Describe the new feature or enhancement
Currently apply_hilbert can be applied only to raw/epochs/epoched data through, for example, epochs. apply_hilbert.
The idea is to change this whole function into the time_frequency module. Then the epochs/raw/evoked/source data can be an argument to the function (EX: mne.time_frequency.EpochsTFR)
Describe your proposed implementation
It can be a new class in the tfr.py file. It would be based on the ancient .apply_hilbert function.
Describe possible alternatives
The alternative that is being used now is script hilbert function for source data or apply_hilbert for other types.
The proposed implementation will make the function independent of the data type/object
Additional context
I am happy to propose an implementation. I just want to check with maintainers for directions before starting. As this is a huge change in a lot of classes/files. I think it should be discussed before starting the implementation.
Describe the new feature or enhancement
Currently apply_hilbert can be applied only to raw/epochs/epoched data through, for example, epochs. apply_hilbert.
The idea is to change this whole function into the time_frequency module. Then the epochs/raw/evoked/source data can be an argument to the function (EX: mne.time_frequency.EpochsTFR)
Describe your proposed implementation
It can be a new class in the tfr.py file. It would be based on the ancient .apply_hilbert function.
Describe possible alternatives
The alternative that is being used now is script hilbert function for source data or apply_hilbert for other types.
The proposed implementation will make the function independent of the data type/object
Additional context
I am happy to propose an implementation. I just want to check with maintainers for directions before starting. As this is a huge change in a lot of classes/files. I think it should be discussed before starting the implementation.