def test_lattice(self):
# define links and network layout
N_side = 20
N = N_side**2
links = get_2D_lattice_links(N_side,
periodic=True,
diagonal_links=True)
network = get_grid_layout(N)
# define model
R0 = 3
recovery_rate = 1 / 8
model = StochasticSIRModel(N,
R0,
recovery_rate,
edge_weight_tuples=links)
model.set_random_initial_conditions({'I': 20, 'S': N - 20})
sampling_dt = 2
visualize(model,
network,
sampling_dt,
config={
'draw_nodes_as_rectangles': True,
'draw_links': False,
'show_legend': False,
'show_curves': False,
})
def test_grid_well_mixed(self):
N = 20 * 20
network = get_grid_layout(N)
R0 = 3
recovery_rate = 1 / 8
model = StochasticSIRModel(N, R0, recovery_rate)
model.set_random_initial_conditions({'I': 20, 'S': N - 20})
sampling_dt = 2
visualize(model,
network,
sampling_dt,
ignore_plot_compartments=['S'],
config={
'draw_nodes_as_rectangles': True,
'show_legend': False,
})
return self.u.flatten()
else:
return self.v.flatten()
if __name__=="__main__":
NSide = 200
N = NSide**2
Du = 0.16
Dv = 0.08
f = 0.060
k = 0.062
u, v = get_initial_configuration(NSide,random_influence=0.2)
dt = 20
GS = GrayScott(u,v,k,f,Du,Dv,periodic=True,diagonal_links=True)
network = get_grid_layout(N)
visualize_reaction_diffusion(GS,
network,
dt,
node_compartments=np.arange(N),
n_integrator_midpoints=20,
value_extent=[0,1],
config={'draw_nodes_as_rectangles':True}
)
NSide = 200
N = NSide**2
u, v = get_initial_configuration(NSide,random_influence=0.2)
Du = 0.16
Dv = 0.08
f = 0.060
k = 0.062
#DA, DB, f, k = 0.14, 0.06, 0.035, 0.065 # bacteria
dt = 1
updates_per_frame = 40
sampling_dt = updates_per_frame * dt
GS = GrayScott(u,v,k,f,Du,Dv,periodic=True,diagonal_links=False)
network = get_grid_layout(N,windowwidth=NSide)
visualize_reaction_diffusion(GS,
network,
sampling_dt,
node_compartments=np.arange(N),
n_integrator_midpoints=updates_per_frame-1,
#value_extent=[0.35,0.48],
config={'draw_nodes_as_rectangles':True}
)
#from bfmplot import pl
#pl.hist(GS.u)
#pl.show()
from epipack.vis import visualize, get_grid_layout
from epipack import get_2D_lattice_links
if __name__ == "__main__":
import netwulf as nw
from epipack import StochasticEpiModel
import networkx as nx
N_side = 200
N = N_side * N_side
links = get_2D_lattice_links(N_side, periodic=True, diagonal_links=True)
#links = get_2D_lattice_links(N_side,periodic=True,diagonal_links=False)
network = get_grid_layout(N, links, windowwidth=400)
k0 = 2 * len(links) / N
model = StochasticEpiModel(
list("SIRXTQ"),
N=N,
edge_weight_tuples=links,
)
Reff = 3
R0 = 10
recovery_rate = 1 / 8
quarantine_rate = 1 / 32
tracing_rate = 1 / 2
waning_immunity_rate = 1 / 14
infection_rate = Reff * (recovery_rate + quarantine_rate) / k0
infection_rate = R0 * (recovery_rate) / k0