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:
# !