public void WriteRLMSettings(RlmSettings settings)
{
var collection = settings.GetType().GetProperties();
List <string> headers = new List <string>();
List <string> data = new List <string>();
foreach (PropertyInfo pi in collection)
{
headers.Add(pi.Name);
data.Add(pi.GetValue(settings).ToString());
}
Sr.WriteLine(String.Join(",", headers));
Sr.WriteLine(String.Join(",", data));
}
private bool UpdateScoreHit(ref int currentHits, RlmSettings settings)
{
bool retVal = false;
if (TrainingVariables["SessionScore"].Value >= settings.SimulationTarget && settings.SimulationType == RlmSimulationType.Score)
{
currentHits++;
if (currentHits >= settings.NumScoreHits)
{
retVal = true;
}
}
else
{
currentHits = 0;
}
return(retVal);
}
static void Main(string[] args)
{
IRlmDbData rlmDbData = new RlmDbDataSQLServer("BasketballPrototype");
RlmOptimizer opt = new RlmOptimizer(rlmDbData);
Dictionary <string, Resource> resources = new Dictionary <string, Resource>();
Resource r1 = new Resource
{
Name = "Position",
Type = Category.Range,
RLMObject = RLMObject.Input,
Min = 1,
Max = 5,
DataType = "System.Int32",
RlmInputDataType = RlmInputDataType.Int,
RlmInputType = RlmInputType.Distinct
};
opt.Resources.Add(r1.Name, r1);
Resource r2 = new Resource
{
Name = "Player",
Type = Category.Data,
RLMObject = RLMObject.Output,
DataType = "System.Int32",
RlmInputDataType = RlmInputDataType.Int
};
r2.UploadDataResource("PlayerDetails2.csv");
opt.Resources.Add(r2.Name, r2);
//PG
var pgMetric = new Resource();
pgMetric.Name = "PGMetric";
pgMetric.Type = Category.Computed;
pgMetric.Formula = new string[]
{
@"([Player.Playmaking] * .3) +
([Player.OutsideScoring] * .3) +
([Player.PerimeterDefense] * .3) +
([Player.Speed] * .1)"
//([Player.Rebounding] * .05) +
//([Player.LowPostDefense] * .05) +
//([Player.Strength] * .05) +
//([Player.InsideScoring] * .05)"
};
opt.Resources.Add(pgMetric.Name, pgMetric);
//SG
var sgMetric = new Resource()
{
Name = "SGMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.Playmaking] * .1) +
([Player.OutsideScoring] * .5) +
([Player.PerimeterDefense] * .3) +
([Player.Speed] * .1)"
//([Player.Rebounding] * .07) +
//([Player.LowPostDefense] * .07) +
//([Player.Strength] * .06) +
//([Player.InsideScoring] * .1)"
}
};
opt.Resources.Add(sgMetric.Name, sgMetric);
//SF
var sfMetric = new Resource()
{
Name = "SFMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.OutsideScoring] * .3) +
([Player.PerimeterDefense] * .3) +
([Player.Speed] * .1) +
([Player.LowPostDefense] * .15) +
([Player.InsideScoring] * .15)"
}
};
opt.Resources.Add(sfMetric.Name, sfMetric);
//PF
var pfMetric = new Resource()
{
Name = "PFMetric",
Type = Category.Computed,
Formula = new string[]
{
//@"([Player.Playmaking] * .05) +
//([Player.OutsideScoring] * .05) +
//([Player.PerimeterDefense] * .05) +
//([Player.Speed] * .05) +
@"([Player.Rebounding] * .2) +
([Player.LowPostDefense] * .15) +
([Player.Strength] * .15) +
([Player.InsideScoring] * .5)"
}
};
opt.Resources.Add(pfMetric.Name, pfMetric);
//CENTER
var centerMetric = new Resource()
{
Name = "CenterMetric",
Type = Category.Computed,
Formula = new string[]
{
//@"([Player.Playmaking] * .05) +
//([Player.OutsideScoring] * .05) +
//([Player.PerimeterDefense] * .05) +
//([Player.Speed] * .05) +
@"([Player.Rebounding] * .4) +
([Player.LowPostDefense] * .3) +
([Player.Strength] * .2) +
([Player.InsideScoring] * .1)"
}
};
opt.Resources.Add(centerMetric.Name, centerMetric);
var totalMetric = new Resource();
totalMetric.Name = "Total";
totalMetric.Type = Category.Variable;
totalMetric.Value = 0;
opt.Resources.Add(totalMetric.Name, totalMetric);
//PG
Constraint pgConst = new Constraint()
{
Name = "PGConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 1 && [Player.Height] <= 194"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[PGMetric]" }
}
};
//SG
Constraint sgConst = new Constraint()
{
Name = "SGConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 2 && [Player.Height] > 194 && [Player.Height] <= 200"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[SGMetric]" }
}
};
//SF
Constraint sfConst = new Constraint()
{
Name = "SFConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 3 && [Player.Height] > 200 && [Player.Height] <= 208"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[SFMetric]" }
}
};
//PF
Constraint pfConst = new Constraint()
{
Name = "PFConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 4 && [Player.Height] > 208 && [Player.Height] <= 212"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[PFMetric]" }
}
};
//CENTER
Constraint centerConst = new Constraint()
{
Name = "CenterConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 5 && [Player.Height] > 212"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[CenterMetric]" }
}
};
var cyclePhase = new ScoringPhase();
cyclePhase.Name = "CycleScore";
cyclePhase.Formula = new string[]
{
"[CycleScore] = [PGConstraint] + [SGConstraint] + [SFConstraint] + [PFConstraint] + [CenterConstraint]",
"[SessionScore] = [SessionScore] + [CycleScore]",
};
//cyclePhase.Constraints.Add(cons1);
opt.Constraints[pgConst.Name] = pgConst; //PG
opt.Constraints[sgConst.Name] = sgConst; //SG
opt.Constraints[sfConst.Name] = sfConst; //SF
opt.Constraints[pfConst.Name] = pfConst; //PF
opt.Constraints[centerConst.Name] = centerConst; //CENTER
opt.CyclePhase = cyclePhase;
var sessionPhase = new ScoringPhase();
sessionPhase.Name = "SessionScore";
sessionPhase.Formula = new string[]
{
"[SessionScore]",
//"[Total] = 0"
};
opt.SessionPhase = sessionPhase;
RlmSettings settings = new RlmSettings()
{
Name = "BasketballOptimizer",
StartRandomness = 50,
EndRandomness = 0,
MaxLinearBracket = 15,
MinLinearBracket = 3,
NumOfSessionsReset = 100,
SimulationTarget = TargetForThisRun,
NumScoreHits = 10,
SimulationType = RlmSimulationType.Score,
Time = new TimeSpan(0, 5, 0),
DatabaseName = "BasketballPrototype"
};
opt.StartTraining(settings);
//Save to CSV Code
SaveToCSV saveToCSV = new SaveToCSV(FileNameForThisTest);
saveToCSV.WriteRLMSettings(settings);
//saveToCSV.WriteData(opt.SessionData, "Session,SessionScore");
//saveToCSV.WriteData(opt.PredictData, "Position,Score");
saveToCSV.WriteSpace();
for (int i = 1; i <= r1.Max; i++)
{
int output = Convert.ToInt32(opt.SessionOutputs["Player"].ElementAt(i - 1));
string line = $"Position: {i}, Player: {opt.Resources["Player"].DataObjDictionary.ElementAt(output).Value.AttributeDictionary["PlayerName"]}";
Console.WriteLine(line);
saveToCSV.WriteLine(line);
}
saveToCSV.WriteSpace();
//saveToCSV.WriteLine("Total Elapsed Time: " + opt.Elapsed);
//Console.WriteLine(compiler.Parse(cyclePhase));
Console.ReadLine();
}
public IDictionary <int, RlmCyclecompleteArgs> StartTraining(RlmSettings settings, CancellationToken?token = null)
{
dataPersistEvent.Reset();
//stopTraining = false;
//settings = this.Settings;
this.Settings = settings;
//Get RLM Settings from user
int startRandomness = settings.StartRandomness;
int endRandomness = settings.EndRandomness;
int maxBracket = settings.MaxLinearBracket;
int minBracket = settings.MinLinearBracket;
RlmSimulationType simType = settings.SimulationType;
TimeSpan time = settings.Time;
double target = settings.SimulationTarget;
// clear previous network, if any
ClearNetwork();
IDictionary <int, RlmCyclecompleteArgs> cycleOutputDic = null;
network = (string.IsNullOrEmpty(DatabaseName) ? new RlmNetwork() : new RlmNetwork(RlmDbData, true));
network.DataPersistenceComplete += Network_DataPersistenceComplete;
network.StartRandomness = startRandomness;
network.EndRandomness = endRandomness;
network.MaxLinearBracket = maxBracket;
network.MinLinearBracket = minBracket;
List <RlmIO> inputs = new List <RlmIO>();
List <RlmIO> outputs = new List <RlmIO>();
//get inputs/outputs from resources
var resourceInputs = Resources.Where(a => a.Value.RLMObject == RLMObject.Input);
var resourceOutputs = Resources.Where(a => a.Value.RLMObject == RLMObject.Output);
//set rlm inputs/outputs
inputs = GetRlmIOFromResource(resourceInputs);
outputs = GetRlmIOFromResource(resourceOutputs);
//create network
if (!network.LoadNetwork())
{
network.NewNetwork("RlmOptimizer", inputs, outputs);
}
//start training
int sessions = settings.SimulationType == RlmSimulationType.Sessions ? Convert.ToInt32(settings.SimulationTarget) : settings.NumOfSessionsReset;
double hours = settings.SimulationType == RlmSimulationType.Time ? settings.Time.TotalHours : 0;
DateTime endsOn = DateTime.Now.AddHours(hours);
TraceLog($"RLM Settings: \n\n" +
$"Randomness: Max = {startRandomness}, End = {endRandomness}\nLinear Bracket: Max = {maxBracket}, Min = {minBracket}\n" +
$"Simulation Type: {simType}\nTarget: {target}\nTime: {hours}\n" +
$"Cycle Score Formula: {string.Join(" | ", CyclePhase.Formula)}\n" +
$"Session Score Formula: {string.Join(" | ", SessionPhase.Formula)}");
TraceLog();
int scoreHits = 0;
bool timesUp = false;
//for (var trial = 1; trial <= 5; trial++)
//{
//TrainingLog($"\nTrial #{trial}");
do
{
//settings
network.NumSessions = sessions;
network.StartRandomness = startRandomness;
network.EndRandomness = endRandomness;
network.MaxLinearBracket = maxBracket;
network.MinLinearBracket = minBracket;
network.ResetRandomizationCounter();
if ((simType == RlmSimulationType.Time && DateTime.Compare(DateTime.Now, endsOn) == 1) || token?.IsCancellationRequested == true)
{
timesUp = true;
}
if (!timesUp)
{
TraceLog("\nTraining...\n");
for (int i = 1; i <= sessions; i++)
{
cycleOutputDic = RunOneSession(network, resourceInputs, true);
if (settings.SimulationType == RlmSimulationType.Score)
{
if (UpdateScoreHit(ref scoreHits, settings) || token?.IsCancellationRequested == true)
{
break;
}
}
if ((simType == RlmSimulationType.Time && DateTime.Compare(DateTime.Now, endsOn) == 1) || token?.IsCancellationRequested == true)
{
timesUp = true;
break;
}
if (stopTraining || token?.IsCancellationRequested == true)
{
break;
}
}
}
//predict
TraceLog("\nPredicting...\n");
if (settings.SimulationType == RlmSimulationType.Score)
{
for (int i = 1; i <= settings.NumScoreHits; i++)
{
cycleOutputDic = RunOneSession(network, resourceInputs, false, (i == settings.NumScoreHits));
if (UpdateScoreHit(ref scoreHits, settings) || token?.IsCancellationRequested == true)
{
break;
}
}
}
else
{
cycleOutputDic = RunOneSession(network, resourceInputs, false, true);
}
if (stopTraining || token?.IsCancellationRequested == true)
{
break;
}
} while ((!timesUp && simType == RlmSimulationType.Time) ||
(simType == RlmSimulationType.Score && settings.NumScoreHits > scoreHits));
//}
//end training
network.TrainingDone();
if (simType == RlmSimulationType.Score)
{
TraceLog($"Score Hits: {scoreHits}");
}
TraceLog("Optimization Done");
return(cycleOutputDic);
}
public static RlmOptimizer GetOptimizer()
{
RlmDbDataSQLServer rlmDb = new RlmDbDataSQLServer("BasketballOptimizer");
RlmOptimizer rlmOptimizer = new RlmOptimizer(rlmDb);
Dictionary <string, Resource> resources = new Dictionary <string, Resource>();
//input resource
Resource input1 = new Resource
{
Name = "Position",
Type = Category.Range,
RLMObject = RLMObject.Input,
Min = 1,
Max = 5,
DataType = "System.Int32",
RlmInputDataType = RlmInputDataType.Int,
RlmInputType = RlmInputType.Distinct
};
rlmOptimizer.Resources.Add(input1.Name, input1);
//output resource
Resource output1 = new Resource
{
Name = "Player",
Type = Category.Data,
RLMObject = RLMObject.Output,
DataType = "System.Int32",
RlmInputDataType = RlmInputDataType.Int
};
output1.UploadDataResource("PlayerDetails2.csv");
rlmOptimizer.Resources.Add(output1.Name, output1);
#region Metrics
//PG
var pgMetric = new Resource();
pgMetric.Name = "PGMetric";
pgMetric.Type = Category.Computed;
pgMetric.Formula = new string[]
{
@"([Player.Playmaking] * .3) +
([Player.OutsideScoring] * .3) +
([Player.PerimeterDefense] * .3) +
([Player.Speed] * .1)"
};
rlmOptimizer.Resources.Add(pgMetric.Name, pgMetric);
//SG
var sgMetric = new Resource()
{
Name = "SGMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.Playmaking] * .1) +
([Player.OutsideScoring] * .1) +
([Player.PerimeterDefense] * .2) +
([Player.Speed] * .6)"
}
};
rlmOptimizer.Resources.Add(sgMetric.Name, sgMetric);
//SF
var sfMetric = new Resource()
{
Name = "SFMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.OutsideScoring] * .1) +
([Player.PerimeterDefense] * .45) +
([Player.Speed] * .1) +
([Player.LowPostDefense] * .15) +
([Player.InsideScoring] * .25)"
}
};
rlmOptimizer.Resources.Add(sfMetric.Name, sfMetric);
//PF
var pfMetric = new Resource()
{
Name = "PFMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.Playmaking] * .05) +
([Player.OutsideScoring] * .35) +
([Player.PerimeterDefense] * .05) +
([Player.Speed] * .05) +
([Player.Rebounding] * .2) +
([Player.LowPostDefense] * .15) +
([Player.Strength] * .1) +
([Player.InsideScoring] * .05)"
}
};
rlmOptimizer.Resources.Add(pfMetric.Name, pfMetric);
//CENTER
var centerMetric = new Resource()
{
Name = "CenterMetric",
Type = Category.Computed,
Formula = new string[]
{
@"([Player.Playmaking] * .05) +
([Player.OutsideScoring] * .50) +
([Player.PerimeterDefense] * .05) +
([Player.Speed] * .1) +
([Player.Rebounding] * .1) +
([Player.LowPostDefense] * .1) +
([Player.Strength] * .1) +
([Player.InsideScoring] * .1)"
}
};
rlmOptimizer.Resources.Add(centerMetric.Name, centerMetric);
#endregion
#region Constraints
//PG
Constraint pgConst = new Constraint()
{
Name = "PGConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 1 && [Player.Height] > 195 && [Player.Height] <= 198"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[PGMetric]" }
}
};
//SG
Constraint sgConst = new Constraint()
{
Name = "SGConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 2 && [Player.Height] > 198 && [Player.Height] <= 203"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[SGMetric]" }
}
};
//SF
Constraint sfConst = new Constraint()
{
Name = "SFConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 3 && [Player.Height] == 200"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[SFMetric]" }
}
};
//PF
Constraint pfConst = new Constraint()
{
Name = "PFConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 4 && [Player.Height] > 205 && [Player.Height] <= 213"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[PFMetric]" }
}
};
//CENTER
Constraint centerConst = new Constraint()
{
Name = "CenterConstraint",
Formula = new List <string> {
"[CycleInputs.Position] == 5 && [Player.Height] > 205"
},
FailScore = new ConstraintScore()
{
Name = "FailScore", Formula = new string[] { "0" }
},
SuccessScore = new ConstraintScore()
{
Name = "SucessScore", Formula = new string[] { "[CenterMetric]" }
}
};
rlmOptimizer.Constraints[pgConst.Name] = pgConst; //PG
rlmOptimizer.Constraints[sgConst.Name] = sgConst; //SG
rlmOptimizer.Constraints[sfConst.Name] = sfConst; //SF
rlmOptimizer.Constraints[pfConst.Name] = pfConst; //PF
rlmOptimizer.Constraints[centerConst.Name] = centerConst; //CENTER
#endregion
//Cycle scoring formula
var cyclePhase = new ScoringPhase();
cyclePhase.Name = "CycleScore";
cyclePhase.Formula = new string[]
{
"[CycleScore] = [PGConstraint] + [SGConstraint] + [SFConstraint] + [PFConstraint] + [CenterConstraint]",
"[SessionScore] = [SessionScore] + [CycleScore]",
};
rlmOptimizer.CyclePhase = cyclePhase;
//Session scoring formula
var sessionPhase = new ScoringPhase();
sessionPhase.Name = "SessionScore";
sessionPhase.Formula = new string[]
{
"[SessionScore]"
};
rlmOptimizer.SessionPhase = sessionPhase;
//Settings
RlmSettings settings = new RlmSettings()
{
StartRandomness = 30,
EndRandomness = 0,
MaxLinearBracket = 15,
MinLinearBracket = 3,
NumOfSessionsReset = 100,
SimulationTarget = 500,
NumScoreHits = 10,
SimulationType = RlmSimulationType.Sessions,
Time = new TimeSpan(0, 0, 10)
};
rlmOptimizer.Settings = settings;
var resourceIn = rlmOptimizer.Resources.Where(a => a.Value.RLMObject == RLMObject.Input).First();
rlmOptimizer.CycleInputs[resourceIn.Value.Name] = 0;
var resourceOut = rlmOptimizer.Resources.Where(a => a.Value.RLMObject == RLMObject.Output).First();
rlmOptimizer.CycleOutputs[resourceOut.Value.Name] = 0;
rlmOptimizer.SessionOutputs["Player"] = new List <object> {
};
return(rlmOptimizer);
}
