input: Write a function to generate three plots: a histogram, an interpolated image, and a contour plot from a given data file using specific configurations and libraries. The function should perform cubic spline interpolation on the data, apply a threshold to remove small values, and ensure the necessary files and libraries are correctly loaded. The function should return True if the plots are successfully generated and saved, otherwise False.
  
  assert generate_plots_from_file("foam_ball_short.dsa") == True
  assert generate_plots_from_file("nonexistent_file.dsa") == False
  assert generate_plots_from_file("") == False
  assert generate_plots_from_file("correct_file.dsa") == True
output: def generate_plots_from_file(file_path):
      try:
          import numpy as np
          import matplotlib.pyplot as plt
          from scipy.interpolate import griddata
          from scipy.ndimage import gaussian_filter
  
          if not file_path or not os.path.exists(file_path):
              return False
  
          data = np.loadtxt(file_path)
          x, y, z = data[:, 0], data[:, 1], data[:, 2]
  
          # Histogram
          plt.figure()
          plt.hist(z, bins=50, color='blue', edgecolor='black')
          plt.title('Histogram of Z values')
          plt.savefig('histogram.png')
          plt.close()
  
          # Interpolated Image
          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')
          grid_z = gaussian_filter(grid_z, sigma=1)
          plt.figure()
          plt.imshow(grid_z.T, extent=(min(x), max(x), min(y), max(y)), origin='lower', cmap='viridis')
          plt.colorbar(label='Z values')
          plt.title('Interpolated Image')
          plt.savefig('interpolated_image.png')
          plt.close()
  
          # Contour Plot
          plt.figure()
          plt.contourf(grid_x, grid_y, grid_z, levels=50, cmap='viridis')
          plt.colorbar(label='Z values')
          plt.title('Contour Plot')
          plt.savefig('contour_plot.png')
          plt.close()
  
          return True
      except Exception as e:
          return False