you can access the sql query code, the data retrieved, the python codes used and the ipython notebooks mentioned here with on the github reposity here.

In [1]:

!ls
# the files in the github repository are

gal_coordinates_plot.py  MyTable_rahul.poruri.csv  quasar_coordinates.ipynb  quasars_coordinates_galactic.png  quasars_coordinates_ra,dec.png  sdss_coverage.jpg  sql_query

sql query request¶

select
plateX.plate, plateX.mjd, 
PhotoPrimary.ra, PhotoPrimary.dec, PhotoPrimary.l, PhotoPrimary.b, PhotoPrimary.ObjID, 
specObj.fiberID, specObj.z into mydb.MyTable from PhotoPrimary, specObj, plateX

where
specObj.bestObjid = PhotoPrimary.ObjID 
AND plateX.plateID = specObj.plateID 
AND specObj.class = 'qso' 
AND specObj.zWarning = 0 
AND PhotoPrimary.modelMag_u < 22.3 
AND PhotoPrimary.modelMag_g < 22.6 
AND PhotoPrimary.modelMag_r < 22.7 
AND PhotoPrimary.modelMag_i < 22.4 
AND PhotoPrimary.modelMag_z < 20.5

you can submit the sql query here at the SDSS sql query page.

In [2]:

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

In [1]:

data = [line.split(',') for line in open('MyTable_rahul.poruri.csv')]
# a .csv file has values or columns seperated by commas

In [4]:

# the data format in the .csv file
print data[0]
print data[1]

['plate', 'mjd', 'ra', 'dec', 'l', 'b', 'ObjID', 'fiberID', 'z\n']
['339', '51692', '196.240031499488', '-1.23006495320075', '310.018771055342', '61.4554170817091', '1237648702972100785', '413', '0.4322039\n']

equatorial coordinates of the quasars¶

In [5]:

#ra = np.zeros(len(data))
#dec = np.zeros(len(data))
ra, dec = [], []
for i in range(1,len(data)):
    temp = float(data[i][2])
    temp1 = float(data[i][3])
    ra.append(temp)
    dec.append(temp1)
    #ra[i] = float(temp)
    #dec[i] = float(temp1)

In [6]:

ra = np.asarray(ra)
dec = np.asarray(dec)
ra = (ra-180)*(np.pi/180)
dec = dec*(np.pi/180)

In [7]:

plt.subplot(111,projection='aitoff')
# aitoff, mollweide and hammer are 3 of the options
plt.grid(True)
plt.scatter(ra,dec,s=5)
plt.title('Quasars from the SDSS DR10')
plt.xlabel('ra')
plt.ylabel('dec')

Out[7]:

<matplotlib.text.Text at 0xab6e0a4c>

for a brief theory on how the conversion between equatorial and galactic coordinates works, refer here

galactic coordinates of the quasars¶

In [8]:

#ra = np.zeros(len(data))
#dec = np.zeros(len(data))
l, b = [], []
for i in range(1,len(data)):
    temp = float(data[i][4])
    temp1 = float(data[i][5])
    l.append(temp)
    b.append(temp1)
    #ra[i] = float(temp)
    #dec[i] = float(temp1)

In [9]:

b = np.asarray(b)
l = np.asarray(l)
l = (l-180)*(np.pi/180)
b = b*(np.pi/180)

In [10]:

plt.subplot(111,projection='aitoff')
plt.grid(True)
plt.scatter(l,b,s=5)
plt.title('Quasars from the SDSS DR10')
plt.xlabel('galactic longitude')
plt.ylabel('galactic latitude')

Out[10]:

<matplotlib.text.Text at 0xab6808ec>

now we can use the coordinate transformation utilities available in the astropy library. you can refer to the docs here or here

gnuplot code¶

gnuplot> set term wxt
gnuplot> set datafile separator ','
gnuplot> plot 'MyTable_rahul.poruri.csv' u 3:4 or 5:6 for a simple pllot of (ra, dec) or (l, b).

we figure out how to do projections in gnuplot!

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