Galaxy.py 20.5 KB
Newer Older
Fang Yuedong's avatar
Fang Yuedong committed
1
2
3
4
5
import numpy as np
import galsim
import os, sys
import astropy.constants as cons
from astropy.table import Table
Zhang Xin's avatar
Zhang Xin committed
6
from ._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG,convolveGaussXorders
Fang Yuedong's avatar
Fang Yuedong committed
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
from .SpecDisperser import SpecDisperser
from .MockObject import MockObject
from scipy import interpolate

class Galaxy(MockObject):
    def __init__(self, param, rotation=None):
        super().__init__(param)
        self.thetaR = self.param["theta"]
        self.bfrac = self.param["bfrac"]
        self.hlr_disk = self.param["hlr_disk"]
        self.hlr_bulge = self.param["hlr_bulge"]

        # Extract ellipticity components
        self.e_disk = galsim.Shear(g=self.param["ell_disk"], beta=self.thetaR*galsim.degrees)
        self.e_bulge = galsim.Shear(g=self.param["ell_bulge"], beta=self.thetaR*galsim.degrees)
        self.e_total = galsim.Shear(g=self.param["ell_tot"], beta=self.thetaR*galsim.degrees)
        self.e1_disk, self.e2_disk = self.e_disk.g1, self.e_disk.g2
        self.e1_bulge, self.e2_bulge = self.e_bulge.g1, self.e_bulge.g2
        self.e1_total, self.e2_total = self.e_total.g1, self.e_total.g2

        if rotation is not None:
            self.rotateEllipticity(rotation)

Fang Yuedong's avatar
Fang Yuedong committed
30
    def load_SED(self, survey_type, sed_path=None, cosids=None, objtypes=None, sed_templates=None, normFilter=None, target_filt=None):
Fang Yuedong's avatar
Fang Yuedong committed
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
110
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
224
225
226
227
228
229
230
231
232
233
234
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
        if survey_type == "photometric":
            norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
            if sed_templates is None:
                # Read SED data directly
                itype = objtypes[cosids==self.sed_type][0]
                sed_file = os.path.join(sed_path, itype + "_ID%s.sed"%(self.sed_type))
                if not os.path.exists(sed_file):
                    raise ValueError("!!! No SED found.")
                sed_data = Table.read(sed_file, format="ascii")
                wave, flux = sed_data["observedLambda"].data, sed_data["observedFlux"].data
            else:
                # Load SED from templates
                sed_data = sed_templates[self.sed_type]
                # redshift, intrinsic extinction
                sed_data = getObservedSED(
                    sedCat=sed_data, 
                    redshift=self.z, 
                    av=self.param['av'], 
                    redden=self.param['redden'])
                wave, flux = sed_data[0], sed_data[1] 
            flux_photon = flux * (wave / (cons.h.value * cons.c.value)) * 1e-13
            sed_photon = Table(np.array([wave, flux_photon]).T, names=('WAVELENGTH', 'FLUX'))
            # Get scaling factor for SED
            sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'],
                spectrum=sed_photon,
                norm_thr=normFilter,
                sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
                eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
            sed_photon = np.array([sed_photon['WAVELENGTH'], sed_photon['FLUX']*sedNormFactor]).T
            # Convert to galsim.SED object
            spec = galsim.LookupTable(x=np.array(sed_photon[:, 0]), f=np.array(sed_photon[:, 1]), interpolant='nearest')
            self.sed = galsim.SED(spec, wave_type='A', flux_type='1', fast=False)
            # Get magnitude
            interFlux = integrate_sed_bandpass(sed=self.sed, bandpass=target_filt.bandpass_full)
            self.param['mag_%s'%target_filt.filter_type] = getABMAG(
                interFlux=interFlux, 
                bandpass=target_filt.bandpass_full)
            # print('mag_use_normal = ', self.param['mag_use_normal'])
            # print('mag_%s = '%target_filt.filter_type, self.param['mag_%s'%target_filt.filter_type])
            # print('redshift = %.3f'%(self.z))
            # print('sed_type = %d, av = %.2f, redden = %d'%(self.sed_type, self.param['av'], self.param['redden']))

        elif survey_type == "spectroscopic":
            if sed_templates is None:
                self.sedPhotons(sed_path=sed_path, cosids=cosids, objtypes=objtypes)
            else:
                sed_data = sed_templates[self.sed_type]
                sed_data = getObservedSED(
                    sedCat=sed_data, 
                    redshift=self.z, 
                    av=self.param['av'], 
                    redden=self.param['redden'])
                speci = interpolate.interp1d(sed_data[0], sed_data[1])
                lamb = np.arange(2500, 10001 + 0.5, 0.5)
                y = speci(lamb)
                # erg/s/cm2/A --> photo/s/m2/A
                all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
                self.sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))


    def unload_SED(self):
        """(Test) free up SED memory
        """
        del self.sed

    def sedPhotons(self, sed_path, cosids, objtypes):

        itype = objtypes[cosids == self.sed_type][0]
        sed_file = os.path.join(sed_path, itype + "_ID%s.sed" % (self.sed_type))
        if not os.path.exists(sed_file):
            raise ValueError("!!! No SED found.")
        sed = Table.read(sed_file, format="ascii")
        spec_data = {}
        f_orig = sed["observedFlux"].data
        w_orig = sed["observedLambda"].data

        speci = interpolate.interp1d(w_orig, f_orig)
        lamb = np.arange(2500, 10001 + 0.5, 0.5)
        y = speci(lamb)
        # erg/s/cm2/A --> photo/s/m2/A
        all_sed = y * lamb / (cons.h.value * cons.c.value) * 1e-13
        self.sed = Table(np.array([lamb, all_sed]).T, names=('WAVELENGTH', 'FLUX'))

    def getGSObj_multiband(self, tel, psf_list, bandpass_list, filt, nphotons_tot=None, g1=0, g2=0, exptime=150.):
        if len(psf_list) != len(bandpass_list):
            raise ValueError("!!!The number of PSF profiles and the number of bandpasses must be equal.")
        objs = []
        if nphotons_tot == None:
            nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
        # print("nphotons_tot = ", nphotons_tot)

        try:
            full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
        except Exception as e:
            print(e)
            return -1
        for i in range(len(bandpass_list)):
            bandpass = bandpass_list[i]
            try:
                sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
            except Exception as e:
                print(e)
                return -1
            
            ratio = sub/full
            if not (ratio == -1 or (ratio != ratio)):
                nphotons = ratio * nphotons_tot
            else:
                return -1

            psf = psf_list[i]
            disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0)
            disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
            disk = disk.shear(disk_shape)
            bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0)
            bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
            bulge = bulge.shear(bulge_shape)

            gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
            gal = gal.withFlux(nphotons)
            gal_shear = galsim.Shear(g1=g1, g2=g2)
            gal = gal.shear(gal_shear)
            gal = galsim.Convolve(psf, gal)
            objs.append(gal)
        final = galsim.Sum(objs)
        return final

    def drawObj_multiband(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, exptime=150.):
        if nphotons_tot == None:
            nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
        # print("nphotons_tot = ", nphotons_tot)

        try:
            full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full)
        except Exception as e:
            print(e)
            return False

        nphotons_sum = 0
        photons_list = []
        xmax, ymax = 0, 0

        # print('hlr_disk = %.4f, hlr_bulge = %.4f'%(self.hlr_disk, self.hlr_bulge))
        big_galaxy = False
        if self.hlr_disk > 3.0: # Very big galaxy
            big_galaxy = True

        # (TEST) Galsim Parameters
        if self.getMagFilter(filt) <= 15 and (not big_galaxy):
            folding_threshold = 5.e-4
        else:
            folding_threshold = 5.e-3
        gsp = galsim.GSParams(folding_threshold=folding_threshold)

        for i in range(len(bandpass_list)):
            bandpass = bandpass_list[i]

            try:
                sub = integrate_sed_bandpass(sed=self.sed, bandpass=bandpass)
            except Exception as e:
                print(e)
                # return False
                continue
            
            ratio = sub/full
            if not (ratio == -1 or (ratio != ratio)):
                nphotons = ratio * nphotons_tot
            else:
                # return False
                continue
            nphotons_sum += nphotons
            # print("nphotons_sub-band_%d = %.2f"%(i, nphotons))

            psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
            disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
            disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
            disk = disk.shear(disk_shape)
            bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
            bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
            bulge = bulge.shear(bulge_shape)

            gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
            gal = gal.withFlux(nphotons)
            gal_shear = galsim.Shear(g1=g1, g2=g2)
            gal = gal.shear(gal_shear)

            if self.hlr_disk < 10.0: # Not apply PSF for very big galaxy
                gal = galsim.Convolve(psf, gal)

            # Use (explicit) stamps to draw
            stamp = gal.drawImage(wcs=self.localWCS, method='phot', offset=self.offset, save_photons=True)
            xmax = max(xmax, stamp.xmax)
            ymax = max(ymax, stamp.ymax)
            photons = stamp.photons
            photons.x += self.x_nominal
            photons.y += self.y_nominal
            photons_list.append(photons)

        # print('xmax = %d, ymax = %d '%(xmax, ymax))

        stamp = galsim.ImageF(int(xmax*1.1), int(ymax*1.1))
        stamp.wcs = self.localWCS
        stamp.setCenter(self.x_nominal, self.y_nominal)
        bounds = stamp.bounds & chip.img.bounds
        stamp[bounds] = chip.img[bounds]

        if not big_galaxy:
            for i in range(len(photons_list)):
                if i == 0:
                    chip.sensor.accumulate(photons_list[i], stamp)
                else:
                    chip.sensor.accumulate(photons_list[i], stamp, resume=True)
        else:
            sensor = galsim.Sensor()
            for i in range(len(photons_list)):
                if i == 0:
                    sensor.accumulate(photons_list[i], stamp)
                else:
                    sensor.accumulate(photons_list[i], stamp, resume=True)

        # print(stamp.array.sum())
        # chip.img[bounds] += stamp[bounds]
        chip.img[bounds] = stamp[bounds]
        # print("nphotons_sum = ", nphotons_sum)
        del photons_list
        del stamp
        return True, pos_shear

    def drawObj_slitless(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
Xin Zhang's avatar
Xin Zhang committed
260
                         exptime=150., normFilter=None, grating_split_pos=3685):
Fang Yuedong's avatar
Fang Yuedong committed
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281

        norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
        sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
                                                      norm_thr=normFilter,
                                                      sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]),
                                                      eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
        if sedNormFactor == 0:
            return False
        normalSED = Table(np.array([self.sed['WAVELENGTH'], self.sed['FLUX'] * sedNormFactor]).T,
                          names=('WAVELENGTH', 'FLUX'))

        big_galaxy = False
        if self.hlr_disk > 3.0: # Very big galaxy
            big_galaxy = True

        if self.getMagFilter(filt) <= 15 and (not big_galaxy):
            folding_threshold = 5.e-4
        else:
            folding_threshold = 5.e-3
        gsp = galsim.GSParams(folding_threshold=folding_threshold)
        # nphotons_sum = 0
Zhang Xin's avatar
Zhang Xin committed
282
        xOrderSigPlus = {'A':1.3909419820029296,'B':1.4760376591236062,'C':4.035447379743442,'D':5.5684364343742825,'E':16.260021029735388}
Xin Zhang's avatar
Xin Zhang committed
283
        grating_split_pos_chip = chip.bound.xmin + grating_split_pos
Fang Yuedong's avatar
Fang Yuedong committed
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
        for i in range(len(bandpass_list)):
            bandpass = bandpass_list[i]

            psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, folding_threshold=folding_threshold)
            disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0, gsparams=gsp)
            disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
            disk = disk.shear(disk_shape)
            bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0, gsparams=gsp)
            bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
            bulge = bulge.shear(bulge_shape)

            gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
            gal = gal.withFlux(tel.pupil_area * exptime)
            gal_shear = galsim.Shear(g1=g1, g2=g2)
            gal = gal.shear(gal_shear)
            gal = galsim.Convolve(psf, gal)

            starImg = gal.drawImage(wcs=self.localWCS)

            origin_star = [self.y_nominal - (starImg.center.y - starImg.ymin),
                           self.x_nominal - (starImg.center.x - starImg.xmin)]

Xin Zhang's avatar
Xin Zhang committed
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
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
            gal_origin = [origin_star[0], origin_star[1]]
            gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1]

            if gal_origin[1] < grating_split_pos_chip < gal_end[1]:
                subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1)
                ## part img disperse

                subImg_p1 = starImg.array[:, 0:subSlitPos]
                star_p1 = galsim.Image(subImg_p1)
                origin_p1 = origin_star
                xcenter_p1 = min(self.x_nominal,grating_split_pos_chip-1) - chip.bound.xmin
                ycenter_p1 = self.y_nominal-chip.bound.ymin

                sdp_p1 = SpecDisperser(orig_img=star_p1, xcenter=xcenter_p1,
                                    ycenter=ycenter_p1, origin=origin_p1,
                                    tar_spec=normalSED,
                                    band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
                                    conf=chip.sls_conf[0],
                                    isAlongY=0)

                self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus = xOrderSigPlus)

                subImg_p2 = starImg.array[:, subSlitPos+1:starImg.array.shape[1]]
                star_p2 = galsim.Image(subImg_p2)
                origin_p2 = [origin_star[0], grating_split_pos_chip]
                xcenter_p2 = max(self.x_nominal, grating_split_pos_chip - 1) - chip.bound.xmin
                ycenter_p2 = self.y_nominal - chip.bound.ymin

                sdp_p2 = SpecDisperser(orig_img=star_p2, xcenter=xcenter_p2,
                                       ycenter=ycenter_p2, origin=origin_p2,
                                       tar_spec=normalSED,
                                       band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
                                       conf=chip.sls_conf[1],
                                       isAlongY=0)

                self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus = xOrderSigPlus)

                del sdp_p1
                del sdp_p2
            elif grating_split_pos_chip<=gal_origin[1]:
                sdp = SpecDisperser(orig_img=starImg, xcenter=self.x_nominal - chip.bound.xmin,
                                    ycenter=self.y_nominal - chip.bound.ymin, origin=origin_star,
                                    tar_spec=normalSED,
                                    band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
                                    conf=chip.sls_conf[1],
                                    isAlongY=0)
                self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus)
                del sdp
            elif grating_split_pos_chip>=gal_end[1]:
                sdp = SpecDisperser(orig_img=starImg, xcenter=self.x_nominal - chip.bound.xmin,
                                    ycenter=self.y_nominal - chip.bound.ymin, origin=origin_star,
                                    tar_spec=normalSED,
                                    band_start=bandpass.blue_limit * 10, band_end=bandpass.red_limit * 10,
                                    conf=chip.sls_conf[0],
                                    isAlongY=0)
                self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus = xOrderSigPlus)
                del sdp
Fang Yuedong's avatar
Fang Yuedong committed
363

Xin Zhang's avatar
Xin Zhang committed
364
            # print(self.y_nominal, starImg.center.y, starImg.ymin)
Fang Yuedong's avatar
Fang Yuedong committed
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
            del psf
        return True, pos_shear

    def getGSObj(self, psf, g1=0, g2=0, flux=None, filt=None, tel=None, exptime=150.):
        if flux == None:
            flux = self.getElectronFluxFilt(filt, tel, exptime)
        disk = galsim.Sersic(n=1.0, half_light_radius=self.hlr_disk, flux=1.0)
        disk_shape = galsim.Shear(g1=self.e1_disk, g2=self.e2_disk)
        disk = disk.shear(disk_shape)

        bulge = galsim.Sersic(n=4.0, half_light_radius=self.hlr_bulge, flux=1.0)
        bulge_shape = galsim.Shear(g1=self.e1_bulge, g2=self.e2_bulge)
        bulge = bulge.shear(bulge_shape)

        gal = self.bfrac * bulge + (1.0 - self.bfrac) * disk
        gal = gal.withFlux(flux)
        gal_shear = galsim.Shear(g1=g1, g2=g2)
        gal = gal.shear(gal_shear)
        final = galsim.Convolve(psf, gal)
        return final

    def rotateEllipticity(self, rotation):
        if rotation == 1:
            self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = -self.e2_disk, self.e1_disk, -self.e2_bulge, self.e1_bulge, -self.e2_total, self.e1_total
        if rotation == 2:
            self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = -self.e1_disk, -self.e2_disk, -self.e1_bulge, -self.e2_bulge, -self.e1_total, -self.e2_total
        if rotation == 3:
            self.e1_disk, self.e2_disk, self.e1_bulge, self.e2_bulge, self.e1_total, self.e2_total = self.e2_disk, -self.e1_disk, self.e2_bulge, -self.e1_bulge, self.e2_total, -self.e1_total

    def drawObject(self, img, final, noise_level=0.0, flux=None, filt=None, tel=None, exptime=150.):
        """ Override the method in parent class 
        Need to constrain the size of image stamp for extended objects
        """
        isUpdated = True
        if flux == None:
            flux = self.getElectronFluxFilt(filt, tel, exptime)
        stamp = final.drawImage(wcs=self.localWCS, offset=self.offset)
        stamp_arr = stamp.array
        mask = (stamp_arr >= 0.001*noise_level) # why 0.001?
        err = int(np.sqrt(mask.sum()))
        if np.mod(err, 2) == 1:
            err += 1
        # if err == 1:
        if err == 0:
            subSize = 16 # why 16?
        else:
            subSize = max([err, 16])
            fluxRatio = flux / stamp_arr[mask].sum()
            final = final.withScaledFlux(fluxRatio)

        imgSub = galsim.ImageF(subSize, subSize)

        # Draw with FFT
        # stamp = final.drawImage(image=imgSub, wcs=self.localWCS, offset=self.offset)

        # Draw with Photon Shoot
        stamp = final.drawImage(image=imgSub, wcs=self.localWCS, method='phot', offset=self.offset)
        
        stamp.setCenter(self.x_nominal, self.y_nominal)
        if np.sum(np.isnan(stamp.array)) >= 1:
            stamp.setZero()
        bounds = stamp.bounds & img.bounds
        if bounds.area() == 0:
            isUpdated = False
        else:
            img[bounds] += stamp[bounds]
        return img, stamp, isUpdated


    def getObservedEll(self, g1=0, g2=0):
        e1_obs, e2_obs, e_obs, theta = eObs(self.e1_total, self.e2_total, g1, g2)
Zhang Xin's avatar
Zhang Xin committed
436
        return self.e1_total, self.e2_total, g1, g2, e1_obs, e2_obs