revanalyzer.generators.pnm_generator.generate_PNM

revanalyzer.generators.pnm_generator.generate_PNM(image, size, n_steps, sREV_max_step, outputdir, n_threads=1, resolution=1.0, show_time=False)

Running PNM extractor for all the selected subsamples.

Input:

image (numpy.ndarray): 3D array representing the image;

size (tuple (int, int, int)): linear image sizes in x, y and z directions;

n_steps (int): number of subsamples selection steps;

sREV_max_step (int): maximal step for which sREV and stationarity analysis can be performed;

outputdir (str): path to the output folder containing generated data;

n_threads (int): number of threads used for data generation, default: 1;

resolution (float): resolution of studied sample, default: 1;

show_time (bool): Added to monitor time cost for large images, default: False.