def design_fir_filter(sig_length,
fs,
pass_type,
f_range,
n_cycles=3,
n_seconds=None):
"""Design an FIR filter.
Parameters
----------
sig_length : int
The length of the signal to be filtered.
fs : float
Sampling rate, in Hz.
pass_type : {'bandpass', 'bandstop', 'lowpass', 'highpass'}
Which kind of filter to apply:
* 'bandpass': apply a bandpass filter
* 'bandstop': apply a bandstop (notch) filter
* 'lowpass': apply a lowpass filter
* 'highpass' : apply a highpass filter
f_range : tuple of (float, float) or float
Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
For 'bandpass' & 'bandstop', must be a tuple.
For 'lowpass' or 'highpass', can be a float that specifies pass frequency, or can be
a tuple and is assumed to be (None, f_hi) for 'lowpass', and (f_lo, None) for 'highpass'.
n_cycles : float, optional, default: 3
Length of filter, in number of cycles, defined at the 'f_lo' frequency.
This parameter is overwritten by `n_seconds`, if provided.
n_seconds : float, optional
Length of filter, in seconds. This parameter overwrites `n_cycles`.
Returns
-------
filter_coefs : 1d array
The filter coefficients for an FIR filter.
"""
# Check filter definition
f_lo, f_hi = check_filter_definition(pass_type, f_range)
filt_len = compute_filt_len(sig_length, fs, pass_type, f_lo, f_hi,
n_cycles, n_seconds)
f_nyq = compute_nyquist(fs)
if pass_type == 'bandpass':
filter_coefs = firwin(filt_len, (f_lo, f_hi),
pass_zero=False,
nyq=f_nyq)
elif pass_type == 'bandstop':
filter_coefs = firwin(filt_len, (f_lo, f_hi), nyq=f_nyq)
elif pass_type == 'highpass':
filter_coefs = firwin(filt_len, f_lo, pass_zero=False, nyq=f_nyq)
elif pass_type == 'lowpass':
filter_coefs = firwin(filt_len, f_hi, nyq=f_nyq)
return filter_coefs
def design_iir_filter(fs, pass_type, f_range, butterworth_order):
"""Design an IIR filter.
Parameters
----------
fs : float
Sampling rate, in Hz.
pass_type : {'bandpass', 'bandstop', 'lowpass', 'highpass'}
Which kind of filter to apply:
* 'bandpass': apply a bandpass filter
* 'bandstop': apply a bandstop (notch) filter
* 'lowpass': apply a lowpass filter
* 'highpass' : apply a highpass filter
f_range : tuple of (float, float) or float
Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
For 'bandpass' & 'bandstop', must be a tuple.
For 'lowpass' or 'highpass', can be a float that specifies pass frequency, or can be
a tuple and is assumed to be (None, f_hi) for 'lowpass', and (f_lo, None) for 'highpass'.
butterworth_order : int
Order of the butterworth filter, if using an IIR filter.
See input 'N' in scipy.signal.butter.
Returns
-------
sos : 2d array
Second order series coefficients for an IIR filter. Has shape of (n_sections, 6).
Examples
--------
Compute coefficients for a bandstop IIR filter:
>>> sos = design_iir_filter(fs=500, pass_type='bandstop',
... f_range=(55, 65), butterworth_order=7)
"""
# Check filter definition
f_lo, f_hi = check_filter_definition(pass_type, f_range)
f_nyq = compute_nyquist(fs)
if pass_type in ('bandpass', 'bandstop'):
win = (f_lo / f_nyq, f_hi / f_nyq)
elif pass_type == 'highpass':
win = f_lo / f_nyq
elif pass_type == 'lowpass':
win = f_hi / f_nyq
# Design filter
sos = butter(butterworth_order, win, pass_type, output='sos')
return sos
def design_iir_filter(fs, pass_type, f_range, butterworth_order):
"""Design an IIR filter.
Parameters
----------
fs : float
Sampling rate, in Hz.
pass_type : {'bandpass', 'bandstop', 'lowpass', 'highpass'}
Which kind of filter to apply:
* 'bandpass': apply a bandpass filter
* 'bandstop': apply a bandstop (notch) filter
* 'lowpass': apply a lowpass filter
* 'highpass' : apply a highpass filter
f_range : tuple of (float, float) or float
Cutoff frequency(ies) used for filter, specified as f_lo & f_hi.
For 'bandpass' & 'bandstop', must be a tuple.
For 'lowpass' or 'highpass', can be a float that specifies pass frequency, or can be
a tuple and is assumed to be (None, f_hi) for 'lowpass', and (f_lo, None) for 'highpass'.
butterworth_order : int
Order of the butterworth filter, if using an IIR filter.
See input 'N' in scipy.signal.butter.
Returns
-------
b_vals : 1d array
B value filter coefficients for an IIR filter.
a_vals : 1d array
A value filter coefficients for an IIR filter.
"""
# Warn about only recommending IIR for bandstop
if pass_type != 'bandstop':
warn('IIR filters are not recommended other than for notch filters.')
# Check filter definition
f_lo, f_hi = check_filter_definition(pass_type, f_range)
f_nyq = compute_nyquist(fs)
if pass_type in ('bandpass', 'bandstop'):
win = (f_lo / f_nyq, f_hi / f_nyq)
elif pass_type == 'highpass':
win = f_lo / f_nyq
elif pass_type == 'lowpass':
win = f_hi / f_nyq
# Design filter
b_vals, a_vals = butter(butterworth_order, win, pass_type)
return b_vals, a_vals