input: 
  from typing import List
  
  def calculate_and_plot(data: List[float], instructions: List[str]) -> None:
      """ Perform a series of calculations and generate plots based on input data and instructions.
      Before running this function, ensure that eval_spectrum.py and calibration.py are executed with appropriate measurements.
      The function loads the input data, performs calibration, calculates various values, and generates plots including:
      1. Absorbed power vs Emitted power
      2. Absorbed power vs Reflectivity
      3. Dissipated power vs Wavelength
      The function also calculates thermal resistance and displays it on the plot.
      
      >>> calculate_and_plot([1.0, 2.0, 3.0], ["instruction1", "instruction2"])
      # Output: No explicit return value, but generates plots as described.
      """
  
output:     import matplotlib.pyplot as plt
      import numpy as np
  
      # Load input data
      absorbed_power = data[0]
      emitted_power = data[1]
      reflectivity = data[2]
      wavelength = np.linspace(1, 10, len(data))
  
      # Perform calibration
      absorbed_power = absorbed_power * 0.9  # Example calibration factor
      emitted_power = emitted_power * 1.1  # Example calibration factor
  
      # Calculate dissipated power
      dissipated_power = absorbed_power - emitted_power
  
      # Plot Absorbed power vs Emitted power
      plt.figure(1)
      plt.plot(absorbed_power, emitted_power, 'bo-')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Emitted Power')
      plt.title('Absorbed Power vs Emitted Power')
      plt.grid(True)
  
      # Plot Absorbed power vs Reflectivity
      plt.figure(2)
      plt.plot(absorbed_power, reflectivity, 'ro-')
      plt.xlabel('Absorbed Power')
      plt.ylabel('Reflectivity')
      plt.title('Absorbed Power vs Reflectivity')
      plt.grid(True)
  
      # Plot Dissipated power vs Wavelength
      plt.figure(3)
      plt.plot(wavelength, dissipated_power, 'go-')
      plt.xlabel('Wavelength')
      plt.ylabel('Dissipated Power')
      plt.title('Dissipated Power vs Wavelength')
      plt.grid(True)
  
      # Calculate thermal resistance
      thermal_resistance = np.mean(dissipated_power) / np.mean(emitted_power)
      plt.text(0.5, 0.5, f'Thermal Resistance: {thermal_resistance:.2f}', transform=plt.gca().transAxes)
  
      # Display plots
      plt.show()