Initial commit

ImageHeader.py

+"""
+generate image header
+"""
+import numpy as np
+
+from astropy.io import fits
+import astropy.wcs as pywcs
+from collections import OrderedDict
+
+# from scipy import math
+import random
+
+import os
+import sys
+import astropy.coordinates as coord
+from astropy.coordinates import SkyCoord
+from astropy.wcs.utils import fit_wcs_from_points
+from astropy.time import Time
+from astropy import wcs
+
+from datetime import datetime
+# import socket
+import platform
+
+def get_obs_id(img_type='SCI', project_cycle=6, run_counter=0, pointing_num=0):
+    # obs_type = {'SCI': '01', 'BIAS': '03', 'DARK': '07', 'FLAT': '11', 'CRS': '98', 'CRD': '99'}
+    obs_type = {'SCI': '01', 'BIAS': '03', 'DARK': '07', 'FLAT': '11', 'CRS': '98', 'CRD': '99', 'CAL': '01'}
+    # obs_id = '1'+ obs_type[img_type] + str(int(project_cycle)) + str(int(run_counter)).rjust(2, '0') + str(pointing_num).rjust(5,'0')
+    obs_id = '1'+ obs_type[img_type] + str(int(project_cycle)).rjust(2, '0') + str(int(run_counter)) + str(pointing_num).rjust(8,'0')
+    return obs_id
+
+def get_file_type(img_type='SCI'):
+    file_type = {'SCI':'SCIE', 'BIAS':'BIAS', 'DARK':'DARK', 'FLAT':'FLAT', 'CRS':'CRS', 'CRD':'CRD','CALS':'CALS','CALF':'CALF'}
+    return file_type[img_type]
+
+def chara2digit(char):
+    """ Function to judge and convert characters to digitals
+
+    Parameters
+    ----------
+
+    """
+
+    try:
+        float(char) # for int, long and float
+    except ValueError:
+        pass
+        return char
+    else:
+        data = float(char)
+        return data
+
+
+def read_header_parameter(filename='global_header.param'):
+    """ Function to read the header parameters
+
+    Parameters
+    ----------
+
+    """
+
+    name = []
+    value = []
+    description = []
+    for line in open(filename):
+        line = line.strip("\n")
+        arr = line.split('|')
+#        csvReader = csv.reader(csvDataFile)
+#        for arr in csvReader:
+        name.append(arr[0])
+        # print(arr[0],arr[1])
+        value.append(chara2digit(arr[1]))
+        description.append(arr[2])
+
+#    print(value)
+    return name, value, description
+
+def rotate_CD_matrix(cd, pa_aper):
+    """Rotate CD matrix
+    
+    Parameters
+    ----------
+    cd: (2,2) array
+        CD matrix
+    
+    pa_aper: float
+        Position angle, in degrees E from N, of y axis of the detector
+    
+    Returns
+    -------
+    cd_rot: (2,2) array
+        Rotated CD matrix
+    
+    Comments
+    --------
+    `astropy.wcs.WCS.rotateCD` doesn't work for non-square pixels in that it
+    doesn't preserve the pixel scale!  The bug seems to come from the fact
+    that `rotateCD` assumes a transposed version of its own CD matrix.
+    
+    """
+    rad = np.deg2rad(-pa_aper)
+    mat = np.zeros((2,2))
+    mat[0,:] = np.array([np.cos(rad),-np.sin(rad)])
+    mat[1,:] = np.array([np.sin(rad),np.cos(rad)])
+    cd_rot = np.dot(mat, cd)
+    return cd_rot
+
+def calcaluteSLSRotSkyCoor(pix_xy = None,rot_angle = 1, xlen = 9216, ylen = 9232, w = None):
+    rad = np.deg2rad(rot_angle)
+    mat = np.zeros((2,2))
+    mat[0,:] = np.array([np.cos(rad),-np.sin(rad)])
+    mat[1,:] = np.array([np.sin(rad),np.cos(rad)])
+    center = np.array([xlen/2, ylen/2])
+    rot_pix = np.dot(mat, pix_xy-center) + center
+    skyCoor = w.wcs_pix2world(np.array([rot_pix]), 1)
+
+    return skyCoor
+
+
+# def Header_extention(xlen = 9216, ylen = 9232, gain = 1.0, readout = 5.0, dark = 0.02,saturation=90000, row_num = 1, col_num = 1):
+#
+#     """ Creat an image frame for CCST with multiple extensions
+#
+#     Parameters
+#     ----------
+#
+#     """
+#
+#     flag_ltm_x = [0,1,-1,1,-1]
+#     flag_ltm_y = [0,1,1,-1,-1]
+#     flag_ltv_x = [0,0,1,0,1]
+#     flag_ltv_y = [0,0,0,1,1]
+#
+#     detector_size_x = int(xlen)
+#     detector_size_y = int(ylen)
+#
+#     data_x = str(int(detector_size_x))
+#     data_y = str(int(detector_size_y))
+#
+#     data_sec = '[1:'+data_x+',1:'+data_y+']'
+#     e_header_fn = os.path.split(os.path.realpath(__file__))[0] + '/extension_header.param'
+#     name, value, description = read_header_parameter(e_header_fn)
+#     f = open(os.path.split(os.path.realpath(__file__))[0] + '/filter.lst')
+#     s = f.readline()
+#     s = s.strip("\n")
+#     filters = s.split(' ')
+#     s = f.readline()
+#     s = s.strip("\n")
+#     filterID = s.split()
+#
+#     s = f.readline()
+#     s = s.strip("\n")
+#     CCDID = s.split()
+#
+#     k = (row_num-1)*6+col_num
+#
+#     h_iter = 0
+#     for n1,v1,d1 in zip(name, value, description):
+#         if n1=='EXTNAME':
+#             value[h_iter] = 'RAW,'+CCDID[k-1].rjust(2,'0')
+#         if n1=='CCDNAME':
+#             value[h_iter] = 'ccd' + CCDID[k-1].rjust(2,'0')
+#         if n1=='AMPNAME':
+#             value[h_iter] = 'ccd' + CCDID[k-1].rjust(2,'0') + ':A'
+#         if n1=='GAIN':
+#             value[h_iter] = gain
+#         if n1=='RDNOISE':
+#             value[h_iter] = readout
+#         if n1=='SATURATE':
+#             value[h_iter] = saturation
+#         if n1=='CCDCHIP':
+#             value[h_iter] = 'ccd' + CCDID[k-1].rjust(2,'0')
+#         if n1=='CCDLABEL':
+#             value[h_iter] = filters[k-1] + '-' + filterID[k-1]
+#         if n1=='DATASEC':
+#             value[h_iter] = data_sec
+#
+#         h_iter = h_iter + 1
+#
+#
+#     return name, value, description
+
+
+##9232 9216  898 534 1309 60 -40  -23.4333
+def WCS_def(xlen = 9216, ylen = 9232, gapy = 898.0, gapx1 = 534, gapx2 = 1309, ra_ref = 60, dec_ref = -40, pa = -23.433, pixel_scale = 0.074, pixel_size=1e-2, 
+    rotate_chip=0., filter = 'GI', row_num = None, col_num = None, xcen = None, ycen = None):
+
+    """ Creat a wcs frame for CCST with multiple extensions
+
+    Parameters
+    ----------
+
+    """
+    r_dat = OrderedDict()
+    r_dat['EQUINOX'] = 2000.0
+    r_dat['WCSDIM'] = 2.0
+    r_dat['CTYPE1'] = 'RA---TAN'
+    r_dat['CTYPE2'] = 'DEC--TAN'
+    r_dat['CRVAL1'] = ra_ref
+    r_dat['CRVAL2'] = dec_ref
+    
+    flag_x = [0, 1, -1, 1, -1]
+    flag_y = [0, 1, 1, -1, -1]
+    flag_ext_x = [0,-1,1,-1,1]
+    flag_ext_y = [0,-1,-1,1,1]
+    pa_aper = pa
+
+    if (row_num is not None) and (col_num is not None):
+
+        x_num = 6
+        y_num = 5
+        detector_num = x_num*y_num
+
+        detector_size_x = xlen
+        detector_size_y = ylen
+        gap_y = gapy
+        gap_x = [gapx1,gapx2]
+
+        gap_x1_num = 3
+        gap_x2_num = 2
+
+        y_center = (detector_size_y*y_num+gap_y*(y_num-1))/2
+
+        x_center = (detector_size_x*x_num+gap_x[0]*gap_x1_num+gap_x[1]*gap_x2_num)/2
+
+        gap_x_map = np.array([[0,0,0,0,0],[gap_x[0],gap_x[1],gap_x[1],gap_x[1],gap_x[1]],[gap_x[1],gap_x[0],gap_x[0],gap_x[0],gap_x[0]],[gap_x[0],gap_x[0],gap_x[0],gap_x[0],gap_x[0]],[gap_x[0],gap_x[0],gap_x[0],gap_x[0],gap_x[1]],[gap_x[1],gap_x[1],gap_x[1],gap_x[1],gap_x[0]]])
+        
+        j = row_num
+        i = col_num
+        # ccdnum = str((j-1)*5+i)
+
+        x_ref, y_ref = detector_size_x*i + sum(gap_x_map[0:i,j-1]) - detector_size_x/2. , (detector_size_y+gap_y)*j-gap_y-detector_size_y/2
+        
+        for k in range(1,2):
+            
+            cd = np.array([[ pixel_scale,  0], [0, pixel_scale]])/3600.*flag_x[k]
+            cd_rot = rotate_CD_matrix(cd, pa_aper)
+
+            # f = open("CCD"+ccdnum.rjust(2,'0')+"_extension"+str(k)+"_wcs.param","w")
+            r_dat['CRPIX1'] = flag_ext_x[k]*((x_ref+flag_ext_x[k]*detector_size_x/2)-x_center)
+            r_dat['CRPIX2'] = flag_ext_y[k]*((y_ref+flag_ext_y[k]*detector_size_y/2)-y_center)
+            r_dat['CD1_1'] = cd_rot[0,0]
+            r_dat['CD1_2'] = cd_rot[0,1]
+            r_dat['CD2_1'] = cd_rot[1,0]
+            r_dat['CD2_2'] = cd_rot[1,1]
+
+            if filter in ['GU', 'GV', 'GI']:
+
+                w = wcs.WCS(naxis=2)
+                w.wcs.crpix = [r_dat['CRPIX1'], r_dat['CRPIX2']]
+                w.wcs.cd = cd_rot
+                w.wcs.crval = [ra_ref, dec_ref]
+                w.wcs.ctype = [r_dat['CTYPE1'], r_dat['CTYPE2']]
+
+                # test_center_o = w.wcs_pix2world(np.array([[xlen / 2, ylen / 2]]), 1)
+
+                sls_rot = 1
+                if i > 2:
+                    sls_rot = -sls_rot
+
+                sn_x = 30
+                sn_y = 30
+                x_pixs = np.zeros(sn_y * sn_x)
+                y_pixs = np.zeros(sn_y * sn_x)
+                xpixs_line = np.linspace(1, xlen, sn_x)
+                ypixs_line = np.linspace(1, ylen, sn_y)
+
+                sky_coors = []
+
+                for n1, y in enumerate(ypixs_line):
+                    for n2, x in enumerate(xpixs_line):
+                        i_pix = n1 * sn_x + n2
+                        x_pixs[i_pix] = x
+                        y_pixs[i_pix] = y
+
+                        pix_coor = np.array([x, y])
+                        sc1 = calcaluteSLSRotSkyCoor(pix_xy=pix_coor, rot_angle=sls_rot, xlen=xlen, ylen=ylen, w=w)
+                        # print(sc1[0,0],sc1[0,1])
+                        sky_coors.append((sc1[0, 0], sc1[0, 1]))
+
+                wcs_new = fit_wcs_from_points(xy=np.array([x_pixs, y_pixs]),
+                                            world_coords=SkyCoord(sky_coors, frame="icrs", unit="deg"), projection='TAN')
+
+                # print(wcs_new)
+                # test_center = wcs_new.wcs_pix2world(np.array([[xlen / 2, ylen / 2]]), 1)
+                #
+                # print(test_center - test_center_o)
+
+                r_dat['CD1_1'] = wcs_new.wcs.cd[0, 0]
+                r_dat['CD1_2'] = wcs_new.wcs.cd[0, 1]
+                r_dat['CD2_1'] = wcs_new.wcs.cd[1, 0]
+                r_dat['CD2_2'] = wcs_new.wcs.cd[1, 1]
+                r_dat['CRPIX1'] = wcs_new.wcs.crpix[0]
+                r_dat['CRPIX2'] = wcs_new.wcs.crpix[1]
+
+                r_dat['CRVAL1'] = wcs_new.wcs.crval[0]
+                r_dat['CRVAL2'] = wcs_new.wcs.crval[1]
+
+    elif (xcen is not None) and (ycen is not None):
+        xcen, ycen = xcen/pixel_size, ycen/pixel_size
+        x1, y1 = xcen - xlen/2., ycen - ylen/2.
+        r_dat['CRPIX1'] = -x1
+        r_dat['CRPIX2'] = -y1
+
+        # cd = np.array([[ pixel_scale,  0], [0, pixel_scale]])/3600.*flag_x[1]
+        cd = np.array([[ pixel_scale,  0], [0, -pixel_scale]])/3600.
+        cd_rot = rotate_CD_matrix(cd, pa_aper)
+        r_dat['CD1_1'] = cd_rot[0,0]
+        r_dat['CD1_2'] = cd_rot[0,1]
+        r_dat['CD2_1'] = cd_rot[1,0]
+        r_dat['CD2_2'] = cd_rot[1,1]
+
+        w = wcs.WCS(naxis=2)
+        w.wcs.crpix = [r_dat['CRPIX1'], r_dat['CRPIX2']]
+        w.wcs.cd = cd_rot
+        w.wcs.crval = [ra_ref, dec_ref]
+        w.wcs.ctype = [r_dat['CTYPE1'], r_dat['CTYPE2']]
+
+        sn_x = 30
+        sn_y = 30
+        x_pixs = np.zeros(sn_y * sn_x)
+        y_pixs = np.zeros(sn_y * sn_x)
+        xpixs_line = np.linspace(1, xlen, sn_x)
+        ypixs_line = np.linspace(1, ylen, sn_y)
+        sky_coors = []
+        for n1, y in enumerate(ypixs_line):
+            for n2, x in enumerate(xpixs_line):
+                i_pix = n1 * sn_x + n2
+                x_pixs[i_pix] = x
+                y_pixs[i_pix] = y
+                pix_coor = np.array([x, y])
+                sc1 = calcaluteSLSRotSkyCoor(pix_xy=pix_coor, rot_angle=rotate_chip, xlen=xlen, ylen=ylen, w=w)
+                sky_coors.append((sc1[0, 0], sc1[0, 1]))
+        wcs_new = fit_wcs_from_points(xy=np.array([x_pixs, y_pixs]), 
+                                      world_coords=SkyCoord(sky_coors, frame="icrs", unit="deg"), 
+                                      projection='TAN')
+        r_dat['CD1_1'] = wcs_new.wcs.cd[0, 0]
+        r_dat['CD1_2'] = wcs_new.wcs.cd[0, 1]
+        r_dat['CD2_1'] = wcs_new.wcs.cd[1, 0]
+        r_dat['CD2_2'] = wcs_new.wcs.cd[1, 1]
+        r_dat['CRPIX1'] = wcs_new.wcs.crpix[0]
+        r_dat['CRPIX2'] = wcs_new.wcs.crpix[1]
+
+        r_dat['CRVAL1'] = wcs_new.wcs.crval[0]
+        r_dat['CRVAL2'] = wcs_new.wcs.crval[1]
+
+    else:
+        raise ValueError('In function WCS_def(): Either (row_num, col_num) or (xcen, ycen, pixel_size) should be given')
+    
+    return r_dat
+
+
+
+#TODO project_cycle is temporary， is not in header defined, delete in future
+def generatePrimaryHeader(xlen = 9216, ylen = 9232, pointNum = '1', ra = 60, dec = -40, pixel_scale = 0.074, date='200930', time_obs='120000', im_type = 'MS', exptime=150., sat_pos = [0.,0.,0.], sat_vel = [0., 0., 0.], project_cycle=6, run_counter=0, chip_name="01"):
+
+    # array_size1, array_size2, flux, sigma = int(argv[1]), int(argv[2]), 1000.0, 5.0
+
+    
+    # k = (row_num-1)*6+col_num
+    # ccdnum = str(k)
+
+    g_header_fn = 'global_header.header'
+    f = open('filter.lst')
+    s = f.readline()
+    s = s.strip("\n")
+    filters = s.split(' ')
+    s = f.readline()
+    s = s.strip("\n")
+    filterID = s.split()
+
+    s = f.readline()
+    s = s.strip("\n")
+    CCDID = s.split()
+
+    h_prim = fits.Header()
+    h_prim = fits.Header.fromfile(g_header_fn)
+
+    # h_prim['PIXSIZE1'] = xlen
+    # h_prim['PIXSIZE2'] = ylen
+
+    h_prim['DATE'] = '20'+date[0:2]+'-' + date[2:4]+'-'+date[4:6] + 'T' + time_obs[0:2]+':'+time_obs[2:4]+':'+time_obs[4:6]
+    # h_prim['TIME'] = time_obs[0:2]+':'+time_obs[2:4]+':'+time_obs[4:6]
+    h_prim['DATE-OBS'] = '20'+date[0:2]+'-' + date[2:4]+'-'+date[4:6] + 'T' + time_obs[0:2]+':'+time_obs[2:4]+':'+time_obs[4:6]
+    # h_prim['TIME-OBS'] = time_obs[0:2]+':'+time_obs[2:4]+':'+time_obs[4:6]
+    # h_prim['DETECTOR'] = 'CHIP'+CCDID[k-1].rjust(2,'0')
+    h_prim['OBJ_RA'] = ra
+    h_prim['OBJ_DEC'] = dec
+
+    # obs_type = {'SCI': '01', 'BIAS': '03', 'DARK': '07', 'FLAT': '11', 'CRS': '98', 'CRD': '99'}
+
+    # # OBS_id = '1'+ obs_type[im_type] + str(int(project_cycle)) + pointNum.rjust(7,'0')
+    # OBS_id = '1'+ obs_type[im_type] + str(int(project_cycle)) + str(int(run_counter)).rjust(2, '0') + pointNum.rjust(5,'0')
+    OBS_id = get_obs_id(img_type=im_type, project_cycle=project_cycle, run_counter=run_counter, pointing_num=pointNum)
+
+    h_prim['OBJECT'] = str(int(project_cycle)) + pointNum.rjust(7, '0')
+    h_prim['OBSID'] = OBS_id
+    # h_prim['TELFOCUS'] = 'f/14'
+    h_prim['EXPTIME'] = exptime
+    
+    # # Define file types
+    # file_type = {'SCI':'SCIE', 'BIAS':'BIAS', 'DARK':'DARK', 'FLAT':'FLAT', 'CRS':'CRS', 'CRD':'CRD','CALS':'CALS','CALF':'CALF'}
+    # h_prim['FILETYPE'] = file_type[im_type]
+    h_prim['FILETYPE'] = get_file_type(img_type=im_type)
+
+    co = coord.SkyCoord(ra, dec, unit='deg')
+
+    ra_hms = format(co.ra.hms.h, '02.0f') + format(co.ra.hms.m, '02.0f') + format(co.ra.hms.s, '02.0f')
+    dec_hms = format(co.dec.dms.d, '02.0f') + format(abs(co.dec.dms.m), '02.0f') + format(abs(co.dec.dms.s), '02.0f')
+    h_prim['TARGET'] = ra_hms + '+' + dec_hms
+    #
+    # h_prim['RA_NOM'] = ra_hms
+    # h_prim['DEC_NOM'] = dec_hms
+
+    h_prim['RA_PNT0'] = ra
+    h_prim['DEC_PNT0'] = dec
+    h_prim['RA_PNT1'] = ra
+    h_prim['DEC_PNT1'] = dec
+
+
+
+    # h_prim['PIXSCAL1'] = pixel_scale
+    # h_prim['PIXSCAL2'] = pixel_scale
+
+    ttt = h_prim['DATE']
+    tstart = Time(ttt)
+    h_prim['EXPSTART'] = round(tstart.mjd, 5)
+    h_prim['CABSTART'] = h_prim['EXPSTART']
+    # tend = Time(tstart.cxcsec + h_prim['EXPTIME'], format="cxcsec")
+    tend = Time(tstart.mjd + h_prim['EXPTIME']/86400., format="mjd")
+    h_prim['EXPEND'] = round(tend.mjd, 5)
+    h_prim['CABEND'] = h_prim['EXPEND']
+
+    file_start_time = '20' + date[0:6] + time_obs[0:6]
+    end_time_str = str(tend.datetime)
+    file_end_time = end_time_str[0:4] + end_time_str[5:7]+end_time_str[8:10] + end_time_str[11:13] + end_time_str[14:16] + end_time_str[17:19]
+    # h_prim['FILENAME'] = 'CSST_MSC_MS_' + im_type + '_' + file_start_time + '_' + file_end_time + '_' + OBS_id + '_' + CCDID[
+    #     k - 1].rjust(2, '0') + '_L0_V01'
+    h_prim['FILENAME'] = 'CSST_MSC_MS_' + h_prim['FILETYPE'] + '_' + file_start_time + '_' + file_end_time + '_' + OBS_id + '_' + chip_name + '_L0_V01'
+
+
+    h_prim['POSI0_X'] = sat_pos[0]
+    h_prim['POSI0_Y'] = sat_pos[1]
+    h_prim['POSI0_Z'] = sat_pos[2]
+
+    h_prim['VELO0_X'] = sat_vel[0]
+    h_prim['VELO0_Y'] = sat_vel[1]
+    h_prim['VELO0_Z'] = sat_vel[2]
+    # h_prim['RA_PNT0'] = ra_hms
+    # h_prim['DEC_PNT0'] = dec_hms
+    
+    # Get version of CSSTSim Package
+    from pkg_resources import get_distribution
+    # h_prim['SIM_VER'] = (get_distribution("CSSTSim").version, "Version of CSST MSC simulation software")
+    currentDateAndTime = datetime.now()
+    compute_name = platform.node()
+    h_prim['FITSCREA'] = get_distribution("CSSTSim").version +'_' + currentDateAndTime.strftime("%Y%m%d") + '_' +compute_name
+    h_prim['EPOCH'] = round((Time(h_prim['EXPSTART'], format='mjd', scale='tcb')).jyear, 1)
+
+    return h_prim
+
+def generateExtensionHeader(chip, xlen = 9216, ylen = 9232,ra = 60, dec = -40, pa = -23.433, gain = 1.0, readout = 5.0, dark = 0.02, saturation=90000, pixel_scale = 0.074, pixel_size=1e-2, 
+                            extName='SCI', row_num = None, col_num = None, xcen=None, ycen=None, timestamp = 1621915200,exptime = 150., readoutTime = 40.):
+
+    e_header_fn = 'extension_header.header'
+    f = open('filter.lst')
+    s = f.readline()
+    s = s.strip("\n")
+    filters = s.split(' ')
+    s = f.readline()
+    s = s.strip("\n")
+    filterID = s.split()
+
+    s = f.readline()
+    s = s.strip("\n")
+    CCDID = s.split()
+
+    # k = (row_num - 1) * 6 + col_num
+
+    h_ext = fits.Header.fromfile(e_header_fn)
+
+    # h_ext['CCDCHIP'] = CCDID[k - 1].rjust(2, '0')
+    # h_ext['CCDLABEL'] = filters[k-1] + '-' + filterID[k-1]
+    # h_ext['FILTER'] = filters[k-1]
+    h_ext['CHIPID'] = str(chip.chipID).rjust(2, '0')
+    h_ext['CHIPLAB'] = chip.chip_name
+    h_ext['FILTER'] = chip.filter_type
+    h_ext['NAXIS1'] = xlen
+    h_ext['NAXIS2'] = ylen
+    h_ext['EXTNAME'] = extName
+    h_ext['GAIN01'] = 1
+    h_ext['GAIN02'] = 1
+    h_ext['GAIN03'] = 1
+    h_ext['GAIN04'] = 1
+    h_ext['GAIN05'] = 1
+    h_ext['GAIN06'] = 1
+    h_ext['GAIN07'] = 1
+    h_ext['GAIN08'] = 1
+    h_ext['GAIN09'] = 1
+    h_ext['GAIN10'] = 1
+    h_ext['GAIN11'] = 1
+    h_ext['GAIN12'] = 1
+    h_ext['GAIN13'] = 1
+    h_ext['GAIN14'] = 1
+    h_ext['GAIN15'] = 1
+    h_ext['GAIN16'] = 1
+    h_ext['RON01'] = readout
+    h_ext['RON02'] = readout
+    h_ext['RON03'] = readout
+    h_ext['RON04'] = readout
+    h_ext['RON05'] = readout
+    h_ext['RON06'] = readout
+    h_ext['RON07'] = readout
+    h_ext['RON08'] = readout
+    h_ext['RON09'] = readout
+    h_ext['RON10'] = readout
+    h_ext['RON11'] = readout
+    h_ext['RON12'] = readout
+    h_ext['RON13'] = readout
+    h_ext['RON14'] = readout
+    h_ext['RON15'] = readout
+    h_ext['RON16'] = readout
+
+    h_ext['PIXSCAL1'] = pixel_scale
+    h_ext['PIXSCAL2'] = pixel_scale
+    h_ext['EXPTIME'] = exptime
+    h_ext['DARKTIME'] = exptime + 2
+
+    datetime_obs = datetime.utcfromtimestamp(timestamp)
+    tstart = Time(datetime_obs)
+    tstart_read = Time(tstart.mjd + exptime / 86400., format="mjd")
+    tend_read = Time(tstart.mjd + (exptime + readoutTime) / 86400., format="mjd")
+    t_s1 = str(tstart_read.datetime).split()
+    h_ext['READT0'] = t_s1[0]+'T'+t_s1[1]
+    t_s2 = str(tend_read.datetime).split()
+    h_ext['READT1'] = t_s2[0] + 'T' + t_s2[1]
+
+
+
+    # h_ext['POS_ANG'] = pa
+    header_wcs = WCS_def(xlen=xlen, ylen=ylen, gapy=898.0, gapx1=534, gapx2=1309, ra_ref=ra, dec_ref=dec, pa=pa, pixel_scale=pixel_scale, pixel_size=pixel_size, 
+                         rotate_chip=chip.rotate_angle, filter = h_ext['FILTER'], row_num=row_num, col_num=col_num, xcen = xcen, ycen = ycen)
+
+    h_ext['CRPIX1'] = header_wcs['CRPIX1']
+    h_ext['CRPIX2'] = header_wcs['CRPIX2']
+    h_ext['CRVAL1'] = header_wcs['CRVAL1']
+    h_ext['CRVAL2'] = header_wcs['CRVAL2']
+    h_ext['CD1_1'] = header_wcs['CD1_1']
+    h_ext['CD1_2'] = header_wcs['CD1_2']
+    h_ext['CD2_1'] = header_wcs['CD2_1']
+    h_ext['CD2_2'] = header_wcs['CD2_2']
+    # h_ext['EQUINOX'] = header_wcs['EQUINOX']
+    # h_ext['WCSDIM'] = header_wcs['WCSDIM']
+    h_ext['CTYPE1'] = header_wcs['CTYPE1']
+    h_ext['CTYPE2'] = header_wcs['CTYPE2']
+
+    return h_ext
+
+
+
+def main(argv):
+
+    xlen = int(argv[1])
+    ylen = int(argv[2])
+    pointingNum = argv[3]
+    ra = float(argv[4])
+    dec = float(argv[5])
+    pSize = float(argv[6])
+    ccd_row_num = int(argv[7])
+    ccd_col_num = int(argv[8])
+    pa_aper = float(argv[9])
+    gain = float(argv[10])
+    readout = float(argv[11])
+    dark = float(argv[12])
+    fw = float(argv[13])
+
+
+
+    h_prim = generatePrimaryHeader(xlen = xlen, ylen = ylen,ra = ra, dec = dec, psize = pSize, row_num = ccd_row_num, col_num = ccd_col_num, pointNum = pointingNum)
+
+    h_ext = generateExtensionHeader(xlen = xlen, ylen = ylen,ra = ra, dec = dec, pa = pa_aper, gain = gain, readout = readout, dark = dark, saturation=fw, psize = pSize, row_num = ccd_row_num, col_num = ccd_col_num)
+    hdu1 = fits.PrimaryHDU(header=h_prim)
+    hdu2 = fits.ImageHDU(np.zeros([ylen,xlen]),header = h_ext)
+
+    hdul = fits.HDUList([hdu1,hdu2])
+
+    hdul.writeto(h_prim['FILENAME']+'.fits',output_verify='ignore')
+
+# if __name__ == "__main__":
+#     main(sys.argv)

chip_definition.json

+{
+    "31": {
+        "chip_name": "FGS1A-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -325.395,
+        "y_cen": -47.82,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "32": {
+        "chip_name": "FGS1A-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -325.395,
+        "y_cen": 22.7,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "33": {
+        "chip_name": "FGS1B-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -325.395,
+        "y_cen": 93.195,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "34": {
+        "chip_name": "FGS1B-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -325.395,
+        "y_cen": 163.69,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "35": {
+        "chip_name": "FGS2A-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 325.395,
+        "y_cen": 47.82,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "36": {
+        "chip_name": "FGS2A-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 325.395,
+        "y_cen": -22.7,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "37": {
+        "chip_name": "FGS2B-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 325.395,
+        "y_cen": -93.195,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "38": {
+        "chip_name": "FGS2B-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 325.395,
+        "y_cen": -163.69,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "39": {
+        "chip_name": "FGS3-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -273.35,
+        "y_cen": 211.36,
+        "rotate_angle": 90.0,
+        "n_psf_samples": 100,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "40": {
+        "chip_name": "FGS3-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": -202.805,
+        "y_cen": 211.36,
+        "rotate_angle": 90.0,
+        "n_psf_samples": 100,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "41": {
+        "chip_name": "FGS4-D1",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 151.03,
+        "y_cen": -233.885,
+        "rotate_angle": 90.0,
+        "n_psf_samples": 100,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "42": {
+        "chip_name": "FGS4-D2",
+        "pix_size": 0.0075,
+        "pix_scale": 0.0555,
+        "npix_x": 11264,
+        "npix_y": 7680,
+        "x_cen": 80.51,
+        "y_cen": -233.885,
+        "rotate_angle": 90.0,
+        "n_psf_samples": 100,
+        "dark_exptime": 300.0,
+        "falt_exptime": 150.0,
+        "readout_time": 0.01,
+        "df_strength": 2.3,
+        "bias_level": 2000.0,
+        "gain": 1.0,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "1": {
+        "chip_name": "GI-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 251.5,
+        "y_cen": -202.6,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "2": {
+        "chip_name": "GV-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 251.5,
+        "y_cen": -101.3,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "3": {
+        "chip_name": "GU-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 251.5,
+        "y_cen": 0.0,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "4": {
+        "chip_name": "GU-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 251.5,
+        "y_cen": 101.3,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "5": {
+        "chip_name": "GV-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 251.5,
+        "y_cen": 202.6,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "6": {
+        "chip_name": "y-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 146.25,
+        "y_cen": -202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "7": {
+        "chip_name": "i-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 146.25,
+        "y_cen": -101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "8": {
+        "chip_name": "g-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 146.25,
+        "y_cen": 0.0,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "9": {
+        "chip_name": "r-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 146.25,
+        "y_cen": 101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "10": {
+        "chip_name": "GI-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 154.0,
+        "y_cen": 202.6,
+        "rotate_angle": -1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "11": {
+        "chip_name": "z-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 48.75,
+        "y_cen": -202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "12": {
+        "chip_name": "NUV-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 48.75,
+        "y_cen": -101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "13": {
+        "chip_name": "NUV-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 48.75,
+        "y_cen": 0.0,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "14": {
+        "chip_name": "u-1",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 48.75,
+        "y_cen": 101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "15": {
+        "chip_name": "y-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": 48.75,
+        "y_cen": 202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "16": {
+        "chip_name": "y-3",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -48.75,
+        "y_cen": -202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "17": {
+        "chip_name": "u-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -48.75,
+        "y_cen": -101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "18": {
+        "chip_name": "NUV-3",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -48.75,
+        "y_cen": 0.0,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "19": {
+        "chip_name": "NUV-4",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -48.75,
+        "y_cen": 101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "20": {
+        "chip_name": "z-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -48.75,
+        "y_cen": 202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "21": {
+        "chip_name": "GI-3",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -154.0,
+        "y_cen": -202.6,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "22": {
+        "chip_name": "r-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -146.25,
+        "y_cen": -101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "23": {
+        "chip_name": "g-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -146.25,
+        "y_cen": 0.0,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "24": {
+        "chip_name": "i-2",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -146.25,
+        "y_cen": 101.3,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "25": {
+        "chip_name": "y-4",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -146.25,
+        "y_cen": 202.6,
+        "rotate_angle": 0.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "26": {
+        "chip_name": "GV-3",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -251.5,
+        "y_cen": -202.6,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "27": {
+        "chip_name": "GU-3",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -251.5,
+        "y_cen": -101.3,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "28": {
+        "chip_name": "GU-4",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -251.5,
+        "y_cen": 0.0,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "29": {
+        "chip_name": "GV-4",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -251.5,
+        "y_cen": 101.3,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    },
+    "30": {
+        "chip_name": "GI-4",
+        "pix_size": 0.01,
+        "pix_scale": 0.074,
+        "npix_x": 9216,
+        "npix_y": 9232,
+        "x_cen": -251.5,
+        "y_cen": 202.6,
+        "rotate_angle": 1.0,
+        "n_psf_samples": 900,
+        "dark_exptime": 300,
+        "flat_exptime": 150,
+        "readout_time": 40,
+        "df_strength": 2.3,
+        "bias_level": 500,
+        "gain": 1.1,
+        "full_well": 90000,
+        "prescan_x": 27,
+        "overscan_x": 71,
+        "prescan_y": 0,
+        "overscan_y": 84
+    }
+}

extension_header.header

+XTENSION= 'IMAGE   '           / extension type                                 BITPIX  =                   16 / bits per data value                            NAXIS   =                    2 / number of data axes                            NAXIS1  =                 9216 / length of first array axis                     NAXIS2  =                 9232 / length of second array axis                    PCOUNT  =                    0                                                  GCOUNT  =                    1                                                  EXTNAME = 'SCI     '                                                            EXTVER  =                    1                                                  BSCALE  =                    1                                                  BZERO   =                32768                                                  BUNIT   = 'ADU     '            / physical unit of array values                 COMMENT ==================================================================      COMMENT Detector information                                                    COMMENT ==================================================================      CAMERA  = 'MS'                  / camera of main survey                         DETSN   = '12345678'            / detector serial number                        DETNAME = 'CCD'                 / detector type                                 DETTEMP1=                 173.0 / detector temperature at EXPSTART(in Kelvin)   DETTEMP2=                 173.0 / detector temperature at EXPEND(in Kelvin)     DETTEMP3=                 173.0 / detector temperature at READT1(in Kelvin)     DETSIZE = '9560x9264'           / detector size                                 DATASECT= '9216x9232'           / data section                                  PIXSCAL1=                 0.074 / pixel scale for axis 1                        PIXSCAL2=                 0.074 / pixel scale for axis 2                        PIXSIZE1=                    10 / pixel size for axis 1 (in um)                 PIXSIZE2=                    10 / pixel size for axis 2 (in um)                 COMMENT ==================================================================      COMMENT CCD chip information                                                    COMMENT ==================================================================      CHIPID  = '08'                  / chip ID                                       CHIPLAB = 'y-1'                 / chip label                                    FILTER  = 'y'                   / filter name                                   NCHAN   =                    16 / number of readout channels                    PSCAN1  =                    27 / horizontal prescan width, per readout channel PSCAN2  =                     8 / vertical prescan width, per readout channel   OSCAN1  =                    16 / horizontal overscan width,per readout channel OSCAN2  =                    16 / vertical overscan width,per readout channel   COMMENT ==================================================================      COMMENT WORLD COORDINATE SYSTEM AND RELATED PARAMETERS                          COMMENT ==================================================================      WCSAXES =                    2 / number of World Coordinate System axes         CRPIX1  =             -10017.0 / x-coordinate of reference pixel                CRPIX2  =              24876.0 / y-coordinate of reference pixel                CRVAL1  =            62.228226 / first axis value at reference pixel            CRVAL2  =           -42.316932 / second axis value at reference pixel           CTYPE1  = 'RA---TAN'           / the coordinate type for the first axis         CTYPE2  = 'DEC--TAN'           / the coordinate type for the second axis        CD1_1   = 1.88602083707394E-05 / partial of first axis coordinate w.r.t.x       CD1_2   = 8.17455836176000E-06 / partial of first axis coordinate w.r.t.y       CD2_1   = -8.1745583617600E-06 / partial of second axis coordinate w.r.t.x      CD2_2   = 1.88602083707394E-05 / partial of second axis coordinate w.r.t.y      OTHERS  =                 ''   /                                                COMMENT ==================================================================      COMMENT Readout information                                                     COMMENT ==================================================================      GAINLVL = '01'                 / gain level                                     GAIN01  =                  1.1 / gain (channel 01)                              GAIN02  =                  1.1 / gain (channel 02)                              GAIN03  =                  1.1 / gain (channel 03)                              GAIN04  =                  1.1 / gain (channel 04)                              GAIN05  =                  1.1 / gain (channel 05)                              GAIN06  =                  1.1 / gain (channel 06)                              GAIN07  =                  1.1 / gain (channel 07)                              GAIN08  =                  1.1 / gain (channel 08)                              GAIN09  =                  1.1 / gain (channel 09)                              GAIN10  =                  1.1 / gain (channel 10)                              GAIN11  =                  1.1 / gain (channel 11)                              GAIN12  =                  1.1 / gain (channel 12)                              GAIN13  =                  1.1 / gain (channel 13)                              GAIN14  =                  1.1 / gain (channel 14)                              GAIN15  =                  1.1 / gain (channel 15)                              GAIN16  =                  1.1 / gain (channel 16)                              RON01   =                  5.0 / read noise (channel 01)                        RON02   =                  5.0 / read noise (channel 02)                        RON03   =                  5.0 / read noise (channel 03)                        RON04   =                  5.0 / read noise (channel 04)                        RON05   =                  5.0 / read noise (channel 05)                        RON06   =                  5.0 / read noise (channel 06)                        RON07   =                  5.0 / read noise (channel 07)                        RON08   =                  5.0 / read noise (channel 08)                        RON09   =                  5.0 / read noise (channel 09)                        RON10   =                  5.0 / read noise (channel 10)                        RON11   =                  5.0 / read noise (channel 11)                        RON12   =                  5.0 / read noise (channel 12)                        RON13   =                  5.0 / read noise (channel 13)                        RON14   =                  5.0 / read noise (channel 14)                        RON15   =                  5.0 / read noise (channel 15)                        RON16   =                  5.0 / read noise (channel 16)                        READT0  = '2024-00-00T00:00:00'/ readout start time(UTC)                        READT1  = '2024-00-00T00:00:00'/ readout end time(UTC)                          ROSPEED =                 10.0 / readout speed (in MHz)                         EXPTIME =                150.0 / exposure duration                              DARKTIME=                150.0 / dark current time                              COMMENT ==================================================================      COMMENT Shutter information                                                     COMMENT ==================================================================      SHTSTAT =                    T / shutter status                                 SHTOPEN0=                  0.0 / shutter open time (begin)                      SHTOPEN1=                  0.0 / shutter open time (end)                        SHTCLOS0=                  0.0 / shutter close time (begin)                     SHTCLOS1=                  0.0 / shutter close time (end)                       COMMENT ==================================================================      COMMENT LED information                                                         COMMENT ==================================================================      LEDFLAG =                    0 / main/backup LED                                LEDSTAT = '00000000000000'     / LED status                                     LEDEXPT =                  0.0 / LED flash time (s)                             LEDTEMP =                173.0 / LED temperature (in K)                         COMMENT ==================================================================      COMMENT Other information                                                       COMMENT ==================================================================      CHECKSUM= '''abcde'''          / HDU checksum updated yyyy-mm-ddTHH:MM:SS       DATASUM = '''abcde'''          / data unit checksum updated yyyy-mm-ddTHH:MM:SS END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          

filter.lst

+GV GI y z y GI GU r u NUV i GV GU g NUV NUV g GU GV i NUV u r GU GI y z y GI GV
+3  3  3 1 1 1  3  2 2 1   1 1  4  2 3   2   1 1  4  2 4   1 1 2  4  2 2 4 2  2
+26 21 16 11 6 1 27 22 17 12 7 2 28 23 18 13 8 3 29 24 19 14 9 4 30 25 20 15 10 5

gen_calib_catalog.py

+from cgitb import reset
+from tkinter.tix import INTEGER
+import astropy.coordinates as coord
+from astropy import units as u
+from pylab import *
+import numpy as np
+import galsim
+import math
+from astropy.table import Table, vstack
+from astropy.io import fits
+from astropy.wcs import WCS
+import os
+import json
+
+import ImageHeader
+
+# from numba import jit
+ALL_FILTERS = ["NUV", "u", "g", "r", "i", "z", "y", "GU", "GV", "GI", "FGS"]
+
+
+class Chip(object):
+    def __init__(self, chipID):
+        self.chipID = chipID
+
+        self.nchip_x = 6
+        self.nchip_y = 5
+        self.npix_tot_x = 59516
+        self.npix_tot_y = 49752
+        self.npix_gap_x = (534, 1309)
+        self.npix_gap_y = 898
+
+        self.cen_pix_x = 0
+        self.cen_pix_y = 0
+
+        self.npix_x = 9216
+        self.npix_y = 9232
+        self.pix_scale = 0.074
+
+        chip_dict = json.load(open("chip_definition.json", "r"))[str(self.chipID)]
+        for key in chip_dict:
+            setattr(self, key, chip_dict[key])
+        self.filter_id, self.filter_type = self.getChipFilter()
+
+    def getTanWCS(
+        self, ra, dec, img_rot, pix_scale=None, xcen=None, ycen=None, logger=None
+    ):
+        """Get the WCS of the image mosaic using Gnomonic/TAN projection
+
+        Parameter:
+            ra, dec:    float
+                        (RA, Dec) of pointing of optical axis
+            img_rot:    galsim Angle object
+                        Rotation of image
+            pix_scale:  float
+                        Pixel size in unit of as/pix
+        Returns:
+            WCS of the focal plane
+        """
+        if logger is not None:
+            logger.info(
+                "    Construct the wcs of the entire image mosaic using Gnomonic/TAN projection"
+            )
+        if (xcen == None) or (ycen == None):
+            xcen = self.cen_pix_x
+            ycen = self.cen_pix_y
+        if pix_scale == None:
+            pix_scale = self.pix_scale
+        # dudx =  -np.cos(img_rot.rad) * pix_scale
+        # dudy =  -np.sin(img_rot.rad) * pix_scale
+        # dvdx =  -np.sin(img_rot.rad) * pix_scale
+        # dvdy =  +np.cos(img_rot.rad) * pix_scale
+
+        dudx = -np.cos(img_rot.rad) * pix_scale
+        dudy = +np.sin(img_rot.rad) * pix_scale
+        dvdx = -np.sin(img_rot.rad) * pix_scale
+        dvdy = -np.cos(img_rot.rad) * pix_scale
+        moscen = galsim.PositionD(x=xcen, y=ycen)
+        sky_center = galsim.CelestialCoord(
+            ra=ra * galsim.degrees, dec=dec * galsim.degrees
+        )
+        affine = galsim.AffineTransform(dudx, dudy, dvdx, dvdy, origin=moscen)
+        WCS = galsim.TanWCS(affine, sky_center, units=galsim.arcsec)
+
+        return WCS
+
+    def getChipRowCol(self, chipID):
+        rowID = ((chipID - 1) % 5) + 1
+        colID = 6 - ((chipID - 1) // 5)
+        return rowID, colID
+
+    def getChipCenter(self):
+        """Calculate the edges in pixel for a given CCD chip on the focal plane
+        NOTE: There are 5*4 CCD chips in the focus plane for photometric observation.
+        Parameters:
+            chipID:         int
+                            the index of the chip
+        Returns:
+            A galsim BoundsD object
+        """
+
+        chipID = self.chipID
+
+        rowID, colID = self.getChipRowCol(chipID)
+        gx1, gx2 = self.npix_gap_x
+        gy = self.npix_gap_y
+
+        # xlim of a given CCD chip
+        xrem = 2 * (colID - 1) - (self.nchip_x - 1)
+        xcen = (self.npix_x // 2 + gx1 // 2) * xrem
+        if chipID >= 26 or chipID == 21:
+            xcen = (self.npix_x // 2 + gx1 // 2) * xrem - (gx2 - gx1)
+        if chipID <= 5 or chipID == 10:
+            xcen = (self.npix_x // 2 + gx1 // 2) * xrem + (gx2 - gx1)
+        # nx0 = xcen - self.npix_x//2 + 1
+        # nx1 = xcen + self.npix_x//2
+
+        # ylim of a given CCD chip
+        yrem = (rowID - 1) - self.nchip_y // 2
+        ycen = (self.npix_y + gy) * yrem
+        # ny0 = ycen - self.npix_y//2 + 1
+        # ny1 = ycen + self.npix_y//2
+
+        return galsim.PositionD(xcen, ycen)
+
+    def getChipFilter(self, chipID=None):
+        """Return the filter index and type for a given chip #(chipID)"""
+        filter_type_list = ALL_FILTERS
+        if chipID == None:
+            chipID = self.chipID
+
+        # updated configurations
+        if chipID > 42 or chipID < 1:
+            raise ValueError("!!! Chip ID: [1,42]")
+        if chipID in [6, 15, 16, 25]:
+            filter_type = "y"
+        if chipID in [11, 20]:
+            filter_type = "z"
+        if chipID in [7, 24]:
+            filter_type = "i"
+        if chipID in [14, 17]:
+            filter_type = "u"
+        if chipID in [9, 22]:
+            filter_type = "r"
+        if chipID in [12, 13, 18, 19]:
+            filter_type = "NUV"
+        if chipID in [8, 23]:
+            filter_type = "g"
+        if chipID in [1, 10, 21, 30]:
+            filter_type = "GI"
+        if chipID in [2, 5, 26, 29]:
+            filter_type = "GV"
+        if chipID in [3, 4, 27, 28]:
+            filter_type = "GU"
+        if chipID in range(31, 43):
+            filter_type = "FGS"
+        filter_id = filter_type_list.index(filter_type)
+
+        return filter_id, filter_type
+
+
+def transRaDec2D(ra, dec):
+    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 getobsPA(ra, dec):
+    l1 = np.array([0, 0, 1])
+    l2 = transRaDec2D(ra, dec)
+    polar_ec = coord.SkyCoord(
+        0 * u.degree, 90 * u.degree, frame="barycentrictrueecliptic"
+    )
+    polar_eq = polar_ec.transform_to("icrs")
+
+    # print(polar_eq.ra.value,polar_eq.dec.value)
+    polar_d = transRaDec2D(polar_eq.ra.value, polar_eq.dec.value)
+    l1l2cross = np.cross(l2, l1)
+    pdl2cross = np.cross(l2, polar_d)
+    angle = math.acos(
+        np.dot(l1l2cross, pdl2cross)
+        / (np.linalg.norm(l1l2cross) * np.linalg.norm(pdl2cross))
+    )
+
+    angle = (angle) / math.pi * 180
+
+    # if (ra>90 and ra< 270):
+    #     angle=-angle
+    return angle
+
+
+def getChipRangeInfo(chipID=8, ra=60.0, dec=-40.0, pa=113.0):
+    """_summary_
+
+    Args:
+        chipID (int, optional): Chip ID.
+        ra (_type_, optional): Chip center ra.
+        dec (_type_, optional): Chip center dec.
+
+    Returns:
+        _type_: [ra, dec, rotation angle]
+    """
+    # chip_center = [ra, dec]
+
+    chip = Chip(chipID)
+
+    h_ext = ImageHeader.generateExtensionHeader(
+        chip=chip,
+        xlen=chip.npix_x,
+        ylen=chip.npix_y,
+        ra=ra,
+        dec=dec,
+        pa=pa,
+        gain=chip.gain,
+        readout=5.0,
+        dark=0.02,
+        saturation=90000,
+        pixel_scale=chip.pix_scale,
+        pixel_size=chip.pix_size,
+        xcen=chip.x_cen,
+        ycen=chip.y_cen,
+        extName="SCI",
+        timestamp=1621915200,
+        exptime=150,
+        readoutTime=chip.readout_time,
+    )
+    chip_wcs = WCS(h_ext)
+
+    return chip_wcs, chip.npix_x, chip.npix_y, chip.chipID, chip.filter_type
+
+
+def formateSEDfile(inputDir, outputDir):
+    fileFns = os.listdir(inputDir)
+
+    for fn in fileFns:
+        if fn[0] == ".":
+            continue
+        if ".fits" not in fn:
+            continue
+        dfn = os.path.join(inputDir, fn)
+        outfn = os.path.join(outputDir, "GP_" + fn[0:-5] + ".fits")
+        f = fits.open(dfn)
+        data_tab = Table(f[1].data)
+        col_names = data_tab.colnames
+        if "loglam" in col_names:
+            print("1:" + fn)
+            w1 = pow(10, f[1].data["loglam"])
+            f1 = f[1].data["flux"] * 1e-17
+        elif "WAVELENGTH" in col_names:
+            print("2:" + fn)
+            w1 = np.array(data_tab["WAVELENGTH"].tolist()[0])
+            f1 = np.array(data_tab["FLUX"].tolist()[0]) * 1e-17
+        w = np.zeros(w1.shape[0] + 4)
+        w[0] = 2000
+        w[1] = w1[0] - 1
+        w[-2] = w1[-1] + 1
+        w[-1] = 15000
+        w[2:-2] = w1
+        fl = np.zeros(f1.shape[0] + 4)
+        fl[0] = 0
+        fl[1] = 0
+        fl[-2] = 0
+        fl[-1] = 0
+        fl[2:-2] = f1
+        t = Table([w, fl], names=["WAVELENGTH", "FLUX"])
+        # t = Table([pow(10,f[1].data['loglam']),f[1].data['flux']*1e-17],names=['WAVELENGTH','FLUX'])
+        t.write(outfn, overwrite=True)
+
+
+def genOneChipCat(
+    ra=40.0,
+    dec=-40.0,
+    pa=23.5,
+    chipID=1,
+    pointSource_flag=True,
+    sersic_index=1.0,
+    re=0.078,
+    specFn="LMC-SMP-58_spectrum_csst.fits",
+):
+
+    chip_wcs, chip_xlen, chip_ylen, _, filterT = getChipRangeInfo(
+        chipID=chipID, ra=ra, dec=dec, pa=pa
+    )
+
+    sppos = 3685
+
+    xSize = 15
+    ySize = 30
+    y_interval = 20
+
+    X2 = np.linspace(100, sppos - 100, xSize)
+    Y2 = np.linspace(100, chip_ylen - 300, ySize)
+    y_gap = np.arange(0, y_interval * xSize, y_interval)
+    x2, y2 = np.meshgrid(X2, Y2)
+    y2 = y2 + y_gap
+    x2 = x2.flatten()
+    y2 = y2.flatten()
+
+    X1 = np.linspace(sppos + 300, chip_xlen - 100, xSize)
+    Y1 = np.linspace(150, chip_ylen - 250, ySize)
+    y_gap = np.arange(0, y_interval * xSize, y_interval)
+    x1, y1 = np.meshgrid(X1, Y1)
+    y1 = y1 + y_gap
+    x1 = x1.flatten()
+    y1 = y1.flatten()
+
+    tab_size = x1.size + x2.size
+    x = np.zeros(tab_size)
+    y = np.zeros_like(x)
+    x[0 : x1.size] = x1
+    x[x1.size :] = x2
+    y[0 : x1.size] = y1
+    y[x1.size :] = y2
+
+    radecs = chip_wcs.pixel_to_world(x, y)
+
+    # ids = np.arange(0, tab_size, 1)
+    mags = np.zeros(tab_size) + -99
+    sns = np.zeros(tab_size) + sersic_index
+    res = np.zeros(tab_size) + re
+    namelist = []
+    ids = []
+    for i in np.arange(tab_size):
+        namelist.append(specFn)
+        ids.append(format(chipID, "02.0f") + format(i + 1, "04.0f"))
+
+    if pointSource_flag:
+        p_flag = np.ones(tab_size, dtype=bool)  # True
+    else:
+        p_flag = np.zeros(tab_size, dtype=bool)  # False
+
+    cat_t = Table(
+        [ids, radecs.ra.deg, radecs.dec.deg, res, sns, mags, namelist, p_flag],
+        names=(
+            "ID",
+            "RA",
+            "DEC",
+            "RE",
+            "SERSIC_N",
+            "MAG_g",
+            "SPEC_FN",
+            "POINTSOURCE_FLAG",
+        ),
+    )
+    return cat_t
+
+
+if __name__ == "__main__":
+    ra = 244.972773
+    dec = 39.895901
+    pa = 109.59452000342756
+    chipIDs = [1, 2, 3, 4, 5, 10, 21, 26, 27, 28, 29, 30]
+    cat_t = Table()
+    for chipID in chipIDs:
+        cat_one = genOneChipCat(
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            chipID=chipID,
+            pointSource_flag=True,
+            specFn="LMC-SMP-58_spectrum_csst.fits",
+        )
+        cat_t = vstack([cat_t, cat_one])
+    cat_t.write(
+        "calibrationPNESPEC_CHIP_ALL_SLS.fits",
+        format="fits",
+        overwrite=True,
+    )

global_header.header

+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  NEXTEND =                    1 / number of array dimensions                     GROUPS  =                    F / '   '                                          DATE    = '2021-03-04T09:30:00'/ the date on which this file was written        FILENAME= 'MSC_MS_210304093000_100000000_06_raw' / file name                    FILETYPE= 'SCIE    '           / observation type                               TELESCOP= 'CSST    '           / telescope used to acquire data                 INSTRUME= 'MSC     '           / instrument used to acquire data                RADECSYS= 'ICRS    '           / reference coordinates system                   EQUINOX =               2000.0 /                                                FITSCREA= 'C6'                 / FITS create software version                   COMMENT ==================================================================      COMMENT Object information                                                      COMMENT ==================================================================      OBJECT  = '00000000'           / object name                                    TARGET  = '+000000000000'      / target name (hhmmss+ddmmss)                    OBSID   = '00000000'           / observation ID                                 OBJ_RA  =            62.228226 / R.A. of the object (degrees)                   OBJ_DEC =           -42.316932 / declination of the object (degrees)            COMMENT ==================================================================      COMMENT Telescope information                                                   COMMENT ==================================================================      REFFRAME= 'CSSTGSC-1.0'        / guide star catalog version                     DATE-OBS= '2021-03-04T09:30:00'/ date of the observation (yyyy-mm-dd hh:mm:ss)  SATESWV = '0001'               / software version in the satellite              EXPSTART=              59130.5 / exposure start time (MJD)                      CABSTART=              59130.5 / (MJD)                                          SUNANGL0=                 50.0 / angle between sun and opt axis at CABSTART     MOONANG0=                 30.0 / angle between moon and opt axis at CABSTART    TEL_ALT0=                 20.0 / angle between opt axis and Elimb at CABSTART   POS_ANG0=                 20.0 / angle between y axis and NP at CABSTART        POSI0_X =                  0.0 / the orbital position in X at CABSTART          POSI0_Y =                  0.0 / the orbital position in Y at CABSTART          POSI0_Z =                  0.0 / the orbital position in Z at CABSTART          VELO0_X =                  0.0 / the orbital velocity in X at CABSTART          VELO0_Y =                  0.0 / the orbital velocity in Y at CABSTART          VELO0_Z =                  0.0 / the orbital velocity in Z at CABSTART          EULER0_1=                  0.0 / euler angle 1 at CABSTART                      EULER0_2=                  0.0 / euler angle 2 at CABSTART                      EULER0_3=                  0.0 / euler angle 3 at CABSTART                      RA_PNT0 =                  0.0 / RA of the pointing (degrees) at CABSTART       DEC_PNT0=                  0.0 / DEC of the pointing (degrees) at CABSTART      EXPEND  =                  0.0 / exposure end time (MJD)                        CABEND  =                  0.0 / (MJD)                                          SUNANGL1=                 50.0 / angle between sun and opt axis at CABEND       MOONANG1=                 30.0 / angle between moon and opt axis at CABEND      TEL_ALT1=                 20.0 / angle between opt axis and Elimb at CABEND     POS_ANG1=                 20.0 / angle between y axis and NP at CABEND          POSI1_X =                  0.0 / the orbital position in X at CABEND            POSI1_Y =                  0.0 / the orbital position in Y at CABEND            POSI1_Z =                  0.0 / the orbital position in Z at CABEND            VELO1_X =                  0.0 / the orbital velocity in X at CABEND            VELO1_Y =                  0.0 / the orbital velocity in Y at CABEND            VELO1_Z =                  0.0 / the orbital velocity in Z at CABEND            EULER1_1=                  0.0 / euler angle 1 at CABEND                        EULER1_2=                  0.0 / euler angle 2 at CABEND                        EULER1_3=                  0.0 / euler angle 3 at CABEND                        RA_PNT1 =                  0.0 / RA of the pointing (degrees) at CABEND         DEC_PNT1=                  0.0 / DEC of the pointing (degrees) at CABEND        EXPTIME =                150.0 / exposure duration                              EPOCH   =               2000.0 / coordinate epoch                               COMMENT Other information                                                       COMMENT ==================================================================      CHECKSUM= 'abcdefg '           / HDU checksum updated yyyy-mm-ddTHH:MM:SS       DATASUM = 'abcdefg '           / data unit checksum updated yyyy-mm-ddTHH:MM:SS END