# MathJax

"MathJax is a cross-browser JavaScript library that displays mathematical equations in web browsers, using LaTeX math and MathML markup. MathJax is released as open-source software under the Apache license."
Source: http://en.wikipedia.org/wiki/MathJax

# Tiki20+

Native support was added via https://sourceforge.net/p/tikiwiki/code/68624 and should appear here: https://packages.tiki.org/

# Before Tiki 20

Add the following line to tiki-admin.php -> Look and Feel -> Custom HTML Content:

To include in all pages



To include only in one page (choose your own page name)
{if \$page eq 'MathJax'}

{/if}

The other possibility (working in http and https) is to install (copy) the MathJax locally

as described at: http://docs.mathjax.org/en/latest/installation.html
and add to tiki-admin.php -> Look and Feel -> Custom HTML Content:

For local instalation



Then, just use math in your page using PluginHTML. It will sometimes work without that but there can be conflicts with wiki syntax or other code. Click here to see the source of the current wiki page for an example.

Nice presentation won't load just after you save a page. So after saving, go to another page, and click back to your page

Below are math samples copied from http://www.mathjax.org/demos/tex-samples/. Right-click on the formulae for more options.

# The Lorenz Equations

\begin{aligned} \dot{x} & = \sigma(y-x) \\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{aligned}

# The Cauchy-Schwarz Inequality

$\left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right)$

# A Cross Product Formula

$\mathbf{V}_1 \times \mathbf{V}_2 = \begin{vmatrix} \mathbf{i} & \mathbf{j} & \mathbf{k} \\ \frac{\partial X}{\partial u} & \frac{\partial Y}{\partial u} & 0 \\ \frac{\partial X}{\partial v} & \frac{\partial Y}{\partial v} & 0 \end{vmatrix}$

# The probability of getting $$k$$ heads when flipping $$n$$ coins is

$P(E) = {n \choose k} p^k (1-p)^{ n-k}$

# An Identity of Ramanujan

$\frac{1}{\Bigl(\sqrt{\phi \sqrt{5}}-\phi\Bigr) e^{\frac25 \pi}} = 1+\frac{e^{-2\pi}} {1+\frac{e^{-4\pi}} {1+\frac{e^{-6\pi}} {1+\frac{e^{-8\pi}} {1+\ldots} } } }$