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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

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<title>Summary and excercise — Python4Astronomers 2.0 documentation</title>

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<a class="brand" title="Documentation Home" href="../index.html">python4astronomers</a>

<ul>

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<h3>Navigation</h3>

<ul>

</a>

</li>

« previous

</a>

</li>

<li>

<a href="../index.html">Python4Astronomers 2.0 documentation</a>

</li>

<li><a href="files.html" accesskey="U">Reading and Writing files</a> »</li>

<li>Summary and excercise</li>

</ul>

</div>

<h1>Summary and excercise<a class="headerlink" href="#summary-and-excercise" title="Permalink to this headline">¶</a></h1>

These pages show a way to read most of the files astronomers will need in their day-to-day work.

However, no format is so obscure that is could not be used and there are certainly

files out there that will not fall into one of the categories above.

Here are some hints:

<ul>

<li>If it is an ASCII file, often some manual editing will do the job.

E.g. in a space-separated table there are missing values:

<div class="highlight-python"><div class="highlight"><pre>col1 col2 col3

aaaa 1 2

bbbb 3

cccc 4 5

</pre></div>

</div>

In a text editor put <code class="docutils literal">nan</code> in the empty space and <code class="docutils literal">aciitable</code> will read the file.

</li>

<li>Google. No file format is too obscure to find a reader for it.

</li>

<li>When writing files, use standard formats like fits, ascii, hdu5 and not

your personal, undocumented binary format.

</li>

</ul>

Final exercise

A word of warning: This excercise makes use of almost all concepts shown in

the tutorial this far, don’t get frustrated. If you are stuck, you are

allowed to peak at the solution!

We want to compare the X-ray luminosity function (XLF) of young

star-forming regions.

The data is taken from the literature, but comes in different formats.

Read the tables and plot the XLF (fraction of stars vs. log(L_X)) of all

three clusters.

Download the example <a class="reference download internal" href="../_downloads/files-excercise.tar.gz"><code class="xref download docutils literal">data</code></a>:

<div class="highlight-python"><div class="highlight"><pre>from astropy.extern.six.moves.urllib import request

import tarfile

url = 'http://python4astronomers.github.com/_downloads/files-excercise.tar.gz'

tarfile.open(fileobj=request.urlopen(url), mode='r|gz').extractall()

cd files

</pre></div>

</div>

In your directory there are 3 files:

<dd>The final results of the Chandra Orion Ultradeep project (COUP).

The logarithmic X-ray luminosities are in column <code class="docutils literal">Ltc</code>.</dd>

<dd>CDS machine readable table, downloaded directly from CDS.

All documentation is in the file itself. Open the file in your

preferred text viewer (vi, emacs, less) and you will see that column

<code class="docutils literal">XLum</code> contains the X-ray luminosities in unites of 1e28 erg/s.</dd>

</dl>

</div></blockquote>

Read each data file and put the X-ray luminosity in a varible. Normalize all

luminosity functions to 1 at log(L_X) = 29.3.

Make a plot.

Hint 1 All tables have missing L_X values. Be careful when plotting.

Remember boolean masks from <a class="reference internal" href="../core/numpy_scipy.html">A Crash Course in Scientific Python: 2D STIS Reduction</a>?:

<div class="highlight-python"><div class="highlight"><pre>index_good_data = (dat['Ltc'] > 0)

# make new array, which only has good L_X values

# These two lines can be concatenated:

good_LX_values = dat['Ltc'][dat['Ltc'] > 0]

</pre></div>

</div>

Hint 2 If you have all you luminosities in vector called <cite>L_X</cite> then

this code will plot a good XLF:

<div class="highlight-python"><div class="highlight"><pre>L_X.sort()

# np.arange(len(L_X)) makes a y-axis from 0 to len(L_X)

# np.arange(len(L_X), 0, -1) makes a y-axis from len(L_X) to 0

# -> dtype = float, because 4 / 5 = 0 (integer devision)

yaxis = np.arange(len(L_X), 0, -1, dtype = float)

plt.plot(L_X, yaxis)

</pre></div>

</div>

Extra points:

<dt><code class="docutils literal">Winston2010tab4.txt</code></dt>

<dd>From Winston and al (2010). I took this table from the journal

page and just pasted it into a text file. Open the file in your

preferred text viewer (vi, emacs, less) to decide how

you could read this file.

The logarithmic X-ray luminosities are in column <code class="docutils literal">L_X</code>.</dd>

</dl>

</div></blockquote>

</div>

Click to Show/Hide Solution <div class="panel7">This is a complex excercise and several solutions are possible. This is one:

<div class="highlight-python"><div class="highlight"><pre>import asciitable

import atpy

COUP = atpy.Table('COUP.fits')

# atpy.Table(... , type = 'ascii') tells atpy to use asciitable to read the file

IC348 = atpy.Table('IC348.dat', type = 'ascii')

# take only L_X greater than 0, that gets rid of nans etc.

# Nans in the table mark missing values and things like that.

couplx=COUP.Ltc[COUP.Ltc > 0.]

# L_X is in linear units of 1e28 erg/s

# take logarithm and add 25

IC348lx = 28. + np.log10(IC348.XLum[np.isfinite(IC348.XLum)])

# sort - highest first

couplx.sort()

IC348lx.sort()

Lx0 = 29.3 # normalize L_X at 29.3

# np.arange(len(couplx)) makes a y-axis from 0 to len(couplx)

# np.arange(len(couplx), 0, -1) makes a y-axis from len(couplx) to 0

# -> dtype = float, because 4 / 5 = 0 (integer devision)

# (IC348lx>Lx0).sum() -> number of sources brighther than Lx0

plt.plot(couplx, np.arange(len(couplx), 0, -1, dtype=float)/(couplx>Lx0).sum(), lw=2.,label = 'ONC')

plt.plot(IC348lx, np.arange(len(IC348lx),0 ,-1, dtype=float)/(IC348lx>Lx0).sum(), '--', lw=3.,label = 'IC 348')

# add some nice labels etc.

plt.xlabel('log $L_X$ [erg/s]')

plt.xlim([28,32])

plt.legend(loc = 'upper right')

#Extra points

winston = atpy.Table('Winston2010tab4.txt', type='ascii', \

Reader = asciitable.Tab, comment='#', guess=False, fill_values=([' ... ', 'nan']))

Serplx = winston.L_X[winston.L_X > 0]

Serplx.sort()

plt.plot(Serplx, np.arange(len(Serplx), 0, -1, dtype=float)/(Serplx>Lx0).sum(), 's', label = 'Serpens')

</pre></div>

</div>

And this is how it could look like:

</div></div>

</div>

<div class="sphinxsidebarwrapper"><h3>Page Contents</h3>

<ul>

<li><a class="reference internal" href="#">Summary and excercise</a></li>

</ul>

<h4>Previous topic</h4>

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title="previous chapter">Reading and Writing binary data</a>

<h4>Next topic</h4>

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