Note
Go to the end to download the full example code.
Sphinx-Gallery#
This example shows how to add a new example when using Sphinx-Gallery.
To use Sphinx-Gallery, first install the package with this command:
pip install sphinx-gallery
Then, add the package to the extensions variable in your Sphinx conf.py file:
extensions = [
"sphinx_gallery.gen_gallery",
]
Plot a simple sphere using PyVista#
This code plots a simple sphere using PyVista.
import pyvista as pv
pv.set_jupyter_backend("html")
sphere = pv.Sphere()
sphere.plot()
Plot a simple sphere using PyVista with a plotter
plotter = pv.Plotter(notebook=True)
plotter.add_mesh(sphere, color="white", show_edges=True)
plotter.title = "3D Sphere Visualization"
plotter.show()
EmbeddableWidget(value='<iframe srcdoc="<!DOCTYPE html>\n<html lang="en-US" dir="ltr">\n <head>\n <meta charset="utf-8">\n <meta name="viewport" content="width=device-width,initial-scale=1">\n <title>404 | VTK.js </title>\n <meta name="description" content="Not Found">\n <meta name="generator" content="VitePress v1.6.4">\n <link rel="preload stylesheet" href="/vtk-js/assets/style.BfuHIIC4.css" as="style">\n <link rel="preload stylesheet" href="/vtk-js/vp-icons.css" as="style">\n \n <script type="module" src="/vtk-js/assets/app.DfjizcSH.js"></script>\n <link rel="preload" href="/vtk-js/assets/inter-roman-latin.Di8DUHzh.woff2" as="font" type="font/woff2" crossorigin="">\n <script id="check-dark-mode">(()=>{const e=localStorage.getItem("vitepress-theme-appearance")||"auto",a=window.matchMedia("(prefers-color-scheme: dark)").matches;(!e||e==="auto"?a:e==="dark")&&document.documentElement.classList.add("dark")})();</script>\n <script 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{ base64Str });\n</script>\n </body>\n</html>" class="pyvista" style="width: 99%; height: 600px; border: 1px solid rgb(221,221,221);"></iframe>')
Figures with Matplotlib#
This example shows how to render a figure using Matplotlib.
import matplotlib.pyplot as plt
import numpy as np
time = np.linspace(0, 2 * np.pi, 100)
fig, ax = plt.subplots()
ax.plot(time, np.cos(time), color="blue", label=r"$\cos{(t)}$")
ax.plot(time, np.sin(time), color="red", label=r"$\sin{(t)}$")
ax.set_xlabel("Time [time units]")
ax.set_ylabel("Amplitude [distance units]")
ax.set_title("Trigonometric functions")
plt.show()
Figures with Plotly#
This example shows how to render a figure using Plotly.
import plotly.graph_objs as go
# More info: https://plotly.com/python/renderers/
time = np.linspace(0, 2 * np.pi, 100)
cos_trace = go.Scatter(x=time, y=np.cos(time), mode="lines", name="cos(t)")
sin_trace = go.Scatter(x=time, y=np.sin(time), mode="lines", name="sin(t)")
fig = go.Figure(data=[cos_trace, sin_trace])
fig
import numpy as np
import plotly.express as px
df = px.data.tips()
fig = px.bar(
df,
x="sex",
y="total_bill",
facet_col="day",
color="smoker",
barmode="group",
template="presentation+plotly",
)
fig.update_layout(height=400)
fig
Render equations using IPython math#
This example shows how to render equations using the IPython math module.
<IPython.core.display.Math object>
from IPython.display import Latex
Latex(r"This is a \LaTeX{} equation: $a^2 + b^2 = c^2$")
<IPython.core.display.Latex object>
Render a table#
This is an example to render a table with Sphinx-Gallery.
A |
B |
A and B |
|---|---|---|
False |
False |
False |
True |
False |
False |
False |
True |
False |
True |
True |
True |
Render a table using pandas
Total running time of the script: (0 minutes 9.213 seconds)