Merge pull request #111 from ukhsa-collaboration/feature/prep-doc

Feature/prep doc

.github/workflows/book.yml

@@ -8,6 +8,7 @@ on:
   push:
     branches:
     - master
+    - dev
 
 jobs:
     build-book:

.github/workflows/main.yml

@@ -22,7 +22,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, windows-latest] # macos-latest
-        python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v2

README.md

@@ -0,0 +1,113 @@
+# PyGOM - Python Generic ODE Model
+
+[![pypi version](https://img.shields.io/pypi/v/pygom.svg)](https://pypi.python.org/pypi/pygom)
+[![Documentation Status](https://readthedocs.org/projects/pygom/badge/?version=master)](https://pygom.readthedocs.io/en/master/?badge=master)
+[![licence](https://img.shields.io/pypi/l/pygom?color=green)](https://raw.githubusercontent.com/PublicHealthEngland/pygom/master/LICENSE.txt)
+[![Github actions](https://github.com/PublicHealthEngland/pygom/workflows/pygom/badge.svg)](https://github.com/PublicHealthEngland/pygom/actions/)
+[![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://hwilliams-phe.github.io/pygom/intro.html)
+
+A generic framework for Ordinary Differential Equation (ODE) models, especially compartmental type systems.
+This package provides a simple interface for users to construct ODE models backed by a comprehensive and easy to use tool–box implementing functions to easily perform common operations such as parameter estimation and solving for deterministic or stochastic time evolution.
+With both the algebraic and numeric calculations performed automatically (but still accessible),
+the end user is free to focus on model development.
+
+## Installation
+
+You can download a local copy of the PyGOM source files from this GitHub repository:
+
+    git clone https://github.com/ukhsa-collaboration/pygom.git
+
+Please be aware that there may be redundant files within the package as it is under active development.
+
+> [!NOTE]
+> The latest fully reviewed version of PyGOM will be on the `master` branch and we generally recommend that users install this version. However, the current version being prepared for release (featuring up-to-date documentation) is hosted on the `feature/prep-doc` branch.
+
+When running the following command line commands, ensure that your current working directory is the one where the PyGOM source files were downloaded to. This should be found from your home directory:
+
+    cd pygom
+
+Activate the relevant branch for installation via Git Bash, if you have been recruited to test code for the
+new release then this is the `feature/prep-doc` branch:
+
+    git checkout feature/prep-doc
+
+Package dependencies can be found in the file, `requirements.txt`.
+An easy way to install these to create a new [conda](https://conda.io/docs) environment in Anaconda Prompt via:
+
+    conda env create -f conda-env.yml
+
+which you should ensure is active for the installation process using
+
+    conda activate pygom
+
+Alternatively, you may add dependencies to your own environment through conda:
+
+    conda install --file requirements.txt
+
+**or** via pip:
+
+    pip install -r requirements.txt
+
+The final prerequisite, if you are working on a Windows machine, is that you will also need to install:
+- [Graphviz](https://graphviz.org/)
+- Microsoft Visual C++ 14.0 or greater, which you can get with [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/)
+
+You should now be able to install the PyGOM package via command line:
+
+    python setup.py install
+
+and test that installation has completed successfully
+
+    python setup.py test
+
+This will run a few test cases and can take some minutes to complete.
+
+## Documentation
+
+Documentation must be built locally and all necessary files can be found in the `docs` folder.
+Documentation is built from the command line by first installing the additional documentation requirements:
+
+    pip install -r docs/requirements.txt
+
+and then building the documentation:
+
+    jupyter-book build docs
+
+The html files will be saved in the local copy of your repository under:
+
+    docs/_build/html
+
+You can view the documentation by opening the index file in your browser of choice:
+
+    docs/_build/html/index.html
+
+> [!NOTE]
+> Building the documentation involves running many examples in python which can take up to 30 minutes. Subsequent builds with these examples unchanged are much quicker due to caching of the code outputs.
+
+Please be aware that if the module tests fails, then the documentation for the package will not compile.
+
+## Contributors
+
+Thomas Finnie ([email protected])
+
+Edwin Tye
+
+Hannah Williams
+
+Jonty Carruthers
+
+Martin Grunnill
+
+Joseph Gibson
+
+## Version
+
+0.1.7 Add Approximate Bayesian Computation (ABC) as a method of fitting to data 
+
+0.1.6 Bugfix scipy API, pickling, print to logging and simulation
+
+0.1.5 Remove auto-simplification for much faster startup
+
+0.1.4 Much faster Tau leap for stochastic simulations
+
+0.1.3 Defaults to python built-in unittest and more in sync with conda

conda-env.yml

@@ -11,5 +11,5 @@ dependencies:
   - graphviz
   - cython
   - pip
-  -pip:
+  - pip:
     - -r requirements.txt