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Merge branch 'Joel-ML' of https://git.wmi.amu.edu.pl/s425077/PotatoPlan into Joel-ML

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Joel 2020-05-25 11:08:14 +02:00
commit 631ad7c12f
6 changed files with 17 additions and 17 deletions
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2
Game1/Game1.cs
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@ -170,9 +170,9 @@ namespace Game1
input.controlWindowSize(); //Controls the size of the screen depending on the number of tiles input.controlWindowSize(); //Controls the size of the screen depending on the number of tiles
houseUnit.updateRectangle(input.getSize(), input.getTileSize(), input.getSpacing()); //Updates the position of the house if the house appears out of bound houseUnit.updateRectangle(input.getSize(), input.getTileSize(), input.getSpacing()); //Updates the position of the house if the house appears out of bound
Time.updateTime(tractorUnit.getSpeed()); Time.updateTime(tractorUnit.getSpeed());
//System.Threading.Thread updatethread = new System.Threading.Thread(new System.Threading.ParameterizedThreadStart(Update));
base.Update(gameTime); base.Update(gameTime);
} }

2
Game1/Sources/Crops/Farm.cs
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@ -319,7 +319,7 @@ class Farm
public float getProductionRate(int x, int y, int Type) public float getProductionRate(int x, int y, int Type)
{ {
return crops[x, y].getProductionRate(PresetCrops.getPresetCropTypes(Type)); return crops[x, y]. getProductionRate(PresetCrops.getPresetCropTypes(Type));
} }
public float GetRandomNumber(double minimum, double maximum) public float GetRandomNumber(double minimum, double maximum)

6
Game1/Sources/ML/MLModel.cs
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@ -11,7 +11,7 @@ using Microsoft.ML.Trainers.LightGbm;
class MLModel class MLModel
{ {
private static MLContext mlContext = new MLContext(seed: 1); private static MLContext mlContext = new MLContext(seed: 1);
/*
private static string path = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/Fertilizer_Prediction.csv"; private static string path = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/Fertilizer_Prediction.csv";
private static string modelpath = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodel"; private static string modelpath = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodel";
private static string report = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report"; private static string report = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report";
@ -19,7 +19,7 @@ class MLModel
private static string pathBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/BigFertPredict.csv"; private static string pathBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/BigFertPredict.csv";
private static string modelpathBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodelBig"; private static string modelpathBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodelBig";
private static string reportBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report_BigModel"; private static string reportBig = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report_BigModel";
*/ /*
private static string pathBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/BigFertPredict.csv"; private static string pathBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/BigFertPredict.csv";
private static string modelpathBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodelBig"; private static string modelpathBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodelBig";
private static string reportBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_BigModel"; private static string reportBig = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_BigModel";
@ -27,7 +27,7 @@ class MLModel
private static string path = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Fertilizer_Prediction.csv"; private static string path = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Fertilizer_Prediction.csv";
private static string modelpath = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel"; private static string modelpath = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel";
private static string report = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report"; private static string report = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report";
*/
// Loading data, creatin and saving ML model for smaller dataset (100) // Loading data, creatin and saving ML model for smaller dataset (100)
public static void CreateModel() public static void CreateModel()
{ {

5
Game1/Sources/ML_Joel/DataModel/OutputArea.cs
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@ -9,12 +9,7 @@ namespace Game1.Sources.ML_Joel
{ {
class OutputArea class OutputArea
{ {
//[ColumnName("PredictedLabel")]
public float Prediction { get; set; } public float Prediction { get; set; }
public float Score { get; set; } public float Score { get; set; }
//[ColumnName("Score")]
// public float[] Score { get; set; }
} }
} }

2
Game1/Sources/ML_Joel/Engine.cs
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@ -41,7 +41,7 @@ namespace Game1.Sources.ML_Joel
{ {
Season = Time.getTimeOfYear(), Season = Time.getTimeOfYear(),
Area = soilProperties.Area, Area = soilProperties.Area,
Rainfall = soilProperties.Humidity, Rainfall = soilProperties.prevRainfall,
}; };
OutputArea modelOutput = new OutputArea(); OutputArea modelOutput = new OutputArea();

17
Game1/Sources/ML_Joel/Model.cs
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@ -13,19 +13,24 @@ namespace Game1.Sources.ML_Joel
class Model class Model
{ {
private static MLContext mlContext = new MLContext(seed: 1); private static MLContext mlContext = new MLContext(seed: 1);
private static string path = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/Rainfall.csv";
private static string modelpath = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodel_Joel";
private static string report = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report_Joel";
private static string path_area = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/Rainfall_area.csv";
private static string modelpath_area = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/MLmodel_Joel_area";
private static string report_area = "C:/Users/Oskar/source/repos/PotatoPlanFinal/Game1/Content/ML/report_Joel_area";
/* /*
private static string path = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Rainfall.csv"; private static string path = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Rainfall.csv";
private static string modelpath = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel_Joel"; private static string modelpath = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel_Joel";
private static string report = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_Joel"; private static string report = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_Joel";
*/
private static string path = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Rainfall.csv";
private static string modelpath = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel_Joel";
private static string report = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_Joel";
private static string path_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Rainfall_area.csv"; private static string path_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/Rainfall_area.csv";
private static string modelpath_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel_Joel_area"; private static string modelpath_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/MLmodel_Joel_area";
private static string report_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_Joel_area"; private static string report_area = "C:/Users/Joel/source/repos/Oskars Repo/Game1/Content/ML/report_Joel_area";
*/
// Loading data, creatin and saving ML model for smaller dataset (100) // Loading data, creatin and saving ML model for smaller dataset (100)
public static void CreateModel() public static void CreateModel()
{ {
@ -142,7 +147,7 @@ namespace Game1.Sources.ML_Joel
var eval = mlContext.Regression.Evaluate(trainingDataView, labelColumnName: labelColumnName); var eval = mlContext.Regression.Evaluate(trainingDataView, labelColumnName: labelColumnName);
var report = File.CreateText(reportPath); var report = File.CreateText(reportPath);
report.Write("Mean Absolute Error: " + eval.MeanAbsoluteError + '\n' + "Mean Squared Error: " + eval.MeanSquaredError + '\n' + "R Squared: " + eval.RSquared, 0, 0); report.Write("Mean Absolute Error: " + eval.MeanAbsoluteError + '\n' + "R Squared: " + eval.RSquared, 0, 0);
report.Flush(); report.Flush();
report.Close(); report.Close();
} }