diff --git a/constants.py b/constants.py
index 8122b1180c72781760448decc51055e476a8637e..11a6a569edae5d96531ea07c51dba8ef4d36c841 100644
--- a/constants.py
+++ b/constants.py
@@ -2,27 +2,31 @@
SAMPLING_FREQ = 250 #mintavételi freq, ez stabil, írja, ha megváltozik, nem változtatni
SIGNAL_TIME = 350 #ha időre fut a kód, akkor a start signal után az input() helyére sleep(...)
-RESIST_TIME = 5
+RESIST_TIME = 10
EPOCH_LEN = 30 #30 s-nyi epochokkal dolgozik
YASA_INPUT_LEN = 2*60 #percben (az epoch 30 s)
#EEG metadata values
+NAME = "PG"
MALE = True
AGE = 22
#file managing
-FILE_IDENTIFIER = "full_night_audio2"
+FILE_IDENTIFIER = "full_night_audio"
FILE_FOLDER_NAME = "C:\Programkornyezet\PythonProjects\AudiostimulationProject\AudiostimulationDirectory\output_files"
-ANALYZE_FILE = True #ábrázoljuk a mentett fájlokat. Futtatásnál false
-SHOW_FEEDBACK = True #sárgával színezi, hogy a check_pip alapján mikor volt ing. Aktuális check_pip!
#audiofeedback
-CHECK_LEN = 3
-FREQUENCY_RIGHT = 138 #a kettő különbségét érzékeljük a sztereo hangzásból
-FREQUENCY_LEFT = 135
+DELAY = 10 #hány epochal a kezdés után indul el a mérés
+CHECK_LEN = 8
+
+#EZT A NÉGYET KELL ÁLLÍTANI, MÁSHOZ NE NYÚLJATOK
+FREQUENCY_RIGHT = 250
+FREQUENCY_LEFT = 253
+N2_N3 = 1
+N3 = 0.5
#sleepstaging first wake hour file path
diff --git a/device_controller.py b/device_controller.py
index 0447296f2f01ff8fd0d17eff847da7a9328e68a0..8255f21fa2150c53689b6db99e5d01d19f85c5d2 100644
--- a/device_controller.py
+++ b/device_controller.py
@@ -135,7 +135,6 @@ try:
print("Disconnect from sensor")
del sensor
-
del scanner
print('Remove scanner')
except Exception as err:
diff --git a/file_manager.py b/file_manager.py
index 5a11707182f4ae461f4179efda89157ee6e75e49..2932bb13d5eb1ed84fad3e62000aa41687f8952a 100644
--- a/file_manager.py
+++ b/file_manager.py
@@ -8,11 +8,9 @@ Feldolgozáshoz beírni az analyze_file()-ba a fájl abszolút elérési útvona
import os
import datetime
import pandas as pd
-import matplotlib.pyplot as plt
-import yasa
import constants as c
import sleep_stage_classifer as s
-import audio_feedback as a
+import visualizer as v
def sleep_stage_file_maker():
@@ -36,64 +34,7 @@ def sleep_stage_file_maker():
yasa_output_df = pd.DataFrame(s.yasa_output_list)
yasa_output_df.to_csv(file_path, index=False)
+ v.analyze_file(file_path)
-def analyze_file(csv_file_path):
- """
- Fájl feldolgozása, statisztika, valószínűségi plot,
- hisztogram.
-
- - A csv.-t feldolgozzuk, külön DataFrame-be kerülnek a betűvel jelzett 'Stage'-k és az 5 oszlopnyi 'Probability'.
- - Ábrázoljuk egy 'yasa' parancssor alapján a hisztogramot. Méretét az adatok mennyisége határozza meg.
- - Ábrázoljuk 'matplotlib'-bel a valószínűségeket (ahogy a 'yasa'-ban is, de az fájlból nem működik). Méretét az
- adatmennyiség határozza meg.
- - Ábrázoljuk az összes szükséges értéket és kimutatást 'yasa' függvény segítségével.
- - A c.SHOW_FEEDBACK egy kapcsoló, jelzi (kiemelővel a valószínűségploton) hogy mikor volt a check_pip szerint audio
- stimuláció. Mindig az aktuális check_pip feltételekre!
- :param csv_file_path: output_list-be mentett .csv fájlok abszolút elérési útvonala
- """
- df = pd.read_csv(csv_file_path)
- stages = df['Stage']
- probabilities = df.iloc[:, 1:] # Az első oszlop a 'Stages', a többi a valószínűsége
- stages_int = yasa.hypno_str_to_int(stages)
-
- if c.SHOW_FEEDBACK:
- dict_list = df.to_dict(orient='records')
- pip_results = [a.check_pip(dict_list[:i + 1]) for i in range(len(dict_list))]
-
- # Hipnogram ábrázolása
- plt.figure(figsize=(int(len(stages) / 40), 5))
- hypn = yasa.Hypnogram(stages, freq="30s")
- hypn.plot_hypnogram(lw=2, fill_color="whitesmoke")
- plt.show()
-
- # Valószínűségplot ábrázolása
- colors = ["#99d7f1", "#009DDC", "xkcd:twilight blue", "xkcd:rich purple", "xkcd:sunflower"]
- ax = probabilities.plot(kind='area', figsize=(int(len(probabilities) / 6), 5), stacked=True, color=colors,
- alpha=0.8, linewidth=0)
- ax.set_xlabel('Time (30-sec epoch)')
- ax.set_ylabel('Probability')
- ax.legend(frameon=False, bbox_to_anchor=(1, 1))
-
- if c.SHOW_FEEDBACK:
- for i, result in enumerate(pip_results):
- if result: # Ha True, akkor kiemeljük az adott szakaszt
- ax.axvspan(i, i + 1, color='yellow', alpha=0.5) # Kiemelés sárga színnel
- plt.show()
- # print((sum(pip_results) / 2), "percnyi ingerlés volt összesen")
-
- # Alvási statisztikák kiíratása táblázatban
- statistics = yasa.sleep_statistics(stages_int, sf_hyp=1 / 30)
- stat_df = pd.DataFrame(list(statistics.items()), columns=['Parameter', 'Value'])
- plt.figure(figsize=(4, 6))
- plt.title('Sleep Statistics')
- plt.axis('off')
- plt.table(cellText=stat_df.values, colLabels=stat_df.columns, loc='center', cellLoc='center',
- colColours=['lightgray'] * 2)
- plt.tight_layout()
- plt.show()
-
-if c.ANALYZE_FILE:
- analyze_file(
- r'C:\Programkornyezet\PythonProjects\AudiostimulationProject\AudiostimulationDirectory\output_files\02_28_full_night_audio2.csv')
diff --git a/output_files/03_14_andris_full_night_audio.csv b/output_files/03_14_andris_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fe42e42eb15956a6a8d7771bcab06ed24fde2a0b
--- /dev/null
+++ b/output_files/03_14_andris_full_night_audio.csv
@@ -0,0 +1,1080 @@
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diff --git a/output_files/03_15_andris_full_night_audio.csv b/output_files/03_15_andris_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..f8131760a1a19283a99c8c34e0286fedca9b7675
--- /dev/null
+++ b/output_files/03_15_andris_full_night_audio.csv
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diff --git a/output_files/03_16_full_night_audio.csv b/output_files/03_16_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..fa397c0822b656b860c7d4e62bd9609144c18309
--- /dev/null
+++ b/output_files/03_16_full_night_audio.csv
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diff --git a/output_files/03_18_full_night_audio.csv b/output_files/03_18_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e89d95acd251e74b6950bf77bc34991cdedc5955
--- /dev/null
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diff --git a/output_files/03_19_full_night_audio.csv b/output_files/03_19_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..70a265127ed985e0fb8f64efa12997d8fc765750
--- /dev/null
+++ b/output_files/03_19_full_night_audio.csv
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diff --git a/output_files/03_20_full_night_audio.csv b/output_files/03_20_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4d2d4a064842e1bda22c9ce132ef70c193990f45
--- /dev/null
+++ b/output_files/03_20_full_night_audio.csv
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diff --git a/output_files/03_21_full_night_audio.csv b/output_files/03_21_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ca1d8c5849f1597b7e24b340c39d79192c8c1f79
--- /dev/null
+++ b/output_files/03_21_full_night_audio.csv
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diff --git a/output_files/03_22_full_night_audio.csv b/output_files/03_22_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..13eca5fd762642b93297bd4bac1dea09776f8f57
--- /dev/null
+++ b/output_files/03_22_full_night_audio.csv
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diff --git a/output_files/03_27_full_night_audio.csv b/output_files/03_27_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..836c0291fadfb20bd4cc24f4babaf16ffd2aeb4a
--- /dev/null
+++ b/output_files/03_27_full_night_audio.csv
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diff --git a/output_files/03_29_full_night_audio.csv b/output_files/03_29_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..97ae8de8edf0d52c5e1d019251d849534fa0081a
--- /dev/null
+++ b/output_files/03_29_full_night_audio.csv
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diff --git a/output_files/03_30_full_night_audio.csv b/output_files/03_30_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..98bb69b3418c1fee7ba4b7a5ec65891e9b56ade5
--- /dev/null
+++ b/output_files/03_30_full_night_audio.csv
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diff --git a/output_files/04_01_full_night_audio.csv b/output_files/04_01_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..c81c930bb709457d2f07d84ad304245655c87b5a
--- /dev/null
+++ b/output_files/04_01_full_night_audio.csv
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diff --git a/output_files/04_08_full_night_audio.csv b/output_files/04_08_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d5530af28a5aa1f47bba418df651c27cc9cc5669
--- /dev/null
+++ b/output_files/04_08_full_night_audio.csv
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diff --git a/output_files/04_09_full_night_audio.csv b/output_files/04_09_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..17ef6640894ef631c3677c28d85d51557ef6af0b
--- /dev/null
+++ b/output_files/04_09_full_night_audio.csv
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diff --git a/output_files/04_11_full_night_audio.csv b/output_files/04_11_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..335f234eab04f421c08b3845d1205b2d2dec488a
--- /dev/null
+++ b/output_files/04_11_full_night_audio.csv
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diff --git a/output_files/04_12_full_night_audio.csv b/output_files/04_12_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..a7885a33f838b18983018bc224fd6fda16cf6b03
--- /dev/null
+++ b/output_files/04_12_full_night_audio.csv
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diff --git a/output_files/04_13_full_night_audio.csv b/output_files/04_13_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..e298be7b67e3972cdd42e0f49aceeaba0c6debc0
--- /dev/null
+++ b/output_files/04_13_full_night_audio.csv
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diff --git a/output_files/04_14_full_night_audio.csv b/output_files/04_14_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d0fdbe3d7518345af859d14fcd9bfcc1aafa74b3
--- /dev/null
+++ b/output_files/04_14_full_night_audio.csv
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diff --git a/output_files/04_15_full_night_audio.csv b/output_files/04_15_full_night_audio.csv
new file mode 100644
index 0000000000000000000000000000000000000000..73cb538e8230d1bef280469e07573ff711c263c7
--- /dev/null
+++ b/output_files/04_15_full_night_audio.csv
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+N1,0.5646811314274985,0.14094732425917067,0.0016339314036957929,0.04201206823245341,0.2507255446771815
+W,0.313299357802016,0.2619425925788958,0.0009491103413461281,0.008791418430314805,0.41501752084742727
+W,0.36998302611122075,0.22567143321130093,0.0005967597614668055,0.014373428729896663,0.38937535218611496
diff --git a/sleep_stage_classifer.py b/sleep_stage_classifer.py
index c1891aabf0391d414edec722f7901396e3f52550..5e90236188027c46f8f7527c890b872cced3f701 100644
--- a/sleep_stage_classifer.py
+++ b/sleep_stage_classifer.py
@@ -27,14 +27,10 @@ epoch_data_list = [] # egy epochnyi adat
yasa_output_list = [] # a fájlba írandó lista folyamatos bővüléggel
one_hour_list = []
-if os.path.exists(c.ONE_HOUR_WAKE) and c.ANALYZE_FILE == False: # betöltünk egy órányi ébrenlétet
- with open(c.ONE_HOUR_WAKE, 'rb') as file:
- yasa_input_list = pickle.load(file)
- print("egy óra beolvasva")
-elif c.ANALYZE_FILE == False:
- yasa_input_list = []
- print("yasa_input_list is empty")
+with open(c.ONE_HOUR_WAKE, 'rb') as file:
+ yasa_input_list = pickle.load(file)
+ print("egy óra beolvasva")
def yasa_classifier(raw):
"""
diff --git a/visualizer.py b/visualizer.py
new file mode 100644
index 0000000000000000000000000000000000000000..1d8ad39983614a49fa8da131b23c2ea58d47126c
--- /dev/null
+++ b/visualizer.py
@@ -0,0 +1,103 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import yasa
+import os
+import audio_feedback as a
+import constants as c
+from datetime import datetime, timedelta
+import sleep_stage_classifer as s
+
+
+def txt_maker(file_path):
+ """
+ Szöveges
+ fájlba kimenti az ingerlési és egyéb adatokat.
+
+ Params:
+ file_path (str): A szöveges fájl elérési útvonala és neve, ahová a szöveg mentésre kerül.
+ """
+
+
+ finish_time = datetime.now()
+ start_time = finish_time - timedelta(seconds=len(s.yasa_output_list) * c.EPOCH_LEN)
+
+ # A szöveg, ahol a konstansokat azok értékével helyettesítjük
+ generated_text = f"Kezdés ideje: {start_time.strftime('%Y-%m-%d %H:%M')}\n"
+ generated_text += f"Befejezés ideje: {finish_time.strftime('%Y-%m-%d %H:%M')}\n"
+ generated_text += f"Ingerlés: \n Az első {c.DELAY / 2} percben nem történik ingerlés az alvás megszilárdulásának elősegítése miatt.\n"
+ generated_text += f"Az utolsó {c.CHECK_LEN} epochban ellenőrzi a feltételek teljesülését.\n"
+ generated_text += f"Audio_feedback történik, ha az N2+N3 valószínűség átlépi a {c.N2_N3} valószínűséget.\n"
+ generated_text += f"Leáll, ha az N3 valószínűsége átlépi a {c.N3} értéket.\n"
+ generated_text += f"A binaurális ütem jobb oldali vivőfrekvenciája {c.FREQUENCY_RIGHT}, a bal {c.FREQUENCY_LEFT} Hz\n"
+ generated_text += f"Az ütem frekvenciája: {c.FREQUENCY_RIGHT-c.FREQUENCY_LEFT}"
+
+ # A generált szöveg mentése a megadott fájlba
+ with open(file_path, "w") as text_file:
+ text_file.write(generated_text)
+
+
+def analyze_file(csv_file_path):
+ a.past_first_N3 = False #a mentéshez az első N3-at ne számolja bele
+ base_dir = "C:\\Users\\pinde\\OneDrive\\Szakdolgozat\\Mérések"
+ today = datetime.now().strftime("%m.%d") # MM.DD formátum
+ save_dir = os.path.join(base_dir, today)
+ counter = 1
+
+ original_save_dir = save_dir
+ while os.path.exists(save_dir):
+ save_dir = f"{original_save_dir}_{c.NAME}_{counter}"
+ counter += 1
+
+ os.makedirs(save_dir)
+
+ df = pd.read_csv(csv_file_path)
+ stages = df['Stage']
+ probabilities = df.iloc[:, 1:] # Az első oszlop a 'Stages', a többi a valószínűsége
+ stages_int = yasa.hypno_str_to_int(stages)
+
+ dict_list = df.to_dict(orient='records')
+ pip_results = [a.check_pip(dict_list[:i + 1]) for i in range(len(dict_list))]
+
+ # Hipnogram ábrázolása, megjelenítése és mentése
+ plt.figure(figsize=(int(len(stages) / 40), 5))
+ hypn = yasa.Hypnogram(stages, freq="30s")
+ hypn.plot_hypnogram(lw=2, fill_color="whitesmoke")
+ hypno_save_path = os.path.join(save_dir, "hypnogram.png")
+ plt.savefig(hypno_save_path)
+ plt.show()
+ plt.close()
+
+ # Valószínűségplot ábrázolása, megjelenítése és mentése
+ colors = ["#99d7f1", "#009DDC", "xkcd:twilight blue", "xkcd:rich purple", "xkcd:sunflower"]
+ ax = probabilities.plot(kind='area', figsize=(int(len(probabilities) / 6), 5), stacked=True, color=colors,
+ alpha=0.8, linewidth=0)
+ ax.set_xlabel('Time (30-sec epoch)')
+ ax.set_ylabel('Probability')
+ ax.legend(frameon=False, bbox_to_anchor=(1, 1))
+
+ for i, result in enumerate(pip_results):
+ if result: # Ha True, akkor kiemeljük az adott szakaszt
+ ax.axvspan(i, i + 1, color='yellow', alpha=0.5) # Kiemelés sárga színnel
+
+ probability_save_path = os.path.join(save_dir, "probability_plot.png")
+ plt.savefig(probability_save_path)
+ plt.show()
+ plt.close()
+
+ # Alvási statisztikák táblázatának ábrázolása, megjelenítése és mentése
+ statistics = yasa.sleep_statistics(stages_int, sf_hyp=1 / 30)
+ stat_df = pd.DataFrame(list(statistics.items()), columns=['Parameter', 'Value'])
+ plt.figure(figsize=(4, 6))
+ plt.title('Sleep Statistics')
+ plt.axis('off')
+ plt.table(cellText=stat_df.values, colLabels=stat_df.columns, loc='center', cellLoc='center', colColours=['lightgray'] * 2)
+ plt.tight_layout()
+ statistics_save_path = os.path.join(save_dir, "sleep_statistics.png")
+ plt.savefig(statistics_save_path)
+ plt.show()
+ plt.close()
+
+ text_file_path = os.path.join(save_dir, "Adatok.txt")
+ txt_maker(text_file_path)
+
+#analyze_file(r'C:\Programkornyezet\PythonProjects\AudiostimulationProject\AudiostimulationDirectory\output_files\04_12_full_night_audio.csv')