def create_chaser_model(seg_map=None, locs=None, isovist=None):
if locs is None:
locs = [[0.100, 1 - 0.900], [0.566, 1 - 0.854], [0.761, 1 - 0.665],
[0.523, 1 - 0.604], [0.241, 1 - 0.660], [0.425, 1 - 0.591],
[0.303, 1 - 0.429], [0.815, 1 - 0.402], [0.675, 1 - 0.075],
[0.432, 1 - 0.098]]
if seg_map is None:
seg_map = polygons_to_segments(load_polygons("./paths.txt"))
if isovist is None:
isovist = i.Isovist(load_isovist_map())
model = Chaser(isovist=isovist, locs=locs, seg_map=seg_map)
return model
if __name__ == '__main__':
# XXX This is testing the runner model. We can view samples from the prior
# conditioned [on the variable list below]
#test_chaser()
# setup
locs = [[0.100, 1 - 0.900], [0.566, 1 - 0.854], [0.761, 1 - 0.665],
[0.523, 1 - 0.604], [0.241, 1 - 0.660], [0.425, 1 - 0.591],
[0.303, 1 - 0.429], [0.815, 1 - 0.402], [0.675, 1 - 0.075],
[0.432, 1 - 0.098]]
seg_map = polygons_to_segments(load_polygons("./paths.txt"))
isovist = i.Isovist(load_isovist_map())
polys, epolys = load_segs()
# # for writing the smart preplanned runner
# way_pts = [[0.100, 1-0.9], [.28,.20] , [.26, .32],[.16,.36], [.11, .057], [.179, .086], [.38, .87], [.432, 1-.098]]
# way_pts = np.asarray(way_pts)
# print way_pts
dets = []
simulation_Q_history = []
# TODO: for x simulations
runner_intercepted_cnt = 0
for x in xrange(5):
sim_id = str(int(time.time()))
detection, Q_history = run_simulation(sim_id, locs, seg_map, isovist,
polys, epolys)