Allow concatenating BaseRaw objects

[cbrnr]

As reported in this forum post, mne.concatenate_raws() only works if all objects share the exact same type. In particular, this means that it is not possible to concatenate Raw (an alias for RawFIF) and RawArray objects, and other types like RawEDF, RawEEGLAB, etc. do not work either. However, since all concrete types inherit from BaseRaw, I think we could relax the compatibility check accordingly.

The following example fails on main, but works on this branch:

import numpy as np

import mne

sfreq = 100.0
ch_names = ["EEG 001", "EEG 002"]
ch_types = ["eeg"] * 2
info = mne.create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
data = np.random.randn(len(ch_names), 1000)

raw_array = mne.io.RawArray(data, info)
raw_array.save("temp_raw.fif", overwrite=True)
raw_fiff = mne.io.read_raw_fif("temp_raw.fif", preload=True)

mne.concatenate_raws([raw_fiff, raw_array])

[hoechenberger]

I didn't review any of the changes and don't know if there's any side effects to be expected; but purely from a user's POV, I'd say we should definitely try to support this

[sappelhoff]

I also think we should support this. Potential issues could arise from concatenating Raw types that support different attributes. For example, the BrainVision Raw supports impedances, but other Raws might not.

[larsoner]

At a bare minimum we would have to ensure all data are preloaded. And as @sappelhoff points out to keep things simple the resulting class should probably be RawArray since IIRC it doesn't have any extra attributes like impedance and such. (We could later maybe think about how to combine/keep them but I'd rather instead move toward removing them entirely.)