SOAPBelow is the example of using the SetMs operation to edit equation parameters. The following information is sent in the requests (SOAP, JSON): an instance of opened modeling container, operation execution parameters, equation settings for the Exponential smoothing method, and a pattern for getting changed data. After execution the operation returns the model that contains the changed equation.
The C# functions SetMsExpSmoothing_grid and SetMsExpSmoothing_opt change the method of equation calculation. Input parameters:
ms. Opened modeling container instance.
modelKey. Key of the model that contains the equation.
eqKey. Equation key.
After executing the function returns a model that contains the equation.
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},
"tArg" :
{
"pattern" :
{
"obInst" : "true",
"item" :
{
"key" : "89669",
"problem" :
{
"metamodel" :
{
"calculationChain" : "Change"
}
}
}
},
"meta" :
{
"item" :
{
"k" : "89669",
"type" : "Problem",
"problemMd" :
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"metamodel" :
{
"calculationChain" :
{
"its" :
{
"Item" :
{
"k" : "4",
"type" : "Model",
"model" :
{
"transform" :
{
"formulas" :
{
"its" :
{
"it" :
[
{
"k" : "0",
"kind" : "ExponentialSmoothing",
"method" :
{
"exponentialSmoothing" :
{
"trendComponent" : "Linear",
"confidenceLevel" : "0.96",
"missingData" : "",
"params" :
{
"alpha" : "0.12"
},
"seasonalComponent" : "",
"autoSearch" :
{
"mode" : "Grid",
"criterion" : "MeanAbsError",
"quickestDescent" :
{
"initialApproximation" :
{
"gamma" : "0.12"
},
"finalApproximation" :
{
"gamma" : "0.92"
},
"gridStep" : "0.12"
},
"alphaSearch" : "false",
"gammaSearch" : "true",
"deltaSearch" : "false",
"phiSearch" : "false"
}
}
}
}
]
}
}
}
}
}
}
}
}
}
}
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"scenarios" : "Get",
"period" : "true",
"item" :
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"key" : "89669",
"problem" :
{
"metamodel" :
{
"calculationChain" : "Get",
"calcChainPattern" :
{
"modelPattern" :
{
"transform" :
{
"formulaCount" : "true",
"formulas" :
{
"method" : ""
},
"equationsFormula" :
{
"method" : ""
},
"kind" : "true"
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"visualControllerPattern" :
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"variableRubricatorKey" : "true",
"useSourceName" : "false",
"freeVariables" : "true",
"levelFormat" : "Short"
}
},
"scenarios" : "Get",
"details" : "true",
"useSavedCoefficients" : "true"
}
}
}
}
}
}
{
"SetMsResult" :
{
"id" :
{
"id" : "GDJKDKNCADNBFOAEGIAGHFCPECMLNKAEELPBDMJJHANMFGHH!M!S!CHDHKBONCADNBFOAEGHFNLPPFLAGHDKEEMLCEJLNILCOPLEEN"
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"@isLink" : "0",
"@ver" : "4",
"@hf" : "0",
"i" : "MODELSPACE",
"n" : "Modeling container",
"k" : "1581",
"c" : "5121",
"p" : "1580",
"h" : "0",
"hasPrv" : "0",
"ic" : "0",
"isPermanent" : "1",
"isTemp" : "0"
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"dirty" : "0",
"period" :
{
"start" : "1970-01-01",
"end" : "2020-12-31"
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"scenarios" :
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"item" :
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"id" : "MODEL_NEW",
"n" : "MODEL_NEW",
"vis" : "1",
"type" : "Problem",
"problemMd" :
{
"metamodel" :
{
"k" : "89670",
"calculationChain" :
{
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"originalShortName" : "MyOutputVavable",
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"id" : "OBJ4",
"n" : "MyOutputVavable|A[t] = An*t^n + ... + A2*t^2 + A1*t + A0, (From parent)-(From parent)",
"vis" : "1",
"type" : "Model",
"excluded" : "0",
"graphMeta" : "",
"model" :
{
"transform" :
{
"formulaCount" : "1",
"formulas" :
{
"its" :
{
"it" :
[
{
"k" : "0",
"kind" : "ExponentialSmoothing",
"method" :
{
"exponentialSmoothing" :
{
"trendComponent" : "Linear",
"confidenceLevel" : "0.96",
"missingData" :
{
"specifiedVector" : "",
"method" : "Casewise",
"methodParameter" : "5",
"specifiedValue" : "0",
"specifiedTerm" :
{
"k" : "4294967295"
}
},
"params" :
{
"alpha" : "0.12",
"gamma" : "0.1",
"delta" : "0.1",
"phi" : "0.1"
},
"seasonalComponent" :
{
"mode" : "None",
"cycle" : "4"
},
"autoSearch" :
{
"mode" : "Grid",
"criterion" : "MeanAbsError",
"quickestDescent" :
{
"initialApproximation" :
{
"alpha" : "0",
"gamma" : "0.12",
"delta" : "0",
"phi" : "0.1"
},
"finalApproximation" :
{
"alpha" : "1",
"gamma" : "0.92",
"delta" : "1",
"phi" : "0.9"
},
"gridStep" : "0.12"
},
"bestTrial" :
{
"initialApproximation" :
{
"alpha" : "0.1",
"gamma" : "0.1",
"delta" : "0.1",
"phi" : "0.1"
},
"order" : "10",
"methodConstant" : "0.1",
"maxIteration" : "15"
},
"alphaSearch" : "0",
"gammaSearch" : "1",
"deltaSearch" : "0",
"phiSearch" : "0"
},
"explained" :
{
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"id" : "MyOutputVavable|A",
"n" : "MyOutputVavable|A",
"vis" : "1",
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"parametrizedDimensions" :
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"its" :
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"Item" :
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"dimension" : "0",
"parameter" : "0"
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"measure" : "4294967295",
"baseUnit" : "4294967295",
"unitsDimensionKey" : "0"
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"level" : "Year"
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"lag" : "",
"key" : "0",
"termToText" : "{MyOutputVavable|A[t]}",
"termToInnerText" : "@_1:0[]",
"termInfo" :
{
"k" : "4294967295",
"lag" : "0",
"inversion" :
{
"type" : "None",
"lag" : "PrecidingValue",
"previousLag" : "-1",
"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
"slice" :
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"id" : "MyOutputVavable|A",
"n" : "MyOutputVavable|A",
"vis" : "1",
"variableKey" : "1",
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{
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{
"its" :
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"unitsDimensionKey" : "0"
},
"level" : "Year"
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"date" : "1899-12-30"
},
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"measure" : "4294967295",
"baseUnit" : "4294967295",
"unitsDimensionKey" : "0"
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"included" : "0"
},
"asForecasting" : "0"
},
"inversionInfo" :
{
"type" : "None",
"lag" : "PrecidingValue",
"previousLag" : "-1",
"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
"doUseR" : "0",
"supportsR" : "1"
},
"calendarLevel" : "Year",
"outputSliceKey" : "0"
}
]
}
},
"kind" : "Simple"
},
"warnings" : "",
"readOnly" : "0"
}
}
]
}
},
"visualController" :
{
"variableRubricatorKey" : "89671",
"freeVariables" :
{
"its" : ""
},
"userRPath" : "",
"isRExist" : "0"
},
"suppressEmptyFilter" :
{
"suppressEmpty" : "0",
"suppressEmptyArea" : "SerieBounds"
},
"readOnly" : "0",
"variableTestUseR" : "0",
"calculateIdentOnFact" : "0"
},
"scenarios" :
{
"its" : ""
},
"details" :
{
"period" :
{
"identificationStartDate" : "1990-01-01",
"identificationEndDate" : "2018-04-24",
"forecastStartDate" : "2018-04-25",
"forecastEndDate" : "2020-01-01",
"identificationStartDateParamID" : "",
"identificationEndDateParamID" : "",
"forecastStartDateParamID" : "",
"forecastEndDateParamID" : "",
"autoPeriod" : "0",
"identificationStartOffset" : "0",
"identificationEndOffset" : "0",
"forecastEndOffset" : "0",
"isIdentStartCorrect" : "1",
"isIdentEndCorrect" : "1",
"isForecastEndCorrect" : "1"
},
"currentPoint" : "2018-04-25"
},
"useSavedCoefficients" : "0",
"useScenarios" : "0",
"readOnly" : "0"
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}
}
}
}
public static MsItem SetMsExpSmoothing_grid(MsId ms, ulong modelKey, ulong eqKey)
{
var setMsOp = new SetMs();
// Set operation execution parameters
setMsOp.tMs = ms;
setMsOp.tArg = new SetMsArg()
{ // Set data change pattern
pattern = new MsMdPattern()
{
item = new MsItemPattern()
{ // Specify equation key
key = modelKey,
problem = new MsProblemPattern()
{
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Change
}
}
}
},
// Set data that must be changed
meta = new MsMd()
{
item = new MsItem()
{
k = modelKey,
type = MsItemType.Problem,
problemMd = new MsProblem()
{
metamodel = new MsMetaModel()
{
calculationChain = new MsCalculationChainEntries()
{
its = new MsCalculationChainEntry[]
{
new MsCalculationChainEntry()
{
k = eqKey,
type = MsCalculationChainType.Model,
model = new MsModel()
{
transform = new MsFormulaTransform()
{
formulas = new TsFormulas()
{
its = new TsFormula[]
{
new TsFormula()
{
kind = TsFormulaKind.ExponentialSmoothing,
method = new TsMethod()
{ // Set parameters of the Exponential Smoothing method
exponentialSmoothing = new TsExponentialSmoothingMethod()
{ // Set confidence limits relevance
confidenceLevel = 0.96,
// Set seasonal effect
seasonalComponent = new StatSeasonal(){},
// Set missing data treatment parameters
missingData = new StatMissingData(){},
// Set growth model: additive
trendComponent = StatTrendType.Linear,
// Set coefficient values
@params = new ExponentialSmoothingParams()
{
alpha = 0.12, delta = null,
gamma = null, phi = null
}, // Set parameters of coefficient value autoselection
autoSearch = new ExponentialSmoothingAutoSearch()
{ // Set selected coefficients
alphaSearch = false, deltaSearch = false,
gammaSearch = true, phiSearch = false,
// Set parameters of the Grid Search method
mode = StatSearchType.Grid,
quickestDescent =new ExponentialSmoothingQuickestDescentParams()
{ // Set search interval start values
initialApproximation = new ExponentialSmoothingParams()
{
alpha = null, delta = null,
gamma = 0.12, phi = null
}, // Set search interval end values
finalApproximation = new ExponentialSmoothingParams()
{
alpha = null, delta = null,
gamma = 0.92, phi = null
}, // Set grid step
gridStep = 0.12
},
criterion = StatCriterionType.MeanAbsError
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}, // Set changed data extraction pattern
metaGet = new MsMdPattern()
{
scenarios = ListOperation.Get,
period = true,
item = new MsItemPattern()
{
key = modelKey,
problem = new MsProblemPattern()
{
details = true,
scenarios = ListOperation.Get,
useSavedCoefficients = true,
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Get,
calcChainPattern = new MsCalculationChainPattern()
{
modelPattern = new MsModelPattern()
{
transform = new MsFormulaTransformPattern()
{
kind = true,
formulaCount = true,
formulas = new TsFormulaPattern()
{
method = new TsMethodPattern() { }
},
equationsFormula = new TsFormulaPattern()
{
method = new TsMethodPattern() { }
}
}
}
},
visualControllerPattern = new MsMetaModelVisualControllerPattern()
{
variableRubricatorKey = true,
levelFormat = MsLevelFormat.Short,
useSourceName = false,
freeVariables = true
}
}
}
}
}
};
// Create a proxy object for operation execution
var somClient = new SomPortTypeClient();
// Set operation execution parameters
var result = somClient.SetMs(setMsOp);
return result.meta.item;
}
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{
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{
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},
"tArg" :
{
"pattern" :
{
"obInst" : "true",
"item" :
{
"key" : "89669",
"problem" :
{
"metamodel" :
{
"calculationChain" : "Change"
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},
"meta" :
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{
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{
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{
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{
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{
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"type" : "Model",
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{
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{
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{
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{
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{
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"kind" : "ExponentialSmoothing",
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{
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"autoSearch" :
{
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"criterion" : "MeanError",
"bestTrial" :
{
"initialApproximation" :
{
"gamma" : "0.12"
},
"order" : "9",
"methodConstant" : "0.15",
"maxIteration" : "20"
},
"alphaSearch" : "false",
"gammaSearch" : "true",
"deltaSearch" : "false",
"phiSearch" : "false"
}
}
}
}
]
}
}
}
}
}
}
}
}
}
}
},
"metaGet" :
{
"obInst" : "true",
"scenarios" : "Get",
"period" : "true",
"item" :
{
"key" : "89669",
"problem" :
{
"metamodel" :
{
"calculationChain" : "Get",
"calcChainPattern" :
{
"modelPattern" :
{
"transform" :
{
"formulaCount" : "true",
"formulas" :
{
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},
"equationsFormula" :
{
"method" : ""
},
"kind" : "true"
}
}
},
"visualControllerPattern" :
{
"variableRubricatorKey" : "true",
"useSourceName" : "false",
"freeVariables" : "true",
"levelFormat" : "Short"
}
},
"scenarios" : "Get",
"details" : "true",
"useSavedCoefficients" : "true"
}
}
}
}
}
}
{
"SetMsResult" :
{
"id" :
{
"id" : "FOHJOFJNADNBFOAEPDEIMKPCLJLPFLDEBILEJKOJMGKNANDD!M!S!CDJFPKJJNADNBFOAENAKODJNNPDGOIFMEKIFADEIKBFGIGHID"
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{
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{
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{
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"@isShortcut" : "0",
"@isLink" : "0",
"@ver" : "4",
"@hf" : "0",
"i" : "MODELSPACE",
"n" : "Modeling container",
"k" : "1581",
"c" : "5121",
"p" : "1580",
"h" : "0",
"hasPrv" : "0",
"ic" : "0",
"isPermanent" : "1",
"isTemp" : "0"
}
},
"dirty" : "0",
"period" :
{
"start" : "1970-01-01",
"end" : "2020-12-31"
},
"scenarios" :
{
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{
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]
}
},
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{
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{
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"type" : "Variable",
"excluded" : "0",
"graphMeta" : "{"Geometry":{"x":30,"y":140,"width":150,"height":50}}",
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"its" :
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"it" :
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"kind" : "ExponentialSmoothing",
"method" :
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"exponentialSmoothing" :
{
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"confidenceLevel" : "0.96",
"missingData" :
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"method" : "Casewise",
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},
"gridStep" : "0.12"
},
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{
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]
}
},
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},
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},
"scenarios" :
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},
"details" :
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}
}
}
}
public static MsItem SetMsExpSmoothing_opt(MsId ms, ulong modelKey, ulong eqKey)
{
var setMsOp = new SetMs();
// Set operation execution parameters
setMsOp.tMs = ms;
setMsOp.tArg = new SetMsArg()
{ // Set data change pattern
pattern = new MsMdPattern()
{
item = new MsItemPattern()
{ // Specify model key
key = modelKey,
problem = new MsProblemPattern()
{
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Change
}
}
}
},
// Set data that must be changed
meta = new MsMd()
{
item = new MsItem()
{
k = modelKey,
type = MsItemType.Problem,
problemMd = new MsProblem()
{
metamodel = new MsMetaModel()
{
calculationChain = new MsCalculationChainEntries()
{
its = new MsCalculationChainEntry[]
{
new MsCalculationChainEntry()
{
k = eqKey,
type = MsCalculationChainType.Model,
model = new MsModel()
{
transform = new MsFormulaTransform()
{
formulas = new TsFormulas()
{
its = new TsFormula[]
{
new TsFormula()
{
kind = TsFormulaKind.ExponentialSmoothing,
method = new TsMethod()
{ // Set parameters of the Exponential Smoothing method
exponentialSmoothing = new TsExponentialSmoothingMethod()
{
// Set growth model: additive
trendComponent = StatTrendType.Linear,
// Set coefficient values
@params = new ExponentialSmoothingParams()
{
alpha = 0.12, delta = null,
gamma = null, phi = null
}, // Set parameters of coefficient value autoselection
autoSearch = new ExponentialSmoothingAutoSearch()
{ // Set selected coefficients
alphaSearch = false, deltaSearch = false,
gammaSearch = true, phiSearch = false,
// Set best trial method parameters
mode = StatSearchType.Optimal,
bestTrial = new ExponentialSmoothingBestTrialParams()
{
// Set initial values
initialApproximation = new ExponentialSmoothingParams()
{
alpha = null, delta = null,
gamma = 0.12, phi = null
},
methodConstant = 0.15,
order = 9,
maxIteration = 20
},
criterion = StatCriterionType.MeanError
}
}
}
}
}
}
}
}
}
}
}
}
}
}
}, // Set changed data extraction pattern
metaGet = new MsMdPattern()
{
scenarios = ListOperation.Get,
period = true,
item = new MsItemPattern()
{
key = modelKey,
problem = new MsProblemPattern()
{
details = true,
scenarios = ListOperation.Get,
useSavedCoefficients = true,
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Get,
calcChainPattern = new MsCalculationChainPattern()
{
modelPattern = new MsModelPattern()
{
transform = new MsFormulaTransformPattern()
{
kind = true,
formulaCount = true,
formulas = new TsFormulaPattern()
{
method = new TsMethodPattern() { }
},
equationsFormula = new TsFormulaPattern()
{
method = new TsMethodPattern() { }
}
}
}
},
visualControllerPattern = new MsMetaModelVisualControllerPattern()
{
variableRubricatorKey = true,
levelFormat = MsLevelFormat.Short,
useSourceName = false,
freeVariables = true
}
}
}
}
}
};
// Create a proxy object for operation execution
var somClient = new SomPortTypeClient();
// Set operation execution parameters
var result = somClient.SetMs(setMsOp);
return result.meta.item;
}
See also:
SetMs: Operation | Exponential smoothing