// BFGF Minimizer
public static Value Argmin(Value function, Value initial, Value tolerance, Netlist netlist, Style style, int s)
{
if (!(initial is ListValue <Value>))
{
throw new Error("argmin: expecting a list for second argument");
}
Vector <double> initialGuess = CreateVector.Dense((initial as ListValue <Value>).ToDoubleArray("argmin: expecting a list of numbers for second argument"));
if (!(tolerance is NumberValue))
{
throw new Error("argmin: expecting a number for third argument");
}
double toler = (tolerance as NumberValue).value;
if (!(function is FunctionValue))
{
throw new Error("argmin: expecting a function as first argument");
}
FunctionValue closure = function as FunctionValue;
if (closure.parameters.parameters.Count != 1)
{
throw new Error("argmin: initial values and function parameters have different lengths");
}
IObjectiveFunction objectiveFunction = ObjectiveFunction.Gradient(
(Vector <double> objParameters) => {
const string badResult = "argmin: objective function should return a list with a number (cost) and a list of numbers (partial derivatives of cost)";
List <Value> parameters = new List <Value>(); foreach (double parameter in objParameters)
{
parameters.Add(new NumberValue(parameter));
}
ListValue <Value> arg1 = new ListValue <Value>(parameters);
List <Value> arguments = new List <Value>(); arguments.Add(arg1);
bool autoContinue = netlist.autoContinue; netlist.autoContinue = true;
Value result = closure.ApplyReject(arguments, netlist, style, s);
if (result == null)
{
throw new Error(badResult);
}
netlist.autoContinue = autoContinue;
if (!(result is ListValue <Value>))
{
throw new Error(badResult);
}
List <Value> results = (result as ListValue <Value>).elements;
if (results.Count != 2 || !(results[0] is NumberValue) || !(results[1] is ListValue <Value>))
{
throw new Error(badResult);
}
double cost = (results[0] as NumberValue).value;
ListValue <Value> gradients = results[1] as ListValue <Value>;
KGui.gui.GuiOutputAppendText("argmin: parameters=" + arg1.Format(style) + " => cost=" + style.FormatDouble(cost) + ", gradients=" + results[1].Format(style) + Environment.NewLine);
return(new Tuple <double, Vector <double> >(cost, CreateVector.Dense(gradients.ToDoubleArray(badResult))));
});
try {
BfgsMinimizer minimizer = new BfgsMinimizer(toler, toler, toler);
MinimizationResult result = minimizer.FindMinimum(objectiveFunction, initialGuess);
if (result.ReasonForExit == ExitCondition.Converged || result.ReasonForExit == ExitCondition.AbsoluteGradient || result.ReasonForExit == ExitCondition.RelativeGradient)
{
List <Value> elements = new List <Value>();
for (int i = 0; i < result.MinimizingPoint.Count; i++)
{
elements.Add(new NumberValue(result.MinimizingPoint[i]));
}
ListValue <Value> list = new ListValue <Value>(elements);
KGui.gui.GuiOutputAppendText("argmin: converged with parameters " + list.Format(style) + " and reason '" + result.ReasonForExit + "'" + Environment.NewLine);
return(list);
}
else
{
throw new Error("reason '" + result.ReasonForExit.ToString() + "'");
}
} catch (Exception e) { throw new Error("argmin ended: " + ((e.InnerException == null) ? e.Message : e.InnerException.Message)); } // somehow we need to recatch the inner exception coming from CostAndGradient
}
