Parameters: 
 data : ndarray, shape (…, n_times)
The data to filter.
 sfreq : float
The sample frequency in Hz.
 l_freq : float  None
Low cutoff frequency in Hz. If None the data are only lowpassed.
 h_freq : float  None
High cutoff frequency in Hz. If None the data are only
highpassed.
 picks : list  slice  None
Channels to include. Slices and lists of integers will be
interpreted as channel indices. None (default) will pick all channels.
Currently this is only supported for 2D (n_channels, n_times) and
3D (n_epochs, n_channels, n_times) arrays.
 filter_length : 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 humanreadable 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 poweroftwo length at least that duration for
phase="zerodouble" .
 int: specified length in samples. For fir_design=”firwin”,
this should not be used.
 l_trans_bandwidth : float  str
Width of the transition band at the low cutoff frequency in Hz
(high pass or cutoff 1 in bandpass). Can be “auto”
(default in 0.14) to use a multiple of l_freq :
min(max(l_freq * 0.25, 2), l_freq)
Only used for method='fir' .
 h_trans_bandwidth : float  str
Width of the transition band at the high cutoff frequency in Hz
(low pass or cutoff 2 in bandpass). Can be “auto”
(default in 0.14) to use a multiple of h_freq :
min(max(h_freq * 0.25, 2.), info['sfreq'] / 2.  h_freq)
Only used for method='fir' .
 n_jobs : int  str
Number of jobs to run in parallel. Can be ‘cuda’ if cupy
is installed properly and method=’fir’.
 method : str
‘fir’ will use overlapadd FIR filtering, ‘iir’ will use IIR
forwardbackward filtering (via filtfilt).
 iir_params : dict  None
Dictionary of parameters to use for IIR filtering.
See mne.filter.construct_iir_filter for details. If iir_params
is None and method=”iir”, 4th order Butterworth will be used.
 copy : bool
If True, a copy of x, filtered, is returned. Otherwise, it operates
on x in place.
 phase : str
Phase of the filter, only used if method='fir' .
By default, a symmetric linearphase FIR filter is constructed.
If phase='zero' (default), the delay of this filter
is compensated for. If phase=='zerodouble' , then this filter
is applied twice, once forward, and once backward. If ‘minimum’,
then a minimumphase, causal filter will be used.
 fir_window : str
The window to use in FIR design, can be “hamming” (default),
“hann” (default in 0.13), or “blackman”.
 fir_design : str
Can be “firwin” (default) to use scipy.signal.firwin() ,
or “firwin2” to use scipy.signal.firwin2() . “firwin” uses
a timedomain design technique that generally gives improved
attenuation using fewer samples than “firwin2”.
..versionadded:: 0.15
 pad : str
The type of padding to use. Supports all numpy.pad() mode
options. Can also be “reflect_limited” (default), 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' .
 verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
