def get_comparison_star_descriptions(comparison_stars_1):
logging.info(f'Getting star description of comparison star: {comparison_stars_1}')
comp_star_description = do_calibration.get_star_descriptions(comparison_stars_1)
comparison_stars_1_desc = do_calibration.add_ucac4_to_star_descriptions(comp_star_description)
logging.info(f'Added apass info to comparison stars: {comparison_stars_1_desc}')
if np.isnan(comparison_stars_1_desc[0].vmag):
logging.info("Comparison star has nan vmag, will screw up everything coming after")
exit()
return comparison_stars_1_desc
def run_standard_field_charts(vsx_star_descr, wcs):
trash_and_recreate_dir(settings.fieldchartsdirs)
# reference_frame, reference_frame_index=reading.read_reference_frame()
# reference_fits_frame=settings.convfitsdir+reference_frame
reference_fits_frame=settings.reference_header
SHOW_UPSILON = False
# if SHOW_UPSILON:
# candidates = do_calibration.get_candidates(0.5)
# TODO hand labeled stars
# hand_candidates_descr = do_calibration.get_star_descriptions(init.wwcra_certain_candidates)
all_stars_descr = do_calibration.get_star_descriptions()
# if SHOW_UPSILON:
# big_green = set_custom_label(comparison_ star_descr, 'comp')
# small_red = set_custom_label(apass_star_descr, [o.vmag for o in apass_star_descr])
# big_green = set_custom_label(vsx_star_descr, [o.match['catalog_dict']['name'] for o in vsx_star_descr])
# small_red = set_custom_label(hand_candidates_descr, [o.local_id for o in hand_candidates_descr])
# big_green = set_aavso_id_label(vsx_star_descr)
# small_red = set_local_id_label(hand_candidates_descr)
all_stars_labeled = set_custom_label(all_stars_descr, '')
vsx_labeled = set_aavso_id_label(vsx_star_descr)
#vsx_labeled = set_custom_label(vsx_star_descr, [o.local_id for o in vsx_star_descr])
# TODO hand labeled stars
# hand_candidates_labeled = set_local_id_label(hand_candidates_descr)
# default fields
empty = []
# field chart with all detections
logging.info("Plotting field chart with all detected stars...")
big_green = empty
small_red = all_stars_labeled
fig = plot_it(big_green, small_red, reference_fits_frame, wcs, "All detected stars", PADDING)
save(fig, settings.fieldchartsdirs + 'all_detections_for_{}_stars'.format(len(small_red)))
# field chart with all vsx stars
logging.info("Plotting field chart with all VSX variable stars...")
big_green = vsx_labeled
small_red = empty
fig = plot_it(big_green, small_red, reference_fits_frame, wcs, "All VSX variable stars", PADDING)
save(fig, settings.fieldchartsdirs + 'all_vsx_stars_{}'.format(len(big_green)))
# field chart with all vsx stars
logging.info("Plotting field chart with all VSX variable stars + hand picked vars...")
big_green = vsx_labeled
# TODO hand labeled stars
small_red = [] # hand_candidates_labeled
fig = plot_it(big_green, small_red, reference_fits_frame, wcs, "VSX variable stars + detected variables", PADDING)
save(fig, settings.fieldchartsdirs + 'all_vsx_stars_{}_hand_picked_{}'.format(len(big_green), len(small_red)))
def construct_star_descriptions(args, do_compstars_flag):
# Start with the list of all detected stars
star_descriptions = do_calibration.get_star_descriptions(init.star_list)
if args.laststars:
file_to_load = settings.basedir + 'star_descriptions_to_chart.bin'
logging.info(f"Loading premade star_descriptions: {file_to_load}")
with open(file_to_load, 'rb') as fp:
star_descriptions = pickle.load(fp)
else:
if args.upsilon:
# now we generate a list of StarDescriptions, with which all further processing will be done
logging.info("Setting star_descriptions to upsilon candidates")
star_descriptions = do_calibration.add_candidates_to_star_descriptions(
star_descriptions, 0.1)
if args.vsx:
logging.info("Adding vsx names to star_descriptions")
star_descriptions = do_calibration.add_vsx_names_to_star_descriptions(
star_descriptions, 0.01)
# compstar data is added to star descriptions
if do_compstars_flag:
logging.info("Getting comparison stars...")
# getting compstars
comparison_stars_1, comparison_stars_1_desc = do_compstars.get_fixed_compstars(
)
logging.info(f"Comparison stars_1: {comparison_stars_1}")
np.savetxt(settings.basedir + "comparison_stars_1.txt",
comparison_stars_1,
fmt='%d',
delimiter=';')
with open(settings.basedir + 'comparison_stars_1_desc.bin',
'wb') as compfile:
pickle.dump(comparison_stars_1_desc, compfile)
else:
logging.info("Loading best compstars...")
comparison_stars_1, comparison_stars_1_desc = reading.read_compstars(
)
logging.info(f"comparison stars: {comparison_stars_1}")
logging.info("Writing star_descriptions_to_chart.bin...")
with open(settings.basedir + 'star_descriptions_to_chart.bin',
'wb') as fp:
pickle.dump(star_descriptions, fp)
return comparison_stars_1, comparison_stars_1_desc, star_descriptions
def get_fixed_compstars(star_descriptions=None):
logging.info(f"Using fixed compstars {init.comparison_stars}")
if star_descriptions is None:
star_descriptions = do_calibration.get_star_descriptions(init.star_list)
star_ids_1 = []
star_desc_result = []
star_catalog = do_calibration.create_star_descriptions_catalog(star_descriptions)
for ucac_id in init.comparison_stars:
# getting star_id_1
df = do_calibration.get_ucac4_id_as_dataframe(ucac_id)
star_id_1 = do_calibration.get_starid_1_for_radec(df['RAJ2000'], df['DEJ2000'], star_catalog)
star_ids_1.append(star_id_1)
# adding info to star_description
star = star_descriptions[star_id_1 - 1]
coord_catalog = SkyCoord(df['RAJ2000'], df['DEJ2000'], unit='deg')
logging.info(df.info())
# df['e_Vmag'] is not present !!!
logging.info(df['UCAC4'].iloc(0)[0])
vmag = df['Vmag'].iloc(0)[0]
do_calibration.add_info_to_star_description(star, vmag, np.nan, df['UCAC4'].iloc(0)[0].decode("utf-8"),
"UCAC4", coord_catalog)
star_desc_result.append(star)
logging.debug(f"Using fixed compstar '{ucac_id}' with Vmag: '{vmag}' and star id: {star_id_1}")
return star_ids_1, star_desc_result
logging.warning(f"Returned result from vizier for object {object_name} is empty.")
df = result[0].to_pandas()
df2 = df.loc[df['UCAC4'] == object_name.split()[1].encode('UTF-8')]
return df2
def get_vizier_field(center_coord, radius, catalog, row_limit=2):
# Select all columns (this is a generic function so has to be all)
v = Vizier(columns=['all'])
# Limit the number of rows returned to row_limit
v.ROW_LIMIT = row_limit
result = v.query_region(center_coord,
radius=radius,
catalog=[catalog])
logging.info(f"result of getting vizier field: {result}")
try:
df = result[0].to_pandas() if len(result) > 0 else None
except:
logging.error("Error processing vizier results in do_calibration")
return None
return df
if __name__ == '__main__':
star_descriptions = do_calibration.get_star_descriptions(init.star_list)
star_catalog = create_star_descriptions_catalog(star_descriptions)
result = get_starid_1_for_radec(star_catalog, [271.234735], [-43.845816])
logging.info(f"calibration result: {result}")