// CHANGE COST FUNCTION
public string SetCFType(string tmpString)
{
// CHECKING NETWORK
if (network == null)
{
return(noNetworkMessage);
}
// CHECKING INPUTED STRING
if (tmpString.Length == 0)
{
return("\n-> Error changing network's cost function type: no input text.");
}
CFTypeBase newCFType = null;
bool isLast = false;
string answer = Parsing.ParseCFType(ref tmpString, ref newCFType, ref isLast);
if (answer.Length > 0)
{
return(answer);
}
network.SetCFType(newCFType);
return("\n-> Cost function type set successful.");
}
/// <summary>
/// Parses inputed string, trying to read array of indexes of cost functions (see CFTypeBase class and its subclasses), passed as a reference.
/// </summary>
/// <param name="tmpString">Input string argument to be parsed.</param>
/// <param name="resultCFType">Reference on result array with subclass objects.</param>
/// <param name="isLast">Reference on a variable, indicating on success if read array was last in inputed string or not.</param>
/// <returns>Empty string on success or error message.</returns>
public static string ParseCFType(ref string tmpString, ref CFTypeBase resultCFType, ref bool isLast)
{
int CFTypeInd = -1;
string result = ParseInt(ref tmpString, ref CFTypeInd, ref isLast, "CFType index", AfterParsingCheck.Positive);
if (result.Length > 0)
{
return("\n-> Error parsing CFType index. " + result);
}
// DETERMINING THE TYPE OF COST FAUNCTION SUBCLASS
switch (CFTypeInd)
{
case 1:
resultCFType = new CFTypeQuadratic();
break;
case 2:
resultCFType = new CFTypeCrossEntropy();
break;
case 3:
resultCFType = new CFTypeLogLikelihood();
break;
default:
return("\n-> Error parsing CFType index: unknown CFType index (" + CFTypeInd.ToString() + ").");
}
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("");
}
