porespy.generators.blobs#

porespy.generators.blobs(shape: List[int], porosity: float = 0.5, blobiness: int = 1, parallel_kw: dict = {'divs': 1}, seed: int = None, periodic: bool = True)#

Generates an image containing amorphous blobs

Parameters:

  • shape (list) – The size of the image to generate in [Nx, Ny, Nz] where N is the number of voxels

  • porosity (float) – If specified, this will threshold the image to the specified value prior to returning. If None is specified, then the scalar noise field is converted to a uniform distribution and returned without thresholding.

  • blobiness (int or list of ints (default = 1)) – Controls the morphology of the blobs. A higher number results in a larger number of small blobs. If a list is supplied then the blobs are anisotropic.

  • parallel_kw (dict) –

    Dictionary containing the settings for parallelization by chunking. The optional settings include divs (scalar or list of scalars, default = [2, 2, 2]), overlap (scalar or list of scalars, optional), and cores (scalar, default is all available cores).

    divs is the number of times to divide the image for parallel processing. If 1 then parallel processing does not occur. 2 is equivalent to [2, 2, 2] for a 3D image. If a list is provided, each respective axis will be divided by its corresponding number in the list. For example, [2, 3, 4] will divide z, y, and x axis to 2, 3, and 4 respectively.

    overlap is the amount of overlap to include when dividing up the image. This value is controlled by the blobiness and shape of the image by default but can be controlled using parallel_kw!

    cores is the number of cores that will be used to parallel process all domains. If None then all cores will be used but user can specify any integer values to control the memory usage. Setting value to 1 will effectively process the chunks in serial to minimize memory usage.

  • seed (int, default = None) – Initializes numpy’s random number generator to the specified state. If not provided, the current global value is used. This means calls to np.random.seed(seed) prior to calling this function will be respected.

  • periodic (bool, default = True) – If True the blobs will be periodic, meaning that the image can be tiled and the phases will be continuous. False will provide the “legacy” version of an image, which has high-porosity artifacts at the image boundaries.

Returns:

image – A boolean array with True values denoting the pore space

Return type:

ndarray

See also

all_to_uniform

Notes

This function generates random noise, the applies a gaussian blur to the noise with a sigma controlled by the blobiness argument as: np.mean(shape) / (40 * blobiness)

The value of 40 was chosen so that a blobiness of 1 gave a reasonable result.

Examples

Click here to view online example.

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