firwin(numtaps, cutoff, width=None, window='hamming', pass_zero=True, scale=True, nyq=None, fs=None)
This function computes the coefficients of a finite impulse response filter. The filter will have linear phase; it will be Type I if :None:None:`numtaps` is odd and Type II if :None:None:`numtaps` is even.
Type II filters always have zero response at the Nyquist frequency, so a ValueError exception is raised if firwin is called with :None:None:`numtaps` even and having a passband whose right end is at the Nyquist frequency.
Length of the filter (number of coefficients, i.e. the filter order + 1). :None:None:`numtaps` must be odd if a passband includes the Nyquist frequency.
Cutoff frequency of filter (expressed in the same units as :None:None:`fs`) OR an array of cutoff frequencies (that is, band edges). In the latter case, the frequencies in :None:None:`cutoff` should be positive and monotonically increasing between 0 and :None:None:`fs/2`. The values 0 and :None:None:`fs/2` must not be included in :None:None:`cutoff`.
If :None:None:`width` is not None, then assume it is the approximate width of the transition region (expressed in the same units as :None:None:`fs`) for use in Kaiser FIR filter design. In this case, the :None:None:`window` argument is ignored.
Desired window to use. See scipy.signal.get_window
for a list of windows and required parameters.
If True, the gain at the frequency 0 (i.e., the "DC gain") is 1. If False, the DC gain is 0. Can also be a string argument for the desired filter type (equivalent to btype
in IIR design functions).
Support for string arguments.
Set to True to scale the coefficients so that the frequency response is exactly unity at a certain frequency. That frequency is either:
0 (DC) if the first passband starts at 0 (i.e. pass_zero is True)
:None:None:`fs/2` (the Nyquist frequency) if the first passband ends at :None:None:`fs/2` (i.e the filter is a single band highpass filter); center of first passband otherwise
Deprecated. Use `fs` instead. This is the Nyquist frequency. Each frequency in :None:None:`cutoff` must be between 0 and :None:None:`nyq`. Default is 1.
The sampling frequency of the signal. Each frequency in :None:None:`cutoff` must be between 0 and fs/2
. Default is 2.
If any value in :None:None:`cutoff` is less than or equal to 0 or greater than or equal to fs/2
, if the values in :None:None:`cutoff` are not strictly monotonically increasing, or if :None:None:`numtaps` is even but a passband includes the Nyquist frequency.
Coefficients of length :None:None:`numtaps` FIR filter.
FIR filter design using the window method.
Low-pass from 0 to f:
>>> from scipy import signal
... numtaps = 3
... f = 0.1
... signal.firwin(numtaps, f) array([ 0.06799017, 0.86401967, 0.06799017])
Use a specific window function:
>>> signal.firwin(numtaps, f, window='nuttall') array([ 3.56607041e-04, 9.99286786e-01, 3.56607041e-04])
High-pass ('stop' from 0 to f):
>>> signal.firwin(numtaps, f, pass_zero=False) array([-0.00859313, 0.98281375, -0.00859313])
Band-pass:
>>> f1, f2 = 0.1, 0.2
... signal.firwin(numtaps, [f1, f2], pass_zero=False) array([ 0.06301614, 0.88770441, 0.06301614])
Band-stop:
>>> signal.firwin(numtaps, [f1, f2]) array([-0.00801395, 1.0160279 , -0.00801395])
Multi-band (passbands are [0, f1], [f2, f3] and [f4, 1]):
>>> f3, f4 = 0.3, 0.4
... signal.firwin(numtaps, [f1, f2, f3, f4]) array([-0.01376344, 1.02752689, -0.01376344])
Multi-band (passbands are [f1, f2] and [f3,f4]):
>>> signal.firwin(numtaps, [f1, f2, f3, f4], pass_zero=False) array([ 0.04890915, 0.91284326, 0.04890915])See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._fir_filter_design.firwin
scipy.signal._fir_filter_design.firwin2
scipy.signal._fir_filter_design.remez
scipy.signal._fir_filter_design.minimum_phase
scipy.signal._signaltools.resample_poly
scipy.signal._fir_filter_design.firls
scipy.signal._fir_filter_design.kaiserord
scipy.signal._filter_design.gammatone
scipy.signal._filter_design.freqz
scipy.signal._signaltools.oaconvolve
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