input: Write a function to load a configuration file, libraries, and data, perform cubic spline interpolation, apply a threshold to remove small values, and generate three plots: a histogram, an interpolated image, and a contour plot. If the code runs successfully, return True; otherwise, return False. Ensure the function handles the necessary parameters and paths for the data and libraries.
  assert visualize_data("../matplotlib/", "../../lib", "../data/foam_ball_short.dsa", 230, 1, 25, 10, "histogram.pdf", "interpolation.pdf", "contour.pdf")==True
  assert visualize_data("wrong_path/", "../../lib", "../data/foam_ball_short.dsa", 230, 1, 25, 10, "histogram.pdf", "interpolation.pdf", "contour.pdf")==False
  assert visualize_data("../matplotlib/", "../../lib", "../data/nonexistent_file.dsa", 230, 1, 25, 10, "histogram.pdf", "interpolation.pdf", "contour.pdf")==False
  assert visualize_data("../matplotlib/", "../../lib", "../data/foam_ball_short.dsa", -1, 1, 25, 10, "histogram.pdf", "interpolation.pdf", "contour.pdf")==False
output: def visualize_data(matplotlib_path, lib_path, data_path, threshold, x_step, y_step, z_step, hist_file, interp_file, contour_file):
      try:
          import sys
          sys.path.append(lib_path)
          import numpy as np
          import matplotlib.pyplot as plt
          from scipy.interpolate import griddata
          import os
  
          if not os.path.exists(matplotlib_path) or not os.path.exists(data_path) or threshold < 0:
              return False
  
          data = np.loadtxt(data_path)
          x, y, z, v = data[:, 0], data[:, 1], data[:, 2], data[:, 3]
  
          grid_x, grid_y, grid_z = np.mgrid[min(x):max(x):x_step, min(y):max(y):y_step, min(z):max(z):z_step]
          grid_v = griddata((x, y, z), v, (grid_x, grid_y, grid_z), method='cubic')
  
          grid_v[grid_v < threshold] = 0
  
          plt.figure()
          plt.hist(v, bins=50)
          plt.savefig(hist_file)
          plt.close()
  
          plt.figure()
          plt.imshow(grid_v[:, :, grid_v.shape[2]//2], extent=(min(x), max(x), min(y), max(y)), origin='lower')
          plt.colorbar()
          plt.savefig(interp_file)
          plt.close()
  
          plt.figure()
          plt.contourf(grid_v[:, :, grid_v.shape[2]//2], extent=(min(x), max(x), min(y), max(y)))
          plt.colorbar()
          plt.savefig(contour_file)
          plt.close()
  
          return True
      except Exception as e:
          return False