def _synDelayParams(self):
delays = {}<EOL>loc = np.zeros((len(self.y), len(self.X)))<EOL>loc[:, <NUM_LIT:0>] = self.delays[<NUM_LIT:0>]<EOL>loc[:, <NUM_LIT:1>::<NUM_LIT:2>] = self.delays[<NUM_LIT:0>]<EOL>loc[:, <NUM_LIT:2>::<NUM_LIT:2>] = self.delays[<NUM_LIT:1>]<EOL>scale = loc * self.delay_rel_sd<EOL>delay_loc = {}<EOL>for i, y in enumerate(self.y):<EOL><INDENT>delay_loc.update({y : loc[i]})<EOL><DEDENT>delay_scale = {}<EOL>for i, y in enumerate(self.y):<EOL><INDENT>delay_scale.update({y : scale[i]})<EOL><DEDENT>return delay_loc, delay_scale<EOL>
set up the detailed synaptic delay parameters,
loc is mean delay,
scale is std with low bound cutoff,
assumes numpy.random.normal is used later