3D Mesh Plots in Python

How to make 3D Mesh Plots

New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Simple 3D Mesh example¶

go.Mesh3d draws a 3D set of triangles with vertices given by x, y and z. If only coordinates are given, an algorithm such as Delaunay triangulation is used to draw the triangles. Otherwise the triangles can be given using the i, j and k parameters (see examples below).

In [1]:

import plotly.graph_objects as go
import numpy as np

# Download data set from plotly repo
pts = np.loadtxt(np.DataSource().open('https://raw.githubusercontent.com/plotly/datasets/master/mesh_dataset.txt'))
x, y, z = pts.T

fig = go.Figure(data=[go.Mesh3d(x=x, y=y, z=z, color='lightpink', opacity=0.50)])
fig.show()

3D Mesh example with Alphahull¶

The alphahull parameter sets the shape of the mesh. If the value is -1 (default value) then Delaunay triangulation is used. If >0 then the alpha-shape algorithm is used. If 0, the convex hull is represented (resulting in a convex body).

In [2]:

import plotly.graph_objects as go
import numpy as np

pts = np.loadtxt(np.DataSource().open('https://raw.githubusercontent.com/plotly/datasets/master/mesh_dataset.txt'))
x, y, z = pts.T

fig = go.Figure(data=[go.Mesh3d(x=x, y=y, z=z,
                   alphahull=5,
                   opacity=0.4,
                   color='cyan')])
fig.show()

3D Mesh in Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

Out[3]:

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Mesh Tetrahedron¶

In this example we use the i, j and k parameters to specify manually the geometry of the triangles of the mesh.

In [4]:

import plotly.graph_objects as go

fig = go.Figure(data=[
    go.Mesh3d(
        x=[0, 1, 2, 0],
        y=[0, 0, 1, 2],
        z=[0, 2, 0, 1],
        colorbar=dict(title=dict(text='z')),
        colorscale=[[0, 'gold'],
                    [0.5, 'mediumturquoise'],
                    [1, 'magenta']],
        # Intensity of each vertex, which will be interpolated and color-coded
        intensity=[0, 0.33, 0.66, 1],
        # i, j and k give the vertices of triangles
        # here we represent the 4 triangles of the tetrahedron surface
        i=[0, 0, 0, 1],
        j=[1, 2, 3, 2],
        k=[2, 3, 1, 3],
        name='y',
        showscale=True
    )
])

fig.show()

Mesh Cube¶

In [5]:

import plotly.graph_objects as go
import numpy as np

fig = go.Figure(data=[
    go.Mesh3d(
        # 8 vertices of a cube
        x=[0, 0, 1, 1, 0, 0, 1, 1],
        y=[0, 1, 1, 0, 0, 1, 1, 0],
        z=[0, 0, 0, 0, 1, 1, 1, 1],
        colorbar=dict(title=dict(text='z')),
        colorscale=[[0, 'gold'],
                    [0.5, 'mediumturquoise'],
                    [1, 'magenta']],
        # Intensity of each vertex, which will be interpolated and color-coded
        intensity = np.linspace(0, 1, 8, endpoint=True),
        # i, j and k give the vertices of triangles
        i = [7, 0, 0, 0, 4, 4, 6, 6, 4, 0, 3, 2],
        j = [3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3],
        k = [0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6],
        name='y',
        showscale=True
    )
])

fig.show()

Intensity values defined on vertices or cells¶

The intensitymode attribute of go.Mesh3d can be set to vertex (default mode, in which case intensity values are interpolated between values defined on vertices), or to cell (value of the whole cell, no interpolation). Note that the intensity parameter should have the same length as the number of vertices or cells, depending on the intensitymode.

Whereas the previous example used the default intensitymode='vertex', we plot here the same mesh with intensitymode='cell'.

In [6]:

import plotly.graph_objects as go
fig = go.Figure(data=[
    go.Mesh3d(
        # 8 vertices of a cube
        x=[0, 0, 1, 1, 0, 0, 1, 1],
        y=[0, 1, 1, 0, 0, 1, 1, 0],
        z=[0, 0, 0, 0, 1, 1, 1, 1],
        colorbar=dict(title=dict(text='z')),
        colorscale=[[0, 'gold'],
                    [0.5, 'mediumturquoise'],
                    [1, 'magenta']],
        # Intensity of each vertex, which will be interpolated and color-coded
        intensity = np.linspace(0, 1, 12, endpoint=True),
        intensitymode='cell',
        # i, j and k give the vertices of triangles
        i = [7, 0, 0, 0, 4, 4, 6, 6, 4, 0, 3, 2],
        j = [3, 4, 1, 2, 5, 6, 5, 2, 0, 1, 6, 3],
        k = [0, 7, 2, 3, 6, 7, 1, 1, 5, 5, 7, 6],
        name='y',
        showscale=True
    )
])

fig.show()

Reference¶

See https://plotly.com/python/reference/mesh3d/ for more information and chart attribute options!

What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter