sum#

VarDictND.sum(*pattern)[source]#

Sum 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:

highspy.highs_linear_expression

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 highspy model:

>>> from highspy import Highs, HighsVarType
>>> mdl = Highs()

Create index-set:

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

Add variables:

>>> from opti_extensions.highspy import addVariables
>>> arc_flow = addVariables(
...     mdl, arcs, ub=10, type=HighsVarType.kContinuous, name_prefix='arc-flow_'
... )

Sum all variables:

>>> arc_flow.sum()
1.0_v0  1.0_v1  1.0_v2

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

>>> arc_flow.sum('*', 'B')
1.0_v0  1.0_v2

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

>>> arc_flow.sum('Z', '*')