input: 
  def generate_plots_and_calculations(logfile: str, calib_folder: str, instrfile: str) -> None:
      """Generate plots and perform calculations based on input data and calibration.
      Load input data, perform calibration, calculate various values, and generate plots
      showing 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', '../24_LL_ev/20150211_sample21-1-d6/spot333um_instr.csv')
      Max emission at (25.0) degC at (1.5) W absorbed power: (0.8) W
      Max emission at (30.0) degC at (2.0) W absorbed power: (1.0) W
      Thermal impedance: (1.2) K/W
      """
  
output:     
      import pandas as pd
      import matplotlib.pyplot as plt
  
      # Load input data
      data = pd.read_csv(logfile)
  
      # Load calibration data
      calib_files = [f for f in os.listdir(calib_folder) if f.endswith('.csv')]
      calib_data = pd.concat([pd.read_csv(os.path.join(calib_folder, f)) for f in calib_files])
  
      # Load instrument file
      instr_data = pd.read_csv(instrfile)
  
      # Perform calibration
      data = pd.merge(data, calib_data, on='timestamp')
  
      # Calculate absorbed power
      data['absorbed_power'] = data['input_power'] - data['reflected_power']
  
      # Calculate emitted power
      data['emitted_power'] = data['absorbed_power'] * data['calibration_factor']
  
      # Calculate reflectivity
      data['reflectivity'] = data['reflected_power'] / data['input_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['absorbed_power']
  
      # Generate plots
      plt.figure(figsize=(15, 5))
  
      # Plot absorbed power vs emitted power
      plt.subplot(1, 3, 1)
      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')
  
      # Plot absorbed power vs reflectivity
      plt.subplot(1, 3, 2)
      plt.plot(data['absorbed_power'], data['reflectivity'], 'ro-')
      plt.xlabel('Absorbed Power (W)')
      plt.ylabel('Reflectivity')
      plt.title('Absorbed Power vs Reflectivity')
  
      # Plot dissipated power vs wavelength
      plt.subplot(1, 3, 3)
      plt.plot(data['wavelength'], data['dissipated_power'], 'go-')
      plt.xlabel('Wavelength (nm)')
      plt.ylabel('Dissipated Power (W)')
      plt.title('Dissipated Power vs Wavelength')
  
      # Display thermal resistance on the plot
      thermal_impedance = data['thermal_resistance'].mean()
      plt.suptitle(f'Thermal Impedance: {thermal_impedance:.2f} K/W')
  
      # Show the plot
      plt.show()
  
      # Print max emission values
      max_emission = data.groupby('temperature')['emitted_power'].max()
      for temp, power in max_emission.items():
          print(f'Max emission at ({temp:.1f}) degC at ({data[data["temperature"] == temp]["absorbed_power"].iloc[0]:.1f}) W absorbed power: ({power:.1f}) W')
  
      # Print thermal impedance
      print(f'Thermal impedance: ({thermal_impedance:.1f}) K/W')
  