diff --git a/src/SimNDT/run_setup/SimulationVideo.py b/src/SimNDT/run_setup/SimulationVideo.py new file mode 100644 index 0000000..7feff29 --- /dev/null +++ b/src/SimNDT/run_setup/SimulationVideo.py @@ -0,0 +1,52 @@ +import numpy as np +import os +import cv2 +from datetime import datetime + +def create_vector_field_video(folder_path, video_path): + """ + Reads all .npy files from the specified folder, separates Vx and Vy arrays, + calculates the net vector field V, and creates a video using the jet colormap. + + Parameters: + folder_path (str): Path to the folder containing .npy files. + video_path (str): Path to save the output video. + """ + # Get list of all .npy files in the folder + file_list = [f for f in os.listdir(folder_path) if f.endswith('.npy')] + file_list.sort() # Ensure files are processed in order + + # Initialize lists to hold Vx and Vy arrays + Vx_list = [] + Vy_list = [] + + # Load each file and separate Vx and Vy + for file_name in file_list: + file_path = os.path.join(folder_path, file_name) + data = np.load(file_path) + Vx_list.append(data[0]) + Vy_list.append(data[1]) + + # Convert lists to numpy arrays + Vx_array = np.array(Vx_list) + Vy_array = np.array(Vy_list) + + # Calculate the net vector V + V = np.sqrt(Vx_array**2 + Vy_array**2) + + # Create a video from the net vector V + height, width = V.shape[1], V.shape[2] + current_time = datetime.now().strftime("%Y%m%d_%H%M%S") + video_filename = 'output_video_{current_time}.avi'.format(current_time=current_time) + video_path = os.path.join(video_path, video_filename) + fourcc = cv2.VideoWriter_fourcc(*'XVID') + video = cv2.VideoWriter(video_path, fourcc, 1, (width, height), isColor=True) + + for i in range(V.shape[0]): + normalized_frame = (V[i] * 255 / np.max(V[i])).astype(np.uint8) # Normalize and convert to uint8 + colored_frame = cv2.applyColorMap(normalized_frame, cv2.COLORMAP_JET) # Apply jet colormap + video.write(colored_frame) + + video.release() + print("Video saved at:", video_path) +