Merge remote-tracking branch 'refs/remotes/origin/master'

Author: Sceki

.readthedocs.yaml

@@ -0,0 +1,27 @@
+# .readthedocs.yaml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Set the version of Python and other tools you might need
+#build:
+#  os: ubuntu-20.04
+#  tools:
+#    python: "3.8"
+
+
+# Build documentation in the docs/ directory with Sphinx
+sphinx:
+   configuration: docs/source/conf.py
+
+# If using Sphinx, optionally build your docs in additional formats such as PDF
+formats:
+    - htmlzip
+
+# Optionally declare the Python requirements required to build your docs
+python:
+   version: 3.8
+   install:
+     - requirements: docs/requirements.txt

README.md

@@ -4,6 +4,7 @@
 
 -----------------------------------------
 [![Build Status](https://github.com/kesslerlib/kessler/workflows/build/badge.svg)](https://github.com/kesslerlib/kessler/actions)
+[![Documentation Status](https://readthedocs.org/projects/kessler/badge/?version=latest)](https://kessler.readthedocs.io/en/latest/?badge=latest)
 
 Kessler is a Python package for simulation-based inference and machine learning for space collision avoidance and assessment. It is named in honor of NASA scientist [Donald J. Kessler](https://en.wikipedia.org/wiki/Donald_J._Kessler) known for proposing the [Kessler syndrome](https://en.wikipedia.org/wiki/Kessler_syndrome).
 

docs/source/credits.ipynb

@@ -16,7 +16,7 @@
     "Kessler was initially developed by the Constellations team at the [Frontier Development Lab](https://frontierdevelopmentlab.org/) (FDL) Europe 2020, a public-private partnership between the European Space Agency (ESA), Trillium Technologies, and University of Oxford.\n",
     "\n",
     "\n",
-    "Constellations team members: Giacomo Acciarini (University of Strathclyde), Francesco Pinto (University of Oxford), Sascha Metz (TU Darmstadt), Sarah Boufelja (IBM), Sylvester Kaczmarek (Imperial College London), Klaus Merz (European Space Agency), José A. Martinez-Heras (European Space Agency), Francesca Letizia (European Space Agency), Christopher Bridges (University of Surrey), Atılım Güneş Baydin (University of Oxford).\n",
+    "Constellations team members: Giacomo Acciarini (University of Oxford), Francesco Pinto (University of Oxford), Sascha Metz (TU Darmstadt), Sarah Boufelja (IBM), Sylvester Kaczmarek (Imperial College London), Klaus Merz (European Space Agency), José A. Martinez-Heras (European Space Agency), Francesca Letizia (European Space Agency), Christopher Bridges (University of Surrey), Atılım Güneş Baydin (University of Oxford).\n",
     "\n",
     "The main developers are: Giacomo Acciarini ( giacomo.acciarini@gmail.com ), Francesco Pinto ( francesco1.pinto@gmail.com ), Atılım Güneş Baydin ( gunes@robots.ox.ac.uk ).\n",
     "\n"

docs/source/index.rst

@@ -1,7 +1,11 @@
-kessler reference documentation
+Kessler Reference Documentation
 ================================
 
-kessler is a probabilistic programming system designed for use with existing simulators and high-performance computing. It is based on PyTorch.
+Kessler is a Python package for machine learning applied to spacecraft collision avoidance. It provides functionalities to import, export, analyze, and plot conjunction data messages (CDMs) in their standard format and predict the evolution of satellite conjunction events based on explainable machine learning models. 
+
+The package comprises a Deep Learning module, where a Bayesian recurrent neural network can be trained with existing collections of CDM data and then deployed in order to predict the contents of future CDMs received up to now, with associated uncertainty estimates about all predictions.
+
+Kessler also includes a novel generative model of conjunction events and CDM sequences implemented using probabilistic programming and simulating the CDM generation process, which we will soon release to the public: stay tuned!
 
 The documentation is currently a work in progress.