finished plot in chasing

code/modules/plotstyle.py

@@ -110,7 +110,7 @@ def PlotStyle() -> None:
             plt.setp(bp["boxes"], color=color)
             plt.setp(bp["whiskers"], color=white)
             plt.setp(bp["caps"], color=white)
-            plt.setp(bp["medians"], color=white)
+            plt.setp(bp["medians"], color=black)
 
 
         @classmethod
@@ -255,10 +255,10 @@ def PlotStyle() -> None:
     plt.rcParams["boxplot.boxprops.color"] = gray
     plt.rcParams["boxplot.whiskerprops.color"] = gray
     plt.rcParams["boxplot.capprops.color"] = gray
-    plt.rcParams["boxplot.medianprops.color"] = gray
+    plt.rcParams["boxplot.medianprops.color"] = black
     plt.rcParams["text.color"] = white
     plt.rcParams["axes.facecolor"] = black  # axes background color
-    plt.rcParams["axes.edgecolor"] = gray  # axes edge color
+    plt.rcParams["axes.edgecolor"] = white  # axes edge color
     # plt.rcParams["axes.grid"] = True    # display grid or not
     # plt.rcParams["axes.grid.axis"] = "y"  # which axis the grid is applied to
     plt.rcParams["axes.labelcolor"] = white
@@ -284,9 +284,9 @@ def PlotStyle() -> None:
             "#f5c2e7",
         ],
     )
-    plt.rcParams["xtick.color"] = gray  # color of the ticks
+    plt.rcParams["xtick.color"] = white  # color of the ticks
-    plt.rcParams["ytick.color"] = gray  # color of the ticks
+    plt.rcParams["ytick.color"] = white  # color of the ticks
-    plt.rcParams["grid.color"] = dark_gray  # grid color
+    plt.rcParams["grid.color"] = white  # grid color
     plt.rcParams["figure.facecolor"] = black  # figure face color
     plt.rcParams["figure.edgecolor"] = black  # figure edge color
     plt.rcParams["savefig.facecolor"] = black  # figure face color when saving

code/plot_chirp_size.py

@@ -252,9 +252,9 @@ def main(datapath: str):
     size_loser_pearsonr = pearsonr(size_diffs_loser, size_chirps_loser)
 
     fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(
-        21*ps.cm, 10*ps.cm), width_ratios=[1, 0.8, 0.8], sharey=True)
+        21*ps.cm, 8*ps.cm), width_ratios=[1, 0.8, 0.8], sharey=True)
-    plt.subplots_adjust(left=0.11, right=0.948, top=0.905,
+    plt.subplots_adjust(left=0.11, right=0.948, top=0.86,
-                        wspace=0.343, bottom=0.145)
+                        wspace=0.343, bottom=0.18)
     scatterwinner = 1.15
     scatterloser = 1.85
     chirps_winner = np.asarray(chirps_winner)[~np.isnan(chirps_winner)]
@@ -262,47 +262,51 @@ def main(datapath: str):
 
     stat = wilcoxon(chirps_winner, chirps_loser)
     print(stat)
+    winner_color = ps.lavender
+    loser_color = ps.purple
 
     bplot1 = ax1.boxplot(chirps_winner, positions=[
         0.9], showfliers=False, patch_artist=True)
 
     bplot2 = ax1.boxplot(chirps_loser,  positions=[
         2.1], showfliers=False, patch_artist=True)
+
     ax1.scatter(np.ones(len(chirps_winner)) *
-                scatterwinner, chirps_winner, color=ps.red)
+                scatterwinner, chirps_winner, color=winner_color)
     ax1.scatter(np.ones(len(chirps_loser)) *
-                scatterloser, chirps_loser, color=ps.orange)
+                scatterloser, chirps_loser, color=loser_color)
-    ax1.set_xticklabels(['winner', 'loser'])
+    ax1.set_xticklabels(['Winner', 'Loser'])
 
-    ax1.text(0.1, 0.95, f'n={len(chirps_winner)}', transform=ax1.transAxes, color=ps.white)
+    ax1.text(0.1, 0.95, f'n={len(chirps_winner)}',
+             transform=ax1.transAxes, color=ps.white)
 
     for w, l in zip(chirps_winner, chirps_loser):
         ax1.plot([scatterwinner, scatterloser], [w, l],
-                 color=ps.white, alpha=1, linewidth=0.5)
+                 color=ps.white, alpha=0.6, linewidth=1, zorder=-1)
-    ax1.set_ylabel('chirpcounts', color=ps.white)
+    ax1.set_ylabel('Chirp counts', color=ps.white)
-    ax1.set_xlabel('outcome',    color=ps.white)
+    ax1.set_xlabel('Competition outcome',    color=ps.white)
 
-    colors1 = ps.red
+    ps.set_boxplot_color(bplot1, winner_color)
-    ps.set_boxplot_color(bplot1, colors1)
+    ps.set_boxplot_color(bplot2, loser_color)
-    colors1 = ps.orange
-    ps.set_boxplot_color(bplot2, colors1)
 
     ax2.scatter(size_diffs_winner, size_chirps_winner,
-                color=ps.red, label=f'winner')
+                color=winner_color, label=f'Winner')
     ax2.scatter(size_diffs_loser, size_chirps_loser,
-                color=ps.orange, label='loser')
+                color=loser_color, label='Loser')
 
-    ax2.text(0.05, 0.95, f'n={len(size_chirps_winner)}', transform=ax2.transAxes, color=ps.white)
+    ax2.text(0.05, 0.95, f'n={len(size_chirps_winner)}',
+             transform=ax2.transAxes, color=ps.white)
 
-    ax2.set_xlabel('size difference [cm]')
+    ax2.set_xlabel('Size difference [cm]')
     # ax2.set_xticks(np.arange(-10, 10.1, 2))
 
-    ax3.scatter(freq_diffs_higher, freq_chirps_winner, color=ps.red)
+    ax3.scatter(freq_diffs_higher, freq_chirps_winner, color=winner_color)
-    ax3.scatter(freq_diffs_lower, freq_chirps_loser, color=ps.orange)
+    ax3.scatter(freq_diffs_lower, freq_chirps_loser, color=loser_color)
 
-    ax3.text(0.1, 0.95, f'n={len(freq_chirps_loser)}', transform=ax3.transAxes, color=ps.white)
+    ax3.text(0.1, 0.95, f'n={len(freq_chirps_loser)}',
+             transform=ax3.transAxes, color=ps.white)
 
-    ax3.set_xlabel('absolute frequency [Hz]')
+    ax3.set_xlabel('EODf [Hz]')
     handles, labels = ax2.get_legend_handles_labels()
     fig.legend(handles, labels, loc='upper center', ncol=2)
     # pearson r

code/plot_chirps_in_chasing.py

@@ -45,33 +45,46 @@ def main(datapath: str):
 
         chirps_in_chasings = []
         for onset, offset in zip(chasing_onset, chasing_offset):
-            chirps_in_chasing = [c for c in bh.chirps if (c > onset) & (c < offset)]
+            chirps_in_chasing = [
+                c for c in bh.chirps if (c > onset) & (c < offset)]
             chirps_in_chasings.append(chirps_in_chasing)
 
         try:
-            time_chasing = np.sum(chasing_offset[chasing_offset<3*60*60] - chasing_onset[chasing_onset<3*60*60])
+            time_chasing = np.sum(
+                chasing_offset[chasing_offset < 3*60*60] - chasing_onset[chasing_onset < 3*60*60])
         except:
-            time_chasing = np.sum(chasing_offset[chasing_offset<3*60*60] - chasing_onset[chasing_onset<3*60*60][:-1])
+            time_chasing = np.sum(
-
+                chasing_offset[chasing_offset < 3*60*60] - chasing_onset[chasing_onset < 3*60*60][:-1])
 
         time_chasing_percent = (time_chasing/(3*60*60))*100
         chirps_chasing = np.asarray(flatten(chirps_in_chasings))
-        chirps_chasing_new = chirps_chasing[chirps_chasing<3*60*60]
+        chirps_chasing_new = chirps_chasing[chirps_chasing < 3*60*60]
-        chirps_percent = (len(chirps_chasing_new)/len(bh.chirps[bh.chirps<3*60*60]))*100
+        chirps_percent = (len(chirps_chasing_new) /
+                          len(bh.chirps[bh.chirps < 3*60*60]))*100
 
         time_precents.append(time_chasing_percent)
         chirps_percents.append(chirps_percent)
 
-    fig, ax = plt.subplots(1, 1, figsize=(14*ps.cm, 10*ps.cm))
+    fig, ax = plt.subplots(1, 1, figsize=(7*ps.cm, 7*ps.cm))
-
+    scatter_time = 1.20
-    ax.boxplot([time_precents, chirps_percents])
+    scatter_chirps = 1.80
-    ax.set_xticklabels(['Time Chasing', 'Chirps in Chasing'])
+    size = 10
+    bplot1 = ax.boxplot([time_precents, chirps_percents],
+                        showfliers=False, patch_artist=True)
+    ps.set_boxplot_color(bplot1, ps.gray)
+    ax.set_xticklabels(['Time \nChasing', 'Chirps \nin Chasing'])
     ax.set_ylabel('Percent')
-    ax.scatter(np.ones(len(time_precents))*1.25, time_precents, color=ps.white)
+    ax.scatter(np.ones(len(time_precents))*scatter_time, time_precents,
-    ax.scatter(np.ones(len(chirps_percents))*1.75, chirps_percents, color=ps.white)
+               facecolor=ps.white, s=size)
+    ax.scatter(np.ones(len(chirps_percents))*scatter_chirps, chirps_percents,
+               facecolor=ps.white, s=size)
+
     for i in range(len(time_precents)):
-        ax.plot([1.25, 1.75], [time_precents[i], chirps_percents[i]], color=ps.white)
+        ax.plot([scatter_time, scatter_chirps], [time_precents[i],
-    ax.text(0.99, 0.99, f'{len(time_precents)} fish', transform=ax.transAxes)
+                chirps_percents[i]], alpha=0.6, linewidth=1, color=ps.white)
+
+    ax.text(0.1, 0.9, f'n={len(time_precents)}', transform=ax.transAxes)
+    plt.subplots_adjust(left=0.221, bottom=0.186, right=0.97, top=0.967)
     plt.savefig('../poster/figs/chirps_in_chasing.pdf')
     plt.show()
 
@@ -80,5 +93,3 @@ if __name__ == '__main__':
     # Path to the data
     datapath = '../data/mount_data/'
     main(datapath)
-
-        

code/plot_event_timeline.py

@@ -79,7 +79,6 @@ def main(datapath: str):
         ax[0].set_xticks([])
         ax[0].set_yticks([])
         ps.hide_ax(ax[0])
-        ax[0].yaxis.set_label_coords(-0.1, 0.5)
 
         ax[1].grid(False)
         ax[1].set_frame_on(False)
@@ -99,19 +98,23 @@ def main(datapath: str):
 
         labelpad = 30
         fsize = 12
-        ax[0].set_ylabel('contact', rotation=0,
+
+        ax[0].set_ylabel('Contact', rotation=0,
                          labelpad=labelpad, fontsize=fsize)
-        ax[1].set_ylabel('chasing', rotation=0,
+        ax[0].yaxis.set_label_coords(-0.062, -0.08)
+        ax[1].set_ylabel('Chasing', rotation=0,
                          labelpad=labelpad, fontsize=fsize)
-        ax[2].set_ylabel('chirps', rotation=0,
+        ax[1].yaxis.set_label_coords(-0.06, -0.08)
+        ax[2].set_ylabel('Chirps', rotation=0,
                          labelpad=labelpad, fontsize=fsize)
+        ax[2].yaxis.set_label_coords(-0.07, -0.08)
         ax[4].set_ylabel('EODf')
 
-        ax[4].set_xlabel('time [h]')
+        ax[4].set_xlabel('Time [h]')
         # ax[0].set_title(foldername.split('/')[-2])
         # 2020-03-31-9_59
-        plt.subplots_adjust(left=0.158, right=0.987, top=0.918)
+        plt.subplots_adjust(left=0.158, right=0.987, top=0.918, bottom=0.136)
-        # plt.savefig('../poster/figs/timeline.pdf')
+        plt.savefig('../poster/figs/timeline.pdf')
         plt.show()
 
     # plot chirps

poster/main.tex

@@ -22,20 +22,20 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
     weakly electric fish impossible. This profoundly limits our current
     understanding of chirps to experiments
     with single - or physically separated - individuals.
-    % \begin{tikzfigure}[]
+    \begin{tikzfigure}[]
-    %     \label{griddrawing}
+        \label{griddrawing}
-    %     \includegraphics[width=0.8\linewidth]{figs/introplot}
+        \includegraphics[width=0.6\linewidth]{figs/introplot}
-    % \end{tikzfigure}
+    \end{tikzfigure}
 }
 \myblock[TranspBlock]{Chirp detection}{
     \begin{tikzfigure}[]
         \label{fig:alg1}
-        \includegraphics[width=0.9\linewidth]{figs/algorithm1}
+        \includegraphics[width=0.6\linewidth]{figs/algorithm1}
     \end{tikzfigure}
     \vspace{2cm}
     \begin{tikzfigure}[]
         \label{fig:alg2}
-        \includegraphics[width=1\linewidth]{figs/algorithm}
+        \includegraphics[width=0.9\linewidth]{figs/algorithm}
     \end{tikzfigure}
     \vspace{0cm}
 }
@@ -63,8 +63,8 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
 
     \begin{itemize}
         \setlength\itemsep{0.5em}
-        \item Fish who won the competition chirped more often than the fish who lost.
+        \item Fish who lost the competition chirped more often than the fish who lost.
-        \item
+        \item Size has an effect on the Competition outcome, and the chirp count.
     \end{itemize}
 
 }