code: def sample_random_position(grid):
      obstacles_grid = grid[0, :, :, 0]
      x_coords, y_coords = np.argwhere(obstacles_grid == 0).T
      position = np.random.randint(x_coords.size)
      return (x_coords[position], y_coords[position])
  
file_path: neupy/examples/reinforcement_learning/vin/visualize.py
imports: from itertools import product
  import numpy
  import matplotlib.pyplot
  import matplotlib.gridspec
  import matplotlib.patches
  from neupy import storage
  from loaddata import load_data
  from train_vin import parser, create_VIN
  from settings import environments
  from evaluation import detect_trajectory
label_desc: Use image node_id 2 for calling a global function with example usage: sample_random_position(grid) and returns: x_coords,  y_coords