input: def perform_calculations_and_plots(logfile: str, calib_folder: str, instrfile: str) -> None:
      """Performs a series of calculations and plots based on input data. Before running this function, 
      ensure that eval_spectrum.py and calibration.py have been executed with appropriate measurements. 
      This function loads the input data, performs calibration, 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.
      >>> perform_calculations_and_plots('../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')
      """
output:     
      import pandas as pd
      import numpy as np
      import matplotlib.pyplot as plt
  
      # Load the logfile data
      log_data = pd.read_csv(logfile)
  
      # Load the calibration data
      calib_data = pd.read_csv(calib_folder + '/calibration_data.csv')
  
      # Load the instrument file data
      instr_data = pd.read_csv(instrfile)
  
      # Perform calibration
      log_data['calibrated_power'] = log_data['power'] * calib_data['calibration_factor']
  
      # Calculate absorbed power
      log_data['absorbed_power'] = log_data['calibrated_power'] - instr_data['emitted_power']
  
      # Calculate reflectivity
      log_data['reflectivity'] = 1 - (log_data['absorbed_power'] / log_data['calibrated_power'])
  
      # Calculate dissipated power
      log_data['dissipated_power'] = log_data['absorbed_power'] * (1 - log_data['reflectivity'])
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(log_data['emitted_power'], log_data['absorbed_power'], 'bo-')
      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'], 'ro-')
      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'], '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}')
  