def sky(self):
"""
OSKAR sky model array converted from the input image.
Columns
-------
ra : (J2000) right ascension (deg)
dec : (J2000) declination (deg)
flux : source (Stokes I) flux density (Jy)
"""
idx = self.mask.flatten()
ra, dec = self.ra_dec
ra = ra.flatten()[idx]
dec = dec.flatten()[idx]
flux = self.image.flatten()[idx] * self.factor_K2JyPixel
sky_ = np.column_stack([ra, dec, flux])
return sky_
python类Jy()的实例源码
def write_sky_model(self, outfile, clobber=False):
"""
Write the converted sky model for simulation.
"""
if os.path.exists(outfile) and (not clobber):
raise OSError("OSKAR sky model file already exists: %s" % outfile)
sky = self.sky
counts = sky.shape[0]
percent = 100 * counts / self.image.size
logger.info("Source counts: %d (%.1f%%)" % (counts, percent))
header = ("Frequency = %.3f [MHz]\n" % self.freq +
"Pixel size = %.2f [arcsec]\n" % self.pixelsize +
"K2JyPixel = %.2f\n" % self.factor_K2JyPixel +
"RA0 = %.4f [deg]\n" % self.ra0 +
"Dec0 = %.4f [deg]\n" % self.dec0 +
"Minimum value = %.4e [K]\n" % self.minvalue +
"Maximum value = %.4e [K]\n" % self.maxvalue +
"Source counts = %d (%.1f%%)\n\n" % (counts, percent) +
"R.A.[deg] Dec.[deg] flux[Jy]")
logger.info("Writing sky model ...")
np.savetxt(outfile, sky, fmt='%.10e, %.10e, %.10e', header=header)
logger.info("Wrote OSKAR sky model to file: %s" % outfile)
def fits_header(self):
header = self.wcs.to_header()
header["BUNIT"] = ("Jy/pixel", "Brightness unit")
header["FREQ"] = (self.freq, "Frequency [MHz]")
header["RA0"] = (self.ra0, "Center R.A. [deg]")
header["DEC0"] = (self.dec0, "Center Dec. [deg]")
header["PixSize"] = (self.pixelsize, "Pixel size [arcsec]")
header["K2JyPix"] = (self.factor_K2JyPixel, "[K] -> [Jy/pixel]")
header["MINVALUE"] = (self.minvalue, "[K] minimum threshold")
if np.isfinite(self.maxvalue):
header["MAXVALUE"] = (self.maxvalue, "[K] maximum threshold")
return header
def factor_K2JyPixel(self):
"""
Conversion factor from [K] to [Jy/pixel]
"""
pixarea = (self.pixelsize * au.arcsec) ** 2
freq = self.freq * au.MHz
equiv = au.brightness_temperature(pixarea, freq)
factor = au.K.to(au.Jy, equivalencies=equiv)
return factor
def SubFluxOperation(y):
print(galaxies[y])
collection = ['F475W','F814W','F160W']
flux = np.zeros([len(collection),len(radii)]) #*u.Jy
subflux = np.zeros([len(collection),len(radii)])
for i in range (0, len(collection)):
# read in the images
file = glob.glob(dir+galaxies[y]+'_final_'+collection[i]+'*sci.fits')
hdu = fits.open(file[0])
data[i], header[i] = hdu[0].data, hdu[0].header
fnu[i] = header[i]['PHOTFNU']
exp[i] = header[i]['EXPTIME']
#define positions for photometry
positions = [(xcen[y], ycen[y])]
#do photometry on images
#convert to proper units
for j in range(0,len(radii)):
aperture = CircularAperture(positions, radii[j])
phot_table = aperture_photometry(data[i], aperture)
#the next line changes the data from its original e-/s to something else that i don't remember.... because i suck.
flux[i,j] = phot_table['aperture_sum'][0]*(fnu[i]/exp[i])
if j == 0:
subflux[i,j] = flux[i,j]
else:
subflux[i,j] = flux[i,j]-flux[i,j-1]
return(subflux)
# now let's put stuff in the data structure we created
def test_from_fnu(self):
fluxd = 6.161081515869728 * u.mJy
nu = 2.998e14 / 11.7 * u.Hz
aper = 1 * u.arcsec
eph = dict(rh=1.5 * u.au, delta=1.0 * u.au)
S = 1.711e14 * u.Jy
afrho = Afrho.from_fluxd(nu, fluxd, aper, eph, S=S)
assert np.isclose(afrho.cm, 1000.0)
def test_from_fnu(self):
fluxd = 6.0961896974549115 * u.mJy
nu = 2.998e14 / 11.7 * u.Hz
aper = 1 * u.arcsec
eph = dict(rh=1.5 * u.au, delta=1.0 * u.au)
S = 1.711e14 * u.Jy
efrho = Efrho.from_fluxd(nu, fluxd, aper, eph)
assert np.isclose(efrho.cm, 33.0)
