New release: 0.2.5. Cleaning, cleaning...

MANIFEST.in

@@ -1,7 +1,9 @@
-include .travis.yml
+include *.md
+include *.py
+include setup.cfg
 include MANIFEST.in
-include README.rst
+include README.md
+include LICENCE.txt
 include requirements.txt
-include PyEMD
-
-include PyEMD/tests/*.py
+recursive-include PyEMD *.py
+recursive-include example *.py

README.md

@@ -0,0 +1,150 @@
+[![codecov](https://codecov.io/gh/laszukdawid/PyEMD/branch/master/graph/badge.svg)](https://codecov.io/gh/laszukdawid/PyEMD)
+[![BuildStatus](https://travis-ci.org/laszukdawid/PyEMD.png?branch=master)](https://travis-ci.org/laszukdawid/PyEMD)
+[![DocStatus](https://readthedocs.org/projects/pyemd/badge/?version=latest)](https://pyemd.readthedocs.io/)
+![Codacy](https://api.codacy.com/project/badge/Grade/5385d5ddc8e84908bd4e38f325443a21%0A%20:alt:%20Codacy%20Badge%0A%20:target:%20https://www.codacy.com/app/laszukdawid/PyEMD?utm_source=github.com&utm_medium=referral&utm_content=laszukdawid/PyEMD&utm_campaign=badger)
+
+# PyEMD
+
+## Links
+
+-   HTML documentation: <https://pyemd.readthedocs.org>
+-   Issue tracker: <https://github.com/laszukdawid/pyemd/issues>
+-   Source code repository: <https://github.com/laszukdawid/pyemd>
+
+## Introduction
+
+This is yet another Python implementation of Empirical Mode
+Decomposition (EMD). The package contains many EMD variations and
+intends to deliver more in time.
+
+### EMD variations:
+* Ensemble EMD (EEMD),
+* Image decomposition (EMD2D),
+* "Complete Ensemble EMD" (CEEMDAN)
+* different settings and configurations of vanilla EMD.
+
+*PyEMD* allows to use different splines for envelopes, stopping criteria
+and extrema interpolation.
+
+### Available splines:
+* Natural cubic [default]
+* Pointwise cubic
+* Akima
+* Linear
+
+### Available stopping criteria:
+* Cauchy convergence [default]
+* Fixed number of iterations
+* Number of consecutive proto-imfs
+
+### Extrema detection:
+* Discrete extrema [default]
+* Parabolic interpolation
+
+## Installation
+
+### Recommended
+
+Simply download this directory either directly from GitHub, or using
+command line:
+
+> \$ git clone <https://github.com/laszukdawid/PyEMD>
+
+Then go into the downloaded project and run from command line:
+
+> \$ python setup.py install
+
+### PyPi
+
+Packaged obtained from PyPi is/will be slightly behind this project, so
+some features might not be the same. However, it seems to be the
+easiest/nicest way of installing any Python packages, so why not this
+one?
+
+> \$ pip install EMD-signal
+
+## Example
+
+More detailed examples are included in the
+[documentation](https://pyemd.readthedocs.io/en/latest/examples.html) or
+in the
+[PyEMD/examples](https://github.com/laszukdawid/PyEMD/tree/master/example).
+
+### EMD
+
+In most cases default settings are enough. Simply import `EMD` and pass
+your signal to instance or to `emd()` method.
+
+```python
+from PyEMD import EMD
+import numpy as np
+
+s = np.random.random(100)
+emd = EMD()
+IMFs = emd(s)
+```
+
+The Figure below was produced with input:
+$S(t) = cos(22 \pi t^2) + 6t^2$
+
+![simpleExample](https://github.com/laszukdawid/PyEMD/raw/master/example/simple_example.png?raw=true)
+
+### EEMD
+
+Simplest case of using Ensemble EMD (EEMD) is by importing `EEMD` and
+passing your signal to the instance or `eemd()` method.
+
+```python
+from PyEMD import EEMD
+import numpy as np
+
+s = np.random.random(100)
+eemd = EEMD()
+eIMFs = eemd(s)
+```
+
+### CEEMDAN
+
+As with previous methods, there is also simple way to use `CEEMDAN`.
+
+```python
+from PyEMD import CEEMDAN
+import numpy as np
+
+s = np.random.random(100)
+ceemdan = CEEMDAN()
+cIMFs = ceemdan(s)
+```
+
+### EMD2D
+
+Simplest case is to pass image as monochromatic numpy 2D array. As with
+other modules one can use default setting of instance or more explicitly
+use `emd2d()` method.
+
+```python
+from PyEMD import EMD2D
+import numpy as np
+
+x, y = np.arange(128), np.arange(128).reshape((-1,1))
+img = np.sin(0.1*x)*np.cos(0.2*y)
+emd2d = EMD2D()
+IMFs_2D = emd2d(img)
+```
+
+## Contact
+
+Feel free to contact me with any questions, requests or simply saying
+*hi*. It's always nice to know that I might have contributed to saving
+someone's time or that I might improve my skills/projects.
+
+Contact me either through gmail (laszukdawid @ gmail) or search me
+favourite web search.
+
+### Citation
+
+If you found this package useful and would like to cite it in your work
+please use following structure:
+
+Dawid Laszuk (2017-), **Python implementation of Empirical Mode
+Decomposition algorithm**. <http://www.laszukdawid.com/codes>.

doc/conf.py

@@ -72,9 +72,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = u'0.2.03'
+version = u'0.2.5'
 # The full version, including alpha/beta/rc tags.
-release = u'0.2.03'
+release = u'0.2.5'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

requirements-extra.txt

@@ -0,0 +1,6 @@
+numpy>=1.12
+numpydoc
+scipy>=0.19
+matplotlib
+pathos>=0.2.1
+scikit-image>=0.13

requirements.txt

@@ -1,6 +1,4 @@
-numpy
-numpydoc
+numpy>=1.12
 scipy>=0.19
-matplotlib
-pathos
+pathos>=0.2.1
 scikit-image>=0.13