qiskit Upgrade EstimatorResult dataclass

trafficstars

Summary

Upgrades the EstimatorResult dataclass.

Breaking change* Closes #8100 Changelog: New Feature

Details and comments

Rename values field to expectation_values.
Add variances field, pulling it out of metadata.
Remove numpy array type in favor of core python tuple.
Change metadata list type (mutable) in favor of tuple (immutable).

*Assuming that these objects are meant to be consumed by the users, not instantiated, the only breaking change is the metadata type change from list to tuple; since we can alias expectation_values to the old name values with the appropriate type casting.

To do

[x] Update Estimator class.
[x] Fix and update tests.
[ ] Add release note.

May 24 '22 16:05 pedrorrivero

Thank you for opening a new pull request.

Before your PR can be merged it will first need to pass continuous integration tests and be reviewed. Sometimes the review process can be slow, so please be patient.

While you're waiting, please feel free to review other open PRs. While only a subset of people are authorized to approve pull requests for merging, everyone is encouraged to review open pull requests. Doing reviews helps reduce the burden on the core team and helps make the project's code better for everyone.

One or more of the the following people are requested to review this:

@Qiskit/terra-core
@ajavadia
@ikkoham
@levbishop
@t-imamichi

May 24 '22 16:05 qiskit-bot

I'm not involved in this module at all, so my view isn't especially important, I just wanted to point out that making breaking changes to an API is generally not something we allow within Qiskit. We have a complete deprecation policy, but extensible APIs that other people are meant to implement can't really be changed without some form of versioning, because there's not usually a way to make things valid for two different versions of Terra at the same time.

But do note that I'm not involved with primitives at all, so I'm not a reviewer for this change, and welcome to the org!

May 25 '22 13:05 jakelishman

We put variance in metadata because we have not concluded which information to add in addition to the expectation value, variance, standard deviation or standard error. We currently use metadata because we can modify it without changing the interface. If we put the additional information as the attribute, we have to choose which to include, variance, standard deviation or standard error.