input: def perform_data_analysis_and_plotting(logfile: str, calib_folder: str, instrfile: str) -> None:
      """
      This function performs a series of calculations and generates plots based on input data.
      It loads input data from a log file, performs calibration using data from a calibration folder,
      calculates various values, and generates plots showing absorbed power vs emitted power,
      absorbed power vs reflectivity, and dissipated power vs wavelength. It also calculates thermal
      resistance and displays it on the plot. The plot properties are read from an instruction file.
  
      >>> perform_data_analysis_and_plotting('../24_LL_ev/20150211_sample21-1-d6/spot333um.csv', '../24_LL_ev/20150204_calib_333um_s21-1-d6', '../24_LL_ev/20150211_sample21-1-d6/spot333um_instr.csv')
      None
      """
output:     import pandas as pd
      import matplotlib.pyplot as plt
      import os
  
      # Load log file data
      log_data = pd.read_csv(logfile)
  
      # Load calibration data
      calib_files = [os.path.join(calib_folder, f) for f in os.listdir(calib_folder) if f.endswith('.csv')]
      calib_data = pd.concat([pd.read_csv(f) for f in calib_files])
  
      # Load instruction file
      instr_data = pd.read_csv(instrfile)
  
      # Perform calibration
      log_data['calibrated_power'] = log_data['power'] * calib_data['calibration_factor'].mean()
  
      # Calculate absorbed power vs emitted power
      log_data['absorbed_power'] = log_data['calibrated_power'] - log_data['emitted_power']
  
      # Calculate absorbed power vs reflectivity
      log_data['reflectivity'] = log_data['emitted_power'] / log_data['calibrated_power']
  
      # Calculate dissipated power vs wavelength
      log_data['dissipated_power'] = log_data['absorbed_power'] * (1 - log_data['reflectivity'])
  
      # Calculate thermal resistance
      thermal_resistance = log_data['dissipated_power'].mean() / log_data['temperature'].mean()
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(log_data['emitted_power'], log_data['absorbed_power'], 'o-')
      plt.xlabel('Emitted Power')
      plt.ylabel('Absorbed 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(log_data['reflectivity'], log_data['absorbed_power'], 'o-')
      plt.xlabel('Reflectivity')
      plt.ylabel('Absorbed Power')
      plt.title('Absorbed Power vs 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'], 'o-')
      plt.xlabel('Wavelength')
      plt.ylabel('Dissipated Power')
      plt.title('Dissipated Power vs Wavelength')
      plt.grid(True)
      plt.show()
  
      # Display thermal resistance on the plot
      plt.text(0.5, 0.5, f'Thermal Resistance: {thermal_resistance:.2f}', transform=plt.gca().transAxes, fontsize=12, ha='center')
      plt.show()