agent = agent[0] - min_y, agent[1] - min_x
items = [((y - min_y, x - min_x), p) for (y, x), p in items]
path = [(y - min_y, x - min_x) for (y, x) in path]
# print size_x
# exit()
import numpy as np
np.set_printoptions(edgeitems=3200, linewidth=10000, precision=3)
world = ItemPickWorld.ItemPickWorld()
world.items = items
# world.map = np.zeros((32, 32))
world.map = np.zeros((size_y, size_x))
world.agent = agent
world.path = path
world.s = world.map.shape[0] * world.map.shape[1]
world.eval_id = eval_id
import pickle
# pickle.dump(world, open("dump/sample_world_" + str(eval_id) + ".pkl", "w"))
pickle.dump(
world, open("../experiment/dump/sample_world_" + str(eval_id) + ".pkl",
"w"))
exit()
import graph_world2
graph_world2.GraphWorld(world, 0.5)
world.show_world(path, save=True)
# world.show_world([], save=True)
prob_data = [{k: v[1] for k, v in u.viewitems()} for u in format_data]
human = np.zeros((len(prob_data), 10, 4))
for i, d in enumerate(prob_data):
for k, v in d.viewitems():
human[i][k - 1] = v
# top = np.zeros((11, 10, 4))
bottom = np.zeros((11, 10, 4))
# bottom2 = np.zeros((11, 10, 4))
for beta in range(0, 11):
for eval_id in range(1, 11):
world = pickle.load(
open("dump/sample_world_" + str(eval_id) + ".pkl", "r"))
wb = graph_world2.GraphWorld(world, 0.4, 0.1 * beta)
_, b, _ = wb.check_action(wb.base_action)
bottom[beta, eval_id - 1] = b[answer_index[eval_id]]
bottom[beta] = bottom[beta] / np.sum(bottom[beta], axis=1, keepdims=True)
print bottom
# for h in human:
# values = []
# for beta in range(0, 11):
# values.append(scipy.stats.pearsonr(h.flatten(), bottom[beta].flatten())[0])
# print np.argmax(np.array(values))
task_bb = []
task_b = []
task_t = []
for h in human:
}
top = np.zeros((10, 4))
bottom = np.zeros((10, 4))
bottom2 = np.zeros((10, 4))
# for eval_id in range(1, 11):
for eval_id in range(1, 11):
# for eval_id in [5]:
# for beta in range(10):
# for beta in [5]:
for beta in [4]:
# for beta in [5]:
world = pickle.load(
open("dump/sample_world_" + str(eval_id) + ".pkl", "r"))
wb = graph_world2.GraphWorld(world, 0.5, 0.5)
_, b, _ = wb.check_action(wb.base_action)
# wti graph_world2.GraphWorld(world, 0.5)
# world.show_world([], True)
# exit()
# wt= graph_world2.GraphWorld(world, beta*0.1)
# wb= graph_world2.GraphWorld(world, beta*0.1)
# wt= graph_world2.GraphWorld(world, 0.4)
# wb= graph_world2.GraphWorld(world, 0.4, 0.7)
# wb2= graph_world2.GraphWorld(world, 0.5)
wt = graph_world2.GraphWorld(world, 0.5)
wb = graph_world2.GraphWorld(world, 0.5, 0.5)
wb2 = graph_world2.GraphWorld(world, 0.5)
# t, _ = wt.check_action(wt.base_action)
t, _, _ = wt.check_action(wt.base_action)
_, b, _ = wb.check_action(wb.base_action)
bottom="off",
left="off")
plt.gca().set_aspect('equal', adjustable='box')
if save:
# plt.savefig("data/eval_" + str(self.eval_id) + "/stimuli.jpg", bbox_inches="tight")
plt.savefig("data/eval_" + str(self.eval_id) + "/stimuli.eps",
bbox_inches="tight",
format="eps",
str=s)
# plt.show()
if __name__ == '__main__':
world = ItemPickWorld()
import graph_world2
graph = graph_world2.GraphWorld(world)
exit()
world.show_world([
(1, 1),
(1, 2),
(1, 3),
(1, 4),
(2, 4),
(3, 4),
(4, 4),
(5, 4),
(6, 4),
(7, 4),
(8, 4),
(9, 4),
(10, 4),