CSVVisualizer/CSVVisualizer.py
2025-05-26 20:45:26 +02:00

215 lines
8.2 KiB
Python

# -*- coding: utf-8 -*-
import os
import csv
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from tkinter import Tk, filedialog, messagebox
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import tkinter as tk
from tkinter import ttk
class CSVVisualizer:
def __init__(self, root):
self.root = root
self.root.protocol("WM_DELETE_WINDOW", self.cleanup)
self.root.title("CSV to Graph Converter")
self.root.geometry("1000x700")
# Farben für die Phasen
self.phase_colors = {
"Charge": "#4E79A7", # Blau
"Discharge": "#E15759", # Rot
"Resting (Post-Charge)": "#59A14F", # Grün
"Resting (Post-Discharge)": "#EDC948", # Gelb
"Resting Between Cycles": "#B07AA1", # Lila
"Initial Discharge": "#FF9DA7" # Rosa
}
self.setup_ui()
def setup_ui(self):
"""Erstellt die Benutzeroberfläche"""
main_frame = ttk.Frame(self.root)
main_frame.pack(fill=tk.BOTH, expand=True, padx=10, pady=10)
# Steuerleiste oben
control_frame = ttk.Frame(main_frame)
control_frame.pack(fill=tk.X, pady=(0, 10))
ttk.Button(control_frame, text="CSV auswählen", command=self.load_csv).pack(side=tk.LEFT, padx=5)
ttk.Button(control_frame, text="Grafik speichern", command=self.save_plot).pack(side=tk.LEFT, padx=5)
# Anzeige des aktuellen Dateipfads
self.file_label = ttk.Label(control_frame, text="Keine Datei ausgewählt")
self.file_label.pack(side=tk.LEFT, padx=10, expand=True)
# Plot-Bereich
self.plot_frame = ttk.Frame(main_frame)
self.plot_frame.pack(fill=tk.BOTH, expand=True)
# Platzhalter für den Plot
self.fig, self.ax = plt.subplots(figsize=(10, 5))
self.canvas = FigureCanvasTkAgg(self.fig, master=self.plot_frame)
self.canvas.get_tk_widget().pack(fill=tk.BOTH, expand=True)
# Statusleiste
self.status_var = tk.StringVar()
self.status_var.set("Bereit")
ttk.Label(main_frame, textvariable=self.status_var, relief=tk.SUNKEN).pack(fill=tk.X, pady=(5, 0))
def load_csv(self):
"""Load CSV file with robust error handling for Raspberry Pi"""
filepath = filedialog.askopenfilename(
title="Select CSV File",
filetypes=[("CSV Files", "*.csv"), ("All Files", "*.*")]
)
if not filepath:
return
try:
# First detect problematic lines
good_lines = []
with open(filepath, 'r') as f:
reader = csv.reader(f)
headers = next(reader) # Keep header
for i, row in enumerate(reader):
# Skip summary lines and malformed rows
if not row or len(row) < 4 or row[0].startswith('Cycle'):
continue
# Validate numeric columns
try:
float(row[0]) # Time(s)
float(row[1]) # Voltage(V)
float(row[2]) # Current(A)
good_lines.append(i+1) # +1 to account for header
except ValueError:
continue
if not good_lines:
messagebox.showwarning("Warnung", "Keine gültigen Datenzeilen gefunden.")
self.status_var.set("Keine gültigen Daten")
return
# Now read only valid lines
self.df = pd.read_csv(
filepath,
skiprows=lambda x: x not in good_lines and x != 0, # keep header
dtype={
'Time(s)': 'float32',
'Voltage(V)': 'float32',
'Current(A)': 'float32',
'Phase': 'category',
'Discharge_Capacity(Ah)': 'float32',
'Charge_Capacity(Ah)': 'float32',
'Coulomb_Eff(%)': 'float32',
'Cycle': 'int32'
},
engine='c',
memory_map=True
)
self.file_label.config(text=os.path.basename(filepath))
self.status_var.set(f"Loaded: {len(self.df)} valid measurements")
self.update_plot()
except Exception as e:
messagebox.showerror("Error", f"Failed to load file:\n{str(e)}")
self.status_var.set("Error loading file")
def update_plot(self):
"""Aktualisiert den Plot mit den aktuellen Daten"""
if not hasattr(self, 'df'):
return
df_clean = self.df.copy()
# Zeit relativ zum Start berechnen
start_time = df_clean["Time(s)"].min()
df_clean["Relative_Time(s)"] = df_clean["Time(s)"] - start_time
# Plot zurücksetzen
self.ax.clear()
# Spannung plotten
self.ax.plot(df_clean["Relative_Time(s)"], df_clean["Voltage(V)"],
label="Voltage (V)", color="black", linewidth=1.5)
# Phasen als farbige Hintergründe
start_idx = 0
for i in range(1, len(df_clean)):
if df_clean.iloc[i]["Phase"] != df_clean.iloc[i-1]["Phase"] or i == len(df_clean) - 1:
end_idx = i
start_time_rel = df_clean.iloc[start_idx]["Relative_Time(s)"]
end_time_rel = df_clean.iloc[end_idx]["Relative_Time(s)"]
phase = df_clean.iloc[start_idx]["Phase"]
# Verwende Standardfarbe falls Phase nicht definiert ist
color = self.phase_colors.get(phase, "#CCCCCC")
self.ax.axvspan(start_time_rel, end_time_rel, facecolor=color, alpha=0.3)
start_idx = i
# Legende erstellen
patches = [mpatches.Patch(color=self.phase_colors[phase], label=phase)
for phase in self.phase_colors if phase in df_clean["Phase"].unique()]
# Füge Spannungs-Linie zur Legende hinzu
patches.append(plt.Line2D([0], [0], color='black', label='Voltage (V)'))
self.ax.legend(handles=patches, loc="upper right")
self.ax.set_xlabel("Time (s) since start")
self.ax.set_ylabel("Voltage (V)")
self.ax.set_title("Battery Test Analysis")
self.ax.grid(True)
# Aktualisiere den Canvas
self.canvas.draw()
self.status_var.set("Grafik aktualisiert")
def save_plot(self):
"""Speichert den aktuellen Plot als Bilddatei"""
if not hasattr(self, 'df'):
messagebox.showwarning("Warnung", "Keine Daten zum Speichern vorhanden")
return
filetypes = [
('PNG Image', '*.png'),
('JPEG Image', '*.jpg'),
('PDF Document', '*.pdf'),
('SVG Vector', '*.svg')
]
default_filename = "battery_test_plot.png"
if hasattr(self, 'file_label'):
base = os.path.splitext(self.file_label.cget("text"))[0]
if base:
default_filename = f"{base}_plot.png"
filepath = filedialog.asksaveasfilename(
title="Grafik speichern",
initialfile=default_filename,
filetypes=filetypes,
defaultextension=".png"
)
if filepath:
try:
self.fig.savefig(filepath, dpi=300, bbox_inches='tight')
self.status_var.set(f"Grafik gespeichert als: {os.path.basename(filepath)}")
messagebox.showinfo("Erfolg", "Grafik wurde erfolgreich gespeichert")
except Exception as e:
messagebox.showerror("Fehler", f"Konnte Grafik nicht speichern:\n{str(e)}")
self.status_var.set("Fehler beim Speichern")
def cleanup(self):
"""Perform cleanup before closing"""
if hasattr(self, 'fig'):
plt.close(self.fig)
self.root.destroy()
if __name__ == "__main__":
root = Tk()
app = CSVVisualizer(root)
root.mainloop()