input: 
  def data_analysis_and_plotting(logfile: str, calib_folder: str, instrfile: str) -> None:
      """ This function performs a series of calculations and plots based on input data. 
      Before running this script, run eval_spectrum.py and calibration.py with appropriate measurements.
      The function 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.
  
      >>> 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 numpy as np
      import matplotlib.pyplot as plt
      import os
  
      # Load the logfile data
      log_data = pd.read_csv(logfile)
  
      # Load the calibration data
      calib_files = os.listdir(calib_folder)
      calib_data = pd.concat([pd.read_csv(os.path.join(calib_folder, f)) for f in calib_files])
  
      # Load the instrument file data
      instr_data = pd.read_csv(instrfile)
  
      # Perform calibration
      calibrated_data = pd.merge(log_data, calib_data, on='timestamp')
  
      # Calculate absorbed power
      absorbed_power = calibrated_data['emitted_power'] - calibrated_data['reflected_power']
  
      # Calculate dissipated power
      dissipated_power = calibrated_data['emitted_power'] - absorbed_power
  
      # Calculate thermal resistance
      thermal_resistance = np.mean(dissipated_power / absorbed_power)
  
      # Plot absorbed power vs emitted power
      plt.figure(figsize=(10, 6))
      plt.plot(calibrated_data['emitted_power'], absorbed_power, label='Absorbed Power')
      plt.xlabel('Emitted Power')
      plt.ylabel('Absorbed Power')
      plt.title('Absorbed Power vs Emitted Power')
      plt.legend()
      plt.show()
  
      # Plot absorbed power vs reflectivity
      plt.figure(figsize=(10, 6))
      plt.plot(calibrated_data['reflected_power'], absorbed_power, label='Absorbed Power')
      plt.xlabel('Reflectivity')
      plt.ylabel('Absorbed Power')
      plt.title('Absorbed Power vs Reflectivity')
      plt.legend()
      plt.show()
  
      # Plot dissipated power vs wavelength
      plt.figure(figsize=(10, 6))
      plt.plot(calibrated_data['wavelength'], dissipated_power, label='Dissipated Power')
      plt.xlabel('Wavelength')
      plt.ylabel('Dissipated Power')
      plt.title('Dissipated Power vs Wavelength')
      plt.legend()
      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, verticalalignment='center', horizontalalignment='center')
      plt.show()
  