model.result().numerical().create(<ftag>,"EvalPointMatrix") creates an evaluation feature with the name <ftag>.

model.result().numerical(<ftag>).getReal() returns the real result, recomputing the feature if necessary. Data is ordered such that one row contains data for all solution numbers. This is identical to (<columnwise>) when columnwise is false. If columnwise is true, the ordering is the opposite: each column contains the values for all solution numbers.

model.result().numerical(<ftag>).getImag(<allocate>, <columnwise>) returns the imaginary part of complex result, recomputing the feature if necessary. If allocate is true, a zero-valued matrix is allocated even when the result is real. getImag() uses <allocate> true and <columnwise> false.

model.result().numerical(<ftag>).isComplex() returns true if the result is complex. The resulting value is a scalar, which true if any of the expressions in an array is complex-valued.

model.result().numerical(<ftag>).isComplex(<outersolnum>) returns true if the result is complex for the given outer solution. <outersolnum> is applicable only for parametric sweep solutions and is the index of each outer parametric solution.

model.result().numerical(<ftag>).computeResult() returns the matrix of data that the setResult method adds to a table. The matrix includes data only, not the parameter columns, and it does not use any table-specific settings.

model.result().numerical(<ftag>).setResult() and model.result().numerical(<ftag>).appendResult() evaluates the feature and set or append the result in the table indicated by the table property.

model.result().numerical(<ftag>).selection() selects the points where the matrix quantity should be evaluated. model.result().numerical(<ftag>).selection().all(); selects all points in the geometry.

EvalGlobal, Eval, EvalPoint, EvalGlobalMatrix