Matplotlib Tools and Interactive Functions |

Matplotlib Reference Documentation

This set of functions provides event handling, property manipulation, mouse interaction, and debugging tools.

Function Overview

Function	Functionality
connect()	Bind an event callback function
disconnect()	Unbind an event callback function
ginput()	Get coordinates via mouse clicks
waitforbuttonpress()	Wait for mouse or keyboard press
findobj()	Find Artist objects matching given criteria
get() / setp()	Get / set Artist properties
getp()	Get Artist properties (alias for get())
get_current_fig_manager()	Get the current Figure manager
new_figure_manager()	Create a manager for a Figure
set_loglevel()	Set logging level
xkcd()	Switch to xkcd hand-drawn comic style

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Event Handling — connect() / disconnect()

matplotlib.pyplot.connect(s, func) matplotlib.pyplot.disconnect(cid)

Example

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(figsize=(6,4))
ax.plot(np.random.randn(50).cumsum())
ax.set_title('Click anywhere on the figure')

# Click event callback
def on_click(event):
    print(f'Clicked at: x={event.xdata:.2f}, y={event.ydata:.2f}')

# Bind event
cid = fig.canvas.mpl_connect('button_press_event', on_click)

plt.show()
print("tutorial: click events registered")

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ginput() — Mouse Selection of Coordinates

matplotlib.pyplot.ginput(n=1, timeout=30, show_clicks=True, mouse_add=MouseButton.LEFT, mouse_pop=MouseButton.RIGHT, mouse_stop=MouseButton.MIDDLE)

Example

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(figsize=(7,5))
ax.plot(np.arange(10), np.random.randn(10), 'o-')
ax.set_title('Click 3 points (timeout=15s)')
ax.set_xlim(-1, 10)
ax.set_ylim(-3, 3)
ax.grid(True, alpha=0.3)

print("Please click 3 points...")
points = plt.ginput(3, timeout=15, show_clicks=True)

for i, (x, y) in enumerate(points):
    print(f"Point {i+1}: ({x:.2f}, {y:.2f})")

plt.show()

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waitforbuttonpress() — Wait for Key Press

matplotlib.pyplot.waitforbuttonpress(timeout=-1)
Return value: True indicates a key press; False indicates a mouse click.

Example

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()
ax.plot(np.sin(np.linspace(0, 10, 100)))
ax.set_title('Press any key or click mouse')

print("Waiting for button press...")
result = plt.waitforbuttonpress(timeout=10)

if result is None:
    print("Timeout!")
elif result:
    print("Key was pressed")
else:
    print("Mouse was clicked")

plt.show()

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findobj() — Find Artist Objects

matplotlib.pyplot.findobj(o=None, match=None, include_self=False)

Example

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.lines import Line2D

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6], label='Line A')
ax.plot([1, 2, 3], [1, 2, 3], label='Line B')
ax.set_title('Find Objects Demo')

# Find all Line2D objects
lines = ax.findobj(match=Line2D)
print(f"Found {len(lines)} line objects")

# Get specific properties
for line in lines:
    print(f" - label: {line.get_label()}")

# Use get() to retrieve properties
ax_title = ax.get_title()
print(f"Axes title: {ax_title}")

plt.show()

Found 2 line objects
- label: Line A
- label: Line B
Axes title: Find Objects Demo

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get() / setp() — Property Manipulation

matplotlib.pyplot.get(obj, *args, **kwargs)
matplotlib.pyplot.setp(obj, *args, **kwargs)
matplotlib.pyplot.getp(obj, *args, **kwargs)

Example

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(layout='constrained')
line, = ax.plot([0, 1], [0, 1], label='test')

# get() retrieve a single property
print("line color:", plt.get(line, 'color'))

# getp() retrieve multiple properties
props = plt.getp(line)
print(f"line has {len(props)} properties")

# setp() batch set properties
plt.setp(line, color='red', linewidth=3, linestyle='--')

ax.set_title('setp() demo')
ax.legend()
plt.show()

print("tutorial: properties modified via setp()")

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xkcd() — Hand-drawn Comic Style

matplotlib.pyplot.xkcd(scale=1, length=100, randomness=2)

Example

import matplotlib.pyplot as plt
import numpy as np

# Enable xkcd hand-drawn style
with plt.xkcd():
    fig, ax = plt.subplots(figsize=(8, 5))
    x = np.linspace(0, 10, 100)
    ax.plot(x, np.sin(x), label='sin(x)')
    ax.plot(x, np.cos(x), label='cos(x)')
    ax.set_title('XKCD-style Plot')
    ax.set_xlabel('Time')
    ax.set_ylabel('Amplitude')
    ax.legend()
    ax.annotate('This is peak!',
                xy=(np.pi/2, 1), xytext=(2, 1.3),
                arrowprops=dict(arrowstyle='->'))
    plt.show()

print("tutorial: xkcd style displayed")

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set_loglevel() — Logging Level

matplotlib.pyplot.set_loglevel(level)
level options: 'debug', 'info', 'warning', 'error', 'critical'.

Example

import matplotlib.pyplot as plt
import numpy as np

# Set logging level to 'info' (to view Matplotlib internal messages)
plt.set_loglevel('info')

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
ax.set_title('Debugging with loglevel')

plt.show()

Matplotlib Reference Documentation