[SOLVED] How to set xlim when save some frames to file by matplotlib in python?

A short summary of what follows and the answer addressing the expectations formulated in the question which can't be satisfied by means of matplotlib:

Matplotlib itself does not automatically pre-compute or evaluate all frames of an animation to set axis limits or other properties ahead of time when you use its `FuncAnimation()` method.

In FuncAnimation(), each frame's data is computed and rendered independently as part of the iterative update process. This is because of design for efficiency, particularly in scenarios where frames represent a continuous time series or simulation, and pre-computing every frame's data might be impractical due to memory constraints or computational cost.

But you can overcome this limitation using the solutions provided in this answer below.

Short overview of provided code addressing questions about the x_limit for the x-axis values of a plot:

code demonstrating how to set the maximum value of the x-axis for all the frames in an animation
code demonstrating how to dynamically adjust the maximul value of the x-axis for all the frames in the animation
code demonstrating how to save only the last ten frames of an animation
code demonstrating how to save only the last ten frames of an animation setting a constant maximum value for the x-axis obtained from the data set in advance so all the frames have same x-axis limit

See demonstration how:

# Set up the figure and axis
fig, ax = plt.subplots()
ax.set_xlim(0, 10)
ax.set_ylim(-1.5, 1.5)

impacts the outcome of animation:

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

# Set up the figure and axis
fig, ax = plt.subplots()
ax.set_xlim(0, 10)
ax.set_ylim(-1.5, 1.5)

# Initialize the line plot
line, = ax.plot([], [], lw=2)

# Initial data
x = np.linspace(0, 10, 1000)
y = np.sin(x)

def init():
    line.set_data([], [])
    return line,

def update(frame):
    # Adjust the right endpoint to shorten the wave from the right
    x_new = np.linspace(0, 10 - frame / 10, 1000)
    y_new = np.sin(x_new * np.pi)  # Multiply by pi to maintain wave pattern despite shrinking domain

    line.set_data(x_new, y_new)
    return line,

# Create animation
ani = animation.FuncAnimation(fig, update, frames=np.linspace(0, 30, 100), init_func=init, blit=True)
ani.event_source.stop() #stop the looping
ani.save('fixXaxisRange.gif', writer='pillow', fps=10)

plt.show()

Another approach is to dynamically set the range of x axis depending on incoming data:

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

def generate_sine_wave(frame, step=0.1):
    """ Generate x and y data for a sine wave up to the current frame. """
    # Ensure that frame is positive to avoid empty array
    if frame <= 0:
        return np.array([]), np.array([])
    x = np.linspace(0, 2 * np.pi * frame * step, int(frame * step * 100))
    y = np.sin(x)
    return x, y

# Set up the figure, axis, and plot element
fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.set_ylim(-1.5, 1.5)  # Set fixed y-axis limits for clarity

# Initialize the animation by setting blank data
def init():
    line.set_data([], [])
    ax.set_xlim(0, 10)  # Initial x-axis limit
    return line,

# Update function for animation
def update(frame):
    x, y = generate_sine_wave(frame)
    if x.size == 0:
        return line,  # If x is empty, just return the existing line object

    line.set_data(x, y)
    
    # Update the x-axis limits dynamically as the line grows
    if x[-1] > ax.get_xlim()[1]:  # Check if we need to expand the x-axis
        ax.set_xlim(ax.get_xlim()[0], x[-1] + 1)  # Add some padding to the right limit
        ax.figure.canvas.draw()  # Redraw the canvas to update the axis labels
    
    return line,

# Number of frames depends on how long you want the animation to run
frames = 60

# Create the animation
ani = animation.FuncAnimation(fig, update, frames=range(1, frames + 1), init_func=init, blit=False, repeat=False)

ani.save('fixXaxisRange_2.gif', writer='pillow', fps=10)

plt.show()

If you want to save only the last 10 frames of the animation but run the entire range of data you can specify a start frame number for the animation ( the version storing all frames is outcommented):

# Total frames in the full animation
total_frames = 100
# Calculate start frame for the last ten frames
start_frame = total_frames - 10

# Create the animation object, but only generate the last ten frames
ani = animation.FuncAnimation(fig, update, frames=range(start_frame, total_frames), init_func=init, blit=False, repeat=False)
#ani = animation.FuncAnimation(fig, update, frames=range(1,total_frames), init_func=init, blit=False, repeat=False)

Below the case in which the range of the x-data is determined running the original animation function first letting it generate all the data for the animation first in order to define the actual animation function using the generated data. This way all of the data for the animation is known in advance what allows to set the x-axis limit for the entire animation:

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

def generate_sine_wave(num_frames, step=0.1):
    data = []
    for frame in range(1, num_frames + 1):
        x = np.linspace(0, 2 * np.pi * frame * step, int(100 * step * frame))
        y = np.sin(x)
        data.append((x, y))
    return data

# Number of frames
total_frames = 100

# Precompute all frame data
frame_data = generate_sine_wave(total_frames)

# Determine the maximum x-value across all frames
max_x = max(np.max(x) for x, y in frame_data)

# Set up the figure, axis, and plot element
fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2)
ax.set_ylim(-1.5, 1.5)  # Set fixed y-axis limits for clarity
ax.set_xlim(0, max_x + 1)  # Set the x-axis to the maximum found

# Initialize the animation by setting blank data
def init():
    line.set_data([], [])
    return line,

# Update function for animation
def update(frame):
    x, y = frame_data[frame - 1]  # Use precomputed data
    line.set_data(x, y)
    return line,

# Create the animation object using precomputed frame data
numberOfFinalFramesToSave = 10
ani = animation.FuncAnimation(fig, update, frames=range(total_frames-numberOfFinalFramesToSave, total_frames + 1), init_func=init, blit=False, repeat=False)

# Save the animation as GIF
ani.save('fixXaxisRange_4.gif', writer='pillow', fps=10)

plt.show()

In case of your data take the animation updating function, rename it and let it generate the data for all frames. Then define the animation function as done in the code above delivering frame by frame the data generated in first step. The side-effect of this way of creating the animation is that the maximum x-value is known in advance and can be set for all the frames from within the script with no need to fix its value in code.

How to set xlim when save some frames to file by matplotlib in python?

Matplotlib itself does not automatically pre-compute or evaluate all frames of an animation to set axis limits or other properties ahead of time when you use its FuncAnimation() method.

But you can overcome this limitation using the solutions provided in this answer below.

Matplotlib itself does not automatically pre-compute or evaluate all frames of an animation to set axis limits or other properties ahead of time when you use its `FuncAnimation()` method.