private void ShowLinearRegressionModel()
{
tabControlMain.SelectedIndex = 0;
string qualityParam = XMLWork.FindNameWithID(_linearEquation.OutputParameter.Id.Value,
Properties.Settings.Default.Languages);
double[] coefficients =
_linearEquation.InputParameters.Select(item => item.Coefficient).ToArray();
string inputParam = XMLWork.FindNameWithID(_linearEquation.InputParameters[1].Id.Value,
Properties.Settings.Default.Languages);
for (int i = 0; i < comboBoxInputParams.Items.Count; i++)
{
if (comboBoxInputParams.Items[i].Equals(inputParam))
{
comboBoxInputParams.SelectedIndex = i;
break;
}
}
for (int i = 0; i < comboBoxQualityParams.Items.Count; i++)
{
if (comboBoxQualityParams.Items[i].Equals(qualityParam))
{
comboBoxQualityParams.SelectedIndex = i;
break;
}
}
labelRMSE.Text = _linearEquation.RMSEString;
checkBoxNormalizeValuesPage1.Checked = _linearEquation.NormalizeValues;
GetLinearRegressionModel(qualityParam, inputParam, false);
}
bool GetLinearRegressionModel(string qualityParam, string inputParam, bool writeModel = true)
{
int inputParameterID = XMLWork.FindIDWithName(inputParam, Properties.Settings.Default.Languages);
int qualityParameterID = XMLWork.FindIDWithName(qualityParam, Properties.Settings.Default.Languages);
try
{
var generalData = (from row in TrainData.Train
select new PointD {
X = (double)row.Input[inputParameterID], Y = (double)row.Output[qualityParameterID]
}).ToList();
if (!generalData.Any(item => Math.Abs(item.X) > DataSensitivityThreshhold && Math.Abs(item.Y) > DataSensitivityThreshhold))
{
throw new Exception("Incorrect input data");
}
DrawMainChart(generalData, writeModel);
DrawErrorsChart(generalData);
return(true);
}
catch (Exception ex)
{
MessageBox.Show($"Error parsing data: \"{ex.Message}\"", "Exception", MessageBoxButtons.OK);
return(false);
}
}
private void ShowMultipleRegressionModel()
{
tabControlMain.SelectedIndex = 2;
string qualityParam = XMLWork.FindNameWithID(_multipleRegressionEquation.OutputParameter.Id.Value,
Properties.Settings.Default.Languages);
double[] coefficients =
_multipleRegressionEquation.InputParameters.Select(item => item.Coefficient).ToArray();
string[] inputParametersToCheck = _multipleRegressionEquation.InputParameters.Skip(1)
.Select(item => XMLWork.FindNameWithID(item.Id.Value, Properties.Settings.Default.Languages)).ToArray();
for (int i = 0; i < comboBoxQualityParametersPage3.Items.Count; i++)
{
if (comboBoxQualityParametersPage3.Items[i].Equals(qualityParam))
{
comboBoxQualityParametersPage3.SelectedIndex = i;
break;
}
}
for (int i = 0; i < checkedListBoxInputParametersToCheckPage3.Items.Count; i++)
{
checkedListBoxInputParametersToCheckPage3.SetItemCheckState(i,
inputParametersToCheck.Contains(checkedListBoxInputParametersToCheckPage3.Items[i])
? CheckState.Checked
: CheckState.Unchecked);
}
labelRMSEPage3.Text = _multipleRegressionEquation.RMSEString;
checkBoxNormalizeValuesPage3.Checked = _multipleRegressionEquation.NormalizeValues;
ShowRegressionEquasion(qualityParam, coefficients);
ShowRegressionEquasionHelp(inputParametersToCheck);
}
private void TrafficLight_Shown(object sender, EventArgs e)
{
var parameters = TrainData.nameParameter.Values.Where(o => o.StartsWith("Def")).ToArray();
foreach (var parameter in parameters)
{
parameterCondition.Items.Add(XMLWork.FindNameWithScada(parameter, Properties.Settings.Default.Languages));
}
if (parameterCondition.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.WithoutDefect);
}
if (parameterCondition.Items.Count != 0)
{
parameterCondition.SelectedIndex = 0;
}
if (ListAdd.Items.Count != 0)
{
ListAdd.SelectedIndex = 0;
}
if (ListDelete.Items.Count != 0)
{
ListDelete.SelectedIndex = 0;
}
if (ListAddError.Items.Count != 0)
{
ListAddError.SelectedIndex = 0;
}
if (ListDeleteError.Items.Count != 0)
{
ListDeleteError.SelectedIndex = 0;
}
}
private void PreprocessToWorkTree()
{
var c45 = new DecisionTreeC45();
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
_root = c45.MountTree(TrainData.Train, TrainData.nameParameter, parameterID, Convert.ToInt32(textEdit1.Value) + 1);
MessageBox.Show(Localization.MyStrings.Over);
}
private void NormalDistribution_Shown(object sender, EventArgs e)
{
name_parametrs = TrainData.nameParameter.Values.Where(o => o.StartsWith("Def")).ToList();// || o.StartsWith("OPC")).ToList();
ListParam.Items.Clear();
foreach (var item in name_parametrs)
{
ListParam.Items.Add(XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages));
}
}
private void simpleButton1_Click_1(object sender, EventArgs e)
{
foreach (OneRow row in TrainData.Train)
{
var point = CalculateShrinkageValue(row.Temperatures.Values.ToArray(), row.Velocities.Values.ToArray());
XMLWork.addShrinkageFile(row.Date, point);
}
MessageBox.Show("Данные об усадке собраны");
}
private void GetPoints(ref decimal pointX, OneRow data, ref decimal pointY)
{
foreach (var item in ListDelete.Items)
{
int parameterID = XMLWork.FindIDWithName(item.ToString(), Properties.Settings.Default.Languages);
pointX = pointX * data.Input[parameterID]; //234 232
}
foreach (var item in ListDeleteError.Items)
{
int parameterID = XMLWork.FindIDWithName(item.ToString(), Properties.Settings.Default.Languages);
pointY = pointY * data.Input[parameterID]; //234 232
}
}
void ShowProcessParameters()
{
string[] input, quality;
input = _inputParams.Select(item => XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages)).ToArray();
quality = _qualityParams.Select(item => XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages)).ToArray();
comboBoxInputParams.Items.Clear();
comboBoxInputParams.Items.AddRange(input);
comboBoxInputParams.SelectedIndex = 0;
comboBoxQualityParams.Items.Clear();
comboBoxQualityParams.Items.AddRange(quality);
comboBoxQualityParams.SelectedIndex = 0;
}
public Kohonen()
{
if (!string.IsNullOrEmpty(Properties.Settings.Default.Languages))
{
System.Threading.Thread.CurrentThread.CurrentUICulture =
System.Globalization.CultureInfo.GetCultureInfo(Properties.Settings.Default.Languages);
System.Threading.Thread.CurrentThread.CurrentCulture =
System.Globalization.CultureInfo.GetCultureInfo(Properties.Settings.Default.Languages);
}
InitializeComponent();
ListAdd.Items.Clear();
ListDelete.Items.Clear();
List <int> keys = new List <int>();
Dictionary <int, decimal> firstRow = TrainData.Train.First().Input;
foreach (OneRow data in TrainData.Train)
{
foreach (var item in data.Input)
{
if (keys.Contains(item.Key))
{
continue;
}
if (item.Key != firstRow[item.Key])
{
keys.Add(item.Key);
}
}
break;
}
var parameters = TrainData.nameParameter.Values.Where(o => o.StartsWith("Def")).ToArray();
foreach (var parameter1 in parameters)
{
ListAdd.Items.Add(XMLWork.FindNameWithScada(parameter1, Properties.Settings.Default.Languages));
}
foreach (int key in keys)
{
ListAdd.Items.Add(XMLWork.FindNameWithID(key, Properties.Settings.Default.Languages));
}
if (ListAdd.Items.Count != 0)
{
ListAdd.SelectedIndex = 0;
}
if (ListDelete.Items.Count != 0)
{
ListDelete.SelectedIndex = 0;
}
}
void ShowParametersOnPage3()
{
if (checkedListBoxInputParametersToCheckPage3.SelectedItems.Count != 0)
{
return;
}
string[] input, quality;
input = _inputParams.Select(item => XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages)).ToArray();
quality = _qualityParams.Select(item => XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages)).ToArray();
comboBoxQualityParametersPage3.Items.Clear();
comboBoxQualityParametersPage3.Items.AddRange(quality);
comboBoxQualityParametersPage3.SelectedIndex = 0;
checkedListBoxInputParametersToCheckPage3.Items.Clear();
checkedListBoxInputParametersToCheckPage3.Items.AddRange(input);
}
private void GetBooleanForOutput(List <OneRow> trainData, decimal criterion)
{
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
foreach (OneRow oneRow in trainData)
{
if (oneRow.Output[parameterID] >= criterion)
{
oneRow.OutputBool[parameterID] = true;
}
else
{
oneRow.OutputBool[parameterID] = false;
}
}
}
private void PreprocessToWorkTreeRandomForest(TrainData trainedData, TrainData checkData,
Dictionary <int, string> analysParameter)
{
int numberOfForest = Convert.ToInt32(numberOfForests.Value);
RandForests = new List <DM.DecisionTree.TreeNode>();
//double accuracy = 0.0;
//do
//{
//Random rand = new Random((int) (DateTime.Now.Ticks));
//DivideSet(rand, trainData, trainedData, checkData);
List <DM.DecisionTree.TreeNode> rndForests = new List <DM.DecisionTree.TreeNode>();
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
int restrictCountOfParameters = Convert.ToInt32(Math.Sqrt(analysParameter.Count)) + 1;
Dictionary <int, string> newParameters = new Dictionary <int, string>();
for (int forestsCount = 0; forestsCount < numberOfForest;)
{
DM.DecisionTree.RandomForest random = new RandomForest();
List <int> parametersName = new List <int>();
foreach (KeyValuePair <int, string> keyValuePair in analysParameter)
{
if (!keyValuePair.Value.StartsWith("Def"))
{
parametersName.Add(keyValuePair.Key);
}
}
for (int i = 0; i < restrictCountOfParameters; i++)
{
int j = rand.Next(0, analysParameter.Count);
if (!newParameters.ContainsKey(parametersName[j]))
{
newParameters.Add(parametersName[j], analysParameter[parametersName[j]]);
}
}
List <OneRow> trainData = new List <OneRow>();
trainData = GetRandomData(TrainData.Train, newParameters, parameterID);
_root = random.MountTree(trainData, newParameters, parameterID, Convert.ToInt32(textEdit1.Value) + 1);
if (_root.attributeName != "False")
{
RandForests.Add(_root);
forestsCount++;
}
newParameters.Clear();
}
}
/// <summary>
/// Calculate Dispersion all parameters
/// </summary>
private void CalculateDispersion()
{
int countElements = 10;
Dictionary <int, decimal> mathematicalExpectation = new Dictionary <int, decimal>();
Dictionary <int, decimal> dispersion = new Dictionary <int, decimal>();
Dictionary <int, decimal> bestValues = new Dictionary <int, decimal>();
ProcessingData.MathematicalExpectation(TrainData.Train, mathematicalExpectation);
ProcessingData.Dispersion(TrainData.Train, mathematicalExpectation, dispersion);
List <FisherCritery> elements = new List <FisherCritery>();
foreach (var @decimal in dispersion)
{
elements.Add(new FisherCritery(@decimal.Key, @decimal.Value));
}
ListOfElements dispoersionElements = new ListOfElements(elements);
dispoersionElements.InsertionSort();
for (int i = 0; i < countElements; i++)
{
bestValues.Add(dispoersionElements.Fisher[i].Key, dispoersionElements.Fisher[i].Value);
}
this.chart2.Series.Clear();
this.chart2.Titles.Clear();
this.chart2.ChartAreas[0].AxisY.Maximum = Math.Round(Convert.ToDouble(bestValues.First().Value), 0) + 25;
this.chart2.ChartAreas[0].AxisY.Minimum = Math.Round(Convert.ToDouble(bestValues.Last().Value), 0) - 25;
// Set palette.
this.chart2.Palette = ChartColorPalette.SeaGreen;
// Set title.
this.chart2.Titles.Add("Deviation");
double numberOfParameters = 1.0;
foreach (var item in bestValues)
{
// Add series.
Series series = this.chart2.Series.Add(XMLWork.FindNameWithID(item.Key, Properties.Settings.Default.Languages));
// Add point.
//series.Points.Add(Convert.ToDouble(item.Value));
series.Points.AddXY(numberOfParameters, item.Value);
numberOfParameters += 0.1;
}
// Add series.
}
private void RegressionAnalysisNew_Shown(object sender, EventArgs e)
{
_qualityParams = TrainData.nameParameter.Values.Where(o => o.StartsWith("Def")).ToArray();
_inputParams = TrainData.nameParameter.Values.Where(o => o.StartsWith("OPC")).ToArray();
comboBoxInputParams.Items.Clear();
comboBoxQualityParams.Items.Clear();
foreach (var qualityParam in _qualityParams)
{
comboBoxQualityParams.Items.Add(XMLWork.FindNameWithScada(qualityParam, Properties.Settings.Default.Languages));
}
foreach (var inputParam in _inputParams)
{
comboBoxInputParams.Items.Add(XMLWork.FindNameWithScada(inputParam, Properties.Settings.Default.Languages));
}
comboBoxInputParams.SelectedIndex = comboBoxQualityParams.SelectedIndex = 0;
}
/// <summary>
/// Main method
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void DictionaryMeasurement_Shown(object sender, EventArgs e)
{
int columns = TrainData.Train[0].Input.Count;
int i;
DataTable sourceTable = new DataTable();
sourceTable.Columns.Add("Date");
foreach (KeyValuePair <int, decimal> keyValuePair in TrainData.Train[0].Input)
{
String parName = XMLWork.FindNameWithID(keyValuePair.Key, Properties.Settings.Default.Languages);
sourceTable.Columns.Add(parName);
}
foreach (KeyValuePair <int, decimal> keyValuePair in TrainData.Train[0].Output)
{
String parName = XMLWork.FindNameWithID(keyValuePair.Key, Properties.Settings.Default.Languages);
sourceTable.Columns.Add(parName);
}
foreach (OneRow oneRow in TrainData.Train)
{
DataRow row = sourceTable.NewRow();
i = 1;
foreach (KeyValuePair <int, decimal> valuePair in oneRow.Input.OrderBy(o => o.Key))
{
row[0] = oneRow.Date;
row[i] = valuePair.Value;
i++;
}
foreach (KeyValuePair <int, decimal> valuePair in oneRow.Output.OrderBy(o => o.Key))
{
row[i] = valuePair.Value;
i++;
}
sourceTable.Rows.Add(row);
}
gridMeasurements.DataSource = sourceTable;
EnableDoubleBuffering();
}
bool GetDataForRSquaredGraph(string qualityParam)
{
var allData = new Dictionary <string, KeyValuePair <double, double> >();
var inputParametersToCheck = checkedListBoxInputParametersToCheck.CheckedItems.Cast <string>();
int qualityParameterID = XMLWork.FindIDWithName(qualityParam, Properties.Settings.Default.Languages);
try
{
foreach (var inputParam in inputParametersToCheck)
{
int inputParameterID = XMLWork.FindIDWithName(inputParam, Properties.Settings.Default.Languages);
double rSquared, Fisher;
var generalData = (from row in TrainData.Train
select new PointD {
X = (double)row.Input[inputParameterID], Y = (double)row.Output[qualityParameterID]
}).ToList();
if (!generalData.Any(item => Math.Abs(item.X) > DataSensitivityThreshhold && Math.Abs(item.Y) > DataSensitivityThreshhold))
{
throw new Exception("Incorrect input data");
}
Regression.Correlation(generalData, checkBoxNormalizeValuesPage2.Checked, out rSquared, out Fisher);
allData.Add(inputParam, new KeyValuePair <double, double>(rSquared, Fisher));
}
allData = allData.Where(item => !IsNanOrInfinity(item.Value)).OrderByDescending(item => item.Value.Key)
.Take(BestSimpleRegressionsShowingCount).ToDictionary(item => item.Key, item => item.Value);
ShowRSquaredGraph(allData);
return(true);
}
catch (Exception ex)
{
MessageBox.Show($"Error processing data: \"{ex.Message}\"", "Exception", MessageBoxButtons.OK);
return(false);
}
}
private void parameterCondition_SelectedIndexChanged(object sender, EventArgs e)
{
ListAdd.Items.Clear();
ListDelete.Items.Clear();
List <int> keys = new List <int>();
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
Dictionary <int, decimal> firstRow = TrainData.Train.First().Input;
foreach (OneRow data in TrainData.Train)
{
foreach (var item in data.Input)
{
if (keys.Contains(item.Key))
{
continue;
}
if (item.Key != firstRow[item.Key])
{
keys.Add(item.Key);
}
}
break;
}
foreach (int key in keys)
{
ListAdd.Items.Add(XMLWork.FindNameWithID(key, Properties.Settings.Default.Languages));
}
if (ListAdd.Items.Count != 0)
{
ListAdd.SelectedIndex = 0;
}
if (ListDelete.Items.Count != 0)
{
ListDelete.SelectedIndex = 0;
}
}
//Сбор данных
private void dataAcq_Click(object sender, EventArgs e)
{
if (ListDelete.Items.Count != 0)
{
Stopwatch sw = new Stopwatch();
sw.Start();
TrainData.Train.Clear();
measurementses.Clear();
Dictionary <string, int> newElements = new Dictionary <string, int>();
if (ListDelete.Items.Count != 0)
{
//Сохранения имен параметров и их ID в справочник newElements
foreach (var item in ListDelete.Items)
{
string t = item.ToString();
int j = elements.Where(s => s.Key == t).Single().Value;
newElements.Add(t, j);
//Работа с локальной базой данных(сохранения данных туда)
XMLWork.AddRow(j, t);
}
}
var stream = File.Open(path.Text, FileMode.Open, FileAccess.Read);
var eReader = ExcelReaderFactory.CreateOpenXmlReader(stream);
bool check = true;
try
{
_counter = 0;
while (eReader.Read()) // Одну строку пропускаем с общей информацией
{
++_counter;
break;
}
DateTime lastTime = new DateTime();
while (eReader.Read()) // Считывание информации с EXCEL файла
{
var date = eReader.GetDateTime(0);
var time = eReader.GetDateTime(1);
TimeSpan ts = new TimeSpan(time.Hour, time.Minute, time.Second);
date = date + ts;
if (_counter == 1)
{
lastTime = date;
}
else
{
if (lastTime == date)
{
continue;
}
lastTime = date;
}
Measurements measurements;
foreach (var value in newElements)
{
Decimal parValue;
var val = Convert.ToString(eReader.GetValue(value.Value));
val = val.Trim();
if (val == "")
{
parValue = -1;
}
else
{
var extA = Convert.ToString(eReader.GetValue(value.Value)).Replace(",", ".");
try
{
parValue = Decimal.Parse(extA, NumberStyles.Float, _formatProvider);
}
catch (Exception exe)
{
throw new Exception("Invalid value format in row " + _counter, exe);
}
measurements = new Measurements(parValue, date, value.Key, value.Value); // созеания измерения
measurementses.Add(measurements); // и добавление его в коллекцию
}
}
++_counter;
}
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
}
finally
{
eReader.Close();
}
try
{
List <OneRow> dataSet = new List <OneRow>();
var uniqueTimestamp = measurementses.OrderBy(o => o.TimeStamp).Select(o => o.TimeStamp).Distinct();
OneRow lastRow = new OneRow();
// Отделение технологических параметров от показателей качество.
//TODO: сделать отдельную колонку в бд, в которой хранить краткую информацию о расположении датчика относительно производственной линии
foreach (DateTime dateTime in uniqueTimestamp)
{
var moveData =
measurementses.Where(
o => ((dateTime == o.TimeStamp) && (!o.ParameterName.StartsWith("Def"))))
.ToDictionary(o => o.ParID, s => s.Value); // Добавление технологических параметров в дикшионари
//температуры для усадки
var temperatureData = measurementses.Where(o => ((dateTime == o.TimeStamp) && (o.ParameterName.Contains("XT"))))
.ToDictionary(o => o.ParameterName, s => s.Value);
//скорости для усадки
var velocityData = measurementses.Where(o => ((dateTime == o.TimeStamp) && (o.ParameterName.Contains("XV"))))
.ToDictionary(o => o.ParameterName, s => s.Value);
OneRow row = new OneRow();
row.Input = moveData;
row.Temperatures = temperatureData;
row.Velocities = velocityData;
if (row.Input.Count >= 1)
{
row.Date = dateTime;
var dataOutput =
measurementses.Where(
o => ((dateTime == o.TimeStamp) && (o.ParameterName.StartsWith("Def"))))
.ToDictionary(o => o.ParID, s => s.Value);
row.Output = dataOutput;
dataSet.Add(row); // Добавление показателя качества в ОЗУ
}
lastRow = row;
}
var datas =
measurementses.Where(o => dataSet.First().Date == o.TimeStamp)
.ToDictionary(o => o.ParID, s => s.ParameterName);
TrainData.GetData();
foreach (KeyValuePair <int, string> keyValuePair in datas)
{
if (!TrainData.Pairs.ContainsKey(keyValuePair.Value))
{
TrainData.Pairs.Add(keyValuePair.Value, keyValuePair.Value);
}
}
TrainData.nameParameter = datas;
TrainData.Train = dataSet; // Присвоение статической переменной данных
}
catch (InvalidOperationException iex)
{
var parameters = measurementses.Where(o => !o.ParameterName.StartsWith("Def")).ToArray();
if (parameters.Count() == 0)
{
MessageBox.Show(
Localization.MyStrings.QualityParameters);
}
else
{
MessageBox.Show(iex.ToString());
}
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
}
sw.Stop();
var parametersInput = measurementses.Where(o => o.ParameterName.StartsWith("Def")).ToArray();
if (parametersInput.Count() == 0)
{
MessageBox.Show(
Localization.MyStrings.RegimeParameters, Localization.MyStrings.Warning);
}
MessageBox.Show(Localization.MyStrings.TimeParameters + sw.Elapsed);
string pathToShrinkage = System.AppDomain.CurrentDomain.BaseDirectory + "\\Shrinkage.xml";
if (File.Exists(pathToShrinkage))
{
File.Delete(pathToShrinkage);
}
}
else
{
MessageBox.Show(Localization.MyStrings.SelectedParameters);
}
}
/// <summary>
/// Implement FisherCritery
/// </summary>
private void FisherCritery()
{
if (parameterCondition.Items.Count != 0)
{
int countElements = 10;
List <OneRow> trainData = TrainData.Train;
Dictionary <int, decimal> bestValues = new Dictionary <int, decimal>();
List <FisherCritery> fishers = new List <FisherCritery>();
try
{
int parameterID = XMLWork.FindIDWithName((string)parameterCondition.SelectedItem, Properties.Settings.Default.Languages);
decimal averageY = AverageOutput(trainData, parameterID);
//Fisher Critery
foreach (var item in trainData[0].Input)
{
Fisher fisher = new Fisher(trainData, item.Key, parameterID, averageY);
fisher.CalculateFisher();
fishers.Add(new FisherCritery(item.Key, fisher.Critery));
}
//Sort of data
ListOfElements fisherElements = new ListOfElements(fishers);
fisherElements.InsertionSort();
//Give Best Value
for (int i = 0; i < countElements; i++)
{
bestValues.Add(fisherElements.Fisher[i].Key, fisherElements.Fisher[i].Value);
}
//Clear Palette
this.chart1.Series.Clear();
this.chart1.Titles.Clear();
this.chart1.ChartAreas[0].AxisY.Maximum = Math.Round(Convert.ToDouble(bestValues.First().Value), 0) + 25;
this.chart1.ChartAreas[0].AxisY.Minimum = Math.Round(Convert.ToDouble(bestValues.Last().Value), 0) - 25;
// Set palette.
this.chart1.Palette = ChartColorPalette.SeaGreen;
// Set title.
this.chart1.Titles.Add("Critery F-Test");
double numberOfParameters = 1.0;
foreach (var item in bestValues)
{
// Add series.
Series series = this.chart1.Series.Add(XMLWork.FindNameWithID(item.Key, Properties.Settings.Default.Languages));
// Add point.
//series.Points.Add(Convert.ToDouble(item.Value));
series.Points.AddXY(numberOfParameters, item.Value);
numberOfParameters += 0.1;
}
}
catch (InvalidOperationException ex)
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
}
catch (Exception excep)
{
MessageBox.Show(excep.ToString());
}
}
else
{
MessageBox.Show(Localization.MyStrings.WithoutDefect);
}
// Add series.
}
public void LoadFromDB()
{
values = null;
normalise = null;
weights = null;
normaliseRandom = null;
listParameter.Clear();
values = new decimal[ListDelete.Items.Count, TrainData.Train.Count];
normalise = new decimal[ListDelete.Items.Count, TrainData.Train.Count];
normaliseRandom = new decimal[ListDelete.Items.Count, TrainData.Train.Count];
weights = new decimal[ListDelete.Items.Count, Convert.ToInt32(numberOfNeurons.Text)];
dimensionOfVector.Text = Convert.ToString(ListDelete.Items.Count);
int count = 0;
foreach (var item in ListDelete.Items)
{
int parameterID = XMLWork.FindIDWithName(item.ToString(), Properties.Settings.Default.Languages);
OneRow row = TrainData.Train.First();
decimal value = 0.0M;
if (row.Input.ContainsKey(parameterID))
{
value = row.Input[parameterID];
}
else if (row.Output.ContainsKey(parameterID))
{
value = row.Output[parameterID];
}
listParameter.Add(count, new ParameterCharacteristics(item.ToString(), value, value, value, 0.0M, 0.0M));
count++;
}
if (TrainData.Train.Count > 0)
{
int j = 0;
//Вычисление среднего значения каждого атрибута выборки + сумма, минимум и максимум также вычисляются
foreach (OneRow row in TrainData.Train)
{
for (int i = 0; i < listParameter.Count; i++)
{
try
{
int parameterID = XMLWork.FindIDWithName(listParameter[i].ParameterName, Properties.Settings.Default.Languages);
if (row.Input.ContainsKey(parameterID))
{
values[i, j] = row.Input[parameterID];
}
else if (row.Output.ContainsKey(parameterID))
{
values[i, j] = row.Output[parameterID];
}
if (values[i, j] < listParameter[i].Min)
{
listParameter[i].Min = values[i, j];
}
if (values[i, j] > listParameter[i].Max)
{
listParameter[i].Max = values[i, j];
}
listParameter[i].Sum += values[i, j];
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
}
}
j++;
}
//Поиск среднего значения по выборке
for (int i = 0; i < listParameter.Count; i++)
{
listParameter[i].Mean = listParameter[i].Sum / Convert.ToDecimal(TrainData.Train.Count);
j = 0;
decimal differenceSquares = 0.0M;
foreach (OneRow row in TrainData.Train)
{
differenceSquares += ((values[i, j] - listParameter[i].Mean) * (values[i, j] - listParameter[i].Mean));
j++;
}
listParameter[i].Deviation = differenceSquares / (decimal)(TrainData.Train.Count - 1);
}
//Нормализация данных
for (int i = 0; i < listParameter.Count; i++)
{
for (int k = 0; k < TrainData.Train.Count; k++)
{
if (listParameter[i].Max - listParameter[i].Min != 0)
{
normalise[i, k] = Normalisation.NormaliseWithDeviation(values[i, k], listParameter[i].Mean, listParameter[i].Deviation);
}
else
{
normalise[i, k] = 0.0M;
}
}
}
}
else
{
MessageBox.Show(Localization.MyStrings.Absent, Localization.MyStrings.Warning);
}
//
int step = TrainData.Train.Count / Convert.ToInt32(numberOfNeurons.Text);
//Здесь задаются начальные значения весов
/*
* for (int j = 0, n = 0; j < TrainData.Train.Count; j = j + step, n++)
* {
* if (n < Convert.ToInt32(numberOfNeurons.Text))
* {
* for (int i = 0; i < listParameter.Count; i++)
* weights[i,n] = normalise[i,j];
* }
* }*/
Random rand = new Random((int)(DateTime.Now.Ticks));
for (int j = 0; j < Convert.ToInt32(numberOfNeurons.Text); j++)
{
for (int k = 0; k < listParameter.Count; k++)
{
weights[k, j] = Randomise.RandomDecimal(rand);
}
}
}
private void ShowThrend(object sender)
{
FormsPlot chartControl = chartControl1;
try
{
List <double> xs = new List <double>();
List <double> ys = new List <double>();
// Процедура поиска текущего контрола для отрисовки трендов
if (extruderTabPage.Visible)
{
chartControl = chartTrends;
}
if (calenderRollTabPage.Visible)
{
chartControl = chartCalenderRoll;
}
if (takeoffRollTabPage.Visible)
{
chartControl = chartTakeOffRoll;
}
if (temperingRollTabPage.Visible)
{
chartControl = chartTemperingRoll;
}
if (winderTabPage.Visible)
{
chartControl = chartWinder;
}
if (qualityTabPage.Visible) // Ситуация когда мы находимся на вкладке показателей качества является нетривиальной
{
chartControl = chartControl1;
if (sender is TextBox)
{
//Поиск текстбокса и указание ограничений по времени
TextBox edit = sender as TextBox;
DateTime timeBefore = TrainData.Train.OrderBy(o => o.Date).First().Date;
DateTime timeAfter = TrainData.Train.OrderByDescending(o => o.Date).First().Date;
chartControl.plt.Clear();
if (edit.Name.Contains("Shrinkage")) //если выбрана усадка
{
TimeSpan ts = new TimeSpan(ProductionTime.TakeOffTime);
foreach (OneRow row in TrainData.Train)
{
DataSet AuthorsDataSet = new DataSet();
AuthorsDataSet.ReadXml(XMLWork.PathShrinkage);
string shrinkageValues = XMLWork.FindShrinkageWithTimestamp(row.Date);
if ((row.Date >= timeBefore) && (row.Date <= timeAfter))
{
xs.Add((row.Date - ts).ToOADate());
ys.Add(Convert.ToDouble(shrinkageValues.Replace(".", ",")));
}
}
chartControl.plt.PlotScatter(xs.ToArray(), ys.ToArray(), lineWidth: 2, markerShape: MarkerShape.none, label: "Shrinkage value");
}
else
{
//Отрисовка
int parameterID = XMLWork.FindID(edit.Name.Replace("_", "."));
foreach (OneRow row in TrainData.Train)
{
if ((row.Date >= timeBefore) && (row.Date <= timeAfter))
{
xs.Add(row.Date.ToOADate());
ys.Add(Convert.ToDouble(row.Output[parameterID]));
}
}
chartControl.plt.PlotScatter(xs.ToArray(), ys.ToArray(), lineWidth: 2, markerShape: MarkerShape.none, label: XMLWork.FindNameWithID(parameterID, Properties.Settings.Default.Languages));
}
}
chartControl.plt.Ticks(dateTimeX: true);
chartControl.plt.Legend(location: legendLocation.upperRight, shadowDirection: shadowDirection.none);
chartControl.plt.AxisAuto();
double xDelta = Math.Abs(xs.Max() - xs.Min());
double yDelta = Math.Abs(ys.Max() - ys.Min());
chartControl.plt.Axis(xs.Min() - xDelta * 0.05, xs.Max() + xDelta * 0.05, ys.Min() - yDelta * 0.05, ys.Max() + yDelta * 0.05); chartControl.Render();
return;
}
if (sender is TextBox)
{
//Поиск текстбокса и указание ограничений по времени
TextBox edit = sender as TextBox;
DateTime timeBefore = TrainData.Train.OrderBy(o => o.Date).First().Date;
DateTime timeAfter = TrainData.Train.OrderByDescending(o => o.Date).First().Date;
chartControl.plt.Clear();
//Отрисовка
int parameterID = XMLWork.FindID(edit.Name);
foreach (OneRow row in TrainData.Train)
{
if ((row.Date >= timeBefore) && (row.Date <= timeAfter) && (!qualityTabPage.Visible))
{
xs.Add(row.Date.ToOADate());
ys.Add(Convert.ToDouble(row.Input[parameterID]));
}
}
chartControl.plt.PlotScatter(xs.ToArray(), ys.ToArray(), lineWidth: 2, markerShape: MarkerShape.none, label: XMLWork.FindNameWithID(parameterID, Properties.Settings.Default.Languages));
chartControl.plt.Ticks(dateTimeX: true);
chartControl.plt.Legend(location: legendLocation.upperRight, shadowDirection: shadowDirection.none);
chartControl.plt.AxisAuto();
double xDelta = Math.Abs(xs.Max() - xs.Min());
double yDelta = Math.Abs(ys.Max() - ys.Min());
chartControl.plt.Axis(xs.Min() - xDelta * 0.05, xs.Max() + xDelta * 0.05, ys.Min() - yDelta * 0.05, ys.Max() + yDelta * 0.05);
chartControl.Render();
}
}
catch (Exception exception)
{
MessageBox.Show(Localization.MyStrings.SomethingWrong + exception.ToString());
}
}
bool GetMultipleRegressionModel(string qualityParam)
{
double[,] processParametersData;
double[] qualityParameterData;
var inputParametersToCheck = checkedListBoxInputParametersToCheckPage3.CheckedItems.Cast <string>().ToList();
int qualityParameterID = XMLWork.FindIDWithName(qualityParam, Properties.Settings.Default.Languages);
processParametersData = new double[TrainData.Train.Count, inputParametersToCheck.Count + 1];
qualityParameterData = new double[TrainData.Train.Count];
//Setting first column of input values of regression matrix X with "1" values
for (int i = 0; i < processParametersData.GetLength(0); i++)
{
processParametersData[i, 0] = 1;
}
List <double> parametersLowerBounds = new List <double>(), parametersUpperBounds = new List <double>();
//Setting all input data
for (int paramNumber = 0; paramNumber < inputParametersToCheck.Count; paramNumber++)
{
double minValue = double.MaxValue, maxValue = double.MinValue;
int inputParameterID = XMLWork.FindIDWithName(inputParametersToCheck[paramNumber], Properties.Settings.Default.Languages);
for (int rowNumber = 0; rowNumber < TrainData.Train.Count; rowNumber++)
{
processParametersData[rowNumber, paramNumber + 1] =
(double)TrainData.Train[rowNumber].Input[inputParameterID];
if (processParametersData[rowNumber, paramNumber + 1] < minValue)
{
minValue = processParametersData[rowNumber, paramNumber + 1];
}
if (processParametersData[rowNumber, paramNumber + 1] > maxValue)
{
maxValue = processParametersData[rowNumber, paramNumber + 1];
}
}
parametersLowerBounds.Add(minValue);
parametersUpperBounds.Add(maxValue);
}
//Setting output data
for (int i = 0; i < TrainData.Train.Count; i++)
{
qualityParameterData[i] = (double)TrainData.Train[i].Output[qualityParameterID];
}
//Call for multiple regression calculation method
try
{
for (int j = 1; j < processParametersData.GetLength(1); j++)
{
bool throwData = true;
for (int i = 0; i < processParametersData.GetLength(0); i++)
{
if (Math.Abs(processParametersData[i, j]) > DataSensitivityThreshhold)
{
throwData = false;
break;
}
}
if (throwData)
{
throw new Exception("Incorrect input data");
}
}
if (!qualityParameterData.Any(item => Math.Abs(item) > DataSensitivityThreshhold))
{
throw new Exception("Incorrect input data");
}
var coefficients = Regression.MultipleRegression(processParametersData, qualityParameterData, checkBoxNormalizeValuesPage3.Checked);
double rmse = Regression.MultipleRMSE(processParametersData, qualityParameterData, coefficients);
labelRMSEPage3.Text = $"RMSE = {Math.Round(rmse, RMSESignificantDigitsCount)}";
_multipleRegressionEquation = new RegressionModelEquation("DefaultName", qualityParam,
inputParametersToCheck, rmse, coefficients,
inputParametersToCheck.ToArray(), parametersLowerBounds.ToArray(), parametersUpperBounds.ToArray(), checkBoxNormalizeValuesPage3.Checked);
ShowRegressionEquasion(qualityParam, coefficients);
ShowRegressionEquasionHelp(inputParametersToCheck.ToArray());
return(true);
}
catch (Exception ex)
{
MessageBox.Show($"Exception thrown in multiple regression calculation: \"{ex.Message}\"!");
return(false);
}
}
/// <summary>
/// Selects parameters in orange
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
/*private void DrawItem(object sender, ListBoxDrawItemEventArgs e)
* {
* ListBoxControl control = (ListBoxControl)sender;
* if (e.Index == (control.SelectedIndex))
* {
* e.Appearance.BackColor = Color.Orange;
* }
* }*/
#endregion
private void parameterCondition_SelectedIndexChanged(object sender, EventArgs e)
{
ListAdd.Items.Clear();
ListDelete.Items.Clear();
ListAddError.Items.Clear();
ListDeleteError.Items.Clear();
List <int> keys = new List <int>();
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
Dictionary <int, decimal> firstRow = TrainData.Train.First(o => o.Output[parameterID] > (Convert.ToDecimal(uppLimit.Value) * 0.9M)).Input;
foreach (OneRow data in TrainData.Train)
{
if (data.Output[parameterID] > 1.0M)
{
foreach (var item in data.Input)
{
if (keys.Contains(item.Key))
{
continue;
}
if (item.Key != firstRow[item.Key])
{
keys.Add(item.Key);
}
}
}
}
foreach (int key in keys)
{
ListAdd.Items.Add(XMLWork.FindNameWithID(key, Properties.Settings.Default.Languages));
ListAddError.Items.Add(XMLWork.FindNameWithID(key, Properties.Settings.Default.Languages));
}
addAllToFirstCoordinate.Enabled = true;
addAllToSecondCoordinate.Enabled = true;
addOneCoordinate.Enabled = true;
addOneToSecondCoordinate.Enabled = true;
deleteAllToFirstCoordinate.Enabled = true;
deleteAllToSecondCoordinate.Enabled = true;
deleteOneToSecondCoordinate.Enabled = true;
deleteToFirstCoordinate.Enabled = true;
if (parameterCondition.SelectedIndex != -1)
{
parameterCondition.BackColor = Color.White;
}
if (ListAdd.Items.Count != 0)
{
ListAdd.SelectedIndex = 0;
}
if (ListDelete.Items.Count != 0)
{
ListDelete.SelectedIndex = 0;
}
if (ListAddError.Items.Count != 0)
{
ListAddError.SelectedIndex = 0;
}
if (ListDeleteError.Items.Count != 0)
{
ListDeleteError.SelectedIndex = 0;
}
}
public Diagramm(List <DM.DecisionTree.TreeNode> rndForests)
{
if (!string.IsNullOrEmpty(Properties.Settings.Default.Languages))
{
System.Threading.Thread.CurrentThread.CurrentUICulture =
System.Globalization.CultureInfo.GetCultureInfo(Properties.Settings.Default.Languages);
System.Threading.Thread.CurrentThread.CurrentCulture =
System.Globalization.CultureInfo.GetCultureInfo(Properties.Settings.Default.Languages);
}
InitializeComponent();
TrainData.GetData();
List <string> dictForestsSort = new List <string>();
List <string> secForestsSort = new List <string>();
Dictionary <string, int> dictForests = new Dictionary <string, int>();
Dictionary <string, int> secondForests = new Dictionary <string, int>();
foreach (DM.DecisionTree.TreeNode rndForest in rndForests)
{
if (!dictForests.ContainsKey(rndForest.attributeName))
{
dictForests.Add(rndForest.attributeName, 1);
}
else
{
dictForests[rndForest.attributeName]++;
}
}
dictForestsSort = dictForests.Keys.ToList();
InsertionSort(dictForestsSort, dictForests);
this.chart1.Series.Clear();
this.chart1.Titles.Clear();
// Set palette.
this.chart1.Palette = ChartColorPalette.SeaGreen;
// Set title.
this.chart1.Titles.Add("1st Node");
double numberOfParameters = 1.0;
foreach (var item in dictForestsSort)
{
//TODO Russian name
if ((item != "False") && (item != "True"))
{
var name = TrainData.nameParameter.SingleOrDefault(parameter => parameter.Value == item).Value;
// Add series.
Series series = this.chart1.Series.Add(XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages));
// Add point.
//series.Points.Add(Convert.ToDouble(item.Value));
series.Points.Add(dictForests[item]);
}
}
foreach (var rndForest in rndForests)
{
foreach (var treeNode in rndForest.MChilds)
{
if ((treeNode != null) && (treeNode.attributeName != "False") && ((treeNode.attributeName != "True")))
{
if (!secondForests.ContainsKey(treeNode.attributeName))
{
secondForests.Add(treeNode.attributeName, 1);
}
else
{
secondForests[treeNode.attributeName]++;
}
}
}
}
secForestsSort = secondForests.Keys.ToList();
InsertionSort(secForestsSort, secondForests);
this.chart2.Series.Clear();
this.chart2.Titles.Clear();
// Set palette.
this.chart2.Palette = ChartColorPalette.SeaGreen;
// Set title.
this.chart2.Titles.Add("2nd Node");
foreach (var item in secForestsSort)
{
//TODO Russian name
var name = TrainData.nameParameter.Single(parameter => parameter.Value == item).Value;
// Add series.
Series series = this.chart2.Series.Add(XMLWork.FindNameWithScada(item, Properties.Settings.Default.Languages));
// Add point.
series.Points.Add(secondForests[item]);
}
}
void ShowThrends2()
{
if ((ListDelete.Items.Count > 10) || (ListDeleteError.Items.Count > 10))
{
MessageBox.Show(
Localization.MyStrings.ParametersSelected);
return;
}
if (parameterCondition.SelectedIndex == -1)
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
parameterCondition.BackColor = Color.Red;
return;
}
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
Chart.plt.Clear();
List <OneRow> trainData = TrainData.Train;
List <double> xs1 = new List <double>(), ys1 = new List <double>(), xs2 = new List <double>(), ys2 = new List <double>();
decimal minX = 0.0M;
decimal maxX = 0.0M;
decimal minY = 0.0M;
decimal maxY = 0.0M;
foreach (OneRow data in trainData)
{
decimal pointX = 1.0M;
decimal pointY = 1.0M;
if (data.Output[parameterID] > (Convert.ToDecimal(uppLimit.Value) * 0.9M))
{
GetPoints(ref pointX, data, ref pointY);
maxX = pointX;
maxY = pointY;
minX = pointX;
minY = pointY;
}
else
{
GetPoints(ref pointX, data, ref pointY);
maxX = pointX;
maxY = pointY;
minX = pointX;
minY = pointY;
}
break;
}
foreach (OneRow data in trainData)
{
decimal pointX = 1.0M;
decimal pointY = 1.0M;
if (data.Output[parameterID] > (Convert.ToDecimal(uppLimit.Value) * 0.9M))
{
GetPoints(ref pointX, data, ref pointY);
if (pointX > maxX)
{
maxX = pointX;
}
if (pointY > maxY)
{
maxY = pointY;
}
if (pointX < minX)
{
minX = pointX;
}
if (pointY < minY)
{
minY = pointY;
}
xs1.Add(Convert.ToDouble(pointX));
ys1.Add(Convert.ToDouble(pointY));
}
else
{
GetPoints(ref pointX, data, ref pointY);
if (pointX > maxX)
{
maxX = pointX;
}
if (pointY > maxY)
{
maxY = pointY;
}
if (pointX < minX)
{
minX = pointX;
}
if (pointY < minY)
{
minY = pointY;
}
xs2.Add(Convert.ToDouble(pointX));
ys2.Add(Convert.ToDouble(pointY));
}
}
Chart.plt.PlotScatter(xs1.ToArray(), ys1.ToArray(), lineWidth: 0, markerShape: MarkerShape.filledCircle, label: Localization.MyStrings.WithD);
Chart.plt.PlotScatter(xs2.ToArray(), ys2.ToArray(), lineWidth: 0, markerShape: MarkerShape.filledCircle, label: Localization.MyStrings.WithoutD);
Chart.plt.Legend(location: legendLocation.upperRight, shadowDirection: shadowDirection.none);
Chart.plt.AxisAuto();
decimal deltaX = Math.Abs(maxX - minX);
decimal deltaY = Math.Abs(maxY - minY);
Chart.plt.Axis(Convert.ToDouble(minX - deltaX * 0.05m), Convert.ToDouble(maxX + deltaX * 0.05m),
Convert.ToDouble(minY - deltaY * 0.05m), Convert.ToDouble(maxY + deltaY * 0.05m));
Chart.Render();
}
private void trainButton_Click(object sender, EventArgs e)
{
if ((parameterCondition.Items.Count != 0) && (ListDelete.Items.Count != 0) && (parameterCondition.SelectedIndex != -1))
{
try
{
GetBooleanForOutput(TrainData.Train, criterion.Value);
bool falseData = false;
bool trueData = false;
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
foreach (OneRow oneRow in TrainData.Train)
{
if ((oneRow.OutputBool[parameterID] == true) && (trueData == false))
{
trueData = true;
}
else if ((oneRow.OutputBool[parameterID] == false) && (falseData == false))
{
falseData = true;
}
}
if ((falseData) && (trueData))
{
PreprocessToWorkTree();
}
else
{
MessageBox.Show(Localization.MyStrings.AnotherCriterion);
}
}
catch
(InvalidOperationException ex)
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.Red;
}
catch
(Exception excep)
{
if (criterion.Text.Trim() == "")
{
MessageBox.Show(Localization.MyStrings.SelectPartitioninCriterion);
criterion.BackColor = Color.Red;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.White;
}
else if (ListDelete.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.AddParameter);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.Red;
parameterCondition.BackColor = Color.White;
}
else
{
MessageBox.Show(excep.ToString());
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.White;
}
}
}
else
{
if (parameterCondition.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.WithoutDefect);
}
else if ((parameterCondition.SelectedIndex == -1))
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.Red;
}
if (ListDelete.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.AddParameter);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.Red;
parameterCondition.BackColor = Color.White;
}
}
// Add series.
}
private void DecisionTreeRandomForest()
{
var checkData = new TrainData();
var analysParameter = new Dictionary <int, string>();
var trainData = new TrainData();
var trainedData = new TrainData();
if ((parameterCondition.Items.Count != 0) && (ListDelete.Items.Count != 0) &&
(parameterCondition.SelectedIndex != -1))
{
try
{
GetBooleanForOutput(TrainData.Train, Convert.ToDecimal(criterion.Text));
analysParameter = TrainData.nameParameter.Where(o => !o.Value.StartsWith("Def"))
.ToDictionary(o => o.Key, o => o.Value);
bool falseData = false;
bool trueData = false;
int parameterID = XMLWork.FindIDWithName(parameterCondition.SelectedItem.ToString(), Properties.Settings.Default.Languages);
foreach (OneRow oneRow in TrainData.Train)
{
if ((oneRow.OutputBool[parameterID] == true) && (trueData == false))
{
trueData = true;
}
else if ((oneRow.OutputBool[parameterID] == false) && (falseData == false))
{
falseData = true;
}
}
if ((falseData) && (trueData))
{
PreprocessToWorkTreeRandomForest(trainedData, checkData, analysParameter);
System.Windows.Forms.MessageBox.Show(Localization.MyStrings.Over);
}
else
{
MessageBox.Show(Localization.MyStrings.AnotherCriterion);
}
}
catch (FormatException formatException)
{
MessageBox.Show(Localization.MyStrings.SelectPartitioninCriterion);
criterion.BackColor = Color.Red;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.White;
}
catch
(InvalidOperationException ex)
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.Red;
}
catch (Exception excep)
{
if (ListDelete.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.AddParameter);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.Red;
parameterCondition.BackColor = Color.White;
}
else
{
MessageBox.Show(excep.ToString());
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.White;
}
}
}
else
{
if (parameterCondition.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.WithoutDefect);
}
else if ((parameterCondition.SelectedIndex == -1))
{
MessageBox.Show(Localization.MyStrings.SelectCriterion);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.White;
parameterCondition.BackColor = Color.Red;
}
if (ListDelete.Items.Count == 0)
{
MessageBox.Show(Localization.MyStrings.AddParameter);
criterion.BackColor = Color.White;
ListDelete.BackColor = Color.Red;
parameterCondition.BackColor = Color.White;
}
}
}
void ShowParameterData(string parameterName)
{
if (Calculation.stringName != parameterName)
{
Calculation.stringName = parameterName;
TextBoxColumnCount.Text = "";
TextBoxMax.Text = "";
TextBoxMin.Text = "";
}
List <KeyValuePair <DateTime, double> > data;
int parameterID = XMLWork.FindIDWithName(parameterName, Properties.Settings.Default.Languages);
var scadaName = XMLWork.FindScadaNameWithID(parameterID);
if (scadaName.StartsWith("Def"))
{
data = (from row in TrainData.Train
select new KeyValuePair <DateTime, double>(row.Date, (double)row.Output[parameterID])).ToList();
}
else
{
data = (from row in TrainData.Train
select new KeyValuePair <DateTime, double>(row.Date, (double)row.Input[parameterID])).ToList();
}
/* double min, max;
* min = String.IsNullOrWhiteSpace(TextBoxMin.Text) ? data.Min(item => item.Value) : double.Parse(TextBoxMin.Text);
* TextBoxMin.Text = min.ToString();
* max = String.IsNullOrWhiteSpace(TextBoxMax.Text) ? data.Max(item => item.Value) : double.Parse(TextBoxMax.Text);
* TextBoxMax.Text = max.ToString();*/
if (options.log)
{
data = data.Where(item => item.Value != 0).ToList();
List <KeyValuePair <DateTime, double> > keyValuePairs = new List <KeyValuePair <DateTime, double> >();
foreach (var d in data)
{
keyValuePairs.Add(new KeyValuePair <DateTime, double>(d.Key, Math.Round(Math.Log(d.Value), 2)));
}
data = keyValuePairs;
if (!String.IsNullOrWhiteSpace(TextBoxMin.Text) || !String.IsNullOrWhiteSpace(TextBoxMin.Text))
{
if (data.Max(n => n.Value) < Convert.ToDouble(TextBoxMax.Text) || data.Min(n => n.Value) > Convert.ToDouble(TextBoxMin.Text))
{
TextBoxMin.Text = "";
TextBoxMax.Text = "";
}
}
}
if (options.unlog)
{
List <KeyValuePair <DateTime, double> > keyValuePairs = new List <KeyValuePair <DateTime, double> >();
foreach (var d in data)
{
keyValuePairs.Add(new KeyValuePair <DateTime, double>(d.Key, Math.Round(Math.Exp(d.Value), 2)));
}
data = keyValuePairs;
TextBoxMin.Text = "";
TextBoxMax.Text = "";
}
if (options.sigma)
{
List <KeyValuePair <DateTime, double> > dataControl;
double expectedValue = data.Sum(item => item.Value) / data.Count;
double standartDeviation = Math.Sqrt(data.Sum(item => Math.Pow(item.Value - expectedValue, 2)) / (data.Count - 1));
do
{
data = data.Where(item => item.Value > (expectedValue - 3 * standartDeviation) && item.Value < (expectedValue + 3 * standartDeviation)).ToList();
expectedValue = data.Sum(item => item.Value) / data.Count;
standartDeviation = Math.Sqrt(data.Sum(item => Math.Pow(item.Value - expectedValue, 2)) / (data.Count - 1));
double a = expectedValue - 3 * standartDeviation;
double b = expectedValue + 3 * standartDeviation;
dataControl = data.Where(item => item.Value <= a || item.Value >= b).ToList();
} while (dataControl.Count() > 0);
}
double min, max;
if (options.language)
{
TextBoxMin.Text = TextBoxMin.Text.Replace(".", ",");
TextBoxMax.Text = TextBoxMax.Text.Replace(".", ",");
}
else
{
TextBoxMin.Text = TextBoxMin.Text.Replace(",", ".");
TextBoxMax.Text = TextBoxMax.Text.Replace(",", ".");
}
min = String.IsNullOrWhiteSpace(TextBoxMin.Text) ? data.Min(item => item.Value) : double.Parse(TextBoxMin.Text);
TextBoxMin.Text = min.ToString();
max = String.IsNullOrWhiteSpace(TextBoxMax.Text) ? data.Max(item => item.Value) : double.Parse(TextBoxMax.Text);
TextBoxMax.Text = max.ToString();
if (options.minmax)
{
data = data.Where(item => item.Value >= min && item.Value <= max).ToList();
}
dataResult = data;
ShowChart1(data, parameterName);
ShowChart2(data, parameterName);
}
