def sensitivity_analysis(force=False):
data_file = os.path.join(DATA_FOLDER, 'sensitivity_analysis.p')
if os.path.exists(data_file) and not force:
data = backup.load(data_file)
return data
n_good_cond = 3, 4
data = {g: {} for g in n_good_cond}
for n_good in n_good_cond:
d = simulation.run.get_data(n_good=n_good)
alpha = [i[0] for i in d.cognitive_parameters]
beta = [i[1] for i in d.cognitive_parameters]
gamma = [i[2] for i in d.cognitive_parameters]
observation = analysis.metric.metric.get_economy_measure(
in_hand=d.in_hand,
desired=d.desired,
prod=d.prod,
cons=d.cons,
m=0)
data[n_good][r'$\alpha$'] = alpha
data[n_good][r'$\beta$'] = beta
data[n_good][r'$\gamma$'] = gamma
data[n_good]['ind0'] = observation
backup.save(data, data_file)
return data
def get_data(force=False):
if force or not os.path.exists(DATA_FILE):
data = _load__data_from_db()
backup.save(obj=data, file_name=DATA_FILE)
else:
data = backup.load(DATA_FILE)
return data
def load_if_not_existing(file_name, method, **kwargs):
folder = os.path.join("data", "pickle")
os.makedirs(folder, exist_ok=True)
file_path = os.path.join(folder, file_name)
if os.path.exists(file_path):
data = load(file_path)
else:
data = method(**kwargs)
save(obj=data, file_name=file_path)
return data
def get(xp_data_list=None, room_n_good=None, room_uniform=None, extension=''):
if xp_data_list is None:
xp_data_list, room_n_good, room_uniform = xp.get_data()
file_path = f'{DATA_FOLDER}/fit{extension}.p'
if not os.path.exists(file_path):
alpha, beta, gamma, mean_p, lls, bic, eco = \
produce_fit(xp_data_list, room_n_good, room_uniform)
backup.save(obj=(alpha, beta, gamma, mean_p, lls, bic, eco),
file_name=file_path)
else:
alpha, beta, gamma, mean_p, lls, bic, eco = \
backup.load(file_name=file_path)
return alpha, beta, gamma, mean_p, lls, bic, eco
def phase_diagram(m=0):
data_file = f'{DATA_FOLDER}/formatted_phase_diagram.p'
if os.path.exists(data_file):
data, labels = backup.load(data_file)
return data, labels
data = {}
for n_good in (4, 3):
d = simulation.run.get_data(n_good=n_good)
dist = d.distribution
n = len(dist) # Number of economies in this batch
observation = metric.get_economy_measure(in_hand=d.in_hand,
desired=d.desired,
prod=d.prod,
cons=d.cons,
m=m)
unq_repartition = np.unique(dist, axis=0)
labels = np.unique([i[-1] for i in unq_repartition])
n_side = len(labels)
scores = np.array([
np.mean([observation[i] for i in range(n) if np.all(dist[i] == r)])
for r in unq_repartition
])
d = scores.reshape(n_side, n_side).T
data[n_good] = d
backup.save((data, labels), data_file)
return data, labels
def phase_diagram(f_name='phase.pdf'):
"""
plot phase diagrams
with 3 and 4 goods
"""
# Number of column
# (Plot for each good considered as money if max_col == None)
max_col = 1
data_file = f'{DATA_FOLDER}/formatted_phase_diagram.p'
if os.path.exists(data_file):
data, labels = backup.load(data_file)
else:
data = []
for n_good in 3, 4:
d = simulation.run.get_data(phase=True, n_good=n_good)
formatted_data, labels = metric.phase_diagram(
in_hand=d.in_hand,
desired=d.desired,
prod=d.prod,
cons=d.cons,
distribution=d.distribution,
n_good=len(d.distribution[0]))
data.append(formatted_data)
backup.save((data, labels), data_file)
graph.phase_diagram.plot(data=data,
labels=labels,
f_name=f_name,
max_col=max_col)
def run(file_name='data/exp.p'):
if os.path.exists(file_name):
return backup.load(file_name)
rooms = Room.objects.all().order_by('id')
data = {}
for r in rooms:
n_good = r.n_type
print(r.id)
monetary_behavior = np.zeros((n_good, r.n_user, r.t_max))
medium = np.ones((n_good, r.n_user, r.t_max)) * -1
ordered_goods = [
n_good - 1,
] + list(range(n_good - 1))
group_users = [
User.objects.filter(room_id=r.id,
production_good=Converter.reverse_value(
g, n_good)).order_by('id')
for g in ordered_goods
]
for m in range(n_good):
for t in range(r.t_max):
i = 0
for users in group_users:
for u in users:
choices = Choice.objects.filter(room_id=r.id,
t=t,
user_id=u.id)
for c in choices:
desired = Converter.convert_value(c.desired_good,
n_good=n_good)
in_hand = Converter.convert_value(c.good_in_hand,
n_good=n_good)
prod = Converter.convert_value(u.production_good,
n_good=n_good)
cons = Converter.convert_value(u.consumption_good,
n_good=n_good)
if m in (prod, cons):
monetary_conform = (in_hand, desired) == (prod,
cons)
medium[m, i, t] = -1
else:
monetary_conform = (in_hand,
desired) in [(prod, m),
(m, cons)]
medium[m, i, t] = monetary_conform
monetary_behavior[m, i, t] = monetary_conform
i += 1
distribution = economy.distributions.get(r.id)
label = economy.labels.get(r.id)
data[label] = {
'monetary_bhv': monetary_behavior,
'medium': medium,
'distribution': distribution
}
backup.save(data, file_name=file_name)
return data
def save(self, data_folder):
os.makedirs(data_folder, exist_ok=True)
for k, v in self._files_mapping(data_folder).items():
backup.save(obj=getattr(self, v), file_name=k)