Method sample_ising

dwave/cloud/solver.py:1203–1255

Sample from the specified :term:`Ising` model. Args: linear (dict/list): Linear biases of the Ising problem. If a dict, should be of the form `{v: bias, ...}` where v is a spin-valued variable and `bias` is its associated bias. If

(self, linear, quadratic, offset=0, label=None, **params)

    # Sampling methods

    def sample_ising(self, linear, quadratic, offset=0, label=None, **params):
        """Sample from the specified :term:`Ising` model.

        Args:
            linear (dict/list):
                Linear biases of the Ising problem. If a dict, should be of the
                form `{v: bias, ...}` where v is a spin-valued variable and `bias`
                is its associated bias. If a list, it is treated as a list of
                biases where the indices are the variable labels.

            quadratic (dict[(int, int), float]):
                Quadratic terms of the model (J), stored in a dict. With keys
                that are 2-tuples of variables and values are quadratic biases
                associated with the pair of variables (the interaction).

            offset (float, optional, default=0):
                Constant offset applied to the model.

            label (str, optional):
                Problem label you can optionally tag submissions with for ease
                of identification.

            **params:
                Parameters for the sampling method, solver-specific.

        Returns:
            :class:`~dwave.cloud.computation.Future`

        Examples:
            This example creates a client using the local system's default D-Wave
            Cloud Client configuration file, which is configured to access an 
            Advantage QPU, submits a simple :term:`Ising` problem (opposite 
            linear biases on two coupled qubits), and samples 5 times.

            >>> from dwave.cloud import Client
            >>> with Client.from_config() as client:
            ...     solver = client.get_solver()
            ...     u, v = next(iter(solver.edges))
            ...     computation = solver.sample_ising({u: -1, v: 1}, {}, num_reads=5)   # doctest: +SKIP
            ...     for i in range(5):
            ...         print(computation.samples[i][u], computation.samples[i][v])
            ...
            ...
            (1, -1)
            (1, -1)
            (1, -1)
            (1, -1)
            (1, -1)

        """
        # Our linear and quadratic objective terms are already separated in an
        # ising model so we can just directly call `_sample`.
        return self._sample('ising', linear, quadratic, offset, params, label=label)

    def sample_qubo(self, qubo, offset=0, label=None, **params):
        """Sample from the specified :term:`QUBO`.