import numpy as np
from matplotlib import pyplot as plt
# warning: due to a bug in healpy, importing it before pylab can cause
# a segmentation fault in some circumstances.
import healpy as hp
from astroML.datasets import fetch_wmap_temperatures
#------------------------------------------------------------
# Fetch the wmap data
wmap_unmasked = fetch_wmap_temperatures(masked=False)
#------------------------------------------------------------
# plot the unmasked map
fig = plt.figure(1)
hp.mollview(wmap_unmasked, min=-1, max=1, title='Raw WMAP data',
fig=1, cmap=plt.cm.jet, unit=r'$\Delta$T (mK)')
plt.show()
"""
# Author: Jake VanderPlas <*****@*****.**>
# License: BSD
# The figure produced by this code is published in the textbook
# "Statistics, Data Mining, and Machine Learning in Astronomy" (2013)
# For more information, see http://astroML.github.com
import numpy as np
from matplotlib import pyplot as plt
# warning: due to a bug in healpy, importing it before pylab can cause
# a segmentation fault in some circumstances.
import healpy as hp
from astroML.datasets import fetch_wmap_temperatures
#------------------------------------------------------------
# Fetch the wmap data
wmap_unmasked = fetch_wmap_temperatures(masked=False)
#------------------------------------------------------------
# plot the unmasked map
fig = plt.figure(1)
hp.mollview(wmap_unmasked,
min=-1,
max=1,
title='Raw WMAP data',
fig=1,
cmap=plt.cm.jet,
unit=r'$\Delta$T (mK)')
plt.show()
# 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)
#------------------------------------------------------------
# First plot an example pixellization
# Prepare the healpix pixels
NSIDE = 4
m = np.arange(hp.nside2npix(NSIDE))
print "number of pixels:", len(m)
# Plot the pixelization
fig = plt.figure(1, figsize=(5, 3.75))
hp.mollview(m, nest=True, title="HEALPix Pixels (Mollweide)", fig=1)
# remove colorbar: we don't need it for this plot
fig.delaxes(fig.axes[1])
#------------------------------------------------------------
# Next plot the wmap pixellization
wmap_unmasked = fetch_wmap_temperatures(masked=True)
# plot the unmasked map
fig = plt.figure(2, figsize=(5, 3.75))
hp.mollview(wmap_unmasked, min=-1, max=1, title='Raw WMAP data',
unit=r'$\Delta$T (mK)', fig=2)
fig.axes[1].texts[0].set_fontsize(8)
plt.show()