Address issues

[pollytur]

Small PR to address issues #32 , #70 , #73

[gitnotebooks]

Review these changes at https://app.gitnotebooks.com/sensorium-competition/experanto/pull/90

[Copilot]

Pull request overview

This PR addresses issues #32, #70, and #73 by introducing a return_valid parameter to interpolation methods, removing unused code, and renaming a confusing transform option. The changes enable callers to optionally request validation masks from interpolation operations, making the API more flexible while maintaining backward compatibility through default parameter values.

Key Changes:

• Added return_valid parameter to all interpolator classes to conditionally return validation masks
• Renamed "standardize" transform mode to "normalize_variance_only" for clarity
• Removed unused namedtuple imports and DataPoint class

Reviewed changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated 9 comments.

Show a summary per file

File	Description
experanto/interpolators.py	Added return_valid parameter to abstract method and all concrete implementations (SequenceInterpolator, PhaseShiftedSequenceInterpolator, ScreenInterpolator, TimeIntervalInterpolator) with conditional return logic
experanto/experiment.py	Updated interpolate method signature to accept and propagate return_valid parameter; removed unused namedtuple import
experanto/datasets.py	Updated interpolate calls to use return_valid=False; renamed "standardize" to "normalize_variance_only"; removed unused namedtuple and DataPoint
configs/default.yaml	Updated normalization config value from "standardize" to "normalize_variance_only"
docs/source/concepts/demo_configs.rst	Updated example config to use "normalize_variance_only"
README.md	Added documentation badge link

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[Copilot]

Pull request overview

Copilot reviewed 8 out of 8 changed files in this pull request and generated 7 comments.

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Pull request overview

Copilot reviewed 11 out of 11 changed files in this pull request and generated 5 comments.

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[pollytur]

@reneburghardt @schewskone would be great if you could take a look
I also run pyright locally, so the type annotation should be actually fine. We could add it to the CI/CD later but I think this PR is big enough already