Merge pull request #484 from grlee77/joss_release

archive reviewed JOSS text to 1.0.x and add 1.0.3 release notes
PyWavelets · Apr 8, 2019 · 1c12f25 · 1c12f25
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diff --git a/doc/paper/paper.bib b/doc/paper/paper.bib
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+
+
+@Book{mallat2008wavelet,
+  title = {A wavelet tour of signal processing: the sparse way},
+  author = {Mallat, Stéphane},
+  year = {2008},
+  publisher = {Academic press}
+}
+
+@book{Daubechies1992,
+ author = {Daubechies, Ingrid},
+ title = {Ten Lectures on Wavelets},
+ year = {1992},
+ isbn = {0-89871-274-2},
+ publisher = {Society for Industrial and Applied Mathematics},
+ address = {Philadelphia, PA, USA},
+ doi = {10.1137/1.9781611970104},
+ url = {https://doi.org/10.1137/1.9781611970104}
+}
+
+@Article{cython,
+author = {S. Behnel and R. Bradshaw and C. Citro and L. Dalcin and D. S. Seljebotn and K. Smith},
+journal = {Computing in Science Engineering},
+title = {Cython: The Best of Both Worlds},
+year = {2011},
+volume = {13},
+number = {2},
+pages = {31-39},
+keywords = {C language;numerical analysis;Python language extension;Fortran code;numerical loops;Cython language;programming language;Sparse matrices;Runtime;Syntactics;Computer programs;Programming;Python;Cython;numerics;scientific computing},
+doi = {10.1109/MCSE.2010.118},
+ISSN = {1521-9615},
+month = {March},}
+
+@Article{scikit-image,
+ title = {scikit-image: image processing in {P}ython},
+ author = {van der Walt, {S}t\'efan and {S}ch\"onberger, {J}ohannes {L}. and
+           {Nunez-Iglesias}, {J}uan and {B}oulogne, {F}ran\c{c}ois and {W}arner,
+           {J}oshua {D}. and {Y}ager, {N}eil and {G}ouillart, {E}mmanuelle and
+           {Y}u, {T}ony and the scikit-image contributors},
+ year = {2014},
+ month = {6},
+ keywords = {Image processing, Reproducible research, Education,
+             Visualization, Open source, Python, Scientific programming},
+ volume = {2},
+ pages = {e453},
+ journal = {PeerJ},
+ issn = {2167-8359},
+ url = {http://dx.doi.org/10.7717/peerj.453},
+ doi = {10.7717/peerj.453}
+}
+
+@article{kymatio,
+  author    = {Mathieu Andreux and
+               Tom{\'{a}}s Angles and
+               Georgios Exarchakis and
+               Roberto Leonarduzzi and
+               Gaspar Rochette and
+               Louis Thiry and
+               John Zarka and
+               St{\'{e}}phane Mallat and
+               Joakim And{\'{e}}n and
+               Eugene Belilovsky and
+               Joan Bruna and
+               Vincent Lostanlen and
+               Matthew J. Hirn and
+               Edouard Oyallon and
+               Sixhin Zhang and
+               Carmine{-}Emanuele Cella and
+               Michael Eickenberg},
+  title     = {Kymatio: Scattering Transforms in Python},
+  journal   = {CoRR},
+  volume    = {abs/1812.11214},
+  year      = {2018},
+  url       = {http://arxiv.org/abs/1812.11214},
+  archivePrefix = {arXiv},
+  eprint    = {1812.11214},
+  timestamp = {Wed, 02 Jan 2019 14:40:18 +0100},
+  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1812-11214},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+
+@Misc{odl,
+  author       = {Jonas Adler and
+                  Holger Kohr and
+                  Axel Ringh and
+                  Julian Moosmann and
+                  Sebastian Banert and
+                  Matthias J. Ehrhardt and
+                  Gregory R. Lee and
+                  niinimaki and
+                  bgris and
+                  Olivier Verdier and
+                  Johan Karlsson and
+                  zickert and
+                  Willem Jan Palenstijn and
+                  \"Oktem Ozan and
+                  Chong Chen and
+                  Hector Andrade Loarca and
+                  Michael Lohmann},
+  title        = {odlgroup/odl: ODL 0.7.0},
+  month        = sep,
+  year         = 2018,
+  doi          = {10.5281/zenodo.1442734},
+  url          = {https://doi.org/10.5281/zenodo.1442734}
+}
+TODO: determine real name for bgris, zickert, niinimaki
diff --git a/doc/paper/paper.md b/doc/paper/paper.md
@@ -0,0 +1,96 @@
+---
+title: 'PyWavelets: A Python package for wavelet analysis'
+tags:
+  - Python
+  - wavelets
+  - wavelet packets
+  - discrete wavelet transform
+  - continuous wavelet transform
+  - computational harmonic analysis
+authors:
+  - name: Gregory R. Lee
+    orcid: 0000-0001-8895-2740
+    affiliation: "1, 2" # (Multiple affiliations must be quoted)
+  - name: Ralf Gommers
+    orcid: 0000-0002-0300-3333
+    affiliation: "3, 4"
+  - name: Filip Waselewski
+    orcid: 0000-0003-0729-5879
+    affiliation:
+  - name: Kai Wohlfahrt
+    orcid: 0000-0002-0970-5539
+    affiliation: 5
+  - name: Aaron O'Leary
+    orcid: 0000-0003-1984-2323
+    affiliation:
+affiliations:
+ - name: Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
+   index: 1
+ - name: Department of Radiology, University of Cincinnati School of Medicine, Cincinnati, OH, USA
+   index: 2
+ - name: Scion, 49 Sala Street, Private Bag 3020, Rotorua 3046, New Zealand
+   index: 3
+ - name: FPInnovations, 2665 East Mall, Vancouver, BC V6T 1Z4, Canada
+   index: 4
+ - name: Department of Biochemistry, University of Cambridge, Old Addenbrookes Site, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom
+   index: 5
+
+date: 24 August 2018
+bibliography: paper.bib
+---
+
+# Summary
+
+Wavelets are a popular tool for computational harmonic analysis. They provide
+localization in both the temporal (or spatial) domain as well as in the
+frequency domain [@Daubechies1992]. A prominent feature is the ability to
+perform a multiresolution analysis [@mallat2008wavelet]. The wavelet transform
+of natural signals and images tends to have most of its energy concentrated in
+a small fraction of the coefficients. This sparse representation property is
+key to the good performance of wavelets in applications such as data
+compression and denoising. For example, the wavelet transform is a key
+component of the JPEG 2000 image compression standard.
+
+``PyWavelets`` is a Python package implementing a number of n-dimensional
+discrete wavelet transforms as well as the 1D continuous wavelet transform. A
+wide variety of predefined wavelets are provided and it is possible for users
+to specify custom wavelet filter banks. All discrete wavelet transforms are
+implemented by convolution with finite impulse response filters. The required
+up/downsampling convolutions are implemented in C for good performance.
+Cython [@cython] is used to wrap the C code and implement axis-specific 1D
+transformations based on the low-level C routines. All multi-dimensional
+transforms are implemented in Python via separable application of the 1D
+transforms. The API for ``PyWavelets`` was designed to be similar to Matlab's
+wavelet toolbox and functions such as the 1D, 2D and 3D discrete wavelet
+transforms are tested for accuracy vs. their Matlab counterparts. PyWavelets
+has additional functionality not common in other wavelet toolboxes such as
+support for dimension $n > 3$ and support for both real and complex-valued
+data in either single or double precision. It is also possible to transform
+only a subset of axes and to vary the wavelet and signal boundary extension
+mode on a per-axis basis.
+
+``PyWavelets`` was designed for use by scientists working within a range of
+applications including time-series analysis, signal processing, image
+processing and medical imaging. It has already been adopted as a required
+or optional dependency by a number of other software projects. For example,
+it has enabled wavelet-based image denoising in scikit-image [@scikit-image].
+The Operator Discretization Library (ODL) [@odl] uses PyWavelets to enable
+wavelet-based regularization in iterative inverse problems such as computed
+tomography image reconstruction. Another related package which is independent
+of ``PyWavelets`` is Kymatio, which implements the wavelet scattering
+transform in 1D-3D [@kymatio]. The current implementation in Kymatio uses
+non-separable 2D and 3D wavelets defined in the frequency domain and is well
+suited to signal classification tasks, but does not have a simple inverse
+transform like the standard discrete wavelet transform.
+
+A number of common 1D demo signals used in the literature and in the manuscript
+by Stephan Mallat [-@mallat2008wavelet] are provided for use in teaching and for
+purposes of reproducible research.
+
+# Acknowledgements
+
+We would to acknowledge the various PyWavelets contributors for their
+contributions to the library, and specifically Holger Nahrstaedt for
+contributing a continuous wavelet transform.
+
+# References
diff --git a/doc/release/1.0.3-notes.rst b/doc/release/1.0.3-notes.rst
@@ -0,0 +1,8 @@
+==============================
+PyWavelets 1.0.3 Release Notes
+==============================
+
+PyWavelets 1.0.3 is functionally equivalent to the 1.0.2 release. It was made
+to add the add an archive of the JOSS paper to the 1.0.x branch and serve as a
+reference corresponding to the version of the software reviewed that was peer
+reviewed.
diff --git a/doc/source/releasenotes.rst b/doc/source/releasenotes.rst
@@ -10,3 +10,4 @@ Release Notes
    release.1.0.0
    release.1.0.1
    release.1.0.2
+   release.1.0.3