porespy.networks.get_throat_area#

porespy.networks.get_throat_area(im, sk, throats, voxel_size=1, n_walkers=10, step_size=0.5, max_n_steps=None)#

This function returns the cross-sectional acrea of throats.

Parameters:

  • im (ndarray (boolean)) – Image of porous material where True indicates the void phase and False indicates solid

  • sk (ndarray) – The skeleton of an image

  • throats (ndarray) – An ndarray the same shape as im with clusters of throat voxels uniquely labelled (1…Nt). If a boolean array is provided then a cluster labeling is performed with full cubic connectivity. Walkers are sent from each voxel in throats. Therefore, reducing clusters of throat voxels beforehand could help reduce computation time but consequently will reduce the amount of imformation available. It is important that each voxel specified in this image has exactly two neighbours on the skeleton!

  • 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

  • n_walkers (int (default=10)) – The number of walkers to start from each voxel in throats. If 2D image is passed then 2 walkers is used automatically since there are only two directions perpendicular to normal in 2D.

  • step_size (float or ndarray (default=0.5)) – The size of each step to take. This is equivalent to r in spherical coordinates. If an ndarray is passed, it is assume that this is the distance transform the same shape as im. Pass the distance transform if you would like to adaptively effect step size for significant speed up.

  • max_n_steps (int (optional)) – The maximum number of steps to take. The default is None, in which case there is no maximum and the walk will stop when ALL walkers have reached solid.

Returns:

throat_area – The original throats image with labelled voxels overwritten by their measured throat areas.

Return type:

ndarray

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