noah/CS-7863-Sci-Stat-Final
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Model Parameters

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This commit is contained in:
Noah L. Schrick 2023-04-28 18:26:05 -05:00
parent 56f6a9bb90
commit 7942bbb48a
2 changed files with 62 additions and 11 deletions
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2
Analysis/1_mo_color_DOTFILE.dot
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@ -393,6 +393,7 @@ strict digraph G {
391;
392;
393;
394 [fillcolor=red,style=filled];
0->1 [label=5];
1->2 [label=5];
2->3 [label=2];
@ -1771,4 +1772,5 @@ strict digraph G {
390->393 [label=1];
391->393 [label=2];
392->393 [label=2];
393->394 [label=99];
}

71
Analysis/prep_model.py
View File

@ -4,20 +4,23 @@ import networkx as nx
import matplotlib.pyplot as plt
from collections import OrderedDict
from operator import getitem
import itertools, os
import itertools, os, sys
# Change dir to location of this python file
os.chdir(os.path.dirname(sys.argv[0]))
# AGraph preserves attributes, networkx Graph does not.
# Many of the desired functions are in networkx.
# So import AGraph to keep attributes, then convert to Networkx.
A = nx.drawing.nx_agraph.to_agraph(nx.drawing.nx_pydot.read_dot("./1_mo_color_DOTFILE.dot"))
A.layout('dot')
A.draw('tree.png')
#A.draw('tree.png')
A.remove_node('\\n') # Remove "newline" node from newline end of dot file
G=nx.DiGraph(A)
color_map = []
color_d = {}
node_pos = {}
node_pos = {} # used for drawing/graphing
# Compartments
S = 0
@ -26,14 +29,7 @@ E = 0
R = 0
D = 0
# Params
beta = 0
delta = 0
gamma_r = 0
gamma_d = 0
mu = 0
epsilon = 0
omega = 0
ep_tmp = 0 # counter for epsilon
for node in A:
color = A.get_node(node).attr.to_dict()['fillcolor']
@ -46,11 +42,64 @@ for node in A:
color_map.append("white")
color_d[node] = color
in_edges = list(G.in_edges(node))
tmp_S = 1
for source in in_edges:
tmp_S = 1
# If previous node was infected, then we are recovered
if (color_d[source[0]] == 'red'):
R = R + 1
tmp_S = 0
break # No need to check the other nodes
S = S + tmp_S
#G[source[0]][node]['weight'] = 3
elif color == 'yellow':
color_map.append(color)
color_d[node] = color
in_edges = list(G.in_edges(node))
tmp_E = 1
for source in in_edges:
tmp_E = 1
# If previous node was infected, then we are recovered
if (color_d[source[0]] == 'red'):
R = R + 1
tmp_E = 0
break # No need to check the other nodes
E = E + tmp_E
else:
color_map.append(color)
color_d[node] = color
I = I + 1
# Check if node dies
out_edges = list(G.out_edges(node))
if not out_edges:
D = D + 1
# Check if imported
in_edges = list(G.in_edges(node))
if not in_edges:
ep_tmp = ep_tmp + 1
# Params
beta = I/len(A) # rate of infec (I/total?)
delta = E/len(A) # symptom appearance rate (E/total?)
gamma_r = R/len(A) # recov rate (R/total?)
gamma_d = D/len(A) # death rate (D/total?)
mu = D/I # fatality ratio (D/I)
epsilon = ep_tmp/len(A) # infected import rate
omega = 0 # waning immunity rate
print("Model Compartments:")
print("S:", str(S))
print("I:", str(I))
print("E:", str(E))
print("R:", str(R))
print("D:", str(D))
print("\n")
print("Model Parameters:")
print("beta:", str(beta))
print("delta:", str(delta))
print("gamma_r:", str(gamma_r))
print("gamma_d:", str(gamma_d))
print("mu:", str(mu))
print("epsilon:", str(epsilon))