dimod.as_bqm

as_bqm(*args, cls=None, copy=False)[source]

Convert the input to a binary quadratic model.

Converts the following input formats to a binary quadratic model (BQM):

as_bqm(vartype)

Creates an empty binary quadratic model.

as_bqm(bqm)

Creates a BQM from another BQM. See copy and cls kwargs below.

as_bqm(bqm, vartype)

Creates a BQM from another BQM, changing to the appropriate vartype if necessary. See copy and cls kwargs below.

as_bqm(n, vartype)

Creates a BQM with n variables, indexed linearly from zero, setting all biases to zero.

as_bqm(quadratic, vartype)

Creates a BQM from quadratic biases given as a square array_like or a dictionary of the form {(u, v): b, …}. Note that when formed with SPIN-variables, biases on the diagonal are added to the offset.

as_bqm(linear, quadratic, vartype)

Creates a BQM from linear and quadratic biases, where linear is a one-dimensional array_like or a dictionary of the form {v: b, …}, and quadratic is a square array_like or a dictionary of the form {(u, v): b, …}. Note that when formed with SPIN-variables, biases on the diagonal are added to the offset.

as_bqm(linear, quadratic, offset, vartype)

Creates a BQM from linear and quadratic biases, where linear is a one-dimensional array_like or a dictionary of the form {v: b, …}, and quadratic is a square array_like or a dictionary of the form {(u, v): b, …}, and offset is a numerical offset. Note that when formed with SPIN-variables, biases on the diagonal are added to the offset.

Parameters
  • *args – See above.

  • cls (type/list, optional) – Class of the returned BQM. If given as a list, the returned BQM is of one of the types in the list. Default is AdjVectorBQM.

  • copy (bool, optional, default=False) – If False, a new BQM is only constructed when necessary.

Returns

A binary quadratic model.