SOAP-запрос:
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</tMs>
<tArg xmlns=""><pattern> <obInst>false</obInst>
<all>false</all>
<item> <key>89669</key>
<problem><metamodel> <calculationChain>Get</calculationChain>
<calcChainPattern><modelPattern><transform> <outputs>Get</outputs>
<formulaCount>true</formulaCount>
<formulas><method> <series>true</series>
</method>
</formulas>
<displayId>true</displayId>
<equationsFormula> <method />
</equationsFormula>
<series>Get</series>
<kind>true</kind>
<displaySettings>true</displaySettings>
<additionalAttributes>true</additionalAttributes>
<calculationType>true</calculationType>
<calculationDirection>true</calculationDirection>
<transformVariable> <slices>Get</slices>
<transformSlice> <selection>Get</selection>
</transformSlice>
</transformVariable>
</transform>
<stochastic>true</stochastic>
<calculationPeriod>true</calculationPeriod>
<useModelPeriod>true</useModelPeriod>
<useExistingData>true</useExistingData>
<treatNullsAsZeros>true</treatNullsAsZeros>
<autoName>true</autoName>
<generatedName>true</generatedName>
<period>true</period>
<isExclusive>true</isExclusive>
<useAutoPeriod>true</useAutoPeriod>
</modelPattern>
<entryKeys> <l>4</l>
</entryKeys>
</calcChainPattern>
</metamodel>
</problem>
</item>
</pattern>
<execParams> <k>0</k>
<modelKeys> <l>4</l>
</modelKeys>
<scenarioKeys />
<execMethod>true</execMethod>
<execEvaluateSeries>true</execEvaluateSeries>
<execIsCoefficientsSaved>true</execIsCoefficientsSaved>
<execStatCoefficients>true</execStatCoefficients>
</execParams>
</tArg>
</GetMs>
</s:Body>
</s:Envelope>
SOAP-ответ:
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</id>
<meta xmlns=""><item> <k>89669</k>
<id>MODEL_NEW</id>
<n>MODEL_NEW</n>
<vis>1</vis>
<type>Problem</type>
<problemMd><metamodel> <k>89670</k>
<calculationChain><its><Item> <k>4</k>
<id>OBJ4</id>
<n>MyOutputVavable|A[t] = MyInputVavable|A[t] * a + b, 1990A1-2010A1</n>
<vis>1</vis>
<type>Model</type>
<excluded>0</excluded>
<graphMeta />
<model><transform><outputs><its><Item> <k>1</k>
<id>VARIABLES_89670</id>
<n>Variables</n>
<vis>1</vis>
<slices><its><Item> <k>0</k>
<id>MyOutputVavable|A</id>
<n>MyOutputVavable|A</n>
<vis>1</vis>
<variableKey>1</variableKey>
<stubKey>89671</stubKey>
<selections><its><Item><id> <id>89683</id>
</id>
<variant>2</variant>
</Item>
</its>
</selections>
<aggregator>None</aggregator>
<parametrizedDimensions><its><Item> <dimension>0</dimension>
<parameter>0</parameter>
</Item>
</its>
</parametrizedDimensions>
<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
<baseUnit>4294967295</baseUnit>
<unitsDimensionKey>0</unitsDimensionKey>
</unitInfo>
<level>Year</level>
</Item>
</its>
</slices>
<variableStubKey>89671</variableStubKey>
<parameterID />
<kind>Stub</kind>
<attributeId />
<attributeType>Series</attributeType>
</Item>
</its>
</outputs>
<formulaCount>1</formulaCount>
<formulas><its><it> <k>0</k>
<kind>NonLinearRegression</kind>
<method><nonLinearRegression><missingData> <specifiedVector />
<method>LinTrend</method>
<methodParameter>5</methodParameter>
<specifiedValue>0</specifiedValue>
<specifiedTerm> <k>4294967295</k>
</specifiedTerm>
</missingData>
<confidenceLevel>0.9</confidenceLevel>
<useDerivatives>1</useDerivatives>
<initialApproximation> <d>0.15</d>
<d>0.09</d>
</initialApproximation>
<maxIterations>500</maxIterations>
<maxStep>0.4</maxStep>
<dampingFactorTolerance>0.6</dampingFactorTolerance>
<expression>@_2:0[] * a + b</expression>
<result><slice> <k>0</k>
<id>MyOutputVavable|A</id>
<n>MyOutputVavable|A</n>
<vis>1</vis>
<variableKey>1</variableKey>
<stubKey>89671</stubKey>
<selections><its><Item><id> <id>89683</id>
</id>
<variant>2</variant>
</Item>
</its>
</selections>
<aggregator>None</aggregator>
<parametrizedDimensions><its><Item> <dimension>0</dimension>
<parameter>0</parameter>
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<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
<baseUnit>4294967295</baseUnit>
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</unitInfo>
<level>Year</level>
</slice>
<lag />
<key>0</key>
<termToText>{MyOutputVavable|A[t]}</termToText>
<termToInnerText>@_1:0[]</termToInnerText>
<termInfo> <k>4294967295</k>
<lag>0</lag>
<inversion> <type>None</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversion>
<slice> <k>0</k>
<id>MyOutputVavable|A</id>
<n>MyOutputVavable|A</n>
<vis>1</vis>
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<selections><its><Item><id> <id>89683</id>
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<variant>2</variant>
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<aggregator>None</aggregator>
<parametrizedDimensions><its><Item> <dimension>0</dimension>
<parameter>0</parameter>
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<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
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<unitsDimensionKey>0</unitsDimensionKey>
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<level>Year</level>
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<date>1899-12-30</date>
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<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
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</unitInfo>
<included>0</included>
</result>
<operands><its><Item> <k>0</k>
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<id>MyInputVavable|A</id>
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<selections><its><Item><id> <id>89683</id>
</id>
<variant>1</variant>
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<aggregator>None</aggregator>
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<parameter>0</parameter>
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<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
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<unitsDimensionKey>0</unitsDimensionKey>
</unitInfo>
<level>Year</level>
</slice>
<lag>1</lag>
<key>1</key>
<termToText>{TS(MyInputVavable|A[t+1], Linear)}</termToText>
<termToInnerText>@_2:0[1][9:0]</termToInnerText>
<termInfo> <k>4294967295</k>
<lag>1</lag>
<inversion> <type>TS</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversion>
<slice> <k>0</k>
<id>MyInputVavable|A</id>
<n>MyInputVavable|A</n>
<vis>1</vis>
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<aggregator>None</aggregator>
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<parameter>0</parameter>
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</parametrizedDimensions>
<unitInfo> <unit>4294967295</unit>
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<included>0</included>
</Item>
<Item> <k>1</k>
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<id>MyInputVavable|A</id>
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<selections><its><Item><id> <id>89683</id>
</id>
<variant>1</variant>
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</selections>
<aggregator>None</aggregator>
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<parameter>0</parameter>
</Item>
</its>
</parametrizedDimensions>
<unitInfo> <unit>4294967295</unit>
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<level>Year</level>
</slice>
<lag>0</lag>
<key>2</key>
<termToText>{MyInputVavable|A[t]}</termToText>
<termToInnerText>@_2:0[]</termToInnerText>
<termInfo> <k>4294967295</k>
<lag>0</lag>
<inversion> <type>None</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversion>
<slice> <k>0</k>
<id>MyInputVavable|A</id>
<n>MyInputVavable|A</n>
<vis>1</vis>
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<stubKey>89671</stubKey>
<selections><its><Item><id> <id>89683</id>
</id>
<variant>1</variant>
</Item>
</its>
</selections>
<aggregator>None</aggregator>
<parametrizedDimensions><its><Item> <dimension>0</dimension>
<parameter>0</parameter>
</Item>
</its>
</parametrizedDimensions>
<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
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<unitsDimensionKey>0</unitsDimensionKey>
</unitInfo>
<level>Year</level>
</slice>
<date>1899-12-30</date>
</termInfo>
<unitInfo> <unit>4294967295</unit>
<measure>4294967295</measure>
<baseUnit>4294967295</baseUnit>
<unitsDimensionKey>0</unitsDimensionKey>
</unitInfo>
<included>1</included>
</Item>
</its>
</operands>
<coefficients> <it>a</it>
<it>b</it>
</coefficients>
<isCoefficientsSaved>0</isCoefficientsSaved>
<statCoefficients><its><Item> <estimate>-0.07833068250940456</estimate>
<standardError>0.04307364909196183</standardError>
<tStatistic>-1.818529058036604</tStatistic>
<probability>0.08900474700852867</probability>
</Item>
<Item> <estimate>4.374510772763077</estimate>
<standardError>0.6880094965630595</standardError>
<tStatistic>6.358212778480349</tStatistic>
<probability>1.285011021923133e-05</probability>
</Item>
</its>
</statCoefficients>
<optimizationMethod>LevenbergMarquardt</optimizationMethod>
<tolerance>0.0001</tolerance>
<useDefaultInitValues>0</useDefaultInitValues>
</nonLinearRegression>
<name>X2 * (-0.0783) + 4.3745</name>
<series><input> <k>4294967295</k>
<lag>0</lag>
<inversion> <type>None</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversion>
<slice> <k>0</k>
<id>MyOutputVavable|A</id>
<n>MyOutputVavable|A</n>
<vis>1</vis>
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<selections><its><Item><id> <id>89683</id>
</id>
<variant>2</variant>
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</selections>
<aggregator>None</aggregator>
<parametrizedDimensions><its><Item> <dimension>0</dimension>
<parameter>0</parameter>
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</parametrizedDimensions>
<unitInfo> <unit>4294967295</unit>
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<level>Year</level>
</slice>
<date>1899-12-30</date>
</input>
<addFactor> <k>4294967295</k>
</addFactor>
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<evaluateSeries><its><Item> <scenarioKey>4294967295</scenarioKey>
<fact> <d>3</d>
<d>7</d>
<d>2</d>
<d>6</d>
<d>4</d>
<d>1</d>
<d>5</d>
<d>3.42857143</d>
<d>3.28571429</d>
<d>3.14285714</d>
<d>3</d>
<d>2.85714286</d>
<d>2.71428571</d>
<d>2.57142857</d>
<d>2.42857143</d>
<d>2.28571429</d>
<d>2.14285714</d>
</fact>
<modelling> <d>4.296180090253672</d>
<d>4.061188042725458</d>
<d>4.217849407744268</d>
<d>3.826195995197245</d>
<d>3.787030653942542</d>
<d>3.661701561927495</d>
<d>3.536372469912448</d>
<d>3.4110433778974</d>
<d>3.285714285882353</d>
<d>3.160385193867306</d>
<d>3.035056101852258</d>
<d>2.909727009837211</d>
<d>2.784397917822164</d>
<d>2.659068825807117</d>
<d>2.53373973379207</d>
<d>2.408410641777022</d>
<d>2.283081549761975</d>
</modelling>
<residuals> <d>-1.296180090253672</d>
<d>2.938811957274542</d>
<d>-2.217849407744268</d>
<d>2.173804004802755</d>
<d>0.2129693460574575</d>
<d>-2.661701561927495</d>
<d>1.463627530087552</d>
<d>0.01752805210259956</d>
<d>4.117647112167333e-09</d>
<d>-0.01752805386730616</d>
<d>-0.03505610185225816</d>
<d>-0.05258414983721105</d>
<d>-0.07011220782216387</d>
<d>-0.08764025580711676</d>
<d>-0.1051683037920697</d>
<d>-0.1226963517770217</d>
<d>-0.1402244097619749</d>
</residuals>
<input> <d>3</d>
<d>7</d>
<d>2</d>
<d>6</d>
<d>4</d>
<d>1</d>
<d>5</d>
<d>3.42857143</d>
<d>3.28571429</d>
<d>3.14285714</d>
<d>3</d>
<d>2.85714286</d>
<d>2.71428571</d>
<d>2.57142857</d>
<d>2.42857143</d>
<d>2.28571429</d>
<d>2.14285714</d>
<d>2</d>
<d>1.85714286</d>
<d>1.71428571</d>
<d>1.57142857</d>
</input>
<factors><its><it> <termToText>{MyInputVavable|A[t]}</termToText>
<serie> <d>1</d>
<d>4</d>
<d>2</d>
<d>7</d>
<d>7.5</d>
<d>9.1</d>
<d>10.7</d>
<d>12.3</d>
<d>13.9</d>
<d>15.5</d>
<d>17.1</d>
<d>18.7</d>
<d>20.3</d>
<d>21.9</d>
<d>23.5</d>
<d>25.1</d>
<d>26.7</d>
<d>28.3</d>
<d>29.9</d>
<d>31.5</d>
<d>33.1</d>
</serie>
<inversion> <type>None</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversion>
<entryKey>1</entryKey>
</it>
</its>
</factors>
</Item>
</its>
<dates> <it>1990A1</it>
<it>1991A1</it>
<it>1992A1</it>
<it>1993A1</it>
<it>1994A1</it>
<it>1995A1</it>
<it>1996A1</it>
<it>1997A1</it>
<it>1998A1</it>
<it>1999A1</it>
<it>2000A1</it>
<it>2001A1</it>
<it>2002A1</it>
<it>2003A1</it>
<it>2004A1</it>
<it>2005A1</it>
<it>2006A1</it>
<it>2007A1</it>
<it>2008A1</it>
<it>2009A1</it>
<it>2010A1</it>
</dates>
</evaluateSeries>
<inversionInfo> <type>None</type>
<lag>PrecidingValue</lag>
<previousLag>-1</previousLag>
<seasonality>None</seasonality>
<dependence>Linear</dependence>
<K>3</K>
</inversionInfo>
<doUseR>0</doUseR>
<supportsR>1</supportsR>
</method>
<calendarLevel>Year</calendarLevel>
<outputSliceKey>0</outputSliceKey>
</it>
</its>
</formulas>
<displayId>0</displayId>
<series> <its />
</series>
<kind>Simple</kind>
<displaySettings> <displayTermsAs>Derive</displayTermsAs>
</displaySettings>
<additionalAttributes />
<calculationType>Serie</calculationType>
<calculationDirection>Forward</calculationDirection>
</transform>
<stochastic>1</stochastic>
<calculationPeriod>Forecast</calculationPeriod>
<useModelPeriod>1</useModelPeriod>
<useExistingData>0</useExistingData>
<treatNullsAsZeros>0</treatNullsAsZeros>
<autoName>1</autoName>
<period> <identificationStartDate>1990-01-01</identificationStartDate>
<identificationEndDate>2006-01-01</identificationEndDate>
<forecastStartDate>2006-01-02</forecastStartDate>
<forecastEndDate>2010-01-01</forecastEndDate>
<identificationStartDateParamID />
<identificationEndDateParamID />
<forecastStartDateParamID />
<forecastEndDateParamID />
<autoPeriod>0</autoPeriod>
<identificationStartOffset>0</identificationStartOffset>
<identificationEndOffset>0</identificationEndOffset>
<forecastEndOffset>0</forecastEndOffset>
<isIdentStartCorrect>1</isIdentStartCorrect>
<isIdentEndCorrect>1</isIdentEndCorrect>
<isForecastEndCorrect>1</isForecastEndCorrect>
</period>
<isExclusive>1</isExclusive>
<useAutoPeriod>0</useAutoPeriod>
<generatedName>MyOutputVavable|A[t] = MyInputVavable|A[t] * a + b</generatedName>
<warnings />
<readOnly>0</readOnly>
</model>
</Item>
</its>
</calculationChain>
<visualController> <userRPath />
<isRExist>0</isRExist>
</visualController>
<suppressEmptyFilter> <suppressEmpty>0</suppressEmpty>
<suppressEmptyArea>SerieBounds</suppressEmptyArea>
</suppressEmptyFilter>
<readOnly>0</readOnly>
<variableTestUseR>0</variableTestUseR>
<calculateIdentOnFact>0</calculateIdentOnFact>
</metamodel>
<useScenarios>0</useScenarios>
<readOnly>0</readOnly>
</problemMd>
</item>
</meta>
</GetMsResult>
</soapenv:Body>
</soapenv:Envelope>
JSON-запрос:
{
"GetMs" :
{
"tMs" :
{
"id" : "CGNGLNJJAFNBFOAEAMLDKJBMDFDMIKBECLCCPAGGMMNHDHAO!M!S!CCFELIOJJAFNBFOAEGCJLMLPJNCHIHJEEHKPLONIGDEKIBJDL"
},
"tArg" :
{
"pattern" :
{
"obInst" : "false",
"all" : "false",
"item" :
{
"key" : "89669",
"problem" :
{
"metamodel" :
{
"calculationChain" : "Get",
"calcChainPattern" :
{
"modelPattern" :
{
"transform" :
{
"outputs" : "Get",
"formulaCount" : "true",
"formulas" :
{
"method" :
{
"series" : "true"
}
},
"displayId" : "true",
"equationsFormula" :
{
"method" : ""
},
"series" : "Get",
"kind" : "true",
"displaySettings" : "true",
"additionalAttributes" : "true",
"calculationType" : "true",
"calculationDirection" : "true",
"transformVariable" :
{
"slices" : "Get",
"transformSlice" :
{
"selection" : "Get"
}
}
},
"stochastic" : "true",
"calculationPeriod" : "true",
"useModelPeriod" : "true",
"useExistingData" : "true",
"treatNullsAsZeros" : "true",
"autoName" : "true",
"generatedName" : "true",
"period" : "true",
"isExclusive" : "true",
"useAutoPeriod" : "true"
},
"entryKeys" :
{
"l" : "4"
}
}
}
}
}
},
"execParams" :
{
"k" : "0",
"modelKeys" :
{
"l" : "4"
},
"scenarioKeys" : "",
"execMethod" : "true",
"execEvaluateSeries" : "true",
"execIsCoefficientsSaved" : "true",
"execStatCoefficients" : "true"
}
}
}
}
JSON-ответ:
{
"GetMsResult" :
{
"id" :
{
"id" : "CGNGLNJJAFNBFOAEAMLDKJBMDFDMIKBECLCCPAGGMMNHDHAO!M!S!CCFELIOJJAFNBFOAEGCJLMLPJNCHIHJEEHKPLONIGDEKIBJDL"
},
"meta" :
{
"item" :
{
"k" : "89669",
"id" : "MODEL_NEW",
"n" : "MODEL_NEW",
"vis" : "1",
"type" : "Problem",
"problemMd" :
{
"metamodel" :
{
"k" : "89670",
"calculationChain" :
{
"its" :
{
"Item" :
{
"k" : "4",
"id" : "OBJ4",
"n" : "MyOutputVavable|A[t] = MyInputVavable|A[t] * a + b, 1990A1-2010A1",
"vis" : "1",
"type" : "Model",
"excluded" : "0",
"graphMeta" : "",
"model" :
{
"transform" :
{
"outputs" :
{
"its" :
{
"Item" :
{
"k" : "1",
"id" : "VARIABLES_89670",
"n" : "Variables",
"vis" : "1",
"slices" :
{
"its" :
{
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{
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"id" : "MyOutputVavable|A",
"n" : "MyOutputVavable|A",
"vis" : "1",
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"stubKey" : "89671",
"selections" :
{
"its" :
{
"Item" :
{
"id" :
{
"id" : "89683"
},
"variant" : "2"
}
}
},
"aggregator" : "None",
"parametrizedDimensions" :
{
"its" :
{
"Item" :
{
"dimension" : "0",
"parameter" : "0"
}
}
},
"unitInfo" :
{
"unit" : "4294967295",
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},
"level" : "Year"
}
}
},
"variableStubKey" : "89671",
"parameterID" : "",
"kind" : "Stub",
"attributeId" : "",
"attributeType" : "Series"
}
}
},
"formulaCount" : "1",
"formulas" :
{
"its" :
{
"it" :
[
{
"k" : "0",
"kind" : "NonLinearRegression",
"method" :
{
"nonLinearRegression" :
{
"missingData" :
{
"specifiedVector" : "",
"method" : "LinTrend",
"methodParameter" : "5",
"specifiedValue" : "0",
"specifiedTerm" :
{
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}
},
"confidenceLevel" : "0.9",
"useDerivatives" : "1",
"initialApproximation" :
{
"d" :
[
"0.15",
"0.09"
]
},
"maxIterations" : "500",
"maxStep" : "0.4",
"dampingFactorTolerance" : "0.6",
"expression" : "@_2:0[] * a + b",
"result" :
{
"slice" :
{
"k" : "0",
"id" : "MyOutputVavable|A",
"n" : "MyOutputVavable|A",
"vis" : "1",
"variableKey" : "1",
"stubKey" : "89671",
"selections" :
{
"its" :
{
"Item" :
{
"id" :
{
"id" : "89683"
},
"variant" : "2"
}
}
},
"aggregator" : "None",
"parametrizedDimensions" :
{
"its" :
{
"Item" :
{
"dimension" : "0",
"parameter" : "0"
}
}
},
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{
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},
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},
"lag" : "",
"key" : "0",
"termToText" : "{MyOutputVavable|A[t]}",
"termToInnerText" : "@_1:0[]",
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{
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{
"type" : "None",
"lag" : "PrecidingValue",
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"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
"slice" :
{
"k" : "0",
"id" : "MyOutputVavable|A",
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{
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},
"aggregator" : "None",
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{
"its" :
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},
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},
"unitInfo" :
{
"unit" : "4294967295",
"measure" : "4294967295",
"baseUnit" : "4294967295",
"unitsDimensionKey" : "0"
},
"included" : "0"
},
"operands" :
{
"its" :
{
"Item" :
[
{
"k" : "0",
"slice" :
{
"k" : "0",
"id" : "MyInputVavable|A",
"n" : "MyInputVavable|A",
"vis" : "1",
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"stubKey" : "89671",
"selections" :
{
"its" :
{
"Item" :
{
"id" :
{
"id" : "89683"
},
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}
}
},
"aggregator" : "None",
"parametrizedDimensions" :
{
"its" :
{
"Item" :
{
"dimension" : "0",
"parameter" : "0"
}
}
},
"unitInfo" :
{
"unit" : "4294967295",
"measure" : "4294967295",
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"unitsDimensionKey" : "0"
},
"level" : "Year"
},
"lag" : "1",
"key" : "1",
"termToText" : "{TS(MyInputVavable|A[t+1], Linear)}",
"termToInnerText" : "@_2:0[1][9:0]",
"termInfo" :
{
"k" : "4294967295",
"lag" : "1",
"inversion" :
{
"type" : "TS",
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"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
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{
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},
"aggregator" : "None",
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{
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},
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"termToText" : "{MyInputVavable|A[t]}",
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},
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{
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{
"its" :
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},
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},
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"unit" : "4294967295",
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},
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}
]
}
},
"coefficients" :
{
"it" :
[
"a",
"b"
]
},
"isCoefficientsSaved" : "0",
"statCoefficients" :
{
"its" :
{
"Item" :
[
{
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"standardError" : "0.04307364909196183",
"tStatistic" : "-1.818529058036604",
"probability" : "0.08900474700852867"
},
{
"estimate" : "4.374510772763077",
"standardError" : "0.6880094965630595",
"tStatistic" : "6.358212778480349",
"probability" : "1.285011021923133e-05"
}
]
}
},
"optimizationMethod" : "LevenbergMarquardt",
"tolerance" : "0.0001",
"useDefaultInitValues" : "0"
},
"name" : "X2 * (-0.0783) + 4.3745",
"series" :
{
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{
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"lag" : "0",
"inversion" :
{
"type" : "None",
"lag" : "PrecidingValue",
"previousLag" : "-1",
"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
"slice" :
{
"k" : "0",
"id" : "MyOutputVavable|A",
"n" : "MyOutputVavable|A",
"vis" : "1",
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"stubKey" : "89671",
"selections" :
{
"its" :
{
"Item" :
{
"id" :
{
"id" : "89683"
},
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}
}
},
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{
"its" :
{
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{
"dimension" : "0",
"parameter" : "0"
}
}
},
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{
"unit" : "4294967295",
"measure" : "4294967295",
"baseUnit" : "4294967295",
"unitsDimensionKey" : "0"
},
"level" : "Year"
},
"date" : "1899-12-30"
},
"addFactor" :
{
"k" : "4294967295"
}
},
"evaluateSeries" :
{
"its" :
{
"Item" :
{
"scenarioKey" : "4294967295",
"fact" :
{
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[
"3",
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]
},
"modelling" :
{
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"residuals" :
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{
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},
"factors" :
{
"its" :
{
"it" :
[
{
"termToText" : "{MyInputVavable|A[t]}",
"serie" :
{
"d" :
[
"1",
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"previousLag" : "-1",
"seasonality" : "None",
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"K" : "3"
},
"entryKey" : "1"
}
]
}
}
}
},
"dates" :
{
"it" :
[
"1990A1",
"1991A1",
"1992A1",
"1993A1",
"1994A1",
"1995A1",
"1996A1",
"1997A1",
"1998A1",
"1999A1",
"2000A1",
"2001A1",
"2002A1",
"2003A1",
"2004A1",
"2005A1",
"2006A1",
"2007A1",
"2008A1",
"2009A1",
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]
}
},
"inversionInfo" :
{
"type" : "None",
"lag" : "PrecidingValue",
"previousLag" : "-1",
"seasonality" : "None",
"dependence" : "Linear",
"K" : "3"
},
"doUseR" : "0",
"supportsR" : "1"
},
"calendarLevel" : "Year",
"outputSliceKey" : "0"
}
]
}
},
"displayId" : "0",
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{
"its" : ""
},
"kind" : "Simple",
"displaySettings" :
{
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},
"additionalAttributes" : "",
"calculationType" : "Serie",
"calculationDirection" : "Forward"
},
"stochastic" : "1",
"calculationPeriod" : "Forecast",
"useModelPeriod" : "1",
"useExistingData" : "0",
"treatNullsAsZeros" : "0",
"autoName" : "1",
"period" :
{
"identificationStartDate" : "1990-01-01",
"identificationEndDate" : "2006-01-01",
"forecastStartDate" : "2006-01-02",
"forecastEndDate" : "2010-01-01",
"identificationStartDateParamID" : "",
"identificationEndDateParamID" : "",
"forecastStartDateParamID" : "",
"forecastEndDateParamID" : "",
"autoPeriod" : "0",
"identificationStartOffset" : "0",
"identificationEndOffset" : "0",
"forecastEndOffset" : "0",
"isIdentStartCorrect" : "1",
"isIdentEndCorrect" : "1",
"isForecastEndCorrect" : "1"
},
"isExclusive" : "1",
"useAutoPeriod" : "0",
"generatedName" : "MyOutputVavable|A[t] = MyInputVavable|A[t] * a + b",
"warnings" : "",
"readOnly" : "0"
}
}
}
},
"visualController" :
{
"userRPath" : "",
"isRExist" : "0"
},
"suppressEmptyFilter" :
{
"suppressEmpty" : "0",
"suppressEmptyArea" : "SerieBounds"
},
"readOnly" : "0",
"variableTestUseR" : "0",
"calculateIdentOnFact" : "0"
},
"useScenarios" : "0",
"readOnly" : "0"
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}
}
}
}
public static MsCalculationChainEntry GetMsNonLinearRegr(MsId ms, ulong modelKey, ulong eqKey)
{
var getMsOp = new GetMs();
// Задаём параметры выполнения операции
getMsOp.tMs = ms;
getMsOp.tArg = new GetMsArg()
{ // Задаём шаблон извлечения данных
pattern = new MsMdPattern()
{
obInst = false,
all = false,
item = new MsItemPattern()
{ // Указываем ключ рассчитываемой модели
key = modelKey,
problem = new MsProblemPattern()
{
metamodel = new MsMetaModelPattern()
{
calculationChain = ListOperation.Get,
calcChainPattern = new MsCalculationChainPattern()
{
// Указываем ключ рассчитываемого уравнения
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
}
}
}
}
}
}
}
}
}, // Задаём параметры расчёта уравнения
execParams = new MsMdExecParams()
{
k = 0,
execMethod = true,
execEvaluateSeries = true,
scenarioKeys = new long[] { },
execStatCoefficients = true,
execIsCoefficientsSaved = true,
modelKeys = new long[] { (long)eqKey }
}
};
// Создаем прокси-объект для выполнения операции
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;
// Выводим ошибки и предупреждения
MsModel eq = chainEntry.model;
if (eq.warnings != null)
{
Console.WriteLine("-- Предупреждения --");
Console.WriteLine("".PadRight(3) + printArray(eq.warnings));
}
if (eq.error == null) //Проверяем, возникли ли ошибки при расчёте уравнения
{ // Уравнение рассчитано без ошибок, получаем результаты расчёта
TsFormula formula = eq.transform.formulas.its.GetValue(0) as TsFormula;
TsNonLinearRegressionMethod nonLinR = formula.method.nonLinearRegression;
Console.WriteLine("-- Коэффициенты --");
Console.WriteLine("".PadRight(3) + printArray(nonLinR.coefficients));
Console.WriteLine("".PadRight(3) + "- сохранены: " + nonLinR.isCoefficientsSaved);
Console.WriteLine("-- Значения коэффициентов --");
Console.WriteLine("".PadRight(3) + printArray(nonLinR.coefficientsData));
// Получаем значения коэффициентов уравнения и выводим в окно консоли
Console.WriteLine("-- Подробное описание коэффициентов --");
StatConstCoefficientsArr cArr = nonLinR.statCoefficients;
Console.WriteLine("".PadRight(3) + "- точность вычислений: " + cArr.precision);
int i = 0;
foreach (StatConstCoefficients n in cArr.its)
{
Console.WriteLine("".PadRight(3) + "Коэффициент '" + nonLinR.coefficients.GetValue(i) + "'");
Console.WriteLine("".PadRight(6) + " - значение: " + n.estimate);
Console.WriteLine("".PadRight(6) + " - стандартная ошибка: " + n.standardError);
Console.WriteLine("".PadRight(6) + " - t-статистика: " + n.tStatistic);
Console.WriteLine("".PadRight(6) + " - вероятность: " + n.probability);
i++;
}
// Получаем рассчитанные значения и выводим в окно консоли
MsEvaluateSeriesResult seriesRes = formula.method.evaluateSeries;
printSeries(seriesRes);
}
else // При расчёте уравнения возникли ошибки
{
Console.WriteLine("-- Ошибки --");
Console.WriteLine(eq.error);
}
// Возвращаем модель, содержащую уравнение
return chainEntry;
}