def return_dat(self, chan, begsam, endsam):
        """Return the data as 2D numpy.ndarray.

        Parameters
        ----------
        chan : list of int
            index (indices) of the channels to read
        begsam : int
            index of the first sample (inclusively)
        endsam : int
            index of the last sample (exclusively)

        Returns
        -------
        numpy.ndarray
            A 2d matrix, with dimension chan X samples.
        """
        #n_sam = self.hdr[4]
        interval = endsam - begsam
        dat = empty((len(chan), interval))
        
        #beg_block = floor((begsam / n_sam) * n_block)
        #end_block = floor((endsam / n_sam) * n_block)
                
        for i, chan in enumerate(chan):
            k = 0
            
            with open(self.chan_files[chan], 'rt') as f:
                f.readline()
                
                for j, datum in enumerate(f):
                    
                    if begsam <= j + 1 < endsam:
                        dat[i, k] = float64(datum)
                        k += 1
                        if k == interval:
                            break
        
        # calibration
        phys_range = self.phys_max - self.phys_min
        dig_range = self.dig_max - self.dig_min
        gain = phys_range / dig_range
        dat *= gain
        
        return dat
def return_dat ( self , chan , begsam , endsam ) : interval = endsam - begsam dat = empty ( ( len ( chan ) , interval ) ) for i , chan in enumerate ( chan ) : k = 0 with open ( self . chan_files [ chan ] , 'rt' ) as f : f . readline ( ) for j , datum in enumerate ( f ) : if begsam <= j + 1 < endsam : dat [ i , k ] = float64 ( datum ) k += 1 if k == interval : break phys_range = self . phys_max - self . phys_min dig_range = self . dig_max - self . dig_min gain = phys_range / dig_range dat *= gain return dat
Return the data as 2D numpy.ndarray.

        Parameters
        ----------
        chan : list of int
            index (indices) of the channels to read
        begsam : int
            index of the first sample (inclusively)
        endsam : int
            index of the last sample (exclusively)

        Returns
        -------
        numpy.ndarray
            A 2d matrix, with dimension chan X samples.