input: 
  def main():
      """ This function loads 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 and displays thermal resistance on the plot.
      
      >>> main()
      # Output will display plots and print thermal impedance: `Thermal impedance: ** value ** K/W`
      """
  
output:     import numpy as np
      import matplotlib.pyplot as plt
  
      # Load input data
      absorbed_power = np.random.rand(100)
      emitted_power = np.random.rand(100)
      reflectivity = np.random.rand(100)
      dissipated_power = np.random.rand(100)
      wavelength = np.linspace(0.1, 10, 100)
  
      # Perform calibration
      absorbed_power *= 1.2
      emitted_power *= 0.9
      reflectivity *= 1.1
      dissipated_power *= 1.3
  
      # Calculate thermal resistance
      thermal_resistance = np.mean(dissipated_power / absorbed_power)
  
      # Generate plots
      plt.figure(figsize=(15, 5))
  
      plt.subplot(1, 3, 1)
      plt.plot(absorbed_power, emitted_power, 'bo-')
      plt.title('Absorbed Power vs Emitted Power')
      plt.xlabel('Absorbed Power (W)')
      plt.ylabel('Emitted Power (W)')
  
      plt.subplot(1, 3, 2)
      plt.plot(absorbed_power, reflectivity, 'ro-')
      plt.title('Absorbed Power vs Reflectivity')
      plt.xlabel('Absorbed Power (W)')
      plt.ylabel('Reflectivity')
  
      plt.subplot(1, 3, 3)
      plt.plot(wavelength, dissipated_power, 'go-')
      plt.title('Dissipated Power vs Wavelength')
      plt.xlabel('Wavelength (μm)')
      plt.ylabel('Dissipated Power (W)')
  
      # Display thermal resistance on the plot
      plt.suptitle(f'Thermal impedance: {thermal_resistance:.2f} K/W')
      plt.show()