With go.Isosurface, you can plot isosurface contours of a scalar field value, which is defined on x, y and z coordinates.

Basic Isosurface¶

In this first example, we plot the isocontours of values isomin=2 and isomax=6. In addition, portions of the sides of the coordinate domains for which the value is between isomin and isomax (named the caps) are colored. Please rotate the figure to visualize both the internal surfaces and the caps surfaces on the sides.

In [1]:

import plotly.graph_objects as go

fig= go.Figure(data=go.Isosurface(
    x=[0,0,0,0,1,1,1,1],
    y=[1,0,1,0,1,0,1,0],
    z=[1,1,0,0,1,1,0,0],
    value=[1,2,3,4,5,6,7,8],
    isomin=2,
    isomax=6,
))

fig.show()

Removing caps when visualizing isosurfaces¶

For a clearer visualization of internal surfaces, it is possible to remove the caps (color-coded surfaces on the sides of the visualization domain). Caps are visible by default.

In [2]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]

# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    isomin=10,
    isomax=40,
    caps=dict(x_show=False, y_show=False)
    ))
fig.show()

Modifying the number of isosurfaces¶

In [3]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]

# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    isomin=10,
    isomax=50,
    surface_count=5, # number of isosurfaces, 2 by default: only min and max
    colorbar_nticks=5, # colorbar ticks correspond to isosurface values
    caps=dict(x_show=False, y_show=False)
    ))
fig.show()

Changing the opacity of isosurfaces¶

In [4]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]

# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    opacity=0.6,
    isomin=10,
    isomax=50,
    surface_count=3,
    caps=dict(x_show=False, y_show=False)
    ))
fig.show()

Isosurface with Additional Slices¶

Here we visualize slices parallel to the axes on top of isosurfaces. For a clearer visualization, the fill ratio of isosurfaces is decreased below 1 (completely filled).

In [5]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]

# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    isomin=5,
    isomax=50,
    surface_fill=0.4,
    caps=dict(x_show=False, y_show=False),
    slices_z=dict(show=True, locations=[-1, -3,]),
    slices_y=dict(show=True, locations=[0]),
    ))
fig.show()

Multiple Isosurfaces with Caps¶

In [6]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, 0:5:20j]

values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    isomin=30,
    isomax=50,
    surface=dict(count=3, fill=0.7, pattern='odd'),
    caps=dict(x_show=True, y_show=True),
    ))
fig.show()

Changing the default colorscale of isosurfaces¶

In [7]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]

# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    colorscale='BlueRed',
    isomin=10,
    isomax=50,
    surface_count=3,
    caps=dict(x_show=False, y_show=False)
    ))
fig.show()

Customizing the layout and appearance of isosurface plots¶

In [8]:

import plotly.graph_objects as go
import numpy as np

X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, 0:5:20j]

values = X * X * 0.5 + Y * Y + Z * Z * 2

fig = go.Figure(data=go.Isosurface(
    x=X.flatten(),
    y=Y.flatten(),
    z=Z.flatten(),
    value=values.flatten(),
    isomin=30,
    isomax=50,
    surface=dict(count=3, fill=0.7, pattern='odd'),
    showscale=False, # remove colorbar
    caps=dict(x_show=True, y_show=True),
    ))

fig.update_layout(
    margin=dict(t=0, l=0, b=0), # tight layout
    scene_camera_eye=dict(x=1.86, y=0.61, z=0.98))
fig.show()

Reference¶

See https://plotly.com/python/reference/isosurface/ 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(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter