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package neurgo
import (
"encoding/json"
"fmt"
"github.com/couchbaselabs/go.assert"
"log"
"testing"
"time"
)
func identityActivationFunction() ActivationFunction {
return func(x float64) float64 { return x }
}
func encodableIdentityActivationFunction() *EncodableActivation {
return &EncodableActivation{
Name: "identityActivation",
ActivationFunction: identityActivationFunction(),
}
}
func TestNeuronJsonMarshal(t *testing.T) {
neuronNodeId := NewNeuronId("neuron", 0.25)
neuron := &Neuron{
ActivationFunction: EncodableSigmoid(),
NodeId: neuronNodeId,
Bias: -30,
}
json, err := json.Marshal(neuron)
if err != nil {
log.Fatal(err)
}
assert.True(t, err == nil)
jsonString := fmt.Sprintf("%s", json)
log.Printf("jsonString: %v", jsonString)
}
func TestRecurrentNeuron(t *testing.T) {
// injector -> n1 -> n2 -> wiretap where n2 has recurrent connection
// back to n1. send a two passes of inputs, and make sure the
// wiretap gets a signal
activation := encodableIdentityActivationFunction()
injectorNodeId_1 := &NodeId{
UUID: "injector-1",
NodeType: SENSOR,
LayerIndex: 0.0,
}
neuron1NodeId := &NodeId{
UUID: "neuron1",
NodeType: NEURON,
LayerIndex: 0.125,
}
neuron2NodeId := &NodeId{
UUID: "neuron2",
NodeType: NEURON,
LayerIndex: 0.25,
}
inboundConnectionToN2 := &InboundConnection{
NodeId: neuron1NodeId,
Weights: []float64{1},
}
inboundN2 := []*InboundConnection{inboundConnectionToN2}
closingN2 := make(chan chan bool)
dataN2 := make(chan *DataMessage, 1)
inboundConnectionToN1 := &InboundConnection{
NodeId: injectorNodeId_1,
Weights: []float64{1, 1, 1, 1, 1},
}
recurrentInboundConnectionToN1 := &InboundConnection{
NodeId: neuron2NodeId,
Weights: []float64{1},
}
outboundConnectionToN2 := &OutboundConnection{
NodeId: neuron2NodeId,
DataChan: dataN2,
}
outbound := []*OutboundConnection{
outboundConnectionToN2,
}
inboundN1 := []*InboundConnection{
inboundConnectionToN1,
recurrentInboundConnectionToN1,
}
closingN1 := make(chan chan bool)
dataN1 := make(chan *DataMessage, 1)
neuronN1 := &Neuron{
ActivationFunction: activation,
NodeId: neuron1NodeId,
Bias: 20,
Inbound: inboundN1,
Outbound: outbound,
Closing: closingN1,
DataChan: dataN1,
}
wiretapNodeId := &NodeId{
UUID: "wireteap-node",
NodeType: ACTUATOR,
LayerIndex: 0.5,
}
wiretapDataChan := make(chan *DataMessage, 1)
wiretapConnection := &OutboundConnection{
NodeId: wiretapNodeId,
DataChan: wiretapDataChan,
}
n2ToN1Connection := &OutboundConnection{
NodeId: neuron1NodeId,
DataChan: dataN1,
}
outboundN2 := []*OutboundConnection{
wiretapConnection,
n2ToN1Connection,
}
neuronN2 := &Neuron{
ActivationFunction: activation,
NodeId: neuron2NodeId,
Bias: 20,
Inbound: inboundN2,
Outbound: outboundN2,
Closing: closingN2,
DataChan: dataN2,
}
recurrentConnections := neuronN2.RecurrentOutboundConnections()
assert.Equals(t, len(recurrentConnections), 1)
neuronN1.Init()
neuronN2.Init()
go neuronN1.Run()
go neuronN2.Run()
// send one input
inputs_1 := []float64{20, 20, 20, 20, 20}
dataMessage := &DataMessage{
SenderId: injectorNodeId_1,
Inputs: inputs_1,
}
neuronN1.DataChan <- dataMessage
// wait for output
log.Printf("wiretapDataChan: %v", wiretapDataChan)
select {
case outputDataMessage := <-wiretapDataChan:
outputVector := outputDataMessage.Inputs
log.Printf("outputVector: %v", outputVector)
outputValue := outputVector[0]
expectedOut := 100 + 20 + 20 // inputs plus two biases
assert.Equals(t, int(outputValue), expectedOut)
case <-time.After(time.Second):
assert.Errorf(t, "Did not get result at wiretap")
}
// send another input
inputs_2 := []float64{20, 20, 20, 20, 20}
dataMessage2 := &DataMessage{
SenderId: injectorNodeId_1,
Inputs: inputs_2,
}
neuronN1.DataChan <- dataMessage2
// wait for output
select {
case outputDataMessage2 := <-wiretapDataChan:
outputVector2 := outputDataMessage2.Inputs
log.Printf("outputVector #2: %v", outputVector2)
outputValue2 := outputVector2[0]
expectedOut2 := (100 + 20 + 20) * 2
assert.Equals(t, int(outputValue2), expectedOut2)
case <-time.After(time.Second):
assert.Errorf(t, "Did not get result #2 at wiretap")
}
neuronN1.Shutdown()
neuronN2.Shutdown()
}
func TestRunningNeuron(t *testing.T) {
log.Printf("")
activation := encodableIdentityActivationFunction()
neuronNodeId := &NodeId{
UUID: "neuron",
NodeType: NEURON,
LayerIndex: 0.25,
}
nodeId_1 := &NodeId{UUID: "node-1", NodeType: SENSOR, LayerIndex: 0.0}
nodeId_2 := &NodeId{UUID: "node-2", NodeType: SENSOR, LayerIndex: 0.0}
nodeId_3 := &NodeId{UUID: "node-3", NodeType: SENSOR, LayerIndex: 0.0}
weights_1 := []float64{1, 1, 1, 1, 1}
weights_2 := []float64{1}
weights_3 := []float64{1}
inboundConnection1 := &InboundConnection{
NodeId: nodeId_1,
Weights: weights_1,
}
inboundConnection2 := &InboundConnection{
NodeId: nodeId_2,
Weights: weights_2,
}
inboundConnection3 := &InboundConnection{
NodeId: nodeId_3,
Weights: weights_3,
}
inbound := []*InboundConnection{
inboundConnection1,
inboundConnection2,
inboundConnection3,
}
closing := make(chan chan bool)
data := make(chan *DataMessage, len(inbound))
wiretapNodeId := &NodeId{
UUID: "wireteap-node",
NodeType: ACTUATOR,
LayerIndex: 0.5,
}
wiretapDataChan := make(chan *DataMessage, 1)
wiretapConnection := &OutboundConnection{
NodeId: wiretapNodeId,
DataChan: wiretapDataChan,
}
outbound := []*OutboundConnection{
wiretapConnection,
}
neuron := &Neuron{
ActivationFunction: activation,
NodeId: neuronNodeId,
Bias: 20,
Inbound: inbound,
Outbound: outbound,
Closing: closing,
DataChan: data,
}
neuron.Init()
go neuron.Run()
// send one input
inputs_1 := []float64{20, 20, 20, 20, 20}
dataMessage := &DataMessage{
SenderId: nodeId_1,
Inputs: inputs_1,
}
data <- dataMessage
// wait for output - should timeout
select {
case output := <-wiretapDataChan:
assert.Errorf(t, "Got unexpected output: %v", output)
case <-time.After(time.Second / 100):
}
// send rest of inputs
inputs_2 := []float64{20}
dataMessage2 := &DataMessage{
SenderId: nodeId_2,
Inputs: inputs_2,
}
data <- dataMessage2
inputs_3 := []float64{20}
dataMessage3 := &DataMessage{
SenderId: nodeId_3,
Inputs: inputs_3,
}
data <- dataMessage3
// get output - should receive something
select {
case outputDataMessage := <-wiretapDataChan:
outputVector := outputDataMessage.Inputs
outputValue := outputVector[0]
assert.Equals(t, int(outputValue), int(160))
case <-time.After(time.Second):
assert.Errorf(t, "Timed out waiting for output")
}
neuron.Shutdown()
}
func TestComputeScalarOutput(t *testing.T) {
activation := encodableIdentityActivationFunction()
weights_1 := []float64{1, 1, 1, 1, 1}
weights_2 := []float64{1}
weights_3 := []float64{1}
neuron := &Neuron{
ActivationFunction: activation,
Bias: 0,
NodeId: NewNeuronId("neuron", 0.0),
}
inputs_1 := []float64{20, 20, 20, 20, 20}
inputs_2 := []float64{10}
inputs_3 := []float64{10}
weightedInput1 := &weightedInput{weights: weights_1, inputs: inputs_1}
weightedInput2 := &weightedInput{weights: weights_2, inputs: inputs_2}
weightedInput3 := &weightedInput{weights: weights_3, inputs: inputs_3}
weightedInputs := []*weightedInput{
weightedInput1,
weightedInput2,
weightedInput3,
}
result := neuron.computeScalarOutput(weightedInputs)
assert.Equals(t, result, float64(120))
}
func TestNeuronShutdown(t *testing.T) {
sensor := &Sensor{
NodeId: NewSensorId("sensor", 0.0),
VectorLength: 2,
}
sensor.Init()
neuron := &Neuron{
ActivationFunction: EncodableSigmoid(),
NodeId: NewNeuronId("neuron", 0.35),
Bias: -10,
}
neuron.Init()
sensor.ConnectOutbound(neuron)
neuron.ConnectInboundWeighted(sensor, []float64{20, 20})
go sensor.Run()
go neuron.Run()
sensor.Shutdown()
neuron.Shutdown()
outboundConnection := sensor.Outbound[0]
assert.True(t, outboundConnection.DataChan == nil)
assert.True(t, neuron.wg == nil)
assert.True(t, sensor.wg == nil)
}
func TestRecurrentOutboundConnections(t *testing.T) {
// make a recurrent connection
neuron1NodeId := &NodeId{
UUID: "neuron1",
NodeType: NEURON,
LayerIndex: 0.0,
}
neuron2NodeId := &NodeId{
UUID: "neuron2",
NodeType: NEURON,
LayerIndex: 0.5,
}
outboundConnectionN2ToN1 := &OutboundConnection{
NodeId: neuron1NodeId,
DataChan: make(chan *DataMessage, 1),
}
outboundN2 := []*OutboundConnection{
outboundConnectionN2ToN1,
}
neuronN2 := &Neuron{
ActivationFunction: nil,
NodeId: neuron2NodeId,
Bias: 20,
Inbound: nil,
Outbound: outboundN2,
Closing: nil,
DataChan: nil,
}
recurrentConnections := neuronN2.RecurrentOutboundConnections()
assert.Equals(t, len(recurrentConnections), 1)
}