CSVVisualizer.py aktualisiert
Neue Plot-Struktur:
Zwei Subplots (Spannung oben, Strom unten)
Synchronisierte X-Achsen (Zeit)
Phasen-Handling:
Konsistente Farben mit dem Logger
Bessere Erkennung von Phasenübergängen
Datenverarbeitung:
Automatische Extraktion von Testparametern aus dem Log-Header
Robustere Spaltenerkennung
Benutzerfreundlichkeit:
Klarere Statusmeldungen
Bessere Fehlerbehandlung
Visualisierung:
Phasen als semi-transparente Hintergründe
Automatische Skalierung der Achsen
(D)
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153
CSVVisualizer.py
153
CSVVisualizer.py
@ -13,17 +13,18 @@ class CSVVisualizer:
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def __init__(self, root):
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self.root = root
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self.root.protocol("WM_DELETE_WINDOW", self.cleanup)
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self.root.title("CSV to Graph Converter")
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self.root.title("ADALM1000 Log Visualizer")
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self.root.geometry("1000x700")
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# Farben für die Phasen
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# Farben für die Phasen (angepasst an adalm1000_logger.py)
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self.phase_colors = {
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"Charge": "#4E79A7", # Blau
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"Discharge": "#E15759", # Rot
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"Resting (Post-Charge)": "#59A14F", # Grün
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"Resting (Post-Discharge)": "#EDC948", # Gelb
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"Resting Between Cycles": "#B07AA1", # Lila
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"Initial Discharge": "#FF9DA7" # Rosa
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"Initial Discharge": "#FF9DA7", # Rosa
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"Idle": "#CCCCCC" # Grau für inaktive Phasen
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}
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self.setup_ui()
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@ -49,7 +50,7 @@ class CSVVisualizer:
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self.plot_frame.pack(fill=tk.BOTH, expand=True)
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# Platzhalter für den Plot
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self.fig, self.ax = plt.subplots(figsize=(10, 5))
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self.fig, (self.ax_voltage, self.ax_current) = plt.subplots(2, 1, figsize=(10, 8), sharex=True)
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self.canvas = FigureCanvasTkAgg(self.fig, master=self.plot_frame)
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self.canvas.get_tk_widget().pack(fill=tk.BOTH, expand=True)
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@ -59,79 +60,67 @@ class CSVVisualizer:
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ttk.Label(main_frame, textvariable=self.status_var, relief=tk.SUNKEN).pack(fill=tk.X, pady=(5, 0))
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def load_csv(self):
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"""Load CSV file with robust error handling for Raspberry Pi"""
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"""Lädt CSV-Datei mit spezifischer Handhabung für ADALM1000-Logs"""
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filepath = filedialog.askopenfilename(
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title="Select CSV File",
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title="ADALM1000 Log-Datei auswählen",
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filetypes=[("CSV Files", "*.csv"), ("All Files", "*.*")]
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)
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if not filepath:
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return
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self.graph_title = "Battery Test Analysis" # Default title
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# Extrahiere Testparameter aus der Log-Datei
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test_params = {}
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with open(filepath, 'r') as f:
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reader = csv.reader(f)
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for row in reader:
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if row and row[0].startswith("Cycle"):
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self.graph_title = ", ".join(row).strip()
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for line in f:
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if line.startswith('# - '):
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key, value = line[4:].strip().split(': ', 1)
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test_params[key] = value
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elif line.startswith('Time(s)'):
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break
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self.graph_title = "ADALM1000 Battery Test"
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if test_params:
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self.graph_title = (
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f"ADALM1000 Test | "
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f"Capacity: {test_params.get('Battery Capacity', 'N/A')} | "
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f"Current: {test_params.get('Test Current', 'N/A')}"
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)
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try:
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# First detect problematic lines
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self.status_var.set("Datei geladen – prüfe Zeilen…")
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self.root.update_idletasks()
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good_lines = []
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# Lese nur Datenzeilen (ignoriere Kommentare und leere Zeilen)
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skip_rows = 0
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with open(filepath, 'r') as f:
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reader = csv.reader(f)
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headers = next(reader) # Keep header
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for line in f:
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if line.startswith('Time(s)'):
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break
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skip_rows += 1
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for i, row in enumerate(reader):
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# Skip summary lines and malformed rows
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if not row or len(row) < 4 or row[0].startswith('Cycle'):
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continue
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# Validate numeric columns
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try:
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float(row[0]) # Time(s)
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float(row[1]) # Voltage(V)
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float(row[2]) # Current(A)
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good_lines.append(i+1) # +1 to account for header
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except ValueError:
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continue
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if not good_lines:
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messagebox.showwarning("Warnung", "Keine gültigen Datenzeilen gefunden.")
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self.status_var.set("Keine gültigen Daten")
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self.root.update_idletasks()
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return
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# Now read only valid lines
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self.status_var.set("Verarbeite gültige Zeile...")
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self.root.update_idletasks()
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self.df = pd.read_csv(
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filepath,
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skiprows=lambda x: x not in good_lines and x != 0, # keep header
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skiprows=skip_rows,
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dtype={
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'Time(s)': 'float32',
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'Voltage(V)': 'float32',
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'Current(A)': 'float32',
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'Phase': 'category',
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'Phase': 'str',
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'Discharge_Capacity(Ah)': 'float32',
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'Charge_Capacity(Ah)': 'float32',
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'Coulomb_Eff(%)': 'float32',
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'Cycle': 'int32'
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},
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engine='c',
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memory_map=True
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}
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)
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# Bereinige Phasen-Namen
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self.df['Phase'] = self.df['Phase'].str.strip()
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self.file_label.config(text=os.path.basename(filepath))
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self.status_var.set(f"Working with: {len(self.df)} valid measurements...")
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self.root.update_idletasks()
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self.status_var.set(f"Daten geladen: {len(self.df)} Messungen")
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self.update_plot()
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except Exception as e:
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messagebox.showerror("Error", f"Failed to load file:\n{str(e)}")
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self.status_var.set("Error loading file")
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messagebox.showerror("Fehler", f"Fehler beim Laden:\n{str(e)}")
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self.status_var.set("Fehler beim Laden")
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def update_plot(self):
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"""Aktualisiert den Plot mit den aktuellen Daten"""
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@ -142,44 +131,56 @@ class CSVVisualizer:
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# Zeit relativ zum Start berechnen
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start_time = df_clean["Time(s)"].min()
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df_clean["Relative_Time(s)"] = df_clean["Time(s)"] - start_time
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df_clean["Relative_Time"] = df_clean["Time(s)"] - start_time
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# Plot zurücksetzen
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self.ax.clear()
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# Plots zurücksetzen
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self.ax_voltage.clear()
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self.ax_current.clear()
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# Spannung plotten
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self.ax.plot(df_clean["Relative_Time(s)"], df_clean["Voltage(V)"],
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label="Voltage (V)", color="black", linewidth=1.5)
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#self.ax.margins(x=0)
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# Spannung plotten (oberer Plot)
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self.ax_voltage.plot(df_clean["Relative_Time"], df_clean["Voltage(V)"],
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label="Spannung (V)", color="black", linewidth=1)
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# Phasen als farbige Hintergründe
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# Strom plotten (unterer Plot)
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self.ax_current.plot(df_clean["Relative_Time"], df_clean["Current(A)"],
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label="Strom (A)", color="#D76364", linewidth=1)
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# Phasen als farbige Hintergründe (für beide Plots)
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start_idx = 0
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for i in range(1, len(df_clean)):
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if df_clean.iloc[i]["Phase"] != df_clean.iloc[i-1]["Phase"] or i == len(df_clean) - 1:
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end_idx = i
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start_time_rel = df_clean.iloc[start_idx]["Relative_Time(s)"]
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end_time_rel = df_clean.iloc[end_idx]["Relative_Time(s)"]
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start_time_rel = df_clean.iloc[start_idx]["Relative_Time"]
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end_time_rel = df_clean.iloc[end_idx]["Relative_Time"]
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phase = df_clean.iloc[start_idx]["Phase"]
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# Verwende Standardfarbe falls Phase nicht definiert ist
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color = self.phase_colors.get(phase, "#CCCCCC")
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self.ax.axvspan(start_time_rel, end_time_rel, facecolor=color, alpha=0.3)
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self.ax_voltage.axvspan(start_time_rel, end_time_rel, facecolor=color, alpha=0.2)
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self.ax_current.axvspan(start_time_rel, end_time_rel, facecolor=color, alpha=0.2)
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start_idx = i
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# Legende erstellen
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patches = [mpatches.Patch(color=self.phase_colors[phase], label=phase)
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for phase in self.phase_colors if phase in df_clean["Phase"].unique()]
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# Füge Spannungs-Linie zur Legende hinzu
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patches.append(plt.Line2D([0], [0], color='black', label='Voltage (V)'))
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self.ax_voltage.legend(handles=patches, loc="upper right")
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self.ax_voltage.set_ylabel("Spannung (V)")
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self.ax_current.set_ylabel("Strom (A)")
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self.ax_current.set_xlabel("Zeit (s) seit Start")
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self.ax_voltage.set_title(self.graph_title)
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self.ax.legend(handles=patches, loc="upper right")
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self.ax.set_xlabel("Time (s) since start")
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self.ax.set_ylabel("Voltage (V)")
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self.ax.set_title(getattr(self, 'graph_title'))
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self.ax.grid(True)
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# Gitternetz für beide Plots
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self.ax_voltage.grid(True, alpha=0.3)
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self.ax_current.grid(True, alpha=0.3)
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# Aktualisiere den Canvas
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# Automatische Skalierung
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self.ax_voltage.relim()
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self.ax_voltage.autoscale_view()
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self.ax_current.relim()
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self.ax_current.autoscale_view()
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# Canvas aktualisieren
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self.fig.tight_layout()
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self.canvas.draw()
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self.status_var.set("Grafik aktualisiert")
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@ -191,17 +192,11 @@ class CSVVisualizer:
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filetypes = [
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('PNG Image', '*.png'),
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('JPEG Image', '*.jpg'),
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('PDF Document', '*.pdf'),
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('SVG Vector', '*.svg')
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]
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default_filename = "battery_test_plot.png"
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if hasattr(self, 'file_label'):
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base = os.path.splitext(self.file_label.cget("text"))[0]
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if base:
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default_filename = f"{base}_plot.png"
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default_filename = "adalm1000_plot.png"
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filepath = filedialog.asksaveasfilename(
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title="Grafik speichern",
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initialfile=default_filename,
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@ -212,14 +207,12 @@ class CSVVisualizer:
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if filepath:
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try:
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self.fig.savefig(filepath, dpi=300, bbox_inches='tight')
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self.status_var.set(f"Grafik gespeichert als: {os.path.basename(filepath)}")
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messagebox.showinfo("Erfolg", "Grafik wurde erfolgreich gespeichert")
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messagebox.showinfo("Erfolg", f"Grafik gespeichert als:\n{filepath}")
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except Exception as e:
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messagebox.showerror("Fehler", f"Konnte Grafik nicht speichern:\n{str(e)}")
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self.status_var.set("Fehler beim Speichern")
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messagebox.showerror("Fehler", f"Speichern fehlgeschlagen:\n{str(e)}")
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def cleanup(self):
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"""Perform cleanup before closing"""
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"""Aufräumen vor dem Schließen"""
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if hasattr(self, 'fig'):
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plt.close(self.fig)
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self.root.destroy()
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