Notch filter for the signal x.
Applies a zero-phase notch filter to the signal x, operating on the last dimension.
array
Signal to filter.
float
Sampling rate in Hz.
float
| array
of float
| None
Frequencies to notch filter in Hz, e.g. np.arange(60, 241, 60). None can only be used with the mode ‘spectrum_fit’, where an F test is used to find sinusoidal components.
str
| int
Length of the FIR filter to use (if applicable):
‘auto’ (default): The filter length is chosen based on the size of the transition regions (6.6 times the reciprocal of the shortest transition band for fir_window=’hamming’ and fir_design=”firwin2”, and half that for “firwin”).
str: A human-readable time in
units of “s” or “ms” (e.g., “10s” or “5500ms”) will be
converted to that number of samples if phase="zero"
, or
the shortest power-of-two length at least that duration for
phase="zero-double"
.
int: Specified length in samples. For fir_design=”firwin”, this should not be used.
When method=='spectrum_fit'
, this sets the effective window duration
over which fits are computed. See mne.filter.create_filter()
for options. Longer window lengths will give more stable frequency
estimates, but require (potentially much) more processing and are not able
to adapt as well to non-stationarities.
The default in 0.21 is None, but this will change to '10s'
in 0.22.
float
| array
of float
| None
Width of the stop band (centred at each freq in freqs) in Hz. If None, freqs / 200 is used.
float
Width of the transition band in Hz.
Only used for method='fir'
.
str
‘fir’ will use overlap-add FIR filtering, ‘iir’ will use IIR forward-backward filtering (via filtfilt). ‘spectrum_fit’ will use multi-taper estimation of sinusoidal components. If freqs=None and method=’spectrum_fit’, significant sinusoidal components are detected using an F test, and noted by logging.
dict
| None
Dictionary of parameters to use for IIR filtering.
If iir_params is None and method=”iir”, 4th order Butterworth will be used.
For more information, see mne.filter.construct_iir_filter()
.
float
| None
The bandwidth of the multitaper windowing function in Hz. Only used in ‘spectrum_fit’ mode.
float
P-value to use in F-test thresholding to determine significant sinusoidal components to remove when method=’spectrum_fit’ and freqs=None. Note that this will be Bonferroni corrected for the number of frequencies, so large p-values may be justified.
list
| slice
| None
Channels to include. Slices and lists of integers will be interpreted as channel indices.
None (default) will pick all channels. Note that channels in info['bads']
will be included if their indices are explicitly provided.
Only supported for 2D (n_channels, n_times) and 3D
(n_epochs, n_channels, n_times) data.
int
| str
Number of jobs to run in parallel. Can be ‘cuda’ if cupy
is installed properly and method=’fir’.
If True, a copy of x, filtered, is returned. Otherwise, it operates on x in place.
str
Phase of the filter, only used if method='fir'
.
Symmetric linear-phase FIR filters are constructed, and if phase='zero'
(default), the delay of this filter is compensated for, making it
non-causal. If phase='zero-double'
,
then this filter is applied twice, once forward, and once backward
(also making it non-causal). If 'minimum'
, then a minimum-phase filter
will be constricted and applied, which is causal but has weaker stop-band
suppression.
New in version 0.13.
str
The window to use in FIR design, can be “hamming” (default), “hann” (default in 0.13), or “blackman”.
New in version 0.15.
str
Can be “firwin” (default) to use scipy.signal.firwin()
,
or “firwin2” to use scipy.signal.firwin2()
. “firwin” uses
a time-domain design technique that generally gives improved
attenuation using fewer samples than “firwin2”.
New in version 0.15.
str
The type of padding to use. Supports all numpy.pad()
mode
options. Can also be "reflect_limited"
, which pads with a
reflected version of each vector mirrored on the first and last values
of the vector, followed by zeros.
Only used for method='fir'
.
The default is 'reflect_limited'
.
str
| int
| None
Control verbosity of the logging output. If None
, use the default
verbosity level. See the logging documentation and
mne.verbose()
for details. Should only be passed as a keyword
argument.
array
The x array filtered.
See also
Notes
The frequency response is (approximately) given by:
1-|---------- -----------
| \ /
|H| | \ /
| \ /
| \ /
0-| -
| | | | |
0 Fp1 freq Fp2 Nyq
For each freq in freqs, where Fp1 = freq - trans_bandwidth / 2
and
Fs2 = freq + trans_bandwidth / 2
.
References
Multi-taper removal is inspired by code from the Chronux toolbox, see www.chronux.org and the book “Observed Brain Dynamics” by Partha Mitra & Hemant Bokil, Oxford University Press, New York, 2008. Please cite this in publications if method ‘spectrum_fit’ is used.