imporved text and grammar

docs/source/chapters/chapter1.rst

@@ -39,32 +39,32 @@ containing either Python functions or classes:
 
    * - File Name 
      - Content
-   * - *Prepare.py* 
+   * - Prepare.py 
      - *Prepare* class: Methods for preparing the non-dimensionalization of the
        units
-   * - *Utilities.py* 
+   * - Utilities.py
      - *Utilities* class: General-purpose methods, inherited by all other
        classes
-   * - *InitializeSimulation.py*
+   * - InitializeSimulation.py
      - *InitializeSimulation* class: Methods necessary to set up the system and
        prepare the simulation, inherited by all the classes below
-   * - *MinimizeEnergy.py* 
+   * - MinimizeEnergy.py
      - *MinimizeEnergy* class: Methods for performing energy minimization
-   * - *MonteCarlo.py*
+   * - MonteCarlo.py
      - *MonteCarlo* class: Methods for performing Monte Carlo simulations in
        different ensembles (e.g., Grand Canonical, Canonical)
-   * - *MolecularDynamics.py*
+   * - MolecularDynamics.py
      - *MolecularDynamics* class: Methods for performing molecular dynamics in
        different ensembles (NVE, NPT, NVT)
-   * - *measurements.py* 
-     - Functions for performing specific measurements on the system
+   * - Measurements.py
+     - *Measurements* class: Methods for for performing specific measurements on the system
    * - *potentials.py* 
      - Functions for calculating the potentials and forces between atoms
-   * - *logger.py*
+   * - logger.py
      - Functions for outputting data into text files
-   * - *dumper.py*
+   * - dumper.py
      - Functions for outputting data into trajectory files for visualization
-   * - *reader.py*
+   * - reader.py
      - Functions for importing data from text files
 
 Some of these files are created in this chapter; others will be created later
@@ -73,31 +73,25 @@ on. All of these files must be created within the same folder.
 Potential for Inter-Atomic Interaction
 --------------------------------------
 
-In molecular simulations, potential functions are used to mimic the interaction
-between atoms. Although more complicated options exist, potentials are usually
+In molecular simulations, potential functions are used to model the interaction
+between atoms. Although more complex options exist, potentials are usually
 defined as functions of the distance :math:`r` between two atoms.
 
-Create the first file named *potentials.py*. This file will contain a function
-called *potentials*. For the moment, the only potential that can be returned by
-this function is the Lennard-Jones potential (LJ). This may change in the
-future.
+Create a file named *potentials.py*. This file will contain a function called
+*potentials*. For now, the only potential that can be returned by this function
+is the Lennard-Jones (LJ) potential, but this may change in the future.
 
 Copy the following lines into *potentials.py*:
 
 .. label:: start_potentials_class
 
 .. code-block:: python
 
-    import numpy as np
-
-    def potentials(potential_type, epsilon, sigma, r, derivative=False):
-        if potential_type == "Lennard-Jones":
-            if derivative:
-                return 48 * epsilon * ((sigma / r) ** 12 - 0.5 * (sigma / r) ** 6) / r
-            else:
-                return 4 * epsilon * ((sigma / r) ** 12 - (sigma / r) ** 6)
+    def potentials(epsilon, sigma, r, derivative=False):
+        if derivative:
+            return 48 * epsilon * ((sigma / r) ** 12 - 0.5 * (sigma / r) ** 6) / r
         else:
-            raise ValueError(f"Unknown potential type: {potential_type}")
+            return 4 * epsilon * ((sigma / r) ** 12 - (sigma / r) ** 6)
 
 .. label:: end_potentials_class
 
@@ -108,14 +102,19 @@ i.e., the force, :math:`F_\text{LJ} = - \mathrm{d} U_\text{LJ} / \mathrm{d} r`:
 .. math::
 
     F_\text{LJ} = 48 \dfrac{\epsilon}{r} \left[ \left( \frac{\sigma}{r} \right)^{12}
-    - \frac{1}{2} \left( \frac{\sigma}{r} \right)^6 \right],
+    - \frac{1}{2} \left( \frac{\sigma}{r} \right)^6 \right], ~ \text{for} ~ r < r_\text{c},
 
 or the potential energy:
 
 .. math::
 
     U_\text{LJ} = 4 \epsilon \left[ \left( \frac{\sigma}{r} \right)^{12}
-    - \left( \frac{\sigma}{r} \right)^6 \right].
+    - \left( \frac{\sigma}{r} \right)^6 \right], ~ \text{for} ~ r < r_\text{c}.
+
+Here, :math:`\sigma` is the distance at which the potential :math:`U_\text{LJ}`
+is zero, :math:`\epsilon` is the depth of the potential well, and
+:math:`r_\text{c}` is a cutoff distance. For :math:`r > r_\text{c}`,
+:math:`U_\text{LJ} = 0` and :math:`F_\text{LJ} = 0`.
 
 Create the Classes
 ------------------
@@ -183,8 +182,14 @@ Within the *InitializeSimulation.py* file, copy the following lines:
 .. label:: end_InitializeSimulation_class
 
 The *InitializeSimulation* class inherits from the previously created
-*Prepare* and Utilities classes. Additionally, we anticipate that *NumPy* will
-be required.
+*Prepare* and *Utilities* classes. Additionally, we anticipate that |NumPy|
+will be required :cite:`harris2020array`. We also anticipate that the *os*
+module, which provides a way to interact with the operating system, will
+be required :cite:`Rossum2009Python3`.
+
+.. |NumPy| raw:: html
+
+   <a href="https://numpy.org/" target="_blank">NumPy</a>
 
 Within the *Measurements.py* file, copy the following lines:
 
@@ -204,13 +209,13 @@ Within the *Measurements.py* file, copy the following lines:
           
 .. label:: end_Measurements_class
 
-The *Measurements* class inherits both the *InitializeSimulation* and
-*Utilities* classes. 
+The *Measurements* class inherits from *InitializeSimulation* (and thus
+also inherits from the *Prepare* and *Utilities* classes).
 
-Finally, let us create the three remaining classes, named *MinimizeEnergy*,
-*MonteCarlo*, and *MolecularDynamics*. Each of these three classes inherits
-from the *Measurements* class, and thus from the classes inherited by
-*Measurements*.
+Finally, let us create the three remaining classes: *MinimizeEnergy*,
+*MonteCarlo*, and *MolecularDynamics*. Each of these classes inherits
+from the *Measurements* class (and thus also from the *Prepare*, *Utilities*,
+and *InitializeSimulation* classes).
 
 Within the *MinimizeEnergy.py* file, copy the following lines:
 
@@ -219,6 +224,8 @@ Within the *MinimizeEnergy.py* file, copy the following lines:
 .. code-block:: python
 
     from Measurements import Measurements
+    import numpy as np
+    import copy
     import os
 
 
@@ -230,19 +237,17 @@ Within the *MinimizeEnergy.py* file, copy the following lines:
 
 .. label:: end_MinimizeEnergy_class
 
-We anticipate that the *os* module, which provides a way to interact with the
-operating system, will be required :cite:`Rossum2009Python3`.
+The *copy* library, which provides functions to create shallow or deep copies of
+objects, is imported, along with *NumPy* and *os*.
 
 Within the *MonteCarlo.py* file, copy the following lines:
 
 .. label:: start_MonteCarlo_class
 
 .. code-block:: python
 
-    from scipy import constants as cst
     import numpy as np
     import copy
-    import os
     from Measurements import Measurements
 
     import warnings
@@ -257,12 +262,10 @@ Within the *MonteCarlo.py* file, copy the following lines:
 
 .. label:: end_MonteCarlo_class
 
-Several libraries were imported, namely *Constants* from *SciPy*, *NumPy*, *copy*
-and *os*.
-
-The *warnings* was placed to avoid the anoying message "*RuntimeWarning: overflow
-encountered in exp*" that is sometimes triggered by the exponential of the
-*acceptation_probability* (see :ref:`chapter6-label`).
+The *ignore warnings* commands are optional; they were added to avoid the
+annoying message "*RuntimeWarning: overflow encountered in exp*" that is sometimes
+triggered by the exponential function of *acceptation_probability* (see the
+:ref:`chapter6-label` chapter).
 
 Finally, within the *MolecularDynamics.py* file, copy the following lines:
 
@@ -331,9 +334,9 @@ Alternatively, this test can also be launched using *Pytest* by typing in a term
 
     pytest .
 
-We can also test that calling the *__init__*
-method of the *MonteCarlo* class does not return any error. In new Python file
-called *test_1b.py*, copy the following lines:
+We can also test that calling the *__init__* method of the *MonteCarlo* class
+does not return any error. In new Python file called *test_1b.py*, copy the
+following lines:
 
 .. label:: start_test_1b_class
 

docs/source/chapters/chapter2.rst

@@ -29,7 +29,7 @@ The *real* unit system follows the conventions outlined in the |lammps-unit-syst
 - Forces are in (kcal/mol)/Ångström,
 - Temperature is in Kelvin,
 - Pressure is in atmospheres,
-- Density is in g/cm\ :sup:`3` (in 3D).
+- Density is in g/cm\ :sup:`3`.
 
 .. |lammps-unit-systems| raw:: html
 
@@ -56,12 +56,8 @@ where :math:`k_\text{B}` is the Boltzmann constant.
 Start coding
 ------------
 
-Let's fill in the previously created class named Prepare. To facilitate unit
-conversion, we will import |NumPy| and the constants module from |SciPy|.
-
-.. |NumPy| raw:: html
-
-   <a href="https://numpy.org/" target="_blank">NumPy</a>
+Let's fill in the previously created class named *Prepare*. To facilitate unit
+conversion, we will import NumPy and the constants module from |SciPy|.
 
 .. |SciPy| raw:: html
 
@@ -78,7 +74,7 @@ In the file named *Prepare.py*, add the following lines:
 
 .. label:: end_Prepare_class
 
-Four parameters are provided to the *Prepare* class:
+Four atom parameters are provided to the *Prepare* class:
 
 - the atom masses :math:`m`,
 - the LJ parameters :math:`\sigma` and :math:`\epsilon`,
@@ -100,26 +96,26 @@ Modify the *Prepare* class as follows:
                     epsilon, # List - Kcal/mol
                     sigma, # List - Angstrom
                     atom_mass,  # List - g/mol
-                    potential_type="Lennard-Jones",
                     *args,
                     **kwargs):
             self.ureg = ureg
             self.number_atoms = number_atoms
             self.epsilon = epsilon
             self.sigma = sigma
             self.atom_mass = atom_mass
-            self.potential_type = potential_type
             super().__init__(*args, **kwargs)
 
 .. label:: end_Prepare_class
 
-Here, the four lists *number_atoms* :math:`N`, *epsilon* :math:`\epsilon`,
-*sigma* :math:`\sigma`, and *atom_mass* :math:`m` are given default values of
-:math:`10`, :math:`0.1~\text{[Kcal/mol]}`, :math:`3~\text{[Å]}`, and
-:math:`10~\text{[g/mol]}`, respectively.
+Here, *number_atoms* :math:`N`, *epsilon* :math:`\epsilon`,
+*sigma* :math:`\sigma`, and *atom_mass* :math:`m` must be provided as lists
+where the elements have no units, kcal/mol, angstrom, and g/mol units,
+respectively. The units will be enforced with the |Pint| unit registry, *ureg*,
+which must also be provided as a parameter.
+
+.. |Pint| raw:: html
 
-The type of potential is also specified, with Lennard-Jones being chosen as
-the default option.
+   <a href="https://pint.readthedocs.io" target="_blank">Pint</a>
 
 All the parameters are assigned to *self*, allowing other methods to access
 them. The *args* and *kwargs* parameters are used to accept an arbitrary number

docs/source/chapters/chapter4.rst

@@ -47,19 +47,7 @@ minimized energy state.
 Prepare the minimization
 ------------------------
 
-Let us start by importing NumPy and the copy libraries. Add the following
-to the beginning of the *MinimizeEnergy.py* file:
-
-.. label:: start_MinimizeEnergy_class
-
-.. code-block:: python
-
-    import numpy as np
-    import copy
-
-.. label:: end_MinimizeEnergy_class
-
-Then, let us fill the *__init__()* method:
+Let us fill the *__init__()* method:
 
 .. label:: start_MinimizeEnergy_class
 
@@ -154,8 +142,7 @@ class:
             # Measure potential using information about cross coefficients
             sigma_ij = self.sigma_ij_list[Ni]
             epsilon_ij = self.epsilon_ij_list[Ni]
-            energy_potential += np.sum(potentials(self.potential_type,
-                                                  epsilon_ij, sigma_ij, rij))
+            energy_potential += np.sum(potentials(epsilon_ij, sigma_ij, rij))
         return energy_potential
     
 .. label:: end_Utilities_class
@@ -207,8 +194,7 @@ let us create a new method that is dedicated solely to measuring forces:
             # Measure force using information about cross coefficients
             sigma_ij = self.sigma_ij_list[Ni]
             epsilon_ij = self.epsilon_ij_list[Ni]       
-            fij_xyz = potentials(self.potential_type, epsilon_ij,
-                                 sigma_ij, rij, derivative = True)
+            fij_xyz = potentials(epsilon_ij, sigma_ij, rij, derivative = True)
             if return_vector:
                 # Add the contribution to both Ni and its neighbors
                 force_vector[Ni] += np.sum((fij_xyz*rij_xyz.T/rij).T, axis=0)

docs/source/chapters/chapter8.rst

@@ -215,7 +215,6 @@ We need to calculate Lambda:
 
     def calculate_Lambda(self, mass):
         """Estimate the de Broglie wavelength."""
-        m = mass/cst.Avogadro*cst.milli  # kg
         T = self.desired_temperature  # N
         return 1/np.sqrt(2*np.pi*mass*T)
 

docs/source/journal-article.bib

@@ -61,4 +61,27 @@ @book{Rossum2009Python3
  isbn = {1441412697},
  publisher = {CreateSpace},
  address = {Scotts Valley, CA}
-} 
+}
+
+@article{         harris2020array,
+ title         = {Array programming with {NumPy}},
+ author        = {Charles R. Harris and K. Jarrod Millman and St{\'{e}}fan J.
+                 van der Walt and Ralf Gommers and Pauli Virtanen and David
+                 Cournapeau and Eric Wieser and Julian Taylor and Sebastian
+                 Berg and Nathaniel J. Smith and Robert Kern and Matti Picus
+                 and Stephan Hoyer and Marten H. van Kerkwijk and Matthew
+                 Brett and Allan Haldane and Jaime Fern{\'{a}}ndez del
+                 R{\'{i}}o and Mark Wiebe and Pearu Peterson and Pierre
+                 G{\'{e}}rard-Marchant and Kevin Sheppard and Tyler Reddy and
+                 Warren Weckesser and Hameer Abbasi and Christoph Gohlke and
+                 Travis E. Oliphant},
+ year          = {2020},
+ month         = sep,
+ journal       = {Nature},
+ volume        = {585},
+ number        = {7825},
+ pages         = {357--362},
+ doi           = {10.1038/s41586-020-2649-2},
+ publisher     = {Springer Science and Business Media {LLC}},
+ url           = {https://doi.org/10.1038/s41586-020-2649-2}
+}