input: def perform_calculations_and_plots(logfile: str, calib_folder: str) -> None:
      """
      This script performs a series of calculations and plots based on input data. Before running the main function, run eval_spectrum.py and calibration.py with appropriate measurements. The main function loads the input data, performs calibration, calculates various values, and generates plots. 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.
  
      >>> perform_calculations_and_plots('../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 scipy.constants import Stefan_Boltzmann
  
      # Load the logfile data
      data = pd.read_csv(logfile)
  
      # Load calibration data
      calib_data = pd.read_csv(calib_folder + '/calibration_data.csv')
  
      # Perform calibration
      data['calibrated_power'] = data['power'] * calib_data['calibration_factor']
  
      # Calculate absorbed power
      data['absorbed_power'] = data['calibrated_power'] - data['reflected_power']
  
      # Calculate emitted power using Stefan-Boltzmann law
      data['emitted_power'] = Stefan_Boltzmann * data['temperature']**4
  
      # Calculate reflectivity
      data['reflectivity'] = data['reflected_power'] / data['calibrated_power']
  
      # Calculate dissipated power
      data['dissipated_power'] = data['absorbed_power'] - data['emitted_power']
  
      # Calculate thermal resistance
      data['thermal_resistance'] = (data['temperature'] - data['ambient_temperature']) / data['dissipated_power']
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(data['absorbed_power'], data['emitted_power'], 'bo-')
      plt.xlabel('Absorbed Power (W)')
      plt.ylabel('Emitted Power (W)')
      plt.title('Absorbed Power vs Emitted Power')
      plt.grid(True)
      plt.show()
  
      # Plot absorbed power vs reflectivity
      plt.figure(figsize=(10, 6))
      plt.plot(data['absorbed_power'], data['reflectivity'], 'ro-')
      plt.xlabel('Absorbed Power (W)')
      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(data['wavelength'], data['dissipated_power'], 'go-')
      plt.xlabel('Wavelength (nm)')
      plt.ylabel('Dissipated Power (W)')
      plt.title('Dissipated Power vs Wavelength')
      plt.grid(True)
      plt.show()
  
      # Display thermal resistance on the plot
      plt.figure(figsize=(10, 6))
      plt.plot(data['temperature'], data['thermal_resistance'], 'mo-')
      plt.xlabel('Temperature (K)')
      plt.ylabel('Thermal Resistance (K/W)')
      plt.title('Thermal Resistance vs Temperature')
      plt.grid(True)
      plt.show()
  