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Add combine_tfr to API #13054

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merged 9 commits into from
Jan 14, 2025
Merged

Add combine_tfr to API #13054

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02d9dc6
Squashed commit of the following:
tsbinns Jan 10, 2025
0047dec
Add combine_tfr to API
tsbinns Jan 10, 2025
3f88e2b
Add link to combine_tfr in changelog
tsbinns Jan 10, 2025
676fa13
Add changelog entry
tsbinns Jan 10, 2025
10b0e3d
Change changelog entry
tsbinns Jan 10, 2025
583acd1
Merge branch 'main' into add_combine_tfr_to_api
tsbinns Jan 10, 2025
feb9a0a
Merge branch 'main' into add_combine_tfr_to_api
tsbinns Jan 13, 2025
9dd932c
Cleanup after upstream merge
tsbinns Jan 13, 2025
00edc4f
Merge branch 'main' into add_combine_tfr_to_api
drammock Jan 13, 2025
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1 change: 1 addition & 0 deletions doc/api/time_frequency.rst
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Expand Up @@ -31,6 +31,7 @@ Functions that operate on mne-python objects:
.. autosummary::
:toctree: ../generated/

combine_tfr
csd_tfr
csd_fourier
csd_multitaper
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1 change: 1 addition & 0 deletions doc/changes/devel/13054.newfeature.rst
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@@ -0,0 +1 @@
Added :func:`mne.time_frequency.combine_tfr` to allow combining TFRs across tapers, by `Thomas Binns`_.
2 changes: 2 additions & 0 deletions mne/time_frequency/__init__.pyi
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Expand Up @@ -11,6 +11,7 @@ __all__ = [
"RawTFRArray",
"Spectrum",
"SpectrumArray",
"combine_tfr",
"csd_array_fourier",
"csd_array_morlet",
"csd_array_multitaper",
Expand Down Expand Up @@ -71,6 +72,7 @@ from .tfr import (
EpochsTFRArray,
RawTFR,
RawTFRArray,
combine_tfr,
fwhm,
morlet,
read_tfrs,
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8 changes: 4 additions & 4 deletions mne/time_frequency/tfr.py
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Expand Up @@ -3914,10 +3914,10 @@ def __init__(
def combine_tfr(all_tfr, weights="nave"):
"""Merge AverageTFR data by weighted addition.

Create a new AverageTFR instance, using a combination of the supplied
instances as its data. By default, the mean (weighted by trials) is used.
Subtraction can be performed by passing negative weights (e.g., [1, -1]).
Data must have the same channels and the same time instants.
Create a new :class:`mne.time_frequency.AverageTFR` instance, using a combination of
the supplied instances as its data. By default, the mean (weighted by trials) is
used. Subtraction can be performed by passing negative weights (e.g., [1, -1]). Data
must have the same channels and the same time instants.

Parameters
----------
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