Merge pull request #6 from Athanaseus/Prepare-release

Prepare release

README.rst

@@ -0,0 +1,61 @@
+=======
+aimfast
+=======
+|Doc Status|
+|Pypi Version|
+|Python Versions|
+
+aimfast is an Astronomical Image Fidelity Assessment Tool
+
+Main website: https://aimfast.readthedocs.io
+
+==============
+Introduction
+==============
+
+Image fidelity is a measure of the accuracy of the reconstructed sky brightness distribution. A related metric, dynamic range, is a measure of the degree to which imaging artifacts around strong sources are suppressed, which in turn implies a higher fidelity of the on-source reconstruction. Moreover, the choice of image reconstruction algorithm also affects the correctness of the on-source brightness distribution. For high dynamic ranges with wide bandwidths, algorithms that model the sky spectrum as well as the average intensity can yield more accurate reconstructions.
+
+==============
+Installation
+==============
+Installation from source_,
+working directory where source is checked out
+
+.. code-block:: bash
+  
+    $ pip install .
+
+This package is available on *PYPI*, allowing
+
+.. code-block:: bash
+  
+    $ pip install aimfast
+
+=======
+License
+=======
+
+This project is licensed under the GNU General Public License v3.0 - see license_ for details.
+
+=============
+Contribute
+=============
+
+Contributions are always welcome! Please ensure that you adhere to our coding
+standards pep8_.
+
+.. |Doc Status| image:: https://readthedocs.org/projects/aimfast/badge/?version=latest
+                :target: http://aimfast.readthedocs.io/en/latest
+                :alt:
+
+.. |Pypi Version| image:: https://img.shields.io/pypi/v/aimfast.svg
+                  :target: https://pypi.python.org/pypi/aimfast
+                  :alt:
+
+.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/aimfast.svg
+                     :target: https://pypi.python.org/pypi/aimfast/
+                     :alt:
+
+.. _source: https://github.com/Athanaseus/aimfast
+.. _license: https://github.com/Athanaseus/aimfast/blob/master/LICENSE
+.. _pep8: https://www.python.org/dev/peps/pep-0008

aimfast/aimfast.py

@@ -190,7 +190,7 @@ def main():
         R = '\033[31m'  # red
         W = '\033[0m'   # white (normal)
         print("%sPlease provide fits file name(s)."
-              "\nOr\nimage_fidelity -h for arguments%s" % (R, W))
+              "\nOr\naimfast -h for arguments%s" % (R, W))
     else:
         json_dump(output_dict)
-        print output_dict
+        print(output_dict)

doc/intro.rst

@@ -53,7 +53,7 @@ and
 
 .. math::
 
-    VARIANCE = \sum_{i=1}^{n}(x_{i} - \overline{x})^2
+    VARIANCE = \frac{1}{n}\sum_{i=1}^{n}(x_{i} - \overline{x})^2
 
 whereby
 
@@ -77,7 +77,7 @@ The coefficient of skewness, the 3-rd moment, is obtained by
 
     SKEWNESS = \frac{m_3}{{m_2}^{\frac{3}{2}}}
 
-If there is a long tail in the positive directin, skewness will be positive,
+If there is a long tail in the positive direction, skewness will be positive,
 while if there is a long tail in the negative direction, skewness will be negative.
 
    .. figure:: https://user-images.githubusercontent.com/16665629/35336554-7ce4953e-0121-11e8-8a14-ce1fbf3eece4.jpg
@@ -114,25 +114,36 @@ Installation from source_, working directory where source is checked out
 
     $ pip install .
 
+This package is available on *PYPI*, allowing
+
+.. code-block:: bash
+  
+    $ pip install aimfast
+
 Command line usage
 ------------------
 
 Get the four (4) statistical moments of the residual image
 
 .. code-block:: bash
 
-    $ image_fidelity --residual-image cube.residual.fits
+    $ aimfast --residual-image cube.residual.fits
 
-Get the dynamic range of the restored image
+Get the dynamic range of the restored image, where argument -af is the multiplying factor of the peak source area  
 
 .. code-block:: bash
     
-    $ image_fidelity --restored-image cube.image.fits -af 5
+    $ aimfast --restored-image cube.image.fits -af 5
 
 Get combination of the four (4) moments and dynamic range
 
 .. code-block:: bash
 
-    $ image_fidelity --residual-image cube.residual.fits --restored-image cube.image.fits -af 5
+    $ aimfast --residual-image cube.residual.fits --restored-image cube.image.fits -af 5
 
 NB: Outputs will be printed on the terminal and dumped into `fidelity_results.json` file.
+
+.. code-block:: bash
+
+    $ cat fidelity_results.json
+    $ {"cube.residual.fits": {"SKEW": 0.124, "KURT": 3.825, "STDDev": 5.5e-05, "MEAN": 4.747e-07}, "cube.image.fits": {"DR": 53.868}}