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JSON response:
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"n" : "MODEL_NEW",
"vis" : "1",
"type" : "Problem",
"problemMd" :
{
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{
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"calculationChain" :
{
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{
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{
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"id" : "OBJ4",
"n" : "MyOutputVavable|A[t] = MyInputVavable|A[t] * a + b, 1990A1-2010A1",
"vis" : "1",
"type" : "Model",
"excluded" : "0",
"graphMeta" : "",
"model" :
{
"transform" :
{
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{
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{
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},
"formulaCount" : "1",
"formulas" :
{
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{
"it" :
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{
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"operands" :
{
"its" :
{
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{
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]
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},
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},
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{
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{
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}
]
}
},
"optimizationMethod" : "LevenbergMarquardt",
"tolerance" : "0.0001",
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},
"name" : "X2 * (-0.0783) + 4.3745",
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},
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},
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"autoName" : "1",
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},
"visualController" :
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}
public static MsCalculationChainEntry GetMsNonLinearRegr(MsId ms, ulong modelKey, ulong eqKey)
{
var getMsOp = new GetMs();
// Set operation execution parameters
getMsOp.tMs = ms;
getMsOp.tArg = new GetMsArg()
{ // Set data getting pattern
pattern = new MsMdPattern()
{
obInst = false,
all = false,
item = new MsItemPattern()
{ // Specify calculated model class
key = modelKey,
problem = new MsProblemPattern()
{
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Get,
calcChainPattern = new MsCalculationChainPattern()
{
// Specify calculated equation key
entryKeys = new long[] { (long)eqKey },
modelPattern = new MsModelPattern()
{
autoName = true,
calculationPeriod = true,
generatedName = true,
isExclusive = true,
period = true,
stochastic = true,
treatNullsAsZeros = true,
useAutoPeriod = true,
useExistingData = true,
useModelPeriod = true,
transform = new MsFormulaTransformPattern()
{
additionalAttributes = true,
calculationDirection = true,
calculationType = true,
displayId = true,
displaySettings = true,
formulaCount = true,
outputs = ListOperation.Get,
series = ListOperation.Get,
kind = true,
formulas = new TsFormulaPattern()
{
method = new TsMethodPattern()
{
series = true
}
},
equationsFormula = new TsFormulaPattern()
{
method = new TsMethodPattern() { }
},
transformVariable = new MsFormulaTransformVariablePattern()
{
slices = ListOperation.Get,
transformSlice = new MsFormulaTransformSlicePattern()
{
selection = ListOperation.Get
}
}
}
}
}
}
}
}
}, // Set equation calculation parameters
execParams = new MsMdExecParams()
{
k = 0,
execMethod = true,
execEvaluateSeries = true,
scenarioKeys = new long[] { },
execStatCoefficients = true,
execIsCoefficientsSaved = true,
modelKeys = new long[] { (long)eqKey }
}
};
// Create a proxy object for operation execution
var somClient = new SomPortTypeClient();
GetMsResult getMsResult = somClient.GetMs(getMsOp);
MsMetaModel meta = getMsResult.meta.item.problemMd.metamodel;
MsCalculationChainEntry chainEntry = meta.calculationChain.its.GetValue(0) as MsCalculationChainEntry;
// Display errors and warnings
MsModel eq = chainEntry.model;
if (eq.warnings != null)
{
Console.WriteLine("-- Warnings --");
Console.WriteLine("".PadRight(3) + printArray(eq.warnings));
}
if (eq.error == null) //Check if errors occurred on equation calculation
{ // Equation is calculated without errors, get calculation results
TsFormula formula = eq.transform.formulas.its.GetValue(0) as TsFormula;
TsNonLinearRegressionMethod nonLinR = formula.method.nonLinearRegression;
Console.WriteLine("-- Coefficients --");
Console.WriteLine("".PadRight(3) + printArray(nonLinR.coefficients));
Console.WriteLine("".PadRight(3) + "- saved: " + nonLinR.isCoefficientsSaved);
Console.WriteLine("-- Coefficient values --");
Console.WriteLine("".PadRight(3) + printArray(nonLinR.coefficientsData));
// Get equation coefficient values and display into console window
Console.WriteLine("-- Detailed description of coefficients --");
StatConstCoefficientsArr cArr = nonLinR.statCoefficients;
Console.WriteLine("".PadRight(3) + "- accuracy of solution: " + cArr.precision);
int i = 0;
foreach (StatConstCoefficients n in cArr.its)
{
Console.WriteLine("".PadRight(3) + "Coefficient '" + nonLinR.coefficients.GetValue(i) + "'");
Console.WriteLine("".PadRight(6) + " - value: " + n.estimate);
Console.WriteLine("".PadRight(6) + " - standard error: " + n.standardError);
Console.WriteLine("".PadRight(6) + " - t-statistics: " + n.tStatistic);
Console.WriteLine("".PadRight(6) + " - probability: " + n.probability);
i++;
}
// Get calculated values and display into console window
MsEvaluateSeriesResult seriesRes = formula.method.evaluateSeries;
printSeries(seriesRes);
}
else // Errors occurred on equation calculation
{
Console.WriteLine("-- Errors --");
Console.WriteLine(eq.error);
}
// Return the model that contains equation
return chainEntry;
}