def _build_parsed_values(self, match):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.date_time_string.append(str(match.group(1)))
self.data.serial_number.append(int(match.group(2)))
self.data.timer.append(float(match.group(3)))
# Unpack the binary data packet
(delay, ch1, ch2, ch3, ch4, ch5, ch6, ch7,
Vin, Va, temp, count, check) = SPKIR.unpack(match.group(4))
# Assign the remaining SPKIR data to the named parameters
self.data.sample_delay.append(delay)
self.data.raw_channels.append([ch1, ch2, ch3, ch4, ch5, ch6, ch7])
self.data.input_voltage.append(Vin)
self.data.analog_rail_voltage.append(Va)
self.data.frame_counter.append(count)
self.data.internal_temperature.append(temp)
def _build_parsed_values(self, collect_time, process_time, sample):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string from the collection time to calculate an
# epoch timestamp (seconds since 1970-01-01), using that values as the
# preferred time record for the data
epts = dcl_to_epoch(collect_time)
self.data.time.append(epts)
self.data.collect_date_time.append(collect_time)
self.data.process_date_time.append(process_time)
self.data.unique_id.append(int(sample[1:3], 16))
self.data.record_length.append(int(sample[3:5], 16))
self.data.record_type.append(int(sample[5:7], 16))
self.data.record_time.append(int(sample[7:15], 16))
cnt = 15 # set the counter for the light measurements
light = [] # create empty list to hold the 14 light measurements
for i in range(0, 14):
indx = (i * 4) + cnt
light.append(int(sample[indx:indx + 4], 16))
self.data.light_measurements.append(light)
cnt = indx + 4 # reset the counter for the final parameters
self.data.voltage_battery.append(int(sample[cnt:cnt + 4], 16))
self.data.thermistor_raw.append(int(sample[cnt + 4:cnt + 8], 16))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining WAVSS data to the named parameters
self.data.date_string.append(str(match.group(2)))
self.data.time_string.append(str(match.group(3)))
self.data.serial_number.append(str(match.group(4)))
self.data.num_zero_crossings.append(int(match.group(5)))
self.data.average_wave_height.append(float(match.group(6)))
self.data.mean_spectral_period.append(float(match.group(7)))
self.data.maximum_wave_height.append(float(match.group(8)))
self.data.significant_wave_height.append(float(match.group(9)))
self.data.significant_wave_period.append(float(match.group(10)))
self.data.average_tenth_height.append(float(match.group(11)))
self.data.average_tenth_period.append(float(match.group(12)))
self.data.average_wave_period.append(float(match.group(13)))
self.data.peak_period.append(float(match.group(14)))
self.data.peak_period_read.append(float(match.group(15)))
self.data.spectral_wave_height.append(float(match.group(16)))
self.data.mean_wave_direction.append(float(match.group(17)))
self.data.mean_directional_spread.append(float(match.group(18)))
def _build_parsed_values(self, match):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds
# since 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining FDCHP data to the named parameters, where the
# rest of the data is in a (mostly) comma separated string, so ... need
# to use filter and a split that looks for both commas and spaces
# (sloppy programming by the developer of the instrument).
data = filter(None, re.split(r',|\s', match.group(2)))
# index through the list of parameter names and assign the data
cnt = 0
for p in _parameter_names_fdchp[1:]:
if cnt == 2:
# the status parameter is a 6 character hex value ...
self.data[p].append(str(data[cnt]))
else:
# all other values are floats
self.data[p].append(float(data[cnt]))
cnt += 1
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.temperature.append(float(match.group(2)))
self.data.conductivity.append(float(match.group(3)))
self.data.pressure.append(float(match.group(4)))
if self.ctd_type == 1:
self.data.ctd_date_time_string.append(str(match.group(5)))
if self.ctd_type == 2:
self.data.oxygen_concentration.append(float(match.group(5)))
self.data.ctd_date_time_string.append(str(match.group(6)))
if self.ctd_type == 3:
self.data.raw_backscatter.append(int(match.group(5)))
self.data.raw_chlorophyll.append(int(match.group(6)))
self.data.raw_cdom.append(int(match.group(7)))
self.data.ctd_date_time_string.append(str(match.group(8)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.hydrogen_concentration.append(float(match.group(2)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds
# since 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining PRESF data to the named parameters
self.data.presf_date_time_string.append(str(match.group(2)))
self.data.absolute_pressure.append(float(match.group(3)))
self.data.pressure_temp.append(float(match.group(4)))
self.data.seawater_temperature.append(float(match.group(5)))
def _build_parsed_values(self, match, spectra):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds
# since 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.date_time_string.append(str(match.group(1)))
# Assign the remaining NUTNR data to the named parameters
self.data.measurement_type.append(str(match.group(2)))
self.data.serial_number.append(int(match.group(3)))
# the rest of the data is in a comma separated string, so...
data = (match.group(4)).split(',')
# data found in all frames
self.data.date_string.append(str(data[0]))
self.data.decimal_hours.append(float(data[1]))
self.data.nitrate_concentration.append(float(data[2]))
self.data.auxiliary_fit_1st.append(float(data[3]))
self.data.auxiliary_fit_2nd.append(float(data[4]))
self.data.auxiliary_fit_3rd.append(float(data[5]))
self.data.rms_error.append(float(data[6]))
# data found only in the full frames
if self.spectra == 1:
self.data.temperature_internal.append(float(data[7]))
self.data.temperature_spectrometer.append(float(data[8]))
self.data.temperature_lamp.append(float(data[9]))
self.data.lamp_on_time.append(int(data[10]))
self.data.humidity.append(float(data[11]))
self.data.voltage_lamp.append(float(data[12]))
self.data.voltage_analog.append(float(data[13]))
self.data.voltage_main.append(float(data[14]))
self.data.average_reference.append(float(data[15]))
self.data.variance_reference.append(float(data[16]))
self.data.seawater_dark.append(float(data[17]))
self.data.spectal_average.append(float(data[18]))
self.data.channel_measurements.append(map(int, data[19:]))
def _build_parsed_values(self, match):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.flort_date_time_string.append(
re.sub('\t', ' ', str(match.group(2))))
self.data.measurement_wavelength_beta.append(int(match.group(3)))
self.data.raw_signal_beta.append(int(match.group(4)))
self.data.measurement_wavelength_chl.append(int(match.group(4)))
self.data.raw_signal_chl.append(int(match.group(5)))
self.data.measurement_wavelength_cdom.append(int(match.group(6)))
self.data.raw_signal_cdom.append(int(match.group(7)))
self.data.raw_internal_temp.append(int(match.group(8)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.barometric_pressure.append(float(match.group(2)))
self.data.relative_humidity.append(float(match.group(3)))
self.data.air_temperature.append(float(match.group(4)))
self.data.longwave_irradiance.append(float(match.group(5)))
self.data.precipitation_level.append(float(match.group(6)))
self.data.sea_surface_temperature.append(float(match.group(7)))
self.data.sea_surface_conductivity.append(float(match.group(8)))
self.data.shortwave_irradiance.append(float(match.group(9)))
self.data.eastward_wind_velocity.append(float(match.group(10)))
self.data.northward_wind_velocity.append(float(match.group(11)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.co2_date_time_string.append(str(match.group(2)))
self.data.zero_a2d.append(int(match.group(3)))
self.data.current_a2d.append(int(match.group(4)))
self.data.measured_water_co2.append(float(match.group(5)))
self.data.avg_irga_temperature.append(float(match.group(6)))
self.data.humidity.append(float(match.group(7)))
self.data.humidity_temperature.append(float(match.group(8)))
self.data.gas_stream_pressure.append(int(match.group(9)))
self.data.irga_detector_temperature.append(float(match.group(10)))
self.data.irga_source_temperature.append(float(match.group(11)))
self.data.co2_source.append(str(match.group(12)))
def _build_parsed_values(self, timestamp, sample):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(timestamp)
self.data.time.append(epts)
self.data.dcl_date_time_string.append(timestamp)
self.data.record_length.append(int(sample[3:5], 16))
self.data.record_type.append(int(sample[5:7], 16))
self.data.record_time.append(int(sample[7:15], 16))
self.data.thermistor_start.append(int(sample[15:19], 16))
cnt = 19
reference = [
] # create empty list to hold the 16 reference measurements
for i in range(0, 16):
indx = (i * 4) + cnt
reference.append(int(sample[indx:indx + 4], 16))
self.data.reference_measurements.append(reference)
cnt = indx + 4 # reset the counter to start with the light measurements
light = [] # create empty list to hold the 92 light measurements
for i in range(0, 92):
indx = (i * 4) + cnt
light.append(int(sample[indx:indx + 4], 16))
self.data.light_measurements.append(light)
cnt = indx + 8 # reset the counter for the final parameters
self.data.voltage_battery.append(int(sample[cnt:cnt + 4], 16))
self.data.thermistor_end.append(int(sample[cnt + 4:cnt + 8], 16))
def _build_parsed_values(self, match):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.latitude.append(float(match.group(2)))
self.data.longitude.append(float(match.group(3)))
self.data.speed_over_ground.append(float(match.group(4)))
self.data.course_over_ground.append(float(match.group(5)))
self.data.fix_quality.append(int(match.group(6)))
self.data.number_satellites.append(int(match.group(7)))
self.data.horiz_dilution_precision.append(float(match.group(8)))
self.data.altitude.append(float(match.group(9)))
self.data.gps_date_string.append(str(match.group(10)))
self.data.gps_time_string.append(str(match.group(11)))
self.data.latitude_string.append(str(match.group(12)))
self.data.longitude_string.append(str(match.group(13)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.cpm_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.main_voltage.append(float(match.group(2)))
self.data.main_current.append(float(match.group(3)))
self.data.backup_battery_voltage.append(float(match.group(4)))
self.data.backup_battery_current.append(float(match.group(5)))
self.data.error_flags.append(int(match.group(6), 16))
self.data.temperature1.append(float(match.group(7)))
self.data.temperature2.append(float(match.group(8)))
self.data.humidity.append(float(match.group(9)))
self.data.pressure.append(float(match.group(10)))
self.data.ground_fault_enable.append(int(match.group(11), 16))
self.data.ground_fault_sbd.append(float(match.group(12)))
self.data.ground_fault_gps.append(float(match.group(13)))
self.data.ground_fault_main.append(float(match.group(14)))
self.data.ground_fault_9522_fw.append(float(match.group(15)))
self.data.leak_detect_enable.append(int(match.group(16), 16))
self.data.leak_detect_voltage1.append(int(match.group(17)))
self.data.leak_detect_voltage2.append(int(match.group(18)))
self.data.heartbeat_enable.append(int(match.group(19)))
self.data.heartbeat_delta.append(int(match.group(20)))
self.data.heartbeat_threshold.append(int(match.group(21)))
self.data.wake_code.append(int(match.group(22)))
self.data.iridium_power_state.append(int(match.group(23)))
self.data.iridium_voltage.append(float(match.group(24)))
self.data.iridium_current.append(float(match.group(25)))
self.data.iridium_error_flag.append(int(match.group(26)))
self.data.fwwf_power_state.append(int(match.group(27), 16))
self.data.fwwf_voltage.append(float(match.group(28)))
self.data.fwwf_current.append(float(match.group(29)))
self.data.fwwf_power_flag.append(int(match.group(30)))
self.data.gps_power_state.append(float(match.group(31)))
self.data.sbd_power_state.append(float(match.group(32)))
self.data.sbd_message_pending.append(float(match.group(33)))
self.data.pps_source.append(float(match.group(34)))
self.data.dcl_power_state.append(int(match.group(35), 16))
self.data.wake_time_count.append(float(match.group(36)))
self.data.wake_power_count.append(int(match.group(37)))
self.data.esw_power_state.append(int(match.group(38), 16))
self.data.dsl_power_state.append(int(match.group(39)))
def main():
# load the input arguments
args = inputs()
infile = os.path.abspath(args.infile)
outfile = os.path.abspath(args.outfile)
coeff_file = os.path.abspath(args.coeff_file)
blnk_file = os.path.abspath(args.devfile)
# check for the source of calibration coeffs and load accordingly
dev = Calibrations(coeff_file) # initialize calibration class
if os.path.isfile(coeff_file):
# we always want to use this file if it exists
dev.load_coeffs()
elif args.csvurl:
# load from the CI hosted CSV files
csv_url = args.csvurl
dev.read_csv(csv_url)
dev.save_coeffs()
else:
raise Exception(
'A source for the PCO2W calibration coefficients could not be found'
)
# check for the source of instrument blanks and load accordingly
blank = Blanks(blnk_file, 1.0,
1.0) # initialize the calibration class using default blank
if os.path.isfile(blnk_file):
blank.load_blanks()
else:
blank.save_blanks()
# load the PCO2W data file
with open(infile, 'rb') as f:
pco2w = Munch(json.load(f))
if len(pco2w.time) == 0:
# This is an empty file, end processing
return None
# convert the raw battery voltage and thermistor values from counts
# to V and degC, respectively
pco2w.thermistor = ph_thermistor(np.array(pco2w.thermistor_raw)).tolist()
pco2w.voltage_battery = ph_battery(np.array(
pco2w.voltage_battery)).tolist()
# compare the instrument clock to the GPS based DCL time stamp
# --> PCO2W uses the OSX date format of seconds since 1904-01-01
mac = datetime.strptime("01-01-1904", "%m-%d-%Y")
offset = []
for i in range(len(pco2w.time)):
rec = mac + timedelta(seconds=pco2w.record_time[i])
rec.replace(tzinfo=timezone('UTC'))
dcl = datetime.utcfromtimestamp(pco2w.time[i])
# we use the sample collection time as the time record for the sample.
# the record_time, however, is when the sample was processed. so the
# true offset needs to include the difference between the collection
# and processing times
collect = dcl_to_epoch(pco2w.collect_date_time[i])
process = dcl_to_epoch(pco2w.process_date_time[i])
diff = process - collect
if np.isnan(diff):
diff = 300
offset.append((rec - dcl).total_seconds() - diff)
pco2w.time_offset = offset
# set calibration inputs to pCO2 calculations
ea434 = 19706. # factory constants
eb434 = 3073. # factory constants
ea620 = 34. # factory constants
eb620 = 44327. # factory constants
# calculate pCO2
pCO2 = []
blank434 = []
blank620 = []
for i in range(len(pco2w.record_type)):
if pco2w.record_type[i] == 4:
# this is a light measurement, calculate the pCO2
pCO2.append(
pco2_pco2wat(pco2w.record_type[i], pco2w.light_measurements[i],
pco2w.thermistor[i], ea434, eb434, ea620, eb620,
dev.coeffs['calt'], dev.coeffs['cala'],
dev.coeffs['calb'], dev.coeffs['calc'],
blank.blank_434, blank.blank_620)[0])
# record the blanks used
blank434.append(blank.blank_434)
blank620.append(blank.blank_620)
if pco2w.record_type[i] == 5:
# this is a dark measurement, update and save the new blanks
blank.blank_434 = pco2_blank(pco2w.light_measurements[i][6])
blank.blank_620 = pco2_blank(pco2w.light_measurements[i][7])
blank.save_blanks()
blank434.append(blank.blank_434)
blank620.append(blank.blank_620)
# save the resulting data to a json formatted file
pco2w.pCO2 = pCO2
pco2w.blank434 = blank434
pco2w.blank620 = blank620
with open(outfile, 'w') as f:
f.write(pco2w.toJSON())
def _build_parsed_values(self, match):
"""
Start by parsing the beginning portion of the ensemble (Header Data)
"""
# build the ensemble string from match.group(2) through to the end.
length = unpack("<H", unhexlify(match.group(3)))[0]
ensemble = unhexlify(''.join(match.groups()[1:]))
# Calculate the checksum
total = int(0)
for i in range(0, length):
total += int(ord(ensemble[i]))
checksum = total & 65535 # bitwise and with 65535 or mod vs 65536
if checksum != unpack("<H", ensemble[length:length + 2])[0]:
raise Exception("Checksum mismatch")
(header_id, data_source_id, num_bytes, spare, num_data_types) = \
unpack('<2BH2B', ensemble[0:6])
self.data.time.append(dcl_to_epoch(match.group(1)))
self.data.header.num_bytes.append(num_bytes)
self.data.header.num_data_types.append(num_data_types)
offsets = [] # create list for offsets
strt = 6 # offsets start at byte 6 (using 0 indexing)
nDT = 1 # counter for N data types
while nDT <= num_data_types:
value = unpack('<H', ensemble[strt:strt + 2])[0]
offsets.append(value)
strt += 2
nDT += 1
for offset in offsets:
# for each offset, using the starting byte, determine the data type
# and then parse accordingly.
data_type = unpack('<H', ensemble[offset:offset + 2])[0]
# fixed leader data (x00x00)
if data_type == 0:
chunk = ensemble[offset:offset + 59]
self._parse_fixed_chunk(chunk)
iCells = self.num_depth_cells # grab the # of depth cells
# variable leader data (x80x00)
if data_type == 128:
chunk = ensemble[offset:offset + 65]
self._parse_variable_chunk(chunk)
# velocity data (x00x01)
if data_type == 256:
# number of bytes is a function of the user selectable number
# of depth cells (WN command), obtained above
nBytes = 2 + 8 * iCells
chunk = ensemble[offset:offset + nBytes]
self._parse_velocity_chunk(chunk)
# correlation magnitude data (x00x02)
if data_type == 512:
# number of bytes is a function of the user selectable number
# of depth cells (WN command), obtained above
nBytes = 2 + 4 * iCells
chunk = ensemble[offset:offset + nBytes]
self._parse_corelation_magnitude_chunk(chunk)
# echo intensity data (x00x03)
if data_type == 768:
# number of bytes is a function of the user selectable number
# of depth cells (WN command), obtained above
nBytes = 2 + 4 * iCells
chunk = ensemble[offset:offset + nBytes]
self._parse_echo_intensity_chunk(chunk)
# percent-good data (x00x04)
if data_type == 1024:
# number of bytes is a function of the user selectable number
# of depth cells (WN command), obtained above
nBytes = 2 + 4 * iCells
chunk = ensemble[offset:offset + nBytes]
self._parse_percent_good_chunk(chunk)
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining data to the named parameters
self.data.main_voltage.append(float(match.group(2)))
self.data.main_current.append(float(match.group(3)))
self.data.error_flags.append(int(match.group(4), 16))
self.data.temperature1.append(float(match.group(5)))
self.data.temperature2.append(float(match.group(6)))
self.data.temperature3.append(float(match.group(7)))
self.data.temperature4.append(float(match.group(8)))
self.data.temperature5.append(float(match.group(9)))
self.data.humidity.append(float(match.group(10)))
self.data.pressure.append(float(match.group(11)))
self.data.ground_fault_enable.append(int(match.group(12), 16))
self.data.ground_fault_isov3.append(float(match.group(13)))
self.data.ground_fault_main.append(float(match.group(14)))
self.data.ground_fault_sensors.append(float(match.group(15)))
self.data.leak_detect_enable.append(int(match.group(16), 16))
self.data.leak_detect_voltage1.append(int(match.group(17)))
self.data.leak_detect_voltage2.append(int(match.group(18)))
self.data.port1_power_state.append(int(match.group(19)))
self.data.port1_voltage.append(float(match.group(20)))
self.data.port1_current.append(float(match.group(21)))
self.data.port1_error_flag.append(int(match.group(22)))
self.data.port2_power_state.append(int(match.group(23)))
self.data.port2_voltage.append(float(match.group(24)))
self.data.port2_current.append(float(match.group(25)))
self.data.port2_error_flag.append(int(match.group(26)))
self.data.port3_power_state.append(int(match.group(27)))
self.data.port3_voltage.append(float(match.group(28)))
self.data.port3_current.append(float(match.group(29)))
self.data.port3_error_flag.append(int(match.group(30)))
self.data.port4_power_state.append(int(match.group(31)))
self.data.port4_voltage.append(float(match.group(32)))
self.data.port4_current.append(float(match.group(33)))
self.data.port4_error_flag.append(int(match.group(34)))
self.data.port5_power_state.append(int(match.group(35)))
self.data.port5_voltage.append(float(match.group(36)))
self.data.port5_current.append(float(match.group(37)))
self.data.port5_error_flag.append(int(match.group(38)))
self.data.port6_power_state.append(int(match.group(39)))
self.data.port6_voltage.append(float(match.group(40)))
self.data.port6_current.append(float(match.group(41)))
self.data.port6_error_flag.append(int(match.group(42)))
self.data.port7_power_state.append(int(match.group(43)))
self.data.port7_voltage.append(float(match.group(44)))
self.data.port7_current.append(float(match.group(45)))
self.data.port7_error_flag.append(int(match.group(46)))
self.data.port8_power_state.append(int(match.group(47)))
self.data.port8_voltage.append(float(match.group(48)))
self.data.port8_current.append(float(match.group(49)))
self.data.port8_error_flag.append(int(match.group(50)))
self.data.heartbeat_enable.append(int(match.group(51)))
self.data.heartbeat_delta.append(int(match.group(52)))
self.data.heartbeat_threshold.append(int(match.group(53)))
self.data.wake_code.append(int(match.group(54)))
self.data.wake_time_count.append(float(match.group(55)))
self.data.wake_power_count.append(int(match.group(56)))
self.data.power_state.append(int(match.group(57)))
self.data.power_board_mode.append(int(match.group(58)))
self.data.power_voltage_select.append(int(match.group(59)))
self.data.power_voltage_main.append(float(match.group(60)))
self.data.power_current_main.append(float(match.group(61)))
self.data.power_voltage_12.append(float(match.group(62)))
self.data.power_current_12.append(float(match.group(63)))
self.data.power_voltage_24.append(float(match.group(64)))
self.data.power_current_24.append(float(match.group(65)))
def _build_parsed_values(self, match):
"""
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
"""
# Use the date_time_string to calculate an epoch timestamp (seconds since
# 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining MET data to the named parameters
self.data.main_voltage.append(float(match.group(2)))
self.data.main_current.append(float(match.group(3)))
self.data.percent_charge.append(float(match.group(4)))
self.data.override_flag.append(str(match.group(5)))
self.data.error_flag1.append(str(match.group(6)))
self.data.error_flag2.append(str(match.group(7)))
self.data.solar_panel1_state.append(int(match.group(8)))
self.data.solar_panel1_voltage.append(float(match.group(9)))
self.data.solar_panel1_current.append(float(match.group(10)))
self.data.solar_panel2_state.append(int(match.group(11)))
self.data.solar_panel2_voltage.append(float(match.group(12)))
self.data.solar_panel2_current.append(float(match.group(13)))
self.data.solar_panel3_state.append(int(match.group(14)))
self.data.solar_panel3_voltage.append(float(match.group(15)))
self.data.solar_panel3_current.append(float(match.group(16)))
self.data.solar_panel4_state.append(int(match.group(17)))
self.data.solar_panel4_voltage.append(float(match.group(18)))
self.data.solar_panel4_current.append(float(match.group(19)))
self.data.wind_turbine1_state.append(int(match.group(20)))
self.data.wind_turbine1_voltage.append(float(match.group(21)))
self.data.wind_turbine1_current.append(float(match.group(22)))
self.data.wind_turbine2_state.append(int(match.group(23)))
self.data.wind_turbine2_voltage.append(float(match.group(24)))
self.data.wind_turbine2_current.append(float(match.group(25)))
self.data.fuel_cell1_state.append(int(match.group(26)))
self.data.fuel_cell1_voltage.append(float(match.group(27)))
self.data.fuel_cell1_current.append(float(match.group(28)))
self.data.fuel_cell2_state.append(int(match.group(29)))
self.data.fuel_cell2_voltage.append(float(match.group(30)))
self.data.fuel_cell2_current.append(float(match.group(31)))
self.data.battery_bank1_temperature.append(float(match.group(32)))
self.data.battery_bank1_voltage.append(float(match.group(33)))
self.data.battery_bank1_current.append(float(match.group(34)))
self.data.battery_bank2_temperature.append(float(match.group(35)))
self.data.battery_bank2_voltage.append(float(match.group(36)))
self.data.battery_bank2_current.append(float(match.group(37)))
self.data.battery_bank3_temperature.append(float(match.group(38)))
self.data.battery_bank3_voltage.append(float(match.group(39)))
self.data.battery_bank3_current.append(float(match.group(40)))
self.data.battery_bank4_temperature.append(float(match.group(41)))
self.data.battery_bank4_voltage.append(float(match.group(42)))
self.data.battery_bank4_current.append(float(match.group(43)))
self.data.external_voltage.append(float(match.group(44)))
self.data.external_current.append(float(match.group(45)))
self.data.internal_voltage.append(float(match.group(46)))
self.data.internal_current.append(float(match.group(47)))
self.data.internal_temperature.append(float(match.group(48)))
self.data.fuel_cell_volume.append(float(match.group(49)))
self.data.seawater_ground_state.append(int(match.group(50)))
self.data.seawater_ground_positve.append(float(match.group(51)))
self.data.seawater_ground_negative.append(float(match.group(52)))
self.data.cvt_state.append(int(match.group(53)))
self.data.cvt_voltage.append(float(match.group(54)))
self.data.cvt_current.append(float(match.group(55)))
self.data.cvt_interlock.append(int(match.group(56)))
self.data.cvt_temperature.append(float(match.group(57)))
self.data.error_flag3.append(str(match.group(58)))
def _build_parsed_values(self, match):
'''
Extract the data from the relevant regex groups and assign to elements
of the data dictionary.
'''
# Use the date_time_string to calculate an epoch timestamp (seconds
# since 1970-01-01)
epts = dcl_to_epoch(match.group(1))
self.data.time.append(epts)
self.data.dcl_date_time_string.append(str(match.group(1)))
# Assign the remaining ZPLSC data to the named parameters
self.data.transmission_date_string.append(str(match.group(2)))
# the rest of the data is in a comma separated string, so...
data = (match.group(3)).split(',')
# serial number, phase and burst number
self.data.serial_number.append(int(data[0]))
self.data.phase.append(int(data[1]))
self.data.burst_number.append(int(data[2]))
# number of frequencies and bins per profile
nfreq = int(data[3])
strt = 4
stop = strt + nfreq
nbins = map(int, data[strt:stop])
self.data.number_bins.append(nbins)
# minimum values per frequency
strt = stop
stop = strt + nfreq
self.data.minimum_values.append(map(int, data[strt:stop]))
# tilts, battery and temperature (no pressure sensor)
strt = stop
self.data.burst_date_string.append(str(data[strt]))
self.data.tilts.append(map(float, data[strt + 1:strt + 3]))
self.data.battery_voltage.append(float(data[strt + 3]))
self.data.temperature.append(float(data[strt + 4]))
# frequency #1
strt += 7
freq = [int(data[strt])]
self.data.profiles_freq1.append(
map(int, data[strt + 1:strt + 1 + nbins[0]]))
# frequency #2
if nfreq >= 2:
strt += 2 + nbins[0]
freq.append(int(data[strt]))
self.data.profiles_freq2.append(
map(int, data[strt + 1:strt + 1 + nbins[1]]))
# frequency #3
if nfreq >= 3:
strt += 2 + nbins[1]
freq.append(int(data[strt]))
self.data.profiles_freq3.append(
map(int, data[strt + 1:strt + 1 + nbins[2]]))
# frequency #4
if nfreq == 4:
strt += 2 + nbins[2]
freq.append(int(data[strt]))
self.data.profiles_freq4.append(
map(int, data[strt + 1:strt + 1 + nbins[3]]))
self.data.frequencies.append(freq)