..
  This file is part of AudioLazy, the signal processing Python package.
  Copyright (C) 2012-2016 Danilo de Jesus da Silva Bellini

  AudioLazy is free software: you can redistribute it and/or modify
  it under the terms of the GNU General Public License as published by
  the Free Software Foundation, version 3 of the License.

  This program is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  GNU General Public License for more details.

  You should have received a copy of the GNU General Public License
  File auto-generated by the rst_creator.py script.
  along with this program. If not, see <http://www.gnu.org/licenses/>.


Installing
==========
The package works both on Linux and on Windows. You can find the last stable
version at `PyPI <http://pypi.python.org/pypi/audiolazy>`_ and install it with
the usual Python installing mechanism::

  python setup.py install

If you have pip, you can go directly (use ``-U`` for update or reinstall)::

  pip install audiolazy

for downloading (from PyPI) and installing the package for you, or::

  pip install -U .

To install from a path that has the ``setup.py`` file and the package data
uncompressed previously.

For the *bleeding-edge* version, you can install directly from the github
repository (requires ``git`` for cloning)::

  pip install -U git+git://github.com/danilobellini/audiolazy.git

For older versions, you can install from the PyPI link or directly from the
github repository, based on the repository tags. For example, to install the
version 0.04 (requires ``git`` for cloning)::

  pip install -U git+git://github.com/danilobellini/audiolazy.git@v0.04

The package doesn't have any strong dependency for its core besides the Python
itself (versions 2.7, 3.2 or newer) as well as its standard library, but you
might need:

- PyAudio: needed for playing and recording audio (``AudioIO`` class);
- NumPy: needed for doing some maths, such as finding the LSFs from a filter
  or roots from a polynomial;
- MatPlotLib: needed for all default plotting, like in ``LinearFilter.plot``
  method and several examples;
- SciPy (testing and examples only): used as an oracle for LTI filter testing
  and for the Butterworth filter example;
- Sympy (testing only): used for testing linear filters with time-varying
  matrices of symbolic coeffs where the Stream samples are these matrices;
- tox for testing all at once, or pytest, pytest-cov and pytest-timeout for
  testing in a single environment (testing only): runs test suite and
  shows code coverage status;
- wxPython (example only): used by one example with FM synthesis in an
  interactive GUI;
- Tkinter (example only): needed for the pitch follower based on the
  zero-crossing rate example GUI;
- Music21 (example only): there's one example that gets the Bach chorals from
  that package corpora for synthesizing and playing;
- Sphinx (documentation only): it can create the software documentation in
  several different file formats.

Beside examples and tests, only the filter plotting with ``plot`` and
``zplot`` methods needs MatPlotLib. Also, the routines that needs NumPy up to
now are:

- Root finding with ``zeros`` and ``poles`` properties (filter classes) or
  with ``roots`` property (Poly class);
- Some Linear Predictive Coding (``lpc``) strategies: ``nautocor``,
  ``autocor`` and ``covar``;
- Line Spectral Frequencies ``lsf`` and ``lsf_stable`` functions.