porespy.filters.find_trapped_clusters

porespy.filters.find_trapped_clusters(im: numpy.typing.ArrayLike, seq: numpy.typing.ArrayLike, outlets: numpy.typing.ArrayLike, conn: Literal['min', 'max'] = 'min', method: Literal['queue', 'labels'] = 'labels')

Find the trapped regions given an invasion sequence map and specified outlets

Parameters:

• im (ndarray) – The boolean image of the porous material with True indicating the phase of interest.

• seq (ndarray) – An image with invasion sequence values in each voxel. Regions labelled -1 are considered uninvaded, and regions labelled 0 are considered solid. Because sequence values are used, this function is agnostic to whether the invasion followed drainage or imbibition.

• outlets (ndarray) – An image the same size as im with True indicating outlets and False elsewhere.

• conn (str) –

  Controls the shape of the structuring element used to determine if voxels are connected. Options are:

  Option	Description
  ’min’	This corresponds to a cross with 4 neighbors in 2D and 6 neighbors in 3D.
  ’max’	This corresponds to a square or cube with 8 neighbors in 2D and 26 neighbors in 3D.

• method (str) –

  Controls which method is used to analyze the invasion sequence. Options are:

  Option	Description
  ’labels’	Uses scipy.ndimage.label to find all clusters of invading phase connected to the outlet at each value of sequence found on the outlet face. This method is faster if ibop was used for the simulation.
  ’queue’	Uses a priority queue and walks the invasion process in reverse to find all trapped voxels. This method is faster if ibip or qbip was used for the simulation.

Returns:

trapped – A boolean mask indicating which voxels were found to be trapped.

Return type:

ndarray

Examples

Click here to view online example.