public static Position getPositionFromInputCode(string input)
{
Position pos = new Position(0, 0);
int Letter = ColumnEnum.returnInt(input.Substring(0, 1));
if (Letter == -1)
{
return(pos);
}
int numberOfRow = 0;
bool successfulParse = int.TryParse(input.Substring(1, 1), out numberOfRow);
if (!successfulParse)
{
return(pos);
}
else
{
// invert number
numberOfRow = 9 - numberOfRow;
}
pos.X = Letter;
pos.Y = numberOfRow;
return(pos);
}
private void CellGUI(Rect rect, AssetTreeItem item, ColumnEnum column, ref RowGUIArgs args)
{
CenterRectUsingSingleLineHeight(ref rect);
switch (column)
{
case ColumnEnum.Check:
bool b = GUI.Toggle(rect, item.Check, GUIContent.none);
if (item.Check != b)
{
if (IsSelected(item.id))
{
foreach (AssetTreeItem selectedItem in FindRows(GetSelection()))
{
selectedItem.Check = b;
}
}
else
{
item.Check = b;
}
}
break;
case ColumnEnum.Path:
float space = 0;
GUI.DrawTexture(new Rect(rect.x + space, rect.y, rect.height, rect.height),
AssetDatabase.GetCachedIcon(item.displayName) as Texture2D ?? emptyTexture, ScaleMode.ScaleToFit);
GUI.Label(new Rect(rect.x + space + rect.height, rect.y, rect.width - space - rect.height, rect.height), item.displayName);
break;
default:
break;
}
}
private void CellGUI(Rect rect, BundleTreeItem item, ColumnEnum column, ref RowGUIArgs args)
{
CenterRectUsingSingleLineHeight(ref rect);
switch (column)
{
case ColumnEnum.Name:
float space = 5 + foldoutWidth + depthIndentWidth * item.depth;
GUI.DrawTexture(new Rect(rect.x + space, rect.y, rect.height, rect.height), item.icon, ScaleMode.ScaleToFit);
GUI.Label(new Rect(rect.x + space + rect.height, rect.y, rect.width - space - rect.height, rect.height),
item.displayName, item.style);
break;
case ColumnEnum.Connection:
foreach (var p in item.packageItems)
{
float width = rect.height;
float x = rect.x;
Rect r = new Rect(x + G.g.packageTree.Packages.IndexOf(p.package) * (rect.height + 4), rect.y, width, rect.height);
if (GUI.Button(r, GUIContent.none, p.complete ? p.package.colorBlockStyle : p.package.colorBlockStyle_hollow))
{
LocatePackage(p);
}
}
break;
default:
break;
}
}
public static void SetColumn(ColumnEnum column, params MyStats[] stats)
{
List<MyStats> statList;
if (!m_stats.TryGetValue(column, out statList))
{
statList = new List<MyStats>();
m_stats[column] = statList;
}
statList.Clear();
statList.AddArray(stats);
}
private DataColumn CachedDataColumn(ColumnEnum column)
{
if (null == columnCache[(int)column])
{
int index = columns.IndexOf(DBCOLUMN_NAME[(int)column]);
if (-1 != index)
{
columnCache[(int)column] = columns[index];
}
}
return(columnCache[(int)column]);
}
public static void SetColumn(ColumnEnum column, params MyStats[] stats)
{
List <MyStats> statList;
if (!m_stats.TryGetValue(column, out statList))
{
statList = new List <MyStats>();
m_stats[column] = statList;
}
statList.Clear();
statList.AddArray(stats);
}
private ITransformer BuildAndTrainUsingParams(ColumnEnum column)
{
List <string> features = new List <string>();
TextFeaturizingEstimator textTransformer = null;
EstimatorChain <ColumnConcatenatingTransformer> estimatorColumn = null;
EstimatorChain <ITransformer> estimatorTransformer = null;
if (_includeDay)
{
textTransformer = _mlContext.Transforms.Text.FeaturizeText("DayString", "Day");
features.Add("DayString");
}
if (_includeMonth)
{
if (textTransformer != null)
{
estimatorTransformer = textTransformer.Append(_mlContext.Transforms.Text.FeaturizeText("MonthString", "Month"));
}
else
{
textTransformer = _mlContext.Transforms.Text.FeaturizeText("MonthString", "Month");
}
features.Add("MonthString");
}
if (_includeWeek)
{
features.Add("Week");
}
if (textTransformer == null)
{
var res = _mlContext.Transforms.Concatenate("Features", features.ToArray())
.Append(_mlContext.Transforms.CopyColumns("Label", System.Enum.GetName(typeof(ColumnEnum), column)))
.Append(_mlContext.Regression.Trainers.FastTreeTweedie());
return(res.Fit(_trainData));
}
if (estimatorTransformer != null)
{
var res2 = estimatorTransformer.Append(_mlContext.Transforms.Concatenate("Features", features.ToArray()))
.Append(_mlContext.Transforms.CopyColumns("Label", System.Enum.GetName(typeof(ColumnEnum), column)))
.Append(_mlContext.Regression.Trainers.FastTreeTweedie());
return(res2.Fit(_trainData));
}
var res3 = textTransformer.Append(_mlContext.Transforms.Concatenate("Features", features.ToArray()))
.Append(_mlContext.Transforms.CopyColumns("Label", System.Enum.GetName(typeof(ColumnEnum), column)))
.Append(_mlContext.Regression.Trainers.FastTreeTweedie());
return(res3.Fit(_trainData));
}
public static ITransformer BuildAndTrainModel(ColumnEnum column)
{
// STEP 3: Create the training algorithm/trainer
// Use the multi-class SDCA algorithm to predict the label using features.
//Set the trainer/algorithm and map label to value (original readable state)
// <SnippetAddTrainer>
// var trainingPipeline = pipeline.Append(_mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy("Label", "Feature"))
/* .Append(_mlContext.Transforms.Conversion.MapKeyToValue("Column1Predicted"));*/
switch (column)
{
case ColumnEnum.Column1:
return(BuildAndTrainUsingParams(ColumnEnum.Column1));
case ColumnEnum.Column2:
return(BuildAndTrainUsingParams(ColumnEnum.Column2));
case ColumnEnum.Column3:
return(BuildAndTrainUsingParams(ColumnEnum.Column3));
case ColumnEnum.Column4:
return(BuildAndTrainUsingParams(ColumnEnum.Column4));
case ColumnEnum.Column5:
return(BuildAndTrainUsingParams(ColumnEnum.Column5));
case ColumnEnum.Column6:
return(BuildAndTrainUsingParams(ColumnEnum.Column6));
case ColumnEnum.Bonus:
return(BuildAndTrainUsingParams(ColumnEnum.Bonus));
}
// </SnippetAddTrainer>
// STEP 4: Train the model fitting to the DataSet
Console.WriteLine($"=============== Training the model ===============");
// <SnippetTrainModel>
// </SnippetTrainModel>
Console.WriteLine($"=============== Finished Training the model Ending time: {DateTime.Now.ToString()} ===============");
// (OPTIONAL) Try/test a single prediction with the "just-trained model" (Before saving the model)
Console.WriteLine($"=============== Single Prediction just-trained-model ===============");
return(_trainedModel);
}
private DataColumn CachedDataColumn(ColumnEnum column, ColumnEnum column2)
{
DataColumn column3 = this.columnCache[(int)column];
if (column3 == null)
{
int index = this.columns.IndexOf(DBCOLUMN_NAME[(int)column]);
if ((-1 == index) && (column != column2))
{
index = this.columns.IndexOf(DBCOLUMN_NAME[(int)column2]);
}
if (-1 != index)
{
column3 = this.columns[index];
this.columnCache[(int)column] = column3;
}
}
return(column3);
}
private DataColumn CachedDataColumn(ColumnEnum column, ColumnEnum column2)
{
DataColumn dataColumn = _columnCache[(int)column];
if (null == dataColumn)
{
int index = _columns.IndexOf(s_DBCOLUMN_NAME[(int)column]);
if ((-1 == index) && (column != column2))
{
index = _columns.IndexOf(s_DBCOLUMN_NAME[(int)column2]);
}
if (-1 != index)
{
dataColumn = _columns[index];
_columnCache[(int)column] = dataColumn;
}
}
return(dataColumn);
}
private DataColumn CachedDataColumn(ColumnEnum column, ColumnEnum column2)
{
DataColumn dataColumn = this.columnCache[(int)column];
if (dataColumn == null)
{
int index = this.columns.IndexOf(DbcolumnName[(int)column]);
if (-1 == index && column != column2)
{
index = this.columns.IndexOf(DbcolumnName[(int)column2]);
}
if (-1 != index)
{
dataColumn = this.columns[index];
this.columnCache[(int)column] = dataColumn;
}
}
return(dataColumn);
}
private int PredictColumn(ITransformer model, ColumnEnum column)
{
var test = new ResultatJsonFormat()
{
Date = _datePrediction,
DateString = _datePrediction.ToShortDateString()
};
switch (column)
{
case ColumnEnum.Column1:
var predictionFunction = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn1>(model);
return((int)predictionFunction.Predict(test).Column1);
case ColumnEnum.Column2:
var predictionFunction2 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn2>(model);
return((int)predictionFunction2.Predict(test).Column2);
case ColumnEnum.Column3:
var predictionFunction3 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn3>(model);
return((int)predictionFunction3.Predict(test).Column3);
case ColumnEnum.Column4:
var predictionFunction4 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn4>(model);
return((int)predictionFunction4.Predict(test).Column4);
case ColumnEnum.Column5:
var predictionFunction5 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn5>(model);
return((int)predictionFunction5.Predict(test).Column5);
case ColumnEnum.Column6:
var predictionFunction6 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn6>(model);
return((int)predictionFunction6.Predict(test).Column6);
case ColumnEnum.Bonus:
var predictionFunctionBonus = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionBonus>(model);
return((int)predictionFunctionBonus.Predict(test).Bonus);
}
return(0);
}
private DataColumn?CachedDataColumn(ColumnEnum column)
{
return(CachedDataColumn(column, column));
}
public ColumnProperties(int idx, string headerText, string dataPropertyName, string columnName, ColumnEnum templateId)
{
_displayIndex = idx;
_templateId = templateId;
_headerText = headerText;
_dataPropertyName = dataPropertyName;
_name = columnName;
}
public void Add(ColumnEnum Item, bool Ascendente)
{
Item.Ascendente = Ascendente;
this._Columns.Add(Item);
}
public void Remove(ColumnEnum Item)
{
this._Columns.Remove(Item);
}
private DataColumn CachedDataColumn(ColumnEnum column)
{
return(this.CachedDataColumn(column, column));
}
private static float TestPrediction(ITransformer model, ColumnEnum column)
{
switch (column)
{
case ColumnEnum.Column1:
var predictionFunction = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn1>(model);
var test = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction.Predict(test).Column1);
case ColumnEnum.Column2:
var predictionFunction2 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn2>(model);
var test2 = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction2.Predict(test2).Column2);
case ColumnEnum.Column3:
var predictionFunction3 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn3>(model);
var test3 = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction3.Predict(test3).Column3);
case ColumnEnum.Column4:
var predictionFunction4 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn4>(model);
var test4 = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction4.Predict(test4).Column4);
case ColumnEnum.Column5:
var predictionFunction5 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn5>(model);
var test5 = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction5.Predict(test5).Column5);
case ColumnEnum.Column6:
var predictionFunction6 = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionColumn6>(model);
var test6 = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunction6.Predict(test6).Column6);
case ColumnEnum.Bonus:
var predictionFunctionBonus = _mlContext.Model.CreatePredictionEngine <ResultatJsonFormat, PredictionBonus>(model);
var testBonus = new ResultatJsonFormat()
{
Date = _datePrediction
};
return(predictionFunctionBonus.Predict(testBonus).Bonus);
}
return(0);
}
private void CellGUI(Rect rect, PackageTreeItem item, ColumnEnum column, ref RowGUIArgs args)
{
CenterRectUsingSingleLineHeight(ref rect);
switch (column)
{
case ColumnEnum.Name:
//args.rowRect = rect;
float space = 5 + foldoutWidth + depthIndentWidth * item.depth;
GUI.DrawTexture(new Rect(rect.x + space, rect.y, rect.height, rect.height), item.isPackage ? item.icon : item.bundleItem.icon, ScaleMode.ScaleToFit);
GUI.Label(new Rect(rect.x + space + rect.height, rect.y, rect.width - space - rect.height, rect.height),
item.isPackage ? item.displayName : item.bundleItem.displayName,
item.lost ? labelErrorStyle : (item.isPackage ? EditorStyles.label : item.bundleItem.style));
break;
case ColumnEnum.Connection:
Color color = EditorGUI.ColorField(new Rect(rect.x /* + Packages.IndexOf(item.package) * (rect.height + 4)*/,
rect.y, rect.height, rect.height), GUIContent.none, item.package.packageColor, false, false, false, colorPickerHDRConfig);
if (color != item.package.packageColor)
{
item.package.packageColor = color;
}
break;
case ColumnEnum.FileName:
if (item.isPackage)
{
GUI.Label(rect, item.fileName);
}
break;
case ColumnEnum.Necessery:
if (item.isPackage && G.Module.UserConfig.Json.PackageMode == "Addon")
{
int index = G.NecesseryEnum.IndexOf(item.necessery);
int index_new = EditorGUI.Popup(rect, index, G.NecesseryEnum, inDropDownStyle);
if (index_new != index)
{
item.necessery = G.NecesseryEnum[index_new];
G.Module.IsDirty = true;
}
}
break;
case ColumnEnum.DeploymentLocation:
if (item.isPackage && G.Module.UserConfig.Json.PackageMode == "Addon")
{
int index = G.DeploymentLocationEnum.IndexOf(item.deploymentLocation);
int index_new = EditorGUI.Popup(rect, index, G.DeploymentLocationEnum, inDropDownStyle);
if (index_new != index)
{
item.deploymentLocation = G.DeploymentLocationEnum[index_new];
G.Module.IsDirty = true;
}
}
break;
case ColumnEnum.CopyToStreaming:
if (item.isPackage && G.Module.UserConfig.Json.PackageMode == "Addon")
{
Rect rect_new = new Rect(rect.x + rect.width / 2 - 8, rect.y, 16, rect.height);
bool selected = EditorGUI.Toggle(rect_new, item.copyToStreaming, inToggleStyle);
if (selected != item.copyToStreaming)
{
item.copyToStreaming = selected;
G.Module.IsDirty = true;
}
}
break;
default:
break;
}
}
private DataColumn CachedDataColumn(ColumnEnum column, ColumnEnum column2)
{
DataColumn dataColumn = this.columnCache[(int)column];
if (dataColumn == null)
{
int index = this.columns.IndexOf(DbcolumnName[(int)column]);
if (-1 == index && column != column2)
{
index = this.columns.IndexOf(DbcolumnName[(int)column2]);
}
if (-1 != index)
{
dataColumn = this.columns[index];
this.columnCache[(int)column] = dataColumn;
}
}
return dataColumn;
}
private DataColumn CachedDataColumn(ColumnEnum column)
{
return this.CachedDataColumn(column, column);
}
private DataColumn CachedDataColumn(ColumnEnum column, ColumnEnum column2) {
DataColumn dataColumn = columnCache[(int) column];
if (null == dataColumn) {
int index = columns.IndexOf(DBCOLUMN_NAME[(int) column]);
if ((-1 == index) && (column != column2)) {
index = columns.IndexOf(DBCOLUMN_NAME[(int) column2]);
}
if (-1 != index) {
dataColumn = columns[index];
columnCache[(int) column] = dataColumn;
}
}
return dataColumn;
}
public void Remove(ColumnEnum Item)
{
this._Columns.Remove(Item);
}
public void Add(ColumnEnum Item, bool Ascendente)
{
Item.Ascendente = Ascendente;
this._Columns.Add(Item);
}
