improved references for binary gcd

Author: thomasWeise

bookbase

@@ -11,17 +11,14 @@ set -o errexit   # set -e : exit the script if any statement returns a non-true
 
 hasOutput=false  # Do we have some output and need a separator?
 
-# Check the versions of the tools and packages.
-for pack in "pytest" "pytest-timeout" "mypy" "ruff" "pylint"; do
-  version="$(python3 -m pip show "$pack" 2>/dev/null || true)"
-  if [ -z "$version" ]; then
-    # pytest or the plugin is not installed, so we install it now.
-    # We do this silently, without printing any information...
-    python3 -m pip install --require-virtualenv "$pack" 1>/dev/null 2>&1
-    version="$(python3 -m pip show "$pack" 2>/dev/null)"
-  fi
+# Make sure that all packages are installed.
+packages=("pytest" "pytest-timeout" "mypy" "ruff" "pylint" "moptipy")
+python3 -m pip install --require-virtualenv "${packages[@]}" 1>/dev/null 2>&1
 
+# Check the versions of the tools and packages.
+for pack in "${packages[@]}"; do
   # For each tool or plugin, we get the version separately.
+  version="$(python3 -m pip show "$pack" 2>/dev/null || true)"
   version="$(grep Version: <<< "$version")"
   version="$(sed -n 's/.*Version:\s*\([.0-9]*\)/\1/p' <<< "$version")"
   if [ -n "$version" ]; then  # ... and we concatenate them

text/front/preface/__dependencyVersionsInner.sh

@@ -242,7 +242,7 @@
 %
 Finally, we confirm that \pythonil{gcd} and \pythonil{math_gcd} compute the same result for four test cases at the bottom of our program.
 Now that all is said and done, it should be mentioned that the Euclidean Algorithm has a particularly efficient binary variant which is faster than our implementation in \cref{lst:functions:def_gcd}.
-This binary variant may have been developed in China in the first century~\pgls{CE}~\cite{B1999FAOTBEA}.
+This binary variant may have been developed in China in the first century~\pgls{CE}~\cite{B1999FAOTBEA} and published in the famous \emph{Jiu Zhang Suanshu}~(九章算术)~\cite{OR2003LH,SCL1999TNCOTMACAC,S1998LHATFGAOCM,D2010AALHOCAS,C2002LFLHADWTDM}.
 
 We are now able, to implement our own functions.
 We can properly annotate them with \pglspl{typeHint} and \pglspl{docstring}.

text/main/controlFlow/functions/functions.tex

@@ -8,5 +8,6 @@
 %
 \hinput{packages}{packages.tex}%
 \hinput{git}{git.tex}%
+\hinput{moptipy}{moptipy.tex}%
 %
 \endhsection%

text/main/ecosystem/ecosystem.tex

@@ -0,0 +1,10 @@
+\hsection{moptipy: Metaheuristic Optimization in Python}%
+%
+\moptipy~\cite{WW2023RSDEWASSAA} is the \emph{Metaheuristic Optimization in \python} package.
+Its core website is \url{https://thomasweise.github.io/moptipy}.
+The package offers different optimization algorithms, experiment execution, and result evaluation facilities.
+It provides two example application areas that can be used for testing algorithms, namely the \pgls{optJSSP}~\cite{W2019JRDAIOTJSSP,WLCW2021SJSSPWUABFGS,WWLC2021FFAMOAIUBTOTOFV} and discrete optimization benchmarks such as those used in~\cite{WWLC2021FFAMOAIUBTOTOFV,WWLCL2023FFAOWBFGSCBE}.
+Its companion package \softwareStyle{moptipyapps}~(\url{https://thomasweise.github.io/moptipyapps}) offers even more example application areas, including the \pgls{optQAP}~\cite{TOvdBLW2024ESTAEFFFA,CWTW2024FFAOWBFGSORLSOTQAP}, the \pgls{optTSP}~\cite{LWLvdBTW2024ATTSPWFFAAHA,LWLvdBW2022STTSPUFFA,LWTWW2024GSIWIFFTTSP}, the two-dimensional bin packing task~\cite{ZLWvdBTW2024RLSOT2RBPPWIR,ZWvdBTLTW2024RLSFTDBPAANRFFFA}, as well as the \pgls{optTTP}~\cite{XWvdBW2024RLSVNVFFAOTTTP}.
+Here we shall briefly outline the structure of this package as well as how it can be used.%
+%
+\endhsection%