5 Best Ways to Get the Properties of a Picked Object in Mplot3d Matplotlib Using Python

💡 Problem Formulation: When working with 3D plots in Matplotlib’s mplot3d toolkit, interaction with the plot often requires retrieving properties of a picked object, such as its color, size, or data points. For instance, when clicking on a 3D scatter plot, one might want to get the coordinates (x, y, z) or color information of the selected marker. This article aims to provide clear solutions for accessing those properties programmatically.

Method 1: Using the pick_event Attribute

An effective way to obtain properties of picked objects in an mplot3d plot is by using Matplotlib’s event handling system. Upon a pick event, you can access an object’s properties through the pick_event attribute, which contains information about the picked artist.

Here’s an example:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
line = ax.plot([1, 2, 3], [4, 5, 6], [7, 8, 9], picker=5) # 5 points tolerance

def on_pick(event):
    artist = event.artist
    xline, yline, zline = artist.get_data_3d()
    print(f"Picked object properties: {xline}, {yline}, {zline}")

fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

Output:

When you pick an object on the graph, the output will be its properties:

Picked object properties: [1 2 3], [4 5 6], [7 8 9]

This code snippet creates a simple 3D line plot and sets up a picker tolerance. When the line is picked with a cursor click, the on_pick function is triggered, and it prints the properties of the picked line.

Method 2: Accessing Specific Object Properties

It is possible to print out specific properties, such as color or linestyle, directly by accessing them from the artist object within the pick event.

Here’s an example:

import matplotlib.pyplot as plt

# ... (setup fig, ax, and events as above)

def on_pick(event):
    artist = event.artist
    if isinstance(artist, mpl.lines.Line2D):
        print(f"Line color: {artist.get_color()}, Line linestyle: {artist.get_linestyle()}")

fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

Output:

When you pick a line, for example:

Line color: b, Line linestyle: -

This modified on_pick function checks if the artist is an instance of a Line2D object and then prints out the color and linestyle of the picked line.

Method 3: Using Artist Methods to Get Properties

You can use the various getter methods associated with the Artist object in Matplotlib to retrieve properties such as the marker’s data points or properties of a surface.

Here’s an example:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# ... (setup fig, ax, and events as above)

def on_pick(event):
    artist = event.artist
    if isinstance(artist, mpl.collections.PathCollection):
        offsets = artist.get_offsets()
        print(f"Marker coordinates: {offsets}")

fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

Output:

When you pick a marker in a scatter plot:

Marker coordinates: [[1 4 7]]

This example is targeted at a scatter plot’s markers. The on_pick function determines if the picked artist is a PathCollection, then uses get_offsets to print the marker’s coordinates.

Method 4: Extracting and Formatting Picked Properties

In some cases, you may want to format the properties of a picked object for display or further processing. This can be accomplished by wrapping the property extraction logic in a formatting function.

Here’s an example:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# ... (setup fig, ax, and events as above)

def format_properties(artist):
    properties = {
        'color': artist.get_color(),
        # Add more properties as needed
    }
    return properties

def on_pick(event):
    artist = event.artist
    formatted_properties = format_properties(artist)
    print(f"Picked object properties: {formatted_properties}")

fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

Output:

After picking something in your plot:

Picked object properties: {'color': '#1f77b4'}

The on_pick function now uses a helper function format_properties() that returns a dictionary of the properties for easy access and better code organization.

Bonus One-Liner Method 5: Lambda Functions

Lambda functions offer a quick way to assign a simple pick handler that can print out properties on-the-fly without the need for a dedicated function definition.

Here’s an example:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# ... (setup fig, ax, and events as above)

fig.canvas.mpl_connect('pick_event', lambda event: print(event.artist.get_color()))
plt.show()

Output:

Pick a plot element and you’ll get:

#1f77b4

A simple lambda function is connected to the pick event, which prints the color of the object being picked, providing a quick and concise solution for simple property fetching.

Summary/Discussion

• Method 1: Using the pick_event Attribute. Offers direct access to an object’s properties. Strong in general use cases. Might require additional checks for different artist types.
• Method 2: Accessing Specific Object Properties. Provides a straightforward way to retrieve individual properties. Best for when only one or two properties are needed. Is artist-type dependent.
• Method 3: Using Artist Methods to Get Properties. Utilizes inherent methods of the artist class, making it a versatile choice. Requires knowledge of specific Artist methods.
• Method 4: Extracting and Formatting Picked Properties. Enables the customization of property output. Ideal for complex interactions. Requires extra coding effort.
• Method 5: Lambda Functions. Perfect for quick tasks with minimal coding. It is limited in complexity and not appropriate for all scenarios.