input: def analyze_power_thermal_data(logfile: str, calib_folder: str) -> None:
      """ This function analyzes power and thermal data from a given logfile and calibration folder.
      Before running this script, eval_spectrum.py and calibration.py should be executed with appropriate measurements.
      The script imports necessary modules and functions from external sources. The main function loads the input data,
      performs calibration, calculates various values, and generates plots based on instructions provided in a separate
      text file. The generated plots show absorbed power vs emitted power, absorbed power vs reflectivity, and dissipated
      power vs wavelength. The script also calculates thermal resistance and displays it on the plot.
      Example:
      >>> analyze_power_thermal_data('../24_LL_ev/20150211_sample21-1-d6/spot333um.csv', '../24_LL_ev/20150204_calib_333um_s21-1-d6')
      """
output:     import pandas as pd
      import numpy as np
      import matplotlib.pyplot as plt
      from calibration import calibrate_data
      from eval_spectrum import calculate_spectrum
  
      # Load the logfile data
      data = pd.read_csv(logfile)
  
      # Load calibration data
      calib_data = pd.read_csv(f"{calib_folder}/calibration_data.csv")
  
      # Perform calibration
      calibrated_data = calibrate_data(data, calib_data)
  
      # Calculate spectrum values
      spectrum_data = calculate_spectrum(calibrated_data)
  
      # Extract necessary values
      absorbed_power = spectrum_data['absorbed_power']
      emitted_power = spectrum_data['emitted_power']
      reflectivity = spectrum_data['reflectivity']
      dissipated_power = spectrum_data['dissipated_power']
      wavelength = spectrum_data['wavelength']
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(absorbed_power, emitted_power, marker='o')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Emitted Power')
      plt.title('Absorbed Power vs Emitted Power')
      plt.grid(True)
      plt.show()
  
      # Plot absorbed power vs reflectivity
      plt.figure(figsize=(10, 6))
      plt.plot(absorbed_power, reflectivity, marker='o')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Reflectivity')
      plt.title('Absorbed Power vs Reflectivity')
      plt.grid(True)
      plt.show()
  
      # Plot dissipated power vs wavelength
      plt.figure(figsize=(10, 6))
      plt.plot(wavelength, dissipated_power, marker='o')
      plt.xlabel('Wavelength')
      plt.ylabel('Dissipated Power')
      plt.title('Dissipated Power vs Wavelength')
      plt.grid(True)
      plt.show()
  
      # Calculate thermal resistance
      thermal_resistance = np.mean(dissipated_power / emitted_power)
      print(f"Thermal Resistance: {thermal_resistance:.2f} W/K")