From fadef774d4dc33e680f4f207f41b5409d041e3d2 Mon Sep 17 00:00:00 2001
From: Diana <diana.stoll@stundent.uni-tuebingen.de>
Date: Thu, 24 Oct 2024 13:49:57 +0200
Subject: [PATCH 1/2] changed highlight function

---
 code/plot_functions.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/code/plot_functions.py b/code/plot_functions.py
index 7bf001f..5fb4c17 100644
--- a/code/plot_functions.py
+++ b/code/plot_functions.py
@@ -136,7 +136,7 @@ def plot_highlighted_integrals(frequency, power, points, color_mapping, points_c
     ax.set_title('Power Spectrum with Highlighted Integrals')
     ax.legend()
     
-    return fig
+    return fig, ax
 
 
 

From edc8d832e10a9b5f369704d6096320ed8ae5ed95 Mon Sep 17 00:00:00 2001
From: mbergmann <maximilian.bergmann@student.uni-tuebingen.de>
Date: Thu, 24 Oct 2024 15:14:57 +0200
Subject: [PATCH 2/2] [useful_functions.py] added true_eodf function

---
 code/useful_functions.py | 27 +++++++++++++++++++++++----
 1 file changed, 23 insertions(+), 4 deletions(-)

diff --git a/code/useful_functions.py b/code/useful_functions.py
index 6c17064..ed94b8e 100644
--- a/code/useful_functions.py
+++ b/code/useful_functions.py
@@ -1,9 +1,5 @@
-import glob
-import pathlib
 import numpy as np
-import matplotlib.pyplot as plt
 import rlxnix as rlx
-from IPython import embed
 from scipy.signal import welch
 
 def all_coming_together(freq_array, power_array, points_list, categories, num_harmonics_list, colors, delta=2.5, threshold=0.5):
@@ -513,6 +509,29 @@ def spike_times(stim):
     dt = ti.sampling_interval  
     return spikes, stim_dur, dt # se changed spike_times to spikes so its not the same as name of function
 
+def true_eodf(eodf_file):
+    '''
+    Calculates the Eodf of the fish when it was awake from a nix file.
+
+    Parameters
+    ----------
+    eodf_file : str
+        path to the file with nix-file for the eodf.
+
+    Returns
+    -------
+    orig_eodf : int
+        The original eodf.
+
+    '''
+    eod_data = rlx.Dataset(eodf_file)#load eodf file
+    baseline = eod_data.repro_runs('baseline')[0]
+    eod, time = baseline.trace_data('EOD') # get time and eod
+    dt = baseline.trace_info('EOD').sampling_interval
+    eod_freq, eod_power = welch(eod, fs = 1/dt, nperseg = 2**16, noverlap = 2**15)
+    orig_eodf = round(eod_freq[np.argmax(eod_power)])
+    return orig_eodf
+
 def valid_integrals(integral, local_mean, point, threshold = 0.1):
     """
     Check if the integral exceeds the threshold compared to the local mean and