raab/GP2023_chirp_detection
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new algoplot

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weygoldt 2023-01-26 15:32:00 +01:00
parent 87127fb718
commit 41235c4188
3 changed files with 7 additions and 6 deletions

7
code/plot_kdes.py
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@ -275,14 +275,15 @@ def main(dataroot):
# loser_physicals_conv = acausal_kde1d(
# loser_physicals[-1], kde_time, kernel_width)
ax[i].plot(kde_time, loser_offsets_conv/len(offsets))
ax[i].plot(kde_time, loser_offsets_conv /
len(offsets), lw=2, zorder=100)
ax[i].fill_between(
kde_time,
np.percentile(loser_offsets_boot[-1], 1, axis=0),
np.percentile(loser_offsets_boot[-1], 99, axis=0),
color=ps.white,
alpha=0.5)
alpha=0.4)
ax[i].plot(kde_time, np.median(loser_offsets_boot[-1], axis=0),
color=ps.black, linewidth=2)
@ -519,7 +520,7 @@ def main(dataroot):
# loser_physicals_boot_quarts[2],
# color=ps.gray,
# alpha=0.5)
plt.subplots_adjust(bottom=0.21)
plt.subplots_adjust(bottom=0.21, top=0.93)
plt.savefig('../poster/figs/kde.pdf')
plt.show()

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poster/figs/kde.pdf
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6
poster/main.tex
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@ -7,7 +7,7 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
\begin{document}
\renewcommand{\baselinestretch}{1}
\title{\parbox{1500pt}{Bypassing time-frequency uncertainty in the detection of transient communication signals in weakly electric fish}}
\title{\parbox{1600pt}{Bypassing time-frequency uncertainty in the detection of transient communication signals in weakly electric fish}}
\author{Sina Prause, Alexander Wendt, and Patrick Weygoldt}
\institute{Supervised by Till Raab \& Jan Benda, Neuroethology Lab, University of Tuebingen}
\usetitlestyle[]{sampletitle}
@ -17,7 +17,7 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
\begin{columns}
\column{0.4}
\myblock[TranspBlock]{Introduction}{
\textbf{Chirps} are the most common communication signals in weakly electric fish. They are characterized by \textbf{short frequency excursions} and are emitted during various social contexts. It is nearly impossible to reliably \textbf{detect and assign} chirps in freely interacting fish using only a Fourier transform. To overcome these limits, we developed a new method of \textbf{dynamic feature extraction} and classification.
\textbf{Chirps} are the most common communication signals in weakly electric fish. They are characterized by \textbf{short frequency excursions} and are emitted during various social contexts. It is nearly impossible to reliably \textbf{detect and assign} chirps in freely interacting fish using only a Fourier transform. To overcome these limits, we developed a new method of \textbf{dynamic feature extraction} and classification.
\vspace{1cm}
\begin{tikzfigure}[]
\label{griddrawing}
@ -52,7 +52,7 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
\item Experiment had a 3 hour long darkphase and a 3 hour long light phase.
\end{itemize}
\end{multicols}
\noindent
\begin{tikzfigure}[]