This is a package for generating LaTeX maths from julia objects.

This package utilises Julias homoiconicity to convert expressions to LaTeX-formatted strings. Latexify.jl supplies functionalities for converting a range of different Julia objects, including:

- Expressions,
- Strings,
- Numbers (including rationals and complex),
- Symbolic expressions from SymEngine.jl,
- ParameterizedFunctions and ReactionNetworks from DifferentialEquations.jl,
- Other types for which a user recipe has been defined

as well as arrays or dicts of supported types.

To extend Latexify to work with your own type, you define a recipe using the
`@latexrecipe`

macro. See the documentation.

```
using Latexify
ex = :(x/(y+x)^2)
latexify(ex)
```

This generates a LaTeXString (from LaTeXStrings.jl) which, when printed looks like:

`$\frac{x}{\left( y + x \right)^{2}}$`

And when this LaTeXString is displayed in an environment which supports the tex/latex MIME type (Jupyter and Pluto notebooks, Jupyterlab and Hydrogen for Atom) it will automatically render as:

Latexify.jl is equipped to convert a whole range of types to latex formatted
maths. This includes primitive types such as `Symbol`

s and `Complex`

, but also
of containers such as `Array`

s and `Dict`

s.

```
using Latexify
print(latexify("x+y/(b-2)^2"))
```

outputs:

`$x + \frac{y}{\left( b - 2 \right)^{2}}$`

```
arr = ["x/y" 3//7 2+3im; 1 :P_x :(gamma(3))]
latexify(arr)
```

The GitHub website does not really support rendering of equations in the README file, so I therefore refer you to the documentation for more info/examples.

You can add support for a type via `@latexrecipe`

```
using Latexify
struct Ket{T}
x::T
end
@latexrecipe function f(x::Ket)
return Expr(:latexifymerge, "\\left|", x.x, "\\right>")
end
latexify(:($(Ket(:a)) + $(Ket(:b))))
```

The DifferentialEquations.jl suite has some nifty tools for generating differential equations. One of them is ParameterizedFunctions which allows you to type in an ODE in something which looks very much like just plain mathematics. The ability to latexify such ODEs is pretty much what lured me to create this package.

```
using ParameterizedFunctions
using Latexify
f = @ode_def positiveFeedback begin
dx = v*y^n/(k^n+y^n) - x
dy = x/(k_2+x) - y
end v n k k_2
latexify(f)
```

outputs:

DiffEqBiological.jl provides another cool domain-specific language which allows you to generate equations using a chemical arrow notation.

```
using DiffEqBiological
using Latexify
rn = @reaction_network demoNetwork begin
(r_bind, r_unbind), A + B ↔ C
Hill(C, v, k, n), 0 --> X
d_x, X --> 0
end r_bind r_unbind v k n d_x
latexify(rn)
```

Or you can output the arrow notation directly to latex:

`latexify(rn; env=:arrow)`

There are more stuff that you can do, but for that I will refer you to the docs.

One can use `ImageInTerminal`

with the `Sixel`

backend in order to display rendered `latexify`

ed equations.

`copy_to_clipboard(::Bool)`

, toggle automatic copying of the resulting LaTeX code to the clipboard (default is false).`auto_display(::Bool)`

toggles automatic display of your output, even if it is not the last command to have run.`set_default(; kwargs...)`

, set your own default kwargs for your Julia session. This is not to be used within a package since the effect is global.`reset_default(; kwargs...)`

, reset the changes you made with the above command.`get_default(; kwargs...)`

, view the changes you have made to the default kwargs.

This package is registered in the Julia registry, so to install it you can just run

`Pkg.add("Latexify")`

For further information see the docs.

I would be happy to receive feedback, suggestions, and help with improving this package. Please feel free to open an issue or a PR.

If you want to add support for types defined in another package, primarily create a PR in that package with a recipe. Latexify.jl is not intended to be a collection of recipes for different types. The exceptions are the few types which were included before the recipe system was finished. If the other package is hesitant to pull in Latexify as a dependency, you can either use Requires.jl, or create a separate glue package. If you do add support for another package, please help update the list below:

- Many base types
- LaTeXStrings.jl
- DifferentialEquations.jl
- DiffEqBiological.jl
- ParametrizedFunctions.jl
- DataFrames.jl
- Symbolics.jl
- Unitful.jl (via UnitfulLatexify.jl)

And more ...