public SVM_Matlab(string path, double sigma, double gamma, Kernel kernel, ImageVector[] goodImages, ImageVector[] badImages)
{
type = "SVM";
this.goodImages = goodImages;
this.badImages = badImages;
learnedTrue = new bool[goodImages.Length];
learnedFalse = new bool[badImages.Length];
confidenceTrue = new double[goodImages.Length];
confidenceFalse = new double[badImages.Length];
restartTest();
userPath = path + "\\SVM_" + getKernel(kernel) + "_" + sigma;
resultPath = userPath + "\\" + sigma + "_" + gamma;
learn = GetLearnCommand(userPath, sigma, gamma, kernel);
learn_Test = GetLearnCommand_Test(userPath, sigma, gamma, kernel,goodImages[0].getNumOfParameters());
decide = GetDecideCommand(userPath, kernel);
decide_Test = GetDecideCommand_Test(userPath, kernel, goodImages[0].getNumOfParameters());
matlab = new MLApp.MLApp();
cd = "cd " + smartAlbum.getMatlabDirectory();
matlab.Execute(cd);
}
/// <summary>
/// This method executes the specific matlab code of the vectorfield. The stream- or pathlines are handed to matlab.
/// </summary>
/// <param name="matlab">The instance of the matlab connection</param>
public void executeMatlab(MLApp.MLApp matlab)
{
matlab.Execute("highNumberSamples = 0;");
if (freshySimulated)
{
bool first = true;
foreach (Line line in rungeLines)
{
if (line.Points.Count > 0)
{
string t = Util.getLineMatrix(line);
if (first)
{
matlab.Execute("connections = [" + Util.getLineMatrix(line));
first = false;
}
else
{
matlab.Execute("connections = [connections; " + Util.getLineMatrix(line));
}
}
}
freshySimulated = false;
}
}
/// <summary>
/// Constructor of the Mainwindow. The matlab connection and other variables get initialized.
/// </summary>
public MainWindow()
{
InitializeComponent();
clusterCanvas = new Canvas[5];
clusterCanvas[0] = clusterCanvas1;
clusterCanvas[1] = clusterCanvas2;
clusterCanvas[2] = clusterCanvas3;
clusterCanvas[3] = clusterCanvas4;
clusterCanvas[4] = clusterCanvas5;
matlab = new MLApp.MLApp();
string current = Directory.GetCurrentDirectory();
using (StreamReader reader = new StreamReader("SVP.config"))
{
matlabPath = current + "\\" + reader.ReadLine();
ressourcePath = current + "\\" + reader.ReadLine();
}
//current = "cd '" + current.Substring(0, current.IndexOf("SVP")) + "Matlab'";
current = "cd '" + matlabPath + "'";
matlab.Execute(current);
travel = new Travel();
toPolylineConverter = new Util();
}
private void Record_BT_Click(object sender, EventArgs e)
{
MLApp.MLApp matlab = null;
Type matlabAppType = System.Type.GetTypeFromProgID("Matlab.Application");
matlab = System.Activator.CreateInstance(matlabAppType) as MLApp.MLApp;
string command;
if (Record_BT.Text == "录音")
{
command = "R = audiorecorder( 16000, 8 ,1) ; record(R);";
matlab.Visible = 0;
matlab.Execute(command);
Record_BT.Text = "停止";
}
else if (Record_BT.Text == "停止")
{
string outpath = Application.StartupPath + "/speak.wav";
command = "stop(R); myspeech = getaudiodata(R);audiowrite('" + outpath + "', myspeech, 16000);";
matlab.Visible = 0;
matlab.Execute(command);
Record_BT.Text = "录音";
}
}
private void button2_Click(object sender, EventArgs e)//修正值摁钮
{
string str = System.Environment.CurrentDirectory;
MLApp.MLApp matlab = new MLApp.MLApp();
string comm = "";
matlab.Execute(@"cd " + str + "\\第二步计算");
//matlab.Execute("");
// Define the output
object result = null;
// Call the MATLAB function myfunc
matlab.Feval("T", 1, out result);
// matlab.Feval("myfunc", 2, out result, 3.14, 42.0, "world");
// Display result
object[] res = result as object[];
ans = (double[, ])res[0];
for (int i = 0; i < 48; i++)
{
textBox3.Text += "第" + (i + 1).ToString() + "组解: " + " dx: " + ans[i, 0].ToString() + " dy: " + ans[i, 1].ToString() + " dz: " + ans[i, 2].ToString() + Environment.NewLine;
}
//textBox3.Text = ans[1,1].ToString();
// ans = result;
// MessageBox.Show(result);
// Console.WriteLine(res[0]);
// Console.WriteLine(res[1]);
// Console.ReadLine();
// n = excel.solve1();//解第二个方程
//for(int i=0;i<48;i++)
//{ textBox3.Text += "第" + (i + 1).ToString() + "组解: " + " dx: " + n[i * 3].ToString() + " dy: " + n[i * 3 + 1].ToString() + " dz: " + n[i * 3 + 2].ToString()+Environment.NewLine; }
}
protected void EnhanceImage_Click(object sender, EventArgs e)
{
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute("cd " + Server.MapPath(MATLAB_FUNCTIONS_FOLDER));
object result = null;
App_Code.Image image = App_Code.SqlUtilities.GetImage(int.Parse(Request["id"]));
string[] temp = image.Path.Split('/');
string imageName = temp[temp.Length - 1];
matlab.Feval("enhance", 1, out result, Server.MapPath(image.Path), imageName, loggedUsername);
object[] res = result as object[];
string resultPath = "~/Images/" + loggedUsername + "/" + (string)res[0];
System.Web.UI.WebControls.Image imageControl = (System.Web.UI.WebControls.Image)ThumbnailsHolder.Controls[1];
imageControl.ImageUrl = resultPath;
if (ViewState["editedImagePath"] != null)
{
DeleteImage(null, null);
}
ViewState["editedImagePath"] = resultPath;
AddSaveDeleteButtons();
}
public void Init(double rsm_lb, double rsm_ub, int pc_b)
{
step = 0.01;
States = new List <RTPState>();
Observations = new List <RTPObservation>();
ModelSamples = new List <Sample>();
SystemSamples = new List <Sample>();
EstimateSamples = new List <Sample>();
//TestEstimateSamples = new List<Sample>();
MBuilder = Matrix <double> .Build;
VBuilder = Vector <double> .Build;
E = new Matrix <double> [N];
F = new Matrix <double> [M];
for (int i = 0; i < N; i++)
{
E[i] = MBuilder.Dense(N, 1);
E[i][i, 0] = 1;
}
for (int i = 0; i < M; i++)
{
F[i] = MBuilder.Dense(M, 1);
F[i][i, 0] = 1;
}
Matlab = new MLApp.MLApp();
DefineStates(rsm_lb, rsm_ub);
DefineObservations(pc_b);
//ModelParamsInit();
}
private RecognitionProvider()
{
_matlab = new MLApp.MLApp();
// Change to the directory where the function is located
_matlab.Execute(@"cd " + AppDomain.CurrentDomain.BaseDirectory + "ReconScript/");
}
public NetGAxaml()
{
InitializeComponent();
matlab = new MLApp.MLApp();
matlab.Visible = 0;
}
public BestHybrid()
{
InitializeComponent();
matlab = new MLApp.MLApp();
matlab.Visible = 0;
}
public KNN_SVM(string path, double sigma, double gamma, Kernel kernel, int k, ImageVector[] goodImages, ImageVector[] badImages)
{
type = "KNN & SVM";
svm = new SVM_Matlab(path, sigma, gamma, (SVM_Matlab.Kernel)kernel, goodImages, badImages);
knn = new KNN_Matlab(path, k, goodImages, badImages);
totalImages = 0;
this.goodImages = goodImages;
this.badImages = badImages;
learnedTrue = new bool[goodImages.Length];
learnedFalse = new bool[badImages.Length];
restartTest();
userPath = path + "\\KNN_SVM";
resultPath = userPath + "\\sigma_" + sigma + "_gamma_" + gamma;
learn = GetLearnCommand(userPath, sigma, gamma, kernel);
decideSVM = GetDecideCommandSVM(userPath, kernel);
decideKNN = GetDecideCommandKNN(userPath, k);
matlab = new MLApp.MLApp();
cd = "cd " + smartAlbum.getMatlabDirectory();
matlab.Execute(cd);
}
// Start Matlab.
/// <summary>
/// Starts with Program, either connects to COM-Enabled Matlab or starts a Matlab File.
/// </summary>
/// <remarks> The call "enableservice('AutomationServer',true);" COM-enables Matlab and ensures it doesn't close with the program.</remarks>
public static void MatlabStartup()
{
// Matlab Startup and Connection to Desktop
Type MatlabType = Type.GetTypeFromProgID("Matlab.Desktop.Application");
try
{
//To make sure COM enabled for running Matlab
//Connect to an open Matlab
// Execute = enableservice('AutomationServer',true);
matlab = (MLApp.MLApp)Marshal.GetActiveObject("Matlab.Desktop.Application");
}
catch (System.Runtime.InteropServices.COMException ex1)
{
try
{
//Open Matlab program
matlab = (MLApp.MLApp)Activator.CreateInstance(MatlabType);
//IMPORTANT: Stops exiting from Matlab when program closes
matlab.Execute("enableservice('AutomationServer',true);");
}
catch (System.Runtime.InteropServices.COMException ex2)
{
// Matlab not on computer.
}
}
}
private void masstochargeMatlab_Range(double startXval, double endXval)
{
int selectedfileNumber_start = Convert.ToInt32(startXval) + 1;
int selectedfileNumber_end = Convert.ToInt32(endXval) + 1;
int selectedFileNumber = selectedfileNumber_end - selectedfileNumber_start + 1;
if (selectedfileNumber_start > intFileNumber || selectedfileNumber_start > intFileNumber)
{
//not to over max Xvalue
selectedfileNumber_start = intFileNumber;
selectedfileNumber_end = intFileNumber;
}
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute(matlab_path);
object resultdata = null;
//There is no xLength Data
if (xLength == 0)
{
xLength = 25000;
}
matlab.Feval("mTcPlot_Range", 2, out resultdata, selectedfileNumber_start, selectedfileNumber_end, xLength);
object[] res = resultdata as object[];
object_To_double(res);
}
public HybridArimaSVM()
{
InitializeComponent();
matlab = new MLApp.MLApp();
matlab.Visible = 0;
}
private void getMatlabdata()
{
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute(matlab_path);
object resultdata = null;
matlab.Feval("binfileReader2", 2, out resultdata);
object[] res = resultdata as object[];
double[,] intensity = (double[, ])res[0];
fileNumber = (double)res[1];
intFileNumber = Convert.ToInt32(fileNumber);
dintensity = new double[intensity.Length];
for (int i = 0; i < intensity.Length; i++)
{
dintensity[i] = intensity[0, i];
}
InitialZedGraph();
}
public MainModelView(Canvas canvas, Window master)
{
if (Properties.Settings.Default.ModelPath.Length == 0)
{
Properties.Settings.Default.ModelPath = Directory.GetCurrentDirectory();
}
if (Properties.Settings.Default.AppPath.Length == 0)
{
Properties.Settings.Default.AppPath = Directory.GetCurrentDirectory();
}
this._master = master;
this.TrashCommand = new Command(this.TrashAction, this.TrashActionCan);
this.BackCommand = new Command(this.BackAction, this.BackActionCan);
this.ProcessCommand = new Command(this.ProcessAction, this.ProcessActionCan);
this.TrueCommand = new Command(this.TrueAction, this.TrueActionCan);
this.FalseCommand = new Command(this.FalseAction, this.FalseActionCan);
this.OpenMatriceCommand = new Command(this.OpenMatriceAction);
this.ResetDataCommand = new Command(this.ResetDataAction);
this.OpenSettingsCommand = new Command(this.OpenSettingsAction);
this.matrix = new Stack <Point>();
this.canvas = canvas;
this.FunctionPredictor = Properties.Settings.Default.NameModel;
this.Data = Data.Open(this.FunctionPredictor);
this.state = false;
this.StateValid = true;
this.worker = new BackgroundWorker()
{
WorkerSupportsCancellation = true
};
this.worker.RunWorkerCompleted += worker_RunWorkerCompleted;
this.worker.DoWork += (sender, e) =>
{
try
{
bool[,] image = new bool[28, 28];
foreach (Point point in this.matrix)
{
image[(int)point.Y * 2, (int)point.X * 2] = true;
image[(int)point.Y * 2 + 1, (int)point.X * 2] = true;
image[(int)point.Y * 2, (int)point.X * 2 + 1] = true;
image[(int)point.Y * 2 + 1, (int)point.X * 2 + 1] = true;
}
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute("cd " + Properties.Settings.Default.ModelPath);
matlab.PutWorkspaceData("X", "base", image);
matlab.Execute(@"label = " + this.FunctionPredictor + "(X)");
var label = matlab.GetVariable("label", "base");
e.Result = label;
}
catch (Exception err)
{
e.Result = err.Message;
}
};
this.InProcess = "Hidden";
}
private void reducereEBtn_Click(object sender, EventArgs e)
{
if (pathTB.Text.Trim() != "")
{
try
{
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute(@"cd E:\FisiereWAV");
object result = null;
matlab.Feval("MyFunc3", 1, out result, selectedFile, "REcho-", selectedFilePath);
rezultatFiltrareTB.Text = "REcho-" + selectedFile;
soundFilter = new SoundPlayer(@"E:\FisiereWAV\Workspace\" + "REcho-" + selectedFile);
soundFilter.Play();
pictureBox1.Visible = true;
pictureBox1.ImageLocation = @"E:\FisiereWAV\Workspace\" + "REcho-" + Path.GetFileNameWithoutExtension(selectedFile) + ".jpg";
}
catch (Exception ex)
{
MessageBox.Show("Eroare la conexiunea cu MATLAB: " + ex.Message);
}
}
else
{
MessageBox.Show("Nu ati ales fisierul audio!", reducereEBtn.Text, MessageBoxButtons.OK, MessageBoxIcon.Warning);
}
}
private void MatlabAction(string sWPID, string sPathOfApp)
{
// Folgenden Zeilen basieren auf einem Beispiel von Matlab
// Create the MATLAB instance
String sFileName = System.IO.Path.GetFileName(sPathOfApp);
String sFilePath = sPathOfApp.Replace("\\" + sFileName, "");
Type MatlabType = Type.GetTypeFromProgID("Matlab.Desktop.Application");
MLApp.MLApp matlab = (MLApp.MLApp)Activator.CreateInstance(MatlabType);
// Change to the directory where the function is located
String sExecutePath = "cd " + sFilePath;
matlab.Execute(sExecutePath);
// Define the output
object result = null;
// Call the MATLAB function myfunc
matlab.Feval(sFileName.Replace(".m", ""), 1, out result, sWPID);
// Display result
object[] res = result as object[];
// Hier könnte noch eine Abfrage folgen ob das Result ein Fehler ist !!! Ist noch nicht definiert wie das aussieht.
}
// Constructor
CalibrationClient(HoloDataClient holoDataClient, NatNetClient natNetClient)
{
logStartTime_ = System.DateTime.Now;
outputFile_ = outputFile_ + logStartTime_.ToString("_yyMMdd_hhmmss") + ".csv";
WriteToLog("# hl_pos_x,hl_pos_y,hl_pos_z,hl_rot_w,hl_rot_x,hl_rot_y,hl_rot_z,rb_pos_x,rb_pos_y,rb_pos_z,rb_rot_w,rb_rot_x,rb_rot_y,rb_rot_z,timestamp");
outputFile1_ = outputFile1_ + logStartTime_.ToString("_yyMMdd_hhmmss") + ".csv";
outputFile2_ = outputFile2_ + logStartTime_.ToString("_yyMMdd_hhmmss") + ".csv";
// Create the MATLAB instance
matlab_ = new MLApp.MLApp();
// Change to the directory where the function is located
string startupPath = Environment.CurrentDirectory;
string pathCmd = string.Format("cd {0}\\..\\..", startupPath);
matlab_.Execute(pathCmd);
holoDataClient_ = holoDataClient;
natNetClient_ = natNetClient;
holoDataClient_.StartFetchLoop(2000);
holoDataClient_.OnPoseUpdate = PoseDataReceived;
nnStartFetchLoop(20);
}
public static void reCreateMatlabCom()
{
matlab = null;
matlab = new MLApp.MLApp {
Visible = 0
};
}
private void weights_ga_matlab()
{
string path_MatlabFunctions = Environment.CurrentDirectory;
// داده ورودی باید حتما در مسیر توابع متلب باشد
// توابع هزینه هم باید با عنوان
//cost_func
//در همان مسیر توابع متلب تعریف شوند.
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute("clear vars all;");
matlab.Execute(@"cd '" + path_MatlabFunctions + "'");
string temp = matlab.Execute("a=2");
string x = matlab.Execute(@"[x]=GeneticForWighting()");
// string IDX = matlab.Execute("IDX");
try
{
matlab.Execute("quit");
}
catch (Exception ex)
{
}
}
public ArimaGA()
{
InitializeComponent();
matlab = new MLApp.MLApp();
matlab.Visible = 0;
}
public int maxGAIteretionInHybrid = 20; //30
public HybridComplexModel()
{
InitializeComponent();
matlab = new MLApp.MLApp();
matlab.Visible = 0;
}
public OdeSolver()
{
new Thread(() =>
{
_matlab = new MLApp.MLApp();
_matlab.Execute($"cd {Directory.GetCurrentDirectory()}\\Matlab");
}).Start();
}
public void pcaVisualization(double[] Orignal, double[] Pca)
{
MLApp.MLApp matlb = new MLApp.MLApp();
matlb.Execute("cd C:\\temp");
object res = null;
matlb.Feval("pcaVisualizeFunc", 1, out res, Orignal, Pca);
}
public static void PlotarVetor(double[] vetor)
{
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Visible = 0;
//matlab.PutWorkspaceData("a", "base", matriz);
matlab.PutWorkspaceData("a", "base", vetor);
matlab.Execute("plot(a);");
}
private void runMATLAB(string s, string[] args)
{
MLApp.MLApp matlab = new MLApp.MLApp();
object matlabResult = null;
matlab.Execute(@"cd C:\work\temp\images\simple");
matlab.Feval(s, 0, out matlabResult, args[0], args[1], args[2]);
}
private void InitBackgroundMatlabService()
{
_matlab = new MLApp.MLApp();
if (_matlab == null)
{
throw new ApplicationException("Matlab com object is null");
}
}
// 初始化 matlab 引擎
private MLApp.MLApp initMatlabEp()
{
MLApp.MLApp matlab = null;
Type matlabAppType = System.Type.GetTypeFromProgID("Matlab.Application");
matlab = System.Activator.CreateInstance(matlabAppType) as MLApp.MLApp;
return(matlab);
}
public List <RecommendedArtist> GetRecommendationsOnGenre(User fan, List <Artist> artists, int noOfRecommendations)
{
List <Artist> recommendedArtists = new List <Artist>();
List <RecommendedArtist> recommendations = new List <RecommendedArtist>();
if (fan.Genres.Count == 0)
{
return(recommendations);
}
String genresTxt = "";
using (var unitOfWork = new UnitOfWork())
{
var genresRepository = unitOfWork.GetRepository <Genre>();
foreach (Genre g in genresRepository.GetAll())
{
if (fan.Genres.Where(x => x.Id == g.Id).Count() != 0)
{
genresTxt += fan.Id + "," + g.Id + "," + 1 + ";";
}
else
{
genresTxt += fan.Id + "," + g.Id + "," + 0 + ";";
}
}
}
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Execute(@"cd C:\Users\Luiza");
object result = null;
// Call the MATLAB function myfunc
matlab.Feval("genreSimilarity", 1, out result, genresTxt);
// Display result
object[] res = result as object[];
object arr = res[0];
double[,] pairs = (double[, ])arr;
for (int i = 0; i < pairs.Length / 2; i++)
{
var artist = artists.Where(a => a.User.Role == (int)RolesEnum.ARTIST && a.ArtistId == pairs[i, 0]).FirstOrDefault();
if (artist != null && pairs[i, 1] * 100 > 10 && artist.Ratings.Where(r => r.FanId == fan.Id).Count() == 0)
{
recommendations.Add(new RecommendedArtist
{
Id = artist.ArtistId,
Name = artist.User.Name,
Score = pairs[i, 1] * 100,
PictureUrl = artist.PictureUrl,
Why = "Acest artist iti este recomandat deoarece genurile tale muzicale preferate se potrivesc cu ale sale" +
" in proportie de " + Math.Round(pairs[i, 1] * 100, 2) + "%."
});
}
}
return(recommendations.Take(noOfRecommendations).ToList());
}
public void signalVisualization(double[] Orignal, double[] Pca, double[] Ica)
{
MLApp.MLApp matlb = new MLApp.MLApp();
matlb.Execute("cd C:\\temp");
object res = null;
matlb.Feval("myfunc2", 1, out res, Orignal, Pca, Ica);
}
public SimTF()
{
MWinstance = new MLApp.MLApp();
result = "";
resultD = 0;
resultobj = new object();
Mlocation = "D:/SimTF";
result = MWinstance.Execute("cd('" + Mlocation + "');");
}
private void txtMalSpeech_Click(object sender, EventArgs e)
{
if (txtFilePath.Text != "")
{
MLApp.MLApp matlab = new MLApp.MLApp();
matlab.Visible = 0;
matlab.Execute("VoiceChange('" + txtFilePath.Text + "',0)");
}
else
MessageBox.Show("Select a file", "No file selected", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
public SVM_Matlab(string path, double sigma, double gamma, Kernel kernel, ImageVector[] allImages)
{
type = "SVM";
this.allImages = allImages;
filesTrueResults = new Algorithm[allImages.Length];
for (int i = 0; i < filesTrueResults.Length; i++)
filesTrueResults[i] = LearningAlgorithmML.Algorithm.BAD;
userPath = path + "\\SVM_" + getKernel(kernel) + "_" + sigma;
resultPath = userPath + "\\" + sigma + "_" + gamma;
learn = GetLearnCommand(userPath, sigma, gamma, kernel);
decide = GetDecideCommand(userPath, kernel);
matlab = new MLApp.MLApp();
cd = "cd " + smartAlbum.getMatlabDirectory();
matlab.Execute(cd);
}
private void proc()
{
MLApp.MLApp Call_Matlab = new MLApp.MLApp();
Call_Matlab.Visible = 0;
object result = null;
Call_Matlab.Execute(@"cd C:\MatlabProcessing");
try
{
Call_Matlab.Feval("MAIN_PROCESSING", 1, out result, PthTs, PthTr, PthAl);
Res = result as object[];
MessageBox.Show(Res[0].ToString());
Call_Matlab.Quit();
Marshal.ReleaseComObject(Call_Matlab);
}
catch (Exception e)
{
Marshal.ReleaseComObject(Call_Matlab);
MessageBox.Show(e.ToString());
}
}
//private double runConf;
public KNN_Matlab(string path, int k, ImageVector[] goodImages, ImageVector[] badImages)
{
type = "KNN";
this.goodImages = goodImages;
this.badImages = badImages;
learnedTrue = new bool[goodImages.Length];
learnedFalse = new bool[badImages.Length];
restartTest();
userPath = path + "\\KNN";
resultPath = userPath + "\\" + k;
decide = GetCommand(userPath, k);
decide_Test = GetCommand_Test(userPath, k, goodImages[0].getNumOfParameters());
matlab = new MLApp.MLApp();
cd = "cd " + smartAlbum.getMatlabDirectory();
matlab.Execute(cd);
}
public MATLABWrapper(string _mcodepath, string _groupID)
{
groupID = _groupID;
mcodepath = new DirectoryInfo(_mcodepath);
if (!mcodepath.Exists)
{
throw new Exception("The mcode folder can not be found.");
}
var activationContext = Type.GetTypeFromProgID("matlab.application.single");
matlab = (MLApp.MLApp)Activator.CreateInstance(activationContext);
matlab.Visible = 0;
String output;
output= matlab.Execute("cd " + mcodepath.FullName);
output=matlab.Execute("pwd");
var currentDirCheck = matlab.GetVariable("ans", "base");
DirectoryInfo currentDirCheckDi = new DirectoryInfo(currentDirCheck);
if (currentDirCheckDi.FullName != mcodepath.FullName)
{
throw new Exception("Changing MATLAB working directory to mcode directory failed. Working directory stuck at " + currentDirCheck);
}
}
public Tuple<double[], double> Execute(double l1, double l2, double l3)
{
MLApp.MLApp matlab = new MLApp.MLApp();
var appFolder = Path.GetDirectoryName(
Assembly.GetExecutingAssembly().Location
);
var workFolder = Path.Combine(appFolder, "Matlab");
matlab.Execute(@"cd " + workFolder);
object result = null;
matlab.Feval("Calculation", 2, out result, l1, l2, l3);
// Display result
object[] res = (object[])result;
var x = (double[,])res[0];
var fval = (double)res[1];
return Tuple.Create(new double[] { x[0, 0], x[0, 1], x[0, 2] }, fval);
}
public bool Decide()
{
// Get list of files in folders
String[] files = Testing.GetFilesFromDirectory(decidePath).ToArray();
string csvPath = userPath + "\\Decide.txt";
string resultPath = userPath + "\\Result.txt";
for (int i = 0; i < files.Length; i++)
{
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPath, false);
ImageVector vec = new ImageVector(files[i], null);
file.WriteLine(vec.getAllParameters(false));
file.Close();
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
//string exe = "albumSvm('" + userPath + "');";
string exe = "albumKnn('" + userPath + "', " + 1 + ");"; //K = 1
matlab.Execute(cd);
matlab.Execute(exe);
string[] readText = File.ReadAllLines(resultPath);
if (readText[0] == "1")
{
Console.WriteLine("Good Image");
}
else
{
Console.WriteLine("Bad Image. Delete it");
File.Delete(files[i]);
}
}
return true;
}
static void Main(string[] args)
{
/////////////////////////////////////// Looking for a file ///////////////////////////////////////
int m = 0, n;
//Learning the value of m(Number of training examples) and n(number of atributes)
using (TextReader reader = File.OpenText("C:/Users/laerte/Desktop/ex1data1.txt"))
{
string linha = reader.ReadLine();
string[] temp = linha.Split(',');
n = temp.Length - 1;
while (linha != null)
{
m++;
linha = reader.ReadLine();
}
reader.Close();
}
double[,] X = new double[m, n + 1];
double[,] y = new double[m, 1];
double[,] theta = new double[n + 1, 1];
//filling out the matrix X, the vector y, and the vector theta
using (TextReader reader = File.OpenText("C:/Users/laerte/Desktop/ex1data1.txt"))
{
int i = 0;
string linha = reader.ReadLine();
while (linha != null)
{
string[] temp = linha.Split(',');
X[i, 0] = 1;
for (int j = 1; j < n + 1; j++)
{
//Console.Write(temp[j - 1]);
X[i, j] = Convert.ToDouble(temp[j - 1]);
}
y[i, 0] = Convert.ToDouble(temp[n]);
linha = reader.ReadLine();
i++;
}
reader.Close();
}
for (int i = 0; i < n + 1; i++)
{
theta[i, 0] = 0;
}
/*
////////////////////////////////////////////// PRINT ////////////////////////////////////////////////
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n + 1; j++)
{
Console.Write("X[{0}][{1}] = {2} ", i, j, X[i, j]);
}
Console.Write("\n");
}
for (int i = 0; i < m; i++)
{
Console.Write("y[{0}] = {1}\n", i, y[i,0]);
}
for (int i = 0; i < n + 1; i++)
{
Console.Write("theta[{0}] = {1}\n", i, theta[i,0]);
}
*/
////////////////////////////////////////////Matlab calculations/////////////////////////////////////////////
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
// Change to the directory where the function is located
matlab.Execute(@"cd C:\Users\laerte\Desktop");
// Define the output
object result = null;
// Call the MATLAB function myfunc
matlab.Execute("clear all");
matlab.Feval("computeCost", 1, out result, X, y, theta);
// Display result
object[] res = result as object[];
Console.WriteLine("Computing the cost J = " + res[0]);
// Closing the matblab window
//matlab.Quit();
// Wait until fisnih
Console.ReadLine();
}
private void init()
{
matlab = new MLApp.MLApp();
matlab.Visible = 0;
runsCount = errorCount = 0;
data = new List<MyNumber>();
ResourceDictionary rd = new ResourceDictionary();
rd.Source = new Uri("MyResourceDictionary.xaml", UriKind.Relative);
this.Resources.MergedDictionaries.Add(rd);
worker = new BackgroundWorker();
worker.DoWork += new DoWorkEventHandler(worker_DoWork);
worker.RunWorkerCompleted += new RunWorkerCompletedEventHandler(worker_RunWorkerCompleted);
}
void matlab(string code)
{
string[] lines, var_temp;
List<string> variables=new List<string>();
List<string> var_result = new List<string>();
int var_count=0;
lines = code.Split('\r');
MLApp.MLApp matlab = new MLApp.MLApp();
for (int a = 0; a < lines.Count(); a++)
{
if(lines[a].StartsWith("\n"))
lines[a]=lines[a].Remove(0,1);
string i = matlab.Execute(lines[a]);
//TODO osetrit ak nie je spravny matlabovsky prikaz
if (lines[a].Contains('=')) //ak obsahuje = prekpokladame ze pred = je premenna ktoru posleme spet
{
var_temp = lines[a].Split('=')[0].Split(", ".ToCharArray());
for (int b = 0; b < var_temp.Count(); b++)
{
if (var_temp[b].StartsWith("[")) //odstranime [] ak nahodou obsahuje
{
var_temp[b]=var_temp[b].Remove(0, 1);
}
if (var_temp[b].EndsWith("]")) //odstranime [] ak nahodou obsahuje
{
var_temp[b]=var_temp[b].Remove(var_temp[b].Length - 1, 1);
}
if (!variables.Contains(var_temp[b]) && var_temp[b]!="")
{
variables.Add(var_temp[b]);
var_count++;
}
}
}
//matlab.Execute(lines[a]);
}
foreach (string variable in variables)
{
try
{
var_result.Add(Convert.ToString(matlab.GetVariable(variable, "base")));
}
catch(Exception e)
{
var_result.Add(variable + ": ??? Undefined function or variable");
}
}
for (int a = 0; a < variables.Count; a++)
{
result += variables[a] + " = " + var_result[a] + "\r\n";
}
}
static void Main(string[] args)
{
/////////////////////////////////////// Looking for a file ///////////////////////////////////////
// Variables used in matlab
//double lambda = 1.5;
//Reading the file to get the size of lines and columns of R and Y, which will be used in training colloborative filtering
int num_jobs_init;
int num_users_init;
int num_features;
using (TextReader readerR = File.OpenText("C:/Users/larissaf/Desktop/files/Y.txt"))
{
num_jobs_init = 0;
string line = readerR.ReadLine();
string[] temp = line.Split('\t');
num_users_init = temp.Length;
while (line != null)
{
line = readerR.ReadLine();
num_jobs_init++;
}
readerR.Close();
}
//it needs to be between 1 and num_users_init (PUT A VERIFICATION HERE)
/*
Console.Write("Write down the user number that will receive job recommendation from 1 to {0}\n", num_users_init);
string read = Console.ReadLine();
*
*/
int user_number = 1;
StreamWriter writetext = new StreamWriter("results.txt");
string space = "\t";
string new_line = "\n";
while (user_number <= 100)
{
//Now we read R and Y from theirs files (-1 because I will remove the chosen user from the matrixes)
double[,] Y = new double[num_jobs_init, num_users_init - 1];
double[,] R = new double[num_jobs_init, num_users_init - 1];
// Movie rating file for a user
double[,] my_ratings = new double[num_jobs_init, 1];
//reading Y_training
using (TextReader readerY = File.OpenText("C:/Users/larissaf/Desktop/files/Y.txt"))
{
int i = 0;
string line = readerY.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
int k = 0;
for (int j = 0; j < num_users_init; j++)
{
if (j != (user_number - 1))
{
Y[i, k] = Convert.ToDouble(temp[j]);
k++;
}
else
my_ratings[i, 0] = Convert.ToDouble(temp[j]);
}
line = readerY.ReadLine();
i++;
}
readerY.Close();
}
//reading R_training
using (TextReader readerR = File.OpenText("C:/Users/larissaf/Desktop/files/R.txt"))
{
int i = 0;
string line = readerR.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
int k = 0;
for (int j = 0; j < num_users_init; j++)
{
if (j != (user_number - 1))
{
R[i, k] = Convert.ToDouble(temp[j]);
k++;
}
}
line = readerR.ReadLine();
i++;
}
readerR.Close();
}
//reading X to get the number of features
using (TextReader readerX = File.OpenText("C:/Users/larissaf/Desktop/files/X.txt"))
{
num_features = 0;
string line = readerX.ReadLine();
if (line != null)
{
string[] temp = line.Split('\t');
num_features = temp.Length;
}
readerX.Close();
}
//allocating the X matriz
double[,] X = new double[num_jobs_init, num_features];
//reading X_training
using (TextReader readerX = File.OpenText("C:/Users/larissaf/Desktop/files/X.txt"))
{
int i = 0;
string line = readerX.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < num_features; j++)
{
X[i, j] = Convert.ToDouble(temp[j]);
}
line = readerX.ReadLine();
i++;
}
readerX.Close();
}
// make sure that the data will be zero for all the positions
using (TextReader reader_movies_ratings = File.OpenText("C:/Users/larissaf/Desktop/files/one_user_rating.txt"))
{
int i = 0;
string line = reader_movies_ratings.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
my_ratings[Convert.ToInt32(temp[0]) - 1, 0] = Convert.ToInt32(temp[1]);
line = reader_movies_ratings.ReadLine();
i++;
}
reader_movies_ratings.Close();
}
// Job names
string[] job_list = new string[num_jobs_init];
using (TextReader reader_movie_list = File.OpenText("C:/Users/larissaf/Desktop/files/job_names.txt"))
{
string line = reader_movie_list.ReadLine();
int i = 0;
while (line != null)
{
job_list[i] = line;
line = reader_movie_list.ReadLine();
i++;
}
reader_movie_list.Close();
}
////////////////////////////////////////////Matlab calculations///////////////////////////////////////////
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
// Change to the directory where the functions are located --- always use the desktop to make tests to avoid problems with pathway
matlab.Execute(@"cd C:\Users\larissaf\Desktop\files");
// Define the output to print the final result
object result_movies_search = null;
matlab.Execute("my_ratings");
// Movie erecommendations script
matlab.Feval("scriptGeneration", 6, out result_movies_search, my_ratings, job_list, Y, R, X, num_features);
object[] res = result_movies_search as object[];
//Console.Write("{0} {1}", res[5], job_list[(int)(((double[,])res[0])[0, 0]) - 1]);
// ----------------------------------------------------------------------
// writetext.Write(res[5]);
int len = ((double[,])res[0]).Length;
for (int i = 0; i < len; i++)
{
writetext.Write(job_list[(int)(((double[,])res[0])[i, 0]) - 1]);
writetext.Write(space);
writetext.Write((((double[,])res[1])[i, 0]));
writetext.Write(space);
writetext.Write(job_list[(int)(((double[,])res[2])[i, 0]) - 1]);
writetext.Write(space);
writetext.Write((((double[,])res[3])[i, 0]));
writetext.Write(space);
writetext.Write((((double[,])res[4])[i, 0]));
writetext.Write(space);
writetext.Write(user_number);
writetext.Write(new_line);
}
user_number++;
} // while ends
writetext.Close();
Console.Write(" DONE");
// Wait until fisnih
Console.ReadLine();
}
private void button_run_matlab_Click(object sender, EventArgs e)
{
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
// Change to the directory where the function is located
matlab.Execute(@"cd('c:/Users/Boris/Documents/Visual Studio 2010/Projects/FieldFox_1/Matlab')");
string cmd = @"folderToObject('C:\\FieldFox\\" + folderName + @"')";
matlab.Execute(cmd);
}
static void Main(string[] args)
{
int num_jobs_init;
int num_users_init;
int num_features;
int user_number = 1;
//Reading the file to get the size of lines and columns of R and Y,
//which will be used in training colloborative filtering.
using (TextReader readerR = File.OpenText("C:/Users/larissaf/Desktop/files/Y.txt"))
{
num_jobs_init = 0;
string line = readerR.ReadLine();
string[] temp = line.Split('\t');
num_users_init = temp.Length;
while (line != null)
{
line = readerR.ReadLine();
num_jobs_init++;
}
readerR.Close();
}
//File that is going to be written with the Top ten jobs and ratings and similarity for all users
StreamWriter writetext = new StreamWriter("results.txt");
//Dictionary that contains a list of top ten jobs compared with other jobs for each user
Dictionary<int, List<MyData>> finalList = new Dictionary<int, List<MyData>>();
//consider that we have 100 users (we can ask how may and change the while-condition)
while (user_number <= 100)
{
//Now we read R and Y from theirs files (-1 because I will remove the chosen user from the matrixes)
double[,] Y = new double[num_jobs_init, num_users_init - 1];
double[,] R = new double[num_jobs_init, num_users_init - 1];
// Movie rating file for a user
double[,] my_ratings = new double[num_jobs_init, 1];
//reading Y_training
using (TextReader readerY = File.OpenText("C:/Users/larissaf/Desktop/files/Y.txt"))
{
int i = 0;
string line = readerY.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
int k = 0;
for (int j = 0; j < num_users_init; j++)
{
if (j != (user_number - 1))
{
Y[i, k] = Convert.ToDouble(temp[j]);
k++;
}
else
my_ratings[i, 0] = Convert.ToDouble(temp[j]);
}
line = readerY.ReadLine();
i++;
}
readerY.Close();
}
//reading R_training
using (TextReader readerR = File.OpenText("C:/Users/larissaf/Desktop/files/R.txt"))
{
int i = 0;
string line = readerR.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
int k = 0;
for (int j = 0; j < num_users_init; j++)
{
if (j != (user_number - 1))
{
R[i, k] = Convert.ToDouble(temp[j]);
k++;
}
}
line = readerR.ReadLine();
i++;
}
readerR.Close();
}
//reading X to get the number of features
using (TextReader readerX = File.OpenText("C:/Users/larissaf/Desktop/files/X.txt"))
{
num_features = 0;
string line = readerX.ReadLine();
if (line != null)
{
string[] temp = line.Split('\t');
num_features = temp.Length;
}
readerX.Close();
}
//allocating the X matriz
double[,] X = new double[num_jobs_init, num_features];
//reading X_training
using (TextReader readerX = File.OpenText("C:/Users/larissaf/Desktop/files/X.txt"))
{
int i = 0;
string line = readerX.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < num_features; j++)
{
X[i, j] = Convert.ToDouble(temp[j]);
}
line = readerX.ReadLine();
i++;
}
readerX.Close();
}
/*
using (TextReader reader_movies_ratings = File.OpenText("C:/Users/larissaf/Desktop/files/one_user_rating.txt"))
{
int i = 0;
string line = reader_movies_ratings.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
my_ratings[Convert.ToInt32(temp[0]) - 1, 0] = Convert.ToInt32(temp[1]);
line = reader_movies_ratings.ReadLine();
i++;
}
reader_movies_ratings.Close();
}*/
// Job names
string[] job_list = new string[num_jobs_init];
using (TextReader reader_movie_list = File.OpenText("C:/Users/larissaf/Desktop/files/job_names.txt"))
{
string line = reader_movie_list.ReadLine();
int i = 0;
while (line != null)
{
job_list[i] = line;
line = reader_movie_list.ReadLine();
i++;
}
reader_movie_list.Close();
}
////////////////////////////////////////////Matlab calculations///////////////////////////////////////////
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
//this is used to do not show the matlab window
//matlab.Visible = 0;
// Change to the directory where the functions are located --- always use the desktop to make tests to avoid problems with pathway
matlab.Execute(@"cd C:\Users\larissaf\Desktop\files");
// Define the output to print the final result
object result_movies_search = null;
matlab.Execute("my_ratings");
// Movie erecommendations script
matlab.Feval("scriptGeneration", 6, out result_movies_search, my_ratings, job_list, Y, R, X, num_features);
object[] res = result_movies_search as object[];
int len = ((double[,])res[0]).Length;
//for each one of the users, we will have a list containg all the comparassions between the top ten jobs for him, and
//the other jobs (that had similarity >= 70%)
List<MyData> mylist = new List<MyData>();
MyData aux;
for (int i = 0; i < len; i++)
{
//adding a new element in the list for each user.
aux = new MyData(job_list[(int)(((double[,])res[0])[i, 0]) - 1], (((double[,])res[1])[i, 0]), job_list[(int)(((double[,])res[2])[i, 0]) - 1], (((double[,])res[3])[i, 0]), (((double[,])res[4])[i, 0]));
mylist.Add(aux);
writetext.Write(job_list[(int)(((double[,])res[0])[i, 0]) - 1] + "\t");
writetext.Write((((double[,])res[1])[i, 0]) + "\t");
writetext.Write(job_list[(int)(((double[,])res[2])[i, 0]) - 1] + "\t");
writetext.Write((((double[,])res[3])[i, 0]) + "\t");
writetext.Write((((double[,])res[4])[i, 0]) + "\t");
writetext.Write(user_number + "\n");
}
//adding the list at the Dictionary for each user
finalList.Add(user_number, mylist);
user_number++;
} // while ends
writetext.Close();
//creating a instance of an object for user 1: (maybe send null)
dataResult avgs = new dataResult(null, 10);
avgs.WriteInAFile(finalList);
Console.WriteLine("DONE");
// Wait until fisnih
Console.ReadLine();
}
protected void plot(LinkedList<double> ds)
{
MLApp.MLApp matlab = new MLApp.MLApp();
System.Array pr = new double[ds.Count+1];
System.Array pi = new double[ds.Count+1];
int i = 0;
foreach (double d in ds)
{
pr.SetValue(d, i);
i++;
pi.SetValue(i, i);
}
matlab.PutFullMatrix("plottable", "base", pi, pr);
matlab.Execute("plot(plottable)");
}
private void Interanl_Learn(ImageVector[] goodImages, ImageVector[] badImages, int[] subsetFilesTrue, int[] subsetFilesFalse)
{
string csvPathLearn = userPath + "\\Learn.txt";
System.IO.StreamWriter fileLearn = new System.IO.StreamWriter(@csvPathLearn, false);
for (int index = 0; index < subsetFilesTrue.Length; index++)
{
fileLearn.WriteLine(goodImages[subsetFilesTrue[index]].getAllParameters(true));
}
for (int index = 0; index < subsetFilesFalse.Length; index++)
{
fileLearn.WriteLine(badImages[subsetFilesFalse[index]].getAllParameters(false));
}
fileLearn.Close();
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
matlab.Execute(cd);
//TODO: choose only the algo u need...
matlab.Execute("albumLearnPoly5('" + userPath + "');");
matlab.Execute("albumLearnPolyTen('" + userPath + "');");
matlab.Execute("albumLearnPolyTenFive('" + userPath + "');");
matlab.Execute("albumLearnQuadratic('" + userPath + "');");
matlab.Execute("albumLearnRbf1('" + userPath + "');");
matlab.Execute("albumLearnRbf3('" + userPath + "');");
matlab.Execute("albumLearnRbf5('" + userPath + "');");
}
private string Internal_Decide(ImageVector[] filesTrue, ImageVector[] filesFalse, int algo)
{
int trueAndSelected = 0;
int FalseAndNotSelected = 0;
int trueButNotSelected = 0;
int falseButSelected = 0;
string data;
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
matlab.Execute(cd);
for (int i = 0; i < filesTrue.Length; i++)
{
if (Internal_DecideImage(matlab, filesTrue[i], algo))
trueAndSelected++;
else
trueButNotSelected++;
}
for (int i = 0; i < filesFalse.Length; i++)
{
if (Internal_DecideImage(matlab, filesFalse[i], algo))
falseButSelected++;
else
FalseAndNotSelected++;
}
data = trueAndSelected + "," + trueButNotSelected + "," + falseButSelected + "," + FalseAndNotSelected;
return data;
}
static void Main(string[] args)
{
//////////////////////////////////////////////////////////////////// Loading files /////////////////////////////////////////////////////////////////////
// Variables used in matlab
//double lambda = 1.5;
double num_users = 4;
double num_movies = 5;
double num_features = 3;
// Generate data according with the logic express in Matlab
double[,] X = new double[(int)num_movies, (int)num_features];
double[,] Y = new double[(int)num_movies, (int)num_users];
double[,] Theta = new double[(int)num_users, (int)num_features];
double[,] R = new double[(int)num_movies, (int)num_users];
//filling out the matrix X
using (TextReader readerX = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/data_x.txt"))
{
int i = 0;
string line = readerX.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < (int)num_features; j++)
{
//Console.Write(temp[j - 1]);
X[i, j] = Convert.ToDouble(temp[j]);
}
line = readerX.ReadLine();
i++;
}
readerX.Close();
}
//filling out the matrix Y
using (TextReader readerY = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/data_y.txt"))
{
int i = 0;
string line = readerY.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < (int)num_users; j++)
{
//Console.Write(temp[j - 1]);
Y[i, j] = Convert.ToDouble(temp[j]);
}
line = readerY.ReadLine();
i++;
}
readerY.Close();
}
// Filling out the matrix theta
using (TextReader readerTheta = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/data_theta.txt"))
{
int i = 0;
string line = readerTheta.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < (int)num_features; j++)
{
//Console.Write(temp[j - 1]);
Theta[i, j] = Convert.ToDouble(temp[j]);
}
line = readerTheta.ReadLine();
i++;
}
readerTheta.Close();
}
// Filling out the matrix theta
using (TextReader readerR = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/data_r.txt"))
{
int i = 0;
string line = readerR.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
for (int j = 0; j < (int)num_users; j++)
{
//Console.Write(temp[j - 1]);
R[i, j] = Convert.ToDouble(temp[j]);
}
line = readerR.ReadLine();
i++;
}
readerR.Close();
}
//Reading the file to get the size of lines and columns of R and Y, which will be used in training colloborative filtering
int num_movies_init;
int num_users_init;
using (TextReader readerSize = File.OpenText("C:/Users/laerte/Desktop/Y_training.txt"))
{
num_movies_init = 0;
string line = readerSize.ReadLine();
string[] temp = line.Split('\t');
num_users_init = temp.Length;
while (line != null)
{
line = readerSize.ReadLine();
num_movies_init++;
}
readerSize.Close();
}
//Now we read R and Y from theirs files
double[,] Y_training = new double[num_movies_init, num_users_init];
double[,] R_training = new double[num_movies_init, num_users_init];
//reading Y_training
using (TextReader readerY = File.OpenText("C:/Users/laerte/Desktop/Y_training.txt"))
{
int i = 0;
string line = readerY.ReadLine();
string[] temp = line.Split('\t');
while (line != null)
{
for (int j = 0; j < num_users_init; j++)
{
Y_training[i, j] = Convert.ToDouble(temp[j]);
}
line = readerY.ReadLine();
i++;
}
readerY.Close();
}
//reading R_training
using (TextReader readerR = File.OpenText("C:/Users/laerte/Desktop/R_training.txt"))
{
int i = 0;
string line = readerR.ReadLine();
string[] temp = line.Split('\t');
while (line != null)
{
for (int j = 0; j < num_users_init; j++)
{
R_training[i, j] = Convert.ToDouble(temp[j]);
}
line = readerR.ReadLine();
i++;
}
readerR.Close();
}
// Movie rating file for a user X
double[,] my_ratings = new double[num_movies_init, 1];
// make sure that the data will be zero for all the other positions
Array.Clear(my_ratings, 0, num_movies_init);
using (TextReader reader_movies_ratings = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/movies_ratings.txt"))
{
int i = 0;
string line = reader_movies_ratings.ReadLine();
while (line != null)
{
string[] temp = line.Split('\t');
my_ratings[Convert.ToInt32(temp[0]) - 1, 0] = Convert.ToInt32(temp[1]);
line = reader_movies_ratings.ReadLine();
i++;
}
reader_movies_ratings.Close();
}
// Movie list file for a user X
string[] movie_list = new string[num_movies_init];
using (TextReader reader_movie_list = File.OpenText("C:/Users/laerte/Documents/GitHub/ummatlab/Recommender systems/Data/movie_ids.txt"))
{
string line = reader_movie_list.ReadLine();
int i = 0;
while (line != null)
{
line = line.Replace((i + 1).ToString() + " ", "");
movie_list[i] = line;
line = reader_movie_list.ReadLine();
i++;
}
reader_movie_list.Close();
}
/////////////////////////////////////////////////////////////////////// Matlab calculations /////////////////////////////////////////////////////////////////////
// Create the MATLAB instance
MLApp.MLApp matlab = new MLApp.MLApp();
// Change to the directory where the functions are located --- always use the desktop to make tests to avoid problems with pathway
matlab.Execute(@"cd C:\Users\laerte\Desktop");
// Calling a function to calculate the parameters to send it to cofiCostFunc
object parameters = null;
matlab.Feval("generateParams", 1, out parameters, X, Theta);
object[] par = parameters as object[];
// Define the output to print the final result for CofiCostFunc
//object result = null;
// Call the MATLAB function myfunc
matlab.Execute("clear all");
// Execute the function in Matlab function to check J
// matlab.Feval("cofiCostFunc", 2, out result, (par[0]), Y, R, num_users, num_movies, num_features, lambda);
// Checking the gradients
//object check = null;
//matlab.Feval("checkCostFunction", 0, out check, lambda);
// Display result [cost, grad] = costFunctionReg(initial_theta, X, y, lambda);
//object[] res = result as object[];
// Print J and grad from CofiCostFunc, which are the returned by this function --- I will commment this part
Console.WriteLine("Go to Matlab to do the interactions...");
/*
Console.WriteLine("Computing the cost J = " + res[0]);
int len = ((double[,])(res[1])).Length;
for (int n=0; n < len; n++)
{
Console.WriteLine("grad = " +((double[,])res[1])[n,0]);
}
*/
// Define the output to print the final result
object result_movies_search = null;
// Movie recommendations script
matlab.Feval("scriptGeneration", 1, out result_movies_search, my_ratings, movie_list, Y_training, R_training);
// Wait until fisnih
Console.Write("Presse ENTER to close the window");
Console.ReadLine();
// Closing the matblab window
//matlab.Quit();
}
public override IOperation Apply() {
lock (locker) {
var initializationScript = MatlabInitializationScriptParameter.ActualValue;
if (!string.IsNullOrEmpty(initializationScript.Value) && !initializationScript.Exists())
throw new FileNotFoundException(string.Format("The initialization script \"{0}\" cannot be found.", initializationScript.Value));
var evaluationScript = MatlabEvaluationScriptParameter.ActualValue;
if (string.IsNullOrEmpty(evaluationScript.Value))
throw new FileNotFoundException("The evaluation script in the problem is not set.");
if (!evaluationScript.Exists())
throw new FileNotFoundException(string.Format("The evaluation script \"{0}\" cannot be found.", evaluationScript.Value));
string result;
if (matLabConnector == null) {
Type matlabtype = Type.GetTypeFromProgID("matlab.application.single");
matLabConnector = (MLApp.MLApp)Activator.CreateInstance(matlabtype);
matLabConnector.Visible = 0;
if (!string.IsNullOrEmpty(initializationScript.Value)) {
var directoryName = Path.GetDirectoryName(initializationScript.Value);
if (string.IsNullOrEmpty(directoryName)) directoryName = Environment.CurrentDirectory;
result = matLabConnector.Execute(string.Format("cd '{0}'", directoryName));
if (!string.IsNullOrEmpty(result)) throw new InvalidOperationException(result);
result = matLabConnector.Execute(Path.GetFileNameWithoutExtension(initializationScript.Value));
if (!string.IsNullOrEmpty(result)) throw new InvalidOperationException(result);
}
}
if (!changedDirectory) {
var directoryName = Path.GetDirectoryName(evaluationScript.Value);
if (string.IsNullOrEmpty(directoryName)) directoryName = Environment.CurrentDirectory;
result = matLabConnector.Execute(string.Format("cd '{0}'", directoryName));
if (!string.IsNullOrEmpty(result)) throw new InvalidOperationException(result);
changedDirectory = true;
}
var parameterVector = ParameterVectorParameter.ActualValue;
var parameterNames = ParameterNamesParameter.ActualValue;
for (int i = 0; i < ProblemSizeParameter.ActualValue.Value; i++) {
matLabConnector.PutWorkspaceData(parameterNames[i], "base", parameterVector[i]);
}
result = matLabConnector.Execute(Path.GetFileNameWithoutExtension(evaluationScript.Value));
if (!string.IsNullOrEmpty(result)) throw new InvalidOperationException(result);
string qualityVariableName = QualityVariableParameter.ActualValue.Value;
var quality = matLabConnector.GetVariable(qualityVariableName, "base");
if (double.IsNaN(quality)) quality = double.MaxValue;
if (double.IsInfinity(quality)) quality = double.MaxValue;
QualityParameter.ActualValue = new DoubleValue(quality);
return base.Apply();
}
}
// Protected implementation of Dispose pattern.
protected virtual void Dispose(bool disposing)
{
if (disposed)
return;
if (disposing)
{
// Free any other managed objects here.
//
matlab.Quit();
matlab = null;
}
// Free any unmanaged objects here.
//
disposed = true;
}
/*unused variables for poorly timed autofocus method
static private long currentSum;
static private long prevSum;
static private long locMaxSum;
static Bitmap bmp;*/
static int initialize()
{
try
{
CameraHandler = new SDKHandler();
CameraHandler.LiveViewUpdated += new SDKHandler.StreamUpdate(SDK_LiveViewUpdated);
CameraHandler.CameraHasShutdown += SDK_CameraHasShutdown;
CameraHandler.SDKObjectEvent += handler_SDKObjectEvent;
List<Camera> cameras = CameraHandler.GetCameraList();
Console.WriteLine("List of connected camers:");
foreach (Camera cam in cameras)
{
Console.WriteLine(cam.Info.szDeviceDescription);
}
if (cameras.Count > 0)
{
CameraHandler.OpenSession(cameras[0]);
Console.WriteLine("Opened session with camera: " + cameras[0].Info.szDeviceDescription);
}
else
{
Console.WriteLine("No camera found. Please plug in camera");
CameraHandler.CameraAdded += handler_CameraAdded;
CallEvent();
}
CameraHandler.ImageSaveDirectory = System.IO.Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.MyPictures), "RemotePhoto");
CameraHandler.SetSetting(EDSDK.PropID_SaveTo, (uint)EDSDK.EdsSaveTo.Host);
//create a buffer in memory to capture images
uint memory_alloc_error = EDSDK.EdsCreateMemoryStream(buffer_size, out frame_stream);
img_array = new int[1, 1];
matlab = new MLApp.MLApp();
}
catch (Exception ex)
{
Console.WriteLine("Error: " + ex.Message);
return 0;
}
//MTB Initiailization Protocol
INIT:
try
{
m_MTBConnection = new MTBConnection(); //establish a connection to the MTB server
}
catch (Exception e)
{
Console.WriteLine(e.Message);
Console.WriteLine("Try again?(y/n): "); //connection unsuccessful
string command = Console.ReadLine();
switch (command)
{
case "y":
goto INIT;
default:
return 0;
}
}
// no ID yet
m_ID = "";
// create event sink helper class for base events
baseEvents = new MTBBaseEventSink();
// connect event handler with helper class
baseEvents.MTBErrorEvent += new MTBBaseErrorHandler(OnMtbError);
return 1;
}
static void initialize()
{
try
{
CameraHandler = new SDKHandler();
CameraHandler.LiveViewUpdated += new SDKHandler.StreamUpdate(SDK_LiveViewUpdated);
CameraHandler.CameraHasShutdown += SDK_CameraHasShutdown;
CameraHandler.SDKObjectEvent += handler_SDKObjectEvent;
List<Camera> cameras = CameraHandler.GetCameraList();
Console.WriteLine("List of connected camers:");
foreach (Camera cam in cameras)
{
Console.WriteLine(cam.Info.szDeviceDescription);
}
if (cameras.Count > 0)
{
CameraHandler.OpenSession(cameras[0]);
Console.WriteLine("Opened session with camera: " + cameras[0].Info.szDeviceDescription);
}
else
{
Console.WriteLine("No camera found. Please plug in camera");
CameraHandler.CameraAdded += handler_CameraAdded;
CallEvent();
}
CameraHandler.ImageSaveDirectory = System.IO.Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.MyPictures), "RemotePhoto");
CameraHandler.SetSetting(EDSDK.PropID_SaveTo, (uint)EDSDK.EdsSaveTo.Host);
//create a buffer in memory to capture images
uint memory_alloc_error = EDSDK.EdsCreateMemoryStream(buffer_size, out frame_stream);
img_array = new int[1,1];
matlab = new MLApp.MLApp();
/*
Console.WriteLine("Taking photo with current settings...");
CameraHandler.TakePhoto();
CallEvent();
Console.WriteLine("Photo taken and saved");
*/
}
catch (Exception ex) { Console.WriteLine("Error: " + ex.Message); }
}
public bool Learn()
{
// Get list of files in folders
string[] filesAll = Testing.GetFilesFromDirectory(allPath).ToArray();
string[] filesTrue = Testing.GetFilesFromDirectory(truePath).ToArray();
if (filesAll.Length <= 0 || filesTrue.Length <= 0)
return false;
// Make False vector list - All the files in all that are not in true.
int index = 0;
string[] filesFalse = new string[filesAll.Length - filesTrue.Length];
bool exist;
string fn_all, fn_true;
for (int i = 0; i < filesAll.Length; i++)
{
fn_all = filesAll[i].Substring(filesAll[i].LastIndexOf("\\") + 1);
exist = false;
for (int j = 0; j < filesTrue.Length; j++)
{
fn_true = filesTrue[j].Substring(filesTrue[j].LastIndexOf("\\") + 1);
if (fn_true.Equals(fn_all))
{
exist = true;
break;
}
}
if (exist)
continue;
filesFalse[index++] = filesAll[i];
}
string csvPath = userPath + "\\Learn.txt";
System.IO.StreamWriter file = new System.IO.StreamWriter(@csvPath, true);
// Convert to vector List
foreach (string path in filesTrue)
{
ImageVector vec = new ImageVector(path, null);
file.WriteLine(vec.getAllParameters(true));
}
foreach (string path in filesFalse)
{
ImageVector vec = new ImageVector(path, null);
file.WriteLine(vec.getAllParameters(false));
}
file.Close();
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Users\\anoach\\Desktop\\papa_matlab";
string exe = "albumLearn('" + userPath + "');";
matlab.Execute(cd);
matlab.Execute(exe);
return true;
}
// Start Matlab.
/// <summary>
/// Starts with Program, either connects to COM-Enabled Matlab or starts a Matlab File.
/// </summary>
/// <remarks> The call "enableservice('AutomationServer',true);" COM-enables Matlab and ensures it doesn't close with the program.</remarks>
public static void MatlabStartup()
{
// Matlab Startup and Connection to Desktop
Type MatlabType = Type.GetTypeFromProgID("Matlab.Desktop.Application");
try
{
//To make sure COM enabled for running Matlab
//Connect to an open Matlab
// Execute = enableservice('AutomationServer',true);
matlab = (MLApp.MLApp)Marshal.GetActiveObject("Matlab.Desktop.Application");
}
catch (System.Runtime.InteropServices.COMException ex1)
{
try
{
//Open Matlab program
matlab = (MLApp.MLApp)Activator.CreateInstance(MatlabType);
//IMPORTANT: Stops exiting from Matlab when program closes
matlab.Execute("enableservice('AutomationServer',true);");
}
catch (System.Runtime.InteropServices.COMException ex2)
{
// Matlab not on computer.
}
}
}
private string Internal_Decide(ImageVector[] filesTrue, ImageVector[] filesFalse, int algo)
{
int trueAndSelected = 0;
int FalseAndNotSelected = 0;
int trueButNotSelected = 0;
int falseButSelected = 0;
string data;
MLApp.MLApp matlab = new MLApp.MLApp();
string cd = "cd C:\\Program Files\\MATLAB\\R2013a\\bin";
matlab.Execute(cd);
for (int i = 0; i < filesTrue.Length; i++)
{
if (Internal_DecideImage(matlab, filesTrue[i], algo))
trueAndSelected++;
else
trueButNotSelected++;
}
for (int i = 0; i < filesFalse.Length; i++)
{
if (Internal_DecideImage(matlab, filesFalse[i], algo))
falseButSelected++;
else
FalseAndNotSelected++;
}
data = trueAndSelected + "," + trueButNotSelected + "," + falseButSelected + "," + FalseAndNotSelected;
return data;
}
/// <summary>
/// Send a array of strings to Matlab.
/// </summary>
/// <param name="varName"> The unique variable name.</param>
/// <param name="strInput"> Passed Array of Data.</param>
/// <exception cref="System.RunTime.InteropServices.COMException"> Thrown when matlab is closed and no connection.</exception>
public static void sendDataToMatlab(string varName, string[] strInput)
{
try
{
matlab.PutWorkspaceData(varName, "base", strInput); // varname, workspace, values
}
catch (System.Runtime.InteropServices.COMException ex)
{
matlab = null;
}
}
/// <summary>
/// Start the MATLAB COM Automation Server via a BackgroundWorker.
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
void matlabStarter_DoWork(object sender, DoWorkEventArgs e)
{
Instance = new MLApp.MLApp();
}
