def usefullsky(self, aperture, inner_annulus, centroid='c'):
lightcurves = []
for index in range(self.extimage.shape[0]):
print index
photometry = mf.APhot(self.extimage[index])
# Image centring
if centroid == 'g':
best_gfit = photometry.fitguassian()
centre = photometry.gauss_centre(best_gfit)
if centroid == 'c':
centre = photometry.centroid()
# Measurement of source
apt = photometry.aptvalue(centre, aperture)
# Measurement of background
sky = photometry.skyvalue2(centre, inner_annulus)
# measuring source intensity
intensity = apt[1] - apt[0] * sky[2]
# column: time, intensity, x, y, aperture size, sky value
lightcurves.append([
index * self.exposuretime, intensity, centre[0], centre[1],
apt[0], sky[2]
])
self.f_lightcurves = np.asarray(lightcurves)
self.aperture = aperture
def Lightcurve_seul(image_dir,
fits_filename,
output_dir,
aperture=8,
inner_annulus=13,
outer_annulus=0,
centroid='c'):
"""
aperture photometry for all the firbres in the FITS images
The results are saved in the FITS table format.
"""
# getting numbers of active fibres and other header information
temp = pf.open(image_dir + '/' + fits_filename)
priheader = temp[0].header
num_of_fibre = priheader['FIBREACT']
exposure_time = priheader['EXPTIME']
tzero = 0.0
snapshot = temp[0].data
fstheader = temp[1].header
length_of_cube = fstheader['NAXIS3']
cols_ext = []
for index in range(num_of_fibre):
ext_image = temp[index + 1].data
temp_lcs = []
for numimage in range(length_of_cube):
temp_image = ext_image[numimage]
photo_temp = mf.APhot(temp_image)
# Image centring
if centroid == 'g':
best_gfit = photo_temp.fitguassian()
centre = photo_temp.gauss_centre(best_gfit)
if centroid == 'c':
centre = photo_temp.centroid()
# Measurement of source
apt = photo_temp.aptvalue(centre, aperture)
# Measurement of background
if (outer_annulus <= inner_annulus):
sky = photo_temp.skyvalue2(centre, inner_annulus)
else:
sky = photo_temp.skyvalue(centre, inner_annulus, outer_annulus)
# measuring source intensity
intensity = apt[1] - apt[0] * sky[2]
time_stamp = tzero + numimage * exposure_time
temp_lcs.append(
[time_stamp, intensity, centre[0], centre[1], apt[0], sky[2]])
temp_lcs = np.asarray(temp_lcs)
# Creating FITS table
time = np.array(temp_lcs[:, 0])
src_flux = np.array(temp_lcs[:, 1])
x_centre = np.array(temp_lcs[:, 2])
y_centre = np.array(temp_lcs[:, 3])
src_pixl = np.array(temp_lcs[:, 4])
avg_skyv = np.array(temp_lcs[:, 5])
col1 = pf.Column(name='Time (sec)', format='E', array=time)
col2 = pf.Column(name='Src_Flux (count)', format='E', array=src_flux)
col3 = pf.Column(name='X_Centre (pixel)', format='E', array=x_centre)
col4 = pf.Column(name='Y_Centre (pixel)', format='E', array=y_centre)
col5 = pf.Column(name='Src_Area (pixel)', format='E', array=src_pixl)
col6 = pf.Column(name='Median_Sky (count)', format='E', array=avg_skyv)
cols = pf.ColDefs([col1, col2, col3, col4, col5, col6])
tbhdu = pf.new_table(cols)
cols_ext.append(tbhdu)
hdu = pf.PrimaryHDU(snapshot, priheader)
thdulist = pf.HDUList([hdu] + cols_ext)
# Update extension header
for itable in range(num_of_fibre):
ext_table = thdulist[itable + 1]
ext_table.header.update('FIBRE',
priheader['EXTEN_' + str(itable + 1).zfill(2)])
ext_table.header.update('RA',
priheader['RA_' + str(itable + 1).zfill(2)])
ext_table.header.update('DEC',
priheader['DEC_' + str(itable + 1).zfill(2)])
ext_table.header.update('MAG',
priheader['MAG_' + str(itable + 1).zfill(2)])
ext_table.header.update('EQUINOX', priheader['EQUINOX'])
ext_table.header.update('APERTURE', aperture,
'aperture radius in pixels')
ext_table.header.update('SKYRADIN', inner_annulus,
'inner sky radius in pixels')
if (outer_annulus > inner_annulus):
ext_table.header.update('SKYRADOU', outer_annulus,
'outer sky radius in pixels')
thdulist.writeto(
output_dir + '/' + fits_filename, output_verify='fix'
) # pyfits 3.0.3 changes the behaviour of verify (default is 'exception'), but is reversed to fix in 3.0.4
temp.close()