def __init__(self,<EOL>X = ['<STR_LIT>', '<STR_LIT>'],<EOL>networkSim = '<STR_LIT>',<EOL>k_yXL = [[<NUM_LIT:20>,  <NUM_LIT:0>], [<NUM_LIT:20>, <NUM_LIT:10>]],<EOL>synParams = {<EOL>'<STR_LIT>': {<EOL>'<STR_LIT>': ['<STR_LIT>', '<STR_LIT>'],<EOL>'<STR_LIT>': '<STR_LIT>',<EOL>},<EOL>'<STR_LIT>': {<EOL>'<STR_LIT>': ['<STR_LIT>'],<EOL>'<STR_LIT>': '<STR_LIT>',<EOL>},<EOL>},<EOL>synDelayLoc = [<NUM_LIT>, <NUM_LIT>],<EOL>synDelayScale = [None, None],<EOL>J_yX = [<NUM_LIT>, -<NUM_LIT>],<EOL>tau_yX = [<NUM_LIT:0.5>, <NUM_LIT:0.5>],<EOL>**kwargs):
tic = time()<EOL>PopulationSuper.__init__(self, **kwargs)<EOL>self.X = X<EOL>self.networkSim = networkSim<EOL>self.k_yXL = np.array(k_yXL)<EOL>self.synParams = synParams<EOL>self.synDelayLoc = synDelayLoc<EOL>self.synDelayScale = synDelayScale<EOL>self.J_yX = J_yX<EOL>self.tau_yX = tau_yX<EOL>self.synIdx = self.get_all_synIdx()<EOL>self.SpCells = self.get_all_SpCells()<EOL>self.synDelays = self.get_all_synDelays()<EOL>if RANK == <NUM_LIT:0>:<EOL><INDENT>print(("<STR_LIT>" % (time()-tic)))<EOL><DEDENT>
Class `hybridLFPy.Population`, inherited from class `PopulationSuper`.

This class rely on spiking times recorded in a network simulation,
layer-resolved indegrees, synapse parameters, delay parameters, all per
presynaptic population.


Parameters
----------
X : list of str
    Each element denote name of presynaptic populations.
networkSim : `hybridLFPy.cachednetworks.CachedNetwork` object
    Container of network spike events resolved per population
k_yXL : numpy.ndarray
    Num layers x num presynapse populations array specifying the
    number of incoming connections per layer and per population type.
synParams : dict of dicts
    Synapse parameters (cf. `LFPy.Synapse` class).
    Each toplevel key denote each presynaptic population,
    bottom-level dicts are parameters passed to `LFPy.Synapse`, however,
    time constants `tau' takes one value per presynaptic population. 
synDelayLoc : list
    Average synapse delay for each presynapse connection.
synDelayScale : list
    Synapse delay std for each presynapse connection.
J_yX : list of floats
    Synapse weights for connections from each presynaptic population,
    see class `LFPy.Synapse`
tau_yX : list of floats
    Synapse time constants for connections from each presynaptic
    population
#calculateCSD : bool
#    Flag for computing the ground-source CSD.


Returns
-------
`hybridLFPy.population.Population` object


See also
--------
PopulationSuper, CachedNetwork, CachedFixedSpikesNetwork,
CachedNoiseNetwork, LFPy.Cell, LFPy.RecExtElectrode