input: def generate_plots_and_calculations(logfile: str, calib_folder: str) -> None:
      """
      This function performs a series of calculations and plots based on input data. It 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.
  
      >>> generate_plots_and_calculations('../24_LL_ev/20150211_sample21-1-d6/spot333um.csv', '../24_LL_ev/20150204_calib_333um_s21-1-d6')
      """
output:     import pandas as pd
      import os
      import matplotlib.pyplot as plt
  
      # Load the logfile data
      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])
  
      # Perform calibration
      data['calibrated_emitted_power'] = data['emitted_power'] * calib_data['calibration_factor'].mean()
  
      # Calculate absorbed power
      data['absorbed_power'] = data['emitted_power'] - data['reflected_power']
  
      # Calculate dissipated power
      data['dissipated_power'] = data['absorbed_power'] - data['emitted_power']
  
      # Calculate thermal resistance
      data['thermal_resistance'] = data['dissipated_power'] / data['temperature_change']
  
      # Generate plots
      plt.figure(figsize=(15, 5))
  
      # Plot 1: Absorbed power vs Emitted power
      plt.subplot(1, 3, 1)
      plt.plot(data['emitted_power'], data['absorbed_power'], 'bo-')
      plt.xlabel('Emitted Power')
      plt.ylabel('Absorbed Power')
      plt.title('Absorbed Power vs Emitted Power')
  
      # Plot 2: Absorbed power vs Reflectivity
      plt.subplot(1, 3, 2)
      plt.plot(data['reflected_power'], data['absorbed_power'], 'ro-')
      plt.xlabel('Reflectivity')
      plt.ylabel('Absorbed Power')
      plt.title('Absorbed Power vs Reflectivity')
  
      # Plot 3: Dissipated power vs Wavelength
      plt.subplot(1, 3, 3)
      plt.plot(data['wavelength'], data['dissipated_power'], 'go-')
      plt.xlabel('Wavelength')
      plt.ylabel('Dissipated Power')
      plt.title('Dissipated Power vs Wavelength')
  
      # Display thermal resistance on the plot
      plt.suptitle(f'Thermal Resistance: {data["thermal_resistance"].mean():.2f} K/W')
  
      plt.tight_layout()
      plt.show()