dwave.optimization.mathematical.where

where(condition: ArraySymbol, x: ArraySymbol, y: ArraySymbol) → Where

Return elements chosen from x or y depending on condition.

Parameters:

• condition – Where True, yield x, otherwise yield y.

• x – Values from which to choose. If x and y are dynamically sized then condition must be a single value.

• y – Values from which to choose. If x and y are dynamically sized then condition must be a single value.

Returns:

An ArraySymbol with elements from x where condition is True, and elements from y elsewhere.

Examples

This example uses a single binary variable to choose between two arrays.

>>> from dwave.optimization import Model
>>> from dwave.optimization.mathematical import where
...
>>> model = Model()
>>> condition = model.binary()
>>> x = model.constant([1., 2., 3.])
>>> y = model.constant([4., 5., 6.])
>>> a = where(condition, x, y)
>>> with model.lock():
...     model.states.resize(1)
...     condition.set_state(0, False)
...     print(a.state())
[4. 5. 6.]

This example uses a binary array to to select between two arrays.

>>> model = Model()
>>> condition = model.binary(3)
>>> x = model.constant([1., 2., 3.])
>>> y = model.constant([4., 5., 6.])
>>> a = where(condition, x, y)
>>> with model.lock():
...     model.states.resize(1)
...     condition.set_state(0, [True, True, False])
...     print(a.state())
[1. 2. 6.]

This example uses a single binary variable to choose between two sets.

>>> model = Model()
>>> condition = model.binary()
>>> x = model.set(10)  # any subset of range(10)
>>> y = model.set(10)  # any subset of range(10)
>>> a = where(condition, x, y)
>>> with model.lock():
...     model.states.resize(1)
...     condition.set_state(0, True)
...     x.set_state(0, [0., 2., 3.])
...     y.set_state(0, [1])
...     print(a.state())
[0. 2. 3.]