xticks=[], yticks=[]) pylab.show() # ! Thick red lines mark the mask, dashed red lines to the right one, two and # ! three standard deviations. The sender location is marked by the red spot # ! in the center. Layers are 40x40 in size. # ! A more complex network # ! ====================== # ! # ! This network has layers A and B, with E and I populations in B. The added # ! complexity comes from the fact that we now have four synapse types: AMPA, # ! NMDA, GABA_A and GABA_B. These synapse types are known to ConnPlotter. # ! Setup and tabular display c_layer, c_conn, c_model = ex.complex() c_cp = cpl.ConnectionPattern(c_layer, c_conn) showTextTable(c_cp, 'complex_tt') # $ \centerline{\includegraphics{complex_tt.pdf}} # ! Pattern in full detail # ! ---------------------- c_cp.plot() pylab.show() # ! Note the following differences to the simple pattern case: # ! # ! - For each pair of populations, e.g., B/E as sender and B/E as target, # ! we now have two patches representing AMPA and NMDA synapse for the E # ! population, GABA_A and _B for the I population. # ! - Colors are as follows:
xticks=[], yticks=[]) plt.show() # ! Thick red lines mark the mask, dashed red lines to the right one, two and # ! three standard deviations. The sender location is marked by the red spot # ! in the center. Layers are 40x40 in size. # ! A more complex network # ! ====================== # ! # ! This network has layers A and B, with E and I populations in B. The added # ! complexity comes from the fact that we now have four synapse types: AMPA, # ! NMDA, GABA_A and GABA_B. These synapse types are known to ConnPlotter. # ! Setup and tabular display c_layer, c_conn, c_model = ex.complex() # p is evaluated, in case it is a Parameter for i in range(len(c_conn)): c_conn[i][2]['p'] = eval(str(c_conn[i][2]['p'])) c_cp = cpl.ConnectionPattern(c_layer, c_conn) showTextTable(c_cp, 'complex_tt') # $ \centerline{\includegraphics{complex_tt.pdf}} # ! Pattern in full detail # ! ---------------------- c_cp.plot() plt.show() # ! Note the following differences to the simple pattern case: # !