Pick events for data interaction in Matplotlib

Introduction

Pick events let you click on parts of a plot to get more information or interact with the data.

You want to click on a point in a scatter plot to see its value.

You want to select bars in a bar chart to highlight them.

You want to interact with a plot to filter or update data.

You want to make your plots interactive for presentations.

You want to build simple data exploration tools.

Syntax

Matplotlib

fig.canvas.mpl_connect('pick_event', onpick)

# where onpick is a function that handles the event

The 'pick_event' triggers when you click on a pickable artist (like points or lines).

You must set the 'picker' property on plot elements to make them pickable.

Examples

This makes the line pickable with a 5-point tolerance around it.

Matplotlib

line, = plt.plot(x, y, picker=5)

# picker=5 means the click tolerance in points

Each point in the scatter plot can be clicked to trigger pick events.

Matplotlib

scatter = plt.scatter(x, y, picker=True)

# picker=True makes each point pickable

Sample Program

This code creates a scatter plot where you can click on points. When you click, it prints the point's index and coordinates.

Matplotlib

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 40]

fig, ax = plt.subplots()
scatter = ax.scatter(x, y, picker=True)

# Define the pick event handler
def onpick(event):
    ind = event.ind[0]  # index of the picked point
    print(f"You clicked on point {ind} with coordinates ({x[ind]}, {y[ind]})")

# Connect the pick event to the handler
fig.canvas.mpl_connect('pick_event', onpick)

plt.title('Click on a point')
plt.show()

Important Notes

Pick events only work if the plot elements have the 'picker' property set.

The event object gives you information about what was clicked, like the index of the point.

Pick events are useful for adding interactivity without complex GUI code.

Summary

Pick events let you click on plot elements to interact with data.

Set 'picker' on plot elements to make them clickable.

Use 'fig.canvas.mpl_connect' to link pick events to your handler function.

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