model.result().table().create(<ftag>,"Table") creates a table feature named
<ftag>. Tables support two data formats,
all or
filled. Filled data is typically produced from parametric sweeps and makes it possible to retrieve data for a pair of parameters on a matrix format. Filled tables can be used to make response surface plots. (See
TableSurface.)
model.result().table(<ftag>).setColumnHeaders(<headers>) sets the table’s column headers from the string array
<headers>.
model.result().table(<ftag>).setTableData(<realData>) sets the table content from a double matrix containing real data. Any previous real or imaginary data is removed.
model.result().table(<ftag>).setTableData(<realData>,<imagData>) sets both real and imaginary data from the double matrices
<realData> and
<imagData>, which must be of the same size.
<imagData> can be
null to indicate that there is no imaginary data.
model.result().table(<ftag>).getColumnHeaders() retrieves the column headers.
model.result().table(<ftag>).addColumns(<headers>,<realData>) adds one or more columns and associated real data to the table.
model.result().table(<ftag>).addColumns(<headers>,<realData>,<imagData>) adds one or more columns and associated real data and imaginary data to the table.
model.result().table(<ftag>).addRow(<realData>) adds one row of real data to the table.
model.result().table(<ftag>).addRow(<realData>,<imagData>) adds one row of real and imaginary data to the table.
Similarly model.result().table(<ftag>).addRows(<realData>) and
model.result().table(<ftag>).addRows(<realData>,<imagData>) add multiple rows of real or real and imaginary data to the table, and
model.result().table(<ftag>).addRows(<realData>,<warnings>) and
model.result().table(<ftag>).addRows(<realData>,<imagData>,<warnings>) add multiple rows of real or real and imaginary data as well as Boolean warnings to the table.
model.result().table(<ftag>).removeRow(<index>) removes the row with a given index from the table. If the row index is out of bounds, nothing happens.
model.result().table(<ftag>).removeRows(<index_array>) removes the rows listed as an array of positive integers as the input argument.
model.result().table(<ftag>).getColumnHeaders() returns the column headers in the table.
model.result().table(<ftag>).getReal() returns the real part of the table content.
model.result().table(<ftag>).getImag() returns the imaginary part of the table content. Note: this method allocates imaginary data if there was none. Check for imaginary content with the
isComplex method before calling this method if you want to avoid this.
model.result().table(<ftag>).getRealRow(<index>) returns the real data in one row.
model.result().table(<ftag>).getImagRow(<index>) returns the imaginary data in one row.
model.result().table(<ftag>).getFilledReal() returns the real part of the table content on a filled format, when available.
model.result().table(<ftag>).getFilledImag() returns the imaginary part of the table content on a filled format, when available.
model.result().table(<ftag>).getTableData(<fullPrecision>) returns the table data as a string matrix, with limited or full precision as specified by the Boolean
<fullPrecision>.
model.result().table(<ftag>).getTableRow(<index>,<fullPrecision>) returns the table data for one row as a string array, with limited or full precision.
model.result().table(<ftag>).getNRows() returns the number of rows in the table.
model.result().table(<ftag>).isComplex() returns true if the table contains imaginary data. This method checks whether imaginary data has been allocated, not if it is different from
0.
model.result().table(<ftag>).clearTableData() removes all table data and column headers.