Add generated files to .gitignore (#84)

* Add generated files to .gitignore * Fix formatting in gaas-map * Format and rewrap .sec files * Move contribution instructions to the end of the list * Added new cookbook address --------- Co-authored-by: Michele Ceriotti <[email protected]>
lab-cosmo · Oct 6, 2024 · f0e68e4 · f0e68e4
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diff --git a/docs/src/.gitignore b/docs/src/.gitignore
@@ -1 +1,2 @@
 sg_execution_times.rst
+all-examples.rst
diff --git a/docs/src/conf.py b/docs/src/conf.py
@@ -5,7 +5,6 @@
 # Add any Sphinx extension module names here, as strings.
 extensions = [
     "sphinx_sitemap",
-    "sphinx_design",
     "sphinx.ext.viewcode",
     "sphinx.ext.intersphinx",
     "sphinx_gallery.load_style",
@@ -34,7 +33,7 @@
 
 html_js_files = [
     (  # plausible.io tracking
-        "https://plausible.io/js/script.file-downloads.hash.outbound-links.pageview-props.tagged-events.js",
+        "https://plausible.io/js/script.file-downloads.hash.outbound-links.pageview-props.tagged-events.js",  # noqa: E501
         {"data-domain": "atomistic-cookbook.org", "defer": "defer"},
     ),
 ]

diff --git a/docs/src/index.rst b/docs/src/index.rst
@@ -16,8 +16,8 @@ then use with conda to create a new environment with all the required dependenci
    # when you want to use the environment
    conda env activate --name <environment-name>
 
-Additional data needed for each example is usually either downloaded 
-dynamically, or can be found in a ``data`` folder for each example, 
+Additional data needed for each example is usually either downloaded
+dynamically, or can be found in a ``data`` folder for each example,
 or downloaded as a ``data.zip`` file at the end of each recipe in
 the website.
 
@@ -26,8 +26,8 @@ Table of contents
 
 .. toctree::
    :maxdepth: 1
-
-   contributing
+
    topics/index
    software/index
    all-examples
+   contributing
diff --git a/docs/src/software/.gitignore b/docs/src/software/.gitignore
@@ -0,0 +1,2 @@
+*.rst
+!index.rst
diff --git a/docs/src/software/chemiscope.sec b/docs/src/software/chemiscope.sec
@@ -3,16 +3,14 @@
 chemiscope
 ==========
 
-Chemiscope is a tool for interactive exploration of databases of 
-materials and molecules, correlating local and global structural 
-representations with the properties of the systems.
-Chemiscope files can be viewed 
-`online <https://chemiscope.org/>`_, generated using a
-`python library <https://pypi.org/project/chemiscope/>`_ and
-used inside jupyter notebooks or sphinx documentations, which
-is how it's used in the cookbook examples. 
-You can check the `documentation <https://chemiscope.org/docs/>`_ and the 
-`github repository <https://github.com/lab-cosmo/chemiscope>`_.
+Chemiscope is a tool for interactive exploration of databases of materials and
+molecules, correlating local and global structural representations with the
+properties of the systems. Chemiscope files can be viewed `online
+<https://chemiscope.org/>`_, generated using a `python library
+<https://pypi.org/project/chemiscope/>`_ and used inside jupyter notebooks or
+sphinx documentations, which is how it's used in the cookbook examples. You can
+check the `documentation <https://chemiscope.org/docs/>`_ and the `github
+repository <https://github.com/lab-cosmo/chemiscope>`_.
 
 - examples/roy-gch/roy-gch
 - examples/gaas-map/gaas-map

diff --git a/docs/src/software/cp2k.sec b/docs/src/software/cp2k.sec
@@ -1,10 +1,9 @@
 cp2k
 ====
 
-CP2K is a quantum chemistry and solid state physics software package 
-that can perform atomistic simulations of solid state, liquid, 
-molecular, periodic, material, crystal, and biological systems.
-Learn more about it on its 
-`homepage <https://cp2k.org>`_.
+CP2K is a quantum chemistry and solid state physics software package that can
+perform atomistic simulations of solid state, liquid, molecular, periodic,
+material, crystal, and biological systems. Learn more about it on its `homepage
+<https://cp2k.org>`_.
 
 - examples/batch-cp2k/reference-trajectory
diff --git a/docs/src/software/i-pi.sec b/docs/src/software/i-pi.sec
@@ -1,13 +1,12 @@
 i-PI
 ====
 
-i-PI is a universal force engine interface written in Python, 
-designed to be used together with an ab-initio, machine-learned, 
-or force-field based evaluation of the interactions between the 
-atoms. You can see learn more about it on the
-`ipi-code website <http://ipi-code.org>`_, the
-`documentation pages <http://ipi-code.org/i-pi>`_ or
-`the github repository <https://github.com/i-pi/i-pi>`_.
+i-PI is a universal force engine interface written in Python, designed to be
+used together with an ab-initio, machine-learned, or force-field based
+evaluation of the interactions between the atoms. You can see learn more about
+it on the `ipi-code website <http://ipi-code.org>`_, the `documentation pages
+<http://ipi-code.org/i-pi>`_ or `the github repository
+<https://github.com/i-pi/i-pi>`_.
 
 
 - examples/path-integrals/path-integrals

diff --git a/docs/src/software/lammps.sec b/docs/src/software/lammps.sec
@@ -1,13 +1,11 @@
 LAMMPS
 ======
 
-LAMMPS is a classical molecular dynamics (MD) code, with a 
-focus on materials simulations. It includes a wealth of interatomic
-potentials, and of basic and advanced molecular simulations
-techniques, and is highly parallelized using an efficient
-domain decomposition scheme.
-Learn more about LAMMPS on its 
-`homepage <https://www.lammps.org>`_.
+LAMMPS is a classical molecular dynamics (MD) code, with a focus on materials
+simulations. It includes a wealth of interatomic potentials, and of basic and
+advanced molecular simulations techniques, and is highly parallelized using an
+efficient domain decomposition scheme. Learn more about LAMMPS on its `homepage
+<https://www.lammps.org>`_.
 
 - examples/path-integrals/path-integrals
 - examples/heat-capacity/heat-capacity
diff --git a/docs/src/software/plumed.sec b/docs/src/software/plumed.sec
@@ -1,15 +1,13 @@
 PLUMED
 ======
 
-PLUMED is an open-source, community-developed library that provides 
-a wide range of different methods, which include enhanced-sampling 
-algorithms, free-energy methods, tools to analyze the vast amounts 
-of data produced by molecular dynamics (MD) simulations.
-These techniques can be used in combination with a large toolbox of 
-collective variables that describe complex processes in physics, 
-chemistry, material science, and biology.
-Documentation, examples and installation instructions for the various
-packages are discussed on the
-`PLUMED website <http://plumed.org>`_.
+PLUMED is an open-source, community-developed library that provides a wide range
+of different methods, which include enhanced-sampling algorithms, free-energy
+methods, tools to analyze the vast amounts of data produced by molecular
+dynamics (MD) simulations. These techniques can be used in combination with a
+large toolbox of collective variables that describe complex processes in
+physics, chemistry, material science, and biology. Documentation, examples and
+installation instructions for the various packages are discussed on the `PLUMED
+website <http://plumed.org>`_.
 
 - examples/pi-metad/pi-metad
diff --git a/docs/src/software/rascaline.sec b/docs/src/software/rascaline.sec
@@ -1,14 +1,12 @@
 rascaline
 =========
 
-Rascaline is a library for the efficient computing of representations 
-for atomistic machine learning also called “descriptors” or “fingerprints”. 
-These representation can be used for atomistic machine learning (ML) models 
-including ML potentials, visualization or similarity analysis.
-You can learn how to use it reading the 
-`documentation <https://luthaf.fr/rascaline/>`_, and get the latest
-version from the 
-`github repository <https://github.com/Luthaf/rascaline>`_
+Rascaline is a library for the efficient computing of representations for
+atomistic machine learning also called “descriptors” or “fingerprints”. These
+representation can be used for atomistic machine learning (ML) models including
+ML potentials, visualization or similarity analysis. You can learn how to use it
+reading the `documentation <https://luthaf.fr/rascaline/>`_, and get the latest
+version from the `github repository <https://github.com/Luthaf/rascaline>`_
 
 - examples/gaas-map/gaas-map
 - examples/lpr/lpr

diff --git a/docs/src/software/scikit-matter.sec b/docs/src/software/scikit-matter.sec
@@ -1,16 +1,14 @@
 scikit-matter
 =============
 
-scikit-matter is a toolbox of methods developed in the computational chemical 
-and materials science community, following the scikit-learn API and coding 
+scikit-matter is a toolbox of methods developed in the computational chemical
+and materials science community, following the scikit-learn API and coding
 guidelines to promote usability and interoperability with existing workflows.
-You can get the latest version from its
-`github repository <https://github.com/scikit-learn-contrib/scikit-matter>`_
-and learn how to use it from its
-`documentation <https://scikit-matter.readthedocs.io/en/latest/>`_.
+You can get the latest version from its `github repository
+<https://github.com/scikit-learn-contrib/scikit-matter>`_ and learn how to use
+it from its `documentation <https://scikit-matter.readthedocs.io/en/latest/>`_.
 
 - examples/sample-selection/sample-selection
 - examples/roy-gch/roy-gch
 - examples/lpr/lpr
 - examples/gaas-map/gaas-map
-
diff --git a/docs/src/topics/.gitignore b/docs/src/topics/.gitignore
@@ -0,0 +1,2 @@
+*.rst
+!index.rst
diff --git a/docs/src/topics/ml-models.sec b/docs/src/topics/ml-models.sec
@@ -1,9 +1,9 @@
 Machine learning models
 =======================
 
-This section contains recipes that concern the training of 
-machine-learning models, or the pre-processing of data to 
-optimize the model architecture or data. 
+This section contains recipes that concern the training of machine-learning
+models, or the pre-processing of data to optimize the model architecture or
+data.
 
 - examples/dos-align/dos-align
 - examples/lode-linear/lode-linear

diff --git a/docs/src/topics/nqes.sec b/docs/src/topics/nqes.sec
@@ -1,11 +1,10 @@
 Nuclear quantum effects
 =======================
 
-Most atomistic simulations treat nuclei as classical particles,
-that sample a Boltzmann distribuion. This approximation breaks
-down for light nuclei (hydrogen above all) and high-frequency 
-vibrations, requiring more sophisticated statistical sampling
-to compute accurate statistical and dynamical properties.
+Most atomistic simulations treat nuclei as classical particles, that sample a
+Boltzmann distribution. This approximation breaks down for light nuclei
+(hydrogen above all) and high-frequency vibrations, requiring more sophisticated
+statistical sampling to compute accurate statistical and dynamical properties.
 
 - examples/path-integrals/path-integrals
 - examples/pi-metad/pi-metad

diff --git a/docs/src/topics/sampling.sec b/docs/src/topics/sampling.sec
@@ -2,7 +2,7 @@ Statistical sampling and dynamics
 =================================
 
 This section contains recipes that compute thermodynamic averages by sampling,
-evaluates dynamical properties, or otherwise computes the properties of a 
+evaluates dynamical properties, or otherwise computes the properties of a
 set of configurations of an atomistic system.
 
 - examples/path-integrals/path-integrals

diff --git a/examples/gaas-map/gaas-map.py b/examples/gaas-map/gaas-map.py
@@ -33,6 +33,7 @@
 from skmatter.decomposition import PCovR
 from skmatter.preprocessing import StandardFlexibleScaler
 
+
 # sphinx_gallery_thumbnail_number = 2
 
 ######################################################################