// LISTNET COMMAND
public void ListNets()
{
if (network == null)
{
// NO NETWORK CREATED - CREATING NEW
network = ANNetwork.NewNetwork(new int[] { 1 }, 1);
}
network.ShowFileList();
}
// LOAD NETWORK COMMAND
public string LoadNetwork(string tmpString, ref ANNetwork externalNetworkLink)
{
if (network == null)
{
// NO NETWORK CREATED - CREATING NEW
network = ANNetwork.NewNetwork(new int[] { 1 }, 1);
externalNetworkLink = network;
}
string result = network.LoadFromFile(tmpString);
if (result.Length > 0)
{
return(result);
}
return("");
}
////////// *******************************************************************************************************************************
////////// *******************************************************************************************************************************
////////// NETWORK FUNCTIONS
// CREATE NEW NETWORK
public string CreateNewANN(string tmpString, ref ANNetwork externalNetworkLink)
{
/* newANN <inputsNumber> <layersNumber> <L1NeuronNumber>...
* (<alpha> <CostFunctionIndex> {<L1ActivationFunctionIndex>...} {<L1LowerBoundary>... <L1UpperBoundary>...} <scaleBoolean>)*/
bool isLast = true;
string result = "";
// PARSING INPUTS NUMBER
if (tmpString.Length == 0)
{
return("\n-> Error creating new network: no <inputsNumber> argument entered.");
}
int inputsNumber = -1;
result = Parsing.ParseInt(ref tmpString, ref inputsNumber, ref isLast, "inputsNumber", Parsing.AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if (isLast)
{
return("\n-> Error creating new network: no <layersNumber> argument entered.");
}
// PARSING LAYER NUMBER
int layersNumber = -1;
result = Parsing.ParseInt(ref tmpString, ref layersNumber, ref isLast, "inputsNumber", Parsing.AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
// PARSING LAYER NEURONS NUMBER FOR EACH LAYER
int[] neuronNumbers = new int[layersNumber];
for (int layerInd = 0; layerInd < layersNumber; layerInd++)
{
result = Parsing.ParseInt(ref tmpString, ref neuronNumbers[layerInd], ref isLast, "<LxNeuronNumber>", Parsing.AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if ((isLast) && (layerInd < layersNumber - 1))
{
return("\n-> Error creating new network: no <LxNeuronNumber> for layer " + layerInd.ToString() + " .");
}
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber);
externalNetworkLink = network;
return("");
}
// PARSING TRAINING SPEED IF ABLE
float learningSpeed = -1;
result = Parsing.ParseFloat(ref tmpString, ref learningSpeed, ref isLast, "trainingSpeed", Parsing.AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed);
externalNetworkLink = network;
return("");
}
// PARSING ALPHA IF ABLE
float alpha = -1;
result = Parsing.ParseFloat(ref tmpString, ref alpha, ref isLast, "alpha", Parsing.AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha);
externalNetworkLink = network;
return("");
}
// PARSING LYAMBDA IF ABLE
float lyambda = -1;
result = Parsing.ParseFloat(ref tmpString, ref lyambda, ref isLast, "lyambda", Parsing.AfterParsingCheck.NonNegative);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha, lyambda);
externalNetworkLink = network;
return("");
}
// PARSING COST FUNCTION
CFTypeBase CFType = null;
result = Parsing.ParseCFType(ref tmpString, ref CFType, ref isLast);
if (result.Length > 0)
{
return(result);
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha, lyambda, CFType);
externalNetworkLink = network;
return("");
}
// PARSING ACTIVATION FUNCTIONS FOR ALL LAYERS
AFTypeBase[] AFTypes = new AFTypeBase[layersNumber];
result = Parsing.ParseAFTypesArray(ref tmpString, ref AFTypes, ref isLast);
if (result.Length > 0)
{
return(result);
}
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha, lyambda, CFType, AFTypes);
externalNetworkLink = network;
return("");
}
// PARSING INIT SCALE
bool initScale;
int initScaleInt = -1;
result = Parsing.ParseInt(ref tmpString, ref initScaleInt, ref isLast, "scaleBoolean", Parsing.AfterParsingCheck.NonNegative);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if ((initScaleInt != 0) && (initScaleInt != 1))
{
return("\n-> Error creating new network: non-boolean initScale " + initScaleInt.ToString() + " .");
}
initScale = initScaleInt == 0 ? false : true;
if (isLast)
{
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha, lyambda, CFType, AFTypes, initScale);
externalNetworkLink = network;
return("");
}
// PARSING LOWER BOUNDARY AND UPPER BOUNDARY
float[] lowerBoundaries = new float[layersNumber];
result = Parsing.ParseFloatArray(ref tmpString, ref lowerBoundaries, ref isLast, "lower boundaries", Parsing.AfterParsingCheck.NoCheck);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
if (isLast)
{
return("\n-> Error creating new network: no text for upper boundaties ");
}
float[] upperBoundaries = new float[layersNumber];
result = Parsing.ParseFloatArray(ref tmpString, ref upperBoundaries, ref isLast, "upper boundaries", Parsing.AfterParsingCheck.NoCheck);
if (result.Length > 0)
{
return("\n-> Error creating new network. " + result);
}
network = ANNetwork.NewNetwork(neuronNumbers, inputsNumber, learningSpeed, alpha, lyambda, CFType, AFTypes, initScale, lowerBoundaries, upperBoundaries);
externalNetworkLink = network;
return("");
}