# These are mostly actually needed.
from cvxopt import matrix, printing, solvers
-from cones import CartesianProduct, IceCream, NonnegativeOrthant
-from errors import GameUnsolvableException
-from matrices import (append_col, append_row, eigenvalues_re, identity,
- inner_product, norm)
-import options
+from .cones import CartesianProduct, IceCream, NonnegativeOrthant
+from .errors import GameUnsolvableException
+from .matrices import (append_col, append_row, eigenvalues_re, identity,
+ inner_product, norm)
+from . import options
printing.options['dformat'] = options.FLOAT_FORMAT
solvers.options['show_progress'] = options.VERBOSE
Examples
--------
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(3)
>>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]]
>>> e1 = [1,1,1]
Lists can (and probably should) be used for every argument::
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(2)
>>> L = [[1,0],[0,1]]
>>> e1 = [1,1]
>>> import cvxopt
>>> import numpy
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(2)
>>> L = [[1,0],[0,1]]
>>> e1 = cvxopt.matrix([1,1])
otherwise indexed by columns::
>>> import cvxopt
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(2)
>>> L = [[1,2],[3,4]]
>>> e1 = [1,1]
This example is computed in Gowda and Ravindran in the section
"The value of a Z-transformation"::
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(3)
>>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]]
>>> e1 = [1,1,1]
The value of the following game can be computed using the fact
that the identity is invertible::
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(3)
>>> L = [[1,0,0],[0,1,0],[0,0,1]]
>>> e1 = [1,2,3]
Examples
--------
- >>> from cones import NonnegativeOrthant
>>> K = NonnegativeOrthant(3)
>>> L = [[1,-5,-15],[-1,2,-3],[-12,-15,1]]
>>> e1 = [1,1,1]