added references

.gitignore

@@ -1,14 +1,16 @@
 # Python3 dev files
-__pycache__
+_build/
+*_build*
+build/
 .cache
+*coverage*
+dist
 *.egg-info
-*_build*
+generated/
+.ipynb_checkpoints
+__pycache__
+.pytest_cache
+setup.cfg
 *_static*
-*_templates*
 *.swp
-*coverage*
-setup.cfg
-.pytest_cache
-.ipynb_checkpoints
-_build/
-generated/
+*_templates*

.readthedocs.yml

@@ -19,6 +19,9 @@ formats: all
 
 # Optionally set the version of Python and requirements required to build your docs
 python:
-  version: 3.7
-  install:
-    - requirements: docs/requirements.txt
+   version: 3.7
+   install:
+      - requirements: docs/requirements.txt
+      - method: setuptools
+        path: PerMaViss
+   system_packages: true

CITATION.rst

@@ -0,0 +1,15 @@
+Please use the following to cite the latest version of PerMaViss::
+
+    @misc{permaviss,
+        author          = \'Alvaro Torras Casas,
+        title           = {PerMaViss:<RELEASE TITLE>},
+        year            = 2020,
+        doi             = {<DOI INFORMATION>},
+        url             = {http://doi.org/10.5281/zenodo.<DOI NUMBER>}
+    }
+
+To check the details (RELEASE TITLE, DOI INFORMATION and DOI NUMBER) please view 
+the Zenodo page for the project.
+
+.. image:: https://zenodo.org/badge/222728935.svg
+   :target: https://zenodo.org/badge/latestdoi/222728935    

INSTALLATION.rst

@@ -2,12 +2,17 @@
 Installation
 ============
 
-Permaviss is built on Python 3, and relies only on `NumPy <http://www.numpy.org/>`_, `Math <https://docs.python.org/2/library/math.html>`_ and `Scipy <https://www.scipy.org/>`_. 
-Additionally, Matplotlib and mpl_toolkits are used for the tutorials. 
+Permaviss is built on Python 3, and relies only on `NumPy <http://www.numpy.org/>`_  and `Scipy <https://www.scipy.org/>`_. 
 
-To install, clone from GitHub repository and install::
+Additionally, `Matplotlib <https://matplotlib.org/>`_ and `mpl_toolkits <https://matplotlib.org/mpl_toolkits/>`_ are used for the tutorials.
+
+
+To install using :code:`pip3`::
+
+    $ pip3 install permaviss
+
+If you prefer to install from source, clone from GitHub repository::
 
     $ git clone https://github.com/atorras1618/PerMaViss
     $ cd PerMaViss
     $ pip3 install -e .
-

README.rst

@@ -2,6 +2,10 @@
 .. image:: https://github.com/atorras1618/permaviss/workflows/test/badge.svg
    :target: https://github.com/atorras1618/PerMaViss/actions?query=workflow%3Atest+branch%3Amaster
 
+.. image:: https://readthedocs.org/projects/permaviss/badge/?version=latest
+   :target: https://permaviss.readthedocs.io/en/latest/?badge=latest
+   :alt: Documentation Status
+
 .. image:: https://zenodo.org/badge/222728935.svg
    :target: https://zenodo.org/badge/latestdoi/222728935
 
@@ -39,10 +43,15 @@ Optional for examples and notebooks:
 Installation
 ============
 
-Permaviss is built on Python 3, and relies only on `NumPy <http://www.numpy.org/>`_, `Math <https://docs.python.org/2/library/math.html>`_ and `Scipy <https://www.scipy.org/>`_. 
-Additionally, Matplotlib and mpl_toolkits are used for the tutorials. 
+Permaviss is built on Python 3, and relies only on `NumPy <http://www.numpy.org/>`_  and `Scipy <https://www.scipy.org/>`_. 
+
+Additionally, `Matplotlib <https://matplotlib.org/>`_ and `mpl_toolkits <https://matplotlib.org/mpl_toolkits/>`_ are used for the tutorials. 
+
+To install using :code:`pip3`::
+
+    $ pip3 install permaviss
 
-To install, clone from GitHub repository and install::
+If you prefer to install from source, clone from GitHub repository::
 
     $ git clone https://github.com/atorras1618/PerMaViss
     $ cd PerMaViss
@@ -135,7 +144,7 @@ SOFTWARE.**
 How to cite
 ===========
 
-Álvaro Torras Casas (20th of January 2020). PerMaViss: Persistence Mayer Vietoris spectral sequence (Version 0.0.1)
+Álvaro Torras Casas (20th of January 2020). PerMaViss: Persistence Mayer Vietoris spectral sequence (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.3613423 
 
 Reference
 =========

docs/about/index.rst

@@ -72,7 +72,7 @@ Notice that in this case, there was no need to solve the extension problem. See
 How to cite
 ===========
 
-Álvaro Torras Casas (20th of January 2020). PerMaViss: Persistence Mayer Vietoris spectral sequence (Version 0.0.1)
+Álvaro Torras Casas (20th of January 2020). PerMaViss: Persistence Mayer Vietoris spectral sequence (Version 0.0.1). Zenodo. http://doi.org/10.5281/zenodo.3613423
 
 
 Reference

docs/examples/index.rst

@@ -251,17 +251,19 @@ Here we look at the extension information on one dimensional persistence classes
     >>>         for k in range(diag + 1):
     >>>             if k == diag and current_rad == b[0]:
     >>>                 break
-    >>>             for i, rad in enumerate(MV_ss.Hom[
-    >>>                     MV_ss.no_pages - 1][diag - k][k].barcode[:,0]):
-    >>>                 if np.allclose(rad, current_rad):
-    >>>                     next_rad = MV_ss.Hom[
-    >>>                         MV_ss.no_pages - 1][diag - k][k].barcode[i,1]
-    >>>                     ax.fill([current_rad, next_rad, next_rad, current_rad],
-    >>>                             [y_coord,y_coord,y_coord+step,y_coord+step],
-    >>>                             c=colors[k + no_diag - diag - 1])
-    >>>                     current_rad = next_rad
-    >>>                 # end if
-    >>>             # end for
+    >>>             if len(MV_ss.Hom[MV_ss.no_pages - 1][diag - k][k]) != 0:
+    >>>                 for i, rad in enumerate(MV_ss.Hom[
+    >>>                         MV_ss.no_pages - 1][diag - k][k].barcode[:,0]):
+    >>>                     if np.allclose(rad, current_rad):
+    >>>                         next_rad = MV_ss.Hom[
+    >>>                             MV_ss.no_pages - 1][diag - k][k].barcode[i,1]
+    >>>                         ax.fill([current_rad, next_rad, next_rad, current_rad],
+    >>>                                 [y_coord,y_coord,y_coord+step,y_coord+step],
+    >>>                                 c=colors[k + no_diag - diag - 1])
+    >>>                         current_rad = next_rad
+    >>>                     # end if
+    >>>                 # end for
+    >>>             # end if
     >>> 
     >>>         # end for
     >>>         if current_rad < b[1]:

docs/index.rst

@@ -3,10 +3,10 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to PerMaViss 0.0.1 documentation!
-=========================================
+Welcome to PerMaViss documentation!
+===================================
 
-Welcome to PerMaViss 0.0.1! This is a Python3 implementation of the Persistence Mayer Vietoris spectral sequence. 
+Welcome to PerMaViss! This is a Python3 implementation of the Persistence Mayer Vietoris spectral sequence. 
 For a mathematical description of the procedure, see `Distributing Persistent Homology via Spectral Sequences <https://arxiv.org/abs/1907.05228>`_.
 
 In a nutshell, this library is intended to be a `proof of concept` for persistence homology parallelization. That is, one can divide a point cloud into covering regions, compute persistent homology on each part, and combine all results to obtain the global persistent homology again. This is done by means of the Persistence Mayer Vietoris spectral sequence. Here we present two examples, the torus and random point clouds in three dimensions. Both of these are divided into `8` mutually overlapping regions, and the spectral sequence is computed with respect to this cover. The resulting barcodes coincide with that which would be obtained by computing persistent homology directly.

examples/Random 3D cube.ipynb

@@ -301,17 +301,19 @@
     "        for k in range(diag + 1):\n",
     "            if k == diag and current_rad == b[0]:\n",
     "                break\n",
-    "            for i, rad in enumerate(MV_ss.Hom[\n",
-    "                    MV_ss.no_pages - 1][diag - k][k].barcode[:,0]):\n",
-    "                if np.allclose(rad, current_rad):\n",
-    "                    next_rad = MV_ss.Hom[\n",
-    "                        MV_ss.no_pages - 1][diag - k][k].barcode[i,1]\n",
-    "                    ax.fill([current_rad, next_rad, next_rad, current_rad],\n",
-    "                            [y_coord,y_coord,y_coord+step,y_coord+step],\n",
-    "                            c=colors[k + no_diag - diag - 1])\n",
-    "                    current_rad = next_rad\n",
-    "                # end if\n",
-    "            # end for\n",
+    "            if len(MV_ss.Hom[MV_ss.no_pages - 1][diag - k][k]) != 0:\n",
+    "                for i, rad in enumerate(MV_ss.Hom[\n",
+    "                        MV_ss.no_pages - 1][diag - k][k].barcode[:,0]):\n",
+    "                    if np.allclose(rad, current_rad):\n",
+    "                        next_rad = MV_ss.Hom[\n",
+    "                            MV_ss.no_pages - 1][diag - k][k].barcode[i,1]\n",
+    "                        ax.fill([current_rad, next_rad, next_rad, current_rad],\n",
+    "                                [y_coord,y_coord,y_coord+step,y_coord+step],\n",
+    "                                c=colors[k + no_diag - diag - 1])\n",
+    "                        current_rad = next_rad\n",
+    "                    # end if\n",
+    "                # end for\n",
+    "            # end if\n",
     "\n",
     "        # end for\n",
     "        if current_rad < b[1]:\n",

setup.py

@@ -15,6 +15,8 @@
     long_description_content_type="text/x-rst",
     author_email="atorras1618@gmail.com",
     author="Alvaro Torras Casas",
+    url="https://github.com/atorras1618/PerMaViss",
+    download_url="https://github.com/atorras1618/PerMaViss/tarball/v0.0.1",
     licence="MIT",
     keywords=["spectral sequence", "persistent homology", "Mayer Vietoris"],
     packages=find_packages("src"),