def plot_gasflow(gf, vent=None, scale=100., **kargs):
if vent is None:
raise VizException("Please provide a vent location (lon, lat)")
pos = gf.position[:]
vx = gf.vx[:]
vy = gf.vy[:]
lon_min = vent[0] - 0.03
lon_max = vent[0] + 0.03
lat_min = vent[1] - 0.03
lat_max = vent[1] + 0.03
tiler = StamenTerrain()
mercator = tiler.crs
fig = plt.figure(figsize=(10, 10))
ax = plt.axes(projection=mercator)
fig.add_axes(ax)
ax.add_image(tiler, 11)
p = ccrs.PlateCarree()
g = pyproj.Geod(ellps='WGS84')
for lon, lat, _vx, _vy in zip(pos[:, 0], pos[:, 1], vx, vy):
wd = vec2bearing(_vx, _vy)
ws = np.sqrt(_vx * _vx + _vy * _vy)*scale
elon, elat, _ = g.fwd(lon, lat, wd, ws)
x, y = p.transform_points(ccrs.Geodetic(),
np.array([lon, elon]),
np.array([lat, elat]))
dx = y[0] - x[0]
dy = y[1] - x[1]
ax.quiver(np.array([x[0]]), np.array([x[1]]), np.array([dx]),
np.array([dy]), transform=ccrs.PlateCarree())
ax.scatter(vent[0], vent[1], marker='^', color='red', s=50,
transform=ccrs.Geodetic())
ax.set_extent([lon_min, lon_max, lat_min, lat_max])
return fig
def test_wind(self):
"""
Test handling of wind data files with different numbers
of entries for wind speed and wind direction.
"""
d = Dataset(tempfile.mktemp(), 'w')
windd_filepath = os.path.join(self.data_dir, '20170515_WD_00.txt')
winds_filepath = os.path.join(self.data_dir, '20170515_WS_00.txt')
e = d.read({'direction': windd_filepath,
'speed': winds_filepath},
ftype='minidoas-wind', timeshift=13)
gfb = e['GasFlowBuffer']
dates = gfb.datetime[:].astype('datetime64[s]')
dates += np.timedelta64(13, 'h')
self.assertEqual(dates.size, 5)
self.assertEqual(int(vec2bearing(gfb.vx[0], gfb.vy[0])), 240)
self.assertAlmostEqual(np.sqrt(gfb.vx[0]**2 + gfb.vy[0]**2), 2.5, 1)
self.assertEqual(int(vec2bearing(gfb.vx[-1], gfb.vy[-1])), 240)
self.assertAlmostEqual(np.sqrt(gfb.vx[-1]**2 + gfb.vy[-1]**2), 4.2, 1)
def test_read_wind(self):
d = Dataset(tempfile.mktemp(), 'w')
fin = os.path.join(self.data_dir, 'TOFP04', 'wind', '2017_06_14.txt')
gf = d.read(fin, ftype='flyspecwind', timeshift=13)
vx = gf.vx[0]
vy = gf.vy[0]
dt = gf.datetime[0]
v = np.sqrt(vx * vx + vy * vy)
self.assertAlmostEqual(v, 10.88, 2)
self.assertAlmostEqual(vec2bearing(vx, vy), 255, 6)
self.assertEqual(dt, np.datetime64('2017-06-13T17:00:00'))
def test_read(self):
d = Dataset(tempfile.mktemp(), 'w')
d.read(os.path.join(self.data_dir,
'gns_wind_model_data_ecmwf_20160921_0630.txt'),
ftype='NZMETSERVICE')
gf = d.elements['GasFlow'][0]
res = get_wind_speed(gf, 174.735, -36.890, 1000,
'2016-09-21T06:00:00+12:00')
(lon, lat, hght, time, vx, vx_error, vy, vy_error, vz, vz_error,
dist) = res
self.assertEqual(lon, 174.735)
self.assertEqual(lat, -36.890)
self.assertEqual(hght, 1000)
v = math.sqrt(vx * vx + vy * vy)
self.assertAlmostEqual(v / 0.514444, 17, 6)
self.assertAlmostEqual(70., vec2bearing(vx, vy), 6)
m = gf.methods[0]
self.assertEqual(m.name, 'gfs')
d.read(os.path.join(self.data_dir,
'gns_wind_model_data_ecmwf_20160921_0630.txt'),
ftype='NZMETSERVICE',
preferred_model='ecmwf')
gf1 = d.elements['GasFlow'][1]
res = get_wind_speed(gf1, 174.755, -36.990, 1000,
'2016-09-21T06:00:00+12:00')
(lon, lat, hght, time, vx, vx_error, vy, vy_error, vz, vz_error,
dist) = res
v = math.sqrt(vx * vx + vy * vy)
self.assertEqual(lon, 174.735)
self.assertEqual(lat, -36.890)
self.assertEqual(hght, 1000)
v = math.sqrt(vx * vx + vy * vy)
self.assertAlmostEqual(v / 0.514444, 19, 6)
self.assertAlmostEqual(65., vec2bearing(vx, vy), 6)
self.assertEqual(gf1.methods[0].name, 'ecmwf')
self.assertEqual(gf1.unit, 'm/s')
def test_read(self):
d = Dataset(tempfile.mktemp(), 'w')
e = d.read(os.path.join(self.data_dir, 'minidoas', 'NE_20161101.csv'),
ftype='minidoas-raw')
rb = e['RawDataBuffer']
self.assertEqual(rb.d_var.shape, (7615, 482))
self.assertEqual(rb.d_var[0, 0], 78)
self.assertEqual(rb.datetime[0],
np.datetime64('2016-11-01T09:00:00.070'))
self.assertEqual(rb.datetime[-1],
np.datetime64('2016-11-01T16:29:54.850'))
with self.assertRaises(MiniDoasException):
e1 = d.read(os.path.join(self.data_dir, 'minidoas',
'NE_2016_11_01_Spectra.csv'),
ftype='minidoas-spectra')
e1 = d.read(os.path.join(self.data_dir, 'minidoas',
'NE_2016_11_01_Spectra.csv'),
date='2016-11-01', ftype='minidoas-spectra', timeshift=13)
cb = e1['ConcentrationBuffer']
self.assertEqual(cb.datetime[-1],
np.datetime64('2016-11-01T03:28:07.410'))
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}, timeshift=13,
ftype='minidoas-wind')
gfb = e2['GasFlowBuffer']
self.assertEqual(int(vec2bearing(gfb.vx[0], gfb.vy[0])), 240)
self.assertAlmostEqual(np.sqrt(gfb.vx[0]**2 + gfb.vy[0]**2), 3.2, 1)
self.assertEqual(gfb.datetime[0],
np.datetime64("2016-10-31T19:10:00.000"))
e3 = d.read(os.path.join(self.data_dir, 'minidoas',
'XX_2016_11_01_Combined.csv'),
date='2016-11-01', ftype='minidoas-scan', station='NE',
timeshift=13)
fb = e3['FluxBuffer']
np.testing.assert_array_almost_equal(fb.value[:],
np.array([3.8, 1.2]), 1)
self.assertEqual(fb.datetime[0],
np.datetime64('2016-10-31T23:15:04'))
def flux_ah(pf, perror_thresh=0.5, smoothing=False):
"""
Compute the flux for assumed height.
"""
f = pf.fluxes[0]
c = f.concentration
errors = []
for i, fidx in enumerate(pf.flux_indices[0][:]):
idx0, idx1 = f.concentration_indices[fidx]
so2_raw = c.value[idx0:idx1]
r = c.rawdata
ridx = c.rawdata_indices[idx0:idx1]
angles = r[0].inc_angle[ridx]
bearing = r[0].bearing[0]
if smoothing:
so2_smooth = binomial_filter(so2_raw, [1, 2, 1], 5)
p = fit_gaussian(angles, so2_smooth)
so2 = gaussian_pts(angles, p)
else:
so2 = so2_raw
# Get the wind direction
gf = f.gasflow
gf_times = f.gasflow.datetime[:].astype('datetime64[s]')
gf_idx = np.argmin(np.abs(gf_times - np.datetime64(f.datetime[fidx])))
vx, vy = gf.vx[gf_idx], gf.vy[gf_idx]
wd = vec2bearing(vx, vy)
ws = np.sqrt(vx * vx + vy * vy)
t_angle = np.cos(np.deg2rad(bearing - wd - 90.))
_, _, elev0 = gf.position[gf_idx]
_, _, elev2 = gf.position[gf_idx + 2]
plumewidth = elev2 - elev0
plmax = np.argmax(so2)
edge = 0.05 * so2.max()
pidx = np.where(so2 >= edge)
plstart = pidx[0][0]
plend = pidx[0][-1]
plrange = np.abs(
np.deg2rad(angles[plstart]) - np.deg2rad(angles[plend]))
# calculate distance between measurements assuming dx = r * theta
int_time = r[0].integration_time[ridx] / 1000.
dx = (np.ones(angles.size) * 0.015707963 * 1000. / 992 * int_time *
plumewidth / plrange)
col_amt = dx[plstart:plend + 1] * so2[plstart:plend + 1]
ica = np.sum(col_amt)
# correct for a non-perpendicular transect through the plume
ica = abs(t_angle * ica)
flux = ica * ws * 0.000230688
# Compute percentage error
x = pf.value[i] * 86.4
x0 = flux
p_error = 100. * abs(x0 - x) / x
if p_error > perror_thresh:
msg = "ERROR 03: Error of {:.3f} exceeds threshold"
msg += " for assumed height flux.\n"
msg += "Date: {:s}\n"
msg += "Expected flux (FITS): {:.3f}; Original flux: {:.3f}; "
msg += "Estimated flux: {:.3f}\n"
msg += "Plume geometry: start={:.3f}, max={:.3f}, end={:.3f}"
msg += ", width={:.3f}\n"
msg += "Wind: track={:.3f} sp={:.3f}\n"
msg = msg.format(p_error, f.datetime[fidx], x,
f.value[fidx] * 86.4, x0,
np.deg2rad(angles[plstart]),
np.deg2rad(angles[plmax]),
np.deg2rad(angles[plend]), plumewidth, wd, ws)
errors.append(msg)
if len(errors) > 0:
raise MDOASException(''.join(errors))
def write_testfile(d, date, time, fin):
"""
This will write a file that is identical to the input file
but taking all the information from the GasFlow element.
"""
gf = d.elements['GasFlow'][0]
mod = gf.methods[0].name
year, month, day = int(date[0:4]), int(date[4:6]), int(date[6:8])
hour, minute = int(time[0:2]), int(time[2:4])
lines = []
# Write the header
_h, _s = re.match('(\d+)(\S+)', ampm(hour)).groups()
line = 'Forecast issued by MetService at '
line += '{:02d}:{:02d}{:s} '.format(int(_h), minute, _s)
line += '{:02d}-{:02d}-{:4d}\n\n'.format(day, month, year)
line += 'For GNS Wairakei Research Centre - Volcano Watch All times NZDT '
line += 'e.g. {:02d}{:02d}00 '.format(day, hour)
line += 'is {:s} on {:s}. '.format(ampm(hour), ord(day))
line += 'Winds in degrees/knots, heights in metres.\n'
line += 'Model of the day is {:s}\n\n'.format(mod.upper())
line += 'Data for model {:s}\n'.format(mod.upper())
lines.append(line)
# Cycle through all points
for point in volc_dict_keys:
# Write header for each point
lines.append('{:s}\n'.format(point))
times = []
ntimes = len(np.unique(gf.datetime[:]))
line = 'Height '
for i in range(ntimes):
line += 'Valid at '
line += '\n'
lines.append(line)
line = '{:8}'.format('')
# Write datetimes
dt = (nztz.localize(datetime.datetime(year, month,
day, hour)).astimezone(
timezone('UTC')))
otimes = np.unique(gf.datetime[:])
otimes.sort()
for t in otimes.astype(np.str_):
dt = timezone('UTC').localize(parse_iso_8601(t))
times.append(dt)
line += '{:<14s}'.format(dt.astimezone(nztz).strftime('%d%H%M'))
line += '\n'
lines.append(line)
ln, lt = volc_dict[point]
# Write actual wind data
for height in [1000, 2000, 3000, 4000, 6000, 8000, 10000, 12000]:
line = ''
line += '{:<8d}'.format(height)
for i, dt in enumerate(times):
res = get_wind_speed(gf, ln, lt, height,
dt.astimezone(pytz.utc))
(lon, lat, hght, time, vx, vx_error, vy, vy_error, vz,
vz_error, dist) = res
if dist > 0.0001:
line += '{0:<14s}'.format('-')
else:
try:
v = int(round(math.sqrt(vx * vx + vy * vy) / 0.514444))
vd = int(round(vec2bearing(vx, vy)))
if vd == 0:
vd = 360
except Exception as e:
print(point, hght, time)
raise e
line += '{0:03d}/{1:02d}{2:8}'.format(vd, v, '')
line += '\n'
lines.append(line)
lines.append('\n')
fin = fin.replace('ecmwf', mod)
fout = os.path.basename(fin)
fout = os.path.join('/tmp', fout.replace('.txt', '_test.txt'))
fh = open(fout, 'w')
fh.writelines(lines)
fh.close()
# Now compare with the original
if not filecmp.cmp(fout, fin, shallow=False):
raise Exception('Files %s and %s are not identical!' % (fin, fout))
else:
os.unlink(fout)