class PeriodRadarTestCase(RadarTestCase):
def setUp(self):
self.radar = PeriodRadar(x=200,
y=200,
dt=0.1,
r_std=1.,
theta_std=0.001,
phi_std=0.001,
time_std=0.001)
def test_compute_meas_time(self):
size = 10
computed_meas_times = self.radar.compute_meas_times(size)
self.assertEqual(size, len(computed_meas_times))
# ex_time = 0
# for time in computed_meas_times:
# self.assertTrue(isclose(time,ex_time,rel_tol = self.radar.time_std))
# ex_time = time + self.radar.dt
def test_compute_measurements_tags(self):
position_data = np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2], [3, 3, 3],
[4, 4, 4], [5, 5, 5], [6, 6, 6], [7, 7, 7],
[8, 8, 8], [9, 9, 9]])
self.radar.tag = 0
labeled_measurements = self.radar.compute_measurements(position_data)
for labeled_meas in labeled_measurements:
self.assertEqual(labeled_meas.tag, self.radar.tag)
def setUp(self):
self.radar = PeriodRadar(x=200,
y=200,
dt=0.1,
r_std=1.,
theta_std=0.001,
phi_std=0.001,
time_std=0.001)
def setUp_radars_states(self):
# Radars definitions
dt_rad1 = 0.01
self.radar1 = PeriodRadar(x=2000,y=2000,dt=dt_rad1)
dt_rad2 = 0.02
self.radar2 = PeriodRadar(x=1000,y=1000,dt=dt_rad2)
self.radars = [self.radar1, self.radar2]
# States definition
self.states = np.array([[i,i/2,i/10]*3 for i in range(300)])
def setUp_radar_states(self):
# Radar definition
dt_rad1 = 0.01
self.radar1 = PeriodRadar(x=2000, y=2000, dt=dt_rad1)
dt_rad2 = 0.02
self.radar2 = PeriodRadar(x=1000, y=1000, dt=dt_rad2)
self.radars = [self.radar1, self.radar2]
# States definition
self.states = np.array([[i, i / 2, i / 10] * 3 for i in range(100)])
self.len_elements = int(len(self.states) / self.radar1.step) + int(
len(self.states) / self.radar2.step)
def generate_radars(radar_type):
global std_dict
global prec_dict
global radars
if radar_type == "Radar":
if std_dict["is_chosen"]:
x = int(std_dict["x"])
y = int(std_dict["y"])
std_radar = Radar(x=x,
y=y,
r_std=5.,
theta_std=0.005,
phi_std=0.005)
radars.append(std_radar)
if prec_dict["is_chosen"]:
x = int(prec_dict["x"])
y = int(prec_dict["y"])
prec_radar = Radar(x=x, y=y)
radars.append(prec_radar)
elif radar_type == "PeriodRadar":
if std_dict["is_chosen"]:
x = int(std_dict["x"])
y = int(std_dict["y"])
dt = float(std_dict["dt"])
std_radar = PeriodRadar(x=x,
y=y,
r_std=5.,
theta_std=0.005,
phi_std=0.005,
dt=dt)
radars.append(std_radar)
if prec_dict["is_chosen"]:
x = int(prec_dict["x"])
y = int(prec_dict["y"])
dt = float(prec_dict["dt"])
prec_radar = PeriodRadar(x=x, y=y, dt=dt)
radars.append(prec_radar)
# ==========================================================================
## =================== Standard Radars (same data rates)
## Specify your own radar positions and beliefs over measurements!
# Radar 1: Precision radar
radar1 = Radar(x = -6000, y = 10000)
# Radar 2: Standard radar
radar2 = Radar(x = 1000, y = 8000,
r_std = 5., theta_std = 0.005, phi_std = 0.005)
radars = [radar1,radar2]
## ================== Period Radars (different data rates)
# Radar 1: Precision radar
dt_rad1 = 0.1
pradar1 = PeriodRadar(x = -6000, y = 10000, dt = dt_rad1)
# Radar 2: Standard radar
pradar2 = PeriodRadar(x = 1000, y = 8000, dt = dt_rad2,
r_std = 5., theta_std = 0.005, phi_std = 0.005)
dt_rad2 = 0.4
pradars = [pradar1,pradar2]
# ==========================================================================
# ========================= Detector Generation ============================
# ==========================================================================
## Comment the unused detectors!
detector = None
detector = MahalanobisDetector()
detector = EuclidianDetector()
def test_initialization_noise_finder(self):
self.assertEqual(self.process_noise_finder.radars, [PeriodRadar(x=2000,y=2000,dt=0.01),PeriodRadar(x=1000,y=1000,dt=0.02)])
self.assertTrue(np.array_equal(self.process_noise_finder.states,np.array([[i,i/2,i/10]*3 for i in range(300)])))