Add windowed vs whole plot

src/qec-meeting-presentation/main.tex

@@ -238,10 +238,63 @@ decorations.pathreplacing, calc}
 \begin{frame}
     \frametitle{An ``Upper Bound'' on the Performance}
 
-    \begin{itemize}
+    \begin{minipage}{0.65\textwidth}
-        \item \red{Whole vs windowed for min sum and spa, different
+        \begin{figure}[H]
-            window sizes }
+            % \centering
-    \end{itemize}
+            \hspace*{-8mm}
+            \begin{tikzpicture}
+                \begin{axis}[
+                        width=10cm,
+                        height=8cm,
+                        ymode=log,
+                        ylabel={LER},
+                        xlabel={Physical error rate},
+                        legend pos=south east,
+                        legend style={
+                            cells={anchor=west},
+                            cells={align=left},
+                        },
+                        xticklabel style={/pgf/number format/fixed},
+                        xticklabel style={/pgf/number format/precision=4},
+                        scaled x ticks=false,
+                        grid,
+                        xtick={0.001,0.0015,...,0.004},
+                        xmin=0.001, xmax=0.004,
+                    ]
+
+                    \addplot+[NavyBlue, mark=none, line width=1pt]
+                    table[col sep=comma, x=p, y=LER_sw]
+                    {res/whole_vs_windowed_spa.csv};
+                    \addlegendentry{Windowed - SPA}
+
+                    \addplot+[BurntOrange, mark=none, line width=1pt]
+                    table[col sep=comma, x=p, y=LER_sw]
+                    {res/whole_vs_windowed_min_sum.csv};
+                    \addlegendentry{Windowed - Min-Sum}
+
+                    \addplot+[NavyBlue, mark=none, line width=1pt,
+                    densely dashed]
+                    table[col sep=comma, x=p, y=LER_whole]
+                    {res/whole_vs_windowed_spa.csv};
+                    \addlegendentry{Whole - SPA}
+
+                    \addplot+[BurntOrange, mark=none, line width=1pt,
+                    densely dashed]
+                    table[col sep=comma, x=p, y=LER_whole]
+                    {res/whole_vs_windowed_min_sum.csv};
+                    \addlegendentry{Whole - Min-Sum}
+
+                \end{axis}
+            \end{tikzpicture}
+        \end{figure}
+    \end{minipage}%
+    \begin{minipage}{0.35\textwidth}
+        \begin{itemize}
+            \item $[[144,12,12]]$ BB code
+            \item $n_\text{rounds} = 12$
+            \item $W=3$, $F=1$
+        \end{itemize}
+    \end{minipage}
 \end{frame}
 
 \begin{frame}
@@ -272,11 +325,8 @@ decorations.pathreplacing, calc}
     \vspace*{15mm}
 
     \begin{itemize}
-        \item Deeper investigation into difference between hard- and
+        \item Look at behavior during iterations
-            soft-info decoding for BP
         \item Move from BP to BPGD
-        \item Spend much more effort to decode first window (inspired
-            by rate-loss of SC-LDPC codes in first window)
 
             \vspace{15mm}
 
@@ -287,5 +337,21 @@ decorations.pathreplacing, calc}
     \end{itemize}
 \end{frame}
 
+% TODOs
+% - Whole vs windowed for min sum and spa
+%    - Basic implementation
+%    - Choose parameters (e.g., window sizes)
+% - soft vs hard for min sum and spa (4 plots)
+%    - Basic implementation
+%    - Choose parameters (e.g., window sizes)
+% - Comparison of numbers of iterations for soft vs hard
+%    - Basic implementation (more or less done)
+%    - Choose parameters
+% - Convergence analysis
+%    - Basic implementation (more or less done)
+%    - Choose parameters
+% - Make sure min sum vs spa question makes sense
+% - Think of a few words for each slide (and take notes)
+
 \end{document}
 

src/qec-meeting-presentation/res/whole_vs_windowed_min_sum.csv

@@ -0,0 +1,8 @@
+p,LER_whole,LER_sw
+0.001,0.046,0.086
+0.0015,0.11,0.2
+0.002,0.185,0.345
+0.0025,0.346,0.546
+0.003,0.587,0.721
+0.0035,0.732,0.852
+0.004,0.871,0.941

src/qec-meeting-presentation/res/whole_vs_windowed_spa.csv

@@ -0,0 +1,8 @@
+p,LER_whole,LER_sw
+0.001,0.072,0.101
+0.0015,0.128,0.234
+0.002,0.213,0.352
+0.0025,0.374,0.517
+0.003,0.544,0.676
+0.0035,0.711,0.823
+0.004,0.83,0.905