blimpy/filterbank.py
def read_hdf5(self, filename, f_start=None, f_stop=None,
                        t_start=None, t_stop=None, load_data=True):
        """ Populate Filterbank instance with data from HDF5 file

        Note:
            This is to be deprecated in future, please use Waterfall() to open files.
        """
        print("Warning: this function will be deprecated in the future. Please use Waterfall to open HDF5 files.")
#        raise DeprecationWarning('Please use Waterfall to open HDF5 files.')

        self.header = {}
        self.filename = filename
        self.h5 = h5py.File(filename)
        for key, val in self.h5[b'data'].attrs.items():
            if six.PY3:
                key = bytes(key, 'ascii')
            if key == b'src_raj':
                self.header[key] = Angle(val, unit='hr')
            elif key == b'src_dej':
                self.header[key] = Angle(val, unit='deg')
            else:
                self.header[key] = val

        self.n_ints_in_file = self.h5[b"data"].shape[0]
        i_start, i_stop, chan_start_idx, chan_stop_idx = self._setup_freqs(f_start=f_start, f_stop=f_stop)
        ii_start, ii_stop, n_ints = self._setup_time_axis(t_start=t_start, t_stop=t_stop)

        if load_data:
            self.data = self.h5[b"data"][ii_start:ii_stop, :, chan_start_idx:chan_stop_idx]

            self.file_size_bytes = os.path.getsize(self.filename)

#         if self.header[b'foff'] < 0:
#             self.data = self.data[..., ::-1] # Reverse data

        else:
            print("Skipping data load...")
            self.data = np.array([0])
            self.n_ints_in_file  = 0
            self.file_size_bytes = os.path.getsize(self.filename)
def read_hdf5(self, filename, f_start=None, f_stop=None,
                        t_start=None, t_stop=None, load_data=True):
        """ Populate Filterbank instance with data from HDF5 file

        Note:
            This is to be deprecated in future, please use Waterfall() to open files.
        """
        print("Warning: this function will be deprecated in the future. Please use Waterfall to open HDF5 files.")
#        raise DeprecationWarning('Please use Waterfall to open HDF5 files.')

        self.header = {}
        self.filename = filename
        self.h5 = h5py.File(filename)
        for key, val in self.h5[b'data'].attrs.items():
            if six.PY3:
                key = bytes(key, 'ascii')
            if key == b'src_raj':
                self.header[key] = Angle(val, unit='hr')
            elif key == b'src_dej':
                self.header[key] = Angle(val, unit='deg')
            else:
                self.header[key] = val

        self.n_ints_in_file = self.h5[b"data"].shape[0]
        i_start, i_stop, chan_start_idx, chan_stop_idx = self._setup_freqs(f_start=f_start, f_stop=f_stop)
        ii_start, ii_stop, n_ints = self._setup_time_axis(t_start=t_start, t_stop=t_stop)

        if load_data:
            self.data = self.h5[b"data"][ii_start:ii_stop, :, chan_start_idx:chan_stop_idx]

            self.file_size_bytes = os.path.getsize(self.filename)

#         if self.header[b'foff'] < 0:
#             self.data = self.data[..., ::-1] # Reverse data

        else:
            print("Skipping data load...")
            self.data = np.array([0])
            self.n_ints_in_file  = 0
            self.file_size_bytes = os.path.getsize(self.filename)
def read_hdf5 ( self , filename , f_start = None , f_stop = None , t_start = None , t_stop = None , load_data = True ) : print ( "Warning: this function will be deprecated in the future. Please use Waterfall to open HDF5 files." ) #        raise DeprecationWarning('Please use Waterfall to open HDF5 files.') self . header = { } self . filename = filename self . h5 = h5py . File ( filename ) for key , val in self . h5 [ b'data' ] . attrs . items ( ) : if six . PY3 : key = bytes ( key , 'ascii' ) if key == b'src_raj' : self . header [ key ] = Angle ( val , unit = 'hr' ) elif key == b'src_dej' : self . header [ key ] = Angle ( val , unit = 'deg' ) else : self . header [ key ] = val self . n_ints_in_file = self . h5 [ b"data" ] . shape [ 0 ] i_start , i_stop , chan_start_idx , chan_stop_idx = self . _setup_freqs ( f_start = f_start , f_stop = f_stop ) ii_start , ii_stop , n_ints = self . _setup_time_axis ( t_start = t_start , t_stop = t_stop ) if load_data : self . data = self . h5 [ b"data" ] [ ii_start : ii_stop , : , chan_start_idx : chan_stop_idx ] self . file_size_bytes = os . path . getsize ( self . filename ) #         if self.header[b'foff'] < 0: #             self.data = self.data[..., ::-1] # Reverse data else : print ( "Skipping data load..." ) self . data = np . array ( [ 0 ] ) self . n_ints_in_file = 0 self . file_size_bytes = os . path . getsize ( self . filename )
Populate Filterbank instance with data from HDF5 file

        Note:
            This is to be deprecated in future, please use Waterfall() to open files.
Populate Filterbank instance with data from HDF5 file