Brett 2024-02-16 00:36:38 -05:00
parent ddc22c7ca1
commit 0f03b172b0
9 changed files with 70 additions and 50 deletions

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Subproject commit 558ed1e0fdc147551d004891dda6dd3b24f61aa2
Subproject commit 68f6a0af44fe8ba5044a7f37b8bac9809ab709f1

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@ -44,7 +44,7 @@
title=\lstname, % show the filename of files included with \lstinputlisting; also try caption instead of title
columns=fixed % Using fixed column width (for e.g. nice alignment)
}
\lstMakeShortInline$
\lstMakeShortInline|
\newtcolorbox{answerbox}[2][]{%
attach boxed title to top center
@ -190,7 +190,16 @@ The best average fitness of all the tests was 0.19384 using 0.9 crossover and 0.
\end{center}
\section{Compiling / Executing}
This assignment was made for linux using GCC 13.2.0, however any C++17 compliant compiler should work.
The minimum GCC version appears to be 8.5, meaning this assignment can be built on sandcastle.
\begin{lstlisting}
cd your_path_to_this_source/
mkdir build
cd build
cmake ../
make -j 32
\end{lstlisting}
The actual assignment executable is called |Assignment_1| while the automatic run system is called |Assignment_1_RUNNER|. |Assignment_1_RUNNER| has a help menu with options but the defaults will work assuming you run from the build directory and are using part b only. If you want to build for Part A run |cmake -DPART_B=OFF| and run |Assignment_1_RUNNER| with |-b|
\end{document}

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\contentsline {section}{\numberline {1}Symbolic regression}{2}{section.0.1}%
\contentsline {subsection}{\numberline {1.1}Introduction}{2}{subsection.0.1.1}%
\contentsline {subsection}{\numberline {1.2}Parameter Table}{2}{subsection.0.1.2}%
\contentsline {subsection}{\numberline {1.3}Fitness Evaluation}{2}{subsection.0.1.3}%
\contentsline {subsection}{\numberline {1.4}Fitness Plots}{3}{subsection.0.1.4}%
\contentsline {subsection}{\numberline {1.5}Analysis And Conclusion}{4}{subsection.0.1.5}%
\contentsline {section}{\numberline {2}Rice Classification}{4}{section.0.2}%
\contentsline {section}{\numberline {3}Compiling / Executing}{4}{section.0.3}%
\contentsline {section}{\numberline {1}Introduction}{2}{section.0.1}%
\contentsline {section}{\numberline {2}Symbolic regression}{2}{section.0.2}%
\contentsline {subsection}{\numberline {2.1}Introduction}{2}{subsection.0.2.1}%
\contentsline {subsection}{\numberline {2.2}Parameter Table}{2}{subsection.0.2.2}%
\contentsline {subsection}{\numberline {2.3}Fitness Evaluation}{2}{subsection.0.2.3}%
\contentsline {subsection}{\numberline {2.4}Fitness Plots}{3}{subsection.0.2.4}%
\contentsline {subsection}{\numberline {2.5}Analysis And Conclusion}{4}{subsection.0.2.5}%
\contentsline {section}{\numberline {3}Rice Classification}{4}{section.0.3}%
\contentsline {subsection}{\numberline {3.1}Introduction}{4}{subsection.0.3.1}%
\contentsline {subsection}{\numberline {3.2}Parameter Table}{4}{subsection.0.3.2}%
\contentsline {section}{\numberline {4}Compiling / Executing}{4}{section.0.4}%

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@ -411,13 +411,13 @@ extern "C" int app_initialize(int startfromcheckpoint)
app_fitness_cases[5] = (double*) MALLOC(fitness_cases * sizeof(double));
app_fitness_cases[6] = (double*) MALLOC(fitness_cases * sizeof(double));
app_fitness_cases[7] = (double*) MALLOC(fitness_cases * sizeof(double));
auto data = rice_data.getTrainingSet(fitness_cases);
#else
app_fitness_cases[0] = (double*) MALLOC(fitness_cases * sizeof(double));
app_fitness_cases[1] = (double*) MALLOC(fitness_cases * sizeof(double));
#endif
oprintf(OUT_PRG, 50, "%d fitness cases:\n", fitness_cases);
auto data = rice_data.getTrainingSet(fitness_cases);
for (i = 0; i < fitness_cases; ++i)
{
#ifndef PART_B