##################################
################# define the group and start it
finder = "resender.mpt.F2FPubSub"; # Jva (ROS) node that does this job
modem = "nengoros.comm.nodeFactory.modem.impl.DefaultModem"; # custom modem here
# create group with a name
g = NodeGroup("MinMaxFinder", True); # create independent group called..
g.addNC(finder, "Finder", "java"); # start java node and name it finder
g.addNC(modem,"Modem","modem") # add modem to the group
g.startGroup()
##################################
################# setup the smart neuron and add it to the Nengo network
modem = g.getModem()
neuron = NeuralModule('MinMaxFinder', modem) # construct the smart neuron
neuron.createEncoder("ann2rosFloatArr", "float",4) # termination = input of neuron (4xfloat)
neuron.createDecoder("ros2annFloatArr", "float",2) # origin = output of neuron (min and max)
many=net.add(neuron) # add it into the network
#Create a white noise input function with params: baseFreq, maxFreq [rad/s], RMS, seed
input=FunctionInput('Randomized input', [FourierFunction(.1, 10,1, 12),
FourierFunction(.4, 20,1.5, 11),
FourierFunction(.1, 10,0.9, 10),
FourierFunction(.5, 11,1.6, 17)],Units.UNK)
net.add(input) # Add to the network and connect to neuron
net.connect(input,neuron.getTermination('ann2rosFloatArr'))
##################################
################# define the group and start it
turtlesim = "../testnodes/turtlesim/turtlesim_node" # turtle under this project
act = "resender.turtle.Controller";
modemCls = "nengoros.comm.nodeFactory.modem.impl.DefaultModem"; # custom modem here
##################################
################# turtle 1
g = NodeGroup("zelvicka", True);
g.addNC(turtlesim, "zelva", "native"); # start native node called zelva
g.addNC(modemCls,"turtlemodem","modem")
g.startGroup()
modem = g.getModem()
bigneuron = NeuralModule('TurtleController',modem)
bigneuron.createDecoder("turtle1/pose", "pose") # origin
bigneuron.createDecoder("turtle1/color_sensor", "color") # origin
bigneuron.createEncoder("turtle1/command_velocity", "velocity") # termination
many=net.add(bigneuron)
#Create a white noise input function with parameters: baseFreq, maxFreq (rad/s), RMS, Seed
input=FunctionInput('Randomized input', [FourierFunction(.5, 10, 6, 12),
FourierFunction(2, 11, 5, 17)],
Units.UNK)
# Add the input node to the network and connect it to the smart enuron
net.add(input)
net.connect(input,many.getTermination('turtle1/command_velocity'))
# make neural network and connect it to the smart neuron
A=net.make('PositionData',neurons=10,dimensions=5,radius=20)
net.connect(many.getOrigin('turtle1/pose'),A)
# make neural network and connect it to the smart neuron
#RosUtils.prefferJroscore(True) # preffer jroscore before the roscore?
##################################
################# define the group and start it
finder = "resender.mpt.F2IPubSub"; # Jva (ROS) node that does this job
modem = "nengoros.comm.nodeFactory.modem.impl.DefaultModem";
g = NodeGroup("MinMaxFinder", True);
g.addNC(finder, "Finder", "java");
g.addNC(modem,"Modem","modem")
g.startGroup()
##################################
################# setup the smart neuron and add it to the Nengo network
modem = g.getModem()
neuron = NeuralModule('MinMaxFinder', modem)
neuron.createEncoder("ann2rosFloatArr", "float",4)
neuron.createDecoder("ros2annFloatArr", "int",2,False) # HERE: decorer is asynchronous
many=net.add(neuron)
#Create a white noise input function with params: baseFreq, maxFreq [rad/s], RMS, seed
input=FunctionInput('Randomized input', [FourierFunction(.1, 10,1, 12),
FourierFunction(.4, 20,1.5, 11),
FourierFunction(.1, 10,0.9, 10),
FourierFunction(.5, 11,1.6, 17)],Units.UNK)
net.add(input) # Add to the network and connect to neuron
net.connect(input,neuron.getTermination('ann2rosFloatArr'))
