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NASA Sloan AtlasΒΆ

This shows some visualizations of the data from the NASA SDSS Atlas

../../_images/plot_nasa_atlas_1.png ../../_images/plot_nasa_atlas_2.png ../../_images/plot_nasa_atlas_3.png
Optimization terminated successfully.
         Current function value: -30227.574882
         Iterations: 18
         Function evaluations: 50
# Author: Jake VanderPlas <vanderplas@astro.washington.edu>
# License: BSD
#   The figure is an example from astroML: see http://astroML.github.com
import numpy as np
from matplotlib import pyplot as plt

from astroML.datasets import fetch_nasa_atlas

data = fetch_nasa_atlas()

#------------------------------------------------------------
# plot the RA/DEC in an area-preserving projection

RA = data['RA']
DEC = data['DEC']

# convert coordinates to degrees
RA -= 180
RA *= np.pi / 180
DEC *= np.pi / 180

ax = plt.axes(projection='mollweide')
plt.scatter(RA, DEC, s=1, c=data['Z'], cmap=plt.cm.copper,
            edgecolors='none', linewidths=0)
plt.grid(True)

plt.title('NASA Atlas Galaxy Locations')
cb = plt.colorbar(cax=plt.axes([0.05, 0.1, 0.9, 0.05]),
                  orientation='horizontal',
                  ticks=np.linspace(0, 0.05, 6))
cb.set_label('redshift')


#------------------------------------------------------------
# plot the r vs u-r color-magnitude diagram

absmag = data['ABSMAG']

u = absmag[:, 2]
r = absmag[:, 4]

plt.figure()
ax = plt.axes()
plt.scatter(u - r, r, s=1, lw=0, c=data['Z'], cmap=plt.cm.copper)
plt.colorbar(ticks=np.linspace(0, 0.05, 6)).set_label('redshift')

plt.xlim(0, 3.5)
plt.ylim(-10, -24)

plt.xlabel('u-r')
plt.ylabel('r')

#------------------------------------------------------------
# plot a histogram of the redshift
from astroML.plotting import hist

plt.figure()
hist(data['Z'], bins='knuth',
     histtype='stepfilled', ec='k', fc='#F5CCB0')
plt.xlabel('z')
plt.ylabel('N(z)')

plt.show()