public override void MakeMatlabSimulinkModelFile(string outputfile, string original = "")
{
if (original == "")
{
original = DefaultOriginalSimulinkModelFile;
}
String id_values = "[";
String psid_values = "[";
var results = Results as PM_MMAnalysisResults;
var sortedResultsById = results.ListResults.OrderBy(r => r.FluxLinkage_dq.d).ToArray();
foreach (var item in sortedResultsById)
{
id_values += item.Idq.d + " ";
psid_values += item.FluxLinkage_dq.d + " ";
}
id_values += "]";
psid_values += "]";
String iq_values = "[";
String psiq_values = "[";
var sortedResultsByIq = results.ListResults.OrderBy(r => r.FluxLinkage_dq.q).ToArray();
foreach (var item in sortedResultsByIq)
{
iq_values += item.Idq.q + " ";
psiq_values += item.FluxLinkage_dq.q + " ";
}
iq_values += "]";
psiq_values += "]";
MATLAB ml = MATLAB.DefaultInstance;
String pathtomodel = Path.GetDirectoryName(original);
String modelname = Path.GetFileNameWithoutExtension(original);
String pathtoblock = modelname + "/PMSM";
ml.ChangeWorkingFolder(pathtomodel);
ml.load_system(modelname);
// set values
ml.set_param(pathtoblock, "id_values", id_values);
ml.set_param(pathtoblock, "iq_values", iq_values);
ml.set_param(pathtoblock, "psid_values", psid_values);
ml.set_param(pathtoblock, "psiq_values", psiq_values);
ml.set_param(pathtoblock, "R", results.PhaseResistance.ToString());
ml.set_param(pathtoblock, "pp", results.Analyser.Motor.Rotor.p.ToString());
String outputpath = Path.GetDirectoryName(outputfile);
String outputname = Path.GetFileNameWithoutExtension(outputfile);
ml.ChangeWorkingFolder(outputpath);
ml.save_system(modelname, outputname); //save as new name
ml.close_system(outputname); //close it
ml.Quit();
}
public static void Run(IEnumerable <string> args)
{
if (args.Count() != 1)
{
Console.WriteLine("Usage: AnnLab <nRuns>");
return;
}
int nRuns = int.Parse(args.First());
if (nRuns < 0)
{
Console.WriteLine("Usage: AnnLab <nRuns>");
return;
}
int[] possibleN = { 100, 200 };
int[] possibleP = { 10, 20, 30, 40, 50, 75, 100, 150, 200 };
var jobs = possibleN.SelectMany(N => possibleP.Select(p => new JobDescription {
N = N, p = p
}));
var runs = Enumerable.Repeat(jobs, nRuns).SelectMany(x => x);
TotalJobs = runs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = runs.AsParallel().Select(RunJob).ToList();
var resByJob = results
.GroupBy(res => Tuple.Create(res.Job.p, res.Job.N));
var avgByJob = resByJob.Select(byJob => Tuple.Create(byJob.Key.Item1 / (double)byJob.Key.Item2,
byJob.Key,
byJob.Average(res => res.AverageErrorRate)))
.OrderBy(byJob => byJob.Item1);
string fileStr = nRuns + "_" + DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
string filename = "result_" + fileStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew), Encoding.ASCII))
{
foreach (var avg in avgByJob)
{
sw.WriteLine(avg.Item1.ToString(CultureInfo.InvariantCulture) + " " + avg.Item3.ToString(CultureInfo.InvariantCulture) + " " + avg.Item2.Item1 + " " + avg.Item2.Item2);
}
}
string errorLog = "result_matlab_" + fileStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task1Grapher", "'" + filename + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
#if DEBUG
args = new List <string> {
"60000"
};
#endif
if (args.Count() < 1)
{
Console.WriteLine("Must specify nRuns");
return;
}
if (args.Count() > 2)
{
Console.WriteLine("Too many arguments");
return;
}
int nRuns = int.Parse(args.First());
if (nRuns < 0)
{
Console.WriteLine("nRuns can't be negative");
return;
}
int qSteps = 100;
if (args.Count() == 2)
{
qSteps = int.Parse(args.Last());
if (qSteps < 1)
{
Console.WriteLine("qSteps can't be zero or negative");
return;
}
}
var qs = Enumerable.Range(0, qSteps).Select(step => step * 1d / (qSteps - 1));
Matrix <double> W = Task1.InitWeights(160, DIGITS);
var jobs = qs.Select(q => new JobDescription {
q = q, W = W
});
var runs = Enumerable.Repeat(jobs, nRuns).SelectMany(x => x);
TotalJobs = runs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = runs.AsParallel().Select(RunJob).ToList();
var resByJob = results.GroupBy(res => res.q);
var avgByJobByDigit = AggregateThrowsStackOverflowExceptionWorkaround(resByJob, nRuns);
var avgByJob = resByJob.Select(byJob => Tuple.Create(byJob.Key,
avgByJobByDigit[byJob.Key],
/* Throws StackOverflowException when nRuns is somewhat large,
* avgByJobByDigit is a "manual" implementation that works
* byJob.Select(res => res.Corrects)
* .Aggregate(Enumerable.Repeat(0, DIGITS.Length), (acc, next) => acc.Zip(next, (a, b) => b ? a + 1 : a))
* .Select(avg => avg / (double)nRuns),*/
byJob.Average(res => res.AverageCorrectRate)))
.OrderBy(avg => avg.Item1);
string fileStr = nRuns + "_" + qSteps + "_" + DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
string filename = "task2_" + fileStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew), Encoding.ASCII))
{
foreach (var avg in avgByJob)
{
sw.Write(avg.Item1.ToString(CultureInfo.InvariantCulture));
foreach (var dig in avg.Item2)
{
sw.Write(" " + dig.ToString(CultureInfo.InvariantCulture));
}
sw.WriteLine(" " + avg.Item3.ToString(CultureInfo.InvariantCulture));
}
}
string errorLog = "task2_" + fileStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task2Grapher", "'" + filename + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
#if DEBUG
args = new List <string> {
"100"
};
#endif
if (args.Count() != 1)
{
Console.WriteLine("Usage: lab2.task1 <sigma_0>");
return;
}
double sigma0 = int.Parse(args.First());
if (sigma0 < 1)
{
Console.WriteLine("sigma_0 must be larger than 0");
return;
}
double n0 = 0.1;
int T = 200;
double sigmaconv = 0.9;
double nconv = 0.01;
int iters_order = (int)1E3, iters_conv = (int)5E4;
string dateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
string fileStr = sigma0 + "_" + dateStr;
TotalJobs = iters_order + iters_conv;
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
//Matrix<double> input = GenerateTriangleInput(1000, 1, 0, 0.5, 1);
Matrix <double> input = GenerateCircleInput(1000);
Matrix <double> weights = new Matrix <double>(100, 2);
Random rng = new Random();
for (int i = 0; i < weights.Rows; i++)
{
for (int j = 0; j < weights.Cols; j++)
{
weights[i, j] = rng.NextDouble();
}
}
double[] hood = new double[weights.Rows];
// ordering phase
for (int t = 0; t < iters_order; t++)
{
int target = rng.Next(input.Rows);
int bmu = BMU(input, weights, target);
double sigma = NeighbourhoodWidth(t, T, sigma0);
double learningRate = LearningRate(t, T, n0);
Neighbourhood(hood, bmu, sigma);
for (int i = 0; i < weights.Rows; i++)
{
weights[i, 0] += hood[i] * learningRate * (input[target, 0] - weights[i, 0]);
weights[i, 1] += hood[i] * learningRate * (input[target, 1] - weights[i, 1]);
}
JobsCompleted++;
}
string filename = "lab2task1_ordering_" + fileStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew)))
{
for (int i = 0; i < weights.Rows; i++)
{
sw.WriteLine(weights[i, 0].ToString(CultureInfo.InvariantCulture) + ", " + weights[i, 1].ToString(CultureInfo.InvariantCulture));
}
}
// convergance phase
double[][] hoods = new double[input.Rows][];
for (int t = 0; t < iters_conv; t++)
{
int target = rng.Next(input.Rows);
int bmu = BMU(input, weights, target);
if (hoods[bmu] == null)
{
Neighbourhood(hoods[bmu] = new double[weights.Rows], bmu, sigmaconv);
}
for (int i = 0; i < weights.Rows; i++)
{
weights[i, 0] += hoods[bmu][i] * nconv * (input[target, 0] - weights[i, 0]);
weights[i, 1] += hoods[bmu][i] * nconv * (input[target, 1] - weights[i, 1]);
}
JobsCompleted++;
}
filename = "lab2task1_convergance_" + fileStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.Create)))
{
for (int i = 0; i < weights.Rows; i++)
{
sw.WriteLine(weights[i, 0].ToString(CultureInfo.InvariantCulture) + ", " + weights[i, 1].ToString(CultureInfo.InvariantCulture));
}
}
filename = "lab2task1_input_" + fileStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew)))
{
for (int i = 0; i < input.Rows; i++)
{
sw.WriteLine(input[i, 0].ToString(CultureInfo.InvariantCulture) + ", " + input[i, 1].ToString(CultureInfo.InvariantCulture));
}
}
string errorLog = "lab2task1_matlab_" + fileStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Lab2Task1InputGrapher", "'lab2task1_%s_%d_" + dateStr + ".txt'", sigma0.ToString()))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
#if DEBUG
args = new List <string> {
"2"
};
#endif
if (!args.Any())
{
Console.WriteLine("Usage: task3 <nRuns> <aSteps>");
return;
}
if (args.Count() > 2)
{
Console.WriteLine("Too many arguments");
return;
}
int nRuns = int.Parse(args.First());
if (nRuns < 0)
{
Console.WriteLine("nRuns can't be negative");
return;
}
int aSteps = 50;
if (args.Count() == 2)
{
aSteps = int.Parse(args.Last());
if (aSteps < 1)
{
Console.WriteLine("aSteps can't be zero or negative");
return;
}
}
var alphas = Enumerable.Range(1, aSteps).Select(step => step * 1d / aSteps);
var Ns = new int[] { 50, 100, 250, 500 };
double Beta = 2;
foreach (var N in Ns)
{
if (N % aSteps != 0)
{
Console.WriteLine("Invalid aSteps, " + N + " is not divisable with " + aSteps);
return;
}
}
var jobs = alphas.SelectMany(a => Ns.Select(N => new JobDescription {
p = Math.Max(1, (int)(a * N)), N = N, Beta = Beta
}));
var runs = Enumerable.Repeat(jobs, nRuns).SelectMany(x => x);
TotalJobs = runs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = runs.AsParallel().Select(RunJob).ToList();
var byJob = results.GroupBy(res => Tuple.Create(res.Job.p, res.Job.N));
var avgByN = byJob.GroupBy(job => job.Key.Item2, job => Tuple.Create(job.Key.Item1 / (double)job.Key.Item2, job.Average(res => res.m)));
string argStr = nRuns + "_" + aSteps;
string dateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
foreach (var N in avgByN)
{
string filename = "task3_" + argStr + "_" + N.Key + "_" + dateStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew), Encoding.ASCII))
{
foreach (var avg in N.OrderBy(avg => avg.Item1))
{
sw.WriteLine(avg.Item1.ToString(CultureInfo.InvariantCulture) + " " + avg.Item2.ToString(CultureInfo.InvariantCulture));
}
}
}
string errorLog = "task3_" + argStr + "_" + dateStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task3Grapher", "'task3_" + argStr + "_%d_" + dateStr + ".txt'", "[" + string.Join(" ", Ns) + "]"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
if (!args.Any())
{
args = new List <string> {
"1", "20", "5", "20"
}
}
;
if (args.Count() < 2)
{
Console.WriteLine("Usage: lab2.task3 <ost_file> <kLow> <kHigh> <kDumps...>");
return;
}
string ostFile;
int koffset;
if (int.TryParse(args.First(), out koffset))
{
if (args.Count() < 3)
{
Console.WriteLine("Usage: lab2.task3 <ost_file> <kLow> <kHigh> <kDumps...>");
return;
}
ostFile = "C:\\ann\\task3.txt";
koffset = 0;
}
else
{
ostFile = args.First();
koffset = 1;
}
int klow = int.Parse(args.Skip(koffset).First()), khigh = int.Parse(args.Skip(koffset + 1).First());
if (klow < 1)
{
Console.WriteLine("kLow must be larger than 0");
return;
}
if (khigh < klow)
{
Console.WriteLine("kHigh must be larger than kLow");
return;
}
List <int> kDumps = args.Skip(koffset + 2).Select(x => int.Parse(x)).ToList();
int[] ks = Enumerable.Range(klow, khigh - klow + 1).ToArray();
int iters_kohonen = (int)1E5;
double eta_kohonen = 0.02;
int iters_perceptron = 3000;
double beta = 0.5, eta_perceptron = 0.1;
int runsPerJob = 20;
int[][] ostClasses;
Matrix <double> ost = ReadOst(ostFile, out ostClasses);
var jobs = ks.SelectMany(k => Enumerable.Repeat(new JobDescription
{
ost = ost,
ostClasses = ostClasses,
iters_kohonen = iters_kohonen,
iters_perceptron = iters_perceptron,
eta_kohonen = eta_kohonen,
eta_perceptron = eta_perceptron,
beta = beta,
k = k,
}, runsPerJob));
TotalJobs = jobs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = jobs.AsParallel().Select(RunJob).ToList();
var resultsByK = results.GroupBy(res => res.k).OrderBy(byK => byK.Key);
string dateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
string filename = "lab2task3_k_" + dateStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew)))
{
foreach (var res in resultsByK)
{
sw.WriteLine(res.Key + "," + res.Average(r => r.validationErrorRate).ToString(CultureInfo.InvariantCulture));
if (kDumps.Contains(res.Key))
{
string fileStr = res.Key + "_" + dateStr;
var minError = res.OrderBy(r => r.validationErrorRate).First();
string dumpname = "lab2task3_kohonen_" + fileStr + ".txt";
Console.WriteLine("Writing to " + dumpname + "...");
using (StreamWriter sw2 = new StreamWriter(new FileStream(dumpname, FileMode.CreateNew)))
{
for (int i = 0; i < minError.weights.Rows; i++)
{
sw2.WriteLine(minError.weights[i, 0].ToString(CultureInfo.InvariantCulture) + "," + minError.weights[i, 1].ToString(CultureInfo.InvariantCulture));
}
}
BoundaryDump(fileStr, ost, minError.weights, minError.radial, minError.nn);
}
}
}
string errorLog = "lab2task3_" + dateStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Lab2Task3Grapher", "'" + ostFile + "'", "'lab2task3_%s_" + dateStr + ".txt'", "[" + string.Join(" ", kDumps) + "]"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
int nRuns;
if (!Task4a.ParseArgs("task4b", ref args, out nRuns, out Dump))
{
return;
}
DateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
Matrix <double>[][] dataAll;
int[][][] classesAll;
Task4a.ReadNormalizeSplit(out classesAll, out dataAll, args.First(), args.Skip(1).First());
int[][] trainingClasses = classesAll[0], validationClasses = classesAll[1];
Matrix <double>[] trainingData = dataAll[0], validationData = dataAll[1];
double Beta = 0.5;
double learningRate = 0.01;
int[] hiddenNeurons = { 0, 2, 4, 8, 16, 32 };
var jobs = hiddenNeurons.Select(hn => new JobDescription
{
HiddenNeurons = hn,
Beta = Beta,
LearningRate = learningRate,
TrainingData = trainingData,
TrainingClasses = trainingClasses,
ValidationData = validationData,
ValidationClasses = validationClasses
});
var runs = Enumerable.Repeat(jobs, nRuns).SelectMany(x => x);
TotalJobs = runs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = runs.AsParallel().Select(RunJob).ToList();
if (!Dump)
{
var byNeurons = results.GroupBy(res => res.HiddenNeurons).OrderBy(n => n.Key);
string filename = "task4b_" + nRuns + "_" + DateStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew), Encoding.ASCII))
{
foreach (var byNeuron in byNeurons)
{
double trainingErrorRate = byNeuron.Average(res => res.Training);
double validationErrorRate = byNeuron.Average(res => res.Validation);
sw.WriteLine(byNeuron.Key + " " +
trainingErrorRate.ToString(CultureInfo.InvariantCulture) + " " +
validationErrorRate.ToString(CultureInfo.InvariantCulture));
}
}
string errorLog = "task4b_" + nRuns + "_" + DateStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task4bGrapher", "'" + filename + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
}
else
{
string errorRateFile = Directory.EnumerateFiles(Directory.GetCurrentDirectory(), "task4b_*_*.txt")
.Where(file => !file.StartsWith("task4b_dump_"))
.OrderBy(file => file)
.LastOrDefault();
if (errorRateFile == null)
{
Console.WriteLine("Unable to find an error rates file, skipping MATLAB script...");
}
else
{
Console.WriteLine(errorRateFile);
string errorLog = "task4b_dump_" + DateStr + ".log";
string dumpname = "task4b_dump_%d_" + DateStr + ".txt";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task4bExtra", "'" + dumpname + "'", "'" + errorRateFile + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
}
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
double sigma_0 = 30, eta_0 = 0.1, sigma_conv = 0.9, eta_conv = 0.01;
int T_order = (int)1E3, T_conv = (int)2E4, tou = 300;
if (!args.Any())
{
args = new List <string> {
"C:\\ann\\wine.data.txt"
};
}
if (args.Count() > 1)
{
Console.WriteLine("Usage: lab2.task2 <wine_file>");
return;
}
string wineFile = args.First();
int[] wineClasses;
Matrix <double> wine = ReadWine(wineFile, out wineClasses);
NormalizeMeanAndVarInPlace(wine);
double[,,] weights = GenerateRandomWeights();
double[,] hood = new double[20, 20];
Random rng = new Random();
TotalJobs = T_order + T_conv;
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
// ordering phase
for (int t = 0; t < T_order; t++)
{
int wineIndex = rng.Next(wine.Rows);
var bmu = BMU(wine, weights, wineIndex);
Neighbourhood(hood, bmu, Task1.NeighbourhoodWidth(t, tou, sigma_0));
double eta_t = Task1.LearningRate(t, tou, eta_0);
for (int i = 0; i < weights.GetLength(0); i++)
{
for (int j = 0; j < weights.GetLength(1); j++)
{
if (hood[i, j] == 0)
{
continue;
}
for (int k = 0; k < weights.GetLength(2); k++)
{
weights[i, j, k] += hood[i, j] * eta_t * (wine[wineIndex, k] - weights[i, j, k]);
}
}
}
JobsCompleted++;
}
// convergance phase
double[, ][,] hoods = new double[weights.GetLength(0), weights.GetLength(1)][, ];
for (int t = 0; t < T_conv; t++)
{
int wineIndex = rng.Next(wine.Rows);
var bmu = BMU(wine, weights, wineIndex);
double[,] myHood = hoods[bmu.Item1, bmu.Item2];
if (myHood == null)
{
Neighbourhood(hoods[bmu.Item1, bmu.Item2] = myHood = new double[20, 20], bmu, sigma_conv);
}
for (int i = 0; i < weights.GetLength(0); i++)
{
for (int j = 0; j < weights.GetLength(1); j++)
{
for (int k = 0; k < weights.GetLength(2); k++)
{
weights[i, j, k] += myHood[i, j] * eta_conv * (wine[wineIndex, k] - weights[i, j, k]);
}
}
}
JobsCompleted++;
}
// coloring phase
int[,] colors = new int[20, 20];
for (int wineIndex = 0; wineIndex < wine.Rows; wineIndex++)
{
var bmu = BMU(wine, weights, wineIndex);
colors[bmu.Item1, bmu.Item2] = wineClasses[wineIndex];
}
string dateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
string filename = "lab2task2_" + dateStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew)))
{
for (int i = 0; i < colors.GetLength(0); i++)
{
for (int j = 0; j < colors.GetLength(1); j++)
{
sw.WriteLine(i + "," + j + "," + colors[i, j]);
}
}
}
string errorLog = "lab2task2_" + dateStr + ".log";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Lab2Task2Grapher", "'" + filename + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
Console.WriteLine("Done!");
}
public static void Run(IEnumerable <string> args)
{
int nRuns;
if (!ParseArgs("task4a", ref args, out nRuns, out Dump))
{
return;
}
DateStr = DateTime.Now.ToString("yyyy-MM-dd-HH-mm-ss");
Matrix <double>[][] dataAll;
int[][][] classesAll;
ReadNormalizeSplit(out classesAll, out dataAll, args.First(), args.Skip(1).First());
int[][] trainingClasses = classesAll[0], validationClasses = classesAll[1];
Matrix <double>[] trainingData = dataAll[0], validationData = dataAll[1];
int[] Ns = new int[] { 2, 1 };
double Beta = 0.5;
double learningRate = 0.01;
var job = new JobDescription
{
Beta = Beta,
LearningRate = learningRate,
Ns = Ns,
TrainingData = trainingData,
TrainingClasses = trainingClasses,
ValidationData = validationData,
ValidationClasses = validationClasses
};
var runs = Enumerable.Repeat(job, nRuns);
TotalJobs = runs.Count();
Thread progress = new Thread(() => Progress.ProgressFunc(ref TotalJobs, ref JobsCompleted));
progress.Start();
var results = runs.AsParallel().Select(RunJob).ToList();
if (!Dump)
{
double trainingErrorRate = results.Average(res => res.Training);
double validationErrorRate = results.Average(res => res.Validation);
string filename = "task4a_" + nRuns + "_" + DateStr + ".txt";
Console.WriteLine("Writing to " + filename + "...");
using (StreamWriter sw = new StreamWriter(new FileStream(filename, FileMode.CreateNew), Encoding.ASCII))
{
sw.WriteLine("Average training error: " + trainingErrorRate.ToString(CultureInfo.InvariantCulture));
sw.WriteLine("Average validation error: " + validationErrorRate.ToString(CultureInfo.InvariantCulture));
}
}
else
{
string errorLog = "task4a_dump_" + DateStr + ".log";
string dumpname = "task4a_dump_" + DateStr + ".txt";
Console.WriteLine("Executing MATLAB script...");
if (!MATLAB.RunScript(errorLog, "Task4aGrapher", "'" + dumpname + "'"))
{
Console.WriteLine("An error occured while running MATLAB, check the log\n\tLog file:" + errorLog);
}
}
Console.WriteLine("Done!");
}
