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IV/bib.bib
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IV/bib.bib
@ -150,3 +150,22 @@
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year={1974},
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publisher={Elsevier}
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}
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@article{knuth1976big,
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title={Big omicron and big omega and big theta},
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author={Knuth, Donald E},
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journal={ACM Sigact News},
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volume={8},
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number={2},
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pages={18--24},
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year={1976},
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publisher={ACM New York, NY, USA}
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}
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@book{bachmann1894analytische,
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title={Die analytische zahlentheorie},
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author={Bachmann, Paul},
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volume={2},
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year={1894},
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publisher={Teubner}
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}
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137
IV/mj-msc.tex
137
IV/mj-msc.tex
@ -183,7 +183,7 @@ thus convenient to analyze for both small and large scale generalization.
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\begin{figure}[h]
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\centering
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\includegraphics[width=\textwidth]{salvis-25k}
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\caption{Example rivers for visual tests (1:25000)}
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\caption{Example rivers for visual tests (1:25000).}
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\label{fig:salvis-25}
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\end{figure}
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@ -197,15 +197,15 @@ river for a smaller scale is worthy.
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\centering
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{salvis-50k}
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\caption{Example scaled 1:50000}
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\caption{Example scaled 1:50000.}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{.49\textwidth}
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\centering
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\includegraphics[width=.2\textwidth]{salvis-250k}
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\caption{Example scaled 1:250000}
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\caption{Example scaled 1:250000.}
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\end{subfigure}
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\caption{Down-scaled original river (1:50000 and 1:250000)}
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\caption{Down-scaled original river (1:50000 and 1:250000).}
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\label{fig:salvis-50-250}
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\end{figure}
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@ -276,6 +276,7 @@ many cases, corner cases are discussed and clarified.
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Assume Euclidean geometry throughout this document, unless noted otherwise.
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\subsection{Vocabulary and terminology}
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\label{sec:vocab}
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This section defines vocabulary and terms as defined in the rest of the paper.
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@ -289,7 +290,7 @@ This section defines vocabulary and terms as defined in the rest of the paper.
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$(x_2, y_2)$. Line Segment and Segment are used interchangeably
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throughout the paper.
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\item[Line] (or \textsc{linestring}) represents a single linear feature in
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\item[Line], or \textsc{linestring}, represents a single linear feature in
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the real world. For example, a river or a coastline.
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Geometrically, A line is a series of connected line segments, or,
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@ -305,6 +306,16 @@ This section defines vocabulary and terms as defined in the rest of the paper.
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\item[Sum of inner angles] TBD.
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\item[Algorithmic Complexity] also called \textsc{big o notation}, is a
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relative measure to explain how long will the algorithm run depending
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on it's input. For example, given $n$ objects and time complexity of
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$O(n)$, the time it takes to execute the algorithm is proportional to
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$n$. Conversely, if complexity is $O(n^2)$, then the time it takes to
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execute the algorithm is quadratic. $O$ notation was first suggested by
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Bachmann\cite{bachmann1894analytische} in late XIX'th century, and
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adopted for computer science by Donald Knuth\cite{knuth1976big} in
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1970s.
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\end{description}
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\subsection{Radians and Degrees}
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@ -341,7 +352,7 @@ figure~\ref{fig:test-figures}.
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\begin{figure}[h]
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\centering
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\includegraphics[width=\textwidth]{test-figures}
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\caption{Line geometries for automated test cases}
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\caption{Line geometries for automated test cases.}
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\label{fig:test-figures}
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\end{figure}
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@ -349,6 +360,25 @@ The full test suite can be executed with a single command, and completes in a
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few seconds. Having an easily accessible test suite boosts confidence that no
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unexpected bugs have snug in while modifying the algorithm.
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\subsection{Reproducing generalizations in this paper}
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\label{sec:reproducing-the-paper}
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It is widely believed that the ability to reproduce the results of a published
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study is important to the scientific community. In practice, however, it is
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often hard to impossible: research methodologies, as well as algorithms
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themselves, are explained in prose, which, due to the nature of the non-machine
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language, lends itself to inexact interpretations.
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This article, besides explaining the algorithm in prose, \emph{includes} the
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program of the algorithm in a way that can be executed on reader's workstation.
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On top of it, all the illustrations in this paper are generated using that
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algorithm, from a predefined list of test geometries (test geometries were
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explained in section~\ref{sec:automated-tests}).
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Instructions how to re-generate all the visualizations are found in
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appendix~\ref{sec:code-regenerate}. The visualization code serves as a good
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example reference for anyone willing to start using the algorithm.
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\section{Description of the implementation}
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Like alluded in section~\ref{sec:introduction}, {\WM} paper skims over
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@ -411,7 +441,7 @@ but with bends colored as polygons: each color is a distinctive bend.
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\begin{figure}[h]
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\centering
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\includegraphics[width=\textwidth]{fig8-definition-of-a-bend}
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\caption{Originally figure 8: detected bends are highlighted}
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\caption{Originally figure 8: detected bends are highlighted.}
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\label{fig:fig8-definition-of-a-bend}
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\end{figure}
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@ -431,14 +461,14 @@ when a single vertex is moved outwards the end of the bend.
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\centering
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{fig5-gentle-inflection-before}
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\caption{Before applying the inflection rule}
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\caption{Before applying the inflection rule.}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{fig5-gentle-inflection-after}
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\caption{After applying the inflection rule}
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\caption{After applying the inflection rule.}
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\end{subfigure}
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\caption{Originally figure 5: gentle inflections at the ends of the bend}
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\caption{Originally figure 5: gentle inflections at the ends of the bend.}
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\label{fig:fig5-gentle-inflection}
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\end{figure}
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@ -458,15 +488,15 @@ vertices to the next bend.
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\centering
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{inflection-1-gentle-inflection-before}
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\caption{Before applying the inflection rule}
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\caption{Before applying the inflection rule.}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{inflection-1-gentle-inflection-after}
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\caption{After applying the inflection rule}
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\caption{After applying the inflection rule.}
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\end{subfigure}
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\caption{Gentle inflection at the end of the bend when multiple vertices
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are moved}
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are moved.}
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\label{fig:inflection-1-gentle-inflection}
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\end{figure}
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@ -494,58 +524,65 @@ The "quite small angle" was arbitrarily chosen to $\smallAngle$.
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\subsection{Self-line Crossing When Cutting a Bend}
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When bend's baseline crosses another bend, it is called self-crossing.
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Self-crossing is undesirable in the upcoming operators, thus should be removed
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following the rules of the article.
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Self-crossing is undesirable for the upcoming bend manipulation operators, thus
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should be removed. There are a few rules on when and how they should be removed
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--- this section explains them in higher detail, discusses their time
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complexity and applied optimizations. Figure~\ref{fig:fig6-selfcrossing} is
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copied from the original article.
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\begin{figure}[h]
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\centering
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{fig6-selfcrossing-before}
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\caption{Bend's baseline (dotted) is crossing a neighboring bend}
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\caption{Bend's baseline (dotted) is crossing a neighboring bend.}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{fig6-selfcrossing-after}
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\caption{Self-crossing removed following the algorithm}
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\caption{Self-crossing removed.}
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\end{subfigure}
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\caption{Originally figure 6: simple case of self-line crossing}
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\caption{Originally figure 6: simple case of self-line crossing.}
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\label{fig:fig6-selfcrossing}
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\end{figure}
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The original description does not go into detail which bends may self-cross, and which <TBD>
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The self-line-crossing may happen not by the neighboring bend, but by any other
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bend in the line. For example, the baseline of the bend may cross different
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bends in between, as depicted in figure~\ref{fig:selfcrossing-1-non-neighbor}.
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\begin{figure}[h]
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\centering
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{selfcrossing-1-before}
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\caption{Bend's baseline (dotted) is crossing a non-neighboring bend}
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\caption{Bend's baseline (dotted) is crossing a non-neighboring bend.}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{.49\textwidth}
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\includegraphics[width=\textwidth]{selfcrossing-1-after}
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\caption{Self-crossing removed following the algorithm}
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\caption{Self-crossing removed.}
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\end{subfigure}
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\caption{Self-crossing with non-neighboring bend}
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\caption{Self-crossing with non-neighboring bend.}
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\label{fig:selfcrossing-1-non-neighbor}
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\end{figure}
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Naively implemented, checking every bend with every bend is costs $O(n^2)$. In
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other words, the time it takes to run the algorithm grows quadratically with
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the with the number of vertices.
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Looking at the {\WM} paper alone, it may seem like self-crossing may happen
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only with the neighboring bend. This would mean an efficient $O(n)$
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implementation\footnote{where $n$ is the number of bends in a line. See
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explanation of \textsc{algorithmic complexity} in section~\ref{sec:vocab}.}.
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However, as one can see in figure~\ref{fig:selfcrossing-1-non-neighbor}, it may
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not be the case: any other bend in the line may be crossing it.
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It is possible to optimize this step and skip checking some of the bends. Only
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bends whose sum of inner angles is $\pi$ can ever self-cross. If the value is
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less than $\pi$, it cannot cross other bends. That way, only a fraction of
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bends need to be checked.
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If one translates the requirements to code in a straightforward way, it would
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be quite computationally expensive: naively implemented, complexity of checking
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every bend with every bend is $O(n^2)$. In other words, the time it takes to
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run the algorithm grows quadratically with the with the number of vertices.
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It is possible to optimize this step and skip checking most of the bends. Only
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bends whose sum of inner angles is larger than $\pi$ can ever self-cross. If
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the value is less than $\pi$, it cannot cross other bends. That way, only a
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fraction of bends need to be checked. The worst-case complexity is still
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$O(n^2)$, when all bends' inner angles are larger than $\pi$, but, assuming no
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more than $20\%$ of the bends' inner angles are larger than $\pi$, the time it
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takes to run this piece of the algorithm drops by $80\%$.
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\subsection{Attributes of a Single Bend}
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\textsc{Compactness Index} is "the ratio of the area of the polygon over the
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circle whose circumference length is the same as the length of the
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circumference of the polygon" \cite{wang1998line}. Given a bend, its
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@ -555,10 +592,10 @@ compactness index is calculated as follows:
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\item Construct a polygon by joining first and last vertices of the bend.
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\item Calculate area of the polygon $P$.
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\item Calculate area of the polygon.
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\item Calculate perimeter of the polygon $u$. The same value is the
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circumference of the circle.
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\item Calculate perimeter $u$ of the polygon. The same value is the
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circumference of the circle.
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\item Given circle's perimeter $u$, circle's area $A$ is:
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@ -599,8 +636,8 @@ Two conditions must be true to claim that a bend is isolated:
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\begin{enumerate}
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\item \textsc{average curvature} of neighboring bends, should be larger
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than the "candidate" bend's curvature; this implementation arbitrarily
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chose $\isolationThreshold$.
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than the "candidate" bend's curvature. The article did not offer a
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value, this implementation arbitrarily chose $\isolationThreshold$.
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\item Bends on both sides of the "candidate" should be longer than a
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certain value. This implementation does not (yet) define such a
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@ -617,7 +654,7 @@ To find out whether two bends are similar, they are compared by 3 components:
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\item Baseline length
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\end{enumerate}
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These 3 components represent a point in the 3-dimensional space, and Euclidean
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Components 1, 2 and 3 represent a point in a 3-dimensional space, and Euclidean
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distance $d$ between those is calculated to differentiate between bends $p$ and
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$q$:
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@ -627,7 +664,7 @@ $q$:
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(baseline_p-baseline_q)^2}
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\]
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The more similar the bends are, the smaller the distance $d$.
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The smaller the distance $d$, the more similar the bends are.
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\subsection{Elimination Operator}
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@ -651,19 +688,17 @@ The more similar the bends are, the smaller the distance $d$.
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\section{Code listings}
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\subsection{Reproducing the generalizations in this paper}
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\subsection{Re-generating this paper}
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\label{sec:code-regenerate}
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We strongly believe in the ability to reproduce the results is critical for any
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scientific work. To make it possible for this paper, all source files and
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accompanying scripts have been attached to the PDF. To re-generate this
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document and its accompanying graphics, run this script (assuming name of
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this document is {\tt mj-msc-full.pdf}):
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Like explained in section~\ref{sec:reproducing-the-paper}, illustrations in
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this paper are generated from a small list of sample geometries. To observe
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the source geometries or regenerate this paper, run this script (assuming
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name of this document is {\tt mj-msc-full.pdf}):
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\inputcode{bash}{extract-and-generate}
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This was tested on Linux Debian 11 with upstream packages only.
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\subsection{Algorithm code listings}
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%\subsection{Algorithm code listings}
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%\inputcode{postgresql}{wm.sql}
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\end{appendices}
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