C6_50sqdeg.py 21.9 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
import os
import galsim
import random
import numpy as np
import h5py as h5
import healpy as hp
import astropy.constants as cons
import traceback
from astropy.coordinates import spherical_to_cartesian
from astropy.table import Table
from scipy import interpolate
from datetime import datetime

from ObservationSim.MockObject import CatalogBase, Star, Galaxy, Quasar
from ObservationSim.MockObject._util import tag_sed, getObservedSED, getABMAG, integrate_sed_bandpass, comoving_dist
from ObservationSim.Astrometry.Astrometry_util import on_orbit_obs_position

# (TEST)
from astropy.cosmology import FlatLambdaCDM
from astropy import constants
from astropy import units as U
from astropy.coordinates import SkyCoord
from astropy.io import fits

try:
    import importlib.resources as pkg_resources
except ImportError:
    # Try backported to PY<37 'importlib_resources'
    import importlib_resources as pkg_resources

NSIDE = 128

bundle_file_list = ['galaxies_C6_bundle000199.h5','galaxies_C6_bundle000200.h5','galaxies_C6_bundle000241.h5','galaxies_C6_bundle000242.h5','galaxies_C6_bundle000287.h5','galaxies_C6_bundle000288.h5','galaxies_C6_bundle000714.h5','galaxies_C6_bundle000715.h5','galaxies_C6_bundle000778.h5','galaxies_C6_bundle000779.h5','galaxies_C6_bundle000842.h5','galaxies_C6_bundle000843.h5','galaxies_C6_bundle002046.h5','galaxies_C6_bundle002110.h5','galaxies_C6_bundle002111.h5','galaxies_C6_bundle002173.h5','galaxies_C6_bundle002174.h5','galaxies_C6_bundle002238.h5','galaxies_C6_bundle002596.h5','galaxies_C6_bundle002597.h5','galaxies_C6_bundle002656.h5','galaxies_C6_bundle002657.h5','galaxies_C6_bundle002711.h5','galaxies_C6_bundle002712.h5','galaxies_C6_bundle002844.h5','galaxies_C6_bundle002845.h5','galaxies_C6_bundle002884.h5','galaxies_C6_bundle002885.h5','galaxies_C6_bundle002921.h5','galaxies_C6_bundle002922.h5']

qsosed_file_list = ['quickspeclib_interp1d_run1.fits','quickspeclib_interp1d_run2.fits','quickspeclib_interp1d_run3.fits','quickspeclib_interp1d_run4.fits','quickspeclib_interp1d_run5.fits','quickspeclib_interp1d_run6.fits','quickspeclib_interp1d_run7.fits','quickspeclib_interp1d_run8.fits','quickspeclib_interp1d_run9.fits','quickspeclib_interp1d_run10.fits','quickspeclib_interp1d_run11.fits','quickspeclib_interp1d_run12.fits','quickspeclib_interp1d_run13.fits','quickspeclib_interp1d_run14.fits','quickspeclib_interp1d_run15.fits','quickspeclib_interp1d_run16.fits','quickspeclib_interp1d_run17.fits','quickspeclib_interp1d_run18.fits','quickspeclib_interp1d_run19.fits','quickspeclib_interp1d_run20.fits','quickspeclib_interp1d_run21.fits','quickspeclib_interp1d_run22.fits','quickspeclib_interp1d_run23.fits','quickspeclib_interp1d_run24.fits','quickspeclib_interp1d_run25.fits','quickspeclib_interp1d_run26.fits','quickspeclib_interp1d_run27.fits','quickspeclib_interp1d_run28.fits','quickspeclib_interp1d_run29.fits','quickspeclib_interp1d_run30.fits']

star_file_list = ['C7_Gaia_Galaxia_RA170DECm23_healpix.hdf5', 'C7_Gaia_Galaxia_RA180DECp60_healpix.hdf5', 'C7_Gaia_Galaxia_RA240DECp30_healpix.hdf5', 'C7_Gaia_Galaxia_RA300DECm60_healpix.hdf5', 'C7_Gaia_Galaxia_RA30DECm48_healpix.hdf5']
star_center_list = [(170., -23.), (180., 60.), (240., 30.), (300., -60.), (30., -48.)]

def get_bundleIndex(healpixID_ring, bundleOrder=4, healpixOrder=7):
    assert NSIDE == 2**healpixOrder
    shift = healpixOrder - bundleOrder
    shift = 2*shift

    nside_bundle = 2**bundleOrder
    nside_healpix= 2**healpixOrder

    healpixID_nest= hp.ring2nest(nside_healpix, healpixID_ring)
    bundleID_nest = (healpixID_nest >> shift)
    bundleID_ring = hp.nest2ring(nside_bundle, bundleID_nest)

    return bundleID_ring

def get_agnsed_file(bundle_file_name):
    return qsosed_file_list[bundle_file_list.index(bundle_file_name)]

def get_star_cat(ra_pointing, dec_pointing):
    pointing_c = SkyCoord(ra=ra_pointing*U.deg, dec=dec_pointing*U.deg)
    max_dist = 10
    return_star_path = None
    for star_file, center in zip(star_file_list, star_center_list):
        center_c = SkyCoord(ra=center[0]*U.deg, dec=center[1]*U.deg)
        dist = pointing_c.separation(center_c).to(U.deg).value
        if dist < max_dist:
            return_star_path = star_file
            max_dist = dist
    return return_star_path

class Catalog(CatalogBase):
    def __init__(self, config, chip, pointing, chip_output, filt, **kwargs):
        super().__init__()
        self.cat_dir = os.path.join(config["data_dir"], config["catalog_options"]["input_path"]["cat_dir"])
        self.seed_Av = config["catalog_options"]["seed_Av"]

        self.cosmo = FlatLambdaCDM(H0=67.66, Om0=0.3111)

        self.chip_output = chip_output
        self.filt = filt
        self.logger = chip_output.logger

        with pkg_resources.path('Catalog.data', 'SLOAN_SDSS.g.fits') as filter_path:
            self.normF_star = Table.read(str(filter_path))
        
        self.config = config
        self.chip = chip
        self.pointing = pointing

        self.max_size = 0.

        if "star_cat" in config["catalog_options"]["input_path"] and config["catalog_options"]["input_path"]["star_cat"] and not config["catalog_options"]["galaxy_only"]:
            # Get the cloest star catalog file
            star_file_name = get_star_cat(ra_pointing=self.pointing.ra, dec_pointing=self.pointing.dec)
            star_path = os.path.join(config["catalog_options"]["input_path"]["star_cat"], star_file_name)
            star_SED_file = config["catalog_options"]["SED_templates_path"]["star_SED"]
            self.star_path = os.path.join(self.cat_dir, star_path)
            self.star_SED_path = os.path.join(config["data_dir"], star_SED_file)
            self._load_SED_lib_star()
        
        if "galaxy_cat" in config["catalog_options"]["input_path"] and config["catalog_options"]["input_path"]["galaxy_cat"] and not config["catalog_options"]["star_only"]:
            galaxy_dir = config["catalog_options"]["input_path"]["galaxy_cat"]
            self.galaxy_path = os.path.join(self.cat_dir, galaxy_dir)
            self.galaxy_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["galaxy_SED"])
            self._load_SED_lib_gals()
            self.agn_seds = {}

        if "AGN_SED" in config["catalog_options"]["SED_templates_path"] and not config["catalog_options"]["star_only"]:
            self.AGN_SED_path = os.path.join(config["data_dir"], config["catalog_options"]["SED_templates_path"]["AGN_SED"])

        if "rotateEll" in config["catalog_options"]:
110
            self.rotation = np.radians(float(config["catalog_options"]["rotateEll"]))
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
        else:
            self.rotation = 0.

        # Update output .cat header with catalog specific output columns
        self._add_output_columns_header()

        self._get_healpix_list()
        self._load()
    
    def _add_output_columns_header(self):
        self.add_hdr = " model_tag teff logg feh"
        self.add_hdr += " bulgemass diskmass detA e1 e2 kappa g1 g2 size galType veldisp "

        self.add_fmt = " %10s %8.4f %8.4f %8.4f"
        self.add_fmt += " %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %8.4f %4d %8.4f "
        self.chip_output.update_ouptut_header(additional_column_names=self.add_hdr)

    def _get_healpix_list(self):
        self.sky_coverage = self.chip.getSkyCoverageEnlarged(self.chip.img.wcs, margin=0.2)
        ra_min, ra_max, dec_min, dec_max = self.sky_coverage.xmin, self.sky_coverage.xmax, self.sky_coverage.ymin, self.sky_coverage.ymax
        ra = np.deg2rad(np.array([ra_min, ra_max, ra_max, ra_min]))
        dec = np.deg2rad(np.array([dec_max, dec_max, dec_min, dec_min]))
        self.pix_list = hp.query_polygon(
            NSIDE,
            hp.ang2vec(np.radians(90.) - dec, ra),
            inclusive=True
        )
        if self.logger is not None:
            msg = str(("HEALPix List: ", self.pix_list))
            self.logger.info(msg)
        else:
            print("HEALPix List: ", self.pix_list)

    def load_norm_filt(self, obj):
        if obj.type == "star":
            return self.normF_star
        elif obj.type == "galaxy" or obj.type == "quasar":
            # return self.normF_galaxy
            return None
        else:
            return None

    def _load_SED_lib_star(self):
        self.tempSED_star = h5.File(self.star_SED_path,'r')

    def _load_SED_lib_gals(self):
        pcs = h5.File(os.path.join(self.galaxy_SED_path, "pcs.h5"), "r")
        lamb = h5.File(os.path.join(self.galaxy_SED_path, "lamb.h5"), "r")
        self.lamb_gal = lamb['lamb'][()]
        self.pcs = pcs['pcs'][()]

    def _load_gals(self, gals, pix_id=None, cat_id=0, agnsed_file=""):
        ngals = len(gals['ra'])

        # Apply astrometric modeling
        ra_arr = gals['ra'][:]
        dec_arr = gals['dec'][:]
        if self.config["obs_setting"]["enable_astrometric_model"]:
            ra_list = ra_arr.tolist()
            dec_list = dec_arr.tolist()
            pmra_list = np.zeros(ngals).tolist()
            pmdec_list = np.zeros(ngals).tolist()
            rv_list = np.zeros(ngals).tolist()
            parallax_list = [1e-9] * ngals
            dt = datetime.utcfromtimestamp(self.pointing.timestamp)
            date_str = dt.date().isoformat()
            time_str = dt.time().isoformat()
            ra_arr, dec_arr = on_orbit_obs_position(
                input_ra_list=ra_list,
                input_dec_list=dec_list,
                input_pmra_list=pmra_list,
                input_pmdec_list=pmdec_list,
                input_rv_list=rv_list,
                input_parallax_list=parallax_list,
                input_nstars=ngals,
                input_x=self.pointing.sat_x,
                input_y=self.pointing.sat_y,
                input_z=self.pointing.sat_z,
                input_vx=self.pointing.sat_vx,
                input_vy=self.pointing.sat_vy,
                input_vz=self.pointing.sat_vz,
                input_epoch="J2000",
                input_date_str=date_str,
                input_time_str=time_str
            )

        for igals in range(ngals):
            # # (TEST)
            # if igals > 100:
            #     break
            
            param = self.initialize_param()
            param['ra'] = ra_arr[igals]
            param['dec'] = dec_arr[igals]
            param['ra_orig'] = gals['ra'][igals]
            param['dec_orig'] = gals['dec'][igals]
            # param['mag_use_normal'] = gals['mag_csst_%s'%(self.filt.filter_type)][igals]
            if self.filt.filter_type == 'NUV':
                param['mag_use_normal'] = gals['mag_csst_nuv'][igals]
            else:
                param['mag_use_normal'] = gals['mag_csst_%s'%(self.filt.filter_type)][igals]
            if self.filt.is_too_dim(mag=param['mag_use_normal'], margin=self.config["obs_setting"]["mag_lim_margin"]):
                continue

            param['z'] = gals['redshift'][igals]
            param['model_tag'] = 'None'
            param['g1'] = gals['shear'][igals][0]
            param['g2'] = gals['shear'][igals][1]
            param['kappa'] = gals['kappa'][igals]
            param['e1'] = gals['ellipticity_true'][igals][0]
            param['e2'] = gals['ellipticity_true'][igals][1]
            
            # For shape calculation
224
225
226
227
228
229
            param['e1'], param['e2'], param['ell_total'] = self.rotate_ellipticity(
                                                                    e1=gals['ellipticity_true'][igals][0],
                                                                    e2=gals['ellipticity_true'][igals][1],
                                                                    rotation=self.rotation,
                                                                    unit='radians')
            # param['ell_total'] = np.sqrt(param['e1']**2 + param['e2']**2)
230
231
            if param['ell_total'] > 0.9:
                continue
232
233
234
            # phi_e = cmath.phase(complex(param['e1'], param['e2']))
            # param['e1'] = param['ell_total'] * np.cos(phi_e + 2*self.rotation)
            # param['e2'] = param['ell_total'] * np.sin(phi_e + 2*self.rotation)
235
            
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
            param['e1_disk'] = param['e1']
            param['e2_disk'] = param['e2']
            param['e1_bulge'] = param['e1']
            param['e2_bulge'] = param['e2']


            param['delta_ra'] = 0
            param['delta_dec'] = 0

            # Masses
            param['bulgemass'] = gals['bulgemass'][igals]
            param['diskmass'] = gals['diskmass'][igals]

            param['size'] = gals['size'][igals]
            if param['size'] > self.max_size:
                self.max_size = param['size']

            # Sersic index
            param['disk_sersic_idx'] = 1.
            param['bulge_sersic_idx'] = 4.

            # Sizes
            param['bfrac'] = param['bulgemass']/(param['bulgemass'] + param['diskmass'])
            if param['bfrac'] >= 0.6:
                param['hlr_bulge'] = param['size']
                param['hlr_disk'] = param['size'] * (1. - param['bfrac'])
            else:
                param['hlr_disk'] = param['size']
                param['hlr_bulge'] = param['size'] * param['bfrac']

            # SED coefficients
            param['coeff'] = gals['coeff'][igals]
            param['detA'] = gals['detA'][igals]

            # Others
            param['galType'] = gals['type'][igals]
            param['veldisp'] = gals['veldisp'][igals]
            
            # TEST no redening and no extinction
            param['av'] = 0.0
            param['redden'] = 0

            # Is this an Quasar?
            param['qsoindex'] = gals['qsoindex'][igals]
            if param['qsoindex'] == -1:
                param['star'] = 0   # Galaxy
                param['agnsed_file'] = ""
            else:
                param['star'] = 2   # Quasar
                param['agnsed_file'] = agnsed_file

            # NOTE: this cut cannot be put before the SED type has been assigned
            if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
                continue

            # TEMP
            self.ids += 1
            param['id'] = '%06d'%(int(pix_id)) + '%06d'%(cat_id) + '%08d'%(igals)
            
            if param['star'] == 0:
296
                obj = Galaxy(param, logger=self.logger)
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
            elif param['star'] == 2:
                obj = Quasar(param, logger=self.logger)
            
            # Need to deal with additional output columns
            obj.additional_output_str = self.add_fmt%("n", 0., 0., 0.,
                                                    param['bulgemass'], param['diskmass'], param['detA'],
                                                    param['e1'], param['e2'], param['kappa'], param['g1'], param['g2'], param['size'],
                                                    param['galType'], param['veldisp'])
            
            self.objs.append(obj)

    def _load_stars(self, stars, pix_id=None):
        nstars = len(stars['sourceID'])
        # Apply astrometric modeling
        ra_arr = stars["RA"][:]
        dec_arr = stars["Dec"][:]
        pmra_arr = stars['pmra'][:]
        pmdec_arr = stars['pmdec'][:]
        rv_arr = stars['RV'][:]
        parallax_arr = stars['parallax'][:]
        if self.config["obs_setting"]["enable_astrometric_model"]:
            ra_list = ra_arr.tolist()
            dec_list = dec_arr.tolist()
            pmra_list = pmra_arr.tolist()
            pmdec_list = pmdec_arr.tolist()
            rv_list = rv_arr.tolist()
            parallax_list = parallax_arr.tolist()
            dt = datetime.utcfromtimestamp(self.pointing.timestamp)
            date_str = dt.date().isoformat()
            time_str = dt.time().isoformat()
            ra_arr, dec_arr = on_orbit_obs_position(
                input_ra_list=ra_list,
                input_dec_list=dec_list,
                input_pmra_list=pmra_list,
                input_pmdec_list=pmdec_list,
                input_rv_list=rv_list,
                input_parallax_list=parallax_list,
                input_nstars=nstars,
                input_x=self.pointing.sat_x,
                input_y=self.pointing.sat_y,
                input_z=self.pointing.sat_z,
                input_vx=self.pointing.sat_vx,
                input_vy=self.pointing.sat_vy,
                input_vz=self.pointing.sat_vz,
                input_epoch="J2000",
                input_date_str=date_str,
                input_time_str=time_str
            )
        for istars in range(nstars):
Fang Yuedong's avatar
Fang Yuedong committed
346
347
348
            # (TEST)
            if istars > 100:
                break
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470

            param = self.initialize_param()
            param['ra'] = ra_arr[istars]
            param['dec'] = dec_arr[istars]
            param['ra_orig'] = stars["RA"][istars]
            param['dec_orig'] = stars["Dec"][istars]
            param['pmra'] = pmra_arr[istars]
            param['pmdec'] = pmdec_arr[istars]
            param['rv'] = rv_arr[istars]
            param['parallax'] = parallax_arr[istars]
            if not self.chip.isContainObj(ra_obj=param['ra'], dec_obj=param['dec'], margin=200):
                continue
            param['mag_use_normal'] = stars['app_sdss_g'][istars]
            self.ids += 1
            param['id'] = stars['sourceID'][istars]
            param['sed_type'] = stars['sourceID'][istars]
            param['model_tag'] = stars['model_tag'][istars]
            param['teff'] = stars['teff'][istars]
            param['logg'] = stars['grav'][istars]
            param['feh'] = stars['feh'][istars]
            param['z'] = 0.0
            param['star'] = 1   # Star
            obj = Star(param, logger=self.logger)

            # Append additional output columns to the .cat file
            obj.additional_output_str = self.add_fmt%(param["model_tag"], param['teff'], param['logg'], param['feh'],
                                                    0., 0., 0., 0., 0., 0., 0., 0., 0., -1, 0.)

            self.objs.append(obj)

    def _load(self, **kwargs):
        self.objs = []
        self.ids = 0
        
        if "star_cat" in self.config["catalog_options"]["input_path"] and self.config["catalog_options"]["input_path"]["star_cat"] and not self.config["catalog_options"]["galaxy_only"]:
            star_cat = h5.File(self.star_path, 'r')['catalog']
            for pix in self.pix_list:
                try:
                    stars = star_cat[str(pix)]
                    self._load_stars(stars, pix_id=pix)
                    del stars
                except Exception as e:
                    self.logger.error(str(e))
                    print(e)
        
        if "galaxy_cat" in self.config["catalog_options"]["input_path"] and self.config["catalog_options"]["input_path"]["galaxy_cat"] and not self.config["catalog_options"]["star_only"]:
            for pix in self.pix_list:
                try:
                    bundleID  = get_bundleIndex(pix)
                    bundle_file = "galaxies_C6_bundle{:06}.h5".format(bundleID)
                    file_path = os.path.join(self.galaxy_path, bundle_file)
                    gals_cat = h5.File(file_path, 'r')['galaxies']
                    gals = gals_cat[str(pix)]

                    # Get corresponding AGN SED file
                    agnsed_file = get_agnsed_file(bundle_file)
                    agnsed_path = os.path.join(self.AGN_SED_path, agnsed_file)
                    self.agn_seds[agnsed_file] = fits.open(agnsed_path)[0].data

                    self._load_gals(gals, pix_id=pix, cat_id=bundleID, agnsed_file=agnsed_file)

                    del gals
                except Exception as e:
                    traceback.print_exc()
                    self.logger.error(str(e))
                    print(e)

        if self.logger is not None:
            self.logger.info("maximum galaxy size: %.4f"%(self.max_size))
            self.logger.info("number of objects in catalog: %d"%(len(self.objs)))
        else:
            print("number of objects in catalog: ", len(self.objs))

    def load_sed(self, obj, **kwargs):
        if obj.type == 'star':
            _, wave, flux = tag_sed(
                h5file=self.tempSED_star,
                model_tag=obj.param['model_tag'],
                teff=obj.param['teff'],
                logg=obj.param['logg'],
                feh=obj.param['feh']
            )
        elif obj.type == 'galaxy' or obj.type == 'quasar':
            factor = 10**(-.4 * self.cosmo.distmod(obj.z).value)
            if obj.type == 'galaxy':
                flux = np.matmul(self.pcs, obj.coeff) * factor
                #  if np.any(flux < 0):
                #     raise ValueError("Glaxy %s: negative SED fluxes"%obj.id)
                flux[flux < 0] = 0.
                sedcat = np.vstack((self.lamb_gal, flux)).T
                sed_data = getObservedSED(
                    sedCat=sedcat,
                    redshift=obj.z,
                    av=obj.param["av"],
                    redden=obj.param["redden"]
                )
                wave, flux = sed_data[0], sed_data[1]
            elif obj.type == 'quasar':
                flux = self.agn_seds[obj.agnsed_file][int(obj.qsoindex)] * 1e-17
                flux[flux < 0] = 0.
                wave = self.lamb_gal
        else:
            raise ValueError("Object type not known")
        speci = interpolate.interp1d(wave, flux)
        lamb = np.arange(2000, 11001+0.5, 0.5)
        y = speci(lamb)
        # erg/s/cm2/A --> photon/s/m2/A
        all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
        sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))
        
        if obj.type == 'quasar':
            # integrate to get the magnitudes
            sed_photon = np.array([sed['WAVELENGTH'], sed['FLUX']]).T
            sed_photon = galsim.LookupTable(x=np.array(sed_photon[:, 0]), f=np.array(sed_photon[:, 1]), interpolant='nearest')
            sed_photon = galsim.SED(sed_photon, wave_type='A', flux_type='1', fast=False)
            interFlux = integrate_sed_bandpass(sed=sed_photon, bandpass=self.filt.bandpass_full)
            obj.param['mag_use_normal'] = getABMAG(interFlux, self.filt.bandpass_full)
            # mag = getABMAG(interFlux, self.filt.bandpass_full)
            # print("mag diff = %.3f"%(mag - obj.param['mag_use_normal']))
        del wave
        del flux
        return sed