def absloc(ndim_M, grid_shape_M, request, loc_with_3coord_M):
if request.param == 'middle':
loc = AbsLoc((np.array(grid_shape_M) - 1) // 2, ndim_M)
assert loc.shape == (1, ndim_M)
return loc
elif request.param == 'end':
loc = AbsLoc(np.array(grid_shape_M) - 1, ndim_M)
assert loc.shape == (1, ndim_M)
return loc
elif request.param == 'origin':
loc = AbsLoc(np.repeat(0, ndim_M), ndim_M)
assert loc.shape == (1, ndim_M)
return loc
elif request.param == '3coord':
loc = loc_with_3coord_M
assert loc.shape == (3, ndim_M)
return loc
raise UserWarning("misconfiguration of test fixture")
def test_visit_counts4(cart_M, agent_id, loc_at_origin_M, loc_at_ones_M):
'''when a distributed agent moves such that two of its coordinates are the
same, ensure we count that visit as 1 rather than 2 visits
'''
# absolute loc at [[0, ...], [1, ...]]
loc_2coords = AbsLoc(np.concatenate(
[loc_at_origin_M, loc_at_ones_M]),
ndim=loc_at_origin_M.shape[1])
# relative loc at [[1, ...], [0, ...]]
relloc = RelLoc(np.zeros(loc_2coords.shape, dtype='int'))
relloc[0] = 1
relloc[-1] = 0
cart_M.add_agent(agent_id, loc_2coords)
cart_M._process_agent_move(agent_id, relloc)
assert (cart_M.visit_counts(loc_2coords + relloc) ==
np.array([1, 1])).all()
# sanity check that the location of each coordinate is the same
newloc = cart_M.agent_location(agent_id)
assert (newloc == newloc[[0]].repeat(2, axis=0)).all()
def loc_at_ones_M(ndim_M):
return AbsLoc(np.ones((1, ndim_M), dtype='int'), ndim_M)
def loc_at_origin_M(ndim_M):
return AbsLoc(np.zeros((1, ndim_M), dtype='int'), ndim_M)
def loc_with_3coord_M(grid_shape_M, ndim_M):
return AbsLoc(np.array([
np.array(grid_shape_M) - 1, # max point on each dimension
(np.array(grid_shape_M) - 1) // 2, # middle point in each dimension
np.repeat(0, ndim_M), # min point on each dimension
], dtype='int'), ndim_M)
def cart_big_twos(cart_big):
return 1 + AbsLoc(np.ones((1, cart_big.grid_ndim), dtype='int'))
def relloc_small():
return AbsLoc((1, -1))
def origin_small():
return AbsLoc((0,0))