sum_squares#

VarDictND.sum_squares(*pattern)[source]#

Sum squares of all variables, or a subset based on wildcard pattern, in an expression.

Parameters:

*patternAny, optional: For subsets, the pattern requires one value for each dimension of the N-dim tuple key. The single-character string '*' (asterisk) can be used as a wildcard to represent all possible values for a dimension.

Returns:

Raises:

TypeError: If the pattern includes non-scalar(s).
ValueError: If the pattern is not the same as the length of N-dim tuple keys.
ValueError: If the pattern has no wildcard or all wildcards.

Examples

Create DOcplex model:

>>> from docplex.mp.model import Model
>>> mdl = Model()

Create index-set:

>>> arcs = IndexSetND([('A', 'B'), ('B', 'C'), ('C', 'B')], names=['ori', 'des'])

Add variables:

>>> from opti_extensions.docplex import add_variables
>>> arc_flow = add_variables(mdl, arcs, 'C', ub=10, name='arc-flow')

Sum squares of all variables:

>>> arc_flow.sum_squares()
docplex.mp.quad.QuadExpr(arc-flow_A_B^2+arc-flow_B_C^2+arc-flow_C_B^2)

Sum squares of subset of variables having 'B' at the second dimension index:

>>> arc_flow.sum_squares('*', 'B')
docplex.mp.quad.QuadExpr(arc-flow_A_B^2+arc-flow_C_B^2)

Sum squares of subset of variables having 'Z' at the first dimension index:

>>> arc_flow.sum_squares('Z', '*')
docplex.mp.ZeroExpr()