Add files via upload

initial commit

spectra_entropy3.py

@@ -0,0 +1,135 @@
+import tkinter as tk
+from tkinter import filedialog, messagebox
+import re
+import csv
+from pathlib import Path
+import threading
+import math
+
+
+
+
+class Application(tk.Tk):
+    def __init__(self):
+        super().__init__()
+
+        self.title("Spectra Entropy Calculator")
+        self.geometry("400x400")
+        self.file_paths = []
+
+        self.upload_button = tk.Button(self, text="Upload files", command=self.upload_files)
+        self.upload_button.pack(pady=10)
+
+        self.file_listbox = tk.Listbox(self)
+        self.file_listbox.pack(pady=10)
+
+        self.start_button = tk.Button(self, text="Start", command=self.start_processing)
+        self.start_button.pack(pady=10)
+
+        self.iconbitmap(r'C:\Users\Figeys Lab M5846\PycharmProjects\pythonProject\icon.ico')
+
+    def upload_files(self):
+        filenames = filedialog.askopenfilenames(filetypes=(("MS1 files", "*.ms1"), ("All files", "*.*")))
+        for file in filenames:
+            if file not in self.file_paths:
+                self.file_paths.append(file)
+                self.file_listbox.insert('end', file)
+
+    def start_processing(self):
+        if not self.file_paths:
+            messagebox.showerror("error", "Please upload the file first.")
+            return
+
+        self.processed_files = 0
+        for file_path in self.file_paths:
+            thread = threading.Thread(target=self.process_file, args=(file_path,))
+            thread.start()
+
+
+        messagebox.showinfo("Running", "File uploaded successfully, please wait.")
+
+    def process_file(self, file_path):
+        # Read the file
+        with open(file_path, "r") as file:
+            ms1 = file.read().splitlines()
+
+        # Function to calculate entropy
+        def cal_entropy(intensities):
+            I = [i / sum(intensities) for i in intensities]
+            IlnI = [-i * math.log(i) for i in I if i > 0]  # Exclude zero intensities to avoid log(0)
+            entropy = sum(IlnI)
+            return entropy
+
+        # Remove empty spectra
+        rt_indices = [i for i, s in enumerate(ms1) if "RTime" in s]
+        tic_indices = [i for i, s in enumerate(ms1) if "TIC" in s]
+        remove_indices = [i for i in rt_indices if (i + 3) not in tic_indices]
+
+        new_indices = []
+        for i in remove_indices:
+            new_indices.extend([i - 1, i - 2])
+        remove_indices.extend(new_indices)
+
+        remove_indices = set(remove_indices)
+        ms1 = [s for i, s in enumerate(ms1) if i not in remove_indices]
+
+
+
+        # Extract TIC, BPM, RT, and Scan
+        tic = [re.search(r'TIC\t(.*)', s).group(1) for s in ms1 if "TIC" in s]
+        bpm = [re.search(r'BPM\t(.*)', s).group(1) for s in ms1 if "BPM" in s]
+        rt = [re.search(r'RTime\t(.*)', s).group(1) for s in ms1 if "RTime" in s]
+        scan = [re.search(r'scan=(.*)', s).group(1) for s in ms1 if "scan" in s]
+
+        # Pre-process MS1 data for entropy calculation
+        ms1 = ms1[5:]
+        ms1.append("S")
+        scan_index = [i for i, s in enumerate(ms1) if "scan" in s]
+        s_index = [i for i, s in enumerate(ms1) if "S" in s]
+        ion_count = [s_index - scan_index - 5 for s_index, scan_index in zip(s_index, scan_index)]
+
+
+        # Calculate entropy for each spectrum
+        spec_entr = []
+        for i in range(len(s_index)):
+            c = ms1[(scan_index[i] + 5):(s_index[i] - 1)]
+            intensities = []
+            for line in c:
+                parts = line.split(" ")
+                if len(parts) == 2:
+                    try:
+                        intensity = float(parts[1])
+                        intensities.append(intensity)
+                    except ValueError:
+                        continue
+            spec_entr.append(cal_entropy(intensities))
+
+        spec_entr_n = [e / math.log(count) for e, count in zip(spec_entr, ion_count)]
+
+        # Create a list of results
+        spec_entr_table = zip(spec_entr, spec_entr_n, ion_count, tic, rt, scan, bpm)
+
+        # Save the results
+        output_file = Path(file_path).with_suffix('.csv')
+        with open(output_file, 'w', newline='') as csvfile:
+            csvwriter = csv.writer(csvfile)
+            csvwriter.writerow(
+                ["spectra entropy", "normalized spectra entropy", "number of peaks", "TIC", "RT", "scan", "BPM"])
+            for row in spec_entr_table:
+                csvwriter.writerow(row)
+
+        # 处理完成后增加已处理文件数量
+        self.processed_files += 1
+
+        # 当所有文件都处理完成时，显示成功消息
+        if self.processed_files == len(self.file_paths):
+            self.show_success_message()
+
+    def show_success_message(self):
+        messagebox.showinfo("Success", "All files have been dealt with.")
+
+
+
+if __name__ == "__main__":
+    app = Application()
+    app.mainloop()