def load_astro_dataset():
"""
The BUPA dataset can be obtained from
http://www.cs.huji.ac.il/~shais/datasets/ClassificationDatasets.html
See description of this dataset at
http://www.cs.huji.ac.il/~shais/datasets/bupa/bupa.names
"""
quasars = fetch_dr7_quasar()
stars = fetch_sdss_sspp()
quasars = quasars[::5]
stars = stars[::5]
Nqso = len(quasars)
#print 'Numero quasars: ',Nqso
Nstars = len(stars)
#print 'Numero estrellas: ',Nstars
X = empty((Nqso + Nstars, 4), dtype=float)
X[:Nqso, 0] = quasars['mag_u'] - quasars['mag_g']
X[:Nqso, 1] = quasars['mag_g'] - quasars['mag_r']
X[:Nqso, 2] = quasars['mag_r'] - quasars['mag_i']
X[:Nqso, 3] = quasars['mag_i'] - quasars['mag_z']
X[Nqso:, 0] = stars['upsf'] - stars['gpsf']
X[Nqso:, 1] = stars['gpsf'] - stars['rpsf']
X[Nqso:, 2] = stars['rpsf'] - stars['ipsf']
X[Nqso:, 3] = stars['ipsf'] - stars['zpsf']
y = zeros(Nqso + Nstars, dtype=int)
y[:Nqso] = 1
y[y == 0] = -1
#print 'Salida', y
stars = map(tuple, stars)
quasars = map(tuple, quasars)
stars = array(stars)
quasars = array(quasars)
#print "Tamano Astro: ", len(X)
return X, y
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 7 15:30:22 2018
@author: zyv57124
"""
import numpy as np
from astroML.datasets import fetch_LINEAR_geneva
from astroML.datasets import fetch_dr7_quasar
from astroML.datasets import fetch_sdss_sspp
quasars = fetch_dr7_quasar()
stars = fetch_sdss_sspp()
np.save('quasars.npy', quasars)
np.save('stars.npy', stars)
#---------------------------------------------------------------------- # This function adjusts matplotlib settings for a uniform feel in the textbook. # Note that with usetex=True, fonts are rendered with LaTeX. This may # result in an error if LaTeX is not installed on your system. In that case, # you can set usetex to False. from astroML.plotting import setup_text_plots setup_text_plots(fontsize=8, usetex=True) #------------------------------------------------------------ # Fetch data and split into training and test samples from astroML.datasets import fetch_dr7_quasar from astroML.datasets import fetch_sdss_sspp quasars = fetch_dr7_quasar() stars = fetch_sdss_sspp() # Truncate data for speed quasars = quasars[::5] stars = stars[::5] # stack colors into matrix X Nqso = len(quasars) Nstars = len(stars) X = np.empty((Nqso + Nstars, 4), dtype=float) X[:Nqso, 0] = quasars['mag_u'] - quasars['mag_g'] X[:Nqso, 1] = quasars['mag_g'] - quasars['mag_r'] X[:Nqso, 2] = quasars['mag_r'] - quasars['mag_i'] X[:Nqso, 3] = quasars['mag_i'] - quasars['mag_z']
SDSS Data Release 7 Quasar catalog
----------------------------------
This demonstrates how to fetch and visualize the colors from the SDSS DR7
quasar sample.
"""
# Author: Jake VanderPlas <*****@*****.**>
# 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.plotting import MultiAxes
from astroML.datasets import fetch_dr7_quasar
data = fetch_dr7_quasar()
colors = np.empty((len(data), 5))
colors[:, 0] = data['mag_u'] - data['mag_g']
colors[:, 1] = data['mag_g'] - data['mag_r']
colors[:, 2] = data['mag_r'] - data['mag_i']
colors[:, 3] = data['mag_i'] - data['mag_z']
colors[:, 4] = data['mag_z'] - data['mag_J']
labels = ['u-g', 'g-r', 'r-i', 'i-z', 'z-J']
bins = [
np.linspace(-0.4, 1.0, 100),
np.linspace(-0.4, 1.0, 100),
np.linspace(-0.3, 0.6, 100),
# To report a bug or issue, use the following forum: # https://groups.google.com/forum/#!forum/astroml-general from matplotlib import pyplot as plt from astroML.datasets import fetch_dr7_quasar #---------------------------------------------------------------------- # This function adjusts matplotlib settings for a uniform feel in the textbook. # Note that with usetex=True, fonts are rendered with LaTeX. This may # result in an error if LaTeX is not installed on your system. In that case, # you can set usetex to False. from astroML.plotting import setup_text_plots setup_text_plots(fontsize=8, usetex=True) #------------------------------------------------------------ # Fetch the quasar data data = fetch_dr7_quasar() # select the first 10000 points data = data[:10000] r = data['mag_r'] i = data['mag_i'] z = data['redshift'] #------------------------------------------------------------ # Plot the quasar data fig, ax = plt.subplots(figsize=(5, 3.75)) ax.plot(z, r - i, marker='.', markersize=2, linestyle='none', color='black') ax.set_xlim(0, 5) ax.set_ylim(-0.5, 1.0)
