def build_normalised_cooperation(self):
"""
Returns:
--------
The list of per turn cooperation counts.
List of the form:
[ML1, ML2, ML3..., MLn]
Where n is the number of players and MLi is a list of the form:
[pi1, pi2, pi3, ..., pin]
Where pij is the mean number of
cooperations per turn played by player i against player j in each
repetition.
"""
plist = list(range(self.nplayers))
normalised_cooperations = [[0 for opponent in plist]
for player in plist]
for player in plist:
for opponent in plist:
coop_counts = []
if (player, opponent) in self.interactions:
repetitions = self.interactions[(player, opponent)]
for interaction in repetitions:
coop_counts.append(
iu.compute_normalised_cooperation(interaction)[0])
if (opponent, player) in self.interactions:
repetitions = self.interactions[(opponent, player)]
for interaction in repetitions:
coop_counts.append(
iu.compute_normalised_cooperation(interaction)[1])
if ((player, opponent) not in self.interactions) and (
(opponent, player) not in self.interactions):
coop_counts.append(0)
# Mean over all reps:
normalised_cooperations[player][opponent] = mean(coop_counts)
return normalised_cooperations
def build_normalised_cooperation(self):
"""
Returns:
--------
The list of per turn cooperation counts.
List of the form:
[ML1, ML2, ML3..., MLn]
Where n is the number of players and MLi is a list of the form:
[pi1, pi2, pi3, ..., pin]
Where pij is the mean number of
cooperations per turn played by player i against player j in each
repetition.
"""
plist = list(range(self.nplayers))
normalised_cooperations = [[0 for opponent in plist] for player in plist]
for player in plist:
for opponent in plist:
coop_counts = []
if (player, opponent) in self.interactions:
repetitions = self.interactions[(player, opponent)]
for interaction in repetitions:
coop_counts.append(iu.compute_normalised_cooperation(interaction)[0])
if (opponent, player) in self.interactions:
repetitions = self.interactions[(opponent, player)]
for interaction in repetitions:
coop_counts.append(iu.compute_normalised_cooperation(interaction)[1])
if ((player, opponent) not in self.interactions) and ((opponent, player) not in self.interactions):
coop_counts.append(0)
# Mean over all reps:
normalised_cooperations[player][opponent] = mean(coop_counts)
return normalised_cooperations
def _update_normalised_cooperation(self, p1, p2, interaction):
"""
During a read of the data, update the normalised cooperation attribute
Parameters
----------
p1, p2 : int
The indices of the first and second player
interaction : list of tuples
A list of interactions
"""
normalised_cooperations = iu.compute_normalised_cooperation(interaction)
self.normalised_cooperation[p1][p2].append(normalised_cooperations[0])
self.normalised_cooperation[p2][p1].append(normalised_cooperations[1])
def _update_normalised_cooperation(self, p1, p2, interaction):
"""
During a read of the data, update the normalised cooperation attribute
Parameters
----------
p1, p2 : int
The indices of the first and second player
interaction : list of tuples
A list of interactions
"""
normalised_cooperations = iu.compute_normalised_cooperation(interaction)
self.normalised_cooperation[p1][p2].append(normalised_cooperations[0])
self.normalised_cooperation[p2][p1].append(normalised_cooperations[1])
def test_compute_normalised_cooperations(self):
for inter, coop in zip(self.interactions, self.normalised_cooperations):
self.assertEqual(coop, iu.compute_normalised_cooperation(inter))
def normalised_cooperation(self):
"""Returns the count of cooperations by each player per turn"""
return iu.compute_normalised_cooperation(self.result)
def test_compute_normalised_cooperations(self):
for inter, coop in zip(self.interactions, self.normalised_cooperations):
self.assertEqual(coop, iu.compute_normalised_cooperation(inter))
def normalised_cooperation(self):
"""Returns the count of cooperations by each player per turn"""
return iu.compute_normalised_cooperation(self.result)
def _update_normalised_cooperation(self, p1, p2, interaction):
normalised_cooperations = iu.compute_normalised_cooperation(
interaction)
self.normalised_cooperation[p1][p2].append(normalised_cooperations[0])
self.normalised_cooperation[p2][p1].append(normalised_cooperations[1])
