public bool SolveSimple(AD.Term equation, AD.Variable[] args, double[,] limits, double[][] seeds)
{
rResults.Clear();
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
for (int i = 0; i < dim; i++)
{
this.ranges[i] = (this.limits[i, 1] - this.limits[i, 0]);
}
equation = equation.AggregateConstants();
term = AD.TermUtils.Compile(equation, args);
this.rpropStepWidth = new double[dim];
this.rpropStepConvergenceThreshold = new double[dim];
if (seeds != null)
{
for (int i = 0; i < seeds.Length; i++)
{
RpropResult r = RPropLoopSimple(seeds[i]);
rResults.Add(r);
if (r.finalUtil > 0.75)
{
return(true);
}
}
}
int runs = 2 * dim - (seeds == null?0:seeds.Length);
for (int i = 0; i < runs; i++)
{
RpropResult r = RPropLoopSimple(null);
rResults.Add(r);
if (r.finalUtil > 0.75)
{
return(true);
}
}
int adit = 0;
while (!EvalResults() && adit++ < 20)
{
RpropResult r = RPropLoopSimple(null);
rResults.Add(r);
if (r.finalUtil > 0.75)
{
return(true);
}
}
if (adit > 20)
{
Console.WriteLine("Failed to satisfy heuristic!");
}
return(false);
}
public double[] SolveTest(AD.Term equation, AD.Variable[] args, double[,] limits)
{
#if (GSOLVER_LOG)
InitLog();
#endif
rResults.Clear();
double[] res = null;
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
for (int i = 0; i < dim; i++)
{
this.ranges[i] = (this.limits[i, 1] - this.limits[i, 0]);
}
term = AD.TermUtils.Compile(equation, args);
this.rpropStepWidth = new double[dim];
this.samplePoint = new double[dim];
this.Runs = 1;
//this.Runs = 0;
this.FEvals = 0;
//int runs = 1000000;
RpropResult rfirst = RPropLoop(null, false, true);
if (rfirst.finalUtil > 0.75)
{
res = rfirst.finalValue;
}
else
{
while (true)
{
this.Runs++;
//RpropResult r = RPropLoopSimple(null);
RpropResult r = RPropLoop(null, false, false);
//Console.WriteLine("Run: {0} Util: {1}",i,r.finalUtil);
/*for(int k=0; k<dim; k++) {
* Console.Write("{0}\t",r.finalValue[k]);
* }
* Console.WriteLine();*/
if (r.finalUtil > 0.75)
{
res = r.finalValue;
break;
}
}
}
#if (GSOLVER_LOG)
CloseLog();
#endif
return(res);
}
public double[] SolveTest(AD.Term equation, AD.Variable[] args, double[,] limits, int maxRuns, out bool found)
{
#if (GSOLVER_LOG)
InitLog();
#endif
found = false;
rResults.Clear();
double[] res = null;
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
for (int i = 0; i < dim; i++)
{
this.ranges[i] = (this.limits[i, 1] - this.limits[i, 0]);
}
term = AD.TermUtils.Compile(equation, args);
this.rpropStepWidth = new double[dim];
this.rpropStepConvergenceThreshold = new double[dim];
this.Runs = 0;
this.FEvals = 0;
while (this.Runs < maxRuns)
{
this.Runs++;
//RpropResult r = RPropLoopSimple(null);
RpropResult r = RPropLoop(null, false);
//Console.WriteLine("Run: {0} Util: {1}",i,r.finalUtil);
/*for(int k=0; k<dim; k++) {
* Console.Write("{0}\t",r.finalValue[k]);
* }
* Console.WriteLine();*/
if (r.finalUtil > 0.75)
{
res = r.finalValue;
found = true;
break;
}
}
#if (GSOLVER_LOG)
CloseLog();
#endif
return(res);
}
private static bool TryTransformToAutoDiff(ISymbolicExpressionTreeNode node, List <AutoDiff.Variable> variables, List <AutoDiff.Variable> parameters, List <string> variableNames, bool updateVariableWeights, out AutoDiff.Term term)
{
if (node.Symbol is Constant)
{
var var = new AutoDiff.Variable();
variables.Add(var);
term = var;
return(true);
}
if (node.Symbol is Variable)
{
var varNode = node as VariableTreeNode;
var par = new AutoDiff.Variable();
parameters.Add(par);
variableNames.Add(varNode.VariableName);
if (updateVariableWeights)
{
var w = new AutoDiff.Variable();
variables.Add(w);
term = AutoDiff.TermBuilder.Product(w, par);
}
else
{
term = par;
}
return(true);
}
if (node.Symbol is Addition)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
terms.Add(t);
}
term = AutoDiff.TermBuilder.Sum(terms);
return(true);
}
if (node.Symbol is Subtraction)
{
List <AutoDiff.Term> terms = new List <Term>();
for (int i = 0; i < node.SubtreeCount; i++)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(i), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
if (i > 0)
{
t = -t;
}
terms.Add(t);
}
if (terms.Count == 1)
{
term = -terms[0];
}
else
{
term = AutoDiff.TermBuilder.Sum(terms);
}
return(true);
}
if (node.Symbol is Multiplication)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
terms.Add(t);
}
if (terms.Count == 1)
{
term = terms[0];
}
else
{
term = terms.Aggregate((a, b) => new AutoDiff.Product(a, b));
}
return(true);
}
if (node.Symbol is Division)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
terms.Add(t);
}
if (terms.Count == 1)
{
term = 1.0 / terms[0];
}
else
{
term = terms.Aggregate((a, b) => new AutoDiff.Product(a, 1.0 / b));
}
return(true);
}
if (node.Symbol is Logarithm)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Log(t);
return(true);
}
}
if (node.Symbol is Exponential)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Exp(t);
return(true);
}
}
if (node.Symbol is Square)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Power(t, 2.0);
return(true);
}
}
if (node.Symbol is SquareRoot)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Power(t, 0.5);
return(true);
}
}
if (node.Symbol is Sine)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = sin(t);
return(true);
}
}
if (node.Symbol is Cosine)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = cos(t);
return(true);
}
}
if (node.Symbol is Tangent)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = tan(t);
return(true);
}
}
if (node.Symbol is Erf)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = erf(t);
return(true);
}
}
if (node.Symbol is Norm)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out t))
{
term = null;
return(false);
}
else
{
term = norm(t);
return(true);
}
}
if (node.Symbol is StartSymbol)
{
var alpha = new AutoDiff.Variable();
var beta = new AutoDiff.Variable();
variables.Add(beta);
variables.Add(alpha);
AutoDiff.Term branchTerm;
if (TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, updateVariableWeights, out branchTerm))
{
term = branchTerm * alpha + beta;
return(true);
}
else
{
term = null;
return(false);
}
}
term = null;
return(false);
}
public double[] Solve(AD.Term equation, AD.Variable[] args, double[,] limits, double[][] seeds, double sufficientUtility, out double util)
{
this.FEvals = 0;
this.Runs = 0;
util = 0;
this.utilityThreshold = sufficientUtility;
#if (GSOLVER_LOG)
InitLog();
#endif
rResults.Clear();
ulong begin = RosCS.RosSharp.Now();
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
for (int i = 0; i < dim; i++)
{
this.ranges[i] = (this.limits[i, 1] - this.limits[i, 0]);
}
#if AGGREGATE_CONSTANTS
equation = equation.AggregateConstants();
#endif
term = AD.TermUtils.Compile(equation, args);
AD.ConstraintUtility cu = (AD.ConstraintUtility)equation;
bool utilIsConstant = (cu.Utility is AD.Constant);
if (utilIsConstant)
{
this.utilityThreshold = 0.75;
}
bool constraintIsConstant = (cu.Constraint is AD.Constant);
if (constraintIsConstant)
{
if (((AD.Constant)cu.Constraint).Value < 0.25)
{
util = ((AD.Constant)cu.Constraint).Value;
double[] ret = new double[dim];
for (int i = 0; i < dim; i++)
{
ret[i] = this.ranges[i] / 2.0 + this.limits[i, 0];
}
return(ret);
}
}
//Optimize given seeds
this.rpropStepWidth = new double[dim];
this.rpropStepConvergenceThreshold = new double[dim];
if (seeds != null)
{
this.Runs++;
//Run with prefered cached seed
RpropResult rpfirst = RPropLoop(seeds[0], true);
if (rpfirst.finalUtil > this.utilityThreshold)
{
util = rpfirst.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rpfirst.finalValue);
}
rResults.Add(rpfirst);
//run with seeds of all other agends
for (int i = 1; i < seeds.Length; i++)
{
if (begin + this.maxSolveTime < RosCS.RosSharp.Now() || this.FEvals > this.MaxFEvals)
{
break; //do not check any further seeds
}
this.Runs++;
RpropResult rp = RPropLoop(seeds[i], false);
if (rp.finalUtil > this.utilityThreshold)
{
util = rp.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rp.finalValue);
}
rResults.Add(rp);
}
}
//Here: Ignore all constraints search optimum
if (begin + this.maxSolveTime > RosCS.RosSharp.Now() && this.FEvals < this.MaxFEvals)
{
//if time allows, do an unconstrained run
if (!constraintIsConstant && !utilIsConstant && seedWithUtilOptimum)
{
AD.ICompiledTerm curProb = term;
term = AD.TermUtils.Compile(((AD.ConstraintUtility)equation).Utility, args);
this.Runs++;
double[] utilitySeed = RPropLoop(null).finalValue;
term = curProb;
//Take result and search with constraints
RpropResult ru = RPropLoop(utilitySeed, false);
/*if (ru.finalUtil > this.utilityThreshold) {
* util = ru.finalUtil;
* return ru.finalValue;
* }*/
rResults.Add(ru);
}
}
do //Do runs until termination criteria, running out of time, or too many function evaluations
{
this.Runs++;
RpropResult rp = RPropLoop(null, false);
if (rp.finalUtil > this.utilityThreshold)
{
util = rp.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rp.finalValue);
}
rResults.Add(rp);
} while(begin + this.maxSolveTime > RosCS.RosSharp.Now() && this.FEvals < this.MaxFEvals);
//return best result
int resIdx = 0;
RpropResult res = rResults[0];
for (int i = 1; i < rResults.Count; i++)
{
if (Double.IsNaN(res.finalUtil) || rResults[i].finalUtil > res.finalUtil)
{
if (resIdx == 0 && seeds != null && !Double.IsNaN(res.finalUtil))
{
if (rResults[i].finalUtil - res.finalUtil > utilitySignificanceThreshold && rResults[i].finalUtil > 0.75)
{
res = rResults[i];
resIdx = i;
}
}
else
{
res = rResults[i];
resIdx = i;
}
}
}
//Console.WriteLine("ResultIndex: {0} Delta {1}",resIdx,res.finalUtil-rResults[0].finalUtil);
#if (GSOLVER_LOG)
CloseLog();
#endif
// Console.Write("Found: ");
// for(int i=0; i<dim; i++) {
// Console.Write("{0}\t",res.finalValue[i]);
// }
// Console.WriteLine();
//
//Console.WriteLine("Runs: {0} FEvals: {1}",this.Runs,this.FEvals);
util = res.finalUtil;
return(res.finalValue);
}
public bool SolveSimple(AD.Term equation, AD.Variable[] args, double[,] limits)
{
return(SolveSimple(equation, args, limits, null));
}
public double[] Solve(AD.Term equation, AD.Variable[] args, double[,] limits, out double util)
{
return(Solve(equation, args, limits, null, Double.MaxValue, out util));
}
private static bool TryTransformToAutoDiff(ISymbolicExpressionTreeNode node, List <AutoDiff.Variable> variables, List <AutoDiff.Variable> parameters, List <string> variableNames, out AutoDiff.Term term)
{
if (node.Symbol is Constant)
{
var var = new AutoDiff.Variable();
variables.Add(var);
term = var;
return(true);
}
if (node.Symbol is Variable)
{
var varNode = node as VariableTreeNode;
var par = new AutoDiff.Variable();
parameters.Add(par);
variableNames.Add(varNode.VariableName);
var w = new AutoDiff.Variable();
variables.Add(w);
term = AutoDiff.TermBuilder.Product(w, par);
return(true);
}
if (node.Symbol is Addition)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
terms.Add(t);
}
term = AutoDiff.TermBuilder.Sum(terms);
return(true);
}
if (node.Symbol is Subtraction)
{
List <AutoDiff.Term> terms = new List <Term>();
for (int i = 0; i < node.SubtreeCount; i++)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(i), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
if (i > 0)
{
t = -t;
}
terms.Add(t);
}
term = AutoDiff.TermBuilder.Sum(terms);
return(true);
}
if (node.Symbol is Multiplication)
{
AutoDiff.Term a, b;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out a) ||
!TryTransformToAutoDiff(node.GetSubtree(1), variables, parameters, variableNames, out b))
{
term = null;
return(false);
}
else
{
List <AutoDiff.Term> factors = new List <Term>();
foreach (var subTree in node.Subtrees.Skip(2))
{
AutoDiff.Term f;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, out f))
{
term = null;
return(false);
}
factors.Add(f);
}
term = AutoDiff.TermBuilder.Product(a, b, factors.ToArray());
return(true);
}
}
if (node.Symbol is Division)
{
// only works for at least two subtrees
AutoDiff.Term a, b;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out a) ||
!TryTransformToAutoDiff(node.GetSubtree(1), variables, parameters, variableNames, out b))
{
term = null;
return(false);
}
else
{
List <AutoDiff.Term> factors = new List <Term>();
foreach (var subTree in node.Subtrees.Skip(2))
{
AutoDiff.Term f;
if (!TryTransformToAutoDiff(subTree, variables, parameters, variableNames, out f))
{
term = null;
return(false);
}
factors.Add(1.0 / f);
}
term = AutoDiff.TermBuilder.Product(a, 1.0 / b, factors.ToArray());
return(true);
}
}
if (node.Symbol is Logarithm)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Log(t);
return(true);
}
}
if (node.Symbol is Exponential)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Exp(t);
return(true);
}
}
if (node.Symbol is Square)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Power(t, 2.0);
return(true);
}
}
if (node.Symbol is SquareRoot)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = AutoDiff.TermBuilder.Power(t, 0.5);
return(true);
}
}
if (node.Symbol is Sine)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = sin(t);
return(true);
}
}
if (node.Symbol is Cosine)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = cos(t);
return(true);
}
}
if (node.Symbol is Tangent)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = tan(t);
return(true);
}
}
if (node.Symbol is Erf)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = erf(t);
return(true);
}
}
if (node.Symbol is Norm)
{
AutoDiff.Term t;
if (!TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out t))
{
term = null;
return(false);
}
else
{
term = norm(t);
return(true);
}
}
if (node.Symbol is StartSymbol)
{
var alpha = new AutoDiff.Variable();
var beta = new AutoDiff.Variable();
variables.Add(beta);
variables.Add(alpha);
AutoDiff.Term branchTerm;
if (TryTransformToAutoDiff(node.GetSubtree(0), variables, parameters, variableNames, out branchTerm))
{
term = branchTerm * alpha + beta;
return(true);
}
else
{
term = null;
return(false);
}
}
term = null;
return(false);
}
private AutoDiff.Term ConvertToAutoDiff(ISymbolicExpressionTreeNode node)
{
if (node.Symbol is Constant)
{
initialConstants.Add(((ConstantTreeNode)node).Value);
var var = new AutoDiff.Variable();
variables.Add(var);
return(var);
}
if (node.Symbol is Variable || node.Symbol is BinaryFactorVariable)
{
var varNode = node as VariableTreeNodeBase;
var factorVarNode = node as BinaryFactorVariableTreeNode;
// factor variable values are only 0 or 1 and set in x accordingly
var varValue = factorVarNode != null ? factorVarNode.VariableValue : string.Empty;
var par = FindOrCreateParameter(parameters, varNode.VariableName, varValue);
if (makeVariableWeightsVariable)
{
initialConstants.Add(varNode.Weight);
var w = new AutoDiff.Variable();
variables.Add(w);
return(AutoDiff.TermBuilder.Product(w, par));
}
else
{
return(varNode.Weight * par);
}
}
if (node.Symbol is FactorVariable)
{
var factorVarNode = node as FactorVariableTreeNode;
var products = new List <Term>();
foreach (var variableValue in factorVarNode.Symbol.GetVariableValues(factorVarNode.VariableName))
{
var par = FindOrCreateParameter(parameters, factorVarNode.VariableName, variableValue);
initialConstants.Add(factorVarNode.GetValue(variableValue));
var wVar = new AutoDiff.Variable();
variables.Add(wVar);
products.Add(AutoDiff.TermBuilder.Product(wVar, par));
}
return(AutoDiff.TermBuilder.Sum(products));
}
if (node.Symbol is LaggedVariable)
{
var varNode = node as LaggedVariableTreeNode;
var par = FindOrCreateParameter(parameters, varNode.VariableName, string.Empty, varNode.Lag);
if (makeVariableWeightsVariable)
{
initialConstants.Add(varNode.Weight);
var w = new AutoDiff.Variable();
variables.Add(w);
return(AutoDiff.TermBuilder.Product(w, par));
}
else
{
return(varNode.Weight * par);
}
}
if (node.Symbol is Addition)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
terms.Add(ConvertToAutoDiff(subTree));
}
return(AutoDiff.TermBuilder.Sum(terms));
}
if (node.Symbol is Subtraction)
{
List <AutoDiff.Term> terms = new List <Term>();
for (int i = 0; i < node.SubtreeCount; i++)
{
AutoDiff.Term t = ConvertToAutoDiff(node.GetSubtree(i));
if (i > 0)
{
t = -t;
}
terms.Add(t);
}
if (terms.Count == 1)
{
return(-terms[0]);
}
else
{
return(AutoDiff.TermBuilder.Sum(terms));
}
}
if (node.Symbol is Multiplication)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
terms.Add(ConvertToAutoDiff(subTree));
}
if (terms.Count == 1)
{
return(terms[0]);
}
else
{
return(terms.Aggregate((a, b) => new AutoDiff.Product(a, b)));
}
}
if (node.Symbol is Division)
{
List <AutoDiff.Term> terms = new List <Term>();
foreach (var subTree in node.Subtrees)
{
terms.Add(ConvertToAutoDiff(subTree));
}
if (terms.Count == 1)
{
return(1.0 / terms[0]);
}
else
{
return(terms.Aggregate((a, b) => new AutoDiff.Product(a, 1.0 / b)));
}
}
if (node.Symbol is Absolute)
{
var x1 = ConvertToAutoDiff(node.GetSubtree(0));
return(abs(x1));
}
if (node.Symbol is AnalyticQuotient)
{
var x1 = ConvertToAutoDiff(node.GetSubtree(0));
var x2 = ConvertToAutoDiff(node.GetSubtree(1));
return(x1 / (TermBuilder.Power(1 + x2 * x2, 0.5)));
}
if (node.Symbol is Logarithm)
{
return(AutoDiff.TermBuilder.Log(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Exponential)
{
return(AutoDiff.TermBuilder.Exp(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Square)
{
return(AutoDiff.TermBuilder.Power(
ConvertToAutoDiff(node.GetSubtree(0)), 2.0));
}
if (node.Symbol is SquareRoot)
{
return(AutoDiff.TermBuilder.Power(
ConvertToAutoDiff(node.GetSubtree(0)), 0.5));
}
if (node.Symbol is Cube)
{
return(AutoDiff.TermBuilder.Power(
ConvertToAutoDiff(node.GetSubtree(0)), 3.0));
}
if (node.Symbol is CubeRoot)
{
return(cbrt(ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Sine)
{
return(sin(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Cosine)
{
return(cos(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Tangent)
{
return(tan(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is HyperbolicTangent)
{
return(tanh(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Erf)
{
return(erf(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is Norm)
{
return(norm(
ConvertToAutoDiff(node.GetSubtree(0))));
}
if (node.Symbol is StartSymbol)
{
if (addLinearScalingTerms)
{
// scaling variables α, β are given at the beginning of the parameter vector
var alpha = new AutoDiff.Variable();
var beta = new AutoDiff.Variable();
variables.Add(beta);
variables.Add(alpha);
var t = ConvertToAutoDiff(node.GetSubtree(0));
return(t * alpha + beta);
}
else
{
return(ConvertToAutoDiff(node.GetSubtree(0)));
}
}
throw new ConversionException();
}
public void Compile(Term term)
{
term.Accept(this);
}
public double[] Solve(AD.Term equation, AD.Variable[] args, double[,] limits, double[][] seeds, out double util)
{
//this.FEvals = 0;
util = 0;
#if (GSOLVER_LOG)
InitLog();
#endif
rResults.Clear();
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
for (int i = 0; i < dim; i++)
{
this.ranges[i] = (this.limits[i, 1] - this.limits[i, 0]);
}
equation = equation.AggregateConstants();
term = AD.TermUtils.Compile(equation, args);
AD.ConstraintUtility cu = (AD.ConstraintUtility)equation;
bool utilIsConstant = (cu.Utility is AD.Constant);
bool constraintIsConstant = (cu.Constraint is AD.Constant);
if (constraintIsConstant)
{
if (((AD.Constant)cu.Constraint).Value < 0.25)
{
util = ((AD.Constant)cu.Constraint).Value;
double[] ret = new double[dim];
for (int i = 0; i < dim; i++)
{
ret[i] = this.ranges[i] / 2.0 + this.limits[i, 0];
}
return(ret);
}
}
this.rpropStepWidth = new double[dim];
this.samplePoint = new double[dim];
if (seeds != null)
{
RpropResult rpfirst = RPropLoop(seeds[0], true, false);
if (utilIsConstant && rpfirst.finalUtil > 0.75)
{
util = rpfirst.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rpfirst.finalValue);
}
rResults.Add(rpfirst);
for (int i = 1; i < seeds.Length; i++)
{
RpropResult rp = RPropLoop(seeds[i], false, false);
if (utilIsConstant && rp.finalUtil > 0.75)
{
util = rp.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rp.finalValue);
}
rResults.Add(rp);
}
}
if (!constraintIsConstant && !utilIsConstant && seedWithUtilOptimum)
{
AD.ICompiledTerm curProb = term;
term = AD.TermUtils.Compile(((AD.ConstraintUtility)equation).Utility, args);
double[] utilitySeed = RPropLoop(null).finalValue;
/*Console.WriteLine("Unconstraint Seed:");
* Console.Write("S: ");
* foreach(double d in utilitySeed) Console.Write("{0} ",d);
* Console.WriteLine();
*/
term = curProb;
rResults.Add(RPropLoop(utilitySeed, false, false));
}
int runs = Math.Max(3, 1 * dim - (seeds == null?0:seeds.Length));
//runs = 10;
RpropResult rpQS = RPropLoop(null, false, true);
if (utilIsConstant && rpQS.finalUtil > 0.75)
{
util = rpQS.finalUtil;
return(rpQS.finalValue);
}
rResults.Add(rpQS);
for (int i = 1; i < runs; i++)
{
RpropResult rp = RPropLoop(null, false, false);
if (utilIsConstant && rp.finalUtil > 0.75)
{
util = rp.finalUtil;
//Console.WriteLine("FEvals: {0}",this.FEvals);
return(rp.finalValue);
}
rResults.Add(rp);
}
int resIdx = 0;
RpropResult res = rResults[0];
for (int i = 1; i < rResults.Count; i++)
{
if (Double.IsNaN(res.finalUtil) || rResults[i].finalUtil > res.finalUtil)
{
if (resIdx == 0 && seeds != null && !Double.IsNaN(res.finalUtil))
{
if (rResults[i].finalUtil - res.finalUtil > utilitySignificanceThreshold && rResults[i].finalUtil > 0.75)
{
res = rResults[i];
resIdx = i;
}
}
else
{
res = rResults[i];
resIdx = i;
}
}
}
//Console.WriteLine("ResultIndex: {0} Delta {1}",resIdx,res.finalUtil-rResults[0].finalUtil);
#if (GSOLVER_LOG)
CloseLog();
#endif
// Console.Write("Found: ");
// for(int i=0; i<dim; i++) {
// Console.Write("{0}\t",res.finalValue[i]);
// }
// Console.WriteLine();
//
//Console.WriteLine("FEvals: {0}",this.FEvals);
util = res.finalUtil;
return(res.finalValue);
}
protected RpropResult RPropOptimizeFeasible(List <CNSAT.Var> constraints, AD.Term ut, AD.Variable[] args, double[] seed, bool precise)
{
//Compiled Term zusammenbauen
AD.Term constr = AD.Term.True;
foreach (CNSAT.Var v in constraints)
{
if (v.Assignment == Alica.Reasoner.CNSAT.Assignment.True)
{
constr &= v.Term;
}
else
{
constr &= ConstraintBuilder.Not(v.Term);
}
}
AD.ConstraintUtility cu = new AD.ConstraintUtility(constr, ut);
AD.ICompiledTerm term = AD.TermUtils.Compile(cu, args);
Tuple <double[], double> tup;
//fertig zusammengebaut
runCount++;
InitialStepSize();
double[] curGradient;
RpropResult ret = new RpropResult();
// curGradient = InitialPoint(constraints, ret);
if (seed != null)
{
curGradient = InitialPointFromSeed(constraints, ret, seed);
}
else
{
curGradient = InitialPoint(constraints, ret);
}
double curUtil = ret.initialUtil;
double[] formerGradient = new double[dim];
double[] curValue = new double[dim];
//Tuple<double[],double> tup;
Buffer.BlockCopy(ret.initialValue, 0, curValue, 0, sizeof(double) * dim);
formerGradient = curGradient;
int itcounter = 0;
int badcounter = 0;
#if (GSOLVER_LOG)
Log(curUtil, curValue);
#endif
int maxIter = 60;
int maxBad = 30;
double minStep = 1E-11;
if (precise)
{
maxIter = 120; //110
maxBad = 60; //60
minStep = 1E-15; //15
}
int convergendDims = 0;
while (itcounter++ < maxIter && badcounter < maxBad)
{
convergendDims = 0;
for (int i = 0; i < dim; i++)
{
if (curGradient[i] * formerGradient[i] > 0)
{
rpropStepWidth[i] *= 1.3;
}
else if (curGradient[i] * formerGradient[i] < 0)
{
rpropStepWidth[i] *= 0.5;
}
rpropStepWidth[i] = Math.Max(minStep, rpropStepWidth[i]);
//rpropStepWidth[i] = Math.Max(0.000001,rpropStepWidth[i]);
if (curGradient[i] > 0)
{
curValue[i] += rpropStepWidth[i];
}
else if (curGradient[i] < 0)
{
curValue[i] -= rpropStepWidth[i];
}
if (curValue[i] > limits[i, 1])
{
curValue[i] = limits[i, 1];
}
else if (curValue[i] < limits[i, 0])
{
curValue[i] = limits[i, 0];
}
//Console.Write("{0}\t",curValue[i]);
if (rpropStepWidth[i] < rpropStepConvergenceThreshold[i])
{
++convergendDims;
}
}
//Abort if all dimensions are converged
if (!precise && convergendDims >= dim)
{
return(ret);
}
this.fevalsCount++;
formerGradient = curGradient;
tup = term.Differentiate(curValue);
bool allZero = true;
for (int i = 0; i < dim; i++)
{
if (Double.IsNaN(tup.Item1[i]))
{
ret.aborted = false; //true; //HACK!
#if (GSOLVER_LOG)
LogStep();
#endif
return(ret);
}
allZero &= (tup.Item1[i] == 0);
}
curUtil = tup.Item2;
formerGradient = curGradient;
curGradient = tup.Item1;
#if (GSOLVER_LOG)
Log(curUtil, curValue);
#endif
//Console.WriteLine("CurUtil: {0} Final {1}",curUtil,ret.finalUtil);
if (curUtil > ret.finalUtil)
{
badcounter = 0; //Math.Max(0,badcounter-1);
ret.finalUtil = curUtil;
Buffer.BlockCopy(curValue, 0, ret.finalValue, 0, sizeof(double) * dim);
//ret.finalValue = curValue;
if (curUtil > 0.75)
{
return(ret);
}
}
else
{
badcounter++;
}
if (allZero)
{
ret.aborted = false;
#if (GSOLVER_LOG)
LogStep();
#endif
return(ret);
}
}
#if (GSOLVER_LOG)
LogStep();
#endif
ret.aborted = false;
return(ret);
}
//Stripped down method for simpler testing
public double[] SolveTest(AD.Term equation, AD.Variable[] args, double[,] limits)
{
lastSeed = null;
probeCount = 0;
successProbeCount = 0;
intervalCount = 0;
successIntervalCount = 0;
fevalsCount = 0;
runCount = 0;
//this.FEvals = 0;
double util = 0;
this.begin = RosCS.RosSharp.Now();
#if (GSOLVER_LOG)
InitLog();
#endif
//ft.Reset();
rResults.Clear();
currentArgs = args;
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
this.rpropStepWidth = new double[dim];
this.rpropStepConvergenceThreshold = new double[dim];
equation = equation.AggregateConstants();
ss = new CNSAT.CNSat();
ss.UseIntervalProp = this.UseIntervalProp;
//Console.WriteLine(cu.Constraint);
LinkedList <CNSAT.Clause> cnf = ft.TransformToCNF(equation, ss);
/*Console.WriteLine("Atoms: {0}, Occurrence: {1}",ft.Atoms.Count,ft.AtomOccurrence);
* Console.WriteLine("Clauses: {0}",cnf.Count);
* foreach(AD.Term atom in ft.Atoms.Keys) {
* Console.WriteLine("-------");
* Console.WriteLine(atom);
* Console.WriteLine("-------");
* }*/
/*
* int litc=1;
* List<AD.Term> terms = new List<AD.Term>(ft.Atoms);
*
* currentAtoms = new Dictionary<int, Term>();
*
* foreach(AD.Term t in terms) {
* foreach(Literal l in ft.References[t]) {
* l.Id = litc;
* }
* currentAtoms.Add(litc,t);
* litc++;
* }*/
ip.SetGlobalRanges(args, limits, ss);
foreach (CNSAT.Clause c in cnf)
{
if (!c.IsTautologic)
{
if (c.Literals.Count == 0)
{
util = Double.MinValue;
double[] ret = new double[dim];
for (int i = 0; i < dim; i++)
{
ret[i] = (this.limits[i, 1] + this.limits[i, 0]) / 2.0;
}
return(ret);
}
//Post Clause Here
//Console.Write("\nAdding Clause with "+c.Literals.Count+" Literals\n");
//c.Print();
ss.addBasicClause(c);
}
}
ss.CNSMTGSolver = this;
ss.Init();
//PRE-Propagation:
#if DO_PREPROPAGATION
if (!ip.PrePropagate(ss.Variables))
{
Console.WriteLine("Unsatisfiable (unit propagation)");
//return null;
}
#endif
//END-PrePropagation
//Console.WriteLine("Variable Count: " + ss.Variables.Count);
bool solutionFound = false;
solutionFound = ss.solve();
//Console.WriteLine("Solution Found!!!!!");
if (!solutionFound && r1.finalUtil > 0)
{
r1.finalUtil = -1;
}
util = r1.finalUtil;
//if(util>this.utilitySignificanceThreshold) return r1.finalValue;
return(r1.finalValue);
}
public double[] Solve(AD.Term equation, AD.Variable[] args, double[,] limits, double[][] seeds, out double util)
{
lastSeed = null;
probeCount = 0;
successProbeCount = 0;
intervalCount = 0;
successIntervalCount = 0;
fevalsCount = 0;
runCount = 0;
this.begin = RosCS.RosSharp.Now();
//this.FEvals = 0;
util = 0;
#if (GSOLVER_LOG)
InitLog();
#endif
//ft.Reset();
rResults.Clear();
currentArgs = args;
this.dim = args.Length;
this.limits = limits;
this.ranges = new double[dim];
this.rpropStepWidth = new double[dim];
this.rpropStepConvergenceThreshold = new double[dim];
equation = equation.AggregateConstants();
AD.ConstraintUtility cu = (AD.ConstraintUtility)equation;
bool utilIsConstant = (cu.Utility is AD.Constant);
bool constraintIsConstant = (cu.Constraint is AD.Constant);
if (constraintIsConstant)
{
if (((AD.Constant)cu.Constraint).Value < 0.25)
{
util = ((AD.Constant)cu.Constraint).Value;
double[] ret = new double[dim];
for (int i = 0; i < dim; i++)
{
ret[i] = (this.limits[i, 1] + this.limits[i, 0]) / 2.0;
//this.ranges[i]/2.0+this.limits[i,0];
}
return(ret);
}
}
ss = new CNSAT.CNSat();
ss.UseIntervalProp = this.UseIntervalProp;
//Console.WriteLine(cu.Constraint);
LinkedList <CNSAT.Clause> cnf = ft.TransformToCNF(cu.Constraint, ss);
/*Console.WriteLine("Atoms: {0}, Occurrence: {1}",ft.Atoms.Count,ft.AtomOccurrence);
* Console.WriteLine("Clauses: {0}",cnf.Count);
* foreach(AD.Term atom in ft.Atoms.Keys) {
* Console.WriteLine("-------");
* Console.WriteLine(atom);
* Console.WriteLine("-------");
* }*/
/*
* int litc=1;
* List<AD.Term> terms = new List<AD.Term>(ft.Atoms);
*
* currentAtoms = new Dictionary<int, Term>();
*
* foreach(AD.Term t in terms) {
* foreach(Literal l in ft.References[t]) {
* l.Id = litc;
* }
* currentAtoms.Add(litc,t);
* litc++;
* }*/
if (UseIntervalProp)
{
ip.SetGlobalRanges(args, limits, ss);
}
foreach (CNSAT.Clause c in cnf)
{
if (!c.IsTautologic)
{
if (c.Literals.Count == 0)
{
util = Double.MinValue;
double[] ret = new double[dim];
for (int i = 0; i < dim; i++)
{
ret[i] = (this.limits[i, 1] + this.limits[i, 0]) / 2.0;
}
return(ret);
}
//Post Clause Here
//Console.Write("\nAdding Clause with "+c.Literals.Count+" Literals\n");
//c.Print();
ss.addBasicClause(c);
}
}
ss.CNSMTGSolver = this;
ss.Init();
//PRE-Propagation:
if (UseIntervalProp)
{
#if DO_PREPROPAGATION
if (!ip.PrePropagate(ss.Variables))
{
Console.WriteLine("Unsatisfiable (unit propagation)");
return(null);
}
#endif
}
//END-PrePropagation
//Console.WriteLine("Variable Count: " + ss.Variables.Count);
bool solutionFound = false;
ss.UnitDecissions = ss.Decisions.Count;
do
{
if (!solutionFound)
{
ss.EmptySATClause();
ss.EmptyTClause();
ss.backTrack(ss.UnitDecissions);
}
solutionFound = ss.solve();
if (Optimize)
{
r1 = RPropOptimizeFeasible(ss.Decisions, ((AD.ConstraintUtility)equation).Utility, args, r1.finalValue, false);
}
if (!solutionFound && r1.finalUtil > 0)
{
r1.finalUtil = -1;
}
util = r1.finalUtil;
if (!Optimize && solutionFound)
{
return(r1.finalValue);
}
else if (Optimize)
{
//optimization case
rResults.Add(r1);
CNSAT.Clause c = new Alica.Reasoner.CNSAT.Clause();
foreach (CNSAT.Var v in ss.Decisions)
{
c.Add(new CNSAT.Lit(v, v.Assignment == CNSAT.Assignment.True ? CNSAT.Assignment.False : CNSAT.Assignment.True));
}
//ss.addBasicClause(c);
ss.addIClause(c);
ss.backTrack(ss.Decisions[ss.Decisions.Count - 1].DecisionLevel);
solutionFound = false;
}
} while (!solutionFound && this.begin + this.maxSolveTime > RosCS.RosSharp.Now() /*&& this.runCount < this.MaxFEvals*/);
//Console.WriteLine("Probes: {0}/{1}\tIntervals: {2}/{3}",successProbeCount,probeCount,successIntervalCount,intervalCount);
//ip.PrintStats();
//Console.WriteLine("Rprop Runs: {0}\t FEvals {1}\t Solutions Found: {2}",this.runCount,this.fevalsCount, rResults.Count);
//return best result
if (rResults.Count > 0)
{
foreach (RpropResult rp in rResults)
{
if (rp.finalUtil > util)
{
util = rp.finalUtil;
r1 = rp;
}
}
return(r1.finalValue);
}
Console.WriteLine("Unsatisfiable");
return(null);
}