.Credibility.Utilities.Table1DScalings.getTableLambdaByTolerance

Information

Evaluate table from the uncertainty matrix and tolerances by a convex combination utilizing attribute lambda. Hereby, the matrix uncertainty contains

• col. 1: grid values,
• col. 2: vector of nominal values.

The convex combination is defined for the Real lambda in a way that

• λ = −1 results in table[:, 2] = uncertainty[:, 2] - tol[:],
• λ = 0 results in table[:, 2] = uncertainty[:, 2] and
• λ = 1 results in table[:, 2] = uncertainty[:, 2] + tol[:].

The tolerance vector tol is defined element-wise by

tol[i] = max( absTol, relTol*abs(uncertainty[i, 2]) ).

This function is called in Table1D to evaluate "table[i,j]". For further details, refer to User's Guide – "Convex scaling by uncertain parameter λ".

Interface

function getTableLambdaByTolerance
  extends Modelica.Icons.Function;
  input Real lambda "Convex scaling between -1 and 1 (=0: nominal)";
  input Real uncertainty[:, 2] "Table uncertainty (x, nominal)";
  input Real absTol "Limits: |value[i] - uncertainty[i,2]| <= max(absTol,relTol*|uncertainty[i,2]|)";
  input Real relTol "Limits: |value[i] - uncertainty[i,2]| <= max(absTol,relTol*|uncertainty[i,2]|)";
  output Real table[size(uncertainty, 1), 2] "Value of table";
end getTableLambdaByTolerance;