def sigmf_recording(csv_file, data_file):
"""
Parameters:
csv_file --- csv file path where are recorded: #Time,Robot_Number,X,Y,Angle,Start_trame,End_trame,Channel_frequency,Sample_rate
data_file --- Sigmf-data file path
"""
# Initialize SigMF file
sigmf_file = SigMFFile(data_file=data_file, global_info=global_info)
# Define archive name for SigMF data and metadata files
archive_name = csv_file.split('.')[0]
with open(csv_file) as csvfile:
reader_csv = csv.DictReader(csvfile)
offset = 0
for row in reader_csv:
sample_rate = int(row['Sample_rate'])
len_packet = int(row['End_trame']) - int(row['Start_trame'])
frequency = int(row['Channel_frequency'])
robot_node = int(row['Robot_node'])
latitude = int(row['X'])
longitude = int(row['Y'])
start_frame = offset
end_frame = offset + len_packet
add_capture(sigmf_file, start_frame, sample_rate, frequency)
add_annotation(sigmf_file, start_frame, end_frame, latitude,
longitude, robot_node)
offset += len_packet
# Dump contents to SigMF archive format
archive_path = sigmf_file.archive(archive_name)
return archive_path
def test_sigmffile(test_data_file):
f = SigMFFile()
f.set_global_field("core:datatype", "f32")
f.add_annotation(start_index=0, length=len(TEST_FLOAT32_DATA))
f.add_capture(start_index=0)
f.set_data_file(test_data_file.name)
assert f._metadata == TEST_METADATA
return f
def test_multichannel_seek():
'''assure that seeking is working correctly with multichannel files'''
_, temp_path = tempfile.mkstemp()
# write some dummy data and read back
np.arange(18, dtype=np.uint16).tofile(temp_path)
temp_signal = SigMFFile(
data_file=temp_path,
global_info={
SigMFFile.DATATYPE_KEY: 'cu16_le',
SigMFFile.NUM_CHANNELS_KEY: 3,
},
)
# read after the first sample
temp_samples = temp_signal.read_samples(start_index=1, autoscale=False)
# assure samples are in the order we expect
assert np.all(temp_samples[:, 0] == np.array([6 + 7j, 12 + 13j]))
def test_multichannel_types():
'''check that real & complex for all types is reading multiple channels correctly'''
lut = {
'i8': np.int8,
'u8': np.uint8,
'i16': np.int16,
'u16': np.uint16,
'u32': np.uint32,
'i32': np.int32,
'f32': np.float32,
}
raw_count = 16
_, temp_path = tempfile.mkstemp()
for key, dtype in lut.items():
# for each type of storage
np.arange(raw_count, dtype=dtype).tofile(temp_path)
for num_channels in [1, 8]:
# for single or 8 channel
for complex_prefix in ['r', 'c']:
# for real or complex
check_count = raw_count * 1 # deepcopy
temp_signal = SigMFFile(
data_file=temp_path,
global_info={
SigMFFile.DATATYPE_KEY: f'{complex_prefix}{key}_le',
SigMFFile.NUM_CHANNELS_KEY: num_channels,
},
)
temp_samples = temp_signal.read_samples()
if complex_prefix == 'c':
# complex data will be half as long
check_count //= 2
assert np.all(np.iscomplex(temp_samples))
if num_channels != 1:
assert temp_samples.ndim == 2
check_count //= num_channels
assert check_count == temp_signal._count_samples()
def test_add_multiple_captures_and_annotations():
sigf = SigMFFile()
for idx in range(3):
simulate_capture(sigf, idx, 1024)
def test_add_multiple_captures_and_annotations():
f = SigMFFile()
for i in range(3):
simulate_capture(f, i, 1024)
def build_sigmf_md(
self,
task_id,
measurement_params,
data,
schedule_entry,
recording_id,
start_time,
end_time,
):
frequency = self.sdr.radio.frequency
sample_rate = self.sdr.radio.sample_rate
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(
GLOBAL_INFO.copy()
) # prevent GLOBAL_INFO from being modified by sigmf
sigmf_md.set_global_field(
"core:datatype", "cf32_le"
) # 2x 32-bit float, Little Endian
sigmf_md.set_global_field("core:sample_rate", sample_rate)
measurement_object = {
"time_start": start_time,
"time_stop": end_time,
"domain": "Time",
"measurement_type": "survey"
if self.is_multirecording
else "single-frequency",
"frequency_tuned_low": frequency,
"frequency_tuned_high": frequency,
}
sigmf_md.set_global_field("ntia-core:measurement", measurement_object)
sensor = capabilities["sensor"]
sensor["id"] = settings.FQDN
get_sensor_location_sigmf(sensor)
sigmf_md.set_global_field("ntia-sensor:sensor", sensor)
from status.views import get_last_calibration_time
sigmf_md.set_global_field(
"ntia-sensor:calibration_datetime", get_last_calibration_time()
)
action_def = {
"name": self.name,
"description": self.description,
"summary": self.description.splitlines()[0],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
if self.is_multirecording:
sigmf_md.set_global_field("ntia-scos:recording", recording_id)
sigmf_md.set_global_field("ntia-scos:task", task_id)
from schedule.serializers import ScheduleEntrySerializer
serializer = ScheduleEntrySerializer(
schedule_entry, context={"request": schedule_entry.request}
)
schedule_entry_json = serializer.to_sigmf_json()
schedule_entry_json["id"] = schedule_entry.name
sigmf_md.set_global_field("ntia-scos:schedule", schedule_entry_json)
sigmf_md.set_global_field(
"ntia-location:coordinate_system", get_coordinate_system_sigmf()
)
num_samples = measurement_params.get_num_samples()
capture_md = {
"core:frequency": frequency,
"core:datetime": self.sdr.radio.capture_time,
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation()
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=calibration_annotation_md
)
time_domain_detection_md = {
"ntia-core:annotation_type": "TimeDomainDetection",
"ntia-algorithm:detector": "sample_iq",
"ntia-algorithm:number_of_samples": num_samples,
"ntia-algorithm:units": "volts",
"ntia-algorithm:reference": "preselector input",
}
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=time_domain_detection_md
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
time_domain_avg_power = 10 * np.log10(np.mean(np.abs(data) ** 2))
time_domain_avg_power += (
10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = False
# explicitly check is not None since 1db compression could be 0
if self.sdr.radio.sensor_calibration_data["1db_compression_sensor"] is not None:
sensor_overload = (
time_domain_avg_power
> self.sdr.radio.sensor_calibration_data["1db_compression_sensor"]
)
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload": sensor_overload or sigan_overload,
"ntia-sensor:gain_setting_sigan": measurement_params.gain,
}
sigmf_md.add_annotation(
start_index=0, length=num_samples, metadata=sensor_annotation_md
)
return sigmf_md
def test_add_capture():
f = SigMFFile()
f.add_capture(start_index=0, metadata={})
def test_add_annotation():
f = SigMFFile()
f.add_capture(start_index=0)
m = {"latitude": 40.0, "longitude": -105.0}
f.add_annotation(start_index=0, length=128, metadata=m)
def test_invalid_capture_seq():
assert not SigMFFile(MD_INVALID_SEQUENCE_CAP).validate()
assert not SigMFFile(MD_INVALID_SEQUENCE_ANN).validate()
def run(self, suites_to_run, pause=False, write_output=True):
for test_suite in self.test_suites:
# Skip test suites that we don't want to run
if suites_to_run != [] and (not test_suite in suites_to_run):
continue
print("[+] Testing suite: '%s'" % test_suite)
summary = TestSummary(suite=test_suite, pause=pause)
# Get all metadata files associated with the suite
get_mtime = lambda f: os.stat(os.path.join(self.test_suites_directory, test_suite, f)).st_mtime
metadata_files = [os.path.join(self.test_suites_directory, test_suite, x) for x in sorted(os.listdir(os.path.join(self.test_suites_directory, test_suite)), key=get_mtime) if x.endswith('.sigmf-meta')]
# Parse metadata files
for metadata_file in metadata_files:
print("[+] %s" % metadata_file)
data_file = os.path.splitext(metadata_file)[0] + '.sigmf-data'
# Load sigmf data TODO abstract
f = open(metadata_file, 'r')
sigmf = SigMFFile(metadata=f.read())
if not sigmf.validate():
raise Exception("Invalid SigMF format")
global_meta = sigmf.get_global_info()
capture_meta = sigmf.get_capture_info(0)
f.close()
# Initialize test parameters
sample_rate = global_meta["core:sample_rate"]
# Get LoRa configuration
capture_freq = capture_meta["core:frequency"]
if "lora:frequency_offset" in capture_meta:
frequency_offset = capture_meta["lora:frequency_offset"]
else:
frequency_offset = 0
transmit_freq = capture_meta["lora:frequency"]
sf = capture_meta["lora:sf"]
cr = capture_meta["lora:cr"]
bw = int(capture_meta["lora:bw"])
prlen = capture_meta["lora:prlen"]
crc = capture_meta["lora:crc"]
implicit = capture_meta["lora:implicit"]
lora_config = LoRaConfig(transmit_freq, sf, cr, bw, prlen, crc, implicit)
# Get test case configuration
payload = capture_meta["test:expected"]
times = capture_meta["test:times"]
test = Test(payload, times)
# Build flowgraph
tb = gr.top_block()
file_source = blocks.file_source(gr.sizeof_gr_complex, data_file, False)
lora_receiver = lora.lora_receiver(sample_rate, capture_freq, [868100000], bw, sf, False, 4, True, reduced_rate=False, decimation=1)
throttle = blocks.throttle(gr.sizeof_gr_complex, sample_rate, True)
message_socket_sink = lora.message_socket_sink("127.0.0.1", 40868, 2)
freq_xlating_fir_filter = filter.freq_xlating_fir_filter_ccc(1, (firdes.low_pass(1, sample_rate, 200000, 100000, firdes.WIN_HAMMING, 6.67)), frequency_offset, sample_rate)
# Make connections
tb.connect((file_source, 0), (throttle, 0))
tb.connect((throttle, 0), (freq_xlating_fir_filter, 0))
tb.connect((freq_xlating_fir_filter, 0), (lora_receiver, 0))
tb.msg_connect((lora_receiver, 'frames'), (message_socket_sink, 'in'))
tb.start()
tb.wait()
decoded_data = self.server.get_payloads(times) # Output from the flowgraph
summary.add(TestResult(decoded_data=decoded_data, lora_config=lora_config, test=test), print_intermediate=True)
# Finally, export the result for the suite
summary.export_summary(path=self.reports_directory, write_output=write_output)
def build_sigmf_md(self):
logger.debug("Building SigMF metadata file")
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
sensor_def = capabilities['sensor_definition']
sigmf_md.set_global_field("ntia:sensor_definition", sensor_def)
sigmf_md.set_global_field("ntia:sensor_id", settings.FQDN)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
capture_md = {
"core:frequency": self.frequency,
"core:time": utils.get_datetime_str_now()
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
single_frequency_fft_md = {
"number_of_samples_in_fft": self.fft_size,
"window": "blackman",
"equivalent_noise_bandwidth": self.enbw,
"detector": detector.name + "_power",
"number_of_ffts": self.nffts,
"units": "dBm",
"reference": "not referenced"
}
annotation_md = {
"scos:measurement_type": {
"single_frequency_fft_detection": single_frequency_fft_md,
}
}
sigmf_md.add_annotation(start_index=(i * self.fft_size),
length=self.fft_size,
metadata=annotation_md)
return sigmf_md
def acquire_data(self, fc, parent_entry, task_id):
tuning_parameters = self.tuning_parameters[fc]
self.configure_usrp(fc, **tuning_parameters)
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.usrp.radio.sample_rate
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sigmf_md.set_global_field("core:description", self.description)
sensor_def = capabilities['sensor_definition']
sigmf_md.set_global_field("ntia:sensor_definition", sensor_def)
sigmf_md.set_global_field("ntia:sensor_id", settings.FQDN)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
# Acquire data and build per-capture metadata
data = np.array([], dtype=np.complex64)
nsamps = int(sample_rate * tuning_parameters['duration_ms'] * 1e-3)
dt = utils.get_datetime_str_now()
acq = self.usrp.radio.acquire_samples(nsamps).astype(np.complex64)
data = np.append(data, acq)
capture_md = {"core:frequency": fc, "core:datetime": dt}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
annotation_md = {"applied_scale_factor": self.usrp.radio.scale_factor}
sigmf_md.add_annotation(start_index=0, length=nsamps,
metadata=annotation_md)
return data, sigmf_md
def test_ordered_metadata():
'''check to make sure the metadata is sorted as expected'''
sigf = SigMFFile()
top_sort_order = ['global', 'captures', 'annotations']
for kdx, key in enumerate(sigf.ordered_metadata()):
assert kdx == top_sort_order.index(key)
def acquire_data(self, parent_entry, task_id):
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
try:
sensor_def_obj = SensorDefinition.objects.get()
sensor_def = SensorDefinitionSerializer(sensor_def_obj).data
sigmf_md.set_global_field("scos:sensor_definition", sensor_def)
except SensorDefinition.DoesNotExist:
pass
try:
fqdn = settings.ALLOWED_HOSTS[1]
except IndexError:
fqdn = 'not.set'
sigmf_md.set_global_field("scos:sensor_id", fqdn)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
# Acquire data and build per-capture metadata
data = np.array([], dtype=np.complex64)
nsamps = self.nsamples
for idx, fc in enumerate(self.fcs):
self.usrp.radio.tune_frequency(fc)
dt = utils.get_datetime_str_now()
acq = self.usrp.radio.acquire_samples(nsamps).astype(np.complex64)
data = np.append(data, acq)
start_idx = idx * nsamps
capture_md = {"core:frequency": fc, "core:datetime": dt}
sigmf_md.add_capture(start_index=start_idx, metadata=capture_md)
annotation_md = {
"applied_scale_factor": self.usrp.radio.scale_factor
}
sigmf_md.add_annotation(start_index=start_idx, length=nsamps,
metadata=annotation_md)
return data, sigmf_md
def build_sigmf_md(self, task_id, data):
logger.debug("Building SigMF metadata file")
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.sdr.radio.sample_rate
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sensor_def = capabilities["sensor_definition"]
sensor_def["id"] = settings.FQDN
sigmf_md.set_global_field("ntia-sensor:sensor", sensor_def)
action_def = {
"name": self.name,
"description": self.description,
"type": ["FrequencyDomain"],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
sigmf_md.set_global_field("ntia-scos:task_id", task_id)
capture_md = {
"core:frequency": self.sdr.radio.frequency,
"core:datetime": utils.get_datetime_str_now(),
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
frequency_domain_detection_md = {
"ntia-core:annotation_type":
"FrequencyDomainDetection",
"ntia-algorithm:number_of_samples_in_fft":
self.measurement_params.fft_size,
"ntia-algorithm:window":
"flattop",
"ntia-algorithm:equivalent_noise_bandwidth":
self.enbw,
"ntia-algorithm:detector":
detector.name + "_power",
"ntia-algorithm:number_of_ffts":
self.measurement_params.num_ffts,
"ntia-algorithm:units":
"dBm",
"ntia-algorithm:reference":
"not referenced",
"nita-algorithm:detection_domain":
"frequency",
}
sigmf_md.add_annotation(
start_index=(i * self.measurement_params.fft_size),
length=self.measurement_params.fft_size,
metadata=frequency_domain_detection_md,
)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=calibration_annotation_md,
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
flattened_data = data.flatten()
time_domain_avg_power = 10 * np.log10(
np.mean(np.abs(flattened_data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = (
time_domain_avg_power >
self.sdr.radio.sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload_sensor": sensor_overload,
"ntia-sensor:overload_sigan": sigan_overload,
"ntia-sensor:gain_setting_sigan": self.measurement_params.gain,
}
location = get_location()
if location:
sensor_annotation_md["core:latitude"] = (location.latitude, )
sensor_annotation_md["core:longitude"] = location.longitude
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=sensor_annotation_md,
)
return sigmf_md
def _run_test(self, config, test):
test_name = "{:s}-{:s}-{:n}".format(self.hw, config.file_repr(), self.test_count)
test_data_path = os.path.join(self.path, test_name + '.sigmf-data')
test_meta_path = os.path.join(self.path, test_name + '.sigmf-meta')
self.test_count += 1
capture_meta = {
"core:sample_start": 0,
"core:frequency": self.capture_freq,
"core:datetime": str(datetime.utcnow()),
"lora:frequency": config.freq,
"lora:frequency_offset": self.frequency_offset,
"lora:sf": config.sf,
"lora:cr": config.cr,
"lora:bw": config.bw,
"lora:prlen": config.prlen,
"lora:crc": config.crc,
"lora:implicit": config.implicit,
"test:expected": test.payload,
"test:times": test.times,
}
# Configure transmitter
try:
#self.lc.set_freq(config.freq)
self.lc.set_sf(config.sf)
self.lc.set_cr(config.cr)
self.lc.set_bw(config.bw / 1e3)
self.lc.set_prlen(str(config.prlen))
self.lc.set_crc("on" if config.crc else "off")
#self.lc.set_implicit("on" if config.implicit else "off")
self.lc.set_pwr(1)
except Exception as e:
print(e)
exit(1)
# Build GNU Radio flowgraph
tb = gr.top_block()
osmosdr_source = osmosdr.source(args="numchan=" + str(1) + " " + '' )
osmosdr_source.set_sample_rate(self.sample_rate)
osmosdr_source.set_center_freq(self.capture_freq, 0)
osmosdr_source.set_freq_corr(0, 0)
osmosdr_source.set_dc_offset_mode(0, 0)
osmosdr_source.set_iq_balance_mode(0, 0)
osmosdr_source.set_gain_mode(False, 0)
osmosdr_source.set_gain(10, 0)
osmosdr_source.set_if_gain(20, 0)
osmosdr_source.set_bb_gain(20, 0)
osmosdr_source.set_antenna('', 0)
osmosdr_source.set_bandwidth(0, 0)
file_sink = blocks.file_sink(gr.sizeof_gr_complex, test_data_path, False)
# Connect blocks
tb.connect((osmosdr_source, 0), (file_sink, 0))
# Run
print("Running %s" % test_name)
tb.start()
self.transmit_data(test)
tb.stop()
tb.wait()
# Save metadata file
with open(test_meta_path, 'w') as f:
test_sigmf = SigMFFile(data_file=test_data_path, global_info=copy.deepcopy(self.global_meta))
test_sigmf.add_capture(0, metadata=capture_meta)
test_sigmf.dump(f, pretty=True)
def build_sigmf_md(self, task_id, data, schedule_entry, start_time,
end_time):
logger.debug("Building SigMF metadata file")
# Use the radio's actual reported sample rate instead of requested rate
sample_rate = self.sdr.radio.sample_rate
frequency = self.sdr.radio.frequency
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO.copy(
)) # prevent GLOBAL_INFO from being modified by sigmf
sigmf_md.set_global_field("core:datatype",
"rf32_le") # 32-bit float, Little Endian
sigmf_md.set_global_field("core:sample_rate", sample_rate)
measurement_object = {
"time_start": start_time,
"time_stop": end_time,
"domain": "Frequency",
"measurement_type": "single-frequency",
"frequency_tuned_low": frequency,
"frequency_tuned_high": frequency,
}
sigmf_md.set_global_field("ntia-core:measurement", measurement_object)
sensor = capabilities["sensor"]
sensor["id"] = settings.FQDN
get_sensor_location_sigmf(sensor)
sigmf_md.set_global_field("ntia-sensor:sensor", sensor)
from status.views import get_last_calibration_time
sigmf_md.set_global_field("ntia-sensor:calibration_datetime",
get_last_calibration_time())
sigmf_md.set_global_field("ntia-scos:task", task_id)
action_def = {
"name": self.name,
"description": self.description,
"summary": self.description.splitlines()[0],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
from schedule.serializers import ScheduleEntrySerializer
serializer = ScheduleEntrySerializer(
schedule_entry, context={"request": schedule_entry.request})
schedule_entry_json = serializer.to_sigmf_json()
schedule_entry_json["id"] = schedule_entry.name
sigmf_md.set_global_field("ntia-scos:schedule", schedule_entry_json)
sigmf_md.set_global_field("ntia-location:coordinate_system",
get_coordinate_system_sigmf())
capture_md = {
"core:frequency": frequency,
"core:datetime": self.sdr.radio.capture_time,
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
frequencies = get_fft_frequencies(self.measurement_params.fft_size,
sample_rate, frequency).tolist()
for i, detector in enumerate(M4sDetector):
frequency_domain_detection_md = {
"ntia-core:annotation_type":
"FrequencyDomainDetection",
"ntia-algorithm:number_of_samples_in_fft":
self.measurement_params.fft_size,
"ntia-algorithm:window":
"flattop",
"ntia-algorithm:equivalent_noise_bandwidth":
self.enbw,
"ntia-algorithm:detector":
"fft_" + detector.name + "_power",
"ntia-algorithm:number_of_ffts":
self.measurement_params.num_ffts,
"ntia-algorithm:units":
"dBm",
"ntia-algorithm:reference":
"preselector input",
"ntia-algorithm:frequency_start":
frequencies[0],
"ntia-algorithm:frequency_stop":
frequencies[-1],
"ntia-algorithm:frequency_step":
frequencies[1] - frequencies[0],
}
sigmf_md.add_annotation(
start_index=(i * self.measurement_params.fft_size),
length=self.measurement_params.fft_size,
metadata=frequency_domain_detection_md,
)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=calibration_annotation_md,
)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
flattened_data = data.flatten()
time_domain_avg_power = 10 * np.log10(
np.mean(np.abs(flattened_data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = False
# explicitly check is not None since 1db compression could be 0
if self.sdr.radio.sensor_calibration_data[
"1db_compression_sensor"] is not None:
sensor_overload = (
time_domain_avg_power > self.sdr.radio.
sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload": sensor_overload or sigan_overload,
"ntia-sensor:gain_setting_sigan": self.measurement_params.gain,
}
sigmf_md.add_annotation(
start_index=0,
length=self.measurement_params.fft_size * len(M4sDetector),
metadata=sensor_annotation_md,
)
return sigmf_md
def _run_test(self, config, test):
test_name = "{:s}-{:s}-{:n}".format(self.hw, config.file_repr(), self.test_count)
test_data_path = os.path.join(self.path, test_name + '.sigmf-data')
test_meta_path = os.path.join(self.path, test_name + '.sigmf-meta')
self.test_count += 1
capture_meta = {
"core:sample_start": 0,
"core:frequency": self.capture_freq,
"core:datetime": str(datetime.utcnow()),
"lora:frequency": config.freq,
"lora:frequency_offset": self.frequency_offset,
"lora:sf": config.sf,
"lora:cr": config.cr,
"lora:bw": config.bw,
"lora:prlen": config.prlen,
"lora:crc": config.crc,
"lora:implicit": config.implicit,
"test:expected": test.payload,
"test:times": test.times,
}
# Configure transmitter
try:
#self.lc.set_freq(config.freq)
self.lc.set_sf(config.sf)
self.lc.set_cr(config.cr)
self.lc.set_bw(config.bw / 1e3)
self.lc.set_prlen(str(config.prlen))
self.lc.set_crc("on" if config.crc else "off")
#self.lc.set_implicit("on" if config.implicit else "off")
self.lc.set_pwr(1)
except Exception as e:
print(e)
exit(1)
# Build GNU Radio flowgraph
gr.enable_realtime_scheduling()
tb = gr.top_block()
osmosdr_source = osmosdr.source(args="numchan=" + str(1) + " " + '' )
osmosdr_source.set_sample_rate(self.sample_rate)
osmosdr_source.set_center_freq(self.capture_freq, 0)
osmosdr_source.set_freq_corr(0, 0)
osmosdr_source.set_dc_offset_mode(0, 0)
osmosdr_source.set_iq_balance_mode(0, 0)
osmosdr_source.set_gain_mode(False, 0)
osmosdr_source.set_gain(10, 0)
osmosdr_source.set_if_gain(20, 0)
osmosdr_source.set_bb_gain(20, 0)
osmosdr_source.set_antenna('', 0)
osmosdr_source.set_bandwidth(0, 0)
file_sink = blocks.file_sink(gr.sizeof_gr_complex, test_data_path, False)
# Connect blocks
tb.connect((osmosdr_source, 0), (file_sink, 0))
# Run
print("Running %s" % test_name)
tb.start()
self.transmit_data(test)
tb.stop()
tb.wait()
# Save metadata file
with open(test_meta_path, 'w') as f:
test_sigmf = SigMFFile(data_file=test_data_path, global_info=copy.deepcopy(self.global_meta))
test_sigmf.add_capture(0, metadata=capture_meta)
test_sigmf.dump(f, pretty=True)
def create_sigmf_metafile(self, x_len, dest_data_filename, _file):
sigmf_md = SigMFFile(data_file=dest_data_filename)
sigmf_md.set_global_field("core:datatype", self.datatype)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:author", self.author)
sigmf_md.set_global_field("core:description", self.description)
sha = sigmf_md.calculate_hash()
print sha
start_index = 0
capture_len = x_len
capture_md = {
"core:time": utils.get_sigmf_iso8601_datetime_now(),
"frequency": self.frequency
}
sigmf_md.add_capture(start_index=start_index, metadata=capture_md)
annotation_md = {
"genesys:transmitter": {
"antenna": {
"model": "Ettus VERT2450",
"type": "Vertical",
"gain": 3,
"high_frequency": 2480000000,
"low_frequency": 2400000000
},
"model":
"Ettus USRP X310 with UBX-160 (10 MHz-6 GHz, 160 MHz BW) Daughterboard"
},
"genesys:reciever": {
"antenna": {
"model": "Ettus VERT2450",
"type": "Vertical",
"gain": 3,
"high_frequency": 2480000000,
"low_frequency": 2400000000
},
"model": "Ettus USRP B210"
}
}
sigmf_md.add_annotation(start_index=start_index,
length=capture_len,
metadata=annotation_md)
return sigmf_md
def build_sigmf_md(self, task_id, measurement_params, data):
# Build global metadata
sigmf_md = SigMFFile()
sigmf_md.set_global_info(GLOBAL_INFO)
sample_rate = self.sdr.radio.sample_rate
sigmf_md.set_global_field("core:sample_rate", sample_rate)
sensor_def = capabilities["sensor_definition"]
sensor_def["id"] = settings.FQDN
sigmf_md.set_global_field("ntia-sensor:sensor", sensor_def)
action_def = {
"name": self.name,
"description": self.description,
"type": ["TimeDomain"],
}
sigmf_md.set_global_field("ntia-scos:action", action_def)
sigmf_md.set_global_field("ntia-scos:task_id", task_id)
dt = utils.get_datetime_str_now()
num_samples = measurement_params.get_num_samples()
capture_md = {
"core:frequency": self.sdr.radio.frequency,
"core:datetime": dt
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
calibration_annotation_md = self.sdr.radio.create_calibration_annotation(
)
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=calibration_annotation_md)
time_domain_detection_md = {
"ntia-core:annotation_type": "TimeDomainDetection",
"ntia-algorithm:detector": "sample_iq",
"ntia-algorithm:detection_domain": "time",
"ntia-algorithm:number_of_samples": num_samples,
"ntia-algorithm:units": "volts",
"ntia-algorithm:reference": "not referenced",
}
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=time_domain_detection_md)
# Recover the sigan overload flag
sigan_overload = self.sdr.radio.sigan_overload
# Check time domain average power versus calibrated compression
time_domain_avg_power = 10 * np.log10(np.mean(np.abs(data)**2))
time_domain_avg_power += (10 * np.log10(1 / (2 * 50)) + 30
) # Convert log(V^2) to dBm
sensor_overload = (
time_domain_avg_power >
self.sdr.radio.sensor_calibration_data["1db_compression_sensor"])
# Create SensorAnnotation and add gain setting and overload indicators
sensor_annotation_md = {
"ntia-core:annotation_type": "SensorAnnotation",
"ntia-sensor:overload_sensor": sensor_overload,
"ntia-sensor:overload_sigan": sigan_overload,
"ntia-sensor:gain_setting_sigan": measurement_params.gain,
}
location = get_location()
if location:
sensor_annotation_md["core:latitude"] = (location.latitude, )
sensor_annotation_md["core:longitude"] = location.longitude
sigmf_md.add_annotation(start_index=0,
length=num_samples,
metadata=sensor_annotation_md)
return sigmf_md
def create_sigmf_metafile(self, x_len, dest_data_filename, _file):
sigmf_md = SigMFFile(data_file=dest_data_filename)
sigmf_md.set_global_field("core:datatype", self.datatype)
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:author", self.author)
sigmf_md.set_global_field("core:version", self.version)
pattern = '(\d+)ft'
distance = re.findall(pattern, _file)
print 'distance', distance
#--description "SigMF IQ samples recording of demodulated data derived from over-the-cable WiFi transmissions collected by a fixed USRP B210 as a receiver. The transmitter emitted IEEE 802.11a standards compliant frames generated via a MATLAB WLAN System toolbox. Using UHD software, a controlled level of IQ imbalance is introduced at the runtime such that the demodulated symbols acquire unique characteristics."
self.description = "SigMF IQ samples recording of over-the-air WiFi transmissions collected by a fixed USRP B210 as a receiver. The data is collected in indoor environmnet of Kostas Research Institute (KRI), at Northeastern University, with a transmitter-receiver separation distance of " + distance[
0] + "ft. The transmitter emitted IEEE 802.11a standards compliant frames generated via a MATLAB WLAN System toolbox."
sigmf_md.set_global_field("core:description", self.description)
sha = sigmf_md.calculate_hash()
print sha
start_index = 0
capture_len = x_len
capture_md = {
"core:time": utils.get_sigmf_iso8601_datetime_now(),
"frequency": self.frequency
}
sigmf_md.add_capture(start_index=start_index, metadata=capture_md)
# annotation_md = {
# "core:latitude": 40.0 + 0.0001 * 0,
# "core:longitude": -105.0 + 0.0001 * 0,
# }
print sigmf_md
annotation_md = {
"genesys:transmitter": {
"antenna": {
"model": "Ettus VERT2450",
"type": "Vertical",
"gain": 3,
"high_frequency": 2480000000,
"low_frequency": 2400000000
},
"model":
"Ettus USRP X310 with UBX-160 (10 MHz-6 GHz, 160 MHz BW) Daughterboard"
},
"genesys:reciever": {
"antenna": {
"model": "Ettus VERT2450",
"type": "Vertical",
"gain": 3,
"high_frequency": 2480000000,
"low_frequency": 2400000000
},
"model": "Ettus USRP B210"
}
}
# annotation_md = {
# "genesys:transmitter_identification": 'hello',
# "genesys:receiver_identification": 'hello',
# }
sigmf_md.add_annotation(start_index=start_index,
length=capture_len,
metadata=annotation_md)
#print "Hello"
#sigmf_md.set_annotations("genesys:transmitter_identification","Hello")
return sigmf_md
def build_sigmf_md(self):
logger.debug("Building SigMF metadata file")
sigmf_md = SigMFFile()
sigmf_md.set_global_field("core:datatype", "rf32_le")
sigmf_md.set_global_field("core:sample_rate", self.sample_rate)
sigmf_md.set_global_field("core:description", self.description)
sensor_def_obj = SensorDefinition.objects.get()
sensor_def_json = SensorDefinitionSerializer(sensor_def_obj).data
sigmf_md.set_global_field("scos:sensor_definition", sensor_def_json)
try:
fqdn = settings.ALLOWED_HOSTS[1]
except IndexError:
fqdn = 'not.set'
sigmf_md.set_global_field("scos:sensor_id", fqdn)
sigmf_md.set_global_field("scos:version", SCOS_TRANSFER_SPEC_VER)
capture_md = {
"core:frequency": self.frequency,
"core:time": utils.get_datetime_str_now()
}
sigmf_md.add_capture(start_index=0, metadata=capture_md)
for i, detector in enumerate(M4sDetector):
single_frequency_fft_md = {
"number_of_samples_in_fft": self.fft_size,
"window": "blackman",
"equivalent_noise_bandwidth": self.enbw,
"detector": detector.name + "_power",
"number_of_ffts": self.nffts,
"units": "dBm",
"reference": "not referenced"
}
annotation_md = {
"scos:measurement_type": {
"single_frequency_fft_detection": single_frequency_fft_md,
}
}
sigmf_md.add_annotation(start_index=(i * self.fft_size),
length=self.fft_size,
metadata=annotation_md)
return sigmf_md
def test_default_constructor():
SigMFFile()
def test_valid_data():
assert SigMFFile(MD_VALID).validate()
def test_set_non_required_global_field():
f = SigMFFile()
f.set_global_field('this_is:not_in_the_schema', None)
def run(self, suites_to_run, pause=False, write_output=True):
for test_suite in self.test_suites:
# Skip test suites that we don't want to run
if suites_to_run != [] and (not test_suite in suites_to_run):
continue
print("[+] Testing suite: '%s'" % test_suite)
summary = TestSummary(suite=test_suite, pause=pause)
# Get all metadata files associated with the suite
get_mtime = lambda f: os.stat(
os.path.join(self.test_suites_directory, test_suite, f)
).st_mtime
metadata_files = [
os.path.join(self.test_suites_directory, test_suite, x)
for x in sorted(os.listdir(
os.path.join(self.test_suites_directory, test_suite)),
key=get_mtime) if x.endswith('.sigmf-meta')
]
# Parse metadata files
for metadata_file in metadata_files:
print("[+] %s" % metadata_file)
data_file = os.path.splitext(metadata_file)[0] + '.sigmf-data'
# Load sigmf data TODO abstract
f = open(metadata_file, 'r')
sigmf = SigMFFile(metadata=f.read())
if not sigmf.validate():
raise Exception("Invalid SigMF format")
global_meta = sigmf.get_global_info()
capture_meta = sigmf.get_capture_info(0)
f.close()
# Initialize test parameters
sample_rate = global_meta["core:sample_rate"]
# Get LoRa configuration
capture_freq = capture_meta["core:frequency"]
if "lora:frequency_offset" in capture_meta:
frequency_offset = capture_meta["lora:frequency_offset"]
else:
frequency_offset = 0
transmit_freq = capture_meta["lora:frequency"]
sf = capture_meta["lora:sf"]
cr = capture_meta["lora:cr"]
bw = int(capture_meta["lora:bw"])
prlen = capture_meta["lora:prlen"]
crc = capture_meta["lora:crc"]
implicit = capture_meta["lora:implicit"]
lora_config = LoRaConfig(transmit_freq, sf, cr, bw, prlen, crc,
implicit)
# Get test case configuration
payload = capture_meta["test:expected"]
times = capture_meta["test:times"]
test = Test(payload, times)
# Build flowgraph
tb = gr.top_block()
file_source = blocks.file_source(gr.sizeof_gr_complex,
data_file, False)
lora_receiver = lora.lora_receiver(sample_rate,
capture_freq, [868100000],
bw,
sf,
False,
4,
True,
reduced_rate=False,
decimation=1)
throttle = blocks.throttle(gr.sizeof_gr_complex, sample_rate,
True)
message_socket_sink = lora.message_socket_sink(
"127.0.0.1", 40868, 2)
freq_xlating_fir_filter = filter.freq_xlating_fir_filter_ccc(
1, (firdes.low_pass(1, sample_rate, 200000, 100000,
firdes.WIN_HAMMING, 6.67)),
frequency_offset, sample_rate)
# Make connections
tb.connect((file_source, 0), (throttle, 0))
tb.connect((throttle, 0), (freq_xlating_fir_filter, 0))
tb.connect((freq_xlating_fir_filter, 0), (lora_receiver, 0))
tb.msg_connect((lora_receiver, 'frames'),
(message_socket_sink, 'in'))
tb.start()
tb.wait()
decoded_data = self.server.get_payloads(
times) # Output from the flowgraph
summary.add(TestResult(decoded_data=decoded_data,
lora_config=lora_config,
test=test),
print_intermediate=True)
# Finally, export the result for the suite
summary.export_summary(path=self.reports_directory,
write_output=write_output)
def run_gui():
window_input = WindowInput()
capture_data_input = CaptureData()
capture_text_blocks = dict()
window_text_blocks = dict()
f = SigMFFile()
capture_selector_dict = dict()
layout = [
[
Text('This is the APL SIGMF tool to archive RF datasets',
size=(80, 1))
],
[
Text('Enter your data and signal captures below. You must include',
auto_size_text=True),
Text('required',
text_color='red',
font=DEFAULT_FONT + ('italic', ),
auto_size_text=True),
Text('fields.', size=(50, 1), auto_size_text=True)
], [Text('_' * 150, auto_size_text=True)]
]
layout.append([Text('Global Data', font=('Arial', 12, 'bold'))])
num_components = 0
line = []
for el in window_input.iter_core():
size = (30, 1) if len(line) == 0 else (None, None)
auto_size = True if len(line) == 0 else (10, 1)
line.extend([
Text(el,
justification='right',
size=size,
text_color='red' if el in window_input.req_tags else None,
auto_size_text=auto_size)
])
if el in window_input.el_multiline:
window_text_blocks.update({
el:
Multiline(window_input.el_text.get(el, ''),
key=el,
tooltip=window_input.el_tooltips.get(el, None),
size=(30, 2))
})
elif el in window_input.el_selector:
window_text_blocks.update({
el:
Combo(values=window_input.el_selector[el],
key=el,
size=window_input.el_size.get(el, (None, None)))
})
elif el in window_input.el_checkbox:
window_text_blocks.update({
el:
Checkbox(window_input.el_text.get(el, ''),
key=el,
size=window_input.el_size.get(el, (None, None)))
})
else:
window_text_blocks.update({
el:
InputText(window_input.el_text.get(el, ''),
key=el,
tooltip=window_input.el_tooltips.get(el, None))
})
line.append(window_text_blocks[el])
if el in window_input.el_units:
line.append(Text(window_input.el_units[el]))
num_components += 1
if num_components < window_input.first_line_size:
continue
layout.append(line)
line = []
for el1, el2 in window_input.iter_x_secondary(2):
line = []
for el, size in zip([el1, el2], [30, 22]):
if el is None:
continue
color = 'red' if el in window_input.req_tags else None
window_text_blocks.update({
el:
InputText(window_input.el_text.get(el, ''),
key=el,
tooltip=window_input.el_tooltips.get(el, None))
})
line.extend([
Text(el,
justification='right',
size=(size, 1),
text_color=color), window_text_blocks[el]
])
if el in window_input.el_units:
line.append(Text(window_input.el_units[el], size=(5, 1)))
else:
line.append(Text('', size=(5, 1)))
layout.append(line)
layout.extend(
[[Text('_' * 150, auto_size_text=True)],
[Text('Individual Capture Data', font=('Arial', 12, 'bold'))],
[
Text('Capture Selector', auto_size_text=True), combo_button,
Text('', size=(10, 1)),
Button('Add Capture', enable_events=True),
Button('Remove Capture', enable_events=True, size=(15, 1)),
Button('Clear Capture', enable_events=True, size=(15, 1))
]])
for el1, el2, el3 in capture_data_input.iter_x(3):
line = []
for el in [el1, el2, el3]:
if el is None:
continue
capture_text_blocks.update({
el:
InputText(key=el,
tooltip=capture_data_input.el_tooltips.get(el, None))
})
color = 'red' if el in capture_data_input.req_tags else None
line.extend([
Text(el, justification='right', size=(20, 1),
text_color=color), capture_text_blocks[el]
])
if el in capture_data_input.el_units:
line.append(Text(capture_data_input.el_units[el], size=(5, 1)))
else:
line.append(Text('', size=(5, 1)))
layout.append(line)
window_text_blocks.update(
{WindowInput.DATA_FILE: InputText('', key=WindowInput.DATA_FILE)})
layout.extend([[Text('_' * 150, auto_size_text=True)],
[Text('Data Location', font=('Arial', 12, 'bold'))],
[
Text(WindowInput.DATA_FILE,
size=(30, 1),
justification='right',
text_color='red'),
window_text_blocks[WindowInput.DATA_FILE],
FileBrowse()
],
[
Text(WindowInput.OUTPUT_FOLDER,
size=(30, 1),
justification='right'),
InputText('', key=WindowInput.OUTPUT_FOLDER),
FolderBrowse(), submit_button
],
[
Text(WindowInput.LOAD_PATH,
size=(30, 1),
justification='right'),
InputText('', key=WindowInput.LOAD_PATH),
FileBrowse(file_types=(("Archive Files", "*.sigmf"), )),
load_button
], [validate_button, Button('View Data')]])
window = Window('APL SigMF Archive Creator',
auto_size_buttons=False,
default_element_size=(20, 1),
auto_size_text=False,
default_button_element_size=(10, 1)).Layout(layout)
while True:
validate_button.Update(text='Update')
load_button.Update(text='Load')
submit_button.Update(text='Save Archive')
window.Refresh()
event, values = window.Read()
print(event, values)
if event == 'Load Archive':
load_path = values[WindowInput.LOAD_PATH]
if load_path == '':
show_error('No archive file provided')
continue
load_button.Update(text='Loading...')
window.Refresh()
print('reading from ', values[WindowInput.LOAD_PATH])
f = fromarchive(values[WindowInput.LOAD_PATH])
update_global_screen(window_input, window_text_blocks,
f.get_global_info(), f)
capture_selector_dict = {}
for capture in f.get_captures():
add_capture(capture_data_input,
capture,
capture_selector_dict,
f,
from_archive=True)
elif event == 'Data Type Help':
PopupOK(
'Format: <TypeCharacters><ElementBitSize>_<Endianness>\n\n'
'\tTypeCharacters:\n'
'\t\tUnsigned data: \"u\"\n'
'\t\tComplex data: \"c\"\n'
'\t\tFixedpoint data: \"f\"\n'
'\tElementBitSize:\n'
'\t\t32 bits, 16 bits, or 8 bits\n'
'\tEndianness:\n'
'\t\tl: Little Endian\n'
'\t\tb: Big Endian\n\n\n\n'
'Example: \"uc32_l\"\n'
'Unsigned complex data where each element is 32 bits, or 64 bits total, formatted in little endian.',
title='Data Type Help')
elif event == 'Update':
validate_button.Update(text='Validating...')
window.Refresh()
window_data_type_dict = {}
added = True
for el in window_input.iter():
req_field = True if el in window_input.req_tags else False
el_type = window_input.el_types.get(el, None)
el_unit = window_input.el_units.get(el, None)
if el in window_input.partial_component_list:
added = added and add_sigmf_field(update_dictionary,
values,
el,
window_data_type_dict,
window_input.get_tag(el),
required=req_field,
type=el_type,
unit=el_unit)
else:
added = added and add_sigmf_field(
SigMFFile.set_global_field,
values,
el,
f,
window_input.get_tag(el),
required=req_field,
type=el_type,
unit=el_unit)
data_type_str = ''
data_type_str += 'c' if bool(
window_data_type_dict[WindowInput.DATA_TYPE_COMPLEX]) else ''
data_type_str += 'f' if not bool(window_data_type_dict[
WindowInput.DATA_TYPE_FIXEDPOINT]) else ''
data_type_str += 'u' if bool(
window_data_type_dict[WindowInput.DATA_TYPE_UNSIGNED]) else ''
data_type_str += str(
window_data_type_dict[WindowInput.DATA_SAMPLE_SIZE]) + '_'
data_type_str += 'l' if window_data_type_dict[
WindowInput.DATA_BYTE_ORDER] == 'little endian' else 'b'
data_type_dict = {SigMFFile.DATATYPE_KEY: data_type_str}
added = added and add_sigmf_field(SigMFFile.set_global_field,
data_type_dict,
SigMFFile.DATATYPE_KEY,
f,
SigMFFile.DATATYPE_KEY,
required=True)
print('HERE: ', window_data_type_dict)
added = added and add_sigmf_field(SigMFFile.set_data_file,
values,
WindowInput.DATA_FILE,
f,
required=True) and added
if not added:
# requirement not given
continue
if validate_data(f):
submit_button.Update(disabled=False,
button_color=DEFAULT_BUTTON_COLOR)
elif event == 'Capture Combo':
capture_dict = capture_selector_dict[values['Capture Combo']]
update_capture_screen(capture_data_input, capture_text_blocks,
capture_dict)
elif event == 'Add Capture':
add_capture(capture_data_input, values, capture_selector_dict, f)
elif event == 'Remove Capture':
capture_dict = dict()
added = add_sigmf_field(update_dictionary,
values,
CaptureData.START_INDEX,
capture_dict,
SigMFFile.START_INDEX_KEY,
required=True,
type=int)
if not added:
# requirement not given
continue
captures = []
for capture in f._metadata[SigMFFile.CAPTURE_KEY]:
if capture[SigMFFile.START_INDEX_KEY] != capture_dict[
SigMFFile.START_INDEX_KEY]:
captures.append(capture)
f._metadata[SigMFFile.CAPTURE_KEY] = captures
annotations = []
for annotation in f._metadata[SigMFFile.ANNOTATION_KEY]:
if annotation[SigMFFile.START_INDEX_KEY] != capture_dict[
SigMFFile.START_INDEX_KEY]:
annotations.append(annotation)
f._metadata[SigMFFile.ANNOTATION_KEY] = annotations
new_values = list(combo_button.Values)
rm_val = 'Capture {}'.format(
capture_dict[SigMFFile.START_INDEX_KEY])
if rm_val in capture_selector_dict:
capture_selector_dict.pop(rm_val)
if rm_val in new_values:
new_values.remove(rm_val)
combo_button.Update(values=new_values, set_to_index=0)
capture_dict = capture_selector_dict.get(
combo_button.DefaultValue, None)
update_capture_screen(capture_data_input, capture_text_blocks,
capture_dict)
elif event == 'Clear Capture':
update_capture_screen(capture_data_input, capture_text_blocks,
None)
elif event == 'View Data':
PopupOK('Current data:\n', f.dumps(pretty=True), title='')
elif event == 'Save Archive':
output_folder = values[WindowInput.OUTPUT_FOLDER]
if output_folder == '':
show_error('No output folder provided')
continue
elif len(capture_selector_dict.keys()) == 0:
show_error('No capture data specified')
submit_button.Update(text='Saving...')
window.Refresh()
archive_file = output_folder + '/' + os.path.basename(
f.data_file).split('.')[0] + SIGMF_ARCHIVE_EXT
f.archive(archive_file)
PopupOK('Saved archive as \n', archive_file, title='')
elif event in ['Cancel', None, 'Exit']:
window.Close()
break
window.Close()