def SI(json_simulated, position_simulated):
"""
Generate a the list of coordinatesfor each agent mentionned
in the standardised JSON file filled with measured information
Args:
json_simulated : JSON file in the standardised format of the
main program, filled with simulated measured information
position_simulated : list of measured coordinates of each agent
Output:
listeposbis : list of coordinates for each agent deduced thanks
to SI fusion
"""
listepos = []
SI_list = soft_information.parse_scenario(
'soft_information\data\data_simulated.json')
positions, _ = soft_information.compute_positions(SI_list,
len(position_simulated),
listepos)
listeposbis = []
for pos in positions:
listeposbis.append([int(pos[0]), int(pos[1])])
return (listeposbis)
import soft_information
import time
pas_temps = 10
listepos = []
listepos_temps = []
while (1):
SI_list = soft_information.parse_scenario(
'soft_information/data/si1_2.json')
positions, _ = soft_information.compute_positions(SI_list, 2, listepos)
T = soft_information.get_time()
# print(positions.round(3))
listepos += [positions.round(3)]
listepos_temps.append([T[-1], positions.round(3)])
print(listepos_temps[-1])
time.sleep(pas_temps)
import soft_information
pas_temps = 1
listepos = [] #initialisation de la liste des positions
listepos_temps = [] #initialisation de la liste des temps
SI_list = soft_information.parse_scenario(
'data_simulated.json') #extraction des données
positions, _ = soft_information.compute_positions(
SI_list, 4, listepos
) #Utilisation de la fonction compute_positions dans le init avec 4 points
print(positions.round(3))