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7cb84b8d37d239738c7c51278d3e7831
mooc-rr
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cfd8fcb4
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cfd8fcb4
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Nov 12, 2020
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7cb84b8d37d239738c7c51278d3e7831
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module2/exo3/exercice_python_en.org
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cfd8fcb4
#+TITLE:
Your titl
e
#+TITLE:
Votre titr
e
#+AUTHOR:
Your name
#+AUTHOR:
Votre nom
#+DATE:
Today's date
#+DATE:
La date du jour
#+LANGUAGE:
en
#+LANGUAGE:
fr
# #+PROPERTY: header-args :eval never-export
# #+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/htmlize.css"/>
...
@@ -11,84 +11,42 @@
...
@@ -11,84 +11,42 @@
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/lib/js/jquery.stickytableheaders.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/lib/js/jquery.stickytableheaders.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/readtheorg/js/readtheorg.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="http://www.pirilampo.org/styles/readtheorg/js/readtheorg.js"></script>
* S
ome explanations
* S
avoir faire un calcul simple soi-même
This is an org-mode document with code examples in R. Once opened in
#+begin_src python :results output :session :exports both
Emacs, this document can easily be exported to HTML, PDF, and Office
import matplotlib.pyplot as plt
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
import numpy as np
is exxecuted by typing ~C-c C-c~):
#+begin_src python :results output :exports both
data = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]
print("Hello world!"
)
x=np.array(data
)
#+end_src
#+end_src
#+RESULTS:
#+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:
* Réaliser un affichage graphique
#+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:
1) Sequence plot
#+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()
#+begin_src python :results output graphics file :session :var matplot_lib_filename=(org-babel-temp-file "figure1" ".png") :exports both
plt.clf()
plt.plot(x)
plt.savefig(matplot_lib_filename)
plt.savefig(matplot_lib_filename)
print(matplot_lib_filename)
print(matplot_lib_filename)
#+end_src
#+end_src
#+RESULTS:
#+RESULTS:
[[file:./cosxsx.png]]
[[file:/tmp/babel-oymgiS/figure1oaBBrp.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
#+begin_src python :results output graphics file :session :var matplot_lib_filename=(org-babel-temp-file "figure2" ".png") :exports both
the org document. It's a plain file, here named ~cosxsx.png~. You have
plt.clf()
to commit it explicitly if you want your analysis to be legible and
plt.hist(x)
understandable on GitLab.
plt.savefig(matplot_lib_filename)
print(matplot_lib_filename)
Finally, don't forget that we provide in the resource section of this
#+end_src
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
#+RESULTS:
by your computational document.
[[file:/tmp/babel-oymgiS/figure23T6EDX.png]]
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