Interactive Mode

Interactive mode allows dynamic updating of plots without blocking script execution.

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Enabling Interactive Mode

import matplotlib.pyplot as plt

plt.ion()   # Turn ON interactive mode
plt.ioff()  # Turn OFF interactive mode

Check current state:

plt.isinteractive()  # Returns True or False

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Basic Interactive Example

import matplotlib.pyplot as plt
import numpy as np
import time

def main():
    # Enable interactive mode
    plt.ion()

    # Create initial plot
    fig, ax = plt.subplots()
    x = np.linspace(0, 10, 100)
    y = np.sin(x)
    line, = ax.plot(x, y)

    # Set labels
    ax.set_xlabel('X-axis')
    ax.set_ylabel('Y-axis')
    ax.set_title('Interactive Plotting')

    # Update the plot dynamically
    for i in range(50):
        y = np.sin(x + i * 0.1)
        line.set_ydata(y)

        # Redraw the figure
        plt.draw()

        # Pause for animation effect
        plt.pause(0.1)

    # Turn off interactive mode
    plt.ioff()

    # Keep window open
    plt.show()

if __name__ == "__main__":
    main()

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Key Functions

plt.ion()

Turns on interactive mode:

• Plots update immediately
• Non-blocking execution
• Figures display without show()

plt.ion()
plt.plot([1, 2, 3])  # Displays immediately

plt.ioff()

Turns off interactive mode:

• Returns to default behavior
• Requires plt.show() to display
• Blocking execution

plt.ioff()
plt.plot([1, 2, 3])
plt.show()  # Required to display

plt.draw()

Redraws the current figure:

• Updates modified elements
• Non-blocking
• Use after changing data

line.set_ydata(new_data)
plt.draw()  # Update display

plt.pause(interval)

Pauses execution and updates display:

• Combines draw() with sleep
• Processes GUI events
• Essential for animations

plt.pause(0.1)  # Pause 0.1 seconds and update

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Animation Pattern

The standard pattern for interactive animations:

import matplotlib.pyplot as plt
import numpy as np

def animate():
    plt.ion()

    fig, ax = plt.subplots()
    x = np.linspace(0, 2*np.pi, 100)
    line, = ax.plot(x, np.sin(x))
    ax.set_ylim(-1.5, 1.5)

    for phase in np.linspace(0, 4*np.pi, 100):
        line.set_ydata(np.sin(x + phase))
        plt.draw()
        plt.pause(0.05)

    plt.ioff()
    plt.show()

animate()

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Updating Plot Elements

Update Line Data

line, = ax.plot(x, y)  # Note the comma for unpacking

# Update y-data only
line.set_ydata(new_y)

# Update both x and y
line.set_data(new_x, new_y)

Update Axis Limits

ax.set_xlim(new_xmin, new_xmax)
ax.set_ylim(new_ymin, new_ymax)

Update Title

ax.set_title(f'Frame {i}')

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Real-Time Data Example

import matplotlib.pyplot as plt
import numpy as np

def real_time_plot():
    plt.ion()

    fig, ax = plt.subplots()
    ax.set_xlim(0, 100)
    ax.set_ylim(-2, 2)

    x_data = []
    y_data = []
    line, = ax.plot([], [])

    for i in range(100):
        # Simulate incoming data
        x_data.append(i)
        y_data.append(np.sin(i * 0.1) + np.random.normal(0, 0.1))

        line.set_data(x_data, y_data)
        ax.set_title(f'Data Point: {i}')

        plt.draw()
        plt.pause(0.05)

    plt.ioff()
    plt.show()

real_time_plot()

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Interactive Mode vs FuncAnimation

For more complex animations, consider FuncAnimation:

from matplotlib.animation import FuncAnimation
import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()
x = np.linspace(0, 2*np.pi, 100)
line, = ax.plot(x, np.sin(x))
ax.set_ylim(-1.5, 1.5)

def update(frame):
    line.set_ydata(np.sin(x + frame * 0.1))
    return line,

ani = FuncAnimation(fig, update, frames=100, interval=50, blit=True)
plt.show()

Feature	Interactive Mode	FuncAnimation
Simplicity	Simple	More setup
Performance	Lower	Higher (blit)
Saving	Manual	Built-in
Control	Full	Callback-based

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Key Takeaways

• plt.ion() enables non-blocking interactive mode
• plt.draw() updates the display
• plt.pause() combines draw with a delay
• Update data with line.set_ydata() or line.set_data()
• Use for real-time data and simple animations
• Consider FuncAnimation for complex animations