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197adccdacbb60bb13053a3357332d5b
mooc-rr
Commits
3acaf1f5
Commit
3acaf1f5
authored
Sep 05, 2024
by
Gwenael Dumont
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toy_document_fr.Rmd
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toy_document_fr.html
module2/exo1/toy_document_fr.Rmd
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3acaf1f5
---
output:
html_document: default
pdf_document: default
---
# À propos du calcul de pi
_Arnaud Legrand_
_25 juin 2018_
## En demandant à la lib maths
Mon ordinateur m’indique que $\pi$ vaut _approximativement_
...
...
module2/exo1/toy_document_fr.html
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...
...
@@ -166,8 +166,7 @@ pre code {
<div
id=
"à-propos-du-calcul-de-pi"
class=
"section level1"
>
<h1>
À propos du calcul de pi
</h1>
<p><em>
Arnaud Legrand
</em></p>
<p><em>
25 juin 2018
</em></p>
<p><em>
Arnaud Legrand
</em>
<em>
25 juin 2018
</em></p>
<div
id=
"en-demandant-à-la-lib-maths"
class=
"section level2"
>
<h2>
En demandant à la lib maths
</h2>
<p>
Mon ordinateur m’indique que
<span
class=
"math inline"
>
\(\pi\)
</span>
vaut
<em>
approximativement
</em></p>
...
...
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! LaTeX Error: Unicode character π (U+03C0)
not
set
up
for
use
with
LaTeX
.
See
the
LaTeX
manual
or
LaTeX
Companion
for
explanation
.
Type
H
<
return
>
for
immediate
help
.
...
l
.120
Mon
ordinateur
m
'indique que π
vaut \emph{approximativement}
Here is how much of TeX'
s
memory
you
used
:
11333
strings
out
of
475538
175182
string
characters
out
of
5775359
1926960
words
of
memory
out
of
5000000
33862
multiletter
control
sequences
out
of
15000
+
600000
577316
words
of
font
info
for
42
fonts
,
out
of
8000000
for
9000
14
hyphenation
exceptions
out
of
8191
89
i
,
3
n
,
93
p
,
291
b
,
434
s
stack
positions
out
of
10000
i
,
1000
n
,
20000
p
,
200000
b
,
200000
s
! ==> Fatal error occurred, no output PDF file produced!
module2/exo1/toy_document_fr.tex
0 → 100644
View file @
3acaf1f5
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uxe0-propos-du-calcul-de-pi
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%
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À propos du calcul de pi
}
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uxe0-propos-du-calcul-de-pi
}}
\emph
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Arnaud Legrand
}
\emph
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25 juin 2018
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en-demandant-uxe0-la-lib-maths
}{
%
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En demandant à la lib
maths
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en-demandant-uxe0-la-lib-maths
}}
Mon ordinateur m'indique que π vaut
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approximativement
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pi
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## [1] 3.141593
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en-utilisant-la-muxe9thode-des-aiguilles-de-buffon
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%
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{
En utilisant la méthode des aiguilles de
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}
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en-utilisant-la-muxe9thode-des-aiguilles-de-buffon
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Mais calculé avec la
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méthode
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des
\href
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https://fr.wikipedia.org/wiki/Aiguille
_
de
_
Buffon
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aiguilles de
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approximation
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}
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{
(
}
\FunctionTok
{
mean
}
\NormalTok
{
(x
}
\SpecialCharTok
{
+
}
\FunctionTok
{
sin
}
\NormalTok
{
(theta)
}
\SpecialCharTok
{
\textgreater
{}}
\DecValTok
{
1
}
\NormalTok
{
))
}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] 3.14327
\end{verbatim}
\hypertarget
{
avec-un-argument-fruxe9quentiel-de-surface
}{
%
\subsection
{
Avec un argument ``fréquentiel'' de
surface
}
\label
{
avec-un-argument-fruxe9quentiel-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
\href
{
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{Shaded}
\begin{Highlighting}
[]
\FunctionTok
{
set.seed
}
\NormalTok
{
(
}
\DecValTok
{
42
}
\NormalTok
{
)
}
\NormalTok
{
N
}
\OtherTok
{
=
}
\DecValTok
{
1000
}
\NormalTok
{
df
}
\OtherTok
{
=
}
\FunctionTok
{
data.frame
}
\NormalTok
{
(
}
\AttributeTok
{
X =
}
\FunctionTok
{
runif
}
\NormalTok
{
(N),
}
\AttributeTok
{
Y =
}
\FunctionTok
{
runif
}
\NormalTok
{
(N))
}
\NormalTok
{
df
}
\SpecialCharTok
{$}
\NormalTok
{
Accept
}
\OtherTok
{
=
}
\NormalTok
{
(
df
}
\SpecialCharTok
{$}
\NormalTok
{
X
}
\SpecialCharTok
{
**
}
\DecValTok
{
2
}
\SpecialCharTok
{
+
}
\NormalTok
{
df
}
\SpecialCharTok
{$}
\NormalTok
{
Y
}
\SpecialCharTok
{
**
}
\DecValTok
{
2
}
\SpecialCharTok
{
\textless
{}
=
}
\DecValTok
{
1
}
\NormalTok
{
)
}
\FunctionTok
{
library
}
\NormalTok
{
(
ggplot
2
)
}
\end
{
Highlighting
}
\end
{
Shaded
}
\begin
{
verbatim
}
## Warning: le package 'ggplot
2
' a été compilé avec la version R
4
.
3
.
3
\end
{
verbatim
}
\begin
{
Shaded
}
\begin
{
Highlighting
}
[]
\FunctionTok
{
ggplot
}
\NormalTok
{
(
df,
}
\FunctionTok
{
aes
}
\NormalTok
{
(
}
\AttributeTok
{
x
=
}
\NormalTok
{
X,
}
\AttributeTok
{
y
=
}
\NormalTok
{
Y,
}
\AttributeTok
{
color
=
}
\NormalTok
{
Accept
))
}
\SpecialCharTok
{
+
}
\FunctionTok
{
geom
\_
point
}
\NormalTok
{
(
}
\AttributeTok
{
alpha
=
}
\NormalTok
{
.
}
\DecValTok
{
2
}
\NormalTok
{
)
}
\SpecialCharTok
{
+
}
\FunctionTok
{
coord
\_
fixed
}
\NormalTok
{
()
}
\SpecialCharTok
{
+
}
\FunctionTok
{
theme
\_
bw
}
\NormalTok
{
()
}
\end
{
Highlighting
}
\end
{
Shaded
}
\includegraphics
{
toy
_
document
_
fr
_
files
/
figure
-
latex
/
unnamed
-
chunk
-
3
-
1
.pdf
}
Il est alors aisé d'obtenir une approximation
(
pas terrible
)
de π en
comptant combien de fois, en moyenne, X
2
+
Y
2
est inférieur à
1
:
\begin
{
Shaded
}
\begin
{
Highlighting
}
[]
\DecValTok
{
4
}
\SpecialCharTok
{
*
}
\FunctionTok
{
mean
}
\NormalTok
{
(
df
}
\SpecialCharTok
{$}
\NormalTok
{
Accept)
}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] 3.156
\end{verbatim}
\end{document}
mooc-rr.Rproj
0 → 100644
View file @
3acaf1f5
Version: 1.0
RestoreWorkspace: Default
SaveWorkspace: Default
AlwaysSaveHistory: Default
EnableCodeIndexing: Yes
UseSpacesForTab: Yes
NumSpacesForTab: 2
Encoding: UTF-8
RnwWeave: Sweave
LaTeX: pdfLaTeX
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