/// <summary>
/// Associates the input icon data structure to an icon which the networks belives in
/// </summary>
/// <param name="iconInputDataStructure">input icon</param>
/// <returns>icon shich the network believes in</returns>
public IconInputDataStructure Associate(IconInputDataStructure iconInputDataStructure)
{
var biPolarIcon = _binaryToBiPolarVecConvertor.ConvertBinaryVecToBiPolar(iconInputDataStructure.IconVector);
var biPolarPhoneNumber = _phoneNumberToBiPolarConvertor.ConvertStringPhoneNumberToBiPolar(iconInputDataStructure.PhoneNumber);
// convert the input arguments to biPolar and run associate
_bamNeuralNetwork.Associate(biPolarIcon, biPolarPhoneNumber);
var phoneNumber = _phoneNumberToBiPolarConvertor.ConvertBiPolarPhoneNumberToString(biPolarPhoneNumber);
var icon = _binaryToBiPolarVecConvertor.ConvertBiPolarVecToBinary(biPolarIcon);
return new IconInputDataStructure(icon, phoneNumber);
}
/// <summary>
///
/// </summary>
/// <param name="errorPrecentage"></param>
/// <returns></returns>
public IconInputDataStructure CreateError(int errorPrecentage)
{
var errorIcon = new IconInputDataStructure(IconVector, PhoneNumber);
var numOfPixelsToChange = (int) (RepresentationVectorSize*((double) errorPrecentage/100));
var rand = new Random(DateTime.Now.Millisecond);
for (var i = 0; i < numOfPixelsToChange; i++)
{
// Get a random index and change it's value
var index = rand.Next(0, RepresentationVectorSize - 1);
// Flip bit
errorIcon.IconVector[index] = 1 - errorIcon.IconVector[index];
}
return errorIcon;
}