def center(xx):
global imdata
# The aperture size for finding the location of the stars is arbitrarily set here
app = 7.
flux = -photutils.aperture_circular(
imdata, xx[0], xx[1], app, method='exact', subpixels=10)
return flux
def _aperture_phot(self,
x,
y,
radsize=1,
sky_inner=5,
skywidth=5,
method="subpixel",
subpixels=4):
"""Perform sky subtracted aperture photometry, uses photutils functions, photutil must be installed
Parameters
----------
radsize: int
Size of the radius
sky_inner: int
Inner radius of the sky annulus
skywidth: int
Width of the sky annulus
method: string
Pixel sampling method to use
subpixels: int
How many subpixels to use
Notes
-----
background is taken from sky annulus pixels, check into masking bad pixels
"""
if not photutils_installed:
print("Install photutils to enable")
else:
aper_flux = photutils.aperture_circular(self._data,
x,
y,
radsize,
subpixels=subpixels,
method=method)
aperture_area = np.pi * (radsize)**2
annulus_sky = photutils.annulus_circular(self._data, x, y,
sky_inner,
sky_inner + skywidth)
outer = sky_inner + skywidth
inner = sky_inner
annulus_area = np.pi * (outer**2 - inner**2)
skysub_flux = aper_flux - annulus_sky * (aperture_area /
annulus_area)
return (aper_flux, annulus_sky, skysub_flux)
def _aperture_phot(self,x,y,radsize=1,sky_inner=5,skywidth=5,method="subpixel",subpixels=4):
"""Perform sky subtracted aperture photometry, uses photutils functions
background is taken from sky annulus pixels, check into masking
"""
aper_flux=photutils.aperture_circular(self._data,x,y,radsize,subpixels=subpixels,method=method)
aperture_area = np.pi * (radsize)**2
annulus_sky=photutils.annulus_circular(self._data,x,y,sky_inner,sky_inner+skywidth)
outer=sky_inner+skywidth
inner=sky_inner
annulus_area = np.pi * (outer**2 - inner**2)
skysub_flux=aper_flux - annulus_sky * (aperture_area / annulus_area)
return (aper_flux,annulus_sky,skysub_flux)
def _aperture_phot(self, x, y, radsize=1, sky_inner=5, skywidth=5, method="subpixel", subpixels=4):
"""Perform sky subtracted aperture photometry, uses photutils functions, photutil must be installed
Parameters
----------
radsize: int
Size of the radius
sky_inner: int
Inner radius of the sky annulus
skywidth: int
Width of the sky annulus
method: string
Pixel sampling method to use
subpixels: int
How many subpixels to use
Notes
-----
background is taken from sky annulus pixels, check into masking bad pixels
"""
if not photutils_installed:
print("Install photutils to enable")
else:
aper_flux = photutils.aperture_circular(
self._data, x, y, radsize, subpixels=subpixels, method=method)
aperture_area = np.pi * (radsize) ** 2
annulus_sky = photutils.annulus_circular(
self._data, x, y, sky_inner, sky_inner + skywidth)
outer = sky_inner + skywidth
inner = sky_inner
annulus_area = np.pi * (outer ** 2 - inner ** 2)
skysub_flux = aper_flux - annulus_sky * (aperture_area / annulus_area)
return (aper_flux, annulus_sky, skysub_flux)
def get_fluxes(regfile, outfile, inneraprad=35, outeraprad=60, hdu=None,
PPBEAM=1.0, debug=False, print_nulls=False, photut=True):
"""
Extract fluxes from a region-defined aperture with inner and outer circular apertures
specififed
MUST BE IN GALACTIC COORDINATES
"""
if hdu is None:
raise ValueError("hdu keyword is required")
data = hdu.data
header = hdu.header
wcs = pywcs.WCS(header)
glonmax = wcs.wcs_pix2sky(0,0,0)[0]
glonmin = wcs.wcs_pix2sky(data.shape[1],0,0)[1]
reglist = pyregion.open(regfile)
outf = open(outfile,'w')
print "".join("%16s" % s for s in ['Source_Name','SumJy','ApSumJy','MeanApSumJy','SumJyBm','ApSumJyBm','BgMed','BgMean','BgStd','FracErrBg'])
print >>outf,"".join("%16s" % s for s in ['Source_Name','SumJy','ApSumJy','MeanApSumJy','SumJyBm','ApSumJyBm','BgMed','BgMean','BgStd','FracErrBg'])
if photut and not photut_ok:
photut = False
print "photutils is not loaded"
if photut:
dsqueeze = data.squeeze()
for reg in reglist:
glon,glat = position_region(reg).galactic()
if not((glon > glonmin) and (glon < glonmax)):
# these are the limits of the survey
if print_nulls:
print >>outf,"%16s" % sourcename,"".join("%16s" % f
for f in ['-','-','-','-','-','-','-','-','-'])
continue
xc,yc = wcs.wcs_sky2pix(glon,glat,0)
if xc < 0 or xc > data.shape[1] or yc < 0 or yc > data.shape[0]:
if print_nulls:
print >>outf,"%16s" % sourcename,"".join("%16s" % f
for f in ['-','-','-','-','-','-','-','-','-'])
continue
regL = pyregion.ShapeList()
reg.name = 'circle'
while len(reg.coord_list) < 3:
reg.coord_list.append(0)
reg.coord_list[2] = inneraprad/3600.0 # set inner aperture (foreground) to R=25"
regL.append(reg)
if not photut:
innerap = regL.get_mask(hdu=hdu)
if innerap.sum() == 0:
print "Skipped a source that was in the boundaries: ",reg
continue
regL[0].coord_list[2] = outeraprad/3600.0 # set outer aperture (background) to R=100"
#regL.append(reg) # I think this turns two circles into a panda?
if not photut:
outerap = regL.get_mask(hdu=hdu)
backreg = outerap-innerap
if photut:
innerappix = inneraprad / 3600. / np.abs(wcs.wcs.get_cdelt()[0]) / 2.
outerappix = outeraprad / 3600. / np.abs(wcs.wcs.get_cdelt()[0]) / 2.
total = photutils.aperture_circular(dsqueeze, xc, yc, innerappix)
outer = photutils.aperture_circular(dsqueeze, xc, yc, outerappix)
background = (outer-total) / ((outerappix**2-innerappix**2)*np.pi)
backmean = background
backstd = np.nan
else:
total = data[innerap].sum()
background = np.median(data[backreg])
backmean = data[backreg].mean()
backstd = data[backreg].std()
sourcename = pos_to_name(reg)
if backstd > total or total < 0:
print "%s set to zero" % reg.attr[1]['text']
total = np.float(0)
total_backsub = np.float(0)
total_mbacksub = np.float(0)
else:
if photut:
total_backsub = total_mbacksub = outer-total
else:
total_backsub = total - innerap.sum() * background
total_mbacksub = total - innerap.sum() * backmean
if total_backsub == 0:
total_backsub = -np.inf
print "%16s" % sourcename,"".join("%16.5g" % f
for f in [total/PPBEAM,total_backsub/PPBEAM,total_mbacksub/PPBEAM,total,total_backsub,background,backmean,backstd,backstd/total_backsub])
print >>outf,"%16s" % sourcename,"".join("%16.5g" % f
for f in [total/PPBEAM,total_backsub/PPBEAM,total_mbacksub/PPBEAM,total,total_backsub,background,backmean,backstd,backstd/total_backsub])
print "Done with %s" % outfile
outf.close()
def aperture(image, hdr):
global iap, pguess_old, nstars, svec
dnorm = 500.
rann1 = 18.
dann = 2.
rann2 = rann1 + dann
app_min = 1.
app_max = 19.
dapp = 1.
app_sizes = np.arange(app_min, app_max, dapp)
# If first time through, read in "guesses" for locations of stars
if iap == 0:
var = np.loadtxt('phot_coords')
xvec = var[:, 0]
yvec = var[:, 1]
nstars = len(xvec)
#print app_sizes,'\n'
else:
xvec = svec[:, 0]
yvec = svec[:, 1]
# Find locations of stars
dxx0 = 10.
for i in range(nstars):
xx0 = [xvec[i], yvec[i]]
xbounds = (xx0[0] - dxx0, xx0[0] + dxx0)
ybounds = (xx0[1] - dxx0, xx0[1] + dxx0)
#res = sco.minimize(center, xx0, method='BFGS', jac=der_center)
#res = sco.fmin_tnc(center, xx0, bounds=(xbounds,ybounds))
#res = sco.minimize(center, xx0, method='tnc', bounds=(xbounds,ybounds))
res = sco.minimize(center,
xx0,
method='L-BFGS-B',
bounds=(xbounds, ybounds),
jac=der_center)
xx0 = res.x
xvec[i] = xx0[0]
yvec[i] = xx0[1]
# Calculate sky around stars
sky = photutils.annulus_circular(image,
xvec,
yvec,
rann1,
rann2,
method='exact',
subpixels=10)
# Do psf fits to stars. Results are stored in arrays fwhm, pflux, psky, psf_x, and psf_y
fwhm = np.zeros(nstars)
# Make stacked array of star positions from aperture photometry
svec = np.dstack((xvec, yvec))[0]
#print svec
# Make stacked array of star positions from PSF fitting
# pvec = np.dstack((psf_x,psf_y))[0]
pvec = svec
iap = iap + 1
starr = []
apvec = []
app = -1.0
# Get time of observation from the header
#date = hdr['DATE-OBS'] # for Argos files
#utc = hdr['UTC'] # for Argos files
date = hdr['UTC-DATE'] # for Pro-EM files
utc = hdr['UTC-BEG'] # for Pro-EM files
times = date + " " + utc
t = Time(times, format='iso', scale='utc')
# Calculate Julian Date of observation
jd = t.jd
for app in app_sizes:
flux = photutils.aperture_circular(image,
xvec,
yvec,
app,
method='exact',
subpixels=10)
skyc = sky * app**2 / (rann2**2 - rann1**2)
fluxc = flux - skyc
starr.append([fluxc, skyc, fwhm])
apvec.append(app)
starr = np.array(starr)
apvec = np.array(apvec)
#print starr
return jd, svec, pvec, apvec, starr
def get_fluxes(regfile,
outfile,
inneraprad=35,
outeraprad=60,
hdu=None,
PPBEAM=1.0,
debug=False,
print_nulls=False,
photut=True):
"""
Extract fluxes from a region-defined aperture with inner and outer circular apertures
specififed
MUST BE IN GALACTIC COORDINATES
"""
if hdu is None:
raise ValueError("hdu keyword is required")
data = hdu.data
header = hdu.header
wcs = pywcs.WCS(header)
glonmax = wcs.wcs_pix2sky(0, 0, 0)[0]
glonmin = wcs.wcs_pix2sky(data.shape[1], 0, 0)[1]
reglist = pyregion.open(regfile)
outf = open(outfile, 'w')
print "".join("%16s" % s for s in [
'Source_Name', 'SumJy', 'ApSumJy', 'MeanApSumJy', 'SumJyBm',
'ApSumJyBm', 'BgMed', 'BgMean', 'BgStd', 'FracErrBg'
])
print >> outf, "".join("%16s" % s for s in [
'Source_Name', 'SumJy', 'ApSumJy', 'MeanApSumJy', 'SumJyBm',
'ApSumJyBm', 'BgMed', 'BgMean', 'BgStd', 'FracErrBg'
])
if photut and not photut_ok:
photut = False
print "photutils is not loaded"
if photut:
dsqueeze = data.squeeze()
for reg in reglist:
glon, glat = position_region(reg).galactic()
if not ((glon > glonmin) and (glon < glonmax)):
# these are the limits of the survey
if print_nulls:
print >> outf, "%16s" % sourcename, "".join(
"%16s" % f
for f in ['-', '-', '-', '-', '-', '-', '-', '-', '-'])
continue
xc, yc = wcs.wcs_sky2pix(glon, glat, 0)
if xc < 0 or xc > data.shape[1] or yc < 0 or yc > data.shape[0]:
if print_nulls:
print >> outf, "%16s" % sourcename, "".join(
"%16s" % f
for f in ['-', '-', '-', '-', '-', '-', '-', '-', '-'])
continue
regL = pyregion.ShapeList()
reg.name = 'circle'
while len(reg.coord_list) < 3:
reg.coord_list.append(0)
reg.coord_list[
2] = inneraprad / 3600.0 # set inner aperture (foreground) to R=25"
regL.append(reg)
if not photut:
innerap = regL.get_mask(hdu=hdu)
if innerap.sum() == 0:
print "Skipped a source that was in the boundaries: ", reg
continue
regL[0].coord_list[
2] = outeraprad / 3600.0 # set outer aperture (background) to R=100"
#regL.append(reg) # I think this turns two circles into a panda?
if not photut:
outerap = regL.get_mask(hdu=hdu)
backreg = outerap - innerap
if photut:
innerappix = inneraprad / 3600. / np.abs(
wcs.wcs.get_cdelt()[0]) / 2.
outerappix = outeraprad / 3600. / np.abs(
wcs.wcs.get_cdelt()[0]) / 2.
total = photutils.aperture_circular(dsqueeze, xc, yc, innerappix)
outer = photutils.aperture_circular(dsqueeze, xc, yc, outerappix)
background = (outer - total) / (
(outerappix**2 - innerappix**2) * np.pi)
backmean = background
backstd = np.nan
else:
total = data[innerap].sum()
background = np.median(data[backreg])
backmean = data[backreg].mean()
backstd = data[backreg].std()
sourcename = pos_to_name(reg)
if backstd > total or total < 0:
print "%s set to zero" % reg.attr[1]['text']
total = np.float(0)
total_backsub = np.float(0)
total_mbacksub = np.float(0)
else:
if photut:
total_backsub = total_mbacksub = outer - total
else:
total_backsub = total - innerap.sum() * background
total_mbacksub = total - innerap.sum() * backmean
if total_backsub == 0:
total_backsub = -np.inf
print "%16s" % sourcename, "".join("%16.5g" % f for f in [
total / PPBEAM, total_backsub / PPBEAM, total_mbacksub / PPBEAM,
total, total_backsub, background, backmean, backstd, backstd /
total_backsub
])
print >> outf, "%16s" % sourcename, "".join("%16.5g" % f for f in [
total / PPBEAM, total_backsub / PPBEAM, total_mbacksub / PPBEAM,
total, total_backsub, background, backmean, backstd, backstd /
total_backsub
])
print "Done with %s" % outfile
outf.close()