input: Write a function to load a data file, perform cubic spline interpolation on the data, apply a threshold to remove small values, and generate three plots: a histogram, an interpolated image, and a contour plot. The function should ensure all necessary libraries are loaded and paths are correctly set. It should also define and register custom colormaps for plotting.
  assert process_data("foam_ball_short.dsa", 230, 1, 10, 25, 50) == True
  assert process_data("nonexistent_file.dsa", 230, 1, 10, 25, 50) == False
  assert process_data("foam_ball_short.dsa", 999, 1, 10, 25, 50) == False
  assert process_data("foam_ball_short.dsa", 230, 1, 10, 100, 150) == True
  assert process_data("foam_ball_short.dsa", 230, 1, 10, 0, 0) == True
output: 
  def process_data(file_path, threshold, x_scale, y_scale, x_range, y_range):
      try:
          import numpy as np
          import matplotlib.pyplot as plt
          from scipy.interpolate import griddata
          from scipy.interpolate import CubicSpline
          from scipy.ndimage import gaussian_filter
          from matplotlib.colors import ListedColormap
  
          data = np.loadtxt(file_path)
          x, y, z = data[:, 0], data[:, 1], data[:, 2]
  
          x_new = np.linspace(min(x), max(x), x_range)
          y_new = np.linspace(min(y), max(y), y_range)
          X, Y = np.meshgrid(x_new, y_new)
  
          cs = CubicSpline(x, y)
          Z = griddata((x, y), z, (X, Y), method='cubic')
          Z[Z < threshold] = 0
  
          custom_cmap = ListedColormap(['blue', 'green', 'yellow', 'red'])
          plt.register_cmap(name='CustomCmap', cmap=custom_cmap)
  
          plt.figure(figsize=(15, 5))
  
          plt.subplot(131)
          plt.hist(z, bins=50, color='skyblue', edgecolor='black')
          plt.title('Histogram of Data')
  
          plt.subplot(132)
          plt.imshow(Z, extent=(min(x), max(x), min(y), max(y)), origin='lower', cmap='CustomCmap')
          plt.colorbar()
          plt.title('Interpolated Image')
  
          plt.subplot(133)
          plt.contourf(X, Y, Z, levels=20, cmap='CustomCmap')
          plt.colorbar()
          plt.title('Contour Plot')
  
          plt.show()
          return True
      except Exception as e:
          return False
  