dimod.ConstrainedQuadraticModel.add_discrete_from_iterable#

ConstrainedQuadraticModel.add_discrete_from_iterable(variables: Iterable[Hashable], label: Hashable | None = None, check_overlaps: bool = True) → Hashable[source]#

Add a one-hot constraint from an iterable.

One-hot constraints can represent discrete variables (for example a color variable that has values {"red", "blue", "green"}) by requiring that only one of a set of two or more binary variables is assigned a value of 1.

These constraints support only BINARY variables and must be disjoint; that is, variables in such a constraint must not be used elsewhere in the model.

Constraints added by this method are guaranteed to be satisfied in solutions returned by the LeapHybridCQMSampler hybrid sampler.

Parameters:

  • variables – An iterable of variables.

  • label – Label for the constraint. Must be unique. If no label is provided, then one is generated using uuid.

  • check_overlaps – If True we perform a variable overlap check. In particular, if the variables already exist, we make sure they’re not used in another discrete constraint.

Returns:

Label of the added constraint.

Examples

>>> cqm = dimod.ConstrainedQuadraticModel()
>>> color = ["red", "blue", "green"]
>>> for v in color:
...      cqm.add_variable('BINARY', v)
'red'
'blue'
'green'
>>> cqm.add_discrete(color, label='one-color')
'one-color'
>>> print(cqm.constraints['one-color'].to_polystring())
red + blue + green == 1.0