Merge branch 'master' into development(calysta)

.github/workflows/ci.yaml

@@ -25,16 +25,16 @@ jobs:
       matrix:
         python-version: ["3.8","3.9","3.10","3.11"]
         os: [ubuntu-latest,]
-    
+
     runs-on: ${{matrix.os}}
     steps:
     - uses: actions/checkout@v3
-    
+
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
-    
+
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
@@ -44,21 +44,20 @@ jobs:
         pip install pytest-cov
         pip install pytest-mpl
         pip install -e .
-    
+
     - name: Check package versions
       run: |
         pip show -V pytest
         pip show -V ase
         pip show -V matplotlib
-    
+
     - name: Run tests
       run: pytest --cov=macrodensity --mpl tests/unit_tests.py --cov-report=xml -v
-    
+
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v3
       with:
         token: ${{ secrets.CODECOV_TOKEN }}
         fail_ci_if_error: true
         verbose: true
         files: ./coverage.xml
-

.github/workflows/release_to_pypi.yml

@@ -0,0 +1,56 @@
+name: Release and publish
+
+on:
+  workflow_run:
+    workflows: [ "MacroDensity CI" ]
+    branches: [ main ]
+    types:
+      - completed  # only release when tests have passed
+
+  workflow_dispatch:
+
+jobs:
+  release:
+    runs-on: ubuntu-latest
+    if: ${{ github.event_name == 'workflow_dispatch' || (github.event_name == 'workflow_run' && github.event.workflow_run.conclusion == 'success') }}
+    # only run when tests have passed (or manually triggered)
+
+    steps:
+      - uses: actions/checkout@v1
+
+      - uses: actions/setup-python@v1
+        with:
+          python-version: 3.9
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install setuptools setuptools_scm wheel
+          pip install -e .[tests]
+
+      - name: Build packages
+        run: |
+          python setup.py sdist bdist_wheel
+
+      - name: Publish
+        uses: pypa/gh-action-pypi-publish@master
+        with:
+          user: __token__
+          password: ${{ secrets.TWINE_PASSWORD }}
+
+      - name: Generate release info
+        run: |
+          awk 'BEGIN {p = 0} {a = 0 }; /^v\d*.\d*.\d*./ { p += 1; a = 1}; p + a == 1 { print } ' CHANGELOG.rst | sed -e '1,1d' | sed  -e '/./,$!d' -e :a -e '/^\n*$/{$d;N;ba' -e '}' > release_info.txt
+          echo "version=$(grep version setup.py | awk -F\" '{print $2}')" >> $GITHUB_ENV
+
+      - name: Release
+        uses: actions/create-release@v1
+        id: create_release
+        env:
+          GITHUB_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
+        with:
+          tag_name: v${{ env.version }}
+          release_name: ${{ env.version }}
+          body_path: release_info.txt
+          draft: false
+          prerelease: false

CHANGELOG.rst

@@ -0,0 +1 @@
+

README.md

@@ -1,26 +1,23 @@
-MacroDensity
-====================
-![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.884521.svg)
+# Welcome to MacroDensity
 
-A set of Python scripts to read in a electrostatic potentials and electron densities from electronic structure calculations and plot in a number of ways, including:
+``MacroDensity`` is a Python package to post-process electrostatic potential and
+electron density files from electronic structure calculations and plot in a number of ways, including:
 
-* Planar average
-* Spherical average
-* Atom centred average
+1. Planar average
+2. Spherical average
+3. Atom centred average
 
 # Statement of Need
 
-To assess the potential utility of novel semiconducting devices (like p-n junctions, heterostructures, surface terminations), it is key to understand how the electrostatic potential and electron density change across the system. However, extraction and useful presentation of this data from the raw output of the simulation can prove cumbersome and often requires the use of visualisation software followed by manual data extraction. This can result in bottlenecks in high throughput screening projects, where the same data extraction procedure is repeatedly applied to large databases of candidate structures.
+To assess the potential utility of novel semiconducting devices (like p-n junctions, heterostructures, surface terminations),
+it is key to understand how the electrostatic potential and electron density change across the system.
+However, extraction and useful presentation of this data from the raw output of the simulation can prove cumbersome and often requires the use of visualisation software followed by manual data extraction.
+This can result in bottlenecks in high throughput screening projects, where the same data extraction procedure is repeatedly applied to large databases of candidate structures.
 
-To address this, the Macrodensity package has been developed to post-process the output of ab-initio codes like `VASP`, `FHI-AIMS` and `GULP`. The package contains functions that enable the user to format the data from the `VASP LOCPOT` and `CHGCAR` files, the `FHI-AIMS *.cube` file, and `GULP *.out` file into physically meaningful quantities, which can then be plotted for user interpretation.
+To address this, the Macrodensity package has been developed to post-process the output of ab-initio codes like ``VASP``, ``FHI-AIMS`` and ``GULP``.
+The package contains functions that enable the user to format the data from the ``VASP`` ``LOCPOT`` and ``CHGCAR`` files, the ``FHI-AIMS`` ``*.cube`` file,
+and ``GULP`` ``*.out`` file into physically meaningful quantities, which can then be plotted for user interpretation.
 
-# Requirements
-
-* [Python](https://www.python.org)
-* [Matplotlib](http://matplotlib.org) (to plot results on the fly)
-* [ASE](https://wiki.fysik.dtu.dk/ase/) (for atom centred functionality)
-* [Pandas](https://pandas.pydata.org/) (optional - for quicker reading speeds; requires pandas 1.2.0 or newer)
-* [Jupyter](https://jupyter.org/) (optional - for `.ipynb` notebooks in the [tutorials](https://github.com/WMD-group/MacroDensity/tree/V3.1.0/tutorials))
 
 # Installation
 
@@ -33,6 +30,7 @@ pip install macrodensity
 ```
 
 ## Developer installation
+
 For development of MacroDensity, you can install a copy of the package from the source directory:
 
 ```
@@ -42,17 +40,17 @@ pip install -e .
 ```
 
 
-Literature
-========================
+# Literature
+
 For more information on the theory behind the package, please see the following references:
 
 - General Approach: Butler, K. T., Hendon, C. H., & Walsh, A. [Electronic chemical potentials of porous Metal–Organic frameworks](https://doi.org/10.1021/ja4110073). *Journal of the American Chemical Society*, 136(7), 2703–2706, 2014
-- Theoretical Background: 
+- Theoretical Background:
    * Politzer, P., & Murray, J. S. [The fundamental nature and role of the electrostatic potential in atoms and molecules](https://link.springer.com/article/10.1007/s00214-002-0363-9). *Theoretical Chemistry Accounts*, 108(3), 134–142, 2002
    * Peressi, M., Binggeli, N. & Baldereschi, A. [Band engineering at interfaces: theory and numerical experiments](https://iopscience.iop.org/article/10.1088/0022-3727/31/11/002/meta). *Journal of Physics D: Applied Physics*,31(11), 1273, 1998
 - Application to MOFs:
    * Butler, K. T., Hendon, C. H. & Aron Walsh, A. [Electronic Chemical Potentials of Porous Metal–Organic Frameworks](https://doi.org/10.1021/ja4110073). *Journal of the American Chemical Society*, 136(7), 2703–2706, 2014
-  
+
 
 
 # Contributing
@@ -81,4 +79,3 @@ MacroDensity is made available under the MIT License.
 If you use it in your research, please cite:
 
 * Method: Harnett-Caulfield, L., & Walsh, A.  [*Journal of Chemical Physics*](https://doi.org/10.1063/5.0044866) 2021
-