-
Notifications
You must be signed in to change notification settings - Fork 0
/
menu1.py
155 lines (122 loc) · 6.24 KB
/
menu1.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
from processData import *
from sim3001 import *
import numpy as np
import sys
# to be called in the command line as:
# python menu.py <N> <Width> <Height>
#
# loading comand line arguments
# N - Number of particles
# Width and Height of window
#parameters_file = 'parameters'
#parameters_file = 'parameters/' + parameters_file + ".txt"
#data_file = 'data.csv'
def menu(parameters_file):
####################################### Ask for requirements ################################################
repeat = raw_input("Repeat simulation ([y]/n)?\n")
while repeat not in ['', 'y', 'n']:
repeat = raw_input("Please enter valid input ([y]/n)?\n")
repeat = 'y'
if repeat == 'n':
N = input("Number of agents: N = ")
save_parameters(['N'], [N], parameters_file)
############################ Model Selection ################################
print('Models available:\n'
'Simple speed coupling............ 0\n'
'Couzin model..................... 1\n'
'Viscek model..................... 2\n'
'Couzin-2 model................... 3\n'
'Mill model....................... 4')
model = input("Please choose a model.\n")
while model not in range(5):
model = input("Please enter a valid model.\n")
save_parameters(['model'], [model], parameters_file)
############################## Use same Parameter? ####################################
rep_par = raw_input("Use saved parameters ([y]/n)?\n")
while rep_par not in ['', 'y', 'n']:
rep_par = raw_input("Please enter valid input ([y]/n)?\n")
if rep_par in ['', 'y']:
pass
else:
print('Previous parameters will be overwritten.')
if model in ['None', 0]:
s = input("Speed: s = ")
a = input("Coupling: a = ")
save_parameters(['s', 'a'], [s, a], parameters_file)
elif model == 1:
s = input("Speed: s = ")
noise = input("Noise: noise = ")
dTheta = input("Max angle of turn: dTheta = ")
rr = input("Repulsion radius: rr = ")
ro = input("Orientation radius: ro = ")
ra = input("Atraction radius: ra = ")
sight_theta = input("Field of view: sight_theta = ")
save_parameters(['s', 'noise', 'dTheta', 'rr',
'ro', 'ra', 'sight_theta'],
[s, noise, dTheta, rr, ro, ra, sight_theta],
parameters_file)
elif model == 3:
s = input("Speed: s = ")
noise = input("Noise: noise = ")
dTheta = input("Max angle of turn: dTheta = ")
rr = input("Repulsion radius: rr = ")
roa = input("Orientation/atraction radius: roa = ")
orient = input("Orientation weight: orient = ")
atract = input("Atract weight: atract = ")
save_parameters(['s', 'noise', 'dTheta', 'rr',
'roa', 'atract', 'orient'],
[s, noise, dTheta, rr, roa, atract, orient],
parameters_file)
elif model == 2:
s = input("Speed: s = ")
noise = input("Noise: noise = ")
r = input("Repulsion radius: r = ")
save_parameters(['s', 'noise', 'r'],
[s, noise, r], parameters_file)
elif model == 4:
cr = input("Repulsion coeficient: cr = ")
ca = input("Atraction coeficient: ca = ")
lr = input("Repulsion length: lr = ")
la = input("Atraction length: la = ")
alpha = input("Self propulsion: alpha = ")
beta = input("Friction coeficient: beta = ")
mass = input("Agents's mass: mass = ")
save_parameters(['cr', 'ca', 'lr', 'la', 'alpha', 'beta', 'mass'],
[cr, ca, lr, la, alpha, beta, mass], parameters_file)
######################### Bias Selection ############################
use_bias = raw_input("Use bias ([y]/n)?\n")
while use_bias not in ['', 'y', 'n']:
use_bias = raw_input("Please enter valid input ([y]/n)?\n")
if use_bias in ['', 'y']:
use_bias = 1
prop = input("Fraction of leading agents: prop = ")
weight = input("Intensity of bias: weight = ")
dev_bias = input("Jitter of bias: dev_bias = ")
n_lead = input("Number of biased groups: n_lead = ")
save_parameters(['n_lead', 'prop', 'weight', 'dev_bias'],
[n_lead, prop, weight, dev_bias], parameters_file)
for i in range(n_lead):
bias_angle = input("Bias angle for group " + str(i + 1) + ": bias_angle_" + str(i + 1) + " = ")
save_parameters(['bias_angle_' + str(i + 1)],
[bias_angle], parameters_file)
else:
use_bias = 0
save_parameters(['use_bias'],
[use_bias], parameters_file)
######################################################################
#################### Periodic Boudary Conditions ####################
use_pbc = raw_input("Use PBCs ([y]/n)?\n")
while use_pbc not in ['', 'y', 'n']:
use_pbc = raw_input("Please enter valid input ([y]/n)?\n")
if use_pbc in ['', 'y']:
use_pbc = 1
else:
use_pbc = 0
save_parameters(['use_pbc'],
[use_pbc], parameters_file)
######################################################################
else:
model = load_model('parameters.txt')
#####################################################################################################
return load_parameters(parameters_file)
########################################## Implement requirements ################################################