I decided to create a library from the codes that I use for myself. I hope it will be useful for you too.
And here are our dependencies for this library:
- Structure of Module
- Introduction
- Detecting Sources
- Plot detected sources
- Query and match detected objects with the GAIA DR1
- Matching with GAIA DR1
- Astrometry with IRAF's ccmap
- Solve field with astrometry.net
- Plot Asteroids
- Plot Asteroids without a FITS File
- FITS Data Reduction with ccdproc
- Photometry of an asteroid
astrolib | |----> astronomy.py | |----> catalog.py | |----> io.py | |----> visuals.py | |----> photometry.py For detailed information and help give help(module_name) command in the command line.
Here I created help documentation for the commands I use the frequently. You can work the same way for others. You can find detailed help in the code.
%load_ext autoreload
%autoreload 2
from astrolib import astronomy
fo = astronomy.FitsOps("108hecuba-001_R_affineremap.fits")
ds= fo.detect_sources(max_sources=10)
print(ds)The autoreload extension is already loaded. To reload it, use:
%reload_ext autoreload
10 objects detected.
thresh npix tnpix xmin xmax ... ypeak flag ra_calc dec_calc
------------- ---- ----- ---- ---- ... ----- ---- ------------- --------------
19.1716499329 514 482 770 798 ... 709 0 306.771497336 -23.4704661458
19.1716499329 406 375 491 512 ... 328 0 306.824877954 -23.396690687
19.1716499329 288 275 254 274 ... 447 1 306.874213526 -23.4164391737
19.1716499329 277 256 424 442 ... 380 0 306.839362608 -23.405562815
19.1716499329 198 181 424 440 ... 906 0 306.845308447 -23.5039523172
19.1716499329 194 176 979 994 ... 732 0 306.73060855 -23.4768569137
19.1716499329 191 179 421 436 ... 502 0 306.841689712 -23.4283372785
19.1716499329 186 172 748 763 ... 535 0 306.775505562 -23.4377531371
19.1716499329 217 195 968 983 ... 851 0 306.734126873 -23.4989537639
19.1716499329 146 133 304 317 ... 898 0 306.869815661 -23.5011624192
If you just want to get physical coordinates of sources;
print(ds['x', 'y']) x y
------------- -------------
784.445069846 708.599934474
501.969623282 328.856251826
265.640606005 447.07089538
433.446658084 379.95420757
432.153302841 906.369369574
986.64280869 732.173102742
428.481743905 502.05257089
755.619674466 535.11980348
975.565085076 850.958300649
311.27460779 897.879261611
If you want to plot detected objects on the FITS file;
fo.detect_sources(plot=True, max_sources=10)
10 objects detected.
<Table length=10>
| thresh | npix | tnpix | xmin | xmax | ymin | ymax | x | y | x2 | y2 | xy | errx2 | erry2 | errxy | a | b | theta | cxx | cyy | cxy | cflux | flux | cpeak | peak | xcpeak | ycpeak | xpeak | ypeak | flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| float64 | int64 | int64 | int64 | int64 | int64 | int64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | int64 | int64 | int64 | int64 | int64 |
| 19.1716499329 | 514 | 482 | 770 | 798 | 696 | 721 | 784.445069846 | 708.599934474 | 7.13037778034 | 7.14998870343 | -0.212358140872 | 7.09243459217e-06 | 6.17207043114e-06 | -1.98509663699e-07 | 2.71159863472 | 2.63203310966 | -0.808468878269 | 0.140369191766 | 0.139984190464 | 0.00833806581795 | 723850.0 | 724231.8125 | 17705.0605469 | 18033.3535156 | 785 | 709 | 784 | 709 | 0 |
| 19.1716499329 | 406 | 375 | 491 | 512 | 318 | 340 | 501.969623282 | 328.856251826 | 6.85129620045 | 6.80527345789 | -0.232098936969 | 1.135928646e-05 | 1.08330602851e-05 | 1.04181566067e-06 | 2.65735244751 | 2.56808257103 | -0.735987305641 | 0.146126613021 | 0.14711484313 | 0.00996751524508 | 443818.09375 | 444089.75 | 13129.0449219 | 14977.5058594 | 502 | 329 | 502 | 328 | 0 |
| 19.1716499329 | 288 | 275 | 254 | 274 | 438 | 457 | 265.640606005 | 447.07089538 | 6.23960234427 | 6.07421432435 | -0.279671671578 | 3.41360150936e-05 | 3.11016713517e-05 | -2.11652827665e-06 | 2.53939938545 | 2.4218313694 | -0.641652643681 | 0.160598054528 | 0.164970800281 | 0.0147886537015 | 185113.59375 | 185279.53125 | 6102.23291016 | 7160.66992188 | 266 | 447 | 266 | 447 | 1 |
| 19.1716499329 | 277 | 256 | 424 | 442 | 371 | 389 | 433.446658084 | 379.95420757 | 6.35316222658 | 6.31800704473 | -0.299843333379 | 4.85704037652e-05 | 4.50648124042e-05 | -1.72250253383e-06 | 2.57603240013 | 2.45666980743 | -0.756120383739 | 0.157755285501 | 0.158633068204 | 0.0149736674502 | 146899.203125 | 147146.46875 | 4537.37988281 | 5280.50488281 | 434 | 380 | 434 | 380 | 0 |
| 19.1716499329 | 198 | 181 | 424 | 440 | 899 | 914 | 432.153302841 | 906.369369574 | 5.90303042003 | 5.47633612435 | -0.184753256665 | 0.000164622405043 | 0.000146496989951 | -3.67874889536e-06 | 2.44374871254 | 2.32539439201 | -0.356847733259 | 0.169583573937 | 0.182796850801 | 0.0114423651248 | 57640.0429688 | 57828.2695312 | 1876.25524902 | 2155.50537109 | 432 | 906 | 432 | 906 | 0 |
| 19.1716499329 | 194 | 176 | 979 | 994 | 725 | 740 | 986.64280869 | 732.173102742 | 5.8286040971 | 5.77761345379 | -0.123682777674 | 0.000149828861925 | 0.000146736762267 | -1.92272602728e-06 | 2.43503427505 | 2.38260889053 | -0.683754503727 | 0.171645641327 | 0.173160508275 | 0.00734891975299 | 57640.6875 | 57787.3632812 | 1833.14978027 | 2154.9621582 | 987 | 732 | 987 | 732 | 0 |
| 19.1716499329 | 191 | 179 | 421 | 436 | 494 | 509 | 428.481743905 | 502.05257089 | 5.73049328878 | 5.83927472126 | -0.08271646368 | 0.000185882394818 | 0.000196906906581 | 6.81651164286e-06 | 2.42567110062 | 2.38450980186 | -1.07623255253 | 0.174540728331 | 0.171289175749 | 0.00494492659345 | 49968.703125 | 50177.390625 | 1583.44250488 | 1840.37927246 | 429 | 502 | 429 | 502 | 0 |
| 19.1716499329 | 186 | 172 | 748 | 763 | 528 | 543 | 755.619674466 | 535.11980348 | 5.84952315959 | 5.86444076657 | -0.302552966408 | 0.000190548947294 | 0.000193111256106 | -1.3837525619e-05 | 2.48185944557 | 2.35676407814 | -0.797722101212 | 0.171411499381 | 0.170975476503 | 0.0176866166294 | 48653.1601562 | 48840.03125 | 1514.21801758 | 1737.78015137 | 756 | 535 | 756 | 535 | 0 |
| 19.1716499329 | 217 | 195 | 968 | 983 | 837 | 859 | 975.565085076 | 850.958300649 | 5.45041439198 | 8.61544221634 | -0.369553518093 | 0.000244768135719 | 0.000640536321842 | -2.73328688175e-05 | 2.94245123863 | 2.32547569275 | -1.45609033108 | 0.184007450938 | 0.116409212351 | 0.015785748139 | 41191.078125 | 41409.0390625 | 1270.40551758 | 1463.90539551 | 976 | 851 | 976 | 851 | 0 |
| 19.1716499329 | 146 | 133 | 304 | 317 | 891 | 904 | 311.27460779 | 897.879261611 | 4.95460770899 | 5.00588141734 | -0.189383535264 | 0.000252084341226 | 0.000276073972364 | -1.24180158269e-05 | 2.27406144142 | 2.18840885162 | -0.852674245834 | 0.202124610543 | 0.200054317713 | 0.0152936400846 | 32531.5585938 | 32735.9355469 | 1089.45288086 | 1271.76538086 | 311 | 898 | 311 | 898 | 0 |
from astrolib import catalog
q = catalog.Query()
q.gaia_query(306.77168051, -23.47029011, 0.1, max_sources=5)<Table masked=True length=5>
| Source | RA_ICRS | DE_ICRS | e_RA_ICRS | e_DE_ICRS | __Gmag_ | pmRA | pmDE | e_pmRA | e_pmDE | Epoch | Plx |
|---|---|---|---|---|---|---|---|---|---|---|---|
| deg | deg | mas | mas | mag | mas / yr | mas / yr | mas / yr | mas / yr | yr | mas | |
| int64 | float64 | float64 | float32 | float32 | float32 | float64 | float64 | float32 | float32 | float32 | float32 |
| 6849534850623923456 | 306.7733664604 | -23.5149644759 | 0.262 | 0.221 | 17.121 | -- | -- | -- | -- | 2015.0 | -- |
| 6849534850623925120 | 306.7712467689 | -23.5125792734 | 0.870 | 0.749 | 19.499 | -- | -- | -- | -- | 2015.0 | -- |
| 6849534988062874624 | 306.7217934709 | -23.5187662526 | 0.690 | 0.589 | 19.120 | -- | -- | -- | -- | 2015.0 | -- |
| 6849534988062875264 | 306.7263979238 | -23.5181699239 | 0.325 | 0.264 | 17.535 | -- | -- | -- | -- | 2015.0 | -- |
| 6849535056782354560 | 306.7183059223 | -23.5126694863 | 0.196 | 0.133 | 17.308 | -- | -- | -- | -- | 2015.0 | -- |
If you just want to query the target object, reduce the radius like;
from astrolib import catalog
q = catalog.Query()
q.gaia_query(306.77168051, -23.47029011, 0.01, max_sources=5)<Table masked=True length=1>
| Source | RA_ICRS | DE_ICRS | e_RA_ICRS | e_DE_ICRS | __Gmag_ | pmRA | pmDE | e_pmRA | e_pmDE | Epoch | Plx |
|---|---|---|---|---|---|---|---|---|---|---|---|
| deg | deg | mas | mas | mag | mas / yr | mas / yr | mas / yr | mas / yr | yr | mas | |
| int64 | float64 | float64 | float32 | float32 | float32 | float64 | float64 | float32 | float32 | float32 | float32 |
| 6849629099386034304 | 306.7717090460 | -23.4702787742 | 0.216 | 0.126 | 9.603 | 8.059 | 4.816 | 0.910 | 0.619 | 2015.0 | 3.17 |
q.match_catalog("108hecuba-001_R_affineremap.fits", plot=True, max_sources=10)10 objects detected.
/usr/local/lib/python3.6/site-packages/numpy/core/numeric.py:531: UserWarning: Warning: converting a masked element to nan.
return array(a, dtype, copy=False, order=order)
Matched objects: 9
<Table length=9>
| id | x | y | ra | dec | e_ra | e_dec | g_mean_mag | pmra | pmdec | e_pmra | e_pmdec | epoch | plx | flux | a | b | theta | ra_calc | dec_calc | ra_diff | dec_diff |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 | float64 |
| 6.84962909939e+18 | 784.445069846 | 708.599934474 | 306.771709046 | -23.4702787742 | 0.216000005603 | 0.126000002027 | 9.60299968719 | 8.059 | 4.816 | 0.910000026226 | 0.619000017643 | 2015.0 | 3.17000007629 | 724231.8125 | 2.71159863472 | 2.63203310966 | -0.808468878269 | 306.771497336 | -23.4704661458 | 762.154325162 | 674.53790621 |
| 6.84964298072e+18 | 501.969623282 | 328.856251826 | 306.825119424 | -23.3966105431 | 0.155000001192 | 0.0960000008345 | 10.1719999313 | nan | nan | nan | nan | 2015.0 | nan | 444089.75 | 2.65735244751 | 2.56808257103 | -0.735987305641 | 306.824877954 | -23.396690687 | 869.293691494 | 288.518125998 |
| 6.84963092045e+18 | 265.640606005 | 447.07089538 | 306.874457724 | -23.4164026349 | 0.34999999404 | 0.171000003815 | 11.0909996033 | 19.918 | -7.057 | 1.93099999428 | 1.28299999237 | 2015.0 | 3.65000009537 | 185279.53125 | 2.53939938545 | 2.4218313694 | -0.641652643681 | 306.874213526 | -23.4164391737 | 879.11293615 | 131.539743526 |
| 6.84963122969e+18 | 433.446658084 | 379.95420757 | 306.839605839 | -23.4054917128 | 0.195999994874 | 0.140000000596 | 11.3380002975 | -1.037 | -1.896 | 1.43299996853 | 0.952000021935 | 2015.0 | 0.579999983311 | 147146.46875 | 2.57603240013 | 2.45666980743 | -0.756120383739 | 306.839362608 | -23.405562815 | 875.629978918 | 255.967955209 |
| 6.84962782808e+18 | 432.153302841 | 906.369369574 | 306.845545923 | -23.5038156954 | 0.231999993324 | 0.163000002503 | 12.3310003281 | -6.099 | -11.584 | 1.67200005054 | 1.0909999609 | 2015.0 | 1.14999997616 | 57828.2695312 | 2.44374871254 | 2.32539439201 | -0.356847733259 | 306.845308447 | -23.5039523172 | 854.913985108 | 491.838601999 |
| 6.84954694525e+18 | 986.64280869 | 732.173102742 | 306.730808533 | -23.4766263796 | 0.152999997139 | 0.119999997318 | 12.3090000153 | nan | nan | nan | nan | 2015.0 | nan | 57787.3632812 | 2.43503427505 | 2.38260889053 | -0.683754503727 | 306.73060855 | -23.4768569137 | 719.935376696 | 829.922643453 |
| 6.8496409535e+18 | 755.619674466 | 535.11980348 | 306.775712653 | -23.4375940654 | 0.097000002861 | 0.0750000029802 | 12.5030002594 | nan | nan | nan | nan | 2015.0 | nan | 48840.03125 | 2.48185944557 | 2.35676407814 | -0.797722101212 | 306.775505562 | -23.4377531371 | 745.527969957 | 572.658003705 |
| 6.84953515986e+18 | 975.565085076 | 850.958300649 | 306.734327716 | -23.4987547309 | 0.104999996722 | 0.082000002265 | 12.7259998322 | nan | nan | nan | nan | 2015.0 | nan | 41409.0390625 | 2.94245123863 | 2.32547569275 | -1.45609033108 | 306.734126873 | -23.4989537639 | 723.032314954 | 716.51890772 |
| 6.84962820603e+18 | 311.27460779 | 897.879261611 | 306.870049861 | -23.5010591944 | 0.109999999404 | 0.0729999989271 | 12.875 | nan | nan | nan | nan | 2015.0 | nan | 32735.9355469 | 2.27406144142 | 2.18840885162 | -0.852674245834 | 306.869815661 | -23.5011624192 | 843.118385296 | 371.609451281 |
First of all we need a FITS file that has been resolved with astrometry.net (For example: 108hecuba-001_R_affineremap.fits). Then our code will map the resources found here to the GAIA catalog and again perform astrometry with these coordinates via ccmap.
from astrolib import catalog
from astrolib import astronomy
q = catalog.Query()
# Resolved image with Astrometry.net (108hecuba-001_R_affineremap.fits).
objects_matrix = q.match_catalog("108hecuba-001_R_affineremap.fits", max_sources=20)
ac = astronomy.AstCalc()
# Image with no WCS header keywords (108hecuba-001_R.fits).
ac.ccmap(objects_matrix, "./108hecuba-001_R.fits", ppm_parallax_cor=False)20 objects detected.
Matched objects: 19
Refsystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Insystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Coords File: /Users/ykilic/Documents/playground/coords Image: ./108hecuba-001_R.fits
Database: /Users/ykilic/Documents/playground/solutions.txt Solution: ./108hecuba-001_R.fits
Coordinate mapping status
XI fit ok. ETA fit ok.
Ra/Dec or Long/Lat fit rms: 0.038 0.0485 (arcsec arcsec)
Coordinate mapping parameters
Sky projection geometry: tan
Reference point: 20:27:17.965 -23:27:09.36 (hours degrees)
Reference point: 519.031 627.677 (pixels pixels)
X and Y scale: 0.673 0.673 (arcsec/pixel arcsec/pixel)
X and Y axis rotation: 177.025 176.983 (degrees degrees)
Wcs mapping status
Ra/Dec or Long/Lat wcs rms: 0.038 0.0485 (arcsec arcsec)
Updating image header wcs
<Table length=3>
| Ra/Dec or Long/Lat fit rms | Ra/Dec or Long/Lat wcs rms | Reference point (RA, DEC) | Reference point (X, Y) | X and Y scale | X and Y axis rotation |
|---|---|---|---|---|---|
| str16 | str16 | str16 | str16 | str28 | str18 |
| 0.038 | 0.038 | 20:27:17.965 | 519.031 | 0.673 | 177.025 |
| 0.0485 | 0.0485 | -23:27:09.36 | 627.677 | 0.673 | 176.983 |
| (arcsec arcsec) | (arcsec arcsec) | (hours degrees) | (pixels pixels) | (arcsec/pixel arcsec/pixel) | (degrees degrees) |
You can see the results coordinates with;
ac.ccmap(objects_matrix, "./108hecuba-001_R.fits", ppm_parallax_cor=False, stdout=True)Refsystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Insystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Coords File: /Users/ykilic/Documents/playground/coords Image: ./108hecuba-001_R.fits
Database: /Users/ykilic/Documents/playground/solutions.txt Solution: ./108hecuba-001_R.fits
Coordinate mapping status
XI fit ok. ETA fit ok.
Ra/Dec or Long/Lat fit rms: 0.038 0.0485 (arcsec arcsec)
Coordinate mapping parameters
Sky projection geometry: tan
Reference point: 20:27:17.965 -23:27:09.36 (hours degrees)
Reference point: 519.031 627.677 (pixels pixels)
X and Y scale: 0.673 0.673 (arcsec/pixel arcsec/pixel)
X and Y axis rotation: 177.025 176.983 (degrees degrees)
Wcs mapping status
Ra/Dec or Long/Lat wcs rms: 0.038 0.0485 (arcsec arcsec)
Updating image header wcs
# Refsystem: icrs Coordinates: equatorial ICRS
# Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
# Insystem: icrs Coordinates: equatorial ICRS
# Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
# Coords File: /Users/ykilic/Documents/playground/coords Image: ./108hecuba-001_R.fits
# Database: /Users/ykilic/Documents/playground/solutions.txt Solution: ./108hecuba-001_R.fits
# Coordinate mapping status
# XI fit ok. ETA fit ok.
# Ra/Dec or Long/Lat fit rms: 0.038 0.0485 (arcsec arcsec)
# Coordinate mapping parameters
# Sky projection geometry: tan
# Reference point: 20:27:17.965 -23:27:09.36 (hours degrees)
# Reference point: 519.031 627.677 (pixels pixels)
# X and Y scale: 0.673 0.673 (arcsec/pixel arcsec/pixel)
# X and Y axis rotation: 177.025 176.983 (degrees degrees)
# Wcs mapping status
# Ra/Dec or Long/Lat wcs rms: 0.038 0.0485 (arcsec arcsec)
# Updating image header wcs
# Input Coordinate Listing
# Column 1: X (pixels)
# Column 2: Y (pixels)
# Column 3: Ra / Longitude (hours)
# Column 4: Dec / Latitude (degrees)
# Column 5: Fitted Ra / Longitude (hours)
# Column 6: Fitted Dec / Latitude (degrees)
# Column 7: Residual Ra / Longitude (arcseconds)
# Column 8: Residual Dec / Latitude (arcseconds)
784.445 708.600 20:27:05.210 -23:28:13.00 20:27:05.210 -23:28:13.02 0.005 0.018
501.970 328.856 20:27:18.029 -23:23:47.80 20:27:18.028 -23:23:47.80 0.005 0.006
265.641 447.071 20:27:29.870 -23:24:59.05 20:27:29.871 -23:24:59.02 -0.014 -0.026
433.447 379.954 20:27:21.505 -23:24:19.77 20:27:21.505 -23:24:19.77 0.005 0.002
432.153 906.369 20:27:22.931 -23:30:13.74 20:27:22.927 -23:30:13.75 0.051 0.013
986.643 732.173 20:26:55.394 -23:28:35.85 20:26:55.394 -23:28:35.87 0.006 0.013
755.620 535.120 20:27:06.171 -23:26:15.34 20:27:06.174 -23:26:15.35 -0.037 0.013
975.565 850.958 20:26:56.239 -23:29:55.52 20:26:56.237 -23:29:55.37 0.022 -0.143
311.275 897.879 20:27:28.812 -23:30:03.81 20:27:28.811 -23:30:03.80 0.017 -0.014
29.622 370.084 20:27:41.190 -23:23:58.91 20:27:41.193 -23:23:58.93 -0.044 0.014
397.766 476.658 20:27:23.496 -23:25:23.58 20:27:23.497 -23:25:23.56 -0.010 -0.017
670.751 693.912 20:27:10.729 -23:27:59.25 20:27:10.725 -23:27:59.20 0.045 -0.052
189.583 760.212 20:27:34.392 -23:28:26.92 20:27:34.398 -23:28:26.94 -0.085 0.020
185.898 512.106 20:27:33.936 -23:25:39.96 20:27:33.933 -23:25:39.95 0.042 -0.009
577.371 579.237 20:27:14.995 -23:26:38.81 20:27:14.991 -23:26:38.82 0.056 0.008
1003.779 979.693 20:26:55.184 -23:31:22.81 20:26:55.186 -23:31:22.93 -0.028 0.111
179.822 591.192 20:27:34.437 -23:26:32.96 20:27:34.435 -23:26:32.92 0.026 -0.031
221.017 307.520 20:27:31.687 -23:23:23.55 20:27:31.687 -23:23:23.61 -0.001 0.051
956.476 867.597 20:26:57.208 -23:30:05.88 20:26:57.212 -23:30:05.91 -0.059 0.023
<Table length=3>
| Ra/Dec or Long/Lat fit rms | Ra/Dec or Long/Lat wcs rms | Reference point (RA, DEC) | Reference point (X, Y) | X and Y scale | X and Y axis rotation |
|---|---|---|---|---|---|
| str16 | str16 | str16 | str16 | str28 | str18 |
| 0.038 | 0.038 | 20:27:17.965 | 519.031 | 0.673 | 177.025 |
| 0.0485 | 0.0485 | -23:27:09.36 | 627.677 | 0.673 | 176.983 |
| (arcsec arcsec) | (arcsec arcsec) | (hours degrees) | (pixels pixels) | (arcsec/pixel arcsec/pixel) | (degrees degrees) |
But this solution does not include parallax and proper motion correction. To include these corrections;
ac.ccmap(objects_matrix, "./108hecuba-001_R.fits", ppm_parallax_cor=True)Refsystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Insystem: icrs Coordinates: equatorial ICRS
Equinox: J2000.000 Epoch: J2000.00000000 MJD: 51544.50000
Coords File: /Users/ykilic/Documents/playground/coords Image: ./108hecuba-001_R.fits
Database: /Users/ykilic/Documents/playground/solutions.txt Solution: ./108hecuba-001_R.fits
Coordinate mapping status
XI fit ok. ETA fit ok.
Ra/Dec or Long/Lat fit rms: 0.0377 0.0486 (arcsec arcsec)
Coordinate mapping parameters
Sky projection geometry: tan
Reference point: 20:27:17.965 -23:27:09.36 (hours degrees)
Reference point: 519.031 627.677 (pixels pixels)
X and Y scale: 0.673 0.673 (arcsec/pixel arcsec/pixel)
X and Y axis rotation: 177.025 176.983 (degrees degrees)
Wcs mapping status
Ra/Dec or Long/Lat wcs rms: 0.0377 0.0486 (arcsec arcsec)
Updating image header wcs
<Table length=3>
| Ra/Dec or Long/Lat fit rms | Ra/Dec or Long/Lat wcs rms | Reference point (RA, DEC) | Reference point (X, Y) | X and Y scale | X and Y axis rotation |
|---|---|---|---|---|---|
| str16 | str16 | str16 | str16 | str28 | str18 |
| 0.0377 | 0.0377 | 20:27:17.965 | 519.031 | 0.673 | 177.025 |
| 0.0486 | 0.0486 | -23:27:09.36 | 627.677 | 0.673 | 176.983 |
| (arcsec arcsec) | (arcsec arcsec) | (hours degrees) | (pixels pixels) | (arcsec/pixel arcsec/pixel) | (degrees degrees) |
Coordinates α and δ of a star in a fixed reference system change with time proportional to its proper motion μα and μδ. Let α0 and δ0 be its position at some time origin; its values at time t are;
μα = μα∗ / cosδ0
α = α0 + tμα
δ = δ0 + tμδ
Deltaα = π (x sin α − y cos α) / cos δ
Deltaδ = π [(x cos α + y sin α) sin δ − z cos δ]
where the coordinates x, y, z of the Earth are expressed in astronomical units and the corrections to the position are in arcseconds.
Ref: Kovalevsky, J., & Seidelmann, P. (2004). Fundamentals of Astrometry. Cambridge: Cambridge University Press. doi:10.1017/CBO9781139106832
from astrolib import astronomy
ac = astronomy.AstCalc()
# Solve field with astrometry.net
# Please provide image path, so ./ is important!
ac.solve_field("./5247_0007_R.fits")Image has been solved!
True
pwd'/Users/ykilic/Documents/playground'
Copy solved image with FITS file extension.
cp -rv 5247_0007_R.new 5247_0007_R_new.fits5247_0007_R.new -> 5247_0007_R_new.fits
You may want to plot asteroids, comets etc. on FITS image. Especially this can be very useful to find the moving objects in asteroid observations. Note that in the header of the FITS file, there must be RA, DEC, and DATE-OBS keywords. This code has made use of IMCCE's SkyBoT VO tool.
from astrolib import visuals
ap = visuals.StarPlot()
# time_travel parameter expresses the observation time in hours.
ap.asteroids_plot("./5247_0007_R_new.fits", time_travel=4)
num name ra(h) dec(deg) class m_v err(arcsec) d(arcsec)
---- ------ ------------- ------------ -------- ---- ----------- ---------
5247 Krylov 20 58 36.6685 +26 02 0.871 MB>Inner 15.3 0.040 159.851
True
Suppose that you do not have a FITS file, but you want to plot asteroids in the field of view (in arcmin) that you want at a particular time in a particular region. Then you should have indicated the coordinates of the region (RA, DEC) and the time of observation you wanted. No that, time_travel parameter expresses the approximate observation time duration in hours.
from astrolib import visuals
ap = visuals.StarPlot()
ap.asteroids_plot(ra="20 11 38.6159",
dec="-07 09 12.734",
odate="2017-08-15T19:50:00.95",
time_travel=4,
radius=21,
max_mag=21)Target Coordinates: 20:11:38.6159 -07:09:12.734 in 21 arcmin
num name ra(h) dec(deg) ... m_v err(arcsec) d(arcsec)
------ ---------- ------------- ------------- ... ---- ----------- ---------
61174 2000 NN22 20 11 37.0007 -07 09 28.118 ... 17.1 0.088 28.541
368990 2007 EA170 20 11 10.5560 -07 09 25.010 ... 20.8 0.041 417.801
84962 2003 YM9 20 12 20.6282 -07 04 58.914 ... 19.2 0.080 674.879
- 2003 UU95 20 11 42.2090 -07 20 33.771 ... 19.1 0.463 683.135
462308 2008 GM89 20 11 47.4887 -07 23 2.466 ... 21.1 0.428 840.175
154028 2002 CV42 20 10 33.0059 -07 15 32.548 ... 19.9 0.063 1047.658
416647 2004 TA96 20 10 40.5785 -07 20 1.355 ... 20.3 0.259 1080.074
490226 2008 VH54 20 10 56.7180 -07 24 32.520 ... 20.8 0.172 1111.152
True
This class provides simple FITS image data reduction with ccdproc. In order to use RedOps() class of my astrolib, you should have special directory tree like this;
dir/
| \
BDF/ SCI_IMAGESNow, you are ready to use RedOps.ccdproc function;
from astrolib import astronomy
import glob
ro = astronomy.RedOps()
ro.ccdproc("./data/20160415N/43032/")>>> Scientific images are copied!
>>> Calibration images are copied!
>>> Master bias file is created.
>>> Master flat file is created.
>>> ccdproc is working for: 43032_0001_R_new.fits
[*] Gain correction is done.
[*] Cosmic correction is done.
[*] Bias correction is done.
[*] Flat correction is done.
[*] ccdproc is done for: 43032_0001_R_new.fits: [#-------------------] 2.63%
>>> ccdproc is working for: 43032_0002_R_new.fits
[*] Gain correction is done.
[*] Cosmic correction is done.
[*] Bias correction is done.
[*] Flat correction is done.
...
>>> ccdproc is working for: 43032_0042_R_new.fits
[*] Gain correction is done.
[*] Cosmic correction is done.
[*] Bias correction is done.
[*] Flat correction is done.
[*] ccdproc is done for: 43032_0042_R_new.fits: [####################] 100.0%
DONE
True
You will find your calibrated images under atmp/ directory as named "bf_" prefix.
If you want to apply asteroid photometry on a squential FITS images give this commands. Don't forget! All images must have WCS keywords and astrometrically solved. If you change the "multi_object" value as True, asteroids_phot function will perform photometry to all asteroids in the frame queried from SkyBoT.
from astrolib import photometry
from astrolib import visuals
import glob
ap = photometry.PhotOps()
plc = visuals.StarPlot()
ap.asteroids_phot("atmp/*.fits", multi_object=False)
# For plotting ligt curve of results.
plc.lc_plot("43032.txt")Photometry is done for: atmp/43032_0011_R_new.fits: [--------------------] 0.0%
...
Photometry done!: [####################] 100%
DONE
Plotting asteroid's LC...
To be continued! :)