#!/usr/bin/env python # coding: utf-8 # In[3350]: import tkinter as tk #The main library for GUI design in Python from tkinter import ttk from tkinter import filedialog, Text import tkinter.font as font import os #Allows the GUI to interact with the rest of the PC import numpy as np # Offers more manipulative numeric data types import pandas as pd # Offers CSV reading and data storage import re import matplotlib # Allows us to plot our data import matplotlib.pyplot as plt from matplotlib.backends.backend_tkagg import (FigureCanvasTkAgg, NavigationToolbar2Tk) # Little Documentation from matplotlib.figure import Figure import subprocess # Gives the ability to use "command line" functions from datetime import datetime # Allows us to get the current date and time # In[3351]: #Create a window with a canvas to work off of root = tk.Tk() #root.attributes('-fullscreen', True) root.state("zoomed") canvas = tk.Canvas(root, height = 600, width = 1024, bg = "black") canvas.pack() frame = tk.Frame(root, bg = "white") frame.place(anchor = "c", relwidth = 0.95, relheight = 0.9, relx = 0.5, rely = 0.5) # In[3352]: # Create a figure for the plot to reside fig = Figure(figsize = (6.4, 4.1), dpi = 100) # Create a subplot to add data too plot1 = fig.add_subplot(111) plot1.set_xlabel("Raman Shift", fontsize = 10) plot1.set_ylabel("Intensity (Counts)", fontsize = 10) plot1.set_title("Spectrum", fontsize = 16) plot1.set_xlim(left = 150, right = 4000) plot1.set_ylim(bottom = 0, top = 8000) plot1.plot() # Put the plot in a tkinter canvas plotframe = FigureCanvasTkAgg(fig, master = frame) # Add a toolbar to control the plot toolbar = NavigationToolbar2Tk(plotframe, frame) # Dark set dataframe dark_set = pd.DataFrame() dark_counts_list = list() # Create a global array to hold multiple test sets test_sets_680 = [] test_sets_785 = [] # Create a global to hold our control samples ctrl_680_h2o = pd.DataFrame() ctrl_680_bio = pd.DataFrame() ctrl_785_h2o = pd.DataFrame() ctrl_785_bio = pd.DataFrame() # Global lists to store the x's and y's for future use # 680 h2o h2o_680_cmi_shifted_list = [] h2o_680_dark_list = [] # 680 bio bio_680_cmi_shifted_list = [] bio_680_dark_list = [] # 785 h2o h2o_785_cmi_shifted_list = [] h2o_785_dark_list = [] # 785 bio bio_785_cmi_shifted_list = [] bio_785_dark_list = [] # 680 test test_waves_data = [] test_680_cmi_shifted_list = [] test_680_dark_list = [] # 785 test test_785_cmi_shifted_list = [] test_785_dark_list = [] # Warning flags # Set all to 1 to debug with pre-provided data dark_flag = 0 ctrl_flags = [0, 0, 0, 0] test_flags = [0, 0] # In[3353]: # Function that attatches a plot to the frame def plot(): # Pull the outside plotframe and toolbar, needed to stop the toolbar from duplicating global plotframe global toolbar toolbar.destroy() # containing the Matplotlib figure plotframe = FigureCanvasTkAgg(fig, master = frame) plotframe.draw() # placing the canvas on the Tkinter window plotframe.get_tk_widget().place(x = 390, y = -20) # creating the Matplotlib toolbar toolbar = NavigationToolbar2Tk(plotframe, frame) toolbar.update() # placing the toolbar on the Tkinter window plotframe.get_tk_widget().place() # In[3354]: #Initialize fonts title_font = font.Font(family = "Arial", size = 25) button_font = font.Font(family = "Arial", size = 15) label_font = font.Font(family = "Arial", size = 20, underline = True) ticker_font = font.Font(family = "Arial", size = 16) control_font = font.Font(family = "Arial", size = 12) sample_font = font.Font(family = "Arial", size = 18) dropdown_font = font.Font(family = "Arial", size = 15) laser_font = font.Font(family = "Arial", size = 12) new_label = font.Font(family = "Arial", size = 15) # In[3355]: # RSCL label rscl_text = tk.Label(frame, font = title_font, text = "RSCL", bg = "white", fg = "orange") rscl_text.place(x = 300, y = 10) # In[3356]: # Tries to take a dark, will give an error message if fails def get_spec_dark(int_time): try: # Run OceanDirect Program to get dark subprocess.run(["Release/get_spec.exe", f"{int_time}", "dark.csv"]) # import relevant globals global dark_set global dark_counts_list global dark_flag # Read in dark data and save it to a list dark_set = pd.read_csv('dark.csv', header = None) dark_counts = dark_set.iloc[:, 1] dark_counts_list = dark_counts.values.tolist() # Confirm to the rest of the program that a dark has been collected dark_flag = 1 # Show a error message if the dark fails to collect except FileNotFoundError: tk.messagebox.showwarning(title = "Dark Not Collected", message = "Dark not collected. Please check spectrometer connection.") # In[3357]: #Collect Dark Button collect_dark_btn = tk.Button(frame, text = "Collect Dark", height = 1, width = 14, padx = 10, pady = 5, fg = "white", bg = "gray", command = lambda: get_spec_dark(time.get())) collect_dark_btn.place(x = 25, y = 25) collect_dark_btn["font"] = font.Font(family = "Arial", size = 16) # In[3358]: # Ticker Box for Integration time time_val = tk.IntVar() int_spb = tk.Spinbox(frame, from_ = 1, to = 5000, increment = 1, textvariable = time_val, font = ticker_font, width = 3) int_spb.place(x = 230, y = 80) # In[3359]: # Time variable drop down for integration time root.option_add("*TCombobox*Listbox*Font", ticker_font) OPTIONS = [ "s", "us", ] #etc time_var = tk.StringVar(frame) time_var.set(OPTIONS[0]) # default value int_opt = ttk.Combobox(frame, textvariable = time_var, values = OPTIONS) int_opt.config(width = 3, height = 4, font = dropdown_font) int_opt.place(x = 290, y = 80) # In[3360]: def set_int_time(time_val, time_var): if time_var == "s": time.set((time_val * np.power(10, 6))) else: time.set(time_val) #Integration time Button time = tk.IntVar(value = 1000000) int_time_btn = tk.Button(frame, text = "Set Integration Time", height = 1, width = 14, padx = 10, pady = 5, fg = "white", bg = "gray", command = lambda: set_int_time(time_val.get(), time_var.get())) int_time_btn.place(x = 25, y = 80) int_time_btn["font"] = font.Font(family = "Arial", size = 16) # In[3361]: # Controls Label ctrl_text = tk.Label(frame, font = label_font, text = "Control", bg = "white") ctrl_text.place(x = 25, y = 130) # In[3362]: # Control Sample name label # Controls Label ctrl_sample_text = tk.Label(frame, font = new_label, text = "Control Sample Name:", bg = "white") ctrl_sample_text.place(x = 25, y = 170) # In[3363]: # Control Sample drop down from tkinter import * root.option_add("*TCombobox*Listbox*Font", control_font) TEST_OPTIONS = [ "100%_Water", "100%_Biofuel" ] #etc control_var = tk.StringVar(frame) control_var.set(TEST_OPTIONS[0]) # default value int_opt = ttk.Combobox(frame, textvariable = control_var, values = TEST_OPTIONS) int_opt.config(width = 11, height = 5, font = dropdown_font) int_opt.place(x = 230, y = 170) # In[3364]: # Check to see if a dark has been taken, if so, get the 680 control sample def try_get_ctrl_680(): global dark_flag if dark_flag == 0: tk.messagebox.showwarning(title = "No Dark", message = "You have not collected a dark! Please collect a dark before continuing.") else: get_ctrl("680", time.get()) # In[3365]: # Check to see if a dark has been taken, if so, get the 785 control sample def try_get_ctrl_785(): global dark_flag if dark_flag == 0: tk.messagebox.showwarning(title = "No Dark", message = "You have not collected a dark! Please collect a dark before continuing.") else: get_ctrl("785", time.get()) # In[3366]: # Get Control Function def get_ctrl(laser, int_time): # Call the necessary globals global ctrl_680_h2o global ctrl_680_bio global ctrl_785_h2o global ctrl_785_bio global dark_counts_list global h2o_680_cmi_shifted_list global h2o_680_dark_list global bio_680_cmi_shifted_list global bio_680_dark_list global h2o_785_cmi_shifted_list global h2o_785_dark_list global bio_785_cmi_shifted_list global bio_785_dark_list global ctrl_flags # Clear the plot plot1.clear() # The next four blocks all function the same way as the commented one below if laser == "680": if control_var.get() == "100%_Water": # OceanDirect driver to get spectrum subprocess.run(["Release/get_spec.exe", f"{int_time}", "680_100%_Water.csv"]) # Read spectrum ctrl_680_h2o = pd.read_csv("680_100%_Water.csv", header = None) # Convert wavelengths and counts to list form h2o_680_waves = ctrl_680_h2o.iloc[:, 0] h2o_680_waves_list = h2o_680_waves.values.tolist() h2o_680_counts = ctrl_680_h2o.iloc[:, 1] h2o_680_counts_list = h2o_680_counts.values.tolist() # Dark correct the counts h2o_680_counts_np = np.array(h2o_680_counts_list) dark_counts_np = np.array(dark_counts_list) h2o_dark_np = h2o_680_counts_np - dark_counts_np h2o_680_dark_list = h2o_dark_np.tolist() # Convert the wavelengths to centimeters inverse and Raman Shift them. h2o_cmi = np.power(10, 7)/np.array(h2o_680_waves_list) shift_constant_680 = np.power(10, 7)/680 h2o_cmi_shifted = (shift_constant_680) - (h2o_cmi) h2o_680_cmi_shifted_list = h2o_cmi_shifted.tolist() plot1.plot(h2o_680_cmi_shifted_list, h2o_680_dark_list) # Flip the control flag ctrl_flags[0] = 1 if control_var.get() == "100%_Biofuel": subprocess.run(["Release/get_spec.exe", f"{int_time}", f"680_{control_var.get()}.csv"]) ctrl_680_bio = pd.read_csv('680_100%_Biofuel.csv', header = None) bio_680_waves = ctrl_680_bio.iloc[:, 0] bio_680_waves_list = bio_680_waves.values.tolist() bio_680_counts = ctrl_680_bio.iloc[:, 1] bio_680_counts_list = bio_680_counts.values.tolist() bio_680_counts_np = np.array(bio_680_counts_list) dark_counts_np = np.array(dark_counts_list) bio_dark_np = bio_680_counts_np - dark_counts_np bio_680_dark_list = bio_dark_np.tolist() bio_cmi = np.power(10, 7)/np.array(bio_680_waves_list) shift_constant_680 = np.power(10, 7)/680 bio_cmi_shifted = (shift_constant_680) - (bio_cmi) bio_680_cmi_shifted_list = bio_cmi_shifted.tolist() plot1.plot(bio_680_cmi_shifted_list, bio_680_dark_list) ctrl_flags[1] = 1 if laser == "785": if control_var.get() == "100%_Water": subprocess.run(["Release/get_spec.exe", f"{int_time}", f"785_{control_var.get()}.csv"]) ctrl_785_h2o = pd.read_csv('785_100%_Water.csv', header = None) h2o_785_waves = ctrl_785_h2o.iloc[:, 0] h2o_785_waves_list = h2o_785_waves.values.tolist() h2o_785_counts = ctrl_785_h2o.iloc[:, 1] h2o_785_counts_list = h2o_785_counts.values.tolist() h2o_785_counts_np = np.array(h2o_785_counts_list) dark_counts_np = np.array(dark_counts_list) h2o_dark_np = h2o_785_counts_np - dark_counts_np h2o_785_dark_list = h2o_dark_np.tolist() h2o_cmi = np.power(10, 7)/np.array(h2o_785_waves_list) shift_constant_785 = np.power(10, 7)/785 h2o_cmi_shifted = (shift_constant_785) - (h2o_cmi) h2o_785_cmi_shifted_list = h2o_cmi_shifted.tolist() plot1.plot(h2o_785_cmi_shifted_list, h2o_785_dark_list) ctrl_flags[2] = 1 if control_var.get() == "100%_Biofuel": subprocess.run(["Release/get_spec.exe", f"{int_time}", f"785_{control_var.get()}.csv"]) ctrl_785_bio = pd.read_csv('785_100%_Biofuel.csv', header = None) bio_785_waves = ctrl_785_bio.iloc[:, 0] bio_785_waves_list = bio_785_waves.values.tolist() bio_785_counts = ctrl_785_bio.iloc[:, 1] bio_785_counts_list = bio_785_counts.values.tolist() bio_785_counts_np = np.array(bio_785_counts_list) dark_counts_np = np.array(dark_counts_list) bio_dark_np = bio_785_counts_np - dark_counts_np bio_785_dark_list = bio_dark_np.tolist() bio_cmi = np.power(10, 7)/np.array(bio_785_waves_list) shift_constant_785 = np.power(10, 7)/785 bio_cmi_shifted = (shift_constant_785) - (bio_cmi) bio_785_cmi_shifted_list = bio_cmi_shifted.tolist() plot1.plot(bio_785_cmi_shifted_list, bio_785_dark_list) ctrl_flags[3] = 1 plot1.set_xlabel("Raman Shift", fontsize = 10) plot1.set_ylabel("Intensity (Counts)", fontsize = 10) plot1.set_title("Spectrum", fontsize = 16) plot1.set_xlim(left = 150, right = 4000) plot1.set_ylim(bottom = 0, top = 8000) plot() # In[3367]: # Collect 680 Control Button collect_680_ctrl_btn = tk.Button(frame, text = "Take 680 nm", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: try_get_ctrl_680()) collect_680_ctrl_btn.place(x = 25, y = 210) collect_680_ctrl_btn["font"] = laser_font # In[3368]: # Collect 785 Control Button collect_785_ctrl_btn = tk.Button(frame, text = "Take 785 nm", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: try_get_ctrl_785()) collect_785_ctrl_btn.place(x = 160, y = 210) collect_785_ctrl_btn["font"] = laser_font # In[3369]: # Data Label data_text = tk.Label(frame, font = label_font, text = "Data", bg = "white") data_text.place(x = 25, y = 250) # In[3370]: # Test Number Label test_num_text = tk.Label(frame, font = new_label, text = "Test Number:", bg = "white") test_num_text.place(x = 25, y = 290) # In[3371]: # Ticker Box for Integration time var2 = tk.IntVar() int_spb = tk.Spinbox(frame, from_ = 1, to = 100, increment = 1, textvariable = var2, font = ticker_font, width = 3) int_spb.place(x = 230, y = 290) # In[3372]: # Check to see if four control samples have been taken, one for each laser + control combination. If so get a test sample def try_get_test_680(): global ctrl_flags if ctrl_flags != [1, 1, 1, 1]: tk.messagebox.showwarning(title = "Not Enough Controls", message = "You have not collected all four control samples! Please collect all four control samples before continuing.") else: get_test_680(time.get(), var2.get()) # In[3373]: # Check to see if four control samples have been taken, one for each laser + control combination. If so get a test sample def try_get_test_785(): global ctrl_flags if ctrl_flags != [1, 1, 1, 1]: tk.messagebox.showwarning(title = "Not Enough Controls", message = "You have not collected all four control samples! Please collect all four control samples before continuing.") else: get_test_785(time.get(), var2.get()) # In[3374]: # Function to get a test sample def get_test_680(int_time, testnum): # Call in the relevant globals global test_waves_data global test_sets_680 global dark_counts_list global test_cmi global test_680_cmi_shifted_list global test_680_dark_list global test_flags # Clear the plot plot1.clear() # Check to see if the potential test number is at most one more than the current number of tests taken if len(test_sets_680) + 1 >= testnum: # Run the OceanDirect driver to collect the spectrum subprocess.run(["Release/get_spec.exe", f"{int_time}", f"test{testnum}_680.csv"]) # Check if the test has been taken or not already. If so, we overwrite the data if len(test_sets_680) >= testnum: test_sets_680[testnum - 1] = pd.read_csv(f"test{testnum}_680.csv", header = None) else: test_sets_680.append(pd.read_csv(f"test{testnum}_680.csv", header = None)) # Convert the wavelengths and counts to lists test_waves = test_sets_680[testnum-1].iloc[:, 0] test_waves_list = test_waves.values.tolist() test_counts = test_sets_680[testnum-1].iloc[:, 1] test_counts_list = test_counts.values.tolist() # Dark correct the counts test_counts_np= np.array(test_counts_list) dark_counts_np = np.array(dark_counts_list) test_dark_np = test_counts_np - dark_counts_np test_680_dark_counts = test_dark_np.tolist() # Convert the wavelengths to centimeters inverse test_cmi = np.power(10, 7)/np.array(test_waves_list) shift_constant_680 = np.power(10, 7)/680 # Raman Shift test_cmi_shifted = (shift_constant_680) - (test_cmi) # Same check to determine if an overwrite should occur if len(test_680_cmi_shifted_list) >= testnum: test_680_cmi_shifted_list[testnum - 1] = test_cmi_shifted.tolist() test_680_dark_list[testnum - 1] = test_680_dark_counts test_waves_data[testnum - 1] = test_waves_list else: test_680_cmi_shifted_list.append(test_cmi_shifted.tolist()) test_680_dark_list.append(test_680_dark_counts) test_waves_data.append(test_waves_list) # Plot the data plot1.plot(test_680_cmi_shifted_list[testnum - 1], test_680_dark_list[testnum - 1]) plot1.set_xlabel("Raman Shift", fontsize = 10) plot1.set_ylabel("Intensity (Counts)", fontsize = 10) plot1.set_title("Spectrum", fontsize = 16) plot1.set_xlim(left = 150, right = 4000) plot1.set_ylim(bottom = 0, top = 8000) plot() # Flip the flag to confirm the test was taken test_flags[0] = 1 else: tk.messagebox.showerror(message = "Please take prior tests before continuing.") # In[3375]: def get_test_785(int_time, testnum): global test_sets_785 global dark_counts_list global test_785_cmi_shifted_list global test_785_dark_list global test_flags plot1.clear() if len(test_sets_785) + 1 >= testnum: subprocess.run(["Release/get_spec.exe", f"{int_time}", f"test{testnum}_785.csv"]) if len(test_sets_785) >= testnum: test_sets_785[testnum - 1] = pd.read_csv(f"test{testnum}_785.csv", header = None) else: test_sets_785.append(pd.read_csv(f"test{testnum}_785.csv", header = None)) test_waves = test_sets_785[testnum-1].iloc[:, 0] test_waves_list = test_waves.values.tolist() test_counts = test_sets_785[testnum-1].iloc[:, 1] test_counts_list = test_counts.values.tolist() test_counts_np= np.array(test_counts_list) dark_counts_np = np.array(dark_counts_list) test_dark_np = test_counts_np - dark_counts_np test_785_dark_list = test_dark_np.tolist() test_cmi = np.power(10, 7)/np.array(test_waves_list) shift_constant_785 = np.power(10, 7)/785 test_cmi_shifted = (shift_constant_785) - (test_cmi) if len(test_785_cmi_shifted_list) >= testnum: test_785_cmi_shifted_list[testnum - 1] = test_cmi_shifted.tolist() else: test_785_cmi_shifted_list.append(test_cmi_shifted.tolist()) plot1.plot(test_785_cmi_shifted_list[testnum - 1], test_785_dark_list) plot1.set_xlabel("Raman Shift", fontsize = 10) plot1.set_ylabel("Intensity (Counts)", fontsize = 10) plot1.set_title("Spectrum", fontsize = 16) plot1.set_xlim(left = 150, right = 4000) plot1.set_ylim(bottom = 0, top = 8000) plot() test_flags[1] = 1 else: tk.messagebox.showerror(message = "Please take prior tests before continuing.") # In[3376]: # Collect 680 Test Button collect_680_test_btn = tk.Button(frame, text = "Take 680 nm", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: try_get_test_680()) collect_680_test_btn.place(x = 25, y = 330) collect_680_test_btn["font"] = laser_font # In[3377]: # Collect 785 Test Button collect_785_test_btn = tk.Button(frame, text = "Take 785 nm", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: try_get_test_785()) collect_785_test_btn.place(x = 160, y = 330) collect_785_test_btn["font"] = laser_font # In[3378]: # Percent Label percent_text = tk.Label(frame, font = new_label, text = "Percent H2O:", bg = "white") percent_text.place(x = 430, y = 390) # In[3379]: # Text box to update percentage percent_box = Text(frame, height = 1, width = 5) percent_box.configure(font = new_label) percent_box.place(x = 560, y = 390) # In[3380]: # Check to see if atleast one test sample has been collect with both the 680 and 785 laser. If so plot the graphs and show the percentage def try_plot_concatenate(): global test_flags if test_flags != [1, 1]: tk.messagebox.showwarning(title = "Not Enough Tests", message = "You have not collected test samples for both lasers! Please collect test samples for both lasers before continuing.") else: plot_concatenate(var2.get()) # In[3381]: # Function to plot the controls and currently selected test sample. def plot_concatenate(testnum): # Clear the plot plot1.clear() # Plot the plots plot1.plot(h2o_680_cmi_shifted_list, h2o_680_dark_list, c = "blue") plot1.plot(bio_680_cmi_shifted_list, bio_680_dark_list, c = "green") plot1.plot(test_680_cmi_shifted_list[testnum - 1], test_680_dark_list[testnum - 1], c = "orange") plot1.plot(h2o_785_cmi_shifted_list, h2o_785_dark_list, c = "blue") plot1.plot(bio_785_cmi_shifted_list, bio_785_dark_list, c = "green") plot1.plot(test_785_cmi_shifted_list[testnum - 1], test_785_dark_list, c = "orange") # Array of our m & b found using data analytics coeff = [ 0.19440593616483076, -158.27747274277147] m = coeff[0] b = coeff[1] # Find the maximum peak on the 680 test x = test_waves_data[testnum - 1] y = ctrl_680_bio.iloc[:, 1].values.tolist() max_val = 0 max_index = 0 for i in range(len(list(x))): if x[i] >= 860 and x[i] <=900: if y[i] > max_val: max_val = y[i] max_index = 374 print(max_index) print(max_val) print(test_680_dark_list[testnum - 1][max_index]) # Calculate percentage percent = ((test_680_dark_list[testnum - 1][max_index] * m) + b) percent_box.delete('1.0', END) percent_box.insert(INSERT, f"{percent}%") plot1.set_xlabel("Raman Shift", fontsize = 10) plot1.set_ylabel("Intensity (Counts)", fontsize = 10) plot1.set_title("Spectrum", fontsize = 16) plot1.legend(['Water', 'Biofuel', 'Test']) plot1.set_xlim(left = 150, right = 4000) plot1.set_ylim(bottom = 0, top = 8000) plot() # In[3382]: # Concatenate Button concatenate_btn = tk.Button(frame, text = "Concatenate", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: try_plot_concatenate()) concatenate_btn.place(x = 25, y = 390) concatenate_btn["font"] = laser_font # In[3383]: # Function that creates a folder if one doesn't already exist, and then moves the relevant files to that folder, while also # appending a timestamp to prevent overwrite. def save_data(): date = datetime.now().strftime("%m_%d_%Y_%I_%M_%p") try: os.mkdir("Saved_Data") except: pass try: os.replace("dark.csv", f"Saved_Data/dark_{date}.csv") except: pass try: os.replace("680_100%_Water.csv", f"Saved_Data/680_100%_Water_{date}.csv") except: pass try: os.replace("680_100%_Biofuel.csv", f"Saved_Data/680_100%_Biofuel_{date}.csv") except: pass try: os.replace("785_100%_Water.csv", f"Saved_Data/785_100%_Water_{date}.csv") except: pass try: os.replace("785_100%_Biofuel.csv", f"Saved_Data/785_100%_Biofuel_{date}.csv") except: pass for i in range(len(test_sets_680)): try: os.replace(f"test{i + 1}_680.csv", f"Saved_Data/test{i + 1}_680_{date}.csv") except: pass for i in range(len(test_sets_785)): try: os.replace(f"test{i + 1}_785.csv", f"Saved_Data/test{i + 1}_785_{date}.csv") except: pass # In[3384]: # Save data button save_data_btn = tk.Button(frame, text = "Save Data", height = 1, width = 12, padx = 7, pady = 3, fg = "white", bg = "gray", command = lambda: save_data()) save_data_btn.place(x = 825, y = 390) save_data_btn["font"] = laser_font # In[3386]: plot() root.mainloop() # In[ ]: # Delete files in order to free up space and ensure no data is reused on the next use of the device. try: os.remove("dark.csv") except: pass try: os.remove("680_100%_Water.csv") except: pass try: os.remove("680_100%_Biofuel.csv") except: pass try: os.remove("785_100%_Water.csv") except: pass try: os.remove("785_100%_Biofuel.csv") except: pass for i in range(len(test_sets_680)): try: os.remove(f"test{i + 1}_680.csv") except: pass for i in range(len(test_sets_785)): try: os.remove(f"test{i + 1}_785.csv") except: pass