example bends generalized

II/Referatas/Makefile

@@ -4,7 +4,7 @@ GEN = $(addsuffix .pdf, \
 		  $(addprefix zeimena-visvalingam-,$(TOLERANCES)))
 
 mj-referatas.pdf: mj-referatas.tex version.tex bib.bib zeimena-pretty.pdf \
-	sinewave-douglas-100.pdf $(GEN)
+	sinewave.pdf sinewave-douglas-5.pdf $(GEN)
 	latexmk -g -pdf $<
 
 define algo2img
@@ -16,13 +16,16 @@ $(1)-$(2)-$(3).pdf: layer2img.py db/.faux_$(1)-$(2)-$(3)
 	./layer2img.py --table=$(1)_$(2)_$(3) --size=52x74 --outfile $(1)-$(2)-$(3).pdf
 endef
 
-$(eval $(call algo2img,sinewave,douglas,100))
+$(eval $(call algo2img,sinewave,douglas,5))
 $(foreach t,$(TOLERANCES),$(eval $(call algo2img,zeimena,douglas,$(t))))
 $(foreach t,$(TOLERANCES),$(eval $(call algo2img,zeimena,visvalingam,$(t))))
 
 sinewave.gpkg: sinewave.py
 	./sinewave.py
 
+sinewave.pdf: sinewave.gpkg
+	./layer2img.py --size=52x15 --infile=$< --outfile=$@
+
 db/.faux_ready: zeimena.gpkg sinewave.gpkg managedb
 	-./managedb stop; rm -fr db
 	./managedb init

II/Referatas/bib.bib

@@ -45,6 +45,14 @@
   publisher={John Wiley and Sons}
 }
 
+@article{miuller1995generalization,
+    title={Generalization-state of the art and issues},
+    author={Miuller, JC and Weibel, R and Lagrange, J and {\"E}alge, F},
+    journal={GIS and Generalisation: Methodology and Practice},
+    pages={3--17},
+    year={1995}
+}
+
 @inproceedings{mcmaster1992generalization,
   title={Generalization in digital cartography},
   author={McMaster, Robert Brainerd and Shea, K Stuart},

II/Referatas/mj-referatas.tex

@@ -52,6 +52,16 @@ connect rivers first to a single polylines:
 ideal hypothesis: mueller algorithm + topology may fully realize cartographic generalization tasks.
 
 what scales and what distances?
+
+= Intro: Aktualumas
+FOSS nėra realizuotas tinkamas kartografinio realizavimo algoritmas (2–3 sakiniai). Kad kartografai turėtų
+įrankį upių generalizavimui.
+
+Bazė: imame tai, ką dabar turi kartografai įrankių paletėj.
+
+Imti mažus upės vingius. Paimti mažas atkarpėles ir palyginti su originalia.
+Todėl, kad nėra kilpų.
+
 \fi
 
 \author{Motiejus Jakštys}
@@ -203,11 +213,11 @@ retained.
 To sum up, both {\VW} and {\DP} simplify the lines, but their cartographic
 output poorly represents lines and bends. Where to look for better output?
 
-\section{Suggested alternative}
+\subsection{Combining bends}
-\label{sec:suggested_alternative}
 
-{\WM} observed how professional cartographers are simplifying rivers and encoded it
+Consecutive small bends should be combined into larger bends, and that is one
-to an algorithm which can be implemented by a computer.
+of the least developed aspects of automatic line generalization, according to
+\cite{miuller1995generalization}. {\WM} encoded this process to an algorithm.
 
 Imagine there are two small bends close to each other, similar to
 figure~\ref{pic:example-bend} on page~\pageref{pic:example-bend}, and one needs
@@ -216,22 +226,20 @@ straight line, but too small to retain both and retain their complexity.
 
 \begin{figure}[h]
     \centering
-    \begin{tikzpicture}[xscale=.5]
+    \includegraphics[width=52mm]{sinewave}
-        \draw (-4,-1) -- (-1, -1);
-        \draw (-1,-1) cos (0,0) sin (1,1) cos (2,0) sin (3,-1) cos (4,0) sin (5,1) cos(6,0) sin (7,-1);
-        \draw (7,-1) -- (10, -1);
-    \end{tikzpicture}
     \caption{Example river bend that should be generalized}
-    \label{pic:example-bend}
+    \label{pic:sinewave}
 \end{figure}
 
-We would imagine 
+When one applies {\DP} to figure~\ref{pic:sinewave}, either both bends remain,
+or become a straight line.
 
-\begin{itemize}
+\begin{figure}[h]
-    \item Describe algorithm by {\WM}.
+    \centering
-    \item Explain how outputs will differ.
+    \includegraphics[width=52mm]{sinewave-douglas-5}
-    \item Explain implementation plan?
+    \caption{Example bend, generalized}
-\end{itemize}
+    \label{pic:sinewave-douglas-5}
+\end{figure}
 
 \section{Related Work and future suggestions}
 \label{sec:related_work}

II/Referatas/sinewave.py

@@ -6,7 +6,7 @@ import geopandas as gpd
 from shapely.geometry import LineString, MultiLineString
 
 INTERVAL = 0.1
-TAIL_LEN = 4
+TAIL_LEN = 10
 SINE_LEN = 7
 
 TAILS = np.zeros(int(TAIL_LEN / INTERVAL))