def __init__(self,<EOL>simtime = <NUM_LIT>,<EOL>dt = <NUM_LIT:0.1>,<EOL>spike_output_path='<STR_LIT>',<EOL>label = '<STR_LIT>',<EOL>ext = '<STR_LIT>',<EOL>GIDs={'<STR_LIT>' : [<NUM_LIT:1>, <NUM_LIT>], '<STR_LIT>' : [<NUM_LIT>, <NUM_LIT:100>]},<EOL>autocollect=True,<EOL>cmap='<STR_LIT>',<EOL>):
<EOL>self.simtime = simtime<EOL>self.dt = dt<EOL>self.spike_output_path = spike_output_path<EOL>self.label = label<EOL>self.ext = ext<EOL>self.dbname = '<STR_LIT>'<EOL>self.GIDs = GIDs<EOL>self.X = GIDs.keys()<EOL>self.X.sort()<EOL>self.autocollect = autocollect<EOL>self.nodes = {}<EOL>for X in self.X:<EOL><INDENT>self.nodes[X] = np.arange(self.GIDs[X][<NUM_LIT:1>]) + self.GIDs[X][<NUM_LIT:0>]<EOL><DEDENT>self.N_X = np.array([self.GIDs[X][<NUM_LIT:1>] for X in self.X])<EOL>if self.autocollect:<EOL><INDENT>self.collect_gdf()<EOL><DEDENT>if '<STR_LIT>' in self.X:<EOL><INDENT>numcolors = len(self.X)-<NUM_LIT:1><EOL><DEDENT>else:<EOL><INDENT>numcolors = len(self.X)<EOL><DEDENT>self.colors = []<EOL>for i in range(numcolors):<EOL><INDENT>self.colors += [plt.get_cmap(cmap, numcolors)(i)]<EOL><DEDENT>if '<STR_LIT>' in self.X:<EOL><INDENT>self.colors += ['<STR_LIT:k>']<EOL><DEDENT>
Offline processing and storing of network spike events, used by other
class objects in the package `hybridLFPy`.


Parameters
----------
simtime : float
    Simulation duration.
dt : float
    Simulation timestep size.
spike_output_path : str
    Path to gdf-files with spikes.
label : str
    Prefix of spiking gdf-files.
ext : str
    File extension of gdf-files.
GIDs : dict
    dictionary keys are population names and item a list with first
    GID in population and population size            
autocollect : bool
    If True, class init will process gdf files.
cmap : str
    Name of colormap, must be in dir(plt.cm).


Returns
-------
`hybridLFPy.cachednetworks.CachedNetwork` object


See also
--------
CachedFixedSpikesNetwork, CachedNoiseNetwork