extract_competent_subset

extract_competent_subset(data, cube_size=100, batch=100, pore_class=0, class_to_optimize=0, for_3d_printing=False, max_overhang_angle=20, exhaustive_search=False, debug=False, show_progress=True)

Return type:

ndarray

Finds the best cubic subset for visualizing the segmented dataset. :param data: 3D numpy array, vector class from DPM Tools, Image class from DPM Tools. :param cube_size: Size of the visualization cube, default is 100 (100x100x100). :param batch: Batch size over which to calculate the stats, default is 100. :param pore_class: The class representing pores in the original data, default is 0. :param class_to_optimize: The class to optimize connectivity for (0 or 1), default is 0. :param for_3d_printing: If True, evaluate printability metrics, default is False. :param max_overhang_angle: Maximum overhang angle for 3D printing evaluation, default is 20. :param exhaustive_search: If True, search entire 3D volume independently. If False, search diagonally (faster), default is False. :param debug: If True, print detailed debugging information, default is False. :param show_progress: If True, display tqdm progress bar, default is True.

Returns:

(best_subset_range, stats_array) where best_subset_range maximizes connected component of class_to_optimize

Return type:

tuple