def _extract(Rlist):
r_data = list()
elev = list()
areso = Rlist[0].a_reso if Rlist[0].a_reso else 360
for i in Rlist:
x, d, a = resample(i.data, i.dist, i.az, i.reso, areso)
r_data.append(x)
elev.append(i.elev)
data = np.concatenate(r_data).reshape(len(Rlist), r_data[0].shape[0],
r_data[0].shape[1])
return data, d, a, elev
def _extract(r_list):
d_list = np.array([i.drange for i in r_list])
if d_list.mean() != d_list.max():
raise ValueError('Input radials must have same data range')
r_data = list()
elev = list()
areso = r_list[0].a_reso if r_list[0].a_reso else 360
for i in r_list:
x, d, a = resample(i.data, i.dist, i.az, i.reso, areso)
r_data.append(x)
elev.append(i.elev)
data = np.concatenate(r_data).reshape(len(r_list), r_data[0].shape[0], r_data[0].shape[1])
return data, d, a, np.array(elev)
def _extract(r_list: Volume_T, dtype: str) -> tuple:
if len(set(i.range for i in r_list)) > 1:
raise ValueError("Input radials must have same data range")
adim_shape = set(i.dims["azimuth"] for i in r_list)
if max(adim_shape) > 400:
# CC radar
adim_interp_to = 512
else:
adim_interp_to = 360
r_data = list()
elev = list()
for i in r_list:
x, d, a = resample(
i[dtype].values,
i["distance"].values,
i["azimuth"].values,
i.tangential_reso,
adim_interp_to,
)
r_data.append(x)
elev.append(i.elevation)
data = np.concatenate(r_data).reshape(len(r_list), r_data[0].shape[0],
r_data[0].shape[1])
return data, d, a, np.array(elev)
