ObservationSim.py

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

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.MockObject import calculateSkyMap_split_g
from ObservationSim.PSF import PSFGauss, FieldDistortion, PSFInterp
from ObservationSim._util import get_shear_field, makeSubDir_PointingList

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.Catalog = Catalog

        # if we want to apply field distortion?
        if self.config["ins_effects"]["field_dist"] == True:
            self.fd_model = FieldDistortion(fdModel_path=self.path_dict["fd_path"])
        else:
            self.fd_model = None

        # Construct chips & filters:
        nchips = self.focal_plane.nchip_x*self.focal_plane.nchip_y
        for i in range(nchips):
            chipID = i + 1
            if self.focal_plane.isIgnored(chipID=chipID):
                continue

            # 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, 
                ccd_bandpass=chip.effCurve)
            self.chip_list.append(chip)
            self.filter_list.append(filt)

        # Read catalog and shear(s)
        self.g1_field, self.g2_field, self.nshear = get_shear_field(config=self.config)

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

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

        if self.config["psf_setting"]["psf_model"] == "Gauss":
            psf_model = PSFGauss(chip=chip)
        elif self.config["psf_setting"]["psf_model"] == "Interp":
            psf_model = PSFInterp(chip=chip, PSF_data_file=self.path_dict["psf_dir"])
        else:
            print("unrecognized PSF model type!!", flush=True)

        # Get (extra) shear fields
        if shear_cat_file is not None:
            self.g1_field, self.g2_field, self.nshear = get_shear_field(config=self.config, shear_cat_file=shear_cat_file)

        # Get WCS for the focal plane
        if wcs_fp == None:
            wcs_fp = self.focal_plane.getTanWCS(pointing.ra, pointing.dec, 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 chip.survey_type == "photometric":
            sky_map = None
        # elif chip.survey_type == "spectroscopic":
        #     sky_map = calculateSkyMap_split_g(xLen=chip.npix_x, yLen=chip.npix_y, blueLimit=filt.blue_limit, redLimit=filt.red_limit, skyfn=self.path_dict["sky_file"], conf=chip.sls_conf, pixelSize=chip.pix_scale, isAlongY=0)
        elif chip.survey_type == "spectroscopic":
            flat_normal = np.ones_like(chip.img.array)
            if self.config["ins_effects"]["flat_fielding"] == True:
                print("SLS flat preprocess,CHIP %d : Creating and applying Flat-Fielding"%chip.chipID, flush=True)
                print(chip.img.bounds, flush=True)
                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:
                print("SLS flat preprocess,CHIP %d : Apply shutter effect"%chip.chipID, flush=True)
                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)
            del flat_normal

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

            # Loop over objects
            missed_obj = 0
            bright_obj = 0
            dim_obj = 0
            for j in range(self.nobj):
                # if j >= 10:
                #     break
                obj = self.cat.objs[j]
                if obj.type == 'star' and self.config["run_option"]["galaxy_only"]:
                    continue
                elif obj.type == 'galaxy' and self.config["run_option"]["star_only"]:
                    continue
                elif obj.type == 'quasar' and self.config["run_option"]["star_only"]:
                    continue

                # load SED
                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] = self.cat.convert_sed(
                        mag=obj.param["mag_use_normal"],
                        sed=sed_data,
                        target_filt=filt, 
                        norm_filt=norm_filt,
                    )
                except Exception as e:
                    print(e)
                    continue

                # Exclude very bright/dim objects (for now)
                if filt.is_too_bright(mag=obj.getMagFilter(filt)):
                    # print("obj too birght!!", flush=True)
                    if obj.type != 'galaxy':
                        bright_obj += 1
                        obj.unload_SED()
                        continue
                if filt.is_too_dim(mag=obj.getMagFilter(filt)):
                    # print("obj too dim!!", flush=True)
                    dim_obj += 1
                    obj.unload_SED()
                    # print(obj.getMagFilter(filt))
                    continue

                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"] == "extra":
                    try:
                        # TODO: every object with individual shear from input catalog(s)
                        obj.g1, obj.g2 = self.g1_field[j], self.g2_field[j]
                    except:
                        print("failed to load external shear.")
                        pass
                elif self.config["shear_setting"]["shear_type"] == "catalog":
                    pass
                else:
                    raise ValueError("Unknown shear input")

                pos_img, offset, local_wcs = obj.getPosImg_Offset_WCS(img=chip.img, fdmodel=self.fd_model, chip=chip, verbose=False)
                if pos_img.x == -1 or pos_img.y == -1:
                    # Exclude object which is outside the chip area (after field distortion)
                    # print("obj missed!!")
                    missed_obj += 1
                    obj.unload_SED()
                    continue

                # Draw object & update output catalog
                try:
                    if self.config["run_option"]["out_cat_only"]:
                        isUpdated = True
                    if 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
                            )
                    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,
                            )
                    if isUpdated:
                        # TODO: add up stats
                        # print("updating output catalog...")
                        chip_output.cat_add_obj(obj, pos_img, pos_shear)
                        pass
                    else:
                        # print("object omitted", flush=True)
                        continue
                except Exception as e:
                    print(e)
                    pass
                # Unload SED:
                obj.unload_SED()
                del obj

            del psf_model
            del self.cat

        print("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) ), flush=True)

        # Detector Effects
        # ===========================================================
        # whether to output zero, dark, flat calibration images.
        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,
            pointing_ID=pointing.id,
            timestamp_obs=pointing.timestamp,
            pointing_type=pointing.pointing_type,
            sky_map=sky_map, tel = self.tel)
        
        if pointing.pointing_type == 'MS':
            datetime_obs = datetime.fromtimestamp(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, 
                psize=chip.pix_scale, 
                row_num=chip.rowID, 
                col_num=chip.colID,
                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])
            h_ext = generateExtensionHeader(
                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, 
                psize=chip.pix_scale, 
                row_num=chip.rowID, 
                col_num=chip.colID,
                extName='raw')
            chip.img = galsim.Image(chip.img.array, dtype=np.uint16)
            hdu1 = fits.PrimaryHDU(header=h_prim)
            hdu2 = fits.ImageHDU(chip.img.array, header=h_ext)
            hdu1 = fits.HDUList([hdu1, hdu2])
            fname = os.path.join(chip_output.subdir, h_prim['FILENAME'] + '.fits')
            hdu1.writeto(fname, output_verify='ignore', overwrite=True)
            print("# objects that are too bright %d out of %d"%(bright_obj, self.nobj))
            print("# objects that are too dim %d out of %d"%(dim_obj, self.nobj))
            print("# objects that are missed %d out of %d"%(missed_obj, self.nobj))
        del chip.img

        print("check running:2: pointing-{:} chip-{:} pid-{:} memory-{:6.2}GB".format(pointing.id, chip.chipID, os.getpid(), (psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024 / 1024) ), flush=True)

    def runExposure_MPI_PointingList(self, pointing_list, shear_cat_file=None, 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]
                print("running pointing#%d, chip#%d, at PID#%d..."%(pointing_ID, chip.chipID, pid), flush=True)
                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)
                self.run_one_chip(
                    chip=chip, 
                    filt=filt, 
                    chip_output=chip_output, 
                    pointing=pointing,
                    cat_dir=self.path_dict["cat_dir"])
                print("finished running chip#%d..."%(chip.chipID), flush=True)