CubicTemplate

class openpnm.network.CubicTemplate(*args, **kwargs)[source]

Simple cubic lattice with arbitrary domain shape specified by a template image

The class creates a standard Cubic network the same shape as the provided image, then trims pores from the network that are not in the mask.

Parameters
  • template (array_like) – The array (image) describing the desired shape of the domain. All locations in the image that are marked as True are kept while the rest of trimmed to yeild the shape.

  • spacing (array_like, optional) – The spacing between pore centers in each direction. If not given, then [1, 1, 1] is assumed.

  • name (str) – An optional name for the object to help identify it. If not given, one will be generated.

Notes

The other arguments are the same as Cubic except that shape is inferred from the template image.

Examples

import openpnm as op
import matplotlib.pyplot as plt

im = op.topotools.template_cylinder_annulus(10, 15, 10)
pn = op.network.CubicTemplate(template=im)

# It can be plotted for quick visualization using
fig, ax = plt.subplots(figsize=(5, 5))
op.topotools.plot_connections(network=pn, ax=ax, linewidth=0.5)

plt.show()
../../_images/openpnm-network-CubicTemplate-1.svg

For larger networks and more control over presentation use Paraview.

Attributes
Np

A shortcut to query the total number of pores on the object

Nt

A shortcut to query the total number of throats on the object

Ps

A shortcut to get a list of all pores on the object

Ts

A shortcut to get a list of all throats on the object

am

Adjacency matrix in the specified sparse format, with throat IDs indicating the non-zero values.

conns

Returns the connectivity matrix of the network.

coords

Returns the list of pore coordinates of the network.

im

Incidence matrix in the specified sparse format, with pore IDs indicating the non-zero values.

models

List of available models on the objects

name

String representing the name of the object

network

A shortcut to get a handle to the associated network.

project

A shortcut to get a handle to the associated project.

settings

Dictionary containing object settings.

Methods

add_boundary_pores([labels, spacing])

Add pores to the faces of the network for use as boundary pores.

add_model(propname, model[, regen_mode])

Adds a new model to the models dictionary.

check_network_health()

This method check the network topological health.

create_adjacency_matrix([weights, fmt, ...])

Generates a weighted adjacency matrix in the desired sparse format

create_incidence_matrix([weights, fmt, ...])

Creates a weighted incidence matrix in the desired sparse format

filter_by_label([pores, throats, labels, mode])

Returns which of the supplied pores (or throats) has the specified label(s)

find_connected_pores([throats, flatten, mode])

Return a list of pores connected to the given list of throats

find_connecting_throat(P1, P2)

Return the throat index connecting pairs of pores.

find_nearby_pores(pores, r[, flatten, ...])

Find all pores within a given radial distance of the input pore(s) regardless of whether or not they are toplogically connected.

find_neighbor_pores(pores[, mode, flatten, ...])

Returns a list of pores that are direct neighbors to the given pore(s)

find_neighbor_throats(pores[, mode, flatten])

Returns a list of throats neighboring the given pore(s)

get_adjacency_matrix([fmt])

Adjacency matrix in the specified sparse format, with throat IDs indicating the non-zero values.

get_conduit_data(poreprop[, throatprop, mode])

Combines requested data into a single 3-column array.

get_incidence_matrix([fmt])

Incidence matrix in the specified sparse format, with pore IDs indicating the non-zero values.

interleave_data(prop)

Retrieves requested property from associated objects, to produce a full Np or Nt length array.

interpolate_data(propname[, mode])

Determines a pore (or throat) property as the average of it's neighboring throats (or pores)

labels([pores, throats, element, mode])

Returns a list of labels present on the object

num_neighbors(pores[, mode, flatten])

Returns the number of neigbhoring pores for each given input pore

num_pores([labels, mode])

Returns the number of pores of the specified labels

num_throats([labels, mode])

Return the number of throats of the specified labels

params()

Return parameter names and values in a dictionary

pores([labels, mode, asmask, to_global])

Returns pore indicies where given labels exist, according to the logic specified by the mode argument.

props([element, mode, deep])

Returns a list containing the names of all defined pore or throat properties.

regenerate_models([propnames, exclude, deep])

Re-runs the specified model or models.

remove_model([propname, mode])

Removes model and data from object.

set_label(label[, pores, throats, mode])

Creates or updates a label array

show_hist([props, bins, fontsize])

Shows a quick plot of key property distributions.

throats([labels, mode, asmask, to_global])

Returns throat locations where given labels exist, according to the logic specified by the mode argument.

to_indices(mask)

Converts a boolean mask to a list of pore or throat indices.

to_mask([pores, throats])

Convert a list of pore or throat indices into a boolean mask of the correct length.