def get_data():
query = "SELECT top 1000 * FROM obsPointing WHERE obs_collection='K2' AND dataproduct_type='image'"
df = query_db(CAOM, query)
if len(df) == 0:
return None
df['coords'] = df.apply(lambda x: parse_s_region(x['s_region']), axis=1)
# Generate MOC
results = [get_polygon_moc(row) for _, row in df.iterrows()]
# Union of MOCs
if len(results) > 1:
moc = MOC.union(*results)
else:
moc = results
return moc
def get_data(sector):
query = "SELECT top 1000 * FROM obsPointing WHERE obs_collection='TESS' AND dataproduct_type='image' " \
"AND sequence_number={}".format(sector)
df = query_db(CAOM_OPS, query)
df['coords'] = df.apply(lambda x: parse_s_region(x['s_region']), axis=1)
# Generate MOC
start_time = time.time()
pool = ThreadPoolExecutor(max_workers=4)
results = list(pool.map(get_polygon_moc, [row for _, row in df.iterrows()]))
end_time = time.time()
print('Total time : {} seconds'.format(end_time - start_time))
# Union of MOCs
start_time = time.time()
moc = MOC.union(*results)
end_time = time.time()
print('Total time : {} seconds'.format(end_time - start_time))
return moc
class ASKAPSurvey:
ASKAP_ROTATION = 45 * u.deg # may not be an appropriate assumption!
# full width (diameter)
WIDTH = 2 * 4.1 * u.deg
HEIGHT = WIDTH
def __init__(self, field_list, max_depth=7):
if not os.path.exists(field_list):
raise IOError("Cannot find file %s" % field_list)
self.fields_df = pd.read_csv(field_list)
self.max_depth = max_depth
self.region_list = regions.ShapeList()
self.moc = MOC()
for _, field in self.fields_df.iterrows():
center = SkyCoord(ra=field.RA, dec=field.Dec, unit="hourangle,deg")
sep = np.hypot(self.WIDTH, self.HEIGHT) / 2.0
self.region_list.append(
regions.RectangleSkyRegion(
center,
self.WIDTH,
self.HEIGHT,
self.ASKAP_ROTATION + (field.Rotation * u.deg),
))
self.vertices = SkyCoord([
center.directional_offset_by(
self.ASKAP_ROTATION + pa + (field.Rotation * u.deg), sep)
for pa in [45, 135, 225, 315] * u.deg
])
self.moc = self.moc.union(
MOC.from_polygon_skycoord(self.vertices,
max_depth=self.max_depth))
def to_moc(self, filename):
self.moc.write(filename, overwrite=True)
def to_reg(self, filename):
regions.write_ds9(self.region_list, filename, coordsys="fk5")
return temp_moc
co = 100000
st = 1
en = st + co
query = "SELECT objID,ra,dec FROM objectCoords WITH (NOLOCK) WHERE objID between {} AND {}".format(
st, en)
df = query_db(TIC_CONN, query)
# Generate MOC
start_time = time.time()
pool = ThreadPoolExecutor(max_workers=4)
results = list(pool.map(get_catalog_moc, [row for _, row in df.iterrows()]))
end_time = time.time()
print('Total time : {} seconds'.format(end_time - start_time))
start_time = time.time()
# moc = MOC.union(results[0], *results[1:])
moc = MOC.union(*results)
end_time = time.time()
print('Total time : {} seconds'.format(end_time - start_time))
# Save MOC
# hdulist = moc.serialize(format='fits')
# hdulist.writeto('TIC_v70_{}.fits'.format(MAX_DEPTH))
moc.write('TIC_v70_{}.fits'.format(MAX_DEPTH), format='fits', overwrite=True)
# Read from file
moc = MOC.from_fits('TIC_v70_15.fits')
# Generate the figure(s)
for t in moc_list:
moc, s = t
print(s)
my_plot(moc, frame=Galactic(), save='figures/tess_S{:04d}.png'.format(int(s)))
# fig = plt.figure(111, figsize=(12.5, 10.5))
#
# with WCS(fig,
# fov=360 * u.deg,
# center=SkyCoord(0, 0, unit='deg', frame='galactic'),
# coordsys="galactic",
# rotation=Angle(0, u.degree),
# projection="AIT") as wcs:
# ax = fig.add_subplot(1, 1, 1, projection=wcs)
#
# # Call fill with a matplotlib axe and the `~astropy.wcs.WCS` wcs object.
# moc.fill(ax=ax, wcs=wcs, alpha=1, linewidth=1.5, fill=True, color="black")
# # moc.border(ax=ax, wcs=wcs, alpha=0.5, color="black")
#
# plt.tight_layout()
# plt.savefig('figures/tess_S{:04d}.png'.format(int(s)))
union_moc = MOC.union(*[s[0] for s in moc_list])
my_plot(union_moc, frame=Galactic(), save='caom_TESS_galactic.png')
