-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathcutout_utils.py
2158 lines (1866 loc) · 67.9 KB
/
cutout_utils.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
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
"""
Functions to make various cutouts and plots
"""
def MAD(l, med):
import numpy as np
return np.median(abs( l - med ))
def SED_plot(mags, magErrs, id):
"""
Makes plots of the magnitudes in different bands.
Uses id as title
Assumes VHS and WISE are in Vega and converts them
Uses conversions from WISE explanatory Supplement and CASU website
Sets 99 DES objects to 25.0 with an error of 1.0
Also sets WISE limits to 25.0 and nan magnitudes to 25.0
Returns rather than draws the plot
"""
import matplotlib.pyplot as plt
import numpy as np
import pylab
mids = np.array([4800.0, 6400.0, 7800.0, 9200.0, 9900.0, 13140.0, 16890.0, 22130.0, 34000.0, 46000.0])
filters = np.array(["g", "r", "i", "z", "Y", "J", "H", "K", "W1", "W2"])
convs = np.array([0.0,0.0,0.0,0.0,0.0,0.937,1.384,1.839,2.699,3.339, 5.174, 6.620])
fig = plt.figure()
ax = fig.add_subplot(111)
ids = np.where( (mags <> mags) | (mags == 99.0) | (magErrs <> magErrs) )[0]
magErrs[ids] = 1.0
mags[ids] = 25.0
ax.errorbar(mids, mags+convs, yerr = [magErrs, magErrs], xerr = [[0.0]*len(mags), [0.0]*len(mags)], ls = ".", ms = 0, color = "black")
ax.plot(mids, mags+convs, "k.", label = "Actual values")
ax.invert_yaxis()
ax.set_title(id)
pylab.xticks(mids, filters)
return fig
def make_cutout(filename, RA, DEC, width, nhdu = 0, w_units = "arcsecs", verbose = False):
"""
Makes cutouts from a file passed as either a filename or hdulist
Returns a new hdulist with updated WCS and the cutout as the data
The specified width should be in arcsecs or pixels.
It is the full width.
"""
from astropy import wcs
import wcsutil
import astropy.io.fits as fits
import astropy.io.fits.compression
import numpy as np
import gc
import matplotlib.pyplot as plt
import warnings
from astropy.utils.exceptions import AstropyWarning
import copy
im_status = "good"
if not verbose:
warnings.filterwarnings('ignore', category=UserWarning, append=True)
warnings.simplefilter('ignore', category=AstropyWarning)
if isinstance(filename, basestring):
with fits.open(filename) as h:
hdr = h[nhdu].header
data = h[nhdu].data
else:
try:
hdr = filename[nhdu].header
#It is this line data = filename[nhdu].data
data = filename[nhdu].data
except RuntimeError:
print "File Corrupt"
return None, "bad"
try:
test = hdr["NAXIS1"]
except KeyError:
return None, "bad"
#Figure out how big the square would be at the centre
test_pix = [[hdr["NAXIS1"]/2, hdr["NAXIS2"]/2]]
try:
from astropy import wcs
w = wcs.WCS(hdr, naxis = 2)
if w_units == "arcsecs":
width = width/3600.0/2.0
w_coord = np.array([[RA - width/np.cos(np.deg2rad(DEC)), DEC - width], [RA + width/np.cos(np.deg2rad(DEC)), DEC + width]], np.float_)
pix_coord = w.wcs_world2pix(w_coord, 1)
coords = [int(pix_coord[0][0]), int(pix_coord[0][1]), int(pix_coord[1][0]), int(pix_coord[1][1])]
test_coord = w.wcs_pix2world(test_pix, 1)
test_edges = np.array([[test_coord[0][0], test_coord[0][1] - width], \
[test_coord[0][0], test_coord[0][1] + width]], np.float_)
test_pix = w.wcs_world2pix(test_edges, 1)
[[tx1, ty1], [tx2, ty2]] = test_pix
elif w_units == "pixels":
w_coord = np.array([[RA, DEC]], np.float_)
pix_coord = w.wcs_world2pix(w_coord, 1)
coords = [int(pix_coord[0][0]+width/2.0), int(pix_coord[0][1]-width/2.0), int(pix_coord[0][0]-width/2.0), int(pix_coord[0][1]+width/2.0)]
#Create a background of zeros
blank = np.zeros((width+1, width+1))
except (UnboundLocalError, wcs.wcs.InconsistentAxisTypesError) as e:
try:
wcs = wcsutil.WCS(hdr)
except KeyError:
hdr = h[nhdu-1].header
wcs = wcsutil.WCS(hdr)
width = width/3600.0/2.0
test_coord = wcs.image2sky(test_pix[0][0], test_pix[0][1])
tx1, ty1 = wcs.sky2image(test_coord[0], test_coord[1] - width)
tx2, ty2 = wcs.sky2image(test_coord[0], test_coord[1] + width)
x1, y1 = wcs.sky2image(RA - width/np.cos(np.deg2rad(DEC)), DEC - width)
x2, y2 = wcs.sky2image(RA + width/np.cos(np.deg2rad(DEC)), DEC + width)
coords = [int(x1), int(y1), int(x2), int(y2)]
if tx1 > tx2:
x_width = tx1 - tx2
else:
x_width = tx1 - tx2
if ty1 > ty2:
y_width = ty1 - ty2
else:
y_width = ty2 - ty1
if x_width > y_width:
b_width = x_width
else:
b_width = y_width
blank = np.zeros((int(np.ceil(b_width))+1, int(np.ceil(b_width))+1))
#coords = [x1, y1, x2, y2]
coords_clean = coords + []
for (n,p) in enumerate(coords):
if p < 0.0:
coords_clean[n] = 0.0
im_status = "bad"
elif (p > hdr["NAXIS1"] and n % 2 == 0):
coords_clean[n] = hdr["NAXIS1"]
im_status = "bad"
elif (p > hdr["NAXIS2"] and n % 2 <> 0):
coords_clean[n] = hdr["NAXIS2"]
im_status = "bad"
if len(data.shape) > 2:
data = data[0,0,:,:]
if w_units == "pixels":
im = data[coords_clean[1]:coords_clean[3], coords_clean[2]:coords_clean[0]]
if w_units == "arcsecs":
im = data[int(coords_clean[1]):int(coords_clean[3]), int(coords_clean[2]):int(coords_clean[0])]
if coords[0] > hdr["NAXIS1"]:
by2 = hdr["NAXIS1"]-coords[2]
im_status = "bad"
else:
by2 = im.shape[1]
if coords[2] < 0:
by1 = np.fabs(coords[2])
im_status = "bad"
by2 += by1
else:
by1 = 0
if coords[3] > hdr["NAXIS2"]:
bx2 = hdr["NAXIS2"]-coords[1]
im_status = "bad"
else:
bx2 = im.shape[0]
if coords[1] < 0:
bx1 = np.fabs(coords[1])
im_status = "bad"
bx2 += bx1
else:
bx1 = 0
if (coords_clean[1] == coords_clean[3]) or (coords_clean[0] == coords_clean[2]):
im = blank
im_status = "bad"
else:
try:
blank[int(bx1):int(bx2), int(by1):int(by2)] = im
except ValueError:
#blank = np.zeros((max(im.shape), max(im.shape)))
blank = np.zeros((max([bx2, by2]), max([bx2, by2])))
blank[int(bx1):int(bx2), int(by1):int(by2)] = im
im = blank
phdu = fits.PrimaryHDU()
h2 = copy.deepcopy(hdr)
h2["CRPIX1"] = hdr["CRPIX1"]-coords[2]
h2["CRPIX2"] = hdr["CRPIX2"]-coords[1]
imhdu = fits.ImageHDU(header = h2, data = im)
hdulist = fits.HDUList([phdu, imhdu])
return hdulist, im_status
def draw_crosshairs(ax, w, ra, dec):
"""
Draws crosshairs on an image axis
Requires the axis to draw on, ax the wcs information w as an astropy wcs thing
eg w = wcs.WCS(hdr, naxis = 2) and the ra and dec of object
Also puts on N and E arrows.
Not extensivly tested may require tweaking
"""
import wcsutil
from astropy import wcs
import numpy as np
import matplotlib.pyplot as plt
cen_world = [[ra, dec]]
try:
cen_coord = w.wcs_world2pix(cen_world, 1)
except AttributeError:
cen_coord = [w.sky2image(cen_world[0][0], cen_world[0][1])]
cen_x = cen_coord[0][0]
cen_y = np.floor(cen_coord[0][1])
ax.autoscale(False)
ax.plot([cen_x, cen_x], [cen_y + 7, cen_y + 27], "k", lw = 3)
ax.plot([cen_x, cen_x], [cen_y - 7, cen_y - 27], "k", lw = 3)
ax.plot([cen_x + 7, cen_x + 27], [cen_y, cen_y], "k", lw = 3)
ax.plot([cen_x - 7, cen_x - 27], [cen_y, cen_y], "k", lw = 3)
eline = [[ra + 5.0/3600.0, dec - 10.0/3600.0], [ra + 10.0/3600.0, dec - 10.0/3600.0], [ra + 10.0/3600.0, dec - 12.0/3600.0]]
try:
eline = w.wcs_world2pix(eline, 1)
except AttributeError:
eline1 = w.sky2image(eline[0][0], eline[0][1])
eline2 = w.sky2image(eline[1][0], eline[1][1])
eline3 = w.sky2image(eline[2][0], eline[2][1])
eline = [eline1, eline2, eline3]
ax.arrow(eline[0][0], eline[0][1], eline[1][0]-eline[0][0], eline[1][1]-eline[0][1], fc = "k", ec = "k", head_width = 5.0, head_length = 5.0, lw = 2)
ax.annotate("E", xy = (eline[2][0], eline[2][1]), size = 12, weight = "bold")
nline = [[ra + 5.0/3600.0, dec - 10.0/3600.0], [ra + 5.0/3600.0, dec - 5.0/3600.0], [ra + 9.0/3600.0, dec - 5.0/3600.0]]
try:
nline = w.wcs_world2pix(nline, 1)
except AttributeError:
nline1 = w.sky2image(nline[0][0], nline[0][1])
nline2 = w.sky2image(nline[1][0], nline[1][1])
nline3 = w.sky2image(nline[2][0], nline[2][1])
nline = [nline1, nline2, nline3]
ax.arrow(nline[0][0], nline[0][1], nline[1][0]-nline[0][0], nline[1][1]-nline[0][1], fc = "k", ec = "k", head_width = 5.0, head_length = 5.0, lw = 2)
ax.annotate("N", xy = (nline[2][0]-2.0, nline[2][1]), size = 12, weight = "bold")
return ax
def find_north(RA, DEC, w):
import wcsutil
from astropy import wcs
nline = [[RA + 5.0/3600.0, DEC - 10.0/3600.0], [RA + 5.0/3600.0, DEC - 5.0/3600.0], [RA + 9.0/3600.0, DEC - 5.0/3600.0]]
try:
nline = w.wcs_world2pix(nline, 1)
except AttributeError:
nline1 = w.sky2image(nline[0][0], nline[0][1])
nline2 = w.sky2image(nline[1][0], nline[1][1])
nline3 = w.sky2image(nline[2][0], nline[2][1])
nline = [nline1, nline2, nline3]
if int(nline[1][0])-int(nline[0][0]) > 0:
north = "right"
elif int(nline[1][1])-int(nline[0][1]) < 0:
north = "up"
elif int(nline[1][1])-int(nline[0][1]) > 0:
north = "down"
elif int(nline[1][0])-int(nline[0][0]) < 0:
north = "left"
return north
def PAngle(ra1, dec1, ra2, dec2, frame = "icrs", verbose = True, debug = False, test=False):
"""
Calculates the posistion angle between two objects
"""
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.coordinates import ICRS, Galactic, FK4, FK5
from astropy.coordinates import Angle, Latitude, Longitude
import numpy
import astropy.coordinates as coord
radec1 = SkyCoord(ra1, dec1, unit = (u.degree, u.degree), frame = frame)
radec2 = SkyCoord(ra2, dec2, unit = (u.degree, u.degree), frame = frame)
sep = radec1.separation(radec2).arcsecond
PA = radec1.position_angle(radec2).degree
return sep, PA
def make_DES_finding_chart(RA, DEC, mag, id, tile, run, outdir, filename, release = "Y1A1", band = "z", bright_star = False, width = 4.0*60.0, invert = False, invert_east = False):
"""
If Y2 then put tile and run as ""
"""
import DES_utils as Du
import numpy as np
import matplotlib.pyplot as plt
import wcsutil
from astropy import units as u
from astropy.coordinates import SkyCoord
import sqlutil
from matplotlib.patches import Ellipse, Circle
import match_lists
import matplotlib.patheffects as path_effects
import plotid
if invert:
cmap = "gray_r"
font_col = "white"
line_col = "black"
else:
cmap = "gray"
font_col = "lawngreen"
line_col = "white"
fig = plt.figure(figsize = (8.27, 11.69))
ax = fig.add_axes([0.0, 0.3, 1.0, 0.6])
ax1 = fig.add_axes([0.05, 0.05, 0.90, 0.20])
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax1.axes.get_xaxis().set_visible(False)
ax1.axes.get_yaxis().set_visible(False)
for i in ax1.spines.itervalues():
i.set_linewidth(0.0)
for i in ax.spines.itervalues():
i.set_linewidth(2.0)
if "Y2" in release:
files, bands = Du.DES_Y2_image_file(RA, DEC, bands = [band], download = True)
nhdu = 0
filename = files[0]
else:
filename = "/data/desardata/" + release + "/" + tile + "/" + tile + "_" + band + ".fits.fz"
nhdu = 1
hdulist, im_status = make_cutout(filename, RA, DEC, width, nhdu = nhdu, w_units = "arcsecs")
if (hdulist is None or im_status == "bad") and "Y2" in release:
n = 0
while n < len(files[1:]):
hdulist, im_status = make_cutout(files[n], RA, DEC, width, nhdu = nhdu, w_units = "arcsecs")
if hdulist is not None and im_status == "good":
n = len(files)
n += 1
hdr = hdulist[1].header
image = hdulist[1].data
data = image.flatten()
med = np.median(data)
sigma_MAD = 1.4826 * MAD(data, med)
vmax = med + 5.0*sigma_MAD
vmin = med - 2.0*sigma_MAD
try:
from astropy import wcs
w = wcs.WCS(hdr, naxis = 2)
except (UnboundLocalError, wcs.wcs.InconsistentAxisTypesError) as e:
try:
w = wcsutil.WCS(hdr)
except KeyError:
hdr = h[nhdu-1].header
w = wcsutil.WCS(hdr)
north = find_north(RA, DEC, w)
if north == "up":
rot_mat = np.matrix( ((1,1), (1,1)) )
ax.imshow(image, vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest", cmap = cmap)
elif north == "down":
image = np.flipud(image)
#PLaceholder as just want to subtract(add) centre y from each y.
rot_mat = np.matrix( ((1,1), (1,1)) )
ax.imshow(image, vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest", cmap = cmap)
elif north == "right":
image = np.rot90(image, 1)
rot_mat = np.matrix( ((0,-1), (1,0)) )
ax.imshow(zip(*image)[::-1], vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest", cmap = cmap)
elif north == "left":
image = np.rot90(image, 3)
rot_mat = np.matrix( ((0,1), (-1,0)) )
ax.imshow(image, vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest", cmap = cmap)
cen_world = [[RA, DEC]]
try:
cen_coord = w.wcs_world2pix(cen_world, 1)
except AttributeError:
cen_coord = [w.sky2image(cen_world[0][0], cen_world[0][1])]
cen_x = cen_coord[0][0]
cen_y = np.floor(cen_coord[0][1])
ax.autoscale(False)
ax.plot([cen_x, cen_x], [cen_y + 10, cen_y + 30], color = line_col, lw = 2)
ax.plot([cen_x, cen_x], [cen_y - 10, cen_y - 30], color = line_col, lw = 2)
ax.plot([cen_x + 10, cen_x + 30], [cen_y, cen_y], color = line_col, lw = 2)
ax.plot([cen_x - 10, cen_x - 30], [cen_y, cen_y], color = line_col, lw = 2)
#Add arrows
if invert_east:
ax.annotate("", xy=(0.15, 0.05), xytext=(0.05, 0.05), textcoords = "axes fraction", \
color = line_col, fontsize = 15, xycoords = "axes fraction", \
arrowprops=dict(fc=line_col, width = 2.0, frac = 0.3, ec = line_col))
text = ax.annotate("E", xy = (0.17,0.04), xycoords = "axes fraction", \
color = font_col, fontsize = 15)
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
ax.annotate("", xy=(0.05, 0.15), xytext=(0.05, 0.05), textcoords = "axes fraction", \
color = line_col, fontsize = 15, xycoords = "axes fraction", \
arrowprops=dict(fc= line_col, width = 2.0, frac = 0.3, ec = line_col))
text = ax.annotate("N", xy = (0.04,0.17), xycoords = "axes fraction", \
color = font_col, fontsize = 15)
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
if not invert_east:
ax.annotate("", xy=(0.05, 0.15), xytext=(0.15, 0.15), textcoords = "axes fraction", \
color = line_col, fontsize = 15, xycoords = "axes fraction", \
arrowprops=dict(fc=line_col, width = 2.0, frac = 0.3, ec = line_col))
text = ax.annotate("E", xy = (0.02,0.14), xycoords = "axes fraction", \
color = font_col, fontsize = 15)
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
ax.annotate("", xy=(0.15, 0.25), xytext=(0.15, 0.15), textcoords = "axes fraction", \
color = line_col, fontsize = 15, xycoords = "axes fraction", \
arrowprops=dict(fc= line_col, width = 2.0, frac = 0.3, ec = line_col))
text = ax.annotate("N", xy = (0.14,0.27), xycoords = "axes fraction", \
color = font_col, fontsize = 15)
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
#Add box
try:
s_coords = [[RA + 30.0/3600.0/np.cos(np.deg2rad(DEC)), DEC + 30.0/3600.0], [RA - 30.0/3600.0/np.cos(np.deg2rad(DEC)), DEC - 30.0/3600.0]]
[[raplus, decplus], [raminus, decminus]] = w.wcs_world2pix(s_coords, 1)
except AttributeError:
raplus, decplus = w.sky2image(RA + 30.0/3600.0/np.cos(np.deg2rad(DEC)), DEC + 30.0/3600.0)
raminus, decminus = w.sky2image(RA - 30.0/3600.0/np.cos(np.deg2rad(DEC)), DEC - 30.0/3600.0)
ax.plot([raplus, raplus], [decminus, decplus], color = line_col, lw = 2)
ax.plot([raminus, raminus], [decminus, decplus], color = line_col, lw = 2)
ax.plot([raminus, raplus], [decminus, decminus], color = line_col, lw = 2)
ax.plot([raminus, raplus], [decplus, decplus], color = line_col, lw = 2)
if invert_east:
text = ax.annotate('60"', xy = (raplus-20, cen_y), color = font_col, fontsize = 15)
else:
text = ax.annotate('60"', xy = (raplus-50, cen_y), color = font_col, fontsize = 15)
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
#Add circles
c_width = abs(raplus - raminus)
ax.add_patch(Ellipse(xy = (cen_x, cen_y), width = c_width*2, height = c_width*2, angle = 0.0, fill = False, lw = 1, color = line_col))
ax.add_patch(Ellipse(xy = (cen_x, cen_y), width = c_width*4, height = c_width*4, angle = 0.0, fill = False, lw = 1, color = line_col))
#Add object details
c = SkyCoord(ra=RA*u.degree, dec=DEC*u.degree, frame='icrs')
coord_string = "%02.0f:%02.0f:%06.3f %02.0f:%02.0f:%05.2f" % (c.ra.hms[0], c.ra.hms[1], c.ra.hms[2], c.dec.dms[0], np.fabs(c.dec.dms[1]), np.fabs(c.dec.dms[2]))
ax1.text(0.01, 0.88, "Name RA Dec " + band + " [AB] PA ROA", fontweight = "bold", family = "monospace")
ax1.text(0.01, 0.73, "Object " + coord_string + " %0.2f " % mag, family = "monospace")
radius = "%0.5f" % (60.0/3600.0/2.0)
if release == "Y1A1":
query = "select RA, DEC, MAG_PSF_" + band.upper() + " from des_y1a1.coadd_objects WHERE \
q3c_radial_query(ra, dec, " + str(RA) + ", " + str(DEC) + \
", " + radius + ")"
ras_info, decs_info, mags_info = sqlutil.get(query, db = "wsdb", host = "cappc127", user = "sophiereed", password = "5ef23edc6")
if release == "Y2Q1":
query = "select RA, DEC, MAG_PSF_" + band.upper() + " from des_y2q1.objects WHERE \
q3c_radial_query(ra, dec, " + str(RA) + ", " + str(DEC) + \
", " + radius + ")"
ras_info, decs_ino, mags_info = sqlutil.get(query, db = "wsdb", host = "cappc127", user = "sophiereed", password = "5ef23edc6")
for (ra_info, dec_info, mag_info) in zip(ras_info, decs_info, mags_info):
try:
xy_info = w.wcs_world2pix([[ra_info, dec_info]], 1)
except AttributeError:
xy_info = [w.sky2image(ra_info, dec_info)]
if north <> "down":
xy_info = np.array((xy_info[0][0], xy_info[0][1]))*rot_mat
xy_info = (xy_info.getA()[0][0], xy_info.getA()[0][1])
else:
y_info = xy_info[0][1]
y_info = cen_y + (cen_y - y_info)
xy_info = (xy_info[0][0], y_info)
if invert_east:
text1 = ax.annotate("%0.2f" % mag_info, xy = (xy_info[0] - 10.0, xy_info[1] - 0.0) , color = "k", fontweight = "light")
else:
text1 = ax.annotate("%0.2f" % mag_info, xy = (xy_info[0] + 10.0, xy_info[1] + 0.0) , color = "k", fontweight = "light")
if bright_star:
radius = str(width/2.0*np.sqrt(2.0)/3600.0)
if release == "Y1A1":
query = "select RA, DEC, MAG_PSF_" + band.upper() + " from des_y1a1.coadd_objects WHERE \
q3c_radial_query(ra, dec, " + str(RA) + ", " + str(DEC) + \
", " + radius + ") and MAG_PSF_" + band.upper() + "< 20 and MAG_PSF_" + band.upper() + "> 16"
ras_bs, decs_bs, mags_bs = sqlutil.get(query, db = "wsdb", host = "cappc127", user = "sophiereed", password = "5ef23edc6")
if release == "Y2Q1":
print band.upper(), "band"
query = "select RA, DEC, MAG_PSF_" + band.upper() + " from des_y2q1.objects WHERE \
q3c_radial_query(ra, dec, " + str(RA) + ", " + str(DEC) + \
", " + radius + ") and MAG_PSF_" + band.upper() + " < 19 and MAG_PSF_" + band.upper() + " > 16"
ras_bs, decs_bs, mags_bs = sqlutil.get(query, db = "wsdb", host = "cappc127", user = "sophiereed", password = "5ef23edc6")
"""
pm_ra, pm_dec, ra_proMot, dec_proMot = sqlutil.get(pm_query, db = "wsdb", host = "cappc127", user = "sophiereed", password = "5ef23edc6")
dists, inds = match_lists.match_lists(ras_bs, decs_bs, pm_ra, pm_dec, 2.0/3600.0)
ids = np.where( (inds <> len(pm_ra)) )[0]
print ids
ras_bs = ras_bs[ids]
decs_bs = decs_bs[ids]
print ra_proMot[inds[ids]]
"""
dists = []
PAs = []
for (ra_bs, dec_bs) in zip(ras_bs, decs_bs):
dist, PA = PAngle(RA, DEC, ra_bs, dec_bs)
PAs.append(PA)
dists.append(dist)
info_bs = zip(ras_bs, decs_bs, mags_bs, dists, PAs)
info_bs.sort(key = lambda tup: tup[3])
info_bs = info_bs[1:]
letters = ["A", "B", "C", "D", "E", "F", "G", "H"]
m = 0
y_pos = 0.58
for (ra_bs, dec_bs, mag_bs, dist, PA) in info_bs:
try:
xy_bs = w.wcs_world2pix([[ra_bs, dec_bs]], 1)
except AttributeError:
xy_bs = [w.sky2image(ra_bs, dec_bs)]
if north <> "down":
xy_bs = np.array((xy_bs[0][0], xy_bs[0][1]))*rot_mat
xy_bs = (xy_bs.getA()[0][0], xy_bs.getA()[0][1])
else:
y_bs = xy_bs[0][1]
y_bs = cen_y + (cen_y - y_bs)
xy_bs = (xy_bs[0][0], y_bs)
ax.add_patch(Ellipse(xy = xy_bs, width = 20.0, height = 20.0, angle = 0.0, fill = False, lw = 1, color = font_col))
if m < len(letters):
print letters[m], ra_bs, dec_bs
if invert_east:
text = ax.annotate(letters[m], xy = (xy_bs[0] - 10.0, xy_bs[1] - 10.0) , color = font_col, fontweight = "bold")
#text1 = ax.annotate("%0.2f" % mag_bs, xy = (xy_bs[0] - 20.0, xy_bs[1] - 10.0) , color = "k", fontweight = "light")
else:
text = ax.annotate(letters[m], xy = (xy_bs[0] + 15.0, xy_bs[1] + 15.0) , color = font_col, fontweight = "bold")
#text1 = ax.annotate("%0.2f" % mag_bs, xy = (xy_bs[0] + 30.0, xy_bs[1] + 15.0) , color = "k", fontweight = "light")
text.set_path_effects([path_effects.Stroke(linewidth=3, foreground='black'), path_effects.Normal()])
c_bs = SkyCoord(ra=ra_bs*u.degree, dec=dec_bs*u.degree, frame='icrs')
coord_string_bs = "%02.0f:%02.0f:%06.3f %02.0f:%02.0f:%05.2f" % \
(c_bs.ra.hms[0], c_bs.ra.hms[1], c_bs.ra.hms[2], c_bs.dec.dms[0], np.fabs(c_bs.dec.dms[1]), np.fabs(c_bs.dec.dms[2]))
ROA = PA - 90.0
letter_info = letters[m] + " " + coord_string_bs + " %04.2f %06.2f %06.2f" % (mag_bs, PA, ROA)
ax1.text(0.01, y_pos, letter_info, family = "monospace")
m += 1
y_pos -= 0.08
if invert_east:
ax.invert_xaxis()
ax.set_title(filename + " " + tile)
plotid.plotid()
name = " - VDES%02.0f%02.0f%02.0f%02.0f" % (c.ra.hms[0], c.ra.hms[1], c.dec.dms[0], np.fabs(c.dec.dms[1]))
fig.suptitle(id + name, fontweight = "bold")
#plt.show()
if invert_east:
out_name = outdir + "Finding_Chart_" + str(id) + "_" + band + "_%02.0f_WE.pdf" % width
else:
out_name = outdir + "Finding_Chart_" + str(id) + "_" + band + "_%02.0f_EW.pdf" % width
plt.savefig(out_name, dpi = 300)
plt.close()
def cutout_scale(im, num_min = 2.0, num_max = 5.0):
"""
Takes an image array and returns the vmin and vmax required to scale the image
between median + 5 * sigma MAD and median - 2 * sigma MAD
"""
import numpy as np
data = im.flatten()
try:
med = np.median(data[data <> 0.0])
sigma_MAD = 1.4826 *MAD(data[data <> 0.0], med)
except IndexError:
med = 0.0
sigma_MAD = 0.0
vmax = med + num_max * sigma_MAD
vmin = med - num_min * sigma_MAD
return vmin, vmax
def cutout_WISE(outdir, RA, DEC, id1, save = False, width = 30.0, small = False, release = "WISE_Images", verbose = True, return_val = False):
"""
Makes cutouts from the WISE images stored here.
If the image doesn't exist downloads it.
Width is the full width of the cutout and is in arcsecs
Small removes the title and reduces the white space around the plot
Missing data is given as a blank cutout
"""
import atpy
import numpy as np
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import os
import subprocess
import astropy.io.fits as fits
t = atpy.Table("/data/rgm/wise/wise_allwise_metadata_thin.fits")
id = np.where( (RA < t["ra1"]) & (RA < t["ra4"]) & (RA > t["ra2"]) & (RA > t["ra3"]) & (DEC < t["dec3"]) & (DEC < t["dec4"]) & (DEC > t["dec2"]) & (DEC > t["dec1"]) )[0]
datas = []
n = 0
while n < len(t):
ras = sorted([t["ra1"][n], t["ra2"][n], t["ra3"][n], t["ra4"][n]])
decs = sorted([t["dec1"][n], t["dec2"][n], t["dec3"][n], t["dec4"][n]])
min_ra = ras[1]
max_ra = ras[2]
min_dec = decs[1]
max_dec = decs[2]
if max_ra > min_ra + 10.0:
min_ra, max_ra = max_ra, min_ra
if DEC > min_dec and DEC < max_dec and RA > min_ra and RA < max_ra:
tile_id_unWISE = t["coadd_id"][n][0:8]
f2 = tile_id_unWISE[0:3]
wise_dir = "/data/wiseardata/" + release + "/p3am_cdd/" + f2 + "/" + tile_id_unWISE + "/"
if verbose:
print wise_dir
n += 1
if len(id) > 0:
tile_id = t["coadd_id"][id[0]][0:13]
f1 = tile_id[0:2]
f2 = tile_id[0:4]
bands = ["w1", "w2", "w3", "w4"]
fig = plt.figure()
gs = gridspec.GridSpec(1,4)
s = 0
for band in bands:
filename = "/data/wiseardata/" + release + "/p3am_cdd/" + f1 + "/" + f2 + "/" + tile_id + "/" + tile_id + "-" + band + "-int-3.fits.gz"
nhdu = 0
if release == "unWISE":
filename = wise_dir + "unwise-" + tile_id_unWISE + "-" + band + "-img-m.fits"
nhdu = 1
ax = fig.add_subplot(gs[0,s])
for i in ax.spines.itervalues():
i.set_linewidth(3.0)
if not os.path.exists(filename) and os.path.exists(filename + ".fz"):
filename = filename + ".fz"
if not os.path.exists(filename):
print "Downloading....", filename
subprocess.call(["bash", "/home/sr525/bash_scripts/wise_tile_get.bash", filename])
try:
with fits.open(filename) as h:
if verbose:
print filename
hdulist, im_status = make_cutout(h, RA, DEC, width, nhdu = nhdu)
im = hdulist[1].data
vmin, vmax = cutout_scale(im)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.imshow(im, vmax = vmax, vmin = vmin, interpolation = "none")
datas.append((im, vmin, vmax))
ax.set_title(band)
except IOError as e:
#print e
null_image = np.zeros(shape = (10,10), dtype = "int8")
ax.imshow(null_image)
ax.annotate("No data", xy = (0.01,0.9), size = "small")
datas.append((np.zeros(29, 29), 0, 1))
s += 1
if not small: plt.suptitle(id)
else:
fig = plt.figure()
null_image = np.zeros(shape = (10,10), dtype = "int8")
plt.imshow(null_image)
plt.annotate("No data", xy = (0.01,0.9), size = "small")
if small:
fig.subplots_adjust(wspace = 0.00, left = 0.05, right = 0.95, top = 1.0, bottom = 0.0, hspace = 0.0)
fig = plt.gcf()
fig.set_size_inches(6.7,2.0)
fig.patch.set_facecolor("none")
if return_val:
plt.close(fig)
return datas
if save:
plt.savefig(outdir + "/Cutouts_WISE_" + str(id1) + ".png", transparent = True)
plt.close()
else: return fig
def cutout_HST(outdir, RA, DEC, id, save = True, sigma = 0, width = 30.0, type = "png", return_data = False):
"""
Makes cutouts from the HST image of the COSMOS field
Width is the full width and needs to be given in arcsecs
Can return a fits file or a png
Can also return just the array used to make the image and the scaling parameters
sigma applies a gaussian filter
"""
import astropy.io.fits as fits
from astropy import wcs
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter
datas = []
with open("/data/desardata/COSMOS/acs_mosaic_2.0/tiles/corners.txt", "r") as f:
for line in f:
l = line.split(",")
ra_min = float(l[0])
ra_max = float(l[2])
dec_min = float(l[1])
dec_max = float(l[3])
filename = l[4]
if RA < ra_min and RA > ra_max and DEC > dec_min and DEC < dec_max:
print filename
with fits.open(filename[:-1]) as h:
hdulist, im_status = make_cutout(h, RA, DEC, width, nhdu = 0)
im = hdulist[1].data
vmin, vmax = cutout_scale(im)
if sigma > 0:
im = gaussian_filter(im, sigma)
if type == "fits":
hdulist.writeto(outdir + "/" + id + "_HST_" + band + ".fits")
fig = plt.figure()
ax = fig.add_subplot(111)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.imshow(im, vmax = vmax, vmin = vmin)
ax.set_title(id)
if return_data:
datas.append((im, vmin, vmax))
fig = plt.gcf()
fig.set_size_inches(2.5,2.5)
if save:
plt.savefig(outdir + "/Cutouts_HST_" + str(id) + ".png", transparent = True)
if return_data:
return datas
else:
return fig
def DES_Y2_cutout(RA, DEC, id, outdir, width = 30.0, save = False, cmap = False, crosshairs = False, bands = ["g", "r", "i", "z", "Y"], vmin_scale = False, vmax_scale = False, verbose = True, fits_out = False):
"""
Makes cutouts from the DES Y2 single epoch images
Can specify the cmap with cmap = whatever you want
If vmin_scale and vmax_scale are not set it scales image between median +
5*sigma MAD and median -2 * sigma MAD else uses median - vmin_scale *
sigma MAD and median + 5 * sigma MAD
crosshairs = True draws cross hairs and a N and E arrow
"""
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import os
import numpy as np
import DES_utils
import astropy.io.fits as fits
import gc
import wcsutil
files, out_bands = DES_utils.DES_Y2_image_file(RA, DEC, bands = bands)
if len(files) >= 20:
files = files[:20]
out_bands = out_bands[:20]
fig = plt.figure()
print len(files)
if len(files) < 5:
gs = gridspec.GridSpec(1,len(files))
else:
x = int(np.ceil(len(files)/5.0))
gs = gridspec.GridSpec(x,5)
n = 0
m = 0
c = 0
for file in files:
ax = fig.add_subplot(gs[m, n])
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
for i in ax.spines.itervalues():
i.set_linewidth(3.0)
if os.path.exists(file):
if verbose: print file
try:
with fits.open(file) as h:
hdulist, im_status = make_cutout(h, RA, DEC, width, nhdu = 0, w_units = "arcsecs")
try:
hdr = hdulist[1].header
image = hdulist[1].data
except (ValueError, TypeError):
image = np.zeros((60,60))
#image = hdulist[1].data
#hdr = hdulist[1].header
except IOError:
image = np.zeros((10,10))
data = image.flatten()
med = np.median(data)
sigma_MAD = 1.4826 * MAD(data, med)
if not vmax_scale:
vmax = med + 5.0*sigma_MAD
else:
vmax = med + vmax_scale*sigma_MAD
if not vmin_scale:
vmin = med - 2.0*sigma_MAD
else:
vmin = med - vmin_scale*sigma_MAD
if vmax == vmin:
vmax = np.max(data)
vmin = np.min(data)
if fits_out and hdulist is not None:
hdulist.writeto(outdir + "/" + str(id) + "_" + out_bands[c] + ".fits", clobber = True)
if cmap:
ax.imshow(image, vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest", cmap = cmap)
else:
ax.imshow(image, vmin = vmin, vmax = vmax, picker = True, interpolation = "nearest")
if crosshairs and hdulist is not None:
try:
from astropy import wcs
w = wcs.WCS(hdr, naxis = 2)
except (UnboundLocalError, wcs.wcs.InconsistentAxisTypesError) as e:
try:
w = wcsutil.WCS(hdr)
except KeyError:
hdr = h[nhdu-1].header
w = wcsutil.WCS(hdr)
ax = draw_crosshairs(ax, w, RA, DEC)
ax.set_title(out_bands[c])
gc.collect()
gc.collect()
gc.collect()
if len(files) > 5 and (n+1) % 5 == 0:
n = 0
m += 1
else:
n += 1
c += 1
if save:
plt.savefig(outdir + "DESY2N_cutout_" + str(id) + ".png")
else:
return fig
def HST_DES_i(outdir, RA, DEC, tile, run, id, width = 30.0, save = False, release = "SVA1"):
"""
Makes an i band cutout from DES and HST scaled to not saturate in the middle
Written for Gourav's webpage things
"""
import matplotlib.pyplot as plt
HST_im = cutout_HST(outdir, RA, DEC, id, save = False, sigma = 0, width = width, return_val = "data")
DES_im = cutout_image(outdir, RA, DEC, tile, run, id, save = False, width = width, field = release, bands = ["i"], return_val = "data")
DES_im1 = cutout_image(outdir, RA, DEC, tile, run, id, save = False, width = width, field = release, bands = ["i"], return_val = "data", vmin_num = -2.0, vmax_num = 50.0)
plt.close()
plt.close()
plt.close()
fig = plt.figure()
ax1 = fig.add_subplot(131)
ax2 = fig.add_subplot(132)
ax3 = fig.add_subplot(133)
ax1.imshow(HST_im[0][0], vmin = HST_im[0][1], vmax = HST_im[0][2])
ax2.imshow(DES_im[0][0], vmin = DES_im[0][1], vmax = DES_im[0][2])
ax3.imshow(DES_im1[0][0], vmin = DES_im1[0][1], vmax = DES_im1[0][2])
for axis in [ax1, ax2, ax3]:
axis.axes.get_xaxis().set_visible(False)
axis.axes.get_yaxis().set_visible(False)
for i in axis.spines.itervalues():
i.set_linewidth(3.0)
fig.subplots_adjust(wspace = 0.00, left = 0.02, right = 0.98, top = 0.98, bottom = 0.02, hspace = 0.0)
if save:
plt.savefig(outdir + "HST_DES_i_" + id + ".png")
plt.close()
else: plt.show()
def composite(outdir, RA, DEC, tile, run, id, width = 30.0, save = False, field = "SVA1"):
"""
Creates two compostites from the DES images, gri and izY
"""
import os
import numpy as np
import matplotlib.pyplot as plt
import img_scale
ims = []
sfs = [1.0, 1.0, 1.0, 1.0, 0.9]
for (i,band) in enumerate(["g", "r", "i", "z", "Y"]):
filename = "/data/desardata/" + field + "/" + tile + "/" + tile + "_" + band + ".fits.fz"
if not os.path.exists(filename):
subprocess.call(["bash", "/home/sr525/bash_scripts/wget_ims.bash", tile, str(run), field])
hdulist, im_status = make_cutout(filename, RA, DEC, width, nhdu = 1)
im = hdulist[1].data
ims.append(im*sfs[i])
smax, smin = img_scale.MAD(ims[0:3], 30, -10)
img_blue = np.zeros((ims[2].shape[0], ims[2].shape[1], 3), dtype=float)
j = 0
for i in [2,1,0]:
img_blue[:,:,j] = img_scale.linear(ims[i], scale_min = smin, scale_max = smax)
gc.collect()
gc.collect()
j += 1
smax, smin = img_scale.MAD(ims[2:], 5, -10)
img_red = np.zeros((ims[2].shape[0], ims[2].shape[1], 3), dtype=float)
j = 0
for i in [4,3,2]:
img_red[:,:,j] = img_scale.linear(ims[i], scale_min = smin, scale_max = smax)
j += 1
figs = []
j = 0
for im in [img_blue, img_red]:
fig = plt.figure()
ax = fig.add_subplot(111)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
for i in ax.spines.itervalues():
i.set_linewidth(3.0)
ax.imshow(im, aspect = "equal")
figs.append(fig)
if not save:
plt.show()
if save:
if j == 0:
plt.title("gri")
fig.savefig(outdir + "Composite_gri_" + id + ".png")
elif j == 1:
plt.title("izY")
fig.savefig(outdir + "Composite_izY_" + id + ".png")
def cutout_Spitzer(outdir, RA, DEC, id, save = False, width = 30.0):
"""
Makes a cutout from the COSMOS spitzer image