def projection(self, reso:float, h_offset:bool=False) -> tuple:
r'''Calculate the geographic coordinates of the requested data range.'''
theta = self.get_azimuth_angles(self.tilt)
r = self.get_range(self.drange, reso)
lonx, latx = get_coordinate(r, theta, self.elev, self.stationlon, self.stationlat, h_offset=h_offset)
hght = height(r, self.elev, self.radarheight) * np.ones(theta.shape[0])[:, np.newaxis]
return lonx, latx, hght, r, theta
def get_data(self):
dist = np.arange(self.start_range + self.reso,
self.end_range + self.reso, self.reso)
lon, lat = get_coordinate(dist, self.azi, self.el, self.stationlon,
self.stationlat)
hgt = (height(dist, self.el, self.radarheight) *
np.ones(self.azi.shape[0])[:, np.newaxis])
da = DataArray(self.data,
coords=[self.azi, dist],
dims=["azimuth", "distance"])
ds = Dataset(
{self.dtype: da},
attrs={
"elevation": self.el,
"range": self.end_range,
"scan_time": self.scantime,
"site_code": self.code,
"site_name": self.name,
"site_longitude": self.stationlon,
"site_latitude": self.stationlat,
"tangential_reso": self.reso,
"task": self.task_name,
},
)
ds["longitude"] = (["azimuth", "distance"], lon)
ds["latitude"] = (["azimuth", "distance"], lat)
ds["height"] = (["azimuth", "distance"], hgt)
if self.dtype in ["VEL", "SW"]:
ds["RF"] = (["azimuth", "distance"], self.data[1])
return ds
def echo_top(ref, distance, elev, radarheight, threshold=18.):
r'''
Calculate height of echo tops (ET) in one full scan
Parameters
----------
ref: numpy.ndarray dim=3 (elevation angle, distance, azimuth)
reflectivity data
distance: numpy.ndarray dim=2 (distance, azimuth)
distance from radar site
elev: numpy.ndarray or list dim=1
elevation angles in degree
radarheight: int or float
height of radar
drange: float or int
range of data to be calculated
threshold: float
minimum value of reflectivity to be taken into calculation
Returns
-------
data: numpy.ndarray
echo tops data
'''
r = np.ma.array(ref, mask=(ref > threshold))
xshape, yshape = r[0].shape
et = np.zeros((xshape, yshape))
h_ = list()
for i in elev:
h = height(distance, i, radarheight)
h_.append(h)
hght = np.concatenate(h_).reshape(r.shape)
for i in range(xshape):
for j in range(yshape):
vert_h = hght[:, i, j]
vert_r = ref[:, i, j]
if vert_r.max(
) < threshold: # Vertical points don't satisfy threshold
et[i][j] = 0
continue
elif vert_r[
-1] >= threshold: # Point in highest scan exceeds threshold
et[i][j] = vert_h[-1]
continue
else:
position = np.where(vert_r >= threshold)[0]
if position[-1] == 0:
et[i][j] = vert_h[0]
continue
else:
pos = position[-1]
z1 = vert_r[pos]
z2 = vert_r[pos + 1]
h1 = vert_h[pos]
h2 = vert_h[pos + 1]
w1 = (z1 - threshold) / (z1 - z2)
w2 = 1 - w1
et[i][j] = w1 * h2 + w2 * h1
return et
def projection(self, reso: float) -> tuple:
r = np.arange(reso, self.drange + reso, reso)
theta = np.array(self.aux[self.tilt]["azimuth"]) * deg2rad
lonx, latx = get_coordinate(r, theta, self.elev, self.stationlon,
self.stationlat)
hght = (height(r, self.elev, self.radarheight) *
np.ones(theta.shape[0])[:, np.newaxis])
return lonx, latx, hght, r, theta
def projection(self, reso):
r = np.arange(reso, self.drange + reso, reso)
theta = np.array(self.data[self.tilt]['azimuth']) * deg2rad
lonx, latx = get_coordinate(r, theta, self.elev, self.stationlon,
self.stationlat)
hght = height(r, self.elev, self.radarheight) * np.ones(
theta.shape[0])[:, np.newaxis]
return lonx, latx, hght, r, theta
def get_data(
self, tilt: int, drange: Number_T, dtype: str
) -> Union[Radial, Slice_]:
r"""
Get radar data
Parameters
----------
tilt: int
index of elevation angle
drange: float
radius of data
dtype: str
type of product (REF, VEL, etc.)
Returns
-------
r_obj: cinrad.datastruct.Radial
"""
reso = self.scan_config[tilt].dop_reso / 1000
ret = self.get_raw(tilt, drange, dtype)
if self.scan_type == "PPI":
shape = ret[0].shape[1] if isinstance(ret, tuple) else ret.shape[1]
r_obj = Radial(
ret,
int(shape * reso),
self.elev,
reso,
self.code,
self.name,
self.scantime,
dtype,
self.stationlon,
self.stationlat,
nyquist_velocity=self.scan_config[tilt].nyquist_spd,
task=self.task_name,
)
x, y, z, d, a = self.projection(reso)
r_obj.add_geoc(x, y, z)
r_obj.add_polarc(d, a)
return r_obj
else:
# Manual projection
shape = ret[0].shape[1] if isinstance(ret, tuple) else ret.shape[1]
dist = np.linspace(reso, self.drange, ret.shape[1])
d, e = np.meshgrid(dist, self.aux[tilt]["elevation"])
h = height(d, e, 0)
rhi = Slice_(
ret,
d,
h,
self.scantime,
self.code,
self.name,
dtype,
azimuth=self.aux[tilt]["azimuth"][0],
)
return rhi
def projection(self, reso:float, h_offset:bool=False) -> tuple:
header = self.f.sweeps[self.tilt][0][4][self.dtype][0]
gatenum = header.num_gates
firstgate = header.first_gate
data_range = np.arange(gatenum) * reso + firstgate
azi = np.array([ray[0].az_angle for ray in self.f.sweeps[self.tilt]]) * deg2rad
datalength = int(self.drange / reso)
lonx, latx = get_coordinate(data_range[:datalength], azi, self.elev, self.stationlon, self.stationlat,
h_offset=h_offset)
hght = height(data_range[:datalength], self.elev, 0) * np.ones(azi.shape[0])[:, np.newaxis]
return lonx, latx, hght, data_range[:datalength], azi
def _geocoor(self):
r_data = list()
x_data = list()
y_data = list()
h_data = list()
for i in self.rl:
r, x, y = grid_2d(i.data, i.lon, i.lat)
r_data.append(r)
x_data.append(x)
y_data.append(y)
for radial, elev in zip(self.rl, self.el):
hgh = height(radial.dist, elev, 0)
hgh_radial = np.asarray(hgh.tolist() * radial.data.shape[0]).reshape(radial.data.shape)
hgh_grid, x, y = grid_2d(hgh_radial, radial.lon, radial.lat)
h_data.append(hgh_grid)
return x_data, y_data, h_data, r_data
def get_data(self, tilt: int, drange: Number_T, dtype: str) -> xr.Dataset:
r"""
Get radar data with extra information
Args:
tilt (int): Index of elevation angle starting from zero.
drange (float): Radius of data.
dtype (str): Type of product (REF, VEL, etc.)
Returns:
xarray.Dataset: Data.
"""
reso = self.scan_config[tilt].dop_reso / 1000
ret = self.get_raw(tilt, drange, dtype)
shape = ret[0].shape[1] if isinstance(ret, tuple) else ret.shape[1]
if self.scan_type == "PPI":
x, y, z, d, a = self.projection(reso)
if dtype in ["VEL", "SW"]:
da = xr.DataArray(ret[0], coords=[a, d], dims=["azimuth", "distance"])
else:
da = xr.DataArray(ret, coords=[a, d], dims=["azimuth", "distance"])
ds = xr.Dataset(
{dtype: da},
attrs={
"elevation": self.elev,
"range": int(np.round(shape * reso)),
"scan_time": self.scantime.strftime("%Y-%m-%d %H:%M:%S"),
"site_code": self.code,
"site_name": self.name,
"site_longitude": self.stationlon,
"site_latitude": self.stationlat,
"tangential_reso": reso,
"nyquist_vel": self.scan_config[tilt].nyquist_spd,
"task": self.task_name,
},
)
ds["longitude"] = (["azimuth", "distance"], x)
ds["latitude"] = (["azimuth", "distance"], y)
ds["height"] = (["azimuth", "distance"], z)
if dtype in ["VEL", "SW"]:
ds["RF"] = (["azimuth", "distance"], ret[1])
else:
# Manual projection
dist = np.linspace(reso, self.drange, ret.shape[1])
azimuth = self.aux[tilt]["azimuth"][0]
elev = self.aux[tilt]["elevation"]
d, e = np.meshgrid(dist, elev)
h = height(d, e, self.radarheight)
if dtype in ["VEL", "SW"]:
da = xr.DataArray(
ret[0], coords=[elev, dist], dims=["tilt", "distance"]
)
else:
da = xr.DataArray(ret, coords=[elev, dist], dims=["tilt", "distance"])
# Calculate the "start" and "end" of RHI scan
# to facilitate tick labeling
start_lon = self.stationlon
start_lat = self.stationlat
end_lon, end_lat = get_coordinate(
drange, azimuth * deg2rad, 0, self.stationlon, self.stationlat
)
ds = xr.Dataset(
{dtype: da},
attrs={
"range": drange,
"scan_time": self.scantime.strftime("%Y-%m-%d %H:%M:%S"),
"site_code": self.code,
"site_name": self.name,
"site_longitude": self.stationlon,
"site_latitude": self.stationlat,
"tangential_reso": reso,
"azimuth": azimuth,
"start_lon": start_lon,
"start_lat": start_lat,
"end_lon": end_lon,
"end_lat": end_lat,
},
)
ds["x_cor"] = (["tilt", "distance"], d)
ds["y_cor"] = (["tilt", "distance"], h)
return ds
def get_data(self, tilt: int, drange: number_type, dtype: str) -> Radial:
r'''
Get radar raw data
Parameters
----------
tilt: int
index of elevation angle
drange: float
radius of data
dtype: str
type of product (REF, VEL, etc.)
Returns
-------
r_obj: cinrad.datastruct.Radial
'''
self.tilt = tilt if self.scan_type == 'PPI' else 0
self.drange = drange
if self.scan_type == 'RHI':
max_range = self.scan_config[0].max_range1 / 1000
if drange > max_range:
drange = max_range
self.elev = self.el[tilt]
try:
raw = np.array(self.data[tilt][dtype])
except KeyError:
raise RadarDecodeError('Invalid product name')
if raw.size == 0:
warnings.warn('Empty data', RuntimeWarning)
data = np.ma.array(raw, mask=(raw <= 5))
reso = self.scan_config[tilt].dop_reso / 1000
cut = data[:, :int(drange / reso)]
shape_diff = np.round(drange / reso) - cut.shape[1]
append = np.zeros((cut.shape[0], int(shape_diff))) * np.ma.masked
if dtype == 'VEL':
rf = np.ma.array(cut.data, mask=(cut.data != 1))
rf = np.ma.hstack([rf, append])
cut = np.ma.hstack([cut, append])
scale, offset = self.aux[tilt][dtype]
r = (cut - offset) / scale
if dtype in ['VEL', 'SW']:
ret = (r, rf)
else:
ret = r
if self.scan_type == 'PPI':
r_obj = Radial(ret,
int(r.shape[1] * reso),
self.elev,
reso,
self.code,
self.name,
self.scantime,
dtype,
self.stationlon,
self.stationlat,
nyquist_velocity=self.scan_config[tilt].nyquist_spd)
x, y, z, d, a = self.projection(reso)
r_obj.add_geoc(x, y, z)
r_obj.add_polarc(d, a)
return r_obj
else:
# Manual projection
dist = np.linspace(reso, self.drange, cut.shape[1])
d, e = np.meshgrid(dist, self.aux[tilt]['elevation'])
h = height(d, e, 0)
rhi = Slice_(ret,
d,
h,
self.scantime,
self.code,
self.name,
dtype,
azimuth=self.aux[tilt]['azimuth'][0])
return rhi
