def merge(cls, files: List[str], output: str):
r"""
Merge single-tilt standard data into a volumetric scan
Args:
files (List[str]): List of path of data to be merged
output (str): The file path to store the merged data
"""
with prepare_file(files[0]) as first_file:
first_file.seek(160)
task = np.frombuffer(first_file.read(256), SDD_task)
cut_num = task["cut_number"][0]
total_seek_bytes = first_file.tell() + 256 * cut_num
all_tilt_data = [b""] * cut_num
first_file.seek(0)
header_bytes = first_file.read(total_seek_bytes)
rad = np.frombuffer(first_file.read(64), SDD_rad_header)
el_num = rad["elevation_number"][0] - 1
first_file.seek(total_seek_bytes)
all_tilt_data[el_num] = first_file.read()
for f in files[1:]:
with prepare_file(f) as buf:
buf.seek(total_seek_bytes)
rad = np.frombuffer(buf.read(64), SDD_rad_header)
buf.seek(total_seek_bytes)
el_num = rad["elevation_number"][0] - 1
all_tilt_data[el_num] = buf.read()
with open(output, "wb") as out:
out.write(header_bytes)
out.write(b"".join(all_tilt_data))
def __init__(self, file: Any, radar_type: Optional[str] = None, file_name: Optional[str] = None):
r'''
Parameters
----------
file: str / obj with read method
path directed to the file to read / file object
radar_type: str, optional
type of radar
'''
f = prepare_file(file)
filename = Path(file).name if isinstance(file, str) else ''
self.code, radartype = _detect_radartype(f, filename, type_assert=radar_type)
if radar_type:
if radartype is not radar_type:
warnings.warn('Contradictory information from input radar type and\
radar type detected from input file.')
self.radartype = radar_type
else:
self.radartype = radartype
f.seek(0)
if radartype in ['SA', 'SB']:
self._SAB_handler(f)
elif radartype in ['CA', 'CB']:
self._SAB_handler(f, SAB=False)
elif radartype is 'CC':
self._CC_handler(f)
elif radartype in ['SC', 'CD']:
self._CD_handler(f)
else:
raise RadarDecodeError('Unrecognized data')
self._update_radar_info()
f.close()
def __init__(
self,
file: Any,
radar_type: Optional[str] = None,
file_name: Optional[str] = None,
):
f = prepare_file(file)
filename = Path(file).name if isinstance(file, str) else ""
self.code, t_infer = infer_type(f, filename)
if radar_type:
if t_infer != radar_type:
warnings.warn(
"Contradictory information from input radar type and"
"radar type detected from input file.")
self.radartype = radar_type
else:
if not t_infer:
raise RadarDecodeError(
"Unable to determine the file type. Use `radar_type` keyword"
"to specify the radar type.")
self.radartype = t_infer
self.site_info = {}
f.seek(0)
if self.radartype in ["SA", "SB"]:
self._SAB_handler(f)
elif self.radartype in ["CA", "CB"]:
self._SAB_handler(f, dtype="CAB")
elif self.radartype == "CC2":
self._CC2_handler(f)
else:
try:
if self.radartype == "CC":
self._CC_handler(f)
elif self.radartype in ["SC", "CD"]:
self._CD_handler(f)
else:
raise RadarDecodeError("Unrecognized data")
except Exception as err:
# Currently there's no good way to differentiate the special
# SC/CC files, so catch the exception of normal decoding process
# and try this one if possible
try:
f.seek(0)
self._SAB_handler(f, dtype="special")
except:
raise err
self._update_radar_info()
# TODO: Override information
if "longitude" in self.site_info:
self.stationlon = self.site_info["longitude"]
if "latitude" in self.site_info:
self.stationlat = self.site_info["latitude"]
if "height" in self.site_info:
self.radarheight = self.site_info["height"]
if "name" in self.site_info:
self.name = self.site_info["name"]
if self.code == None and self.name:
# Use name as code when code is missing
self.code = self.name
f.close()
def __init__(self, file:Any):
f = prepare_file(file)
header = np.frombuffer(f.read(1024), SWAN_dtype)
xdim, ydim, zdim = header['x_grid_num'][0], header['y_grid_num'][0], header['z_grid_num'][0]
dtype = header['m_data_type'][0]
data_size = int(xdim) * int(ydim) * int(zdim) * self.size_conv[dtype]
bittype = self.dtype_conv[dtype]
data_body = np.frombuffer(f.read(data_size), bittype).astype(int)
if zdim == 1:
out = data_body.reshape(xdim, ydim)
else:
out = data_body.reshape(zdim, xdim, ydim)
self.data_time = datetime.datetime(header['year'], header['month'], header['day'], header['hour'], header['minute'])
# TODO: Recognize correct product name
self.product_name = b''.join(header['data_name'][0, :4]).decode()
start_lon = header['start_lon'][0]
start_lat = header['start_lat'][0]
center_lon = header['center_lon'][0]
center_lat = header['center_lat'][0]
end_lon = center_lon * 2 - start_lon
end_lat = center_lat * 2 - start_lat
#x_reso = header['x_reso'][0]
#y_reso = header['y_reso'][0]
self.lon = np.linspace(start_lon, end_lon, xdim) # For shape compatibility
self.lat = np.linspace(start_lat, end_lat, ydim)
if self.product_name == 'CR':
self.data = np.ma.array((out - 66) / 2, mask=(out==0))
else:
self.data = np.ma.array(out, mask=(out==0))
def __init__(self, file):
self.f = prepare_file(file)
self._parse()
self._update_radar_info()
self.stationlat = self.geo["lat"][0]
self.stationlon = self.geo["lon"][0]
self.radarheight = self.geo["height"][0]
if self.name == "None":
self.name = self.code
del self.geo
self.f.close()
def __init__(self, file):
self.f = prepare_file(file)
self._parse()
self._update_radar_info()
self.stationlat = self.geo['lat'][0]
self.stationlon = self.geo['lon'][0]
self.radarheight = self.geo['height'][0]
if self.name == 'None':
self.name = self.code
del self.geo
self.f.close()
def __init__(
self,
file: Any,
radar_type: Optional[str] = None,
file_name: Optional[str] = None,
):
r"""
Parameters
----------
file: str / obj with read method
path directed to the file to read / file object
radar_type: str, optional
type of radar
"""
f = prepare_file(file)
filename = Path(file).name if isinstance(file, str) else ""
self.code, radartype = _detect_radartype(f,
filename,
type_assert=radar_type)
if radar_type:
if radartype is not radar_type:
warnings.warn(
"Contradictory information from input radar type and\
radar type detected from input file.")
self.radartype = radar_type
else:
self.radartype = radartype
f.seek(0)
if radartype in ["SA", "SB"]:
self._SAB_handler(f)
elif radartype in ["CA", "CB"]:
self._SAB_handler(f, dtype="CAB")
else:
try:
if radartype == "CC":
self._CC_handler(f)
elif radartype in ["SC", "CD"]:
self._CD_handler(f)
else:
raise RadarDecodeError("Unrecognized data")
except Exception as err:
# Currently there's no good way to differentiate the special
# SC/CC files, so catch the exception of normal decoding process
# and try this one if possible
try:
f.seek(0)
self._SAB_handler(f, dtype="special")
except:
raise err
self._update_radar_info()
f.close()
def __init__(self, file: Any):
with prepare_file(file) as self.f:
self._parse()
self._update_radar_info()
# In standard data, station information stored in file
# has higher priority, so we override some information.
self.stationlat = self.geo["lat"]
self.stationlon = self.geo["lon"]
self.radarheight = self.geo["height"]
if self.name == "None":
# Last resort to find info
self.name = self.geo["name"]
self.angleindex_r = self.available_tilt("REF") # API consistency
del self.geo
def __init__(self, file: Any, product: Optional[str] = None):
f = prepare_file(file)
header = np.frombuffer(f.read(1024), SWAN_dtype)
xdim, ydim, zdim = (
header["x_grid_num"][0],
header["y_grid_num"][0],
header["z_grid_num"][0],
)
dtype = header["m_data_type"][0]
data_size = int(xdim) * int(ydim) * int(zdim) * self.size_conv[dtype]
bittype = self.dtype_conv[dtype]
data_body = np.frombuffer(f.read(data_size), bittype).astype(int)
# Convert data to i4 to avoid overflow in later calculation
if zdim == 1:
# 2D data
out = data_body.reshape(ydim, xdim)
else:
# 3D data
out = data_body.reshape(zdim, ydim, xdim)
self.data_time = datetime.datetime(
header["year"][0],
header["month"][0],
header["day"][0],
header["hour"][0],
header["minute"][0],
)
# TODO: Recognize correct product name
product_name = ((b"".join(header["data_name"]).decode(
"gbk", "ignore").replace("\x00", "")) if not product else product)
self.product_name = product_name
for pname in ["CR", "3DREF"]:
if product_name.startswith(pname):
self.product_name = pname
start_lon = header["start_lon"][0]
start_lat = header["start_lat"][0]
center_lon = header["center_lon"][0]
center_lat = header["center_lat"][0]
end_lon = center_lon * 2 - start_lon
end_lat = center_lat * 2 - start_lat
# x_reso = header['x_reso'][0]
# y_reso = header['y_reso'][0]
self.lon = np.linspace(start_lon, end_lon,
xdim) # For shape compatibility
self.lat = np.linspace(start_lat, end_lat, ydim)
if self.product_name in ["CR", "3DREF"]:
self.data = (np.ma.masked_equal(out, 0) - 66) / 2
else:
# Leave data unchanged because the scale and offset are unclear
self.data = np.ma.masked_equal(out, 0)
def __init__(self, file: Any):
r'''
Parameters
----------
file: str
path directed to the file to read
'''
self.f = prepare_file(file)
self._parse()
self.f.close()
self._update_radar_info()
if self.name == 'None':
# Last resort to find info
self.stationlat = self.geo['lat'][0]
self.stationlon = self.geo['lon'][0]
self.radarheight = self.geo['height'][0]
self.name = self.code
self.angleindex_r = self.available_tilt('REF') # API consistency
del self.geo
def __init__(self, file: Any):
r"""
Parameters
----------
file: str
path directed to the file to read
"""
self.f = prepare_file(file)
self._parse()
self.f.close()
self._update_radar_info()
# In standard data, station information stored in file
# has higher priority, so we override some information.
self.stationlat = self.geo["lat"][0]
self.stationlon = self.geo["lon"][0]
self.radarheight = self.geo["height"][0]
if self.name == "None":
# Last resort to find info
self.name = self.code
self.angleindex_r = self.available_tilt("REF") # API consistency
del self.geo
def __init__(
self,
file: Any,
radar_type: Optional[str] = None,
file_name: Optional[str] = None,
):
r"""
Parameters
----------
file: str / obj with read method
path directed to the file to read / file object
radar_type: str, optional
type of radar
"""
f = prepare_file(file)
filename = Path(file).name if isinstance(file, str) else ""
self.code, radartype = _detect_radartype(f,
filename,
type_assert=radar_type)
if radar_type:
if radartype is not radar_type:
warnings.warn(
"Contradictory information from input radar type and\
radar type detected from input file.")
self.radartype = radar_type
else:
self.radartype = radartype
f.seek(0)
if radartype in ["SA", "SB"]:
self._SAB_handler(f)
elif radartype in ["CA", "CB"]:
self._SAB_handler(f, SAB=False)
elif radartype is "CC":
self._CC_handler(f)
elif radartype in ["SC", "CD"]:
self._CD_handler(f)
else:
raise RadarDecodeError("Unrecognized data")
self._update_radar_info()
f.close()
def __init__(self, file: Any):
f = prepare_file(file)
header = np.frombuffer(f.read(1024), SWAN_dtype)
xdim, ydim, zdim = header['x_grid_num'][0], header['y_grid_num'][
0], header['z_grid_num'][0]
dtype = header['m_data_type'][0]
data_size = int(xdim) * int(ydim) * int(zdim) * self.size_conv[dtype]
bittype = self.dtype_conv[dtype]
data_body = np.frombuffer(f.read(data_size), bittype).astype(int)
# Convert data to i4 to avoid overflow in later calculation
if zdim == 1:
# 2D data
out = data_body.reshape(xdim, ydim)
else:
# 3D data
out = data_body.reshape(zdim, ydim, xdim)
self.data_time = datetime.datetime(header['year'], header['month'],
header['day'], header['hour'],
header['minute'])
# TODO: Recognize correct product name
self.product_name = b''.join(header['data_name']).decode().replace(
'\x00', '')
start_lon = header['start_lon'][0]
start_lat = header['start_lat'][0]
center_lon = header['center_lon'][0]
center_lat = header['center_lat'][0]
end_lon = center_lon * 2 - start_lon
end_lat = center_lat * 2 - start_lat
#x_reso = header['x_reso'][0]
#y_reso = header['y_reso'][0]
self.lon = np.linspace(start_lon, end_lon,
xdim) # For shape compatibility
self.lat = np.linspace(start_lat, end_lat, ydim)
if self.product_name in ['CR', '3DREF']:
self.data = (np.ma.masked_equal(out, 0) - 66) / 2
else:
# Leave data unchanged because the scale and offset are unclear
self.data = np.ma.masked_equal(out, 0)
def __init__(self, file):
f = prepare_file(file)
filename = Path(file).name if isinstance(file, str) else ""
try:
self.code = self.name = filename.split("_")[3]
except IndexError:
self.code = self.name = "None"
self._d = data = np.frombuffer(f.read(), dtype=PA_radial)
self.stationlon = data["header"]["longitude"][0] * 360 / 65535
self.stationlat = data["header"]["latitude"][0] * 360 / 65535
self.radarheight = data["header"]["height"][0] * 1000 / 65535
self.scantime = datetime.datetime.utcfromtimestamp(
data["data"]["radial_time"][0])
self.reso = np.round(
data["data"]["gate_length"][0] * 1000 / 65535) / 1000
self.first_gate_dist = (
np.round(data["data"]["first_gate_dist"][0] * 1000 / 65535) / 1000)
el_num = data["data"]["el_num"][0]
az_num = data["data"]["az_num"][0]
radial_num = 2000
el = data["data"]["elevation"].astype(int) * 360 / 65535
self.el = el.reshape(az_num, el_num).max(axis=0)
self.data = dict()
self.aux = dict()
# fmt:off
tref = (np.ma.masked_equal(
data["data"]["tref"].reshape(az_num, el_num, radial_num),
255).astype(int) * 106 / 255 - 20)
ref = (np.ma.masked_equal(
data["data"]["ref"].reshape(az_num, el_num, radial_num),
255).astype(int) * 106 / 255 - 20)
vel = (np.ma.masked_equal(
data["data"]["vel"].reshape(az_num, el_num, radial_num),
255).astype(int) * 101 / 255 - 50)
sw = (np.ma.masked_equal(
data["data"]["sw"].reshape(az_num, el_num, radial_num),
255).astype(int) * 101 / 255 - 50)
zdr = (np.ma.masked_equal(
data["data"]["zdr"].reshape(az_num, el_num, radial_num),
255).astype(int) * 16 / 255 - 5)
phi = (np.ma.masked_equal(
data["data"]["phi"].reshape(az_num, el_num, radial_num),
255).astype(int) * 181 / 255)
kdp = (np.ma.masked_equal(
data["data"]["kdp"].reshape(az_num, el_num, radial_num),
255).astype(int) * 31 / 255 - 10)
rho = (np.ma.masked_equal(
data["data"]["rho"].reshape(az_num, el_num, radial_num),
255).astype(int) * 1.1 / 255)
# fmt:on
az = data["data"]["azimuth"].astype(int).reshape(az_num,
el_num) * 360 / 65535
for el_idx in range(el_num):
self.data[el_idx] = dict()
self.data[el_idx]["TREF"] = tref[:, el_idx, :]
self.data[el_idx]["REF"] = ref[:, el_idx, :]
self.data[el_idx]["VEL"] = vel[:, el_idx, :]
self.data[el_idx]["SW"] = sw[:, el_idx, :]
self.data[el_idx]["ZDR"] = zdr[:, el_idx, :]
self.data[el_idx]["PHI"] = phi[:, el_idx, :]
self.data[el_idx]["KDP"] = kdp[:, el_idx, :]
self.data[el_idx]["RHO"] = rho[:, el_idx, :]
self.aux[el_idx] = dict()
self.aux[el_idx]["azimuth"] = az[:, el_idx]
