From 0a628524f44c105abbe791a2a560ecab2a937e82 Mon Sep 17 00:00:00 2001 From: Lana Scravaglieri Date: Thu, 9 Nov 2023 16:12:20 +0100 Subject: [PATCH] Exo 1 issues with python on my machine --- .../exo1/toy_document_orgmode_python_en.org | 117 ++++++++---------- 1 file changed, 52 insertions(+), 65 deletions(-) diff --git a/module2/exo1/toy_document_orgmode_python_en.org b/module2/exo1/toy_document_orgmode_python_en.org index 5782f49..f6e447d 100644 --- a/module2/exo1/toy_document_orgmode_python_en.org +++ b/module2/exo1/toy_document_orgmode_python_en.org @@ -1,8 +1,9 @@ -#+TITLE: Your title -#+AUTHOR: Your name -#+DATE: Today's date +#+TITLE: À propos du calcul de π + +#+AUTHOR: Konrad Hinsen +#+DATE: 2019-03-28 Thu 11:06 #+LANGUAGE: en -# #+PROPERTY: header-args :eval never-export +#+PROPERTY: header-args :eval never-export #+HTML_HEAD: #+HTML_HEAD: @@ -11,84 +12,70 @@ #+HTML_HEAD: #+HTML_HEAD: -* 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. +* En demandant à la lib maths -Like we showed in the video, Python code is included as follows (and -is exxecuted by typing ~C-c C-c~): +Mon ordinateur m'indique que π vaut approximativement: -#+begin_src python :results output :exports both -print("Hello world!") +#+begin_src python :results output :session :exports both +from math import * +pi #+end_src #+RESULTS: -: Hello world! +3.141592653589793 + +* En utilisant la méthode des aiguilles de Buffon -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~. +Mais calculé avec la méthode des [[https://fr.wikipedia.org/wiki/Aiguille_de_Buffon][aiguilles de Buffon]], on obtiendrait comme approximation : #+begin_src python :results output :session :exports both -import numpy -x=numpy.linspace(-15,15) -print(x) +import numpy as np +np.random.seed(seed=42) +N = 10000 +x = np.random.uniform(size=N, low=0, high=1) +theta = np.random.uniform(size=N, low=0, high=pi/2) +2/(sum((x+np.sin(theta))>1)/N) #+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 +3.12891113892 + +* Avec un argument "fréquentiel" de surface + +Sinon, une méthode plus simple à comprendre et ne faisant pas intervenir d'appel à la fonction sinus se base sur le fait que si X∼U(0,1) +et Y∼U(0,1) alors P[X2+Y2≤1]=π/4 + +(voir [[https://fr.wikipedia.org/wiki/M%C3%A9thode_de_Monte-Carlo#D%C3%A9termination_de_la_valeur_de_%CF%80][méthode de Monte Carlo sur Wikipedia]]). Le code suivant illustre ce fait : + +#+begin_src python :results output file :session :var matplot_lib_filename=(org-babel-temp-file "figure" ".png") :exports both import matplotlib.pyplot as plt -plt.figure(figsize=(10,5)) -plt.plot(x,numpy.cos(x)/x) -plt.tight_layout() +np.random.seed(seed=42) +N = 1000 +x = np.random.uniform(size=N, low=0, high=1) +y = np.random.uniform(size=N, low=0, high=1) + +accept = (x*x+y*y) <= 1 +reject = np.logical_not(accept) + +fig, ax = plt.subplots(1) +ax.scatter(x[accept], y[accept], c='b', alpha=0.2, edgecolor=None) +ax.scatter(x[reject], y[reject], c='r', alpha=0.2, edgecolor=None) +ax.set_aspect('equal') 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 ~