How to Install and Uninstall python2-audiolazy Package on openSUSE Leap
Last updated: November 22,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "python2-audiolazy" package
This is a short guide on how to install python2-audiolazy on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
python2-audiolazy
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2. Uninstall "python2-audiolazy" package
In this section, we are going to explain the necessary steps to uninstall python2-audiolazy on openSUSE Leap:
$
sudo zypper remove
python2-audiolazy
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3. Information about the python2-audiolazy package on openSUSE Leap
Information for package python2-audiolazy:
------------------------------------------
Repository : Main Repository
Name : python2-audiolazy
Version : 0.6-bp153.1.16
Arch : noarch
Vendor : openSUSE
Installed Size : 698,5 KiB
Installed : No
Status : not installed
Source package : python-audiolazy-0.6-bp153.1.16.src
Summary : Real-Time Expressive Digital Signal Processing (DSP) Package for Python!
Description :
AudioLazy is a package written in pure Python proposing digital audio signal
processing (DSP).
It prioritizes code expressiveness, clarity and simplicity, without precluding
the lazy evaluation, and can be used together with Numpy, Scipy and
Matplotlib as well as default Python structures like lists and generators.
It also features:
- A ``Stream`` class for finite and endless signals representation with
elementwise operators (auto-broadcast with non-iterables) in a common
Python iterable container accepting heterogeneous data;
- Strongly sample-based representation (Stream class) with easy conversion
to block representation using the ``Stream.blocks(size, hop)`` method;
- Sample-based interactive processing with ``ControlStream``;
- ``Streamix`` mixer for iterables given their starting time deltas;
- Multi-thread audio I/O integration with PyAudio;
- Linear filtering with Z-transform filters directly as equations (e.g.
``filt = 1 / (1 - .3 * z ** -1)``), including linear time variant filters
(i.e., the ``a`` in ``a * z ** k`` can be a Stream instance), cascade
filters (behaves as a list of filters), resonators, etc.. Each
``LinearFilter`` instance is compiled just in time when called;
- Zeros and poles plots and frequency response plotting integration with
MatPlotLib;
- Linear Predictive Coding (LPC) directly to ``ZFilter`` instances, from
which you can find PARCOR coeffs and LSFs;
- Both sample-based (e.g., zero-cross rate, envelope, moving average,
clipping, unwrapping) and block-based (e.g., window functions, DFT,
autocorrelation, lag matrix) analysis and processing tools;
- A simple synthesizer (Table lookup, Karplus-Strong) with processing tools
(Linear ADSR envelope, fade in/out, fixed duration line stream) and basic
wave data generation (sinusoid, white noise, impulse);
- Biological auditory periphery modeling (ERB and gammatone filter models);
- Multiple implementation organization as ``StrategyDict`` instances:
callable dictionaries that allows the same name to have several different
implementations (e.g. ``erb``, ``gammatone``, ``lowpass``, ``resonator``,
``lpc``, ``window``);
- Converters among MIDI pitch numbers, strings like "F#4" and frequencies;
- Polynomials, Stream-based functions from itertools, math, cmath, and more!
Go try yourself! =)
------------------------------------------
Repository : Main Repository
Name : python2-audiolazy
Version : 0.6-bp153.1.16
Arch : noarch
Vendor : openSUSE
Installed Size : 698,5 KiB
Installed : No
Status : not installed
Source package : python-audiolazy-0.6-bp153.1.16.src
Summary : Real-Time Expressive Digital Signal Processing (DSP) Package for Python!
Description :
AudioLazy is a package written in pure Python proposing digital audio signal
processing (DSP).
It prioritizes code expressiveness, clarity and simplicity, without precluding
the lazy evaluation, and can be used together with Numpy, Scipy and
Matplotlib as well as default Python structures like lists and generators.
It also features:
- A ``Stream`` class for finite and endless signals representation with
elementwise operators (auto-broadcast with non-iterables) in a common
Python iterable container accepting heterogeneous data;
- Strongly sample-based representation (Stream class) with easy conversion
to block representation using the ``Stream.blocks(size, hop)`` method;
- Sample-based interactive processing with ``ControlStream``;
- ``Streamix`` mixer for iterables given their starting time deltas;
- Multi-thread audio I/O integration with PyAudio;
- Linear filtering with Z-transform filters directly as equations (e.g.
``filt = 1 / (1 - .3 * z ** -1)``), including linear time variant filters
(i.e., the ``a`` in ``a * z ** k`` can be a Stream instance), cascade
filters (behaves as a list of filters), resonators, etc.. Each
``LinearFilter`` instance is compiled just in time when called;
- Zeros and poles plots and frequency response plotting integration with
MatPlotLib;
- Linear Predictive Coding (LPC) directly to ``ZFilter`` instances, from
which you can find PARCOR coeffs and LSFs;
- Both sample-based (e.g., zero-cross rate, envelope, moving average,
clipping, unwrapping) and block-based (e.g., window functions, DFT,
autocorrelation, lag matrix) analysis and processing tools;
- A simple synthesizer (Table lookup, Karplus-Strong) with processing tools
(Linear ADSR envelope, fade in/out, fixed duration line stream) and basic
wave data generation (sinusoid, white noise, impulse);
- Biological auditory periphery modeling (ERB and gammatone filter models);
- Multiple implementation organization as ``StrategyDict`` instances:
callable dictionaries that allows the same name to have several different
implementations (e.g. ``erb``, ``gammatone``, ``lowpass``, ``resonator``,
``lpc``, ``window``);
- Converters among MIDI pitch numbers, strings like "F#4" and frequencies;
- Polynomials, Stream-based functions from itertools, math, cmath, and more!
Go try yourself! =)