def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
client.squeeze = False
sensor_config = configs.IQServiceConfig()
sensor_config.sensor = args.sensors
sensor_config.range_interval = [0.2, 1.0]
sensor_config.profile = sensor_config.Profile.PROFILE_2
sensor_config.sampling_mode = sensor_config.SamplingMode.B
sensor_config.hw_accelerated_average_samples = 20
sensor_config.downsampling_factor = 2
session_info = client.setup_session(sensor_config)
pg_updater = PGUpdater(sensor_config, None, session_info)
pg_process = PGProcess(pg_updater)
pg_process.start()
client.start_session()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
while not interrupt_handler.got_signal:
data_info, data = client.get_next()
try:
pg_process.put_data(data)
except PGProccessDiedException:
break
print("Disconnecting...")
pg_process.close()
client.disconnect()
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = clients.SocketClient(args.socket_addr)
elif args.spi:
client = clients.SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = clients.UARTClient(port)
client.squeeze = False
sensor_config = get_sensor_config()
processing_config = get_processing_config()
sensor_config.sensor = args.sensors
session_info = client.setup_session(sensor_config)
pg_updater = PGUpdater(sensor_config, processing_config, session_info)
pg_process = PGProcess(pg_updater)
pg_process.start()
client.start_session()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
processor = Processor(sensor_config, processing_config, session_info)
while not interrupt_handler.got_signal:
info, data = client.get_next()
plot_data = processor.process(data)
if plot_data is not None:
try:
pg_process.put_data(plot_data)
except PGProccessDiedException:
break
print("Disconnecting...")
pg_process.close()
client.disconnect()
def check_connection(args):
print("Checking connection to radar")
try:
if args.socket_addr:
client = clients.SocketClient(args.socket_addr)
elif args.spi:
client = clients.SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = clients.UARTClient(port)
client.connect()
client.disconnect()
return True
except Exception:
print()
traceback.print_exc()
print()
return False
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
filename = "data.h5"
if os.path.exists(filename):
print("File '{}' already exists, won't overwrite".format(filename))
sys.exit(1)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.update_rate = 30
session_info = client.setup_session(config)
recorder = recording.Recorder(sensor_config=config,
session_info=session_info)
client.start_session()
n = 100
for i in range(n):
data_info, data = client.get_next()
recorder.sample(data_info, data)
print("Sampled {:>4}/{}".format(i + 1, n), end="\r", flush=True)
print()
client.disconnect()
record = recorder.close()
os.makedirs(os.path.dirname(filename), exist_ok=True)
recording.save(filename, record)
print("Saved to '{}'".format(filename))
def setup(request):
conn_type, *args = request.param
if conn_type == "spi":
client = clients.SPIClient()
sensor = 1
elif conn_type == "uart":
port = args[0] or utils.autodetect_serial_port()
client = clients.UARTClient(port)
sensor = 1
elif conn_type == "socket":
client = clients.SocketClient(args[0])
sensor = int(args[1])
elif conn_type == "mock":
client = clients.MockClient()
sensor = 1
else:
pytest.fail()
client.connect()
yield (client, sensor)
client.disconnect()
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
# Normally when using a single sensor, get_next will return
# (info, data). When using mulitple sensors, get_next will return
# lists of info and data for each sensor, i.e. ([info], [data]).
# This is commonly called squeezing. To disable squeezing, making
# get_next _always_ return lists, set:
# client.squeeze = False
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.range_interval = [0.2, 1] # Range configuration
config.update_rate = 50 # Data collection frequency
session_info = client.setup_session(config)
print("Session info:\n", session_info, "\n")
# Now would be the time to set up plotting, signal processing, etc.
client.start_session()
# Normally, hitting Ctrl-C will raise a KeyboardInterrupt which in
# most cases immediately terminates the script. This often becomes
# an issue when plotting and also doesn't allow us to disconnect
# gracefully. Setting up an ExampleInterruptHandler will capture the
# keyboard interrupt signal so that a KeyboardInterrupt isn't raised
# and we can take care of the signal ourselves. In case you get
# impatient, hitting Ctrl-C a couple of more times will raise a
# KeyboardInterrupt which hopefully terminates the script.
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session\n")
# Here we make use of multiprocessing to run the data collection, sound wave computation, and
# audio output separately. the intrerrupt_handler is passed in
# so that the processes are stopped when a user hits Ctrl-C.
with multiprocessing.Manager() as manager:
shared_value = manager.Value(
'd', 0) # Shared variable to control the determined frequency.
shared_amp = manager.Value(
'd',
0) # Shared variable to control when a sound should be played.
shared_wave = multiprocessing.Array('d', 4410) # Shared Array
p1 = multiprocessing.Process(target=data_handler,
args=(client, interrupt_handler,
shared_value, shared_amp))
p2 = multiprocessing.Process(target=tune_gen,
args=(interrupt_handler, shared_value,
shared_amp, shared_wave))
p3 = multiprocessing.Process(target=tune_play,
args=(interrupt_handler, shared_wave))
# Start processes
p1.start()
p2.start()
p3.start()
# Wait for processes to terminate before moving on
p1.join()
p2.join()
p3.join()
print("Disconnecting...")
client.disconnect()
def main():
# To simplify the examples, we use a generic argument parser. It
# lets you choose between UART/SPI/socket, set which sensor(s) to
# use, and the verbosity level of the logging.
args = utils.ExampleArgumentParser().parse_args()
# The client logs using the logging module with a logger named
# acconeer.exptool.*. We call another helper function which sets up
# the logging according to the verbosity level set in the arguments:
# -q or --quiet: ERROR (typically not used)
# default: WARNING
# -v or --verbose: INFO
# -vv or --debug: DEBUG
utils.config_logging(args)
# Pick client depending on whether socket, SPI, or UART is used
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
# Create a configuration to run on the sensor. A good first choice
# is the envelope service, so let's pick that one.
config = configs.EnvelopeServiceConfig()
# In all examples, we let you set the sensor(s) via the command line
config.sensor = args.sensors
# Set the measurement range [meter]
config.range_interval = [0.2, 0.3]
# Set the target measurement rate [Hz]
config.update_rate = 10
# Other configuration options might be available. Check out the
# example for the corresponding service/detector to see more.
client.connect()
# In most cases, explicitly calling connect is not necessary as
# setup_session below will call connect if not already connected.
# Set up the session with the config we created. If all goes well,
# some information/metadata for the configured session is returned.
session_info = client.setup_session(config)
print("Session info:\n", session_info, "\n")
# Now would be the time to set up plotting, signal processing, etc.
# Start the session. This call will block until the sensor has
# confirmed that it has started.
client.start_session()
# Alternatively, start_session can be given the config instead. In
# that case, the client will call setup_session(config) for you
# before starting the session. For example:
# session_info = client.start_session(config)
# As this will call setup_session in the background, this will also
# connect if not already connected.
# In this simple example, we just want to get a couple of sweeps.
# To get a sweep, call get_next. get_next will block until the sweep
# is recieved. Some information/metadata is returned together with
# the data.
f = open("demo.txt","a");
for i in range(3):
data_info, data = client.get_next()
print("Sweep {}:\n".format(i + 1), data_info, "\n", data, "\n")
f.write(numpy.array2string(data) + "\n")
f.close()
# We're done, stop the session. All buffered/waiting data is thrown
# away. This call will block until the server has confirmed that the
# session has ended.
client.stop_session()
# Calling stop_session before disconnect is not necessary as
# disconnect will call stop_session if a session is started.
# Remember to always call disconnect to do so gracefully
client.disconnect()
def main():
args = utils.ExampleArgumentParser(num_sens=1).parse_args()
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.IQServiceConfig()
config.sensor = args.sensors
config.update_rate = 10
session_info = client.setup_session(config)
depths = utils.get_range_depths(config, session_info)
amplitude_y_max = 1000
fig, (amplitude_ax, phase_ax) = plt.subplots(2)
fig.set_size_inches(8, 6)
fig.canvas.set_window_title("Acconeer matplotlib example")
for ax in [amplitude_ax, phase_ax]:
ax.set_xlabel("Depth (m)")
ax.set_xlim(config.range_interval)
ax.grid(True)
amplitude_ax.set_ylabel("Amplitude")
amplitude_ax.set_ylim(0, 1.1 * amplitude_y_max)
phase_ax.set_ylabel("Phase")
utils.mpl_setup_yaxis_for_phase(phase_ax)
amplitude_line = amplitude_ax.plot(depths, np.zeros_like(depths))[0]
phase_line = phase_ax.plot(depths, np.zeros_like(depths))[0]
fig.tight_layout()
plt.ion()
plt.show()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
client.start_session()
while not interrupt_handler.got_signal:
info, data = client.get_next()
amplitude = np.abs(data)
phase = np.angle(data)
max_amplitude = np.max(amplitude)
if max_amplitude > amplitude_y_max:
amplitude_y_max = max_amplitude
amplitude_ax.set_ylim(0, 1.1 * max_amplitude)
amplitude_line.set_ydata(amplitude)
phase_line.set_ydata(phase)
if not plt.fignum_exists(1): # Simple way to check if plot is closed
break
fig.canvas.flush_events()
print("Disconnecting...")
plt.close()
client.disconnect()
def main():
parser = utils.ExampleArgumentParser()
add_args(parser)
args = parser.parse_args()
if args.model_file_name:
filename = args.model_file_name
else:
print("Not implemented!")
sys.exit(1)
keras_proc = kp.MachineLearning()
model_data, message = keras_proc.load_model(filename)
print(message.replace("<br>", "\n"))
if not model_data["loaded"]:
return False
config = model_data["sensor_config"]
feature_list = model_data["feature_list"]
frame_settings = model_data["frame_settings"]
print("\nFeature detection settings:")
for setting in frame_settings:
if "label" in setting:
continue
print("{}: {}".format(setting, frame_settings[setting]))
feature_process = feature_proc.FeatureProcessing(config)
feature_process.set_feature_list(feature_list)
feature_process.set_frame_settings(frame_settings)
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
session_info = client.setup_session(config)
interrupt_handler = utils.ExampleInterruptHandler()
print("\nPress Ctrl-C to end session")
client.start_session()
while not interrupt_handler.got_signal:
info, sweep = client.get_next()
data = {
"sweep_data": sweep,
"sensor_config": config,
"session_info": session_info,
}
ml_frame_data = feature_process.feature_extraction(data)
feature_map = ml_frame_data["current_frame"]["feature_map"]
complete = ml_frame_data["current_frame"]["frame_complete"]
if complete and feature_map is not None:
predict = keras_proc.predict(feature_map)[0]
label = predict["prediction"]
confidence = predict["confidence"]
print("Prediction: {:10s} ({:6.2f}%)\r".format(
label, confidence * 100),
end="")
print("Disconnecting...")
client.disconnect()
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = clients.SocketClient(args.socket_addr)
elif args.spi:
client = clients.SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = clients.UARTClient(port)
client.squeeze = False
range_start = 0.18
range_end = 0.60
num = int((range_end*100-range_start*100)/6)+1
sensor_config = configs.SparseServiceConfig()
sensor_config.sensor = args.sensors
sensor_config.range_interval = [range_start, range_end]
sensor_config.sweeps_per_frame = 16
sensor_config.hw_accelerated_average_samples = 60
sensor_config.sampling_mode = sensor_config.SamplingMode.A
sensor_config.profile = sensor_config.Profile.PROFILE_2
sensor_config.gain = 0.6
session_info = client.setup_session(sensor_config)
# pg_updater = PGUpdater(sensor_config, None, session_info)
# pg_process = PGProcess(pg_updater)
# pg_process.start()
client.start_session()
storage = []
counter = 0
sample = 300
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
temp = np.zeros(num)
#端末からデータを受け取り、フレームに入っているsweepの平均を取得し、tempに追加
while not interrupt_handler.got_signal:
data_info, data = client.get_next()
counter += 1
for sweep in data[0]:
temp = temp + sweep
temp = temp/len(data[0])
storage.append(temp)
temp = np.zeros(int(num))
if(counter >= sample):
break
#300個のフレームから距離ごとに平均を取得
# result = np.zeros(len(storage[0]))
# for data in storage:
# result = result + data
# result = result/len(storage)
# clr=plt.rcParams['axes.prop_cycle'].by_key()['color']
roop_count = 0
prev_getData = np.loadtxt('sparse.csv')
#生データ300個のフレームの平均を表示
show_raw_data = np.zeros(int(num))
for frame in storage:
show_raw_data += frame
show_curr_RawData = show_raw_data/sample
##保存していたデータの生データ300個のフレームの平均
show_prev_RawData = []
for data in prev_getData:
show_prev_RawData.append(np.sum(data)/sample)
x = np.arange(range_start*100,range_end*100+1,6)
plt.subplot(1,3,1)
plt.plot(x,show_curr_RawData,color='r')
plt.title("Raw Data(Current)")
plt.xlabel("Distance(cm)")
plt.ylabel("Amptitude")
plt.subplot(1,3,2)
plt.plot(x,show_prev_RawData,color='b')
plt.title("Raw Data(Previous)")
plt.xlabel("Distance(cm)")
plt.ylabel("Amptitude")
plt.subplot(1,3,3)
plt.title("Raw Data(Compare)")
plt.plot(x,show_curr_RawData,color='r')
plt.plot(x,show_prev_RawData,color='b')
plt.xlabel("Distance")
plt.ylabel("Amptitude")
# plt.tight_layout()
# plt.show()
# exit(1)
#データを別々に表示
for i in range(num):
show_data = []
plt.subplot(math.ceil(num/2),4,roop_count*2+1)
plt.title(str(range_start*100+i*6)+"cm(Current)")
plt.xlabel("Quantity")
plt.ylabel("Amptitude")
for j in range(len(storage)):
show_data.append(storage[j][i])
plt.plot(range(1,sample+1),show_data,color='r')
plt.subplot(math.ceil(num/2),4,roop_count*2+2)
plt.title(str(range_start*100+i*6)+"cm(Previous)")
plt.plot(range(1,sample+1),prev_getData[i],color='b')
plt.xlabel("Quantity")
plt.ylabel("Amptitude")
roop_count += 1
# plt.tight_layout()
# plt.show()
#データをあわせて表示
for i in range(num):
show_data = []
plt.subplot(math.ceil(num/2),2,i+1)
for j in range(len(storage)):
show_data.append(storage[j][i])
plt.plot(range(1,sample+1),show_data,color='r',label="Current Data")
plt.title(str(range_start*100+i*6)+"cm(Combination)")
plt.plot(range(1,sample+1),prev_getData[i],color='b',label="Previous Data")
plt.xlabel("Quantity")
plt.ylabel("Amptitude")
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0,fontsize='small')
# plt.tight_layout()
# plt.show()
#ある距離の時系列データの遷移とそのデータのヒストグラムの表示
now_getData = []
for i in range(num):
show_data = []
# plt.subplot(math.ceil(num/2),2,i+1)
plt.subplot(math.ceil(num/2),4,i*2+1)
plt.title(str(range_start*100+i*6)+"cm")
plt.xlabel("Distance")
plt.ylabel("Amptitude")
for j in range(len(storage)):
show_data.append(storage[j][i])
now_getData.append(show_data)
# ヒストグラムの作成と表示
# hist, bins = np.histogram(show_data,density=True)
plt.plot(range(1,sample+1),show_data,color = "tomato")
plt.subplot(math.ceil(num/2),4,i*2+2)
plt.hist(show_data,bins=10,density=True,color = "aqua")
plt.title(str(range_start*100+i*6)+"cm")
plt.xlabel("Class")
plt.ylabel("Frequency")
# print("ヒストグラムの度数"+str(hist[0]))
# print("階級を区切る値"+str(hist[1]))
# plt.tight_layout()
# plt.show()
#ndarray型に変換し、保存
# now_getData = np.array(now_getData)
# np.savetxt('sparse.csv',now_getData)
# exit(1)
roop_count = 0
prev_getData = np.loadtxt('sparse.csv')
KL_storage = []
JS_storage = []
#ヒストグラムの度数からKLを算出
for i in zip(prev_getData,now_getData):
plt.subplot(math.ceil(num/2),4,roop_count*2+1)
plt.title(str(range_start*100+roop_count*6)+"cm(Previous)")
plt.xlabel("Distance")
plt.ylabel("Frequency")
now_hist = plt.hist(i[0],bins=10,color = "lime")
now_hist = normalization(np.array(now_hist[0]))
# now_hist_normalization = normalization(np.array(now_hist[0]))
# now_hist[0] = now_hist_normalization
# print(now_hist)
plt.subplot(math.ceil(num/2),4,roop_count*2+2)
plt.title(str(range_start*100+roop_count*6)+"cm(Now)")
plt.xlabel("Distance")
plt.ylabel("Frequency")
prev_hist = plt.hist(i[1],bins=10,color = "deepskyblue")
prev_hist = normalization(np.array(prev_hist[0]))
# print("now_histの要素の数: "+str(len(now_hist[0])))
# print("prev_histの要素の数: "+str(len(now_hist[0])))
KL_value = KLdivergence(now_hist,prev_hist)
print(str(range_start*100+roop_count*6)+"cm時のKL_Divergence: "+str(KL_value))
JS_value = JSdivergence(now_hist,prev_hist)
print(str(range_start*100+roop_count*6)+"cm時のJS_Divergence: "+str(JS_value)+"\n")
KL_storage.append(KL_value)
JS_storage.append(JS_value)
roop_count += 1
# plt.tight_layout()
# plt.show()
temp_KLlist = []
temp_store_KLlist = []
temp_JSlist = []
temp_store_JSlist = []
temp_KLlist.append(np.array(KL_storage))
temp_JSlist.append(np.array(JS_storage))
#ファイルからデータを読みこむ
store_KLarr = np.loadtxt("KLDivergence_Sparse.csv",delimiter = ",")
store_JSarr = np.loadtxt("JSDivergence_Sparse.csv",delimiter = ",")
temp_store_KLlist.append(store_KLarr)
temp_store_JSlist.append(store_JSarr)
#データを追加
store_KLarr = np.empty((0,num),int)
store_JSarr = np.empty((0,num),int)
for data in temp_store_KLlist:
print(data)
store_KLarr = np.append(store_KLarr,np.array(data),axis=0)
# store_KLarr = np.append(store_KLarr,np.array(temp_store_KLlist),axis=0)
for data in temp_store_KLlist:
store_JSarr = np.append(store_JSarr,np.array(data),axis=0)
# store_JSarr = np.append(store_JSarr,np.array(temp_store_JSlist),axis=0)
store_KL = np.append(store_KLarr,np.array(temp_KLlist),axis=0)
store_JS = np.append(store_JSarr,np.array(temp_JSlist),axis=0)
#ファイルを保存
store_KL = np.savetxt("KLDivergence_Sparse.csv",store_KL,delimiter=",")
store_JS = np.savetxt("JSDivergence_Sparse.csv",store_JS,delimiter=",")
#KL,JSの平均値
# print("KL_Divergenceの平均値: "+str(np.sum(np.array(KL_storage))/num)+"\n")
# print("JS_Divergenceの平均値: "+str(np.sum(np.array(JS_storage))/num)+"\n")
#KLとJSを可視化
X = list(range(int(range_start*100),int(range_end*100+1),6))
plt.subplot(1,3,1)
# plt.plot(range(len(KL_storage)),KL_storage,color='r',marker="o")
plt.plot(X,KL_storage,color='r',marker="o")
plt.title("KL Divergence")
plt.xlabel("Distance")
plt.ylabel("Amptitude")
plt.subplot(1,3,2)
plt.plot(X,JS_storage,color='b',marker="o")
plt.title("JS Divergence")
plt.xlabel("Distance")
plt.ylabel("Amptitude")
plt.subplot(1,3,3)
plt.plot(X,KL_storage,color='r',marker="o")
plt.plot(X,JS_storage,color='b',marker="o")
# plt.plot(X,KL_strage,color='r',marker="o",linewidth=0)
# plt.plot(X,JS_strage,color='b',marker="o",linewidth=0)
plt.title("Compare")
plt.xlabel("Distance")
plt.ylabel("Amptitude")
# plt.tight_layout()
# plt.show()
print("Disconnecting...")
client.disconnect()
def main():
parser = utils.ExampleArgumentParser()
parser.add_argument("-o", "--output-dir", type=str, required=True)
parser.add_argument("--file-format", type=str, default="h5")
parser.add_argument("--frames-per-file", type=int, default=10000)
args = parser.parse_args()
utils.config_logging(args)
if os.path.exists(args.output_dir):
print("Directory '{}' already exists, won't overwrite".format(args.output_dir))
sys.exit(1)
file_format = args.file_format.lower()
if file_format == "np":
file_format = "npz"
if file_format not in ["h5", "npz"]:
print("Unknown format '{}'".format(args.file_format))
sys.exit(1)
if args.frames_per_file < 10:
print("Frames per file must be at least 10")
sys.exit(1)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.update_rate = 30
session_info = client.start_session(config)
os.makedirs(args.output_dir)
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
total_num_frames = 0
while not interrupt_handler.got_signal:
record_count, num_frames_in_record = divmod(total_num_frames, args.frames_per_file)
if num_frames_in_record == 0:
recorder = recording.Recorder(sensor_config=config, session_info=session_info)
data_info, data = client.get_next()
recorder.sample(data_info, data)
if num_frames_in_record + 1 == args.frames_per_file:
record = recorder.close()
filename = os.path.join(
args.output_dir, "{:04}.{}".format(record_count + 1, file_format))
print("Saved", filename)
recording.save(filename, record)
total_num_frames += 1
print("Sampled {:>5}".format(total_num_frames), end="\r", flush=True)
try:
client.disconnect()
except Exception:
pass
record_count, num_frames_in_record = divmod(total_num_frames, args.frames_per_file)
if num_frames_in_record > 0:
record = recorder.close()
filename = os.path.join(
args.output_dir, "{:04}.{}".format(record_count + 1, file_format))
print("Saved", filename)
recording.save(filename, record)
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
# Normally when using a single sensor, get_next will return
# (info, data). When using mulitple sensors, get_next will return
# lists of info and data for each sensor, i.e. ([info], [data]).
# This is commonly called squeezing. To disable squeezing, making
# get_next _always_ return lists, set:
# client.squeeze = False
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.range_interval = [0.4, 0.7]
config.update_rate = 20
config.profile = config.Profile.PROFILE_2
config.hw_accelerated_average_samples = 20
config.downsampling_factor = 2
session_info = client.setup_session(config)
print("Session info:\n", session_info, "\n")
# Now would be the time to set up plotting, signal processing, etc.
client.start_session()
# Normally, hitting Ctrl-C will raise a KeyboardInterrupt which in
# most cases immediately terminates the script. This often becomes
# an issue when plotting and also doesn't allow us to disconnect
# gracefully. Setting up an ExampleInterruptHandler will capture the
# keyboard interrupt signal so that a KeyboardInterrupt isn't raised
# and we can take care of the signal ourselves. In case you get
# impatient, hitting Ctrl-C a couple of more times will raise a
# KeyboardInterrupt which hopefully terminates the script.
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session\n")
is_performance_test_done = False
while not interrupt_handler.got_signal:
info, data = client.get_next()
my_data = list(data)
# Get the index of the highest measured signal strength from the list.
index_max_signal_strength = my_data.index(max(my_data))
# Calculate the distance of the highest measured signal strength in meters.
if max(my_data) > 400:
distance_of_strongest_signal_strength = 0.4 + (
index_max_signal_strength * session_info["step_length_m"])
else:
distance_of_strongest_signal_strength = 1000
print("No strong signal")
#print(distance_of_strongest_signal_strength)
#print("meters, signal strength : ")
#print(index_max_signal_strength)
#print("\r")
print(max(my_data))
# Run a performance test.
if is_performance_test_done is False:
is_performance_test_done = run_test(
distance_of_strongest_signal_strength)
print("Disconnecting...")
client.disconnect()
def main():
parser = utils.ExampleArgumentParser()
parser.add_argument("-o", "--output-file", type=str, required=True)
parser.add_argument("-l", "--limit-frames", type=int)
args = parser.parse_args()
utils.config_logging(args)
if os.path.exists(args.output_file):
print("File '{}' already exists, won't overwrite".format(
args.output_file))
sys.exit(1)
_, ext = os.path.splitext(args.output_file)
if ext.lower() not in [".h5", ".npz"]:
print("Unknown format '{}'".format(ext))
sys.exit(1)
if args.limit_frames is not None and args.limit_frames < 1:
print("Frame limit must be at least 1")
sys.exit(1)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.update_rate = 30
session_info = client.setup_session(config)
recorder = recording.Recorder(sensor_config=config,
session_info=session_info)
client.start_session()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
i = 0
while not interrupt_handler.got_signal:
data_info, data = client.get_next()
recorder.sample(data_info, data)
i += 1
if args.limit_frames:
print("Sampled {:>4}/{}".format(i, args.limit_frames),
end="\r",
flush=True)
if i >= args.limit_frames:
break
else:
print("Sampled {:>4}".format(i), end="\r", flush=True)
print()
client.disconnect()
record = recorder.close()
os.makedirs(os.path.dirname(os.path.abspath(args.output_file)),
exist_ok=True)
recording.save(args.output_file, record)
print("Saved to '{}'".format(args.output_file))
def main():
args = utils.ExampleArgumentParser().parse_args()
utils.config_logging(args)
if args.socket_addr:
client = clients.SocketClient(args.socket_addr)
elif args.spi:
client = clients.SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = clients.UARTClient(port)
client.squeeze = False
sensor_config = configs.EnvelopeServiceConfig()
sensor_config.sensor = args.sensors
sensor_config.range_interval = [0.2, 1.0]
sensor_config.profile = sensor_config.Profile.PROFILE_2
sensor_config.hw_accelerated_average_samples = 20
sensor_config.downsampling_factor = 2
session_info = client.setup_session(sensor_config)
pg_updater = PGUpdater(sensor_config, None, session_info)
pg_process = PGProcess(pg_updater)
#pg_process.start()
client.start_session()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
f = open("demo.txt", "w")
while not interrupt_handler.got_signal:
data_info, data = client.get_next()
tempstr = " "
#Array is within another Array, need to get address internal array
dataArray = data[0]
localMaxArray = [0, 0]
breakVariable = 0
iteratorJ = 0
iteratorI = 0
for x in dataArray:
if (iteratorJ > 10):
localMaxArray[0] = iteratorI - iteratorJ
break
else:
if (x >= localMaxArray[0]):
localMaxArray[0] = x
iteratorJ = 0
else:
iteratorJ = iteratorJ + 1
iteratorI = iteratorI + 1
while (dataArray[iteratorI] >= dataArray[iteratorI + 1]):
iteratorI = iteratorI + 1
iteratorJ = 0
while (iteratorI < 827):
if (iteratorJ > 10):
localMaxArray[1] = iteratorI - iteratorJ
break
else:
if (dataArray[iteratorI] >= localMaxArray[1]):
localMaxArray[1] = dataArray[iteratorI]
iteratorJ = 0
else:
iteratorJ = iteratorJ + 1
iteratorI = iteratorI + 1
#try:
#pg_process.put_data(data)
#except PGProccessDiedException:
#break
print(
math.floor(
(((localMaxArray[1] - localMaxArray[0]) / 1.773) * 0.0393701) *
10) / 10)
print("Disconnecting...")
f.close()
#pg_process.close()
client.disconnect()
def main():
args = utils.ExampleArgumentParser(num_sens=1).parse_args()
utils.config_logging(args)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.EnvelopeServiceConfig()
config.sensor = args.sensors
config.update_rate = 30
session_info = client.setup_session(config)
start = session_info["range_start_m"]
length = session_info["range_length_m"]
num_depths = session_info["data_length"]
step_length = session_info["step_length_m"]
depths = np.linspace(start, start + length, num_depths)
num_hist = 2 * int(round(config.update_rate))
hist_data = np.zeros([num_hist, depths.size])
smooth_max = utils.SmoothMax(config.update_rate)
app = QtWidgets.QApplication([])
pg.setConfigOption("background", "w")
pg.setConfigOption("foreground", "k")
pg.setConfigOptions(antialias=True)
win = pg.GraphicsLayoutWidget()
win.setWindowTitle("Acconeer PyQtGraph example")
env_plot = win.addPlot(title="Envelope")
env_plot.showGrid(x=True, y=True)
env_plot.setLabel("bottom", "Depth (m)")
env_plot.setLabel("left", "Amplitude")
env_curve = env_plot.plot(pen=pg.mkPen("k", width=2))
win.nextRow()
hist_plot = win.addPlot()
hist_plot.setLabel("bottom", "Time (s)")
hist_plot.setLabel("left", "Depth (m)")
hist_image_item = pg.ImageItem()
hist_image_item.translate(-2, start)
hist_image_item.scale(2 / num_hist, step_length)
hist_plot.addItem(hist_image_item)
# Get a nice colormap from matplotlib
hist_image_item.setLookupTable(utils.pg_mpl_cmap("viridis"))
win.show()
interrupt_handler = utils.ExampleInterruptHandler()
win.closeEvent = lambda _: interrupt_handler.force_signal_interrupt()
print("Press Ctrl-C to end session")
client.start_session()
while not interrupt_handler.got_signal:
info, data = client.get_next()
hist_data = np.roll(hist_data, -1, axis=0)
hist_data[-1] = data
env_curve.setData(depths, data)
env_plot.setYRange(0, smooth_max.update(data))
hist_image_item.updateImage(hist_data,
levels=(0, np.max(hist_data) * 1.05))
app.processEvents()
print("Disconnecting...")
app.closeAllWindows()
client.disconnect()
def main():
parser = utils.ExampleArgumentParser()
parser.add_argument("-t", "--temp", type=str, required=True)
parser.add_argument("-l", "--label", type=str,
required=False) # Sätt till true sedan
parser.add_argument("-o", "--output-file", type=str, required=True)
parser.add_argument("-lim", "--limit-frames", type=int)
#parser.add_argument("-a", "--angel", type=str, required=False)
#parser.add_argument("-d", "--distance", type=str, required=True)
args = parser.parse_args()
utils.config_logging(args)
try:
float(args.temp)
except:
print("Temp value not a float. Make sure you use . instead of , !")
sys.exit(1)
valid_arguments = ["snow", "wet", "ice", "dry", "metal"]
if args.label.lower() not in valid_arguments:
print("Not a valid label. Only", *valid_arguments,
sep=", "), print("are accepted labels!")
sys.exit(1)
if os.path.exists(args.output_file):
print("File '{}' already exists, won't overwrite".format(
args.output_file))
sys.exit(1)
_, ext = os.path.splitext(args.output_file)
if ext.lower() not in [".h5", ".npz"]:
print("Unknown format '{}'".format(ext))
sys.exit(1)
if args.limit_frames is not None and args.limit_frames < 1:
print("Frame limit must be at least 1")
sys.exit(1)
if args.socket_addr:
client = SocketClient(args.socket_addr)
elif args.spi:
client = SPIClient()
else:
port = args.serial_port or utils.autodetect_serial_port()
client = UARTClient(port)
config = configs.IQServiceConfig()
config.sensor = args.sensors
config.update_rate = 650 #Ändra samplingsfrekvens här
config.range_interval = [0.06, 0.5] #Avståndsintervall i meter
config.profile = config.Profile.PROFILE_1
config.repetition_mode = config.RepetitionMode.SENSOR_DRIVEN
session_info = client.setup_session(config)
recorder = recording.Recorder(sensor_config=config,
session_info=session_info,
temp=args.temp,
label=args.label.lower())
#angel=args.angel,
#distance=args.distance
client.start_session()
interrupt_handler = utils.ExampleInterruptHandler()
print("Press Ctrl-C to end session")
i = 0
while not interrupt_handler.got_signal:
data_info, data = client.get_next()
recorder.sample(data_info, data)
i += 1
if args.limit_frames:
print("Sampled {:>4}/{}".format(i, args.limit_frames),
end="\r",
flush=True)
if i >= args.limit_frames:
break
else:
print("Sampled {:>4}".format(i), end="\r", flush=True)
client.disconnect()
record = recorder.close()
recording.save(args.output_file, record)
print("Saved to '{}'".format(args.output_file))