async def fetch(cls, site, dt, local=False):
if local:
url = f"http://127.0.0.1:8000/data/l2raw/{site}{dt.strftime('%Y%m%d_%H%M%S')}_V06"
else:
url = f"{_url_base}/{site}/{site}_{dt.strftime('%Y%m%d_%H%M')}"
_logger.debug(
f"Downloading radar volume for {site} at {dt.strftime('%d %b %Y %H%M UTC')}"
)
bio = BytesIO()
bio.write(await download(url))
bio.seek(0)
rfile = read_nexrad_archive(bio)
rfile_dealias = dealias_unwrap_phase(rfile)
dt = datetime.strptime(rfile.time['units'],
'seconds since %Y-%m-%dT%H:%M:%SZ')
sweeps = []
for field in rfile.fields.keys():
for ie, elv in enumerate(rfile.fixed_angle['data']):
istart, iend = rfile.get_start_end(ie)
azimuths = rfile.get_azimuth(ie)
ranges = rfile.range['data']
nyquist = rfile.get_nyquist_vel(ie)
if field == 'velocity' and nyquist < 10:
continue
elif field != 'velocity' and len(sweeps) > 0 and sweeps[
-1].elevation == elv and sweeps[-1].field == field:
# Check to see if this is a "duplicate" sweep
if nyquist > 10:
# Assume this is the short-range sweep and ignore it
continue
else:
# Assume that somehow the short-range sweep got put in the file
# first and take it out. I don't think this should ever happen.
sweeps.pop()
saz = azimuths[0]
eaz = azimuths[
-1] if azimuths[-1] > azimuths[0] else azimuths[-1] + 360
dazim = round((eaz - saz) / len(azimuths), 1)
dt_sweep = dt + timedelta(seconds=rfile.time['data'][istart])
if field == 'velocity':
field_data = rfile_dealias['data'][istart:(iend + 1)]
else:
field_data = rfile.get_field(ie, field)
rs = RadarSweep(site, dt_sweep, field, elv, azimuths[0],
float(ranges[0]), dazim, 250, field_data)
sweeps.append(rs)
return cls(sweeps)
def process_NEXRAD(start_hour, end_hour, csv=False):
# start_hour = datetime(2015, 06, 2, 12, 0, 0)
# end_hour = datetime(2015, 06, 2, 13, 0, 0)
td = timedelta(hours=1)
while start_hour < end_hour:
for i, site in enumerate(radars):
# Setup output directories
image_dir = "%s/images/%s/%s" % (os.getcwd(), site, start_hour.strftime("%Y%m%d"))
csv_dir = "%s/csv_vad/%s/%s" % (os.getcwd(), site, start_hour.strftime("%Y%m%d"))
if not os.path.isdir(image_dir):
os.makedirs(image_dir)
if not os.path.isdir(csv_dir):
os.makedirs(csv_dir)
d = 'D:\\TMBell\\projects\\VADAnalysis\\data\\%s\\raw\\%s' % (site, start_hour.strftime("%Y%m%d"))
file_glob = "%s%s" % (site, start_hour.strftime("%Y%m%d_%H*"))
in_files = glob(os.path.join(d, file_glob))
for in_file in in_files:
logging.info(in_file)
try:
# Read in the file and dealias
radar = io.nexrad_archive.read_nexrad_archive(in_file)
logging.info("Dealiasing %s using PyART package..." % in_file)
VEL2 = correct.dealias_unwrap_phase(radar)
radar.add_field('VEL2', VEL2)
# Get some parameters
time = datetime_from_radar(radar)
time_str = "%s_%s" % (site, time.strftime("%Y%m%d_%H%M%S"))
elevs = utils.get_elevs(radar)
radar_elev = radar.altitude['data'][0]
# print "Trying 'our' method"
plt.figure(1, figsize=(15, 7))
our_u, our_v, hgt, gates = vad.get_uv_vs_hgt(radar, 'VEL2')
our_RMSE = utils.calc_RMSE(radar, 'VEL2', our_u, our_v)
display.u_v_rmse_plot(our_u, our_v, our_RMSE, hgt, title=time_str, elevs=elevs, radar_elev=radar_elev)
img_name = "%s_%s" % (time_str, 'fig1')
plt.savefig(os.path.join(image_dir, img_name))
plt.clf()
if csv:
csv_name = time_str + ".csv"
csv_name = os.path.join(csv_dir, csv_name)
logging.info("Exporting VAD as CSV: " + csv_name)
vad_csv.vad_to_csv(csv_name, site, radar, our_u, our_v, our_RMSE, hgt, elevs)
except IOError:
logging.warning("Error Reading NEXRAD lvlII file: " + str(in_file))
except KeyError, e:
logging.warning("Key not found " + str(e))
except Exception, e:
logging.warning(e)
def process_file(filename, outdir, dl='b1', verbose=False):
"""
"""
if verbose:
print 'Processing file: {}'.format(os.path.basename(filename))
# Read radar data
radar = read_kazr(filename, exclude_fields=None)
# Step 1: Radar significant detection
# Includes Hildebrand noise floor estimate and Doppler velocity coherency
gf = noise.velocity_coherency(
radar, gatefilter=None, num_bins=VDOP_COHER_BINS,
limits=VDOP_COHER_LIMITS, texture_window=TEXTURE_WINDOW,
texture_sample=TEXTURE_SAMPLE, min_sigma=None, max_sigma=None,
nyquist=None, rays_wrap_around=None, remove_salt=False,
fill_value=None, vdop_field=VDOP_FIELD, vdop_text_field=None,
cohere_field=None, verbose=verbose)
gf = noise.hildebrand_noise(
radar, gatefilter=gf, scale=1.0, remove_salt=False,
rays_wrap_around=False, fill_value=None, power_field=POWER_FIELD,
noise_field=None, verbose=verbose)
gf = noise.significant_detection(
radar, gatefilter=gf, min_ncp=None, remove_salt=True,
salt_window=SALT_WINDOW, salt_sample=SALT_SAMPLE, fill_holes=False,
dilate=False, structure=None, rays_wrap_around=False, ncp_field=None,
detect_field=None, verbose=verbose)
# Step 2: Doppler velocity correction
if DEALIAS == 'phase':
vdop_corr = dealias_unwrap_phase(
radar, gatefilter=gf, unwrap_unit='sweep', nyquist_vel=None,
rays_wrap_around=False, keep_original=False, skip_checks=True,
vel_field=VDOP_FIELD, corr_vel_field=None)
elif DEALIAS == 'region':
vdop_corr = dealias_region_based(
radar, gatefilter=gf, interval_splits=INTERVAL_SPLITS,
interval_limits=None, skip_between_rays=2, skip_along_ray=2,
centered=True, nyquist_vel=None, rays_wrap_around=False,
keep_original=False, vel_field=VDOP_FIELD, corr_vel_field=None)
else:
raise ValueError('Unsupported velocity correction routine')
radar.add_field(CORR_VDOP_FIELD, vdop_corr, replace_existing=True)
# TODO
# Step 3: Reflectivity correction
# Parse metadata
radar.metadata = _create_metadata(radar, filename)
# ARM file name protocols
date = datetime_from_radar(radar).strftime('%Y%m%d.%H%M%S')
filename = 'sgpkazrgecmacC1.{}.{}.cdf'.format(dl, date)
# Write CMAC NetCDF file
write_cfradial(os.path.join(outdir, filename), radar, format=FORMAT,
arm_time_variables=True)
return
