public void Create(LaboratoryWorkModel laboratoryWorkModel, string userName, List <IFormFile> files)
{
LaboratoryWork laboratoryWork = _mapper.Map <LaboratoryWork>(laboratoryWorkModel);
laboratoryWork.User = _userService.GetUser(userName);
foreach (var item in files)
{
if (item.Length > 0)
{
var stream = _streamFetcher.GetArray(item);
var file = new File
{
Content = _encoder.Encode(stream),
Name = item.FileName,
LaboratoryWork = laboratoryWork
};
laboratoryWork.Files.Add(file);
}
}
Dictionary <LaboratoryWork, List <Similarity> > similarities = _plagiarismDetector.FindAndSaveSimilarities(laboratoryWork);
decimal plagiarismValue = _plagiarismDetector.CalculatePlagiarism(similarities);
laboratoryWork.Similarity = plagiarismValue;
_unitOfWork.LaboratoryWorkRepository.Insert(laboratoryWork);
_unitOfWork.Save();
}
/// <summary>
/// Конструктор класса, для задания начальных параметров.
/// </summary>
public ClassicOptimizationMethod(Delegate function, Vectors vector)
{
this.function = function;
x = new Vectors(vector);
A = new Matrix(x.Size);
getAlpha = new LaboratoryWork(function, x.Size);
}
public async Task <IActionResult> Create([FromBody] LaboratoryWorkDTO model)
{
var laboratoryWork =
new LaboratoryWork {
TemplateLaboratoryWorkId = model.TemplateLaboratoryWorkId == -1 ? null : model.TemplateLaboratoryWorkId, ThemeId = model.ThemeId, Name = model.Name, Description = model.Description, Evaluation = model.Evaluation, DisciplineCipher = model.DisciplineCipher, UserId = model.UserId, Constraints = model.Constraints
};
// тема ЛР будет перезаписывать тему шаблона
/*if (laboratoryWork.TemplateLaboratoryWorkId != null &&
* laboratoryWork.ThemeId != _db.TemplateLaboratoryWorks.FirstOrDefault(x => x.TemplateLaboratoryWorkId == laboratoryWork.TemplateLaboratoryWorkId).ThemeId)
* {
* return BadRequest("Темы лабораторный работы не принадлежит теме шаблона");
* }*/
try
{
await _db.LaboratoryWorks.AddAsync(laboratoryWork);
await _db.SaveChangesAsync();
}
catch (DbUpdateException e)
{
await Response.WriteAsync(e.InnerException.Message);
return(BadRequest(e.InnerException.Message));
}
return(Ok(model));
}
public async Task <ActionResult <LaboratoryWorkDTO> > PostLaboratoryWork(CreateLaboratoryWorkDTO laboratoryWorkDto)
{
LaboratoryWork newLaboratoryWork = new LaboratoryWork(Guid.NewGuid(), laboratoryWorkDto.Name, new Guid(User.Identity.Name), laboratoryWorkDto.DisciplineId);
try
{
await _context.AddAsync(newLaboratoryWork);
await _context.SaveChangesAsync();
return(newLaboratoryWork.ToLaboratoryWorkDto());
}
catch (Exception ex)
{
_logger.LogError(ex.Message);
return(StatusCode(500));
}
}
protected override bool ComponentPredicate(LaboratoryWork laboratoryWork, string nameComponent) => JsonConvert.DeserializeObject <Constrains>(laboratoryWork.Constraints).Checker == nameComponent;
protected abstract bool ComponentPredicate(LaboratoryWork laboratoryWork, string nameComponent);
private void Сalculate_Click(object sender, EventArgs e)
{
button1_Click(new object(), new EventArgs());
eps = Convert.ToDouble(Fault.Text);
m = Convert.ToInt16(Limitation.Text);
string[] NewPoint; // Значение вектора
if (StartingPoint.Text != "") // Если введено значение для вектора то задать
{
NewPoint = StartingPoint.Text.Split(' ');
for (int i = 0; i < NewPoint.Length; i++)
{
x[i] = Convert.ToDouble(NewPoint[i]);
}
}
LaboratoryWork lab3 = new LaboratoryWork(function, x.Size, maxK, mineps); // Создание класса для поиска альфа
Alpha getAlpha; // Метод одномерного поиска
#region Выбор метода одномерного поиска
switch (DimensionalMethods.SelectedIndex)
{
case 0: getAlpha = lab3.getAlphaBolzanoDavidon; break;
case 1: getAlpha = lab3.getAlphaDihotomy; break;
case 2: getAlpha = lab3.getAlphaZS1; break;
case 3: getAlpha = lab3.getAlphaZS2; break;
case 4: getAlpha = lab3.getAlphaCubic; break;
case 5: getAlpha = lab3.getAlphaPauell; break;
case 6: getAlpha = lab3.getAlphaBolzano; break;
default: getAlpha = null; break;
}
#endregion
startpoint = x; // Вектор хранящий значение стартовых точек
minimum = x; // Вектор хранящий значение минимума
#region Выбор метода многомерного поиска
if (ThemeName.SelectedIndex == 0)
{
switch (MethodName.SelectedIndex)
{
case 0: minimum = NewtonOptimizationMethods.NewtonRaphson(getAlpha); break;
case 1: minimum = NewtonOptimizationMethods.NewtonControlStep(getAlpha); break;
case 2: minimum = NewtonOptimizationMethods.NewtonConstHessian(getAlpha); break;
}
}
if (ThemeName.SelectedIndex == 1)
{
VariableMetricMethods MetricMethod = new VariableMetricMethods();
switch (MethodName.SelectedIndex)
{
case 0: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.DFP); break;
case 1: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.BFSH); break;
case 2: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.BFGSH); break;
case 3: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.MK); break;
case 4: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.Broiden); break;
case 5: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.Pirson_2); break;
case 6: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.Pirson_3); break;
case 7: minimum = MetricMethod.QuasiNewton(getAlpha, MetricMethod.PZ); break;
}
}
if (ThemeName.SelectedIndex == 2)
{
switch (MethodName.SelectedIndex)
{
case 0: minimum = new ConjugateGradientMethods().getOptimize(getAlpha, ConjugateGradientMethods.betaDaniel); break;
case 1: minimum = new ConjugateGradientMethods().getOptimize(getAlpha, ConjugateGradientMethods.betaPhitchersRivers); break;
case 2: minimum = new ConjugateGradientMethods().getOptimize(getAlpha, ConjugateGradientMethods.betaPolakRiber); break;
case 3: minimum = new ConjugateGradientMethods().getOptimize(getAlpha, ConjugateGradientMethods.betaDikson); break;
}
}
#endregion
Result.Text = "Начальная точка: [ " + startpoint.ToString() + " ]" + Environment.NewLine;
Result.Text += "Найденный минимум: [ " + minimum.ToString() + " ]" + Environment.NewLine;
Result.Text += "Количество итераций: " + k;
x = null;
lab3 = null;
}
public Dictionary <LaboratoryWork, List <Similarity> > FindAndSaveSimilarities(LaboratoryWork laboratoryWork)
{
Dictionary <LaboratoryWork, List <Similarity> > laboratorySimilarities = new Dictionary <LaboratoryWork, List <Similarity> >();
foreach (File sourceFile in laboratoryWork.Files)
{
var dmp = new diff_match_patch();
foreach (LaboratoryWork anotherLaboratory in _context.LaboratoryWork.ToList())
{
List <Similarity> similarities = new List <Similarity>();
foreach (File file in anotherLaboratory.Files)
{
var diffs = dmp.diff_main(file.Content, sourceFile.Content);
var countEquals = CountEquals(diffs);
decimal similarity = (countEquals / (decimal)Math.Max(sourceFile.Content.Length, file.Content.Length));
if (similarity >= (decimal)0.6)
{
Similarity s = new Similarity {
SimilarityToId = file.Id, Value = similarity, File = sourceFile
};
sourceFile.Similarities.Add(s);
similarities.Add(s);
}
}
if (!laboratorySimilarities.TryAdd(anotherLaboratory, similarities))
{
similarities.AddRange(laboratorySimilarities[anotherLaboratory]);
laboratorySimilarities[anotherLaboratory] = similarities;
}
}
}
return(laboratorySimilarities);
}
