diff --git a/complete_analysis.py b/complete_analysis.py
index b580ead..a0f291b 100644
--- a/complete_analysis.py
+++ b/complete_analysis.py
@@ -238,8 +238,11 @@ def main(data_folder=None):
         if ~np.all(meta_id_in_uid):
             continue
 
+        ids = np.load(os.path.join(trial_path, 'analysis', 'ids.npy'))
+        sorter = -1 if win_id != ids[0] else 1
+
         temp_t, temp = get_temperature(trial_path)
-        baseline_freqs = np.load(os.path.join(trial_path, 'analysis', 'baseline_freqs.npy'))
+        baseline_freqs = np.load(os.path.join(trial_path, 'analysis', 'baseline_freqs.npy'))[::sorter]
         baseline_freq_times = np.load(os.path.join(trial_path, 'analysis', 'baseline_freq_times.npy'))
         q10_comp_freq, q10_vals = frequency_q10_compensation(baseline_freqs, baseline_freq_times, temp, temp_t, light_start_sec=light_start_sec)
 
@@ -252,9 +255,11 @@ def main(data_folder=None):
             got_chirps = True
 
         chirp_times = [chirp_t[chirp_ids == win_id], chirp_t[chirp_ids == lose_id]]
-        rise_idx = np.load(os.path.join(trial_path, 'analysis', 'rise_idx.npy'))
+        rise_idx = np.load(os.path.join(trial_path, 'analysis', 'rise_idx.npy'))[::sorter]
         rise_idx_int = [np.array(rise_idx[i][~np.isnan(rise_idx[i])], dtype=int) for i in range(len(rise_idx))]
 
+
+
         #############################################################################################################
         ### physical behavior
         if video_eval:
@@ -362,9 +367,6 @@ def main(data_folder=None):
 
     plt.show()
 
-    embed()
-    quit()
-
 
     for g in pd.unique(trial_summary['group']):
         fish_no = np.unique(np.concatenate((trial_summary['win_fish'][trial_summary['group'] == g],
diff --git a/trail_analysis.py b/trail_analysis.py
index 6324f6d..27bd40a 100644
--- a/trail_analysis.py
+++ b/trail_analysis.py
@@ -38,6 +38,8 @@ class Trial(object):
         self.winner = None
         self.loser = None
 
+        self.mean_shelter_power = None
+
         if os.path.exists(os.path.join(self.base_path, self.folder, 'fund_v.npy')):
             self.load()
 
@@ -108,8 +110,8 @@ class Trial(object):
         for enu, id in enumerate(self.ids):
             shelter_power[enu] = self.fish_sign_interp[enu][day_idxs, -1]
 
-        mean_shelter_power = np.nanmean(shelter_power, axis=1)
-        self.winner = 1 if mean_shelter_power[1] > mean_shelter_power[0] else 0
+        self.mean_shelter_power = np.nanmean(shelter_power, axis=1)
+        self.winner = 1 if self.mean_shelter_power[1] > self.mean_shelter_power[0] else 0
         self.loser = 0 if self.winner == 1 else 1
 
     def rise_detection(self, rise_th):
@@ -187,7 +189,7 @@ class Trial(object):
 
         for enu, id in enumerate(self.ids):
             c = 'firebrick' if self.winner == enu else 'forestgreen'
-            ax.plot(self.times/3600, self.fish_freq[enu], marker='.', color=c, zorder=1)
+            ax.plot(self.times/3600, self.fish_freq[enu], marker='.', color=c, zorder=1, label=f'{self.mean_shelter_power[enu]:.2f}dB')
             ax.plot(self.times[np.isnan(self.fish_freq[enu])]/3600, self.fish_freq_interp[enu][np.isnan(self.fish_freq[enu])], '.', zorder=1, color=c, alpha=0.25)
             ax.plot(self.baseline_freq_times/3600, self.baseline_freqs[enu], '--', color='k', zorder=2)
             ax.plot(self.baseline_freq_times/3600, self.pct95_freqs[enu], '--', color='k', zorder=2)