blimpy/filterbank.py
def blank_dc(self, n_coarse_chan):
        """ Blank DC bins in coarse channels.

        Note: currently only works if entire file is read
        """

        if n_coarse_chan < 1:
            logger.warning('Coarse channel number < 1, unable to blank DC bin.')
            return None

        if not n_coarse_chan % int(n_coarse_chan) == 0:
            logger.warning('Selection does not contain an interger number of coarse channels, unable to blank DC bin.')
            return None

        n_coarse_chan = int(n_coarse_chan)

        n_chan = self.data.shape[-1]
        n_chan_per_coarse = int(n_chan / n_coarse_chan)

        mid_chan = int(n_chan_per_coarse / 2)

        for ii in range(n_coarse_chan):
            ss = ii*n_chan_per_coarse
            self.data[..., ss+mid_chan] = np.median(self.data[..., ss+mid_chan+5:ss+mid_chan+10])
def blank_dc(self, n_coarse_chan):
        """ Blank DC bins in coarse channels.

        Note: currently only works if entire file is read
        """

        if n_coarse_chan < 1:
            logger.warning('Coarse channel number < 1, unable to blank DC bin.')
            return None

        if not n_coarse_chan % int(n_coarse_chan) == 0:
            logger.warning('Selection does not contain an interger number of coarse channels, unable to blank DC bin.')
            return None

        n_coarse_chan = int(n_coarse_chan)

        n_chan = self.data.shape[-1]
        n_chan_per_coarse = int(n_chan / n_coarse_chan)

        mid_chan = int(n_chan_per_coarse / 2)

        for ii in range(n_coarse_chan):
            ss = ii*n_chan_per_coarse
            self.data[..., ss+mid_chan] = np.median(self.data[..., ss+mid_chan+5:ss+mid_chan+10])
def blank_dc ( self , n_coarse_chan ) : if n_coarse_chan < 1 : logger . warning ( 'Coarse channel number < 1, unable to blank DC bin.' ) return None if not n_coarse_chan % int ( n_coarse_chan ) == 0 : logger . warning ( 'Selection does not contain an interger number of coarse channels, unable to blank DC bin.' ) return None n_coarse_chan = int ( n_coarse_chan ) n_chan = self . data . shape [ - 1 ] n_chan_per_coarse = int ( n_chan / n_coarse_chan ) mid_chan = int ( n_chan_per_coarse / 2 ) for ii in range ( n_coarse_chan ) : ss = ii * n_chan_per_coarse self . data [ ... , ss + mid_chan ] = np . median ( self . data [ ... , ss + mid_chan + 5 : ss + mid_chan + 10 ] )
Blank DC bins in coarse channels.

        Note: currently only works if entire file is read
Blank DC bins in coarse channels .