Source code for porespy.networks.__snow_n__

import scipy as sp
from porespy.networks import regions_to_network
from porespy.networks import label_boundary_cells
from porespy.networks import add_boundary_regions
from porespy.networks import add_phase_interconnections
from import _create_alias_map
from porespy.networks import _net_dict
from porespy.filters import snow_partitioning_n
from import make_contiguous, pad_faces
from porespy.metrics import region_surface_areas, region_interface_areas

[docs]def snow_n(im, voxel_size=1, boundary_faces=['top', 'bottom', 'left', 'right', 'front', 'back'], marching_cubes_area=False, alias=None): r""" Analyzes an image that has been segemented into N phases and extracts all a network for each of the N phases, including geometerical information as well as network connectivity between each phase. Parameters ---------- im : ND-array Image of porous material where each phase is represented by unique integer. Phase integer should start from 1 (0 is ignored) voxel_size : scalar The resolution of the image, expressed as the length of one side of a voxel, so the volume of a voxel would be **voxel_size**-cubed. The default is 1, which is useful when overlaying the PNM on the original image since the scale of the image is always 1 unit lenth per voxel. boundary_faces : list of strings Boundary faces labels are provided to assign hypothetical boundary nodes having zero resistance to transport process. For cubical geometry, the user can choose ‘left’, ‘right’, ‘top’, ‘bottom’, ‘front’ and ‘back’ face labels to assign boundary nodes. If no label is assigned then all six faces will be selected as boundary nodes automatically which can be trimmed later on based on user requirements. marching_cubes_area : bool If ``True`` then the surface area and interfacial area between regions will be calculated using the marching cube algorithm. This is a more accurate representation of area in extracted network, but is quite slow, so it is ``False`` by default. The default method simply counts voxels so does not correctly account for the voxelated nature of the images. alias : dict (Optional) A dictionary that assigns unique image label to specific phases. For example {1: 'Solid'} will show all structural properties associated with label 1 as Solid phase properties. If ``None`` then default labelling will be used i.e {1: 'Phase1',..}. Returns ------- A dictionary containing all N phases size data, as well as the network topological information. The dictionary names use the OpenPNM convention (i.e. 'pore.coords', 'throat.conns') so it may be converted directly to an OpenPNM network object using the ``update`` command. """ # ------------------------------------------------------------------------- # Get alias if provided by user al = _create_alias_map(im, alias=alias) # ------------------------------------------------------------------------- # Perform snow on each phase and merge all segmentation and dt together snow = snow_partitioning_n(im, r_max=4, sigma=0.4, return_all=True, mask=True, randomize=False, alias=al) # ------------------------------------------------------------------------- # Add boundary regions f = boundary_faces regions = add_boundary_regions(regions=snow.regions, faces=f) # ------------------------------------------------------------------------- # Padding distance transform to extract geometrical properties dt = pad_faces(im=snow.dt, faces=f) # ------------------------------------------------------------------------- # For only one phase extraction with boundary regions phases_num = sp.unique(im).astype(int) phases_num = sp.trim_zeros(phases_num) if len(phases_num) == 1: if f is not None: = pad_faces(, faces=f) regions = regions * ( regions = make_contiguous(regions) # ------------------------------------------------------------------------- # Extract N phases sites and bond information from image net = regions_to_network(im=regions, dt=dt, voxel_size=voxel_size) # ------------------------------------------------------------------------- # Extract marching cube surface area and interfacial area of regions if marching_cubes_area: areas = region_surface_areas(regions=regions) interface_area = region_interface_areas(regions=regions, areas=areas, voxel_size=voxel_size) net['pore.surface_area'] = areas * voxel_size ** 2 net['throat.area'] = interface_area.area # ------------------------------------------------------------------------- # Find interconnection and interfacial area between ith and jth phases net = add_phase_interconnections(net=net, snow_partitioning_n=snow, marching_cubes_area=marching_cubes_area, alias=al) # ------------------------------------------------------------------------- # label boundary cells net = label_boundary_cells(network=net, boundary_faces=f) # ------------------------------------------------------------------------- temp = _net_dict(net) = im.copy() temp.dt = dt temp.regions = regions return temp