In writing tests, I discovered that the Buckingham forcefield functions run into a TypeError if the dr input is not a single float (i.e [dr] or for an array of different values).

Here's the error that comes up:
TypeError: can't multiply sequence by non-int of type 'float'

With the ability to write custom forcefields it would be nice for the documentation to have a page dedicated to information about this

Now that there is support for other forcefields, it would be nice to have a Square-well potential

Please add the DOI for Jupyter Notebooks reference.

using the msd plot in the scattering class there is some inconsistency due to the pbc

Describe the bug
I'm working through the ideal_gas_law example. I have a feeling the plot of atoms should animate them moving around the box, but there's no display until the calculation is over, then it just shows what I think is the last frame.

To Reproduce
Steps to reproduce the behavior:

1. Go to 'ideal_gas_law example notebook'
2. Click on 'simulation1 = md_simulation(4, 100., 100, 10000, sample.JustCell)'
3. Scroll down to 'plot'
4. Nothing displays until the calculation is over, then it's just a static plot.

Expected behavior
From the instructions it seems like it should be animated?.

Screenshots

Desktop (please complete the following information):

• OS: CentOS
• Browser chrome
• Version 97

Additional context

Test coverage has dropped a bit, work be nice to see it go back up

Remove the need for a C++ implementation of the pairwise calculation by using numba jit

The documentation is very poor and outdated. At minimum it needs a facelift.

Currently the marker size for the particles in the mpl plots is deteremined based on the size of the simulation cell. However, with the release 1.1, it is now possible to change the forcefield and the values of A and B, therefore requiring the particle marker size to scale with both the simulation cell size and the nature of the potential model.

I reckon it is best to have the marker size be dependent on the position of the minima on the potential well. e.g. the sigma for a (sigma-epsilon) Lennard Jones.

This would involve working on the mk variable in the sample.setup_cellview function. Since it might be forcefield dependent, it might be necessary to define something in the forcefields.py module.

Ideas welcome.

The examples are broken following the move to non-C++ stuff.

1. I really like the idea of running a demo through Jupyter, as it is convenient to test the code directly. I tried the cloud version for molecular_dynamics but not successful. Please correct me if I did it wrong. http://35.230.133.1/notebook/notebooks/examples/molecular_dynamics.ipynb#
   The error message is here:

TypeError                                 Traceback (most recent call last)
 in ()
----> 1 system = md_simulation(100, 273.15, 100, 5000, 50)
 in md_simulation(number_of_particles, temperature, box_length, number_of_steps, sample_frequency)
     16                                                                                                  system.cut_off)
     17         # Run the equations of motion integrator algorithm
---> 18         system.particles = md.velocity_verlet(system.particles, system.timestep_length, system.box_length)
     19         # Sample the thermodynamic and structural parameters of the system
     20         system = md.sample(system.particles, system.box_length, system.initial_particles, system)
TypeError: velocity_verlet() missing 1 required positional argument: 'cut_off' 

2. I tried to run it on a linux computer through a terminal, it was not successful either. I followed exactly all the steps shown in README.md. I suspected I missed installing some libraries. I think it will be beneficial if a detailed installation manual can be provided.

In title

Now that there is support for other forcefields, it would be nice to have a sigma epsilon LJ potential in addition to the A B one there is currently.

How this is done for a Lennard-Jones potential can be found in pylj/forcefields.py

The docs badge in the README.md points here instead of here.

Now that there is support for other forcefields, it would be nice to have a Buckingham potential

For students, it would be nice if they can run the notebooks online using myBinder (e.g. https://jupyter.org/try). I have not managed to get it running since pylj is not apparently not in the "default-binder" collection of packages.

I have tried to get it running with adding it in the requirements.txt or enviroment.yml (https://mybinder.readthedocs.io/en/latest/using/config_files.html#config-files), but have failed so far...

I liked the additional notebooks. I had a few simple fixes; nothing too difficult. Pending these changes I agree that it is ready for publication. Great job!

ideal_gas_law/first_principles.ipynb:

When rearranging ln(Q) add some helpful hints for students:
Between eq 1 and 2: "Using Stirling's approximation"
Between eq 2 and 3: "Substituting the de Broglie thermal wavelength"

ideal_gas_law/intro_to_monte_carlo.ipynb:

typos:
"approxmations" -> "approximations"
"intantenous" -> "instantaneous"
"accoprding" -> "according"
"enivornment" -> "environment"
"neglible" -> "negligible"
"implimented" -> "implemented"

ideal_gas_law/intro_to_molecular_dynamics.ipynb:

typos:
"approxmations" -> "approximations"
"intantenous" -> "instantaneous"
"accoprding" -> "according"
"enivornment" -> "environment"
"deriviative" -> "derivative"

ideal_gas_law/ideal_gas_law.ipynb:

typos:
"approxmations" -> "approximations"
"intantenous" -> "instantaneous"
"accoprding" -> "according"
"showen" -> "shown"
"presssure" -> "pressure"
"disucss" -> "discuss"

In all of the "Atomistic Simulation" cells:

The sentence: "The use of computers in chemistry is becoming more and more commonplace with increases computational resource and more efficient and effective algorithms." sounds a bit awkward.
Consider: "The use of computers in chemistry is becoming more common as computers are increasing in power and the algorithms are becoming more accurate and efficient."

Can we move to having classes that describe the potential models? Does this mean we can have a mixture of particles?

https://pyodide.org/en/stable/

Can we use pyodide for examples that run in the browser?

Include ipywidgets (or similar) to control variables of the simulation such as temperature, number of particles etc.

Improve the forcefield tests such that:

• dr is an array
• different values of constants are being used

This file is part of the distribution.

In the examples, there are several fields/code boxes which are not running, since they contain broken special characters.

Steps to reproduce the behavior:

1. Go to 'pylj/examples/molecular_dynamics/intro_to_molecular_dynamics.ipynb'
2. Check code box 2 and 3, for example
   or
3. pylj/examples/ideal_gas_law/ideal_gas_law.ipynb
4. Check code box 2 and 3, for example

Screenshot from the "raw" notebook:

Checked on Ubuntu 20.04.2 LTS with

• Firefox (87.0+build3-0ubuntu0.20.04.2)
• Chromium (89.0.4389.114)

The readme says all development discussion will take place on gitter. The docs say there is a slack channel. I couldn't sign in to the slack channel because it says I need to "Contact the workspace administrator for an invitation".

Is all communication going to occur via gitter? If so can the read me be changed to make this clearer?

Can these please be replaced with named constants? Preferably with the formula/units in a comment? I think this code has educational utility beyond what is intended. The project is structured well and the code is written well so it is readable. I could imagine more advanced students reading the source and learning something.
E.g.

// four_ep_sigma (UNITS) = 4 * \epsilon * \sigma**6 
four_ep_sigma = 9.273e-78

Instances that I saw:

• MC.py
• sample.py
• sample.py
• util.py
• comp.cpp lines 38 - 45
• comp.cpp
• comp.cpp
• comp.cpp

Since this is pedagogical code, I don't think the focus should be on making things faster if it becomes unreadable. However I had one change that could make things quicker and if someone is reading the code to learn, it could start them thinking about these things when programming.

In comp.cpp, change from

f = (1.635e-133 * pow(dr, -13.) - 5.834e-77 * pow(dr, -7.));
force_arr[k] = f;
e = (1.363e-134 * pow(dr, -12.) - 9.273e-78 * pow(dr, -6.));
energy_arr[k] = e;

to

inv_dr_1 = 1.0 / dr;
inv_dr_6 = pow(inv_dr_1, 6);

f = (1.635e-133 * (inv_dr_1*inv_dr_6*inv_dr_6) - 5.834e-77 * (inv_dr_1*inv_dr_6*));
force_arr[k] = f;
e = (1.363e-134 * (inv_dr_6*inv_dr_6)) - 9.273e-78 * (inv_dr_6));
energy_arr[k] = e;