mathdatech/Python
1
0
Fork 0
mirror of https://github.com/TheAlgorithms/Python.git synced 2025-01-18 00:07:00 +00:00
Code Issues Packages Projects Releases Wiki Activity

Fix sphinx/build_docs warnings for audio_filters (#12449)

Browse Source 
* updating DIRECTORY.md

* Fix sphinx/build_docs warnings for audio_filters

* Improve

* Fix

* Fix

* Fix

---------

Co-authored-by: MaximSmolskiy <MaximSmolskiy@users.noreply.github.com>
This commit is contained in:
Maxim Smolskiy 2024-12-23 06:55:22 +03:00 committed by GitHub
parent f8e595e048
commit 4abfce2791
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 19 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
audio_filters/iir_filter.py
View File

@ -14,9 +14,13 @@ class IIRFilter:
this generalized N-order function was made.
Using the following transfer function
H(z)=\frac{b_{0}+b_{1}z^{-1}+b_{2}z^{-2}+...+b_{k}z^{-k}}{a_{0}+a_{1}z^{-1}+a_{2}z^{-2}+...+a_{k}z^{-k}}
.. math:: H(z)=\frac{b_{0}+b_{1}z^{-1}+b_{2}z^{-2}+...+b_{k}z^{-k}}
{a_{0}+a_{1}z^{-1}+a_{2}z^{-2}+...+a_{k}z^{-k}}
we can rewrite this to
y[n]={\frac{1}{a_{0}}}\left(\left(b_{0}x[n]+b_{1}x[n-1]+b_{2}x[n-2]+...+b_{k}x[n-k]\right)-\left(a_{1}y[n-1]+a_{2}y[n-2]+...+a_{k}y[n-k]\right)\right)
.. math:: y[n]={\frac{1}{a_{0}}}
\left(\left(b_{0}x[n]+b_{1}x[n-1]+b_{2}x[n-2]+...+b_{k}x[n-k]\right)-
\left(a_{1}y[n-1]+a_{2}y[n-2]+...+a_{k}y[n-k]\right)\right)
"""
def __init__(self, order: int) -> None:
@ -34,10 +38,12 @@ class IIRFilter:
def set_coefficients(self, a_coeffs: list[float], b_coeffs: list[float]) -> None:
"""
Set the coefficients for the IIR filter. These should both be of size order + 1.
a_0 may be left out, and it will use 1.0 as default value.
Set the coefficients for the IIR filter.
These should both be of size `order` + 1.
:math:`a_0` may be left out, and it will use 1.0 as default value.
This method works well with scipy's filter design functions
>>> # Make a 2nd-order 1000Hz butterworth lowpass filter
>>> import scipy.signal
>>> b_coeffs, a_coeffs = scipy.signal.butter(2, 1000,
@ -68,7 +74,7 @@ class IIRFilter:
def process(self, sample: float) -> float:
"""
Calculate y[n]
Calculate :math:`y[n]`
>>> filt = IIRFilter(2)
>>> filt.process(0)