Demo

5.1 Suite

  1. ljzoiej fizejf
  2. zefj zoeif
  3. zefij zef


#### Sousous titre



\exo 

## sous section
### sou sous sedctpo,

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\BeginKnitrBlock{theorem}<div class="theorem"><span class="theorem" id="thm:unnamed-chunk-1"><strong>(\#thm:unnamed-chunk-1) </strong></span>Here is my theorem. $E=mc^2$</div>\EndKnitrBlock{theorem}
  1. Réponse à la premier question \(E=mc^2\) ````
Définition 5.1 Un court circuit est un circuit court.. 
install.packages("bookdown")
# or the development version
# devtools::install_github("rstudio/bookdown")

Et voici une équation inline \(E=mc^2\). Affichage d’un résultat avec SI units: \(\SI{3.2e12}{\kilo\gram\per\second}\). Ne fonctionne pas en HTML..

Equation en ligne \[2x = 3 -\sqrt{2}\]

\[\begin{align} x &= 2x +5 \\ -x &= 5 \\ x &= -5 \end{align}\]

Les vecteurs colonnes miam: \[\overrightarrow{v(t)} = \begin{pmatrix}v_x(t) &=& x'(t)\\ v_y(t) &=& y'(t) \end{pmatrix}\]

Insérer une image en utilisant le code markdown ![image](figures/fig.png)

image

En modifiant la largeur: 200px

image réduite 200 pix{width: 200px;}

En utilisant knitr:

Figures and tables with captions will be placed in figure and table environments, respectively

knitr::include_graphics("figures/fig.png")
Here is a nice figure!

Figure 5.1: Here is a nice figure!

Figures and tables with captions will be placed in figure and table environments, respectively

knitr::include_graphics("figures/fig.png")
Here is a nice figure!

Figure 5.2: Here is a nice figure!

Légende

A Retenir 5.1 Here is my theorem.
Définition 5.2 Un court circuit est un circuit court.. 
install.packages("bookdown")
# or the development version
# devtools::install_github("rstudio/bookdown")

Remember each Rmd file contains one and only one chapter, and a chapter is defined by the first-level heading #.

To compile this example to PDF, you need XeLaTeX. You are recommended to install TinyTeX (which includes XeLaTeX): https://yihui.org/tinytex/.

import numpy as np
import matplotlib.pyplot as plt
import numpy.random as rng
import matplotlib.cm as cm
from matplotlib.animation import FuncAnimation

radii=(rng.random(int(1e3))+1)**2
iota=2*np.pi*rng.random(int(1e3))
x_posit=np.sqrt(radii)*np.cos(iota)
y_posit=np.sqrt(radii)*np.sin(iota)
plt.plot(x_posit, y_posit, 'go')
## [<matplotlib.lines.Line2D object at 0x7f9b1202dc18>]
plt.show()