pub fn generate_column(&self, j: usize) -> IM::ColumnComputationInfo {
        debug_assert!(j < self.nr_columns());

        self.inverse_maintainer.generate_column(self.kind.original_column(j))
    }
/// Column of original problem with respect to the current basis.
///
/// Generate a column of the tableau as it would look like with the current basis by matrix
/// multiplying the original column and the carry matrix.
///
/// # Arguments
///
/// * `j`: Column index of the variable, in range `0` until `self.nr_columns()`.
///
/// # Return value
///
/// `SparseVector<T>` of size `m`.
Column of original problem with respect to the current basis.
Generate a column of the tableau as it would look like with the current basis by matrix
multiplying the original column and the carry matrix.
Column of original problem with respect to the current basis . Generate a column of the tableau as it would look like with the current basis by matrix multiplying the original column and the carry matrix .
pub fn generate_column(&self, j: usize) -> IM::ColumnComputationInfo {
        debug_assert!(j < self.nr_columns());
        self.inverse_maintainer.generate_column(self.kind.original_column(j))
    }
pub fn generate_column ( & self , j : usize ) -> IM :: ColumnComputationInfo { debug_assert ! ( j self nr_columns ( ) ) ; self . inverse_maintainer . generate_column ( self . kind . original_column ( j ) ) }
Column of original problem with respect to the current basis.
Column of original problem with respect to the current basis .
&self
j
usize
&self
j
usize
return value
`SparseVector` of size `m`.
` SparseVector ` of size ` m ` .