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Add plots to appendix for defending choice of bin numbers to calculate sigma

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Dennis Huben 2024-09-05 16:52:10 +02:00
parent d821e818bf
commit 2a6d9ae388
1 changed files with 19 additions and 4 deletions

23
main.tex
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@ -654,7 +654,7 @@ To confirm that the $\sigma$ parameter estimated from the fit is indeed a good m
\label{noiseparameters2}
\end{figure}
We tried several different bin sizes (30 to 300 bins) and spike widths. There was little difference between the different parameters (see appendix).
We tried several different bin sizes (30 to 300 bins) and spike widths. There was little difference between the different parameters (see figure \ref{sigma_bins} in appendix).
\section*{Electric fish as a real world model system}
@ -755,9 +755,6 @@ and \ref{fig:popsizenarrow10} C), the ratio of coding fraction in a large popula
to the coding fraction in a single cell is larger for higher frequencies.
%simulation plots are from 200hz/nice coherence curves.ipynb
\begin{figure}
\centering
broad
@ -768,6 +765,24 @@ to the coding fraction in a single cell is larger for higher frequencies.
\includegraphics[width=0.48\linewidth]{img/fish/cf_curves/cfN_broad_3.pdf}
\end{figure}
%compare_params_300.py auf oilbird
\begin{figure}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins100v300.pdf}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins50v300.pdf}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins30v300.pdf}
\hspace{0.30\linewidth}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins50v100.pdf}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins30v100.pdf}
\hspace{0.60\linewidth}
\includegraphics[width=0.30\linewidth]{img/sigma/parameter_assessment/bins30v50.pdf}
\caption{Comparing different bin numbers for the calculation of $\sigma$. Values were in good agreement when we compare 50 bins and 100 bins. For 300 bins $\sigma$ was estimated smaller than for the other bin numbers, especially for $\sigma > 0.8$. For 30 bins a few estimates stuck close to $\sigma = 0$, when they didn't for the other bin numbers. We chose to proceed with 50 bins.}
\label{sigma_bins}
\end{figure}
%box_script.py, quot_sigma() und quot_sigma_narrow()
\begin{figure}
\centering