#+TITLE:  Your title
#+AUTHOR: Your name
#+DATE:   Today's date
#+LANGUAGE: en
# #+PROPERTY: header-args :eval never-export

#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="http://www.pirilampo.org/styles/readtheorg/css/htmlize.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="http://www.pirilampo.org/styles/readtheorg/css/readtheorg.css"/>
#+HTML_HEAD: <script src="https://ajax.googleapis.com/ajax/libs/jquery/2.1.3/jquery.min.js"></script>
#+HTML_HEAD: <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/js/bootstrap.min.js"></script>
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* Some explanations

This is an org-mode document with code examples in R.  Once opened in
Emacs, this document can easily be exported to HTML, PDF, and Office
formats. For more information on org-mode, see
https://orgmode.org/guide/.

When you type the shortcut =C-c C-e h o=, this document will be
exported as HTML. All the code in it will be re-executed, and the
results will be retrieved and included into the exported document. If
you do not want to re-execute all code each time, you can delete the #
and the space before ~#+PROPERTY:~ in the header of this document.

Like we showed in the video, Python code is included as follows (and
is exxecuted by typing ~C-c C-c~):

#+begin_src python :results output :exports both
print("Hello world!")
#+end_src

#+RESULTS:
: Hello world!

And now the same but in an Python session. With a session, Python's
state, i.e. the values of all the variables, remains persistent from
one code block to the next. The code is still executed using ~C-c
C-c~.

#+begin_src python :results output :session :exports both
import numpy
x=numpy.linspace(-15,15)
print(x)
#+end_src

#+RESULTS:
#+begin_example
[-15.         -14.3877551  -13.7755102  -13.16326531 -12.55102041
 -11.93877551 -11.32653061 -10.71428571 -10.10204082  -9.48979592
  -8.87755102  -8.26530612  -7.65306122  -7.04081633  -6.42857143
  -5.81632653  -5.20408163  -4.59183673  -3.97959184  -3.36734694
  -2.75510204  -2.14285714  -1.53061224  -0.91836735  -0.30612245
   0.30612245   0.91836735   1.53061224   2.14285714   2.75510204
   3.36734694   3.97959184   4.59183673   5.20408163   5.81632653
   6.42857143   7.04081633   7.65306122   8.26530612   8.87755102
   9.48979592  10.10204082  10.71428571  11.32653061  11.93877551
  12.55102041  13.16326531  13.7755102   14.3877551   15.        ]
#+end_example

Finally, an example for graphical output:
#+begin_src python :results output file :session :var matplot_lib_filename="./cosxsx.png" :exports results
import matplotlib.pyplot as plt

plt.figure(figsize=(10,5))
plt.plot(x,numpy.cos(x)/x)
plt.tight_layout()

plt.savefig(matplot_lib_filename)
print(matplot_lib_filename)
#+end_src

#+RESULTS:
[[file:./cosxsx.png]]

Note the parameter ~:exports results~, which indicates that the code
will not appear in the exported document. We recommend that in the
context of this MOOC, you always leave this parameter setting as
~:exports both~, because we want your analyses to be perfectly
transparent and reproducible.

Watch out: the figure generated by the code block is /not/ stored in
the org document. It's a plain file, here named ~cosxsx.png~. You have
to commit it explicitly if you want your analysis to be legible and
understandable on GitLab.

Finally, don't forget that we provide in the resource section of this
MOOC a configuration with a few keyboard shortcuts that allow you to
quickly create code blocks in Python by typing ~<p~, ~<P~ or ~<PP~
followed by ~Tab~.

Now it's your turn! You can delete all this information and replace it
by your computational document.