From 1507a506ba362c9a31eadc8c553bdbea935dcd3d Mon Sep 17 00:00:00 2001 From: TheOriginalGraLargeShrimpakaReaper Date: Fri, 18 Oct 2024 15:35:22 +0200 Subject: [PATCH] final branch commit --- code/corelation.py | 6 ++---- data/final/gramic_sleep_hr_correlation.png | Bin 39782 -> 40753 bytes 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/code/corelation.py b/code/corelation.py index 3e2eef0..96d8126 100644 --- a/code/corelation.py +++ b/code/corelation.py @@ -116,7 +116,7 @@ print(f"Die Korrelation zwischen der durchschnittlichen Herzfrequenz und der Sch # plt.savefig(graphic_corr_path) # plt.show() -# Schritt 5: Visualisiere den Zusammenhang zwischen Herzfrequenz und Schlafdauer (invertierte y-Achse) +# Schritt 5: Visualisiere den Zusammenhang zwischen Schlafdauer und Herzfrequenz plt.figure(figsize=(10, 6)) plt.scatter(combined_data['Durchschnittliche Dauer'], combined_data['avg_hr'], color='blue', label='Datenpunkte') plt.title('Zusammenhang zwischen Schlafdauer und Herzfrequenz (Durchschnitt)') @@ -124,16 +124,14 @@ plt.xlabel('Schlafdauer (Stunden)') plt.ylabel('Durchschnittliche Herzfrequenz (bpm)') plt.grid(True) -# Berechne und zeichne die Trendlinie (umgekehrt) +# Berechne und zeichne die Trendlinie m, b = np.polyfit(combined_data['Durchschnittliche Dauer'], combined_data['avg_hr'], 1) plt.plot(combined_data['Durchschnittliche Dauer'], m * combined_data['Durchschnittliche Dauer'] + b, color='red', label=f'Trendlinie (Kor = {correlation:.2f})') -plt.gca().invert_yaxis() # Y-Achse invertieren, da die Herzfrequenz auf der Y-Achse ist plt.legend() plt.savefig(graphic_corr_path) plt.show() - # Schritt 6: Erstelle eine Grafik pro Kalenderwoche (HR und Schlafdaten) fig, ax1 = plt.subplots(figsize=(30, 8)) # Breitere Darstellung diff --git a/data/final/gramic_sleep_hr_correlation.png b/data/final/gramic_sleep_hr_correlation.png index 4157e7fc7332c0e95bf115878818141034657b46..7dc0aa2dc494fdeed252dbbbcbd2584d56d86c29 100644 GIT binary patch literal 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