def set_up_neighbor_arrays(self, grid):
     
     # This function gets arrays of neighboring horizontal and vertical
     # links which are needed for the de Almeida solution
     
     # First we identify all active links
     self.active_ids = links.active_link_ids(grid.shape, grid.node_status)
     
     # And then find all horizontal link IDs (Active and Inactive)
     self.horizontal_ids = links.horizontal_link_ids(grid.shape)
     
     # And make the array 1-D
     self.horizontal_ids = self.horizontal_ids.flatten()
     
     # Find all horizontal active link ids
     self.horizontal_active_link_ids = links.horizontal_active_link_ids(grid.shape, self.active_ids)
     
     # Using the horizontal active link ids, we can find the west and east neighbors
     self.west_neighbors = links.find_horizontal_west_neighbor(grid.shape, self.horizontal_active_link_ids)
     self.east_neighbors = links.find_horizontal_east_neighbor(grid.shape, self.horizontal_active_link_ids)
    
     # Now we repeat this process for the vertical links. 
     # First find the vertical link ids and reshape it into a 1-D array
     self.vertical_ids = links.vertical_link_ids(grid.shape).flatten()
     
     # Find the *active* verical link ids
     self.vertical_active_link_ids = links.vertical_active_link_ids(grid.shape, self.active_ids)
     
     # Using the active vertical link ids we can find the north and south vertical neighbors
     self.north_neighbors = links.find_vertical_north_neighbor(grid.shape, self.vertical_active_link_ids)
     self.south_neighbors = links.find_vertical_south_neighbor(grid.shape, self.vertical_active_link_ids)
     
     # Set up arrays for discharge in the horizontal and vertical directions.
     self.q_horizontal = np.zeros(links.number_of_horizontal_links(grid.shape))
     self.q_vertical = np.zeros(links.number_of_vertical_links(grid.shape))
     
     # Once the neighbor arrays are set up, we change the flag to True!
     self.neighbor_flag = True
horizontal_ids = links.horizontal_link_ids(mg.shape)

# Get ids of left-most link ids for boundary issues...
left_inactive_ids = horizontal_ids[:, 0]

# Then we flatten our array so we can use it elsewhere.
horizontal_ids = horizontal_ids.flatten()

# ... and narrow them down to the active horizontal link ids.
horizontal_active_link_ids = links.horizontal_active_link_ids(mg.shape, active_ids)

# Here we actually identify, for each link, the id of its W and E neighbor. For the
# de Almeida solution, horizontal neighbors are west and east. Only
# active link ids are given, any inactive link id is replaced with a '-1'.
west_neighbors = links.find_horizontal_west_neighbor(mg.shape, horizontal_ids)
east_neighbors = links.find_horizontal_east_neighbor(mg.shape, horizontal_active_link_ids)

# Now we do the same with all vertical link ids. First, we get ALL vertical ids.
vertical_ids = links.vertical_link_ids(mg.shape).flatten()

# And then we narrow them down to just the active vertical link ids.
vertical_active_link_ids = links.vertical_active_link_ids(mg.shape, active_ids)

# For the de Almeida solution, we only need N and S neighbors for vertical active links,
# so for each link, the N and S neighbor ids are given by these two function calls. Any
# inactive link id is replaced with an index of '-1'.
north_neighbors = links.find_vertical_north_neighbor(mg.shape, vertical_active_link_ids)
south_neighbors = links.find_vertical_south_neighbor(mg.shape, vertical_active_link_ids)

# To solve this 2-D problem as two 1-D sets, we need to create arrays for
# discharge in the horizontal and vertical directions.