How to Install and Uninstall libiir-devel Package on openSUSE Leap
Last updated: November 07,2024
1. Install "libiir-devel" package
Please follow the guidance below to install libiir-devel on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
libiir-devel
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2. Uninstall "libiir-devel" package
Learn how to uninstall libiir-devel on openSUSE Leap:
$
sudo zypper remove
libiir-devel
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3. Information about the libiir-devel package on openSUSE Leap
Information for package libiir-devel:
-------------------------------------
Repository : Main Repository
Name : libiir-devel
Version : 1.9.4-bp155.1.6
Arch : x86_64
Vendor : openSUSE
Installed Size : 115.7 KiB
Installed : No
Status : not installed
Source package : iir-1.9.4-bp155.1.6.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 : Main Repository
Name : libiir-devel
Version : 1.9.4-bp155.1.6
Arch : x86_64
Vendor : openSUSE
Installed Size : 115.7 KiB
Installed : No
Status : not installed
Source package : iir-1.9.4-bp155.1.6.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.