def read_grd_array_by_ctl(filename, ctl=None, endian=None):
if ctl is None:
if os.path.exists(filename):
ctl = read_ctl(filename)
return read_grd_array_by_ctl(ctl.data_path, ctl)
else:
if os.path.exists(filename):
if (endian is None):
data = np.fromfile(filename, dtype='f')
else:
data = np.fromfile(filename, dtype='>f')
data = data.reshape(ctl.nvar, ctl.nensemble, ctl.ntime, ctl.nlevel,
ctl.nlat, ctl.nlon)
#print(data.shape)
grid = bd.grid(ctl.slon, ctl.dlon, ctl.elon, ctl.slat, ctl.dlat,
ctl.elat)
arr = [[[[] for t in range(ctl.ntime)]
for n in range(ctl.nensemble)] for v in range(ctl.nvar)]
for v in range(ctl.nvar):
for n in range(ctl.nensemble):
for t in range(ctl.ntime):
for z in range(ctl.nlevel):
grd = bd.grid_data(grid)
grd.dat = data[v, n, t, z, :, :]
grd.reset()
arr[v][n][t].append(grd)
return arr
return None
def read_from_gds_file(filename, grid=None):
print("a")
try:
if not os.path.exists(filename):
print(filename + " is not exist")
return None
file = open(filename, 'rb')
byteArray = file.read()
discriminator = struct.unpack("4s", byteArray[:4])[0].decode("gb2312")
t = struct.unpack("h", byteArray[4:6])
mName = struct.unpack("20s", byteArray[6:26])[0].decode("gb2312")
eleName = struct.unpack("50s", byteArray[26:76])[0].decode("gb2312")
description = struct.unpack("30s",
byteArray[76:106])[0].decode("gb2312")
level, y, m, d, h, timezone, period = struct.unpack(
"fiiiiii", byteArray[106:134])
startLon, endLon, lonInterval, lonGridCount = struct.unpack(
"fffi", byteArray[134:150])
startLat, endLat, latInterval, latGridCount = struct.unpack(
"fffi", byteArray[150:166])
isolineStartValue, isolineEndValue, isolineInterval = struct.unpack(
"fff", byteArray[166:178])
gridCount = lonGridCount * latGridCount
description = mName.rstrip('\x00') + '_' + eleName.rstrip(
'\x00') + "_" + str(level) + '(' + description.rstrip(
'\x00') + ')' + ":" + str(period)
if (gridCount == (len(byteArray) - 278) / 4):
if (startLat > 90): startLat = 90.0
if (startLat < -90): startLat = -90.0
if (endLat > 90): endLat = 90.0
if (endLat < -90): endLat = -90.0
grd = bd.grid_data(
bd.grid(startLon, lonInterval, endLon, startLat, latInterval,
endLat))
grd.dat = np.frombuffer(byteArray[278:], dtype='float32').reshape(
grd.nlat, grd.nlon)
grd.reset()
if (grid is None):
return grd
else:
return bf.ggf.linearInterpolation(grd, grid)
except Exception as e:
print(e)
return None
def read_from_nc(filename, valueName=None, grid=None):
if os.path.exists(filename):
f = Dataset(filename)
lons = None
lats = None
for key in f.variables.keys():
#print(key)
ndim = f.variables[key].ndim
if (ndim < 2):
if 'lon' in key.lower():
lonName = str(key)
lons = f.variables[lonName][:]
if 'lat' in key.lower():
latName = key
lats = f.variables[latName][:]
else:
if (valueName is None):
valueName = key
dlon = (lons[-1] - lons[0]) / (len(lons) - 1)
dlat = (lats[-1] - lats[0]) / (len(lats) - 1)
grd = bd.grid_data(
bd.grid(lons[0], dlon, lons[-1], lats[0], dlat, lats[-1]))
dat = np.squeeze(f.variables[valueName][:])
if (str(type(dat)) == "<class 'numpy.ma.core.MaskedArray'>"):
dat[dat.mask == True] = 0
dat = dat.data
if grd.nlon == grd.nlat:
strings = str(f.variables[valueName]).split("\n")[1]
lon_index = strings.find("lon")
lat_index = strings.find("lat")
if (lon_index < lat_index):
dat = dat.T
else:
if grd.nlon == len(dat):
dat = dat.T
grd.dat = dat
grd.reset()
f.close()
if (grid is None):
return grd
else:
return bf.ggf.linearInterpolation(grd, grid)
def reset(self):
if (self.dlon > 0 and self.dlat > 0):
return
dat1 = None
if (self.dlat < 0):
dat1 = self.dat[::-1, :]
tran = self.slat
self.slat = self.elat
self.elat = tran
self.dlat = abs(self.dlat)
self.dat = dat1
if (self.dlon < 0):
dat1 = self.dat[:, :-1]
tran = self.slon
self.slon = self.elon
self.elon = tran
self.dlon = abs(self.dlon)
self.dat = dat1
self.grid = grid(self.slon, self.dlon, self.elon, self.slat, self.dlat,
self.elat)
return
def read_from_micaps4(filename, grid=None):
try:
if not os.path.exists(filename):
print(filename + " is not exist")
return None
try:
file = open(filename, 'r')
str1 = file.read()
file.close()
except:
file = open(filename, 'r', encoding='utf-8')
str1 = file.read()
file.close()
strs = str1.split()
dlon = float(strs[9])
dlat = float(strs[10])
slon = float(strs[11])
elon = float(strs[12])
slat = float(strs[13])
elat = float(strs[14])
nlon = int(strs[15])
nlat = int(strs[16])
elon = slon + dlon * (nlon - 1)
elat = slat + dlat * (nlat - 1)
grd = bd.grid_data(bd.grid(slon, dlon, elon, slat, dlat, elat))
if len(strs) - 22 >= grd.nlon * grd.nlat:
k = 22
grd.dat = (np.array(strs[k:])).astype(float).reshape(
(grd.nlat, grd.nlon))
grd.reset()
if (grid is None):
return grd
else:
return bf.ggf.linearInterpolation(grd, grid)
else:
return None
except:
print(filename + "'s format is wrong")
return None
def explain_awx_bytes(byteArray):
sat96 = struct.unpack("12s", byteArray[:12])[0]
levl = np.frombuffer(byteArray[12:30], dtype='int16').astype(dtype="int32")
formatstr = struct.unpack("8s", byteArray[30:38])[0]
qualityflag = struct.unpack("h", byteArray[38:40])[0]
satellite = struct.unpack("8s", byteArray[40:48])[0]
lev2 = np.frombuffer(byteArray[48:104],
dtype='int16').astype(dtype="int32")
recordlen = levl[4]
headnum = levl[5]
datanum = levl[6]
timenum = lev2[0:5]
nlon = lev2[7]
nlat = lev2[8]
range = lev2[12:16].astype("float32")
slat = range[0] / 100
elat = range[1] / 100
slon = range[2] / 100
elon = range[3] / 100
#nintels=lev2[20:22].astype("float32")
dlon = (elon - slon) / (nlon - 1)
dlat = (elat - slat) / (nlat - 1)
grd = bd.grid_data(bd.grid(slon, dlon, elon, slat, dlat, elat))
colorlen = lev2[24]
caliblen = lev2[25]
geololen = lev2[26]
#print(levl)
#print(lev2)
head_lenght = headnum * recordlen
data_lenght = datanum * recordlen
#print(head_lenght + data_lenght)
#print( data_lenght)
#print(grd.nlon * grd.nlat)
#headrest = np.frombuffer(byteArray[:head_lenght], dtype='int8')
data_awx = np.frombuffer(byteArray[head_lenght:(head_lenght +
data_lenght)],
dtype='int8')
#print(headrest)
if colorlen <= 0:
calib = np.frombuffer(byteArray[104:(104 + 2048)],
dtype='int16').astype(dtype="float32")
else:
#color = np.frombuffer(byteArray[104:(104+colorlen*2)], dtype='int16')
calib = np.frombuffer(
byteArray[(104 + colorlen * 2):(104 + colorlen * 2 + 2048)],
dtype='int16').astype(dtype="float32")
realcalib = calib / 100.0
realcalib[calib < 0] = (calib[calib < 0] + 65536) / 100.0
awx_index = np.empty(len(data_awx), dtype="int32")
awx_index[:] = data_awx[:]
awx_index[data_awx < 0] = data_awx[data_awx < 0] + 256
awx_index *= 4
real_data_awx = realcalib[awx_index]
grd.dat = real_data_awx.reshape(grd.nlat, grd.nlon)
grd.reset()
return grd