def test_read(self):
"""
Test reading of HDF5 files.
"""
fn = tempfile.mktemp()
d = Dataset(fn, 'w')
tb = TargetBuffer(tags=['WI001'], name='White Island main vent',
position=(177.2, -37.5, 50),
position_error=(0.2, 0.2, 20),
description='Main vent in January 2017')
d.register_tags(['WI001', 'MD01', 'measurement'])
t = d.new(tb)
ib = InstrumentBuffer(tags=['MD01'], sensor_id='F00975',
location='West rim',
no_bits=16, type='DOAS',
description='GeoNet permanent instrument')
i = d.new(ib)
rdtb = RawDataTypeBuffer(tags=['measurement'],
name='1st round measurements',
acquisition='stationary')
rdt = d.new(rdtb)
rb = RawDataBuffer(target=t, instrument=i, type=rdt,
d_var=np.zeros((1, 2048)), ind_var=np.arange(2048),
datetime=['2017-01-10T15:23:00'])
d.new(rb)
d.close()
d1 = Dataset.open(fn)
r1 = d1.elements['RawData'][0]
self.assertEqual(r1.target.name, 'White Island main vent')
self.assertEqual(list(r1.instrument.tags)[0], 'MD01')
def main(datapath, outputpath, start, end, pg=True, deletefiles=False):
msg = "Data path is: {}\n".format(datapath)
msg += "Output path is: {}\n".format(outputpath)
msg += "Start date: {}\n".format(start)
msg += "End date: {}\n".format(end)
logging.info(msg)
dates = pd.date_range(start=start, end=end, freq='D')
if pg:
ndays = len(dates)
bar = Bar('Processing', max=ndays)
for date in dates:
if pg:
bar.next()
else:
print(date)
outputfile = 'MiniDOAS_{:d}{:02d}{:02d}.h5'.format(
date.year, date.month, date.day)
h5file = os.path.join(outputpath, outputfile)
if True:
d = Dataset(h5file, 'w')
# ToDo: get correct plume coordinates
tb = TargetBuffer(name='White Island main plume',
target_id='WI001',
position=[177.18375770, -37.52170799, 321.0])
t = d.new(tb)
wpoptions = "{'Pixel316nm':479, 'TrimLower':30, 'LPFilterCount':3,"
wpoptions += "'MinWindSpeed':3,'BrightEnough':500, 'BlueStep':5, "
wpoptions += "'MinR2:0.8, 'MaxFitCoeffError':50.0, "
wpoptions += "'InPlumeThresh':0.05, 'MinPlumeAngle':0.1, "
wpoptions += "'MaxPlumeAngle':3.0, 'MinPlumeSect':0.4, "
wpoptions += "'MaxPlumeSect':2.0, 'MeanPlumeCtrHeight':310, "
wpoptions += "'SEMeanPlumeCtrHeight':0.442, "
wpoptions += " 'MaxRangeSeperation':5000, 'MaxRangeToPlume':5000, "
wpoptions += " 'MaxPlumeWidth':2600'MaxPlumeCentreAltitude':2000, "
wpoptions += "'MaxAltSeperation':1000, 'MaxTimeDiff':30,"
wpoptions += "'MinTriLensAngle':0.1745, 'MaxTriLensAngle':2.9671,"
wpoptions += "'SEWindSpeed':0.20, 'WindMultiplier':1.24, "
wpoptions += "'SEWindDir':0.174}"
mb1 = MethodBuffer(name='WidPro v1.2',
description='Jscript wrapper for DOASIS',
settings=wpoptions)
m1 = d.new(mb1)
station_info = {}
location_name = 'White Island North-East Point'
station_info['WI301'] = {
'files': {},
'stationID': 'WI301',
'stationLoc': location_name,
'target': t,
'bearing': 6.0214,
'lon': 177.192979384,
'lat': -37.5166903535,
'elev': 49.0,
'widpro_method': m1,
'wp_station_id': 'NE'
}
station_info['WI302'] = {
'files': {},
'stationID': 'WI302',
'stationLoc': 'White Island South Rim',
'target': t,
'bearing': 3.8223,
'lon': 177.189013316,
'lat': -37.5265334424,
'elev': 96.0,
'widpro_method': m1,
'wp_station_id': 'SR'
}
for station in ['WI301', 'WI302']:
# Find the raw data
raw_data_filename = "{:s}_{:d}{:02d}{:02d}.zip"
station_id = station_info[station]['wp_station_id']
raw_data_filename = raw_data_filename.format(
station_id, date.year, date.month, date.day)
raw_data_filepath = os.path.join(datapath, 'spectra',
station_id, raw_data_filename)
if os.path.isfile(raw_data_filepath):
try:
with ZipFile(raw_data_filepath) as myzip:
myzip.extractall('/tmp')
except:
msg = "ERROR 05: Can't unzip file {}"
logging.error(msg.format(raw_data_filepath))
raw_data_filepath = None
else:
raw_data_filename = raw_data_filename.replace(
'.zip', '.csv')
raw_data_filepath = os.path.join(
'/tmp', raw_data_filename)
else:
logging.error(
"file {} does not exist".format(raw_data_filepath))
continue
try:
if not is_file_OK(raw_data_filepath):
raw_data_filepath = None
except Exception as e:
print(raw_data_filepath)
raise (e)
station_info[station]['files']['raw'] = raw_data_filepath
# Find the concentration data
monthdir = '{:d}-{:02d}'.format(date.year, date.month)
spectra_filename = "{:s}_{:d}_{:02d}_{:02d}_Spectra.csv"
spectra_filename = spectra_filename.format(
station_id, date.year, date.month, date.day)
spectra_filepath = os.path.join(datapath, 'results', monthdir,
spectra_filename)
if not is_file_OK(spectra_filepath):
spectra_filepath = None
station_info[station]['files']['spectra'] = spectra_filepath
# Find the flux data
flux_ah_filename = spectra_filename.replace(
'Spectra.csv', 'Scans.csv')
flux_ah_filepath = os.path.join(datapath, 'results', monthdir,
flux_ah_filename)
if not is_file_OK(flux_ah_filepath):
flux_ah_filepath = None
station_info[station]['files']['flux_ah'] = flux_ah_filepath
flux_ch_filename = "XX_{:d}_{:02d}_{:02d}_Combined.csv"
flux_ch_filename = flux_ch_filename.format(
date.year, date.month, date.day)
flux_ch_filepath = os.path.join(datapath, 'results', monthdir,
flux_ch_filename)
if not is_file_OK(flux_ch_filepath):
flux_ch_filepath = None
station_info[station]['files']['flux_ch'] = flux_ch_filepath
fits_flux_ah, fits_flux_ch = FITS_download(date, station)
station_info[station]['files']['fits_flux_ah'] = fits_flux_ah
station_info[station]['files']['fits_flux_ch'] = fits_flux_ch
try:
read_single_station(d, station_info[station], date)
except MiniDoasException as e:
logging.error(str(e))
fn = raw_data_filename.replace('.zip', '.csv')
fn = os.path.join('/tmp', fn)
if fn is not None and os.path.isfile(fn):
os.remove(fn)
# Wind data
windd_dir = os.path.join(datapath, 'wind', 'direction')
winds_dir = os.path.join(datapath, 'wind', 'speed')
sub_dir = '{:02d}-{:02d}'.format(date.year - 2000, date.month)
winds_filename = '{:d}{:02d}{:02d}_WS_00.txt'.format(
date.year, date.month, date.day)
windd_filename = winds_filename.replace('WS', 'WD')
winds_filepath = os.path.join(winds_dir, sub_dir, winds_filename)
windd_filepath = os.path.join(windd_dir, sub_dir, windd_filename)
if is_file_OK(winds_filepath) and is_file_OK(windd_filepath):
# Read in the raw wind data; this is currently
# not needed to reproduce flux estimates so it's
# just stored for reference
e = d.read(
{
'direction': windd_filepath,
'speed': winds_filepath
},
ftype='minidoas-wind',
timeshift=13)
gfb = e['GasFlowBuffer']
gf = d.new(gfb)
d.close()
try:
verify_flux(os.path.join(outputpath, outputfile), 1.)
except MDOASException as e:
msg = str(e)
logging.error(msg)
if deletefiles:
if h5file is not None and os.path.isfile(h5file):
os.remove(h5file)
for station in ['WI301', 'WI302']:
files = [
station_info[station]['files']['raw'],
station_info[station]['files']['fits_flux_ah'],
station_info[station]['files']['fits_flux_ch']
]
for _f in files:
if _f is not None and os.path.isfile(_f):
os.remove(_f)
if pg:
bar.finish()
def test_readall(self):
"""
Produce a complete HDF5 file for 1 day of
MiniDOAS analysis at one station.
"""
d = Dataset(tempfile.mktemp(), 'w')
# ToDo: get correct plume coordinates
tb = TargetBuffer(name='White Island main plume',
target_id='WI001',
position=[177.18375770, -37.52170799, 321.0])
t = d.new(tb)
wpoptions = "{'Pixel316nm':479, 'TrimLower':30, 'LPFilterCount':3,"
wpoptions += "'MinWindSpeed':3, 'BrightEnough':500, 'BlueStep':5,"
wpoptions += "'MinR2:0.8, 'MaxFitCoeffError':50.0,"
wpoptions += "'InPlumeThresh':0.05, 'MinPlumeAngle':0.1,"
wpoptions += "'MaxPlumeAngle':3.0, 'MinPlumeSect':0.4,"
wpoptions += "'MaxPlumeSect':2.0, 'MeanPlumeCtrHeight':310,"
wpoptions += "'SEMeanPlumeCtrHeight':0.442, 'MaxRangeToPlume':5000,"
wpoptions += "'MaxPlumeWidth':2600, 'MaxPlumeCentreAltitude':2000,"
wpoptions += "'MaxRangeSeperation':5000, 'MaxAltSeperation':1000,"
wpoptions += "'MaxTimeDiff':30, 'MinTriLensAngle':0.1745,"
wpoptions += "'MaxTriLensAngle':2.9671, 'SEWindSpeed':0.20,"
wpoptions += "'WindMultiplier':1.24, 'SEWindDir':0.174}"
mb1 = MethodBuffer(name='WidPro v1.2',
description='Jscript wrapper for DOASIS',
settings=wpoptions)
m1 = d.new(mb1)
# Read in the raw wind data; this is currently not needed to reproduce
# flux estimates so it's just stored for reference
fn_wd = os.path.join(self.data_dir, 'minidoas', 'wind',
'20161101_WD_00.txt')
fn_ws = os.path.join(self.data_dir, 'minidoas', 'wind',
'20161101_WS_00.txt')
e2 = d.read({'direction': fn_wd, 'speed': fn_ws},
ftype='minidoas-wind', timeshift=13)
gfb = e2['GasFlowBuffer']
d.new(gfb)
station_info = {}
files = {'raw': os.path.join(self.data_dir, 'minidoas',
'NE_20161101.csv'),
'spectra': os.path.join(self.data_dir, 'minidoas',
'NE_2016_11_01_Spectra.csv'),
'flux_ah': os.path.join(self.data_dir, 'minidoas',
'NE_2016_11_01_Scans.csv'),
'flux_ch': os.path.join(self.data_dir, 'minidoas',
'XX_2016_11_01_Combined.csv'),
'fits_flux_ah': os.path.join(self.data_dir, 'minidoas',
'FITS_NE_20161101_ah.csv'),
'fits_flux_ch': os.path.join(self.data_dir, 'minidoas',
'FITS_NE_20161101_ch.csv')}
station_info['WI301'] = {'files': files,
'stationID': 'WI301',
'stationLoc': 'White Island North-East Point',
'target': t,
'bearing': 6.0214,
'lon': 177.192979384, 'lat': -37.5166903535,
'elev': 49.0,
'widpro_method': m1,
'wp_station_id': 'NE'}
files = {'raw': os.path.join(self.data_dir, 'minidoas',
'SR_20161101.csv'),
'spectra': os.path.join(self.data_dir, 'minidoas',
'SR_2016_11_01_Spectra.csv'),
'flux_ah': os.path.join(self.data_dir, 'minidoas',
'SR_2016_11_01_Scans.csv'),
'flux_ch': os.path.join(self.data_dir, 'minidoas',
'XX_2016_11_01_Combined.csv'),
'fits_flux_ah': os.path.join(self.data_dir, 'minidoas',
'FITS_SR_20161101_ah.csv'),
'fits_flux_ch': os.path.join(self.data_dir, 'minidoas',
'FITS_SR_20161101_ch.csv')}
station_info['WI302'] = {'files': files,
'stationID': 'WI302',
'stationLoc': 'White Island South Rim',
'target': t,
'bearing': 3.8223,
'lon': 177.189013316, 'lat': -37.5265334424,
'elev': 96.0,
'widpro_method': m1,
'wp_station_id': 'SR'}
self.read_single_station(d, station_info['WI301'])
self.read_single_station(d, station_info['WI302'])
d.close()
