def remote_info(table: str):
"""Remote table description and column names.
Parameters
----------
table : str
valid table name from Gaia catalogues.
Returns
-------
description : str
Short text describing contents of the remote table.
cols : list of str
Column names of the remote table.
"""
table = Gaia.load_table(table)
description = f"table = {table}"
cols = [column.name for column in table.columns]
return description, cols
for table in (tables):
print(table.get_qualified_name())
# So that's a lot of tables. The ones we'll use are:
#
# * `gaiadr2.gaia_source`, which contains Gaia data from [data release 2](https://www.cosmos.esa.int/web/gaia/data-release-2),
#
# * `gaiadr2.panstarrs1_original_valid`, which contains the photometry data we'll use from PanSTARRS, and
#
# * `gaiadr2.panstarrs1_best_neighbour`, which we'll use to cross-match each star observed by Gaia with the same star observed by PanSTARRS.
#
# We can use `load_table` (not `load_tables`) to get the metadata for a single table. The name of this function is misleading, because it only downloads metadata.
# In[5]:
meta = Gaia.load_table('gaiadr2.gaia_source')
meta
# Jupyter shows that the result is an object of type `TapTableMeta`, but it does not display the contents.
#
# To see the metadata, we have to print the object.
# In[6]:
print(meta)
# Notice one gotcha: in the list of table names, this table appears as `gaiadr2.gaiadr2.gaia_source`, but when we load the metadata, we refer to it as `gaiadr2.gaia_source`.
#
# **Exercise:** Go back and try
#
# ```
from astroquery.gaia import Gaia
gaiadr2_table = Gaia.load_table('gaiadr2.gaia_source')
for column in (gaiadr2_table.columns):
print(column.name)
# RA = float = RA coordinates in deg # DEC = float = DEC coordinates in deg # dRA = float = Delta RA coordinate, a square of side=2*dRA will be searched # dDEC = float = Delta DEC coordinate, a square of side=2*dDEC will be searched # cat_name = str = Output catalogue name with all objects found # ---------------------------------------------------------------------------------------------------- # Import modules import sys from astroquery.gaia import Gaia # Define the input parameters tablename_all = 'gaiadr2.gaia_source' t = Gaia.load_table(tablename_all) ra = float(sys.argv[1]) dec = float(sys.argv[2]) d_ra = float(sys.argv[3]) d_dec = float(sys.argv[4]) cat_name = sys.argv[5] # Define the searching area of sources ra_min = str(ra - d_ra) ra_max = str(ra + d_ra) dec_min = str(dec - d_dec) dec_max = str(dec + d_dec) # SQL string type
def list_columns(self, table=None):
if table is None:
table = self.table
elif not isinstance(table, str):
raise ValueError("table must be string")
return [column.name for column in Gaia.load_table(table).columns]
def querycat_gaia(ralist=None, declist=None, cone_search=False,
width=10.0, height=10.0, radius=5.0, dr2=False,
test=False, debug=False):
"""
"""
import time
from astropy.table import Table, vstack
import astropy.units as u
from astropy.coordinates import SkyCoord
from astroquery.gaia import Gaia
if dr2:
help(Gaia)
gaiadr2_table = Gaia.load_table('gaiadr2.gaia_source')
for column in (gaiadr1_table.get_columns()):
print(column.get_name())
if debug:
help(Gaia)
width = u.Quantity(width/3600.0, u.degree)
height = u.Quantity(height/3600.0, u.degree)
radius = u.Quantity(radius/3600.0, u.degree)
if test is True:
ralist = [180.0]
declist = [0.0]
width = u.Quantity(30.0, u.arcsec)
height = u.Quantity(30.0, u.arcsec)
radius = u.Quantity(15.0, u.arcsec)
result_nrows = 0
for isource, (ra, dec) in enumerate(zip(ralist, declist)):
coord = SkyCoord(ra=ra, dec=dec,
unit=(u.degree, u.degree),
frame='icrs')
t0 = time.time()
if not cone_search:
result = Gaia.query_object_async(coordinate=coord,
width=width, height=height)
# help(result)
if debug:
result.pprint()
result.info('stats')
if cone_search:
job = Gaia.cone_search_async(coord, radius)
# help(job)
result = job.get_results()
print('Number of rows:', len(result))
print('Elapsed time(secs):',time.time() - t0)
if debug:
help(result)
result.pprint()
result.info('stats')
result_nrows = result_nrows + len(result)
if isource == 0:
result_all = result
if isource > 0:
result_all = vstack([result_all, result])
#def fix_vot_object():
table = result_all
print('icol, format, dtype')
# help(table)
# help(table.columns)
for (icol, column) in enumerate(table.columns):
print(icol, table.columns[icol].name,
table.columns[icol].format,
table.columns[icol].dtype)
# convert the columns for dtype = object which is not
# supported by FITs to bool
if table.columns[icol].dtype == 'object':
colname = table.columns[icol].name
NewColumn = Table.Column(table[colname].data, dtype='bool')
table.replace_column(colname, NewColumn)
print()
result_all = table
print('Number of Gaia sources returned:', result_nrows, len(result_all))
return result_all
def getTableMeta():
meta = Gaia.load_table('gaiadr2.gaia_source')
print(meta)
for column in (meta.columns):
print(column.name)
for table in tables:
# Filter by 'gaiadr3'
name = table.get_qualified_name()
if filter_string in name:
print(name)
filtered_tables.append(table)
# Loading single data and accessing column names
print("=================================================================")
print("Single table columns")
print("=================================================================")
# Just a demo of loading a table from its name
table_query_name = '.'.join(
filtered_tables[1].get_qualified_name().split('.')[1:])
gaiaedr3_table = Gaia.load_table(table_query_name)
# Query and save results to file
# !!!
# Dumping to file results in error
# AttributeError: 'str' object has no attribute 'read'
test_out = './out/gaiaedr3_test.csv'
print("=================================================================")
print(f"Single query and saving results to {test_out}")
print("=================================================================")
query = "select top 100 "\
"solution_id,ref_epoch,ra_dec_corr,astrometric_n_obs_al, "\
"matched_observations,duplicated_source,phot_variable_flag "\
f"from {table_query_name} by source_id"
job = Gaia.launch_job(query, dump_to_file=True)
