input: def generate_plots(data_file: str, profile_name: str) -> None:
      """
      This function loads a configuration file and necessary libraries, defines custom colormaps, loads a data 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.
  
      >>> generate_plots("foam_ball_short.dsa", "bds_highcontrast")
      Saves plots as 'histogram.pdf', 'interpolation.pdf', and 'contour.pdf'
      """
      # Function implementation would follow here, similar to the provided code.
output:     
      import numpy as np
      import matplotlib.pyplot as plt
      from scipy.interpolate import griddata
      from scipy.interpolate import interp2d
  
      # Load configuration file and necessary libraries
      config = load_config(profile_name)
  
      # Define custom colormaps
      custom_cmap = plt.get_cmap(config['colormap'])
  
      # Load data file
      data = np.loadtxt(data_file)
  
      # Perform cubic spline interpolation on the data
      x = data[:, 0]
      y = data[:, 1]
      z = data[:, 2]
      grid_x, grid_y = np.mgrid[min(x):max(x):100j, min(y):max(y):100j]
      grid_z = griddata((x, y), z, (grid_x, grid_y), method='cubic')
  
      # Apply a threshold to remove small values
      threshold = config['threshold']
      grid_z[grid_z < threshold] = np.nan
  
      # Generate histogram plot
      plt.figure()
      plt.hist(z, bins=50, color=config['histogram_color'])
      plt.title('Histogram of Data')
      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=custom_cmap)
      plt.colorbar()
      plt.title('Interpolated Image')
      plt.savefig('interpolation.pdf')
      plt.close()
  
      # Generate contour plot
      plt.figure()
      plt.contourf(grid_x, grid_y, grid_z, levels=20, cmap=custom_cmap)
      plt.colorbar()
      plt.title('Contour Plot')
      plt.savefig('contour.pdf')
      plt.close()
  