import csv import matplotlib.pyplot as plt import matplotlib.animation as animation # Read CSV file and extract timestamp and joint1 (positions[0]) values. timestamps = [] joint1_positions = [] with open('joint_states.csv', 'r') as csvfile: reader = csv.DictReader(csvfile) for row in reader: timestamps.append(float(row['timestamp'])) joint1_positions.append(float(row['joint1'])) # Determine the sampling interval based on timestamps. if len(timestamps) > 1: # Calculate average interval in milliseconds. avg_interval = ((timestamps[-1] - timestamps[0]) / (len(timestamps)-1)) * 1000 else: avg_interval = 100 # fallback value # Create the plot. fig, ax = plt.subplots() line, = ax.plot([], [], 'b-', lw=2, label='Joint 1 Position') # Add the reference position line at 0.0 (red dashed line). ax.axhline(y=0.0, color='red', linestyle='--', lw=2, label='Reference (0.0)') ax.set_xlim(timestamps[0], timestamps[-1]) y_min = min(joint1_positions) - 0.1 y_max = max(joint1_positions) + 0.1 ax.set_ylim(y_min, y_max) ax.set_xlabel('Time (s)') ax.set_ylabel('Joint 1 Position (rad)') ax.set_title('Joint 1 Position vs Time') ax.legend() # Initialization function: plot an empty line. def init(): line.set_data([], []) return line, # Animation update function. def update(frame): # Update the line with data up to the current frame. x = timestamps[:frame+1] y = joint1_positions[:frame+1] line.set_data(x, y) return line, # Create the animation. ani = animation.FuncAnimation(fig, update, frames=len(timestamps), init_func=init, blit=True, interval=avg_interval) # Save the animation as an MP4 video. output_video = 'joint_position_video.mp4' ani.save(output_video, writer='ffmpeg', fps=1000/avg_interval) print(f"Animation saved as {output_video}") plt.show()