input: def plot_data_and_calculate_thermal_resistance(logfile: str, calib_folder: str) -> None:
      """
      This function loads input data from a log file and a calibration folder, 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:
      >>> plot_data_and_calculate_thermal_resistance('../24_LL_ev/20150211_sample21-1-d6/spot333um.csv', '../24_LL_ev/20150204_calib_333um_s21-1-d6')
      (No return value, but generates plots and prints thermal impedance)
      """
output:     
      import pandas as pd
      import numpy as np
      import matplotlib.pyplot as plt
      import os
  
      # Load log file data
      log_data = pd.read_csv(logfile)
  
      # Load calibration data
      calib_files = os.listdir(calib_folder)
      calib_data = pd.DataFrame()
      for file in calib_files:
          if file.endswith('.csv'):
              calib_data = pd.concat([calib_data, pd.read_csv(os.path.join(calib_folder, file))])
  
      # Perform calibration
      log_data['calibrated_emitted_power'] = log_data['emitted_power'] * calib_data['calibration_factor']
      log_data['calibrated_reflectivity'] = log_data['reflectivity'] * calib_data['calibration_factor']
  
      # Calculate dissipated power
      log_data['dissipated_power'] = log_data['absorbed_power'] - log_data['calibrated_emitted_power']
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(log_data['absorbed_power'], log_data['calibrated_emitted_power'], 'bo')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Calibrated Emitted Power')
      plt.title('Absorbed Power vs Calibrated Emitted Power')
      plt.grid(True)
      plt.show()
  
      # Plot absorbed power vs reflectivity
      plt.figure(figsize=(10, 6))
      plt.plot(log_data['absorbed_power'], log_data['calibrated_reflectivity'], 'ro')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Calibrated Reflectivity')
      plt.title('Absorbed Power vs Calibrated Reflectivity')
      plt.grid(True)
      plt.show()
  
      # Plot dissipated power vs wavelength
      plt.figure(figsize=(10, 6))
      plt.plot(log_data['wavelength'], log_data['dissipated_power'], 'go')
      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(log_data['dissipated_power'] / log_data['temperature_change'])
      print(f'Thermal Resistance: {thermal_resistance:.2f} W/K')
  