def get_random_object(self, method=None):
"""Return a random object from the string."""
if method:
objects = self.get_objects()
values = [getattr(obj, method) for obj in objects]
values = self.workspace.temperature_adjusted_values(values)
return objects[toolbox.weighted_index(values)]
return random.choice(self.get_objects())
def get_random_object(self, method=None):
"""Return a random object from the string."""
if method:
objects = self.get_objects()
values = [getattr(obj, method) for obj in objects]
values = self.workspace.temperature_adjusted_values(values)
return objects[toolbox.weighted_index(values)]
return random.choice(self.get_objects())
def run(self, coderack, slipnet, workspace):
category = self.arguments[0]
# Choose a string based on local direction category relevance.
i_string = workspace.initial_string
i_relevance = i_string.local_direction_category_relevance(category)
i_unhappiness = i_string.intra_string_unhappiness
t_string = workspace.target_string
t_relevance = t_string.local_direction_category_relevance(category)
t_unhappiness = t_string.intra_string_unhappiness
choices = [i_string, t_string]
weights = [round(toolbox.average(i_relevance, i_unhappiness)),
round(toolbox.average(t_relevance, t_unhappiness))]
string = toolbox.weighted_select(weights, choices)
obj = string.get_random_object('intra_string_salience')
if obj.spans_whole_string():
return # Fizzle
if obj.is_leftmost_in_string():
direction = slipnet.plato_right
elif obj.is_rightmost_in_string():
direction = slipnet.plato_left
else:
choices = [slipnet.plato_left, slipnet.plato_right]
activations = [slipnet.plato_left.activation,
slipnet.plato_right.activation]
direction = toolbox.weighted_select(activations, choices)
number = toolbox.weighted_index(string.bonds_to_scan_distribution)
if direction == slipnet.plato_left:
bond = obj.left_bond
else:
bond = obj.right_bond
if not bond or bond.direction_category != category:
return # Fizzle
bond_category = bond.bond_category
facet = bond.bond_facet
opposite_bond_category = slipnet.get_related_node(bond_category,
slipnet.plato_opposite)
opposite_category = slipnet.get_related_node(category,
slipnet.plato_opposite)
objects = [bond.left_object, bond.right_object]
bonds = [bond]
next_bond = bond
for i in range(2, number):
bond_to_add = None
if direction == slipnet.plato_left:
next_bond = next_bond.choose_left_neighbor()
if not next_bond:
break
else:
next_object = next_bond.left_object
else:
next_bond = next_bond.choose_right_neighbor()
if not next_bond:
break
else:
next_object = next_bond.right_object
if not next_bond:
bond_to_add = None
elif (next_bond.bond_category == bond_category) and \
(next_bond.direction_category == category) and \
(next_bond.bond_facet == facet):
bond_to_add = next_bond
elif (next_bond.bond_category == opposite_bond_category) and \
(next_bond.direction_category == opposite_category) and \
(next_bond.bond_facet == facet):
bond_to_add = next_bond.flipped_version()
if bond_to_add:
objects.append(next_object)
bonds.append(bond_to_add)
else:
break
group_category = slipnet.get_related_node(bond_category,
slipnet.plato_group_category)
return workspace.propose_group(objects, bonds, group_category, category)
def run(self, coderack, slipnet, workspace):
category = self.arguments[0]
bond_category = slipnet.get_related_node(category,
slipnet.plato_bond_category)
i_string = workspace.initial_string
i_relevance = i_string.local_bond_category_relevance(bond_category)
i_unhappiness = i_string.intra_string_unhappiness
t_string = workspace.target_string
t_relevance = t_string.local_bond_category_relevance(bond_category)
t_unhappiness = t_string.intra_string_unhappiness
weights = [round(toolbox.average(i_relevance, i_unhappiness)),
round(toolbox.average(t_relevance, t_unhappiness))]
choices = [i_string, t_string]
string = toolbox.weighted_select(weights, choices)
obj = string.get_random_object('intra_string_salience')
if obj.spans_whole_string():
return # Fizzle
if obj.is_leftmost_in_string():
direction = slipnet.plato_right
elif obj.is_rightmost_in_string():
direction = slipnet.plato_left
else:
activations = [slipnet.plato_left.activation, slipnet.plato_right.activation]
choices = [slipnet.plato_left, slipnet.plato_right]
direction = toolbox.weighted_select(activations, choices)
number = toolbox.weighted_index(string.bonds_to_scan_distribution)
if direction == slipnet.plato_left:
bond = obj.left_bond
else:
bond = obj.right_bond
if bond == None or bond.bond_category != bond_category:
if obj.type_name == 'group':
return # Fizzle
objects = [obj]
bonds = []
if category == slipnet.plato_sameness_group:
single_letter_group_direction = None
else:
choices = [slipnet.plato_left, slipnet.plato_right]
weights = [node.local_descriptor_support(string, slipnet.plato_group) \
for node in choices]
index = toolbox.weighted_index(weights)
single_letter_group_direction = choices[index]
single_letter_group = Group(workspace, string, category,
single_letter_group_direction,
obj, obj, objects, bonds)
probability = single_letter_group.single_letter_group_probability()
if toolbox.flip_coin(probability):
return workspace.propose_group(objects, bonds, category,
single_letter_group_direction)
return # Fizzle
direction_category = bond.direction_category
facet = bond.bond_facet
opposite_bond_category = slipnet.get_related_node(bond_category,
slipnet.plato_opposite)
if direction_category:
opposite_direction_category = slipnet.get_related_node(direction_category,
slipnet.plato_opposite)
else:
opposite_direction_category = None
objects = [bond.left_object, bond.right_object]
bonds = [bond]
next_bond = bond
for i in range(2, number):
bond_to_add = None
if direction == slipnet.plato_left:
next_bond = next_bond.choose_left_neighbor()
if next_bond == None:
break
else:
next_object = next_bond.left_object
else:
next_bond = next_bond.choose_right_neighbor()
if next_bond == None:
break
else:
next_object = next_bond.right_object
if next_bond == None:
bond_to_add = None
elif all([next_bond.bond_category == bond_category,
next_bond.direction_category == direction_category,
next_bond.bond_facet == facet]):
bond_to_add = next_bond
elif all([next_bond.bond_category == opposite_bond_category,
next_bond.direction_category == opposite_direction_category,
next_bond.bond_facet == facet]):
bond_to_add = next_bond.flipped_version()
if bond_to_add:
objects.append(next_object)
bonds.append(bond_to_add)
else:
break
return workspace.propose_group(objects, bonds, category, direction_category)
def run(self, coderack, slipnet, workspace):
category = self.arguments[0]
# Choose a string based on local direction category relevance.
i_string = workspace.initial_string
i_relevance = i_string.local_direction_category_relevance(category)
i_unhappiness = i_string.intra_string_unhappiness
t_string = workspace.target_string
t_relevance = t_string.local_direction_category_relevance(category)
t_unhappiness = t_string.intra_string_unhappiness
choices = [i_string, t_string]
weights = [round(toolbox.average(i_relevance, i_unhappiness)),
round(toolbox.average(t_relevance, t_unhappiness))]
string = toolbox.weighted_select(weights, choices)
obj = string.get_random_object('intra_string_salience')
if obj.spans_whole_string():
return # Fizzle
if obj.is_leftmost_in_string():
direction = slipnet.plato_right
elif obj.is_rightmost_in_string():
direction = slipnet.plato_left
else:
choices = [slipnet.plato_left, slipnet.plato_right]
activations = [slipnet.plato_left.activation,
slipnet.plato_right.activation]
direction = toolbox.weighted_select(activations, choices)
number = toolbox.weighted_index(string.bonds_to_scan_distribution)
if direction == slipnet.plato_left:
bond = obj.left_bond
else:
bond = obj.right_bond
if not bond or bond.direction_category != category:
return # Fizzle
bond_category = bond.bond_category
facet = bond.bond_facet
opposite_bond_category = slipnet.get_related_node(bond_category,
slipnet.plato_opposite)
opposite_category = slipnet.get_related_node(category,
slipnet.plato_opposite)
objects = [bond.left_object, bond.right_object]
bonds = [bond]
next_bond = bond
for _ in range(2, number):
bond_to_add = None
if direction == slipnet.plato_left:
next_bond = next_bond.choose_left_neighbor()
if not next_bond:
break
else:
next_object = next_bond.left_object
else:
next_bond = next_bond.choose_right_neighbor()
if not next_bond:
break
else:
next_object = next_bond.right_object
if not next_bond:
bond_to_add = None
elif (next_bond.bond_category == bond_category) and \
(next_bond.direction_category == category) and \
(next_bond.bond_facet == facet):
bond_to_add = next_bond
elif (next_bond.bond_category == opposite_bond_category) and \
(next_bond.direction_category == opposite_category) and \
(next_bond.bond_facet == facet):
bond_to_add = next_bond.flipped_version()
if bond_to_add:
objects.append(next_object)
bonds.append(bond_to_add)
else:
break
group_category = slipnet.get_related_node(bond_category,
slipnet.plato_group_category)
return workspace.propose_group(objects, bonds, group_category, category)
def run(self, coderack, slipnet, workspace):
category = self.arguments[0]
bond_category = slipnet.get_related_node(category,
slipnet.plato_bond_category)
i_string = workspace.initial_string
i_relevance = i_string.local_bond_category_relevance(bond_category)
i_unhappiness = i_string.intra_string_unhappiness
t_string = workspace.target_string
t_relevance = t_string.local_bond_category_relevance(bond_category)
t_unhappiness = t_string.intra_string_unhappiness
weights = [round(toolbox.average(i_relevance, i_unhappiness)),
round(toolbox.average(t_relevance, t_unhappiness))]
choices = [i_string, t_string]
string = toolbox.weighted_select(weights, choices)
obj = string.get_random_object('intra_string_salience')
if obj.spans_whole_string():
return # Fizzle
if obj.is_leftmost_in_string():
direction = slipnet.plato_right
elif obj.is_rightmost_in_string():
direction = slipnet.plato_left
else:
activations = [slipnet.plato_left.activation, slipnet.plato_right.activation]
choices = [slipnet.plato_left, slipnet.plato_right]
direction = toolbox.weighted_select(activations, choices)
number = toolbox.weighted_index(string.bonds_to_scan_distribution)
if direction == slipnet.plato_left:
bond = obj.left_bond
else:
bond = obj.right_bond
if bond is None or bond.bond_category != bond_category:
if obj.type_name == 'group':
return # Fizzle
objects = [obj]
bonds = []
if category == slipnet.plato_sameness_group:
single_letter_group_direction = None
else:
choices = [slipnet.plato_left, slipnet.plato_right]
weights = [node.local_descriptor_support(string, slipnet.plato_group) \
for node in choices]
index = toolbox.weighted_index(weights)
single_letter_group_direction = choices[index]
single_letter_group = Group(workspace, string, category,
single_letter_group_direction,
obj, obj, objects, bonds)
probability = single_letter_group.single_letter_group_probability()
if toolbox.flip_coin(probability):
return workspace.propose_group(objects, bonds, category,
single_letter_group_direction)
return # Fizzle
direction_category = bond.direction_category
facet = bond.bond_facet
opposite_bond_category = slipnet.get_related_node(bond_category,
slipnet.plato_opposite)
if direction_category:
opposite_direction_category = slipnet.get_related_node(direction_category,
slipnet.plato_opposite)
else:
opposite_direction_category = None
objects = [bond.left_object, bond.right_object]
bonds = [bond]
next_bond = bond
for _ in range(2, number):
bond_to_add = None
if direction == slipnet.plato_left:
next_bond = next_bond.choose_left_neighbor()
if next_bond is None:
break
else:
next_object = next_bond.left_object
else:
next_bond = next_bond.choose_right_neighbor()
if next_bond is None:
break
else:
next_object = next_bond.right_object
if next_bond is None:
bond_to_add = None
elif all([next_bond.bond_category == bond_category,
next_bond.direction_category == direction_category,
next_bond.bond_facet == facet]):
bond_to_add = next_bond
elif all([next_bond.bond_category == opposite_bond_category,
next_bond.direction_category == opposite_direction_category,
next_bond.bond_facet == facet]):
bond_to_add = next_bond.flipped_version()
if bond_to_add:
objects.append(next_object)
bonds.append(bond_to_add)
else:
break
return workspace.propose_group(objects, bonds, category, direction_category)