title: "On the computation of pi" auteur : Meiling WU output: html_notebook #+HTML_HEAD: #+HTML_HEAD: #+HTML_HEAD: #+HTML_HEAD: #+HTML_HEAD: #+HTML_HEAD: #+PROPERTY: header-args :session :exports both * Asking the maths library My computer tells me that $\pi$ is /approximatively/ #+begin_src R :results output :session *R* :exports both pi #+end_src #+RESULTS: : [1] 3.141593 * Buffon's needle Applying the method of [[https://en.wikipedia.org/wiki/Buffon%2527s_needle_problem][Buffon's needle]], we get the *approximation* #+begin_src R :results output :session *R* :exports both set.seed(42) N = 100000 x = runif(N) theta = pi/2*runif(N) 2/(mean(x+sin(theta)>1)) #+end_src #+RESULTS: : [1] 3.14327 * Using a surface fraction argument A method that is easier to understand and does not make use of the $\sin$ function is based on the fact that if $X\sim U(0,1)$ and $Y\sim U(0,1)$, then $P[X^2+Y^2\leq 1] = \pi/4$ (see [[https://en.wikipedia.org/wiki/Monte_Carlo_method]["Monte Carlo method" on Wikipedia]]). The following code uses this approach: #+begin_src R :results output graphics :file figure_pi_mc1.png :exports both :width 600 :height 400 :session *R* set.seed(42) N = 1000 df = data.frame(X = runif(N), Y = runif(N)) df$Accept = (df$X**2 + df$Y**2 <=1) library(ggplot2) ggplot(df, aes(x=X,y=Y,color=Accept)) + geom_point(alpha=.2) + coord_fixed() + theme_bw() #+end_src #+RESULTS: [[file:figure_pi_mc1.png]] It is then straightforward to obtain a (not really good) approximation to $\pi$ by counting how many times, on average, $X^2 + Y^2$ is smaller than 1: #+begin_src R :results output :session *R* :exports both 4*mean(df$Accept) #+end_src #+RESULTS: : [1] 3.156