Add a bit more information to the experiments section.

2 files changed, 37 insertions, 7 deletions

diff --git a/sampling_alg_lac2020/LAC-20.tex b/sampling_alg_lac2020/LAC-20.tex
index f20f2cf..d0824c1 100644
--- a/sampling_alg_lac2020/LAC-20.tex
+++ b/sampling_alg_lac2020/LAC-20.tex
@@ -468,28 +468,58 @@ Note that by traversing the samples in order of their distance to $p$ (which is
 
 \section{Experiments}
 \todoandre{Talk about the setup.}
-We conducted experiments with the implementation of the new sampling algorithm in DrumGizmo.
-As a comparison we use the previous sample selection algorithm of DrumGizmo.
-To get experiments that show how the sample selection algorithm performs in practice, we use the drum kits of DrumGizmo. We do experiments on three different drum kits. See Figure \ref{fig:drumkit_data} and Table \ref{tab:drumkit_data} for some information about the samples of the drum kits and a visualization of the power level distribution of the different kits.
-
-\todoandre{Talk about what the experiments should show: two close samples are chosen similarly often; playing the same MIDI note plays a reasonably varied sample set; average distance of one sample}
+To conduct the experiments, we use the implementation of the new sampling algorithm in DrumGizmo.
+As a base-line for comparison, we use the previous sample selection algorithm of DrumGizmo.
+We want to evaluate how the sample selection algorithm performs in practice, therefore we use the drum kits of DrumGizmo. In particular, we use the power value distribution of the samples of those kits.
+We do experiments on three different drum kits. See Table \ref{tab:drumkit_data} for some information about the samples of the drum kits and see Figure \ref{fig:power_level_distribution} for a visualization of the power level distribution of the kits.
+
+\begin{table}
+\caption{Drum kit data.}
+\label{tab:drumkit_data}
+\centering
+\begin{tabular}{|l||rr|}
+\hline
+name & number of snare samples & \\
+\hline
+DRS kit & 234 & \\
+other kit & 234 & \\
+and other kit & 234 & \\
+\hline
+\end{tabular}
+\end{table}
+
+\begin{figure}
+	\includegraphics[width=.8\linewidth]{figures/power_level_distribution.pdf}
+	\caption{This shows the power value distribution of the different drum kits.}
+	\label{fig:power_level_distribution}
+\end{figure}
+
+% \todoandre{Talk about what the experiments should show: two close samples are chosen similarly often; playing the same MIDI note plays a reasonably varied sample set; average distance of one sample}
 We want to test the following hypotheses with our experiments:
 \begin{enumerate}
 	\item Two samples with similar power values are chosen similarly often.
 	\item Playing the same MIDI note over and over again plays a reasonably varied set of samples.
 	\item Average distance of one sample \todo{what did I want to say with that?}
 \end{enumerate}
-\todoandre{Experiments are: playing fast sweeps (with multiple hits per velocity); playing a single note over and over again at the same velocity; sound examples that people can listen to online?}
+% \todoandre{Experiments are: playing fast sweeps (with multiple hits per velocity); playing a single note over and over again at the same velocity; sound examples that people can listen to online?}
 To test the above hypotheses, we conduct the following experiments:
 \begin{enumerate}
 	\item Playing fast sweeps over the whole velocity range.
 	\item Playing a single note at high velocity.
+	\item Audio recordings of the processes
 \end{enumerate}
 
 \todoandre{Do beautiful tables and plots here}
 
 \todoandre{Also do an experiment regarding the adaptive search}
-To also experimentally test the performance of the new sampling algorithm, we want to see how many sample power values are evaluated per query. Especially, we expect that the smart search optimization described at the end of Section \label{sec:implementation} reduces the number of evaluations significantly.
+To also get an idea of the performance of the new sampling algorithm, we want to see how many power values of samples are evaluated per query.
+Without the smart search optimization described at the end of Section \ref{sec:implementation}, this number would always be the number of samples. However, we expect that the smart search optimization significantly reduces the number of evaluations. To test this hypothesis, we take the above experiment and look at the number of evaluations. You can see the histogram in Figure \ref{fig:evaluations_histogram}. \todo{fix}
+
+\begin{figure}
+	% \includegraphics[width=.8\linewidth]{figures/evaluations_histogram.pdf}
+	\caption{This plot shows the histogram of the number of evaluations of power values for the queries of experiment bla.\todo{insert correct information}}
+	\label{fig:evaluations_histogram}
+\end{figure}
 
 \todoandre{Summarize experiments}
 
diff --git a/sampling_alg_lac2020/figures/power_level_distribution.pdf b/sampling_alg_lac2020/figures/power_level_distribution.pdf
new file mode 100644
index 0000000..4699f06
--- /dev/null
+++ b/sampling_alg_lac2020/figures/power_level_distribution.pdf