class Activator(pynetsym.Activator):
infected_nodes = Set(CInt)
def tick(self):
if self.infected_nodes:
super(Activator, self).tick()
else:
# no more infected nodes, we can just quit!
self.signal_termination('No more infected')
def infected(self, node):
"""
Whenever a node is infected, it notifies the Activator.
The activator keeps track of the infected nodes,
which are the only ones that receive an `activate` message.
"""
self.infected_nodes.add(node)
self.send(Recorder.name, 'node_infected', node=node)
def not_infected(self, node):
"""
Whenever a node recovers, it notifies the Activator.
"""
self.infected_nodes.remove(node)
self.send(Recorder.name, 'node_recovered', node=node)
def nodes_to_activate(self):
"""
Only the infected nodes are activated.
"""
return self.infected_nodes
class NestedContainerClass(HasTraits):
# Used in regression test for changes to nested containers
# Nested list
list_of_list = List(List)
# enthought/traits#281
dict_of_list = Dict(Str, List(Str))
# Similar to enthought/traits#281
dict_of_union_none_or_list = Dict(Str, Union(List(), None))
# Nested dict
# enthought/traits#25
list_of_dict = List(Dict)
dict_of_dict = Dict(Str, Dict)
dict_of_union_none_or_dict = Dict(Str, Union(Dict(), None))
# Nested set
list_of_set = List(Set)
dict_of_set = Dict(Str, Set)
dict_of_union_none_or_set = Dict(Str, Union(Set(), None))
class BasicConfigurator(AbstractConfigurator):
"""
A BasicConfigurator needs a network_size parameter
that specifies the size of the initial network.
network_size nodes of type node_type (specified in the body
of the configurator) are created and are passed the arguments
from additional_arguments specified in node_options.
"""
options = {"starting_network_size"}
starting_network_size = Int(1000)
node_type = Type
node_options = Set(Str)
def create_edges(self):
pass
def create_nodes(self):
self.node_arguments = extract_sub_dictionary(self.full_parameters,
self.node_options)
node_ids = SequenceAsyncResult([
self.send(NodeManager.name,
'create_node',
cls=self.node_type,
parameters=self.node_arguments)
for _r in xrange(self.starting_network_size)
])
self.node_identifiers = node_ids.get()
class A(HasTraits):
alist = List(Int, list(range(5)))
adict = Dict(Str, Int, dict(a=1, b=2))
aset = Set(Int, set(range(5)))
events = List()
@on_trait_change("alist_items,adict_items,aset_items")
def _receive_events(self, object, name, old, new):
self.events.append((name, new))
class Activator(pynetsym.Activator):
infected_nodes = Set(Int)
def tick(self):
if self.infected_nodes:
super(Activator, self).tick()
else:
self.signal_termination('No more infected')
def infected(self, node):
self.infected_nodes.add(node)
self.send(Recorder.name, 'node_infected', node=node)
def not_infected(self, node):
self.infected_nodes.remove(node)
self.send(Recorder.name, 'node_recovered', node=node)
def nodes_to_activate(self):
return self.infected_nodes
class ClassWithSet(HasTraits):
values = Set()