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LaTeX lets you create lovely, complex mathematical functions from typed text. Plotly will render LaTeX in annotations, labels, and titles. In this post, we’ll show how it works.

### 1. MATLAB plotting with LaTeX

First, here’s an example using Plotly’s MATLAB API. This is a visualization of Bessel Functions of the first kind, solutions for a differential equation. It’s a useful function for studying and understanding heat conduction, how waves travel, and more. The MATLAB code below creates our plot.

plot(X,J,'LineWidth',1.5)
axis([0 20 -.5 1])
grid on
legend('J_0','J_1','J_2','J_3','J_4','Location','Best')
title('Bessel Functions of the First Kind for v = 0,1,2,3,4')
xlabel('X')
ylabel('J_v(X)')
X = 0:0.1:20;
X = 0:0.1:20;
J = zeros(5,201);
for i = 0:4
J(i+1,:) = besselj(i,X);
end
plot(X,J,'LineWidth',1.5)
axis([0 20 -.5 1])
grid on
legend('J_0','J_1','J_2','J_3','J_4','Location','Best')
title('Bessel Functions of the First Kind for v = 0,1,2,3,4')
xlabel('X')
ylabel('J_v(X)')
fig2plotly();


The code generates a web-based version of our plot. We can apply a theme to change the colors, layouts, and fonts. Then, we can share the plot in an iframe, as seen below.

The x axis contains the following formula. Plotly renders the LaTeX version of it.

$x^2 frac{d^2 y}{dx^2} + x frac{dy}{dx} + (x^2 – alpha^2)y = 0$

The plot is saved at a URL: https://plot.ly/~MattSundquist/2135. The URL contains the data, plot and code to translate the plot between MATLAB, R, Python, Julia, and JavaScript. ### 2. Python and matplotlib plotting with LaTeX

We can make matplotlib and Python plots into web-based plots. This is an example using Plotly’s Python API. Here we’re using a Gaussian distribution to study random variables and see where they fall on what is sometimes called a “bell curve.” We can add the standard deviation formula to our plot.

import matplotlib.pyplot as plt   # side-stepping mpl's backend
import plotly.plotly as py
import plotly.tools as tls
from plotly.graph_objs import *
%matplotlib inline
py.sign_in("IPython.Demo", "1fw3zw2o13")
fig1 = plt.figure()

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2.0, 2.0, 10000) # The x-values
sigma = np.linspace(0.4, 1.0, 4) # Some different values of sigma

# Here we evaluate a Gaussians for each sigma
gaussians = [(2*np.pi*s**2)**-0.5 * np.exp(-0.5*x**2/s**2) for s in sigma]

ax = plt.axes()

for s,y in zip(sigma, gaussians):
ax.plot(x, y, lw=1.25, label=r"$sigma = %3.2f$"%s)

formula = r"$y(x)=frac{1}{sqrt{2pisigma^2}}e^{-frac{x^2}{2sigma^2}}$"

ax.text(0.05, 0.80, formula, transform=ax.transAxes, fontsize=20)
ax.set_xlabel(r"$x$", fontsize=18)
ax.set_ylabel(r"$y(x)$", fontsize=18)
ax.legend()
plt.show()


Here is our plot:

The annotation looks like this in the GUI: ### 3. R plotting with LaTeX

We can make plots with R. Here’s an example using the Plotly R API.

library(plotly)

trace1 <- list(
x = c(1, 2, 3, 4),
y = c(1, 4, 9, 16),
name = "$alpha_{1c} = 352 pm 11 text{ km s}^{-1}$",
type = "scatter"
)
trace2 <- list(
x = c(1, 2, 3, 4),
y = c(0.5, 2, 4.5, 8),
name = "$beta_{1c} = 25 pm 11 text{ km s}^{-1}$",
type = "scatter"
)
data <- list(trace1, trace2)
layout <- list(
xaxis = list(title = "$sqrt{(n_text{c}(t|{T_text{early}}))}$"),
yaxis = list(title = "$d, r text{ (solar radius)}$")
)
response <- py$plotly(data, kwargs=list(layout=layout, filename="latex", fileopt="overwrite")) url <- response$url

The title was added in the GUI, and is written as ‘$LaTeX$’. We embed with this snippet; every Plotly graph can similarly be embedded in websites, blogs, and notebooks.

<iframe width="450" frameborder="0" seamless="seamless" scrolling="no" src="https://plot.ly/~MattSundquist/2138.embed?width=500&height=500"></iframe>


### 4. Mathematica plotting with LaTeX

A user-contributed Mathematica API is in the works, which lets us turn our Mathematica plots into D3, web-based plots. Here is our code:

Plotly[Sin[Exp[x]], {x, -Pi, Pi}, AxesLabel -> {"e", "s"}]


And our plot:

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