def calc_signal_sum(self, measure='<STR_LIT>'):
<EOL>if self.RANK_CELLINDICES.size > <NUM_LIT:0>:<EOL><INDENT>for i, cellindex in enumerate(self.RANK_CELLINDICES):<EOL><INDENT>if i == <NUM_LIT:0>:<EOL><INDENT>data = self.output[cellindex][measure]<EOL><DEDENT>else:<EOL><INDENT>data += self.output[cellindex][measure]<EOL><DEDENT><DEDENT><DEDENT>else:<EOL><INDENT>data = np.zeros((len(self.electrodeParams['<STR_LIT:x>']),<EOL>self.cellParams['<STR_LIT>']/self.dt_output + <NUM_LIT:1>),<EOL>dtype=np.float32)<EOL><DEDENT>if RANK == <NUM_LIT:0>:<EOL><INDENT>DATA = np.zeros_like(data, dtype=np.float32)<EOL><DEDENT>else:<EOL><INDENT>DATA = None<EOL><DEDENT>COMM.Reduce(data, DATA, op=MPI.SUM, root=<NUM_LIT:0>)<EOL>return DATA<EOL>
Superimpose each cell's contribution to the compound population signal,
i.e., the population CSD or LFP


Parameters
----------
measure : str
    {'LFP', 'CSD'}: Either 'LFP' or 'CSD'.


Returns
-------
numpy.ndarray
    The populations-specific compound signal.