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Log warning when sf or ch_names are ignored #207

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Log warning when sf or ch_names are ignored #207

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27c470f
warn user when `sf` and `ch_names` are redundant with `data`
remrama Mar 8, 2025
b628c3c
add unittests to cover warnings
remrama Mar 8, 2025
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22 changes: 14 additions & 8 deletions src/yasa/detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,10 @@ def _check_data_hypno(data, sf=None, ch_names=None, hypno=None, include=None, ch
"""Helper functions for preprocessing of data and hypnogram."""
# 1) Extract data as a 2D NumPy array
if isinstance(data, mne.io.BaseRaw):
if sf is not None:
logger.warning("sf parameter will be ignored, sf from MNE Raw will be used")
if ch_names is not None:
logger.warning("ch_names parameter will be ignored, ch_names from MNE Raw will be used")
sf = data.info["sfreq"] # Extract sampling frequency
ch_names = data.ch_names # Extract channel names
data = data.get_data(units=dict(eeg="uV", emg="uV", eog="uV", ecg="uV"))
Expand Down Expand Up @@ -597,19 +601,20 @@ def spindles_detect(
Parameters
----------
data : array_like or :py:class:`mne.io.BaseRaw`
Single or multi-channel data. If ``data`` is array_like, unit must be uV and of
Single or multi-channel data. If ``data`` is *array_like*, unit must be uV and of
shape (n_samples) or (n_chan, n_samples). If ``data`` is a :py:class:`~mne.io.BaseRaw`
instance, ``data``, ``sf``, and ``ch_names`` will be automatically extracted, and
``data`` will be automatically converted from Volts (MNE) to micro-Volts (YASA).
sf : float
Sampling frequency of the data in Hz.
Can be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
Sampling frequency of the data in Hz when ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.

.. tip:: If the detection is taking too long, make sure to downsample
your data to 100 Hz (or 128 Hz). For more details, please refer to
:py:func:`mne.filter.resample`.
ch_names : list of str
Channel names. Can be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
Channel names if ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
hypno : array_like
Sleep stage (hypnogram). If the hypnogram is loaded, the
detection will only be applied to the value defined in
Expand Down Expand Up @@ -1415,19 +1420,20 @@ def sw_detect(
Parameters
----------
data : array_like or :py:class:`mne.io.BaseRaw`
Single or multi-channel data. If ``data`` is array_like, unit must be uV and of
Single or multi-channel data. If ``data`` is *array_like*, unit must be uV and of
shape (n_samples) or (n_chan, n_samples). If ``data`` is a :py:class:`~mne.io.BaseRaw`
instance, ``data``, ``sf``, and ``ch_names`` will be automatically extracted, and
``data`` will be automatically converted from Volts (MNE) to micro-Volts (YASA).
sf : float
Sampling frequency of the data in Hz.
Can be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
Sampling frequency of the data in Hz if ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.

.. tip:: If the detection is taking too long, make sure to downsample
your data to 100 Hz (or 128 Hz). For more details, please refer to
:py:func:`mne.filter.resample`.
ch_names : list of str
Channel names. Can be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
Channel names if ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw` instance.
hypno : array_like
Sleep stage (hypnogram). If the hypnogram is loaded, the
detection will only be applied to the value defined in
Expand Down
25 changes: 13 additions & 12 deletions src/yasa/spectral.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,17 +45,18 @@ def bandpower(

Parameters
----------
data : np.array_like or :py:class:`mne.io.BaseRaw`
1D or 2D EEG data. If ``data`` is array_like, unit must be uV.
data : array_like or :py:class:`mne.io.BaseRaw`
1D or 2D EEG data. If ``data`` is *array_like*, unit must be uV.
If ``data`` is a :py:class:`~mne.io.BaseRaw` instance, ``data``, ``sf``, and
``ch_names`` will be automatically extracted, and ``data`` will be automatically
converted from Volts (MNE) to micro-Volts (YASA).
sf : float
The sampling frequency of data AND the hypnogram. Can be omitted if ``data`` is a
:py:class:`mne.io.BaseRaw`.
The sampling frequency of data AND the hypnogram if ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw`.
ch_names : list
List of channel names, e.g. ['Cz', 'F3', 'F4', ...]. If None, channels will be labelled
['CHAN000', 'CHAN001', ...]. Can be omitted if ``data`` is a :py:class:`mne.io.BaseRaw`.
List of channel names, e.g. ['Cz', 'F3', 'F4', ...], if ``data`` is *array_like*.
If None, channels will be labelled ['CHAN000', 'CHAN001', ...].
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw`.
hypno : array_like
Sleep stage (hypnogram). If the hypnogram is loaded, the bandpower will be extracted for
each sleep stage defined in ``include``.
Expand Down Expand Up @@ -400,17 +401,17 @@ def irasa(
Parameters
----------
data : :py:class:`numpy.ndarray` or :py:class:`mne.io.BaseRaw`
1D or 2D EEG data. If ``data`` is array_like, unit must be uV.
1D or 2D EEG data. If ``data`` is *array_like*, unit must be uV.
If ``data`` is a :py:class:`~mne.io.BaseRaw` instance, ``data``, ``sf``, and
``ch_names`` will be automatically extracted, and ``data`` will be automatically
converted from Volts (MNE) to micro-Volts (YASA).
sf : float
The sampling frequency of data AND the hypnogram.
Can be omitted if ``data`` is a :py:class:`mne.io.BaseRaw`.
The sampling frequency of data AND the hypnogram if ``data`` is *array_like*.
Should be omitted if ``data`` is a :py:class:~`mne.io.BaseRaw`.
ch_names : list
List of channel names, e.g. ['Cz', 'F3', 'F4', ...]. If None,
channels will be labelled ['CHAN000', 'CHAN001', ...].
Can be omitted if ``data`` is a :py:class:`mne.io.BaseRaw`.
List of channel names, e.g. ['Cz', 'F3', 'F4', ...], if ``data`` is *array_like*.
If None, channels will be labelled ['CHAN000', 'CHAN001', ...].
Should be omitted if ``data`` is a :py:class:`~mne.io.BaseRaw`.
band : tuple or None
Broad band frequency range.
Default is 1 to 30 Hz.
Expand Down
14 changes: 12 additions & 2 deletions tests/test_detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,14 @@
import pytest
from mne.filter import filter_data

from yasa.detection import art_detect, compare_detection, rem_detect, spindles_detect, sw_detect
from yasa.detection import (
_check_data_hypno,
art_detect,
compare_detection,
rem_detect,
spindles_detect,
sw_detect,
)
from yasa.fetchers import fetch_sample
from yasa.hypno import hypno_str_to_int, hypno_upsample_to_data

Expand Down Expand Up @@ -62,7 +69,10 @@ class TestDetection(unittest.TestCase):

def test_check_data_hypno(self):
"""Test preprocessing of data and hypno."""
pass
with self.assertLogs("yasa", level="WARNING"):
_check_data_hypno(data_mne, sf=999) # sf is ignored
with self.assertLogs("yasa", level="WARNING"):
_check_data_hypno(data_mne, ch_names=["CH999"]) # ch_names is ignored

def test_spindles_detect(self):
"""Test spindles_detect"""
Expand Down