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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).
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()
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).
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()
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, click "Download" to get the code and run python app.py
.
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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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In this example we use the i
, j
and k
parameters to specify manually the geometry of the triangles of the mesh.
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()
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()
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'
.
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()
See https://plotly.com/python/reference/mesh3d/ for more information and chart attribute options!