ANGLE_stdErrLIN = list()
DISTA_stdErrLIN = list()
ANGLE_stdErrNOL = list()
DISTA_stdErrNOL = list()
for n in range(0, N):
# Adjust Configurations
micA = getPoint(-mic_dist * 1 / 2, +mic_dist * 1 / 2)
micB = getPoint(-mic_dist * 1 / 2, -mic_dist * 1 / 2)
micC = getPoint(+mic_dist * 1 / 2, 0)
micD = getPoint(+mic_dist * 3 / 2, 0)
noise_microphone = 0.003
noise_environment = 0.04
noise_source = 0.01
source_pos = getPoint(dis * np.sin(angle_radians(ang)),
dis * np.cos(angle_radians(ang)))
config = updateConfig(config, micA, micB, micC, micD,
noise_microphone, noise_environment,
noise_source, source_pos)
## Starte Simulation
loaded = simulate(config, config["source_position"],
signal_function)
signals = loaded.get_measurements()
meta = loaded.get_meta_data()
signalA = signals[0]
signalB = signals[1]
signalC = signals[2]
signalD = signals[3]
signalAF = butterWorthFilter(signalA, meta["sampling_rate"], 2000)
)
print(
"arr ; signal ; dist ; angle ; pNoise ; pSigna ; snr_DB ; K_True ; K_Estim ; Dist_Estim",
file=f)
xval = 0.8
arr = "A4"
for signal in ["SX"]: #signals:
for dist in distances:
for angle in anglesA4:
print(arr, signal, angle, dist)
# Determine Sound Source Pos
source_pos = getPoint(
float(dist) *
np.sin(angle_radians(float(angle.replace(",", ".")))),
float(dist) *
np.cos(angle_radians(float(angle.replace(",", ".")))))
# Load Data
data, meta_data = load_measurement(arr, signal, angle, dist)
# Determine SNR
index = keyList.index(arr + "," + signal + "," + dist + "," +
angle)
time_windowNoise = {
"from": limitList[index][0],
"to": limitList[index][1]
}
time_windowSignal = {
"from": limitList[index][2],
error1 = list()
error2 = list()
for d in data:
error1.append(float(d[7]))
error2.append(float(d[11]))
errmax1 = np.max(error1)
errmax2 = np.max(error2)
plt.subplot(1, 2, 1)
plt.grid()
for d in data:
dist = float(d[0])
angl = float(d[1])
distError = float(d[7])
relError = distError / dist
point = getPoint(dist * np.sin(angle_radians(angl)),
dist * np.cos(angle_radians(angl)))
plt.scatter(point[0], point[1], s=1000 * distError / errmax1, c="Black")
#plt.colorbar()
plt.subplot(1, 2, 2)
plt.grid()
for d in data:
dist = float(d[0])
angl = float(d[1])
anglError = float(d[11])
point = getPoint(dist * np.sin(angle_radians(angl)),
dist * np.cos(angle_radians(angl)))
plt.scatter(point[0], point[1], s=1000 * anglError / errmax2, c="Black")
#plt.colorbar()
def getRealDeltaS(source_pos, micAPos, micBPos):
return distance(micAPos, source_pos) - distance(micBPos, source_pos)
def getRealTDOA(source_pos, micAPos, micBPos):
return getRealDeltaS(source_pos, micAPos, micBPos) / 343.3
# Load TimeFrames for Measurements
keyList, limitList = loadTimeWindows()
# Define Array 5
micList = list()
num_mic = 8
mic_dist = 0.38
for i in range(0,num_mic):
micList.append(getPoint(mic_dist*np.sin(angle_radians(360/8*(i))),mic_dist*np.cos(angle_radians(360/8*(i)))))
# Load Measurements
signals = ["CH", "SX"]
distances = ["10", "20", "40", "60", "80"]
anglesA4 = ["00", "22,5", "45", "67,5", "90"]
anglesA5 = ["00", "10", "25"]
file = "results_SSL_LIN_A5M_DesignC.txt"
f = open(file, 'w')
print("arr ; signal ; angle ; dist ; pNoise ; pSigna ; snr_DB ; TDOA_real1 ; TDOA_real2 ; TDOA_CSOM1 ; TDOA_CSOM2 ; angleReal ; angleLIN ; angleNOL ; distanceReal ; distanceLIN ; distanceNOL")
print("arr ; signal ; angle ; dist ; pNoise ; pSigna ; snr_DB ; TDOA_real1 ; TDOA_real2 ; TDOA_CSOM1 ; TDOA_CSOM2 ; angleReal ; angleLIN ; angleNOL ; distanceReal ; distanceLIN ; distanceNOL", file=f)
arr = "A5"
for signal in signals:
for dist in distances:
for xval in [0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95]:
l = list()
for dis in distances:
# print(dis)
lol = list()
for n in range(0, 10):
# dis = 80
ang = 0
# Adjust Configurations
micList = list()
for i in range(0, num_mic):
micList.append(
getPoint(
mic_dist * np.sin(angle_radians(360 / 8 * (2 - i))),
mic_dist * np.cos(angle_radians(360 / 8 * (2 - i)))))
noise_microphone = 0.003
noise_environment = 0.04
noise_source = 0.01
source_pos = getPoint(dis * np.sin(angle_radians(ang)),
dis * np.cos(angle_radians(ang)))
config = updateConfig(config, micList, noise_microphone,
noise_environment, noise_source, source_pos)
# Signal Simulation
loaded = simulate(config, config["source_position"],
signal_function)
signals = loaded.get_measurements()
meta = loaded.get_meta_data()
signalsFiltered = list()
def getRealTDOA(source_pos, micAPos, micBPos):
return getRealDeltaS(source_pos, micAPos, micBPos) / 343.3
# Load TimeFrames for Measurements
keyList, limitList = loadTimeWindows()
# Define Array 5
micList = list()
num_mic = 8
mic_dist = 0.38
for i in range(0, num_mic):
micList.append(
getPoint(mic_dist * np.sin(angle_radians(360 / 8 * (i))),
mic_dist * np.cos(angle_radians(360 / 8 * (i)))))
# Load Measurements
signals = ["CH", "SX"]
distances = ["10", "20", "40", "60", "80"]
anglesA4 = ["00", "22,5", "45", "67,5", "90"]
anglesA5 = ["00", "10", "25"]
file = "results_SSL_LIN_A5M_DesignC.txt"
f = open(file, 'w')
print(
"arr ; signal ; angle ; dist ; pNoise ; pSigna ; snr_DB ; TDOA_real1 ; TDOA_real2 ; TDOA_CSOM1 ; TDOA_CSOM2 ; angleReal ; angleLIN ; angleNOL ; distanceReal ; distanceLIN ; distanceNOL"
)
print(
"arr ; signal ; angle ; dist ; pNoise ; pSigna ; snr_DB ; TDOA_real1 ; TDOA_real2 ; TDOA_CSOM1 ; TDOA_CSOM2 ; angleReal ; angleLIN ; angleNOL ; distanceReal ; distanceLIN ; distanceNOL",
# Load Measurements
signals = ["CH", "SX"]
distances = ["10", "20", "40", "60", "80"]
anglesA4 = ["00", "22,5", "45", "67,5", "90"]
anglesA5 = ["00", "10", "25"]
f = open("CalibrationResultsA4.txt", 'w')
print("arr ; signal ; angle ; dist ; K1 ; K2 ; K3 ; K4 ; K5 ; K6 ; K7 ; K8")
print("arr ; signal ; angle ; dist ; K1 ; K2 ; K3 ; K4 ; K5 ; K6 ; K7 ; K8", file=f)
arr = "A4"
for signal in signals:
for dist in distances:
for angle in anglesA4:
# Determine Sound Source Pos
source_pos = getPoint(float(dist)*np.sin(angle_radians(float(angle.replace(",",".")))), float(dist)*np.cos(angle_radians(float(angle.replace(",",".")))))
# Load Data
data, meta_data = load_measurement(arr, signal, angle, dist)
# Determine SNR
index = keyList.index(arr+","+signal+","+dist+","+angle)
time_windowNoise = {"from" : limitList[index][0], "to": limitList[index][1]}
time_windowSignal = {"from" : limitList[index][2], "to": limitList[index][3]}
# Determine Ks
signalsCut = list()
for d in range(1,9):
timeCut, sigCut = cutSignal(data[d], meta_data, time_windowSignal)
signalsCut.append(sigCut)
K_results = calcKs(signalsCut, meta_data, source_pos, plot_=False)
