random.seed() + np.random.seed(222*self.information['simnumber']) noise_i = np.random.normal(loc=0.0, scale=self.information['i_rdnois'+str(k)], size=(4616+self.overscan,1152+self.overscan+self.prescan)) self.image_i[xmin[k]:xmax[k], ymin[k]:ymax[k]]+=noise_i self.log.info('Bias of %i counts were added to the i band image' % self.information['i_rdnois'+str(k)]) @@ -2217,21 +3497,21 @@ class MCIsimulator(): else: - np.random.seed() + np.random.seed(3*self.information['simnumber']) noise = np.random.normal(loc=0.0, scale=4, size=self.image_g.shape) self.log.info('Sum of readnoise in g channel = %f' % np.sum(noise)) #add to the image self.image_g += noise ####################################################### - np.random.seed() + np.random.seed(33*self.information['simnumber']) noise = np.random.normal(loc=0.0, scale=4, size=self.image_r.shape) self.log.info('Sum of readnoise in r channel= %f' % np.sum(noise)) #add to the image self.image_r += noise ######################################## - np.random.seed() + np.random.seed(333*self.information['simnumber']) noise = np.random.normal(loc=0.0, scale=4, size=self.image_i.shape) self.log.info('Sum of readnoise in i channel= %f' % np.sum(noise)) #add to the image @@ -2307,7 +3587,36 @@ class MCIsimulator(): ### end for return -############################################################################## +############################################################################## + def img_fits_save(self, data, filename): + #### + + ofd_g = fits.PrimaryHDU() + #### World coordinate system and related parameters ##### + hdu_g = fits.ImageHDU(data) + + hdu_g.header['WCSAXES']=(np.int16(2) , 'number of World Coordinate System axes') + hdu_g.header['CRPIX1'] =( round(float(self.information['CRPIX1']) ,1) , 'x-coordinate of reference pixel') + hdu_g.header['CRPIX2'] =( round(float(self.information['CRPIX2']) ,1) , 'y-coordinate of reference pixel') + + hdu_g.header['CRVAL1'] =( float(self.information['CRVAL1']) , 'first axis value at reference pixel') + hdu_g.header['CRVAL2'] =( float(self.information['CRVAL2']) , 'second axis value at reference pixel') + hdu_g.header['CTYPE1'] =( 'RA---TAN' , 'the coordinate type for the first axis') + hdu_g.header['CTYPE2'] =( 'DEC--TAN' , 'the coordinate type for the second axis') + hdu_g.header['CD1_1'] =( float(self.information['CD1_1']) , 'partial of first axis coordinate w.r.t. x') + hdu_g.header['CD1_2'] =( float(self.information['CD1_2']) , 'partial of first axis coordinate w.r.t. y') + hdu_g.header['CD2_1'] =( float(self.information['CD2_1']) , 'partial of second axis coordinate w.r.t. x') + hdu_g.header['CD2_2'] =( float(self.information['CD2_2']) , 'partial of second axis coordinate w.r.t. y') + + hdulist_g=fits.HDUList([ofd_g, hdu_g]) + + file_g=self.result_path+'/ori_Sky/'+filename +'.fits' + + hdulist_g.writeto(file_g, overwrite=True) + return + + + #################################################################################### def applyBleeding(self, img, direction='horizon'): @@ -2422,6 +3731,7 @@ class MCIsimulator(): :return: None """ + #avoid negative numbers in case bias level was not added self.image_g[self.image_g < 0.0] = 0. #cut of the values larger than max @@ -2450,7 +3760,7 @@ class MCIsimulator(): self.image_i = np.rint(self.image_i).astype(int) self.log.info('Maximum and total values of the image are %i and %i, respectively' % (np.max(self.image_i), np.sum(self.image_i))) - return + ################################################################################################## def addScanEffect(self, img): #### read CCD image to matrix as defined data format @@ -2482,14 +3792,14 @@ class MCIsimulator(): #### physical zone index if n<9: - xmin[n]=0 # row number - xmax[n]=4616 + xmin[n]=4616 # row number + xmax[n]=4616*2 ymin[n]=(n-1)*1152 # col number ymax[n]=ymin[n]+1152 else: - xmin[n]=4616 - xmax[n]=4616*2 + xmin[n]=0 + xmax[n]=4616 ymin[n]=(16-n)*1152 ymax[n]=ymin[n]+1152 @@ -2545,36 +3855,6 @@ class MCIsimulator(): return temp ########################################################################### - - def applyPoissonNoise(self): - """ - Add Poisson noise to the image. - """ - - - rounded = np.rint(self.image_g) ### round to - residual = self.image_g.copy() - rounded #ugly workaround for multiple rounding operations... - rounded[rounded < 0.0] = 0.0 - self.image_g = np.random.poisson(rounded).astype(np.float64) - self.log.info('Added Poisson noise on channel g') - self.image_g += residual - - rounded = np.rint(self.image_r) ### round to - residual = self.image_r.copy() - rounded #ugly workaround for multiple rounding operations... - rounded[rounded < 0.0] = 0.0 - self.image_r = np.random.poisson(rounded).astype(np.float64) - self.log.info('Added Poisson noise on channel r') - self.image_r += residual - - rounded = np.rint(self.image_i) ### round to - residual = self.image_i.copy() - rounded #ugly workaround for multiple rounding operations... - rounded[rounded < 0.0] = 0.0 - self.image_i = np.random.poisson(rounded).astype(np.float64) - self.log.info('Added Poisson noise on channel i') - self.image_i += residual - - - ######################################################################################### @@ -2587,103 +3867,143 @@ class MCIsimulator(): """ ## Readout information - + + HeaderTest='no' ########################################################################## - obsid=200000000+obnum - #create a new FITS file, using HDUList instance - ofd_g = fits.PrimaryHDU() - #### add primary header - + if self.source=='EXDF': + obsid=20100000000+obnum + + if self.source=='STAR': + obsid=20200000000+obnum + + if self.source=='PIPR': + obsid=20300000000+obnum + + if self.source=='TRNS': + obsid=20400000000+obnum + + if self.source=='COMB': + obsid=20500000000+obnum + + if self.source=='CALI': + obsid=20600000000+obnum + + if self.source=='BIAS': + obsid=20700000000+obnum + + if self.source=='DARK': + obsid=20800000000+obnum + + if self.source=='FLAT': + obsid=20900000000+obnum + ############################# + + if self.source=='OSBS': + obsid=21000000000+obnum + + if self.source=='OSDK': + obsid=21100000000+obnum + + if self.source=='OSFT': + obsid=21200000000+obnum + + if self.source=='FRNG': + obsid=21300000000+obnum + + ####################################################################### exp_starttime=self.dt.strftime("%Y%m%d%H%M%S") ### exposure end time is t2 ; t2=self.dt+timedelta(seconds=self.information['exptime']) - exp_endtime=t2.strftime("%Y%m%d%H%M%S") - - ### data read time is the exposure end time ### - ### data read end time is t3 + ### data read end time is t3, and this is the write file time; t3=self.dt+timedelta(seconds=self.information['exptime'])+timedelta(seconds=self.information['readouttime']) - filename_g='CSST_MCI_C1_'+self.source+'_'+exp_starttime+'_'+exp_endtime+'_'+str(obsid)+'_'+ \ - str(self.filterP[self.filter_g]['number'])+'_L0_'+self.information['ver']+'.fits' - - - ofd_g.header['GROUPS']=( bool(False), 'always F') - ofd_g.header['DATE'] =( t3.strftime("%Y-%m-%d %H:%M:%S"), 'date this file was written' ) - ofd_g.header['FILENAME']=(filename_g, ' file name C48 ') - ofd_g.header['OBSTYPE'] =( self.source, 'observation type raw,flt, mask, bias, dark, sci') - ofd_g.header['TELESCOP']=('CSST', 'always CSST') - ofd_g.header['INSTRUME']=( 'MCI', ' ') - ofd_g.header['RADECSYS']=('ICRS', ' always ICRS ') - ofd_g.header['EQUINOX'] =( float(2000.0), 'always 2000.0') - ofd_g.header['FITSCREA']=( '4.2.1', 'FITS create software version') - ######### Object information ############# - - ofd_g.header['OBJECT']=( self.information['name_obj'], 'object name') - ofd_g.header['TARGET']=( self.information['target'], 'target name, hhmmss+ddmmss') - ofd_g.header['OBJ_RA'] =(np.float64(self.information['ra_obj']) , 'RA of the object in deg') - ofd_g.header['OBJ_DEC']=(np.float64(self.information['dec_obj']) , 'DEC of the object in deg') - - ofd_g.header['RA_PNT0']=( np.float64(self.information['ra_pnt0']) , 'RA of the pointing (degrees) at EXPSTART') - ofd_g.header['DEC_PNT0']=(np.float64(self.information['dec_pnt0']) , 'DEC of the pointing (degrees) at EXPSTART') - - + if self.filterP[self.filter_g]['number']>9: + filternum=str(self.filterP[self.filter_g]['number']) + else: + filternum='0'+str(self.filterP[self.filter_g]['number']) + - ############## - ofd_g.header['OBSID'] =(str(obsid) , 'observation ID, 3+8bit') + filename_g='CSST_MCI_C1_'+self.source+'_'+exp_starttime+'_'+exp_endtime+'_'+str(obsid)+'_'+ \ + filternum+'_L0_V01' + ####################################################################### + ####################################################################### + #create a new FITS file, using HDUList instance + ofd_g = fits.PrimaryHDU() + #### add primary header + ofd_g = fits.PrimaryHDU() + ofd_g.header['SIMPLE']=( True, 'conforms to FITS standard') + ofd_g.header['BITPIX']=( 0, 'array data type') + ofd_g.header['NAXIS'] =( 0, 'number of array dimensions') + ofd_g.header['NEXTEND']=( np.int16(1), 'number of array dimensions') + ####################################################################### + ########################### + temp=t3.utcnow() + data_time=temp.strftime("%Y-%m-%dT%H:%M:%S.%f") + ofd_g.header['DATE'] =(data_time[:21], 'written date (yyyy-mm-ddThh:mm:ss.s)') + ofd_g.header['FILENAME']=(filename_g[:68],'') + ofd_g.header['FILETYPE'] =( self.source[:12], 'observation type') + ofd_g.header['TELESCOP']=('CSST', 'telescope name') + ofd_g.header['INSTRUME']=('MCI', 'instrument name') + ofd_g.header['RADECSYS']=('ICRS', 'coordinate system of the object') + ofd_g.header['EQUINOX'] =(float(2000.0), '') + ofd_g.header['FITSSWV']=('mci_sim_0.8.03', 'FITS creating software version') + ############################################################################## + ######### Object information ######################################### + ofd_g.header['OBJECT'] =(self.information['name_obj'][:30], 'object name') + ofd_g.header['TARGET'] =(self.information['target'][:13], 'target name (hhmmss.s+ddmmss)') + ####################################################################### + ofd_g.header['OBSID'] =(str(obsid) , 'observation ID') + ofd_g.header['RA_OBJ'] =(float(self.information['ra_obj']) , 'object RA (deg)') + ofd_g.header['DEC_OBJ']=(float(self.information['dec_obj']) , 'object Dec (deg)') + ######## Telescope information ############### - # ofd_g.header['COMMENT'] ='==========================================================' - # ofd_g.header['COMMENT'] ='Telescope information' - # ofd_g.header['COMMENT'] ='==========================================================' - ofd_g.header['REFFRAME']=('CSSTGSC-1.0' , 'guide star catalog version') - ofd_g.header['DATE-OBS']=(self.dt.strftime("%Y-%m-%d %H:%M:%S") , 'date of the observation (yyyy-mm-dd hh:mm:ss)') - - - ofd_g.header['EXPSTART']=(time2jd(self.dt), 'exposure start time, UTC') - ofd_g.header['SUNANGL0']=(np.float32(0.0) , 'angle between sun and optical axis at EXPSTART') - ofd_g.header['MOONANG0']=(np.float32(0.0) , 'angle between moon and optical axis at EXPSTART') - ofd_g.header['POS_ANG0']=(np.float64(0.0), 'angle between optical axis and the North Pole at EXPSTART in arcsec') - ofd_g.header['TEL_ALT0']=(np.float64(0.0), 'angle between optical axis and the ground- piston at EXPSTART in deg') - - ofd_g.header['HOODSTA0']=(np.float32(0.0) , 'lens hood altitude at EXPSTART') - ofd_g.header['HOODANG0']=(np.float32(0.0), 'lens hood azimuth at EXPSTART') - ofd_g.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'the orbital position of CSST in X direction at EXPSTART') - ofd_g.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'the orbital position of CSST in Y direction at EXPSTART') - ofd_g.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'the orbital position of CSST in Z direction at EXPSTART') - ofd_g.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'the orbital velocity of CSST in X direction at EXPSTART') - ofd_g.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'the orbital velocity of CSST in Y direction at EXPSTART') - ofd_g.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'the orbital velocity of CSST in Z direction at EXPSTART') - - ofd_g.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at EXPSTART') - ofd_g.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at EXPSTART') - ofd_g.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at EXPSTART') - - - ofd_g.header['EXPEND'] =(time2jd(t2) , 'exposure end time,UTC') - - ofd_g.header['SUNANGL1']=(np.float32(0.0), 'angle between sun and optical axis at EXPEND') - ofd_g.header['MOONANG1']=(np.float32(0.0) , 'angle between moon and optical axis at EXPEND ') - ofd_g.header['POS_ANG1']=(np.float64(0.0) , 'angle between optical axis and the North Pole at EXPEND in arcsec') - ofd_g.header['TEL_ALT1']=(np.float64(0.0) , 'angle between optical axis and the ground- piston at EXPEND in deg ') - ofd_g.header['HOODSTA1']=(np.float32(0.0), 'lens hood altitude at EXPEND ') - ofd_g.header['HOODANG1']=(np.float32(0.0), 'lens hood azimuth at EXPEND ') + ofd_g.header['REFFRAME']=('CSSTGSC-1.0' , 'guiding catalog version') + ofd_g.header['DATE-OBS']=(data_time[:21] , 'observation date (yyyy-mm-ddThh:mm:ss.s)') + ofd_g.header['SATESWV']=('softwave-1.0', 'satellite software version') + ofd_g.header['EXPSTART']=(np.float64(time2mjd(self.dt)), 'exposure start time (MJD)') + ofd_g.header['CABSTART']=(np.float64(time2jd(self.dt)), 'first cabin time after exposure start (MJD)') + ofd_g.header['SUNANGL0']=(np.float32(0.0) , 'angle between the Sun and opt axis at CABSTART') + ofd_g.header['MOONANG0']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABSTART') + ofd_g.header['TEL_ALT0']=(np.float64(0.0), 'angle between opt axis and Elimb at CABSTART') + ofd_g.header['POS_ANG0']=(np.float64(0.0), 'angle between y axis and North Pole at CABSTART') + ofd_g.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'orbital position in X at CABSTART (km)') + ofd_g.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'orbital position in Y at CABSTART (km)') + ofd_g.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'orbital position in Z at CABSTART (km)') + ofd_g.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'orbital velocity in X at CABSTART (km/s)') + ofd_g.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'orbital velocity in Y at CABSTART (km/s)') + ofd_g.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'orbital velocity in Z at CABSTART (km/s)') + ofd_g.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at CABSTART (deg)') + ofd_g.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at CABSTART (deg)') + ofd_g.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at CABSTART (deg)') + + + ############################################################## + ##### + ofd_g.header['RA_PNT0']=( float(self.information['ra_pnt0']) , 'pointing RA at CABSTART (deg)') + ofd_g.header['DEC_PNT0']=(float(self.information['dec_pnt0']) , 'pointing Dec at CABSTART (deg)') + ofd_g.header['EXPEND'] =(float(time2mjd(t2)), 'exposure end time (MJD)') + ofd_g.header['CABEND'] =(float(time2jd(t2)) , 'first cabin time after exposure end (MJD)') + ofd_g.header['SUNANGL1']=(np.float32(0.0), 'angle between the Sun and opt axis at CABEND') + ofd_g.header['MOONANG1']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABEND') + ofd_g.header['TEL_ALT1']=(np.float64(0.0) , 'angle between opt axis and Elimb at CABEND') + ofd_g.header['POS_ANG1']=(float(0.0) , 'angle between y axis and North Pole at CABEND') + ############################################################## t2jd=time2jd(t2) if self.orbit_pars[-1,0]9: + filternum=str(self.filterP[self.filter_r]['number']) + else: + filternum='0'+str(self.filterP[self.filter_r]['number']) + - ######### add primary header ########## - ofd_r.header['GROUPS']=( bool(False), 'always F') - ofd_r.header['DATE'] =( ofd_g.header['DATE'], 'date this file was written' ) + filename_r='CSST_MCI_C2_'+self.source+'_'+exp_starttime+'_'+exp_endtime+'_'+str(obsid)+'_'+ \ + filternum+'_L0_V01' - ofd_r.header['FILENAME']=(filename_r, ' file name C48 ') - ofd_r.header['OBSTYPE'] =( self.source, 'observation type raw,flt, mask, bias, dark, sci') - ofd_r.header['TELESCOP']=('CSST', 'always CSST') - ofd_r.header['INSTRUME']=( 'MCI', ' ') - ofd_r.header['RADECSYS']=('ICRS', ' always ICRS ') - ofd_r.header['EQUINOX'] =( float(2000.0), 'always 2000.0') - ofd_r.header['FITSCREA']=( '4.2.1', 'FITS create software version') + ####################################################################### + ####################################################################### + #create a new FITS file, using HDUList instance + ofd_r = fits.PrimaryHDU() + #### add primary header - ######### Object information ############# + ########## + ofd_r.header['SIMPLE']=( True, 'conforms to FITS standard') + ofd_r.header['BITPIX']=( 0, 'array data type') + ofd_r.header['NAXIS'] =( 0, 'number of array dimensions') + ofd_r.header['NEXTEND']=( np.int16(1), 'number of array dimensions') + + + temp=t3.utcnow() + data_time=temp.strftime("%Y-%m-%dT%H:%M:%S.%f") + ofd_r.header['DATE'] =(data_time[:21], 'written date (yyyy-mm-ddThh:mm:ss.s)') + ofd_r.header['FILENAME']=(filename_r[:68],'') + ofd_r.header['FILETYPE'] =( self.source[:12], 'observation type') + ofd_r.header['TELESCOP']=('CSST', 'telescope name') + ofd_r.header['INSTRUME']=('MCI', 'instrument name') + ofd_r.header['RADECSYS']=('ICRS', 'coordinate system of the object') + ofd_r.header['EQUINOX'] =(float(2000.0), '') + ofd_r.header['FITSSWV']=('mci_sim_0.8.03', 'FITS creating software version') + ######### Object information ######################################### + ofd_r.header['OBJECT'] =(self.information['name_obj'][:30], 'object name') + ofd_r.header['TARGET'] =(self.information['target'][:13], 'target name (hhmmss.s+ddmmss)') + ####################################################################### + ofd_r.header['OBSID'] =(str(obsid) , 'observation ID') + ofd_r.header['RA_OBJ'] =(float(self.information['ra_obj']) , 'object RA (deg)') + ofd_r.header['DEC_OBJ']=(float(self.information['dec_obj']) , 'object Dec (deg)') - ofd_r.header['OBJECT']=( self.information['name_obj'], 'object name') - ofd_r.header['TARGET']=( self.information['target'], 'target name, hhmmss+ddmmss') - ofd_r.header['OBJ_RA'] =(np.float64(self.information['ra_obj']) , 'RA of the object in deg') - ofd_r.header['OBJ_DEC']=(np.float64(self.information['dec_obj']) , 'DEC of the object in deg') + ######## Telescope information ############### - ofd_r.header['RA_PNT0']=( np.float64(self.information['ra_pnt0']) , 'RA of the pointing (degrees) at EXPSTART') - ofd_r.header['DEC_PNT0']=(np.float64(self.information['dec_pnt0']) , 'DEC of the pointing (degrees) at EXPSTART') + ofd_r.header['REFFRAME']=('CSSTGSC-1.0' , 'guiding catalog version') + ofd_r.header['DATE-OBS']=(data_time[:21] , 'observation date (yyyy-mm-ddThh:mm:ss.s)') + ofd_r.header['SATESWV']=('softwave-1.0', 'satellite software version') + ofd_r.header['EXPSTART']=(np.float64(time2mjd(self.dt)), 'exposure start time (MJD)') + ofd_r.header['CABSTART']=(np.float64(time2jd(self.dt)), 'first cabin time after exposure start (MJD)') + ofd_r.header['SUNANGL0']=(np.float32(0.0) , 'angle between the Sun and opt axis at CABSTART') + ofd_r.header['MOONANG0']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABSTART') + ofd_r.header['TEL_ALT0']=(np.float64(0.0), 'angle between opt axis and Elimb at CABSTART') + ofd_r.header['POS_ANG0']=(np.float64(0.0), 'angle between y axis and North Pole at CABSTART') + ofd_r.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'orbital position in X at CABSTART (km)') + ofd_r.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'orbital position in Y at CABSTART (km)') + ofd_r.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'orbital position in Z at CABSTART (km)') + ofd_r.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'orbital velocity in X at CABSTART (km/s)') + ofd_r.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'orbital velocity in Y at CABSTART (km/s)') + ofd_r.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'orbital velocity in Z at CABSTART (km/s)') + ofd_r.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at CABSTART (deg)') + ofd_r.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at CABSTART (deg)') + ofd_r.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at CABSTART (deg)') + + ############################################################## + ##### + ofd_r.header['RA_PNT0']=( float(self.information['ra_pnt0']) , 'pointing RA at CABSTART (deg)') + ofd_r.header['DEC_PNT0']=(float(self.information['dec_pnt0']) , 'pointing Dec at CABSTART (deg)') + ofd_r.header['EXPEND'] =(float(time2mjd(t2)), 'exposure end time (MJD)') + ofd_r.header['CABEND'] =(float(time2jd(t2)) , 'first cabin time after exposure end (MJD)') + ofd_r.header['SUNANGL1']=(np.float32(0.0), 'angle between the Sun and opt axis at CABEND') + ofd_r.header['MOONANG1']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABEND') + ofd_r.header['TEL_ALT1']=(np.float64(0.0) , 'angle between opt axis and Elimb at CABEND') + ofd_r.header['POS_ANG1']=(float(0.0) , 'angle between y axis and North Pole at CABEND') - ############## - ofd_r.header['OBSID'] =(str(obsid) , 'observation ID, 3+8bit') + + ############################################################## + + ofd_r.header['POSI1_X'] =(float(p1x) , 'orbital position in X at CABEND (km)') + ofd_r.header['POSI1_Y'] =(float(p1y) , 'orbital position in Y at CABEND (km)') + ofd_r.header['POSI1_Z'] =(float(p1z) , 'orbital position in Z at CABEND (km)') + + ofd_r.header['VELO1_X']=(float(p1vx) , 'orbital velocity in X at CABEND (km/s)') + ofd_r.header['VELO1_Y']=(float(p1vy) , 'orbital velocity in Y at CABEND (km/s)') + ofd_r.header['VELO1_Z']=(float(p1vz), 'orbital velocity in Z at CABEND (km/s)') + + ofd_r.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at CABEND (deg)') + ofd_r.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at CABEND (deg)') + ofd_r.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at CABEND (deg)') + ofd_r.header['RA_PNT1'] =(float(ofd_r.header['RA_PNT0']), 'pointing RA at CABEND (deg)') + ofd_r.header['DEC_PNT1']=(float(ofd_r.header['DEC_PNT0']), 'pointing Dec at CABEND (deg)') + ofd_r.header['EPOCH'] =(np.float32(time2jd(t3.utcnow())), 'equinox of pointing RA and Dec') + ofd_r.header['EXPTIME']=(np.float32(self.information['exptime']), 'exposure time (s)') + + ss1='HDU checksum' + ss2='data unit checksum' + ofd_r.header['CHECKSUM']=( data_time[:19] , ss1) + ofd_r.header['DATASUM'] =( data_time[:19] , ss2) - ######## Telescope information ############### - # ofd_r.header['COMMENT'] ='==========================================================' - # ofd_r.header['COMMENT'] ='Telescope information' - # ofd_r.header['COMMENT'] ='==========================================================' - - ofd_r.header['REFFRAME']=('CSSTGSC-1.0' , 'guide star catalog version') - ofd_r.header['DATE-OBS']=(ofd_g.header['DATE-OBS'] , 'date of the observation (yyyy-mm-dd hh:mm:ss)') - - ofd_r.header['EXPSTART']=(ofd_g.header['EXPSTART'], 'exposure start time') - ofd_r.header['SUNANGL0']=(np.float32(0.0) , 'angle between sun and optical axis at EXPSTART') - ofd_r.header['MOONANG0']=(np.float32(0.0) , 'angle between moon and optical axis at EXPSTART') - ofd_r.header['POS_ANG0']=(np.float64(0.0), 'angle between optical axis and the North Pole at EXPSTART in arcsec') - ofd_r.header['TEL_ALT0']=(np.float64(0.0), 'angle between optical axis and the ground- piston at EXPSTART in deg') - - ofd_r.header['HOODSTA0']=(np.float32(0.0) , 'lens hood altitude at EXPSTART') - ofd_r.header['HOODANG0']=(np.float32(0.0), 'lens hood azimuth at EXPSTART') - ofd_r.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'the orbital position of CSST in X direction at EXPSTART') - ofd_r.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'the orbital position of CSST in Y direction at EXPSTART') - ofd_r.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'the orbital position of CSST in Z direction at EXPSTART') - ofd_r.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'the orbital velocity of CSST in X direction at EXPSTART') - ofd_r.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'the orbital velocity of CSST in Y direction at EXPSTART') - ofd_r.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'the orbital velocity of CSST in Z direction at EXPSTART') - - - ofd_r.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at EXPSTART') - ofd_r.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at EXPSTART') - ofd_r.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at EXPSTART') - - - ofd_r.header['EXPEND'] =(ofd_g.header['EXPEND'] , 'exposure end time') - - ofd_r.header['SUNANGL1']=(np.float32(0.0), 'angle between sun and optical axis at EXPEND') - ofd_r.header['MOONANG1']=(np.float32(0.0) , 'angle between moon and optical axis at EXPEND ') - ofd_r.header['POS_ANG1']=(np.float64(0.0) , 'angle between optical axis and the North Pole at EXPEND in arcsec') - ofd_r.header['TEL_ALT1']=(np.float64(0.0) , 'angle between optical axis and the ground- piston at EXPEND in deg ') - ofd_r.header['HOODSTA1']=(np.float32(0.0), 'lens hood altitude at EXPEND ') - ofd_r.header['HOODANG1']=(np.float32(0.0), 'lens hood azimuth at EXPEND ') - ofd_r.header['POSI1_X'] =(np.float64(p1x) , 'the orbital position of CSST in X direction at EXPEND') - ofd_r.header['POSI1_Y'] =(np.float64(p1y) , 'the orbital position of CSST in Y direction at EXPEND') - ofd_r.header['POSI1_Z'] =(np.float64(p1z) , 'the orbital position of CSST in Z direction at EXPEND') - - ofd_r.header['VELO1_X']=(np.float64(p1vx) , 'the orbital velocity of CSST in X direction at EXPEND') - ofd_r.header['VELO1_Y']=(np.float64(p1vy) , 'the orbital velocity of CSST in Y direction at EXPEND') - ofd_r.header['VELO1_Z']=(np.float64(p1vz) , 'the orbital velocity of CSST in Z direction at EXPEND') - - ofd_r.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at EXPEND') - ofd_r.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at EXPEND') - ofd_r.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at EXPEND') - - ofd_r.header['RA_PNT1']=(np.float64(0.0), 'RA of the pointing (degrees) at EXPEND in deg') - ofd_r.header['DEC_PNT1']=(np.float64(0.0), 'DEC of the pointing (degrees) at EXPEND in deg') - - ofd_r.header['EXPTIME']=(self.information['exptime'], 'exposure duration') - ofd_r.header['EPOCH'] =(np.float32(0.0), 'coordinate epoch') - ofd_r.header['CHECKSUM']=( 0 , 'hdu-checksum') + ################################################ + ########## finish header for 0 layer #################### + ########## finish header for 0 layer #################### ########## finish header for 0 layer - #new image HDU - hdu_r = fits.ImageHDU(data=np.uint16(self.image_r)) - - ### MCI header for immage layer ### - #### Instrument information (at EXPSTART time) - hdu_r.header['PMIRRPOS']=( bool(True) , 'FSM pointing,T: point to MCI, F: not point to MCI ') - hdu_r.header['DIFFUSER']=( bool(True) , 'insert diffuser for flat calibration,T: insert diffuser, F: not insert diffuser ') - hdu_r.header['FLAMP'] =( np.int16(0) , 'status of flat lamp,0: off, 1: 1, 2: 2, 3: 3') - hdu_r.header['MCITEMP'] =( np.float32(0.0), 'MCI components temperature') - hdu_r.header['MCISTAT'] =( np.int16(0) , 'MCI components status parameters') + if HeaderTest=='yes': + hdu_r = fits.ImageHDU() + else: + hdu_r = fits.ImageHDU(data=np.uint16(self.image_r)) + ### MCI header for image layer ### + #### need review thie header + hdu_r.header['XTENSION']=( 'IMAGE' , 'extension type') + hdu_r.header['BITPIX'] =( np.int16(16) , 'array data type') + hdu_r.header['NAXIS'] =( np.int16(2) , 'number of array dimensions') + + hdu_r.header['NAXIS1'] =( np.int32(4936) , '') + hdu_r.header['NAXIS2'] =( np.int32(23984) , '') + + + hdu_r.header['PCOUNT']=( np.int16(0) , 'number of parameters') + hdu_r.header['GCOUNT']=( np.int16(1) , 'number of groups') + + hdu_r.header['BSCALE']=(int(1),'') + hdu_r.header['BZERO'] =(int(32768),'') + + hdu_r.header['EXTNAME']=( 'SCI' , '') + hdu_r.header['EXTVER']=(np.int16(1),'') + + hdu_r.header['BUNIT'] =('ADU','physical unit of array values') + + ###### file information ############### + + temp=t3.utcnow() + data_time=temp.strftime("%Y-%m-%dT%H:%M:%S.%f") + hdu_r.header['DATE'] =(data_time[:21], 'written date (yyyy-mm-ddThh:mm:ss.s)') + hdu_r.header['FILENAME']=(filename_r[:68],'') + hdu_r.header['FILETYPE'] =( self.source[:12], 'observation type') + hdu_r.header['RADECSYS']=('ICRS', 'coordinate system of the object') + hdu_r.header['EQUINOX'] =(float(2000.1), '') + hdu_r.header['FITSSWV']=('4.2.1', 'FITS creating software version') + + ######################################## + + #### instrument status and object information ###### + hdu_r.header['TELESCOP']=('CSST', 'telescope name') + hdu_r.header['INSTRUME']=('MCI', 'instrument name') + hdu_r.header['CHANNEL'] =('C1', 'channel number') + hdu_r.header['FILTERNO'] =(filternum, 'filter number') + hdu_r.header['DIFFUSER']=( bool(True) , 'insert diffuser for flat calibration') + hdu_r.header['FLAMP'] =( np.int16(0) , 'status of flat lamp') + hdu_r.header['MCISTAT'] =( np.int16(0) , 'MCI componetns status parameter') - ##### Filter information ##### - hdu_r.header['FILTER'] =(self.filter_r , 'filter band name') + hdu_r.header['DATE_OBS'] =(data_time[:21] , 'observation date (yyyy-mm-ddThh:mm:ss.s)') + hdu_r.header['OBJECT'] =( 'MCI_obj' , 'object name') + hdu_r.header['TARGET'] =(self.information['target'][:13], 'target name (hhmmss.s+ddmmss)') + ####################################################################### + hdu_r.header['OBSID'] =(str(obsid) , 'observation ID') + hdu_r.header['RA_OBJ'] =(float(self.information['ra_obj']) , 'object RA (deg)') + hdu_r.header['DEC_OBJ']=(float(self.information['dec_obj']) , 'object Dec (deg)') + + + + ##### detector and Filter information ##### + hdu_r.header['FILTER'] =(self.filter_r[:6] , 'filter band') ##### Detector information #### - hdu_r.header['DETNAM'] =('C2' , 'detector name for channle 2') - hdu_r.header['DETTEMP'] =(np.float32(0) , 'detector temperature') - hdu_r.header['DETSIZE'] =(str(self.image_r.shape[0])+'*'+str(self.image_r.shape[1]), 'detector size') - hdu_r.header['DATASEC'] =(str(self.information['ysize'])+'*'+str( self.information['xsize']), 'data section') - hdu_r.header['PIXSCAL1']=(np.float32(0.05) , 'pixel scale for axis 1') - hdu_r.header['PIXSCAL2']=(np.float32(0.05) , 'pixel scale for axis 2') - hdu_r.header['PIXSIZE1']=(np.float32(10.0) , 'pixel size for axis 1') - hdu_r.header['PIXSIZE2']=(np.float32(10.0) , 'pixel size for axis 2') - hdu_r.header['NCHAN'] =(np.int16(16) , 'number of readout channels') - hdu_r.header['NCHAN1'] =(np.int16(8) , 'number of horizontal channels') - hdu_r.header['NCHAN2'] =(np.int16(2) , 'number of vertical channels') + hdu_r.header['DETSN'] =('E2V-CCD-290-0000000' , 'detector serial number') + hdu_r.header['DETNAME'] =('opt-blue' , 'detector name') + ####need review here + + + hdu_r.header['DETTEMP0'] =(np.float32(0) , 'detector temperature at EXPSTART (K)') + hdu_r.header['DETTEMP1'] =(np.float32(0) , 'detector temperature at EXPEND (K)') + hdu_r.header['DETTEMP2'] =(np.float32(0) , 'detector temperature at READT1 (K)') + + + + hdu_r.header['DETSIZE'] =(str(self.information['ysize'])+'*'+str( self.information['xsize']), 'detector size') + hdu_r.header['DATASECT'] =(str(self.image_g.shape[0])+'*'+str(self.image_g.shape[1]), 'data section') + + hdu_r.header['PIXSCAL1']=('0.05' , 'pixel scale for axis 1 (arcsec/pixel)') + hdu_r.header['PIXSCAL2']=('0.05' , 'pixel scale for axis 2 (arcsec/pixel)') + + hdu_r.header['PIXSIZE1']=(int(10) , 'pixel size for axis 1 (micron)') + hdu_r.header['PIXSIZE2']=(int(10) , 'pixel size for axis 2 (micron)') + + hdu_r.header['NCHANNEL'] =(np.int16(16) , 'number of readout channels') + + hdu_r.header['PSCAN1'] =(np.int32(27) , 'horizontal prescan width, per readout channel') - hdu_r.header['PSCAN2'] =(np.int32(8) , 'vertical prescan height, per readout channel') - hdu_r.header['OSCAN1'] =(np.int32(16) , 'horizontal overscan width, per readout channel') - hdu_r.header['OSCAN2'] =(np.int32(8) , 'vertical overscan width, per readout channel') - hdu_r.header['BIN_X'] =(np.int16(0) , 'bin number in X (wavelength)') - hdu_r.header['BIN_Y'] =(np.int16(0) , 'bin number in Y (spatial)') + hdu_r.header['PSCAN2'] =(np.int32(0) , 'vertical prescan height, per readout channel') - #### World coordinate system and related parameters ##### + hdu_r.header['OSCAN1'] =(np.int32(320) , 'horizontal overscan width, per readout channel') + hdu_r.header['OSCAN2'] =(np.int32(320) , 'vertical overscan width, per readout channel') + + hdu_r.header['BIN_X'] =(np.int16(1) , 'bin number in X') + hdu_r.header['BIN_Y'] =(np.int16(1) , 'bin number in Y') - hdu_r.header['WCSAXES']=( np.int16(2) , 'number of World Coordinate System axes') - hdu_r.header['CRPIX1'] =( np.float64(self.information['CRPIX1']) , 'x-coordinate of reference pixel') - hdu_r.header['CRPIX2'] =( np.float64(self.information['CRPIX2']) , 'y-coordinate of reference pixel') - hdu_r.header['CRVAL1'] =( np.float64(self.information['CRVAL1']) , 'first axis value at reference pixel') - hdu_r.header['CRVAL2'] =( np.float64(self.information['CRVAL2']) , 'second axis value at reference pixel') - hdu_r.header['CTYPE1'] =( 'RA---TAN' , 'the coordinate type for the first axis') - hdu_r.header['CTYPE2'] =( 'DEC---TAN' , 'the coordinate type for the second axis') - hdu_r.header['CD1_1'] =( np.float64(self.information['CD1_1']) , 'partial of first axis coordinate w.r.t. x') - hdu_r.header['CD1_2'] =( np.float64(self.information['CD1_2']) , 'partial of first axis coordinate w.r.t. y') - hdu_r.header['CD2_1'] =( np.float64(self.information['CD2_1']) , 'partial of second axis coordinate w.r.t. x') - hdu_r.header['CD2_2'] =( np.float64(self.information['CD2_2']) , 'partial of second axis coordinate w.r.t. y') - hdu_r.header['others'] =( 0.0 , 'other specific parameters') + #### World coordinate system information ##### + + hdu_r.header['WCSAXES']=(np.int16(2) , 'number of World Coordinate System axes') + hdu_r.header['CRPIX1'] =( round(float(self.information['CRPIX1']) ,1) , 'x-coordinate of reference pixel') + hdu_r.header['CRPIX2'] =( round(float(self.information['CRPIX2']) ,1) , 'y-coordinate of reference pixel') + + hdu_r.header['CRVAL1'] =( float(self.information['CRVAL1']) , 'value of reference pixel on axis 1') + hdu_r.header['CRVAL2'] =( float(self.information['CRVAL2']) , 'value of reference pixel on axis 2') + + hdu_r.header['CTYPE1'] =( 'RA---TAN' , 'type of RA WCS projection') + hdu_r.header['CTYPE2'] =( 'DEC--TAN' , 'type of Dec WCS projection') + + hdu_r.header['CD1_1'] =( float(self.information['CD1_1']) , 'transformation matrix element (deg/pix)') + hdu_r.header['CD1_2'] =( float(self.information['CD1_2']) , 'transformation matrix element (deg/pix)') + hdu_r.header['CD2_1'] =( float(self.information['CD2_1']) , 'transformation matrix element (deg/pix)') + hdu_r.header['CD2_2'] =( float(self.information['CD2_2']) , 'transformation matrix element (deg/pix)') + ###### Readout information ####### - hdu_r.header['GAIN1'] =( np.float32(self.information['r_gain1']) , 'CCD gain (channel 1)') - hdu_r.header['GAIN2'] =( np.float32(self.information['r_gain2']) , 'CCD gain (channel 2)') - hdu_r.header['GAIN3'] =( np.float32(self.information['r_gain3']) , 'CCD gain (channel 3)') - hdu_r.header['GAIN4'] =( np.float32(self.information['r_gain4']) , 'CCD gain (channel 4)') - hdu_r.header['GAIN5'] =( np.float32(self.information['r_gain5']) , 'CCD gain (channel 5)') - hdu_r.header['GAIN6'] =( np.float32(self.information['r_gain6']) , 'CCD gain (channel 6)') - hdu_r.header['GAIN7'] =( np.float32(self.information['r_gain7']) , 'CCD gain (channel 7)') - hdu_r.header['GAIN8'] =( np.float32(self.information['r_gain8']) , 'CCD gain (channel 8)') - hdu_r.header['GAIN9'] =( np.float32(self.information['r_gain9']) , 'CCD gain (channel 9)') - hdu_r.header['GAIN10']=( np.float32(self.information['r_gain10']) , 'CCD gain (channel 10)') - hdu_r.header['GAIN11']=( np.float32(self.information['r_gain11']) , 'CCD gain (channel 11)') - hdu_r.header['GAIN12']=( np.float32(self.information['r_gain12']) , 'CCD gain (channel 12)') - hdu_r.header['GAIN13']=( np.float32(self.information['r_gain13']) , 'CCD gain (channel 13)') - hdu_r.header['GAIN14']=( np.float32(self.information['r_gain14']) , 'CCD gain (channel 14)') - hdu_r.header['GAIN15']=( np.float32(self.information['r_gain15']) , 'CCD gain (channel 15)') - hdu_r.header['GAIN16']=( np.float32(self.information['r_gain16']) , 'CCD gain (channel 16)') + hdu_r.header['GAINLVL'] =( np.float32(1.5) , 'gain level (e-/ADU)') + hdu_r.header['GAIN01'] =( np.float32(self.information['r_gain1']) , 'CCD gain [channel 1] (e-/ADU)') + hdu_r.header['GAIN02'] =( np.float32(self.information['r_gain2']) , 'CCD gain [channel 2] (e-/ADU)') + hdu_r.header['GAIN03'] =( np.float32(self.information['r_gain3']) , 'CCD gain [channel 3] (e-/ADU)') + hdu_r.header['GAIN04'] =( np.float32(self.information['r_gain4']) , 'CCD gain [channel 4] (e-/ADU)') + hdu_r.header['GAIN05'] =( np.float32(self.information['r_gain5']) , 'CCD gain [channel 5] (e-/ADU)') + hdu_r.header['GAIN06'] =( np.float32(self.information['r_gain6']) , 'CCD gain [channel 6] (e-/ADU)') + hdu_r.header['GAIN07'] =( np.float32(self.information['r_gain7']) , 'CCD gain [channel 7] (e-/ADU)') + hdu_r.header['GAIN08'] =( np.float32(self.information['r_gain8']) , 'CCD gain [channel 8] (e-/ADU)') + hdu_r.header['GAIN09'] =( np.float32(self.information['r_gain9']) , 'CCD gain [channel 9] (e-/ADU)') + hdu_r.header['GAIN10']=( np.float32(self.information['r_gain10']) , 'CCD gain [channel 10] (e-/ADU)') + hdu_r.header['GAIN11']=( np.float32(self.information['r_gain11']) , 'CCD gain [channel 11] (e-/ADU)') + hdu_r.header['GAIN12']=( np.float32(self.information['r_gain12']) , 'CCD gain [channel 12] (e-/ADU)') + hdu_r.header['GAIN13']=( np.float32(self.information['r_gain13']) , 'CCD gain [channel 13] (e-/ADU)') + hdu_r.header['GAIN14']=( np.float32(self.information['r_gain14']) , 'CCD gain [channel 14] (e-/ADU)') + hdu_r.header['GAIN15']=( np.float32(self.information['r_gain15']) , 'CCD gain [channel 15] (e-/ADU)') + hdu_r.header['GAIN16']=( np.float32(self.information['r_gain16']) , 'CCD gain [channel 16] (e-/ADU)') ####### - hdu_r.header['RDNOIS1'] =( np.float32(self.information['r_rdnois1']) , 'read noise (channel 1)') - hdu_r.header['RDNOIS2'] =( np.float32(self.information['r_rdnois2']) , 'read noise (channel 2)') - hdu_r.header['RDNOIS3'] =( np.float32(self.information['r_rdnois3']) , 'read noise (channel 3)') - hdu_r.header['RDNOIS4'] =( np.float32(self.information['r_rdnois4']) , 'read noise (channel 4)') - hdu_r.header['RDNOIS5'] =( np.float32(self.information['r_rdnois5']) , 'read noise (channel 5)') - hdu_r.header['RDNOIS6'] =( np.float32(self.information['r_rdnois6']) , 'read noise (channel 6)') - hdu_r.header['RDNOIS7'] =( np.float32(self.information['r_rdnois7']) , 'read noise (channel 7)') - hdu_r.header['RDNOIS8'] =( np.float32(self.information['r_rdnois8']) , 'read noise (channel 8)') - hdu_r.header['RDNOIS9'] =( np.float32(self.information['r_rdnois9']) , 'read noise (channel 9)') - hdu_r.header['RDNOIS10']=( np.float32(self.information['r_rdnois10']) , 'read noise (channel 10)') - hdu_r.header['RDNOIS11']=( np.float32(self.information['r_rdnois11']) , 'read noise (channel 11)') - hdu_r.header['RDNOIS12']=( np.float32(self.information['r_rdnois12']) , 'read noise (channel 12)') - hdu_r.header['RDNOIS13']=( np.float32(self.information['r_rdnois13']) , 'read noise (channel 13)') - hdu_r.header['RDNOIS14']=( np.float32(self.information['r_rdnois14']) , 'read noise (channel 14)') - hdu_r.header['RDNOIS15']=( np.float32(self.information['r_rdnois15']) , 'read noise (channel 15)') - hdu_r.header['RDNOIS16']=( np.float32(self.information['r_rdnois16']) , 'read noise (channel 16)') + hdu_r.header['RON01'] =( np.float32(self.information['r_rdnois1']) , 'readout noise [channel 01] (e-)') + hdu_r.header['RON02'] =( np.float32(self.information['r_rdnois2']) , 'readout noise [channel 02] (e-)') + hdu_r.header['RON03'] =( np.float32(self.information['r_rdnois3']) , 'readout noise [channel 03] (e-)') + hdu_r.header['RON04'] =( np.float32(self.information['r_rdnois4']) , 'readout noise [channel 04] (e-)') + hdu_r.header['RON05'] =( np.float32(self.information['r_rdnois5']) , 'readout noise [channel 05] (e-)') + hdu_r.header['RON06'] =( np.float32(self.information['r_rdnois6']) , 'readout noise [channel 06] (e-)') + hdu_r.header['RON07'] =( np.float32(self.information['r_rdnois7']) , 'readout noise [channel 07] (e-)') + hdu_r.header['RON08'] =( np.float32(self.information['r_rdnois8']) , 'readout noise [channel 08] (e-)') + hdu_r.header['RON09'] =( np.float32(self.information['r_rdnois9']) , 'readout noise [channel 09] (e-)') + hdu_r.header['RON10']=( np.float32(self.information['r_rdnois10']) , 'readout noise [channel 10] (e-)') + hdu_r.header['RON11']=( np.float32(self.information['r_rdnois11']) , 'readout noise [channel 11] (e-)') + hdu_r.header['RON12']=( np.float32(self.information['r_rdnois12']) , 'readout noise [channel 12] (e-)') + hdu_r.header['RON13']=( np.float32(self.information['r_rdnois13']) , 'readout noise [channel 13] (e-)') + hdu_r.header['RON14']=( np.float32(self.information['r_rdnois14']) , 'readout noise [channel 14] (e-)') + hdu_r.header['RON15']=( np.float32(self.information['r_rdnois15']) , 'readout noise [channel 15] (e-)') + hdu_r.header['RON16']=( np.float32(self.information['r_rdnois16']) , 'readout noise [channel 16] (e-)') ####### - hdu_r.header['DETBIA1']=( np.float32(self.information['r_detbia1']) , 'amplifier bias voltage (channel 1)') - hdu_r.header['DETBIA2']=( np.float32(self.information['r_detbia2']) , 'amplifier bias voltage (channel 2)') - hdu_r.header['DETBIA3']=( np.float32(self.information['r_detbia3']) , 'amplifier bias voltage (channel 3)') - hdu_r.header['DETBIA4']=( np.float32(self.information['r_detbia4']) , 'amplifier bias voltage (channel 4)') - hdu_r.header['DETBIA5']=( np.float32(self.information['r_detbia5']) , 'amplifier bias voltage (channel 5)') - hdu_r.header['DETBIA6']=( np.float32(self.information['r_detbia6']) , 'amplifier bias voltage (channel 6)') - hdu_r.header['DETBIA7']=( np.float32(self.information['r_detbia7']) , 'amplifier bias voltage (channel 7)') - hdu_r.header['DETBIA8']=( np.float32(self.information['r_detbia8']) , 'amplifier bias voltage (channel 8)') - hdu_r.header['DETBIA9']=( np.float32(self.information['r_detbia9']) , 'amplifier bias voltage (channel 9)') - hdu_r.header['DETBIA10']=( np.float32(self.information['r_detbia10']) , 'amplifier bias voltage (channel 10)') - hdu_r.header['DETBIA11']=( np.float32(self.information['r_detbia11']) , 'amplifier bias voltage (channel 11)') - hdu_r.header['DETBIA12']=( np.float32(self.information['r_detbia12']) , 'amplifier bias voltage (channel 12)') - hdu_r.header['DETBIA13']=( np.float32(self.information['r_detbia13']) , 'amplifier bias voltage (channel 13)') - hdu_r.header['DETBIA14']=( np.float32(self.information['r_detbia14']) , 'amplifier bias voltage (channel 14)') - hdu_r.header['DETBIA15']=( np.float32(self.information['r_detbia15']) , 'amplifier bias voltage (channel 15)') - hdu_r.header['DETBIA16']=( np.float32(self.information['r_detbia16']) , 'amplifier bias voltage (channel 16)') - - ###### - ###### - hdu_r.header['READT0'] =( hdu_g.header['READT0'] , 'read start time (UTC)') - hdu_r.header['READT1'] =( hdu_g.header['READT1'] , 'read end time (UTC)') - hdu_r.header['DETTEMP0']=( np.float32(0) , 'detector temperature at READT0') - hdu_r.header['DETTEMP1']=( np.float32(0) , 'detector temperature at READT1') - hdu_r.header['RDSPEED'] =( np.float32(3) , 'read speed (in MHz)') - - ##### Shutter information ##### - hdu_r.header['SHUTHWV'] =( 'XXXXXXXXXXXXXXXX' , 'shutter hardware version') - hdu_r.header['SHUTSWV'] =( 'XXXXXXXXXXXXXXXX' , 'shutter software') - hdu_r.header['SHUTSTAT']=( bool(True) , 'shutter status,T: open, F: close') - hdu_r.header['SHTOPEN0']=( np.float64(0) , 'shutter open time (begin)') - hdu_r.header['SHTOPEN1']=( np.float64(0) , 'shutter open time (end)') - hdu_r.header['SHTCLOS0']=( np.float64(0) , 'shutter close time (begin)') - hdu_r.header['SHTCLOS1']=( np.float64(0) , 'shutter close time (end)') - ################ finish MCI header for image layer + hdu_r.header['DETBIA01']=( np.float32(self.information['r_detbia1']) , 'amplifier bias grey value [channel 1] (ADU)') + hdu_r.header['DETBIA02']=( np.float32(self.information['r_detbia2']) , 'amplifier bias grey value [channel 2] (ADU)') + hdu_r.header['DETBIA03']=( np.float32(self.information['r_detbia3']) , 'amplifier bias grey value [channel 3] (ADU)') + hdu_r.header['DETBIA04']=( np.float32(self.information['r_detbia4']) , 'amplifier bias grey value [channel 4] (ADU)') + hdu_r.header['DETBIA05']=( np.float32(self.information['r_detbia5']) , 'amplifier bias grey value [channel 5] (ADU)') + hdu_r.header['DETBIA06']=( np.float32(self.information['r_detbia6']) , 'amplifier bias grey value [channel 6] (ADU)') + hdu_r.header['DETBIA07']=( np.float32(self.information['r_detbia7']) , 'amplifier bias grey value [channel 7] (ADU)') + hdu_r.header['DETBIA08']=( np.float32(self.information['r_detbia8']) , 'amplifier bias grey value [channel 8] (ADU)') + hdu_r.header['DETBIA09']=( np.float32(self.information['r_detbia9']) , 'amplifier bias grey value [channel 9] (ADU)') + hdu_r.header['DETBIA10']=( np.float32(self.information['r_detbia10']) , 'amplifier bias grey value [channel 10] (ADU)') + hdu_r.header['DETBIA11']=( np.float32(self.information['r_detbia11']) , 'amplifier bias grey value [channel 11] (ADU)') + hdu_r.header['DETBIA12']=( np.float32(self.information['r_detbia12']) , 'amplifier bias grey value [channel 12] (ADU)') + hdu_r.header['DETBIA13']=( np.float32(self.information['r_detbia13']) , 'amplifier bias grey value [channel 13] (ADU)') + hdu_r.header['DETBIA14']=( np.float32(self.information['r_detbia14']) , 'amplifier bias grey value [channel 14] (ADU)') + hdu_r.header['DETBIA15']=( np.float32(self.information['r_detbia15']) , 'amplifier bias grey value [channel 15] (ADU)') + hdu_r.header['DETBIA16']=( np.float32(self.information['r_detbia16']) , 'amplifier bias grey value [channel 16] (ADU)') + hdu_r.header['ROSPEED'] =( np.float32(100) , 'readout speed (MHz)') + + ###################################### + #### exposure and shutter information ##### + hdu_r.header['EXPSTART']=(np.float64(time2mjd(self.dt)), 'exposure start time (MJD)') + hdu_r.header['EXPEND'] =(float(time2mjd(t2)), 'exposure end time (MJD)') + hdu_r.header['EXPTIME'] =(np.float32(self.information['exptime']), 'exposure times (s)') + hdu_r.header['DARKTIME'] =(np.float32(self.information['exptime']), 'dark current time (s)') + hdu_r.header['SHTSTAT']=( bool(True) , 'shutter status') + + ###### satellite and its allitide information ############## + hdu_r.header['REFFRAME']=('CSSTGSC-1.0' , 'guiding catalog version') + hdu_r.header['SATESWV']=('softwave-1.0', 'satellite software version') + hdu_r.header['CABSTART']=(np.float64(time2jd(self.dt)), 'first cabin time after exposure start (MJD)') + hdu_r.header['SUNANGL0']=(np.float32(0.0) , 'angle between the Sun and opt axis at CABSTART') + hdu_r.header['MOONANG0']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABSTART') + hdu_r.header['TEL_ALT0']=(np.float64(0.0), 'angle between opt axis and Elimb at CABSTART') + hdu_r.header['POS_ANG0']=(np.float64(0.0), 'angle between y axis and North Pole at CABSTART') + hdu_r.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'orbital position in X at CABSTART (km)') + hdu_r.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'orbital position in Y at CABSTART (km)') + hdu_r.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'orbital position in Z at CABSTART (km)') + hdu_r.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'orbital velocity in X at CABSTART (km/s)') + hdu_r.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'orbital velocity in Y at CABSTART (km/s)') + hdu_r.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'orbital velocity in Z at CABSTART (km/s)') + hdu_r.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at CABSTART (deg)') + hdu_r.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at CABSTART (deg)') + hdu_r.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at CABSTART (deg)') + hdu_r.header['RA_PNT0']=( float(self.information['ra_pnt0']) , 'pointing RA at CABSTART (deg)') + hdu_r.header['DEC_PNT0']=(float(self.information['dec_pnt0']) , 'pointing Dec at CABSTART (deg)') + hdu_r.header['CABEND'] =(float(time2jd(t2)) , 'first cabin time after exposure end (MJD)') + hdu_r.header['SUNANGL1']=(np.float32(0.0), 'angle between the Sun and opt axis at CABEND') + hdu_r.header['MOONANG1']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABEND') + hdu_r.header['TEL_ALT1']=(np.float64(0.0) , 'angle between opt axis and Elimb at CABEND') + hdu_r.header['POS_ANG1']=(float(0.0) , 'angle between y axis and North Pole at CABEND') + hdu_r.header['POSI1_X'] =(float(p1x) , 'orbital position in X at CABEND (km)') + hdu_r.header['POSI1_Y'] =(float(p1y) , 'orbital position in Y at CABEND (km)') + hdu_r.header['POSI1_Z'] =(float(p1z) , 'orbital position in Z at CABEND (km)') + hdu_r.header['VELO1_X']=(float(p1vx) , 'orbital velocity in X at CABEND (km/s)') + hdu_r.header['VELO1_Y']=(float(p1vy) , 'orbital velocity in Y at CABEND (km/s)') + hdu_r.header['VELO1_Z']=(float(p1vz), 'orbital velocity in Z at CABEND (km/s)') + hdu_r.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at CABEND (deg)') + hdu_r.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at CABEND (deg)') + hdu_r.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at CABEND (deg)') + hdu_r.header['RA_PNT1'] =(float(hdu_r.header['RA_PNT0']), 'pointing RA at CABEND (deg)') + hdu_r.header['DEC_PNT1']=(float(hdu_r.header['DEC_PNT0']), 'pointing Dec at CABEND (deg)') + hdu_r.header['EPOCH'] =(np.float32(time2jd(t3.utcnow())), 'equinox of pointing RA and Dec') + + ############################################################## + ##### + # hdu_r.header['CHECKSUM'] =('','HDU checksum updated yyyy-mm-ddTHH:MM:SS') + + # hdu_r.header['DATASUM'] =('','data unit checksum updated yyyy-mm-ddTHH:MM:SS') + ################ finish MCI header for image layer in G channel + ##############################################################################################333 - #write the actual file hdulist_r=fits.HDUList([ofd_r, hdu_r]) + #### + ofd_r.header.add_comment('========================================================================',after='FITSSWV') + ofd_r.header.add_comment('OBJECT INFORMATION',after='FITSSWV') + ofd_r.header.add_comment('========================================================================',after='FITSSWV') + + ofd_r.header.add_comment('========================================================================',after='DEC_OBJ') + ofd_r.header.add_comment('TELESCOPE INFORMATION',after='DEC_OBJ') + ofd_r.header.add_comment('========================================================================',after='DEC_OBJ') + + ofd_r.header.add_comment('========================================================================',after='EPOCH') + ofd_r.header.add_comment('VERIFICATION INFORMATION',after='EPOCH') + ofd_r.header.add_comment('========================================================================',after='EPOCH') + + ####################################################################### + hdu_r.header.add_comment('========================================================================',after='BUNIT') + hdu_r.header.add_comment('FILE INFORMATION',after='BUNIT') + hdu_r.header.add_comment('========================================================================',after='BUNIT') + + hdu_r.header.add_comment('========================================================================',after='FITSSWV') + hdu_r.header.add_comment('INSTRUMENT STATUS AND OBJECT INFORMATION',after='FITSSWV') + hdu_r.header.add_comment('========================================================================',after='FITSSWV') - #file_r=self.result_path+'/sky_Data/'+filename_r + hdu_r.header.add_comment('========================================================================',after='DEC_OBJ') + hdu_r.header.add_comment('DETECTOR AND FILTER INFORMATION',after='DEC_OBJ') + hdu_r.header.add_comment('========================================================================',after='DEC_OBJ') + hdu_r.header.add_comment('========================================================================',after='BIN_Y') + hdu_r.header.add_comment('WORLD COORDINATE SYSTEM INFORMATION',after='BIN_Y') + hdu_r.header.add_comment('========================================================================',after='BIN_Y') + + hdu_r.header.add_comment('========================================================================',after='CD2_2') + hdu_r.header.add_comment('READOUT INFORMATION',after='CD2_2') + hdu_r.header.add_comment('========================================================================',after='CD2_2') + + hdu_r.header.add_comment('========================================================================',after='ROSPEED') + hdu_r.header.add_comment('EXPOSURE AND SHUTTER INFORMATION',after='ROSPEED') + hdu_r.header.add_comment('========================================================================',after='ROSPEED') + + hdu_r.header.add_comment('========================================================================',after='SHTSTAT') + hdu_r.header.add_comment('SATELLITE AND ITS ATTITUDE INFORMATION',after='SHTSTAT') + hdu_r.header.add_comment('========================================================================',after='SHTSTAT') + + hdu_r.header.add_comment('========================================================================',after='EPOCH') + hdu_r.header.add_comment('VERIFICATION INFORMATION',after='EPOCH') + hdu_r.header.add_comment('========================================================================',after='EPOCH') + + ##################################### + ################ finish MCI header for image layer in R channel + if self.source=='DARK' or self.source=='FLAT' or self.source=='BIAS': - file_r=self.result_path+'/cali_Data/'+filename_r + file_r=self.result_path+'/cali_Data/'+filename_r+'.fits' else: - file_r=self.result_path+'/sky_Data/'+filename_r + file_r=self.result_path+'/sky_Data/'+filename_r +'.fits' - hdulist_r.writeto(file_r, overwrite=True) + hdulist_r.writeto(file_r, checksum=True) + print('MCI_r.fits is created ') ################################################################################# ### i band @@ -3091,222 +4724,380 @@ class MCIsimulator(): #create a new FITS file, using HDUList instance ofd_i = fits.PrimaryHDU() - filename_i='CSST_MCI_C3_'+self.source+'_'+exp_starttime+'_'+exp_endtime+'_'+str(obsid)+'_'+ \ - str(self.filterP[self.filter_i]['number'])+'_L0_'+self.information['ver']+'.fits' - #### add primary header - ofd_i.header['GROUPS']=( bool(False), 'always F') - ofd_i.header['DATE'] =( ofd_g.header['DATE'], 'date this file was written' ) + if self.filterP[self.filter_i]['number']>9: + filternum=str(self.filterP[self.filter_i]['number']) + else: + filternum='0'+str(self.filterP[self.filter_i]['number']) + - ofd_i.header['FILENAME']=(filename_i, ' file name C48 ') - ofd_i.header['OBSTYPE'] =( self.source, 'observation type raw,flt, mask, bias, dark, sci') - ofd_i.header['TELESCOP']=('CSST', 'always CSST') - ofd_i.header['INSTRUME']=( 'MCI', ' ') - ofd_i.header['RADECSYS']=('ICRS', ' always ICRS ') - ofd_i.header['EQUINOX'] =( float(2000.0), 'always 2000.0') - ofd_i.header['FITSCREA']=( '4.2.1', 'FITS create software version') + filename_i='CSST_MCI_C3_'+self.source+'_'+exp_starttime+'_'+exp_endtime+'_'+str(obsid)+'_'+ \ + filternum+'_L0_V01' - ######### Object information ############# + #### add primary header - ofd_i.header['OBJECT']=( self.information['name_obj'], 'object name') - ofd_i.header['TARGET']=( self.information['target'], 'target name, hhmmss+ddmmss') - ofd_i.header['OBJ_RA'] =(np.float64(self.information['ra_obj']) , 'RA of the object in deg') - ofd_i.header['OBJ_DEC']=(np.float64(self.information['dec_obj']) , 'DEC of the object in deg') + ofd_i.header['SIMPLE']=( True, 'conforms to FITS standard') + ofd_i.header['BITPIX']=( 0, 'array data type') + ofd_i.header['NAXIS'] =( 0, 'number of array dimensions') + ofd_i.header['NEXTEND']=( np.int16(1), 'number of array dimensions') + ############################### + temp=t3.utcnow() + data_time=temp.strftime("%Y-%m-%dT%H:%M:%S.%f") + ofd_i.header['DATE'] =(data_time[:21], 'written date (yyyy-mm-ddThh:mm:ss.s)') + ofd_i.header['FILENAME']=(filename_i[:68],'') + ofd_i.header['FILETYPE'] =( self.source[:12], 'observation type') + ofd_i.header['TELESCOP']=('CSST', 'telescope name') + ofd_i.header['INSTRUME']=('MCI', 'instrument name') + ofd_i.header['RADECSYS']=('ICRS', 'coordinate system of the object') + ofd_i.header['EQUINOX'] =(float(2000.0), '') + ofd_i.header['FITSSWV']=('mci_sim_0.8.03', 'FITS creating software version') + ############################################################################## + ######### Object information ######################################### + ofd_i.header['OBJECT'] =(self.information['name_obj'][:30], 'object name') + ofd_i.header['TARGET'] =(self.information['target'][:13], 'target name (hhmmss.s+ddmmss)') + ####################################################################### + ofd_i.header['OBSID'] =(str(obsid) , 'observation ID') + ofd_i.header['RA_OBJ'] =(float(self.information['ra_obj']) , 'object RA (deg)') + ofd_i.header['DEC_OBJ']=(float(self.information['dec_obj']) , 'object Dec (deg)') + - ofd_i.header['RA_PNT0'] =( np.float64(self.information['ra_pnt0']) , 'RA of the pointing (degrees) at EXPSTART') - ofd_i.header['DEC_PNT0']=(np.float64(self.information['dec_pnt0']) , 'DEC of the pointing (degrees) at EXPSTART') - + ######## Telescope information ############### + ofd_i.header['REFFRAME']=('CSSTGSC-1.0' , 'guiding catalog version') + ofd_i.header['DATE-OBS']=(data_time[:21] , 'observation date (yyyy-mm-ddThh:mm:ss.s)') + ofd_i.header['SATESWV']=('softwave-1.0', 'satellite software version') + ofd_i.header['EXPSTART']=(np.float64(time2mjd(self.dt)), 'exposure start time (MJD)') + ofd_i.header['CABSTART']=(np.float64(time2jd(self.dt)), 'first cabin time after exposure start (MJD)') + ofd_i.header['SUNANGL0']=(np.float32(0.0) , 'angle between the Sun and opt axis at CABSTART') + ofd_i.header['MOONANG0']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABSTART') + ofd_i.header['TEL_ALT0']=(np.float64(0.0), 'angle between opt axis and Elimb at CABSTART') + ofd_i.header['POS_ANG0']=(np.float64(0.0), 'angle between y axis and North Pole at CABSTART') + ofd_i.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'orbital position in X at CABSTART (km)') + ofd_i.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'orbital position in Y at CABSTART (km)') + ofd_i.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'orbital position in Z at CABSTART (km)') + ofd_i.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'orbital velocity in X at CABSTART (km/s)') + ofd_i.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'orbital velocity in Y at CABSTART (km/s)') + ofd_i.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'orbital velocity in Z at CABSTART (km/s)') + ofd_i.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at CABSTART (deg)') + ofd_i.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at CABSTART (deg)') + ofd_i.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at CABSTART (deg)') + + + ofd_i.header['RA_PNT0']=( float(self.information['ra_pnt0']) , 'pointing RA at CABSTART (deg)') + ofd_i.header['DEC_PNT0']=(float(self.information['dec_pnt0']) , 'pointing Dec at CABSTART (deg)') + ofd_i.header['EXPEND'] =(float(time2mjd(t2)), 'exposure end time (MJD)') + ofd_i.header['CABEND'] =(float(time2jd(t2)) , 'first cabin time after exposure end (MJD)') + ofd_i.header['SUNANGL1']=(np.float32(0.0), 'angle between the Sun and opt axis at CABEND') + ofd_i.header['MOONANG1']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABEND') + ofd_i.header['TEL_ALT1']=(np.float64(0.0) , 'angle between opt axis and Elimb at CABEND') + ofd_i.header['POS_ANG1']=(float(0.0) , 'angle between y axis and North Pole at CABEND') + + + ############################################################## + + ofd_i.header['POSI1_X'] =(float(p1x) , 'orbital position in X at CABEND (km)') + ofd_i.header['POSI1_Y'] =(float(p1y) , 'orbital position in Y at CABEND (km)') + ofd_i.header['POSI1_Z'] =(float(p1z) , 'orbital position in Z at CABEND (km)') - ############## - ofd_i.header['OBSID'] =(str(obsid) , 'observation ID, 3+8bit') + ofd_i.header['VELO1_X']=(float(p1vx) , 'orbital velocity in X at CABEND (km/s)') + ofd_i.header['VELO1_Y']=(float(p1vy) , 'orbital velocity in Y at CABEND (km/s)') + ofd_i.header['VELO1_Z']=(float(p1vz), 'orbital velocity in Z at CABEND (km/s)') - ######## Telescope information ############### - # ofd_i.header['COMMENT'] ='==========================================================' - # ofd_i.header['COMMENT'] ='Telescope information' - # ofd_i.header['COMMENT'] ='==========================================================' - - ofd_i.header['REFFRAME']=('CSSTGSC-1.0' , 'guide star catalog version') - ofd_i.header['DATE-OBS']=(ofd_g.header['DATE-OBS'] , 'date of the observation (yyyy-mm-dd hh:mm:ss)') - - ofd_i.header['EXPSTART']=(ofd_g.header['EXPSTART'], 'exposure start time') - ofd_i.header['SUNANGL0']=(np.float32(0.0) , 'angle between sun and optical axis at EXPSTART') - ofd_i.header['MOONANG0']=(np.float32(0.0) , 'angle between moon and optical axis at EXPSTART') - ofd_i.header['POS_ANG0']=(np.float64(0.0), 'angle between optical axis and the North Pole at EXPSTART in arcsec') - ofd_i.header['TEL_ALT0']=(np.float64(0.0), 'angle between optical axis and the ground- piston at EXPSTART in deg') - - ofd_i.header['HOODSTA0']=(np.float32(0.0) , 'lens hood altitude at EXPSTART') - ofd_i.header['HOODANG0']=(np.float32(0.0), 'lens hood azimuth at EXPSTART') - ofd_i.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'the orbital position of CSST in X direction at EXPSTART') - ofd_i.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'the orbital position of CSST in Y direction at EXPSTART') - ofd_i.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'the orbital position of CSST in Z direction at EXPSTART') - ofd_i.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'the orbital velocity of CSST in X direction at EXPSTART') - ofd_i.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'the orbital velocity of CSST in Y direction at EXPSTART') - ofd_i.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'the orbital velocity of CSST in Z direction at EXPSTART') - - ofd_i.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at EXPSTART') - ofd_i.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at EXPSTART') - ofd_i.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at EXPSTART') - - ofd_i.header['EXPEND'] =(ofd_g.header['EXPEND'] , 'exposure end time') - - ofd_i.header['SUNANGL1']=(np.float32(0.0), 'angle between sun and optical axis at EXPEND') - ofd_i.header['MOONANG1']=(np.float32(0.0) , 'angle between moon and optical axis at EXPEND ') - ofd_i.header['POS_ANG1']=(np.float64(0.0) , 'angle between optical axis and the North Pole at EXPEND in arcsec') - ofd_i.header['TEL_ALT1']=(np.float64(0.0) , 'angle between optical axis and the ground- piston at EXPEND in deg ') - ofd_i.header['HOODSTA1']=(np.float32(0.0), 'lens hood altitude at EXPEND ') - ofd_i.header['HOODANG1']=(np.float32(0.0), 'lens hood azimuth at EXPEND ') - ofd_i.header['POSI1_X'] =(np.float64(p1x) , 'the orbital position of CSST in X direction at EXPEND') - ofd_i.header['POSI1_Y'] =(np.float64(p1y) , 'the orbital position of CSST in Y direction at EXPEND') - ofd_i.header['POSI1_Z'] =(np.float64(p1z) , 'the orbital position of CSST in Z direction at EXPEND') - - ofd_i.header['VELO1_X']=(np.float64(p1vx) , 'the orbital velocity of CSST in X direction at EXPEND') - ofd_i.header['VELO1_Y']=(np.float64(p1vy) , 'the orbital velocity of CSST in Y direction at EXPEND') - ofd_i.header['VELO1_Z']=(np.float64(p1vz) , 'the orbital velocity of CSST in Z direction at EXPEND') - - ofd_i.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at EXPEND') - ofd_i.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at EXPEND') - ofd_i.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at EXPEND') - - ofd_i.header['RA_PNT1']=(np.float64(0.0), 'RA of the pointing (degrees) at EXPEND in deg') - ofd_i.header['DEC_PNT1']=(np.float64(0.0), 'DEC of the pointing (degrees) at EXPEND in deg') - - ofd_i.header['EXPTIME']=(self.information['exptime'], 'exposure duration') - ofd_i.header['EPOCH'] =(np.float32(0.0), 'coordinate epoch') - ofd_i.header['CHECKSUM']=( 0 , 'hdu-checksum') + ################### + + ofd_i.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at CABEND (deg)') + ofd_i.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at CABEND (deg)') + ofd_i.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at CABEND (deg)') + ofd_i.header['RA_PNT1'] =(float(ofd_i.header['RA_PNT0']), 'pointing RA at CABEND (deg)') + ofd_i.header['DEC_PNT1']=(float(ofd_i.header['DEC_PNT0']), 'pointing Dec at CABEND (deg)') + ofd_i.header['EPOCH'] =(np.float32(time2jd(t3.utcnow())), 'equinox of pointing RA and Dec') + ofd_i.header['EXPTIME']=(np.float32(self.information['exptime']), 'exposure time (s)') + + ss1='HDU checksum' + ss2='data unit checksum' + ofd_i.header['CHECKSUM']=( data_time[:19] , ss1) + ofd_i.header['DATASUM'] =( data_time[:19] , ss2) + ################################################ + ########## finish header for 0 layer #################### + ########## finish header for 0 layer #new image HDU - hdu_i = fits.ImageHDU(data=np.uint16(self.image_i)) + if HeaderTest=='yes': + hdu_i = fits.ImageHDU() + else: + hdu_i = fits.ImageHDU(data=np.uint16(self.image_i)) + + #### need review thie header + ### MCI header for image layer ### + #### need review thie header + hdu_i.header['XTENSION']=( 'IMAGE' , 'extension type') + hdu_i.header['BITPIX'] =( np.int16(16) , 'array data type') + hdu_i.header['NAXIS'] =( np.int16(2) , 'number of array dimensions') + hdu_i.header['NAXIS1'] =( np.int32(4936) , '') + hdu_i.header['NAXIS2'] =( np.int32(23984) , '') - ### MCI header for immage layer ### - #### Instrument information (at EXPSTART time) - hdu_i.header['PMIRRPOS']=( bool(True) , 'FSM pointing,T: point to MCI, F: not point to MCI ') - hdu_i.header['DIFFUSER']=( bool(True) , 'insert diffuser for flat calibration,T: insert diffuser, F: not insert diffuser ') - hdu_i.header['FLAMP'] =( np.int16(0) , 'status of flat lamp,0: off, 1: 1, 2: 2, 3: 3') - hdu_i.header['MCITEMP'] =( np.float32(0.0), 'MCI components temperature') - hdu_i.header['MCISTAT'] =( np.int16(0) , 'MCI components status parameters') - ##### Filter information ##### - hdu_i.header['FILTER'] =(self.filter_i , 'filter band name') - + hdu_i.header['PCOUNT']=( np.int16(0) , 'number of parameters') + hdu_i.header['GCOUNT']=( np.int16(1) , 'number of groups') + + hdu_i.header['BSCALE']=(int(1),'') + hdu_i.header['BZERO'] =(int(32768),'') + + hdu_i.header['EXTNAME']=( 'SCI' , '') + hdu_i.header['EXTVER']=(np.int16(1),'') + + hdu_i.header['BUNIT'] =('ADU','physical unit of array values') + + ###### file information ############### + + temp=t3.utcnow() + data_time=temp.strftime("%Y-%m-%dT%H:%M:%S.%f") + hdu_i.header['DATE'] =(data_time[:21], 'written date (yyyy-mm-ddThh:mm:ss.s)') + hdu_i.header['FILENAME']=(filename_i[:68],'') + hdu_i.header['FILETYPE'] =( self.source[:12], 'observation type') + hdu_i.header['RADECSYS']=('ICRS', 'coordinate system of the object') + hdu_i.header['EQUINOX'] =(float(2000.1), '') + hdu_i.header['FITSSWV']=('4.2.1', 'FITS creating software version') + + ######################################## + + #### instrument status and object information ###### + hdu_i.header['TELESCOP']=('CSST', 'telescope name') + hdu_i.header['INSTRUME']=('MCI', 'instrument name') + hdu_i.header['CHANNEL'] =('C1', 'channel number') + hdu_i.header['FILTERNO'] =(filternum, 'filter number') + hdu_i.header['DIFFUSER']=( bool(True) , 'insert diffuser for flat calibration') + hdu_i.header['FLAMP'] =( np.int16(0) , 'status of flat lamp') + hdu_i.header['MCISTAT'] =( np.int16(0) , 'MCI componetns status parameter') + + hdu_i.header['DATE_OBS'] =(data_time[:21] , 'observation date (yyyy-mm-ddThh:mm:ss.s)') + hdu_i.header['OBJECT'] =( 'MCI_obj' , 'object name') + + hdu_i.header['TARGET'] =(self.information['target'][:13], 'target name (hhmmss.s+ddmmss)') + ####################################################################### + hdu_i.header['OBSID'] =(str(obsid) , 'observation ID') + hdu_i.header['RA_OBJ'] =(float(self.information['ra_obj']) , 'object RA (deg)') + hdu_i.header['DEC_OBJ']=(float(self.information['dec_obj']) , 'object Dec (deg)') + + + + ##### detector and Filter information ##### + hdu_i.header['FILTER'] =(self.filter_i[:6] , 'filter band') ##### Detector information #### - hdu_i.header['DETNAM'] =('C3' , 'detector name for channle 3') - hdu_i.header['DETTEMP'] =(np.float32(0) , 'detector temperature') - hdu_i.header['DETSIZE'] =(str(self.image_i.shape[0])+'*'+str(self.image_i.shape[1]), 'detector size') - hdu_i.header['DATASEC'] =(str(self.information['ysize'])+'*'+str( self.information['xsize']), 'data section') - hdu_i.header['PIXSCAL1']=(np.float32(0.05) , 'pixel scale for axis 1') - hdu_i.header['PIXSCAL2']=(np.float32(0.05) , 'pixel scale for axis 2') - hdu_i.header['PIXSIZE1']=(np.float32(10.0) , 'pixel size for axis 1') - hdu_i.header['PIXSIZE2']=(np.float32(10.0) , 'pixel size for axis 2') - hdu_i.header['NCHAN'] =(np.int16(16) , 'number of readout channels') - hdu_i.header['NCHAN1'] =(np.int16(8) , 'number of horizontal channels') - hdu_i.header['NCHAN2'] =(np.int16(2) , 'number of vertical channels') + hdu_i.header['DETSN'] =('E2V-CCD-290-0000000' , 'detector serial number') + hdu_i.header['DETNAME'] =('opt-red' , 'detector name') + ####need review here + + + hdu_i.header['DETTEMP0'] =(np.float32(0) , 'detector temperature at EXPSTART (K)') + hdu_i.header['DETTEMP1'] =(np.float32(0) , 'detector temperature at EXPEND (K)') + hdu_i.header['DETTEMP2'] =(np.float32(0) , 'detector temperature at READT1 (K)') + + + + hdu_i.header['DETSIZE'] =(str(self.information['ysize'])+'*'+str( self.information['xsize']), 'detector size') + hdu_i.header['DATASECT'] =(str(self.image_g.shape[0])+'*'+str(self.image_g.shape[1]), 'data section') + + hdu_i.header['PIXSCAL1']=('0.05' , 'pixel scale for axis 1 (arcsec/pixel)') + hdu_i.header['PIXSCAL2']=('0.05' , 'pixel scale for axis 2 (arcsec/pixel)') + + hdu_i.header['PIXSIZE1']=(int(10) , 'pixel size for axis 1 (micron)') + hdu_i.header['PIXSIZE2']=(int(10) , 'pixel size for axis 2 (micron)') + + hdu_i.header['NCHANNEL'] =(np.int16(16) , 'number of readout channels') + + hdu_i.header['PSCAN1'] =(np.int32(27) , 'horizontal prescan width, per readout channel') - hdu_i.header['PSCAN2'] =(np.int32(8) , 'vertical prescan height, per readout channel') - hdu_i.header['OSCAN1'] =(np.int32(16) , 'horizontal overscan width, per readout channel') - hdu_i.header['OSCAN2'] =(np.int32(8) , 'vertical overscan width, per readout channel') - hdu_i.header['BIN_X'] =(np.int16(0) , 'bin number in X (wavelength)') - hdu_i.header['BIN_Y'] =(np.int16(0) , 'bin number in Y (spatial)') + hdu_i.header['PSCAN2'] =(np.int32(0) , 'vertical prescan height, per readout channel') - #### World coordinate system and related parameters ##### + hdu_i.header['OSCAN1'] =(np.int32(320) , 'horizontal overscan width, per readout channel') + hdu_i.header['OSCAN2'] =(np.int32(320) , 'vertical overscan width, per readout channel') + + hdu_i.header['BIN_X'] =(np.int16(1) , 'bin number in X') + hdu_i.header['BIN_Y'] =(np.int16(1) , 'bin number in Y') + + #### World coordinate system information ##### - hdu_i.header['WCSAXES']=( np.int16(2) , 'number of World Coordinate System axes') - hdu_i.header['CRPIX1'] =( np.float64(self.information['CRPIX1']) , 'x-coordinate of reference pixel') - hdu_i.header['CRPIX2'] =( np.float64(self.information['CRPIX2']) , 'y-coordinate of reference pixel') - hdu_i.header['CRVAL1'] =( np.float64(self.information['CRVAL1']) , 'first axis value at reference pixel') - hdu_i.header['CRVAL2'] =( np.float64(self.information['CRVAL2']) , 'second axis value at reference pixel') - hdu_i.header['CTYPE1'] =( 'RA---TAN' , 'the coordinate type for the first axis') - hdu_i.header['CTYPE2'] =( 'DEC---TAN' , 'the coordinate type for the second axis') - hdu_i.header['CD1_1'] =( np.float64(self.information['CD1_1']) , 'partial of first axis coordinate w.r.t. x') - hdu_i.header['CD1_2'] =( np.float64(self.information['CD1_2']) , 'partial of first axis coordinate w.r.t. y') - hdu_i.header['CD2_1'] =( np.float64(self.information['CD2_1']) , 'partial of second axis coordinate w.r.t. x') - hdu_i.header['CD2_2'] =( np.float64(self.information['CD2_2']) , 'partial of second axis coordinate w.r.t. y') - hdu_i.header['others'] =( 0.0 , 'other specific parameters') + hdu_i.header['WCSAXES']=(np.int16(2) , 'number of World Coordinate System axes') + hdu_i.header['CRPIX1'] =( round(float(self.information['CRPIX1']) ,1) , 'x-coordinate of reference pixel') + hdu_i.header['CRPIX2'] =( round(float(self.information['CRPIX2']) ,1) , 'y-coordinate of reference pixel') + + hdu_i.header['CRVAL1'] =( float(self.information['CRVAL1']) , 'value of reference pixel on axis 1') + hdu_i.header['CRVAL2'] =( float(self.information['CRVAL2']) , 'value of reference pixel on axis 2') + + hdu_i.header['CTYPE1'] =( 'RA---TAN' , 'type of RA WCS projection') + hdu_i.header['CTYPE2'] =( 'DEC--TAN' , 'type of Dec WCS projection') + + hdu_i.header['CD1_1'] =( float(self.information['CD1_1']) , 'transformation matrix element (deg/pix)') + hdu_i.header['CD1_2'] =( float(self.information['CD1_2']) , 'transformation matrix element (deg/pix)') + hdu_i.header['CD2_1'] =( float(self.information['CD2_1']) , 'transformation matrix element (deg/pix)') + hdu_i.header['CD2_2'] =( float(self.information['CD2_2']) , 'transformation matrix element (deg/pix)') + ###### Readout information ####### - hdu_i.header['GAIN1'] =( np.float32(self.information['i_gain1']) , 'CCD gain (channel 1)') - hdu_i.header['GAIN2'] =( np.float32(self.information['i_gain2']) , 'CCD gain (channel 2)') - hdu_i.header['GAIN3'] =( np.float32(self.information['i_gain3']) , 'CCD gain (channel 3)') - hdu_i.header['GAIN4'] =( np.float32(self.information['i_gain4']) , 'CCD gain (channel 4)') - hdu_i.header['GAIN5'] =( np.float32(self.information['i_gain5']) , 'CCD gain (channel 5)') - hdu_i.header['GAIN6'] =( np.float32(self.information['i_gain6']) , 'CCD gain (channel 6)') - hdu_i.header['GAIN7'] =( np.float32(self.information['i_gain7']) , 'CCD gain (channel 7)') - hdu_i.header['GAIN8'] =( np.float32(self.information['i_gain8']) , 'CCD gain (channel 8)') - hdu_i.header['GAIN9'] =( np.float32(self.information['i_gain9']) , 'CCD gain (channel 9)') - hdu_i.header['GAIN10']=( np.float32(self.information['i_gain10']) , 'CCD gain (channel 10)') - hdu_i.header['GAIN11']=( np.float32(self.information['i_gain11']) , 'CCD gain (channel 11)') - hdu_i.header['GAIN12']=( np.float32(self.information['i_gain12']) , 'CCD gain (channel 12)') - hdu_i.header['GAIN13']=( np.float32(self.information['i_gain13']) , 'CCD gain (channel 13)') - hdu_i.header['GAIN14']=( np.float32(self.information['i_gain14']) , 'CCD gain (channel 14)') - hdu_i.header['GAIN15']=( np.float32(self.information['i_gain15']) , 'CCD gain (channel 15)') - hdu_i.header['GAIN16']=( np.float32(self.information['i_gain16']) , 'CCD gain (channel 16)') + hdu_i.header['GAINLVL'] =( np.float32(1.5) , 'gain level (e-/ADU)') + hdu_i.header['GAIN01'] =( np.float32(self.information['i_gain1']) , 'CCD gain [channel 1] (e-/ADU)') + hdu_i.header['GAIN02'] =( np.float32(self.information['i_gain2']) , 'CCD gain [channel 2] (e-/ADU)') + hdu_i.header['GAIN03'] =( np.float32(self.information['i_gain3']) , 'CCD gain [channel 3] (e-/ADU)') + hdu_i.header['GAIN04'] =( np.float32(self.information['i_gain4']) , 'CCD gain [channel 4] (e-/ADU)') + hdu_i.header['GAIN05'] =( np.float32(self.information['i_gain5']) , 'CCD gain [channel 5] (e-/ADU)') + hdu_i.header['GAIN06'] =( np.float32(self.information['i_gain6']) , 'CCD gain [channel 6] (e-/ADU)') + hdu_i.header['GAIN07'] =( np.float32(self.information['i_gain7']) , 'CCD gain [channel 7] (e-/ADU)') + hdu_i.header['GAIN08'] =( np.float32(self.information['i_gain8']) , 'CCD gain [channel 8] (e-/ADU)') + hdu_i.header['GAIN09'] =( np.float32(self.information['i_gain9']) , 'CCD gain [channel 9] (e-/ADU)') + hdu_i.header['GAIN10']=( np.float32(self.information['i_gain10']) , 'CCD gain [channel 10] (e-/ADU)') + hdu_i.header['GAIN11']=( np.float32(self.information['i_gain11']) , 'CCD gain [channel 11] (e-/ADU)') + hdu_i.header['GAIN12']=( np.float32(self.information['i_gain12']) , 'CCD gain [channel 12] (e-/ADU)') + hdu_i.header['GAIN13']=( np.float32(self.information['i_gain13']) , 'CCD gain [channel 13] (e-/ADU)') + hdu_i.header['GAIN14']=( np.float32(self.information['i_gain14']) , 'CCD gain [channel 14] (e-/ADU)') + hdu_i.header['GAIN15']=( np.float32(self.information['i_gain15']) , 'CCD gain [channel 15] (e-/ADU)') + hdu_i.header['GAIN16']=( np.float32(self.information['i_gain16']) , 'CCD gain [channel 16] (e-/ADU)') ####### - hdu_i.header['RDNOIS1'] =( np.float32(self.information['i_rdnois1']) , 'read noise (channel 1)') - hdu_i.header['RDNOIS2'] =( np.float32(self.information['i_rdnois2']) , 'read noise (channel 2)') - hdu_i.header['RDNOIS3'] =( np.float32(self.information['i_rdnois3']) , 'read noise (channel 3)') - hdu_i.header['RDNOIS4'] =( np.float32(self.information['i_rdnois4']) , 'read noise (channel 4)') - hdu_i.header['RDNOIS5'] =( np.float32(self.information['i_rdnois5']) , 'read noise (channel 5)') - hdu_i.header['RDNOIS6'] =( np.float32(self.information['i_rdnois6']) , 'read noise (channel 6)') - hdu_i.header['RDNOIS7'] =( np.float32(self.information['i_rdnois7']) , 'read noise (channel 7)') - hdu_i.header['RDNOIS8'] =( np.float32(self.information['i_rdnois8']) , 'read noise (channel 8)') - hdu_i.header['RDNOIS9'] =( np.float32(self.information['i_rdnois9']) , 'read noise (channel 9)') - hdu_i.header['RDNOIS10']=( np.float32(self.information['i_rdnois10']) , 'read noise (channel 10)') - hdu_i.header['RDNOIS11']=( np.float32(self.information['i_rdnois11']) , 'read noise (channel 11)') - hdu_i.header['RDNOIS12']=( np.float32(self.information['i_rdnois12']) , 'read noise (channel 12)') - hdu_i.header['RDNOIS13']=( np.float32(self.information['i_rdnois13']) , 'read noise (channel 13)') - hdu_i.header['RDNOIS14']=( np.float32(self.information['i_rdnois14']) , 'read noise (channel 14)') - hdu_i.header['RDNOIS15']=( np.float32(self.information['i_rdnois15']) , 'read noise (channel 15)') - hdu_i.header['RDNOIS16']=( np.float32(self.information['i_rdnois16']) , 'read noise (channel 16)') + hdu_i.header['RON01'] =( np.float32(self.information['i_rdnois1']) , 'readout noise [channel 01] (e-)') + hdu_i.header['RON02'] =( np.float32(self.information['i_rdnois2']) , 'readout noise [channel 02] (e-)') + hdu_i.header['RON03'] =( np.float32(self.information['i_rdnois3']) , 'readout noise [channel 03] (e-)') + hdu_i.header['RON04'] =( np.float32(self.information['i_rdnois4']) , 'readout noise [channel 04] (e-)') + hdu_i.header['RON05'] =( np.float32(self.information['i_rdnois5']) , 'readout noise [channel 05] (e-)') + hdu_i.header['RON06'] =( np.float32(self.information['i_rdnois6']) , 'readout noise [channel 06] (e-)') + hdu_i.header['RON07'] =( np.float32(self.information['i_rdnois7']) , 'readout noise [channel 07] (e-)') + hdu_i.header['RON08'] =( np.float32(self.information['i_rdnois8']) , 'readout noise [channel 08] (e-)') + hdu_i.header['RON09'] =( np.float32(self.information['i_rdnois9']) , 'readout noise [channel 09] (e-)') + hdu_i.header['RON10']=( np.float32(self.information['i_rdnois10']) , 'readout noise [channel 10] (e-)') + hdu_i.header['RON11']=( np.float32(self.information['i_rdnois11']) , 'readout noise [channel 11] (e-)') + hdu_i.header['RON12']=( np.float32(self.information['i_rdnois12']) , 'readout noise [channel 12] (e-)') + hdu_i.header['RON13']=( np.float32(self.information['i_rdnois13']) , 'readout noise [channel 13] (e-)') + hdu_i.header['RON14']=( np.float32(self.information['i_rdnois14']) , 'readout noise [channel 14] (e-)') + hdu_i.header['RON15']=( np.float32(self.information['i_rdnois15']) , 'readout noise [channel 15] (e-)') + hdu_i.header['RON16']=( np.float32(self.information['i_rdnois16']) , 'readout noise [channel 16] (e-)') ####### - hdu_i.header['DETBIA1']=( np.float32(self.information['i_detbia1']) , 'amplifier bias voltage (channel 1)') - hdu_i.header['DETBIA2']=( np.float32(self.information['i_detbia2']) , 'amplifier bias voltage (channel 2)') - hdu_i.header['DETBIA3']=( np.float32(self.information['i_detbia3']) , 'amplifier bias voltage (channel 3)') - hdu_i.header['DETBIA4']=( np.float32(self.information['i_detbia4']) , 'amplifier bias voltage (channel 4)') - hdu_i.header['DETBIA5']=( np.float32(self.information['i_detbia5']) , 'amplifier bias voltage (channel 5)') - hdu_i.header['DETBIA6']=( np.float32(self.information['i_detbia6']) , 'amplifier bias voltage (channel 6)') - hdu_i.header['DETBIA7']=( np.float32(self.information['i_detbia7']) , 'amplifier bias voltage (channel 7)') - hdu_i.header['DETBIA8']=( np.float32(self.information['i_detbia8']) , 'amplifier bias voltage (channel 8)') - hdu_i.header['DETBIA9']=( np.float32(self.information['i_detbia9']) , 'amplifier bias voltage (channel 9)') - hdu_i.header['DETBIA10']=( np.float32(self.information['i_detbia10']) , 'amplifier bias voltage (channel 10)') - hdu_i.header['DETBIA11']=( np.float32(self.information['i_detbia11']) , 'amplifier bias voltage (channel 11)') - hdu_i.header['DETBIA12']=( np.float32(self.information['i_detbia12']) , 'amplifier bias voltage (channel 12)') - hdu_i.header['DETBIA13']=( np.float32(self.information['i_detbia13']) , 'amplifier bias voltage (channel 13)') - hdu_i.header['DETBIA14']=( np.float32(self.information['i_detbia14']) , 'amplifier bias voltage (channel 14)') - hdu_i.header['DETBIA15']=( np.float32(self.information['i_detbia15']) , 'amplifier bias voltage (channel 15)') - hdu_i.header['DETBIA16']=( np.float32(self.information['i_detbia16']) , 'amplifier bias voltage (channel 16)') - - ###### - ###### - hdu_i.header['READT0'] =( hdu_g.header['READT0'] , 'read start time (UTC)') - hdu_i.header['READT1'] =( hdu_g.header['READT1'] , 'read end time (UTC)') - hdu_i.header['DETTEMP0']=( np.float32(0) , 'detector temperature at READT0') - hdu_i.header['DETTEMP1']=( np.float32(0) , 'detector temperature at READT1') - hdu_i.header['RDSPEED'] =( np.float32(3) , 'read speed (in MHz)') - - ##### Shutter information ##### - hdu_i.header['SHUTHWV'] =( 'XXXXXXXXXXXXXXXX' , 'shutter hardware version') - hdu_i.header['SHUTSWV'] =( 'XXXXXXXXXXXXXXXX' , 'shutter software') - hdu_i.header['SHUTSTAT']=( bool(True) , 'shutter status,T: open, F: close') - hdu_i.header['SHTOPEN0']=( np.float64(0) , 'shutter open time (begin)') - hdu_i.header['SHTOPEN1']=( np.float64(0) , 'shutter open time (end)') - hdu_i.header['SHTCLOS0']=( np.float64(0) , 'shutter close time (begin)') - hdu_i.header['SHTCLOS1']=( np.float64(0) , 'shutter close time (end)') - ################ finish MCI header for image layer + hdu_i.header['DETBIA01']=( np.float32(self.information['i_detbia1']) , 'amplifier bias grey value [channel 1] (ADU)') + hdu_i.header['DETBIA02']=( np.float32(self.information['i_detbia2']) , 'amplifier bias grey value [channel 2] (ADU)') + hdu_i.header['DETBIA03']=( np.float32(self.information['i_detbia3']) , 'amplifier bias grey value [channel 3] (ADU)') + hdu_i.header['DETBIA04']=( np.float32(self.information['i_detbia4']) , 'amplifier bias grey value [channel 4] (ADU)') + hdu_i.header['DETBIA05']=( np.float32(self.information['i_detbia5']) , 'amplifier bias grey value [channel 5] (ADU)') + hdu_i.header['DETBIA06']=( np.float32(self.information['i_detbia6']) , 'amplifier bias grey value [channel 6] (ADU)') + hdu_i.header['DETBIA07']=( np.float32(self.information['i_detbia7']) , 'amplifier bias grey value [channel 7] (ADU)') + hdu_i.header['DETBIA08']=( np.float32(self.information['i_detbia8']) , 'amplifier bias grey value [channel 8] (ADU)') + hdu_i.header['DETBIA09']=( np.float32(self.information['i_detbia9']) , 'amplifier bias grey value [channel 9] (ADU)') + hdu_i.header['DETBIA10']=( np.float32(self.information['i_detbia10']) , 'amplifier bias grey value [channel 10] (ADU)') + hdu_i.header['DETBIA11']=( np.float32(self.information['i_detbia11']) , 'amplifier bias grey value [channel 11] (ADU)') + hdu_i.header['DETBIA12']=( np.float32(self.information['i_detbia12']) , 'amplifier bias grey value [channel 12] (ADU)') + hdu_i.header['DETBIA13']=( np.float32(self.information['i_detbia13']) , 'amplifier bias grey value [channel 13] (ADU)') + hdu_i.header['DETBIA14']=( np.float32(self.information['i_detbia14']) , 'amplifier bias grey value [channel 14] (ADU)') + hdu_i.header['DETBIA15']=( np.float32(self.information['i_detbia15']) , 'amplifier bias grey value [channel 15] (ADU)') + hdu_i.header['DETBIA16']=( np.float32(self.information['i_detbia16']) , 'amplifier bias grey value [channel 16] (ADU)') + hdu_i.header['ROSPEED'] =( np.float32(100) , 'readout speed (MHz)') + + ###################################### + #### exposure and shutter information ##### + hdu_i.header['EXPSTART']=(np.float64(time2mjd(self.dt)), 'exposure start time (MJD)') + hdu_i.header['EXPEND'] =(float(time2mjd(t2)), 'exposure end time (MJD)') + hdu_i.header['EXPTIME'] =(np.float32(self.information['exptime']), 'exposure times (s)') + hdu_i.header['DARKTIME'] =(np.float32(self.information['exptime']), 'dark current time (s)') + hdu_i.header['SHTSTAT']=( bool(True) , 'shutter status') + + ###### satellite and its allitide information ############## + hdu_i.header['REFFRAME']=('CSSTGSC-1.0' , 'guiding catalog version') + hdu_i.header['SATESWV']=('softwave-1.0', 'satellite software version') + hdu_i.header['CABSTART']=(np.float64(time2jd(self.dt)), 'first cabin time after exposure start (MJD)') + hdu_i.header['SUNANGL0']=(np.float32(0.0) , 'angle between the Sun and opt axis at CABSTART') + hdu_i.header['MOONANG0']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABSTART') + hdu_i.header['TEL_ALT0']=(np.float64(0.0), 'angle between opt axis and Elimb at CABSTART') + hdu_i.header['POS_ANG0']=(np.float64(0.0), 'angle between y axis and North Pole at CABSTART') + hdu_i.header['POSI0_X'] =(np.float64(self.information['pos_x']) , 'orbital position in X at CABSTART (km)') + hdu_i.header['POSI0_Y'] =(np.float64(self.information['pos_y']) , 'orbital position in Y at CABSTART (km)') + hdu_i.header['POSI0_Z'] =(np.float64(self.information['pos_z']) , 'orbital position in Z at CABSTART (km)') + hdu_i.header['VELO0_X']=( np.float64(self.information['velocity_x']) , 'orbital velocity in X at CABSTART (km/s)') + hdu_i.header['VELO0_Y']=( np.float64(self.information['velocity_y']) , 'orbital velocity in Y at CABSTART (km/s)') + hdu_i.header['VELO0_Z']=( np.float64(self.information['velocity_z']) , 'orbital velocity in Z at CABSTART (km/s)') + hdu_i.header['Euler0_1']=( np.float64(0.0), 'Euler angle 1 at CABSTART (deg)') + hdu_i.header['Euler0_2']=( np.float64(0.0), 'Euler angle 2 at CABSTART (deg)') + hdu_i.header['Euler0_3']=( np.float64(0.0), 'Euler angle 3 at CABSTART (deg)') + hdu_i.header['RA_PNT0']=( float(self.information['ra_pnt0']) , 'pointing RA at CABSTART (deg)') + hdu_i.header['DEC_PNT0']=(float(self.information['dec_pnt0']) , 'pointing Dec at CABSTART (deg)') + hdu_i.header['CABEND'] =(float(time2jd(t2)) , 'first cabin time after exposure end (MJD)') + hdu_i.header['SUNANGL1']=(np.float32(0.0), 'angle between the Sun and opt axis at CABEND') + hdu_i.header['MOONANG1']=(np.float32(0.0) , 'angle between the Moon and opt axis at CABEND') + hdu_i.header['TEL_ALT1']=(np.float64(0.0) , 'angle between opt axis and Elimb at CABEND') + hdu_i.header['POS_ANG1']=(float(0.0) , 'angle between y axis and North Pole at CABEND') + hdu_i.header['POSI1_X'] =(float(p1x) , 'orbital position in X at CABEND (km)') + hdu_i.header['POSI1_Y'] =(float(p1y) , 'orbital position in Y at CABEND (km)') + hdu_i.header['POSI1_Z'] =(float(p1z) , 'orbital position in Z at CABEND (km)') + hdu_i.header['VELO1_X']=(float(p1vx) , 'orbital velocity in X at CABEND (km/s)') + hdu_i.header['VELO1_Y']=(float(p1vy) , 'orbital velocity in Y at CABEND (km/s)') + hdu_i.header['VELO1_Z']=(float(p1vz), 'orbital velocity in Z at CABEND (km/s)') + hdu_i.header['Euler1_1']=( np.float64(0.0), 'Euler angle 1 at CABEND (deg)') + hdu_i.header['Euler1_2']=( np.float64(0.0), 'Euler angle 2 at CABEND (deg)') + hdu_i.header['Euler1_3']=( np.float64(0.0), 'Euler angle 3 at CABEND (deg)') + hdu_i.header['RA_PNT1'] =(float(hdu_i.header['RA_PNT0']), 'pointing RA at CABEND (deg)') + hdu_i.header['DEC_PNT1']=(float(hdu_i.header['DEC_PNT0']), 'pointing Dec at CABEND (deg)') + hdu_i.header['EPOCH'] =(np.float32(time2jd(t3.utcnow())), 'equinox of pointing RA and Dec') + + ############################################################## + ##### - #write the actual file + ################ finish MCI header for image layer in G channel + ##############################################################################################333 + hdulist_i=fits.HDUList([ofd_i, hdu_i]) + #### + ofd_i.header.add_comment('========================================================================',after='FITSSWV') + ofd_i.header.add_comment('OBJECT INFORMATION',after='FITSSWV') + ofd_i.header.add_comment('========================================================================',after='FITSSWV') + + ofd_i.header.add_comment('========================================================================',after='DEC_OBJ') + ofd_i.header.add_comment('TELESCOPE INFORMATION',after='DEC_OBJ') + ofd_i.header.add_comment('========================================================================',after='DEC_OBJ') + + ofd_i.header.add_comment('========================================================================',after='EPOCH') + ofd_i.header.add_comment('VERIFICATION INFORMATION',after='EPOCH') + ofd_i.header.add_comment('========================================================================',after='EPOCH') - #file_i=self.result_path+'/sky_Data/'+filename_i + ####################################################################### + hdu_i.header.add_comment('========================================================================',after='BUNIT') + hdu_i.header.add_comment('FILE INFORMATION',after='BUNIT') + hdu_i.header.add_comment('========================================================================',after='BUNIT') + + hdu_i.header.add_comment('========================================================================',after='FITSSWV') + hdu_i.header.add_comment('INSTRUMENT STATUS AND OBJECT INFORMATION',after='FITSSWV') + hdu_i.header.add_comment('========================================================================',after='FITSSWV') + + hdu_i.header.add_comment('========================================================================',after='DEC_OBJ') + hdu_i.header.add_comment('DETECTOR AND FILTER INFORMATION',after='DEC_OBJ') + hdu_i.header.add_comment('========================================================================',after='DEC_OBJ') + + hdu_i.header.add_comment('========================================================================',after='BIN_Y') + hdu_i.header.add_comment('WORLD COORDINATE SYSTEM INFORMATION',after='BIN_Y') + hdu_i.header.add_comment('========================================================================',after='BIN_Y') + + hdu_i.header.add_comment('========================================================================',after='CD2_2') + hdu_i.header.add_comment('READOUT INFORMATION',after='CD2_2') + hdu_i.header.add_comment('========================================================================',after='CD2_2') + + hdu_i.header.add_comment('========================================================================',after='ROSPEED') + hdu_i.header.add_comment('EXPOSURE AND SHUTTER INFORMATION',after='ROSPEED') + hdu_i.header.add_comment('========================================================================',after='ROSPEED') + + hdu_i.header.add_comment('========================================================================',after='SHTSTAT') + hdu_i.header.add_comment('SATELLITE AND ITS ATTITUDE INFORMATION',after='SHTSTAT') + hdu_i.header.add_comment('========================================================================',after='SHTSTAT') + + hdu_i.header.add_comment('========================================================================',after='EPOCH') + hdu_i.header.add_comment('VERIFICATION INFORMATION',after='EPOCH') + hdu_i.header.add_comment('========================================================================',after='EPOCH') + ##################################### + ################ finish MCI header for image layer in i channel + ################ finish MCI header for image layer if self.source=='DARK' or self.source=='FLAT' or self.source=='BIAS': - file_i=self.result_path+'/cali_Data/'+filename_i + file_i=self.result_path+'/cali_Data/'+filename_i+'.fits' else: - file_i=self.result_path+'/sky_Data/'+filename_i + file_i=self.result_path+'/sky_Data/'+filename_i +'.fits' - hdulist_i.writeto(file_i, overwrite=True) + hdulist_i.writeto(file_i, checksum=True) ################################################################################################# @@ -3321,83 +5112,116 @@ class MCIsimulator(): ############################################################################################## ############################################################################################## - sourcelist=['XDF','CS','PI','TO'] - + sourcelist=['EXDF','STAR','PIPR','TRNS','COMB','CALI'] self.source=self.information['sourcein'] - - self.information['ver']='1.0' - - self._loadGhostModel() - - self.load_filter_PSF() - + self.information['ver']='01' + self._loadGhostModel() + self.load_filter_PSF() self.information['simnumber']=simnumber - - - ############################################################################ + + self.debug=True + ########################### flag=0 + + self.dt_num=int((self.information['simnumber']-1)*(self.information['exptime']+self.information['readouttime']+50)/120) + now_dt=datetime.utcnow() + now_jd=time2jd(now_dt) + for k in range(1,50,1): - fn=self.information['indata_path']+'/TianCe/orbit20160925/'+str(k)+'.txt'; + fn='../MCI_inputData/TianCe/orbit20160925/'+str(k)+'.txt'; d=np.loadtxt(fn); - self.dt_num=int(self.information['simnumber']*(self.information['exptime']+self.information['readouttime']+125)/120) - now_dt=datetime.utcnow() - now_jd=time2jd(now_dt) + for kk in range(len(d[:,0])): if now_jd-d[kk,0]<=0: flag=1 break if flag==1: + print('find time index...... ') break - - self.orbit_pars=d - self.orbit_file_num=k - self.orbit_exp_num =kk - - self.information['pos_x']=float(self.orbit_pars[self.orbit_exp_num,1]) - self.information['pos_y']=float(self.orbit_pars[self.orbit_exp_num,2]) - self.information['pos_z']=float(self.orbit_pars[self.orbit_exp_num,3]) - self.information['velocity_x']=float(self.orbit_pars[self.orbit_exp_num,4]) - self.information['velocity_y']=float(self.orbit_pars[self.orbit_exp_num,5]) - self.information['velocity_z']=float(self.orbit_pars[self.orbit_exp_num,6]) - exptime_start_jd=d[kk,0] #### jd time, utc format + ################################################################ - self.dt=julian.from_jd(exptime_start_jd, fmt='jd') - - ############################################################################# - ############################################################################# + if kk +self.dt_num < len(d[:,0]): + + exptime_start_jd=d[kk+self.dt_num,0] + + self.orbit_pars=d + self.orbit_file_num=k + self.orbit_exp_num =kk + + self.information['pos_x']=float(self.orbit_pars[self.orbit_exp_num,1]) + self.information['pos_y']=float(self.orbit_pars[self.orbit_exp_num,2]) + self.information['pos_z']=float(self.orbit_pars[self.orbit_exp_num,3]) + self.information['velocity_x']=float(self.orbit_pars[self.orbit_exp_num,4]) + self.information['velocity_y']=float(self.orbit_pars[self.orbit_exp_num,5]) + self.information['velocity_z']=float(self.orbit_pars[self.orbit_exp_num,6]) + + else: + + fn='../MCI_inputData/TianCe/orbit20160925/'+str(k+1)+'.txt'; + d=np.loadtxt(fn); + + self.orbit_pars=d + self.orbit_file_num=k+1 + self.orbit_exp_num =self.dt_num + + self.information['pos_x']=float(self.orbit_pars[self.orbit_exp_num,1]) + self.information['pos_y']=float(self.orbit_pars[self.orbit_exp_num,2]) + self.information['pos_z']=float(self.orbit_pars[self.orbit_exp_num,3]) + self.information['velocity_x']=float(self.orbit_pars[self.orbit_exp_num,4]) + self.information['velocity_y']=float(self.orbit_pars[self.orbit_exp_num,5]) + self.information['velocity_z']=float(self.orbit_pars[self.orbit_exp_num,6]) + ########################################## + + ###self.dt=julian.from_jd(exptime_start_jd, fmt='jd') + self.dt = jd2time(exptime_start_jd) + self.TianCe_day=str(self.dt.year)+self.dt.strftime("-%m-%d") ####str(self.dt.year)+'-'+str(self.dt.month)+'-'+str(self.dt.day) - if self.source in sourcelist: - - self.earthshine_theta=30.0 # in degree + self.TianCe_exp_start=dt2hmd(self.dt) - - - self.TianCe_day=str(self.dt.year)+self.dt.strftime("-%m-%d") ####str(self.dt.year)+'-'+str(self.dt.month)+'-'+str(self.dt.day) + ############################################################# + + if self.source in sourcelist: - self.TianCe_exp_start=dt2hmd(self.dt) + #self.earthshine_theta=30.0 # in degree ################################### - if self.sky_shift_rot: - - np.random.seed() - ud = np.random.random() # Choose a random pointing ra in degree - dis_ra = 2*(ud-1)*10/3600.0 - - np.random.seed() - ud = np.random.random() # Choose a random pointing dec in degree - dis_dec = 2*(ud-1)*10/3600.0 # + if self.sky_shift_rot: - np.random.seed() - ud = np.random.random() # Choose a random telescope rotation in degree - rotTelPos = 2*(ud-1)*5.0*galsim.degrees # the image will rotate in clockwise rotaion between -10-10 degree - rotSkyPos = 0.0*galsim.degrees + if self.information['simnumber']>1: + + np.random.seed(self.information['simnumber']) + ud = np.random.random() # Choose a random pointing ra in degree + dis_ra = 2*(ud-1)*10/3600.0 + + np.random.seed(10*self.information['simnumber']) + ud = np.random.random() # Choose a random pointing dec in degree + dis_dec = 2*(ud-1)*10/3600.0 # + + np.random.seed(100*self.information['simnumber']) + ud = np.random.random() # Choose a random telescope rotation in degree + rotTelPos = 2*(ud-1)*5.0*galsim.degrees # the image will rotate in clockwise rotaion between -10-10 degree + rotSkyPos = 0.0*galsim.degrees + + ################################ + # ### test code + # rotTelPos = 90.0*galsim.degrees + # dis_dec= -200*0.05/3600 + # dis_ra = 100*0.05/3600 + + + else: + + dis_ra = 0 # + dis_dec = 0 # T + + rotTelPos = 0.0*galsim.degrees # the image will rotate in clockwise rotaion between -10-10 degree + rotSkyPos = 0.0*galsim.degrees + - ################################ - else: dis_ra = 0 # @@ -3419,34 +5243,56 @@ class MCIsimulator(): theta = self.information['rotTelPos'] - self.information['rotSkyPos'] self.information['rotangle']=theta.deg - + #print('rotangle',theta.deg ) self.log.info('dis_ra(in pixel)=%f, dis_dec(in pixel)=%f, sky_rot(in deg)=%f' % (dis_ra*3600/0.05, dis_dec*3600/0.05, theta.deg)) ####################################################################################################### ############################################################################# - ########## simulate star images from star SED data ################## + ######### simulate star images from star SED data ################## - if self.sim_star : - ############################ + if self.sim_star : + ########################### starimg=self.cal_StarSED_img() + if 'starimg' in dir(): + self.log.info('Generate artifical stars finished...') + # fits.writeto(self.result_path+'/ori_Sky/starimg_C1_'+str(simnumber)+'.fits',starimg['g'], overwrite=True) + # fits.writeto(self.result_path+'/ori_Sky/starimg_C2_'+str(simnumber)+'.fits',starimg['r'], overwrite=True) + # fits.writeto(self.result_path+'/ori_Sky/starimg_C3_'+str(simnumber)+'.fits',starimg['i'], overwrite=True) + + self.img_fits_save(starimg['g'], 'star_ori_C1_'+str(simnumber)) + self.img_fits_save(starimg['r'], 'star_ori_C2_'+str(simnumber)) + self.img_fits_save(starimg['i'], 'star_ori_C3_'+str(simnumber)) + + + print('star image finished') + ########################################################################## # # ######################################################################## # ###### generate galaxy SED image without Lensing effect ########## - if self.sim_galaxy : + if self.sim_galaxy and self.source=='EXDF' : losimg=self.cal_Lensing_galaxy_img() + if 'losimg' in dir(): + self.log.info('Generate los finished...') + print('losimage finished') + fits.writeto(self.result_path+'/ori_Sky/galimg_C1_'+str(simnumber)+'.fits',losimg['g'], overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/galimg_C2_'+str(simnumber)+'.fits',losimg['r'], overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/galimg_C3_'+str(simnumber)+'.fits',losimg['i'], overwrite=True) + + self.img_fits_save(losimg['g'], 'gal_ori_C1_'+str(simnumber)) + self.img_fits_save(losimg['r'], 'gal_ori_C2_'+str(simnumber)) + self.img_fits_save(losimg['i'], 'gal_ori_C3_'+str(simnumber)) + + + ################################################################## - if self.sim_star ==False and self.sim_galaxy == False: - print('error: No image will be simulated...... ') - sys.exit(1) - - #### stack the image + ### stack the image if 'losimg' in dir(): self.image_g+=losimg['g'] @@ -3460,7 +5306,15 @@ class MCIsimulator(): ########################################################################################################### - + + fits.writeto(self.result_path+'/ori_Sky/original_C1_'+str(simnumber)+'.fits',self.image_g, overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/original_C2_'+str(simnumber)+'.fits',self.image_r, overwrite=True) + fits.writeto(self.result_path+'/ori_Sky/original_C3_'+str(simnumber)+'.fits',self.image_i, overwrite=True) + + self.img_fits_save(self.image_g, 'full_ori_C1_'+str(simnumber)) + self.img_fits_save(self.image_g, 'full_ori_C2_'+str(simnumber)) + self.img_fits_save(self.image_g, 'full_ori_C3_'+str(simnumber)) + ######################################################################################################### ####### end if source =='SKY' @@ -3468,20 +5322,20 @@ class MCIsimulator(): elif self.source=='FLAT': theta=0 - + self.information['exptime']=100*self.information['simnumber']#np.ceil(self.information['simnumber']/2.0) self.information['name_obj']='FLAT' self.information['rotangle']=0 self.information['CRVAL1']=0 - self.information['CRVAL2']=0 - - self.information['CRPIX1']=self.information['xsize']/2-0.5 #### - self.information['CRPIX2']=self.information['ysize']/2-0.5 #### + self.information['CRVAL2']=0 self.information['tel_Pra']=0 self.information['tel_Pdec']=0 - + + self.information['CRPIX1']=self.information['tel_Pra']*self.information['pixel_size'] #### + self.information['CRPIX2']=self.information['tel_Pdec']*self.information['pixel_size'] #### + self.information['CD1_1']=-np.cos(theta)*self.information['pixel_size'] #### self.information['CD1_2']= np.sin(theta)*self.information['pixel_size'] #### @@ -3492,17 +5346,17 @@ class MCIsimulator(): self.information['dec_obj'] =0 self.information['ra_pnt0'] =0 self.information['dec_pnt0']=0 - self.information['target'] =0 + self.information['target'] ='FLAT' - self.image_g +=100*self.information['exptime'] - self.image_r +=100*self.information['exptime'] - self.image_i +=100*self.information['exptime'] + self.image_g +=5000*self.information['simnumber'] + self.image_r +=5000*self.information['simnumber'] + self.image_i +=5000*self.information['simnumber'] elif self.source=='DARK': theta=0 - + self.information['exptime']=2*3600*self.information['simnumber'] self.information['name_obj']='DARK' self.information['rotangle']=0 @@ -3512,9 +5366,8 @@ class MCIsimulator(): self.information['tel_Pra']=0 self.information['tel_Pdec']=0 - - self.information['CRPIX1']=self.information['xsize']/2-0.5 #### - self.information['CRPIX2']=self.information['ysize']/2-0.5 #### + self.information['CRPIX1']=self.information['tel_Pra']*self.information['pixel_size'] #### + self.information['CRPIX2']=self.information['tel_Pdec']*self.information['pixel_size'] #### self.information['CD1_1']=-np.cos(theta)*self.information['pixel_size'] #### self.information['CD1_2']= np.sin(theta)*self.information['pixel_size'] #### @@ -3526,11 +5379,11 @@ class MCIsimulator(): self.information['dec_obj'] =0 self.information['ra_pnt0'] =0 self.information['dec_pnt0']=0 - self.information['target'] =0 + self.information['target'] ='DARK' - self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) + self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) elif self.source=='BIAS': @@ -3548,8 +5401,8 @@ class MCIsimulator(): self.information['tel_Pra']=0 self.information['tel_Pdec']=0 - self.information['CRPIX1']=self.information['xsize']/2-0.5 #### - self.information['CRPIX2']=self.information['ysize']/2-0.5 #### + self.information['CRPIX1']=self.information['tel_Pra']*self.information['pixel_size'] #### + self.information['CRPIX2']=self.information['tel_Pdec']*self.information['pixel_size'] #### self.information['CD1_1']=-np.cos(theta)*self.information['pixel_size'] #### self.information['CD1_2']= np.sin(theta)*self.information['pixel_size'] #### @@ -3557,15 +5410,15 @@ class MCIsimulator(): self.information['CD2_1']= np.sin(theta)*self.information['pixel_size'] #### self.information['CD2_2']= np.cos(theta)*self.information['pixel_size'] #### + self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=float) + self.information['target'] ='BIAS' self.information['ra_obj'] =0 self.information['dec_obj'] =0 self.information['ra_pnt0'] =0 self.information['dec_pnt0']=0 - self.information['target'] =0 - - self.image_g=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_r=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) - self.image_i=np.zeros((self.information['ysize'], self.information['xsize']), dtype=np.float64) + else: print('Souce is not correct and programe will return') @@ -3573,95 +5426,101 @@ class MCIsimulator(): ######################################################################################################################## - ######################################################################################################################## #Apply flat-field large scale structure for one chip if self.flatfieldM: self.applyFlat() - #print('applyFlat') + print('applyFlat') ######################################################## if self.PRNUeffect: self.applyPRNUeffect() - #print('applyPRNUeffect') + print('applyPRNUeffect') #################################################################### if self.source in sourcelist: if self.cosmicRays: - self.addCosmicRays() - #print('addCosmicRays finisth') + if self.debug == False: + self.addCosmicRays() + print('addCosmicRays finisth') ################################################## - if self.skyback and self.source in sourcelist: - self.applyPoissonSkyNoise() - #print('apply Poisson Sky Noise') + if self.skyback: + if self.source in sourcelist: + self.applyPoissonSkyNoise() + print('apply Poisson Sky Noise') ################################################# if self.darknoise: self.applyDarkCurrent() - #print('applyDarkCurrent finisth') + print('applyDarkCurrent finisth') ################################################# - if self.shutterEffect: + if self.shutterEffect and self.information['exptime']>2.6: self.addshuttereffect() - #print('add shutter effect ') - ################################################# - - if self.source not in sourcelist: - self.applyPoissonNoise() + print('add shutter effect ') - ################################################### + ################################################# + + if self.bleeding: + if self.debug== False: + self.image_g=self.applyBleeding(self.image_g.copy()) + self.image_r=self.applyBleeding(self.image_r.copy()) + self.image_i=self.applyBleeding(self.image_i.copy()) + print('apply bleeding effect finisth') + + ################################################ + if self.nonlinearity: self.applyNonlinearity() - #print('applyNonlinearity') + print('applyNonlinearity') # ################################################ - if self.bleeding: - self.image_g=self.applyBleeding(self.image_g.copy()) - self.image_r=self.applyBleeding(self.image_r.copy()) - self.image_i=self.applyBleeding(self.image_i.copy()) - #print('apply bleeding effect finisth') - - ################################################ + - #### read CCD image to output matrix as defined + + #### read CCD image to output matrix as defined + if self.overscans and self.information['xsize']==9216 and self.information['ysize']==9232 : self.image_g=self.addScanEffect(self.image_g.copy()) self.image_r=self.addScanEffect(self.image_r.copy()) self.image_i=self.addScanEffect(self.image_i.copy()) - #print('apply overscan zone 1-16') + print('apply overscan zone 1-16') ################################################################# - - if self.radiationDamage: - self.applyRadiationDamage() - #print('applyRadiationDamage()') + if self.source in sourcelist: + if self.radiationDamage: + if self.debug == False: + self.applyRadiationDamage() + print('applyRadiationDamage()') ###################################################################### ###### apply readoutNoise ###### - + + if self.readoutNoise: self.applyReadoutNoise() - #print('apply readout noise') + print('apply readout noise') ###################################################################### - if self.information['xsize']==9216 and self.information['ysize']==9232 : + if self.information['xsize']==9216 and self.information['ysize']==9232 and self.overscans : self.electrons2ADU() ### apply gain - #print('apply 1-16 zone by different gain ') + print('apply 1-16 zone by different gain ') else: self.image_g=self.image_g/1.5 self.image_r=self.image_r/1.5 self.image_i=self.image_i/1.5 - #print('apply gain finish') + print('apply gain finish') ###################################################################### #size of the output image array, xsize is column, ysize is row, xsize = 9216,ysize = 9232 - if self.information['xsize']==9216 and self.information['ysize']==9232 : + + if self.information['xsize']==9216 and self.information['ysize']==9232 and self.overscans : self.applyBias() ### - #print('apply bias finish') + print('apply bias finish') else: self.image_g=self.image_g+500.0 self.image_r=self.image_r+500.0 @@ -3669,8 +5528,9 @@ class MCIsimulator(): ################################################################### if self.cosmetics and self.information['xsize']==9216 and self.information['ysize']==9232 : - self.applyCosmetics() - #print('applyCosmetics') + if self.debug== False: + self.applyCosmetics() + print('apply Cosmetics...') ################################################## if self.intscale: @@ -3678,21 +5538,43 @@ class MCIsimulator(): ################################################## self.writeOutputs(simnumber) - self.log.info('Finished the simulation.') - #print('The iLoop= % d simlaiton finished. ' ) + ####################################################### + self.log.info('Using the following input values:') + + for key, value in self.information.items(): + self.log.info('%s = %s' % (key, value)) + self.log.info('Using the following booleans:') + + for key, value in self.booleans.items(): + self.log.info('%s = %s' % (key, value)) + ####################################################### + + + self.log.info('Finished the ith_Exposure = %i' % (simnumber)) + + print('The iLoop= % d simlaiton finished. ' %simnumber) ################################################################################################ -def mcisim(iLoop,configfile): +def runMCIsim(sourcein,configfile,dir_path,iLoop): + + print('Simulation iLoop = ', iLoop) - opts, args = processArgs() - opts.configfile=configfile - simulate = MCIsimulator(opts) - simulate.configure(1) + # opts, args = processArgs() + # opts.configfile=configfile - simulate.simulate(1) + sim= dict() + sim[iLoop] = MCIsimulator(configfile) + + sim[iLoop].configure(iLoop,sourcein) # load the configfile; + + sim[iLoop].information['sourcein'] =sourcein + + sim[iLoop].information['dir_path'] = dir_path + + sim[iLoop].simulate(iLoop) return @@ -3701,33 +5583,8 @@ def mcisim(iLoop,configfile): ################################################################################################ ################################### main function ############################################# -############################################################################# - -if __name__ == "__main__": - - - - if len(sys.argv[:]) <2: - - configfile='./mci_data/mci_sim_example.config' - - - ########################################################################################### - - if len(sys.argv[:]) >=2: - configfile=sys.argv[1] - if not os.path.exists(configfile): - print('The given input configfile path is wrong......') - sys.exit(1) - - - - - mcisim(1, configfile) - - print('MCI simulation is successful!') - - - +# wfetimes= 2.0 #### wavefront error is wfetimes of CSST primary mirrors; +# # #### calculte MCI filters's PSF date Cube #### - \ No newline at end of file +# cal_Filter_PSF(wfetimes) +# print('finish calculate filter PSF...') diff --git a/csst_mci_sim/support/__pycache__/MCIinstrumentModel.cpython-311.pyc b/csst_mci_sim/support/__pycache__/MCIinstrumentModel.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f77477e17534effbf643611de36058aa48b97e93 Binary files /dev/null and b/csst_mci_sim/support/__pycache__/MCIinstrumentModel.cpython-311.pyc differ diff --git a/csst_mci_sim/support/__pycache__/__init__.cpython-311.pyc b/csst_mci_sim/support/__pycache__/__init__.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..7b97f2768fe746570ce1cadcf9c9e54fdbbb83b4 Binary files /dev/null and b/csst_mci_sim/support/__pycache__/__init__.cpython-311.pyc differ diff --git a/csst_mci_sim/support/__pycache__/cosmicrays.cpython-311.pyc b/csst_mci_sim/support/__pycache__/cosmicrays.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..71d7f3c4c973d74370e9fe6231971f87a80af69c Binary files /dev/null and b/csst_mci_sim/support/__pycache__/cosmicrays.cpython-311.pyc differ diff --git a/csst_mci_sim/support/__pycache__/logger.cpython-311.pyc b/csst_mci_sim/support/__pycache__/logger.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..4be3b6f4491eaf8663bc93746e998a93daa41922 Binary files /dev/null and b/csst_mci_sim/support/__pycache__/logger.cpython-311.pyc differ diff --git a/csst_mci_sim/support/__pycache__/sed.cpython-311.pyc b/csst_mci_sim/support/__pycache__/sed.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..7ab26dd45afb028bdb8bb8347fbbdba1bbd25a27 Binary files /dev/null and b/csst_mci_sim/support/__pycache__/sed.cpython-311.pyc differ diff --git a/csst_mci_sim/support/__pycache__/shao.cpython-311.pyc b/csst_mci_sim/support/__pycache__/shao.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e6195600f5a5949ab8fa6657334a6e58e2ed2655 Binary files /dev/null and b/csst_mci_sim/support/__pycache__/shao.cpython-311.pyc differ diff --git a/csst_mci_sim/support/sed.py b/csst_mci_sim/support/sed.py old mode 100644 new mode 100755 index dccb65403796c1f69a76507ade362c717cdf761c..a6bfc57e0802cbc8004f9a0951dc070d95fab407 --- a/csst_mci_sim/support/sed.py +++ b/csst_mci_sim/support/sed.py @@ -56,7 +56,7 @@ def reddening(wave, flux, ebv = 0.0, law = 'calzetti', Rv = 4.05): fluxNew = flux / (10. ** (0.4 * ebv * curve)) return fluxNew -def flux_to_mag(wave, flux, filepath, band='GAIA_bp'): +def flux_to_mag(wave, flux, band='GAIA_bp'): """Convert flux of given spectra to magnitude Args: @@ -70,12 +70,9 @@ def flux_to_mag(wave, flux, filepath, band='GAIA_bp'): # /home/yan/MCI_sim/MCI_input/SED_Code/data import os - #parent = os.path.dirname(os.path.realpath(__file__)) - - parent=filepath - - band = ascii.read(parent+'/SED_Code/seddata/' + band + '.dat') - + parent = os.path.dirname(os.path.realpath(__file__)) + + band = ascii.read(parent+'/seddata/' + band + '.dat') wave0= band['col1'] curv0= band['col2'] @@ -92,7 +89,7 @@ def flux_to_mag(wave, flux, filepath, band='GAIA_bp'): return -2.5 * np.log10(Tflux) -def calibrate(wave, flux, mag, filepath,band='GAIA_bp'): +def calibrate(wave, flux, mag, band='GAIA_bp'): """ Calibrate the spectra according to the magnitude. @@ -105,7 +102,7 @@ def calibrate(wave, flux, mag, filepath,band='GAIA_bp'): Returns: float: Flux of calibrated spectra. Units: 1e-17 erg/s/A/cm^2 """ - inst_mag = flux_to_mag(wave, flux,filepath ,band = band) + inst_mag = flux_to_mag(wave, flux, band = band) instflux = 10 ** (-0.4 * inst_mag) realflux = (mag * u.STmag).to(u.erg/u.s/u.cm**2/u.AA).value @@ -123,12 +120,12 @@ class Gal_Temp(): Template of Galaxy SED """ - def __init__(self,parent): + def __init__(self): import os - self.parent = parent + parent = os.path.dirname(os.path.realpath(__file__)) - hdulist = fits.open(self.parent+'/SED_Code/seddata/galaxy_temp.fits') + hdulist = fits.open(parent+'/seddata/galaxy_temp.fits') self.wave = hdulist[1].data['wave'] self.flux = hdulist[2].data self.age_grid = hdulist[3].data['logAge'] @@ -141,43 +138,43 @@ class Gal_Temp(): redshift (float, optional): redshift of spectra. Defaults to 0. """ wave = self.wave * (1 + redshift) - self.umag = flux_to_mag(wave, self.flux, self.parent,band='SDSS_u') - self.gmag = flux_to_mag(wave, self.flux, self.parent,band='SDSS_g') - self.rmag = flux_to_mag(wave, self.flux, self.parent,band='SDSS_r') - self.imag = flux_to_mag(wave, self.flux, self.parent,band='SDSS_i') - self.zmag = flux_to_mag(wave, self.flux, self.parent,band='SDSS_z') + self.umag = flux_to_mag(wave, self.flux, band='SDSS_u') + self.gmag = flux_to_mag(wave, self.flux, band='SDSS_g') + self.rmag = flux_to_mag(wave, self.flux, band='SDSS_r') + self.imag = flux_to_mag(wave, self.flux, band='SDSS_i') + self.zmag = flux_to_mag(wave, self.flux, band='SDSS_z') class Star_Temp(): """ Template of Stellar SED """ - def __init__(self, parent): - - #import os + def __init__(self): - #parent = os.path.dirname(os.path.realpath(__file__)) - - ##/home/yan/MCI_sim_Fabu/MCI_inputData/SED_Code - - self.parent = parent + import os - hdulist = fits.open(parent+'/SED_Code/seddata/stellar_temp.fits') + parent = os.path.dirname(os.path.realpath(__file__)) + ###print("获取其父目录——" + parent) # 从当前文件路径中获取目录 + hdulist = fits.open(parent+'/seddata/stellar_temp.fits') self.wave = hdulist[1].data['wave'] self.flux = hdulist[2].data self.Teff_grid = hdulist[3].data['Teff'] self.FeH_grid = hdulist[3].data['FeH'] + self.bpmag = flux_to_mag(self.wave, self.flux, band='GAIA_bp') + self.rpmag = flux_to_mag(self.wave, self.flux, band='GAIA_rp') + + def toMag(self): wave = self.wave - self.bpmag = flux_to_mag(wave, self.flux, self.parent,band='GAIA_bp') - self.rpmag = flux_to_mag(wave, self.flux, self.parent,band='GAIA_rp') + self.bpmag = flux_to_mag(wave, self.flux, band='GAIA_bp') + self.rpmag = flux_to_mag(wave, self.flux, band='GAIA_rp') # ------------- # SED Modelling -def Model_Stellar_SED(wave, bp, rp, temp, filepath): +def Model_Stellar_SED(wave, bp, rp, temp): """Modelling stellar SED based on bp, rp magnitude Args: @@ -197,7 +194,7 @@ def Model_Stellar_SED(wave, bp, rp, temp, filepath): idx = np.argmin(np.abs(colors - color0)) flux0 = temp.flux[idx] flux1 = np.interp(wave, temp.wave, flux0) - flux = calibrate(wave, flux1, rp, filepath, band = 'GAIA_rp') + flux = calibrate(wave, flux1, rp, band = 'GAIA_rp') return flux def Model_Galaxy_SED(wave, ugriz, z, temp): diff --git a/csst_mci_sim/support/seddata/.DS_Store b/csst_mci_sim/support/seddata/.DS_Store new file mode 100755 index 0000000000000000000000000000000000000000..c74d19996a57c2660debeb472e968fcf2510ce84 Binary files /dev/null and b/csst_mci_sim/support/seddata/.DS_Store differ diff --git a/csst_mci_sim/support/seddata/GAIA_bp.dat b/csst_mci_sim/support/seddata/GAIA_bp.dat new file mode 100755 index 0000000000000000000000000000000000000000..c4cde87260a561e289f3c1a5766acf1f5b967155 --- /dev/null +++ b/csst_mci_sim/support/seddata/GAIA_bp.dat @@ -0,0 +1,1701 @@ +3250 0.000159322 +3252.5 0.000287249 +3255 0.000428428 +3257.5 0.000582891 +3260 0.000750667 +3262.5 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b/csst_mci_sim/support/seddata/galaxy_temp.fits new file mode 100755 index 0000000000000000000000000000000000000000..268a6ddf45124358763be193dcc2e52452a5649a Binary files /dev/null and b/csst_mci_sim/support/seddata/galaxy_temp.fits differ diff --git a/csst_mci_sim/support/seddata/stellar_temp.fits b/csst_mci_sim/support/seddata/stellar_temp.fits new file mode 100755 index 0000000000000000000000000000000000000000..770045d633ff2990d8d84bbf5f993cdd0f224073 Binary files /dev/null and b/csst_mci_sim/support/seddata/stellar_temp.fits differ diff --git a/csst_mci_sim/support/shao.py b/csst_mci_sim/support/shao.py index 3717c9fb93fd242bd9b1f524bd5cfe919dd4652d..15ed21118fb28beacbb21717ddfd58cdd655ec23 100644 --- a/csst_mci_sim/support/shao.py +++ b/csst_mci_sim/support/shao.py @@ -86,11 +86,11 @@ def onOrbitObsPosition(input_ra_list, input_dec_list, input_pmra_list, input_pmd raise TypeError("Parameter 16 second range error [0 ~ 60)!", input_second) #Inital dynamic lib - # import os - # currfile=os.getcwd() - # print(currfile) + import os + currfile=os.getcwd() + print(currfile) - shao = cdll.LoadLibrary('./mci_so/libshao.so') + shao = cdll.LoadLibrary('../mci_so/libshao.so') shao.onOrbitObs.restype = c_int