The ComplementPOVMEffect class and supporting functionality.

Module Contents



TODO: docstring

class pygsti.modelmembers.povms.complementeffect.ComplementPOVMEffect(identity, other_effects, called_from_reduce=False)

Bases: pygsti.modelmembers.povms.conjugatedeffect.ConjugatedStatePOVMEffect

TODO: docstring A POVM effect vector that ensures that all the effects of a POVM sum to the identity.

This POVM effect vector is paramterized as I - sum(other_spam_vecs) where I is a (static) identity element and other_param_vecs is a list of other spam vectors in the same parent POVM. This only partially implements the model-member interface (some methods such as to_vector and from_vector will thunk down to base class versions which raise NotImplementedError), as instances are meant to be contained within a POVM which takes care of vectorization.


identityarray_like or POVMEffect

a 1D numpy array representing the static identity operation from which the sum of the other vectors is subtracted.

other_spamvecslist of POVMEffects

A list of the “other” parameterized POVM effect vectors which are subtracted from identity to compute the final value of this “complement” POVM effect vector.

Initialize a new POVM effect Vector

property num_params

Get the number of independent parameters which specify this POVM effect vector.


the number of independent parameters.


Create a serializable dict with references to other objects in the memo.

mmg_memo: dict

Memo dict from a ModelMemberGraph, i.e. keys are object ids and values are ModelMemberGraphNodes (which contain the serialize_id). This is NOT the same as other memos in ModelMember (e.g. copy, allocate_gpindices, etc.).

mm_dict: dict

A dict representation of this ModelMember ready for serialization This must have at least the following fields: module, class, submembers, params, state_space, evotype Additional fields may be added by derived classes.


Get the ModelMember-derived objects contained in this one.




Get the POVM effect vector parameters as an array of values.

numpy array

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

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

Initialize the POVM effect vector using a 1D array of parameters.

vnumpy array

The 1D vector of POVM effect vector parameters. Length must == num_params()

closebool, optional

Whether v is close to this POVM effect vector’s current set of parameters. Under some circumstances, when this is true this call can be completed more quickly.

dirty_valuebool, 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.




The element-wise derivative this POVM effect vector.

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

wrt_filterlist 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 POVM effect vector has a non-zero Hessian with respect to its parameters.