- class openpnm.metrics.Porosimetry(*args, **kwargs)¶
Simulates mercury instrustion porosimetry using ordinary percolation
network (GenericNetwork) – The Network upon which this simulation should be run
name (str, optional) – An identifying name for the object. If none is given then one is generated.
Mercury intrusion progresses by applying increasing pressures to the invading mercury phase, and measuring the resultant volume of invading fluid. This corresponds directly to an ordinary percolation process, with access limitations enabled.
A shortcut to query the total number of pores on the object
A shortcut to query the total number of throats on the object
A shortcut to get a list of all pores on the object
A shortcut to get a list of all throats on the object
String representing the name of the object
A shortcut to get a handle to the associated network.
A shortcut to get a handle to the associated project.
Dictionary containing object settings.
get_conduit_data(poreprop[, throatprop, mode])
Combines requested data into a single 3-column array.
Obtain the numerical values of the calculated intrusion curve.
Find the invasion threshold at which a cluster spans from the inlet to the outlet sites
Retrieves requested property from associated objects, to produce a full Np or Nt length array.
Determines a pore (or throat) property as the average of it's neighboring throats (or pores)
Returns a True or False value to indicate if a percolating cluster spans between the inlet and outlet pores that were specified at the given applied pressure.
map_pores(pores, origin[, filtered])
Given a list of pore on a target object, finds indices of those pores on the calling object
map_throats(throats, origin[, filtered])
Given a list of throats on a target object, finds indices of those throats on the calling object
Plot the percolation curve as the invader volume or number fraction vs the applied capillary pressure.
props([element, mode, deep])
Returns a list containing the names of all defined pore or throat properties.
Resets the various data arrays on the object back to their original state.
run([points, start, stop])
Runs the percolation algorithm to determine which pores and throats will be invaded at each given pressure point.
Sets the locations from which the invader enters the network
Sets the locations through which defender exits the network.
Define which pore filling model to apply.
set_residual([pores, throats, overwrite])
Specify locations of any residual invader.
show_hist([props, bins, fontsize])
Shows a quick plot of key property distributions.
Converts a boolean mask to a list of pore or throat indices.
Convert a list of pore or throat indices into a boolean mask of the correct length.
Brief explanation of tomask
Brief explanation of tomask