def getParLine(img, p1, p2, m, b):
parDists = GT.findDistances(np.array([p1[0],p2[0]]),np.array([p1[1],p2[1]]),m,b)[0]
minD = min(parDists)
maxD = max(parDists)
step = (maxD-minD)/max(img.shape)
return np.arange(minD,maxD,step)
def getStarsHotPixelsAlongTrail(m, b, starX, starY, starR, gX, gY, gR, hotX, hotY, dist):
starX = np.array(starX)
starY = np.array(starY)
starR = np.array(starR)
gX = np.array(gX)
gY = np.array(gY)
gR = np.array(gR)
hotX = np.array(hotX)
hotY = np.array(hotY)
starPar,starPerp = GT.findDistances(starX,starY,m,b)
gPar,gPerp = GT.findDistances(gX,gY,m,b)
hotPar,hotPerp = GT.findDistances(hotX,hotY,m,b)
starMask = (np.abs(np.abs(starPerp)-np.abs(starR))<=dist)
gMask = (np.abs(np.abs(gPerp)-np.abs(gR))<=dist)
hotMask = (np.abs(hotPerp)<=dist)
return (starX[starMask], starY[starMask], starR[starMask], gX[gMask], gY[gMask], gR[gMask], hotX[hotMask], hotY[hotMask])
def getStars(trail, noTrail, baselineImages, trailCoords, noTrailCoords,
baselineCoords, p1, p2):
v = Vizier(row_limit=100000)
center = trailCoords.all_pix2world(
[(trail.shape[0] / 2, trail.shape[1] / 2)], 0, ra_dec_order=True)[0]
corner = trailCoords.all_pix2world([(0, 0)], 0, ra_dec_order=True)[0]
angle = np.sqrt((corner[0] - center[0])**2 + (corner[1] - center[1])**2)
c = coordinates.SkyCoord(center[0],
center[1],
unit=('deg', 'deg'),
frame='icrs')
starResult = v.query_region(c,
radius=angle * u.deg,
catalog=["I/337/gaia"])
starCoords = []
mags = []
for item in starResult:
for i in range(0, item["RA_ICRS"].shape[0]):
starCoords.append((item["RA_ICRS"][i], item["DE_ICRS"][i]))
mags.append(item["__Gmag_"][i])
starPix = np.transpose(
trailCoords.all_world2pix(starCoords, 0, ra_dec_order=True))
starPixX = starPix[0]
starPixY = starPix[1]
mags = np.array(mags)
mask = (starPixX > 50)
mask = np.logical_and(mask, (starPixX < trail.shape[1] - 50))
mask = np.logical_and(mask, (starPixY > 50))
mask = np.logical_and(mask, (starPixY < trail.shape[0] - 50))
mask = np.logical_and(mask, (starPixX + starPixY < 6000))
mags = mags[mask]
newStarCoords = []
for i in range(len(starCoords)):
if mask[i]:
newStarCoords.append(starCoords[i])
starCoords = newStarCoords
starPix = np.transpose(
noTrailCoords.all_world2pix(starCoords, 0, ra_dec_order=True))
starPixX = starPix[0]
starPixY = starPix[1]
mags = np.array(mags)
mask = (starPixX > 50)
mask = np.logical_and(mask, (starPixX < trail.shape[1] - 50))
mask = np.logical_and(mask, (starPixY > 50))
mask = np.logical_and(mask, (starPixY < trail.shape[0] - 50))
mags = mags[mask]
newStarCoords = []
for i in range(len(starCoords)):
if mask[i]:
newStarCoords.append(starCoords[i])
starCoords = newStarCoords
for coords in baselineCoords:
starPix = np.transpose(
coords.all_world2pix(starCoords, 0, ra_dec_order=True))
starPixX = starPix[0]
starPixY = starPix[1]
mags = np.array(mags)
mask = (starPixX > 50)
mask = np.logical_and(mask, (starPixX < trail.shape[1] - 50))
mask = np.logical_and(mask, (starPixY > 50))
mask = np.logical_and(mask, (starPixY < trail.shape[0] - 50))
mags = mags[mask]
newStarCoords = []
for i in range(len(starCoords)):
if mask[i]:
newStarCoords.append(starCoords[i])
starCoords = newStarCoords
trailStarPix = np.transpose(
trailCoords.all_world2pix(starCoords, 0, ra_dec_order=True))
trailStarPixX = trailStarPix[0]
trailStarPixY = trailStarPix[1]
showImageWithDetectedHotPixels(trail, "", trailStarPixX, trailStarPixY,
"b", True)
noTrailStarPix = np.transpose(
noTrailCoords.all_world2pix(starCoords, 0, ra_dec_order=True))
noTrailStarPixX = noTrailStarPix[0]
noTrailStarPixY = noTrailStarPix[1]
showImageWithDetectedHotPixels(noTrail, "", noTrailStarPixX,
noTrailStarPixY, "b", True)
baselineStarPixX = []
baselineStarPixY = []
for i in range(len(baselineCoords)):
baselinePix = np.transpose(baselineCoords[i].all_world2pix(
starCoords, 0, ra_dec_order=True))
baselineStarPixX.append(baselinePix[0])
baselineStarPixY.append(baselinePix[1])
showImageWithDetectedHotPixels(baselineImages[i], "",
baselineStarPixX[-1],
baselineStarPixY[-1], "b", True)
order = np.argsort(mags)
trailStarPixX = trailStarPixX[order]
trailStarPixY = trailStarPixY[order]
noTrailStarPixX = noTrailStarPixX[order]
noTrailStarPixY = noTrailStarPixY[order]
for i in range(len(baselineStarPixX)):
baselineStarPixX[i] = baselineStarPixX[i][order]
baselineStarPixY[i] = baselineStarPixY[i][order]
mags = mags[order]
if p1[0] == p2[0]:
perp = trailStarPixX - p1[0]
else:
m, b = getLineParams(p1, p2)
par, perp = GT.findDistances(trailStarPixX, trailStarPixY, m, b)
mask = (np.abs(perp) <= 20)
antimask = (np.abs(perp) > 20)
baselineStarTrailPixX = []
baselineStarTrailPixY = []
trailStarTrailPixX = trailStarPixX[mask][:12]
trailStarTrailPixY = trailStarPixY[mask][:12]
showImageWithDetectedHotPixels(trail, "", trailStarTrailPixX,
trailStarTrailPixY, "b", True)
noTrailStarTrailPixX = noTrailStarPixX[mask][:12]
noTrailStarTrailPixY = noTrailStarPixY[mask][:12]
showImageWithDetectedHotPixels(noTrail, "", noTrailStarTrailPixX,
noTrailStarTrailPixY, "b", True)
for i in range(len(baselineStarPixX)):
baselineStarTrailPixX.append(baselineStarPixX[i][mask][:12])
baselineStarTrailPixY.append(baselineStarPixY[i][mask][:12])
showImageWithDetectedHotPixels(baselineImages[i], "",
baselineStarTrailPixX[-1],
baselineStarTrailPixY[-1], "b", True)
baselineStarBackPixX = []
baselineStarBackPixY = []
trailStarBackPixX = trailStarPixX[antimask][:200]
trailStarBackPixY = trailStarPixY[antimask][:200]
showImageWithDetectedHotPixels(trail, "", trailStarBackPixX,
trailStarBackPixY, "b", True)
for i in range(len(baselineStarPixX)):
baselineStarBackPixX.append(baselineStarPixX[i][antimask][:200])
baselineStarBackPixY.append(baselineStarPixY[i][antimask][:200])
showImageWithDetectedHotPixels(baselineImages[i], "",
baselineStarBackPixX[-1],
baselineStarBackPixY[-1], "b", True)
return (trailStarTrailPixX, trailStarTrailPixY, noTrailStarTrailPixX,
noTrailStarTrailPixY, baselineStarTrailPixX, baselineStarTrailPixY,
trailStarBackPixX, trailStarBackPixY, baselineStarBackPixX,
baselineStarBackPixY)
def removeStarsPSF(img, starPixX, starPixY, starR, mags, gX, gY, gR, p1, p2, radius, showProgress, inverted = False):
remove = []
for i in range(0,len(starPixX)):
if i%100 == 0:
print(i)
for j in range(i+1,len(starPixX)):
if np.abs(starPixX[i]-starPixX[j])<2.5*radius and np.abs(starPixY[i]-starPixY[j])<2.5*radius:
remove.append(i)
remove.append(j)
mask = np.ones(len(starPixX), dtype = bool)
mask[np.array(remove)] = 0
starPixX = starPixX[mask]
starPixY = starPixY[mask]
starR = starR[mask]
mags = mags[mask]
print(radius)
mask = np.ones(starPixX.shape[0],dtype=bool)
for i in range(gX.shape[0]):
mask = np.logical_and(mask, np.sqrt((starPixX-gX[i])**2+(starPixY-gY[i])**2)>gR[i]+2*radius)
starPixX = starPixX[mask]
starPixY = starPixY[mask]
starR = starR[mask]
mags = mags[mask]
mask = (2*radius<starPixX) & (starPixX<img.shape[1]-2*radius) & (2*radius<starPixY) & (starPixY<img.shape[0]-2*radius)
starPixX = starPixX[mask]
starPixY = starPixY[mask]
starR = starR[mask]
mags = mags[mask]
if p1[0]==p2[0]:
psfMask = np.abs(starPixX-p1[0])>2.5*radius
trailMask = np.abs(starPixX-p1[0])<10
psfX = starPixX[psfMask]
psfY = starPixY[psfMask]
psfR = starR[psfMask]
psfMags = mags[psfMask]
trailX = starPixX[trailMask]
trailY = starPixY[trailMask]
trailMags = mags[trailMask]
else:
m,b = TF.getLineParams(p1,p2)
par,perp = GT.findDistances(starPixX,starPixY,m,b)
psfMask = np.abs(perp)>2.5*radius
trailMask = np.abs(perp)<10
psfX = starPixX[psfMask]
psfY = starPixY[psfMask]
psfR = starR[psfMask]
psfMags = mags[psfMask]
trailX = starPixX[trailMask]
trailY = starPixY[trailMask]
trailMags = mags[trailMask]
mask = psfR>10
psfX = psfX[mask]
psfY = psfY[mask]
psfMags = psfMags[mask]
print(psfX.shape[0])
showImageWithDetectedHotPixels(img, "Image with Star Picks", psfX, psfY, "b", inverted)
psfX,psfY = centroid_sources(img, psfX, psfY, box_size=21, centroid_func=centroid_com)
showImageWithDetectedHotPixels(img, "Image with Star Picks Centroid", psfX, psfY, "b", inverted)
stars = Table()
stars["x"] = psfX
stars["y"] = psfY
#stars2 = Table()
#stars2["x_0"] = psfX
#stars2["y_0"] = psfY
stars = extract_stars(NDData(data=img), stars, size = 2*int(2*radius)+1)
nrows = 5
ncols = 5
fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 20), squeeze=True)
ax = ax.ravel()
for i in range(nrows*ncols):
norm = simple_norm(stars[i], 'log', percent=99.)
ax[i].imshow(stars[i], norm=norm, origin='lower', cmap='viridis')
plt.show()
#sigma_psf = 2.0
#daogroup = DAOGroup(2.0)
#mmm_bkg = MMMBackground()
#fitter = LevMarLSQFitter()
#psf_model = PRF(sigma=sigma_psf)
#photometry = BasicPSFPhotometry(group_maker=daogroup,bkg_estimator=mmm_bkg,psf_model=psf_model,fitter=LevMarLSQFitter(),fitshape=(11,11))
#result_tab = photometry(image=img, init_guesses=stars2)
#residual_image = photometry.get_residual_image()
epsfBuilder = EPSFBuilder(oversampling=2, maxiters=20, smoothing_kernel = "quadratic")
epsf, starFits = epsfBuilder(stars)
#showImage(residual_image,"Image No Stars",True)
norm = simple_norm(epsf.data, 'log', percent=99.)
plt.imshow(epsf.data, norm=norm, origin='lower', cmap='viridis')
plt.colorbar()
plt.show()
nrows = 5
ncols = 5
fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 20), squeeze=True)
ax = ax.ravel()
for i in range(nrows*ncols):
norm = simple_norm(starFits[i], 'log', percent=99.)
ax[i].imshow(starFits[i], norm=norm, origin='lower', cmap='viridis')
plt.show()
nrows = 5
ncols = 5
fig, ax = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 20), squeeze=True)
ax = ax.ravel()
for i in range(nrows*ncols):
norm = simple_norm(stars[i].data-starFits[i].data, 'log', percent=99.)
ax[i].imshow(stars[i].data-starFits[i].data, norm=norm, origin='lower', cmap='viridis')
plt.show()
showImage(finalImg, "Image With No Stars", inverted)