In [1]:
import glob
fns = glob.glob('data/2012-06-22/Dark/*.CR2')
In [2]:
import dark
reload(dark)
bad_pixels = dark.find_badpixels(fns);
Working on image: data/2012-06-22/Dark/IMG_1421.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2533
Working on image: data/2012-06-22/Dark/IMG_1422.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 44.0
StDev: 65.233506301
Number of 8-sigma outliers: 2732
Working on image: data/2012-06-22/Dark/IMG_1423.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2501
Working on image: data/2012-06-22/Dark/IMG_1424.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2497
Working on image: data/2012-06-22/Dark/IMG_1425.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2533
Working on image: data/2012-06-22/Dark/IMG_1426.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2455
Working on image: data/2012-06-22/Dark/IMG_1427.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2523
Working on image: data/2012-06-22/Dark/IMG_1428.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2452
Working on image: data/2012-06-22/Dark/IMG_1429.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2613
Working on image: data/2012-06-22/Dark/IMG_1430.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2543
Working on image: data/2012-06-22/Dark/IMG_1431.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2554
Working on image: data/2012-06-22/Dark/IMG_1432.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2449
Working on image: data/2012-06-22/Dark/IMG_1433.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2411
Working on image: data/2012-06-22/Dark/IMG_1434.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2457
Working on image: data/2012-06-22/Dark/IMG_1435.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2367
Working on image: data/2012-06-22/Dark/IMG_1436.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2480
Working on image: data/2012-06-22/Dark/IMG_1437.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2450
Working on image: data/2012-06-22/Dark/IMG_1438.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2514
Working on image: data/2012-06-22/Dark/IMG_1439.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2535
Working on image: data/2012-06-22/Dark/IMG_1440.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2465
Working on image: data/2012-06-22/Dark/IMG_1441.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2454
Working on image: data/2012-06-22/Dark/IMG_1442.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2417
Working on image: data/2012-06-22/Dark/IMG_1443.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2367
Working on image: data/2012-06-22/Dark/IMG_1444.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2521
Working on image: data/2012-06-22/Dark/IMG_1445.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2531
Working on image: data/2012-06-22/Dark/IMG_1446.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2522
Working on image: data/2012-06-22/Dark/IMG_1447.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2454
Working on image: data/2012-06-22/Dark/IMG_1448.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2589
Working on image: data/2012-06-22/Dark/IMG_1449.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2395
Working on image: data/2012-06-22/Dark/IMG_1450.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2497
Working on image: data/2012-06-22/Dark/IMG_1451.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2471
Working on image: data/2012-06-22/Dark/IMG_1452.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 44.0
StDev: 65.233506301
Number of 8-sigma outliers: 2812
Working on image: data/2012-06-22/Dark/IMG_1453.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2513
Working on image: data/2012-06-22/Dark/IMG_1454.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2532
Working on image: data/2012-06-22/Dark/IMG_1455.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2450
Working on image: data/2012-06-22/Dark/IMG_1456.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2493
Working on image: data/2012-06-22/Dark/IMG_1457.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2508
Working on image: data/2012-06-22/Dark/IMG_1458.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2048.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2491
Working on image: data/2012-06-22/Dark/IMG_1459.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2456
Working on image: data/2012-06-22/Dark/IMG_1460.CR2
Image size: 18024930
Image shape: (3465, 5202)
Median: 2049.0
MAD: 45.0
StDev: 66.7160859896
Number of 8-sigma outliers: 2483
Bad pixels
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In [4]:
reload(dark)
dark_img = dark.make_dark(fns, bad_pixels)
ideep: 0
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medianing
layer medianing
In [10]:
clf()
imshow(dark_img, origin='upper', vmin=2049-66.7*2, vmax=2049+66.7*2)
colorbar()
Out[10]:
<matplotlib.colorbar.Colorbar instance at 0x119191c68>
In [9]:
clf()
hist(dark_img.flatten(), arange(1500, 2500, 10));
In [11]:
import biweight
print biweight.biweight_scale(dark_img)
6.3200531713
In [12]:
dark_img.std()
Out[12]:
35.18980764704186
In [38]:
import astropy.io.fits as fits
fits.writeto('dark.fits', dark_img.astype(numpy.int16), clobber=True)
WARNING:astropy:Overwriting existing file 'dark.fits'.
WARNING: Overwriting existing file 'dark.fits'. [astropy.io.fits.hdu.hdulist]
In [ ]:
Content source: jmeyers314/astrophotoreduce
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