updated for new simulation runs

    #new parameters necessary for the structure

    par.set_xhierarchicalelementsize(2) # log_el(nx) = h <-> nx = el**h 

    par.set_yhierarchicalelementsize(2)

    par.set_gapzoffset(0) # == o_set

    par.set_thresholdrng(seed)

    par.set_structurerng(seed + 1_000_000)

    par.set_weibullparameter(1.5)

    #element sizes as determined by set_xhierarchicalelementsize() and set_yhierarchicalelementsize()

    #in the corresponding directions; arangement dependent on seed given by set_structurerng()

    #for the random positioning

    constructor = mn.cubic3D.ShuffledHierarchicalOffsetDecorator(constructor)

    constructor = mn.cubic3D.ShuffledHierarchicalGapsDecorator(constructor)

    constructor = mn.cubic3D.ScalingWeibullThresholdDecorator(constructor)

    boundaries = mn.general.EmptyBoundariesConstructor()

import sys

import numpy as np

import mechnet as mn

from multiprocessing import Pool

def get_parametercollection(seed):

    par = mn.ParameterCollection()

    nx = 64 # needs to == el**h

    ny = nx

    nz = 9 # need to be >=  h +2 + o_set (+2 bc bound cond)    

    n = nx*ny*nz

    par.set_N(n)

    par.set_Nx(nx)

    par.set_Ny(ny)

    par.set_Nz(nz)

    par.set_NxNy()

    #new parameters necessary for the structure

    par.set_xhierarchicalelementsize(2) # log_el(nx) = h <-> nx = el**h 

    par.set_yhierarchicalelementsize(2)

    par.set_gapzoffset(1) # == o_set

    par.set_thresholdrng(seed)

    par.set_structurerng(seed + 1_000_000)

    par.set_weibullparameter(1.5)

    par.set_scalingfactor(1.00)

    par.set_uniformupperdirichlet(1.0)

    return par

def run_a_simulation_fuse(seed):

    constructor = mn.cubic3D.Cubic3DFullConnectionConstructor()

    #new decorators to modify network structure:

    #random positioning of missing edges fitting to the amount that would be missing in a hierarchical network with

    #element sizes as determined by set_xhierarchicalelementsize() and set_yhierarchicalelementsize()

    #in the corresponding directions; arangement dependent on seed given by set_structurerng()

    #for the random positioning

    constructor = mn.cubic3D.ShuffledHierarchicalOffsetDecorator(constructor)

    constructor = mn.cubic3D.ScalingWeibullThresholdDecorator(constructor)

    boundaries = mn.general.EmptyBoundariesConstructor()

    boundaries = mn.cubic3D.FixedLowerBoundaryDecorator(boundaries)

    boundaries = mn.cubic3D.UniformDisplacedUpperBoundaryDecorator(boundaries)

    parametercollection = get_parametercollection(seed)

    network = constructor.start_construction(parametercollection)

    bounded_network = boundaries.start_assign_boundaries(network)

    #switch to fuse simulation to make it easier to read the resulting stiffness matrix

    dict_of_simulation_parameters = {"niter":10_000_000, "externalV":1.0, "accuracy":12}

    builder = mn.sim.FuseDirichletBuilder()

    solver = mn.sim.PARDISOBindingsSolver()

    intrescal = mn.sim.StartInterimResultsCalculator() #InterimResultsCalculator stack pre-computes data needed for output and simulation step

    intrescal = mn.sim.FuseCurrentsVoltagesCalculator(intrescal)

    outgen = mn.sim.StartOutputGenerator()

    applier = mn.sim.HottestFuseBreakApplier()

    checker = mn.sim.NonInitialChecker(mn.sim.ConnectedPathChecker())

    simulation = mn.sim.Simulation(builder, solver, intrescal, outgen, applier, checker)

    dict_of_crs_edge_data = bounded_network.get_network_data() 

    simdata = simulation.start_simulation(dict_of_crs_edge_data, dict_of_simulation_parameters)

    simdata_dict = simdata.get_simdata_dict()

    network_descriptor_dict = bounded_network.get_construction_data()

    print("done with sim of seed", seed)

    return (network_descriptor_dict, simdata_dict, simulation.simulationname, simulation.simulationdoc)

if __name__=="__main__":

    list_of_parameters =  []

    for seed in range(1000, 1010):

        list_of_parameters.append(seed) 

    with Pool(10) as p:

        results = p.map(run_a_simulation_fuse, list_of_parameters)

    for data in results:

        mn.datman.save_simulation_output(data[0], data[1], data[2], data[3], targetdirectory="./", suffix="", overwritemode=False)

    #print(data[1]["current_data"]["stiffnessmatrix"].toarray())

    print("\nRun successfull.")

 No newline at end of file

    par = mn.ParameterCollection()

    nx = 64 # needs to == el**h

    ny = nx

    nz = 9 # need to be >=  h +2 + o_set (+2 bc bound cond)    

    nz = 10 # need to be >=  h +2 + o_set (+2 bc bound cond)    

    n = nx*ny*nz

    par.set_N(n)

    par.set_Nx(nx)

    #new parameters necessary for the structure

    par.set_xhierarchicalelementsize(2) # log_el(nx) = h <-> nx = el**h 

    par.set_yhierarchicalelementsize(2)

    par.set_gapzoffset(1) # == o_set

    par.set_gapzoffset(2) # == o_set

    par.set_thresholdrng(seed)

    par.set_structurerng(seed + 1_000_000)

    par.set_weibullparameter(1.5)