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Python Data Visualization Cookbook (Second Edition)

You're reading from  Python Data Visualization Cookbook (Second Edition)

Product type Book
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Pages 302 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
1. Preparing Your Working Environment 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Plotting a 3D trefoil knot


In this recipe, we will see how to plot a 3D trefoil knot. A trefoil knot is a closed curve with three crossings. In this recipe, we will draw not just a curve, but a solid 3D curve. This is beyond the plotly capabilities, and we will implement this functionality using a trick.

How to do it...

In this recipe, we will:

  1. Generate all the points of the knot using parametric equations.

  2. Organize the data as required by plotly.

  3. Define a clean layout.

  4. Invoke plotly to draw the chart:

    import numpy as np
    import plotly.plotly as py
    from plotly.graph_objs import Scatter3d, Data, Layout
    from plotly.graph_objs import Figure, Line, Margin, Marker
    
    from numpy import linspace,pi,cos,sin
    phi = linspace(0,2*pi,250)
    x = sin(phi)+2*sin(2*phi)
    y = cos(phi)-2*cos(2*phi)
    z = -sin(3*phi)
    
    traces = list()
    colors = ['rgb(%d,50,210)' % c for c in np.abs(z / max(z)) * 255]
    for i in linspace(-np.pi,np.pi,50):
        trace = Scatter3d(x=x+np.cos(i)*.5, y=y+np.sin(i)*.5, z=z,
                           mode...
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