def find_nearest_stdstar(inimg, data_hdu=0):
f = pyfits.open(inimg)
radec = '%s %s' % (f[data_hdu].header['RA'], f[data_hdu].header['DEC'])
f.close()
ra, dec = wifes_ephemeris.sex2dd(radec)
angsep_array = 3600.0 * ((dec - stdstar_dec_array)**2 +
(numpy.cos(numpy.radians(dec)) *
(ra - stdstar_ra_array))**2)**0.5
best_ind = numpy.argmin(angsep_array)
return stdstar_list[best_ind], angsep_array[best_ind]
def find_nearest_stdstar(inimg, data_hdu=0):
f = pyfits.open(inimg)
radec = '%s %s' % (f[data_hdu].header['RA'],
f[data_hdu].header['DEC'])
f.close()
ra, dec = wifes_ephemeris.sex2dd(radec)
angsep_array = 3600.0*(
(dec-stdstar_dec_array)**2+
(numpy.cos(numpy.radians(dec))*(ra-stdstar_ra_array))**2)**0.5
best_ind = numpy.argmin(angsep_array)
return stdstar_list[best_ind], angsep_array[best_ind]
sso_extinct_interp = scipy.interpolate.interp1d(extinct_data[:,0],
extinct_data[:,1],
bounds_error=False,
fill_value=numpy.nan)
#------------------------------------------------------------------------
#------------------------------------------------------------------------
# high-level function to find nearest standard star for a given frame!
stdstar_list = ref_coords_lookup.keys()
stdstar_list.sort()
nstds = len(stdstar_list)
stdstar_ra_array = numpy.zeros(nstds, dtype='d')
stdstar_dec_array = numpy.zeros(nstds, dtype='d')
for i in range(nstds):
stdstar_radec = ref_coords_lookup[stdstar_list[i]]
stdstar_ra, stdstar_dec = wifes_ephemeris.sex2dd(stdstar_radec)
stdstar_ra_array[i] = stdstar_ra
stdstar_dec_array[i] = stdstar_dec
def find_nearest_stdstar(inimg, data_hdu=0):
f = pyfits.open(inimg)
radec = '%s %s' % (f[data_hdu].header['RA'],
f[data_hdu].header['DEC'])
f.close()
ra, dec = wifes_ephemeris.sex2dd(radec)
angsep_array = 3600.0*(
(dec-stdstar_dec_array)**2+
(numpy.cos(numpy.radians(dec))*(ra-stdstar_ra_array))**2)**0.5
best_ind = numpy.argmin(angsep_array)
return stdstar_list[best_ind], angsep_array[best_ind]
sso_extinct_interp = scipy.interpolate.interp1d(extinct_data[:, 0],
extinct_data[:, 1],
bounds_error=False,
fill_value=numpy.nan)
#------------------------------------------------------------------------
#------------------------------------------------------------------------
# high-level function to find nearest standard star for a given frame!
stdstar_list = ref_coords_lookup.keys()
stdstar_list.sort()
nstds = len(stdstar_list)
stdstar_ra_array = numpy.zeros(nstds, dtype='d')
stdstar_dec_array = numpy.zeros(nstds, dtype='d')
for i in range(nstds):
stdstar_radec = ref_coords_lookup[stdstar_list[i]]
stdstar_ra, stdstar_dec = wifes_ephemeris.sex2dd(stdstar_radec)
stdstar_ra_array[i] = stdstar_ra
stdstar_dec_array[i] = stdstar_dec
def find_nearest_stdstar(inimg, data_hdu=0):
f = pyfits.open(inimg)
radec = '%s %s' % (f[data_hdu].header['RA'], f[data_hdu].header['DEC'])
f.close()
ra, dec = wifes_ephemeris.sex2dd(radec)
angsep_array = 3600.0 * ((dec - stdstar_dec_array)**2 +
(numpy.cos(numpy.radians(dec)) *
(ra - stdstar_ra_array))**2)**0.5
best_ind = numpy.argmin(angsep_array)
return stdstar_list[best_ind], angsep_array[best_ind]
