print_compare_solutions

print_compare_solutions(portfolio1, portfolio2, objective1, objective2, precision, z1, z2, name1, name2, tol)

Given two solutions to a optimal contribution selection problem (robust or non-robust) this prints a comparison of the two solutions to the terminal.

Parameters

• portfolio1 : ndarray
  The portfolio vector $\mathbf{w}_1$ for the first solution to compare.
• portfolio2 : ndarray
  The portfolio vector $\mathbf{w}_2$ for the second solution to compare.
• objective1 : float
  Objective value associated with the first solution vector $\mathbf{w}_1$.
• objective2 : float
  Objective value associated with the second solution vector $\mathbf{w}_2$.
• precision : int, optional
  The number of decimal places to display values to, with a default of 5.
• z1 : float, optional
  Auxiliary variable $z_1$ associated with uncertainty for the first solution $\mathbf{w}_1$. Default is None, which corresponds to the non-robust problem.
• z2 : float, optional
  Auxiliary variable $z_2$ associated with uncertainty for the second solution $\mathbf{w}_2$. Default is None, which corresponds to the non-robust problem.
• name1: str, optional
  Name to use for the first solution in output. Default value is "First".
• name2: str, optional
  Name to use for the second solution in output. Default value is "Second".
• tol: float, optional
  If both portfolios have an entry below this tolerance for a specific candidate, that candidate will be omitted from the output. Default is None, i.e. all values are shown.

Examples

This function does not have a return value, but when used it produces a terminal output like the following:

>>> print_compare_solutions(..., z2=z_rbs, name1="w_std", name2="w_rbs")
i  w_std    w_rbs
1  0.00000  0.38200
2  0.00000  0.38200
3  0.50000  0.11800
4  0.50000  0.11800
w_std objective: 1.87500
w_rbs objective: 0.77684 (z = 0.37924)
Maximum change: 0.38200
Average change: 0.38200
Minimum change: 0.38200