public override double Forward(Matrix Actual, Matrix Expected, MatrixData data, int layerCount)
{
double error = 0.0;
if (Actual.rows != Expected.rows || Actual.cols != Expected.cols)
{
throw new MatrixException("Actual does not have the same size as Expected");
}
double regularizationValue = 0.0;
for (int i = 0; i < layerCount; i++)
{
regularizationValue = RegularizationFunction.CalculateNorm(data.Data["W" + i.ToString()]);
}
for (int i = 0; i < Actual.rows; i++)
{
for (int j = 0; j < Actual.cols; j++)
{
error += Expected[i, j] * Math.Log(Expected[i, j] / Actual[i, j]);
}
}
error += regularizationValue;
BatchCost += error;
return(error);
}
private void zcSlider_ValueChanged(object sender, RoutedPropertyChangedEventArgs <double> e)
{
zc = Math.Round(e.NewValue) * 10;
MatrixData md = new MatrixData(0, zc);
shape.ProjectReal3D(md.Zc);
}
public override void Forward(ref MatrixData input)
{
// First layer will be a-1
// Get previous a
Matrix prev_A = input.Data["a" + (Index - 1).ToString()];
// Get previous W
Matrix W = input.Data["W" + (Index).ToString()];
// Get previous b
Matrix b = input.Data["b" + (Index).ToString()];
// Calculate Z and store it
Matrix Z = Matrix.Transpose(W).Dot((prev_A)) + b;
input.Data["Z" + (Index).ToString()] = Z;
// Calculate a and store it
Matrix A = Activation.Forward(Z);
input.Data["a" + (Index).ToString()] = Z;
// Formula For a[i]: g[i]((W_Transpose[i] . z[i-1]) + B[i])
// Update the global data
GlobalData = input;
}
public override void Backward(ref MatrixData input)
{
// The only thing we need to put into the Input Matrix is the last calculated da
// Calculate dz and store it
Matrix dz = input.Data["da" + (Index).ToString()].ElementMul(Activation.Backward(input.Data["Z" + (Index).ToString()]));
input.Data["dZ" + (Index).ToString()] = dz;
// Calculate dw and store it
Matrix dw = input.Data["dZ" + (Index).ToString()].Dot(Matrix.Transpose(input.Data["a" + (Index - 1).ToString()]));
input.Data["dW" + (Index).ToString()] = dw;
// Calculate db and store it
Matrix db = dz;
input.Data["db" + (Index).ToString()] = db;
// Calculate previous da and store it
Matrix prev_da = input.Data["W" + (Index).ToString()].Dot(input.Data["dZ" + (Index).ToString()]);
input.Data["da" + (Index - 1).ToString()] = prev_da;
// Formula dZ[i]: ((W_Transpose[i+1] . dZ[i+1]) * g'[i](z[i]))
// Update the global data
GlobalData = input;
}
public JsonResult AddQuestions(long GroupTypeVal, string GroupTypeText)
{
bool isResult = false;
int returnResult = 0;
try
{
QuestionsModel question = new QuestionsModel();
question.AssessmentGroupId = GroupTypeVal;
question.QuestionText = GroupTypeText.Trim();
question.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
question.UserId = new Guid(Session["UserID"].ToString());
question.AssessmentGroupId = GroupTypeVal;
string command = "CHECKQUESTION";
isResult = new MatrixData().CheckQuestions(question, command);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().InsertQuestionType(question);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception Ex)
{
clsError.WriteException(Ex);
//return Json("Error occured please try again.");
}
return(Json(isResult, JsonRequestBehavior.AllowGet));
}
public JsonResult DeleteAssessmentGroup(long groupId)
{
bool isResult = false;
int returnResult = 0;
try
{
AssessmentGroup group = new FingerprintsModel.AssessmentGroup();
group.AssessmentGroupId = groupId;
group.UserId = new Guid(Session["UserID"].ToString());
group.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
const string command = "CHECKGROUPREF";
isResult = new MatrixData().CheckAssessmentGroup(group, command);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().DeleteAssessmentGroup(group);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
}
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
public JsonResult DeleteMatrixType(long ID)
{
bool isResult = false;
int returnResult = 0;
try
{
Guid?agencyid = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
Guid userId = new Guid(Session["UserID"].ToString());
isResult = new MatrixData().CheckMatrixRef(ID, agencyid);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().DeleteMatrixType(ID, agencyid, userId);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
//return Json("Error occured please try again.");
}
return(Json(isResult, JsonRequestBehavior.AllowGet));
}
public JsonResult UpdateAssessmentCategory(string categoryName, long categoryId, long position)
{
bool isResult = false;
int returnResult = 0;
string queryCommand = "CHECKUPDATE";
AssessmentCategory assessmentCategory = new FingerprintsModel.AssessmentCategory();
try
{
assessmentCategory.UserId = new Guid(Session["UserID"].ToString());
assessmentCategory.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
assessmentCategory.Category = categoryName.Trim();
assessmentCategory.AssessmentCategoryId = categoryId;
assessmentCategory.CategoryPosition = position;
isResult = new MatrixData().CheckAssessmentCategory(assessmentCategory, queryCommand);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().UpdateAssessmentCategory(assessmentCategory);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
}
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
public virtual void FillRectangle(Rectangle <float> rectangle, Color <float> color)
{
//fill rectangle
//color.alpha means the opacity of rectangle
MatrixData matrixData = new MatrixData();
RenderConfig renderConfig = new RenderConfig()
{
Color = color
};
//1.scale the rectangle
matrixData.World = Matrix4x4.CreateScale(rectangle.Right - rectangle.Left, rectangle.Bottom - rectangle.Top, 1.0f);
//2.translate it
matrixData.World *= Matrix4x4.CreateTranslation(rectangle.Left, rectangle.Top, 0.0f);
//3.keep transform matrix data
matrixData.World *= Transform;
//set projection matrix
matrixData.Project = mProject;
mMatrixDataBuffer.Update(matrixData);
mRenderConfigBuffer.Update(renderConfig);
mDevice.SetPixelShader(mColorPixelShader);
mDevice.SetVertexBuffer(mSquareVertexBuffer);
mDevice.SetIndexBuffer(mSquareIndexBuffer);
mDevice.SetBuffer(mMatrixDataBuffer, mMatrixDataBufferSlot, GpuShaderType.VertexShader);
mDevice.SetBuffer(mRenderConfigBuffer, mRenderConfigBufferSlot, GpuShaderType.PixelShader);
mDevice.DrawIndexed(6, 0, 0);
}
public JsonResult DeleteAssessmentCategory(long categoryId)
{
bool isResult = false;
int returnResult = 0;
try
{
AssessmentCategory assessmentCategory = new FingerprintsModel.AssessmentCategory();
assessmentCategory.UserId = new Guid(Session["UserID"].ToString());
assessmentCategory.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
assessmentCategory.AssessmentCategoryId = categoryId;
const string command = "CHECKCATREF";
isResult = new MatrixData().CheckAssessmentCategory(assessmentCategory, command);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().DeleteAssessmentCategory(assessmentCategory);
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
}
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
public void Run(string fileName)
{
MatrixData m = new MatrixData(fileName, false, true, ',');
for (int i = 0; i < 2; i++)
{
OutputSteps(m[i].GetReShapedMatrix(19), i.ToString());
}
void OutputSteps(MatrixData input, string dir)
{
string _dir = "Data\\" + dir + "";
MatrixData pixelMatrix = input;
pixelMatrix.Clamp(0, 255).UpScale(16).ToImage(_dir + "0.bmp");
pixelMatrix = pixelMatrix.ReduceDimensionByOne(0).ReduceDimensionByOne(1);
pixelMatrix.UpScale(16).Clamp(0, 255).ToImage(_dir + "1.bmp");
pixelMatrix = pixelMatrix.Convert18To6Px(false);
pixelMatrix.Clamp(0, 255);
pixelMatrix.UpScale(16).ToImage(_dir + "3.bmp");
}
}
public void GrayTo255(string fileName)
{
MatrixData m = new MatrixData(fileName, true, true, ',') * 255;
m = m.RoundAll();
m.WriteCSV(fileName.Replace(".csv", "") + "255" + ".csv", false);
}
public dynamic[] ProcessImage2(dynamic[] input)
{
//Turn the input vector into a matrix
//This matrix represents the image
MatrixData pixelMatrix = input.GetReShapedMatrix(19);
//Get the emboss edge
pixelMatrix = pixelMatrix.GetEmbossEdge();
//Apply with hist EQ function
pixelMatrix = pixelMatrix.HistEQ();
//Crop 1 pixel off the edge of the image
//this results in a 17x17 image
pixelMatrix = pixelMatrix.CropEdges(1);
//reduce the size of the image to 16x16 by removing
// a random pixel from each row and column
pixelMatrix = pixelMatrix.ReduceDimensionByOne(0).ReduceDimensionByOne(1);
//Blur the image
pixelMatrix = pixelMatrix.ApplyConvolutionFilter(blurFilter);
//Reduce the 16x16 image to 8x8 using a custom downsampling algorithm
pixelMatrix = pixelMatrix.DownScale(2);
//Clamp the output matrix values between 0 and 255
pixelMatrix = pixelMatrix.Clamp(0, 255);
//return the pixel matrix as a vector
// the size of this vector will be 36 (6x6)
return(pixelMatrix.GetVectorizedMatrix());
}
public dynamic[] ProcessImage1(dynamic[] input)
{
//Turn the input vector into a matrix
//This matrix represents the image
MatrixData pixelMatrix = input.GetReShapedMatrix(19);
//Sharpen the image
pixelMatrix = pixelMatrix.ApplyConvolutionFilter(sharpenFilter);
//Apply the SobelEdge filter
pixelMatrix = pixelMatrix.GetSobelEdge();
//reduce the size of the image to 18x18 by removing
// a random pixel from each row and column
pixelMatrix = pixelMatrix.ReduceDimensionByOne(0).ReduceDimensionByOne(1);
//Blur the image
pixelMatrix = pixelMatrix.ApplyConvolutionFilter(blurFilter);
//Reduce the 18x18 image to 6x6 using a custom downsampling algorithm
pixelMatrix = pixelMatrix.Convert18To6Px();
//Clamp the output matrix values between 0 and 255
pixelMatrix = pixelMatrix.Clamp(0, 255);
//return the pixel matrix as a vector
// the size of this vector will be 36 (6x6)
return(pixelMatrix.GetVectorizedMatrix());
}
private static double[][,] GetMatrix(string file)
{
var traindata = new MatrixData();
traindata.LoadData(file);
return(traindata.ToDoubleMatrix(new Size(16, 16)));
}
public JsonResult UpdateAssessmentGroup(string groupType, long categoryId, int status, long groupId)
{
bool isResult = false;
int returnResult = 0;
try
{
string queryCommand = "UPDATECHECK";
AssessmentGroup assessmentGroup = new FingerprintsModel.AssessmentGroup();
assessmentGroup.UserId = new Guid(Session["UserID"].ToString());
assessmentGroup.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
assessmentGroup.AssessmentCategoryId = categoryId;
assessmentGroup.IsActive = Convert.ToBoolean(status);
assessmentGroup.AssessmentGroupType = groupType;
assessmentGroup.AssessmentGroupId = groupId;
isResult = new MatrixData().CheckAssessmentGroup(assessmentGroup, queryCommand);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().UpdateAssessmentGroup(assessmentGroup);
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
catch (Exception ex)
{
clsError.WriteException(ex);
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
public string ResetData()
{
string output = "";
output += "Setting \"" + nameof(_rawData) + "\" to null" + Environment.NewLine;
_rawData = null;
output += "Setting \"" + nameof(_exemplarData) + "\" to null" + Environment.NewLine;
_exemplarData = null;
output += "Setting \"" + nameof(_trainingData) + "\" to null" + Environment.NewLine;
_trainingData = null;
output += "Setting \"" + nameof(_testingData) + "\" to null" + Environment.NewLine;
_testingData = null;
output += "Setting \"" + nameof(_validationData) + "\" to null" + Environment.NewLine;
_validationData = null;
output += "Setting \"" + nameof(_confusionMatrixTrain) + "\" to null" + Environment.NewLine;
_confusionMatrixTrain = null;
output += "Setting \"" + nameof(_confusionMatrixTest) + "\" to null" + Environment.NewLine;
_confusionMatrixTest = null;
output += "Setting \"" + nameof(_confusionMatrixVal) + "\" to null" + Environment.NewLine;
_confusionMatrixVal = null;
output += "Setting \"" + nameof(_outputMatrixTrain) + "\" to null" + Environment.NewLine;
_outputMatrixTrain = null;
output += "Setting \"" + nameof(_outputMatrixTest) + "\" to null" + Environment.NewLine;
_outputMatrixTest = null;
output += "Setting \"" + nameof(_outputMatrixVal) + "\" to null" + Environment.NewLine;
_outputMatrixVal = null;
output += "Setting \"" + nameof(_graphData) + "\" to null" + Environment.NewLine;
_graphData = null;
return(output);
}
public JsonResult AddMatrxiType(long matrixvalue, string matrixtype)
{
bool isResult = false;
int returnResult = 0;
try
{
string querycommand = "CHECKMATRIX";
Matrix matrix = new FingerprintsModel.Matrix();
matrix.MatrixValue = matrixvalue;
matrix.MatrixType = matrixtype.Trim();
matrix.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
matrix.UserId = new Guid(Session["UserID"].ToString());
isResult = new MatrixData().CheckMatrixType(matrix, querycommand);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().InsertMatrixType(matrix);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception Ex)
{
clsError.WriteException(Ex);
//return Json("Error occured please try again.");
}
return(Json(returnResult));
}
private string trainNN(string nnRef, string matrixTrainRef, string matrixTestRef, int epochs, double eta, string outputFileName)
{
var nn = Value(nnRef);
if (nn.GetType() == typeof(string))
{
return(nn.ToString());
}
var matrixTrain = Value(matrixTrainRef);
if (matrixTrain.GetType() == typeof(string))
{
return(matrixTrain.ToString());
}
var matrixTest = Value(matrixTestRef);
if (matrixTest.GetType() == typeof(string))
{
return(matrixTest.ToString());
}
MatrixData train = (MatrixData)matrixTrain;
MatrixData test = (MatrixData)matrixTest;
W4NeuralNetwork m = (W4NeuralNetwork)nn;
m.train(train.Data.ToJagged().ToDoubleArray(), test.Data.ToJagged().ToDoubleArray(), epochs, eta, outputFileName + ".nnlog.txt");
return("Trained neural network \"" + nnRef + "\" with " + epochs + " epochs, " + eta.ToString() + " eta");
}
public JsonResult UpdateAcronym(long AcronymId, string AcronymName)
{
bool isResult = false;
int returnResult = 0;
try
{
string queryCommand = "UPDATECHECK";
Acronym acronym = new FingerprintsModel.Acronym();
acronym.AcronymId = AcronymId;
acronym.AcronymName = AcronymName;
acronym.UserId = new Guid(Session["UserID"].ToString());
acronym.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
isResult = new MatrixData().CheckUpdateAcronym(acronym, queryCommand);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().UpdateAcronym(acronym);
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
catch (Exception ex)
{
clsError.WriteException(ex);
return(Json("Error occured please try again."));
}
}
public JsonResult UpdateQuestions(long GroupType, string Questiontype, long QuestionId)
{
bool isResult = false;
int returnResult = 0;
try
{
QuestionsModel question = new QuestionsModel();
question.AssessmentQuestion = Questiontype;
question.AssessmentGroupId = GroupType;
question.AssessmentQuestionId = QuestionId;
question.UserId = new Guid(Session["UserID"].ToString());
question.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
const string command = "CHECKQUESTIONUPDATE";
isResult = new MatrixData().CheckQuestions(question, command);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().UpdateQuestionType(question);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
//return Json("Error occured please try again.");
}
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
public JsonResult UpdateMatrixType(long matrixId, string matrixType, long matrixValue)
{
bool isResult = false;
int returnResult = 0;
try
{
string queryCommand = "CHECKUPDATE";
Matrix matrix = new FingerprintsModel.Matrix();
matrix.MatrixId = matrixId;
matrix.MatrixType = matrixType;
matrix.MatrixValue = matrixValue;
matrix.UserId = new Guid(Session["UserID"].ToString());
matrix.AgencyId = (Session["AgencyId"] != null) ? new Guid(Session["AgencyId"].ToString()) : (Guid?)null;
isResult = new MatrixData().CheckMatrixType(matrix, queryCommand);
if (isResult)
{
returnResult = 2;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
isResult = new MatrixData().UpdateMatrixType(matrix);
if (isResult)
{
returnResult = 1;
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
}
catch (Exception ex)
{
clsError.WriteException(ex);
//return Json("Error occured please try again.");
}
return(Json(returnResult, JsonRequestBehavior.AllowGet));
}
public static MatrixData SaveMatrix(MetaTileMap MetaTileMap, bool SingleSave = true,
Vector3?Localboundarie1 = null, Vector3?Localboundarie2 = null, bool UseInstance = false)
{
if (SingleSave)
{
UnserialisedObjectReferences.Clear();
MonoToID.Clear();
FieldsToRefresh.Clear();
IDStatic = 0;
IDmatrixStatic = 0;
}
MatrixData matrixData = new MatrixData();
matrixData.ObjectMapData = SaveObjects(MetaTileMap, Localboundarie1, Localboundarie2, UseInstance);
matrixData.TileMapData = SaveTileMap(MetaTileMap, Localboundarie1, Localboundarie2);
matrixData.MatrixName = MetaTileMap.matrix.NetworkedMatrix.gameObject.name;
matrixData.MatrixID = IDmatrixStatic;
matrixData.Location = Math.Round(MetaTileMap.matrix.NetworkedMatrix.transform.localPosition.x, 2) + "┼" +
Math.Round(MetaTileMap.matrix.NetworkedMatrix.transform.localPosition.y, 2) + "┼" +
Math.Round(MetaTileMap.matrix.NetworkedMatrix.transform.localPosition.z, 2) + "┼";
var Angles = MetaTileMap.matrix.NetworkedMatrix.transform.eulerAngles;
matrixData.Location = matrixData.Location +
Math.Round(Angles.x, 2) + "ø" +
Math.Round(Angles.y, 2) + "ø" +
Math.Round(Angles.z, 2) + "ø";
IDmatrixStatic++;
if (SingleSave)
{
foreach (var MFD in UnserialisedObjectReferences)
{
if (MonoToID.ContainsKey(MFD.Item1))
{
MFD.Item2.AddID(MonoToID[MFD.Item1]);
}
else
{
Logger.LogError("Missing money behaviour in MonoToID");
}
}
UnserialisedObjectReferences.Clear();
MonoToID.Clear();
foreach (var FD in FieldsToRefresh)
{
FD.Serialise();
}
FieldsToRefresh.Clear();
}
return(matrixData);
}
public double rightOrWrong(MatrixData input, string OutFileName)
{
double[][] dataSet = input.Data.ToJagged().ToDoubleArray();
// percentage correct using winner-takes all
bool result;
StreamWriter writer = null;
if (OutFileName.Trim() != "")
{
writer = new StreamWriter(OutFileName);
}
int numCorrect = 0;
int numWrong = 0;
double[] xValues = new double[numInput]; // inputs
double[] tValues = new double[numOutput]; // targets
double[] yValues; // computed Y
confusionMatrix = new int[numOutput, numOutput];
//confusionMatrixCnt = 0;
for (int i = 0; i < dataSet.Length; ++i)
{
Array.Copy(dataSet[i], xValues, numInput); // parse test data into x-values and t-values
Array.Copy(dataSet[i], numInput, tValues, 0, numOutput);
yValues = this.ComputeOutputs(xValues);
int maxIndexOut = MaxIndex(yValues); // which cell in yValues has largest value?
int maxIndexExpected = MaxIndex(tValues); // which cell in yValues has largest value?
if (maxIndexOut == maxIndexExpected)
{
numCorrect++; result = true;
}
else
{
numWrong++; result = false;
}
if (OutFileName.Trim() != "")
{
string linez = "";
for (int j = 0; j < dataSet[i].Length; j++)
{
linez = linez + dataSet[i][j].ToString("F6") + " ";
}
linez = linez + "(" + maxIndexOut + " , " + maxIndexExpected + ") ";
if (result)
{
linez = linez + " Correct\r\n";
}
else
{
linez = linez + " Wrong \r\n";
}
writer.Write(linez);
}
}
if (OutFileName.Trim() != "")
{
writer.Close();
}
return((numCorrect * 1.0) / (numCorrect + numWrong)); // ugly 2 - check for divide by zero note *100 for percent
}
/// <summary>
/// Execute
/// </summary>
/// <returns></returns>
protected override bool Execute()
{
var signature = Utility.GetMD5(Utility.GetCustomConfig("APP_SALSA") + Utility.JsonSerialize_IgnoreLoopingReference(DTO.GetSignatureDTO()));
dynamic validationResult = new ExpandoObject();
List <string> FrqValues = new List <string>();
PxStat.RequestLanguage.LngIsoCode = DTO.LngIsoCode;
bool isValid = false;
isValid = Validate();
// }
if (isValid)
{
validationResult.Signature = signature;
validationResult.FrqValueCandidate = FrqValues;
Response.data = validationResult;
return(true);
}
if (!isValid)
{
if (MatrixData != null)
{
if (MatrixData.MainSpec.requiresResponse)
{
//cancel any validation errors and return an object to enable the user to choose which should be the time dimension
Matrix.Specification langSpec = MatrixData.GetSpecFromLanguage(DTO.LngIsoCode);
if (langSpec == null)
{
langSpec = MatrixData.MainSpec;
}
foreach (var v in langSpec.MainValues)
{
FrqValues.Add(v.Key);
}
validationResult.Signature = null;
validationResult.FrqValueCandidate = FrqValues;
Response.data = validationResult;
return(true);
}
}
Response.data = validationResult;
return(false);
}
//Response.error = Label.Get("error.validation");
return(false);
}
public void OnLoad(int x, int z)
{
MatrixData data = tile_matrix[x, z];
if (data != null)
{
AddToMatrixList(data.data);
}
}
public SNeuralNetwork(int numberOfInputNodes, int numberOfHiddenNodes, int numberOfOutputNodes, double learningRate)
{
_learningRate = learningRate;
_weightInputHidden = new MatrixData(numberOfHiddenNodes, numberOfInputNodes);
_weightHiddenOutput = new MatrixData(numberOfOutputNodes, numberOfHiddenNodes);
RandomizeWeights();
}
public override Matrix Backward(Matrix Actual, Matrix Expected, MatrixData data, int layerCount)
{
if (Actual.rows != Expected.rows || Actual.cols != Expected.cols)
{
throw new MatrixException("Actual Matrix does not have the same size as The Expected Matrix");
}
return(Actual - Expected);
}
static void PI(int img)
{
System.Console.WriteLine(DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss.fff"));
Image <Rgba32> image = Image.Load("data\\" + img + ".bmp");
image.Mutate(ctx => ctx.Resize(image.Width / 8, image.Height / 8));
double ConversionFactor = 255 / (5 - 1);
double AverageValue;
MatrixData m = new MatrixData(image.Width, image.Height);
for (int r = 0; r < image.Width; r++)
{
for (int c = 0; c < image.Height; c++)
{
AverageValue = (image[r, c].R + image[r, c].B + image[r, c].G) / 3;
double pv = ((AverageValue / ConversionFactor) + 0.5) * ConversionFactor;
if (pv < 200)
{
pv = 0;
}
m[r, c] = pv;
}
}
m = m.HistEQ();
int mp = (int)m.MeanIfPixel((s) => { return(s > 0); });
for (int r = 0; r < image.Width; r++)
{
for (int c = 0; c < image.Height; c++)
{
if (m[r, c] < mp)
{
m[r, c] = 0;
}
}
}
m = m.HistEQ();
mp = (int)m.MeanIfPixel((s) => { return(s > 0); });
m = m.NormalizeAllBetween(mp, 255) * 255;
m = m - vm;
Tuple <int, int> centerBlob = new Tuple <int, int>(0, 0);
Tuple <int, int> center = new Tuple <int, int>(image.Width / 2, image.Height / 2);
m = m.ToBinary(m.MeanIfPixel((s) => { return(s > 0); })).GetLargestBlob(ref centerBlob);
System.Console.WriteLine(DateTime.Now.ToString("yyyy-MM-dd HH:mm:ss.fff"));
double angle = Math.Atan2(centerBlob.Item1 - center.Item2, centerBlob.Item1 - center.Item1) * (180 / Math.PI);
double dist = Math.Abs(Math.Pow(centerBlob.Item1 - centerBlob.Item2, 2) + Math.Pow(center.Item1 - center.Item2, 2));
List <dynamic> output = m.GetVectorizedMatrix().ToList();
output.Add(angle);
System.Console.WriteLine("image loaded");
}
public string SetVal()
{
string output = "";
_validationData = _exemplarData.CopyData(NumTrain + NumTest, 0, NumVal);
output += "Validation data:" + Environment.NewLine;
output += _validationData.Head().ToString(5, 16, 300, true);
output += Environment.NewLine + Environment.NewLine;
return(output);
}
public abstract void VisitMatrixData(MatrixData element);
public override void VisitMatrixData(MatrixData element)
{
String MatrixValues = element.getText();
int rowsize = 0, colsize = 0;
for (int i = 1; i < MatrixValues.LastIndexOf(']'); i++)
{
if (MatrixValues[i] == ',')
{ colsize++; continue; }
if (MatrixValues[i] == '[')
continue;
if (MatrixValues[i] == ']')
{ rowsize++; continue; }
int element_value = int.Parse(MatrixValues[i].ToString());
mStack.Push(element_value);
}
colsize = (colsize / rowsize) + 1;
int[,] mat = new int[rowsize, colsize];
for (int i = rowsize - 1; i >= 0; i--)
for (int j = colsize - 1; j >= 0; j--)
{
int result = mStack.Pop();
mat[i, j] = result;
}
matStack.Push(mat);
}
private IMatrixData ProcessAplFiles(ProcessInfo processInfo, int nThreads, IList<MsRunImpl> aplfiles)
{
string tempFile = Path.Combine(FileUtils.GetTempFolder(), "spectraref.txt");
if (File.Exists(tempFile)){
File.Delete(tempFile);
}
IMatrixData matrix;
StreamWriter writer = null;
try{
Enum[] enums = new Enum[]{spectraRef.raw_file, spectraRef.charge, spectraRef.scan_number, spectraRef.location, spectraRef.format, spectraRef.id_format, spectraRef.fragmentation, spectraRef.mz, spectraRef.index};
IList<string> header = enums.Select(Constants.GetPattern).ToList();
if (aplfiles == null || aplfiles.Count == 0){
return null;
}
int nTasks = aplfiles.Count;
processInfo.Progress(0);
processInfo.Status(string.Format("Read Andromeda peaklist files [{0}|{1}]", 0, nTasks));
writer = new StreamWriter(tempFile);
writer.WriteLine(StringUtils.Concat("\t", header));
writer.WriteLine("#!{Type}" + StringUtils.Concat("\t", header.Select(x => "T")));
ThreadDistributor distr = new ThreadDistributor(nThreads, nTasks,
x =>
ParseAplFile(aplfiles[x], writer,
string.Format(
"Read Andromeda peaklist files [{0}|{1}]",
x + 1, nTasks), (x + 1)*100/nTasks,
processInfo));
distr.Start();
processInfo.Status("Close all files");
writer.Close();
writer.Dispose();
writer = null;
processInfo.Progress(0);
processInfo.Status("Create SpectraRef matrix");
matrix = new MatrixData();
LoadData(matrix, tempFile, processInfo);
}
catch (Exception ex){
throw ex;
}
finally{
if (writer != null){
writer.Close();
}
if (File.Exists(tempFile)){
File.Delete(tempFile);
}
}
return matrix;
}
private IMatrixData ProcessDbFiles(ProcessInfo processInfo, int nThreads, IList<Database> databases)
{
string tempFile = Path.Combine(FileUtils.GetTempFolder(), "databaseref.txt");
IMatrixData matrix;
StreamWriter writer = null;
try{
processInfo.Progress(0);
processInfo.Status(string.Format("Read database files [{0}|{1}]", 0, "?"));
Enum[] enums = new Enum[] { databaseRef.file, databaseRef.source, databaseRef.specie, databaseRef.taxid, databaseRef.version, databaseRef.identifier };
IList<string> header = enums.Select(Constants.GetPattern).ToList();
if (databases == null || databases.Count == 0){
return null;
}
writer = new StreamWriter(tempFile);
int nTasks = databases.Count;
writer.WriteLine(StringUtils.Concat("\t", header));
writer.WriteLine("#!{Type}" + StringUtils.Concat("\t", header.Select(x => "T")));
ThreadDistributor distr = new ThreadDistributor(nThreads, nTasks,
x =>
ParseDatabase(writer, databases[x],
string.Format(
"Read database files [{0}|{1}]",
x + 1, nTasks), (x + 1)*100/nTasks,
processInfo));
distr.Start();
processInfo.Status("Close all files");
writer.Close();
writer.Dispose();
writer = null;
processInfo.Progress(0);
processInfo.Status("Create DatabaseRef Matrix");
matrix = new MatrixData();
LoadData(matrix, tempFile, processInfo);
}
catch (Exception ex){
throw ex;
}
finally{
if (writer != null){
writer.Close();
}
if (File.Exists(tempFile)){
File.Delete(tempFile);
}
}
return matrix;
}
