Merge flake8 formatter into workflow

.github/workflows/python-app.yml

@@ -1,7 +1,7 @@
 # This workflow will install Python dependencies, run tests with a single version of Python
 # For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
 
-name: Python application
+name: Build and test
 
 on:
   push:
@@ -26,8 +26,14 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install pytest
+        pip install pytest flake8
         pip install -e .
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Test with pytest
       run: |
         pytest

README.md

@@ -1,13 +1,20 @@
-# Quantum electron solver
+![example workflow](https://github.com/gkoolstra/quantum_electron/actions/workflows/python-app.yml/badge.svg)
+# Quantum Electron Solver
+![image info](./images/electron_results.png)
+## Main use cases
 This package has two main functions
-1. It can simulate electron positions in a two dimensional plane for electrons confined in an electrostatic potential. The electron-electron interactions are also taken into account.
-2. It can solve the Schrodinger equation for a single electron confined in an electrostatic potential.
+1. It simulates electron positions in a two dimensional plane for electrons confined in an electrostatic potential $\phi$. Electron-electron interactions are also taken into account. Physically, it minimizes the total energy of an $N$-electron system, which is given by: 
 
-In both cases there are methods to calculate couplings to a resonator and resonator frequency shifts due to electrons. This is useful the electrons are detected with a microwave resonator. If your experimental setup does not contain a resonator, you can safely ignore the methods in this library without compromise of the results. 
+$$ -e\sum_i \phi(\mathbf{r}_i) + \sum_{i<j} \frac{e^2}{4\pi \epsilon_0} \frac{1}{|\mathbf{r}_i - \mathbf{r}_j|}$$ 
 
-After installation, it is advised to take a look at the `examples` folder to explore some of the functionalities of this module. 
+2. It calculates properties of in-plane electron modes. This is useful in two cases: (a) the electron motional states can be used for quantum computation, and this package can help to determine eigenfrequencies and eigenvectors of electron clusters (b) in the large $N$ limit the electron motional modes are also known as plasmons. There is an abundance of literature about these charge density waves, and many of the properties can be reproduced with this module.
 
-![image info](./images/electron_results.png)
+### Features
+- Robust operation through the use of the `scipy.optimize.minimize` library. We assure proper and fast convergence because the force (gradient of the energy) is supplied as an argument of the minimizer.
+- Supply arbitrary potential energies $\phi$, as long as they're on a rectangular grid. 
+- Handles problems up to $N \approx 400$ electrons in less than 1 minute on a laptop computer. 
+- Periodic boundary condition support for systems with open boundaries.
+- Seemless integration with finite element modeling software ZeroHeliumKit.
 
 ## Installation
 
@@ -21,21 +28,14 @@ In a terminal window, change into the cloned directory:
 cd quantum_electron
 pip install -e .
 ```
+After installation, it is advised to take a look at the `examples` folder to explore some of the functionalities of this module. 
 
 ### Additional packages
 To generate animations, this module relies on `ffmpeg`. On MacOS this can be easily installed using [homebrew](https://formulae.brew.sh/formula/ffmpeg) from the Terminal. On Windows it can be installed using the following [link](https://www.ffmpeg.org/download.html). 
 
 This module also integrates well with the output of the FEM software [ZeroHeliumKit](https://github.com/eeroqlab/zeroheliumkit). Please refer to any dependencies for ZHK on the linked github page.
 
-## To-do list
-- [ ] Standardize units of the arguments. Sometimes it is unclear whether to use microns or meters.
-- [ ] Figure out how to handle warning messages for convergence issues. Why do problems sometimes have a hard time converging?
-- [ ] Write documentation for example notebook 03
-- [ ] Find a place for the code in example notebook 04.
-- [ ] Split off the Schrodinger solver?
-- [ ] Add some documentation to the library folder
-
-## Test suite
+## Tests
 To test the performance of the minimization, we're building and expanding a suite of tests based on the `pytest` framework. To run these tests, `cd` into the main module directory and run `pytest`. Currently, we have implemented a test in `test_wigner_molecules.py`, which compares the energy per particle of Wigner molecules in a parabolic confinement to known tabulated values.
 
 ## Getting started
@@ -68,10 +68,22 @@ options = {"include_screening" : True, # Include screening of electron-electron
            "max_y_displacement" : 0.1e-6} # Maximum y-displacement of solved electron positions during annealing.
 ```
 
-
 ## Tips for the initial condition
-The initial condition can affect the final minimization result quite strongly. If there are issues with convergence you can first check convergence with `f.plot_convergence()`. A good final value for the cost function is ~1-500 eV/m. If the lowest value of the cost function is signifantly higher than this, or if warnings appear, here are some rules of thumb for successful convergence:
+The initial condition can affect the final minimization result quite strongly. We encourage you to take a look at the example notebook about initial conditions. If there are issues with convergence you can first check convergence with `f.plot_convergence()`. A good final value for the cost function is ~1-500 eV/m. If the lowest value of the cost function is signifantly higher than this, or if warnings appear, here are some rules of thumb for successful convergence:
 1. Don't create an initial condition where too many electrons are placed in a small area.
 2. Don't place electrons in an initial condition where the potential is too flat, such as on a ground plane. 
 3. Be mindful of electron sinks, i.e. channels for electrons to escape. These can appear if an electrode is adjacent to the ground plane, and has an applied voltage that is more positive than the ground plane.
 
+## Contributing
+Contributions to this growing repository are welcome. Please feel free to create a fork and create a pull request with your suggested changes.
+
+## Credit
+If you found this module useful in your research, please consider citing this code in your publication using a hyperlink.
+
+## To-do list
+- [ ] Standardize units of the arguments. Sometimes it is unclear whether to use microns or meters.
+- [ ] Figure out how to handle warning messages for convergence issues. Why do problems sometimes have a hard time converging?
+- [ ] Write documentation for example notebook 03
+- [ ] Find a place for the code in example notebook 04.
+- [ ] Split off the Schrodinger solver?
+- [ ] Performance metrics

quantum_electron/__init__.py

@@ -1,4 +1,4 @@
 from .electron_counter import FullModel
 from .schrodinger_solver import QuantumAnalysis
 from .utils import PotentialVisualization, package_versions
-from ._version import __version__
+from ._version import __version__

quantum_electron/_version.py

@@ -2,4 +2,4 @@
 # 1) we don't load dependencies by storing it in __init__.py
 # 2) we can import it in setup.py for the same reason
 # 3) we can import it into your module module
-__version__ = '0.2.0'
+__version__ = '0.2.1'