Initial Commit

lack_animator.py

@@ -0,0 +1,81 @@
+# -*- coding: utf-8 -*-
+'''Creates animations of hard sphere EDMD silumations from the output of lack_model.py'''
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+
+
+
+def first_index_exceeding_sum(lst, threshold):
+
+    '''Used for the timings of the animation'''
+
+    cumulative_sum = 0
+    for i, num in enumerate(lst):
+        cumulative_sum += num
+        if cumulative_sum > threshold:
+            return i
+
+    return len(lst) - 1  # Return the length of the list if threshold is not exceeded by any index
+
+
+
+def update(frame):
+
+    '''Function to update the animation'''
+
+    # Check if frame exceeds total number of frames
+    if frame >= total_frames:
+        return im,  # No image to update
+
+    # Calculate the index of the file corresponding to the current frame
+    file_index = first_index_exceeding_sum(times, frame)
+    if file_index == len(times):
+        return im,  # No image to update
+
+    # Load the PNG file corresponding to the current frame
+    img = plt.imread(files[file_index])
+
+    # Update the plot with the new image
+    im.set_array(img)
+
+    return im,
+
+
+
+if __name__ == "__main__":
+
+    # User inputs
+    target_dir = '..\\Animation\\test2\\'  # Path to directory
+    animation_time = 10  # Time in seconds for the total animation
+    fps = 100 # Frames per second
+    dpi = 600 # Resolution (dots per square inch)
+
+    # Reading the timings file
+    csv_file_name = target_dir + 'timings.csv'
+    df = pd.read_csv(csv_file_name, sep=',')
+    files = target_dir + df['files']
+
+    # Calulate frames for each image
+    total_frames = animation_time * fps
+    times = (total_frames * df['times'] / sum(df['times'])).round().astype(int)
+
+    # rounded_times = (total_frames * df['times'] / sum(df['times'])).round().astype(int)
+
+    # # Compare the rounded values with the unrounded values
+    # for unrounded, rounded in zip(total_frames * df['times'] / sum(df['times']), rounded_times):
+    #     print(f"Unrounded: {unrounded}, Rounded: {rounded}")
+
+    # Create the figure and axis
+    fig, ax = plt.subplots()
+    ax.axis('off')
+
+    # Load the first image
+    img = plt.imread(files[0])
+    im = ax.imshow(img)
+
+    # Create the animation
+    ani = FuncAnimation(fig, update, frames=sum(times), interval=1000 / fps) # Animating
+    ani.save(target_dir + 'animation.mp4', writer='ffmpeg', fps=fps, dpi=dpi) # Save the animation
+    plt.show() # Show the final frame of the animation