Pick events for data interaction in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a pick event in matplotlib?

A pick event happens when a user clicks on a part of a plot that is set to be 'pickable'. It allows interaction with plot elements like points or lines.

beginner

How do you make a plot element pickable in matplotlib?

You set the 'picker' parameter to True or a tolerance value when creating the plot element, for example: plt.plot(x, y, picker=True).

intermediate

Which matplotlib method connects a pick event to a function?

The 'figure.canvas.mpl_connect' method connects the 'pick_event' to a custom function that handles the event.

intermediate

What information can you get from a pick event object?

You can get the artist (plot element) picked, the mouse event details, and the indices of the picked data points.

beginner

Why are pick events useful in data visualization?

They let users interact with plots by clicking on data points or elements, enabling features like showing details, highlighting, or updating data dynamically.

What parameter makes a plot element respond to pick events in matplotlib?

A clickable

B selectable

C interactive

D picker

The 'picker' parameter enables pick events on plot elements.

Which function connects a pick event to a handler function?

A plt.connect_event()

B figure.canvas.mpl_connect()

C plt.pick_event()

D figure.connect_pick()

Use 'figure.canvas.mpl_connect()' to connect events like 'pick_event' to handlers.

What does the pick event object NOT provide?

A The artist picked

B Mouse event details

C The plot title

D Indices of picked data points

The pick event object does not provide the plot title.

How can you specify the sensitivity area for picking in matplotlib?

A By setting picker to a float value (tolerance)

B By setting pick_sensitivity parameter

C By changing the plot color

D By resizing the figure

Setting 'picker' to a float value defines the picking tolerance in points.

Pick events in matplotlib are mainly used to:

A Enable user interaction by clicking plot elements

B Change plot colors automatically

C Save plots to files

D Resize the plot window

Pick events allow users to interact with plot elements by clicking them.

Explain how to set up a pick event in matplotlib to respond when a user clicks on a data point.

Think about making elements pickable and linking an event to a function.

Describe what information you can access from the pick event object and how it can be used.

Consider what details help respond to user clicks on plots.

Practice

1. What does setting the picker parameter on a plot element in matplotlib do?

easy

A. Removes the plot element from the figure

B. Makes the plot element respond to mouse clicks for interaction

C. Saves the plot element as an image file

D. Changes the color of the plot element

Solution

1. Step 1: Understand the role of the picker parameter

   The picker parameter enables a plot element to detect mouse clicks or pick events.

2. Step 2: Connect picker to interaction

   When picker is set, the element becomes clickable, allowing interaction like showing data details.

3. Final Answer:

   Makes the plot element respond to mouse clicks for interaction -> Option B

4. Quick Check:

   picker enables click interaction = D [OK]

Hint: picker makes plot elements clickable for interaction [OK]

Common Mistakes:

• Confusing picker with color or style changes
• Thinking picker saves images
• Assuming picker removes elements

2. Which of the following is the correct way to connect a pick event handler function named on_pick to a matplotlib figure fig?

easy

A. fig.mpl_connect('pick_event', on_pick)

B. fig.connect('pick_event', on_pick)

C. fig.canvas.mpl_connect('pick_event', on_pick)

D. fig.canvas.connect('pick_event', on_pick)

Solution

1. Step 1: Recall the correct method to connect events in matplotlib

   Events are connected using mpl_connect on the figure's canvas object.

2. Step 2: Match the syntax for pick events

   The correct syntax is fig.canvas.mpl_connect('pick_event', handler_function).

3. Final Answer:

   fig.canvas.mpl_connect('pick_event', on_pick) -> Option C

4. Quick Check:

   Use fig.canvas.mpl_connect for events = A [OK]

Hint: Use fig.canvas.mpl_connect to link pick events [OK]

Common Mistakes:

• Using fig.connect instead of fig.canvas.mpl_connect
• Calling mpl_connect on fig instead of fig.canvas
• Using connect instead of mpl_connect

3. Consider the code below:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
line, = ax.plot([1, 2, 3], [4, 5, 6], picker=5)
def on_pick(event):
    print(f"Picked point: {event.ind}")
fig.canvas.mpl_connect('pick_event', on_pick)
plt.show()

What will happen when you click near the second point on the line?

medium

A. The program prints 'Picked point: [1]' indicating the second point was picked

B. Nothing happens because picker=5 is invalid

C. An error occurs because on_pick is not connected properly

D. The plot closes immediately

Solution

1. Step 1: Understand picker=5 meaning

   Setting picker=5 means clicks within 5 points of the line points trigger pick events.

2. Step 2: Analyze on_pick behavior on clicking second point

   Clicking near the second point triggers on_pick, printing the index of that point, which is 1 (zero-based).

3. Final Answer:

   The program prints 'Picked point: [1]' indicating the second point was picked -> Option A

4. Quick Check:

   picker=5 triggers pick near points = C [OK]

Hint: picker=5 allows clicks near points to trigger events [OK]

Common Mistakes:

• Thinking picker=5 is invalid
• Assuming event.ind is not available
• Believing on_pick is not connected

4. The following code is intended to print the index of a picked point on a scatter plot, but it raises an error:

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
sc = ax.scatter([1,2,3], [4,5,6], picker=True)
def on_pick(event):
    print(event.ind)
fig.mpl_connect('pick_event', on_pick)
plt.show()

What is the main error causing the failure?

medium

A. Calling mpl_connect on fig instead of fig.canvas

B. Using picker=True instead of a numeric tolerance

C. Not defining on_pick before connecting it

D. Using scatter instead of plot for pick events

Solution

1. Step 1: Check how event connection is done

   The code calls fig.mpl_connect, but the correct method is fig.canvas.mpl_connect.

2. Step 2: Understand impact of wrong connection

   Because mpl_connect is not a method of fig, this causes an AttributeError and failure.

3. Final Answer:

   Calling mpl_connect on fig instead of fig.canvas -> Option A

4. Quick Check:

   Use fig.canvas.mpl_connect, not fig.mpl_connect = A [OK]

Hint: Always connect events on fig.canvas, not fig [OK]

Common Mistakes:

• Using picker=True is allowed, not an error
• Assuming on_pick must be defined before connection
• Thinking scatter can't use pick events

5. You want to create an interactive matplotlib scatter plot where clicking a point highlights it by changing its color. Which approach correctly combines pick events and updating the plot?

hard

A. Set picker on scatter points, connect pick_event to a function that prints point coordinates only

B. Set picker on the figure, not on points, and change colors in the handler

C. Use plt.show() inside the pick event handler to refresh the plot

D. Set picker on scatter points, connect pick_event to a function that changes the point's color and calls fig.canvas.draw()

Solution

1. Step 1: Enable picking on scatter points

   Set the picker parameter on scatter plot points to detect clicks on them.

2. Step 2: Update point color and redraw figure in handler

   In the pick event handler, change the color of the selected point and call fig.canvas.draw() to update the display.

3. Final Answer:

   Set picker on scatter points, connect pick_event to a function that changes the point's color and calls fig.canvas.draw() -> Option D

4. Quick Check:

   picker + color change + canvas.draw() = B [OK]

Hint: Change color in handler and redraw with fig.canvas.draw() [OK]

Common Mistakes:

• Only printing coordinates without updating plot
• Calling plt.show() inside event handler causes errors
• Setting picker on figure instead of points