--- jupyter: jupytext: notebook_metadata_filter: all text_representation: extension: .md format_name: markdown format_version: '1.3' jupytext_version: 1.14.1 kernelspec: display_name: Python 3 language: python name: python3 language_info: codemirror_mode: name: ipython version: 3 file_extension: .py mimetype: text/x-python name: python nbconvert_exporter: python pygments_lexer: ipython3 version: 3.8.8 plotly: description: How to make 3D Mesh Plots display_as: 3d_charts language: python layout: base name: 3D Mesh Plots order: 9 page_type: u-guide permalink: python/3d-mesh/ thumbnail: thumbnail/3d-mesh.jpg --- ### 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](https://en.wikipedia.org/wiki/Delaunay_triangulation) is used to draw the triangles. Otherwise the triangles can be given using the `i`, `j` and `k` parameters (see examples below). ```python 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](https://en.wikipedia.org/wiki/Delaunay_triangulation) is used. If >0 then the [alpha-shape algorithm](https://en.wikipedia.org/wiki/Alpha_shape) is used. If 0, the [convex hull](https://en.wikipedia.org/wiki/Convex_hull) is represented (resulting in a convex body). ```python 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](https://plotly.com/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](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.** ```python hide_code=true from IPython.display import IFrame snippet_url = 'https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-snippets/' IFrame(snippet_url + '3d-mesh', width='100%', height=1200) ```
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