diff --git a/code/plot_event_timeline.py b/code/plot_event_timeline.py
index 96f4e31..2bc8f15 100644
--- a/code/plot_event_timeline.py
+++ b/code/plot_event_timeline.py
@@ -20,87 +20,90 @@ logger = makeLogger(__name__)
 def main(datapath: str):
     
     foldernames = [datapath + x + '/'  for x in os.listdir(datapath) if os.path.isdir(datapath+x)]
-    for foldername in foldernames:
-        if foldername == '../data/mount_data/2020-05-12-10_00/':
-            continue
-        # behabvior is pandas dataframe with all the data
-        bh = Behavior(foldername)
-
-        category = bh.behavior
-        timestamps = bh.start_s
-        # Correct for doubles in chasing on- and offsets to get the right on-/offset pairs
-        # Get rid of tracking faults (two onsets or two offsets after another)
-        category, timestamps = correct_chasing_events(category, timestamps)
-
-        # split categories
-        chasing_onset = (timestamps[category == 0]/ 60) /60
-        chasing_offset = (timestamps[category == 1]/ 60) /60
-        physical_contact = (timestamps[category == 2] / 60) /60
-
-        all_fish_ids = np.unique(bh.chirps_ids)
-        fish1_id = all_fish_ids[0]
-        fish2_id = all_fish_ids[1]
-        # Associate chirps to inidividual fish
-        fish1 = (bh.chirps[bh.chirps_ids == fish1_id] / 60) /60
-        fish2 = (bh.chirps[bh.chirps_ids == fish2_id] / 60) /60
-        fish1_color = ps.red
-        fish2_color = ps.orange
-
-        fig, ax = plt.subplots(4, 1, figsize=(10, 5), height_ratios=[0.5, 0.5, 0.5, 6], sharex=True)
-        # marker size 
-        s = 200
-        ax[0].scatter(physical_contact, np.ones(len(physical_contact)), color='firebrick', marker='|', s=s)
-        ax[1].scatter(chasing_onset, np.ones(len(chasing_onset)), color='green', marker='|', s=s )
-        ax[2].scatter(fish1, np.ones(len(fish1))-0.25, color=fish1_color, marker='|', s=s)
-        ax[2].scatter(fish2, np.zeros(len(fish2))+0.25, color=fish2_color, marker='|', s=s)
-    
-
-        freq_temp = bh.freq[bh.ident==fish1_id]
-        time_temp = bh.time[bh.idx[bh.ident==fish1_id]]
-        ax[3].plot((time_temp/ 60) /60, freq_temp, color=fish1_color)
-
-        freq_temp = bh.freq[bh.ident==fish2_id]
-        time_temp = bh.time[bh.idx[bh.ident==fish2_id]]
-        ax[3].plot((time_temp/ 60) /60, freq_temp, color=fish2_color)
-
-        #ax[3].imshow(decibel(bh.spec), extent=[bh.time[0]/60/60, bh.time[-1]/60/60, 0, 2000], aspect='auto', origin='lower')
-
-            # Hide grid lines
-        ax[0].grid(False)
-        ax[0].set_frame_on(False)
-        ax[0].set_xticks([])
-        ax[0].set_yticks([])
-        ps.hide_ax(ax[0])
-
-
-        ax[1].grid(False)
-        ax[1].set_frame_on(False)
-        ax[1].set_xticks([])
-        ax[1].set_yticks([])
-        ps.hide_ax(ax[1])
-
-        ax[2].grid(False)
-        ax[2].set_frame_on(False)
-        ax[2].set_yticks([])
-        ax[2].set_xticks([])
-        ps.hide_ax(ax[2])
-
-
-
-        ax[3].axvspan(3, 6, 0, 5, facecolor='grey', alpha=0.5)
-        ax[3].set_xticks(np.arange(0, 6.1, 0.5))
-
-        labelpad = 40
-        ax[0].set_ylabel('Physical contact', rotation=0, labelpad=labelpad)
-        ax[1].set_ylabel('Chasing events', rotation=0, labelpad=labelpad)
-        ax[2].set_ylabel('Chirps', rotation=0, labelpad=labelpad)
-        ax[3].set_ylabel('EODf')
+    #for foldername in foldernames:
+    foldername = foldernames[0]
+    # if foldername == '../data/mount_data/2020-05-12-10_00/':
+    #     continue
+    # behabvior is pandas dataframe with all the data
+    bh = Behavior(foldername)
+
+    category = bh.behavior
+    timestamps = bh.start_s
+    # Correct for doubles in chasing on- and offsets to get the right on-/offset pairs
+    # Get rid of tracking faults (two onsets or two offsets after another)
+    category, timestamps = correct_chasing_events(category, timestamps)
+
+    # split categories
+    chasing_onset = (timestamps[category == 0]/ 60) /60
+    chasing_offset = (timestamps[category == 1]/ 60) /60
+    physical_contact = (timestamps[category == 2] / 60) /60
+
+    all_fish_ids = np.unique(bh.chirps_ids)
+    fish1_id = all_fish_ids[0]
+    fish2_id = all_fish_ids[1]
+    # Associate chirps to inidividual fish
+    fish1 = (bh.chirps[bh.chirps_ids == fish1_id] / 60) /60
+    fish2 = (bh.chirps[bh.chirps_ids == fish2_id] / 60) /60
+    fish1_color = ps.red
+    fish2_color = ps.orange
+
+    fig, ax = plt.subplots(4, 1, figsize=(28*ps.cm, 13*ps.cm), height_ratios=[0.5, 0.5, 0.5, 6], sharex=True)
+    # marker size 
+    s = 200
+    ax[0].scatter(physical_contact, np.ones(len(physical_contact)), color='firebrick', marker='|', s=s)
+    ax[1].scatter(chasing_onset, np.ones(len(chasing_onset)), color='green', marker='|', s=s )
+    ax[2].scatter(fish1, np.ones(len(fish1))-0.25, color=fish1_color, marker='|', s=s)
+    ax[2].scatter(fish2, np.zeros(len(fish2))+0.25, color=fish2_color, marker='|', s=s)
+
+
+    freq_temp = bh.freq[bh.ident==fish1_id]
+    time_temp = bh.time[bh.idx[bh.ident==fish1_id]]
+    ax[3].plot((time_temp/ 60) /60, freq_temp, color=fish1_color)
+
+    freq_temp = bh.freq[bh.ident==fish2_id]
+    time_temp = bh.time[bh.idx[bh.ident==fish2_id]]
+    ax[3].plot((time_temp/ 60) /60, freq_temp, color=fish2_color)
+
+    #ax[3].imshow(decibel(bh.spec), extent=[bh.time[0]/60/60, bh.time[-1]/60/60, 0, 2000], aspect='auto', origin='lower')
+
+        # Hide grid lines
+    ax[0].grid(False)
+    ax[0].set_frame_on(False)
+    ax[0].set_xticks([])
+    ax[0].set_yticks([])
+    ps.hide_ax(ax[0])
+
+
+    ax[1].grid(False)
+    ax[1].set_frame_on(False)
+    ax[1].set_xticks([])
+    ax[1].set_yticks([])
+    ps.hide_ax(ax[1])
+
+    ax[2].grid(False)
+    ax[2].set_frame_on(False)
+    ax[2].set_yticks([])
+    ax[2].set_xticks([])
+    ps.hide_ax(ax[2])
+
+
+
+    ax[3].axvspan(3, 6, 0, 5, facecolor='grey', alpha=0.5)
+    ax[3].set_xticks(np.arange(0, 6.1, 0.5))
+
+    labelpad = 40
+    ax[0].set_ylabel('Physical contact', rotation=0, labelpad=labelpad)
+    ax[1].set_ylabel('Chasing events', rotation=0, labelpad=labelpad)
+    ax[2].set_ylabel('Chirps', rotation=0, labelpad=labelpad)
+    ax[3].set_ylabel('EODf')
+
+    ax[3].set_xlabel('Time [h]')
+    #ax[0].set_title(foldername.split('/')[-2])
+    # 2020-03-31-9_59
+    plt.subplots_adjust(left=0.13, right=0.987, top=0.97)
+    plt.savefig('../poster/figs/timeline.pdf')
+    plt.show()
 
-        ax[3].set_xlabel('Time [h]')
-        ax[0].set_title(foldername.split('/')[-2])
-        # 2020-03-31-9_59
-        plt.show()
-        embed()
 
     # plot chirps
 
diff --git a/poster/figs/timeline.pdf b/poster/figs/timeline.pdf
new file mode 100644
index 0000000..38650a3
Binary files /dev/null and b/poster/figs/timeline.pdf differ
diff --git a/poster/main.pdf b/poster/main.pdf
index 92b0871..8e5c90a 100644
Binary files a/poster/main.pdf and b/poster/main.pdf differ
diff --git a/poster/main.tex b/poster/main.tex
index 1738024..03e6fb1 100644
--- a/poster/main.tex
+++ b/poster/main.tex
@@ -38,7 +38,12 @@ blockverticalspace=2mm, colspace=20mm, subcolspace=0mm]{tikzposter} %Default val
 \myblock[TranspBlock]{Chirps during competition}{
     \begin{tikzfigure}[]
         \label{fig:example_b}
-        \includegraphics[width=0.5\linewidth]{example-image-b}
+        \includegraphics[width=\linewidth]{figs/timeline.pdf}
+    \end{tikzfigure}
+    \noindent
+    \begin{tikzfigure}[]
+        \label{fig:example_b}
+        \includegraphics[width=\linewidth]{figs/chirps_winner_loser.pdf}
     \end{tikzfigure}
     \noindent
 }