def read_subset(self, mnemonics, rep=False, seq=False, events=False):
"""
decode the data from the currently loaded message subset
using the specified mnemonics (a 'mnemonic' is simply a
descriptive, alphanumeric name for a data value, like
a key in a python dictionary). The mnemonics string
may contain multiple space delimited mnemonics
(e.g. `mnemonics='MNEMONIC1 MNEMONIC2 MNEMONIC3'`).
By default, the mnemonics are assumed to be part of a delayed
replication sequence, or have no replication at all, and `ufbint`
is used to read the data.
`ncepbufr.open.load_subset` must be called before
trying to decode a subset using `ncepbufr.open.read_subset`.
if `rep = True`, `ufbrep` is used to read data represented
a regular replication sequence. See the comments in `src/ufbrep.f` for
more details. Used for radiance data.
if `seq=True`, `ufbseq` is used to read data represented by
a sequence mnemonic. Used for gps data.
if `events=True`, `ufbevn` is used to read prepbufr
"events", and a 3-d array is returned.
Only one of seq, rep and events can be True.
returns a numpy masked array with decoded values
(missing values are masked).
The shape of the array is `(nm,nlevs)`, where
where `nm` is the number of elements in the specified
mnemonics string, and `nlevs` is the number of levels in the report.
If `events=True`, a 3rd dimension representing the prepbufr
event codes is added.
"""
if not self.subset_loaded:
raise IOError('subset not loaded, call load_subset first')
ndim = len(mnemonics.split())
if np.array([rep, seq, events]).sum() > 1:
raise ValueError('only one of rep, seq and events cannot be True')
if seq:
data = np.empty((_nmaxseq, _maxdim), np.float, order='F')
levs = _bufrlib.ufbseq(self.lunit, data, mnemonics, _nmaxseq,
_maxdim)
elif rep:
data = np.empty((ndim, _maxdim), np.float, order='F')
levs = _bufrlib.ufbrep(self.lunit, data, mnemonics, ndim, _maxdim)
elif events:
#data = np.empty((ndim,_maxdim,maxevents),np.float,order='F')
data = np.empty((ndim, _maxdim, _maxevents), np.float, order='F')
levs = _bufrlib.ufbevn(self.lunit, data, mnemonics, ndim, _maxdim,
_maxevents)
else:
data = np.empty((ndim, _maxdim), np.float, order='F')
levs = _bufrlib.ufbint(self.lunit, data, mnemonics, ndim, _maxdim)
if events:
return np.ma.masked_values(data[:, :levs, :], self.missing_value)
else:
return np.ma.masked_values(data[:, :levs], self.missing_value)
def read_subset(self,mnemonics,rep=False,seq=False,events=False):
"""
decode the data from the currently loaded message subset
using the specified mnemonics (a 'mnemonic' is simply a
descriptive, alphanumeric name for a data value, like
a key in a python dictionary). The mnemonics string
may contain multiple space delimited mnemonics
(e.g. `mnemonics='MNEMONIC1 MNEMONIC2 MNEMONIC3'`).
By default, the mnemonics are assumed to be part of a delayed
replication sequence, or have no replication at all, and `ufbint`
is used to read the data.
`ncepbufr.open.load_subset` must be called before
trying to decode a subset using `ncepbufr.open.read_subset`.
if `rep = True`, `ufbrep` is used to read data represented
a regular replication sequence. See the comments in `src/ufbrep.f` for
more details. Used for radiance data.
if `seq=True`, `ufbseq` is used to read data represented by
a sequence mnemonic. Used for gps data.
if `events=True`, `ufbevn` is used to read prepbufr
"events", and a 3-d array is returned.
Only one of seq, rep and events can be True.
returns a numpy masked array with decoded values
(missing values are masked).
The shape of the array is `(nm,nlevs)`, where
where `nm` is the number of elements in the specified
mnemonics string, and `nlevs` is the number of levels in the report.
If `events=True`, a 3rd dimension representing the prepbufr
event codes is added.
"""
if not self.subset_loaded:
raise IOError('subset not loaded, call load_subset first')
ndim = len(mnemonics.split())
if np.array([rep,seq,events]).sum() > 1:
raise ValueError('only one of rep, seq and events cannot be True')
if seq:
data = np.empty((_nmaxseq,_maxdim),np.float,order='F')
levs = _bufrlib.ufbseq(self.lunit,data,mnemonics,_nmaxseq,_maxdim)
elif rep:
data = np.empty((ndim,_maxdim),np.float,order='F')
levs = _bufrlib.ufbrep(self.lunit,data,mnemonics,ndim,_maxdim)
elif events:
data = np.empty((ndim,_maxdim,maxevent),np.float,order='F')
levs = _bufrlib.ufbevn(self.lunit,data,mnemonics,ndim,_maxdim,_maxevents)
else:
data = np.empty((ndim,_maxdim),np.float,order='F')
levs = _bufrlib.ufbint(self.lunit,data,mnemonics,ndim,_maxdim)
if events:
return np.ma.masked_values(data[:,:levs,:],self.missing_value)
else:
return np.ma.masked_values(data[:,:levs],self.missing_value)
def write_subset(self,data,mnemonics,rep=False,seq=False,events=False,end=False):
"""
write data to message subset using the specified mnemonics
(a 'mnemonic' is simply a descriptive, alphanumeric name for a
data value, like a key in a python dictionary). The mnemonics string
may contain multiple space delimited mnemonics
(e.g. `mnemonics='MNEMONIC1 MNEMONIC2 MNEMONIC3'`).
By default, the mnemonics are assumed to be part of a delayed
replication sequence, or have no replication at all, and `ufbint`
is used to write the data.
if `rep = True`, `ufbrep` is used to write data represented
a regular replication sequence. See the comments in `src/ufbrep.f` for
more details. Used for radiance data.
if `seq=True`, `ufbseq` is used to write data represented by
a sequence mnemonic. Used for gps data.
if `events=True`, `ufbevn` is used to write prepbufr
"events" (a 3-d data array is required)
Only one of seq, rep and events can be True.
If `end=True`, the message subset is closed and written
to the bufr file (default `False`).
"""
# make a fortran contiguous copy of input data.
if len(data.shape) in [2,3]:
dataf = np.empty(data.shape, np.float, order='F')
dataf[:] = data[:]
elif len(data.shape) == 1:
# make 1d array into 2d array with 1 level
dataf = np.empty((data.shape[0],1), np.float, order='F')
dataf[:,0] = data[:]
else:
msg = 'data in write_subset must be 1,2 or 3d'
raise ValueError(msg)
if np.array([rep,seq,events]).sum() > 1:
raise ValueError('only one of rep, seq and events cannot be True')
if seq:
levs = _bufrlib.ufbseq(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
elif rep:
levs = _bufrlib.ufbrep(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
elif events:
levs = _bufrlib.ufbevn(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1],dataf.shape[2])
else:
levs = _bufrlib.ufbint(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
# end subset if desired.
if end:
_bufrlib.writsb(self.lunit)
def write_subset(self,data,mnemonics,rep=False,seq=False,events=False,end=False):
"""
write data to message subset using the specified mnemonics
(a 'mnemonic' is simply a descriptive, alphanumeric name for a
data value, like a key in a python dictionary). The mnemonics string
may contain multiple space delimited mnemonics
(e.g. `mnemonics='MNEMONIC1 MNEMONIC2 MNEMONIC3'`).
By default, the mnemonics are assumed to be part of a delayed
replication sequence, or have no replication at all, and `ufbint`
is used to write the data.
if `rep = True`, `ufbrep` is used to write data represented
a regular replication sequence. See the comments in `src/ufbrep.f` for
more details. Used for radiance data.
if `seq=True`, `ufbseq` is used to write data represented by
a sequence mnemonic. Used for gps data.
if `events=True`, `ufbevn` is used to write prepbufr
"events" (a 3-d data array is required)
Only one of seq, rep and events can be True.
If `end=True`, the message subset is closed and written
to the bufr file (default `False`).
"""
# make a fortran contiguous copy of input data.
if len(data.shape) in [2,3]:
dataf = np.empty(data.shape, np.float, order='F')
dataf[:] = data[:]
elif len(data.shape) == 1:
# make 1d array into 2d array with 1 level
dataf = np.empty((data.shape[0],1), np.float, order='F')
dataf[:,0] = data[:]
else:
msg = 'data in write_subset must be 1,2 or 3d'
raise ValueError(msg)
if np.array([rep,seq,events]).sum() > 1:
raise ValueError('only one of rep, seq and events cannot be True')
if seq:
levs = _bufrlib.ufbseq(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
elif rep:
levs = _bufrlib.ufbrep(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
elif events:
levs = _bufrlib.ufbevn(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1],dataf.shape[2])
else:
levs = _bufrlib.ufbint(self.lunit,dataf,mnemonics,dataf.shape[0],\
dataf.shape[1])
# end subset if desired.
if end:
_bufrlib.writsb(self.lunit)