static double[][] MakeData(List <List <double> > trainData, int numItems,
IndicatorQT1 qt1, int numInput)
{
// make the result matrix holder (now first index is row)
double[][] result = new double[numItems][];
for (int r = 0; r < numItems; ++r)
{
// allocate the cols
result[r] = new double[numInput];
}
double dbInput = 0;
for (int r = 0; r < numItems; ++r)
{
double[] inputs = new double[numInput];
if ((trainData.Count + 1) > numInput)
{
for (int i = 0; i < numInput; ++i)
{
//skip col[0]
dbInput = trainData[i + 1][r];
inputs[i] = dbInput;
}
int c = 0;
for (int i = 0; i < numInput; ++i)
{
result[r][c++] = inputs[i];
}
}
}
return(result);
}
public ML03(int indicatorIndex, string label, string[] mathTerms,
string[] colNames, string[] depColNames,
string subalgorithm, int ciLevel, int iterations,
int random, IndicatorQT1 qT1, CalculatorParameters calcParams)
: base(indicatorIndex, label, mathTerms,
colNames, depColNames, subalgorithm, ciLevel, iterations,
random, qT1, calcParams)
{
}
public PRA1(int ciLevel, int iterations,
int random, IndicatorQT1 qT1, CalculatorParameters calcParams)
: base()
{
CILevel = ciLevel;
Random = random;
Iterations = iterations;
if (qT1 == null)
{
qT1 = new IndicatorQT1();
}
this.IndicatorQT = new IndicatorQT1(qT1);
Params = calcParams;
}
public PRA1(PRA1 pra1)
: base()
{
ColNames = pra1.ColNames;
_depColNames = pra1._depColNames;
MathTerms = pra1.MathTerms;
_subalgorithm = pra1._subalgorithm;
//188 anors can run algos and pass back totals to calling procedure
_totalsNeeded = pra1._totalsNeeded;
Label = pra1.Label;
CILevel = pra1.CILevel;
Random = pra1.Random;
Iterations = pra1.Iterations;
IndicatorQT = new IndicatorQT1(pra1.IndicatorQT);
//getobserveddata
ObsTs = pra1.ObsTs;
}
public Script1(string[] mathTerms, string[] colNames, string[] depColNames,
double[] qs, string algorithm, string subAlgorithm,
CalculatorParameters calcParams, IndicatorQT1 qt1)
: base()
{
_colNames = colNames;
_depColNames = depColNames;
_mathTerms = mathTerms;
_algorithm = algorithm;
_subalgorithm = subAlgorithm;
//estimators
//add an intercept to qs
_qs = new double[qs.Count() + 1];
//1 * b0 = b0
_qs[0] = 1;
qs.CopyTo(_qs, 1);
_params = calcParams;
//public and by ref back to algos
meta = new IndicatorQT1(qt1);
}
public MLBase(int indicatorIndex, string label, string[] mathTerms,
string[] colNames, string[] depColNames, string subalgorithm,
int ciLevel, int iterations, int random,
IndicatorQT1 qT1, CalculatorParameters calcParams)
: base()
{
_colNames = colNames;
_depColNames = depColNames;
_mathTerms = mathTerms;
_subalgorithm = subalgorithm;
_label = label;
_ciLevel = ciLevel;
_random = random;
_iterations = iterations;
if (qT1 == null)
{
qT1 = new IndicatorQT1();
}
IndicatorQT = new IndicatorQT1(qT1);
Params = calcParams;
}
public PRA1(string label, string[] mathTerms, string[] colNames, string[] depColNames,
int totalsNeeded, string subalgorithm, int ciLevel, int iterations,
int random, List <double> qTs, IndicatorQT1 qT1, CalculatorParameters calcParams)
: base()
{
ColNames = colNames;
_depColNames = depColNames;
MathTerms = mathTerms;
_subalgorithm = subalgorithm;
//188 anors can run algos and pass back totals to calling procedure
_totalsNeeded = totalsNeeded;
Label = label;
CILevel = ciLevel;
Random = random;
Iterations = iterations;
if (qT1 == null)
{
qT1 = new IndicatorQT1();
}
IndicatorQT = new IndicatorQT1(qT1);
//getobserveddata
ObsTs = qTs.ToArray();
Params = calcParams;
}
