ObservationSim.py

import os
import numpy as np
import mpi4py.MPI as MPI
import galsim
import logging
import psutil
import gc
from astropy.io import fits
from datetime import datetime

import traceback

from ObservationSim.Config import config_dir, ChipOutput
from ObservationSim.Config.Header import generatePrimaryHeader, generateExtensionHeader
from ObservationSim.Instrument import Telescope, Filter, FilterParam, FocalPlane, Chip
from ObservationSim.Instrument.Chip import Effects
from ObservationSim.Straylight import calculateSkyMap_split_g
from ObservationSim.PSF import PSFGauss, FieldDistortion, PSFInterp, PSFInterpSLS
from ObservationSim._util import get_shear_field, makeSubDir_PointingList
from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position
from ObservationSim.MockObject import FlatLED

class Observation(object):
    def __init__(self, config, Catalog, work_dir=None, data_dir=None):
        self.path_dict = config_dir(config=config, work_dir=work_dir, data_dir=data_dir)
        self.config = config
        self.tel = Telescope()
        self.focal_plane = FocalPlane(survey_type=self.config["obs_setting"]["survey_type"]) 
        self.filter_param = FilterParam() 
        self.chip_list = []
        self.filter_list = []
        self.all_filter = []
        self.Catalog = Catalog

        # Construct chips & filters:
        for i in range(self.focal_plane.nchips):
            chipID = i + 1

            # Make Chip & Filter lists
            chip = Chip(
                chipID=chipID, 
                config=self.config)
            filter_id, filter_type = chip.getChipFilter()
            filt = Filter(filter_id=filter_id, 
                filter_type=filter_type, 
                filter_param=self.filter_param)
            if not self.focal_plane.isIgnored(chipID=chipID):
                self.chip_list.append(chip)
                self.filter_list.append(filt)
            self.all_filter.append(filt)

    def run_one_chip(self, chip, filt, pointing, chip_output, wcs_fp=None, psf_model=None, cat_dir=None, sed_dir=None):

        chip_output.Log_info(':::::::::::::::::::Current Pointing Information::::::::::::::::::')
        chip_output.Log_info("RA: %f, DEC; %f" % (pointing.ra, pointing.dec))
        chip_output.Log_info("Time: %s" % datetime.utcfromtimestamp(pointing.timestamp).isoformat())
        chip_output.Log_info("Exposure time: %f" % pointing.exp_time)
        chip_output.Log_info("Satellite Position (x, y, z): (%f, %f, %f)" % (pointing.sat_x, pointing.sat_y, pointing.sat_z))
        chip_output.Log_info("Satellite Velocity (x, y, z): (%f, %f, %f)" % (pointing.sat_vx, pointing.sat_vy, pointing.sat_vz))
        chip_output.Log_info("Position Angle: %f" % pointing.img_pa.deg)
        chip_output.Log_info('Chip : %d' % chip.chipID)
        chip_output.Log_info(':::::::::::::::::::::::::::END:::::::::::::::::::::::::::::::::::')

        if self.config["psf_setting"]["psf_model"] == "Gauss":
            psf_model = PSFGauss(chip=chip, psfRa=self.config["psf_setting"]["psf_rcont"])
        elif self.config["psf_setting"]["psf_model"] == "Interp":
            if chip.survey_type == "spectroscopic":
                psf_model = PSFInterpSLS(chip, filt,PSF_data_prefix=self.path_dict["psf_sls_dir"])
            else:
                psf_model = PSFInterp(chip=chip, npsf=chip.n_psf_samples, PSF_data_file=self.path_dict["psf_dir"])
        else:
            chip_output.Log_error("unrecognized PSF model type!!", flush=True)

        # Figure out shear fields
        self.g1_field, self.g2_field, self.nshear = get_shear_field(config=self.config)

        # Apply astrometric simulation for pointing
        if self.config["obs_setting"]["enable_astrometric_model"]:
            dt = datetime.utcfromtimestamp(pointing.timestamp)
            date_str = dt.date().isoformat()
            time_str = dt.time().isoformat()
            ra_cen, dec_cen = on_orbit_obs_position(
                input_ra_list=[pointing.ra],
                input_dec_list=[pointing.dec],
                input_pmra_list=[0.],
                input_pmdec_list=[0.],
                input_rv_list=[0.],
                input_parallax_list=[1e-9],
                input_nstars=1,
                input_x=pointing.sat_x,
                input_y=pointing.sat_y,
                input_z=pointing.sat_z,
                input_vx=pointing.sat_vx,
                input_vy=pointing.sat_vy,
                input_vz=pointing.sat_vz,
                input_epoch="J2000",
                input_date_str=date_str,
                input_time_str=time_str
            )
            ra_cen, dec_cen = ra_cen[0], dec_cen[0]
        else:
            ra_cen = pointing.ra
            dec_cen = pointing.dec

        # Get WCS for the focal plane
        if wcs_fp == None:
            wcs_fp = self.focal_plane.getTanWCS(ra_cen, dec_cen, pointing.img_pa, chip.pix_scale)

        # Create chip Image
        chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
        chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
        chip.img.wcs = wcs_fp

        if self.config["obs_setting"]["enable_straylight_model"]:
            filt.setFilterStrayLightPixel(jtime = pointing.jdt, sat_pos = np.array([pointing.sat_x, pointing.sat_y, pointing.sat_z]), pointing_radec = np.array([pointing.ra,pointing.dec]), sun_pos = np.array([pointing.sun_x,pointing.sun_y,pointing.sun_z]))

        chip_output.Log_info("========================sky pix========================")
        chip_output.Log_info(filt.sky_background)

        if chip.survey_type == "photometric":
            sky_map = None
        elif chip.survey_type == "spectroscopic":
            # chip.loadSLSFLATCUBE(flat_fn='flat_cube.fits')
            flat_normal = np.ones_like(chip.img.array)
            if self.config["ins_effects"]["flat_fielding"] == True:
                chip_output.Log_info("SLS flat preprocess,CHIP %d : Creating and applying Flat-Fielding"%chip.chipID)
                msg = str(chip.img.bounds)
                chip_output.Log_info(msg)
                flat_img = Effects.MakeFlatSmooth(
                    chip.img.bounds,
                    int(self.config["random_seeds"]["seed_flat"]))
                flat_normal = flat_normal * flat_img.array / np.mean(flat_img.array)
            if self.config["ins_effects"]["shutter_effect"] == True:
                chip_output.Log_info("SLS flat preprocess,CHIP %d : Apply shutter effect"%chip.chipID)
                shuttimg = Effects.ShutterEffectArr(chip.img, t_shutter=1.3, dist_bearing=735,
                                                    dt=1E-3)  # shutter effect normalized image for this chip
                flat_normal = flat_normal*shuttimg
                flat_normal = np.array(flat_normal,dtype='float32')
            sky_map = calculateSkyMap_split_g(
                skyMap=flat_normal,
                blueLimit=filt.blue_limit,
                redLimit=filt.red_limit,
                conf=chip.sls_conf,
                pixelSize=chip.pix_scale,
                isAlongY=0,
                flat_cube=chip.flat_cube, zoldial_spec = filt.zodical_spec)
            sky_map = sky_map+filt.sky_background
            del flat_normal

        if pointing.pointing_type == 'SCI':
            # Load catalogues and templates
            self.cat = self.Catalog(config=self.config, chip=chip, pointing=pointing, cat_dir=cat_dir, sed_dir=sed_dir, chip_output=chip_output, filt=filt)
            chip_output.create_output_file()
            self.nobj = len(self.cat.objs)

            for ifilt in range(len(self.all_filter)):
                temp_filter = self.all_filter[ifilt]
                # Update the limiting magnitude using exposure time in pointing
                temp_filter.update_limit_saturation_mags(exptime=pointing.get_full_depth_exptime(temp_filter.filter_type), chip=chip)

                # Select cutting band filter for saturation/limiting magnitude
                if temp_filter.filter_type.lower() == self.config["obs_setting"]["cut_in_band"].lower():
                    cut_filter = temp_filter

            if self.config["ins_effects"]["field_dist"] == True:
                self.fd_model = FieldDistortion(chip=chip, img_rot=pointing.img_pa.deg)
            else:
                self.fd_model = None

            # Loop over objects
            missed_obj = 0
            bright_obj = 0
            dim_obj = 0
 
            h_ext = generateExtensionHeader(
                chip=chip,
                xlen=chip.npix_x, 
                ylen=chip.npix_y, 
                ra=pointing.ra, 
                dec=pointing.dec, 
                pa=pointing.img_pa.deg, 
                gain=chip.gain, 
                readout=chip.read_noise, 
                dark=chip.dark_noise, 
                saturation=90000, 
                pixel_scale=chip.pix_scale, 
                pixel_size=chip.pix_size,
                xcen=chip.x_cen,
                ycen=chip.y_cen,
                extName='SCI',
                timestamp = pointing.timestamp,
                exptime = pointing.exp_time,
                readoutTime = chip.readout_time)
            
            chip_wcs = galsim.FitsWCS(header=h_ext)

            for j in range(self.nobj):
                
                # # (DEBUG)
                # if j >= 10:
                #     break

                obj = self.cat.objs[j]

                # (DEBUG)
                # if obj.getMagFilter(filt)>20:
                #     continue

                # load and convert SED; also caculate object's magnitude in all CSST bands
                try:
                    sed_data = self.cat.load_sed(obj)
                    norm_filt = self.cat.load_norm_filt(obj)
                    obj.sed, obj.param["mag_%s"%filt.filter_type.lower()], obj.param["flux_%s"%filt.filter_type.lower()] = self.cat.convert_sed(
                        mag=obj.param["mag_use_normal"],
                        sed=sed_data,
                        target_filt=filt, 
                        norm_filt=norm_filt,
                    )
                    _, obj.param["mag_%s"%cut_filter.filter_type.lower()], obj.param["flux_%s"%cut_filter.filter_type.lower()] = self.cat.convert_sed(
                        mag=obj.param["mag_use_normal"],
                        sed=sed_data,
                        target_filt=cut_filter, 
                        norm_filt=norm_filt,
                    )
                except Exception as e:
                    traceback.print_exc()
                    chip_output.Log_error(e)
                    continue
                
                # [TODO] Testing
                # chip_output.Log_info("mag_%s = %.3f"%(filt.filter_type.lower(), obj.param["mag_%s"%filt.filter_type.lower()]))

                # Exclude very bright/dim objects (for now)
                if cut_filter.is_too_bright(
                    mag=obj.param["mag_%s"%self.config["obs_setting"]["cut_in_band"].lower()],
                    margin=self.config["obs_setting"]["mag_sat_margin"]):
                    chip_output.Log_info("obj %s too birght!! mag_%s = %.3f"%(obj.id, cut_filter.filter_type, obj.param["mag_%s"%self.config["obs_setting"]["cut_in_band"].lower()]))
                    bright_obj += 1
                    obj.unload_SED()
                    continue
                if filt.is_too_dim(
                    mag=obj.getMagFilter(filt),
                    margin=self.config["obs_setting"]["mag_lim_margin"]):
                    chip_output.Log_info("obj %s too dim!! mag_%s = %.3f"%(obj.id, filt.filter_type, obj.getMagFilter(filt)))
                    dim_obj += 1
                    obj.unload_SED()
                    continue

                # Get corresponding shear values
                if self.config["shear_setting"]["shear_type"] == "constant":
                    if obj.type == 'star':
                        obj.g1, obj.g2 = 0., 0.
                    else:
                        obj.g1, obj.g2 = self.g1_field, self.g2_field
                elif self.config["shear_setting"]["shear_type"] == "catalog":
                    pass
                else:
                    chip_output.Log_error("Unknown shear input")
                    raise ValueError("Unknown shear input")

                # Get position of object on the focal plane
                pos_img, offset, local_wcs, real_wcs, fd_shear = obj.getPosImg_Offset_WCS(img=chip.img, fdmodel=self.fd_model, chip=chip, verbose=False, chip_wcs=chip_wcs, img_header=h_ext)

                # [TODO] For now, only consider objects which their centers (after field distortion) are projected within the focal plane
                # Otherwise they will be considered missed objects
                # if pos_img.x == -1 or pos_img.y == -1 or (not chip.isContainObj(x_image=pos_img.x, y_image=pos_img.y, margin=0.)):
                if pos_img.x == -1 or pos_img.y == -1:
                    chip_output.Log_info('obj_ra = %.6f, obj_dec = %.6f, obj_ra_orig = %.6f, obj_dec_orig = %.6f'%(obj.ra, obj.dec, obj.ra_orig, obj.dec_orig))
                    chip_output.Log_error("Objected missed: %s"%(obj.id))
                    missed_obj += 1
                    obj.unload_SED()
                    continue

                # Draw object & update output catalog
                try:
                    if self.config["run_option"]["out_cat_only"]:
                        isUpdated = True
                        obj.real_pos = obj.getRealPos(chip.img, global_x=obj.posImg.x, global_y=obj.posImg.y, img_real_wcs=obj.chip_wcs)
                        pos_shear = 0.
                    elif chip.survey_type == "photometric" and not self.config["run_option"]["out_cat_only"]:
                        isUpdated, pos_shear = obj.drawObj_multiband(
                            tel=self.tel,
                            pos_img=pos_img, 
                            psf_model=psf_model, 
                            bandpass_list=filt.bandpass_sub_list, 
                            filt=filt, 
                            chip=chip, 
                            g1=obj.g1, 
                            g2=obj.g2, 
                            exptime=pointing.exp_time,
                            fd_shear=fd_shear)

                    elif chip.survey_type == "spectroscopic" and not self.config["run_option"]["out_cat_only"]:
                        isUpdated, pos_shear = obj.drawObj_slitless(
                            tel=self.tel, 
                            pos_img=pos_img, 
                            psf_model=psf_model, 
                            bandpass_list=filt.bandpass_sub_list, 
                            filt=filt, 
                            chip=chip, 
                            g1=obj.g1, 
                            g2=obj.g2, 
                            exptime=pointing.exp_time,
                            normFilter=norm_filt,
                            fd_shear=fd_shear)

                    if isUpdated == 1 and self.config["run_option"]["out_psf"]:
                        obj.drawObj_PSF(
                            tel=self.tel,
                            pos_img=pos_img,
                            psf_model=psf_model,
                            bandpass_list=filt.bandpass_sub_list,
                            filt=filt,
                            chip=chip,
                            g1=obj.g1,
                            g2=obj.g2,
                            exptime=pointing.exp_time,
                            fd_shear=fd_shear,
                            chip_output=chip_output)

                    if isUpdated == 1:
                        # TODO: add up stats
                        chip_output.cat_add_obj(obj, pos_img, pos_shear)
                        pass
                    elif isUpdated == 0:
                        missed_obj += 1
                        chip_output.Log_error("Objected missed: %s"%(obj.id))
                    else:
                        chip_output.Log_error("Draw error, object omitted: %s"%(obj.id))
                        continue
                except Exception as e:
                    traceback.print_exc()
                    chip_output.Log_error(e)
                    
                # # [C6 TEST]
                # chip_output.Log_info("check running:1: pointing-{:} chip-{:} pid-{:} memory-{:6.2}GB".format(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024) ))
                # chip_output.Log_info('draw object %s'%obj.id)
                # chip_output.Log_info('mag = %.3f'%obj.param['mag_use_normal'])

                # Unload SED:
                obj.unload_SED()
                del obj
                gc.collect()

            del psf_model
            del self.cat
            gc.collect()

        chip_output.Log_info("check running:1: pointing-%d chip-%d pid-%d memory-%6.2fGB"%(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024) ))

        # Detector Effects
        # ===========================================================
        # whether to output zero, dark, flat calibration images.

        if not self.config["run_option"]["out_cat_only"]:
            chip.img = chip.addEffects(
                config=self.config, 
                img=chip.img, 
                chip_output=chip_output, 
                filt=filt,
                ra_cen=pointing.ra, 
                dec_cen=pointing.dec,
                img_rot=pointing.img_pa,
                exptime=pointing.exp_time,
                pointing_ID=pointing.id,
                timestamp_obs=pointing.timestamp,
                pointing_type=pointing.pointing_type,
                sky_map=sky_map, tel = self.tel,
                logger=chip_output.logger)
            
            if pointing.pointing_type == 'SCI':
                datetime_obs = datetime.utcfromtimestamp(pointing.timestamp)
                date_obs = datetime_obs.strftime("%y%m%d")
                time_obs = datetime_obs.strftime("%H%M%S")
                h_prim = generatePrimaryHeader(
                    xlen=chip.npix_x, 
                    ylen=chip.npix_y, 
                    pointNum = str(pointing.id),
                    ra=pointing.ra, 
                    dec=pointing.dec, 
                    pixel_scale=chip.pix_scale,
                    date=date_obs,
                    time_obs=time_obs,
                    exptime=pointing.exp_time,
                    im_type='SCI',
                    sat_pos=[pointing.sat_x, pointing.sat_y, pointing.sat_z],
                    sat_vel=[pointing.sat_vx, pointing.sat_vy, pointing.sat_vz],
                    project_cycle=self.config["project_cycle"],
                    run_counter=self.config["run_counter"],
                    chip_name=str(chip.chipID).rjust(2, '0'))
                h_ext = generateExtensionHeader(
                    chip=chip,
                    xlen=chip.npix_x,
                    ylen=chip.npix_y,
                    ra=pointing.ra,
                    dec=pointing.dec,
                    pa=pointing.img_pa.deg,
                    gain=chip.gain,
                    readout=chip.read_noise,
                    dark=chip.dark_noise,
                    saturation=90000,
                    pixel_scale=chip.pix_scale,
                    pixel_size=chip.pix_size,
                    xcen=chip.x_cen,
                    ycen=chip.y_cen,
                    extName='SCI',
                    timestamp=pointing.timestamp,
                    exptime=pointing.exp_time,
                    readoutTime=chip.readout_time)
                
                chip.img = galsim.Image(chip.img.array, dtype=np.uint16)
                hdu1 = fits.PrimaryHDU(header=h_prim)
                hdu1.add_checksum()
                hdu1.header.comments['CHECKSUM'] = 'HDU checksum'
                hdu1.header.comments['DATASUM'] = 'data unit checksum'
                hdu2 = fits.ImageHDU(chip.img.array, header=h_ext)
                hdu2.add_checksum()
                hdu2.header.comments['XTENSION'] = 'extension type'
                hdu2.header.comments['CHECKSUM'] = 'HDU checksum'
                hdu2.header.comments['DATASUM'] = 'data unit checksum'
                hdu1 = fits.HDUList([hdu1, hdu2])
                fname = os.path.join(chip_output.subdir, h_prim['FILENAME'] + '.fits')
                hdu1.writeto(fname, output_verify='ignore', overwrite=True)

                chip_output.Log_info("# objects that are too bright %d out of %d"%(bright_obj, self.nobj))
                chip_output.Log_info("# objects that are too dim %d out of %d"%(dim_obj, self.nobj))
                chip_output.Log_info("# objects that are missed %d out of %d"%(missed_obj, self.nobj))
        del chip.img

        chip_output.Log_info("check running:2: pointing-%d chip-%d pid-%d memory-%6.2fGB"%(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024) ))

    def run_one_chip_calibration(self, chip, filt, pointing, chip_output, skyback_level = 20000, sky_level_filt = 'g', wcs_fp=None, psf_model=None, cat_dir=None, sed_dir=None):




        # # Get WCS for the focal plane
        # if wcs_fp == None:
        # wcs_fp = self.focal_plane.getTanWCS(ra_cen, dec_cen, pointing.img_pa, chip.pix_scale)

        # Create chip Image
        chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
        chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
        # chip.img.wcs = wcs_fp
        pf_map = np.zeros_like(chip.img.array)
        if self.config["obs_setting"]["LED_TYPE"] is not None:
            if len(self.config["obs_setting"]["LED_TYPE"]) != 0:
                print("LED OPEN--------")

                led_obj = FlatLED(chip, filt)

                led_flat = led_obj.drawObj_LEDFlat(led_type_list=self.config["obs_setting"]["LED_TYPE"], exp_t_list=self.config["obs_setting"]["LED_TIME"])
                pf_map = led_flat
        # whether to output zero, dark, flat calibration images.
        expTime = self.config["obs_setting"]["exp_time"]
        norm_scaler = skyback_level/expTime / self.filter_param.param[sky_level_filt][5]

        if skyback_level == 0:
            self.config["ins_effects"]["shutter_effect"] = False

        if chip.survey_type == "photometric":
            sky_map = np.ones_like(chip.img.array) * norm_scaler * self.filter_param.param[chip.filter_type][5] / self.tel.pupil_area
        elif chip.survey_type == "spectroscopic":
            flat_normal = np.ones_like(chip.img.array)
            if self.config["ins_effects"]["flat_fielding"] == True:
                chip_output.Log_info("SLS flat preprocess,CHIP %d : Creating and applying Flat-Fielding" % chip.chipID)
                msg = str(chip.img.bounds)
                chip_output.Log_info(msg)
                flat_img = Effects.MakeFlatSmooth(
                    chip.img.bounds,
                    int(self.config["random_seeds"]["seed_flat"]))
                flat_normal = flat_normal * flat_img.array / np.mean(flat_img.array)
            if self.config["ins_effects"]["shutter_effect"] == True:
                chip_output.Log_info("SLS flat preprocess,CHIP %d : Apply shutter effect" % chip.chipID)
                shuttimg = Effects.ShutterEffectArr(chip.img, t_shutter=1.3, dist_bearing=735,
                                                    dt=1E-3)  # shutter effect normalized image for this chip
                flat_normal = flat_normal * shuttimg
                flat_normal = np.array(flat_normal, dtype='float32')
            sky_map = calculateSkyMap_split_g(
                skyMap=flat_normal,
                blueLimit=filt.blue_limit,
                redLimit=filt.red_limit,
                conf=chip.sls_conf,
                pixelSize=chip.pix_scale,
                isAlongY=0,
                flat_cube=chip.flat_cube)
            sky_map = sky_map * norm_scaler

        chip.img = chip.addEffects(
            config=self.config,
            img=chip.img,
            chip_output=chip_output,
            filt=filt,
            ra_cen=pointing.ra,
            dec_cen=pointing.dec,
            img_rot=pointing.img_pa,
            exptime=self.config["obs_setting"]["exp_time"],
            pointing_ID=pointing.id,
            timestamp_obs=pointing.timestamp,
            pointing_type=pointing.pointing_type,
            sky_map=sky_map, tel=self.tel,
            post_flash_map=pf_map,
            logger=chip_output.logger)

        datetime_obs = datetime.utcfromtimestamp(pointing.timestamp)
        date_obs = datetime_obs.strftime("%y%m%d")
        time_obs = datetime_obs.strftime("%H%M%S")
        h_prim = generatePrimaryHeader(
            xlen=chip.npix_x,
            ylen=chip.npix_y,
            pointNum=str(pointing.id),
            ra=pointing.ra,
            dec=pointing.dec,
            pixel_scale=chip.pix_scale,
            date=date_obs,
            time_obs=time_obs,
            exptime=self.config["obs_setting"]["exp_time"],
            im_type='DARKPF',
            sat_pos=[pointing.sat_x, pointing.sat_y, pointing.sat_z],
            sat_vel=[pointing.sat_vx, pointing.sat_vy, pointing.sat_vz],
            chip_name=str(chip.chipID).rjust(2, '0'))
        h_ext = generateExtensionHeader(
            chip=chip,
            xlen=chip.npix_x,
            ylen=chip.npix_y,
            ra=pointing.ra,
            dec=pointing.dec,
            pa=pointing.img_pa.deg,
            gain=chip.gain,
            readout=chip.read_noise,
            dark=chip.dark_noise,
            saturation=90000,
            pixel_scale=chip.pix_scale,
            pixel_size=chip.pix_size,
            xcen=chip.x_cen,
            ycen=chip.y_cen,
            extName='SCI',
            timestamp=pointing.timestamp,
            exptime=self.config["obs_setting"]["exp_time"],
            readoutTime=chip.readout_time)

        chip.img = galsim.Image(chip.img.array, dtype=np.uint16)
        hdu1 = fits.PrimaryHDU(header=h_prim)
        hdu1.add_checksum()
        hdu1.header.comments['CHECKSUM'] = 'HDU checksum'
        hdu1.header.comments['DATASUM'] = 'data unit checksum'
        hdu2 = fits.ImageHDU(chip.img.array, header=h_ext)
        hdu2.add_checksum()
        hdu2.header.comments['XTENSION'] = 'extension type'
        hdu2.header.comments['CHECKSUM'] = 'HDU checksum'
        hdu2.header.comments['DATASUM'] = 'data unit checksum'
        hdu1 = fits.HDUList([hdu1, hdu2])
        fname = os.path.join(chip_output.subdir, h_prim['FILENAME'] + '.fits')
        hdu1.writeto(fname, output_verify='ignore', overwrite=True)

            # chip_output.Log_info("# objects that are too bright %d out of %d" % (bright_obj, self.nobj))
            # chip_output.Log_info("# objects that are too dim %d out of %d" % (dim_obj, self.nobj))
            # chip_output.Log_info("# objects that are missed %d out of %d" % (missed_obj, self.nobj))
        del chip.img

        chip_output.Log_info("check running:2: pointing-%d chip-%d pid-%d memory-%6.2fGB" % (
        pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024)))

    def runExposure_MPI_PointingList(self, pointing_list,chips=None, use_mpi=False):
        if use_mpi:
            comm = MPI.COMM_WORLD
            ind_thread = comm.Get_rank()
            num_thread = comm.Get_size()

        if chips is None:
            nchips_per_fp = len(self.chip_list)
            run_chips = self.chip_list
            run_filts = self.filter_list
        else:
            # Only run a particular set of chips
            run_chips = []
            run_filts = []
            nchips_per_fp = len(chips)
            for ichip in range(len(self.chip_list)):
                chip = self.chip_list[ichip]
                filt = self.filter_list[ichip]
                if chip.chipID in chips:
                    run_chips.append(chip)
                    run_filts.append(filt)


        for ipoint in range(len(pointing_list)):
            for ichip in range(nchips_per_fp):
                i = ipoint*nchips_per_fp + ichip
                pointing = pointing_list[ipoint]
                pointing_ID = pointing.id
                if use_mpi:
                    if i % num_thread != ind_thread:
                        continue

                pid = os.getpid()

                sub_img_dir, prefix = makeSubDir_PointingList(path_dict=self.path_dict, config=self.config, pointing_ID=pointing_ID)

                chip = run_chips[ichip]
                filt = run_filts[ichip]
                # chip_output.Log_info("running pointing#%d, chip#%d, at PID#%d..."%(pointing_ID, chip.chipID, pid))
                chip_output = ChipOutput(
                    config=self.config, 
                    focal_plane=self.focal_plane, 
                    chip=chip, 
                    filt=filt,  
                    exptime=pointing.exp_time,
                    pointing_type=pointing.pointing_type,
                    pointing_ID=pointing_ID,  
                    subdir=sub_img_dir,
                    prefix=prefix)
                chip_output.Log_info("running pointing#%d, chip#%d, at PID#%d..."%(pointing_ID, chip.chipID, pid))
                if self.config["obs_setting"]["survey_type"] == "CALIBRATION":
                    self.run_one_chip_calibration(chip=chip,
                                               filt=filt,
                                               chip_output=chip_output,
                                               pointing=pointing,
                                               skyback_level = self.config["obs_setting"]["FLAT_LEVEL"],
                                               sky_level_filt = self.config["obs_setting"]["FLAT_LEVEL_FIL"])
                else:
                    self.run_one_chip(
                        chip=chip,
                        filt=filt,
                        chip_output=chip_output,
                        pointing=pointing)
                chip_output.Log_info("finished running chip#%d..."%(chip.chipID))
                for handler in chip_output.logger.handlers[:]:
                    chip_output.logger.removeHandler(handler)
                gc.collect()