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]