Script for masking known sources using the Gaia database. #91
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| Big_Fudge = 1.5 #Arbitrary constant to scale large, bright sources. | ||
| small_fudge = .2 #Arbitrary constant to sclae smaller, dim sources. | ||
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| def get_wcs(images): #extracts necessary WCS info from science images. |
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Is this possible to do using astropy.wcs?
| from astropy.coordinates import ICRS, FK5, SkyCoord | ||
| from astroquery.gaia import Gaia | ||
| from matplotlib.colors import LogNorm | ||
| CRVAL1 =[] |
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These arrays look like they could be moved locally into the function to me; they might have side effects if global declarations. LMK if this is not the case.
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as a smaller point, SCREAMING_SNAKE_CASE is used for constants; use snake_case instead.
| CD2_1 =[] | ||
| CD2_2 =[] | ||
| VALS = [] | ||
| Big_Fudge = 1.5 #Arbitrary constant to scale large, bright sources. |
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These are constants, so SCREAMING_SNAKE_CASE is appropriate.
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| def reference(im): #runs GAIA cone search |
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I think it might be appropriate to leave reference to be done by a different script (like ref) and have this script draw reference data from a BinTable instead. This might be better to stay modular and avoid replication of efforts (like the rather tricky optimizations to referencing done in ref).
| ra = VALS[0] | ||
| dec = VALS[1] | ||
| coord = SkyCoord(ra, dec, unit = (u.deg, u.deg), frame = 'icrs') | ||
| radius = u.Quantity(.3, u.deg) #.3 deg is good enough for normal sized images can be adjusted. |
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This is good, I think this should be patched in ref. See Issue #71.
| if (center[0] <= 0) or (center[0] >= 3054): | ||
| continue #makes sure sources are in frame | ||
| print('STEP3') | ||
| if (center[1] <= 0) or (center[1] >= 2042): |
| y[0] = center[1] | ||
| bk_list = [] | ||
| i = 0 | ||
| while i != 100: |
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Does this loop calculate a background? If so, can sep.Background do the job, and/or can we pull this out into a separate function?
| continue | ||
| avlist.append(data[int((y[0]-30)+pnt[1]), int((x[0]-30)+pnt[0])]) | ||
| bk_list.append(np.sum(avlist)/(int(len(avlist)))) | ||
| i +=1 |
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There's a lot of magic with really short variable names happening below, some descriptions would be helpful to the reader.
| empty_mask[mask.bbox.slices] += mask | ||
| print('Step6') | ||
| dlt = np.arange(0, 50, 1) | ||
| np.delete(empty_mask, [i for i in dlt], axis= 0) |
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Is this cropping out borders?
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empty_mask = empty_mask[50:-50,50:-50]
| print('Step7') | ||
| plt.imshow(empty_mask.data, norm=LogNorm(vmin=10, vmax=100)) | ||
| lg = np.log(empty_mask.data+.001) | ||
| plt.imsave(fname='new_mask.png', arr=lg, cmap='viridis', dpi = 300) |
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Should return as opposed to imsaving.
Reviewing code for source masking. (making sure it works with new version of pipeline)