Merge pull request #138 from grlee77/rel040_docs

WIP: Documentation updates for v0.4.0

CHANGES.txt

@@ -2,7 +2,7 @@ Changelog
 
 0.4.0
     changes:
-      - idwt no longer takes a 'correct_length' parameter.
+      - idwt no longer takes a 'correct_size' parameter.
         - Sizes of the arrays passed to all idwt functions must match exactly.
         - use 'multilevel.wavecrec' for multilevel transforms
 

doc/release/0.4.0-notes.rst

@@ -2,18 +2,62 @@
 PyWavelets 0.4.0 Release Notes
 ==============================
 
-.. note:: PyWavelets 0.4.0 is not released yet!
-
 .. contents::
 
-
+PyWavelets 0.4.0 is the culmination of 6 months of work.  In addition to
+several new features, some changes and deprecations have been made to streamline
+the API.
 
 This release requires Python 2.6, 2.7 or 3.3-3.5 and NumPy 1.6.2 or greater.
 
+Highlights of this release include:
+
+- 1D and 2D stationary wavelet transforms
+- Substantially faster 2D and nD discrete wavelet transforms
+- Complex number support
+- nD versions of the multilevel DWT and IDWT
+
 
 New features
 ============
 
+1D and 2D stationary wavelet transforms
+---------------------------------------
+1D (``iswt``) and 2D (``iswt2``) stationary wavelet transforms were added.
+These currently only support even length inputs
+
+
+Faster 2D and nD wavelet transforms
+-----------------------------------
+The multidimensional DWT and IDWT code was refactored and is now an order of
+magnitude faster than in previous releases.  The following functions benefit:
+``dwt2``, ``idwt2``, ``dwtn``, ``idwtn``.
+
+
+Complex floating point support
+------------------------------
+64 and 128-bit complex data types are now supported by all wavelet transforms.
+
+
+nD implementation of the multilevel DWT and IDWT
+------------------------------------------------
+The existing 1D and 2D multilevel transforms were supplemented with an nD
+implementation.
+
+
+Wavelet transforms can be applied along a specific axis/axes
+------------------------------------------------------------
+All wavelet transform functions now support explicit specification of the axis
+or axes upon which to perform the transform.
+
+
+Example Datasets
+----------------
+Two additional 2D grayscale images were added (`camera`, `ascent`).  The
+previously existing 1D ECG data (`ecg`) and the 2D aerial image (`aero`)
+used in the demos can also now be imported via functions defined in
+`pywt.data` (e.g. ``camera = pywt.data.camera()``)
+
 
 Deprecated features
 ===================
@@ -42,19 +86,42 @@ The ``MODES`` object and its attributes are deprecated.  The new name is
 Backwards incompatible changes
 ==============================
 
-``idwt`` no longer takes a ``correct_length`` parameter. As a consequence,
+``idwt`` no longer takes a ``correct_size`` parameter. As a consequence,
 ``idwt2`` inputs must match exactly in length. For multilevel transforms, where
 arrays differing in size by one element may be produced, use the ``waverec``
 functions from the ``multilevel`` module instead.
 
+Bugs Fixed
+==========
+
+float32 inputs were not always respected. All transforms now return float32
+outputs when called using float32 inputs.
+
+Incorrect detail coefficients were returned by `downcoef` when `level > 1`.
 
 Other changes
 =============
 
+Much of the API documentation is now autogenerated from the corresponding
+function docstrings.  The numpydoc sphinx extension is now needed to build the
+documentation.
 
 Authors
 =======
 
+* Thomas Arildsen +
+* François Boulogne
+* Ralf Gommers
+* Gregory R. Lee
+* Michael Marino +
+* Aaron O'Leary +
+* Daniele Tricoli +
+* Kai Wohlfahrt
+
+A total of 8 people contributed to this release.
+People with a "+" by their names contributed a patch for the first time.
+This list of names is automatically generated, and may not be fully complete.
+
 
 Issues closed for v0.4.0
 ------------------------

doc/source/dev/installing_build_dependencies.rst

@@ -61,7 +61,7 @@ via::
 
 
 .. _virtualenv: http://pypi.python.org/pypi/virtualenv
-.. _numpy: http://numpy.scipy.org/
+.. _numpy: http://numpy.org/
 .. _Cython: http://cython.org/
 .. _Sphinx: http://sphinx.pocoo.org
 .. _numpydoc: https://github.com/numpy/numpydoc

doc/source/dev/preparing_windows_build_environment.rst

@@ -116,7 +116,7 @@ After completing these steps continue with
 
 
 .. _Python: http://python.org/
-.. _numpy: http://numpy.scipy.org/
+.. _numpy: http://numpy.org/
 .. _Cython: http://cython.org/
 .. _Sphinx: http://sphinx.pocoo.org/
 .. _MinGW C compiler: http://sourceforge.net/projects/mingwbuilds/

doc/source/index.rst

@@ -1,32 +1,34 @@
 PyWavelets - Discrete Wavelet Transform in Python
 =================================================
 
-PyWavelets is a free Open Source wavelet transform software for Python_
-programming language. It is written in Python, Cython and C for a mix of easy
-and powerful high-level interface and the best performance.
+PyWavelets is free and Open Source wavelet transform software for the Python_
+programming language. It combines a simple high level interface with low level
+C and Cython performance.
 
-PyWavelets is very easy to start with and use. Just install the package, open
-the Python interactive shell and type:
+PyWavelets is very easy to use and get started with. Just install the package,
+open the Python interactive shell and type:
 
   .. sourcecode:: python
 
     >>> import pywt
     >>> cA, cD = pywt.dwt([1, 2, 3, 4], 'db1')
 
-Voilà! Computing wavelet transforms never before has been so simple :)
+Voilà! Computing wavelet transforms has never been so simple :)
 
 Main features
 -------------
 
 The main features of PyWavelets are:
 
   * 1D, 2D and nD Forward and Inverse Discrete Wavelet Transform (DWT and IDWT)
+  * 1D, 2D and nD Multilevel DWT and IDWT
   * 1D and 2D Stationary Wavelet Transform (Undecimated Wavelet Transform)
   * 1D and 2D Wavelet Packet decomposition and reconstruction
   * Approximating wavelet and scaling functions
   * Over seventy `built-in wavelet filters`_
     and custom wavelets supported
   * Single and double precision calculations
+  * Real and complex calculations
   * Results compatible with Matlab Wavelet Toolbox (TM)
 
 Requirements
@@ -61,8 +63,8 @@ Prebuilt Windows binaries and source code packages are also
 available from `Python Package Index`_.
 
 Binary packages for several Linux distributors are maintained by Open Source
-community contributors. Query your Linux package manager tool
-for `python-pywavelets`, `python-wavelets`, `python-pywt` or similar package name.
+community contributors. Query your Linux package manager tool for
+`python-pywavelets`, `python-wavelets`, `python-pywt` or similar package name.
 
 .. seealso::  :ref:`Development notes <dev-index>` section contains more
               information on building and installing from source code.
@@ -78,7 +80,7 @@ For more usage examples see the `demo`_ directory in the source package.
 State of development & Contributing
 -----------------------------------
 
-PyWavelets started in 2006 as an academic project for a master thesis
+PyWavelets started in 2006 as an academic project for a masters thesis
 on `Analysis and Classification of Medical Signals using Wavelet Transforms`
 and was maintained until 2012 by its `original developer`_.  In 2013
 maintenance was taken over in a `new repo <https://github.com/PyWavelets/pywt>`_)

doc/source/ref/other-functions.rst

@@ -43,3 +43,26 @@ Orthogonal Filter Banks
 -----------------------
 
 .. autofunction:: orthogonal_filter_bank
+
+
+Example Datasets
+----------------
+
+The following example datasets are available in the module `pywt.data`:
+
+  ========  =============================
+  **name**         **description**
+  ========  =============================
+    ecg      ECG waveform (1024 samples)
+    aero     grayscale image (512x512)
+   ascent    grayscale image (512x512)
+   camera    grayscale image (512x512)
+  ========  =============================
+
+Each can be loaded via a function of the same name.
+
+**Example:**
+.. sourcecode:: python
+
+    >>> import pywt
+    >>> camera = pywt.data.camera()