/// <summary>
/// Copy from one mapping to another. Deep copy.
/// </summary>
/// <param name="source">The source mapping.</param>
/// <param name="target">The target mapping.</param>
public static void Copy(NeuralDataMapping source, NeuralDataMapping target)
{
for (int i = 0; i < source.From.Count; i++)
{
target.From[i] = source.From[i];
}
for (int i = 0; i < source.To.Count; i++)
{
target.To[i] = source.To[i];
}
}
/// <summary>
/// Copy from one object to the other.
/// </summary>
///
/// <param name="source">The source object.</param>
/// <param name="target">The target object.</param>
public static void Copy(NeuralDataMapping source,
NeuralDataMapping target)
{
for (int i = 0; i < source.From.Count; i++)
{
target.From[i] = source.From[i];
}
for (int i_0 = 0; i_0 < source.To.Count; i_0++)
{
target.To[i_0] = source.To[i_0];
}
}
public static void Copy(NeuralDataMapping source, NeuralDataMapping target)
{
int num = 0;
while (true)
{
if (num >= source.From.Count)
{
for (int i = 0; i < source.To.Count; i++)
{
target.To[i] = source.To[i];
}
if ((((uint) num) - ((uint) num)) >= 0)
{
return;
}
}
else
{
target.From[num] = source.From[num];
}
num++;
}
}
/// <summary>
/// Compute the network for the specified input.
/// </summary>
///
/// <param name="input">The input to the network.</param>
/// <returns>The output from the network.</returns>
public NeuralDataMapping Compute(NeuralDataMapping input)
{
bool stable1;
bool stable2;
do
{
stable1 = PropagateLayer(_weightsF1ToF2, input.From,
input.To);
stable2 = PropagateLayer(_weightsF2ToF1, input.To,
input.From);
} while (!stable1 && !stable2);
return null;
}
public void Execute(IExampleInterface app)
{
this.app = app;
var pattern = new BAMPattern();
pattern.F1Neurons = INPUT_NEURONS;
pattern.F2Neurons = OUTPUT_NEURONS;
var network = (BAMNetwork) pattern.Generate();
// train
for (int i = 0; i < NAMES.Length; i++)
{
network.AddPattern(
StringToBipolar(NAMES[i]),
StringToBipolar(PHONES[i]));
}
// test
for (int i = 0; i < NAMES.Length; i++)
{
var data = new NeuralDataMapping(
StringToBipolar(NAMES[i]),
RandomBiPolar(OUT_CHARS*BITS_PER_CHAR));
RunBAM(network, data);
}
app.WriteLine();
for (int i = 0; i < PHONES.Length; i++)
{
var data = new NeuralDataMapping(
StringToBipolar(PHONES[i]),
RandomBiPolar(IN_CHARS*BITS_PER_CHAR));
RunBAM(network, data);
}
app.WriteLine();
for (int i = 0; i < NAMES.Length; i++)
{
var data = new NeuralDataMapping(
StringToBipolar(NAMES2[i]),
RandomBiPolar(OUT_CHARS*BITS_PER_CHAR));
RunBAM(network, data);
}
}
public void RunBAM(BAMNetwork network, NeuralDataMapping data)
{
var line = new StringBuilder();
line.Append(MappingToString(data));
network.Compute(data);
line.Append(" | ");
line.Append(MappingToString(data));
app.WriteLine(line.ToString());
}
public String MappingToString(NeuralDataMapping mapping)
{
var result = new StringBuilder();
result.Append(BipolalToString((BiPolarMLData) mapping.From));
result.Append(" -> ");
result.Append(BipolalToString((BiPolarMLData) mapping.To));
return result.ToString();
}
public NeuralDataMapping Compute(NeuralDataMapping input)
{
bool flag;
bool flag2;
do
{
flag = PropagateLayer(this._weightsF1ToF2, input.From, input.To);
flag2 = PropagateLayer(this._weightsF2ToF1, input.To, input.From);
}
while (!flag && !flag2);
return null;
}
