def create_fixation_pixellist(self, fixation_list):
# return list of (hi, wi) coord
pixel_list = []
for time, v, _, _ in fixation_list:
theta, phi = head_orientation_lib.vector_to_ang(v)
x, y = head_orientation_lib.ang_to_geoxy(theta, phi, head_orientation_lib.H, head_orientation_lib.W)
pixel_list.append((x, y))
return pixel_list
def pixellist_from_v_list(v_list):
#note, pixellist need to compatible with dataset
#dataset 2: fliplr
#dataset 1: maybe flipud
pixel_list = []
for v in v_list:
theta, phi = head_orientation_lib.vector_to_ang(v)
hi, wi = head_orientation_lib.ang_to_geoxy(theta, phi, head_orientation_lib.H, head_orientation_lib.W)
pixel_list.append([hi, wi])
return pixel_list
def create_fixation_pixelset(self, fixation_list):
# return set of (hi, wi) coord, eliminate redundancy
pixel_set = set()
orifix_list = []
for time, v, _, _ in fixation_list:
theta, phi = head_orientation_lib.vector_to_ang(v)
x, y = head_orientation_lib.ang_to_geoxy(theta, phi, head_orientation_lib.H, head_orientation_lib.W)
if (int(x), int(y)) not in pixel_set:
pixel_set.add((int(x), int(y)))
orifix_list.append([time, v, 0, 0])
return pixel_set, orifix_list
series_t = []
series_v = []
print(f, end='\r')
for item in vector:
if item[0] == f:
series_t.append(item[0])
series_v.append(item[1])
if (len(series_t) != 0):
mean_series_t = np.mean(np.array(series_t)) * dt
mean_series_v = np.mean(np.array(series_v), axis=0)
theta, phi = head_orientation_lib.vector_to_ang(
mean_series_v)
x, y = head_orientation_lib.ang_to_geoxy(
theta, phi, head_orientation_lib.H,
head_orientation_lib.W)
viewport.append([mean_series_t, (x, y)])
pickle.dump(
viewport,
open(
PATH + 'viewport_ds{}_topic{}_user{}'.format(
dataset, topic, user), 'wb'))
user += 1
else:
user = 1
for vector in vector_ds:
viewport = []
print("Usernum={}".format(user))
