misc

Miscellaneous

This submodule contains models for calculating general or generic values that are useful for all other pore-scale models, such as scaling values, or generating an array of random numbers.

Functions

blank(target)	Blank model used in PNM format, acting as a placeholder
clip(target, prop, xmax[, xmin])	Clips the given array within the supplied limits
constant(target, value)	Places the given constant value into the target object
difference(target, props)	Subtracts elements 1:N in props from element 0
fraction(target, numerator, denominator)	Calculates the ratio between two values
from_neighbor_pores(target, prop[, mode, ...])	Adopt a value based on the values in neighboring pores
from_neighbor_throats(target, prop[, mode, ...])	Adopt a value from the values found in neighboring throats
generic_distribution(network, seeds, func, ...)	Accepts an object from the Scipy.stats submodule and returns values from the distribution for the given seeds
generic_function(target, prop, func, **kwargs)	Runs an arbitrary function on the given data
invert(target, prop)	Inverts the given array
linear(target, m, b, prop)	Calculates a property as a linear function of a given property
match_histogram(network, bin_centers, ...[, ...])	Generate values corresponding to a given histogram
normal(network, seeds[, mean, stddev, ...])	Produces values from a Weibull distribution given a set of random numbers.
normalize(target, prop[, xmin, xmax])	Normalizes the given array between the supplied limits
polynomial(target, a, prop)	Calculates a property as a polynomial function of a given property
product(target, props)	Calculates the product of multiple property values
random(network, element[, seed, num_range])	Create an array of random numbers of a specified size.
scaled(target, prop, factor)	Scales an existing value by a factor.
summation(target[, props])	Sums the values in the given arrays
weibull(network, seeds, shape, scale, loc)	Produces values from a Weibull distribution given a set of random numbers.