N.setParam (0, "roessler_omega", 1.0); N.addNode(co.roessler()) #N.addWeightedEdge(0,1,0.5) #N.addWeightedEdge(1,0,0.5) N.addEdge(0,1,co.weightedEdge(0.5)) N.addEdge(1,0,co.weightedEdge(0.5)) N.setState(0, 0.0,0.0,0.0) N.setState(1, 1.0,1.0,0.0) N.printNodeStatistics(); N.observeTime("output/roesslerRoesslerCoupled.py.series") N.observe(0,"output/roesslerRoesslerCoupled.py.series", co.component(0)) N.observe(0,"output/roesslerRoesslerCoupled.py.series", co.component(1)) N.observe(0,"output/roesslerRoesslerCoupled.py.series", co.component(2)) N.observe(1,"output/roesslerRoesslerCoupled.py.series", co.component(0)) N.observe(1,"output/roesslerRoesslerCoupled.py.series", co.component(1)) N.observe(1,"output/roesslerRoesslerCoupled.py.series", co.component(2)) N.evolve(0.0,1500.0)
import conedy as co N = co.network() newNodeNumber = N.addNode( co.roessler() ) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(0)) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(1)) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(2)) N.snapshot()
import conedy as co N = co.network() newNodeNumber = N.addNode(co.roessler()) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(0)) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(1)) N.observe(newNodeNumber, "output/snapshot.py.series", co.component(2)) N.snapshot()
import conedy as co N = co.network() co.set("kuramoto_omega", 0.1) co.set("samplingTime", 0.01) #just one kuramoto oscillator firstNodeNumber = N.addNode(co.kuramoto()) N.setState(firstNodeNumber, 0.0) N.observeTime("output/kuramoto.py.one") N.observe(0, "output/kuramoto.py.one", co.component(0)) N.evolve(0.0, 10.0) N.removeObserver() #adding a second. They should synchronize. secondNodeNumber = N.addNode(co.kuramoto()) N.addEdge(firstNodeNumber, secondNodeNumber, co.weightedEdge(0.1)) N.addEdge(secondNodeNumber, firstNodeNumber, co.weightedEdge(0.1)) #small ring of oscillators. Should not synchronize. N.setState(firstNodeNumber, 0.0) N.setState(secondNodeNumber, 0.3) N.observeTime("output/kuramoto.py.two") N.observeAll("output/kuramoto.py.two") N.evolve(0.0, 40.0) N.removeObserver() thirdNodeNumber = N.addNode(co.kuramoto())
import conedy as co co.set("samplingTime", 0.02) co.set("hodgkinHuxley_I", 20.0) N = co.network() N.lattice(1, 1, 1.0, co.hodgkinHuxley()) N.observeTime("output/hodgkinHuxley.co.single") N.observeAll("output/hodgkinHuxley.co.single", co.component(0)) N.observeAll("output/hodgkinHuxley.co.single", co.component(1)) N.evolve(0.0, 500.0)
import conedy as co N = co.network() firstNode = N.addNode(co.roessler()) secondNode = N.addNode(co.roessler()) N.addEdge(firstNode, secondNode, co.component(2)) N.printNodeStatistics()
import conedy as co N = co.network() N.addNode(co.ornUhl()) N.observeTime("output/doubleEvolveSde.py.series") N.observeAll("output/doubleEvolveSde.py.series", co.component(0)) N.evolve(0.0, 1.0) N.evolve(1.0, 2.0)
import conedy as co N = co.network() co.set("ornUhl_drift" , 0.2) co.set("ornUhl_diffusion" , 0.1) co.set("samplingTime", 0.1) N.addNode(co.ornUhl()) N.setState(0, 1.0) N.observeTime("output/sdeIntegrator.py.series") N.observeAll("output/sdeIntegrator.py.series", co.component(0)) N.evolve(0.0,15000.0) # to calculate the variance of the ornstein-uhlenbeck # the variance should be diffusion^2/(2*drift) file = open('output/sdeIntegrator.py.series') sum = 0 s2 = 0 n = 0 for line in file: fl = float(line.split()[1]) sum += fl s2 += fl*fl
N.addNode(co.roessler()) #co.set("roessler_omega", 1.0) N.setParam(0, "roessler_omega", 1.0) N.addNode(co.roessler()) #N.addWeightedEdge(0,1,0.5) #N.addWeightedEdge(1,0,0.5) N.addEdge(0, 1, co.weightedEdge(0.5)) N.addEdge(1, 0, co.weightedEdge(0.5)) N.setState(0, 0.0, 0.0, 0.0) N.setState(1, 1.0, 1.0, 0.0) N.printNodeStatistics() N.observeTime("output/roesslerRoesslerCoupled.py.series") N.observe(0, "output/roesslerRoesslerCoupled.py.series", co.component(0)) N.observe(0, "output/roesslerRoesslerCoupled.py.series", co.component(1)) N.observe(0, "output/roesslerRoesslerCoupled.py.series", co.component(2)) N.observe(1, "output/roesslerRoesslerCoupled.py.series", co.component(0)) N.observe(1, "output/roesslerRoesslerCoupled.py.series", co.component(1)) N.observe(1, "output/roesslerRoesslerCoupled.py.series", co.component(2)) N.evolve(0.0, 1500.0)
import conedy as co N = co.network() co.set("kuramoto_omega", 0.1) co.set("samplingTime", 0.01) #just one kuramoto oscillator firstNodeNumber = N.addNode(co.kuramoto()) N.setState(firstNodeNumber, 0.0 ) N.observeTime("output/kuramoto.py.one") N.observe(0,"output/kuramoto.py.one", co.component(0)) N.evolve(0.0,10.0) N.removeObserver() #adding a second. They should synchronize. secondNodeNumber = N.addNode(co.kuramoto()) N.addEdge (firstNodeNumber,secondNodeNumber ,co.weightedEdge(0.1)) N.addEdge (secondNodeNumber, firstNodeNumber ,co.weightedEdge(0.1)) #small ring of oscillators. Should not synchronize. N.setState(firstNodeNumber, 0.0 ) N.setState(secondNodeNumber, 0.3 )
import conedy as co N = co.network() co.set("lorenz_S", 10.0) co.set("lorenz_r", 28.0) co.set("lorenz_b", 8.0/3.0) co.set("samplingTime" , 0.01) N.addNode(co.lorenz()) N.setState(0, 1.0, 1.0, 1.0) N.observeTime("output/lorenz.py.series") N.observeAll("output/lorenz.py.series", co.component(0)) N.observeAll("output/lorenz.py.series", co.component(1)) N.observeAll("output/lorenz.py.series", co.component(2)) N.evolve(0.0,1500.0)
import conedy as co N = co.network() newNodeNumber = N.addNode(co.logisticMap()) N.observe(newNodeNumber, "output/setState.py.state") N.setState(newNodeNumber, 0.3) newNodeNumber = N.addNode(co.roessler()) N.setState(newNodeNumber, 0.1,0.2,0.25) N.observe(newNodeNumber, "output/setState.py.state",co.component(0)) N.observe(newNodeNumber, "output/setState.py.state",co.component(1)) N.observe(newNodeNumber, "output/setState.py.state",co.component(2)) N.snapshot()
co.set("roessler_omega", 20.0) co.set("roessler_a", 0.165) co.set("roessler_b", 0.2) co.set("roessler_c", 10.0) co.set("lorenz_S", 10.0) co.set("lorenz_r", 28.0) co.set("lorenz_b", 8.0/3.0) co.set("samplingTime", 0.01) i = N.addNode(co.roessler()) j = N.addNode(co.lorenz()) N.addEdge(i, j, co.weightedEdge(2.5)) N.setState(i, 0.0, 0.0, 0.0) N.setState(j, 1.0, 1.0, 1.0) N.observeTime("output/roesslerLorenzCoupled.py.series") N.observe(i,"output/roesslerLorenzCoupled.py.series",co.component(0)) N.observe(i,"output/roesslerLorenzCoupled.py.series",co.component(1)) N.observe(i,"output/roesslerLorenzCoupled.py.series",co.component(2)) N.observe(j,"output/roesslerLorenzCoupled.py.series",co.component(0)) N.observe(j,"output/roesslerLorenzCoupled.py.series",co.component(1)) N.observe(j,"output/roesslerLorenzCoupled.py.series",co.component(2)) N.evolve(0.0,1500.0)
N = co.network() co.set("roessler_omega", 20.0) co.set("roessler_a", 0.165) co.set("roessler_b", 0.2) co.set("roessler_c", 10.0) co.set("lorenz_S", 10.0) co.set("lorenz_r", 28.0) co.set("lorenz_b", 8.0 / 3.0) co.set("samplingTime", 0.01) i = N.addNode(co.roessler()) j = N.addNode(co.lorenz()) N.addEdge(i, j, co.weightedEdge(2.5)) N.setState(i, 0.0, 0.0, 0.0) N.setState(j, 1.0, 1.0, 1.0) N.observeTime("output/roesslerLorenzCoupled.py.series") N.observe(i, "output/roesslerLorenzCoupled.py.series", co.component(0)) N.observe(i, "output/roesslerLorenzCoupled.py.series", co.component(1)) N.observe(i, "output/roesslerLorenzCoupled.py.series", co.component(2)) N.observe(j, "output/roesslerLorenzCoupled.py.series", co.component(0)) N.observe(j, "output/roesslerLorenzCoupled.py.series", co.component(1)) N.observe(j, "output/roesslerLorenzCoupled.py.series", co.component(2)) N.evolve(0.0, 1500.0)
import conedy as co N = co.network() co.set ("roessler_a", 0.22) co.set ("roessler_b", 0.1) co.set ("roessler_c", 8.5) r1 = N.addNode(co.roessler()) r2 = N.addNode(co.roessler()) r3 = N.addNode(co.roessler()) N.setParam(r1, "roessler_omega", 1.02) N.setParam(r2, "roessler_omega", 1.0) N.setParam(r3, "roessler_omega", 0.98) N.randomizeStates (co.roessler(), co.uniform (-10.0, 10.0),co.uniform (-5.0, 5.0), co.uniform (-0.5, 1.5)) N.addEdge(r1, r2, co.weightedEdge(0.075)) N.addEdge(r2, r1, co.weightedEdge(0.075)) N.addEdge(r1, r3, co.weightedEdge(0.075)) N.addEdge(r3, r1, co.weightedEdge(0.075)) N.evolve(0.0, 100.0) N.observeTime("roessler.dat") N.observe(r1, "roessler.dat", co.component(1)) N.observe(r2, "roessler.dat", co.component(1)) N.observe(r3, "roessler.dat", co.component(1)) co.set("samplingTime", 0.01) N.evolve(100.0, 200.0)
import conedy as co co.set("samplingTime", 0.02) co.set("hodgkinHuxley_I", 20.0) N = co.network() N.lattice(1,1,1.0,co.hodgkinHuxley()) N.observeTime("output/hodgkinHuxley.co.single") N.observeAll("output/hodgkinHuxley.co.single",co.component(0)) N.observeAll("output/hodgkinHuxley.co.single",co.component(1)) N.evolve(0.0,500.0)
import conedy as co N = co.network() co.set("lorenz_S", 10.0) co.set("lorenz_r", 28.0) co.set("lorenz_b", 8.0 / 3.0) co.set("samplingTime", 0.01) N.addNode(co.lorenz()) N.setState(0, 1.0, 1.0, 1.0) N.observeTime("output/lorenz.py.series") N.observeAll("output/lorenz.py.series", co.component(0)) N.observeAll("output/lorenz.py.series", co.component(1)) N.observeAll("output/lorenz.py.series", co.component(2)) N.evolve(0.0, 1500.0)
import conedy as co N = co.network() N.randomNetwork(100, 0.1, co.roessler()) N.randomizeStates(co.roessler(), co.uniform (0.0,1.0), co.uniform (0.2,0.4), co.constant(0.8)) N.observeAll("output/randomizeStates.py.allStates",co.component(0)) N.observeAll("output/randomizeStates.py.allStates",co.component(1)) N.observeAll("output/randomizeStates.py.allStates",co.component(2)) N.snapshot()
import conedy as co co.set("samplingTime", 1.0) co.set("barkley_I", 0.1) N = co.network() N.lattice(1,1,1.0,co.barkley()) N.observeTime("output/barkley.py.single") N.observeAll("output/barkley.py.single", co.component(0) ) N.observeAll("output/barkley.py.single", co.component(1) ) N.evolve(0.0,500.0)
import conedy as co N = co.network() co.set ("gaussianBarkley_sigma", 0.18) bark = co.gaussianBarkley() bark.setState (0.0, 0.0) N.lattice(512, 512, 1.0, bark, co.staticWeightedEdge (3.84)) N.rewire(0.001) N.evolve(0.0, 20.0) N.observeAll("waves.dat", co.component(0)) N.snapshot()
N = co.network() nodeblueprint = co.gaussianRoessler() co.set("gaussianRoessler_a", 0.165) co.set("gaussianRoessler_b", 0.2) co.set("gaussianRoessler_c", 10.0) co.set("gaussianRoessler_sigmaNoise", 0.1) N.cycle(100, 4, nodeblueprint, co.weightedEdge(0.1)) N.rewire(0.1) print "clustering coefficient:" + str(N.meanClustering()) print "mean path length:" + str(N.meanPathLength()) if N.isConnected(): N.betweennessCentrality("N.betweenness") N.closenessCentrality("N.closeness") N.randomizeParameter("gaussianRoessler_omega", co.uniform(0.8, 1.2)) N.randomizeStates(nodeblueprint, co.uniform(-0.1, 0.1), co.uniform(-0.1, 0.1), co.uniform(-0.1, 0.1)) N.evolve(0.0, 100.0) N.observeTime("output_Roessler") N.observeAll("output_Roessler", co.component(2)) co.set("samplingTime", 0.01) N.evolve(100.0, 200.0)
import conedy as co N = co.network() firstNode = N.addNode(co.roessler()) secondNode = N.addNode(co.roessler()) N.addEdge (firstNode,secondNode, co.component (2) ) N.printNodeStatistics()
import conedy as co N = co.network() co.set("gaussianRoessler_omega", 0.89) co.set("gaussianRoessler_a", 0.165) co.set("gaussianRoessler_b", 0.2) co.set("gaussianRoessler_c", 10.0) co.set("gaussianRoessler_sigmaNoise", 1.0) co.set("samplingTime", 0.01) N.addNode(co.gaussianRoessler()) N.setState(0, 0.0, 0.0, 0.0) N.observeTime("output/gaussianRoessler.py.series") N.observeAll("output/gaussianRoessler.py.series", co.component(0)) N.observeAll("output/gaussianRoessler.py.series", co.component(1)) N.observeAll("output/gaussianRoessler.py.series", co.component(2)) N.evolve(0.0, 1500.0)
import conedy as co N = co.network() co.set("samplingTime", 0.01) co.set("roessler_omega", 0.89) co.set("roessler_a", 0.165) co.set("roessler_b", 0.2) co.set("roessler_c", 10.0) N.addNode(co.roessler()) N.setState(0, 0.0, 0.0, 0.0) N.observeTime("output/roessler.py.series") N.observeAll("output/roessler.py.series", co.component(0)) N.observeAll("output/roessler.py.series", co.component(1)) N.observeAll("output/roessler.py.series", co.component(2)) N.evolve(0.0, 1500.0)