Reduce memory usage for defining volume dimensions and add lazy performance profiling

        start = time.time()

        # Merge the slices into one 3D array

        points = np.array([])

        x_range = 0

        y_range = 0

        z_range = 0

        scalars = np.array([])

        for index, path in enumerate(file_list):

        for path in file_list:

            slice_start = time.time()

            slice = get_reader(path).read()

            if len(points) == 0:

                points = slice.points

            if len(scalars) == 0:

                x_range = slice.dimensions[0]

                y_range = slice.dimensions[1]

                scalars = slice.active_scalars

            else:

                slice_points = slice.points

                slice_points[:, 2] += index

                points = np.concatenate((points, slice_points))

                scalars = np.concatenate((scalars, slice.active_scalars))

            z_range += 1

            print(f"Processed slice {z_range}/{len(file_list)} in {time.time() - slice_start:.2f}s")

        print(f"Numpy array creation: {time.time() - start:.2f}s")

        start = time.time()

        # Calculate the data extent

        x_range = int(np.amax(points[:, 0])) + 1

        y_range = int(np.amax(points[:, 1])) + 1

        z_range = int(np.amax(points[:, 2])) + 1

        # Define the 3D volume's extent

        volume = ImageData(dimensions=(x_range, y_range, z_range), origin=(0, 0, 0), spacing=(1, 1, 1))

        # Define the 3D volume's scalars for the color/opacity transfer functions

        print(f"PyVista volume creation: {time.time() - start:.2f}s")

        start = time.time()

        self.plotter.add_volume(volume, clim=[0, 0.007], opacity="linear")

        self.plotter.add_volume(volume, opacity="sigmoid")

        self.plotter.view_isometric(self.plotter)

        print(f"PyVista volume rendering: {time.time() - start:.2f}s")