regions_to_network#
- regions_to_network(regions, phases=None, voxel_size=1, accuracy='standard')[source]#
Analyzes an image that has been partitioned into pore regions and extracts the pore and throat geometry as well as network connectivity.
- Parameters:
regions (ndarray) – An image of the material partitioned into individual regions. Zeros in this image are ignored.
phases (ndarray, optional) – An image indicating to which phase each voxel belongs. The returned network contains a ‘pore.phase’ array with the corresponding value. If not given a value of 1 is assigned to every pore.
voxel_size (scalar (default = 1)) – 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.
accuracy (string) –
Controls how accurately certain properties are calculated. Options are:
- ’standard’ (default)
Computes the surface areas and perimeters by simply counting voxels. This is much faster but does not properly account for the rough, voxelated nature of the surfaces.
- ’high’
Computes surface areas using the marching cube method, and perimeters using the fast marching method. These are substantially slower but better account for the voxelated nature of the images.
- Returns:
net – A dictionary containing all the pore and throat size data, as well as the network topological information. The dictionary names use the OpenPNM convention (i.e. ‘pore.coords’, ‘throat.conns’).
- Return type:
dict
Notes
The meaning of each of the values returned in
net
are outlined below:- ‘pore.region_label’
The region labels corresponding to the watershed extraction. The pore indices and regions labels will be offset by 1, so pore 0 will be region 1.
- ‘throat.conns’
An Nt-by-2 array indicating which pores are connected to each other
- ‘pore.region_label’
Mapping of regions in the watershed segmentation to pores in the network
- ‘pore.local_peak’
The coordinates of the location of the maxima of the distance transform performed on the pore region in isolation
- ‘pore.global_peak’
The coordinates of the location of the maxima of the distance transform performed on the full image
- ‘pore.geometric_centroid’
The center of mass of the pore region as calculated by
skimage.measure.center_of_mass
- ‘throat.global_peak’
The coordinates of the location of the maxima of the distance transform performed on the full image
- ‘pore.region_volume’
The volume of the pore region computed by summing the voxels
- ‘pore.volume’
The volume of the pore found by as volume of a mesh obtained from the marching cubes algorithm
- ‘pore.surface_area’
The surface area of the pore region as calculated by either counting voxels or using the fast marching method to generate a tetramesh (if
accuracy
is set to'high'
.)- ‘throat.cross_sectional_area’
The cross-sectional area of the throat found by either counting voxels or using the fast marching method to generate a tetramesh (if
accuracy
is set to'high'
.)- ‘throat.perimeter’
The perimeter of the throat found by counting voxels on the edge of the region defined by the intersection of two regions.
- ‘pore.inscribed_diameter’
The diameter of the largest sphere inscribed in the pore region. This is found as the maximum of the distance transform on the region in isolation.
- ‘pore.extended_diameter’
The diamter of the largest sphere inscribed in overal image, which can extend outside the pore region. This is found as the local maximum of the distance transform on the full image.
- ‘throat.inscribed_diameter’
The diameter of the largest sphere inscribed in the throat. This is found as the local maximum of the distance transform in the area where to regions meet.
- ‘throat.total_length’
The length between pore centered via the throat center
- ‘throat.direct_length’
The length between two pore centers on a straight line between them that does not pass through the throat centroid.
Examples
Click here to view online example.