def plt_pob_siz_results(plt_file_name = None):
mdl_name = "list_len_mdl.h5"
opt = Options()
pob_siz_len = np.arange(start=3, stop=11,step=2) #not even steps needed
# pob_siz_len =[5,3,5,9,1]
results_success_rate_map_zero = []
results_astar_diff = []
for p in pob_siz_len:
opt.pob_siz = p
opt.state_siz = (p * opt.cub_siz) ** 2
print("start with opt.pob_siz: {}".format(opt.pob_siz))
print("start with opt.state_siz: {}".format(opt.state_siz))
map_ind = opt.map_ind
opt.map_ind = 0
get_data(opt)#generaten new data with the map 0
opt.map_ind = map_ind
train_model(opt, mdl_name, epochs=EPOCHS)
[success_rate, astar_diff] = test_model(opt,mdl_name)
results_success_rate_map_zero.append(success_rate)
results_astar_diff.append(astar_diff)
# Four polar axes
f, axarr = plt.subplots(1,2)
axarr[0].scatter(pob_siz_len, results_success_rate_map_zero)
axarr[0].set_ylabel(r'success rate',usetex=True)
axarr[1].scatter(pob_siz_len, results_astar_diff)
# axarr[1].set_title('difference to astar in number of steps')
axarr[1].set_ylabel(r'mean difference to astar in steps',usetex=True)
axarr[0].set_xlabel(r'view size',usetex=True)
axarr[1].set_xlabel(r'view size',usetex=True)
helper_save(plt_file_name)
def plt_heat_map_results(plt_file_name = None):
opt = Options()
opt.disp_on = False
pob_siz_len = np.arange(start=3, stop=11,step=2) #not even steps needed
hist_len = np.arange(start=1, stop=5)
# pob_siz_len =[5,3,5,9,1]
results_success_rate_map_zero = []
results_astar_diff = []
cnt_Test=0
with K.get_session():
for p in pob_siz_len:
opt.pob_siz = p
opt.state_siz = (p * opt.cub_siz) ** 2
print("start with opt.pob_siz: {}".format(opt.pob_siz))
print("start with opt.state_siz: {}".format(opt.state_siz))
# get_data(opt)#generaten new data
for l in hist_len:
opt.hist_len = l
print("start with opt.hist_len: {}".format(opt.hist_len))
# train_model(opt, mdl_name,epochs=EPOCHS)
# [success_rate, astar_diff] = test_model(opt,mdl_name)
# results_success_rate_map_zero.append(success_rate)
results_success_rate_map_zero.append(cnt_Test)
cnt_Test1+=1
# results_astar_diff.append(astar_diff)
results_success_rate_map_zero=np.array(results_success_rate_map_zero)
plt.imshow(results_success_rate_map_zero.reshape(len(pob_siz_len),len(hist_len)), cmap='hot', interpolation='nearest')
plt.colorbar()
# plt.show()
helper_save(plt_file_name)
