def entropies_set(opentraj_root, datasets_name, M=30, replace=False):
entropies_dir = os.path.join(opentraj_root, 'entropies')
if not os.path.exists(entropies_dir): os.makedirs(entropies_dir)
trajectories_set = get_trajlets(opentraj_root, datasets_name)
entropy_values_set = {}
maximum = []
for name in trajectories_set:
if replace == True: R = '-R'
else: R = '-NR'
trajlet_entropy_file = os.path.join(
entropies_dir, name + str(M) + '-entropy' + R + '.npy')
if os.path.exists(trajlet_entropy_file):
entropy_values = np.load(trajlet_entropy_file)
print("loading entropies from: ", trajlet_entropy_file)
else:
entropy_values = get_entropies(opentraj_root,
trajectories_set[name],
name,
M,
replace=replace)
np.save(trajlet_entropy_file, entropy_values)
print("writing entropies ndarray into: ", trajlet_entropy_file)
entropy_values_set.update({name: entropy_values})
if name in reference_folders:
path = os.path.join(opentraj_root, reference_folders[name])
#visualize_max_entropy(trajectories_set[name], np.argmax(entropy_values_set[name]),path,name,replace)
return entropy_values_set
def entropies_set(opentraj_root, datasets_name, M = 30):
entropies_dir = os.path.join(opentraj_root, 'entropies')
if not os.path.exists(entropies_dir): os.makedirs(entropies_dir)
trajectories_set = get_trajlets(opentraj_root,datasets_name)
entropy_values_set = {}
for name in trajectories_set:
trajlet_entropy_file = os.path.join(entropies_dir, name + str(M) + '-entropy.npy')
if os.path.exists(trajlet_entropy_file):
entropy_values = np.load(trajlet_entropy_file)
print("loading entropies from: ", trajlet_entropy_file)
else:
entropy_values = get_entropies(opentraj_root, trajectories_set[name],name, M)
np.save(trajlet_entropy_file, entropy_values)
print("writing entropies ndarray into: ", trajlet_entropy_file)
entropy_values_set.update({name : entropy_values})
return entropy_values_set
dt = np.diff(trajlets_np[:, :, 4], axis=1)
acc_values = np.diff(speed_values, axis=1) / dt
# acc_values = np.abs(acc_values) # FixMe
return np.mean(np.abs(acc_values), axis=1), np.max(np.abs(acc_values), axis=1)
if __name__ == "__main__":
from toolkit.benchmarking.load_all_datasets import get_trajlets, all_dataset_names
opentraj_root = sys.argv[1] # e.g. os.path.expanduser("~") + '/workspace2/OpenTraj'
output_dir = sys.argv[2] # e.g. os.path.expanduser("~") + '/Dropbox/OpenTraj-paper/exp/ver-0.2'
dataset_names = all_dataset_names
# datasets = get_datasets(opentraj_root, dataset_names)
trajlets = get_trajlets(opentraj_root, dataset_names)
print("calculating speed_var indicator ...")
speed_mean_values, speed_var_values = [], []
for ds_name in dataset_names:
speed_mean_values.append(speed_avg_of_trajs(trajlets[ds_name]))
speed_var_values.append(speed_var_of_trajs(trajlets[ds_name]))
print("calculating acceleration indicator ...")
acc_mean_values, acc_max_values = [], []
for ds_name in dataset_names:
acc_mean_values_i, acc_max_values_i = acceleration_of_tarjs(trajlets[ds_name])
acc_mean_values.append(acc_mean_values_i)
acc_max_values.append(acc_max_values_i)
# down-sample values
import plotly.graph_objs as go
from toolkit.benchmarking.load_all_datasets import get_datasets, get_trajlets, all_dataset_names
from toolkit.benchmarking.indicators.motion_properties import speed_avg_of_trajs, acceleration_of_tarjs
from matplotlib import cm
if __name__ == '__main__':
opentraj_root = sys.argv[1]
datasets = get_datasets(opentraj_root, ['KITTI'])
trajlet_sets = get_trajlets(
opentraj_root,
# all_dataset_names[:1]
[
# 'ETH-Univ',
# 'ETH-Hotel',
# 'UCY-Zara',
# 'UCY-Univ',
# 'SDD-coupa',
# 'SDD-bookstore',
# 'SDD-deathCircle',
# 'WildTrack',
# 'KITTI'
'LCas-Minerva',
])
colormap = cm.get_cmap('Reds', 10)
for ds_name, trajlet_set in trajlet_sets.items():
fig = go.Figure()
speed_avg = speed_avg_of_trajs(trajlet_set)
acc_avg, acc_max = acceleration_of_tarjs(trajlet_set)