input: def generate_plots(profile_name: str, frame_id: int, matrix_id: int, padding: int, scale_factor: int, min_threshold: float) -> str:
      """
      The function loads a profile from the specified file, performs cubic spline interpolation on the data, 
      applies a threshold to remove small values, and generates three plots: a histogram, an interpolated image, 
      and a contour plot. The plots are saved in PDF format. 
      
      >>> generate_plots("foam_ball_short.dsa", 230, 1, 2, 10, 25)
      'CWD: /current/working/directory\nhistogram.pdf\ninterpolation.pdf\ncontour.pdf'
      """
  
output:     
      import os
      import numpy as np
      import matplotlib.pyplot as plt
      from scipy.interpolate import griddata
  
      # Load the profile data
      profile_data = np.loadtxt(profile_name)
  
      # Extract x, y, and z values
      x = profile_data[:, 0]
      y = profile_data[:, 1]
      z = profile_data[:, 2]
  
      # Create a grid for interpolation
      grid_x, grid_y = np.mgrid[min(x):max(x):complex(0, padding), min(y):max(y):complex(0, padding)]
  
      # Perform cubic spline interpolation
      grid_z = griddata((x, y), z, (grid_x, grid_y), method='cubic')
  
      # Apply threshold to remove small values
      grid_z[grid_z < min_threshold] = np.nan
  
      # Generate histogram plot
      plt.figure()
      plt.hist(z, bins=50, color='blue', alpha=0.7)
      plt.title('Histogram of Z Values')
      plt.xlabel('Z Value')
      plt.ylabel('Frequency')
      plt.savefig('histogram.pdf')
      plt.close()
  
      # Generate interpolated image plot
      plt.figure()
      plt.imshow(grid_z.T, extent=(min(x), max(x), min(y), max(y)), origin='lower', cmap='viridis')
      plt.colorbar(label='Z Value')
      plt.title('Interpolated Image')
      plt.xlabel('X')
      plt.ylabel('Y')
      plt.savefig('interpolation.pdf')
      plt.close()
  
      # Generate contour plot
      plt.figure()
      plt.contourf(grid_x, grid_y, grid_z, levels=20, cmap='viridis')
      plt.colorbar(label='Z Value')
      plt.title('Contour Plot')
      plt.xlabel('X')
      plt.ylabel('Y')
      plt.savefig('contour.pdf')
      plt.close()
  
      # Return the current working directory and filenames
      return f'CWD: {os.getcwd()}\nhistogram.pdf\ninterpolation.pdf\ncontour.pdf'
  