-
Notifications
You must be signed in to change notification settings - Fork 22
/
reference.py
632 lines (559 loc) · 25.6 KB
/
reference.py
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
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
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
296
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
346
347
348
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
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
import os
import numpy as np
import fitsio
from astrometry.util.fits import fits_table, merge_tables
import logging
logger = logging.getLogger('legacypipe.reference')
def info(*args):
from legacypipe.utils import log_info
log_info(logger, args)
def debug(*args):
from legacypipe.utils import log_debug
log_debug(logger, args)
def get_reference_sources(survey, targetwcs, pixscale, bands,
tycho_stars=True,
gaia_stars=True,
large_galaxies=True,
star_clusters=True):
# If bands = None, does not create sources.
H,W = targetwcs.shape
H,W = int(H),int(W)
# How big of a margin to search for bright stars and star clusters --
# this should be based on the maximum radius they are considered to
# affect. In degrees.
ref_margin = mask_radius_for_mag(0.)
mpix = int(np.ceil(ref_margin * 3600. / pixscale))
marginwcs = targetwcs.get_subimage(-mpix, -mpix, W+2*mpix, H+2*mpix)
# Table of reference-source properties, including a field 'sources',
# with tractor source objects.
refs = []
# Tycho-2 stars
if tycho_stars:
tycho = read_tycho2(survey, marginwcs, bands)
if tycho and len(tycho):
refs.append(tycho)
# Add Gaia stars
gaia = None
if gaia_stars:
from astrometry.libkd.spherematch import match_radec
gaia = read_gaia(marginwcs, bands)
if gaia is not None:
# Handle sources that appear in both Gaia and Tycho-2 by
# dropping the entry from Tycho-2.
if len(gaia) and len(tycho):
# Before matching, apply proper motions to bring them to
# the same epoch. We want to use the more-accurate Gaia
# proper motions, so rewind Gaia positions to the
# approximate epoch of Tycho-2: 1991.5.
cosdec = np.cos(np.deg2rad(gaia.dec))
gra = gaia.ra + (1991.5 - gaia.ref_epoch) * gaia.pmra / (3600.*1000.) / cosdec
gdec = gaia.dec + (1991.5 - gaia.ref_epoch) * gaia.pmdec / (3600.*1000.)
I,J,_ = match_radec(tycho.ra, tycho.dec, gra, gdec, 1./3600.,
nearest=True)
debug('Matched', len(I), 'Tycho-2 stars to Gaia stars.')
if len(I):
keep = np.ones(len(tycho), bool)
keep[I] = False
tycho.cut(keep)
gaia.isbright[J] = True
if gaia is not None and len(gaia) > 0:
refs.append(gaia)
# Read the catalog of star (open and globular) clusters and add them to the
# set of reference stars (with the isbright bit set).
if star_clusters:
clusters = read_star_clusters(marginwcs)
if clusters is not None:
debug('Found', len(clusters), 'star clusters nearby')
refs.append(clusters)
# Read large galaxies nearby.
if large_galaxies:
galaxies = read_large_galaxies(survey, targetwcs, bands)
if galaxies is not None:
# Resolve possible Gaia-large-galaxy duplicates
if gaia and len(gaia):
I,J,_ = match_radec(galaxies.ra, galaxies.dec, gaia.ra, gaia.dec,
2./3600., nearest=True)
info('Matched', len(I), 'large galaxies to Gaia stars.')
if len(I):
gaia.donotfit[J] = True
refs.append(galaxies)
if len(refs):
refs = merge_tables([r for r in refs if r is not None],
columns='fillzero')
if len(refs) == 0:
return None,None
# these x,y are in the margin-padded WCS; not useful.
# See ibx,iby computed below instead.
for c in ['x','y']:
if c in refs.get_columns():
refs.delete_column(c)
# radius / radius_pix are used to set the MASKBITS shapes;
# keep_radius determines which sources are kept (because we subtract
# stellar halos out to N x their radii)
refs.radius_pix = np.ceil(refs.radius * 3600. / pixscale).astype(int)
keeprad = np.maximum(refs.keep_radius, refs.radius)
# keeprad to pix
keeprad = np.ceil(keeprad * 3600. / pixscale).astype(int)
_,xx,yy = targetwcs.radec2pixelxy(refs.ra, refs.dec)
# ibx = integer brick coords
refs.ibx = np.round(xx-1.).astype(int)
refs.iby = np.round(yy-1.).astype(int)
# cut ones whose position + radius are outside the brick bounds.
refs.cut((xx > -keeprad) * (xx < W+keeprad) *
(yy > -keeprad) * (yy < H+keeprad))
# mark ones that are actually inside the brick area.
refs.in_bounds = ((refs.ibx >= 0) * (refs.ibx < W) *
(refs.iby >= 0) * (refs.iby < H))
for col in ['isbright', 'ismedium', 'islargegalaxy', 'iscluster', 'isgaia',
'donotfit', 'freezeparams']:
if not col in refs.get_columns():
refs.set(col, np.zeros(len(refs), bool))
sources = refs.sources
refs.delete_column('sources')
for i,(donotfit,freeze) in enumerate(zip(refs.donotfit, refs.freezeparams)):
if donotfit:
sources[i] = None
if sources[i] is None:
continue
sources[i].is_reference_source = True
if freeze:
sources[i].freezeparams = True
return refs,sources
def read_gaia(wcs, bands):
'''
*wcs* here should include margin
'''
from legacypipe.gaiacat import GaiaCatalog
from legacypipe.survey import GaiaSource
gaia = GaiaCatalog().get_catalog_in_wcs(wcs)
debug('Got', len(gaia), 'Gaia stars nearby')
gaia.G = gaia.phot_g_mean_mag
# Gaia to DECam color transformations for stars
color = gaia.phot_bp_mean_mag - gaia.phot_rp_mean_mag
# From Rongpu, 2020-04-12
# no BP-RP color: use average color
color[np.logical_not(np.isfinite(color))] = 1.4
# clip to reasonable range for the polynomial fit
color = np.clip(color, -0.6, 4.1)
for b,coeffs in [
('g', [-0.1178631039, 0.3650113495, 0.5608615360, -0.2850687702,
-1.0243473939, 1.4378375491, 0.0679401731, -1.1713172509,
0.9107811975, -0.3374324004, 0.0683946390, -0.0073089582,
0.0003230170]),
('r', [0.1139078673, -0.2868955307, 0.0013196434, 0.1029151074,
0.1196710702, -0.3729031390, 0.1859874242, 0.1370162451,
-0.1808580848, 0.0803219195, -0.0180218196, 0.0020584707,
-0.0000953486]),
('z', [0.4811198057, -0.9990015041, 0.1403990019, 0.2150988888,
-0.2917655866, 0.1326831887, -0.0259205004, 0.0018548776])]:
mag = gaia.G.copy()
for order,c in enumerate(coeffs):
mag += c * color**order
gaia.set('decam_mag_%s' % b, mag)
# For possible future use:
# BASS/MzLS:
# coeffs = dict(
# g = [-0.1299895823, 0.3120393968, 0.5989482686, 0.3125882487,
# -1.9401592247, 1.1011670449, 2.0741304659, -3.3930306403,
# 2.1857291197, -0.7674676232, 0.1542300648, -0.0167007725,
# 0.0007573720],
# r = [0.0901464643, -0.2463711147, 0.0094963025, -0.1187138789,
# 0.4131107392, -0.1832183301, -0.6015486252, 0.9802538471,
# -0.6613809948, 0.2426395251, -0.0505867727, 0.0056462458,
# -0.0002625789],
# z = [0.4862049092, -1.0278704657, 0.1220984456, 0.3000129189,
# -0.3770662617, 0.1696090596, -0.0331679127, 0.0023867628])
# force this source to remain a point source?
# Long history here, starting DJS, [decam-chatter 5486] Solved! GAIA separation
# of point sources from extended sources
# Updated for Gaia DR2 by Eisenstein,
# [decam-data 2770] Re: [desi-milkyway 639] GAIA in DECaLS DR7
# And made far more restrictive following BGS feedback.
gaia.pointsource = np.logical_or((gaia.G <= 18.) * (gaia.astrometric_excess_noise < 10.**0.5),
(gaia.G <= 13.))
# in our catalog files, this is in float32; in the Gaia data model it's
# a byte, with only values 3 and 31 in DR2.
gaia.astrometric_params_solved = gaia.astrometric_params_solved.astype(np.uint8)
# Gaia version?
gaiaver = int(os.getenv('GAIA_CAT_VER', '1'))
gaia_release = 'G%i' % gaiaver
gaia.ref_cat = np.array([gaia_release] * len(gaia))
gaia.ref_id = gaia.source_id
gaia.pmra_ivar = 1./gaia.pmra_error **2
gaia.pmdec_ivar = 1./gaia.pmdec_error**2
gaia.parallax_ivar = 1./gaia.parallax_error**2
# mas -> deg
gaia.ra_ivar = 1./(gaia.ra_error / 1000. / 3600.)**2
gaia.dec_ivar = 1./(gaia.dec_error / 1000. / 3600.)**2
for c in ['ra_error', 'dec_error', 'parallax_error',
'pmra_error', 'pmdec_error']:
gaia.delete_column(c)
for c in ['pmra', 'pmdec', 'parallax', 'pmra_ivar', 'pmdec_ivar',
'parallax_ivar']:
X = gaia.get(c)
X[np.logical_not(np.isfinite(X))] = 0.
# uniform name w/ Tycho-2
gaia.zguess = gaia.decam_mag_z
gaia.mag = gaia.G
# Take the brighter of G, z to expand masks around red stars.
gaia.mask_mag = np.minimum(gaia.G, gaia.zguess + 1.)
# radius to consider affected by this star, for MASKBITS
gaia.radius = mask_radius_for_mag(gaia.mask_mag)
# radius for keeping this source in the ref catalog
# (eg, for halo subtraction)
gaia.keep_radius = 4. * gaia.radius
gaia.delete_column('G')
gaia.isgaia = np.ones(len(gaia), bool)
gaia.isbright = (gaia.mask_mag < 13.)
gaia.ismedium = (gaia.mask_mag < 16.)
gaia.donotfit = np.zeros(len(gaia), bool)
# NOTE, must initialize gaia.sources array this way, or else numpy
# will try to be clever and create a 2-d array, because GaiaSource is
# iterable.
gaia.sources = np.empty(len(gaia), object)
if bands is not None:
for i,g in enumerate(gaia):
gaia.sources[i] = GaiaSource.from_catalog(g, bands)
return gaia
def mask_radius_for_mag(mag):
# Returns a masking radius in degrees for a star of the given magnitude.
# Used for Tycho-2 and Gaia stars.
# This is in degrees, and is from Rongpu in the thread [decam-chatter 12099].
return 1630./3600. * 1.396**(-mag)
def read_tycho2(survey, targetwcs, bands):
from astrometry.libkd.spherematch import tree_open, tree_search_radec
from legacypipe.survey import GaiaSource
tycho2fn = survey.find_file('tycho2')
radius = 1.
ra,dec = targetwcs.radec_center()
# John added the "isgalaxy" flag 2018-05-10, from the Metz &
# Geffert (04) catalog.
# Eddie added the "zguess" column 2019-03-06, by matching with
# 2MASS and estimating z based on APASS.
# The "tycho2.kd.fits" file read here was produced by:
#
# fitscopy ~schlafly/legacysurvey/tycho-isgalaxyflag-2mass.fits"[col \
# tyc1;tyc2;tyc3;ra;dec;sigma_ra;sigma_dec;mean_ra;mean_dec;pm_ra;pm_dec; \
# sigma_pm_ra;sigma_pm_dec;epoch_ra;epoch_dec;mag_bt;mag_vt;mag_hp; \
# isgalaxy;Jmag;Hmag;Kmag,zguess]" /tmp/tycho2-astrom.fits
# startree -P -k -n stars -T -i /tmp/tycho2-astrom.fits \
# -o /global/project/projectdirs/cosmo/staging/tycho2/tycho2.kd.fits
kd = tree_open(tycho2fn, 'stars')
I = tree_search_radec(kd, ra, dec, radius)
debug(len(I), 'Tycho-2 stars within', radius, 'deg of RA,Dec (%.3f, %.3f)' % (ra,dec))
if len(I) == 0:
return None
# Read only the rows within range.
tycho = fits_table(tycho2fn, rows=I)
del kd
if 'isgalaxy' in tycho.get_columns():
tycho.cut(tycho.isgalaxy == 0)
debug('Cut to', len(tycho), 'Tycho-2 stars on isgalaxy==0')
else:
print('Warning: no "isgalaxy" column in Tycho-2 catalog')
tycho.ref_cat = np.array(['T2'] * len(tycho))
# tyc1: [1,9537], tyc2: [1,12121], tyc3: [1,3]
tycho.ref_id = (tycho.tyc1.astype(np.int64)*1000000 +
tycho.tyc2.astype(np.int64)*10 +
tycho.tyc3.astype(np.int64))
with np.errstate(divide='ignore'):
tycho.pmra_ivar = 1./tycho.sigma_pm_ra**2
tycho.pmdec_ivar = 1./tycho.sigma_pm_dec**2
tycho.ra_ivar = 1./tycho.sigma_ra **2
tycho.dec_ivar = 1./tycho.sigma_dec**2
tycho.rename('pm_ra', 'pmra')
tycho.rename('pm_dec', 'pmdec')
for c in ['pmra', 'pmdec', 'pmra_ivar', 'pmdec_ivar']:
X = tycho.get(c)
X[np.logical_not(np.isfinite(X))] = 0.
tycho.mag = tycho.mag_vt
# Patch missing mag values...
tycho.mag[tycho.mag == 0] = tycho.mag_hp[tycho.mag == 0]
tycho.mag[tycho.mag == 0] = tycho.mag_bt[tycho.mag == 0]
# Use zguess
tycho.mask_mag = tycho.mag
with np.errstate(invalid='ignore'):
I = np.flatnonzero(np.isfinite(tycho.zguess) *
(tycho.zguess + 1. < tycho.mag))
tycho.mask_mag[I] = tycho.zguess[I]
# Per discussion in issue #306 -- cut on mag < 13.
# This drops only 13k/2.5M stars.
tycho.cut(tycho.mask_mag < 13.)
tycho.radius = mask_radius_for_mag(tycho.mask_mag)
tycho.keep_radius = 2. * tycho.radius
for c in ['tyc1', 'tyc2', 'tyc3', 'mag_bt', 'mag_vt', 'mag_hp',
'mean_ra', 'mean_dec',
'sigma_pm_ra', 'sigma_pm_dec', 'sigma_ra', 'sigma_dec']:
tycho.delete_column(c)
# add Gaia-style columns
# No parallaxes in Tycho-2
tycho.parallax = np.zeros(len(tycho), np.float32)
# Tycho-2 "supplement" stars, from Hipparcos and Tycho-1 catalogs, have
# ref_epoch = 0. Fill in with the 1991.25 epoch of those catalogs.
tycho.epoch_ra [tycho.epoch_ra == 0] = 1991.25
tycho.epoch_dec[tycho.epoch_dec == 0] = 1991.25
# Tycho-2 has separate epoch_ra and epoch_dec.
# Move source to the mean epoch.
tycho.ref_epoch = (tycho.epoch_ra + tycho.epoch_dec) / 2.
cosdec = np.cos(np.deg2rad(tycho.dec))
tycho.ra += (tycho.ref_epoch - tycho.epoch_ra ) * tycho.pmra / 3600. / cosdec
tycho.dec += (tycho.ref_epoch - tycho.epoch_dec) * tycho.pmdec / 3600.
# Tycho-2 proper motions are in arcsec/yr; Gaia are mas/yr.
tycho.pmra *= 1000.
tycho.pmdec *= 1000.
# We already cut on John's "isgalaxy" flag
tycho.pointsource = np.ones(len(tycho), bool)
# phot_g_mean_mag -- for initial brightness of source
tycho.phot_g_mean_mag = tycho.mag
tycho.delete_column('epoch_ra')
tycho.delete_column('epoch_dec')
tycho.isbright = np.ones(len(tycho), bool)
tycho.ismedium = np.ones(len(tycho), bool)
tycho.sources = np.empty(len(tycho), object)
if bands is not None:
for i,t in enumerate(tycho):
tycho.sources[i] = GaiaSource.from_catalog(t, bands)
return tycho
def get_large_galaxy_version(fn):
preburn = False
hdr = fitsio.read_header(fn)
try:
v = hdr.get('SGAVER')
if v is None: # old version
v = hdr.get('LSLGAVER')
if v is not None:
v = v.strip()
if 'ellipse' in v.lower():
preburn = True
v, _ = v.split('-')
assert(len(v) == 2)
return v, preburn
except KeyError:
pass
for k in ['3.0', '2.0']:
if k in fn:
return 'L'+k[0], preburn
return 'LG', preburn
def read_large_galaxies(survey, targetwcs, bands):
from astrometry.libkd.spherematch import tree_open, tree_search_radec
from legacypipe.catalog import fits_reverse_typemap
from tractor import NanoMaggies, RaDecPos, PointSource
from tractor.ellipses import EllipseE, EllipseESoft
from tractor.galaxy import DevGalaxy, ExpGalaxy
from tractor.sersic import SersicGalaxy
from legacypipe.survey import LegacySersicIndex, LegacyEllipseWithPriors, LogRadius, RexGalaxy
galfn = survey.find_file('large-galaxies')
if galfn is None:
debug('No large-galaxies catalog file')
return None
radius = 1.
rc,dc = targetwcs.radec_center()
kd = tree_open(galfn, 'largegals')
I = tree_search_radec(kd, rc, dc, radius)
debug(len(I), 'large galaxies within', radius,
'deg of RA,Dec (%.3f, %.3f)' % (rc,dc))
if len(I) == 0:
return None
# Read only the rows within range.
galaxies = fits_table(galfn, rows=I)
del kd
refcat, preburn = get_large_galaxy_version(galfn)
#print('Large galaxy cat: ', refcat, 'preburn', preburn)
#print('ref_cat:', galaxies.ref_cat, 'ref_id:', galaxies.ref_id)
#galaxies.about()
#print('lslga id:', galaxies.lslga_id)
if not preburn:
# Original LSLGA
galaxies.ref_cat = np.array([refcat] * len(galaxies))
galaxies.islargegalaxy = np.array([True] * len(galaxies))
galaxies.preburned = np.zeros(len(galaxies), bool)
# new data model
galaxies.rename('sga_id', 'ref_id')
galaxies.rename('mag_leda', 'mag')
galaxies.radius = galaxies.diam / 2. / 60. # [degree]
else:
# Need to initialize islargegalaxy to False because we will bring in
# pre-burned sources that we do not want to use in MASKBITS.
galaxies.islargegalaxy = np.zeros(len(galaxies), bool)
galaxies.radius = np.zeros(len(galaxies), 'f4')
galaxies.rename('mag_leda', 'mag')
galaxies.radius = galaxies.diam / 2. / 60. # [degree]
galaxies.freezeparams = np.zeros(len(galaxies), bool)
galaxies.sources = np.empty(len(galaxies), object)
galaxies.sources[:] = None
# Factor of HyperLEDA to set the galaxy max radius
radius_max_factor = 2.
## use the pre-burned LSLGA catalog
#if 'preburned' in galaxies.get_columns():
# preburned = np.logical_and(preburn, galaxies.preburned)
#else:
# preburned = np.zeros(len(galaxies), bool)
if bands is not None:
I, = np.nonzero(galaxies.preburned)
# only fix the parameters of pre-burned galaxies
for ii,g in zip(I, galaxies[I]):
try:
typ = fits_reverse_typemap[g.type.strip()]
pos = RaDecPos(g.ra, g.dec)
fluxes = dict([(band, g.get('flux_%s' % band)) for band in bands])
bright = NanoMaggies(order=bands, **fluxes)
shape = None
# put the Rex branch first, because Rex is a subclass of ExpGalaxy!
if issubclass(typ, RexGalaxy):
assert(np.isfinite(g.shape_r))
logre = np.log(g.shape_r)
shape = LogRadius(logre)
# set prior max at 2x HyperLEDA radius
shape.setMaxLogRadius(logre + np.log(radius_max_factor))
elif issubclass(typ, (DevGalaxy, ExpGalaxy, SersicGalaxy)):
assert(np.isfinite(g.shape_r))
assert(np.isfinite(g.shape_e1))
assert(np.isfinite(g.shape_e2))
shape = EllipseE(g.shape_r, g.shape_e1, g.shape_e2)
# switch to softened ellipse (better fitting behavior)
shape = EllipseESoft.fromEllipseE(shape)
# and then to our custom ellipse class
logre = shape.logre
shape = LegacyEllipseWithPriors(logre, shape.ee1, shape.ee2)
assert(np.all(np.isfinite(shape.getParams())))
# set prior max at 2x HyperLEDA radius
shape.setMaxLogRadius(logre + np.log(radius_max_factor))
if issubclass(typ, (DevGalaxy, ExpGalaxy)):
src = typ(pos, bright, shape)
elif issubclass(typ, (SersicGalaxy)):
assert(np.isfinite(g.sersic))
sersic = LegacySersicIndex(g.sersic)
src = typ(pos, bright, shape, sersic)
elif issubclass(typ, PointSource):
src = typ(pos, bright)
else:
print('Unknown type', typ)
debug('Created', src)
assert(np.isfinite(src.getLogPrior()))
galaxies.sources[ii] = src
if galaxies.freeze[ii] and galaxies.ref_cat[ii] == refcat:
galaxies.islargegalaxy[ii] = True
assert((galaxies.radius[ii] > 0) * np.isfinite(galaxies.radius[ii]))
assert((galaxies.pa[ii] >= 0) * (galaxies.pa[ii] <= 180) * np.isfinite(galaxies.pa[ii]))
assert((galaxies.ba[ii] > 0) * (galaxies.ba[ii] <= 1.0) * np.isfinite(galaxies.ba[ii]))
#print(galaxies.ref_cat[ii], galaxies.ref_id[ii], galaxies.radius[ii], galaxies.pa[ii], galaxies.ba[ii])
if galaxies.freeze[ii]:
galaxies.freezeparams[ii] = True
except:
import traceback
print('Failed to create Tractor source for LSLGA entry:',
traceback.print_exc())
raise
I, = np.nonzero(np.logical_not(galaxies.preburned))
for ii,g in zip(I, galaxies[I]):
# Initialize each source with an exponential disk--
fluxes = dict([(band, NanoMaggies.magToNanomaggies(g.mag)) for band in bands])
assert(np.all(np.isfinite(list(fluxes.values()))))
rr = g.radius * 3600. / 2 # factor of two accounts for R(25)-->reff [arcsec]
assert(np.isfinite(rr))
assert(np.isfinite(g.ba))
assert(np.isfinite(g.pa))
ba = g.ba
if ba <= 0.0 or ba > 1.0:
# Make round!
ba = 1.0
logr, ee1, ee2 = EllipseESoft.rAbPhiToESoft(rr, ba, 180-g.pa) # note the 180 rotation
assert(np.isfinite(logr))
assert(np.isfinite(ee1))
assert(np.isfinite(ee2))
shape = LegacyEllipseWithPriors(logr, ee1, ee2)
shape.setMaxLogRadius(logr + np.log(radius_max_factor))
src = ExpGalaxy(RaDecPos(g.ra, g.dec),
NanoMaggies(order=bands, **fluxes),
shape)
assert(np.isfinite(src.getLogPrior()))
galaxies.sources[ii] = src
keep_columns = ['ra', 'dec', 'radius', 'mag', 'ref_cat', 'ref_id', 'ba', 'pa',
'sources', 'islargegalaxy', 'freezeparams']
for c in galaxies.get_columns():
if not c in keep_columns:
galaxies.delete_column(c)
return galaxies
def read_star_clusters(targetwcs):
"""The code to generate the NGC-star-clusters-fits catalog is in
legacypipe/bin/build-cluster-catalog.py.
"""
from pkg_resources import resource_filename
from astrometry.util.starutil_numpy import degrees_between
clusterfile = resource_filename('legacypipe', 'data/NGC-star-clusters.fits')
debug('Reading {}'.format(clusterfile))
clusters = fits_table(clusterfile, columns=['ra', 'dec', 'radius', 'type', 'ba', 'pa'])
clusters.ref_id = np.arange(len(clusters))
radius = 1.
rc,dc = targetwcs.radec_center()
d = degrees_between(rc, dc, clusters.ra, clusters.dec)
clusters.cut(d < radius)
if len(clusters) == 0:
return None
debug('Cut to {} star cluster(s) within the brick'.format(len(clusters)))
clusters.ref_cat = np.array(['CL'] * len(clusters))
# Radius in degrees
clusters.radius = clusters.radius
clusters.radius[np.logical_not(np.isfinite(clusters.radius))] = 1./60.
# Set isbright=True
clusters.isbright = np.zeros(len(clusters), bool)
clusters.iscluster = np.ones(len(clusters), bool)
clusters.sources = np.array([None] * len(clusters))
return clusters
def get_reference_map(wcs, refs):
from legacypipe.bits import IN_BLOB
H,W = wcs.shape
H = int(H)
W = int(W)
refmap = np.zeros((H,W), np.uint8)
# circular/elliptical regions:
for col,bit,ellipse in [('isbright', 'BRIGHT', False),
('ismedium', 'MEDIUM', False),
('iscluster', 'CLUSTER', True),
('islargegalaxy', 'GALAXY', True),]:
isit = refs.get(col)
if not np.any(isit):
debug('None marked', col)
continue
I, = np.nonzero(isit)
debug(len(I), 'with', col, 'set')
if len(I) == 0:
continue
thisrefs = refs[I]
if bit == 'BRIGHT':
# decrease the BRIGHT masking radius by a factor of two!
debug('Scaling down BRIGHT masking radius by a factor of 2')
thisrefs.radius_pix[:] = (thisrefs.radius_pix + 1) // 2
_,xx,yy = wcs.radec2pixelxy(thisrefs.ra, thisrefs.dec)
for x,y,ref in zip(xx,yy,thisrefs):
# Cut to bounding square
xlo = int(np.clip(np.floor(x-1 - ref.radius_pix), 0, W))
xhi = int(np.clip(np.ceil (x + ref.radius_pix), 0, W))
ylo = int(np.clip(np.floor(y-1 - ref.radius_pix), 0, H))
yhi = int(np.clip(np.ceil (y + ref.radius_pix), 0, H))
if xlo == xhi or ylo == yhi:
continue
bitval = np.uint8(IN_BLOB[bit])
if not ellipse:
rr = ((np.arange(ylo,yhi)[:,np.newaxis] - (y-1))**2 +
(np.arange(xlo,xhi)[np.newaxis,:] - (x-1))**2)
masked = (rr <= ref.radius_pix**2)
else:
# *should* have ba and pa if we got here...
xgrid,ygrid = np.meshgrid(np.arange(xlo,xhi), np.arange(ylo,yhi))
dx = xgrid - (x-1)
dy = ygrid - (y-1)
debug('Object: PA', ref.pa, 'BA', ref.ba, 'Radius', ref.radius, 'pix', ref.radius_pix)
if not np.isfinite(ref.pa):
ref.pa = 0.
v1x = -np.sin(np.deg2rad(ref.pa))
v1y = np.cos(np.deg2rad(ref.pa))
v2x = v1y
v2y = -v1x
dot1 = dx * v1x + dy * v1y
dot2 = dx * v2x + dy * v2y
r1 = ref.radius_pix
r2 = ref.radius_pix * ref.ba
masked = (dot1**2 / r1**2 + dot2**2 / r2**2 < 1.)
refmap[ylo:yhi, xlo:xhi] |= (bitval * masked)
return refmap