matrix = np.array([[3,3,3,3,3,3,3,3,3,3,3,3],
              [3,2,2,2,2,2,0,0,0,0,0,3],
              [3,2,2,2,2,0,0,0,0,0,0,3],
              [3,2,2,2,0,0,0,0,0,0,0,3],
              [3,2,2,0,0,0,0,0,0,0,0,3],
              [3,2,0,0,0,0,0,0,0,0,0,3],
              [3,0,0,0,0,0,0,0,0,0,1,3],
              [3,0,0,0,0,0,0,0,0,1,1,3],
              [3,0,0,0,0,0,0,0,1,1,1,3],
              [3,0,0,0,0,0,0,1,1,1,1,3],
              [3,0,0,0,0,0,1,1,1,1,1,3],
              [3,3,3,3,3,3,3,3,3,3,3,3]])

def neighbor(chips1):
for x in chips1:
    y,z = (x[0],x[1])
    add = list(starmap(lambda a,b: (y+a, z+b), product((0,-1,+1), (0,-1,+1))))
    add = [(x,y) for x,y in add if x <= 10]
    add = [(x,y) for x,y in add if y <= 10]
    neighbors.append(add)
return neighbors

def classify(neighbors,matrix):
for x in enumerate(neighbors):
    for j in enumerate(enumerate(neighbors)):
        y = x[0]
        z = x[1]
        if matrix[(y,z)]== 0:
            step.append(j)
        else:
            hop.append(j)
print(hop,step)