The FullState class and supporting functionality.

Module Contents



A "fully parameterized" state vector where each element is an independent parameter.

class pygsti.modelmembers.states.fullstate.FullState(vec, evotype='default', state_space=None)

Bases: pygsti.modelmembers.states.densestate.DenseState

A “fully parameterized” state vector where each element is an independent parameter.

  • vec (array_like or SPAMVec) – a 1D numpy array representing the SPAM operation. The shape of this array sets the dimension of the SPAM op.

  • 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 state. If None a default state space with the appropriate number of qubits is used.

set_dense(self, vec)

Set the dense-vector value of this SPAM vector.

Attempts to modify this SPAM vector’s parameters so that the raw SPAM vector becomes vec. Will raise ValueError if this operation is not possible.


vec (array_like or SPAMVec) – A numpy array representing a SPAM vector, or a SPAMVec object.



property num_params(self)

Get the number of independent parameters which specify this SPAM vector.


int – the number of independent parameters.


Get the SPAM vector parameters as an array of values.


numpy array – The parameters as a 1D array with length num_params().

from_vector(self, v, close=False, dirty_value=True)

Initialize the SPAM vector using a 1D array of parameters.

  • v (numpy array) – The 1D vector of SPAM vector parameters. Length must == num_params()

  • close (bool, optional) – Whether v is close to this SPAM vector’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.



deriv_wrt_params(self, wrt_filter=None)

The element-wise derivative this SPAM vector.

Construct a matrix whose columns are the derivatives of the SPAM vector with respect to a single param. Thus, each column is of length dimension and there is one column per SPAM vector parameter.


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.)


numpy array – Array of derivatives, shape == (dimension, num_params)


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