示例#1
0
    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)
示例#2
0
    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)
示例#3
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    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)
示例#4
0
    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)