Change to using distutils.

Currently only builds the simplsndobj module

1 files changed, 0 insertions, 105 deletions

diff --git a/readme.txt b/readme.txt
deleted file mode 100644
index 8bce63b..0000000
--- a/readme.txt
+++ /dev/null
@@ -1,105 +0,0 @@
-Sinusoidal Modelling - A Python Library (SiMPL)
-Version 0.2 (first released in December 2010)
-
-Copyright (c) 2009 John Glover, National University of Ireland, Maynooth
-http://simplsound.sourceforge.net
-john.c.glover@nuim.ie
-
------------------------------------------------------------------------------------------
- 
-This program 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; either version 2 of the License, or
-(at your option) any later version.
-
-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
-along with this program; if not, write to the Free Software
-Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
-
------------------------------------------------------------------------------------------
-
-Introduction
-------------
-
-Simpl is an open source library for sinusoidal modelling written in C/C++ and Python,
-and making use of Scientific Python (SciPy). The aim of this
-project is to tie together many of the existing sinusoidal modelling implementations
-into a single unified system with a consistent API, as well as providing implementations
-of some recently published sinusoidal modelling algorithms, many of which have yet
-to be released in software. Simpl is primarily intended as a tool for other researchers
-in the field, allowing them to easily combine, compare and contrast many of the published
-analysis/synthesis algorithms.
-
-
-Dependencies
-------------
-
-- C/C++ compiler
-- Python (>= 2.6.*)
-- SCons (>= 1.2.0)
-- NumPy
-- SciPy
-- Developers who wish to run the unit tests also need the original open source libraries:
-    - sndobj: http://sndobj.sourceforge.net/
-    - libsms: http://mtg.upf.edu/static/libsms/
-
-
-Installation
-------------
-
-To compile, in the root directory, run:
-> scons
-
-To install, run:
-> sudo scons install
-
-For a full list of options:
-> scons --help
-
-
-Usage
------
-
-See the scripts in the examples folder.
-
-
-Credits
--------
-
-The SndObj library is by Dr. Victor Lazzarini (National University of Ireland, Maynooth) and others. 
-See the main project page at http://sndobj.sourceforge.net/ for more information.
-
-Libsms is an implementation of SMS by Rich Eakin, based on code by Dr. Xavier Serra (MTG,
-Universitat Pompeu Fabra, Barcelona, Spain)
-See the main project page at http://mtg.upf.edu/static/libsms for more information.
-
-The MQ algorithm is based on the following paper:
-R. McAulay, T. Quatieri, "Speech Analysis/Synthesis Based on a Sinusoidal Representation", 
-IEEE Transaction on Acoustics, Speech and Signal Processing, vol. 34, no. 4, pp. 744-754, 1986.
-
-
-To Do
------
-
-general:
-- include new RT Audio code
-- tidy up code for HMM/LP partial tracking and Loris integration
-- include binaries for Mac OS X and Windows so compilation from source is not needed
-- performance issues: MQ, LP and HMM algorithms need to be coded in C/C++ really,
-  Python is just too slow, particularly for real-time use. The pure Python implementations
-  are useful for testing though.
-
-sndobj:
-- create exception objects
-- add a set_synthesis_type property to SndObjSynthesis
-- create properties for threshold and num_bins in SndObjPartialTracking class
-- make sndobjs use self.sampling_rate
-- make peak detection use the new window_size property
-
-sms:
-- move sms_scaleDet to the harmonic analysis phase