In [8]:
import numpy as np
from astropy.table import Table as tbl
import urllib.request
import urllib.parse
import subprocess

In [2]:
url = "http://irsa.ipac.caltech.edu/cgi-bin/Gator/nph-query?"

In [3]:
values = {'catalog':'ptf_objects', 'spatial':'None', 'outfmt':'1', 'selcols':'ra,dec,oid', 'constraints':'"(bestchisq>100)and(ngoodobs>500)"'}

In [21]:
data = urllib.parse.urlencode(values)
data = data.encode('utf-8')
req = urllib.request.Request(url, data)
resp = urllib.request.urlopen(req)
respdata = resp.read()

In [7]:
saveFile = open('objects.tbl', 'wb')
saveFile.write(respdata)
saveFile.close()

In [3]:
objects = tbl.read('/home/nke2/NUREU17/LSST/VariableStarClassification/scripts/ptf_query/objects.tbl', format = 'ipac')

In [10]:
curves = {}
for i in range(0,3):#range(len(objects)):
    saved = "curves_radec_{0}_{1}.tbl".format(objects['ra'][i], objects['dec'][i])
    cmd = 'curl -F catalog=ptf_lightcurves -F spatial=none -F constraints=' + '"(ra={0})"and"(dec={1})"'.format(objects['ra'][i], objects['dec'][i]) + ' -F outfmt=1 -F selcols=oid,obsmjd,mag_autocorr,magerr_auto,fid,ra,dec "http://irsa.ipac.caltech.edu/cgi-bin/Gator/nph-query?" -o ' + saved
    subprocess.call(cmd, shell = True)
    curves[i] = tbl.read(saved, format = 'ipac')

In [12]:
curves[0]


Out[12]:
<Table length=354>
oidobsmjdmag_autocorrmagerr_autofidradecclonclat
daysmagmagdegreesdegrees
int64float64float64float64int64float64float64str12str12
5189200000573756269.368957214.4160.022255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756271.378737214.4080.04255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756273.280517214.3960.049255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756273.311287214.3930.049255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756281.113087214.3520.045255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756281.143647214.3770.045255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756306.287007214.2150.044255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756297.317627214.4090.022255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573756297.347377214.4040.022255.18231268.83013503h40m43.75s68d49m48.49s
...........................
5189200000573755939.129637214.1670.033255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755385.451847214.3630.025255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755384.486547214.3470.024255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755384.441937214.3420.024255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755382.454437214.3350.025255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755380.470437214.3330.029255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755378.470557214.3110.029255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755940.137497214.180.418255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755940.092687214.180.418255.18231268.83013503h40m43.75s68d49m48.49s
5189200000573755941.091747213.8990.078255.18231268.83013503h40m43.75s68d49m48.49s

In [ ]: