-
Notifications
You must be signed in to change notification settings - Fork 1
/
rave-tutorial-simple-cone-search-pg.py
78 lines (61 loc) · 1.71 KB
/
rave-tutorial-simple-cone-search-pg.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
from pkg_resources import parse_version
import requests
import pyvo as vo
import pandas as pd
#
# Verify the version of pyvo
#
if parse_version(vo.__version__) < parse_version('1.0'):
raise ImportError('pyvo version must larger than 1.0')
print('\npyvo version {version} \n'.format(version=vo.__version__))
#
# Setup tap_service
#
service_name = 'rave-survey.org'
url = "https://www.rave-survey.org/tap"
token = 'Token <your-token>'
print('TAP service {} \n'.format(service_name))
# Setup authorization
tap_session = requests.Session()
tap_session.headers['Authorization'] = token
tap_service = vo.dal.TAPService(url, session=tap_session)
#
# Setting the cone search parameters
#
# RA (in degrees)
ra = 245.8962
# DEC (in degreees)
dec = -26.5222
# Radius (in arcsec)
sr = 0.5
#
# Submit the query as an async job
#
query_name = "simple_cs_pg"
lang = 'PostgreSQL'
query = '''
-- Simple cone search
-- WARNING: dist is in degree
SELECT rave_obs_id, ra_input, dec_input, spoint(RADIANS(ra_input), RADIANS(dec_input)) <-> spoint(RADIANS({ra}), RADIANS({dec})) AS dist
FROM ravedr6.dr6_obsdata
WHERE pos @ scircle(spoint(RADIANS({ra}), RADIANS({dec})), RADIANS({radius}))
'''.format(ra=ra, dec=dec, radius=sr)
job = tap_service.submit_job(query, language=lang, runid=query_name, queue="60s")
job.run()
#
# Wait to be completed (or an error occurs)
#
job.wait(phases=["COMPLETED", "ERROR", "ABORTED"], timeout=60.)
print('JOB {name}: {status}'.format(name=job.job.runid , status=job.phase))
#
# Fetch the results
#
job.raise_if_error()
print('\nfetching the results...')
tap_results = job.fetch_result()
print('...DONE\n')
#
# Convert to a pandas.DataFrame
#
results = tap_results.to_table().to_pandas()
print(results.head())