How to Install and Uninstall libiir1 Package on openSuSE Tumbleweed
Last updated: November 23,2024
1. Install "libiir1" package
This guide let you learn how to install libiir1 on openSuSE Tumbleweed
$
sudo zypper refresh
Copied
$
sudo zypper install
libiir1
Copied
2. Uninstall "libiir1" package
Please follow the guidance below to uninstall libiir1 on openSuSE Tumbleweed:
$
sudo zypper remove
libiir1
Copied
3. Information about the libiir1 package on openSuSE Tumbleweed
Information for package libiir1:
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libiir1
Version : 1.9.4-1.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 56.8 KiB
Installed : No
Status : not installed
Source package : iir-1.9.4-1.4.src
Upstream URL : https://github.com/berndporr/iir1
Summary : DSP infinite impulse response realtime C++ filter library
Description :
An infinite impulse response (IIR) filter library for Linux, Mac OSX and Windows
which implements Butterworth, RBJ, Chebychev filters and can easily import coefficients generated by Python (scipy).
The filter processes the data sample by sample for realtime processing.
It uses templates to allocate the required memory so that it can run without any malloc / new commands.
Memory is allocated at compile time so that there is never the risk of memory leaks.
All realtime filter code is in the header files which guarantees efficient integration into the main program
and the compiler can optimise both filter code and main program at the same time.
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : libiir1
Version : 1.9.4-1.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 56.8 KiB
Installed : No
Status : not installed
Source package : iir-1.9.4-1.4.src
Upstream URL : https://github.com/berndporr/iir1
Summary : DSP infinite impulse response realtime C++ filter library
Description :
An infinite impulse response (IIR) filter library for Linux, Mac OSX and Windows
which implements Butterworth, RBJ, Chebychev filters and can easily import coefficients generated by Python (scipy).
The filter processes the data sample by sample for realtime processing.
It uses templates to allocate the required memory so that it can run without any malloc / new commands.
Memory is allocated at compile time so that there is never the risk of memory leaks.
All realtime filter code is in the header files which guarantees efficient integration into the main program
and the compiler can optimise both filter code and main program at the same time.