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quaquelquaquel
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Moving examples to use the new discrete spaces (#198)
1 parent d63ce06 commit 9a05b05

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36 files changed

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‎examples/aco_tsp/aco_tsp/model.py

Lines changed: 27 additions & 19 deletions
Original file line numberDiff line numberDiff line change
@@ -3,6 +3,7 @@
33
import mesa
44
import networkx as nx
55
import numpy as np
6+
from mesa.experimental.cell_space import CellAgent, Network
67

78

89
@dataclass
@@ -77,7 +78,7 @@ def from_tsp_file(cls, file_path: str) -> "TSPGraph":
7778
return cls(g)
7879

7980

80-
class AntTSP(mesa.Agent):
81+
class AntTSP(CellAgent):
8182
"""
8283
An agent
8384
"""
@@ -93,6 +94,7 @@ def __init__(self, model, alpha: float = 1.0, beta: float = 5.0):
9394
self._traveled_distance = 0
9495
self.tsp_solution = []
9596
self.tsp_distance = 0
97+
self.graph = self.model.grid.G
9698

9799
def calculate_pheromone_delta(self, q: float = 100):
98100
results = {}
@@ -102,31 +104,39 @@ def calculate_pheromone_delta(self, q: float = 100):
102104

103105
return results
104106

107+
def move_to(self, cell) -> None:
108+
self._cities_visited.append(cell)
109+
if self.cell:
110+
self._traveled_distance += self.graph[self.cell.coordinate][
111+
cell.coordinate
112+
]["distance"]
113+
super().move_to(cell)
114+
105115
def decide_next_city(self):
106116
# Random
107117
# new_city = self.random.choice(list(self.model.all_cities - set(self.cities_visited)))
108118
# Choose closest city not yet visited
109-
g = self.model.grid.G
110-
current_city = self.pos
111-
neighbors = list(g.neighbors(current_city))
119+
neighbors = self.cell.neighborhood
112120
candidates = [n for n in neighbors if n not in self._cities_visited]
113121
if len(candidates) == 0:
114-
return current_city
122+
return self.cell
115123

116124
# p_ij(t) = 1/Z*[(tau_ij)**alpha * (1/distance)**beta]
117125
results = []
118126
for city in candidates:
119127
val = (
120-
(g[current_city][city]["pheromone"]) ** self.alpha
121-
* (g[current_city][city]["visibility"]) ** self.beta
128+
(self.graph[self.cell.coordinate][city.coordinate]["pheromone"])
129+
** self.alpha
130+
* (self.graph[self.cell.coordinate][city.coordinate]["visibility"])
131+
** self.beta
122132
)
123133
results.append(val)
124134

125135
results = np.array(results)
126136
norm = results.sum()
127137
results /= norm
128138

129-
new_city = self.model.random.choices(candidates, weights=results)[0]
139+
new_city = self.random.choices(candidates, weights=results)[0]
130140

131141
return new_city
132142

@@ -135,16 +145,13 @@ def step(self):
135145
Modify this method to change what an individual agent will do during each step.
136146
Can include logic based on neighbors states.
137147
"""
138-
g = self.model.grid.G
139-
for idx in range(self.model.num_cities - 1):
148+
149+
for _ in range(self.model.num_cities - 1):
140150
# Pick a random city that isn't in the list of cities visited
141-
current_city = self.pos
142151
new_city = self.decide_next_city()
143-
self._cities_visited.append(new_city)
144-
self.model.grid.move_agent(self, new_city)
145-
self._traveled_distance += g[current_city][new_city]["distance"]
152+
self.move_to(new_city)
146153

147-
self.tsp_solution = self._cities_visited.copy()
154+
self.tsp_solution = [entry.coordinate for entry in self._cities_visited]
148155
self.tsp_distance = self._traveled_distance
149156
self._cities_visited = []
150157
self._traveled_distance = 0
@@ -173,14 +180,15 @@ def __init__(
173180
self.num_cities = tsp_graph.num_cities
174181
self.all_cities = set(range(self.num_cities))
175182
self.max_steps = max_steps
176-
self.grid = mesa.space.NetworkGrid(tsp_graph.g)
183+
self.grid = Network(tsp_graph.g, random=self.random)
177184

178185
for _ in range(self.num_agents):
179186
agent = AntTSP(model=self, alpha=ant_alpha, beta=ant_beta)
180187

181-
city = tsp_graph.cities[self.random.randrange(self.num_cities)]
182-
self.grid.place_agent(agent, city)
183-
agent._cities_visited.append(city)
188+
city = self.grid.all_cells.select_random_cell()
189+
agent.move_to(city)
190+
# self.grid.place_agent(agent, city)
191+
# agent._cities_visited.append(city) # FIXME should be endogenous to agent
184192

185193
self.num_steps = 0
186194
self.best_path = None

‎examples/bank_reserves/BankReservesModel_Data.csv

Lines changed: 251 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,251 @@
1+
,RunId,iteration,Step,init_people,rich_threshold,reserve_percent,Rich,Poor,Middle Class,Savings,Wallets,Money,Loans,AgentID,Wealth
2+
0,0,0,1000,25,5,5,11,5,7,251,0,251,173,1,2
3+
1,0,0,1000,25,5,5,11,5,7,251,0,251,173,2,44
4+
2,0,0,1000,25,5,5,11,5,7,251,0,251,173,3,-22
5+
3,0,0,1000,25,5,5,11,5,7,251,0,251,173,4,-10
6+
4,0,0,1000,25,5,5,11,5,7,251,0,251,173,5,8
7+
5,0,0,1000,25,5,5,11,5,7,251,0,251,173,6,17
8+
6,0,0,1000,25,5,5,11,5,7,251,0,251,173,7,5
9+
7,0,0,1000,25,5,5,11,5,7,251,0,251,173,8,1
10+
8,0,0,1000,25,5,5,11,5,7,251,0,251,173,9,2
11+
9,0,0,1000,25,5,5,11,5,7,251,0,251,173,10,51
12+
10,0,0,1000,25,5,5,11,5,7,251,0,251,173,11,14
13+
11,0,0,1000,25,5,5,11,5,7,251,0,251,173,12,-22
14+
12,0,0,1000,25,5,5,11,5,7,251,0,251,173,13,10
15+
13,0,0,1000,25,5,5,11,5,7,251,0,251,173,14,57
16+
14,0,0,1000,25,5,5,11,5,7,251,0,251,173,15,7
17+
15,0,0,1000,25,5,5,11,5,7,251,0,251,173,16,3
18+
16,0,0,1000,25,5,5,11,5,7,251,0,251,173,17,12
19+
17,0,0,1000,25,5,5,11,5,7,251,0,251,173,18,-64
20+
18,0,0,1000,25,5,5,11,5,7,251,0,251,173,19,-2
21+
19,0,0,1000,25,5,5,11,5,7,251,0,251,173,20,9
22+
20,0,0,1000,25,5,5,11,5,7,251,0,251,173,21,7
23+
21,0,0,1000,25,5,5,11,5,7,251,0,251,173,22,-1
24+
22,0,0,1000,25,5,5,11,5,7,251,0,251,173,23,-23
25+
23,0,0,1000,25,5,5,11,5,7,251,0,251,173,24,2
26+
24,0,0,1000,25,5,5,11,5,7,251,0,251,173,25,-29
27+
25,1,0,1000,25,10,5,12,8,3,422,5,427,251,1,38
28+
26,1,0,1000,25,10,5,12,8,3,422,5,427,251,2,30
29+
27,1,0,1000,25,10,5,12,8,3,422,5,427,251,3,-21
30+
28,1,0,1000,25,10,5,12,8,3,422,5,427,251,4,65
31+
29,1,0,1000,25,10,5,12,8,3,422,5,427,251,5,40
32+
30,1,0,1000,25,10,5,12,8,3,422,5,427,251,6,10
33+
31,1,0,1000,25,10,5,12,8,3,422,5,427,251,7,-12
34+
32,1,0,1000,25,10,5,12,8,3,422,5,427,251,8,8
35+
33,1,0,1000,25,10,5,12,8,3,422,5,427,251,9,30
36+
34,1,0,1000,25,10,5,12,8,3,422,5,427,251,10,20
37+
35,1,0,1000,25,10,5,12,8,3,422,5,427,251,11,-5
38+
36,1,0,1000,25,10,5,12,8,3,422,5,427,251,12,-38
39+
37,1,0,1000,25,10,5,12,8,3,422,5,427,251,13,-12
40+
38,1,0,1000,25,10,5,12,8,3,422,5,427,251,14,27
41+
39,1,0,1000,25,10,5,12,8,3,422,5,427,251,15,-29
42+
40,1,0,1000,25,10,5,12,8,3,422,5,427,251,16,6
43+
41,1,0,1000,25,10,5,12,8,3,422,5,427,251,17,-37
44+
42,1,0,1000,25,10,5,12,8,3,422,5,427,251,18,27
45+
43,1,0,1000,25,10,5,12,8,3,422,5,427,251,19,-38
46+
44,1,0,1000,25,10,5,12,8,3,422,5,427,251,20,-10
47+
45,1,0,1000,25,10,5,12,8,3,422,5,427,251,21,-49
48+
46,1,0,1000,25,10,5,12,8,3,422,5,427,251,22,37
49+
47,1,0,1000,25,10,5,12,8,3,422,5,427,251,23,35
50+
48,1,0,1000,25,10,5,12,8,3,422,5,427,251,24,37
51+
49,1,0,1000,25,10,5,12,8,3,422,5,427,251,25,12
52+
50,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,1,-81
53+
51,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,2,27
54+
52,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,3,-56
55+
53,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,4,53
56+
54,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,5,86
57+
55,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,6,77
58+
56,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,7,20
59+
57,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,8,-28
60+
58,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,9,51
61+
59,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,10,-72
62+
60,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,11,-96
63+
61,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,12,81
64+
62,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,13,-43
65+
63,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,14,66
66+
64,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,15,70
67+
65,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,16,7
68+
66,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,17,32
69+
67,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,18,21
70+
68,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,19,64
71+
69,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,20,-54
72+
70,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,21,11
73+
71,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,22,-30
74+
72,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,23,-21
75+
73,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,24,24
76+
74,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,25,-4
77+
75,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,26,-12
78+
76,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,27,-67
79+
77,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,28,53
80+
78,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,29,79
81+
79,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,30,-9
82+
80,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,31,-6
83+
81,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,32,-2
84+
82,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,33,45
85+
83,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,34,85
86+
84,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,35,23
87+
85,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,36,-32
88+
86,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,37,-36
89+
87,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,38,-75
90+
88,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,39,-67
91+
89,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,40,-44
92+
90,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,41,-13
93+
91,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,42,-53
94+
92,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,43,105
95+
93,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,44,20
96+
94,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,45,-77
97+
95,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,46,36
98+
96,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,47,-35
99+
97,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,48,-87
100+
98,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,49,-70
101+
99,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,50,98
102+
100,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,51,109
103+
101,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,52,-93
104+
102,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,53,-18
105+
103,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,54,72
106+
104,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,55,38
107+
105,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,56,-33
108+
106,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,57,43
109+
107,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,58,87
110+
108,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,59,-2
111+
109,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,60,29
112+
110,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,61,123
113+
111,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,62,-22
114+
112,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,63,47
115+
113,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,64,108
116+
114,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,65,-53
117+
115,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,66,-3
118+
116,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,67,-58
119+
117,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,68,-16
120+
118,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,69,-28
121+
119,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,70,41
122+
120,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,71,-60
123+
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124+
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125+
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126+
124,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,75,37
127+
125,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,76,-108
128+
126,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,77,-69
129+
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130+
128,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,79,-11
131+
129,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,80,-18
132+
130,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,81,16
133+
131,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,82,-32
134+
132,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,83,12
135+
133,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,84,8
136+
134,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,85,25
137+
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138+
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139+
137,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,88,-15
140+
138,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,89,33
141+
139,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,90,12
142+
140,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,91,43
143+
141,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,92,2
144+
142,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,93,-139
145+
143,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,94,25
146+
144,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,95,101
147+
145,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,96,78
148+
146,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,97,44
149+
147,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,98,3
150+
148,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,99,-44
151+
149,2,0,1000,100,5,5,50,42,8,2563,7,2570,2219,100,-59
152+
150,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,1,-22
153+
151,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,2,27
154+
152,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,3,60
155+
153,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,4,89
156+
154,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,5,11
157+
155,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,6,12
158+
156,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,7,-47
159+
157,3,0,1000,100,10,5,49,42,9,2598,33,2631,2046,8,60
160+
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