:py:mod:`pygsti.modelmembers.operations.affineshiftop`
======================================================

.. py:module:: pygsti.modelmembers.operations.affineshiftop

.. autoapi-nested-parse::

   The AffineShiftOp class and supporting functionality.






Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   pygsti.modelmembers.operations.affineshiftop.AffineShiftOp




.. py:class:: AffineShiftOp(m, basis=None, evotype='default', state_space=None)


   Bases: :py:obj:`pygsti.modelmembers.operations.denseop.DenseOperator`

   An operation matrix that induces an affine shift.

   An operation matrix with ones on the diagonal and nonzero values in
   the first columns.

   Meant to work in the Pauli basis for now.

   Parameters
   ----------
   m : array_like or LinearOperator
       a square 2D array-like or LinearOperator object representing the operation action.
       The shape of m sets the dimension of the operation.

   basis : Basis or {'pp','gm','std'} or None
       The basis used to construct the Hilbert-Schmidt space representation
       of this state as a super-operator.  If None, certain functionality,
       such as access to Kraus operators, will be unavailable.

   evotype : Evotype or str, optional
       The evolution type.  The special value `"default"` is equivalent
       to specifying the value of `pygsti.evotypes.Evotype.default_evotype`.

   state_space : StateSpace, optional
       The state space for this operation.  If `None` a default state space
       with the appropriate number of qubits is used.

   Attributes
   ----------
   base : numpy.ndarray
       Direct access to the underlying process matrix data.

   Initialize a new LinearOperator 

   .. py:property:: num_params

      Get the number of independent parameters which specify this operation.

      Returns
      -------
      int
          the number of independent parameters.


   .. py:method:: set_dense(m)

      Set the dense-matrix value of this operation.

      Attempts to modify operation parameters so that the specified raw
      operation matrix becomes m.  Will raise ValueError if this operation
      is not possible.

      Parameters
      ----------
      m : array_like or LinearOperator
          An array of shape (dim, dim) or LinearOperator representing the operation action.

      Returns
      -------
      None


   .. py:method:: to_vector()

      Get the operation parameters as an array of values.

      Returns
      -------
      numpy array
          The operation parameters as a 1D array with length num_params().


   .. py:method:: from_vector(v, close=False, dirty_value=True)

      Initialize the operation using a vector of parameters.

      Parameters
      ----------
      v : numpy array
          The 1D vector of operation parameters.  Length
          must == num_params()

      close : bool, optional
          Whether `v` is close to this operation's current
          set of parameters.  Under some circumstances, when this
          is true this call can be completed more quickly.

      dirty_value : bool, optional
          The value to set this object's "dirty flag" to before exiting this
          call.  This is passed as an argument so it can be updated *recursively*.
          Leave this set to `True` unless you know what you're doing.

      Returns
      -------
      None


   .. py:method:: deriv_wrt_params(wrt_filter=None)

      The element-wise derivative this operation.

      Construct a matrix whose columns are the vectorized
      derivatives of the flattened operation matrix with respect to a
      single operation parameter.  Thus, each column is of length
      op_dim^2 and there is one column per operation parameter.

      Parameters
      ----------
      wrt_filter : list or numpy.ndarray
          List of parameter indices to take derivative with respect to.
          (None means to use all the this operation's parameters.)

      Returns
      -------
      numpy array
          Array of derivatives with shape (dimension^2, num_params)


   .. py:method:: has_nonzero_hessian()

      Whether this operation has a non-zero Hessian with respect to its parameters.

      (i.e. whether it only depends linearly on its parameters or not)

      Returns
      -------
      bool